Journal: Oncology Letters

Article Title: lncRNA-CD160 decreases the immunity of CD8 + T cells through epigenetic mechanisms in hepatitis B virus infection

doi: 10.3892/ol.2020.11534

Figure Lengend Snippet: Percentage of CD160 + CD8 + T cells in patients with CHB with different natural history is negatively associated with the progress of CHB. (A) The percentage of CD160 + CD8 + T cells in patients with CHB was detected using a FACSCalibur flow cytometer, and statistical analysis was performed. (B) The percentage of CD160 + CD8 + T cells in patients with different stages of CHB was detected. (C) Analysis of the percentage of CD160 + CD8 + T cells in patients with different stages of CHB. (D) The expression of CD160 was inhibited by CD160-siRNA. (E) CD160 + CD8 + T cells were transfected with CD160-siRNA, and the CD160-siRNA significantly inhibited the expression of CD160. Following inhibition of CD160, (F) the expression of SAP was reduced and (G) the percentage of SAP + CD160 + cells in total CD8 + T cells was inhibited. To further clarify the role of CD160 in the CD8 + T cell immune response, the concentrations of (H) IFN-γ and (I) TNF-α were detected, which are produced by CD8 + T cells. IFN-γ and TNF-α were significantly decreased following CD160-knockdown in CD8 + T cells. **P<0.01, ***P<0.005. HBV, hepatitis B virus; CHB, chronic HBV; siRNA, small interfering RNA; SAP, (SLAM)-associated protein con, control; IT, immune tolerance; LR, low-replicate; IC, immunological clearance.

Article Snippet: Antibodies [CD8 (1:100; sc-1177; Santa Cruz Biotechnology, Inc.); CD160 antibody (1:1,000; AF3899; R&D Systems, Inc.)] specific for cell surface markers diluted in FACS buffer were added directly to this mixture and incubated for 30 min at 4°C.

Techniques: Flow Cytometry, Expressing, Transfection, Inhibition, Produced, Knockdown, Virus, Small Interfering RNA, Control

Journal: Oncology Letters

Article Title: lncRNA-CD160 decreases the immunity of CD8 + T cells through epigenetic mechanisms in hepatitis B virus infection

doi: 10.3892/ol.2020.11534

Figure Lengend Snippet: CD160 inhibits HDAC11 expression via epigenetic regulation in CD8 + T cells. (A) A gene microarray assay was conducted with CD160 + CD8 + T cells and CD160 − CD8 + T cells, which were isolated from patients with chronic hepatitis B virus, with unsupervised clustering analysis. Green indicates decreased expression and red indicates increased expression. (B) Gene microarray assay with supervised clustering analysis was performed with CD160 + CD8 + T cells and CD160 − CD8 + T cells for epigenetic factor detection. (C) The expression of HDAC11 in CD160 + CD8 + T cells and CD160 − CD8 + T cells was detected by RT-qPCR assay. (D) An immunofluorescence assay for CD8, CD160 and HDAC11 detection was performed with CD160 + CD8 + T cells to obtain confocal microscopic images; magnification, ×1,000. (E) CD8 + T cells were transfected with CD160-siRNA and the expression of HDAC11 was detected by RT-qPCR, and the expression level of HDAC11 was negatively associated with the expression of CD160. (F) The protein level of HDAC11 was measured by western blotting following transfection of CD8 + T cells with CD160-siRNA. (G) The expression of HDAC11 following transfection with HDAC11 siRNA. CD8 + T cells were transfected with HDAC11-siRNA and the expression levels of (H) IFN-γ and (I) TNF-α were detected by RT-qPCR assay. (J) Flow cytometry was performed to For detect the percentage of HDAC11 +/− CD160 +/− CD8 + T cells in the total CD8 + T cell population. *P<0.05, ***P<0.005. HDAC11, histone-modification enzyme gene histone deacetylases 11; RT-qPCR, reverse transcription-quantitative PCR; siRNA, small interfering RNA; con, control.

Article Snippet: Antibodies [CD8 (1:100; sc-1177; Santa Cruz Biotechnology, Inc.); CD160 antibody (1:1,000; AF3899; R&D Systems, Inc.)] specific for cell surface markers diluted in FACS buffer were added directly to this mixture and incubated for 30 min at 4°C.

Techniques: Expressing, Microarray, Isolation, Virus, Quantitative RT-PCR, Immunofluorescence, Transfection, Western Blot, Flow Cytometry, Modification, Reverse Transcription, Real-time Polymerase Chain Reaction, Small Interfering RNA, Control

Journal: Oncology Letters

Article Title: lncRNA-CD160 decreases the immunity of CD8 + T cells through epigenetic mechanisms in hepatitis B virus infection

doi: 10.3892/ol.2020.11534

Figure Lengend Snippet: lncRNA-CD160 expression is positively associated with CD160 expression in CD8 + T cells. (A) lncRNA gene microarray assay was conducted with CD160 + CD8 + T cells and CD160 − CD8 + T cells, which were isolated from patients with chronic HBV, with unsupervised clustering analysis. Green indicates decreased expression and red indicates increased expression. (B) lncRNA gene microarray assay with supervised clustering analysis was performed with CD160 + CD8 + T cells and CD160 − CD8 + T cells. (C) Reverse transcription-qPCR assay was performed to detect the lncRNA-CD160 expression level in CD160 +/− CD8 + T cells. (D) Chromosome analysis indicated that both CD160 and lncRNA-CD160 were located at Chr1q42.3, and lncRNA-CD160 was partly located at the region of CD160, which was between the B and C region; therefore, lncRNA-CD160 could also be termed lncRNA-CD160. Chromatin immunoprecipitation-qPCR was performed to investigate the relationship between (E) lncRNA-CD160 and H3K9Me1, (F) the relationship between lncRNA-CD160 and HDAC11 also was detected. HDAC11 and H3K9Me1 trimethylation levels were promoted in the lncRNA-CD160 loci. *P<0.05, **P<0.01, ***P<0.005. qPCR, quantitative PCR; lncRNA, long non-coding RNA; HBV, hepatitis B virus; HDAC11, histone-modification enzyme gene histone deacetylases 11.

Article Snippet: Antibodies [CD8 (1:100; sc-1177; Santa Cruz Biotechnology, Inc.); CD160 antibody (1:1,000; AF3899; R&D Systems, Inc.)] specific for cell surface markers diluted in FACS buffer were added directly to this mixture and incubated for 30 min at 4°C.

Techniques: Expressing, Microarray, Isolation, Reverse Transcription, Chromatin Immunoprecipitation, Real-time Polymerase Chain Reaction, Virus, Modification

Journal: Oncology Letters

Article Title: lncRNA-CD160 decreases the immunity of CD8 + T cells through epigenetic mechanisms in hepatitis B virus infection

doi: 10.3892/ol.2020.11534

Figure Lengend Snippet: lncRNA-CD160 inhibits IFN-γ and TNF-α secretion in CD8 + T cells via epigenetic regulation. In order to demonstrate the role of lncRNA-CD160 on IFN-γ and TNF-α secretion, siRNA targeting lncRNA-CD160 was transfected into the CD8 + T cells. (A) The efficiency of lncRNA-CD160 siRNA was detected, and the concentrations of (B) IFN-γ and (C) TNF-α were detected by ELISA assay. A CHIP-qPCR assay was performed to demonstrate the mechanism of the IFN-γ and TNF-α secretion inhibition. When lncRNA-CD160 was knocked down, the H3K9Me1 expression levels, which could be mediated by HDAC11 at the (D) IFN-γ and (E) TNF-α promoters loci, were significant inhibited. (F) Immunoprecipitation and western blot assays were performed to detect the expression of HDAC11 in the immunoprecipitate using an anti-HDAC11-specific antibody. (G) Gel electrophoresis and (H) an image of biotinylated lncRNA-CD160. (I) Reverse transcription-qPCR analysis of lncRNA-CD160 retrieved by IgG or anti-HDAC11 from CD8 + T-cell lysates of patients with HBV. (J) FISH following lncRNA-CD160 siRNA transfection, magnification, ×1,000. (K) RNA pull-down and western blot assays were conducted to investigate the association between lncRNA-CD160 and HDAC11, and the data indicated that lncRNA-CD160 and HDAC11 could bind to each other. (L) Further RNA FISH and immunofluorescence analyses were performed to investigate the locations of lncRNA-CD160 and HDAC11, and the results demonstrated that both were located in the nucleus of CD8 + T cells, magnification, ×1,000. A CHIP-qPCR assay was also performed to reveal the location of the lncRNA-CD160 and HDAC11 complex, and the results revealed that lncRNA-CD160-siRNA could significantly inhibit the expression of HDAC11 at (M) IFN-γ and (N) TNF-α promoter regions. **P<0.01, ***P<0.005. FISH, fluorescent in situ hybridization; lncRNA, long non-coding RNA; con, control; siRNA, small interfering RNA; qPCR, quantitative PCR; HDAC11, histone-modification enzyme gene histone deacetylases 11.

Article Snippet: Antibodies [CD8 (1:100; sc-1177; Santa Cruz Biotechnology, Inc.); CD160 antibody (1:1,000; AF3899; R&D Systems, Inc.)] specific for cell surface markers diluted in FACS buffer were added directly to this mixture and incubated for 30 min at 4°C.

Techniques: Transfection, Enzyme-linked Immunosorbent Assay, ChIP-qPCR, Inhibition, Expressing, Immunoprecipitation, Western Blot, Nucleic Acid Electrophoresis, Reverse Transcription, Immunofluorescence, In Situ Hybridization, Control, Small Interfering RNA, Real-time Polymerase Chain Reaction, Modification

Journal: Oncology Letters

Article Title: lncRNA-CD160 decreases the immunity of CD8 + T cells through epigenetic mechanisms in hepatitis B virus infection

doi: 10.3892/ol.2020.11534

Figure Lengend Snippet: lncRNA-CD160 suppresses HBV replication during infection in vivo . (A) To investigate the effect of lncRNA-CD160 on HBV replication, an adoptive transfer model was established. (B) Following adoptive transfer, the serum HBsAg levels were detected at different time points using a Roche Cobas 6000 immuno-chemiluminescence analyzer. *P<0.05, ***P<0.005 vs. LV-lncRNA-CD160. (C) The HBV DNA load was detected by reverse transcription--quantitative PCR assay at different time points following adoptive transfer. *P<0.05, **P<0.01 vs. LV-lncRNA-CD160. (D) An immunohistochemistry assay was performed for HBcAg detection in the liver tissues, which were harvested from the adoptive transfer model mice, magnification, ×1,000. (E) The percentages of HBcAg-positive hepatocytes were quantified. **P<0.01 and ***P<0.005. (F) An overview of the role of lncRNA-CD160 in the mediation of IFN-γ and TNF-α. lncRNA, long non-coding RNA; HBV, hepatitis B virus; HBsAg, hepatitis B surface antigen; LV, lentivirus; HBcAg, hepatitis B virus c antibody; SAP, (SLAM)-associated protein; siRNA, small interfering RNA.

Article Snippet: Antibodies [CD8 (1:100; sc-1177; Santa Cruz Biotechnology, Inc.); CD160 antibody (1:1,000; AF3899; R&D Systems, Inc.)] specific for cell surface markers diluted in FACS buffer were added directly to this mixture and incubated for 30 min at 4°C.

Techniques: Infection, In Vivo, Adoptive Transfer Assay, Reverse Transcription, Real-time Polymerase Chain Reaction, Immunohistochemistry, Virus, Small Interfering RNA

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) Workflow for transferring mouse TF open reading frames (ORFs) into a lentiviral vector to overexpress HA-tagged TFs in 3T3-L1 cells. 750 fully sequence-verified entry TF clones were transferred using LR Gateway cloning into the Tet-On expression vector (derived from the original TRE_GOI_rtTA_hPGK vector , ‘Materials and methods’), during which the attL sites recombine with the attR sites. 734 ORF TFs were successfully transferred. ( B ) Barplots: percentage of expressed/transcribed TFs of all TFs that significantly enhance adipogenesis (positive candidates) in mouse 3T3-L1 cells based on microarray expression data in mouse 3T3-L1 (mExpr) and human hASC (hExpr) as well as POLII signal over genes (mPolII) and combined POLII signal and expression (mAny) in mouse 3T3-L1 cells ( ; ); table: positive candidates that are significantly up- or down-regulated in mouse adipose tissue compared to other probed tissues based on ArrayExpress Expression Atlas . ( C ) Protein levels of stably overexpressed HA-tagged TFs selected for follow-up in 3T3-L1 cells (follow-up TFs). The expected molecular mass for each protein is indicated above the image. Note that especially for ZEB1, several bands were detected which likely correspond to cryptic translation or specific protein degradation products given that they stem from the same open-reading frame construct and that they are all tagged by HA. ( D – F ) Relative (to control): Pparg2 ( D ), Cebpa ( E ), and Adipoq ( F ) mRNA fold-changes (FCs) in 3T3-L1 cells stably overexpressing each follow-up TF, as measured by qPCR. To measure Pparg2 mRNA levels, primers were used that target the 5′ UTR of the endogenous transcript, allowing us to differentiate between the overexpression and endogenous Pparg transcripts. ( G ) Microarray-based expression analysis of follow-up TFs during 3T3-L1 adipogenesis. In contrast to Pparg (orange), most follow-up TFs are at their maximal expression level already prior to induction of differentiation (days −2 and day 0). ( H ) Relative (to control; i.e. transduced with the shEmpty vector) Zeb1 mRNA FCs in knockdown 3T3-L1 cells at four different time points during adipogenesis, as measured by qPCR. Error bars depict the standard error of the mean from three biological replicate experiments. **p ≤ 0.01 and 0.01 < *p ≤ 0.05. DOI: http://dx.doi.org/10.7554/eLife.03346.004

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Transferring, Plasmid Preparation, Sequencing, Clone Assay, Cloning, Expressing, Derivative Assay, Microarray, Stable Transfection, Construct, Control, Over Expression, Transduction, Knockdown

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) Schematic overview of high-throughput screening illustrating how 3T3-L1 cells were transduced with 734 individual TFs in three replicates each, 3 days before induction of adipocyte differentiation (‘Materials and methods’). The effect of TF overexpression was quantified at differentiation day 7 by lipid, nucleus and cellular staining and summarized as a percentage of differentiated cells (PDC) per TF. ( B ) Overview of fold-changes (FC) compared to control for all TFs showing a differentiation FC > 1. TFs that significantly induced differentiation (FC ≥ 1.5, α = 0.05) are highlighted in red and PPARγ specifically in orange. ( C ) Effect of stably overexpressing eight putatively novel regulators of adipogenesis, PPARγ, or a control vector on 3T3-L1 differentiation as assessed by Oil Red O staining of lipid droplets at day 5 after induction. ( D ) Effect of knocking down ZEB1 or PPARγ (as a positive control), or the negative control (empty shRNA) on 3T3-L1 differentiation as assessed by Oil Red O staining at day 6 after induction. In the shRNA pool of ZEB1, shRNA2 was not used because the robustness of the cells after treatment was low. Examples of microscopic images illustrating the overexpression or knockdown (KD) effects on 3T3-L1 differentiation are shown in or , respectively. DOI: http://dx.doi.org/10.7554/eLife.03346.003

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: High Throughput Screening Assay, Transduction, Over Expression, Staining, Control, Stable Transfection, Plasmid Preparation, Positive Control, Negative Control, shRNA, Knockdown

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) Relative (to day −2) Zeb1 mRNA levels in wild-type 3T3-L1 cells during differentiation, as measured by qPCR. ( B ) Raw Ct values for Pparg , Zeb1 as well as the housekeeping gene HPRT1 at days 0 and 4 of 3T3-L1 differentiation as measured by qPCR. ( C ) Pparg and Zeb1 mRNA levels in pre-adipocytes and adipocytes derived from publicly available data through ArrayExpress . ( D ) Protein levels (fmol/μg nuclear extract) of ZEB1 during 3T3-L1 differentiation (biological replicate of data shown in ). ( E ) Pparg2 and Cebpa mRNA levels after ZEB1 knockdown and overexpression at day 4 after adipogenic induction as measured by qPCR. ( F ) Fold-changes of expression levels of selected adipogenic factors in response to ZEB1 KD as measured by qPCR and RNA-seq at day 0 and day 2 of 3T3-L1 differentiation. The Pearson's correlation coefficient (r) is indicated. ( G ) Number of significantly up- and down-regulated genes after ZEB1 knockdown belonging to previously defined expression clusters (2/5/Low/1) . The typical expression pattern of genes in each cluster is sketched. Clusters are sorted by decreasing enrichment of up-regulated genes and corresponding p-values (chi-square test) are listed. ( H ) Changes in mRNA levels and POLII binding over gene bodies after ZEB1 and SMRT knockdown, respectively . The Spearman's ρ is indicated, showing a significantly negative correlation. ( I ) Percent of genes with dynamic SMRT binding during adipogenesis (red), of genes that lose/gain POLII upon SMRT KD (red), and of random genes (grey) that are significantly differentially expressed upon ZEB1 KD. Error bars depict the standard error of the mean. **p ≤ 0.01 and 0.01< *p ≤ 0.05. DOI: http://dx.doi.org/10.7554/eLife.03346.008

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Derivative Assay, Knockdown, Over Expression, Expressing, RNA Sequencing, Binding Assay

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) Protein levels (fmol/μg nuclear extract) of ZEB1 during 3T3-L1 differentiation (one representative biological replicate). ( B ) Pparg2 and Cebpa mRNA levels after ZEB1 knockdown and overexpression in un-induced 3T3-L1 pre-adipocytes as measured by qPCR. ( C ) Expression levels [ln(FPKM), ‘Materials and methods’] of mouse genes in ZEB1 KD vs. control cells at day 0 and day 2 after differentiation induction as measured by RNA-seq. Significantly up-regulated genes (FC ≥ 1.5, padj ≤ 0.01) are highlighted in blue, down-regulated genes in orange (FC ≤ 0.67, padj ≤ 0.01), significantly de-regulated follow-up TFs as well as adipogenic TFs such as PPARγ and C/EBPs are indicated in black. Bar plots represent the percentage of genes that are significantly up- or down-regulated. Representative enriched GeneGO pathway categories for up- or down-regulated genes are highlighted (complete results in ). ( D ) Number of significantly up- or down-regulated genes belonging to previously defined expression clusters (High/7/4/3) . The typical expression pattern of genes in each cluster as well as of representative members that are significantly down-regulated upon ZEB1 KD is sketched. Clusters are sorted by increasing enrichment of down-regulated genes and corresponding p-values (chi-square test) are listed. ( E ) Distribution of gene expression FCs at day 0 after ZEB1 KD for genes annotated as positive or negative regulators of adipogenesis . Error bars depict the standard error of the mean. **p ≤ 0.01 and 0.01 < *p ≤ 0.05. DOI: http://dx.doi.org/10.7554/eLife.03346.007

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Knockdown, Over Expression, Expressing, Control, RNA Sequencing, Gene Expression

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) ZEB1, C/EBPβ, POLII, and Control (CTRL) read density tracks at the Pparg locus. ( B ) Number of ZEB1-bound regions and of their proximal (≤ 10 kb) genes in 3T3-L1 cells. Distribution of ZEB1 binding with respect to genomic annotation (‘Materials and methods’). ( C ) De novo motif discovery using MEME and a 50 bp sequence centered on ZEB1 peak summits reveals the canonical ZEB1 motif (p = 10 −8 , ‘Materials and methods’) ( D ) Motif enrichment analysis in a 100 bp window around ZEB1 peak summits reveals 138 significantly enriched motifs (complete results in ). Highlighted here are motif names of the known early adipogenic regulators C/EBPβ, NFI, and AP1 factors as well as RUNX and SMAD3. ( E ) Peak overlap between ZEB1 and C/EBPβ (day 0) as well as AP1 factors (day 0, 4 hr) in 3T3-L1 cells. ( F ) Overview of ZEB1, C/EBPβ, AP1 proteins ATF2 and ATF7, POLII normalized ChIP-seq as well as DNase-seq (DHS) enrichments (‘Materials and methods’) in a 2 kb window around the summits of ZEB1 peaks that overlap C/EBPβ binding. Intervals are sorted based on decreasing ZEB1 enrichment. ( G ) Summarized results from mass spectrometry experiments of proteins that were identified when pulling down ZEB1 (complete results in ). DOI: http://dx.doi.org/10.7554/eLife.03346.009

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Control, Binding Assay, Sequencing, ChIP-sequencing, Mass Spectrometry

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) ZEB1 ChIP-qPCR validation of ChIP-seq data at 12 selected ZEB1 target sites and three negative control (CTRL) regions during 3T3-L1 adipogenesis. ( B ) Scatterplot and Spearman's ρ of ZEB1 ChIP-seq and ZEB1-HA ChIP-seq read counts inside genomic intervals defined by ZEB1 binding in pre-adipocytes. ( C ) Spearman correlations between read counts for replicate ZEB1 ChIP-seq (including ZEB1-HA) as well as publicly available POLII and DNase-seq data ( ; ) inside genomic intervals defined by ZEB1 binding in pre-adipocytes. ( D ) Distribution of randomly shifted ZEB1, C/EBPβ, and POLII peaks with respect to genomic annotation (‘Materials and methods’). ( E ) ZEB1 motif density at 800 bp centered on ZEB1 peak summits. ( F ) Fraction of ZEB1 and randomly shifted ZEB1 peaks (to show background values) that contain at least one or two, respectively, ZEB1, CACCTG (E-box), C/EBPβ, AP1, NFIC and SMAD3 motif hits (‘Materials and methods’). ( G ) Peak overlap between randomly shifted ZEB1 and C/EBPβ bound regions in 3T3-L1 pre-adipocytes. ( H ) Overview of ZEB1, ZEB1-HA, C/EBPβ, AP1 factors ATF2 and ATF7, POLII and H3K9AC normalized ChIP-seq as well as DNase-seq and control (CTRL) enrichments (‘Materials and methods’) in a 2 kb window around the summits of ZEB1 peaks. Intervals are sorted based on decreasing ZEB1 enrichment. ( I ) Mean C/EBPβ and AP1 complex proteins JUN and FOSL normalized (to total read number) ChIP-seq enrichments in human HepG2 and lymphoblastoid cell lines (LCLs) in a 8 kb window around the summits of ZEB1 peaks detected in LCLs. DOI: http://dx.doi.org/10.7554/eLife.03346.010

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: ChIP-qPCR, Biomarker Discovery, ChIP-sequencing, Negative Control, Binding Assay, Control

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) C/EBPβ expression (mRNA level) in stable C/EBPβ KD and control 3T3-L1 pre-adipocytes as measured by qPCR. ( B ) C/EBPβ ChIP-qPCR at 10 C/EBPβ-ZEB1, 6 ZEB1-only and six negative control regions according to our ZEB1 D0 ChIP-seq data and publicly available C/EBPβ ChIP-seq data . 5 out of 6 ZEB1-only regions also show C/EBPβ ChIP enrichment. *C/EBPβ-enriched regions ( C ) ZEB1 ChIP-qPCR at 9 C/EBPβ-ZEB1 regions as well as one ZEB1-only region (10) in C/EBPβ KD and control 3T3-L1 cells. * regions showing changes in ZEB1 enrichment after C/EBPβ KD ( D ) Zeb1 expression (mRNA level) in stable C/EBPβ KD and control 3T3-L1 cells as measured by qPCR. ( E ) POLII, ZEB1, and C/EBPβ read density tracks at the Zeb1 locus in 3T3-L1 pre-adipocytes. DOI: http://dx.doi.org/10.7554/eLife.03346.011

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Expressing, Control, ChIP-qPCR, Negative Control, ChIP-sequencing

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) Overview of ZEB1, C/EBPβ, RXRα, PPARγ, POLII normalized ChIP-seq as well as DNase-seq enrichments (‘Materials and methods’) in a 2 kb window around the summits of static ( padj ≥ 0.1 or FC < 2) and early-only (days-2 and 0 but not days 2 and 4; padj ≤ 0.1, FC ≥ 2) ZEB1-bound regions during 3T3-L1 differentiation. ( B ) Spearman correlations between read counts for ZEB1 ChIP-seq data at distinct adipogenic time points (days −2, 0, 2, and 4) inside genomic intervals defined by ZEB1 binding at any of these time points. ( C ) ZEB1 and POLII read density tracks at the Zbtb16 and Pparg loci during 3T3-L1 differentiation (days-2, 0, 2, and 4). Summarized genome-wide results are included in . ( D ) Differential motif discovery using MEME and a 50 bp sequence centered on summits of early-only vs static ZEB1 peaks reveals non-adipogenic motifs: RUNX1/2 and TEAD1 (p < 10 −5 , ‘Materials and methods’). ( E ) GREAT-based Gene Ontology enrichment analysis of genes associated with early-only vs static ZEB1 binding reveals terms associated with chemokine secretion and non-adipogenic functions. Full results are displayed in . ( F ) Number of significantly up- or down-regulated genes associated (≤10 kb) with at least one early-only or late-only ZEB1 bound region, respectively, belonging to previously defined expression clusters (1/Low/7/5) . The typical expression pattern of genes in each cluster is sketched. Clusters are sorted by increasing enrichment of late-only ZEB1-bound genes and corresponding p-values (chi-square test) are listed. Only clusters showing a highly significant p-value (p < 10 −10 ) are shown. ( G ) Fraction of genes associated with early-only, late-only, and static ZEB1 binding as well as the fraction of all genes significantly up (blue) and down (orange)-regulated after ZEB1 KD as measured at differentiation days 0 and 2. DOI: http://dx.doi.org/10.7554/eLife.03346.013

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: ChIP-sequencing, Binding Assay, Genome Wide, Sequencing, Expressing

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) ZEB1 and POLII read density tracks at the Klf15 locus during 3T3-L1 differentiation (days −2, 0, 2, and 4). Late-only bound regions are highlighted. ( B ) ZEB1, C/EBPβ, RXRα, PPARγ, POLII normalized ChIP (‘Materials and methods’) as well as DHS enrichments in a 2 kb window around the summits of late-only (days 2 and 4 but not days −2 and 0; padj ≤ 0.1, FC ≥ 2) ZEB1-bound regions during 3T3-L1 differentiation. ( C ) Differential motif discovery using MEME and a 50 bp sequence centered on summits of late-only vs. static ZEB1 peaks reveals adipogenic motifs: C/EBPα|C/EBPβ, NFIC and PPARG::RXR (p < 10 −3 , ‘Materials and methods’). ( D ) GREAT-based Gene Ontology enrichment analysis of genes associated with late-only vs. static ZEB1 binding reveals terms associated with fat cell differentiation and function (complete results in ). ( E ) Fraction of genes associated with late-only ZEB1 binding and fraction of all genes significantly up (blue) and down (orange)-regulated after ZEB1 KD as measured at differentiation day 2 (complete results in ). DOI: http://dx.doi.org/10.7554/eLife.03346.012

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Sequencing, Binding Assay, Cell Differentiation

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) Effect of ZEB1 knockdown on the adipogenic gene regulatory network. The network was assembled on the ‘Adipogenesis’ Pathway scaffold in WikiPathways as well as reviews and most recent publications of novel adipogenic regulators ( ; ; ). ZEB1 and C/EBPβ-bound regions that are proximal (within 500 bp) to TSSs or genes in pre-adipocytes are highlighted. *Significant ( padj ≤ 0.01) expression changes after ZEB1 KD at day 0 of 3T3-L1 differentiation. Other candidate adipogenic regulators identified by our high throughput screen are listed. ( B ) Expression changes of adipogenic commitment genes after ZEB1 KD in 3T3-L1 pre-adipocytes as measured by RNA-seq. Displayed genes are either part of the pre-adipocyte expression signature derived by or of the list of pre-adipocyte commitment factors compiled by . Lpl and Igfbp4 occur in both lists. Significant differences in expression ( padj ≤ 0.01) are marked in orange (FC ≤ 0.67) and blue (FC ≥ 1.5). Black-grey squares depict ZEB1 binding to TSSs or gene bodies. ( C ) Effect of ZEB1 knockdown and overexpression on C3H10T1/2 adipogenesis as assessed by Oil Red O staining at day 7 and day 8, respectively after induction. DOI: http://dx.doi.org/10.7554/eLife.03346.014

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Knockdown, Expressing, High Throughput Screening Assay, RNA Sequencing, Derivative Assay, Binding Assay, Over Expression, Staining

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) Effect of ZEB1 knockdown on the expression [log2 (FC) mRNA] of adipogenic ( Adipoq, Cebpa, Ebf1, Pparg2 ) and EMT ( Snai1, Snai2, Twist1 ) factors as measured by qPCR at day 8 after induction. ( B ) Effect of ZEB1 overexpression on the expression [log2 (FC) mRNA] of adipogenic ( Cebpa, Ebf1, Pparg2 ), pre-adipogenic ( Zfp423, Zfp521 ), and EMT ( Snai1, Twist1 ) factors as measured by qPCR at day 0 after induction of differentiation. ( C ) Western Blot showing PPARγ induction upon ZEB1 overexpression (visualized using anti-HA antibody) in C3H10T1/2 cells using PCNA as a normalization control. R1-3 indicates biological replicates. Error bars depict the standard error of the mean. **p ≤ 0.01 and 0.01 < *p ≤ 0.05. DOI: http://dx.doi.org/10.7554/eLife.03346.015

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Knockdown, Expressing, Over Expression, Western Blot, Control

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A and B ) Adipocyte differentiation in stromal vascular fraction (SVF) transplants from different donor mice (as indicated) fed a high-fat diet for 6 weeks . ( A ) Fat sections from representative samples of ZEB1-overexpressing and control SVF transplants stained with Hematoxylin (blue) and Eosin (pink). ( B ) Fat cell content of the transplanted SVF cells containing ZEB1 and control overexpression or knockdown constructs. Error bars depict the standard error of the mean. *p = 0.05, one-sided Wilcoxon-rank sum test. ( C ) Zeb1 mRNA expression normalized to 36B4 in human subcutaneous SVF of obese subjects plotted against percent ex vivo differentiated adipocytes of human subcutaneous SVF, subject fat mass, and adiponectin levels. Spearman's ρ is indicated, **p ≤ 0.01 and 0.01 < *p ≤ 0.05. DOI: http://dx.doi.org/10.7554/eLife.03346.016

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Control, Staining, Over Expression, Knockdown, Construct, Expressing, Ex Vivo

Journal: eLife

Article Title: Identification of the transcription factor ZEB1 as a central component of the adipogenic gene regulatory network

doi: 10.7554/eLife.03346

Figure Lengend Snippet: ( A ) Hematoxylin (blue) and Eosin (pink)-stained fat sections from representative samples of mouse ZEB1 knockdown transplants as well as the corresponding control (scrambled siRNA). ( B ) Number of nuclei per section (average over three sections) from ZEB1 overexpression, KD, or control SVF transplants. DOI: http://dx.doi.org/10.7554/eLife.03346.017

Article Snippet: A ZEB1 antibody (Santa Cruz, sc-25388, 10 μg per IP) and a rabbit isotype control IgG (Santa Cruz Biotechnology, Santa Cruz, CA, sc-8994, 10 μg per IP) was used for each time point.

Techniques: Staining, Knockdown, Control, Over Expression

Journal: BMC Genomics

Article Title: Histological and transcriptome-wide level characteristics of fetal myofiber hyperplasia during the second half of gestation in Texel and Ujumqin sheep

doi: 10.1186/1471-2164-12-411

Figure Lengend Snippet: Hierarchical clustering between the differentially expressed genes and individuals from the two sheep breeds . Clustering was performed using GeneSpring 10.0. A one-way analysis of variance was applied to two within-breed contrasts across developmental time. A pool of the differentially expressed probes from the two groups was used for system hierarchical clustering to clarify the transcriptome-wide similarities among all 31 individuals investigated.

Article Snippet: In the present study, we applied the first specialized and standardized transcriptome-wide sheep oligo DNA microarray (Agilent Sheep Gene Expression Microarray; Agilent Technologies, Santa Clara, CA, USA).

Techniques:

Journal: BMC Genomics

Article Title: Histological and transcriptome-wide level characteristics of fetal myofiber hyperplasia during the second half of gestation in Texel and Ujumqin sheep

doi: 10.1186/1471-2164-12-411

Figure Lengend Snippet: Validation of differential expression by quantitative PCR (qPCR)

Article Snippet: In the present study, we applied the first specialized and standardized transcriptome-wide sheep oligo DNA microarray (Agilent Sheep Gene Expression Microarray; Agilent Technologies, Santa Clara, CA, USA).

Techniques: Expressing, Real-time Polymerase Chain Reaction, Microarray

Journal: BMC Genomics

Article Title: Histological and transcriptome-wide level characteristics of fetal myofiber hyperplasia during the second half of gestation in Texel and Ujumqin sheep

doi: 10.1186/1471-2164-12-411

Figure Lengend Snippet: Abundance of primary functional clustering of differentially expressed genes . Counts of genes involved in muscles, lipids, and the immune system are represented by the ratio of functional categories relative to the total number of genes that exists in the microarray chip for each of those categories, respectively. The ratio illustrates the abundance of different clusters of differentially expressed genes between Texel and Ujumqin sheep at five developmental stages (70, 85, 100, 120, and 135 d of gestation).

Article Snippet: In the present study, we applied the first specialized and standardized transcriptome-wide sheep oligo DNA microarray (Agilent Sheep Gene Expression Microarray; Agilent Technologies, Santa Clara, CA, USA).

Techniques: Functional Assay, Microarray

Journal: Nature Communications

Article Title: Spatiotemporal dynamics of SETD5-containing NCoR–HDAC3 complex determines enhancer activation for adipogenesis

doi: 10.1038/s41467-021-27321-5

Figure Lengend Snippet: a Schematic illustration of enhancer states. Poised enhancer in embryonic stem cells (ESCs) is characterized by the presence of H3K4me1 and H3K27me3. Primed enhancer is characterized by the presence of the only H3K4me1, while active enhancer is characterized by the presence of both H3K4me1 and H3K27ac . b Schematic representation of mouse SETD5 protein and its mutants. c Retroviral expression of SETD5 in 3T3-L1 preadipocytes. Nuclear proteins from indicated 3T3-L1 preadipocytes were subjected to immunoblot (IB) analysis. Equal loading of the proteins was confirmed by blotting with anti-histone H3 (H3) antibody. d ORO staining of 3T3-L1 preadipocytes transduced with empty virus or SETD5. Preadipocytes were induced with MDI mixture or MDI mixture plus troglitazone (Tro). e Transcriptional changes of adipogenic genes in SETD5-transduced 3T3-L1 preadipocytes during adipogenesis by using a microarray. f , g siRNA-mediated knockdown of SETD5 in 3T3-L1 preadipocytes. Setd5 ( f ), Cebpa , and Pparg ( g ) mRNA expression was quantified by qPCR. h , i ORO staining of SETD5 knocked-down 3T3-L1 preadipocytes ( h ) or 3T3-L1 preadipocytes transduced with empty virus, SETD5, or mutants ( i) . Preadipocytes were induced with Dex ( h ), or MDI mixture ( i ). j Proteomics analysis of SETD5 interacting proteins. Nuclear proteins from WT-, ΔSET-, and Δ437-918-SETD5-transduced preadipocytes were subjected to immunoprecipitation with anti-V5 antibody followed by trypsin digestion and mass spectrometry. Color code: proteins lost (<2 −3 -fold) by deletion of a.a. 437–918 (blue); proteins lost by deletion of SET domain (orange); proteins not affected by deletion of a.a. 437–918 or SET domain (white). Proteins of PAF1 complex are highlighted in black. Proteins of APC/C complexes and RNF213 are highlighted in pink. k siRNA-mediated knockdown of NCoR2 in SETD5-transduced 3T3-L1 preadipocytes. Ncor2 mRNA expression was quantified by qPCR. l ORO staining of NCoR2 knocked-down, SETD5-transduced 3T3-L1 preadipocytes. Scale bar = 50 μm. c , f , g , k , l Representative of three independent experiments. f , g , k Data are mean ± SD of three technical replicates. f , g One-way ANOVA with Tukey’s multiple comparisons test. k Unpaired two-tailed Student’s t -test. ** p < 0.01. Source data are provided as a Source data file.

Article Snippet: Antibodies used: anti-H3K27ac mouse mAb 9E2H9 (5 μg of antibody/10 μg of DNA), anti-V5 mouse mAb (Thermo Scientific, R960-25, 5 μg of antibody/25 μg of DNA), anti-SETD5 mouse mAb IgG-F2104 (120 μg of antibody/40 μg of DNA), anti-H3K4me1 rabbit pAb (Abcam, ab8895, 2 μg of antibody/25 μg of DNA), anti-H3K4me3 rabbit pAb (Merck Millipore, 07-473, 3 μl of antibody/30 μg DNA), anti-NCoR2 rabbit pAb (Abcam, ab5802, 3 μg of antibody/25 μg DNA), anti-HDAC3 rabbit pAb (Abcam, ab7030, 25 μg of antibody/12.5 μg DNA), and anti-CBP rabbit mAb (Cell Signaling Technologies, 7425, clone D9B6, 4 μl of antibody/15 μg DNA).

Techniques: Expressing, Western Blot, Staining, Transduction, Microarray, Immunoprecipitation, Mass Spectrometry, Two Tailed Test

Journal: Nature Communications

Article Title: Spatiotemporal dynamics of SETD5-containing NCoR–HDAC3 complex determines enhancer activation for adipogenesis

doi: 10.1038/s41467-021-27321-5

Figure Lengend Snippet: a Immunoblot showing expression of endogenous SETD5 in 3T3-L1 preadipocytes. b Immunoblot showing expression of SETD5-V5, NCoR2, HDAC3, and CDC20 in SETD5-transduced 3T3-L1 preadipocytes. The graph shows the band intensity of SETD5-V5 and CDC20. c Cell cycle analysis of empty virus-transduced 3T3-L1 preadipocytes. The ratios of the cells at G 1 , S, or G 2 /M phase are shown. d Immunoblot showing expression of SETD5-V5 in SETD5-transduced 3T3-L1 preadipocytes treated with MDI and MG132. The graph shows band intensity of SETD5-V5. e Immunoblot showing ubiquitinated SETD5-V5. SETD5-transduced 3T3-L1 preadipocytes were treated with MDI and then MG132 at 9 h after MDI induction. Preadipocytes were subjected to immunoprecipitation using anti-V5 antibody and immunoblotting with anti-ubiquitin and anti-V5 antibodies. f Heatmap representing the abundance of APC/C subunits and RNF213 in SETD5-V5 immunoprecipitates. Spectrum count for each protein in proteomics analysis (Fig. ) was normalized by spectrum count for common region of SETD5 (a.a. 1 to a.a. 272 and a.a. 919 to a.a. 1441). g Expression of mRNAs of APC/C subunits during the early adipogenesis. mRNA expression of Cdc20 and Anapc2 in SETD5-V5-transduced preadipocytes were quantified by qPCR. h Immunoblot showing SETD5-V5 stability by the cycloheximide chase assay. 3T3-L1 preadipocytes transduced with SETD5-V5 were transfected with control siRNA or siRNA targeted to Anapc11 and induced for differentiation with MDI mixture. Preadipocytes were treated with cycloheximide (CHX) at 9 h after MDI induction and subjected to immunoblot analysis with anti-V5. Representative of three independent experiments. The graph shows regression analysis of SETD5-V5 protein stability after CHX treatment. Data are mean ± SEM of three independent experiments. Protein half-life (T 1/2 ) was calculated based on exponential decay curve fit to the average data at each time point. a , b , d Equal loading of the protein was confirmed by blotting with anti-HDAC1 ( a ) or anti-actin β ( b , d ) antibody. a , b, d, e, g Representative of three ( a , b ) or two ( d , e , g ) independent experiments. c , g Data are mean ± SD of three technical replicates. Source data are provided as a Source data file.

Article Snippet: Antibodies used: anti-H3K27ac mouse mAb 9E2H9 (5 μg of antibody/10 μg of DNA), anti-V5 mouse mAb (Thermo Scientific, R960-25, 5 μg of antibody/25 μg of DNA), anti-SETD5 mouse mAb IgG-F2104 (120 μg of antibody/40 μg of DNA), anti-H3K4me1 rabbit pAb (Abcam, ab8895, 2 μg of antibody/25 μg of DNA), anti-H3K4me3 rabbit pAb (Merck Millipore, 07-473, 3 μl of antibody/30 μg DNA), anti-NCoR2 rabbit pAb (Abcam, ab5802, 3 μg of antibody/25 μg DNA), anti-HDAC3 rabbit pAb (Abcam, ab7030, 25 μg of antibody/12.5 μg DNA), and anti-CBP rabbit mAb (Cell Signaling Technologies, 7425, clone D9B6, 4 μl of antibody/15 μg DNA).

Techniques: Western Blot, Expressing, Cell Cycle Assay, Immunoprecipitation, Transduction, Transfection

Journal: Nature Communications

Article Title: Spatiotemporal dynamics of SETD5-containing NCoR–HDAC3 complex determines enhancer activation for adipogenesis

doi: 10.1038/s41467-021-27321-5

Figure Lengend Snippet: a Genome-wide distribution of SETD5-V5 before (0 h) and 6 h of differentiation in 3T3-L1 preadipocytes. TTS, transcription termination site. b Venn diagram ( left ) and heatmap ( middle ) representations of genomic regions occupied by SETD5-V5, H3K4me1, and H3K27ac. Heatmap analysis showing ChIP-seq data for SETD5-V5, H3K4me1, and H3K27ac at a 20-kb region centered on SETD5-V5 binding regions. Pie chart ( right ) shows SETD5-V5 binding on H3K27 acetylated regions repressed by SETD5. c Genome browser representation for SETD5-V5, H3K4me1, H3K27ac, C/EBPβ, and C/EBPδ on Cebpa and Pparg genes in 3T3-L1 preadipocytes. Tracks 3–11 are the same data as Supplementary Fig. or Fig. . d ChIP-qPCR analysis of SETD5-V5 on Cebpa and Pparg genes during the early adipogenesis. 3T3-L1 preadipocytes transduced with SETD5-V5 were subjected to ChIP-qPCR analysis using anti-V5 antibody. Data are mean ± SEM (0, 6, 12, 48 h n = 4; 24 h n = 3; independent experiments). e Motif analysis of SETD5-V5 binding sites at 6 h of differentiation. Motif analysis was performed by Homer bioinformatics resources . p -values were calculated as one-tailed. f Co-immunoprecipitation assay showing the interaction of SETD5-V5 with C/EBPβ. 3T3-L1 preadipocytes transduced with SETD5-V5 at the indicated time of differentiation were cross-linked with ethylene glycerol bis(succinimidyl succinate) and subjected to immunoprecipitation using anti-C/EBPβ antibody. Immunoprecipitates were decrosslinked and examined by immunoblotting using anti-V5 and anti-C/EBPβ antibodies. Representative of two independent experiments. g ChIP-qPCR analysis of SETD5-V5 on Cebpa and Pparg genes under knockdown of C/EBPβ and C/EBPδ. 3T3-L1 preadipocytes transduced with SETD5-V5 were transfected with control siRNA or siRNA targeting to Cebpb and Cebpd and subjected to ChIP-qPCR analysis using anti-V5 antibody. Data are mean ± SEM of four independent experiments. d , g One-way ANOVA with Tukey’s multiple comparisons test. * p < 0.05; ** p < 0.01. Source data are provided as a Source data file.

Article Snippet: Antibodies used: anti-H3K27ac mouse mAb 9E2H9 (5 μg of antibody/10 μg of DNA), anti-V5 mouse mAb (Thermo Scientific, R960-25, 5 μg of antibody/25 μg of DNA), anti-SETD5 mouse mAb IgG-F2104 (120 μg of antibody/40 μg of DNA), anti-H3K4me1 rabbit pAb (Abcam, ab8895, 2 μg of antibody/25 μg of DNA), anti-H3K4me3 rabbit pAb (Merck Millipore, 07-473, 3 μl of antibody/30 μg DNA), anti-NCoR2 rabbit pAb (Abcam, ab5802, 3 μg of antibody/25 μg DNA), anti-HDAC3 rabbit pAb (Abcam, ab7030, 25 μg of antibody/12.5 μg DNA), and anti-CBP rabbit mAb (Cell Signaling Technologies, 7425, clone D9B6, 4 μl of antibody/15 μg DNA).

Techniques: Genome Wide, ChIP-sequencing, Binding Assay, Transduction, One-tailed Test, Co-Immunoprecipitation Assay, Immunoprecipitation, Western Blot, Transfection

Journal: Nature Communications

Article Title: Spatiotemporal dynamics of SETD5-containing NCoR–HDAC3 complex determines enhancer activation for adipogenesis

doi: 10.1038/s41467-021-27321-5

Figure Lengend Snippet: a Venn diagram ( left ) and heatmap ( right ) representation of genomic regions occupied by SETD5-V5, NCoR, and HDAC3. Approximately 60% of NCoR and 71% of HDAC3 genomic binding regions were co-occupied by SETD5-V5. Heatmap analysis showing ChIP-seq data for SETD5-V5, NCoR, and HDAC3 at a 20-kb region centered on SETD5-V5 binding region. b Genome browser representation for SETD5-V5, NCoR, HDAC3, and H3K27ac on Cebpa and Pparg genes in 3T3-L1 preadipocytes. Tracks 1-2 and 7-9 are the same data as Fig. . c , d ChIP-qPCR analyses of NCoR2 ( c ) and HDAC3 ( d ) on Cebpa and Pparg genes during the early adipogenesis. 3T3-L1 preadipocytes transduced with control empty virus were subjected to ChIP-qPCR analyses using anti-NCoR2 or anti-HDAC3 antibody. Data are mean ± SEM (0, 48 h n = 5; 6 h of NCoR2 n = 4; 6 h of HDAC3 n = 5; 12, 24 h n = 3; independent experiments). e ChIP-qPCR analysis of SETD5-V5 on Cebpa and Pparg genes under knockdown of ANAPC11 or CDC20. 3T3-L1 preadipocytes transduced with SETD5-V5 were transfected with control siRNA or siRNA targeting to Anapc11 or Cdc20 and subjected to ChIP-qPCR analysis at 6 h and 24 h of differentiation using anti-V5 antibody. ChIP signal was presented as relative SETD5 recruitment. Data are mean ± SD of four technical replicates. f Schematic model of SETD5-NCoR-HDAC3 complex formation and the loss of SETD5 on enhancers during the transition from primed to active states. Heatmap shows the degree of recruitment of SETD5, NCoR2, and HDAC3 to Cebpa and Pparg enhancers (based on Figs. d, 5c, and 5d). Darker color indicates more recruitment. a, b ChIP-seq for NCoR and HDAC3 was from the previously published paper . c – e One-way ANOVA with Tukey’s multiple comparisons test. * p < 0.05; ** p < 0.01. Source data are provided as a Source data file.

Article Snippet: Antibodies used: anti-H3K27ac mouse mAb 9E2H9 (5 μg of antibody/10 μg of DNA), anti-V5 mouse mAb (Thermo Scientific, R960-25, 5 μg of antibody/25 μg of DNA), anti-SETD5 mouse mAb IgG-F2104 (120 μg of antibody/40 μg of DNA), anti-H3K4me1 rabbit pAb (Abcam, ab8895, 2 μg of antibody/25 μg of DNA), anti-H3K4me3 rabbit pAb (Merck Millipore, 07-473, 3 μl of antibody/30 μg DNA), anti-NCoR2 rabbit pAb (Abcam, ab5802, 3 μg of antibody/25 μg DNA), anti-HDAC3 rabbit pAb (Abcam, ab7030, 25 μg of antibody/12.5 μg DNA), and anti-CBP rabbit mAb (Cell Signaling Technologies, 7425, clone D9B6, 4 μl of antibody/15 μg DNA).

Techniques: Binding Assay, ChIP-sequencing, Transduction, Transfection

Journal: Nature Communications

Article Title: Spatiotemporal dynamics of SETD5-containing NCoR–HDAC3 complex determines enhancer activation for adipogenesis

doi: 10.1038/s41467-021-27321-5

Figure Lengend Snippet: a Venn diagram ( left ) and heatmap ( right ) representation of genomic regions occupied by SETD5-V5 and p300. Approximately 64% of p300 genomic binding regions were co-occupied by SETD5-V5. Heatmap analysis showing ChIP-seq data for SETD5-V5 and p300 at a 20-kb region centered on SETD5-V5 binding region. b Genome browser representation for SETD5-V5, p300, and H3K27ac on Cebpa and Pparg genes in 3T3-L1 preadipocytes. Tracks 1-2 and 5-7 are the same data as Fig. . c , d , e ChIP-qPCR analyses of CBP on Cebpa and Pparg genes during the early adipogenesis. 3T3-L1 preadipocytes transduced with control empty virus or SETD5 were subjected to ChIP-qPCR analyses using anti-CBP antibody c . 3T3-L1 preadipocytes transduced with control empty virus, wild-type SETD5, or Δ437-918 mutant were subjected to ChIP-qPCR analysis using anti-CBP antibody d . 3T3-L1 preadipocytes transfected with control siRNA or siRNA targeting to Setd5 were subjected to ChIP-qPCR analysis using anti-CBP antibody e . f Model of enhancer transition from primed to active state during adipogenesis. Heatmap shows the degree of recruitment of SETD5, NCoR2, HDAC3, and CBP to Cebpa and Pparg enhancers and H3K27 acetylation (based on Figs. d, c, d, 6c, Supplementary Fig. ). Darker color indicates more recruitment and acetylation. (i) SETD5 forms a complex with NCoR-HDAC3 and keeps a hypoacetylation state by restricting the recruitment of CBP to primed enhancers. (ii) SETD5 in NCoR-HDAC complex on primed enhancers is ubiquitinated and degraded by APC/C. (iii) Degradation of SETD5 from NCoR-HDAC3 co-repressor complex allows the unrestricted recruitment of CBP and H3K27 acetylation and transit enhancers from primed to active state. a , b ChIP-seq data for p300 were from the previously published paper . c Data are mean ± SEM (0, 6, 12 h n = 3: 24 h n = 4; 48 h n = 5; independent experiments). Unpaired two-tailed Student’s t -test. d , e Representative of two independent experiments. Data are mean ± SD of three technical replicates. One-way ANOVA with Tukey’s multiple comparisons test. * p < 0.05; ** p < 0.01. Source data are provided as a Source data file.

Article Snippet: Antibodies used: anti-H3K27ac mouse mAb 9E2H9 (5 μg of antibody/10 μg of DNA), anti-V5 mouse mAb (Thermo Scientific, R960-25, 5 μg of antibody/25 μg of DNA), anti-SETD5 mouse mAb IgG-F2104 (120 μg of antibody/40 μg of DNA), anti-H3K4me1 rabbit pAb (Abcam, ab8895, 2 μg of antibody/25 μg of DNA), anti-H3K4me3 rabbit pAb (Merck Millipore, 07-473, 3 μl of antibody/30 μg DNA), anti-NCoR2 rabbit pAb (Abcam, ab5802, 3 μg of antibody/25 μg DNA), anti-HDAC3 rabbit pAb (Abcam, ab7030, 25 μg of antibody/12.5 μg DNA), and anti-CBP rabbit mAb (Cell Signaling Technologies, 7425, clone D9B6, 4 μl of antibody/15 μg DNA).

Techniques: Binding Assay, ChIP-sequencing, Transduction, Mutagenesis, Transfection, Two Tailed Test

Journal: Nature Communications

Article Title: Spatiotemporal dynamics of SETD5-containing NCoR–HDAC3 complex determines enhancer activation for adipogenesis

doi: 10.1038/s41467-021-27321-5

Figure Lengend Snippet: a Transplantation of 3T3-L1 preadipocytes into nude mice. 3T3-L1 preadipocytes transduced with control empty virus or SETD5-V5 were cultured for two days with MDI cocktail. Subsequently, harvested cells were implanted with HydroMatrix and injected into the subcutaneous region on the upper or lower back of nude mice. b, c Two weeks after transplantation, mice were dissected, and isolated transplanted fats were subjected to haematoxylin and eosin (H&E) staining ( b ) and immunohistochemistry using anti-perilipin-1 antibody ( c ). Representative images of transplants from the lower back are shown. d Quantitation of perilipin-1 positive adipocytes. Data are mean ± SE in the section of transplants from empty virus transduced ( n = 5) or SETD5 transduced ( n = 3) preadipocytes Unpaired two-tailed Student’s t -test. ** p < 0.01. Source data are provided as a Source data file.

Article Snippet: Antibodies used: anti-H3K27ac mouse mAb 9E2H9 (5 μg of antibody/10 μg of DNA), anti-V5 mouse mAb (Thermo Scientific, R960-25, 5 μg of antibody/25 μg of DNA), anti-SETD5 mouse mAb IgG-F2104 (120 μg of antibody/40 μg of DNA), anti-H3K4me1 rabbit pAb (Abcam, ab8895, 2 μg of antibody/25 μg of DNA), anti-H3K4me3 rabbit pAb (Merck Millipore, 07-473, 3 μl of antibody/30 μg DNA), anti-NCoR2 rabbit pAb (Abcam, ab5802, 3 μg of antibody/25 μg DNA), anti-HDAC3 rabbit pAb (Abcam, ab7030, 25 μg of antibody/12.5 μg DNA), and anti-CBP rabbit mAb (Cell Signaling Technologies, 7425, clone D9B6, 4 μl of antibody/15 μg DNA).

Techniques: Transplantation Assay, Transduction, Cell Culture, Injection, Isolation, Staining, Immunohistochemistry, Quantitation Assay, Two Tailed Test

Journal: Nature Communications

Article Title: GATA3 induces human T-cell commitment by restraining Notch activity and repressing NK-cell fate

doi: 10.1038/ncomms11171

Figure Lengend Snippet: ( a ) Flow cytometry analysis of CB CD34 + lin − precursors after 18 days of coculture on OP9 stromal cells expressing different Notch ligands, as indicated above the dot plots, and in the presence of IL7, SCF, FLT3L and IL15. Dot plots show analysis of CD56 versus CD5 staining (upper plots) and HLA-DR versus CD7 staining (lower plots, gated on CD5 + CD56 − cells). NK-lineage cells are identified as CD56 + CD5 − and T-lineage cells as CD5 + CD7 + CD56 − HLA-DR − . ( b ) Graphs show the kinetics of the CD56 + CD5 − NK cell numbers generated on OP9 stromal cells expressing different Notch ligands at indicated time points. Data shows average of three independent experiments and error bars indicate s.e.m.

Article Snippet: Next, the depleted cells were stained with CD4-PE, CD34-FITC (Miltenyi, 130-081-001), CD3-FITC (Miltenyi, 130-080-401), CD8-FITC (Miltenyi, 130-080-601) and CD28-APC (Miltenyi, 130-092-923) and CD4 + CD34 − CD3 − CD8 − CD28 − and CD4 + CD34 − CD3 − CD8 − CD28 + pre and post β-selected thymocytes were sorted.

Techniques: Flow Cytometry, Expressing, Staining, Generated

Journal: Nature Communications

Article Title: GATA3 induces human T-cell commitment by restraining Notch activity and repressing NK-cell fate

doi: 10.1038/ncomms11171

Figure Lengend Snippet: ( a ) Quantitative PCR of GATA3 , DTX1 , HES1 and TCF7 expression during early human T cell development in different cell populations as indicated. Data shows the average expression in 3–4 independent samples, and error bars indicate s.e.m. ( b ) Flow cytometry analysis of control and TCF7 -transduced CB CD34 + lin − precursors in OP9-GFP or OP9-DLL1 cocultures in the presence of IL7, SCF and FLT3L, showing the development of CD5 + CD7 + early T cell precursors after 6 days of coculture. ( c ) Absolute numbers of CD5 + CD7 + T precursor cells developed in corresponding cultures from b . Data shows average of three independent experiments and error bars indicate s.e.m. ( d ) Quantitative real-time RT-PCR gene expression analysis of Notch and T cell-related genes in control (white and black bars) or TCF7 (grey and red bars) transduced human CB CD34 + after 2 days of coculture on OP9-GFP (white and grey bars) or OP9-DLL1 (black and red bars), relative to ACTB levels and relative to one control-transduced sample cultured on OP9-DLL1. Data shows average expression in two independent samples. Error bars indicate s.e.m. ( e ) Flow cytometry analysis of control or TCF7 -transduced CD34 + lin − precursors cells in the presence of IL7, SCF, FLT3L and IL15 on OP9-GFP or OP9-DLL1 stromal cells after 13 days of coculture. ( f ) Corresponding absolute number of CD56 + CD5 − NK cells in cocultures from e . Data shows average of three independent experiments and error bars indicate s.e.m.

Article Snippet: Next, the depleted cells were stained with CD4-PE, CD34-FITC (Miltenyi, 130-081-001), CD3-FITC (Miltenyi, 130-080-401), CD8-FITC (Miltenyi, 130-080-601) and CD28-APC (Miltenyi, 130-092-923) and CD4 + CD34 − CD3 − CD8 − CD28 − and CD4 + CD34 − CD3 − CD8 − CD28 + pre and post β-selected thymocytes were sorted.

Techniques: Real-time Polymerase Chain Reaction, Expressing, Flow Cytometry, Control, Quantitative RT-PCR, Gene Expression, Cell Culture

Journal: Nature Communications

Article Title: GATA3 induces human T-cell commitment by restraining Notch activity and repressing NK-cell fate

doi: 10.1038/ncomms11171

Figure Lengend Snippet: ( a ) Flow cytometry analysis of control and GATA3 -transduced CB CD34 + lin − precursor cells in OP9-GFP and OP9-DLL1 cocultures in the presence of IL7, SCF and FLT3L, showing the development of CD5 + CD7 + T precursor cells after 6 days of coculture. ( b ) Graphs show absolute number of CD5 + CD7 + cells generated in corresponding cultures shown in a . Data shows the average of seven independent experiments and error bars indicate s.e.m. * P <0.05 (non-parametric paired Wilcoxon test) ( c ) Quantitative PCR analysis of changes in gene expression in control (white and black bars) and GATA3 (grey and blue bars) transduced CB CD34 + lin − precursors after 2 day coculture on OP9-GFP (white and grey bars) and OP9-DLL1 (black and blue bars). Data shows the average expression of two independent experiments, relative to GAPDH levels and relative to one control-transduced sample cultured on OP9-DLL1. Error bars indicate s.e.m. ( d ) Flow cytometry analysis of control and GATA3 -transduced CB CD34 + lin − precursor cells in OP9-GFP or OP9-DLL1 cocultures in the presence of IL7, SCF, FLT3L and IL15, showing the development of CD56 + NK cells or CD5 + T precursor cells after 13 days of coculture. ( e ) Graphs show absolute numbers of CD56 + CD5 − NK cells generated in corresponding cultures shown in d . Data shows the average of seven independent experiments and error bars indicate s.e.m. * P <0.05 (non-parametric paired Wilcoxon test).

Article Snippet: Next, the depleted cells were stained with CD4-PE, CD34-FITC (Miltenyi, 130-081-001), CD3-FITC (Miltenyi, 130-080-401), CD8-FITC (Miltenyi, 130-080-601) and CD28-APC (Miltenyi, 130-092-923) and CD4 + CD34 − CD3 − CD8 − CD28 − and CD4 + CD34 − CD3 − CD8 − CD28 + pre and post β-selected thymocytes were sorted.

Techniques: Flow Cytometry, Control, Generated, Real-time Polymerase Chain Reaction, Gene Expression, Expressing, Cell Culture

Journal: Nature Communications

Article Title: GATA3 induces human T-cell commitment by restraining Notch activity and repressing NK-cell fate

doi: 10.1038/ncomms11171

Figure Lengend Snippet: ( a ) Quantitative PCR of GATA3 , DTX1 , HES1 and TCF7 expression in different stages of in vitro generated T cell precursors from CB CD34 + lin − HPCs after 7 days of OP9-DLL4 coculture. Data shows the average expression in 3–4 independent samples on a log scale and erros bars indicate s.e.m. ( b , c ) GSEA shows a significant enrichment of the top 500 Notch-dependent genes in human CD34 + thymocytes in the set of genes higher expressed in ( b ) uncommitted CD34 + CD1a − versus CD34 + CD1a + committed T-cell precursors , and genes expressed higher in ( c ) control versus GATA3-transduced CD34 + thymocytes as determined by microarray after 48 h of transduction. ( d ) Flow cytometry analysis of control and GATA3 -transduced CD34 + CD1 − uncommitted thymocytes in OP9-DLL1 cocultures with addition of 0 or 1 μM GSI and in the presence of IL7, SCF and FLT3L, showing the development of CD4 + CD8β + DP thymocytes after 6 days of coculture. ( e ) Graph show absolute number of CD4 + CD8β + DP thymocytes, generated in corresponding cultures shown in d . Data shows the average of four independent experiments and errors bars show s.e.m. * P <0.05 (non-parametric paired Wilcoxon test) ( f ) Flow cytometry analysis of control and TCF1 transduced CD34 + CD1 − uncommitted thymocytes in OP9-DLL1 cocultures in the presence of IL7, SCF and FLT3L, showing the development of CD4 + CD8β + DP thymocytes after 19 days of coculture. ( g ) Graph shows absolute number of CD4 + CD8β + DP thymocytes, generated in corresponding cultures shown in a .

Article Snippet: Next, the depleted cells were stained with CD4-PE, CD34-FITC (Miltenyi, 130-081-001), CD3-FITC (Miltenyi, 130-080-401), CD8-FITC (Miltenyi, 130-080-601) and CD28-APC (Miltenyi, 130-092-923) and CD4 + CD34 − CD3 − CD8 − CD28 − and CD4 + CD34 − CD3 − CD8 − CD28 + pre and post β-selected thymocytes were sorted.

Techniques: Real-time Polymerase Chain Reaction, Expressing, In Vitro, Generated, Control, Microarray, Transduction, Flow Cytometry

Journal: Nature Communications

Article Title: GATA3 induces human T-cell commitment by restraining Notch activity and repressing NK-cell fate

doi: 10.1038/ncomms11171

Figure Lengend Snippet: ( a ) Flow cytometric analysis of control and GATA3 -transduced CD34 + CD1 − uncommitted thymocytes in OP9-GFP or OP9-DLL1 cocultures in the presence of IL7, SCF, FLT3L and IL15, showing the development of CD56 + NK cells or CD5 + T precursor cells after 13 days of coculture. Absolute numbers of CD56 + CD5 − NK cells are depicted in b . Data shows the average of seven independent experiments and errors bars show s.e.m. * P <0.05 (non-parametric paired Wilcoxon test) ( c ) Flow cytometry analysis of control and TCF7 -transduced CD34 + CD1 − uncommitted thymocytes in OP9-GFP or OP9-DLL1 cocultures in the presence of IL7, SCF, FLT3L and IL15, showing the development of CD56 + NK cells or CD5 + T precursor cells after 13 days of coculture. Absolute numbers of CD56 + CD5 − NK cells are depicted in d . ( e ) Double log scatter plot showing genes with significant differential expression between GATA3 and control-transduced CD34 + thymocytes. Data shows significant differential expressed genes over three independent experiments. Red and blue dots represent the significant differentially expressed genes (adjusted P value <0.05). ( f ) GSEA shows a significant enrichment of genes upregulated following GATA3 overexpression in thymic CD34 + progenitors in the set of genes higher expressed in control shRNA versus GATA3 shRNA transduced Jurkat cells ( g ) Quantitative PCR analysis of changes in gene expression in control and GATA3 -transduced CD34 + thymocytes after 2 day coculture on OP9-DLL1. Data shows the average expression of two independent experiments, relative to ACTB levels and relative to one control-transduced sample cultured on OP9-DLL1. Error bars indicate s.e.m. * P <0.05 (paired Student's t -test) ( h ) GSEA shows a significant enrichment for CD56 bright human NK cells signature genes in control versus GATA3-transduced human CD34 + thymocytes.

Article Snippet: Next, the depleted cells were stained with CD4-PE, CD34-FITC (Miltenyi, 130-081-001), CD3-FITC (Miltenyi, 130-080-401), CD8-FITC (Miltenyi, 130-080-601) and CD28-APC (Miltenyi, 130-092-923) and CD4 + CD34 − CD3 − CD8 − CD28 − and CD4 + CD34 − CD3 − CD8 − CD28 + pre and post β-selected thymocytes were sorted.

Techniques: Control, Flow Cytometry, Quantitative Proteomics, Over Expression, shRNA, Real-time Polymerase Chain Reaction, Gene Expression, Expressing, Cell Culture

Journal: Nature Communications

Article Title: GATA3 induces human T-cell commitment by restraining Notch activity and repressing NK-cell fate

doi: 10.1038/ncomms11171

Figure Lengend Snippet: ( a ) Flow cytometry analysis of control shRNA and GATA3 shRNA transduced CD34 + CB progenitors in 2-week OP9-DLL1 cocultures in the presence of IL7, SCF, FLT3L and IL15. ( b ) Number of CD56 + CD5 − NK cells developed in corresponding cultures from a . ( c ) Number of CD5 + CD7 + T-lineage precursors developed in corresponding cultures from a . ( d ) T/NK cell ratio from cultures depicted in a . Data shows the average of six independent experiments and error bars indicate s.e.m. * P <0.05 (non-parametric paired Wilcoxon test) ( e ) Flow cytometry analysis of control shRNA and GATA3 shRNA transduced CD34 + CB progenitors in 2-week OP9-DLL1 cocultures in the presence of IL7, SCF and FLT3L. ( f ) Number of CD56 + NK cells developed in corresponding cultures from e . Data shows the average of four independent experiments and error bars indicate s.e.m. ( g ) Double log scatter plot showing genes with significant differential expression between shRNA GATA3 and shRNA control-transduced RPMI-8402 cells. Data shows significant differential expressed genes over two independent experiments. Red and blue dots represent the significant differentially expressed genes (adjusted P value<0.05). ( h ) GSEA shows a significant enrichment for genes that are upregulated following GATA3 shRNA-mediated knockdown in Notch-dependent genes in OP9-DLL1 versus OP9-GFP cocultured thymocytes ( i ) Quantitative PCR for GATA3 expression in various cell subsets from thymus (CT): CD56 + NK cells, CD34 + CD1 − uncommitted and CD34 + CD1 + committed progenitors and DP thymocytes. Data shows average expression, relative to ACTB , of 4–6 independent samples and error bars indicate s.e.m.

Article Snippet: Next, the depleted cells were stained with CD4-PE, CD34-FITC (Miltenyi, 130-081-001), CD3-FITC (Miltenyi, 130-080-401), CD8-FITC (Miltenyi, 130-080-601) and CD28-APC (Miltenyi, 130-092-923) and CD4 + CD34 − CD3 − CD8 − CD28 − and CD4 + CD34 − CD3 − CD8 − CD28 + pre and post β-selected thymocytes were sorted.

Techniques: Flow Cytometry, Control, shRNA, Quantitative Proteomics, Knockdown, Real-time Polymerase Chain Reaction, Expressing

Journal: Nature Communications

Article Title: GATA3 induces human T-cell commitment by restraining Notch activity and repressing NK-cell fate

doi: 10.1038/ncomms11171

Figure Lengend Snippet: ( a ) GATA3 binding motif analysis following GATA3 ChIP-sequencing (ChIP-Seq) in total human thymocytes. ( b ) Distribution of GATA3 peaks around the transcriptional start site (TSS) of protein coding genes. ( c ) GSEA shows significant enrichment of the top 500 ChIP-Seq peaks in the gene set that is significantly higher expressed in control shRNA versus GATA3 shRNA transduced Jurkat cells showing high correlation between GATA3 binding and GATA3-dependent regulation. ( d ) GATA3 binding at selected gene loci that are associated with T cell development. ( e ) GATA3 binding at selected gene loci that are associated with NK cell development. ( f ) Top Venn diagram shows overlap between Notch dependent and Notch1 bound loci for genes that show significant downregulation at the CD34 + CD1a − to CD34 + CD1a + T-lineage commitment stage. The Venn diagram at the bottom shows overlap between Notch-regulated and GATA-3 regulated genes (bottom).

Article Snippet: Next, the depleted cells were stained with CD4-PE, CD34-FITC (Miltenyi, 130-081-001), CD3-FITC (Miltenyi, 130-080-401), CD8-FITC (Miltenyi, 130-080-601) and CD28-APC (Miltenyi, 130-092-923) and CD4 + CD34 − CD3 − CD8 − CD28 − and CD4 + CD34 − CD3 − CD8 − CD28 + pre and post β-selected thymocytes were sorted.

Techniques: Binding Assay, ChIP-sequencing, Control, shRNA

Journal: Nature Communications

Article Title: GATA3 induces human T-cell commitment by restraining Notch activity and repressing NK-cell fate

doi: 10.1038/ncomms11171

Figure Lengend Snippet: ( a ) GATA3 binding at the DTX1 locus and the neighbouring RASAL1 and OAS2 loci. ( b ) Double log scatter plot showing similar GATA3-mediated repression of genes at the DTX1 locus in GATA3 versus control-transduced CD34 + thymocytes. Data shows the average of three independent experiments. Red dots represent the significant differentially expressed genes (adjusted P value <0.05). ( c ) Quantitative PCR for DTX1 expression in thymus (CT) and adult bone marrow (ABM) CD56 + NK cells, compared with thymus-derived CD34 + CD1 − uncommitted and CD34 + CD1 + committed progenitors and DP thymocytes. Data shows average expression, relative to ACTB , of 3–6 independent samples and error bars indicate s.e.m. ( d ) Flow cytometry analysis of control shRNA and DTX1 shRNA transduced CD34 + lin − CB progenitors in 2-week OP9-DLL1 cocultures in the presence of IL7, SCF, FLT3L and IL15. Number of NK cells ( e ) and T cells ( f ) developed in corresponding cultures from d . Data shows the average of four independent experiments with two different DTX1 shRNAs and error bars indicate s.e.m. * P <0.05 (non-parametric paired Wilcoxon test) ( g ) Flow cytometry analysis of control shRNA and DTX1 shRNA transduced CD34 + CD1 − uncommitted thymocytes in 2-week OP9-GFP co-cultures in the presence of IL7, SCF, FLT3L and IL15. ( h ) Number of NK cells developed in corresponding cultures from g . Data shows the average of twp independent experiments with two different DTX1 shRNAs and error bars indicate s.e.m. * P <0.05 (paired t -test) ( i ) Flow cytometry analysis of control and DTX1 transduced CD34 + CD1 − uncommitted thymocytes in 2-week OP9-DLL1 co-cultures in the presence of IL7, SCF, FLT3L and IL15. Number of NK cells ( j ) and T cells ( k ) developed in corresponding cultures from i . Data shows the average of five independent experiments and error bars indicate s.e.m. * P <0.05 (non-parametric paired Wilcoxon test).

Article Snippet: Next, the depleted cells were stained with CD4-PE, CD34-FITC (Miltenyi, 130-081-001), CD3-FITC (Miltenyi, 130-080-401), CD8-FITC (Miltenyi, 130-080-601) and CD28-APC (Miltenyi, 130-092-923) and CD4 + CD34 − CD3 − CD8 − CD28 − and CD4 + CD34 − CD3 − CD8 − CD28 + pre and post β-selected thymocytes were sorted.

Techniques: Binding Assay, Control, Real-time Polymerase Chain Reaction, Expressing, Derivative Assay, Flow Cytometry, shRNA

Journal: Cancer cell

Article Title: MUTANT EZH2 INDUCES A PRE-MALIGNANT LYMPHOMA NICHE BY REPROGRAMMING THE IMMUNE RESPONSE

doi: 10.1016/j.ccell.2020.04.004

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: Rabbit H3K27me3 (for ChIP) , Cell Signaling , Cat# 9733.

Techniques: Control, Blocking Assay, Recombinant, Adjuvant, Plasmid Preparation, Binding Assay, Staining, RNA Library Preparation, MicroChIP Assay, Sequencing, Microarray, Knock-In, Software, Gene Expression, Targeted Proteomics