mrna magnetic isolation module  (New England Biolabs)


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    NEBNext Poly A mRNA Magnetic Isolation Module
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    NEBNext Poly A mRNA Magnetic Isolation Module 96 rxns
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    e7490l
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    96 rxns
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    mRNA Purification Kits
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    New England Biolabs mrna magnetic isolation module
    NEBNext Poly A mRNA Magnetic Isolation Module
    NEBNext Poly A mRNA Magnetic Isolation Module 96 rxns
    https://www.bioz.com/result/mrna magnetic isolation module/product/New England Biolabs
    Average 99 stars, based on 495 article reviews
    Price from $9.99 to $1999.99
    mrna magnetic isolation module - by Bioz Stars, 2020-07
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    1) Product Images from "Recognition of RNA N6-methyladenosine by IGF2BP Proteins Enhances mRNA Stability and Translation"

    Article Title: Recognition of RNA N6-methyladenosine by IGF2BP Proteins Enhances mRNA Stability and Translation

    Journal: Nature cell biology

    doi: 10.1038/s41556-018-0045-z

    The KH domains of IGF2BPs are critical for m 6 A recognition and binding ( a ) Schematic structures showing RNA binding domains within IGF2BP proteins and a summary of IGF2BP variants used in this study. Blue boxes are RRM domains, red boxes are wild-type KH domains with GxxG core, and grey boxes are inactive KH domain with GxxG to GEEG conversions. ( b ) RNA pulldown followed by Western blotting showed in vitro binding of ssRNA baits with wild-type (wt) or KH domain-mutated IGF2BP variants, representative of 3 independent experiments. ( c ) In vitro binding of CRD1 RNA probes with wild-type or KH3-4 mutated IGF2BPs, representative of 3 independent experiments. ( d ) The association of wild-type and KH3-4 mutated IGF2BPs with MYC CRD in HEK293T cells as assessed by RIP-qPCR. ( e ) Relative luciferase activity of CRD reporters in HEK293T cells with forced expression of wild-type or mutated IGF2BP2 variants. ( f ) Changes in MYC mRNA levels in Hela cells with empty vector or forced expression of wild-type or KH3-4 mutated IGF2BPs one hour post-heat shock (HS). Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in d , e , f (*, P
    Figure Legend Snippet: The KH domains of IGF2BPs are critical for m 6 A recognition and binding ( a ) Schematic structures showing RNA binding domains within IGF2BP proteins and a summary of IGF2BP variants used in this study. Blue boxes are RRM domains, red boxes are wild-type KH domains with GxxG core, and grey boxes are inactive KH domain with GxxG to GEEG conversions. ( b ) RNA pulldown followed by Western blotting showed in vitro binding of ssRNA baits with wild-type (wt) or KH domain-mutated IGF2BP variants, representative of 3 independent experiments. ( c ) In vitro binding of CRD1 RNA probes with wild-type or KH3-4 mutated IGF2BPs, representative of 3 independent experiments. ( d ) The association of wild-type and KH3-4 mutated IGF2BPs with MYC CRD in HEK293T cells as assessed by RIP-qPCR. ( e ) Relative luciferase activity of CRD reporters in HEK293T cells with forced expression of wild-type or mutated IGF2BP2 variants. ( f ) Changes in MYC mRNA levels in Hela cells with empty vector or forced expression of wild-type or KH3-4 mutated IGF2BPs one hour post-heat shock (HS). Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in d , e , f (*, P

    Techniques Used: Binding Assay, RNA Binding Assay, Western Blot, In Vitro, Real-time Polymerase Chain Reaction, Luciferase, Activity Assay, Expressing, Plasmid Preparation, Two Tailed Test

    IGF2BPs regulate MYC expression through binding to methylated CRD ( a ) Distribution of m 6 A peaks across MYC mRNA transcript. The coding region instability determinant (CRD) region is highlighted in yellow. m 6 A-seq was repeated twice while RIP-seq was performed once.( b ) RIP-qPCR showing the association of MYC CRD with FLAG-tagged IGF2BPs in HEK293T cells. ( c ) Enrichment of m 6 A modification in MYC CRD as detected by gene specific m 6 A qPCR assay. ( d ) RIP-qPCR showing the binding of METTL3 and METTL14 to the MYC CRD. ( e ) RNA pulldown of endogenous IGF2BP proteins from HEK293T nuclear extract using synthetic CRD RNA fragments, CRD1 and CRD2, with (m 6 A) or without (A) m 6 A modifications. Images are representative of 3 independent experiments. ( f ) Relative firefly luciferase (Fluc) activity (i.e., protein level; left) and Fluc mRNA level (right) of wild-type (CRD-wt) or mutated (CRD-mut) CRD reporters in HEK293T cells with ectopically expressed IGF2BP1, IGF2BP2, or IGF2BP3. ( g ) RIP-qPCR detecting the in vivo binding of Flag-IGF2BPs to the transcripts of CRD-wt or CRD-mut luciferase reporter in HEK293T cells. ( h and i ) Relative luciferase activity of CRD-wt or CRD-mut in Hela cells with or without stable knockdown of IGF2BPs (h) or METTL14 (i). ( j ) Relative luciferase activity of CRD-wt or CRD-mut in METTL14 stable knockdown or control Hela cells with ectopic expression of IGF2BPs . For all luciferase assays, the Fluc/Rluc ratio (representing luciferase activity) of CRD-wt with empty vector or shNS was used for normalization. Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in b , c , d , f , g , h , i , j . (**, P
    Figure Legend Snippet: IGF2BPs regulate MYC expression through binding to methylated CRD ( a ) Distribution of m 6 A peaks across MYC mRNA transcript. The coding region instability determinant (CRD) region is highlighted in yellow. m 6 A-seq was repeated twice while RIP-seq was performed once.( b ) RIP-qPCR showing the association of MYC CRD with FLAG-tagged IGF2BPs in HEK293T cells. ( c ) Enrichment of m 6 A modification in MYC CRD as detected by gene specific m 6 A qPCR assay. ( d ) RIP-qPCR showing the binding of METTL3 and METTL14 to the MYC CRD. ( e ) RNA pulldown of endogenous IGF2BP proteins from HEK293T nuclear extract using synthetic CRD RNA fragments, CRD1 and CRD2, with (m 6 A) or without (A) m 6 A modifications. Images are representative of 3 independent experiments. ( f ) Relative firefly luciferase (Fluc) activity (i.e., protein level; left) and Fluc mRNA level (right) of wild-type (CRD-wt) or mutated (CRD-mut) CRD reporters in HEK293T cells with ectopically expressed IGF2BP1, IGF2BP2, or IGF2BP3. ( g ) RIP-qPCR detecting the in vivo binding of Flag-IGF2BPs to the transcripts of CRD-wt or CRD-mut luciferase reporter in HEK293T cells. ( h and i ) Relative luciferase activity of CRD-wt or CRD-mut in Hela cells with or without stable knockdown of IGF2BPs (h) or METTL14 (i). ( j ) Relative luciferase activity of CRD-wt or CRD-mut in METTL14 stable knockdown or control Hela cells with ectopic expression of IGF2BPs . For all luciferase assays, the Fluc/Rluc ratio (representing luciferase activity) of CRD-wt with empty vector or shNS was used for normalization. Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in b , c , d , f , g , h , i , j . (**, P

    Techniques Used: Expressing, Binding Assay, Methylation, Real-time Polymerase Chain Reaction, Modification, Luciferase, Activity Assay, In Vivo, Plasmid Preparation, Two Tailed Test

    Selective binding of IGF2BPs to m 6 A-modified RNAs ( a ) Identification of m 6 A specific binding proteins by RNA affinity chromatography using ssRNA probes with methylated (red) or unmethylated (green) adenosine. Silver staining (lower left) and Western blotting (lower right) showed selective pulldown of ~68kDa IGF2BP proteins from HEK293T nuclear extract. Western blot images were representative of 3 independent experiments. ( b ) Enrichment of m 6 A consensus sequence “GGAC” in the binding sites of RBPs. The three IGF2BP paralogues were shown in red, while the YTH domain proteins were shown in orange. ( c ) Quantification of m 6 A/A and m 6 A/AGCU ratios by LC-MS/MS in RNAs bound by ectopically expressed IGF2BP1 (chicken ZBP1), IGF2BP2 (human), or IGF2BP3 (human). Values are mean of n =2 independent experiments and individual data points are showed. ( d ) Overlap of IGF2BP target genes identified by RIP-seq and published PAR-CLIP in HEK293T cells. RIP-seq was performed once. P value was calculated by Fisher’s test. ( e ) Venn diagram showing the numbers of shared high-confidence targets ( i.e. , CLIP+RIP targets) amongst IGF2BP paralogues. P value was calculated by Fisher’s test. ( f ) Top consensus sequences of IGF2BP binding sites and the m 6 A motif detected by HOMER Motif analysis with PAR-CLIP data. ( g ) Pie charts showing numbers and percentages of IGF2BP high-confidence target genes that contain m 6 A peaks. The m 6 A-seq data was reported in Ref. 3 . ( h ) Metagene profiles of enrichment of IGF2BP binding sites and m 6 A modifications across mRNA transcriptome. ( i ) Percentages of various RNA species bound by IGF2BPs. ( j ) The distribution (upper) and enrichment (lower) of IGF2BPs binding peaks within different gene reions. The enrichment was determined by the proportion of IGF2BPs binding peaks normalized by the length of the region. Analyses in i and j were performed twice with similar results. ( k ) In vivo binding of Flag-IGF2BP2 to representative target genes in METTL14 knockdown or control HEK293T cells. Values are mean±s.d. of n =3 independent experiments. *, P
    Figure Legend Snippet: Selective binding of IGF2BPs to m 6 A-modified RNAs ( a ) Identification of m 6 A specific binding proteins by RNA affinity chromatography using ssRNA probes with methylated (red) or unmethylated (green) adenosine. Silver staining (lower left) and Western blotting (lower right) showed selective pulldown of ~68kDa IGF2BP proteins from HEK293T nuclear extract. Western blot images were representative of 3 independent experiments. ( b ) Enrichment of m 6 A consensus sequence “GGAC” in the binding sites of RBPs. The three IGF2BP paralogues were shown in red, while the YTH domain proteins were shown in orange. ( c ) Quantification of m 6 A/A and m 6 A/AGCU ratios by LC-MS/MS in RNAs bound by ectopically expressed IGF2BP1 (chicken ZBP1), IGF2BP2 (human), or IGF2BP3 (human). Values are mean of n =2 independent experiments and individual data points are showed. ( d ) Overlap of IGF2BP target genes identified by RIP-seq and published PAR-CLIP in HEK293T cells. RIP-seq was performed once. P value was calculated by Fisher’s test. ( e ) Venn diagram showing the numbers of shared high-confidence targets ( i.e. , CLIP+RIP targets) amongst IGF2BP paralogues. P value was calculated by Fisher’s test. ( f ) Top consensus sequences of IGF2BP binding sites and the m 6 A motif detected by HOMER Motif analysis with PAR-CLIP data. ( g ) Pie charts showing numbers and percentages of IGF2BP high-confidence target genes that contain m 6 A peaks. The m 6 A-seq data was reported in Ref. 3 . ( h ) Metagene profiles of enrichment of IGF2BP binding sites and m 6 A modifications across mRNA transcriptome. ( i ) Percentages of various RNA species bound by IGF2BPs. ( j ) The distribution (upper) and enrichment (lower) of IGF2BPs binding peaks within different gene reions. The enrichment was determined by the proportion of IGF2BPs binding peaks normalized by the length of the region. Analyses in i and j were performed twice with similar results. ( k ) In vivo binding of Flag-IGF2BP2 to representative target genes in METTL14 knockdown or control HEK293T cells. Values are mean±s.d. of n =3 independent experiments. *, P

    Techniques Used: Binding Assay, Modification, Affinity Chromatography, Methylation, Silver Staining, Western Blot, Sequencing, Liquid Chromatography with Mass Spectroscopy, Mass Spectrometry, Cross-linking Immunoprecipitation, In Vivo

    2) Product Images from "Thermotolerance in the pathogen Cryptococcus neoformans is linked to antigen masking via mRNA decay-dependent reprogramming"

    Article Title: Thermotolerance in the pathogen Cryptococcus neoformans is linked to antigen masking via mRNA decay-dependent reprogramming

    Journal: Nature Communications

    doi: 10.1038/s41467-019-12907-x

    mRNA decay is required for reprogramming the translatome and transcriptome. a Heatmap of expression levels for the top 250 most variable genes in our total data set. The color scale defines the measured expression of a given gene. b Genes with significant change in the polysomal fractions following a shift from 30 °C to 37 °C in the wild-type identified by RNA-Seq were plotted in order of log2 magnitude change (blue circles). The magnitude of change for each corresponding gene in the ccr4 Δ mutant was overlaid (orange circles). RP genes are highlighted in green. c Venn diagrams demonstrate genes that are upregulated and downregulated in response to host temperature in WT and the ccr4 Δ mutant following growth at 37 °C for 1 h. d GO analyses for genes differentially expressed in the ccr4 Δ mutant compared with wild-type 1 h after a shift to host temperature
    Figure Legend Snippet: mRNA decay is required for reprogramming the translatome and transcriptome. a Heatmap of expression levels for the top 250 most variable genes in our total data set. The color scale defines the measured expression of a given gene. b Genes with significant change in the polysomal fractions following a shift from 30 °C to 37 °C in the wild-type identified by RNA-Seq were plotted in order of log2 magnitude change (blue circles). The magnitude of change for each corresponding gene in the ccr4 Δ mutant was overlaid (orange circles). RP genes are highlighted in green. c Venn diagrams demonstrate genes that are upregulated and downregulated in response to host temperature in WT and the ccr4 Δ mutant following growth at 37 °C for 1 h. d GO analyses for genes differentially expressed in the ccr4 Δ mutant compared with wild-type 1 h after a shift to host temperature

    Techniques Used: Expressing, RNA Sequencing Assay, Mutagenesis

    Stabilized RP transcripts are retained in the actively translating pool. a Equivalent amounts of the total RNA from cultures grown at 30 °C or shifted to 37 °C for 1 h were vacuum filtered through a slot blot apparatus onto the nylon membrane. A P32-labeled oligo-dT was used to assess mRNA by northern blot. Graphs show averaged polyA mRNA levels ± s.e.m. from three biological replicates. b Polysome traces show the translational state of each strain during no stress and following a shift to 37 °C for 1 h. Subunits, monosomes, and polysome are indicated. RNA was extracted from fractions collected during polysome profiling for wild-type and ccr4 Δ. Equivalent volumes of RNA from each fraction were run on a formaldehyde-agarose gel for northern blot analysis of RPL2 . The rRNA bands confirm that the fractions correspond to the area of the polysome profile above. The results shown are representative of three biological replicates. Source data are provided as a Source Data file
    Figure Legend Snippet: Stabilized RP transcripts are retained in the actively translating pool. a Equivalent amounts of the total RNA from cultures grown at 30 °C or shifted to 37 °C for 1 h were vacuum filtered through a slot blot apparatus onto the nylon membrane. A P32-labeled oligo-dT was used to assess mRNA by northern blot. Graphs show averaged polyA mRNA levels ± s.e.m. from three biological replicates. b Polysome traces show the translational state of each strain during no stress and following a shift to 37 °C for 1 h. Subunits, monosomes, and polysome are indicated. RNA was extracted from fractions collected during polysome profiling for wild-type and ccr4 Δ. Equivalent volumes of RNA from each fraction were run on a formaldehyde-agarose gel for northern blot analysis of RPL2 . The rRNA bands confirm that the fractions correspond to the area of the polysome profile above. The results shown are representative of three biological replicates. Source data are provided as a Source Data file

    Techniques Used: Dot Blot, Labeling, Northern Blot, Agarose Gel Electrophoresis

    3) Product Images from "Coordinate regulation of alternative pre-mRNA splicing events by the human RNA chaperone proteins hnRNPA1 and DDX5"

    Article Title: Coordinate regulation of alternative pre-mRNA splicing events by the human RNA chaperone proteins hnRNPA1 and DDX5

    Journal: Genes & Development

    doi: 10.1101/gad.316034.118

    Alternative pre-mRNA splicing of RPL7A mRNA is regulated by hnRNPA1 and DDX5. ( A ) Genome browser shot of the RPL7A gene region with RNA-seq data upon hnRNPA1 knockdown ( top ) and DDX5 knockdown ( bottom ), with corresponding nuclear CLIP peak cluster regions shown below . ( B ) icSHAPE-constrained in vivo and in vitro secondary structures for the RPL7A RNA. The nuclear eCLIP cluster/peak region is highlighted in green, the hnRNPA1 cross-link sites are marked with red asterisks, and the DDX5 cross-link sites are marked with blue plus signs. The dotted red rectangles indicate regions of the RNA with secondary structural changes between the in vivo and in vitro icSHAPE constraints. The enriched hnRNPA1 motifs are indicated by orange lines, and the enriched GC-rich motifs for DDX5 is indicated by dark-green lines.
    Figure Legend Snippet: Alternative pre-mRNA splicing of RPL7A mRNA is regulated by hnRNPA1 and DDX5. ( A ) Genome browser shot of the RPL7A gene region with RNA-seq data upon hnRNPA1 knockdown ( top ) and DDX5 knockdown ( bottom ), with corresponding nuclear CLIP peak cluster regions shown below . ( B ) icSHAPE-constrained in vivo and in vitro secondary structures for the RPL7A RNA. The nuclear eCLIP cluster/peak region is highlighted in green, the hnRNPA1 cross-link sites are marked with red asterisks, and the DDX5 cross-link sites are marked with blue plus signs. The dotted red rectangles indicate regions of the RNA with secondary structural changes between the in vivo and in vitro icSHAPE constraints. The enriched hnRNPA1 motifs are indicated by orange lines, and the enriched GC-rich motifs for DDX5 is indicated by dark-green lines.

    Techniques Used: RNA Sequencing Assay, Cross-linking Immunoprecipitation, In Vivo, In Vitro

    Quantitation of differential AS events controlled by hnRNPA1 from RNA-seq using JUM. ( A , left panel) siRNA-mediated knockdown of hnRNPA1 at the protein level. K562 cells were transfected with either nonspecific control siRNA oligos (scr si) or hnRNPA1 duplex siRNA oligos. After a second round of siRNA transfection, the cells were harvested for RNA isolation or protein lysates. ( Right panel) JUM is a splicing annotation-independent method for determining pre-mRNA splicing patterns from RNA-seq data. Only splice junction-spanning reads were taken into account for quantitation. This resulted in a quantitative comparison of AS events (1828) whose splicing patterns were significantly altered in the hnRNPA1 knockdown samples versus the control (false discovery rate [FDR], P
    Figure Legend Snippet: Quantitation of differential AS events controlled by hnRNPA1 from RNA-seq using JUM. ( A , left panel) siRNA-mediated knockdown of hnRNPA1 at the protein level. K562 cells were transfected with either nonspecific control siRNA oligos (scr si) or hnRNPA1 duplex siRNA oligos. After a second round of siRNA transfection, the cells were harvested for RNA isolation or protein lysates. ( Right panel) JUM is a splicing annotation-independent method for determining pre-mRNA splicing patterns from RNA-seq data. Only splice junction-spanning reads were taken into account for quantitation. This resulted in a quantitative comparison of AS events (1828) whose splicing patterns were significantly altered in the hnRNPA1 knockdown samples versus the control (false discovery rate [FDR], P

    Techniques Used: Quantitation Assay, RNA Sequencing Assay, Transfection, Isolation

    The RNA helicase DDX controls alternative pre-mRNA splicing of thousands of target RNAs. ( A , left panel) K562 cells were transfected with either nonspecific control siRNA oligos (scr si) or DDX5 duplex siRNA oligos. After a second round of siRNA transfection, the cells were harvested for RNA isolation or protein lysates. Protein lysates were immunoblotted with DDX5 antibody to detect the efficiency of siRNA-mediated knockdown at the protein level. ( Right panel) Detection of changes in AS events upon DDX5 knockdown in human K562 cells using JUM. JUM analysis revealed 3915 AS events whose splicing patterns were significantly altered in DDX5 RNAi knockdown samples versus the control scrambled siRNA samples, covering 2804 genes (FDR, P
    Figure Legend Snippet: The RNA helicase DDX controls alternative pre-mRNA splicing of thousands of target RNAs. ( A , left panel) K562 cells were transfected with either nonspecific control siRNA oligos (scr si) or DDX5 duplex siRNA oligos. After a second round of siRNA transfection, the cells were harvested for RNA isolation or protein lysates. Protein lysates were immunoblotted with DDX5 antibody to detect the efficiency of siRNA-mediated knockdown at the protein level. ( Right panel) Detection of changes in AS events upon DDX5 knockdown in human K562 cells using JUM. JUM analysis revealed 3915 AS events whose splicing patterns were significantly altered in DDX5 RNAi knockdown samples versus the control scrambled siRNA samples, covering 2804 genes (FDR, P

    Techniques Used: Transfection, Isolation

    4) Product Images from "Targeted enrichment outperforms other enrichment techniques and enables more multi-species RNA-Seq analyses"

    Article Title: Targeted enrichment outperforms other enrichment techniques and enables more multi-species RNA-Seq analyses

    Journal: Scientific Reports

    doi: 10.1038/s41598-018-31420-7

    This schematic illustrates the sample (auburn rectangle) and library (blue rectangle) preparation workflow to generate the libraries that were loaded on the Illumina sequencer. ( a ) For B. malayi and A. fumigatus , a poly(A)-selected sample was created from an aliquot of total RNA that was used to create a poly(A)-selected library. ( b ) The B. malayi or A. fumigatus AgSS baits were subsequently used to capture the targeted RNA from poly(A)-selected libraries. ( c ) For AgSS-enriched w Bm libraries, an RNA library was constructed from an aliquot of total RNA that underwent targeted enrichment with the Wolbachia AgSS baits. Unlike the eukaryotic enrichments, the bacterial AgSS capture is performed on total RNA. For a limited number of libraries described in the text, an RNA library was constructed from an aliquot of total RNA (i.e. without poly(A)-enrichment) that underwent targeted enrichment with the Brugia AgSS baits. ( d ) For poly(A)/rRNA-depleted libraries enriched for w Bm, an aliquot of total RNA from either mosquito thoraces or adult nematodes was enriched for bacterial mRNA by removing Gram-negative and human rRNAs with two RiboZero removal kits and polyadenylated RNAs with DynaBeads.
    Figure Legend Snippet: This schematic illustrates the sample (auburn rectangle) and library (blue rectangle) preparation workflow to generate the libraries that were loaded on the Illumina sequencer. ( a ) For B. malayi and A. fumigatus , a poly(A)-selected sample was created from an aliquot of total RNA that was used to create a poly(A)-selected library. ( b ) The B. malayi or A. fumigatus AgSS baits were subsequently used to capture the targeted RNA from poly(A)-selected libraries. ( c ) For AgSS-enriched w Bm libraries, an RNA library was constructed from an aliquot of total RNA that underwent targeted enrichment with the Wolbachia AgSS baits. Unlike the eukaryotic enrichments, the bacterial AgSS capture is performed on total RNA. For a limited number of libraries described in the text, an RNA library was constructed from an aliquot of total RNA (i.e. without poly(A)-enrichment) that underwent targeted enrichment with the Brugia AgSS baits. ( d ) For poly(A)/rRNA-depleted libraries enriched for w Bm, an aliquot of total RNA from either mosquito thoraces or adult nematodes was enriched for bacterial mRNA by removing Gram-negative and human rRNAs with two RiboZero removal kits and polyadenylated RNAs with DynaBeads.

    Techniques Used: Construct

    5) Product Images from "Enhanced Anti-lymphoma Activity of CAR19-iNKT Cells Underpinned by Dual CD19 and CD1d Targeting"

    Article Title: Enhanced Anti-lymphoma Activity of CAR19-iNKT Cells Underpinned by Dual CD19 and CD1d Targeting

    Journal: Cancer Cell

    doi: 10.1016/j.ccell.2018.08.017

    Transcriptional and Epigenetic Basis for Enhancing CAR19-iNKT Cell Reactivity (A) CD1D mRNA quantification by qPCR in CLL cells from two patients upon ATRA treatment (10 −6 M) for 0–96 hr. (B and C) Bar charts (B) and flow cytometry histograms (C) showing CD1d expression on malignant B cells upon ATRA treatment and mean fluorescent intensity (MFI) analysis of CD1d expression in comparison with isotype control. (D) Cytotoxicity of second- and third-generation CAR19-T and -NKT cells against αGalCer-pulsed CLL cells pre-treated with 0.1% DMSO control or 10 −6 M ATRA. Error bars represent SEM of triplicate assays. (E) ChIP-qPCR assay for H3K4me3 and H3K27me3 enrichment in the promoter of CD1D using IgG as control in U266 cells. GAPDH is an active gene control, while HOXA2 is a repressed gene control. ChIP data are shown as a percentage of the input chromatin. (F) ChIP-re-ChIP qPCR assay showing fold enrichment of H3K27me3 or IgG control after immunoprecipitation (IP) against H3K4me3. (G) ChIP-qPCR assay against RNA Pol II for Ser5 over Ser2 phosphorylated form at the promoter of the indicated genes. (H) ChIP-qPCR assay against RARα, EZH2, and Ig control at the promoters of the genes shown. (I) ChIP-re-ChIP qPCR assay showing enrichment of EZH2 or IgG control after IP against RARα in U266 cells for –(I) (n = 3). (J) qPCR quantification of CD1D mRNA in U266 cells treated with 0.1% DMSO, 10 −6 M GSK343, 10 −6 M ATRA or 10 −6 M GSK343 plus 10 −6 M ATRA. Values are normalized to CD1D mRNA expression levels in normal peripheral PB B cells (n = 3). ND, not detectable. (K and L) Relative MFI analysis (K) and histogram depiction (L) of CD1d expression in comparison with isotype control in U266 cells from the same experiment shown in (J). .
    Figure Legend Snippet: Transcriptional and Epigenetic Basis for Enhancing CAR19-iNKT Cell Reactivity (A) CD1D mRNA quantification by qPCR in CLL cells from two patients upon ATRA treatment (10 −6 M) for 0–96 hr. (B and C) Bar charts (B) and flow cytometry histograms (C) showing CD1d expression on malignant B cells upon ATRA treatment and mean fluorescent intensity (MFI) analysis of CD1d expression in comparison with isotype control. (D) Cytotoxicity of second- and third-generation CAR19-T and -NKT cells against αGalCer-pulsed CLL cells pre-treated with 0.1% DMSO control or 10 −6 M ATRA. Error bars represent SEM of triplicate assays. (E) ChIP-qPCR assay for H3K4me3 and H3K27me3 enrichment in the promoter of CD1D using IgG as control in U266 cells. GAPDH is an active gene control, while HOXA2 is a repressed gene control. ChIP data are shown as a percentage of the input chromatin. (F) ChIP-re-ChIP qPCR assay showing fold enrichment of H3K27me3 or IgG control after immunoprecipitation (IP) against H3K4me3. (G) ChIP-qPCR assay against RNA Pol II for Ser5 over Ser2 phosphorylated form at the promoter of the indicated genes. (H) ChIP-qPCR assay against RARα, EZH2, and Ig control at the promoters of the genes shown. (I) ChIP-re-ChIP qPCR assay showing enrichment of EZH2 or IgG control after IP against RARα in U266 cells for –(I) (n = 3). (J) qPCR quantification of CD1D mRNA in U266 cells treated with 0.1% DMSO, 10 −6 M GSK343, 10 −6 M ATRA or 10 −6 M GSK343 plus 10 −6 M ATRA. Values are normalized to CD1D mRNA expression levels in normal peripheral PB B cells (n = 3). ND, not detectable. (K and L) Relative MFI analysis (K) and histogram depiction (L) of CD1d expression in comparison with isotype control in U266 cells from the same experiment shown in (J). .

    Techniques Used: Real-time Polymerase Chain Reaction, Flow Cytometry, Cytometry, Expressing, Chromatin Immunoprecipitation, Immunoprecipitation

    6) Product Images from "DNA mismatch repair controls the host innate response and cell fate after influenza virus infection"

    Article Title: DNA mismatch repair controls the host innate response and cell fate after influenza virus infection

    Journal: Nature microbiology

    doi: 10.1038/s41564-019-0509-3

    Loss of DNA MMR activity reduces the innate antiviral transcriptional response against influenza A virus. (a) NanoLuc reporter expression and (b) relative cell viability in H441 cells that have been treated with PBS or H2O2 (for 30 min). Data shown as mean ± SD, n=4 independent samples. (c) Fold change of Mx1 RNA levels in H441 cells following treatment with PBS or IFN-alpha +/− H2O2 treatment (for 30 min). Data shown as mean ± SD, n=4 independent samples. (d) Western blot for Mx1 in H441 cells following the specified treatments. Tubulin = loading control. (e) NanoLuc reporter expression and (f) relative cell viability in H441 cells following the specified treatments. Data shown as mean ± SD, n=4 independent samples. (g) Median fluorescent intensity of the ISRE-GFP reporter in 293T cells following the specified treatments. Data shown as mean ± SD, n=3 independent samples. (h) Model depicting the role of DNA MMR in preserving antiviral gene expression. (i) RNAseq data showing fold change of mRNA levels in H441 cells comparing PR8-infected cells transfected with non-targeting siRNA (black) or MSH2+MSH6 siRNA (blue) to mock-infected cells. Inset is a magnified view of all genes induced > 5-fold in PR8-infected cells treated with non-targeting siRNA. (j) Chart grouping all of the genes induced > 5-fold in PR8-infected cells based on the effect MMR knockdown has on their mRNA levels. (k) Heat map displaying the effect of MMR knockdown on ISG and antiviral genes from the group of genes displayed in j. (l-o) Fold induction of (l) IFI44L and (n) IFIT1 RNA levels after viral infection as well as the difference in infection-induced (m) IFI44L and (o) IFIT1 RNA levels (48 hpi) after knockdown of control or MMR genes. Data shown as mean ± SD, n=4 independent samples. Data are representative of at least three independent experiments. (p) Western blot of IFIT1 in H441 cells following the specified treatments. Tubulin = loading control. For all panels: p-values calculated using unpaired two-tailed t tests; representative of two independent experiments, unless otherwise indicated.
    Figure Legend Snippet: Loss of DNA MMR activity reduces the innate antiviral transcriptional response against influenza A virus. (a) NanoLuc reporter expression and (b) relative cell viability in H441 cells that have been treated with PBS or H2O2 (for 30 min). Data shown as mean ± SD, n=4 independent samples. (c) Fold change of Mx1 RNA levels in H441 cells following treatment with PBS or IFN-alpha +/− H2O2 treatment (for 30 min). Data shown as mean ± SD, n=4 independent samples. (d) Western blot for Mx1 in H441 cells following the specified treatments. Tubulin = loading control. (e) NanoLuc reporter expression and (f) relative cell viability in H441 cells following the specified treatments. Data shown as mean ± SD, n=4 independent samples. (g) Median fluorescent intensity of the ISRE-GFP reporter in 293T cells following the specified treatments. Data shown as mean ± SD, n=3 independent samples. (h) Model depicting the role of DNA MMR in preserving antiviral gene expression. (i) RNAseq data showing fold change of mRNA levels in H441 cells comparing PR8-infected cells transfected with non-targeting siRNA (black) or MSH2+MSH6 siRNA (blue) to mock-infected cells. Inset is a magnified view of all genes induced > 5-fold in PR8-infected cells treated with non-targeting siRNA. (j) Chart grouping all of the genes induced > 5-fold in PR8-infected cells based on the effect MMR knockdown has on their mRNA levels. (k) Heat map displaying the effect of MMR knockdown on ISG and antiviral genes from the group of genes displayed in j. (l-o) Fold induction of (l) IFI44L and (n) IFIT1 RNA levels after viral infection as well as the difference in infection-induced (m) IFI44L and (o) IFIT1 RNA levels (48 hpi) after knockdown of control or MMR genes. Data shown as mean ± SD, n=4 independent samples. Data are representative of at least three independent experiments. (p) Western blot of IFIT1 in H441 cells following the specified treatments. Tubulin = loading control. For all panels: p-values calculated using unpaired two-tailed t tests; representative of two independent experiments, unless otherwise indicated.

    Techniques Used: Activity Assay, Expressing, Western Blot, Preserving, Infection, Transfection, Two Tailed Test

    7) Product Images from "Involvement of condensin in cellular senescence through gene regulation and compartmental reorganization"

    Article Title: Involvement of condensin in cellular senescence through gene regulation and compartmental reorganization

    Journal: Nature Communications

    doi: 10.1038/s41467-019-13604-5

    Effects of CAP-H2 condensin depletion on gene regulation in OIS cells. a – c Effect of CAP-H2 KD on mRNA levels of the SASP ( a ), p53 target ( b ), and E2F target genes ( c ). RNA levels of the indicated genes in OIS (control) and CAP-H2 KD (#1-#3) cells were quantified by RT-qPCR. P -values were calculated by two-sided Student’s t -test, using biologically independent samples ( n = 3, error bars represent the SD). d PCA of RNA-seq data showing similarities and differences in global expression profiles among growing, OIS (Bio1 and Bio2) and CAP-H2 KD (#1-#3) IMR90 cells. The positioning of growing and CAP-H2 KD cells at a similar location along the PC2 axis indicates that gene expression profiles in these cell populations are correlated. PC1, PC2, principal components 1 and 2. e Correlation between genes that were upregulated upon OIS and downregulated by CAP-H2 KD. Expression ratios between OIS and growing cells were compared to those between CAP-H2 KD and OIS cells. Upper left quadrant indicates 4553 genes that were upregulated by OIS and downregulated by CAP-H2 KD. Dot colors reflect CAP-H2 ChIP-seq enrichment scores. f GO analysis of genes ( n = 193) significantly upregulated upon OIS and downregulated by CAP-H2 KD, showing enrichment in SASP and other senescence genes (Fisher exact test). g Immunofluorescent (IF) visualization of IL1B (SASP factor) and p21 (p53 target; cell-cycle regulator) in OIS and CAP-H2 KD cells. Nuclear IF signals were quantified in more than 100 cells (Methods), and distributions of nuclear IF signals shown as boxplots (central bar represents the median with boxes indicating the upper and lower quartiles, and whiskers extend to the data points, which are no more than 1.5× the interquartile range from the box) were compared between CAP-H2 KD and control cells (two-sided Mann–Whitney U test). h Effect of CAP-H2 KD on p53 binding at p53 target genes in IMR90 OIS cells, as determined by ChIP-qPCR. i Effect of p53 KD on CAP-H2 binding at the indicated p53 target genes in OIS cells. Cells were prepared as in Fig. 7a except that CAP-H2 KD was replaced by p53 KD. P -values were calculated by two-sided Student’s t -test, using biologically independent samples ( n = 3, error bars represent the SD). j A model explaining how condensin may mediate gene regulation and compartmental reorganization during senescence processes. A hypothesis is that condensin participates in the upregulation of senescence genes and BA transitions, both of which are not completely independent to each other.
    Figure Legend Snippet: Effects of CAP-H2 condensin depletion on gene regulation in OIS cells. a – c Effect of CAP-H2 KD on mRNA levels of the SASP ( a ), p53 target ( b ), and E2F target genes ( c ). RNA levels of the indicated genes in OIS (control) and CAP-H2 KD (#1-#3) cells were quantified by RT-qPCR. P -values were calculated by two-sided Student’s t -test, using biologically independent samples ( n = 3, error bars represent the SD). d PCA of RNA-seq data showing similarities and differences in global expression profiles among growing, OIS (Bio1 and Bio2) and CAP-H2 KD (#1-#3) IMR90 cells. The positioning of growing and CAP-H2 KD cells at a similar location along the PC2 axis indicates that gene expression profiles in these cell populations are correlated. PC1, PC2, principal components 1 and 2. e Correlation between genes that were upregulated upon OIS and downregulated by CAP-H2 KD. Expression ratios between OIS and growing cells were compared to those between CAP-H2 KD and OIS cells. Upper left quadrant indicates 4553 genes that were upregulated by OIS and downregulated by CAP-H2 KD. Dot colors reflect CAP-H2 ChIP-seq enrichment scores. f GO analysis of genes ( n = 193) significantly upregulated upon OIS and downregulated by CAP-H2 KD, showing enrichment in SASP and other senescence genes (Fisher exact test). g Immunofluorescent (IF) visualization of IL1B (SASP factor) and p21 (p53 target; cell-cycle regulator) in OIS and CAP-H2 KD cells. Nuclear IF signals were quantified in more than 100 cells (Methods), and distributions of nuclear IF signals shown as boxplots (central bar represents the median with boxes indicating the upper and lower quartiles, and whiskers extend to the data points, which are no more than 1.5× the interquartile range from the box) were compared between CAP-H2 KD and control cells (two-sided Mann–Whitney U test). h Effect of CAP-H2 KD on p53 binding at p53 target genes in IMR90 OIS cells, as determined by ChIP-qPCR. i Effect of p53 KD on CAP-H2 binding at the indicated p53 target genes in OIS cells. Cells were prepared as in Fig. 7a except that CAP-H2 KD was replaced by p53 KD. P -values were calculated by two-sided Student’s t -test, using biologically independent samples ( n = 3, error bars represent the SD). j A model explaining how condensin may mediate gene regulation and compartmental reorganization during senescence processes. A hypothesis is that condensin participates in the upregulation of senescence genes and BA transitions, both of which are not completely independent to each other.

    Techniques Used: Quantitative RT-PCR, RNA Sequencing Assay, Expressing, Chromatin Immunoprecipitation, MANN-WHITNEY, Binding Assay, Real-time Polymerase Chain Reaction

    8) Product Images from "The yeast Aft2 transcription factor determines selenite toxicity by controlling the low affinity phosphate transport system"

    Article Title: The yeast Aft2 transcription factor determines selenite toxicity by controlling the low affinity phosphate transport system

    Journal: Scientific Reports

    doi: 10.1038/srep32836

    Transcriptomic profiling by RNA-Seq of wild type and aft2 cells treated with 1 mM sodium selenite. ( A ) A total number of 5415 genes with valid data for both the wild-type (dark grey circle) and the aft2 (light grey circle) strains subjected to 1 mM selenite treatment were evaluated. Genes showing induction or repression in both strains are shown as intersection of the circles. The number of genes in each category is indicated. Circles are not drawn to scale. ( B ) Changes in mRNA levels (log 2 scale) of selected genes known to respond to oxidative stress in the wild type (open bars) and aft2 (closed bars) strains after 5 h of treatment with selenite. ( C ) Changes in mRNA levels for genes known to specifically respond to DNA damage 60 . See main text for details. ( D ) Exponential cultures in SC medium of wild type and aft2 cells transformed with reporter plasmids in which the respective gene promoter was fused to lacZ were treated from time 0 with 1 mM selenite. β-galactosidase activity was measured in samples at the indicated times, and for each gene the values were made relative to the respective value in untreated wild type cells. Data are expressed as mean ± SD from three independent experiments.
    Figure Legend Snippet: Transcriptomic profiling by RNA-Seq of wild type and aft2 cells treated with 1 mM sodium selenite. ( A ) A total number of 5415 genes with valid data for both the wild-type (dark grey circle) and the aft2 (light grey circle) strains subjected to 1 mM selenite treatment were evaluated. Genes showing induction or repression in both strains are shown as intersection of the circles. The number of genes in each category is indicated. Circles are not drawn to scale. ( B ) Changes in mRNA levels (log 2 scale) of selected genes known to respond to oxidative stress in the wild type (open bars) and aft2 (closed bars) strains after 5 h of treatment with selenite. ( C ) Changes in mRNA levels for genes known to specifically respond to DNA damage 60 . See main text for details. ( D ) Exponential cultures in SC medium of wild type and aft2 cells transformed with reporter plasmids in which the respective gene promoter was fused to lacZ were treated from time 0 with 1 mM selenite. β-galactosidase activity was measured in samples at the indicated times, and for each gene the values were made relative to the respective value in untreated wild type cells. Data are expressed as mean ± SD from three independent experiments.

    Techniques Used: RNA Sequencing Assay, Transformation Assay, Activity Assay

    9) Product Images from "Enhanced Anti-lymphoma Activity of CAR19-iNKT Cells Underpinned by Dual CD19 and CD1d Targeting"

    Article Title: Enhanced Anti-lymphoma Activity of CAR19-iNKT Cells Underpinned by Dual CD19 and CD1d Targeting

    Journal: Cancer Cell

    doi: 10.1016/j.ccell.2018.08.017

    Transcriptional and Epigenetic Basis for Enhancing CAR19-iNKT Cell Reactivity (A) CD1D mRNA quantification by qPCR in CLL cells from two patients upon ATRA treatment (10 −6 M) for 0–96 hr. (B and C) Bar charts (B) and flow cytometry histograms (C) showing CD1d expression on malignant B cells upon ATRA treatment and mean fluorescent intensity (MFI) analysis of CD1d expression in comparison with isotype control. (D) Cytotoxicity of second- and third-generation CAR19-T and -NKT cells against αGalCer-pulsed CLL cells pre-treated with 0.1% DMSO control or 10 −6 M ATRA. Error bars represent SEM of triplicate assays. (E) ChIP-qPCR assay for H3K4me3 and H3K27me3 enrichment in the promoter of CD1D using IgG as control in U266 cells. GAPDH is an active gene control, while HOXA2 is a repressed gene control. ChIP data are shown as a percentage of the input chromatin. (F) ChIP-re-ChIP qPCR assay showing fold enrichment of H3K27me3 or IgG control after immunoprecipitation (IP) against H3K4me3. (G) ChIP-qPCR assay against RNA Pol II for Ser5 over Ser2 phosphorylated form at the promoter of the indicated genes. (H) ChIP-qPCR assay against RARα, EZH2, and Ig control at the promoters of the genes shown. (I) ChIP-re-ChIP qPCR assay showing enrichment of EZH2 or IgG control after IP against RARα in U266 cells for –(I) (n = 3). (J) qPCR quantification of CD1D mRNA in U266 cells treated with 0.1% DMSO, 10 −6 M GSK343, 10 −6 M ATRA or 10 −6 M GSK343 plus 10 −6 M ATRA. Values are normalized to CD1D mRNA expression levels in normal peripheral PB B cells (n = 3). ND, not detectable. (K and L) Relative MFI analysis (K) and histogram depiction (L) of CD1d expression in comparison with isotype control in U266 cells from the same experiment shown in (J). Error bars represent SEM. See also Figure S4 .
    Figure Legend Snippet: Transcriptional and Epigenetic Basis for Enhancing CAR19-iNKT Cell Reactivity (A) CD1D mRNA quantification by qPCR in CLL cells from two patients upon ATRA treatment (10 −6 M) for 0–96 hr. (B and C) Bar charts (B) and flow cytometry histograms (C) showing CD1d expression on malignant B cells upon ATRA treatment and mean fluorescent intensity (MFI) analysis of CD1d expression in comparison with isotype control. (D) Cytotoxicity of second- and third-generation CAR19-T and -NKT cells against αGalCer-pulsed CLL cells pre-treated with 0.1% DMSO control or 10 −6 M ATRA. Error bars represent SEM of triplicate assays. (E) ChIP-qPCR assay for H3K4me3 and H3K27me3 enrichment in the promoter of CD1D using IgG as control in U266 cells. GAPDH is an active gene control, while HOXA2 is a repressed gene control. ChIP data are shown as a percentage of the input chromatin. (F) ChIP-re-ChIP qPCR assay showing fold enrichment of H3K27me3 or IgG control after immunoprecipitation (IP) against H3K4me3. (G) ChIP-qPCR assay against RNA Pol II for Ser5 over Ser2 phosphorylated form at the promoter of the indicated genes. (H) ChIP-qPCR assay against RARα, EZH2, and Ig control at the promoters of the genes shown. (I) ChIP-re-ChIP qPCR assay showing enrichment of EZH2 or IgG control after IP against RARα in U266 cells for –(I) (n = 3). (J) qPCR quantification of CD1D mRNA in U266 cells treated with 0.1% DMSO, 10 −6 M GSK343, 10 −6 M ATRA or 10 −6 M GSK343 plus 10 −6 M ATRA. Values are normalized to CD1D mRNA expression levels in normal peripheral PB B cells (n = 3). ND, not detectable. (K and L) Relative MFI analysis (K) and histogram depiction (L) of CD1d expression in comparison with isotype control in U266 cells from the same experiment shown in (J). Error bars represent SEM. See also Figure S4 .

    Techniques Used: Real-time Polymerase Chain Reaction, Flow Cytometry, Cytometry, Expressing, Chromatin Immunoprecipitation, Immunoprecipitation

    10) Product Images from "Efficient differentiation of human pluripotent stem cells into skeletal muscle cells by combining RNA-based MYOD1-expression and POU5F1-silencing"

    Article Title: Efficient differentiation of human pluripotent stem cells into skeletal muscle cells by combining RNA-based MYOD1-expression and POU5F1-silencing

    Journal: Scientific Reports

    doi: 10.1038/s41598-017-19114-y

    POU5F1 expression is stably sustained in MYOD1-mRNA (synMYOD1)-treated hESCs. ( a ) synMYOD1 was synthesized in vitro with T7 RNA polymerase. The template cDNA was flanked by 5′UTR and 3′UTR of alpha-globin with an oligo(T) 120 for adding a polyA tail. ARCA (5′cap analog), pseudo-UTP, and 5-methyl-CTP were incorporated to increase mRNA stability and translation efficiency. ( b ) The percentage of mRNA transfection in hESCs was tested using synthetic mRNA encoding Emerald GFP by FACS analysis. ( c ) Schematic diagram of the transfection protocol. hESCs were transfected with synMYOD1 once on day 0, twice on day 1, and once on day 2. ( d ) Immunostaining analysis for MyHC in the synMYOD1-transfected cells. Nuclei were stained with DAPI. The percentage of MyHC-stained cells is shown (mean ± SEM from four independent biological replicates). Scale bar: 200 μm. ( e ) Immunostaining analysis for POU5F1 in the synMYOD1-transfected cells at day 0 to day 3 post transfection. MYOD1 was detected by a MYOD1 specific antibody. Nuclei were stained with DAPI. Scale bar: 10 μm. ( f ) Immunostaining analysis for NANOG in the synMYOD1-transfected cells at day 0 to day 3 post transfection. MYOD1 was detected by the specific antibody. Nuclei were stained with DAPI. Scale bar: 10 μm. ( g ) qRT-PCR analysis for POU5F1 expression day 0 to day 3 after transfection (mean ± SEM from two independent biological replicates). ( h .
    Figure Legend Snippet: POU5F1 expression is stably sustained in MYOD1-mRNA (synMYOD1)-treated hESCs. ( a ) synMYOD1 was synthesized in vitro with T7 RNA polymerase. The template cDNA was flanked by 5′UTR and 3′UTR of alpha-globin with an oligo(T) 120 for adding a polyA tail. ARCA (5′cap analog), pseudo-UTP, and 5-methyl-CTP were incorporated to increase mRNA stability and translation efficiency. ( b ) The percentage of mRNA transfection in hESCs was tested using synthetic mRNA encoding Emerald GFP by FACS analysis. ( c ) Schematic diagram of the transfection protocol. hESCs were transfected with synMYOD1 once on day 0, twice on day 1, and once on day 2. ( d ) Immunostaining analysis for MyHC in the synMYOD1-transfected cells. Nuclei were stained with DAPI. The percentage of MyHC-stained cells is shown (mean ± SEM from four independent biological replicates). Scale bar: 200 μm. ( e ) Immunostaining analysis for POU5F1 in the synMYOD1-transfected cells at day 0 to day 3 post transfection. MYOD1 was detected by a MYOD1 specific antibody. Nuclei were stained with DAPI. Scale bar: 10 μm. ( f ) Immunostaining analysis for NANOG in the synMYOD1-transfected cells at day 0 to day 3 post transfection. MYOD1 was detected by the specific antibody. Nuclei were stained with DAPI. Scale bar: 10 μm. ( g ) qRT-PCR analysis for POU5F1 expression day 0 to day 3 after transfection (mean ± SEM from two independent biological replicates). ( h .

    Techniques Used: Expressing, Stable Transfection, Synthesized, In Vitro, Transfection, FACS, Immunostaining, Staining, Quantitative RT-PCR

    11) Product Images from "Selective sets of mRNAs localize to extracellular paramural bodies in a rice glup6 mutant"

    Article Title: Selective sets of mRNAs localize to extracellular paramural bodies in a rice glup6 mutant

    Journal: Journal of Experimental Botany

    doi: 10.1093/jxb/ery297

    Schematic model showing glutelin mRNA and protein transport in wild-type (WT) and glup6 mutant rice endosperm. In WT endosperm cells (top), glutelin mRNAs are exported from the nucleus (N) and transported to the cisternal ER (C-ER; shown in green). Following translation, the resulting proglutelins are then exported via the Golgi (G) and pre-vacuolar compartment (PVC) to protein storage vacuoles (PSVs) where they are proteolytically processed to acidic and basic subunits and accumulated (shown in green). In contrast, globulin mRNAs, such as prolamine mRNAs, are targeted to the protein body-ER (PB-ER) and, following export, accumulate at the periphery of the PSVs (shown in purple). Prolamine polypeptides remain in the PB-ER lumen as spherical inclusion granules. In glup6 (and glup4 ) mutant endosperm cells (bottom), glutelin mRNAs (shown in green) are mislocalized from the C-ER to the PB-ER, whilst prolamine and globulin mRNAs remain correctly localized to PB-ER as in the wild-type. Following export from the ER via the Golgi, both globulin and proglutelin are secreted as small, electron-dense granules to the extracellular space These granules are then partially endocytosed to form novel paramural bodies (PMBs). At subsequent stages, glutelin and globulin are directly transported to the PMBs, together with lumenal chaperones and membrane markers for the Golgi, PVCs, and PSV, as well as β-glucan. In situ RT-PCR studies of seed sections and RNA-seq analysis of purified PMBs indicate the presence of RNAs that are either specifically enriched on this sub-compartment or are highly expressed, such as those for glutelin. The coloring of the PMB indicates the typical location of globulin (purple) and glutelin (green) proteins. The major RNA species that are enriched in purified PMBs are indicated. PM, plasma membrane; CW, cell wall.
    Figure Legend Snippet: Schematic model showing glutelin mRNA and protein transport in wild-type (WT) and glup6 mutant rice endosperm. In WT endosperm cells (top), glutelin mRNAs are exported from the nucleus (N) and transported to the cisternal ER (C-ER; shown in green). Following translation, the resulting proglutelins are then exported via the Golgi (G) and pre-vacuolar compartment (PVC) to protein storage vacuoles (PSVs) where they are proteolytically processed to acidic and basic subunits and accumulated (shown in green). In contrast, globulin mRNAs, such as prolamine mRNAs, are targeted to the protein body-ER (PB-ER) and, following export, accumulate at the periphery of the PSVs (shown in purple). Prolamine polypeptides remain in the PB-ER lumen as spherical inclusion granules. In glup6 (and glup4 ) mutant endosperm cells (bottom), glutelin mRNAs (shown in green) are mislocalized from the C-ER to the PB-ER, whilst prolamine and globulin mRNAs remain correctly localized to PB-ER as in the wild-type. Following export from the ER via the Golgi, both globulin and proglutelin are secreted as small, electron-dense granules to the extracellular space These granules are then partially endocytosed to form novel paramural bodies (PMBs). At subsequent stages, glutelin and globulin are directly transported to the PMBs, together with lumenal chaperones and membrane markers for the Golgi, PVCs, and PSV, as well as β-glucan. In situ RT-PCR studies of seed sections and RNA-seq analysis of purified PMBs indicate the presence of RNAs that are either specifically enriched on this sub-compartment or are highly expressed, such as those for glutelin. The coloring of the PMB indicates the typical location of globulin (purple) and glutelin (green) proteins. The major RNA species that are enriched in purified PMBs are indicated. PM, plasma membrane; CW, cell wall.

    Techniques Used: Mutagenesis, In Situ, Reverse Transcription Polymerase Chain Reaction, RNA Sequencing Assay, Purification

    12) Product Images from "Promoter-bound METTL3 maintains myeloid leukaemia via m6A-dependent translation control"

    Article Title: Promoter-bound METTL3 maintains myeloid leukaemia via m6A-dependent translation control

    Journal: Nature

    doi: 10.1038/nature24678

    Ribosome profiling analysis. (Related to ) a) Distribution of ribosome profiling reads throughout the mRNA metatranscript from RNA inputs or ribosome-protected fragments (RPF) showing absence of 3’UTR specifically in the RPF dataset. b) Reading frame analysis of ribosome profiling reads from RNA inputs and RPF in MOLM13 cells showing enrichment of the 0 reading frame specifically in the RPF reads. c) Average read alignments to 5' and 3' ends of coding sequences in RNA inputs (upper panel) or RPF (lower panel) showing triplet periodicity and accumulation of reads on the start site typical of cycloheximide pre-treatment. d) Principal component analysis of P-site codon distribution on mRNAs from METTL3-bound TSSs as obtained by ribosome footprinting, 5 or 8 days after doxycycline administration, of METTL3 KD (KD5, KD8) or CTRL (WT5, WT8) MOLM 13 cells. e) Principal component analysis of P-site codon distribution on all mRNAs, as above. f) Frequency of P-site occupancy of codons in METTL3 KD or CTRL MOLM13 cells for either all coding genes or genes harbouring a METTL3 ChIP peak on their promoter (*p
    Figure Legend Snippet: Ribosome profiling analysis. (Related to ) a) Distribution of ribosome profiling reads throughout the mRNA metatranscript from RNA inputs or ribosome-protected fragments (RPF) showing absence of 3’UTR specifically in the RPF dataset. b) Reading frame analysis of ribosome profiling reads from RNA inputs and RPF in MOLM13 cells showing enrichment of the 0 reading frame specifically in the RPF reads. c) Average read alignments to 5' and 3' ends of coding sequences in RNA inputs (upper panel) or RPF (lower panel) showing triplet periodicity and accumulation of reads on the start site typical of cycloheximide pre-treatment. d) Principal component analysis of P-site codon distribution on mRNAs from METTL3-bound TSSs as obtained by ribosome footprinting, 5 or 8 days after doxycycline administration, of METTL3 KD (KD5, KD8) or CTRL (WT5, WT8) MOLM 13 cells. e) Principal component analysis of P-site codon distribution on all mRNAs, as above. f) Frequency of P-site occupancy of codons in METTL3 KD or CTRL MOLM13 cells for either all coding genes or genes harbouring a METTL3 ChIP peak on their promoter (*p

    Techniques Used: Footprinting, Chromatin Immunoprecipitation

    CEBPZ recruits METTL3 on chromatin. (Related to ) a) Histogram representing the positive predictive power of the combined 5 factors compared with the predictive power of the ENCODE factors whose expression levels are tightly correlated with METTL3 expression. b) Correlation between CEBPZ and METTL3 mRNA expression levels in the Human Protein Atlas RNA-seq datasets, including non-transformed (blue) and cancer (pink) cell lines. (ρ= Spearmann correlation coefficient). c) Genomic plot of METTL3 and CEBPZ normalised ChIP-seq datasets on the human SP1 and SP2 gene loci in MOLM13 and K562 cells, respectively. d) Distribution and heatmaps of normalised ChIP-seq reads for METTL3 centred on CEBPZ peaks. e) Distribution and heatmaps of normalised ChIP-seq reads of METTL14 and CEBPZ centred on METTL14 (left panel) and CEBPZ (right panel) peaks. f) Competitive co-culture assay showing negative selection of BFP+ AML cell lines upon targeting of CEBPZ by CRISPR-Cas9 gRNAs. Cells were transduced with lentiviruses expressing a gRNA targeting the first exon of CEBPZ and the BFP-positive fraction was compared with the non-transduced population. Results were normalized to those at day 4. The mean +S.D. of two independent infections is shown. g) CEBPZ mRNA levels detected by RT-qPCR 4 days after shRNA induction with doxycycline in MOLM13 cells. The mean ±S.D. of three independent cultures is shown. h) A proliferation assay of the CEBPZ CTRL and KD cells was performed with cell numbers measured between day 0 (4d post doxycycline) and day 4 (8d post doxycycline). The mean ±S.D. of six independent replicates is shown. i) ChIP-qPCR of METTL3 binding on target TSSs in and MOLM13 cells, expressing a control shRNA or two independent shRNAs against CEBPZ, showing a specific reduction of METTL3 binding in CEBPZ KD cells. The mean of three technical replicates +S.D. is shown. The experiment was performed independently three times. j) . Figure 2
    Figure Legend Snippet: CEBPZ recruits METTL3 on chromatin. (Related to ) a) Histogram representing the positive predictive power of the combined 5 factors compared with the predictive power of the ENCODE factors whose expression levels are tightly correlated with METTL3 expression. b) Correlation between CEBPZ and METTL3 mRNA expression levels in the Human Protein Atlas RNA-seq datasets, including non-transformed (blue) and cancer (pink) cell lines. (ρ= Spearmann correlation coefficient). c) Genomic plot of METTL3 and CEBPZ normalised ChIP-seq datasets on the human SP1 and SP2 gene loci in MOLM13 and K562 cells, respectively. d) Distribution and heatmaps of normalised ChIP-seq reads for METTL3 centred on CEBPZ peaks. e) Distribution and heatmaps of normalised ChIP-seq reads of METTL14 and CEBPZ centred on METTL14 (left panel) and CEBPZ (right panel) peaks. f) Competitive co-culture assay showing negative selection of BFP+ AML cell lines upon targeting of CEBPZ by CRISPR-Cas9 gRNAs. Cells were transduced with lentiviruses expressing a gRNA targeting the first exon of CEBPZ and the BFP-positive fraction was compared with the non-transduced population. Results were normalized to those at day 4. The mean +S.D. of two independent infections is shown. g) CEBPZ mRNA levels detected by RT-qPCR 4 days after shRNA induction with doxycycline in MOLM13 cells. The mean ±S.D. of three independent cultures is shown. h) A proliferation assay of the CEBPZ CTRL and KD cells was performed with cell numbers measured between day 0 (4d post doxycycline) and day 4 (8d post doxycycline). The mean ±S.D. of six independent replicates is shown. i) ChIP-qPCR of METTL3 binding on target TSSs in and MOLM13 cells, expressing a control shRNA or two independent shRNAs against CEBPZ, showing a specific reduction of METTL3 binding in CEBPZ KD cells. The mean of three technical replicates +S.D. is shown. The experiment was performed independently three times. j) . Figure 2

    Techniques Used: Expressing, RNA Sequencing Assay, Transformation Assay, Chromatin Immunoprecipitation, Co-culture Assay, Selection, CRISPR, Transduction, Quantitative RT-PCR, shRNA, Proliferation Assay, Real-time Polymerase Chain Reaction, Binding Assay

    Validation of the m6A RNA-IP upon METTL3 depletion. (Related to ) a) Motif analysis under the identified m6A-IP peaks showing enrichment of the expected UGCAG and GGACU sequences and their central distribution throughout the m6A-IP peaks, as obtained by MEME and CentriMo. b) Distribution of m6A-IP reads throughout the mRNA metatranscript, showing the expected enrichment around the STOP codon in MOML13 cells. c) Scatter plots and density plot showing the general down-regulation of m6A-IP signal upon METTL3 knock-down in MOLM13 cells. d) Histogram showing METTL3–dependent m6A-IP read coverage in mRNAs from METTL3-bound TSSs (ChIP), whole transcriptome (All) or the permutation of random sets of genes (Rand). e) m6A-IP followed by qPCR for m6A peaks of HNRNPL or GAPDH as a control. The plot show the m6A-IP signal over total input in MOLM 13 cells expressing a control shRNA or shRNAs targeting CEBPZ. Mean ±S.D. of three technical replicates are shown; the experiment has been performed independently twice. f) SP1, SP2, HNRNPL and METTL3 mRNA levels detected by RT-qPCR 8 days after doxycycline induction in MOLM13 CTRL or CEBPZ KD cells. The mean ±S.D. of three independent cultures is shown. g) Histogram showing the enrichment of the [GAG] n motif within the transcript sequences of METTL3 ChIP-targets compared with random permutations of genes. Figure 3
    Figure Legend Snippet: Validation of the m6A RNA-IP upon METTL3 depletion. (Related to ) a) Motif analysis under the identified m6A-IP peaks showing enrichment of the expected UGCAG and GGACU sequences and their central distribution throughout the m6A-IP peaks, as obtained by MEME and CentriMo. b) Distribution of m6A-IP reads throughout the mRNA metatranscript, showing the expected enrichment around the STOP codon in MOML13 cells. c) Scatter plots and density plot showing the general down-regulation of m6A-IP signal upon METTL3 knock-down in MOLM13 cells. d) Histogram showing METTL3–dependent m6A-IP read coverage in mRNAs from METTL3-bound TSSs (ChIP), whole transcriptome (All) or the permutation of random sets of genes (Rand). e) m6A-IP followed by qPCR for m6A peaks of HNRNPL or GAPDH as a control. The plot show the m6A-IP signal over total input in MOLM 13 cells expressing a control shRNA or shRNAs targeting CEBPZ. Mean ±S.D. of three technical replicates are shown; the experiment has been performed independently twice. f) SP1, SP2, HNRNPL and METTL3 mRNA levels detected by RT-qPCR 8 days after doxycycline induction in MOLM13 CTRL or CEBPZ KD cells. The mean ±S.D. of three independent cultures is shown. g) Histogram showing the enrichment of the [GAG] n motif within the transcript sequences of METTL3 ChIP-targets compared with random permutations of genes. Figure 3

    Techniques Used: Chromatin Immunoprecipitation, Real-time Polymerase Chain Reaction, Expressing, shRNA, Quantitative RT-PCR

    13) Product Images from "Disruption of Epithelial HDAC3 in Intestine Prevents Diet-induced Obesity in Mice"

    Article Title: Disruption of Epithelial HDAC3 in Intestine Prevents Diet-induced Obesity in Mice

    Journal: Gastroenterology

    doi: 10.1053/j.gastro.2018.04.017

    HDAC3 regulates expression of microbiota-dependent metabolic pathways in IECs RNA-sequencing was performed on IECs isolated from mid-distal small intestine. Volcano plots of differential gene expression between ( A ) germ-free (GF) versus microbiota-replete conventionally-housed (CNV) mice and ( B ) HDAC3 FF versus HDAC3 ΔIEC mice, n=2 per group. ( C ) Venn analysis of genes enriched in lipid metabolism that are dependent on the microbiota and HDAC3. Heat-map of relative transcript abundance of overlapping genes. ( D ) mRNA expression by real-time PCR in IECs from the small intestine. (E ) ChIP-qPCR comparing H3K9Ac levels at Phosphoenolpyruvate Carboxykinase 1 (PCK1 ) promoter in IECs ( F ) TRANSFAC identification of transcription factor binding motifs within hyperacetylated region of PCK1 promoter. Data represent 3-6 mice per group. Results are shown as mean ± s.e.m. * p
    Figure Legend Snippet: HDAC3 regulates expression of microbiota-dependent metabolic pathways in IECs RNA-sequencing was performed on IECs isolated from mid-distal small intestine. Volcano plots of differential gene expression between ( A ) germ-free (GF) versus microbiota-replete conventionally-housed (CNV) mice and ( B ) HDAC3 FF versus HDAC3 ΔIEC mice, n=2 per group. ( C ) Venn analysis of genes enriched in lipid metabolism that are dependent on the microbiota and HDAC3. Heat-map of relative transcript abundance of overlapping genes. ( D ) mRNA expression by real-time PCR in IECs from the small intestine. (E ) ChIP-qPCR comparing H3K9Ac levels at Phosphoenolpyruvate Carboxykinase 1 (PCK1 ) promoter in IECs ( F ) TRANSFAC identification of transcription factor binding motifs within hyperacetylated region of PCK1 promoter. Data represent 3-6 mice per group. Results are shown as mean ± s.e.m. * p

    Techniques Used: Expressing, RNA Sequencing Assay, Isolation, Mouse Assay, Real-time Polymerase Chain Reaction, Chromatin Immunoprecipitation, Binding Assay

    14) Product Images from "Siah2 control of T-regulatory cells limits anti-tumor immunity"

    Article Title: Siah2 control of T-regulatory cells limits anti-tumor immunity

    Journal: Nature Communications

    doi: 10.1038/s41467-019-13826-7

    Siah2 −/− effect on cell proliferation is p27-dependent a , b Jurkat cells were depleted of Siah2 alone or of Siah2 and p27 via infection with lentivirus harboring indicated shRNAs. Proteins prepared were analyzed by immunoblot for p27 and GAPDH as loading control ( n = 4; relative intensity of p27 shown in the graphs) a , while RNA prepared was processed for qPCR analysis of Ki67 transcripts b . c Ccl17 and Ccl22 mRNA expression, as identified by single-cell RNAseq within dendritic cell clusters (C14 and C18) in both genotypes. d Cxcl9 mRNA expression, as identified by single-cell RNAseq within dendritic cell clusters (C14 and C18) in both genotypes. e Ccl17 and Ccl22 mRNA expression of CD11c + -sorted cells from tumors from both genotypes. Ten tumors were collected per sample 11 days after YUMMER1.7 cell inoculation. Data are representative of two independent experiments. f – h Weight of tumors collected 19 days after YUMMER1.7 cell inoculation of WT mice, which were injected i.p. with CCL17 and CCL22 neutralizing antibodies every other day, starting 3 days after melanoma cell inoculation ( n = 4) f . At the end of the treatment described in f (day 19), tumors were collected and frequencies of tumor-infiltrating Foxp3 + cells within the CD4 + T cell population g and of IFN-γ- expressing CD8 + cells ( n = 4) were determined h . i Loss of Siah2 synergizes with PD1 therapy. Mean growth curves over time of tumors derived from YUMM1.7 cells (150,000) injected into WT and Siah2 −/− mice, which were then treated with anti-PD-1 antibody (200 μg/mouse; three times per week for a total of five times) or rat isotype (IgG) starting at day 7 after melanoma cell injection. WT and Siah2 −/− IgG ( n = 8); WT and Siah2 −/− anti - PD-1 antibodies ( n = 7). Shown are complete regression (CR) rates at study termination. j Positive correlation between Siah2 and Foxp3 expression in immunogenic melanoma tumors. Spearman’s rank correlation plots (scatterplots) for pairwise comparisons between SIAH2 expression (mRNA z -scores) and the Genset identified in Treg immune signature seen in Siah2 −/− mice expressed in the metastatic samples with high immune signals from TCGA_SKCM ( n = 66) 48 ; mean ± s.e.m. Data were analyzed by Wilcoxon rank-sum test c , d , unpaired t -test a , b , f – h or two-way ANOVA with Bonferroni multiple comparison i . *** P
    Figure Legend Snippet: Siah2 −/− effect on cell proliferation is p27-dependent a , b Jurkat cells were depleted of Siah2 alone or of Siah2 and p27 via infection with lentivirus harboring indicated shRNAs. Proteins prepared were analyzed by immunoblot for p27 and GAPDH as loading control ( n = 4; relative intensity of p27 shown in the graphs) a , while RNA prepared was processed for qPCR analysis of Ki67 transcripts b . c Ccl17 and Ccl22 mRNA expression, as identified by single-cell RNAseq within dendritic cell clusters (C14 and C18) in both genotypes. d Cxcl9 mRNA expression, as identified by single-cell RNAseq within dendritic cell clusters (C14 and C18) in both genotypes. e Ccl17 and Ccl22 mRNA expression of CD11c + -sorted cells from tumors from both genotypes. Ten tumors were collected per sample 11 days after YUMMER1.7 cell inoculation. Data are representative of two independent experiments. f – h Weight of tumors collected 19 days after YUMMER1.7 cell inoculation of WT mice, which were injected i.p. with CCL17 and CCL22 neutralizing antibodies every other day, starting 3 days after melanoma cell inoculation ( n = 4) f . At the end of the treatment described in f (day 19), tumors were collected and frequencies of tumor-infiltrating Foxp3 + cells within the CD4 + T cell population g and of IFN-γ- expressing CD8 + cells ( n = 4) were determined h . i Loss of Siah2 synergizes with PD1 therapy. Mean growth curves over time of tumors derived from YUMM1.7 cells (150,000) injected into WT and Siah2 −/− mice, which were then treated with anti-PD-1 antibody (200 μg/mouse; three times per week for a total of five times) or rat isotype (IgG) starting at day 7 after melanoma cell injection. WT and Siah2 −/− IgG ( n = 8); WT and Siah2 −/− anti - PD-1 antibodies ( n = 7). Shown are complete regression (CR) rates at study termination. j Positive correlation between Siah2 and Foxp3 expression in immunogenic melanoma tumors. Spearman’s rank correlation plots (scatterplots) for pairwise comparisons between SIAH2 expression (mRNA z -scores) and the Genset identified in Treg immune signature seen in Siah2 −/− mice expressed in the metastatic samples with high immune signals from TCGA_SKCM ( n = 66) 48 ; mean ± s.e.m. Data were analyzed by Wilcoxon rank-sum test c , d , unpaired t -test a , b , f – h or two-way ANOVA with Bonferroni multiple comparison i . *** P

    Techniques Used: Infection, Real-time Polymerase Chain Reaction, Expressing, Mouse Assay, Injection, Derivative Assay

    Reduced proliferation of tumor-infiltrating Tregs in Siah2 − / − mice. a t -SNE plot of CD45 + cells from melanoma tumors collected 11 days after inoculation of YUMMER1.7 cells into WT or Siah2 −/− mice, showing different clusters. b Color-coded bars (left) and table (right) represent proportions of cells in each cluster within CD45 + clusters from WT and Siah2 −/− tumors. c Bar graphs showing cell cycle status of T cells, based on single-cell RNAseq in Siah2 WT and Siah2 −/− cells. d Expression of Ki67 (MKi67) mRNA identified by single-cell RNAseq within indicated clusters in both genotypes. e Violin plot comparing expression levels of E2F1-regulated genes based on single-cell RNAseq. f BrdU was injected into Siah2 WT and Siah2 −/− mice-bearing YUMMER1.7 melanoma tumors 16 h before tumor collection. Shown is BrdU incorporation by T cells, as determined by flow cytometry ( n = 5). g Ki67(red)/Foxp3(green) staining of tumors from Siah2 WT or Siah2 −/− mice analyzed 11 days after melanoma cell injection (left panels), plus quantification (right; n = 3). Scale bar, 100 μm; mean ± s.e.m. Data were analyzed by unpaired t -test in f and g , and by Wilcoxon rank-sum test in d and e . ** P
    Figure Legend Snippet: Reduced proliferation of tumor-infiltrating Tregs in Siah2 − / − mice. a t -SNE plot of CD45 + cells from melanoma tumors collected 11 days after inoculation of YUMMER1.7 cells into WT or Siah2 −/− mice, showing different clusters. b Color-coded bars (left) and table (right) represent proportions of cells in each cluster within CD45 + clusters from WT and Siah2 −/− tumors. c Bar graphs showing cell cycle status of T cells, based on single-cell RNAseq in Siah2 WT and Siah2 −/− cells. d Expression of Ki67 (MKi67) mRNA identified by single-cell RNAseq within indicated clusters in both genotypes. e Violin plot comparing expression levels of E2F1-regulated genes based on single-cell RNAseq. f BrdU was injected into Siah2 WT and Siah2 −/− mice-bearing YUMMER1.7 melanoma tumors 16 h before tumor collection. Shown is BrdU incorporation by T cells, as determined by flow cytometry ( n = 5). g Ki67(red)/Foxp3(green) staining of tumors from Siah2 WT or Siah2 −/− mice analyzed 11 days after melanoma cell injection (left panels), plus quantification (right; n = 3). Scale bar, 100 μm; mean ± s.e.m. Data were analyzed by unpaired t -test in f and g , and by Wilcoxon rank-sum test in d and e . ** P

    Techniques Used: Mouse Assay, Expressing, Injection, BrdU Incorporation Assay, Flow Cytometry, Cytometry, Staining

    15) Product Images from "Global analyses of endonucleolytic cleavage in mammals reveal expanded repertoires of cleavage-inducing small RNAs and their targets"

    Article Title: Global analyses of endonucleolytic cleavage in mammals reveal expanded repertoires of cleavage-inducing small RNAs and their targets

    Journal: Nucleic Acids Research

    doi: 10.1093/nar/gkw164

    Prediction of sciRNA-mediated mRNA cleavage events. ( A ) Bioinformatic pipeline schematic. ( B ) Left panel: average SNR for each mismatch cutoff in mESCs; right panel: optimal mismatch cutoff corresponding to the maximum average SNR for each data set. ( C ) Venn diagram of sciRNAs identified in mESCs, testis 6M PN, and cerebellum 6M PN. ( D ) Pie chart of sciRNA annotations (total = 398, combining sciRNAs from 3 cell types). ( E ) An example of predicted sciRNA-mediated cleavage. Read distributions are shown for the 3′ UTR of the Mtrr gene in Deg-Seq data of wild type (WT, red) and Ago2 knockout (blue) mESCs. Alignment of the sciRNA to the Deg-Seq peak is shown in a box, where a solid line indicates a base pair match, dotted line indicates a G = U wobble, X indicates a mismatch, and black arrow indicates location of the Deg-Seq peak. ( F ) Experimental validation of target RNA cleavage mediated by small RNAs. A total of 200 ng of Kpna4, NONMMUG002900, Zfp389 or NONMMUG003416 ( Trafip2-as ) RNA were incubated with different amount of HeLa S100 loaded with 50 nM synthetic sciRNA at 37°C for 30 min. Arrows indicate cleaved 5′ RNA fragments (whose sizes are consistent with predicted cleavage products). Small RNA/target RNA sequences are shown with arrowheads indicating the predicted cleavage sites (4 sites identified as Deg-Seq peaks in Zfp389 ).
    Figure Legend Snippet: Prediction of sciRNA-mediated mRNA cleavage events. ( A ) Bioinformatic pipeline schematic. ( B ) Left panel: average SNR for each mismatch cutoff in mESCs; right panel: optimal mismatch cutoff corresponding to the maximum average SNR for each data set. ( C ) Venn diagram of sciRNAs identified in mESCs, testis 6M PN, and cerebellum 6M PN. ( D ) Pie chart of sciRNA annotations (total = 398, combining sciRNAs from 3 cell types). ( E ) An example of predicted sciRNA-mediated cleavage. Read distributions are shown for the 3′ UTR of the Mtrr gene in Deg-Seq data of wild type (WT, red) and Ago2 knockout (blue) mESCs. Alignment of the sciRNA to the Deg-Seq peak is shown in a box, where a solid line indicates a base pair match, dotted line indicates a G = U wobble, X indicates a mismatch, and black arrow indicates location of the Deg-Seq peak. ( F ) Experimental validation of target RNA cleavage mediated by small RNAs. A total of 200 ng of Kpna4, NONMMUG002900, Zfp389 or NONMMUG003416 ( Trafip2-as ) RNA were incubated with different amount of HeLa S100 loaded with 50 nM synthetic sciRNA at 37°C for 30 min. Arrows indicate cleaved 5′ RNA fragments (whose sizes are consistent with predicted cleavage products). Small RNA/target RNA sequences are shown with arrowheads indicating the predicted cleavage sites (4 sites identified as Deg-Seq peaks in Zfp389 ).

    Techniques Used: Knock-Out, Incubation

    16) Product Images from "mRNA Cap Methyltransferase, RNMT-RAM, Promotes RNA Pol II-Dependent Transcription"

    Article Title: mRNA Cap Methyltransferase, RNMT-RAM, Promotes RNA Pol II-Dependent Transcription

    Journal: Cell Reports

    doi: 10.1016/j.celrep.2018.04.004

    RNMT-RAM Regulates Transcription Independent of mRNA Cap Methylation (A–C) HeLa cells incubated with 60 μM 3 H-uridine for 30 min. Transcripts were poly(A) selected. Relative 3 H-uridine incorporation was normalized to poly(A) RNA (n = 3). (A) Cells transfected with RAM siRNAs or non-targeting control (sc siRNA) for 36 hr. (B) Cells transfected with RAM siRNA or sc siRNA for 36 hr, and HA-RNMT was induced with doxycycline for 12 hr. (C) Cells transfected with pcDNA5 Fg-RAM and pcDNA5 HA-RNMT wild-type (WT), methyltransferase-dead (MTD), or vector control for 48 hr. Representative western blots are shown. (D) HeLa nuclei incubated with NTPs, BrUTP, and recombinant RNMT (FL)-RAM (1–90) for 20 min. Br-RNA was purified and used as a substrate for RT-PCR. Primers are indicated (n = 4). (E) HeLa cells transfected with RAM siRNAs or sc siRNA for 36 hr. Levels of mature and pre-mRNA were determined by RT-PCR relative to sc siRNA control (n = 4). For charts, average and SD are indicated. Student’s t test was performed. ∗ p
    Figure Legend Snippet: RNMT-RAM Regulates Transcription Independent of mRNA Cap Methylation (A–C) HeLa cells incubated with 60 μM 3 H-uridine for 30 min. Transcripts were poly(A) selected. Relative 3 H-uridine incorporation was normalized to poly(A) RNA (n = 3). (A) Cells transfected with RAM siRNAs or non-targeting control (sc siRNA) for 36 hr. (B) Cells transfected with RAM siRNA or sc siRNA for 36 hr, and HA-RNMT was induced with doxycycline for 12 hr. (C) Cells transfected with pcDNA5 Fg-RAM and pcDNA5 HA-RNMT wild-type (WT), methyltransferase-dead (MTD), or vector control for 48 hr. Representative western blots are shown. (D) HeLa nuclei incubated with NTPs, BrUTP, and recombinant RNMT (FL)-RAM (1–90) for 20 min. Br-RNA was purified and used as a substrate for RT-PCR. Primers are indicated (n = 4). (E) HeLa cells transfected with RAM siRNAs or sc siRNA for 36 hr. Levels of mature and pre-mRNA were determined by RT-PCR relative to sc siRNA control (n = 4). For charts, average and SD are indicated. Student’s t test was performed. ∗ p

    Techniques Used: Methylation, Incubation, Transfection, Plasmid Preparation, Western Blot, Recombinant, Purification, Reverse Transcription Polymerase Chain Reaction

    17) Product Images from "Episomal HBV persistence within transcribed host nuclear chromatin compartments involves HBx"

    Article Title: Episomal HBV persistence within transcribed host nuclear chromatin compartments involves HBx

    Journal: Epigenetics & Chromatin

    doi: 10.1186/s13072-018-0204-2

    Several euchromatin markers are enriched at HBV cccDNA, and suppression of HBx-mRNA expression via FANA antisense oligonucleotides leads to a reduction in episomal HBV DNA in HepG2.2.15 cells. a This figure outlines (from top to bottom) RNA-seq data for cccDNA mRNA transcription (consensus data from HepaRG, HepG2.2.15 and HepG2 H1.3), as well as ChIP-seq derived enrichment of Pol2 (dark blue tracks), H3K4me3 (cyan), H3K36me3 (green), H3K27me3 (red) and HBx (gray). Enrichment peaks are indicated at the top, and read coverage is presented below. Results from RNA-seq suggest that remarkable amounts of mRNA are synthesized from ORF S and ORF X. ChIP-seq reveals that in these cells ‘active’ transcription markers, such as Pol2 and H3K4me3, are enriched at HBV cccDNA. The highest amount of H3K36me3 seemed to be present at the 3′-ends of ORF S and ORF X, whereas comparably low amounts of H3K27me3 were associated with cccDNA. b ]). c This figure outlines a time course of episomal HBV DNA quantification by PCR in HepG2.2.15 cells under the influence of FANA oligonucleotide treatment targeting HBx-mRNA. Specifically, two different oligos (HBx-oligo1/HBx-oligo2) or an oligo mixture (HBx-oligo-mix) was used to suppress HBx-mRNA. For normalization, we performed similar experiments where a scrambled non-sense FANA oligonucleotide was used. This figure demonstrates the increasing attenuation of HBV DNA over time under the influence of FANA oligonucleotide anti-HBx treatment
    Figure Legend Snippet: Several euchromatin markers are enriched at HBV cccDNA, and suppression of HBx-mRNA expression via FANA antisense oligonucleotides leads to a reduction in episomal HBV DNA in HepG2.2.15 cells. a This figure outlines (from top to bottom) RNA-seq data for cccDNA mRNA transcription (consensus data from HepaRG, HepG2.2.15 and HepG2 H1.3), as well as ChIP-seq derived enrichment of Pol2 (dark blue tracks), H3K4me3 (cyan), H3K36me3 (green), H3K27me3 (red) and HBx (gray). Enrichment peaks are indicated at the top, and read coverage is presented below. Results from RNA-seq suggest that remarkable amounts of mRNA are synthesized from ORF S and ORF X. ChIP-seq reveals that in these cells ‘active’ transcription markers, such as Pol2 and H3K4me3, are enriched at HBV cccDNA. The highest amount of H3K36me3 seemed to be present at the 3′-ends of ORF S and ORF X, whereas comparably low amounts of H3K27me3 were associated with cccDNA. b ]). c This figure outlines a time course of episomal HBV DNA quantification by PCR in HepG2.2.15 cells under the influence of FANA oligonucleotide treatment targeting HBx-mRNA. Specifically, two different oligos (HBx-oligo1/HBx-oligo2) or an oligo mixture (HBx-oligo-mix) was used to suppress HBx-mRNA. For normalization, we performed similar experiments where a scrambled non-sense FANA oligonucleotide was used. This figure demonstrates the increasing attenuation of HBV DNA over time under the influence of FANA oligonucleotide anti-HBx treatment

    Techniques Used: Expressing, RNA Sequencing Assay, Chromatin Immunoprecipitation, Derivative Assay, Synthesized, Polymerase Chain Reaction

    18) Product Images from "LINE-1 derepression in senescent cells triggers interferon and inflammaging"

    Article Title: LINE-1 derepression in senescent cells triggers interferon and inflammaging

    Journal: Nature

    doi: 10.1038/s41586-018-0784-9

    Characterization of L1 effectors and the IFN-I response. a, Expression of TREX1 was determined by RT-qPCR and immunoblotting. For gel source data see Supplementary Fig. 1 . b, Expression of RB family genes was compared by RT-qPCR. Primer pairs for all genes were verified to be of equivalent efficiency. c, Enrichment of H3K9me3 and H3K27me3 on L1 elements was examined by ChIP-qPCR (PCR primers illustrated in Fig. 1b were used: 5’UTR, amplicon A; ORF1, amplicon E; ORF2, amplicon F). d, ChIP-seq data from ENCODE were investigated for transcription factors that bind to the L1 consensus sequence. The log2 fold change enrichment relative to input controls is shown for the indicated cell-lines. The binding of YY1 to the L1 promoter has been documented 69 and was used as a positive control. CEBPB was used as a negative control. A schematic illustrating L1 coordinates and relevant features is shown above. Amplicons A-E are the same as shown in Fig. 1b . e , Transcriptional activity of the intact L1 5’UTR or a UTR lacking the FOXA1 binding site (UTR-Δ) was determined using sense and antisense reporters cotransfected into early passage LF1 cells either with a FOXA1 expression plasmid or empty vector (EV). f, FOXA1 was knocked down in senescent cells with shFOXA1 (a) (see also Fig. 2e and Extended Data Fig. 5a ) and binding to the L1 5’UTR (amplicon B) was determined by ChIP-qPCR. g, Knockdown of RB1, TREX1 and ectopic expression of FOXA1 were performed in early passage cells in all single (1X), double (2X) and triple (3X) combinations and assessed by RT-qPCR using poly(A)-purified RNA for activation of L1, IFN-α and IFN-β1 expression (primers for amplicon F). Three controls are shown: cells infected with irrelevant shRNA (shGFP), expression construct (LacZ), or uninfected early passage cells (EP). h, L1 5’UTR occupancy of RB1 and FOXA1 in 3X cells was determined by ChIP-qPCR performed as in Fig. 2a, b . Primers for amplicons A and B were used for RB1 and FOXA1, respectively. For comparison, single interventions in early passage cells with shRB1 (a) or FOXA1 cDNA expression (EP FOXA1-OE) are also shown. i, Confirmation of full length L1 mRNA expression in 3X cells using RT-qPCR with primers for amplicons A and F on poly(A)-purified RNA. CTR, cells infected with irrelevant shRNA (shGFP). j , Heat map representation showing all biological replicates for the 67 genes significantly changing expression in SEN and/or 3X cells ( Fig. 2h , Supplementary Table 6 ). Column clustering was calculated as 1-Pearson correlation. Rows have been grouped into functional subsets of the IFN-I response. k , Venn diagram showing the overlap between the 67 significantly changing genes. ( a - f , h ) n = 3 independent biological samples, repeated in 2 independent experiments. ( g , i ), n = 3 independent experiments. ( a - i ) Data are mean ±s.d. * P ≤ 0.05, ** P ≤ 0.01, unpaired two-sided t -tests. Exact P values can be found in the accompanying Source Data.
    Figure Legend Snippet: Characterization of L1 effectors and the IFN-I response. a, Expression of TREX1 was determined by RT-qPCR and immunoblotting. For gel source data see Supplementary Fig. 1 . b, Expression of RB family genes was compared by RT-qPCR. Primer pairs for all genes were verified to be of equivalent efficiency. c, Enrichment of H3K9me3 and H3K27me3 on L1 elements was examined by ChIP-qPCR (PCR primers illustrated in Fig. 1b were used: 5’UTR, amplicon A; ORF1, amplicon E; ORF2, amplicon F). d, ChIP-seq data from ENCODE were investigated for transcription factors that bind to the L1 consensus sequence. The log2 fold change enrichment relative to input controls is shown for the indicated cell-lines. The binding of YY1 to the L1 promoter has been documented 69 and was used as a positive control. CEBPB was used as a negative control. A schematic illustrating L1 coordinates and relevant features is shown above. Amplicons A-E are the same as shown in Fig. 1b . e , Transcriptional activity of the intact L1 5’UTR or a UTR lacking the FOXA1 binding site (UTR-Δ) was determined using sense and antisense reporters cotransfected into early passage LF1 cells either with a FOXA1 expression plasmid or empty vector (EV). f, FOXA1 was knocked down in senescent cells with shFOXA1 (a) (see also Fig. 2e and Extended Data Fig. 5a ) and binding to the L1 5’UTR (amplicon B) was determined by ChIP-qPCR. g, Knockdown of RB1, TREX1 and ectopic expression of FOXA1 were performed in early passage cells in all single (1X), double (2X) and triple (3X) combinations and assessed by RT-qPCR using poly(A)-purified RNA for activation of L1, IFN-α and IFN-β1 expression (primers for amplicon F). Three controls are shown: cells infected with irrelevant shRNA (shGFP), expression construct (LacZ), or uninfected early passage cells (EP). h, L1 5’UTR occupancy of RB1 and FOXA1 in 3X cells was determined by ChIP-qPCR performed as in Fig. 2a, b . Primers for amplicons A and B were used for RB1 and FOXA1, respectively. For comparison, single interventions in early passage cells with shRB1 (a) or FOXA1 cDNA expression (EP FOXA1-OE) are also shown. i, Confirmation of full length L1 mRNA expression in 3X cells using RT-qPCR with primers for amplicons A and F on poly(A)-purified RNA. CTR, cells infected with irrelevant shRNA (shGFP). j , Heat map representation showing all biological replicates for the 67 genes significantly changing expression in SEN and/or 3X cells ( Fig. 2h , Supplementary Table 6 ). Column clustering was calculated as 1-Pearson correlation. Rows have been grouped into functional subsets of the IFN-I response. k , Venn diagram showing the overlap between the 67 significantly changing genes. ( a - f , h ) n = 3 independent biological samples, repeated in 2 independent experiments. ( g , i ), n = 3 independent experiments. ( a - i ) Data are mean ±s.d. * P ≤ 0.05, ** P ≤ 0.01, unpaired two-sided t -tests. Exact P values can be found in the accompanying Source Data.

    Techniques Used: Expressing, Quantitative RT-PCR, Chromatin Immunoprecipitation, Real-time Polymerase Chain Reaction, Polymerase Chain Reaction, Amplification, Sequencing, Binding Assay, Positive Control, Negative Control, Activity Assay, Plasmid Preparation, Purification, Activation Assay, Infection, shRNA, Construct, Functional Assay

    Establishment of senescent cultures and analysis of L1 and IFN-I activation. a, Passaging regimen to obtain long-term replicatively senescent cells (details in Methods ). Point A was designated as zero for time in senescence. b-d, Confirmation of the senescent status of cultures. A representative experiment is shown; other experiments were monitored in the same manner and generated data that met these benchmarks. EP, early passage control; SEN (E), early senescence (8 weeks); SEN (L), late senescence (16 weeks). b, Cells were labeled with BrdU for 6 hours. BrdU incorporation 67 and senescence-associated β-galactosidase (SA-β-Gal) activity 66 were determined as indicated. DNA damage foci were visualized using γ-H2AX antibodies and immunofluorescence microscopy (IF) 34 . c , Expression of p21 (CDKN1A) and p16 (CDKN2A) proteins was determined by immunoblotting. GAPDH was the loading control. For gel source data see Supplementary Fig. 1 . d , Expression of genes characteristic of the SASP was determined by RT-qPCR. e, L1 activation during senescence of IMR-90 and WI-38 strains of fibroblasts was assessed by RT-qPCR using poly(A) purified RNA and primers for amplicon F ( Fig. 1b ). f , Long-range RT-PCR was performed with primers A-forward and C-reverse (amplicon G) and primers A-forward and D-reverse (amplicon H) ( Fig. 1b , Supplementary Table 1 ) and the cDNAs were cloned and sequenced. Several attempts using the same protocol on early passage proliferating cells did not yield any L1 clones. Sequences were mapped to the unmasked reference genome demanding 100% identify. 658 clones could be thus mapped, 51 additional clones contained at least 1 mismatch and thus likely represent elements that are polymorphic in the cell line, and 58 were cloning artifacts. Among the 658 mappable clones 224 unique elements were represented ( Supplementary Table 3 ). Intact elements are the subset of full length elements annotated with no ORF inactivating mutations. Size of the features corresponds to the number of times the element was represented among the 658 clones. g , Summary of long-range PCR data presented in (f) and Supplementary Table 3 . h , Apparent genomic copy numbers of elements detected with our amplicons (see Fig. 1b for locations of amplicons and Methods for primer design strategy). Predicted: in silico PCR ( Methods ). Observed: qPCR was performed on 1 ng of genomic DNA and normalized to a known single copy locus. i , Activation of IFN-α and IFN-β1 genes during senescence of WI-38 and IMR-90 cells was determined by RT-qPCR. j, Confirmation of the senescent status of cells in OIS (20 days, Fig. 1e ) and SIPS (30 days, Fig. 1e ) by SA-β-Gal activity. EV, empty vector control; CTR, non-irradiated cells. k, Confirmation of full length L1 mRNA expression in all forms of senescence using RT-qPCR with primers for amplicons A and F on poly(A)-purified RNA. Late onset activation is shown by comparing days 9 and 20 for OIS and days 12 and 30 for SIPS. ( b - e , i - k ), n = 3 independent biological samples, repeated in 2 independent experiments. Data are mean ±s.d. * P ≤ 0.05, ** P ≤ 0.01, unpaired two-sided t -tests. Exact P values can be found in the accompanying Source Data.
    Figure Legend Snippet: Establishment of senescent cultures and analysis of L1 and IFN-I activation. a, Passaging regimen to obtain long-term replicatively senescent cells (details in Methods ). Point A was designated as zero for time in senescence. b-d, Confirmation of the senescent status of cultures. A representative experiment is shown; other experiments were monitored in the same manner and generated data that met these benchmarks. EP, early passage control; SEN (E), early senescence (8 weeks); SEN (L), late senescence (16 weeks). b, Cells were labeled with BrdU for 6 hours. BrdU incorporation 67 and senescence-associated β-galactosidase (SA-β-Gal) activity 66 were determined as indicated. DNA damage foci were visualized using γ-H2AX antibodies and immunofluorescence microscopy (IF) 34 . c , Expression of p21 (CDKN1A) and p16 (CDKN2A) proteins was determined by immunoblotting. GAPDH was the loading control. For gel source data see Supplementary Fig. 1 . d , Expression of genes characteristic of the SASP was determined by RT-qPCR. e, L1 activation during senescence of IMR-90 and WI-38 strains of fibroblasts was assessed by RT-qPCR using poly(A) purified RNA and primers for amplicon F ( Fig. 1b ). f , Long-range RT-PCR was performed with primers A-forward and C-reverse (amplicon G) and primers A-forward and D-reverse (amplicon H) ( Fig. 1b , Supplementary Table 1 ) and the cDNAs were cloned and sequenced. Several attempts using the same protocol on early passage proliferating cells did not yield any L1 clones. Sequences were mapped to the unmasked reference genome demanding 100% identify. 658 clones could be thus mapped, 51 additional clones contained at least 1 mismatch and thus likely represent elements that are polymorphic in the cell line, and 58 were cloning artifacts. Among the 658 mappable clones 224 unique elements were represented ( Supplementary Table 3 ). Intact elements are the subset of full length elements annotated with no ORF inactivating mutations. Size of the features corresponds to the number of times the element was represented among the 658 clones. g , Summary of long-range PCR data presented in (f) and Supplementary Table 3 . h , Apparent genomic copy numbers of elements detected with our amplicons (see Fig. 1b for locations of amplicons and Methods for primer design strategy). Predicted: in silico PCR ( Methods ). Observed: qPCR was performed on 1 ng of genomic DNA and normalized to a known single copy locus. i , Activation of IFN-α and IFN-β1 genes during senescence of WI-38 and IMR-90 cells was determined by RT-qPCR. j, Confirmation of the senescent status of cells in OIS (20 days, Fig. 1e ) and SIPS (30 days, Fig. 1e ) by SA-β-Gal activity. EV, empty vector control; CTR, non-irradiated cells. k, Confirmation of full length L1 mRNA expression in all forms of senescence using RT-qPCR with primers for amplicons A and F on poly(A)-purified RNA. Late onset activation is shown by comparing days 9 and 20 for OIS and days 12 and 30 for SIPS. ( b - e , i - k ), n = 3 independent biological samples, repeated in 2 independent experiments. Data are mean ±s.d. * P ≤ 0.05, ** P ≤ 0.01, unpaired two-sided t -tests. Exact P values can be found in the accompanying Source Data.

    Techniques Used: Activation Assay, Passaging, Generated, Labeling, BrdU Incorporation Assay, Activity Assay, Immunofluorescence, Microscopy, Expressing, Quantitative RT-PCR, Purification, Amplification, Reverse Transcription Polymerase Chain Reaction, Clone Assay, Polymerase Chain Reaction, In Silico, Real-time Polymerase Chain Reaction, Plasmid Preparation, Irradiation

    Activation of L1, IFN-I and SASP in senescent cells. Gene expression was assessed by RT-qPCR. Poly(A)-purified RNA was used in all L1 assays. a, Time course of L1 activation. P values were calculated relative to EP, early passage control. b , Schematic of L1 RT-PCR strategy. Blue, sense; red, antisense (AS). For primer specificity see Extended Data Fig. 1f-h ; primer design see Methods . Primers for amplicon F were used in ( a ) and ( e ). c , Strand-specific L1 transcription was assessed using amplicons A-F. Transcription from the 5’UTR antisense promoter was also detected. SEN (L), late senescence (16 weeks). d , Induction of IFN-α and IFN-β1 mRNA levels. e , The temporal induction of genes associated with DNA damage (p21), SASP (IL-1β, CCL2, IL-6, MMP3), and the IFN-I response (IRF7, IFN-α, IFN-β1, OAS1). Row clustering was calculated as 1-Pearson correlation. RS, replicative senescence; OIS, oncogene induced senescence (elicited by Ha-RAS infection); SIPS, stress induced premature senescence (gamma irradiation). Controls: EP, early passage; EV, empty vector infected; CTR, non-irradiated. ( a , c - e ), n = 3 independent biological samples, repeated in 2 independent experiments. ( a , c , d ) Data are mean ±s.d. * P ≤ 0.05, ** P ≤ 0.01, unpaired two-sided t -tests. Exact P values can be found in the accompanying Source Data.
    Figure Legend Snippet: Activation of L1, IFN-I and SASP in senescent cells. Gene expression was assessed by RT-qPCR. Poly(A)-purified RNA was used in all L1 assays. a, Time course of L1 activation. P values were calculated relative to EP, early passage control. b , Schematic of L1 RT-PCR strategy. Blue, sense; red, antisense (AS). For primer specificity see Extended Data Fig. 1f-h ; primer design see Methods . Primers for amplicon F were used in ( a ) and ( e ). c , Strand-specific L1 transcription was assessed using amplicons A-F. Transcription from the 5’UTR antisense promoter was also detected. SEN (L), late senescence (16 weeks). d , Induction of IFN-α and IFN-β1 mRNA levels. e , The temporal induction of genes associated with DNA damage (p21), SASP (IL-1β, CCL2, IL-6, MMP3), and the IFN-I response (IRF7, IFN-α, IFN-β1, OAS1). Row clustering was calculated as 1-Pearson correlation. RS, replicative senescence; OIS, oncogene induced senescence (elicited by Ha-RAS infection); SIPS, stress induced premature senescence (gamma irradiation). Controls: EP, early passage; EV, empty vector infected; CTR, non-irradiated. ( a , c - e ), n = 3 independent biological samples, repeated in 2 independent experiments. ( a , c , d ) Data are mean ±s.d. * P ≤ 0.05, ** P ≤ 0.01, unpaired two-sided t -tests. Exact P values can be found in the accompanying Source Data.

    Techniques Used: Activation Assay, Expressing, Quantitative RT-PCR, Purification, Reverse Transcription Polymerase Chain Reaction, Amplification, Infection, Irradiation, Plasmid Preparation

    Efficacy of genetic and pharmacological interventions. a, Knockdowns with two distinct shRNAs (a, b) or b, ectopic cDNA expression were performed in senescent cells as described in Fig. 2d, e, g (also see Methods ). The effectiveness of these manipulations on their targets was assessed by RT-qPCR and immunoblotting. For gel source data see Supplementary Fig. 1 . c, RB1, TREX1 and FOXA1 mRNA and protein expression after the triple (3X) intervention ( Fig. 2f ). d, The effect of 3TC treatment on the relative abundance of L1HS sequences in senescent cells was determined by multiplex TaqMan qPCR on total DNA (primer set 6, Supplementary Table 1 ). SEN entry, 0 weeks in senescence ( Fig. 1a ; point A in Extended Data Fig. 1a ). 3TC was administered continuously from SEN entry until harvest 16 weeks later. e, The dual luciferase L1 reporter system 52 was used to determine the effect of 3TC dosing on retrotransposition. L1 reporters were introduced into early passage cells using lentivirus vectors ( Methods ) and cells were treated with 3TC for 4 days prior to harvest and assay. JM111, a defective reporter carrying mutations in ORF1 (absence of 3TC); L1RP, a retrotransposition competent reporter. f, The effect of 3TC dosing on the IFN-I response. The experiment above (d) was processed by RT-qPCR to determine the expression of IFN-α and IFN-β1. g, Knockdowns of L1 were performed with two distinct shRNAs (a, b) in senescent cells (as in Fig. 2d, e, g ) or 3X cells (as in Fig. 2g ). The effectiveness on L1 expression was assessed by RT-qPCR using poly(A)-purified RNA and primers F. h, Cells in the experiment in (g) were examined for levels of ORF1 protein by immunofluorescence (IF). Image analysis was performed with CellProfiler software ( Methods ). > 200 cells were examined for each condition (a.f.u., arbitrary fluorescence units). i, The L1 shRNA treatment in the experiment in (g) was substituted with 3TC treatment (10 μM) for the same period of time. j, Five different NRTIs (or combinations) were tested for effects on the IFN-I response. AZT (Zidovudine, 15 μM), ABC (Abacavir, 15 μM), FTC (Emtricitabine, 10 μM), 3TC, (Lamivudine, 10 μM), TZV (Trizivir, a combination of 15 μM AZT, 15 μM ABC and 7.5 μM 3TC). Cells were treated for 4 weeks between 12 and 16 weeks in senescence ( Fig. 1a ; points D and E in Extended Data Fig. 1a ). 3X cells ( Fig. 2f ) were treated with 3TC for 48 hours after the completion of the last drug selection. Interferon α expression was determined by RT-qPCR. k, A native L1 reporter (pLD143) 53 was co-transfected with shRNA plasmid vectors into HeLa cells ( Methods ). Retrotransposition was scored as GFP-positive cells, and shL1 knockdowns were normalized to a shLuc negative control. The absolute average retrotransposition frequency (percentage of GFP-positive cells) was 4.1, which matches the published values for the reporter used (pLD143) 53 . l, Knockdowns of cGAS and STING were performed in senescent or 3X cells as with the other shRNAs ( Fig. 2d, e, g and a, g above). m, Downregulation of interferon signaling after CRISPR-mediated inactivation of IFNAR1 and IFNAR2 genes was verified by the absence of IRF9 nuclear translocation and STAT2 phosphorylation in response to interferon stimulation. Cells were infected with lentivirus vectors expressing Cas9 and gRNAs to both IFNAR1 and IFNAR2 (ΔIFNAR, Methods ). After the infection cells were re-seeded on coverslips, treated with interferon for 2 hours, and examined by IF microscopy. The experiment was repeated 3 times with similar results. ( a - i , l ) n = 3 independent experiments. ( k ) n = 3 independent biological samples, repeated in 2 independent experiments. ( a - l ) Data are mean ±s.d. * P ≤ 0.05, ** P ≤ 0.01, unpaired two-sided t -tests. Exact P values can be found in the accompanying Source Data.
    Figure Legend Snippet: Efficacy of genetic and pharmacological interventions. a, Knockdowns with two distinct shRNAs (a, b) or b, ectopic cDNA expression were performed in senescent cells as described in Fig. 2d, e, g (also see Methods ). The effectiveness of these manipulations on their targets was assessed by RT-qPCR and immunoblotting. For gel source data see Supplementary Fig. 1 . c, RB1, TREX1 and FOXA1 mRNA and protein expression after the triple (3X) intervention ( Fig. 2f ). d, The effect of 3TC treatment on the relative abundance of L1HS sequences in senescent cells was determined by multiplex TaqMan qPCR on total DNA (primer set 6, Supplementary Table 1 ). SEN entry, 0 weeks in senescence ( Fig. 1a ; point A in Extended Data Fig. 1a ). 3TC was administered continuously from SEN entry until harvest 16 weeks later. e, The dual luciferase L1 reporter system 52 was used to determine the effect of 3TC dosing on retrotransposition. L1 reporters were introduced into early passage cells using lentivirus vectors ( Methods ) and cells were treated with 3TC for 4 days prior to harvest and assay. JM111, a defective reporter carrying mutations in ORF1 (absence of 3TC); L1RP, a retrotransposition competent reporter. f, The effect of 3TC dosing on the IFN-I response. The experiment above (d) was processed by RT-qPCR to determine the expression of IFN-α and IFN-β1. g, Knockdowns of L1 were performed with two distinct shRNAs (a, b) in senescent cells (as in Fig. 2d, e, g ) or 3X cells (as in Fig. 2g ). The effectiveness on L1 expression was assessed by RT-qPCR using poly(A)-purified RNA and primers F. h, Cells in the experiment in (g) were examined for levels of ORF1 protein by immunofluorescence (IF). Image analysis was performed with CellProfiler software ( Methods ). > 200 cells were examined for each condition (a.f.u., arbitrary fluorescence units). i, The L1 shRNA treatment in the experiment in (g) was substituted with 3TC treatment (10 μM) for the same period of time. j, Five different NRTIs (or combinations) were tested for effects on the IFN-I response. AZT (Zidovudine, 15 μM), ABC (Abacavir, 15 μM), FTC (Emtricitabine, 10 μM), 3TC, (Lamivudine, 10 μM), TZV (Trizivir, a combination of 15 μM AZT, 15 μM ABC and 7.5 μM 3TC). Cells were treated for 4 weeks between 12 and 16 weeks in senescence ( Fig. 1a ; points D and E in Extended Data Fig. 1a ). 3X cells ( Fig. 2f ) were treated with 3TC for 48 hours after the completion of the last drug selection. Interferon α expression was determined by RT-qPCR. k, A native L1 reporter (pLD143) 53 was co-transfected with shRNA plasmid vectors into HeLa cells ( Methods ). Retrotransposition was scored as GFP-positive cells, and shL1 knockdowns were normalized to a shLuc negative control. The absolute average retrotransposition frequency (percentage of GFP-positive cells) was 4.1, which matches the published values for the reporter used (pLD143) 53 . l, Knockdowns of cGAS and STING were performed in senescent or 3X cells as with the other shRNAs ( Fig. 2d, e, g and a, g above). m, Downregulation of interferon signaling after CRISPR-mediated inactivation of IFNAR1 and IFNAR2 genes was verified by the absence of IRF9 nuclear translocation and STAT2 phosphorylation in response to interferon stimulation. Cells were infected with lentivirus vectors expressing Cas9 and gRNAs to both IFNAR1 and IFNAR2 (ΔIFNAR, Methods ). After the infection cells were re-seeded on coverslips, treated with interferon for 2 hours, and examined by IF microscopy. The experiment was repeated 3 times with similar results. ( a - i , l ) n = 3 independent experiments. ( k ) n = 3 independent biological samples, repeated in 2 independent experiments. ( a - l ) Data are mean ±s.d. * P ≤ 0.05, ** P ≤ 0.01, unpaired two-sided t -tests. Exact P values can be found in the accompanying Source Data.

    Techniques Used: Expressing, Quantitative RT-PCR, Multiplex Assay, Real-time Polymerase Chain Reaction, Luciferase, Purification, Immunofluorescence, Software, Fluorescence, shRNA, Selection, Transfection, Plasmid Preparation, Negative Control, CRISPR, Translocation Assay, Infection, Microscopy

    19) Product Images from "Simultaneous Loss of both Atypical Protein Kinase C Genes in the Intestinal Epithelium Drives Serrated Intestinal Cancer by Impairing Immunosurveillance"

    Article Title: Simultaneous Loss of both Atypical Protein Kinase C Genes in the Intestinal Epithelium Drives Serrated Intestinal Cancer by Impairing Immunosurveillance

    Journal: Immunity

    doi: 10.1016/j.immuni.2018.09.013

    Suppression of the interferon response by PKCζ loss impairs CD8 + -dependent immunosurveillance (A) mRNA expression for the indicated genes in Prkci fl/fl Villin-cre vs. WT IECs from RNA-seq data. (B) Extracellular ATP levels in sgC and sgPKCλ/ι MODE-K cells treated with Oxaliplatin for 24 hr (20 µM). (C) Western Blot of indicated proteins in sgC and sgPKCλ/ι MODE-K cells treated for 24 hr with Oxaliplatin (20 µM), Bortezomib (0.1 µM) or TNFα (10 ng/ml) plus cycloheximide (2.5 µg/ml). (D) qRT-PCR analyses of Cxcl10, Oas1a, Ifnb, and Nlrc5 mRNA levels in MODE-K of the indicated genotypes transfected with 0.5 µg/ml of poly(I:C) or mock transfected for 6 hr. (E) Surface expression (mean fluorescence intensity, MFI) of H-2Kb and H-2Dk in MODE-K cells of the indicated genotypes either HBSS-starved or treated with Oxaliplatin (20 µM) for 24 hr. (F) OT-I cells-MC38OVA killing assay (24 hr) at the indicated T:E ratios (left). PI staining in shNT and sgPKCλ/ι MC38OVA cells after coculture with OT-I cells for 24 hr (right). (G) GSEA of transcriptomic data from RNA-seq on Prkcz fl/fl Villin-cre vs. WT IECs. The indicated gene signatures were applied to the analyses. FDR, false discovery rate. (H) Heatmap of RNA-seq data of WT and Prkcz fl/fl Villin-cre IECs representing the genes related to interferon response differentially expressed between genotypes. (I) qRT-PCR analyses of Irf7, Oas1a, Isg15, and Cxcl10 mRNA levels in organoids of the indicated genotypes with or without 5AZA-CdR treatment. (J) qRT-PCR analyses of CXCL10 and IFNB mRNA levels in 293T cells of the indicated genotypes transfected with 0.5 µg/ml of poly(I:C) or mock transfected for 6 hr. (K) Western blot of indicated proteins in 293T cells of the indicated genotypes transfected with 0.5 µg/ml of poly(I:C) or mock transfected for 6 hr. (L) NextBio analysis of genes differentially expressed in Prkcz fl/fl Villin-cre vs. WT IECs. Venn diagram show the number of common and unique genes in both sets. Gene signatures corresponding to GO terms “antigen processing and presentation of peptide antigen via MHC class l”. (M) Flow cytometry analysis of H-2K b –positive cell population in organoids of the indicated genotypes with or without 5-AZA-CdR treatment. (N) MHC I (H-2) staining in small intestines from mice of the indicated genotypes. Scale bar, 50 μm. .
    Figure Legend Snippet: Suppression of the interferon response by PKCζ loss impairs CD8 + -dependent immunosurveillance (A) mRNA expression for the indicated genes in Prkci fl/fl Villin-cre vs. WT IECs from RNA-seq data. (B) Extracellular ATP levels in sgC and sgPKCλ/ι MODE-K cells treated with Oxaliplatin for 24 hr (20 µM). (C) Western Blot of indicated proteins in sgC and sgPKCλ/ι MODE-K cells treated for 24 hr with Oxaliplatin (20 µM), Bortezomib (0.1 µM) or TNFα (10 ng/ml) plus cycloheximide (2.5 µg/ml). (D) qRT-PCR analyses of Cxcl10, Oas1a, Ifnb, and Nlrc5 mRNA levels in MODE-K of the indicated genotypes transfected with 0.5 µg/ml of poly(I:C) or mock transfected for 6 hr. (E) Surface expression (mean fluorescence intensity, MFI) of H-2Kb and H-2Dk in MODE-K cells of the indicated genotypes either HBSS-starved or treated with Oxaliplatin (20 µM) for 24 hr. (F) OT-I cells-MC38OVA killing assay (24 hr) at the indicated T:E ratios (left). PI staining in shNT and sgPKCλ/ι MC38OVA cells after coculture with OT-I cells for 24 hr (right). (G) GSEA of transcriptomic data from RNA-seq on Prkcz fl/fl Villin-cre vs. WT IECs. The indicated gene signatures were applied to the analyses. FDR, false discovery rate. (H) Heatmap of RNA-seq data of WT and Prkcz fl/fl Villin-cre IECs representing the genes related to interferon response differentially expressed between genotypes. (I) qRT-PCR analyses of Irf7, Oas1a, Isg15, and Cxcl10 mRNA levels in organoids of the indicated genotypes with or without 5AZA-CdR treatment. (J) qRT-PCR analyses of CXCL10 and IFNB mRNA levels in 293T cells of the indicated genotypes transfected with 0.5 µg/ml of poly(I:C) or mock transfected for 6 hr. (K) Western blot of indicated proteins in 293T cells of the indicated genotypes transfected with 0.5 µg/ml of poly(I:C) or mock transfected for 6 hr. (L) NextBio analysis of genes differentially expressed in Prkcz fl/fl Villin-cre vs. WT IECs. Venn diagram show the number of common and unique genes in both sets. Gene signatures corresponding to GO terms “antigen processing and presentation of peptide antigen via MHC class l”. (M) Flow cytometry analysis of H-2K b –positive cell population in organoids of the indicated genotypes with or without 5-AZA-CdR treatment. (N) MHC I (H-2) staining in small intestines from mice of the indicated genotypes. Scale bar, 50 μm. .

    Techniques Used: Expressing, RNA Sequencing Assay, Western Blot, Quantitative RT-PCR, Transfection, Fluorescence, Staining, Flow Cytometry, Cytometry, Mouse Assay

    20) Product Images from "KMT2D regulates p63 target enhancers to coordinate epithelial homeostasis"

    Article Title: KMT2D regulates p63 target enhancers to coordinate epithelial homeostasis

    Journal: Genes & Development

    doi: 10.1101/gad.306241.117

    KMT2D loss leads to reduced keratinocyte proliferation and a broad loss of epithelial development and adhesion genes. ( A ) KMT2D mRNA expression is significantly reduced in both NHEKs ( P = 0.0036) and HaCaTs ( P = 0.0312) treated with shKMT2D as determined by RNA-seq. ( B ) shKMT2D keratinocytes display reduced levels of KMT2D but normal-appearing nuclear morphology. ( C ) shKMT2D keratinocytes display reduced proliferation in comparison with shSC keratinocytes. ( D ) Representative genes from shKMTD NHEKs that are significantly reduced in expression along with corresponding adjusted P -values. ( E ) Gene ontology (GO) analysis of the 134 common genes lost with shKMT2D treatment between both shKMT2D NHEKs and HaCaTs demonstrates that genes involved in key epithelial signaling pathways ( RARG and VDR ), epithelial cell growth and morphogenesis, polarity, and adhesion are enriched among those genes with reduced expression. ( F ) shKMT2D keratinocytes display reduced expression of RARγ and VDR by IF (40×).
    Figure Legend Snippet: KMT2D loss leads to reduced keratinocyte proliferation and a broad loss of epithelial development and adhesion genes. ( A ) KMT2D mRNA expression is significantly reduced in both NHEKs ( P = 0.0036) and HaCaTs ( P = 0.0312) treated with shKMT2D as determined by RNA-seq. ( B ) shKMT2D keratinocytes display reduced levels of KMT2D but normal-appearing nuclear morphology. ( C ) shKMT2D keratinocytes display reduced proliferation in comparison with shSC keratinocytes. ( D ) Representative genes from shKMTD NHEKs that are significantly reduced in expression along with corresponding adjusted P -values. ( E ) Gene ontology (GO) analysis of the 134 common genes lost with shKMT2D treatment between both shKMT2D NHEKs and HaCaTs demonstrates that genes involved in key epithelial signaling pathways ( RARG and VDR ), epithelial cell growth and morphogenesis, polarity, and adhesion are enriched among those genes with reduced expression. ( F ) shKMT2D keratinocytes display reduced expression of RARγ and VDR by IF (40×).

    Techniques Used: Expressing, RNA Sequencing Assay

    21) Product Images from "Targeted enrichment outperforms other enrichment techniques and enables more multi-species RNA-Seq analyses"

    Article Title: Targeted enrichment outperforms other enrichment techniques and enables more multi-species RNA-Seq analyses

    Journal: Scientific Reports

    doi: 10.1038/s41598-018-31420-7

    This schematic illustrates the sample (auburn rectangle) and library (blue rectangle) preparation workflow to generate the libraries that were loaded on the Illumina sequencer. ( a ) For B. malayi and A. fumigatus , a poly(A)-selected sample was created from an aliquot of total RNA that was used to create a poly(A)-selected library. ( b ) The B. malayi or A. fumigatus AgSS baits were subsequently used to capture the targeted RNA from poly(A)-selected libraries. ( c ) For AgSS-enriched w Bm libraries, an RNA library was constructed from an aliquot of total RNA that underwent targeted enrichment with the Wolbachia AgSS baits. Unlike the eukaryotic enrichments, the bacterial AgSS capture is performed on total RNA. For a limited number of libraries described in the text, an RNA library was constructed from an aliquot of total RNA (i.e. without poly(A)-enrichment) that underwent targeted enrichment with the Brugia AgSS baits. ( d ) For poly(A)/rRNA-depleted libraries enriched for w Bm, an aliquot of total RNA from either mosquito thoraces or adult nematodes was enriched for bacterial mRNA by removing Gram-negative and human rRNAs with two RiboZero removal kits and polyadenylated RNAs with DynaBeads.
    Figure Legend Snippet: This schematic illustrates the sample (auburn rectangle) and library (blue rectangle) preparation workflow to generate the libraries that were loaded on the Illumina sequencer. ( a ) For B. malayi and A. fumigatus , a poly(A)-selected sample was created from an aliquot of total RNA that was used to create a poly(A)-selected library. ( b ) The B. malayi or A. fumigatus AgSS baits were subsequently used to capture the targeted RNA from poly(A)-selected libraries. ( c ) For AgSS-enriched w Bm libraries, an RNA library was constructed from an aliquot of total RNA that underwent targeted enrichment with the Wolbachia AgSS baits. Unlike the eukaryotic enrichments, the bacterial AgSS capture is performed on total RNA. For a limited number of libraries described in the text, an RNA library was constructed from an aliquot of total RNA (i.e. without poly(A)-enrichment) that underwent targeted enrichment with the Brugia AgSS baits. ( d ) For poly(A)/rRNA-depleted libraries enriched for w Bm, an aliquot of total RNA from either mosquito thoraces or adult nematodes was enriched for bacterial mRNA by removing Gram-negative and human rRNAs with two RiboZero removal kits and polyadenylated RNAs with DynaBeads.

    Techniques Used: Construct

    22) Product Images from "Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads"

    Article Title: Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads

    Journal: Genome Biology

    doi: 10.1186/s13059-018-1407-3

    Overview of Quartz-Seq2 experimental processes. a Quartz-Seq2 consists of five steps. (1) Each single cell in a droplet is sorted into lysis buffer in each well of a 384-well PCR plate using flow cytometry analysis data. (2) Poly-adenylated RNA in each well is reverse-transcribed into first-strand cDNA with reverse transcription primer, which has a unique cell barcode ( CB ). We prepare 384 or 1536 kinds of cell barcode with a unique sequence based on the Sequence–Levenshtein distance (SeqLv). The edit distance of SeqLv is 5. The RT primer also has a UMI sequence for reduction of PCR bias (MB) and a poly(dT) sequence for binding to poly(A) RNA. (3) Cell barcode-labeled cDNAs from all 384 wells are promptly collected by centrifugation using assembled collectors. (4) Collected first-strand cDNAs are purified and concentrated for subsequent whole-transcript amplification. In the poly(A) tailing step, purified cDNA is extended with a poly(A) tail by terminal deoxynucleotidyl transferase ( TdT ). Subsequently, second-strand cDNA is synthesized with a tagging primer, which has a poly(dT) sequence. The resulting second-strand cDNA has a PCR primer sequence ( M ) at both ends of it. The cDNA is amplifiable in a subsequent PCR amplification. (5) For conversion from amplified cDNA to sequence library DNA, we fragment the amplified cDNA using the ultrasonicator Covaris. Such fragmented cDNA is ligated with a truncated Y-shaped sequence adaptor, which has an Illumina flow-cell binding sequence ( P7 ) and a pool barcode sequence ( PB ). The PB makes it possible to mix different sets of cell barcode-labeled cDNA. Ligated cDNA, which has CB and MB sequences, is enriched by PCR amplification. The resulting sequence library DNA contains P7 and P5 flow-cell binding sequences at respective ends of the DNA. We sequence the cell barcode site and the UMI site at Read1, the pool barcode site at Index1, and the transcript sequence at Read2. b The relationship between initial fastq reads and the number of single cells for sequence analysis in NextSeq500 runs. Typically, one sequence run with NextSeq 500/550 High Output v2 Kit reads out 400–450 M fastq reads. The x-axis represents the input cell number for one sequence run. The y-axis represents the initial data size (fastq reads) on average per cell. The red outline represents the typical range of shallow input read depth for a single cell. c We define the formula for calculating the UMI conversion efficiency. Each parameter is defined as follows: UMI sc is the number of UMI counts, assigned to a single-cell sample, fastq sc is the number of fastq reads derived from each single-cell sample, fastq non-sc is the number of fastq reads derived from non-single-cell samples, which include experimental byproducts such as WTA adaptors, WTA byproducts, and non-STAMPs. Initial fastq reads are composed of fastq sc and fastq non-sc
    Figure Legend Snippet: Overview of Quartz-Seq2 experimental processes. a Quartz-Seq2 consists of five steps. (1) Each single cell in a droplet is sorted into lysis buffer in each well of a 384-well PCR plate using flow cytometry analysis data. (2) Poly-adenylated RNA in each well is reverse-transcribed into first-strand cDNA with reverse transcription primer, which has a unique cell barcode ( CB ). We prepare 384 or 1536 kinds of cell barcode with a unique sequence based on the Sequence–Levenshtein distance (SeqLv). The edit distance of SeqLv is 5. The RT primer also has a UMI sequence for reduction of PCR bias (MB) and a poly(dT) sequence for binding to poly(A) RNA. (3) Cell barcode-labeled cDNAs from all 384 wells are promptly collected by centrifugation using assembled collectors. (4) Collected first-strand cDNAs are purified and concentrated for subsequent whole-transcript amplification. In the poly(A) tailing step, purified cDNA is extended with a poly(A) tail by terminal deoxynucleotidyl transferase ( TdT ). Subsequently, second-strand cDNA is synthesized with a tagging primer, which has a poly(dT) sequence. The resulting second-strand cDNA has a PCR primer sequence ( M ) at both ends of it. The cDNA is amplifiable in a subsequent PCR amplification. (5) For conversion from amplified cDNA to sequence library DNA, we fragment the amplified cDNA using the ultrasonicator Covaris. Such fragmented cDNA is ligated with a truncated Y-shaped sequence adaptor, which has an Illumina flow-cell binding sequence ( P7 ) and a pool barcode sequence ( PB ). The PB makes it possible to mix different sets of cell barcode-labeled cDNA. Ligated cDNA, which has CB and MB sequences, is enriched by PCR amplification. The resulting sequence library DNA contains P7 and P5 flow-cell binding sequences at respective ends of the DNA. We sequence the cell barcode site and the UMI site at Read1, the pool barcode site at Index1, and the transcript sequence at Read2. b The relationship between initial fastq reads and the number of single cells for sequence analysis in NextSeq500 runs. Typically, one sequence run with NextSeq 500/550 High Output v2 Kit reads out 400–450 M fastq reads. The x-axis represents the input cell number for one sequence run. The y-axis represents the initial data size (fastq reads) on average per cell. The red outline represents the typical range of shallow input read depth for a single cell. c We define the formula for calculating the UMI conversion efficiency. Each parameter is defined as follows: UMI sc is the number of UMI counts, assigned to a single-cell sample, fastq sc is the number of fastq reads derived from each single-cell sample, fastq non-sc is the number of fastq reads derived from non-single-cell samples, which include experimental byproducts such as WTA adaptors, WTA byproducts, and non-STAMPs. Initial fastq reads are composed of fastq sc and fastq non-sc

    Techniques Used: Lysis, Polymerase Chain Reaction, Flow Cytometry, Cytometry, Sequencing, Binding Assay, Labeling, Centrifugation, Purification, Amplification, Synthesized, Derivative Assay

    23) Product Images from "Rare cell detection by single cell RNA sequencing as guided by single molecule RNA FISH"

    Article Title: Rare cell detection by single cell RNA sequencing as guided by single molecule RNA FISH

    Journal: Cell systems

    doi: 10.1016/j.cels.2018.01.014

    Estimates of gene expression heterogeneity in single cell RNA sequencing are highly dependent on transcriptome coverage (A) The Gini coefficient measures a gene’s expression distribution and captures rare cell population heterogeneity. (B) Population structure of SOX10 mRNA levels measured by DropSeq (pink), Fluidigm (blue), and single molecule RNA FISH (smRNA FISH, brown). (C) Gini coefficient for six genes measured by DropSeq (left y-axis) binned by levels of transcriptome coverage as well as Gini coefficients measured by smRNA FISH (right y-axis). (D) Pearson correlation between Gini coefficients measured through DropSeq and smRNA FISH across different levels of transcriptome coverage (# genes detected per cell). Error bars represent ± 1 standard deviation across bootstrap replicates. (E,F) Scatter Plot of the correspondence between Gini coefficients for 26 genes measured by both DropSeq and smRNA FISH. (G) Scatter Plot of the correspondence between Gini coefficients for 26 genes measured by Fluidigm and smRNA FISH. (H) Pearson correlation between Gini coefficient estimates measured by DropSeq and smRNA FISH using different population sizes (# of cells) and levels of transcriptome coverage. Error bars represent ± 1 standard deviation across bootstrap replicates. (I) Pearson correlation between Gini coefficient estimates measured by DropSeq and smRNA FISH after subsampling cells with high transcriptome coverage to different degrees of reads depth. Numbers inside the bars represent the number of reads subsampled. The x-axis represents the average number of genes detected across all cells at a given subsample depth. Error bars represent ± 1 standard deviation across bootstrap replicates.
    Figure Legend Snippet: Estimates of gene expression heterogeneity in single cell RNA sequencing are highly dependent on transcriptome coverage (A) The Gini coefficient measures a gene’s expression distribution and captures rare cell population heterogeneity. (B) Population structure of SOX10 mRNA levels measured by DropSeq (pink), Fluidigm (blue), and single molecule RNA FISH (smRNA FISH, brown). (C) Gini coefficient for six genes measured by DropSeq (left y-axis) binned by levels of transcriptome coverage as well as Gini coefficients measured by smRNA FISH (right y-axis). (D) Pearson correlation between Gini coefficients measured through DropSeq and smRNA FISH across different levels of transcriptome coverage (# genes detected per cell). Error bars represent ± 1 standard deviation across bootstrap replicates. (E,F) Scatter Plot of the correspondence between Gini coefficients for 26 genes measured by both DropSeq and smRNA FISH. (G) Scatter Plot of the correspondence between Gini coefficients for 26 genes measured by Fluidigm and smRNA FISH. (H) Pearson correlation between Gini coefficient estimates measured by DropSeq and smRNA FISH using different population sizes (# of cells) and levels of transcriptome coverage. Error bars represent ± 1 standard deviation across bootstrap replicates. (I) Pearson correlation between Gini coefficient estimates measured by DropSeq and smRNA FISH after subsampling cells with high transcriptome coverage to different degrees of reads depth. Numbers inside the bars represent the number of reads subsampled. The x-axis represents the average number of genes detected across all cells at a given subsample depth. Error bars represent ± 1 standard deviation across bootstrap replicates.

    Techniques Used: Expressing, RNA Sequencing Assay, Fluorescence In Situ Hybridization, Standard Deviation

    24) Product Images from "Holo-Seq: single-cell sequencing of holo-transcriptome"

    Article Title: Holo-Seq: single-cell sequencing of holo-transcriptome

    Journal: Genome Biology

    doi: 10.1186/s13059-018-1553-7

    Holo-Seq accurately profiles total RNAs with a complete strand of origin information from single cells. a RPKM scatterplots of expressed genes between the combined dataset (total RNA with a complete strand of origin information from 10 mESCs single cells) and a directional bulk mRNA-Seq. b Comparison of the detected gene number in HEK293T single cells at the maximum exome-mapped depth of MATQ-Seq (UMI labeled reads) and 1.2M unique exome-mapped depth of Holo-Seq, SUPeR-Seq, and Smart-Seq2. c Read coverage across transcripts of different lengths of three methods in HEK293T single cells. The read coverage over the transcripts is displayed along with the percentage of the distance from their 3′ end. Shaded regions indicate the standard deviation
    Figure Legend Snippet: Holo-Seq accurately profiles total RNAs with a complete strand of origin information from single cells. a RPKM scatterplots of expressed genes between the combined dataset (total RNA with a complete strand of origin information from 10 mESCs single cells) and a directional bulk mRNA-Seq. b Comparison of the detected gene number in HEK293T single cells at the maximum exome-mapped depth of MATQ-Seq (UMI labeled reads) and 1.2M unique exome-mapped depth of Holo-Seq, SUPeR-Seq, and Smart-Seq2. c Read coverage across transcripts of different lengths of three methods in HEK293T single cells. The read coverage over the transcripts is displayed along with the percentage of the distance from their 3′ end. Shaded regions indicate the standard deviation

    Techniques Used: Labeling, Standard Deviation

    25) Product Images from "Post-transcriptional 3´-UTR cleavage of mRNA transcripts generates thousands of stable uncapped autonomous RNA fragments"

    Article Title: Post-transcriptional 3´-UTR cleavage of mRNA transcripts generates thousands of stable uncapped autonomous RNA fragments

    Journal: Nature Communications

    doi: 10.1038/s41467-017-02099-7

    Cleavage of 3′-UTR regions results in autonomous uncapped RNA fragments. a RNA-seq read coverage ( y -axis) for Ssr1 , Bcl2 , and Rab2a in mouse T cells 12 , B cells 14 , and brain tissue 15 , demonstrating a gap in read coverage (marked by arrows) at 3′-UTRs, as well as uneven levels of RNA upstream and downstream of the gap site. b Three sets of primers were used per gene for qRT-PCR amplification: upstream (blue rectangle), downstream (red), and across the RNA-seq coverage gap (green). Bar plots (bottom) visualize the relative percentage of cytoplasmic (black) and nuclear (gray) expression of each amplicon out of its total (cytoplasm+nuclear) expression. c A model for post-transcriptional processing of mRNA: mRNA is cleaved at an APA site, resulting in a capped “body” and an uncapped 3′-UTR “tail,” sensitive to terminator 5′-phosphate-dependent exonuclease (TEX) treatment. d qRT-PCR analysis shows cytoplasmic degradation of the “tail” unit (in red) compared to the “body” unit (in blue) following TEX treatment. * p
    Figure Legend Snippet: Cleavage of 3′-UTR regions results in autonomous uncapped RNA fragments. a RNA-seq read coverage ( y -axis) for Ssr1 , Bcl2 , and Rab2a in mouse T cells 12 , B cells 14 , and brain tissue 15 , demonstrating a gap in read coverage (marked by arrows) at 3′-UTRs, as well as uneven levels of RNA upstream and downstream of the gap site. b Three sets of primers were used per gene for qRT-PCR amplification: upstream (blue rectangle), downstream (red), and across the RNA-seq coverage gap (green). Bar plots (bottom) visualize the relative percentage of cytoplasmic (black) and nuclear (gray) expression of each amplicon out of its total (cytoplasm+nuclear) expression. c A model for post-transcriptional processing of mRNA: mRNA is cleaved at an APA site, resulting in a capped “body” and an uncapped 3′-UTR “tail,” sensitive to terminator 5′-phosphate-dependent exonuclease (TEX) treatment. d qRT-PCR analysis shows cytoplasmic degradation of the “tail” unit (in red) compared to the “body” unit (in blue) following TEX treatment. * p

    Techniques Used: RNA Sequencing Assay, Quantitative RT-PCR, Amplification, Expressing

    26) Product Images from "Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance"

    Article Title: Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance

    Journal: Nature

    doi: 10.1038/nature22794

    Rare cell expression of resistance marker genes is coordinated between genes, leading to cells expressing multiple markers a. AXL vs. VEGFC mRNA in individual WM989-A6 melanoma cells. Dotted lines represent thresholds for high/low. Inset tabulates cells. b. Odds ratio for co-expression. Dark gray boxes indicate zero double-positive cells (1 of n=2 biological replicates). c. Co-stain and sort for EGFR and NGFR into 4 populations: double negative and positive, and EGFR/NGFR positive only, followed by 1μM vemurafenib (2 weeks). Resistant colonies circled in the images (1 of n=2 biological replicates). d. Two cells across multiple rounds of hybridization. RNA FISH signal in white; cell nuclei in blue.
    Figure Legend Snippet: Rare cell expression of resistance marker genes is coordinated between genes, leading to cells expressing multiple markers a. AXL vs. VEGFC mRNA in individual WM989-A6 melanoma cells. Dotted lines represent thresholds for high/low. Inset tabulates cells. b. Odds ratio for co-expression. Dark gray boxes indicate zero double-positive cells (1 of n=2 biological replicates). c. Co-stain and sort for EGFR and NGFR into 4 populations: double negative and positive, and EGFR/NGFR positive only, followed by 1μM vemurafenib (2 weeks). Resistant colonies circled in the images (1 of n=2 biological replicates). d. Two cells across multiple rounds of hybridization. RNA FISH signal in white; cell nuclei in blue.

    Techniques Used: Expressing, Marker, Staining, Hybridization, Fluorescence In Situ Hybridization

    Iterative RNA FISH enables quantification of genes that are expressed in rare cells and control genes that are expressed throughout a population a. RNA counts are consistent whether a gene is probed on the first cycle of iterative RNA FISH or subsequent cycles. Boxplots summarizing RNA FISH mRNA counts for each gene in the 19 gene panel (shown in Fig. 2a ). We probed each gene from the panel in resistant WM989-A6 cells without performing iterative hybridizations (n=1 with further validation performed on a 5 gene panel; note that we used resistant cells because the generally higher expression levels allowed for more robust comparisons). We then performed iterative RNA FISH with all the probes and compared the total mRNA counts. We took image z-stacks of each sample and captured a total 15–25 cells per sample. Expression levels were similar between the first round of hybridization and all subsequent hybridization cycles. The color of the boxplot indicates the hybridization cycle during which we used each probe. The p-value for differences in RNA counts between the cycles are labeled above each plot. Some variability may be due to sampling with genes that have low and/or highly variable expression, and in these instances, we expect some differences in the two count distributions. There is some loss for some genes in later cycles, but we do not believe that affects our qualitative findings of rare, high-expressing cells. b. Housekeeping genes correlate more with each other than with resistance markers and vice-versa. We performed RNA FISH on 8672 non-drugged cells with probes targeting LOXL2 and AXL (both of which exhibit rare-cell expression) and LMNA and GAPDH, both of which are control genes not associated with resistance (1 of n=2 biological replicates shown). We then performed principal component analysis to determine which genes covary with which other genes. We transformed the vector representing the expression levels of each cell into the space spanned by the first two principal components. Arrows represent transformations of unit vectors of the specified gene into this same space. We observed two rough axes of variability, one corresponding to the GAPDH and LMNA and the other to AXL and LOXL2. Thus, these results show that there is substantial covariation in housekeeping genes and in resistance markers, but that these two axes of variation separate. c. Same plot as in panel b, but with the RNA FISH data shown for WM989-A6 in Figure 2b . d. There are subpopulations of cells that have high expression of multiple resistance marker genes. Histogram of number/fraction of cells that have high expression for a particular number of genes simultaneously, both before, immediately after and then 4 weeks after application of drug (1 of n=2 biological replicates shown). We found that immediately after adding drug, there was a large general decrease in the amount of high-expressing cells, but a few cells remained that expressed several marker genes at once. This suggests, but certainly does not prove, that these multi-expressing cells may be the pre-resistant cells. At best, it establishes that such a correspondence is plausible. e. We used RNA FISH analysis to look (in WM989-A6 cells) at the expression of APCDD1 cells, which was identified as a potential marker of drug-induced reprogramming (as opposed to pre-re- sistance). We measured APCDD1 expression in a total of 61,770 (20,030 in replicate 1 and 41,740 in replicate 2) cells before adding drug and 11,452 (7,138 in replicate 1 and 4,314 cells in replicate 2) cells after cells became stably resistant (n=2 biological replicates shown). Given the number of cells analyzed, we expected that roughly 30 cells in the untreated population would be pre-resistant (assuming conservatively that the frequency of pre-resistance is 1:2000), but despite that, we found essentially no cells with APCDD1 expression levels approaching those of even the median resistant cell. Thus, expression of this gene must have changed upon the pre-resistant cell becoming stably resistant in the presence of drug, as opposed to a selection effect in which high levels of expression in pre-resistance cells become prevalent due to those cells surviving rather than reprogramming.
    Figure Legend Snippet: Iterative RNA FISH enables quantification of genes that are expressed in rare cells and control genes that are expressed throughout a population a. RNA counts are consistent whether a gene is probed on the first cycle of iterative RNA FISH or subsequent cycles. Boxplots summarizing RNA FISH mRNA counts for each gene in the 19 gene panel (shown in Fig. 2a ). We probed each gene from the panel in resistant WM989-A6 cells without performing iterative hybridizations (n=1 with further validation performed on a 5 gene panel; note that we used resistant cells because the generally higher expression levels allowed for more robust comparisons). We then performed iterative RNA FISH with all the probes and compared the total mRNA counts. We took image z-stacks of each sample and captured a total 15–25 cells per sample. Expression levels were similar between the first round of hybridization and all subsequent hybridization cycles. The color of the boxplot indicates the hybridization cycle during which we used each probe. The p-value for differences in RNA counts between the cycles are labeled above each plot. Some variability may be due to sampling with genes that have low and/or highly variable expression, and in these instances, we expect some differences in the two count distributions. There is some loss for some genes in later cycles, but we do not believe that affects our qualitative findings of rare, high-expressing cells. b. Housekeeping genes correlate more with each other than with resistance markers and vice-versa. We performed RNA FISH on 8672 non-drugged cells with probes targeting LOXL2 and AXL (both of which exhibit rare-cell expression) and LMNA and GAPDH, both of which are control genes not associated with resistance (1 of n=2 biological replicates shown). We then performed principal component analysis to determine which genes covary with which other genes. We transformed the vector representing the expression levels of each cell into the space spanned by the first two principal components. Arrows represent transformations of unit vectors of the specified gene into this same space. We observed two rough axes of variability, one corresponding to the GAPDH and LMNA and the other to AXL and LOXL2. Thus, these results show that there is substantial covariation in housekeeping genes and in resistance markers, but that these two axes of variation separate. c. Same plot as in panel b, but with the RNA FISH data shown for WM989-A6 in Figure 2b . d. There are subpopulations of cells that have high expression of multiple resistance marker genes. Histogram of number/fraction of cells that have high expression for a particular number of genes simultaneously, both before, immediately after and then 4 weeks after application of drug (1 of n=2 biological replicates shown). We found that immediately after adding drug, there was a large general decrease in the amount of high-expressing cells, but a few cells remained that expressed several marker genes at once. This suggests, but certainly does not prove, that these multi-expressing cells may be the pre-resistant cells. At best, it establishes that such a correspondence is plausible. e. We used RNA FISH analysis to look (in WM989-A6 cells) at the expression of APCDD1 cells, which was identified as a potential marker of drug-induced reprogramming (as opposed to pre-re- sistance). We measured APCDD1 expression in a total of 61,770 (20,030 in replicate 1 and 41,740 in replicate 2) cells before adding drug and 11,452 (7,138 in replicate 1 and 4,314 cells in replicate 2) cells after cells became stably resistant (n=2 biological replicates shown). Given the number of cells analyzed, we expected that roughly 30 cells in the untreated population would be pre-resistant (assuming conservatively that the frequency of pre-resistance is 1:2000), but despite that, we found essentially no cells with APCDD1 expression levels approaching those of even the median resistant cell. Thus, expression of this gene must have changed upon the pre-resistant cell becoming stably resistant in the presence of drug, as opposed to a selection effect in which high levels of expression in pre-resistance cells become prevalent due to those cells surviving rather than reprogramming.

    Techniques Used: Fluorescence In Situ Hybridization, Expressing, Hybridization, Labeling, Sampling, Transformation Assay, Plasmid Preparation, Marker, Stable Transfection, Selection

    RNA FISH on thousands of melanoma cells reveals rare cells that express high levels of resistance marker genes a. Histograms of transcript abundance for resistance marker genes (top) and nonresistance markers (bottom). The vertical lines represent the threshold for designating cells as either “high” or “low” expressing for a particular gene. The cells labeled by the red carpet below the histogram are high expressing, and the cells labeled by the gray carpet are low expressing. The data set shown contains a total of 8672 cells and is one of two biological replicates. b. In an untreated population of cells, rare cells express resistance marker genes at much higher levels than the population average, sometimes at levels similar to the drug resistant state. Boxplots showing the distribution of mRNA counts per cell for untreated WM989-A6 cells and resistant WM989-A6 cells. The untreated data set is the same data as shown in a. For the resistant WM989-A6 cells, we performed iterative RNA FISH with the same panel of genes. The untreated data set contains a total of 8672 cells and the resistant data set contains a total of 4082 cells (1 of n=2 biological replicates are shown for each dataset). Asterisks next to the gene names indicates that the max expression of the untreated sample is greater than or equal to the median of the resistant sample, demonstrating that for these 7 of 9 genes, the “high” cells have expression levels potentially equivalent to resistant cells. However, we also point out that given that the sampling of high expressing cells in the untreated samples is low, it is difficult to explicitly compare the distributions to say that the expression in the rare high-expressing cells is equivalent to that in stably resistant cells. c. Rare cells expressing sporadic but high levels of resistance markers are still present when each gene is normalized by GAPDH mRNA counts. Each histogram shows the distribution of GAPDH normalized counts for a particular jackpot gene. The counts for each gene in each cells has been divided by the GAPDH counts in that same cell. This accounts for any volume-dependent differences between cells. Cells that had GAPDH counts less than 50 were dropped from this analysis (these cells were infrequent and gave abnormally high numbers after normalization, thus were dropped). With these cells removed, the data set contains a total of 8477 cells. d. Heatmap shows the odds ratio for co-expression between all pairs of genes in WM989-A6 cells (1 of n=2 biological replicates shown). Dark gray boxes label pairs where there were zero cells with counts high expression threshold for both genes. The heatmap in the middle has the same thresholds for designating cells as “high” or “low” as used in Fig. 3b . Meanwhile, the heatmap on the left shows the same analysis with the thresholds set to 1⁄2 of the their value in 3b and the heatmap on the right shows this analysis with thresholds set to twice their value in Fig. 3b . When the thresholds are at 1⁄2, the result is very similar to that in Fig. 3b . However, increasing the threshold by 2X leads to many gene pairs that do not have any cells that are “high” for both genes (indicated by the dark gray boxes). e. Heatmap showing odds ratios for WM989-A6 data after 4 weeks in drug (1 of n=2 biological replicates shown).
    Figure Legend Snippet: RNA FISH on thousands of melanoma cells reveals rare cells that express high levels of resistance marker genes a. Histograms of transcript abundance for resistance marker genes (top) and nonresistance markers (bottom). The vertical lines represent the threshold for designating cells as either “high” or “low” expressing for a particular gene. The cells labeled by the red carpet below the histogram are high expressing, and the cells labeled by the gray carpet are low expressing. The data set shown contains a total of 8672 cells and is one of two biological replicates. b. In an untreated population of cells, rare cells express resistance marker genes at much higher levels than the population average, sometimes at levels similar to the drug resistant state. Boxplots showing the distribution of mRNA counts per cell for untreated WM989-A6 cells and resistant WM989-A6 cells. The untreated data set is the same data as shown in a. For the resistant WM989-A6 cells, we performed iterative RNA FISH with the same panel of genes. The untreated data set contains a total of 8672 cells and the resistant data set contains a total of 4082 cells (1 of n=2 biological replicates are shown for each dataset). Asterisks next to the gene names indicates that the max expression of the untreated sample is greater than or equal to the median of the resistant sample, demonstrating that for these 7 of 9 genes, the “high” cells have expression levels potentially equivalent to resistant cells. However, we also point out that given that the sampling of high expressing cells in the untreated samples is low, it is difficult to explicitly compare the distributions to say that the expression in the rare high-expressing cells is equivalent to that in stably resistant cells. c. Rare cells expressing sporadic but high levels of resistance markers are still present when each gene is normalized by GAPDH mRNA counts. Each histogram shows the distribution of GAPDH normalized counts for a particular jackpot gene. The counts for each gene in each cells has been divided by the GAPDH counts in that same cell. This accounts for any volume-dependent differences between cells. Cells that had GAPDH counts less than 50 were dropped from this analysis (these cells were infrequent and gave abnormally high numbers after normalization, thus were dropped). With these cells removed, the data set contains a total of 8477 cells. d. Heatmap shows the odds ratio for co-expression between all pairs of genes in WM989-A6 cells (1 of n=2 biological replicates shown). Dark gray boxes label pairs where there were zero cells with counts high expression threshold for both genes. The heatmap in the middle has the same thresholds for designating cells as “high” or “low” as used in Fig. 3b . Meanwhile, the heatmap on the left shows the same analysis with the thresholds set to 1⁄2 of the their value in 3b and the heatmap on the right shows this analysis with thresholds set to twice their value in Fig. 3b . When the thresholds are at 1⁄2, the result is very similar to that in Fig. 3b . However, increasing the threshold by 2X leads to many gene pairs that do not have any cells that are “high” for both genes (indicated by the dark gray boxes). e. Heatmap showing odds ratios for WM989-A6 data after 4 weeks in drug (1 of n=2 biological replicates shown).

    Techniques Used: Fluorescence In Situ Hybridization, Marker, Expressing, Labeling, Sampling, Stable Transfection

    Resistance to vemurafenib is not heritable, and pre-existing pre-resistant cells are marked by very high expression of resistance genes a. Alternative models for heritability of the resistant phenotype and simulated outcomes of each model. b. Distributions of resistant colonies in WM989-A6 (n=2 biological replicates of 43 and 29 clones; WM983B-E9 in Extended Data Fig. 3 ). c. Transcriptome analysis before drug, 48 hours after drug and stably resistant cultures (see Extended Data Fig. 2 ). Heatmap depicts “marker genes” whose expression increased in resistant cells relative to untreated. d. Computational representation of single-cell RNA FISH (8672 untreated cells) for AXL , NGFR , and EGFR mRNA; each dot is a cell colored by number of mRNA (1 of n=2 biological replicates). e. Single-cell AXL RNA FISH (1966 cells) after 4 weeks treatment with 1μM vemurafenib (1 of n=2 biological replicates). f. FACS of cells with an EGFR antibody; isolated an EGFR-high and mixed cell population, then applied vemurafenib. Two-well chamber of populations after 3 weeks vemurafenib(1 of n=3 biological replicates, Extended Data Fig. 5a ). g. Ratio of number of colonies in EGFR-high vs. mixed wells after cells grew without drug for varying periods before vemurafenib application. Error bars represent standard error of the mean (3 biological replicates).
    Figure Legend Snippet: Resistance to vemurafenib is not heritable, and pre-existing pre-resistant cells are marked by very high expression of resistance genes a. Alternative models for heritability of the resistant phenotype and simulated outcomes of each model. b. Distributions of resistant colonies in WM989-A6 (n=2 biological replicates of 43 and 29 clones; WM983B-E9 in Extended Data Fig. 3 ). c. Transcriptome analysis before drug, 48 hours after drug and stably resistant cultures (see Extended Data Fig. 2 ). Heatmap depicts “marker genes” whose expression increased in resistant cells relative to untreated. d. Computational representation of single-cell RNA FISH (8672 untreated cells) for AXL , NGFR , and EGFR mRNA; each dot is a cell colored by number of mRNA (1 of n=2 biological replicates). e. Single-cell AXL RNA FISH (1966 cells) after 4 weeks treatment with 1μM vemurafenib (1 of n=2 biological replicates). f. FACS of cells with an EGFR antibody; isolated an EGFR-high and mixed cell population, then applied vemurafenib. Two-well chamber of populations after 3 weeks vemurafenib(1 of n=3 biological replicates, Extended Data Fig. 5a ). g. Ratio of number of colonies in EGFR-high vs. mixed wells after cells grew without drug for varying periods before vemurafenib application. Error bars represent standard error of the mean (3 biological replicates).

    Techniques Used: Expressing, Clone Assay, Stable Transfection, Fluorescence In Situ Hybridization, FACS, Isolation

    Sorting for EGFR-high cells enriches for pre-resistant cells and removing drug from resistant cells does not appear to reverse the resistant phenotype a. Quantification of 3 biological replicates of the experiment depicted in Fig. 1f . b,c. Histograms showing the transcript abundance measured by RNA FISH in untreated and FACS sorted EGFR-high and mixed cell populations (n=1). The green histograms are from the EGFR-high population and the gray histograms are the mixed population. The percentage of high-expressing cells are labeled on each plot. Panel b shows resistance marker genes EGFR, WNT5A, SERPINE1, and PDGFRβ, and panel c shows melanocyte development genes, SOX10 and MITF, and a housekeeping gene, GAPDH. d. Histograms of percentage of cells that have high expression of a particular number of genes simultaneously. The left histogram is from the FACS sorted EGFR-high cells, and the right histogram is from the mixed population. e. Boxplots summarize the single-cell RNA FISH counts for EGFR and NGFR in flow sorted populations shown in Fig. 3c . These results show that sorting the high populations indeed enriched for EGFR and NGFR mRNA, thus validating the sort procedure (n=1). Furthermore, it shows that the double sorting does not further enrich for either EGFR or NGFR mRNA alone, showing that the effects of the double sort do not arise from a further enrichment of either EGFR or NGFR-high cells per se, but rather the combination of both in the same cell. f. Isolated resistant subclones are stably resistant to vemurafenib. We established stably resistant subclones of WM989-A6 cells grown in vemurafenib by culturing genetically homogeneous WM989-A6 subclones, adding drug, then isolating small resistant colonies and expanding them in the presence of drug into large populations. For three such resistant subclones, we removed drug for a period of three weeks (drug “holiday”), then added drug back for a week and looked for response. Generally, the cells looked fairly similar to the pre-holiday state and continued to proliferate, indicating that they remained insensitive to drug despite the prolonged holiday from drug exposure. The bottom panel is a control experiment consisting of a non-resistant parental line exposed to drug, showing the morphological changes associated with drug response.
    Figure Legend Snippet: Sorting for EGFR-high cells enriches for pre-resistant cells and removing drug from resistant cells does not appear to reverse the resistant phenotype a. Quantification of 3 biological replicates of the experiment depicted in Fig. 1f . b,c. Histograms showing the transcript abundance measured by RNA FISH in untreated and FACS sorted EGFR-high and mixed cell populations (n=1). The green histograms are from the EGFR-high population and the gray histograms are the mixed population. The percentage of high-expressing cells are labeled on each plot. Panel b shows resistance marker genes EGFR, WNT5A, SERPINE1, and PDGFRβ, and panel c shows melanocyte development genes, SOX10 and MITF, and a housekeeping gene, GAPDH. d. Histograms of percentage of cells that have high expression of a particular number of genes simultaneously. The left histogram is from the FACS sorted EGFR-high cells, and the right histogram is from the mixed population. e. Boxplots summarize the single-cell RNA FISH counts for EGFR and NGFR in flow sorted populations shown in Fig. 3c . These results show that sorting the high populations indeed enriched for EGFR and NGFR mRNA, thus validating the sort procedure (n=1). Furthermore, it shows that the double sorting does not further enrich for either EGFR or NGFR mRNA alone, showing that the effects of the double sort do not arise from a further enrichment of either EGFR or NGFR-high cells per se, but rather the combination of both in the same cell. f. Isolated resistant subclones are stably resistant to vemurafenib. We established stably resistant subclones of WM989-A6 cells grown in vemurafenib by culturing genetically homogeneous WM989-A6 subclones, adding drug, then isolating small resistant colonies and expanding them in the presence of drug into large populations. For three such resistant subclones, we removed drug for a period of three weeks (drug “holiday”), then added drug back for a week and looked for response. Generally, the cells looked fairly similar to the pre-holiday state and continued to proliferate, indicating that they remained insensitive to drug despite the prolonged holiday from drug exposure. The bottom panel is a control experiment consisting of a non-resistant parental line exposed to drug, showing the morphological changes associated with drug response.

    Techniques Used: Fluorescence In Situ Hybridization, FACS, Expressing, Labeling, Marker, Flow Cytometry, Isolation, Stable Transfection

    Analysis of multiple patient-derived xenografts reveals cells that sporadically express high levels of some resistance markers a. Table summarizing results of our patient-derived xenograft experiments, including the 4 different models and all the genes tested with each. b. Histograms show full distribution of mRNA expression for genes for which we saw convincing signal. Note that for some expressing genes, there were sporadic noise spots in the analysis, leading to some cells with, say, transcript counts of 1–2 that are probably spurious. c. Image panel of marker gene expression in the patient-derived xenografts. d. Computational representation of CYR61 mRNA expression in patient-derived xenografts. Each cell is represented by a dot on this plot and the color of the dot represents the number of RNA in that particular cell as indicated by the color scale bar. e. Histograms show full distribution of mRNA expression for CYR61 and LOXL2 in WM4335.
    Figure Legend Snippet: Analysis of multiple patient-derived xenografts reveals cells that sporadically express high levels of some resistance markers a. Table summarizing results of our patient-derived xenograft experiments, including the 4 different models and all the genes tested with each. b. Histograms show full distribution of mRNA expression for genes for which we saw convincing signal. Note that for some expressing genes, there were sporadic noise spots in the analysis, leading to some cells with, say, transcript counts of 1–2 that are probably spurious. c. Image panel of marker gene expression in the patient-derived xenografts. d. Computational representation of CYR61 mRNA expression in patient-derived xenografts. Each cell is represented by a dot on this plot and the color of the dot represents the number of RNA in that particular cell as indicated by the color scale bar. e. Histograms show full distribution of mRNA expression for CYR61 and LOXL2 in WM4335.

    Techniques Used: Derivative Assay, Expressing, Marker

    27) Product Images from "Extra-coding RNAs regulate neuronal DNA methylation dynamics"

    Article Title: Extra-coding RNAs regulate neuronal DNA methylation dynamics

    Journal: Nature Communications

    doi: 10.1038/ncomms12091

    Regulation of mRNA and ecRNA by neuronal activity. ( a ) PolyA+ RNA-seq following 1 h neuronal depolarization (25 mM KCl) or inactivation (1 μM TTX) reveals altered mRNA expression at a small subset of genes. Top, heatmap of KCl-altered transcripts (each column=1 biological replicate; 2 replicates per treatment). Bottom, Venn diagram of overlap between transcripts altered by KCl and TTX. ( b ) Corresponding heatmaps from PolyA− RNA-seq reveal relationship between activity-related mRNA and ecRNA changes. PolyA− RNA transcription from 5′, intronic and 3′ sites all correlated significantly with mRNA changes following neuronal depolarization with KCl (linear regression, P
    Figure Legend Snippet: Regulation of mRNA and ecRNA by neuronal activity. ( a ) PolyA+ RNA-seq following 1 h neuronal depolarization (25 mM KCl) or inactivation (1 μM TTX) reveals altered mRNA expression at a small subset of genes. Top, heatmap of KCl-altered transcripts (each column=1 biological replicate; 2 replicates per treatment). Bottom, Venn diagram of overlap between transcripts altered by KCl and TTX. ( b ) Corresponding heatmaps from PolyA− RNA-seq reveal relationship between activity-related mRNA and ecRNA changes. PolyA− RNA transcription from 5′, intronic and 3′ sites all correlated significantly with mRNA changes following neuronal depolarization with KCl (linear regression, P

    Techniques Used: Activity Assay, RNA Sequencing Assay, Expressing

    Fos ecRNA interacts with DNA methyltransferases and blocks DNA methylation. ( a ) Immunostaining reveals nuclear localization of DNMT1 and DNMT3a in neuronal cultures. Cell nuclei are stained with 4,6-diamidino-2-phenylindole (DAPI), and neurons are marked by MAP2 (microtubule-associated protein 2). Scale bar, 50 μm. ( b ) Fos ecRNA/mRNA comparison in total neuronal lysate and nuclear fraction (separated during RNA-IP; n =4 per group; unpaired Student's t -test, t 6 =6.301, P =0.007). ( c ) Fos ecRNA, but not mRNA, immunoprecipitates with anti-DNMT1 or DNMT3a antibodies but not control IgG ( n =4–6 per group; ecRNA one-way ANOVA, F (2,15) =20.53, P
    Figure Legend Snippet: Fos ecRNA interacts with DNA methyltransferases and blocks DNA methylation. ( a ) Immunostaining reveals nuclear localization of DNMT1 and DNMT3a in neuronal cultures. Cell nuclei are stained with 4,6-diamidino-2-phenylindole (DAPI), and neurons are marked by MAP2 (microtubule-associated protein 2). Scale bar, 50 μm. ( b ) Fos ecRNA/mRNA comparison in total neuronal lysate and nuclear fraction (separated during RNA-IP; n =4 per group; unpaired Student's t -test, t 6 =6.301, P =0.007). ( c ) Fos ecRNA, but not mRNA, immunoprecipitates with anti-DNMT1 or DNMT3a antibodies but not control IgG ( n =4–6 per group; ecRNA one-way ANOVA, F (2,15) =20.53, P

    Techniques Used: DNA Methylation Assay, Immunostaining, Staining

    Genome-wide identification and quantification of ecRNAs from neuronal systems. ( a ) RNA-seq workflow identifies both polyadenylated and non-polyadenylated transcripts from the same neuronal tissue. ( b ) Comparison of PolyA+ and PolyA− sequencing from representative gene loci reveals PolyA− transcripts arising from intronic and post-TESs. ( c ) Genome wide, extra-coding transcripts were characterized by averaging PolyA− reads that mapped to 5′ (pre-TSS), intronic or 3′ (post-TES) of a given gene. ( d ) Rank plot of ecRNA index at 17,719 rat genes. ( e ) mRNA expression (PolyA+ RNA-seq) ranked by ecRNA index reveals correlation between ecRNA and mRNA expression. ( f ) Division of ecRNA into discrete quartiles reveals general profile and expression of PolyA− RNA transcripts. Data are aligned to transcription start sites (TSS) and TESs. Heatmap shows PolyA− transcription from all genes. ( g ) MBD-seq reveals metagenomic DNA methylation profiles, including hypomethylation at TSS and hypermethylation at TES. ecRNA transcription is associated with hypomethylated promoters across the genome. ( h , i ) Genome wide, ecRNA levels are positively correlated with mRNA transcription (( h ) one-way ANOVA, F (3,17715) =612.5, P
    Figure Legend Snippet: Genome-wide identification and quantification of ecRNAs from neuronal systems. ( a ) RNA-seq workflow identifies both polyadenylated and non-polyadenylated transcripts from the same neuronal tissue. ( b ) Comparison of PolyA+ and PolyA− sequencing from representative gene loci reveals PolyA− transcripts arising from intronic and post-TESs. ( c ) Genome wide, extra-coding transcripts were characterized by averaging PolyA− reads that mapped to 5′ (pre-TSS), intronic or 3′ (post-TES) of a given gene. ( d ) Rank plot of ecRNA index at 17,719 rat genes. ( e ) mRNA expression (PolyA+ RNA-seq) ranked by ecRNA index reveals correlation between ecRNA and mRNA expression. ( f ) Division of ecRNA into discrete quartiles reveals general profile and expression of PolyA− RNA transcripts. Data are aligned to transcription start sites (TSS) and TESs. Heatmap shows PolyA− transcription from all genes. ( g ) MBD-seq reveals metagenomic DNA methylation profiles, including hypomethylation at TSS and hypermethylation at TES. ecRNA transcription is associated with hypomethylated promoters across the genome. ( h , i ) Genome wide, ecRNA levels are positively correlated with mRNA transcription (( h ) one-way ANOVA, F (3,17715) =612.5, P

    Techniques Used: Genome Wide, RNA Sequencing Assay, Sequencing, Expressing, DNA Methylation Assay

    28) Product Images from "Endogenous acid ceramidase protects epithelial cells from Porphyromonas gingivalis-induced inflammation in vitro"

    Article Title: Endogenous acid ceramidase protects epithelial cells from Porphyromonas gingivalis-induced inflammation in vitro

    Journal: Biochemical and biophysical research communications

    doi: 10.1016/j.bbrc.2017.12.137

    Human epithelial OBA-9 cells show downregulation of acid ceramidase in response to P. gingivalis stimuli in vitro . A: Expression of acid, neutral, and alkaline ceramidases mRNA in OBA-9 cells after 6 h of stimulation with P. gingivalis . Detection of acid, neutral, and alkaline ceramides in OBA-9 cells after incubation with live P. gingivalis for 12 h (B) and only acid ceramidase fluorescence emission shows significant diminished amount in OBA-9 cells incubated with P. gingivalis compared to control untreated cells (C) . Red color corresponds to a particular ceramidase; Blue are nuclei. ** p
    Figure Legend Snippet: Human epithelial OBA-9 cells show downregulation of acid ceramidase in response to P. gingivalis stimuli in vitro . A: Expression of acid, neutral, and alkaline ceramidases mRNA in OBA-9 cells after 6 h of stimulation with P. gingivalis . Detection of acid, neutral, and alkaline ceramides in OBA-9 cells after incubation with live P. gingivalis for 12 h (B) and only acid ceramidase fluorescence emission shows significant diminished amount in OBA-9 cells incubated with P. gingivalis compared to control untreated cells (C) . Red color corresponds to a particular ceramidase; Blue are nuclei. ** p

    Techniques Used: In Vitro, Expressing, Incubation, Fluorescence

    Transduction of OBA-9 cells with adenoviral vector that expresses acid ceramidase ( ASAH1 ) gene attenuates P. gingivalis -induced apoptosis in OBA-9 cells. A) E xpression of caspase-3 mRNA in OBA-9 cells transduced either with control adenoviral vector expressing GFP (Ad-GFP; control) or co-expressing human ASAH1 and GFP (Ad- ASAH1 -GFP) and then incubated with P. gingivalis for 6 h. B) Representative images of annexin V (blue) and Propidium Iodide (red) staining in either Ad-GFP- or Ad -ASAH1 -GFP-transduced OBA-9 cells (green) stimulated with P. gingivalis cells for 24 h. C) ]. * p
    Figure Legend Snippet: Transduction of OBA-9 cells with adenoviral vector that expresses acid ceramidase ( ASAH1 ) gene attenuates P. gingivalis -induced apoptosis in OBA-9 cells. A) E xpression of caspase-3 mRNA in OBA-9 cells transduced either with control adenoviral vector expressing GFP (Ad-GFP; control) or co-expressing human ASAH1 and GFP (Ad- ASAH1 -GFP) and then incubated with P. gingivalis for 6 h. B) Representative images of annexin V (blue) and Propidium Iodide (red) staining in either Ad-GFP- or Ad -ASAH1 -GFP-transduced OBA-9 cells (green) stimulated with P. gingivalis cells for 24 h. C) ]. * p

    Techniques Used: Transduction, Plasmid Preparation, Expressing, Incubation, Staining

    29) Product Images from "Myogenin promoter‐associated lncRNA Myoparr is essential for myogenic differentiation"

    Article Title: Myogenin promoter‐associated lncRNA Myoparr is essential for myogenic differentiation

    Journal: EMBO Reports

    doi: 10.15252/embr.201847468

    Characterization of mouse and human Myoparr Schematic diagram of the results of 5′‐ and 3′‐RACE analysis of sense and anti‐sense transcripts. The 3′‐ends of several sense transcripts overlap with myogenin mRNA. Coding potential assessment of the indicated RNAs using a coding potential assessment tool (CPAT). Low coding probabilities for anti‐sense transcript and sense transcript 1 (Long) and 4 (Short) as well as lincRNA‐p21 are shown. In vitro transcription/translation of pCS2‐Anti‐Sense, pCS2‐Sense (Long), and pCS2‐Sense (Short). The pCS2+ vector was used as a negative control. pCS2‐EGFP and pCS2‐myogenin were used as positive controls. The sequence of Myoparr cloned from mouse C2C12 cells. The potential RNA nuclear retention signal and putative polyadenylation signal are enclosed in a black and red box, respectively. The LINE‐1‐like sequence is underlined. Schematic representation of the upstream region of human myogenin and regions amplified by RT–PCR (top). RT–PCR for novel transcripts in human primary myotubes (bottom). The presence or absence of reverse transcriptase (RT) is indicated by (+) or (−), respectively. The primers used for RT–PCR (top). Strand‐specific RT–PCR for the novel transcripts in the upstream region of human myogenin (bottom). Schematic diagram of the results of 5′‐ and 3′‐RACE analysis of human Myoparr .
    Figure Legend Snippet: Characterization of mouse and human Myoparr Schematic diagram of the results of 5′‐ and 3′‐RACE analysis of sense and anti‐sense transcripts. The 3′‐ends of several sense transcripts overlap with myogenin mRNA. Coding potential assessment of the indicated RNAs using a coding potential assessment tool (CPAT). Low coding probabilities for anti‐sense transcript and sense transcript 1 (Long) and 4 (Short) as well as lincRNA‐p21 are shown. In vitro transcription/translation of pCS2‐Anti‐Sense, pCS2‐Sense (Long), and pCS2‐Sense (Short). The pCS2+ vector was used as a negative control. pCS2‐EGFP and pCS2‐myogenin were used as positive controls. The sequence of Myoparr cloned from mouse C2C12 cells. The potential RNA nuclear retention signal and putative polyadenylation signal are enclosed in a black and red box, respectively. The LINE‐1‐like sequence is underlined. Schematic representation of the upstream region of human myogenin and regions amplified by RT–PCR (top). RT–PCR for novel transcripts in human primary myotubes (bottom). The presence or absence of reverse transcriptase (RT) is indicated by (+) or (−), respectively. The primers used for RT–PCR (top). Strand‐specific RT–PCR for the novel transcripts in the upstream region of human myogenin (bottom). Schematic diagram of the results of 5′‐ and 3′‐RACE analysis of human Myoparr .

    Techniques Used: In Vitro, Plasmid Preparation, Negative Control, Sequencing, Clone Assay, Amplification, Reverse Transcription Polymerase Chain Reaction

    30) Product Images from "Neuronal upregulation of Prospero protein is driven by alternative mRNA polyadenylation and Syncrip-mediated mRNA stabilisation"

    Article Title: Neuronal upregulation of Prospero protein is driven by alternative mRNA polyadenylation and Syncrip-mediated mRNA stabilisation

    Journal: bioRxiv

    doi: 10.1101/135848

    pros long isoform is expressed brains and is specifically transcribed in larval neurons (A) Diagram showing annotated pros transcript isoforms and the position of smFISH ( pros long intron, pros and pros-long ) and Northern blot probes (grey bars). (B) Northern blot confirms the existence of multiple pros mRNA isoforms at 6 kb, 9 kb and 21 kb (red arrows) in the larval CNS. The 21 kb isoform corresponds to pros transcript with 15 kb 3’ UTR. E: embryo, L: larval CNS (C) Costaining with pros exon and pros-long smFISH and Pros IF shows that pros long RNA is detected only in neurons. In the NB (white dotted outline), or the GMCs (pink dotted outline), pros exon is detected without pros-long . Pros protein is upregulated in cells expressing pros long . (D) pros long intron probe only recognises the nascent transcripts of the pros long isoform. pros long intron is detected exclusively in neurons, and not in the NB (white dotted outline) or GMCs (pink dotted outline). Scale bar: 10 µm.
    Figure Legend Snippet: pros long isoform is expressed brains and is specifically transcribed in larval neurons (A) Diagram showing annotated pros transcript isoforms and the position of smFISH ( pros long intron, pros and pros-long ) and Northern blot probes (grey bars). (B) Northern blot confirms the existence of multiple pros mRNA isoforms at 6 kb, 9 kb and 21 kb (red arrows) in the larval CNS. The 21 kb isoform corresponds to pros transcript with 15 kb 3’ UTR. E: embryo, L: larval CNS (C) Costaining with pros exon and pros-long smFISH and Pros IF shows that pros long RNA is detected only in neurons. In the NB (white dotted outline), or the GMCs (pink dotted outline), pros exon is detected without pros-long . Pros protein is upregulated in cells expressing pros long . (D) pros long intron probe only recognises the nascent transcripts of the pros long isoform. pros long intron is detected exclusively in neurons, and not in the NB (white dotted outline) or GMCs (pink dotted outline). Scale bar: 10 µm.

    Techniques Used: Northern Blot, Expressing

    31) Product Images from "ALYREF mainly binds to the 5′ and the 3′ regions of the mRNA in vivo"

    Article Title: ALYREF mainly binds to the 5′ and the 3′ regions of the mRNA in vivo

    Journal: Nucleic Acids Research

    doi: 10.1093/nar/gkx597

    ALYREF binding sites are enriched on exons of mature mRNAs. ( A ) Detection of ALYREF-RNA complexes. RNase I treated (H: 5 U/ml; L: 0.5 U/ml) and 32 P-labeled RNP complexes were immunoprecipitated with or without the ALYREF antibody from normal and ALYREF knockdown cells. After size-separation using denaturing gel electrophoresis, ALYREF-RNA complexes were transferred to a nitrocellulose membrane. The upper panel shows the autoradiograph of the nitrocellulose membrane. The lower panel shows the western blotting result using the indicated antibodies for input of IP. Red box indicates the region that was extracted for subsequent analyses. ( B ) Correlation of ALYREF iCLIP-seq replicates. Clustered ALYREF binding sites in each gene are plotted for three independent biological replicates (Spearman correlation coefficient, R > 0.90 for all comparisons). ( C ) ALYREF binding sites are enriched at mRNA exon. Left pie chart shows the percentage of RNA-seq reads that uniquely mapped to four human genome regions: mRNA exons, mRNA-introns, lncRNAs or others. Right pie chart shows the percentage of clustered ALYREF binding sites mapped to different human genome regions. ( D ) ALYREF mainly binds mature mRNAs. Percentages of the iCLIP tag in ALYREF binding sites specifically mapped to the exon-exon junction (blue) or exon-intron junction (green).
    Figure Legend Snippet: ALYREF binding sites are enriched on exons of mature mRNAs. ( A ) Detection of ALYREF-RNA complexes. RNase I treated (H: 5 U/ml; L: 0.5 U/ml) and 32 P-labeled RNP complexes were immunoprecipitated with or without the ALYREF antibody from normal and ALYREF knockdown cells. After size-separation using denaturing gel electrophoresis, ALYREF-RNA complexes were transferred to a nitrocellulose membrane. The upper panel shows the autoradiograph of the nitrocellulose membrane. The lower panel shows the western blotting result using the indicated antibodies for input of IP. Red box indicates the region that was extracted for subsequent analyses. ( B ) Correlation of ALYREF iCLIP-seq replicates. Clustered ALYREF binding sites in each gene are plotted for three independent biological replicates (Spearman correlation coefficient, R > 0.90 for all comparisons). ( C ) ALYREF binding sites are enriched at mRNA exon. Left pie chart shows the percentage of RNA-seq reads that uniquely mapped to four human genome regions: mRNA exons, mRNA-introns, lncRNAs or others. Right pie chart shows the percentage of clustered ALYREF binding sites mapped to different human genome regions. ( D ) ALYREF mainly binds mature mRNAs. Percentages of the iCLIP tag in ALYREF binding sites specifically mapped to the exon-exon junction (blue) or exon-intron junction (green).

    Techniques Used: Binding Assay, Labeling, Immunoprecipitation, Nucleic Acid Electrophoresis, Autoradiography, Western Blot, RNA Sequencing Assay

    Genome-wide effect of ALYREF-binding motifs on nucleocytoplasmic mRNA distribution. ( A ) Northern blots to examine the purities of nuclear and cytoplasmic fractions. The U6 snRNA and tRNA-Lys were used as nuclear and cytoplasmic maker, respectively. ( B ) Screenshots of the UCSC genome browser for RNA-seq of MALAT1. The y-axis displays the RPM. ( C ) Analysis of the correlation of ALYREF binding motifs number and the C/N ratios of intronless mRNAs. Intronless mRNAs were divided into three groups based on occurrences of ALYREF binding motifs per 1000 nt. Based on C/N (RPM) ratio in RNA-seq, intronless mRNAs were further divided into fourtwo subgroups. The percentage of mRNA in each subgroup is shown in colored block. Chi-square tests were used to determine the association between occurrences of ALYREF binding motif and C/N ratio, P
    Figure Legend Snippet: Genome-wide effect of ALYREF-binding motifs on nucleocytoplasmic mRNA distribution. ( A ) Northern blots to examine the purities of nuclear and cytoplasmic fractions. The U6 snRNA and tRNA-Lys were used as nuclear and cytoplasmic maker, respectively. ( B ) Screenshots of the UCSC genome browser for RNA-seq of MALAT1. The y-axis displays the RPM. ( C ) Analysis of the correlation of ALYREF binding motifs number and the C/N ratios of intronless mRNAs. Intronless mRNAs were divided into three groups based on occurrences of ALYREF binding motifs per 1000 nt. Based on C/N (RPM) ratio in RNA-seq, intronless mRNAs were further divided into fourtwo subgroups. The percentage of mRNA in each subgroup is shown in colored block. Chi-square tests were used to determine the association between occurrences of ALYREF binding motif and C/N ratio, P

    Techniques Used: Genome Wide, Binding Assay, Northern Blot, RNA Sequencing Assay, Blocking Assay

    32) Product Images from "Efficient differentiation of human pluripotent stem cells into skeletal muscle cells by combining RNA-based MYOD1-expression and POU5F1-silencing"

    Article Title: Efficient differentiation of human pluripotent stem cells into skeletal muscle cells by combining RNA-based MYOD1-expression and POU5F1-silencing

    Journal: Scientific Reports

    doi: 10.1038/s41598-017-19114-y

    POU5F1 expression is stably sustained in MYOD1-mRNA (synMYOD1)-treated hESCs. ( a ) synMYOD1 was synthesized in vitro with T7 RNA polymerase. The template cDNA was flanked by 5′UTR and 3′UTR of alpha-globin with an oligo(T) 120 for adding a polyA tail. ARCA (5′cap analog), pseudo-UTP, and 5-methyl-CTP were incorporated to increase mRNA stability and translation efficiency. ( b ) The percentage of mRNA transfection in hESCs was tested using synthetic mRNA encoding Emerald GFP by FACS analysis. ( c ) Schematic diagram of the transfection protocol. hESCs were transfected with synMYOD1 once on day 0, twice on day 1, and once on day 2. ( d ) Immunostaining analysis for MyHC in the synMYOD1-transfected cells. Nuclei were stained with DAPI. The percentage of MyHC-stained cells is shown (mean ± SEM from four independent biological replicates). Scale bar: 200 μm. ( e ) Immunostaining analysis for POU5F1 in the synMYOD1-transfected cells at day 0 to day 3 post transfection. MYOD1 was detected by a MYOD1 specific antibody. Nuclei were stained with DAPI. Scale bar: 10 μm. ( f ) Immunostaining analysis for NANOG in the synMYOD1-transfected cells at day 0 to day 3 post transfection. MYOD1 was detected by the specific antibody. Nuclei were stained with DAPI. Scale bar: 10 μm. ( g ) qRT-PCR analysis for POU5F1 expression day 0 to day 3 after transfection (mean ± SEM from two independent biological replicates). ( h ) Immunoblotting analysis for POU5F1 in the synMYOD1-transfected cells at day 3 post transfection. MYOD1 was detected by the specific antibody. The H3 antibody was used as a loading control. The relative intensities of POU5F1 signals normalized by H3 were compared between no transfection and synMYOD1 transfection (mean ± SEM from three independent biological replicates). NS: not significant. Uncropped images of the blots for Fig. 1h are shown in Supplementary Figure 7 .
    Figure Legend Snippet: POU5F1 expression is stably sustained in MYOD1-mRNA (synMYOD1)-treated hESCs. ( a ) synMYOD1 was synthesized in vitro with T7 RNA polymerase. The template cDNA was flanked by 5′UTR and 3′UTR of alpha-globin with an oligo(T) 120 for adding a polyA tail. ARCA (5′cap analog), pseudo-UTP, and 5-methyl-CTP were incorporated to increase mRNA stability and translation efficiency. ( b ) The percentage of mRNA transfection in hESCs was tested using synthetic mRNA encoding Emerald GFP by FACS analysis. ( c ) Schematic diagram of the transfection protocol. hESCs were transfected with synMYOD1 once on day 0, twice on day 1, and once on day 2. ( d ) Immunostaining analysis for MyHC in the synMYOD1-transfected cells. Nuclei were stained with DAPI. The percentage of MyHC-stained cells is shown (mean ± SEM from four independent biological replicates). Scale bar: 200 μm. ( e ) Immunostaining analysis for POU5F1 in the synMYOD1-transfected cells at day 0 to day 3 post transfection. MYOD1 was detected by a MYOD1 specific antibody. Nuclei were stained with DAPI. Scale bar: 10 μm. ( f ) Immunostaining analysis for NANOG in the synMYOD1-transfected cells at day 0 to day 3 post transfection. MYOD1 was detected by the specific antibody. Nuclei were stained with DAPI. Scale bar: 10 μm. ( g ) qRT-PCR analysis for POU5F1 expression day 0 to day 3 after transfection (mean ± SEM from two independent biological replicates). ( h ) Immunoblotting analysis for POU5F1 in the synMYOD1-transfected cells at day 3 post transfection. MYOD1 was detected by the specific antibody. The H3 antibody was used as a loading control. The relative intensities of POU5F1 signals normalized by H3 were compared between no transfection and synMYOD1 transfection (mean ± SEM from three independent biological replicates). NS: not significant. Uncropped images of the blots for Fig. 1h are shown in Supplementary Figure 7 .

    Techniques Used: Expressing, Stable Transfection, Synthesized, In Vitro, Transfection, FACS, Immunostaining, Staining, Quantitative RT-PCR

    33) Product Images from "mRNA Cap Methyltransferase, RNMT-RAM, Promotes RNA Pol II-Dependent Transcription"

    Article Title: mRNA Cap Methyltransferase, RNMT-RAM, Promotes RNA Pol II-Dependent Transcription

    Journal: Cell Reports

    doi: 10.1016/j.celrep.2018.04.004

    RNMT-RAM Regulates Transcription Independent of mRNA Cap Methylation (A–C) HeLa cells incubated with 60 μM 3 H-uridine for 30 min. Transcripts were poly(A) selected. Relative 3 H-uridine incorporation was normalized to poly(A) RNA (n = 3). (A) Cells transfected with RAM siRNAs or non-targeting control (sc siRNA) for 36 hr. (B) Cells transfected with RAM siRNA or sc siRNA for 36 hr, and HA-RNMT was induced with doxycycline for 12 hr. (C) Cells transfected with pcDNA5 Fg-RAM and pcDNA5 HA-RNMT wild-type (WT), methyltransferase-dead (MTD), or vector control for 48 hr. Representative western blots are shown. (D) HeLa nuclei incubated with NTPs, BrUTP, and recombinant RNMT (FL)-RAM (1–90) for 20 min. Br-RNA was purified and used as a substrate for RT-PCR. Primers are indicated (n = 4). (E) HeLa cells transfected with RAM siRNAs or sc siRNA for 36 hr. Levels of mature and pre-mRNA were determined by RT-PCR relative to sc siRNA control (n = 4). For charts, average and SD are indicated. Student’s t test was performed. ∗ p
    Figure Legend Snippet: RNMT-RAM Regulates Transcription Independent of mRNA Cap Methylation (A–C) HeLa cells incubated with 60 μM 3 H-uridine for 30 min. Transcripts were poly(A) selected. Relative 3 H-uridine incorporation was normalized to poly(A) RNA (n = 3). (A) Cells transfected with RAM siRNAs or non-targeting control (sc siRNA) for 36 hr. (B) Cells transfected with RAM siRNA or sc siRNA for 36 hr, and HA-RNMT was induced with doxycycline for 12 hr. (C) Cells transfected with pcDNA5 Fg-RAM and pcDNA5 HA-RNMT wild-type (WT), methyltransferase-dead (MTD), or vector control for 48 hr. Representative western blots are shown. (D) HeLa nuclei incubated with NTPs, BrUTP, and recombinant RNMT (FL)-RAM (1–90) for 20 min. Br-RNA was purified and used as a substrate for RT-PCR. Primers are indicated (n = 4). (E) HeLa cells transfected with RAM siRNAs or sc siRNA for 36 hr. Levels of mature and pre-mRNA were determined by RT-PCR relative to sc siRNA control (n = 4). For charts, average and SD are indicated. Student’s t test was performed. ∗ p

    Techniques Used: Methylation, Incubation, Transfection, Plasmid Preparation, Western Blot, Recombinant, Purification, Reverse Transcription Polymerase Chain Reaction

    34) Product Images from "In vivo RNA editing of point mutations via RNA-guided adenosine deaminases"

    Article Title: In vivo RNA editing of point mutations via RNA-guided adenosine deaminases

    Journal: Nature methods

    doi: 10.1038/s41592-019-0323-0

    In vivo RNA editing in mouse models of human disease: (a) Schematic of the DNA and RNA targeting approaches to restore dystrophin expression in the mdx mouse model of Duchenne Muscular Dystrophy: (i) a dual gRNA-CRISPR based approach leading to in frame excision of exon 23 and (ii) ADAR2 and MCP-ADAR1 based editing of the ochre codon. (b) Immunofluorescence staining for dystrophin in the TA muscle shows partial restoration of expression in treated samples (intra-muscular injections of AAV8-ADAR2, AAV8-ADAR2 (E488Q), and AAV8-CRISPR). Partial restoration of nNOS localization is also seen in treated samples (scale bar: 250μm). (c) In vivo TAA- > TGG/TAG/TGA RNA editing efficiencies in corresponding treated adult mdx mice. Values represent mean +/− SEM (n=4, 3, 7, 3, 3, 10, 3, 4 independent TA muscles respectively). (d) Schematic of the OTC locus in the spf ash mouse model of Ornithine Transcarbamylase deficiency which have a G- > A point mutation at a donor splice site in the last nucleotide of exon 4, and approach for correction of mutant OTC mRNA via ADAR2 mediated RNA editing. (e) In vivo RNA correction efficiencies in the correctly spliced OTC mRNA in the livers of treated adult spf ash mice (retro-orbital injections of AAV8-ADAR2 and AAV8-ADAR2 (E488Q)). Values represent mean +/− SEM (n=4, 4, 3, 3, 4, 5 independent animals respectively).
    Figure Legend Snippet: In vivo RNA editing in mouse models of human disease: (a) Schematic of the DNA and RNA targeting approaches to restore dystrophin expression in the mdx mouse model of Duchenne Muscular Dystrophy: (i) a dual gRNA-CRISPR based approach leading to in frame excision of exon 23 and (ii) ADAR2 and MCP-ADAR1 based editing of the ochre codon. (b) Immunofluorescence staining for dystrophin in the TA muscle shows partial restoration of expression in treated samples (intra-muscular injections of AAV8-ADAR2, AAV8-ADAR2 (E488Q), and AAV8-CRISPR). Partial restoration of nNOS localization is also seen in treated samples (scale bar: 250μm). (c) In vivo TAA- > TGG/TAG/TGA RNA editing efficiencies in corresponding treated adult mdx mice. Values represent mean +/− SEM (n=4, 3, 7, 3, 3, 10, 3, 4 independent TA muscles respectively). (d) Schematic of the OTC locus in the spf ash mouse model of Ornithine Transcarbamylase deficiency which have a G- > A point mutation at a donor splice site in the last nucleotide of exon 4, and approach for correction of mutant OTC mRNA via ADAR2 mediated RNA editing. (e) In vivo RNA correction efficiencies in the correctly spliced OTC mRNA in the livers of treated adult spf ash mice (retro-orbital injections of AAV8-ADAR2 and AAV8-ADAR2 (E488Q)). Values represent mean +/− SEM (n=4, 4, 3, 3, 4, 5 independent animals respectively).

    Techniques Used: In Vivo, Expressing, CRISPR, Immunofluorescence, Staining, Mouse Assay, Mutagenesis

    35) Product Images from "Gene expression profiling of Trypanosoma cruzi in the presence of heme points to glycosomal metabolic adaptation of epimastigotes inside the vector"

    Article Title: Gene expression profiling of Trypanosoma cruzi in the presence of heme points to glycosomal metabolic adaptation of epimastigotes inside the vector

    Journal: PLoS Neglected Tropical Diseases

    doi: 10.1371/journal.pntd.0007945

    RNAseq and qPCR data of selected genes modulated by heme. For qPCR validation, total RNA was extracted using TRIzol method (Invitrogen) and then was reverse-transcripted to single strand cDNA using High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, USA) according to the manufacturer's instructions. All quantitative measurements were carried out in triplicate and normalized to the internal TCZ control. Results were expressed as mean value ± standard error (SE). The mRNA fold change was calculated as described in the Material and Methods section. qPCR and RNAseq data were plotted for each gene for analysis. ST: sugar transporter; GALK : galactokinase; HK : hexokinase; PMI: phosphomannose isomerase; PFK : phosphofructokinase; ALD : fructose bisphosphate aldolase, glycosomal; ENO: enolase; PPDKg : pyruvate phosphate dikinase, glycosomal; PEPCKg : phosphoenolpyruvate carboxykinase, glycosomal; MDHg : malate dehydrogenase, glycosomal; FRD* : NADH-dependent fumarate reductase; KBL : 2-amino-3-ketobutyrate CoA ligase; P5CDH : δ-1-pyrroline-5-carboxylate dehydrogenase; ASAT: aspartate aminotransferase; AS : asparagine synthetase A; AHADH: aromatic L-2-hydroxyacid dehydrogenase; ME : malic enzyme, cytosolic; COMPLEX I : NADH-ubiquinone oxidoreductase; SDH : succinate dehydrogenase subunit; ABCt : ABC transporter; PdxK : pyridoxal kinase. This graphic presents DEGs in “non-esmeraldo-like” haplotype and some only in “esmeraldo-like” that were marked with (*).
    Figure Legend Snippet: RNAseq and qPCR data of selected genes modulated by heme. For qPCR validation, total RNA was extracted using TRIzol method (Invitrogen) and then was reverse-transcripted to single strand cDNA using High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, USA) according to the manufacturer's instructions. All quantitative measurements were carried out in triplicate and normalized to the internal TCZ control. Results were expressed as mean value ± standard error (SE). The mRNA fold change was calculated as described in the Material and Methods section. qPCR and RNAseq data were plotted for each gene for analysis. ST: sugar transporter; GALK : galactokinase; HK : hexokinase; PMI: phosphomannose isomerase; PFK : phosphofructokinase; ALD : fructose bisphosphate aldolase, glycosomal; ENO: enolase; PPDKg : pyruvate phosphate dikinase, glycosomal; PEPCKg : phosphoenolpyruvate carboxykinase, glycosomal; MDHg : malate dehydrogenase, glycosomal; FRD* : NADH-dependent fumarate reductase; KBL : 2-amino-3-ketobutyrate CoA ligase; P5CDH : δ-1-pyrroline-5-carboxylate dehydrogenase; ASAT: aspartate aminotransferase; AS : asparagine synthetase A; AHADH: aromatic L-2-hydroxyacid dehydrogenase; ME : malic enzyme, cytosolic; COMPLEX I : NADH-ubiquinone oxidoreductase; SDH : succinate dehydrogenase subunit; ABCt : ABC transporter; PdxK : pyridoxal kinase. This graphic presents DEGs in “non-esmeraldo-like” haplotype and some only in “esmeraldo-like” that were marked with (*).

    Techniques Used: Real-time Polymerase Chain Reaction

    36) Product Images from "Post-transcriptional 3´-UTR cleavage of mRNA transcripts generates thousands of stable uncapped autonomous RNA fragments"

    Article Title: Post-transcriptional 3´-UTR cleavage of mRNA transcripts generates thousands of stable uncapped autonomous RNA fragments

    Journal: Nature Communications

    doi: 10.1038/s41467-017-02099-7

    Cleavage of 3′-UTR regions results in autonomous uncapped RNA fragments. a RNA-seq read coverage ( y -axis) for Ssr1 , Bcl2 , and Rab2a in mouse T cells 12 , B cells 14 , and brain tissue 15 , demonstrating a gap in read coverage (marked by arrows) at 3′-UTRs, as well as uneven levels of RNA upstream and downstream of the gap site. b Three sets of primers were used per gene for qRT-PCR amplification: upstream (blue rectangle), downstream (red), and across the RNA-seq coverage gap (green). Bar plots (bottom) visualize the relative percentage of cytoplasmic (black) and nuclear (gray) expression of each amplicon out of its total (cytoplasm+nuclear) expression. c A model for post-transcriptional processing of mRNA: mRNA is cleaved at an APA site, resulting in a capped “body” and an uncapped 3′-UTR “tail,” sensitive to terminator 5′-phosphate-dependent exonuclease (TEX) treatment. d qRT-PCR analysis shows cytoplasmic degradation of the “tail” unit (in red) compared to the “body” unit (in blue) following TEX treatment. * p
    Figure Legend Snippet: Cleavage of 3′-UTR regions results in autonomous uncapped RNA fragments. a RNA-seq read coverage ( y -axis) for Ssr1 , Bcl2 , and Rab2a in mouse T cells 12 , B cells 14 , and brain tissue 15 , demonstrating a gap in read coverage (marked by arrows) at 3′-UTRs, as well as uneven levels of RNA upstream and downstream of the gap site. b Three sets of primers were used per gene for qRT-PCR amplification: upstream (blue rectangle), downstream (red), and across the RNA-seq coverage gap (green). Bar plots (bottom) visualize the relative percentage of cytoplasmic (black) and nuclear (gray) expression of each amplicon out of its total (cytoplasm+nuclear) expression. c A model for post-transcriptional processing of mRNA: mRNA is cleaved at an APA site, resulting in a capped “body” and an uncapped 3′-UTR “tail,” sensitive to terminator 5′-phosphate-dependent exonuclease (TEX) treatment. d qRT-PCR analysis shows cytoplasmic degradation of the “tail” unit (in red) compared to the “body” unit (in blue) following TEX treatment. * p

    Techniques Used: RNA Sequencing Assay, Quantitative RT-PCR, Amplification, Expressing

    37) Product Images from "Holo-Seq: single-cell sequencing of holo-transcriptome"

    Article Title: Holo-Seq: single-cell sequencing of holo-transcriptome

    Journal: Genome Biology

    doi: 10.1186/s13059-018-1553-7

    Holo-Seq accurately profiles total RNAs with a complete strand of origin information from single cells. a RPKM scatterplots of expressed genes between the combined dataset (total RNA with a complete strand of origin information from 10 mESCs single cells) and a directional bulk mRNA-Seq. b Comparison of the detected gene number in HEK293T single cells at the maximum exome-mapped depth of MATQ-Seq (UMI labeled reads) and 1.2M unique exome-mapped depth of Holo-Seq, SUPeR-Seq, and Smart-Seq2. c Read coverage across transcripts of different lengths of three methods in HEK293T single cells. The read coverage over the transcripts is displayed along with the percentage of the distance from their 3′ end. Shaded regions indicate the standard deviation
    Figure Legend Snippet: Holo-Seq accurately profiles total RNAs with a complete strand of origin information from single cells. a RPKM scatterplots of expressed genes between the combined dataset (total RNA with a complete strand of origin information from 10 mESCs single cells) and a directional bulk mRNA-Seq. b Comparison of the detected gene number in HEK293T single cells at the maximum exome-mapped depth of MATQ-Seq (UMI labeled reads) and 1.2M unique exome-mapped depth of Holo-Seq, SUPeR-Seq, and Smart-Seq2. c Read coverage across transcripts of different lengths of three methods in HEK293T single cells. The read coverage over the transcripts is displayed along with the percentage of the distance from their 3′ end. Shaded regions indicate the standard deviation

    Techniques Used: Labeling, Standard Deviation

    38) Product Images from "Dual leucine zipper kinase regulates expression of axon guidance genes in mouse neuronal cells"

    Article Title: Dual leucine zipper kinase regulates expression of axon guidance genes in mouse neuronal cells

    Journal: Neural Development

    doi: 10.1186/s13064-016-0068-8

    Knockdown of DLK in differentiated Neuro-2a cells. Neuro-2a cells were infected with an empty lentiviral vector (pLKO.1) or with lentivirus expressing mouse DLK shRNAs (sh73 and sh69). After infection and selection with puromycin, cells were subjected to differentiation for 24 h before being processed for total RNA extraction and whole-cell extracts. a The relative mRNA level of DLK in infected cells was analyzed by quantitative RT-PCR, normalized to three housekeeping genes and calculated with the ΔΔ C T method. The value of DLK mRNA expression in control cells (pLKO.1) was arbitrarily set to 1. Data are the mean ± SEM (error bars) from three independent experiments carried out in triplicate. ****, p
    Figure Legend Snippet: Knockdown of DLK in differentiated Neuro-2a cells. Neuro-2a cells were infected with an empty lentiviral vector (pLKO.1) or with lentivirus expressing mouse DLK shRNAs (sh73 and sh69). After infection and selection with puromycin, cells were subjected to differentiation for 24 h before being processed for total RNA extraction and whole-cell extracts. a The relative mRNA level of DLK in infected cells was analyzed by quantitative RT-PCR, normalized to three housekeeping genes and calculated with the ΔΔ C T method. The value of DLK mRNA expression in control cells (pLKO.1) was arbitrarily set to 1. Data are the mean ± SEM (error bars) from three independent experiments carried out in triplicate. ****, p

    Techniques Used: Infection, Plasmid Preparation, Expressing, Selection, RNA Extraction, Quantitative RT-PCR

    Validation of RNA-seq data by qRT-PCR and Western blot analyses. a The relative mRNA level of DLK and axon guidance genes in infected cells was analyzed by qRT-PCR, normalized to three housekeeping genes and calculated with the ΔΔ C T method. The value of mRNA expression for each gene in control cells (pLKO.1) was arbitrarily set to 1. Data are the mean ± SEM (error bars) from three independent experiments carried out in triplicate. *, p
    Figure Legend Snippet: Validation of RNA-seq data by qRT-PCR and Western blot analyses. a The relative mRNA level of DLK and axon guidance genes in infected cells was analyzed by qRT-PCR, normalized to three housekeeping genes and calculated with the ΔΔ C T method. The value of mRNA expression for each gene in control cells (pLKO.1) was arbitrarily set to 1. Data are the mean ± SEM (error bars) from three independent experiments carried out in triplicate. *, p

    Techniques Used: RNA Sequencing Assay, Quantitative RT-PCR, Western Blot, Infection, Expressing

    39) Product Images from "Genetic modification of primary human B cells to model high-grade lymphoma"

    Article Title: Genetic modification of primary human B cells to model high-grade lymphoma

    Journal: Nature Communications

    doi: 10.1038/s41467-019-12494-x

    Ex vivo growth and transduction of primary human GC B cells. a Representative flow cytometry analysis ( n > 3) for the expression of GC B cell markers CD38, CD20, CD19, and CD10 in purified GC B cells from pediatric tonsil tissue. The strategy for negative selection of GC B cells is shown. b Representative images are shown of YK6 cells, GC B cells alone, or GC B cells cultured on either YK6-CD40lg or YK6-CD40lg-IL21 feeder cells. Scale bar represents 50 or 100 μm as indicated. Source data are provided as a Source Data file. c Primary human GC B cells were cultured with YK6 control, YK6-CD40lg, or YK6-CD40lg-IL21 feeder cells. Illustrated is bar graph showing the number of viable cells ( ± s.e.m., n = 5) over four timepoints. Viable cells were determined by flow cytometry and counting beads. Source data are provided as a Source Data file. d Bar graph showing the relative transcript expression of SLC20A1 (GaLV receptor) and LDLR (VSV-G receptor) in naïve ( n = 1), GC B cells ( n = 3), and ABC/GCB DLBCL and Burkitt cell lines ( n = 6) as analyzed by RNA-seq. mRNA expression values were calculated as counts per million reads (CPM). Error bars indicate ± s.e.m. Source data are provided as a Source Data file. e Schematic of the retroviral and lentiviral MuLV-GaLV fusion envelopes, GaLV_WT, GaLV_MTR, and GaLV_TR. M = transmembrane region, T = cytoplasmic tail, R = R peptide, SU = surface subunit, TM = transmembrane subunit 19 . f , g Primary human GC B cells were transduced with a retroviral control ( f ) or lentiviral control ( g ) construct using GaLV-MuLV fusion envelope constructs as well as VSV-G and MuLV. Three days after transduction, transduction efficiencies in primary human GC B cells were determined by expression of GFP. Error bars indicate ± s.e.m., n = 3. FSC forward scatter. Source data are provided as a Source Data file
    Figure Legend Snippet: Ex vivo growth and transduction of primary human GC B cells. a Representative flow cytometry analysis ( n > 3) for the expression of GC B cell markers CD38, CD20, CD19, and CD10 in purified GC B cells from pediatric tonsil tissue. The strategy for negative selection of GC B cells is shown. b Representative images are shown of YK6 cells, GC B cells alone, or GC B cells cultured on either YK6-CD40lg or YK6-CD40lg-IL21 feeder cells. Scale bar represents 50 or 100 μm as indicated. Source data are provided as a Source Data file. c Primary human GC B cells were cultured with YK6 control, YK6-CD40lg, or YK6-CD40lg-IL21 feeder cells. Illustrated is bar graph showing the number of viable cells ( ± s.e.m., n = 5) over four timepoints. Viable cells were determined by flow cytometry and counting beads. Source data are provided as a Source Data file. d Bar graph showing the relative transcript expression of SLC20A1 (GaLV receptor) and LDLR (VSV-G receptor) in naïve ( n = 1), GC B cells ( n = 3), and ABC/GCB DLBCL and Burkitt cell lines ( n = 6) as analyzed by RNA-seq. mRNA expression values were calculated as counts per million reads (CPM). Error bars indicate ± s.e.m. Source data are provided as a Source Data file. e Schematic of the retroviral and lentiviral MuLV-GaLV fusion envelopes, GaLV_WT, GaLV_MTR, and GaLV_TR. M = transmembrane region, T = cytoplasmic tail, R = R peptide, SU = surface subunit, TM = transmembrane subunit 19 . f , g Primary human GC B cells were transduced with a retroviral control ( f ) or lentiviral control ( g ) construct using GaLV-MuLV fusion envelope constructs as well as VSV-G and MuLV. Three days after transduction, transduction efficiencies in primary human GC B cells were determined by expression of GFP. Error bars indicate ± s.e.m., n = 3. FSC forward scatter. Source data are provided as a Source Data file

    Techniques Used: Ex Vivo, Transduction, Flow Cytometry, Cytometry, Expressing, Purification, Selection, Cell Culture, RNA Sequencing Assay, Construct

    40) Product Images from "Increased Serine and One Carbon Pathway Metabolism by PKCλ/ι Deficiency Promotes Neuroendocrine Prostate Cancer"

    Article Title: Increased Serine and One Carbon Pathway Metabolism by PKCλ/ι Deficiency Promotes Neuroendocrine Prostate Cancer

    Journal: Cancer cell

    doi: 10.1016/j.ccell.2019.01.018

    Loss of PKCλ/ι is Sufficient to Promote NEPC Differentiation at a Cellular Level (A) Western blot of indicated proteins in shNT and shPKCλ/ι LNCaP cells. (B) qPCR of indicated NEPC-, Basal-, and AR-related genes in shNT and shPKCλ/ι LNCaP cells (n = 3–4). (C) Western blot of indicated proteins in sgC, sgPKCλ/ι and sgPKCλ/ι-R C42B cells (n = 3). (D) qPCR of indicated genes in sgC, sgPKCλ/ι and sgPKCλ/ι-R C42B cells (n = 3). ) in microarray data of shNT (NT) and shPKCλ/ι PrEC cells. (F) Cell proliferation of shNT and shPKCλ/ι LNCaP cells (n = 3) under androgen deprivation (ADT) with or without enzalutamide (enza, 10 μM). Western blot of PKCλ/ι. (G) qPCR of indicated genes in shNT and shPKCλ/ι LNCaP cells (n = 3–6). (H) Cell proliferation in ADT (n = 3) and western blot of PC3 cells expressing FLAG or FLAG-PKCλ/ι. (I) Cell proliferation of sgC and sgPKCλ/ι C42B cells in ADT (n = 3). (J) qPCR analysis of E2F1 mRNA levels in sgC and sgPKCλ/ι C42B cells (n = 4). (K) Tumor growth of xenografts of sgC, sgPKCλ/ι and sgPKCλ/ι-R C42B cells (n = 4–12). .
    Figure Legend Snippet: Loss of PKCλ/ι is Sufficient to Promote NEPC Differentiation at a Cellular Level (A) Western blot of indicated proteins in shNT and shPKCλ/ι LNCaP cells. (B) qPCR of indicated NEPC-, Basal-, and AR-related genes in shNT and shPKCλ/ι LNCaP cells (n = 3–4). (C) Western blot of indicated proteins in sgC, sgPKCλ/ι and sgPKCλ/ι-R C42B cells (n = 3). (D) qPCR of indicated genes in sgC, sgPKCλ/ι and sgPKCλ/ι-R C42B cells (n = 3). ) in microarray data of shNT (NT) and shPKCλ/ι PrEC cells. (F) Cell proliferation of shNT and shPKCλ/ι LNCaP cells (n = 3) under androgen deprivation (ADT) with or without enzalutamide (enza, 10 μM). Western blot of PKCλ/ι. (G) qPCR of indicated genes in shNT and shPKCλ/ι LNCaP cells (n = 3–6). (H) Cell proliferation in ADT (n = 3) and western blot of PC3 cells expressing FLAG or FLAG-PKCλ/ι. (I) Cell proliferation of sgC and sgPKCλ/ι C42B cells in ADT (n = 3). (J) qPCR analysis of E2F1 mRNA levels in sgC and sgPKCλ/ι C42B cells (n = 4). (K) Tumor growth of xenografts of sgC, sgPKCλ/ι and sgPKCλ/ι-R C42B cells (n = 4–12). .

    Techniques Used: Western Blot, Real-time Polymerase Chain Reaction, Microarray, Expressing

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    New England Biolabs mrna magnetic isolation module
    The KH domains of IGF2BPs are critical for m 6 A recognition and binding ( a ) Schematic structures showing <t>RNA</t> binding domains within IGF2BP proteins and a summary of IGF2BP variants used in this study. Blue boxes are RRM domains, red boxes are wild-type KH domains with GxxG core, and grey boxes are inactive KH domain with GxxG to GEEG conversions. ( b ) RNA pulldown followed by Western blotting showed in vitro binding of ssRNA baits with wild-type (wt) or KH domain-mutated IGF2BP variants, representative of 3 independent experiments. ( c ) In vitro binding of CRD1 RNA probes with wild-type or KH3-4 mutated IGF2BPs, representative of 3 independent experiments. ( d ) The association of wild-type and KH3-4 mutated IGF2BPs with MYC CRD in HEK293T cells as assessed by RIP-qPCR. ( e ) Relative luciferase activity of CRD reporters in HEK293T cells with forced expression of wild-type or mutated IGF2BP2 variants. ( f ) Changes in MYC <t>mRNA</t> levels in Hela cells with empty vector or forced expression of wild-type or KH3-4 mutated IGF2BPs one hour post-heat shock (HS). Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in d , e , f (*, P
    Mrna Magnetic Isolation Module, supplied by New England Biolabs, used in various techniques. Bioz Stars score: 99/100, based on 495 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    The KH domains of IGF2BPs are critical for m 6 A recognition and binding ( a ) Schematic structures showing RNA binding domains within IGF2BP proteins and a summary of IGF2BP variants used in this study. Blue boxes are RRM domains, red boxes are wild-type KH domains with GxxG core, and grey boxes are inactive KH domain with GxxG to GEEG conversions. ( b ) RNA pulldown followed by Western blotting showed in vitro binding of ssRNA baits with wild-type (wt) or KH domain-mutated IGF2BP variants, representative of 3 independent experiments. ( c ) In vitro binding of CRD1 RNA probes with wild-type or KH3-4 mutated IGF2BPs, representative of 3 independent experiments. ( d ) The association of wild-type and KH3-4 mutated IGF2BPs with MYC CRD in HEK293T cells as assessed by RIP-qPCR. ( e ) Relative luciferase activity of CRD reporters in HEK293T cells with forced expression of wild-type or mutated IGF2BP2 variants. ( f ) Changes in MYC mRNA levels in Hela cells with empty vector or forced expression of wild-type or KH3-4 mutated IGF2BPs one hour post-heat shock (HS). Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in d , e , f (*, P

    Journal: Nature cell biology

    Article Title: Recognition of RNA N6-methyladenosine by IGF2BP Proteins Enhances mRNA Stability and Translation

    doi: 10.1038/s41556-018-0045-z

    Figure Lengend Snippet: The KH domains of IGF2BPs are critical for m 6 A recognition and binding ( a ) Schematic structures showing RNA binding domains within IGF2BP proteins and a summary of IGF2BP variants used in this study. Blue boxes are RRM domains, red boxes are wild-type KH domains with GxxG core, and grey boxes are inactive KH domain with GxxG to GEEG conversions. ( b ) RNA pulldown followed by Western blotting showed in vitro binding of ssRNA baits with wild-type (wt) or KH domain-mutated IGF2BP variants, representative of 3 independent experiments. ( c ) In vitro binding of CRD1 RNA probes with wild-type or KH3-4 mutated IGF2BPs, representative of 3 independent experiments. ( d ) The association of wild-type and KH3-4 mutated IGF2BPs with MYC CRD in HEK293T cells as assessed by RIP-qPCR. ( e ) Relative luciferase activity of CRD reporters in HEK293T cells with forced expression of wild-type or mutated IGF2BP2 variants. ( f ) Changes in MYC mRNA levels in Hela cells with empty vector or forced expression of wild-type or KH3-4 mutated IGF2BPs one hour post-heat shock (HS). Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in d , e , f (*, P

    Article Snippet: PolyA RNA was subsequently purified from 50–100 ng total RNA using NEBNext Poly(A) mRNA Magnetic Isolation Module.

    Techniques: Binding Assay, RNA Binding Assay, Western Blot, In Vitro, Real-time Polymerase Chain Reaction, Luciferase, Activity Assay, Expressing, Plasmid Preparation, Two Tailed Test

    IGF2BPs regulate MYC expression through binding to methylated CRD ( a ) Distribution of m 6 A peaks across MYC mRNA transcript. The coding region instability determinant (CRD) region is highlighted in yellow. m 6 A-seq was repeated twice while RIP-seq was performed once.( b ) RIP-qPCR showing the association of MYC CRD with FLAG-tagged IGF2BPs in HEK293T cells. ( c ) Enrichment of m 6 A modification in MYC CRD as detected by gene specific m 6 A qPCR assay. ( d ) RIP-qPCR showing the binding of METTL3 and METTL14 to the MYC CRD. ( e ) RNA pulldown of endogenous IGF2BP proteins from HEK293T nuclear extract using synthetic CRD RNA fragments, CRD1 and CRD2, with (m 6 A) or without (A) m 6 A modifications. Images are representative of 3 independent experiments. ( f ) Relative firefly luciferase (Fluc) activity (i.e., protein level; left) and Fluc mRNA level (right) of wild-type (CRD-wt) or mutated (CRD-mut) CRD reporters in HEK293T cells with ectopically expressed IGF2BP1, IGF2BP2, or IGF2BP3. ( g ) RIP-qPCR detecting the in vivo binding of Flag-IGF2BPs to the transcripts of CRD-wt or CRD-mut luciferase reporter in HEK293T cells. ( h and i ) Relative luciferase activity of CRD-wt or CRD-mut in Hela cells with or without stable knockdown of IGF2BPs (h) or METTL14 (i). ( j ) Relative luciferase activity of CRD-wt or CRD-mut in METTL14 stable knockdown or control Hela cells with ectopic expression of IGF2BPs . For all luciferase assays, the Fluc/Rluc ratio (representing luciferase activity) of CRD-wt with empty vector or shNS was used for normalization. Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in b , c , d , f , g , h , i , j . (**, P

    Journal: Nature cell biology

    Article Title: Recognition of RNA N6-methyladenosine by IGF2BP Proteins Enhances mRNA Stability and Translation

    doi: 10.1038/s41556-018-0045-z

    Figure Lengend Snippet: IGF2BPs regulate MYC expression through binding to methylated CRD ( a ) Distribution of m 6 A peaks across MYC mRNA transcript. The coding region instability determinant (CRD) region is highlighted in yellow. m 6 A-seq was repeated twice while RIP-seq was performed once.( b ) RIP-qPCR showing the association of MYC CRD with FLAG-tagged IGF2BPs in HEK293T cells. ( c ) Enrichment of m 6 A modification in MYC CRD as detected by gene specific m 6 A qPCR assay. ( d ) RIP-qPCR showing the binding of METTL3 and METTL14 to the MYC CRD. ( e ) RNA pulldown of endogenous IGF2BP proteins from HEK293T nuclear extract using synthetic CRD RNA fragments, CRD1 and CRD2, with (m 6 A) or without (A) m 6 A modifications. Images are representative of 3 independent experiments. ( f ) Relative firefly luciferase (Fluc) activity (i.e., protein level; left) and Fluc mRNA level (right) of wild-type (CRD-wt) or mutated (CRD-mut) CRD reporters in HEK293T cells with ectopically expressed IGF2BP1, IGF2BP2, or IGF2BP3. ( g ) RIP-qPCR detecting the in vivo binding of Flag-IGF2BPs to the transcripts of CRD-wt or CRD-mut luciferase reporter in HEK293T cells. ( h and i ) Relative luciferase activity of CRD-wt or CRD-mut in Hela cells with or without stable knockdown of IGF2BPs (h) or METTL14 (i). ( j ) Relative luciferase activity of CRD-wt or CRD-mut in METTL14 stable knockdown or control Hela cells with ectopic expression of IGF2BPs . For all luciferase assays, the Fluc/Rluc ratio (representing luciferase activity) of CRD-wt with empty vector or shNS was used for normalization. Values are mean±s.d. of n =3 independent experiments, and two-tailed Student’s t -tests were used in b , c , d , f , g , h , i , j . (**, P

    Article Snippet: PolyA RNA was subsequently purified from 50–100 ng total RNA using NEBNext Poly(A) mRNA Magnetic Isolation Module.

    Techniques: Expressing, Binding Assay, Methylation, Real-time Polymerase Chain Reaction, Modification, Luciferase, Activity Assay, In Vivo, Plasmid Preparation, Two Tailed Test

    Selective binding of IGF2BPs to m 6 A-modified RNAs ( a ) Identification of m 6 A specific binding proteins by RNA affinity chromatography using ssRNA probes with methylated (red) or unmethylated (green) adenosine. Silver staining (lower left) and Western blotting (lower right) showed selective pulldown of ~68kDa IGF2BP proteins from HEK293T nuclear extract. Western blot images were representative of 3 independent experiments. ( b ) Enrichment of m 6 A consensus sequence “GGAC” in the binding sites of RBPs. The three IGF2BP paralogues were shown in red, while the YTH domain proteins were shown in orange. ( c ) Quantification of m 6 A/A and m 6 A/AGCU ratios by LC-MS/MS in RNAs bound by ectopically expressed IGF2BP1 (chicken ZBP1), IGF2BP2 (human), or IGF2BP3 (human). Values are mean of n =2 independent experiments and individual data points are showed. ( d ) Overlap of IGF2BP target genes identified by RIP-seq and published PAR-CLIP in HEK293T cells. RIP-seq was performed once. P value was calculated by Fisher’s test. ( e ) Venn diagram showing the numbers of shared high-confidence targets ( i.e. , CLIP+RIP targets) amongst IGF2BP paralogues. P value was calculated by Fisher’s test. ( f ) Top consensus sequences of IGF2BP binding sites and the m 6 A motif detected by HOMER Motif analysis with PAR-CLIP data. ( g ) Pie charts showing numbers and percentages of IGF2BP high-confidence target genes that contain m 6 A peaks. The m 6 A-seq data was reported in Ref. 3 . ( h ) Metagene profiles of enrichment of IGF2BP binding sites and m 6 A modifications across mRNA transcriptome. ( i ) Percentages of various RNA species bound by IGF2BPs. ( j ) The distribution (upper) and enrichment (lower) of IGF2BPs binding peaks within different gene reions. The enrichment was determined by the proportion of IGF2BPs binding peaks normalized by the length of the region. Analyses in i and j were performed twice with similar results. ( k ) In vivo binding of Flag-IGF2BP2 to representative target genes in METTL14 knockdown or control HEK293T cells. Values are mean±s.d. of n =3 independent experiments. *, P

    Journal: Nature cell biology

    Article Title: Recognition of RNA N6-methyladenosine by IGF2BP Proteins Enhances mRNA Stability and Translation

    doi: 10.1038/s41556-018-0045-z

    Figure Lengend Snippet: Selective binding of IGF2BPs to m 6 A-modified RNAs ( a ) Identification of m 6 A specific binding proteins by RNA affinity chromatography using ssRNA probes with methylated (red) or unmethylated (green) adenosine. Silver staining (lower left) and Western blotting (lower right) showed selective pulldown of ~68kDa IGF2BP proteins from HEK293T nuclear extract. Western blot images were representative of 3 independent experiments. ( b ) Enrichment of m 6 A consensus sequence “GGAC” in the binding sites of RBPs. The three IGF2BP paralogues were shown in red, while the YTH domain proteins were shown in orange. ( c ) Quantification of m 6 A/A and m 6 A/AGCU ratios by LC-MS/MS in RNAs bound by ectopically expressed IGF2BP1 (chicken ZBP1), IGF2BP2 (human), or IGF2BP3 (human). Values are mean of n =2 independent experiments and individual data points are showed. ( d ) Overlap of IGF2BP target genes identified by RIP-seq and published PAR-CLIP in HEK293T cells. RIP-seq was performed once. P value was calculated by Fisher’s test. ( e ) Venn diagram showing the numbers of shared high-confidence targets ( i.e. , CLIP+RIP targets) amongst IGF2BP paralogues. P value was calculated by Fisher’s test. ( f ) Top consensus sequences of IGF2BP binding sites and the m 6 A motif detected by HOMER Motif analysis with PAR-CLIP data. ( g ) Pie charts showing numbers and percentages of IGF2BP high-confidence target genes that contain m 6 A peaks. The m 6 A-seq data was reported in Ref. 3 . ( h ) Metagene profiles of enrichment of IGF2BP binding sites and m 6 A modifications across mRNA transcriptome. ( i ) Percentages of various RNA species bound by IGF2BPs. ( j ) The distribution (upper) and enrichment (lower) of IGF2BPs binding peaks within different gene reions. The enrichment was determined by the proportion of IGF2BPs binding peaks normalized by the length of the region. Analyses in i and j were performed twice with similar results. ( k ) In vivo binding of Flag-IGF2BP2 to representative target genes in METTL14 knockdown or control HEK293T cells. Values are mean±s.d. of n =3 independent experiments. *, P

    Article Snippet: PolyA RNA was subsequently purified from 50–100 ng total RNA using NEBNext Poly(A) mRNA Magnetic Isolation Module.

    Techniques: Binding Assay, Modification, Affinity Chromatography, Methylation, Silver Staining, Western Blot, Sequencing, Liquid Chromatography with Mass Spectroscopy, Mass Spectrometry, Cross-linking Immunoprecipitation, In Vivo

    mRNA decay is required for reprogramming the translatome and transcriptome. a Heatmap of expression levels for the top 250 most variable genes in our total data set. The color scale defines the measured expression of a given gene. b Genes with significant change in the polysomal fractions following a shift from 30 °C to 37 °C in the wild-type identified by RNA-Seq were plotted in order of log2 magnitude change (blue circles). The magnitude of change for each corresponding gene in the ccr4 Δ mutant was overlaid (orange circles). RP genes are highlighted in green. c Venn diagrams demonstrate genes that are upregulated and downregulated in response to host temperature in WT and the ccr4 Δ mutant following growth at 37 °C for 1 h. d GO analyses for genes differentially expressed in the ccr4 Δ mutant compared with wild-type 1 h after a shift to host temperature

    Journal: Nature Communications

    Article Title: Thermotolerance in the pathogen Cryptococcus neoformans is linked to antigen masking via mRNA decay-dependent reprogramming

    doi: 10.1038/s41467-019-12907-x

    Figure Lengend Snippet: mRNA decay is required for reprogramming the translatome and transcriptome. a Heatmap of expression levels for the top 250 most variable genes in our total data set. The color scale defines the measured expression of a given gene. b Genes with significant change in the polysomal fractions following a shift from 30 °C to 37 °C in the wild-type identified by RNA-Seq were plotted in order of log2 magnitude change (blue circles). The magnitude of change for each corresponding gene in the ccr4 Δ mutant was overlaid (orange circles). RP genes are highlighted in green. c Venn diagrams demonstrate genes that are upregulated and downregulated in response to host temperature in WT and the ccr4 Δ mutant following growth at 37 °C for 1 h. d GO analyses for genes differentially expressed in the ccr4 Δ mutant compared with wild-type 1 h after a shift to host temperature

    Article Snippet: To remove rRNA, polyadenylated mRNA was isolated from 4 µg of the total RNA using NEBNext poly(A) mRNA Magnetic Isolation Module (New England Biolabs) as per the manufacturer’s protocol, and RNA-seq libraries were constructed using NEBNext mRNA Library Prep Master Mix Set for Illumina (New England Biolabs) according to the manufacturer’s protocol.

    Techniques: Expressing, RNA Sequencing Assay, Mutagenesis

    Stabilized RP transcripts are retained in the actively translating pool. a Equivalent amounts of the total RNA from cultures grown at 30 °C or shifted to 37 °C for 1 h were vacuum filtered through a slot blot apparatus onto the nylon membrane. A P32-labeled oligo-dT was used to assess mRNA by northern blot. Graphs show averaged polyA mRNA levels ± s.e.m. from three biological replicates. b Polysome traces show the translational state of each strain during no stress and following a shift to 37 °C for 1 h. Subunits, monosomes, and polysome are indicated. RNA was extracted from fractions collected during polysome profiling for wild-type and ccr4 Δ. Equivalent volumes of RNA from each fraction were run on a formaldehyde-agarose gel for northern blot analysis of RPL2 . The rRNA bands confirm that the fractions correspond to the area of the polysome profile above. The results shown are representative of three biological replicates. Source data are provided as a Source Data file

    Journal: Nature Communications

    Article Title: Thermotolerance in the pathogen Cryptococcus neoformans is linked to antigen masking via mRNA decay-dependent reprogramming

    doi: 10.1038/s41467-019-12907-x

    Figure Lengend Snippet: Stabilized RP transcripts are retained in the actively translating pool. a Equivalent amounts of the total RNA from cultures grown at 30 °C or shifted to 37 °C for 1 h were vacuum filtered through a slot blot apparatus onto the nylon membrane. A P32-labeled oligo-dT was used to assess mRNA by northern blot. Graphs show averaged polyA mRNA levels ± s.e.m. from three biological replicates. b Polysome traces show the translational state of each strain during no stress and following a shift to 37 °C for 1 h. Subunits, monosomes, and polysome are indicated. RNA was extracted from fractions collected during polysome profiling for wild-type and ccr4 Δ. Equivalent volumes of RNA from each fraction were run on a formaldehyde-agarose gel for northern blot analysis of RPL2 . The rRNA bands confirm that the fractions correspond to the area of the polysome profile above. The results shown are representative of three biological replicates. Source data are provided as a Source Data file

    Article Snippet: To remove rRNA, polyadenylated mRNA was isolated from 4 µg of the total RNA using NEBNext poly(A) mRNA Magnetic Isolation Module (New England Biolabs) as per the manufacturer’s protocol, and RNA-seq libraries were constructed using NEBNext mRNA Library Prep Master Mix Set for Illumina (New England Biolabs) according to the manufacturer’s protocol.

    Techniques: Dot Blot, Labeling, Northern Blot, Agarose Gel Electrophoresis

    Alternative pre-mRNA splicing of RPL7A mRNA is regulated by hnRNPA1 and DDX5. ( A ) Genome browser shot of the RPL7A gene region with RNA-seq data upon hnRNPA1 knockdown ( top ) and DDX5 knockdown ( bottom ), with corresponding nuclear CLIP peak cluster regions shown below . ( B ) icSHAPE-constrained in vivo and in vitro secondary structures for the RPL7A RNA. The nuclear eCLIP cluster/peak region is highlighted in green, the hnRNPA1 cross-link sites are marked with red asterisks, and the DDX5 cross-link sites are marked with blue plus signs. The dotted red rectangles indicate regions of the RNA with secondary structural changes between the in vivo and in vitro icSHAPE constraints. The enriched hnRNPA1 motifs are indicated by orange lines, and the enriched GC-rich motifs for DDX5 is indicated by dark-green lines.

    Journal: Genes & Development

    Article Title: Coordinate regulation of alternative pre-mRNA splicing events by the human RNA chaperone proteins hnRNPA1 and DDX5

    doi: 10.1101/gad.316034.118

    Figure Lengend Snippet: Alternative pre-mRNA splicing of RPL7A mRNA is regulated by hnRNPA1 and DDX5. ( A ) Genome browser shot of the RPL7A gene region with RNA-seq data upon hnRNPA1 knockdown ( top ) and DDX5 knockdown ( bottom ), with corresponding nuclear CLIP peak cluster regions shown below . ( B ) icSHAPE-constrained in vivo and in vitro secondary structures for the RPL7A RNA. The nuclear eCLIP cluster/peak region is highlighted in green, the hnRNPA1 cross-link sites are marked with red asterisks, and the DDX5 cross-link sites are marked with blue plus signs. The dotted red rectangles indicate regions of the RNA with secondary structural changes between the in vivo and in vitro icSHAPE constraints. The enriched hnRNPA1 motifs are indicated by orange lines, and the enriched GC-rich motifs for DDX5 is indicated by dark-green lines.

    Article Snippet: After RNA isolation using RNeasy minikit (Qiagen, 74104) followed by 30 min of DNase treatment (Ambion, AM2238) at 37°C, poly(A)+ RNA transcript was isolated [NEBNext poly(A) mRNA magnetic isolation module; New England Biolabs, E7490] from 1 µg of total RNA for RNA library preparation and sequencing using NEBNext Ultra directional RNA library preparation kit for Illumina (New England Biolabs, E7420S) according to the manufacturer's instruction.

    Techniques: RNA Sequencing Assay, Cross-linking Immunoprecipitation, In Vivo, In Vitro

    Quantitation of differential AS events controlled by hnRNPA1 from RNA-seq using JUM. ( A , left panel) siRNA-mediated knockdown of hnRNPA1 at the protein level. K562 cells were transfected with either nonspecific control siRNA oligos (scr si) or hnRNPA1 duplex siRNA oligos. After a second round of siRNA transfection, the cells were harvested for RNA isolation or protein lysates. ( Right panel) JUM is a splicing annotation-independent method for determining pre-mRNA splicing patterns from RNA-seq data. Only splice junction-spanning reads were taken into account for quantitation. This resulted in a quantitative comparison of AS events (1828) whose splicing patterns were significantly altered in the hnRNPA1 knockdown samples versus the control (false discovery rate [FDR], P

    Journal: Genes & Development

    Article Title: Coordinate regulation of alternative pre-mRNA splicing events by the human RNA chaperone proteins hnRNPA1 and DDX5

    doi: 10.1101/gad.316034.118

    Figure Lengend Snippet: Quantitation of differential AS events controlled by hnRNPA1 from RNA-seq using JUM. ( A , left panel) siRNA-mediated knockdown of hnRNPA1 at the protein level. K562 cells were transfected with either nonspecific control siRNA oligos (scr si) or hnRNPA1 duplex siRNA oligos. After a second round of siRNA transfection, the cells were harvested for RNA isolation or protein lysates. ( Right panel) JUM is a splicing annotation-independent method for determining pre-mRNA splicing patterns from RNA-seq data. Only splice junction-spanning reads were taken into account for quantitation. This resulted in a quantitative comparison of AS events (1828) whose splicing patterns were significantly altered in the hnRNPA1 knockdown samples versus the control (false discovery rate [FDR], P

    Article Snippet: After RNA isolation using RNeasy minikit (Qiagen, 74104) followed by 30 min of DNase treatment (Ambion, AM2238) at 37°C, poly(A)+ RNA transcript was isolated [NEBNext poly(A) mRNA magnetic isolation module; New England Biolabs, E7490] from 1 µg of total RNA for RNA library preparation and sequencing using NEBNext Ultra directional RNA library preparation kit for Illumina (New England Biolabs, E7420S) according to the manufacturer's instruction.

    Techniques: Quantitation Assay, RNA Sequencing Assay, Transfection, Isolation

    The RNA helicase DDX controls alternative pre-mRNA splicing of thousands of target RNAs. ( A , left panel) K562 cells were transfected with either nonspecific control siRNA oligos (scr si) or DDX5 duplex siRNA oligos. After a second round of siRNA transfection, the cells were harvested for RNA isolation or protein lysates. Protein lysates were immunoblotted with DDX5 antibody to detect the efficiency of siRNA-mediated knockdown at the protein level. ( Right panel) Detection of changes in AS events upon DDX5 knockdown in human K562 cells using JUM. JUM analysis revealed 3915 AS events whose splicing patterns were significantly altered in DDX5 RNAi knockdown samples versus the control scrambled siRNA samples, covering 2804 genes (FDR, P

    Journal: Genes & Development

    Article Title: Coordinate regulation of alternative pre-mRNA splicing events by the human RNA chaperone proteins hnRNPA1 and DDX5

    doi: 10.1101/gad.316034.118

    Figure Lengend Snippet: The RNA helicase DDX controls alternative pre-mRNA splicing of thousands of target RNAs. ( A , left panel) K562 cells were transfected with either nonspecific control siRNA oligos (scr si) or DDX5 duplex siRNA oligos. After a second round of siRNA transfection, the cells were harvested for RNA isolation or protein lysates. Protein lysates were immunoblotted with DDX5 antibody to detect the efficiency of siRNA-mediated knockdown at the protein level. ( Right panel) Detection of changes in AS events upon DDX5 knockdown in human K562 cells using JUM. JUM analysis revealed 3915 AS events whose splicing patterns were significantly altered in DDX5 RNAi knockdown samples versus the control scrambled siRNA samples, covering 2804 genes (FDR, P

    Article Snippet: After RNA isolation using RNeasy minikit (Qiagen, 74104) followed by 30 min of DNase treatment (Ambion, AM2238) at 37°C, poly(A)+ RNA transcript was isolated [NEBNext poly(A) mRNA magnetic isolation module; New England Biolabs, E7490] from 1 µg of total RNA for RNA library preparation and sequencing using NEBNext Ultra directional RNA library preparation kit for Illumina (New England Biolabs, E7420S) according to the manufacturer's instruction.

    Techniques: Transfection, Isolation

    This schematic illustrates the sample (auburn rectangle) and library (blue rectangle) preparation workflow to generate the libraries that were loaded on the Illumina sequencer. ( a ) For B. malayi and A. fumigatus , a poly(A)-selected sample was created from an aliquot of total RNA that was used to create a poly(A)-selected library. ( b ) The B. malayi or A. fumigatus AgSS baits were subsequently used to capture the targeted RNA from poly(A)-selected libraries. ( c ) For AgSS-enriched w Bm libraries, an RNA library was constructed from an aliquot of total RNA that underwent targeted enrichment with the Wolbachia AgSS baits. Unlike the eukaryotic enrichments, the bacterial AgSS capture is performed on total RNA. For a limited number of libraries described in the text, an RNA library was constructed from an aliquot of total RNA (i.e. without poly(A)-enrichment) that underwent targeted enrichment with the Brugia AgSS baits. ( d ) For poly(A)/rRNA-depleted libraries enriched for w Bm, an aliquot of total RNA from either mosquito thoraces or adult nematodes was enriched for bacterial mRNA by removing Gram-negative and human rRNAs with two RiboZero removal kits and polyadenylated RNAs with DynaBeads.

    Journal: Scientific Reports

    Article Title: Targeted enrichment outperforms other enrichment techniques and enables more multi-species RNA-Seq analyses

    doi: 10.1038/s41598-018-31420-7

    Figure Lengend Snippet: This schematic illustrates the sample (auburn rectangle) and library (blue rectangle) preparation workflow to generate the libraries that were loaded on the Illumina sequencer. ( a ) For B. malayi and A. fumigatus , a poly(A)-selected sample was created from an aliquot of total RNA that was used to create a poly(A)-selected library. ( b ) The B. malayi or A. fumigatus AgSS baits were subsequently used to capture the targeted RNA from poly(A)-selected libraries. ( c ) For AgSS-enriched w Bm libraries, an RNA library was constructed from an aliquot of total RNA that underwent targeted enrichment with the Wolbachia AgSS baits. Unlike the eukaryotic enrichments, the bacterial AgSS capture is performed on total RNA. For a limited number of libraries described in the text, an RNA library was constructed from an aliquot of total RNA (i.e. without poly(A)-enrichment) that underwent targeted enrichment with the Brugia AgSS baits. ( d ) For poly(A)/rRNA-depleted libraries enriched for w Bm, an aliquot of total RNA from either mosquito thoraces or adult nematodes was enriched for bacterial mRNA by removing Gram-negative and human rRNAs with two RiboZero removal kits and polyadenylated RNAs with DynaBeads.

    Article Snippet: When targeting eukaryotic mRNA, polyadenylated RNA was isolated using the NEBNext Poly(A) mRNA magnetic isolation module.

    Techniques: Construct