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Expression value distributions of different quantification methods for the same 258 samples. For each method, each gene's expression value was represented by the median value from the 258 samples. a) <t>Affymetrix</t> microarray analysis followed by RMA normalization method. b) Agilent microarray analysis followed by RMA normalization method. c) <t>RNAseq</t> analysis followed by the RPKM normalization method, the last bar represents genes with RPKM over 100. d) RNAseq analysis followed by the RSEM normalization method, the last bar represents genes with RSEM over 3000.
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1) Product Images from "Large Scale Comparison of Gene Expression Levels by Microarrays and RNAseq Using TCGA Data"

Article Title: Large Scale Comparison of Gene Expression Levels by Microarrays and RNAseq Using TCGA Data

Journal: PLoS ONE

doi: 10.1371/journal.pone.0071462

Expression value distributions of different quantification methods for the same 258 samples. For each method, each gene's expression value was represented by the median value from the 258 samples. a) Affymetrix microarray analysis followed by RMA normalization method. b) Agilent microarray analysis followed by RMA normalization method. c) RNAseq analysis followed by the RPKM normalization method, the last bar represents genes with RPKM over 100. d) RNAseq analysis followed by the RSEM normalization method, the last bar represents genes with RSEM over 3000.
Figure Legend Snippet: Expression value distributions of different quantification methods for the same 258 samples. For each method, each gene's expression value was represented by the median value from the 258 samples. a) Affymetrix microarray analysis followed by RMA normalization method. b) Agilent microarray analysis followed by RMA normalization method. c) RNAseq analysis followed by the RPKM normalization method, the last bar represents genes with RPKM over 100. d) RNAseq analysis followed by the RSEM normalization method, the last bar represents genes with RSEM over 3000.

Techniques Used: Expressing, Microarray

Spearman correlation coefficient analysis between different quantification methods. For each comparison, the samples from the tumor dataset that were analyzed by the corresponding methods were extracted. For each sample, the Spearman correlation coefficient of the expression values from those methods was calculated. a) The comparison between the RPKM method and the RSEM method. The Spearman correlation coefficients were as high as around 0.94. b) The comparison between the Affymetrix method and the RPKM/RSEM method. The Spearman correlation coefficients were around 0.8. c) The comparison between the Agilent method and the RPKM/RSEM method. Since the Agilent method generated a ratio value for each gene but the RNAseq methods generated an absolute expression value for each gene, the Spearman correlation coefficients between the Agilent method and the RNAseq methods were as low as ∼0.2. d) The comparison between the Agilent method and the Affymetrix method. Since the Affymetrix method also generated an absolute expression value for each gene, the Spearman correlations were also as low as ∼0.2.
Figure Legend Snippet: Spearman correlation coefficient analysis between different quantification methods. For each comparison, the samples from the tumor dataset that were analyzed by the corresponding methods were extracted. For each sample, the Spearman correlation coefficient of the expression values from those methods was calculated. a) The comparison between the RPKM method and the RSEM method. The Spearman correlation coefficients were as high as around 0.94. b) The comparison between the Affymetrix method and the RPKM/RSEM method. The Spearman correlation coefficients were around 0.8. c) The comparison between the Agilent method and the RPKM/RSEM method. Since the Agilent method generated a ratio value for each gene but the RNAseq methods generated an absolute expression value for each gene, the Spearman correlation coefficients between the Agilent method and the RNAseq methods were as low as ∼0.2. d) The comparison between the Agilent method and the Affymetrix method. Since the Affymetrix method also generated an absolute expression value for each gene, the Spearman correlations were also as low as ∼0.2.

Techniques Used: Expressing, Generated

Fold-change consistency between the Agilent method and the RPKM method from 53 paired tumor-normal breast cancer samples. The common genes were divided into four groups based on their RNAseq expression value, and linear regression was performed to evaluate the fold-change consistency for each group. This indicates that the fold-change derived from genes with higher RNAseq expression was more concordant with the fold-change derived from microarray expression than the fold-change derived from genes with lower RNAseq expression.
Figure Legend Snippet: Fold-change consistency between the Agilent method and the RPKM method from 53 paired tumor-normal breast cancer samples. The common genes were divided into four groups based on their RNAseq expression value, and linear regression was performed to evaluate the fold-change consistency for each group. This indicates that the fold-change derived from genes with higher RNAseq expression was more concordant with the fold-change derived from microarray expression than the fold-change derived from genes with lower RNAseq expression.

Techniques Used: Expressing, Derivative Assay, Microarray

Differentially expressed gene concordance analysis using 53 paired tumor-normal breast cancer samples. a) The Spearman correlation coefficients of tumor/normal ratios between the Agilent method, the RPKM method and the RSEM method. b) Venn diagram summarizing the overlap between genes called as significantly differentially expressed (adjusted FDR less than 0.01 and fold-change larger than 2). The differentially expressed genes in Figure 3b were computed using commonly measured genes between microarray and RNAseq. c) Scatter plot of fold-change per gene as measured by the Agilent method and the RNAseq RPKM method. Genes identified as differentially expressed with consistent fold-change direction by both methods are plotted in green. Genes identified as differentially expressed with inconsistent fold change direction by both methods are plotted in red. Genes identified as differentially expressed by either RNAseq method or Agilent method are plotted in blue and yellow, respectively. Genes not identified as differentially expressed by either method are plotted in black. Only 1.2% genes identified as differentially expressed genes by both methods were inconsistent on the fold-change direction (red data).
Figure Legend Snippet: Differentially expressed gene concordance analysis using 53 paired tumor-normal breast cancer samples. a) The Spearman correlation coefficients of tumor/normal ratios between the Agilent method, the RPKM method and the RSEM method. b) Venn diagram summarizing the overlap between genes called as significantly differentially expressed (adjusted FDR less than 0.01 and fold-change larger than 2). The differentially expressed genes in Figure 3b were computed using commonly measured genes between microarray and RNAseq. c) Scatter plot of fold-change per gene as measured by the Agilent method and the RNAseq RPKM method. Genes identified as differentially expressed with consistent fold-change direction by both methods are plotted in green. Genes identified as differentially expressed with inconsistent fold change direction by both methods are plotted in red. Genes identified as differentially expressed by either RNAseq method or Agilent method are plotted in blue and yellow, respectively. Genes not identified as differentially expressed by either method are plotted in black. Only 1.2% genes identified as differentially expressed genes by both methods were inconsistent on the fold-change direction (red data).

Techniques Used: Microarray

2) Product Images from "Analyses of Allele-Specific Gene Expression in Highly Divergent Mouse Crosses Identifies Pervasive Allelic Imbalance"

Article Title: Analyses of Allele-Specific Gene Expression in Highly Divergent Mouse Crosses Identifies Pervasive Allelic Imbalance

Journal: Nature genetics

doi: 10.1038/ng.3222

Diallel crossing scheme and sample sizes. We selected three divergent inbred strains representative of three subspecies within the Mus musculus species group. We generated offspring from all possible pairwise crosses to form a 3×3 diallel, including age- and sex-matched biological replicates for each of the nine possible genotypic combinations. Mice were aged to 23 days, sacrificed, and total RNA extracted from whole brain, liver, kidney, and lung. Sample size shown is for RNAseq (52 female, 39 male). RNAseq was performed on RNA extracted from brain and microarrays were run on RNA extracted from brain, liver, kidney, and lung.
Figure Legend Snippet: Diallel crossing scheme and sample sizes. We selected three divergent inbred strains representative of three subspecies within the Mus musculus species group. We generated offspring from all possible pairwise crosses to form a 3×3 diallel, including age- and sex-matched biological replicates for each of the nine possible genotypic combinations. Mice were aged to 23 days, sacrificed, and total RNA extracted from whole brain, liver, kidney, and lung. Sample size shown is for RNAseq (52 female, 39 male). RNAseq was performed on RNA extracted from brain and microarrays were run on RNA extracted from brain, liver, kidney, and lung.

Techniques Used: Generated, Mouse Assay

3) Product Images from "RNAseq reveals hypervirulence-specific host responses to M. tuberculosis infection"

Article Title: RNAseq reveals hypervirulence-specific host responses to M. tuberculosis infection

Journal: Virulence

doi: 10.1080/21505594.2016.1250994

qPCR based validation and corresponding secreted proteins of differentially expressed cytokines and chemokines in BMDM after M.tb infection. A. Relative mRNA expression (fold change) of various cytokines and chemokines induced by BMDMs following infection with hypo- and hypervirulent M.tb as analyzed through qPCR (n = 3). B. Corresponding heatmap as generated by RNAseq under the same infection conditions (Red-Upregulation, Green-downregulation). C and D. Corresponding secreted cytokines and chemokines in BMDMs under the same infection conditions as measured by ELISA (n = 6). The means and standard error of a minimum of 3 independent experiments are shown, * indicates significance p
Figure Legend Snippet: qPCR based validation and corresponding secreted proteins of differentially expressed cytokines and chemokines in BMDM after M.tb infection. A. Relative mRNA expression (fold change) of various cytokines and chemokines induced by BMDMs following infection with hypo- and hypervirulent M.tb as analyzed through qPCR (n = 3). B. Corresponding heatmap as generated by RNAseq under the same infection conditions (Red-Upregulation, Green-downregulation). C and D. Corresponding secreted cytokines and chemokines in BMDMs under the same infection conditions as measured by ELISA (n = 6). The means and standard error of a minimum of 3 independent experiments are shown, * indicates significance p

Techniques Used: Real-time Polymerase Chain Reaction, Infection, Expressing, Generated, Enzyme-linked Immunosorbent Assay

Virulence-specific gene expression confirmed through qPCR and Western blot in BMDM and THP-1 macrophages infected with hypo- and hypervirulent M.tb . A. Relative mRNA expression (fold change) of selected differentially expressed genes induced by BMDMs following infection with hypervirulent M.tb after 12 h of infection as analyzed through qPCR (n = 4). B. Corresponding heatmap as generated by RNAseq under the same infection conditions in BMDMs (Red-Upregulation, Green-downregulation), Rep = Replicate. C. Relative mRNA expression (fold change) of the same virulence-specific genes induced by THP-1s following infection with hypervirulent M.tb after 12 h of infection as analyzed through qPCR (n = 4). D. Western blot of corresponding proteins expressed by BMDMs and THP-1s under the same infection conditions, GAPDH was used as a loading control (n = 4), Uninf. = Uninfected BMDM and THP-1, Hypov.= Hypovirulent infection, Hyperv. = Hypervirulent infection. *p
Figure Legend Snippet: Virulence-specific gene expression confirmed through qPCR and Western blot in BMDM and THP-1 macrophages infected with hypo- and hypervirulent M.tb . A. Relative mRNA expression (fold change) of selected differentially expressed genes induced by BMDMs following infection with hypervirulent M.tb after 12 h of infection as analyzed through qPCR (n = 4). B. Corresponding heatmap as generated by RNAseq under the same infection conditions in BMDMs (Red-Upregulation, Green-downregulation), Rep = Replicate. C. Relative mRNA expression (fold change) of the same virulence-specific genes induced by THP-1s following infection with hypervirulent M.tb after 12 h of infection as analyzed through qPCR (n = 4). D. Western blot of corresponding proteins expressed by BMDMs and THP-1s under the same infection conditions, GAPDH was used as a loading control (n = 4), Uninf. = Uninfected BMDM and THP-1, Hypov.= Hypovirulent infection, Hyperv. = Hypervirulent infection. *p

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

4) Product Images from "Activation and repression by oncogenic Myc shape tumour-specific gene expression profiles"

Article Title: Activation and repression by oncogenic Myc shape tumour-specific gene expression profiles

Journal: Nature

doi: 10.1038/nature13473

Binding of Myc to chromatin and Myc-dependent changes in gene expression in U2OS cells. a. Distribution of Myc tags around the TSS of all human Pol II genes with and without induction of exogenous MYC . b. Example of Myc-binding to a promoter and an intragenic enhancer. Enhancers are identified by the presence of H3K4me1 and H3K27Ac and the absence of H3K4me3. Exons are indicated as vertical bars, the UTR shown as a thick black line. c. Heat map documenting binding of Myc to all enhancers identified in U2OS cells. Enhancer positions are centered according to Myc occupancy within a window of +/-1 kb of the centre of the enhancer region and are sorted according to the number of H3K4me1 tags. d. The diagram shows the Myc-induced change in expression (plotted as log 2 FC) versus total expression levels for all genes found in the RNAseq as determined by RNA-sequencing. Red colour indicates significantly regulated genes (q
Figure Legend Snippet: Binding of Myc to chromatin and Myc-dependent changes in gene expression in U2OS cells. a. Distribution of Myc tags around the TSS of all human Pol II genes with and without induction of exogenous MYC . b. Example of Myc-binding to a promoter and an intragenic enhancer. Enhancers are identified by the presence of H3K4me1 and H3K27Ac and the absence of H3K4me3. Exons are indicated as vertical bars, the UTR shown as a thick black line. c. Heat map documenting binding of Myc to all enhancers identified in U2OS cells. Enhancer positions are centered according to Myc occupancy within a window of +/-1 kb of the centre of the enhancer region and are sorted according to the number of H3K4me1 tags. d. The diagram shows the Myc-induced change in expression (plotted as log 2 FC) versus total expression levels for all genes found in the RNAseq as determined by RNA-sequencing. Red colour indicates significantly regulated genes (q

Techniques Used: Binding Assay, Expressing, RNA Sequencing Assay

5) Product Images from "Evidence for Direct Control of Virulence and Defense Gene Circuits by the Pseudomonas aeruginosa Quorum Sensing Regulator, MvfR"

Article Title: Evidence for Direct Control of Virulence and Defense Gene Circuits by the Pseudomonas aeruginosa Quorum Sensing Regulator, MvfR

Journal: Scientific Reports

doi: 10.1038/srep34083

MvfR generates a positive feedback loop by binding to and inducing the small RNA PhrS. ( a ) ChIPseq analysis reveals that MvfR binds to phrS region. The black bar above the binding intensity plots represents the peak identified using SPP peak caller. ( b ) RNAseq analysis indicates that MvfR induces the expression of phrS . Light blue bar = mvfR mutant at OD 600nm 2, dark blue bar = mvfR mutant at OD 600nm 3. ( c ) qRTPCR analysis validates that MvfR induces the expression of phrS . Faint blue bar = mvfR mutant at OD 600nm 1, light blue bar = mvfR mutant at OD 600nm 2. Data show the average +/− SEM of 3 independent replicates. Statistical significance was assessed using one way ANOVA + Dunnett’s post-test.
Figure Legend Snippet: MvfR generates a positive feedback loop by binding to and inducing the small RNA PhrS. ( a ) ChIPseq analysis reveals that MvfR binds to phrS region. The black bar above the binding intensity plots represents the peak identified using SPP peak caller. ( b ) RNAseq analysis indicates that MvfR induces the expression of phrS . Light blue bar = mvfR mutant at OD 600nm 2, dark blue bar = mvfR mutant at OD 600nm 3. ( c ) qRTPCR analysis validates that MvfR induces the expression of phrS . Faint blue bar = mvfR mutant at OD 600nm 1, light blue bar = mvfR mutant at OD 600nm 2. Data show the average +/− SEM of 3 independent replicates. Statistical significance was assessed using one way ANOVA + Dunnett’s post-test.

Techniques Used: Binding Assay, Expressing, Mutagenesis

6) Product Images from "Simian varicella virus causes robust transcriptional changes in T cells that support viral replication"

Article Title: Simian varicella virus causes robust transcriptional changes in T cells that support viral replication

Journal: Virus Research

doi: 10.1016/j.virusres.2017.07.004

SVV infection results in robust gene expression changes in T cells . (A) PCA plot of T cell samples subjected to RNASeq. Each dot represents a CD4 or CD8 T cell sample used for RNA-Seq analysis and each color represents a timepoint. (B) Volcano plot representing overall gene expression changes observed in infected T cells. Each gene is denoted by a dot with red dots representing genes with significant difference in expression in infected compared to naive T cells (FDR p -value
Figure Legend Snippet: SVV infection results in robust gene expression changes in T cells . (A) PCA plot of T cell samples subjected to RNASeq. Each dot represents a CD4 or CD8 T cell sample used for RNA-Seq analysis and each color represents a timepoint. (B) Volcano plot representing overall gene expression changes observed in infected T cells. Each gene is denoted by a dot with red dots representing genes with significant difference in expression in infected compared to naive T cells (FDR p -value

Techniques Used: Infection, Expressing, RNA Sequencing Assay

7) Product Images from "The extraembryonic serosa is a frontier epithelium providing the insect egg with a full-range innate immune response"

Article Title: The extraembryonic serosa is a frontier epithelium providing the insect egg with a full-range innate immune response

Journal: eLife

doi: 10.7554/eLife.04111

Experimental setup. ( A ) We collected eggs from wild-type, control RNAi, and Tc-zen1 RNAi beetles overnight. These eggs were incubated for 24 hr at 30°C to ensure development of the serosa. Eggs are then maximally 40 hr old, while total developmental time is close to 85 hr at 30°C. Eggs were pricked with a sterile needle (sterile injury), pricked with a mix of E. coli and M. luteus (septic injury), or remained untreated (naive). They were incubated for another 6 hr at 30°C before total RNA was extracted for RNAseq. To analyze the immune response, the transcriptomes of sterilely injured eggs and of septically injured eggs were compared to naive eggs. This was done for wild-type, control, and Tc-zen1 RNAi eggs. ( B ) We collected three biological samples for each combination of egg-type (wild-type, control RNAi, or Tc-zen1 RNAi) and treatment (naive, sterile injury, or septic injury) giving a total of 27 biological samples. DOI: http://dx.doi.org/10.7554/eLife.04111.004
Figure Legend Snippet: Experimental setup. ( A ) We collected eggs from wild-type, control RNAi, and Tc-zen1 RNAi beetles overnight. These eggs were incubated for 24 hr at 30°C to ensure development of the serosa. Eggs are then maximally 40 hr old, while total developmental time is close to 85 hr at 30°C. Eggs were pricked with a sterile needle (sterile injury), pricked with a mix of E. coli and M. luteus (septic injury), or remained untreated (naive). They were incubated for another 6 hr at 30°C before total RNA was extracted for RNAseq. To analyze the immune response, the transcriptomes of sterilely injured eggs and of septically injured eggs were compared to naive eggs. This was done for wild-type, control, and Tc-zen1 RNAi eggs. ( B ) We collected three biological samples for each combination of egg-type (wild-type, control RNAi, or Tc-zen1 RNAi) and treatment (naive, sterile injury, or septic injury) giving a total of 27 biological samples. DOI: http://dx.doi.org/10.7554/eLife.04111.004

Techniques Used: Incubation

RT-qPCR verification of immune gene expression. The expression levels of several immune genes was verified by RT-qPCR. Expression shown relative to the expression in naive eggs, the mean fold change of the biological replicates (based on two technical replicates) is plotted and error bars show the standard error. Black bars represent expression after sterile injury, white bars represent expression after septic injury. Expression levels measured by RT-qPCR show very similar results as the expression levels measured by RNAseq (See Supplementary file 2 ). ( A ) PGRP-LC , ( B ) SPH-H57 , ( C ) SPH-H70 , ( D ) cSP-P8 , ( E ) serpin24 , ( F ) serpin26 , ( G ) toll3 , ( H ) TC004646 , ( I ) TC007763 , ( J ) TC007858 , ( K ) TC008806 , ( L ) TC015479 . See ‘Materials and methods’ for experimental details. DOI: http://dx.doi.org/10.7554/eLife.04111.009
Figure Legend Snippet: RT-qPCR verification of immune gene expression. The expression levels of several immune genes was verified by RT-qPCR. Expression shown relative to the expression in naive eggs, the mean fold change of the biological replicates (based on two technical replicates) is plotted and error bars show the standard error. Black bars represent expression after sterile injury, white bars represent expression after septic injury. Expression levels measured by RT-qPCR show very similar results as the expression levels measured by RNAseq (See Supplementary file 2 ). ( A ) PGRP-LC , ( B ) SPH-H57 , ( C ) SPH-H70 , ( D ) cSP-P8 , ( E ) serpin24 , ( F ) serpin26 , ( G ) toll3 , ( H ) TC004646 , ( I ) TC007763 , ( J ) TC007858 , ( K ) TC008806 , ( L ) TC015479 . See ‘Materials and methods’ for experimental details. DOI: http://dx.doi.org/10.7554/eLife.04111.009

Techniques Used: Quantitative RT-PCR, Expressing

8) Product Images from "Loss of RNA expression and allele-specific expression associated with congenital heart disease"

Article Title: Loss of RNA expression and allele-specific expression associated with congenital heart disease

Journal: Nature Communications

doi: 10.1038/ncomms12824

Identification of extreme ASE genes in subjects with CHD. Shown are both alleles of a gene that differ by the SNP haploblocks ‘CC' (blue) and ‘GT' (red), as identified by WES, WGS or SNP-array genotyping. RNAseq analysis (read counts at heterozygous positions) reveals the expression of both alleles (biallelic RNA expression) or the disproportionate expression of one allele over another (ASE). RNAseq expression analyses (comparing each sample to the average of all other samples within a tissue group) identify relative loss and gain of expression. Variant analysis, in conjunction with RNAseq analysis, can further identify LOF mutations in the expressed allele (*).
Figure Legend Snippet: Identification of extreme ASE genes in subjects with CHD. Shown are both alleles of a gene that differ by the SNP haploblocks ‘CC' (blue) and ‘GT' (red), as identified by WES, WGS or SNP-array genotyping. RNAseq analysis (read counts at heterozygous positions) reveals the expression of both alleles (biallelic RNA expression) or the disproportionate expression of one allele over another (ASE). RNAseq expression analyses (comparing each sample to the average of all other samples within a tissue group) identify relative loss and gain of expression. Variant analysis, in conjunction with RNAseq analysis, can further identify LOF mutations in the expressed allele (*).

Techniques Used: Expressing, RNA Expression, Variant Assay

9) Product Images from "A conserved fungal glycosyltransferase facilitates pathogenesis of plants by enabling hyphal growth on solid surfaces"

Article Title: A conserved fungal glycosyltransferase facilitates pathogenesis of plants by enabling hyphal growth on solid surfaces

Journal: PLoS Pathogens

doi: 10.1371/journal.ppat.1006672

All mutant phenotypes of 23–170 result from inactivation of a gene encoding a putative type 2 glycosyltransferase (ZtGT2). (A) The gene model structure identified through TAIL-PCR analysis of the T-DNA insertion site in mutant 23–170. (B) RNAseq raw read mapping confirmed the predicted gene structure and highlights the position of the left border T-DNA insertion. (C) Functional annotation of the tagged gene highlighting the position of the T-DNA left border relative to the predicted type 2 glycosyltransferase catalytic domain. (D) The predicted amino acid sequence of ZtGT2 highlighting the protein region truncated by T-DNA insertion in brown font. The underlined region indicates the peptide sequence chosen for antibody generation (E) Complementation of the 23–170 mutant strain with the wild-type ZtGT2 gene (23–170::GT2comp) restores hyphal growth on solid surfaces and virulence on plants. Independent targeted deletion of ZtGT2 in the wild-type fungus (ΔZtGT2-19) results in the same aberrant hyphal growth and loss of virulence phenotypes shown for 23–170.
Figure Legend Snippet: All mutant phenotypes of 23–170 result from inactivation of a gene encoding a putative type 2 glycosyltransferase (ZtGT2). (A) The gene model structure identified through TAIL-PCR analysis of the T-DNA insertion site in mutant 23–170. (B) RNAseq raw read mapping confirmed the predicted gene structure and highlights the position of the left border T-DNA insertion. (C) Functional annotation of the tagged gene highlighting the position of the T-DNA left border relative to the predicted type 2 glycosyltransferase catalytic domain. (D) The predicted amino acid sequence of ZtGT2 highlighting the protein region truncated by T-DNA insertion in brown font. The underlined region indicates the peptide sequence chosen for antibody generation (E) Complementation of the 23–170 mutant strain with the wild-type ZtGT2 gene (23–170::GT2comp) restores hyphal growth on solid surfaces and virulence on plants. Independent targeted deletion of ZtGT2 in the wild-type fungus (ΔZtGT2-19) results in the same aberrant hyphal growth and loss of virulence phenotypes shown for 23–170.

Techniques Used: Mutagenesis, Polymerase Chain Reaction, Functional Assay, Sequencing

10) Product Images from "Leucine Biosynthesis Is Involved in Regulating High Lipid Accumulation in Yarrowia lipolytica"

Article Title: Leucine Biosynthesis Is Involved in Regulating High Lipid Accumulation in Yarrowia lipolytica

Journal: mBio

doi: 10.1128/mBio.00857-17

Correlation of log-normalized RNAseq read counts with log-normalized protein counts. (A) All measured RNA and protein counts combined in one comparison, with poor correlation observed. (B) Density plot of Pearson’s r for all RNA-protein pairs (dotted line) and for only those RNA-protein pairs that showed differential expression at the level of RNA (adjusted P
Figure Legend Snippet: Correlation of log-normalized RNAseq read counts with log-normalized protein counts. (A) All measured RNA and protein counts combined in one comparison, with poor correlation observed. (B) Density plot of Pearson’s r for all RNA-protein pairs (dotted line) and for only those RNA-protein pairs that showed differential expression at the level of RNA (adjusted P

Techniques Used: Expressing

11) Product Images from "A novel microRNA-based strategy to expand the differentiation potency of stem cells"

Article Title: A novel microRNA-based strategy to expand the differentiation potency of stem cells

Journal: bioRxiv

doi: 10.1101/826446

DNA methyltransferases 3a and 3b are miR-203 targets involved in the regulation of PSCs potential. ( A ) Venn Diagrams representing common genes down-regulated in mi iPSCs, predicted as miR-203 targets and also involved in the epigenetic regulation of gene transcription (GO:0040029). The list of the common 18 transcripts (including Dnmt3a and Dnmt3b ) is presented as Supplementary Table 3. ( B,C ) Relative Luciferase Units (RLU; normalized to Renilla luciferase and relative to DNA amount) in 293T cells transfected with DNA constructs carrying the wild-type 3’UTRs from the indicated transcripts ( B ) or the mutated versions of Dnmt3a and Dnmt3b 3’UTRs, downstream of the luciferase reporter ( C ). Cells were co-transfected with Renilla luciferase as a control of transfection, and a plasmid expressing GFP or miR-203-GFP. Data are represented as mean ± s.d. (n=3 independent experiments). ( D ) Principal Component Analysis from RNAseq data including profiles from wild-type iPSCs, mi iPSCs, and wild-type iPSCs transfected with either control siRNAs (siC), or siRNAs specific against Dnmt3a ( siDnmt3a ), Dnmt3b ( siDnmt3b ) or both ( siDnmt3a /b). ( E ) Representative images of embryoid bodies (EBs) derived from wild-type iPSCs in which the expression of Dnmt3a and Dnmt3b was transiently repressed by siRNAs. Scale bars, 500 μm. Plots show the quantification of the size of EBs and the percentage of EBs with large cavities or beating at different time points during the differentiation process. ( F ) Expression levels of Dnmt3a or Dnmt3b transcripts after transfection of wild-type iPSCs with specific siRNAs either against Dnmt3a , Dnmt3b or a combination of both ( Dnmt3a /b). RNA expression was measured 24 hours after the transfection protocols and was normalized by GAPDH mRNA levels (n=3 independent experiments). ( G ) Representative images of EBs derived from mi iPSCs that were transiently and simultaneously transduced with Dnmt3a and Dnmt3b cDNAs or empty vectors, and simultaneously treated with Dox to induce miR-203 expression. Scale bars, 500 μm. Plots show the quantification of EB size, percentage of EBs with large cavities, and beating EBs at different time points during differentiation. ( H ) RNA expression was measured 24 hours after the transfection protocols and was normalized by a control miRNA (miR-142) or GAPDH mRNA, respectively. In ( B, C, E-H ) * P
Figure Legend Snippet: DNA methyltransferases 3a and 3b are miR-203 targets involved in the regulation of PSCs potential. ( A ) Venn Diagrams representing common genes down-regulated in mi iPSCs, predicted as miR-203 targets and also involved in the epigenetic regulation of gene transcription (GO:0040029). The list of the common 18 transcripts (including Dnmt3a and Dnmt3b ) is presented as Supplementary Table 3. ( B,C ) Relative Luciferase Units (RLU; normalized to Renilla luciferase and relative to DNA amount) in 293T cells transfected with DNA constructs carrying the wild-type 3’UTRs from the indicated transcripts ( B ) or the mutated versions of Dnmt3a and Dnmt3b 3’UTRs, downstream of the luciferase reporter ( C ). Cells were co-transfected with Renilla luciferase as a control of transfection, and a plasmid expressing GFP or miR-203-GFP. Data are represented as mean ± s.d. (n=3 independent experiments). ( D ) Principal Component Analysis from RNAseq data including profiles from wild-type iPSCs, mi iPSCs, and wild-type iPSCs transfected with either control siRNAs (siC), or siRNAs specific against Dnmt3a ( siDnmt3a ), Dnmt3b ( siDnmt3b ) or both ( siDnmt3a /b). ( E ) Representative images of embryoid bodies (EBs) derived from wild-type iPSCs in which the expression of Dnmt3a and Dnmt3b was transiently repressed by siRNAs. Scale bars, 500 μm. Plots show the quantification of the size of EBs and the percentage of EBs with large cavities or beating at different time points during the differentiation process. ( F ) Expression levels of Dnmt3a or Dnmt3b transcripts after transfection of wild-type iPSCs with specific siRNAs either against Dnmt3a , Dnmt3b or a combination of both ( Dnmt3a /b). RNA expression was measured 24 hours after the transfection protocols and was normalized by GAPDH mRNA levels (n=3 independent experiments). ( G ) Representative images of EBs derived from mi iPSCs that were transiently and simultaneously transduced with Dnmt3a and Dnmt3b cDNAs or empty vectors, and simultaneously treated with Dox to induce miR-203 expression. Scale bars, 500 μm. Plots show the quantification of EB size, percentage of EBs with large cavities, and beating EBs at different time points during differentiation. ( H ) RNA expression was measured 24 hours after the transfection protocols and was normalized by a control miRNA (miR-142) or GAPDH mRNA, respectively. In ( B, C, E-H ) * P

Techniques Used: Luciferase, Transfection, Construct, Plasmid Preparation, Expressing, Derivative Assay, RNA Expression, Transduction

Effects of transient induction of miR-203 in iPSC and ESC pluripotency and differentiation potential. ( A ) miR-203 expression, as determined by qPCR, in five temporal different stages of normal early development: oocyte, 2-cell embryo, morula, compacted morula and blastocyst. RNA was extracted from 30 different embryos and pooled in two independent groups for analysis by qPCR. RNA expression is normalized by a housekeeping miRNA (miR-16) that maintained invariable during early embryogenesis. Data represent 6 different qPCR measures. P =0.05 (Student’s t-test) comparing 2C/morula versus compacted morula/blastocyst. ( B ) Protocol for reprogramming of miR-203 mutant MEFs into pluripotent iPSCs and subsequent differentiation into embryoid bodies. MEFs were transduced with lentiviruses expressing Oct4, Sox2, Klf4, and cMyc (OSKM) in a constitutive manner. The resulting iPSCs were then treated with doxycycline (Dox) 1 μg/ml during 5 days to induce miR-203 expression. “ mi iPSCs” refers to iPSCs in which miR-203 was transiently expressed during the indicated 5 days. Dox was removed for 15-30 days before starting the embryoid body generation protocol. Samples for RNA sequencing were taken 30 days after Dox withdrawal. ( C ) Principal Component Analysis of RNAseq data from wild-type iPSCs (n=3 clones), mi iPSCs (n=4) and wild-type ESCs (n=3). ( D ) Enrichment plots of the 282-gene 2-cell signature 16 in mi iPSCs 10 and 25 days after Dox withdrawal. ( E ) Representative images of embryoid bodies (EBs) derived from wild-type iPSCs or ESCs, or from mi iPSC and mi ESCs at day 30 of differentiation. Scale bars, 500 μm. ( F ) Quantification of the percentage of EBs from panel ( E) presenting internal large cavities and EBs beating during the indicated time course. Data are represented as mean ± s.e.m. (n=3 independent experiments). * P
Figure Legend Snippet: Effects of transient induction of miR-203 in iPSC and ESC pluripotency and differentiation potential. ( A ) miR-203 expression, as determined by qPCR, in five temporal different stages of normal early development: oocyte, 2-cell embryo, morula, compacted morula and blastocyst. RNA was extracted from 30 different embryos and pooled in two independent groups for analysis by qPCR. RNA expression is normalized by a housekeeping miRNA (miR-16) that maintained invariable during early embryogenesis. Data represent 6 different qPCR measures. P =0.05 (Student’s t-test) comparing 2C/morula versus compacted morula/blastocyst. ( B ) Protocol for reprogramming of miR-203 mutant MEFs into pluripotent iPSCs and subsequent differentiation into embryoid bodies. MEFs were transduced with lentiviruses expressing Oct4, Sox2, Klf4, and cMyc (OSKM) in a constitutive manner. The resulting iPSCs were then treated with doxycycline (Dox) 1 μg/ml during 5 days to induce miR-203 expression. “ mi iPSCs” refers to iPSCs in which miR-203 was transiently expressed during the indicated 5 days. Dox was removed for 15-30 days before starting the embryoid body generation protocol. Samples for RNA sequencing were taken 30 days after Dox withdrawal. ( C ) Principal Component Analysis of RNAseq data from wild-type iPSCs (n=3 clones), mi iPSCs (n=4) and wild-type ESCs (n=3). ( D ) Enrichment plots of the 282-gene 2-cell signature 16 in mi iPSCs 10 and 25 days after Dox withdrawal. ( E ) Representative images of embryoid bodies (EBs) derived from wild-type iPSCs or ESCs, or from mi iPSC and mi ESCs at day 30 of differentiation. Scale bars, 500 μm. ( F ) Quantification of the percentage of EBs from panel ( E) presenting internal large cavities and EBs beating during the indicated time course. Data are represented as mean ± s.e.m. (n=3 independent experiments). * P

Techniques Used: Expressing, Real-time Polymerase Chain Reaction, RNA Expression, Mutagenesis, Transduction, RNA Sequencing Assay, Derivative Assay

12) Product Images from "Activation and repression by oncogenic Myc shape tumour-specific gene expression profiles"

Article Title: Activation and repression by oncogenic Myc shape tumour-specific gene expression profiles

Journal: Nature

doi: 10.1038/nature13473

Binding of Myc to chromatin and Myc-dependent changes in gene expression in U2OS cells. a. Distribution of Myc tags around the TSS of all human Pol II genes with and without induction of exogenous MYC . b. Example of Myc-binding to a promoter and an intragenic enhancer. Enhancers are identified by the presence of H3K4me1 and H3K27Ac and the absence of H3K4me3. Exons are indicated as vertical bars, the UTR shown as a thick black line. c. Heat map documenting binding of Myc to all enhancers identified in U2OS cells. Enhancer positions are centered according to Myc occupancy within a window of +/-1 kb of the centre of the enhancer region and are sorted according to the number of H3K4me1 tags. d. The diagram shows the Myc-induced change in expression (plotted as log 2 FC) versus total expression levels for all genes found in the RNAseq as determined by RNA-sequencing. Red colour indicates significantly regulated genes (q
Figure Legend Snippet: Binding of Myc to chromatin and Myc-dependent changes in gene expression in U2OS cells. a. Distribution of Myc tags around the TSS of all human Pol II genes with and without induction of exogenous MYC . b. Example of Myc-binding to a promoter and an intragenic enhancer. Enhancers are identified by the presence of H3K4me1 and H3K27Ac and the absence of H3K4me3. Exons are indicated as vertical bars, the UTR shown as a thick black line. c. Heat map documenting binding of Myc to all enhancers identified in U2OS cells. Enhancer positions are centered according to Myc occupancy within a window of +/-1 kb of the centre of the enhancer region and are sorted according to the number of H3K4me1 tags. d. The diagram shows the Myc-induced change in expression (plotted as log 2 FC) versus total expression levels for all genes found in the RNAseq as determined by RNA-sequencing. Red colour indicates significantly regulated genes (q

Techniques Used: Binding Assay, Expressing, RNA Sequencing Assay

13) Product Images from "Large Scale Comparison of Gene Expression Levels by Microarrays and RNAseq Using TCGA Data"

Article Title: Large Scale Comparison of Gene Expression Levels by Microarrays and RNAseq Using TCGA Data

Journal: PLoS ONE

doi: 10.1371/journal.pone.0071462

Expression value distributions of different quantification methods for the same 258 samples. For each method, each gene's expression value was represented by the median value from the 258 samples. a) Affymetrix microarray analysis followed by RMA normalization method. b) Agilent microarray analysis followed by RMA normalization method. c) RNAseq analysis followed by the RPKM normalization method, the last bar represents genes with RPKM over 100. d) RNAseq analysis followed by the RSEM normalization method, the last bar represents genes with RSEM over 3000.
Figure Legend Snippet: Expression value distributions of different quantification methods for the same 258 samples. For each method, each gene's expression value was represented by the median value from the 258 samples. a) Affymetrix microarray analysis followed by RMA normalization method. b) Agilent microarray analysis followed by RMA normalization method. c) RNAseq analysis followed by the RPKM normalization method, the last bar represents genes with RPKM over 100. d) RNAseq analysis followed by the RSEM normalization method, the last bar represents genes with RSEM over 3000.

Techniques Used: Expressing, Microarray

Spearman correlation coefficient analysis between different quantification methods. For each comparison, the samples from the tumor dataset that were analyzed by the corresponding methods were extracted. For each sample, the Spearman correlation coefficient of the expression values from those methods was calculated. a) The comparison between the RPKM method and the RSEM method. The Spearman correlation coefficients were as high as around 0.94. b) The comparison between the Affymetrix method and the RPKM/RSEM method. The Spearman correlation coefficients were around 0.8. c) The comparison between the Agilent method and the RPKM/RSEM method. Since the Agilent method generated a ratio value for each gene but the RNAseq methods generated an absolute expression value for each gene, the Spearman correlation coefficients between the Agilent method and the RNAseq methods were as low as ∼0.2. d) The comparison between the Agilent method and the Affymetrix method. Since the Affymetrix method also generated an absolute expression value for each gene, the Spearman correlations were also as low as ∼0.2.
Figure Legend Snippet: Spearman correlation coefficient analysis between different quantification methods. For each comparison, the samples from the tumor dataset that were analyzed by the corresponding methods were extracted. For each sample, the Spearman correlation coefficient of the expression values from those methods was calculated. a) The comparison between the RPKM method and the RSEM method. The Spearman correlation coefficients were as high as around 0.94. b) The comparison between the Affymetrix method and the RPKM/RSEM method. The Spearman correlation coefficients were around 0.8. c) The comparison between the Agilent method and the RPKM/RSEM method. Since the Agilent method generated a ratio value for each gene but the RNAseq methods generated an absolute expression value for each gene, the Spearman correlation coefficients between the Agilent method and the RNAseq methods were as low as ∼0.2. d) The comparison between the Agilent method and the Affymetrix method. Since the Affymetrix method also generated an absolute expression value for each gene, the Spearman correlations were also as low as ∼0.2.

Techniques Used: Expressing, Generated

Fold-change consistency between the Agilent method and the RPKM method from 53 paired tumor-normal breast cancer samples. The common genes were divided into four groups based on their RNAseq expression value, and linear regression was performed to evaluate the fold-change consistency for each group. This indicates that the fold-change derived from genes with higher RNAseq expression was more concordant with the fold-change derived from microarray expression than the fold-change derived from genes with lower RNAseq expression.
Figure Legend Snippet: Fold-change consistency between the Agilent method and the RPKM method from 53 paired tumor-normal breast cancer samples. The common genes were divided into four groups based on their RNAseq expression value, and linear regression was performed to evaluate the fold-change consistency for each group. This indicates that the fold-change derived from genes with higher RNAseq expression was more concordant with the fold-change derived from microarray expression than the fold-change derived from genes with lower RNAseq expression.

Techniques Used: Expressing, Derivative Assay, Microarray

Differentially expressed gene concordance analysis using 53 paired tumor-normal breast cancer samples. a) The Spearman correlation coefficients of tumor/normal ratios between the Agilent method, the RPKM method and the RSEM method. b) Venn diagram summarizing the overlap between genes called as significantly differentially expressed (adjusted FDR less than 0.01 and fold-change larger than 2). The differentially expressed genes in Figure 3b were computed using commonly measured genes between microarray and RNAseq. c) Scatter plot of fold-change per gene as measured by the Agilent method and the RNAseq RPKM method. Genes identified as differentially expressed with consistent fold-change direction by both methods are plotted in green. Genes identified as differentially expressed with inconsistent fold change direction by both methods are plotted in red. Genes identified as differentially expressed by either RNAseq method or Agilent method are plotted in blue and yellow, respectively. Genes not identified as differentially expressed by either method are plotted in black. Only 1.2% genes identified as differentially expressed genes by both methods were inconsistent on the fold-change direction (red data).
Figure Legend Snippet: Differentially expressed gene concordance analysis using 53 paired tumor-normal breast cancer samples. a) The Spearman correlation coefficients of tumor/normal ratios between the Agilent method, the RPKM method and the RSEM method. b) Venn diagram summarizing the overlap between genes called as significantly differentially expressed (adjusted FDR less than 0.01 and fold-change larger than 2). The differentially expressed genes in Figure 3b were computed using commonly measured genes between microarray and RNAseq. c) Scatter plot of fold-change per gene as measured by the Agilent method and the RNAseq RPKM method. Genes identified as differentially expressed with consistent fold-change direction by both methods are plotted in green. Genes identified as differentially expressed with inconsistent fold change direction by both methods are plotted in red. Genes identified as differentially expressed by either RNAseq method or Agilent method are plotted in blue and yellow, respectively. Genes not identified as differentially expressed by either method are plotted in black. Only 1.2% genes identified as differentially expressed genes by both methods were inconsistent on the fold-change direction (red data).

Techniques Used: Microarray

14) Product Images from "Allelic expression analysis of Imprinted and X-linked genes from bulk and single-cell transcriptomes"

Article Title: Allelic expression analysis of Imprinted and X-linked genes from bulk and single-cell transcriptomes

Journal: bioRxiv

doi: 10.1101/2020.05.20.105841

Analyses of Imprinted gene expression in naive pluripotent cells with BrewerIX a , BrewerIX rational and overall implementation scheme for the Standard pipeline. b , False positives bi-allelic calls estimated by analysis of transcripts on the X chromosome in 6 male BJ fibroblasts samples. On the x axis thresholds combination of overall depth and minimal coverage of the minor allele. c , BrewerIX gene summary panel results on bulk RNAseq data from isogenic human fibroblasts and primed (HPD00) and naive (HPD01/3/4) iPSCs. The larger the dot, the higher the number of SNVs supporting the bi-allelic call. The brighter the color, the closer to 1 is the average of the allelic ratios (minor/major) of all bi-allelic SNVs. When both alleles are expressed at the same level the allelic ratio is equal to 1. Empty dots indicate detected genes with no evidence of bi-allelic expression, while white dots indicate undetected genes. d , BrewerIX SNV summary panel for Meg3 in the case study shown in c. A barplot for each sample is reported with as many bars as the number of SNVs per gene. Solid colors represent actual SNV with both loci expressed, blue and red are the reference and the alternative/minor allele. Transparent colors indicate SNVs detected with no evidence of bi-allelic expression, while grey-scale colors indicate SNVs that do not meet the minimal coverage. e , Experimental validation of the indicated SNVs by PCR followed by Sanger sequencing. The SNVs of interest are highlighted by a red box. See Supplementary Table 4 for a list of all SNVs validated. Each SNVs was detected in two independent experiments, using either Forward or Reverse sequencing primers. f , BrewerIX gene summary panel results on bulk RNAseq data generated by Yagi and colleagues 29 . Murine ESCs were expanded in either 2i/L or S/L conditions, while mouse embryonic fibroblasts (MEF) serve as controls. g , BrewerIX gene summary panel results from bulk RNAseq data of mESCs cultured in 2i/L or S/L (two biological replicates) by Kolodziejczyk and colleagues 35 . See Fig. 2a for matching single-cell RNAseq samples.
Figure Legend Snippet: Analyses of Imprinted gene expression in naive pluripotent cells with BrewerIX a , BrewerIX rational and overall implementation scheme for the Standard pipeline. b , False positives bi-allelic calls estimated by analysis of transcripts on the X chromosome in 6 male BJ fibroblasts samples. On the x axis thresholds combination of overall depth and minimal coverage of the minor allele. c , BrewerIX gene summary panel results on bulk RNAseq data from isogenic human fibroblasts and primed (HPD00) and naive (HPD01/3/4) iPSCs. The larger the dot, the higher the number of SNVs supporting the bi-allelic call. The brighter the color, the closer to 1 is the average of the allelic ratios (minor/major) of all bi-allelic SNVs. When both alleles are expressed at the same level the allelic ratio is equal to 1. Empty dots indicate detected genes with no evidence of bi-allelic expression, while white dots indicate undetected genes. d , BrewerIX SNV summary panel for Meg3 in the case study shown in c. A barplot for each sample is reported with as many bars as the number of SNVs per gene. Solid colors represent actual SNV with both loci expressed, blue and red are the reference and the alternative/minor allele. Transparent colors indicate SNVs detected with no evidence of bi-allelic expression, while grey-scale colors indicate SNVs that do not meet the minimal coverage. e , Experimental validation of the indicated SNVs by PCR followed by Sanger sequencing. The SNVs of interest are highlighted by a red box. See Supplementary Table 4 for a list of all SNVs validated. Each SNVs was detected in two independent experiments, using either Forward or Reverse sequencing primers. f , BrewerIX gene summary panel results on bulk RNAseq data generated by Yagi and colleagues 29 . Murine ESCs were expanded in either 2i/L or S/L conditions, while mouse embryonic fibroblasts (MEF) serve as controls. g , BrewerIX gene summary panel results from bulk RNAseq data of mESCs cultured in 2i/L or S/L (two biological replicates) by Kolodziejczyk and colleagues 35 . See Fig. 2a for matching single-cell RNAseq samples.

Techniques Used: Expressing, Polymerase Chain Reaction, Sequencing, Generated, Cell Culture

15) Product Images from "NT5E/CD73 as Correlative Factor of Patient Survival and Natural Killer Cell Infiltration in Glioblastoma"

Article Title: NT5E/CD73 as Correlative Factor of Patient Survival and Natural Killer Cell Infiltration in Glioblastoma

Journal: Journal of Clinical Medicine

doi: 10.3390/jcm8101526

Survival analysis in the context of NT5E and natural killer (NK) gene signature expression. ( A ) Expression of NT5E in GBM patient samples plotted on the basis of patient vital status. Analysis was done in R2 ( n = 540). ( B ) Disease-free survival of GBM patients on the basis of NT5E expression level from TCGA RNASeq V2 RSEM data ( p = 0.0039; z = 2; left ; n = 166); NK gene signatures comprising 13 NK-specific genes from U133 Affymetrix gene expression data ( p = 0.0285; middle panel ); and both NT5E and NK gene signatures from U133 Affymetrix gene expression data ( p = 0.0109; right ). Kaplan–Meier plots were generated in cBioPortal ( n = 533). ( C ) Overall survival of GBM patients with the mesenchymal subtype based on NT5E expression. Analysis was done in GEPIA2 ( n = 163). ( D ) Overall survival stratified by risk group for patients expressing NT5E and ADORA2A . Analysis was done in R2.
Figure Legend Snippet: Survival analysis in the context of NT5E and natural killer (NK) gene signature expression. ( A ) Expression of NT5E in GBM patient samples plotted on the basis of patient vital status. Analysis was done in R2 ( n = 540). ( B ) Disease-free survival of GBM patients on the basis of NT5E expression level from TCGA RNASeq V2 RSEM data ( p = 0.0039; z = 2; left ; n = 166); NK gene signatures comprising 13 NK-specific genes from U133 Affymetrix gene expression data ( p = 0.0285; middle panel ); and both NT5E and NK gene signatures from U133 Affymetrix gene expression data ( p = 0.0109; right ). Kaplan–Meier plots were generated in cBioPortal ( n = 533). ( C ) Overall survival of GBM patients with the mesenchymal subtype based on NT5E expression. Analysis was done in GEPIA2 ( n = 163). ( D ) Overall survival stratified by risk group for patients expressing NT5E and ADORA2A . Analysis was done in R2.

Techniques Used: Expressing, Generated

16) Product Images from "Reductions in hypothalamic Gfap expression, glial cells and α-tanycytes in lean and hypermetabolic Gnasxl-deficient mice"

Article Title: Reductions in hypothalamic Gfap expression, glial cells and α-tanycytes in lean and hypermetabolic Gnasxl-deficient mice

Journal: Molecular Brain

doi: 10.1186/s13041-016-0219-1

Reduced Gfap RNA expression levels in Gnasxl m+/p- hypothalami. A similar 2-fold down-regulation of Gfap RNA levels was found by RNAseq and qRT-PCR in Gnasxl knock-out hypothalami (*** p
Figure Legend Snippet: Reduced Gfap RNA expression levels in Gnasxl m+/p- hypothalami. A similar 2-fold down-regulation of Gfap RNA levels was found by RNAseq and qRT-PCR in Gnasxl knock-out hypothalami (*** p

Techniques Used: RNA Expression, Quantitative RT-PCR, Knock-Out

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RNA Sequencing Assay:

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Article Snippet: .. 0.5 µg rRNA-depleted total RNA (RiboMinus Plant Kit, Invitrogen) were used to construct transcriptomic libraries according to the instruction from SOLiD Total RNA-Seq Kit. .. Sequence Assembly and Validation We separated candidate mt genome reads from eight Roche/454 GS FLX runs based on 40 published plant mt genome sequences (identity ≥80% and E-value ≤10−5 ).

Article Title: Deposition of Histone Variant H2A.Z within Gene Bodies Regulates Responsive Genes
Article Snippet: .. RNA sequencing Approximately 30 ug total RNA was isolated from 4 week post germination mature rosette leaves using the RNeasy Plant Extraction Kit (Qiagen) with the optional on-column DNAse treatment. mRNA was purified from total RNA by two treatments of poly-A enrichment using the Oligotex kit (Qiagen #72022), followed by a rRNA removal step using the RiboMinus Plant Kit for RNA sequencing (Invitrogen #A1083702). ..

Article Title: DNA Methylation and Histone H1 Jointly Repress Transposable Elements and Aberrant Intragenic Transcripts.
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Article Title: Systematic characterization of novel lncRNAs responding to phosphate starvation in Arabidopsis thaliana
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Article Title: Ancient orphan crop joins modern era: gene-based SNP discovery and mapping in lentil
Article Snippet: .. For all other libraries, including a second CDC Redberry library, equal amounts of the total RNA from each tissue was mixed first, then further purified using the RiboMinus Plant Kit for RNA-Seq (Invitrogen), and then used for cDNA synthesis. .. 3′-anchored cDNA libraries for 454 sequencing were prepared based on a protocol described in Eveland et al. [ ] and modified to incorporate Aci I as the restriction enzyme used to generate 3′ cDNA fragments of the optimal size range for amplification during 454 Titanium chemistry sequencing [ ].

Isolation:

Article Title: Deposition of Histone Variant H2A.Z within Gene Bodies Regulates Responsive Genes
Article Snippet: .. RNA sequencing Approximately 30 ug total RNA was isolated from 4 week post germination mature rosette leaves using the RNeasy Plant Extraction Kit (Qiagen) with the optional on-column DNAse treatment. mRNA was purified from total RNA by two treatments of poly-A enrichment using the Oligotex kit (Qiagen #72022), followed by a rRNA removal step using the RiboMinus Plant Kit for RNA sequencing (Invitrogen #A1083702). ..

Construct:

Article Title: A Complete Sequence and Transcriptomic Analyses of Date Palm (Phoenix dactylifera L.) Mitochondrial Genome
Article Snippet: .. 0.5 µg rRNA-depleted total RNA (RiboMinus Plant Kit, Invitrogen) were used to construct transcriptomic libraries according to the instruction from SOLiD Total RNA-Seq Kit. .. Sequence Assembly and Validation We separated candidate mt genome reads from eight Roche/454 GS FLX runs based on 40 published plant mt genome sequences (identity ≥80% and E-value ≤10−5 ).

Purification:

Article Title: Deposition of Histone Variant H2A.Z within Gene Bodies Regulates Responsive Genes
Article Snippet: .. RNA sequencing Approximately 30 ug total RNA was isolated from 4 week post germination mature rosette leaves using the RNeasy Plant Extraction Kit (Qiagen) with the optional on-column DNAse treatment. mRNA was purified from total RNA by two treatments of poly-A enrichment using the Oligotex kit (Qiagen #72022), followed by a rRNA removal step using the RiboMinus Plant Kit for RNA sequencing (Invitrogen #A1083702). ..

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Incubation:

Article Title: Systematic characterization of novel lncRNAs responding to phosphate starvation in Arabidopsis thaliana
Article Snippet: .. Poly(A)– RNAs, which were retained in the supernatant of incubation products, were processed with a Ribominus kit (RiboMinus™ Plant Kit for RNA-Seq, Invitrogen, A10838-08) to deplete ribosomal RNAs that account for the largest proportion of total RNA. ..

other:

Article Title: Tousled-Like Kinases Suppress Innate Immune Signaling Triggered by Alternative Lengthening of Telomeres
Article Snippet: To avoid limiting our analysis in mRNA polyA+, we performed enrichment of whole transcriptome RNA by depleting ribosomal RNA (rRNA) species.

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    m 5 C mRNA methylation is enriched at transcriptionally active sites with DNA damage. a U2OS-TRE cells transfected with TA-KR/TA-Cherry/tetR-KR/tetR-Cherry plasmids were exposed to light for 30 min for KR activation and allowed to recover for 1 h before harvest (scale bar: 10 μm). Quantification of frequency of cells in 500 cells with m 5 C foci from three independent experiments, mean ± SD (upper right). Fold increase of m 5 C mean intensity = mean intensity of m 5 C at TA-KR/mean intensity of background ( n = 20, mean ± SD) (lower right). b U2OS-TRE cells were transfected with TA-KR/TA-Cherry to induce local oxidative damage or for the control condition. Cells were then stained for m 5 C with four different anti-m 5 C antibodies. Frequency of m 5 C-positive cells in 500 cells was quantified ( n = 3, mean ± SD). c U2OS-TRE cells transfected with TA-KR were digested with <t>RNaseH1,</t> RNaseA, or DNase I and stained for m 5 C quantification (scale bar: 10 μm). d The mRNA from Flp-in 293 cells treated with or without 2 mM H 2 O 2 for 40 min was used for m 5 C measurement via dot blot. Quantification of m 5 C levels (mean ± SD) from three independent experiments normalized with Ctrl and methylene blue is shown. e 32 P-labeled mRNA monophosphate nucleosides were run on 2D gels for 2D-TLC analysis. In vitro-transcribed 4B mRNA with or without m 5 C was run in parallel. Representative images from three sets of independent experiments are shown with arrows showing the directions of each solvent run. Position of each nucleotide and m 5 C are labeled (Left). f 32 P-labeled mRNA monophosphate nucleosides from U2OS cells with or without 2 mM H 2 O 2 for 40 min were run on 2D gels for 2D-TLC analysis. Representative images from three sets of independent experiments. Associated quantification of relative increase in m 5 C in peroxide-treated cells compared to control, normalized to nucleotide C (right). Statistical analysis was performed with the unpaired two tailed Student’s t -test. * p
    Rnase H 5 U µl, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 84/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    In vitro screening of candidate small molecule inhibitors against E. coli <t>RNase</t> E NTD. (A) Representative 20% denaturing PAGE analysis of the cleavage of 1 μM 5′-p-RNA13-FAM-3′ by 5 nM E . coli RNase E NTD after incubation at 28 °C for 45 min in the absence of small molecule (-) or in the presence of 10 mM AS1, AS2, AS3, AS4, AS6, AS7, AS8, AS9, or 5′S1. This is a composite image assembled from multiple gels (complete gels are presented in Supplementary Fig. S2 ). The expected position of the bands representing the full-length FAM-labelled 5′-p-RNA13-FAM-3′ RNA substrate and the FAM-labelled pentamer 5′-p-AUUUG-FAM-3′ cleavage product are indicated on the right-hand-side of the gels. (B) The chemical structures of inhibitory small molecules AS2, AS4 and 5′S1 (further details are presented in Supplementary Table S1 ).
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    Minimization and motif characterization of 80N 44. ( A ) The predicted secondary structure of the aptamer with arrows depicting the location of the RT footprint using <t>RNase</t> T1 digestion (large black arrow), and 3’ end truncations that either remain functional (blue) or lower inhibition (orange/red). Truncation 6 (t6) is truncated from both 5’ and 3’ ends. ( B ) RT:aptamer 3’ boundary. ( C ) Inhibition of HXB2 RT’s DNA-dependent DNA polymerase activity by aptamer truncations. ( D ) The minimally viable 3’ end truncation of the aptamer, 80N 44t6.
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    m 5 C mRNA methylation is enriched at transcriptionally active sites with DNA damage. a U2OS-TRE cells transfected with TA-KR/TA-Cherry/tetR-KR/tetR-Cherry plasmids were exposed to light for 30 min for KR activation and allowed to recover for 1 h before harvest (scale bar: 10 μm). Quantification of frequency of cells in 500 cells with m 5 C foci from three independent experiments, mean ± SD (upper right). Fold increase of m 5 C mean intensity = mean intensity of m 5 C at TA-KR/mean intensity of background ( n = 20, mean ± SD) (lower right). b U2OS-TRE cells were transfected with TA-KR/TA-Cherry to induce local oxidative damage or for the control condition. Cells were then stained for m 5 C with four different anti-m 5 C antibodies. Frequency of m 5 C-positive cells in 500 cells was quantified ( n = 3, mean ± SD). c U2OS-TRE cells transfected with TA-KR were digested with RNaseH1, RNaseA, or DNase I and stained for m 5 C quantification (scale bar: 10 μm). d The mRNA from Flp-in 293 cells treated with or without 2 mM H 2 O 2 for 40 min was used for m 5 C measurement via dot blot. Quantification of m 5 C levels (mean ± SD) from three independent experiments normalized with Ctrl and methylene blue is shown. e 32 P-labeled mRNA monophosphate nucleosides were run on 2D gels for 2D-TLC analysis. In vitro-transcribed 4B mRNA with or without m 5 C was run in parallel. Representative images from three sets of independent experiments are shown with arrows showing the directions of each solvent run. Position of each nucleotide and m 5 C are labeled (Left). f 32 P-labeled mRNA monophosphate nucleosides from U2OS cells with or without 2 mM H 2 O 2 for 40 min were run on 2D gels for 2D-TLC analysis. Representative images from three sets of independent experiments. Associated quantification of relative increase in m 5 C in peroxide-treated cells compared to control, normalized to nucleotide C (right). Statistical analysis was performed with the unpaired two tailed Student’s t -test. * p

    Journal: Nature Communications

    Article Title: m5C modification of mRNA serves a DNA damage code to promote homologous recombination

    doi: 10.1038/s41467-020-16722-7

    Figure Lengend Snippet: m 5 C mRNA methylation is enriched at transcriptionally active sites with DNA damage. a U2OS-TRE cells transfected with TA-KR/TA-Cherry/tetR-KR/tetR-Cherry plasmids were exposed to light for 30 min for KR activation and allowed to recover for 1 h before harvest (scale bar: 10 μm). Quantification of frequency of cells in 500 cells with m 5 C foci from three independent experiments, mean ± SD (upper right). Fold increase of m 5 C mean intensity = mean intensity of m 5 C at TA-KR/mean intensity of background ( n = 20, mean ± SD) (lower right). b U2OS-TRE cells were transfected with TA-KR/TA-Cherry to induce local oxidative damage or for the control condition. Cells were then stained for m 5 C with four different anti-m 5 C antibodies. Frequency of m 5 C-positive cells in 500 cells was quantified ( n = 3, mean ± SD). c U2OS-TRE cells transfected with TA-KR were digested with RNaseH1, RNaseA, or DNase I and stained for m 5 C quantification (scale bar: 10 μm). d The mRNA from Flp-in 293 cells treated with or without 2 mM H 2 O 2 for 40 min was used for m 5 C measurement via dot blot. Quantification of m 5 C levels (mean ± SD) from three independent experiments normalized with Ctrl and methylene blue is shown. e 32 P-labeled mRNA monophosphate nucleosides were run on 2D gels for 2D-TLC analysis. In vitro-transcribed 4B mRNA with or without m 5 C was run in parallel. Representative images from three sets of independent experiments are shown with arrows showing the directions of each solvent run. Position of each nucleotide and m 5 C are labeled (Left). f 32 P-labeled mRNA monophosphate nucleosides from U2OS cells with or without 2 mM H 2 O 2 for 40 min were run on 2D gels for 2D-TLC analysis. Representative images from three sets of independent experiments. Associated quantification of relative increase in m 5 C in peroxide-treated cells compared to control, normalized to nucleotide C (right). Statistical analysis was performed with the unpaired two tailed Student’s t -test. * p

    Article Snippet: For RNaseA treatment: after heat treatment, cells were incubated with 100 μg/mL RNaseA in 100 μL RNase digestion buffer (5 mM EDTA, 300 mM NaCl, 10 mM Tris-HCl, pH 7.5) at room temperature for 25 min. For RNaseH1 treatment, the cells were incubated with 15 U RNaseH1 (Cat#: EN0201, ThermoFisher Scientific) in 100 μL reaction buffer (200 mM Tris-HCl, pH 7.8, 400 mM KCl, 80 mM MgCl2 , 10 mM DTT) at room temperature for 25 min. For DNase I treatment, cells were incubated with 20 U (1 μL) DNase I in 100 μL buffer (10 mM Tris-HCl, 2.5 mM MgCl2 , 0.5 mM CaCl2 , pH 7.5) at 37 °C for 30 min followed by heat treatment.

    Techniques: Methylation, Transfection, Activation Assay, Staining, Dot Blot, Labeling, Thin Layer Chromatography, In Vitro, Two Tailed Test

    In vitro screening of candidate small molecule inhibitors against E. coli RNase E NTD. (A) Representative 20% denaturing PAGE analysis of the cleavage of 1 μM 5′-p-RNA13-FAM-3′ by 5 nM E . coli RNase E NTD after incubation at 28 °C for 45 min in the absence of small molecule (-) or in the presence of 10 mM AS1, AS2, AS3, AS4, AS6, AS7, AS8, AS9, or 5′S1. This is a composite image assembled from multiple gels (complete gels are presented in Supplementary Fig. S2 ). The expected position of the bands representing the full-length FAM-labelled 5′-p-RNA13-FAM-3′ RNA substrate and the FAM-labelled pentamer 5′-p-AUUUG-FAM-3′ cleavage product are indicated on the right-hand-side of the gels. (B) The chemical structures of inhibitory small molecules AS2, AS4 and 5′S1 (further details are presented in Supplementary Table S1 ).

    Journal: Biochemistry and Biophysics Reports

    Article Title: Identification and analysis of novel small molecule inhibitors of RNase E: Implications for antibacterial targeting and regulation of RNase E

    doi: 10.1016/j.bbrep.2020.100773

    Figure Lengend Snippet: In vitro screening of candidate small molecule inhibitors against E. coli RNase E NTD. (A) Representative 20% denaturing PAGE analysis of the cleavage of 1 μM 5′-p-RNA13-FAM-3′ by 5 nM E . coli RNase E NTD after incubation at 28 °C for 45 min in the absence of small molecule (-) or in the presence of 10 mM AS1, AS2, AS3, AS4, AS6, AS7, AS8, AS9, or 5′S1. This is a composite image assembled from multiple gels (complete gels are presented in Supplementary Fig. S2 ). The expected position of the bands representing the full-length FAM-labelled 5′-p-RNA13-FAM-3′ RNA substrate and the FAM-labelled pentamer 5′-p-AUUUG-FAM-3′ cleavage product are indicated on the right-hand-side of the gels. (B) The chemical structures of inhibitory small molecules AS2, AS4 and 5′S1 (further details are presented in Supplementary Table S1 ).

    Article Snippet: A putative small molecule-binding site at the active site of E. coli RNase E was selected in the apo-2BX2 structure based on the presence of the catalytic residues D303, N305 and D346 and a putative small molecule-binding site at the 5′ sensor region was selected in the 2VMK structure based on the presence of the key amino acids G124, V128, R169 and T170.

    Techniques: In Vitro, Polyacrylamide Gel Electrophoresis, Incubation

    Inhibition of F. tularensis and A. baumannii RNase E NTDs by AS2, AS4 and 5′S1. The relative rates of cleavage of 1 μM modified target-guide substrate by 5 nM E. coli (blue), F. tularensis (orange) or A. baumannii (grey) RNase E NTD in the absence of inhibitor and in the presence of either 2 mM AS2, AS4 or 5′S1. For each RNase E NTD, the data have been normalised to the cleavage rate when there was no inhibitor present. Data are the average from duplicate experiments and the error bars represent the standard error of the mean. . (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

    Journal: Biochemistry and Biophysics Reports

    Article Title: Identification and analysis of novel small molecule inhibitors of RNase E: Implications for antibacterial targeting and regulation of RNase E

    doi: 10.1016/j.bbrep.2020.100773

    Figure Lengend Snippet: Inhibition of F. tularensis and A. baumannii RNase E NTDs by AS2, AS4 and 5′S1. The relative rates of cleavage of 1 μM modified target-guide substrate by 5 nM E. coli (blue), F. tularensis (orange) or A. baumannii (grey) RNase E NTD in the absence of inhibitor and in the presence of either 2 mM AS2, AS4 or 5′S1. For each RNase E NTD, the data have been normalised to the cleavage rate when there was no inhibitor present. Data are the average from duplicate experiments and the error bars represent the standard error of the mean. . (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

    Article Snippet: A putative small molecule-binding site at the active site of E. coli RNase E was selected in the apo-2BX2 structure based on the presence of the catalytic residues D303, N305 and D346 and a putative small molecule-binding site at the 5′ sensor region was selected in the 2VMK structure based on the presence of the key amino acids G124, V128, R169 and T170.

    Techniques: Inhibition, Modification

    Potency of AS2, AS4 and 5′S1 as small molecule inhibitors of RNase E. (A) Schematic of the FRET-based real-time RNase E assay. The substrate is a partially double-stranded RNA (modified target-guide) consisting of a 5′ hydroxylated, 3′ FAM-labelled 18-mer “target” RNA and a 5′ monophosphorylated, 3′ TAMRA-labelled 13-mer “guide” RNA, which anneals to the target RNA with partial complementarity. In the uncleaved modified target-guide substrate, the fluorescence of the 3′ FAM group of the 18-mer target RNA is quenched by the 3′ TAMRA group of the 13-mer guide RNA. Endoribonucleolytic cleavage of the single-stranded A/U-rich region of the 18-mer target RNA by RNase E NTD, at the position indicated by the arrow, results in the release of a 3′ FAM-labelled pentamer and the unquenching of the FAM fluorescence. The increase in fluorescence can be monitored in real-time. (B) Plots of the rate of cleavage of 1 μM modified target-guide RNA substrate by 5 nM E . coli RNase E NTD in the presence of 0.25, 0.5, 1, 2, 3, 4, 5 and 10 mM AS2, AS4 or 5′S1. Data are the average from three experiments and the error bars represent the standard error of the mean. Data were fitted as described in Materials and Methods to determine the IC 50 , which is indicated for the respective small molecule inhibitor in the top right-hand corner of the plot.

    Journal: Biochemistry and Biophysics Reports

    Article Title: Identification and analysis of novel small molecule inhibitors of RNase E: Implications for antibacterial targeting and regulation of RNase E

    doi: 10.1016/j.bbrep.2020.100773

    Figure Lengend Snippet: Potency of AS2, AS4 and 5′S1 as small molecule inhibitors of RNase E. (A) Schematic of the FRET-based real-time RNase E assay. The substrate is a partially double-stranded RNA (modified target-guide) consisting of a 5′ hydroxylated, 3′ FAM-labelled 18-mer “target” RNA and a 5′ monophosphorylated, 3′ TAMRA-labelled 13-mer “guide” RNA, which anneals to the target RNA with partial complementarity. In the uncleaved modified target-guide substrate, the fluorescence of the 3′ FAM group of the 18-mer target RNA is quenched by the 3′ TAMRA group of the 13-mer guide RNA. Endoribonucleolytic cleavage of the single-stranded A/U-rich region of the 18-mer target RNA by RNase E NTD, at the position indicated by the arrow, results in the release of a 3′ FAM-labelled pentamer and the unquenching of the FAM fluorescence. The increase in fluorescence can be monitored in real-time. (B) Plots of the rate of cleavage of 1 μM modified target-guide RNA substrate by 5 nM E . coli RNase E NTD in the presence of 0.25, 0.5, 1, 2, 3, 4, 5 and 10 mM AS2, AS4 or 5′S1. Data are the average from three experiments and the error bars represent the standard error of the mean. Data were fitted as described in Materials and Methods to determine the IC 50 , which is indicated for the respective small molecule inhibitor in the top right-hand corner of the plot.

    Article Snippet: A putative small molecule-binding site at the active site of E. coli RNase E was selected in the apo-2BX2 structure based on the presence of the catalytic residues D303, N305 and D346 and a putative small molecule-binding site at the 5′ sensor region was selected in the 2VMK structure based on the presence of the key amino acids G124, V128, R169 and T170.

    Techniques: Modification, Fluorescence

    Molecular docking of potential small molecule inhibitors into E. coli RNase E NTD. The lowest-energy RNase E-small molecule complex conformations obtained from the molecular docking of potential small molecule inhibitors AS1-9 into the active site (A) and 5′S1 and 5′S2 into the 5′ sensor region (B) of E. coli RNase E NTD using 100 starting placement poses. The corresponding docking score is shown above each panel. The docked small molecule is shown as sticks and labelled in each panel. E. coli RNase E NTD is shown as a ribbon representation (S1 subdomain, blue; DNase I subdomain, red; 5′ sensor subdomain, gold; small subdomain, grey). Key amino acids, required for catalytic activity and/or substrate binding, are shown as sticks and labelled. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

    Journal: Biochemistry and Biophysics Reports

    Article Title: Identification and analysis of novel small molecule inhibitors of RNase E: Implications for antibacterial targeting and regulation of RNase E

    doi: 10.1016/j.bbrep.2020.100773

    Figure Lengend Snippet: Molecular docking of potential small molecule inhibitors into E. coli RNase E NTD. The lowest-energy RNase E-small molecule complex conformations obtained from the molecular docking of potential small molecule inhibitors AS1-9 into the active site (A) and 5′S1 and 5′S2 into the 5′ sensor region (B) of E. coli RNase E NTD using 100 starting placement poses. The corresponding docking score is shown above each panel. The docked small molecule is shown as sticks and labelled in each panel. E. coli RNase E NTD is shown as a ribbon representation (S1 subdomain, blue; DNase I subdomain, red; 5′ sensor subdomain, gold; small subdomain, grey). Key amino acids, required for catalytic activity and/or substrate binding, are shown as sticks and labelled. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

    Article Snippet: A putative small molecule-binding site at the active site of E. coli RNase E was selected in the apo-2BX2 structure based on the presence of the catalytic residues D303, N305 and D346 and a putative small molecule-binding site at the 5′ sensor region was selected in the 2VMK structure based on the presence of the key amino acids G124, V128, R169 and T170.

    Techniques: Activity Assay, Binding Assay

    Minimization and motif characterization of 80N 44. ( A ) The predicted secondary structure of the aptamer with arrows depicting the location of the RT footprint using RNase T1 digestion (large black arrow), and 3’ end truncations that either remain functional (blue) or lower inhibition (orange/red). Truncation 6 (t6) is truncated from both 5’ and 3’ ends. ( B ) RT:aptamer 3’ boundary. ( C ) Inhibition of HXB2 RT’s DNA-dependent DNA polymerase activity by aptamer truncations. ( D ) The minimally viable 3’ end truncation of the aptamer, 80N 44t6.

    Journal: bioRxiv

    Article Title: Poly-Target Selection Identifies Broad-Spectrum RNA Aptamers

    doi: 10.1101/302745

    Figure Lengend Snippet: Minimization and motif characterization of 80N 44. ( A ) The predicted secondary structure of the aptamer with arrows depicting the location of the RT footprint using RNase T1 digestion (large black arrow), and 3’ end truncations that either remain functional (blue) or lower inhibition (orange/red). Truncation 6 (t6) is truncated from both 5’ and 3’ ends. ( B ) RT:aptamer 3’ boundary. ( C ) Inhibition of HXB2 RT’s DNA-dependent DNA polymerase activity by aptamer truncations. ( D ) The minimally viable 3’ end truncation of the aptamer, 80N 44t6.

    Article Snippet: RNase T1 digestion was performed by incubating thermally renatured RNA ( > 106 CPM) with 40 units of RNase T1 (Thermo Fisher) in digestion buffer (25 mM sodium citrate pH 5.0, 6 M urea) for 5 minutes at 55° C. T1 digestion was halted with the addition of gel loading buffer.

    Techniques: Functional Assay, Inhibition, Activity Assay

    Minimization and motif characterization of 80N 148. ( A ) The predicted secondary structure of the aptamer with arrows depicting the location of the 3’ boundary using RNase T1 digestion (large black arrow), and 3’ end truncations that either remain functional (blue) or abrogate inhibition (red). ( B ) RT:aptamer 3’ boundary. ( C ) Inhibition of HXB2 RT’s DNA-dependent DNA polymerase activity by aptamer truncations. ( D ) The minimally viable 3’ end truncation of the aptamer, 80N 148t1.

    Journal: bioRxiv

    Article Title: Poly-Target Selection Identifies Broad-Spectrum RNA Aptamers

    doi: 10.1101/302745

    Figure Lengend Snippet: Minimization and motif characterization of 80N 148. ( A ) The predicted secondary structure of the aptamer with arrows depicting the location of the 3’ boundary using RNase T1 digestion (large black arrow), and 3’ end truncations that either remain functional (blue) or abrogate inhibition (red). ( B ) RT:aptamer 3’ boundary. ( C ) Inhibition of HXB2 RT’s DNA-dependent DNA polymerase activity by aptamer truncations. ( D ) The minimally viable 3’ end truncation of the aptamer, 80N 148t1.

    Article Snippet: RNase T1 digestion was performed by incubating thermally renatured RNA ( > 106 CPM) with 40 units of RNase T1 (Thermo Fisher) in digestion buffer (25 mM sodium citrate pH 5.0, 6 M urea) for 5 minutes at 55° C. T1 digestion was halted with the addition of gel loading buffer.

    Techniques: Functional Assay, Inhibition, Activity Assay

    Minimization and motif characterization of 70N 105. ( A ) The predicted secondary structure of the aptamer with arrows depicting the location of the 3’ boundary using RNase T1 digestion (large black arrow), and 3’ end truncations that either remain functional (blue) or abrogate inhibition (red). ( B ) RT:aptamer 3’ boundary. ( C ) Inhibition of HXB2 RT’s DNA-dependent DNA polymerase activity by aptamer truncations. ( D ) The minimally viable 3’ end truncation of the aptamer, 70N 105t2.

    Journal: bioRxiv

    Article Title: Poly-Target Selection Identifies Broad-Spectrum RNA Aptamers

    doi: 10.1101/302745

    Figure Lengend Snippet: Minimization and motif characterization of 70N 105. ( A ) The predicted secondary structure of the aptamer with arrows depicting the location of the 3’ boundary using RNase T1 digestion (large black arrow), and 3’ end truncations that either remain functional (blue) or abrogate inhibition (red). ( B ) RT:aptamer 3’ boundary. ( C ) Inhibition of HXB2 RT’s DNA-dependent DNA polymerase activity by aptamer truncations. ( D ) The minimally viable 3’ end truncation of the aptamer, 70N 105t2.

    Article Snippet: RNase T1 digestion was performed by incubating thermally renatured RNA ( > 106 CPM) with 40 units of RNase T1 (Thermo Fisher) in digestion buffer (25 mM sodium citrate pH 5.0, 6 M urea) for 5 minutes at 55° C. T1 digestion was halted with the addition of gel loading buffer.

    Techniques: Functional Assay, Inhibition, Activity Assay