Project description:Transcription factors (TFs) are fundamental controllers of cellular regulation that function in a complex and combinatorial manner. Accurate identification of a transcription factor's targets is essential to understanding the role that factors play in disease biology. However, due to a high false positive rate, identifying coherent functional target sets is difficult. We have created an improved mapping of targets by integrating ChIP-Seq data with 423 functional modules derived from 9,395 human expression experiments. We identified 5,002 TF-module relationships, significantly improved TF target prediction, and found 30 high-confidence TF-TF associations, of which 14 are known. Importantly, we also connected TFs to diseases through these functional modules and identified 3,859 significant TF-disease relationships. As an example, we found a link between MEF2A and Crohn's disease, which we validated in an independent expression dataset. These results show the power of combining expression data and ChIP-Seq data to remove noise and better extract the associations between TFs, functional modules, and disease.
Project description:BACKGROUND: Histone modifications play an important role in gene regulation. Acetylation of histone 3 lysine 9 (H3K9ac) is generally associated with transcription initiation and unfolded chromatin, thereby positively influencing gene expression. Deep sequencing of the 5' ends of gene transcripts using DeepCAGE delivers detailed information about the architecture and expression level of gene promoters. The combination of H3K9ac ChIP-chip and DeepCAGE in a myeloid leukemia cell line (THP-1) allowed us to study the spatial distribution of H3K9ac around promoters using a novel clustering approach. The promoter classes were analyzed for association with relevant genomic sequence features. RESULTS: We performed a clustering of 4,481 promoters according to their surrounding H3K9ac signal and analyzed the clustered promoters for association with different sequence features. The clustering revealed three groups with major H3K9ac signal upstream, centered and downstream of the promoter. Narrow single peak promoters tend to have a concentrated activity of H3K9ac in the upstream region, while broad promoters tend to have a concentrated activity of H3K9ac and RNA polymerase II binding in the centered and downstream regions. A subset of promoters with high gene expression level, compared to subsets with low and medium gene expression, shows dramatic increase in H3K9ac activity in the upstream cluster only; this may indicate that promoters in the centered and downstream clusters are predominantly regulated at post-initiation steps. Furthermore, the upstream cluster is depleted in CpG islands and more likely to regulate un-annotated genes. CONCLUSIONS: Clustering core promoters according to their surrounding acetylation signal is a promising approach for the study of histone modifications. When examining promoters clustered into groups according to their surrounding H3K9 acetylation signal, we find that the relative localization and intensity of H3K9ac is very specific depending on characteristic sequence features of the promoter. Experimental data from DeepCAGE and ChIP-chip experiments using undifferentiated (monocyte) and differentiated (macrophage) THP-1 cells leads us to the same conclusions.
Project description:We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the original genome-aligned sequence reads. Comparison with a QCi database for >28,000 ChIP-seq assays were used to attribute quality grades (ranging from 'AAA' to 'DDD') to a given dataset. In the present report we used the numerical QC system to assess the factors influencing the quality of ChIP-seq assays, including the nature of the target, the sequencing depth and the commercial source of the antibody. We have used this approach specifically to certify mono and polyclonal antibodies obtained from Active Motif directed against the histone modification marks H3K4me3, H3K27ac and H3K9ac for ChIP-seq. The antibodies received the grades AAA to BBC ( www.ngs-qc.org). We propose to attribute such quantitative grading of all antibodies attributed with the label "ChIP-seq grade".
Project description:The microarray dataset attached to this report is related to the research article with the title: "A genomic approach to susceptibility and pathogenesis leads to identifying potential novel therapeutic targets in androgenetic alopecia" (Dey-Rao and Sinha, 2017) . Male-pattern hair loss that is induced by androgens (testosterone) in genetically predisposed individuals is known as androgenetic alopecia (AGA). The raw dataset is being made publicly available to enable critical and/or extended analyses. Our related research paper utilizes the attached raw dataset, for genome-wide gene-expression associated investigations. Combined with several in silico bioinformatics-based analyses we were able to delineate five strategic molecular elements as potential novel targets towards future AGA-therapy.
Project description:We present One Hand Clapping (OHC), a method for the detection of condition-specific interactions between transcription factors (TFs) from genome-wide gene activity measurements. OHC is based on a mapping between transcription factors and their target genes. Given a single case-control experiment, it uses a linear regression model to assess whether the common targets of two arbitrary TFs behave differently than expected from the genes targeted by only one of the TFs. When applied to osmotic stress data in S. cerevisiae, OHC produces consistent results across three types of expression measurements: gene expression microarray data, RNA Polymerase II ChIP-chip binding data and messenger RNA synthesis rates. Among the eight novel, condition-specific TF pairs, we validate the interaction between Gcn4p and Arr1p experimentally. We apply OHC to a large gene activity dataset in S. cerevisiae and provide a compendium of condition-specific TF interactions.
Project description:Transcriptional gene silencing (TGS) of mammalian genes can be induced by short interfering RNA (siRNA) targeting promoter regions. We previously reported potent TGS of HIV-1 by siRNA (PromA), which targets tandem NF-?B motifs within the viral 5'LTR. In this study, we screened a siRNA panel with the aim of identifying novel 5'LTR targets, to provide multiplexing potential with enhanced viral silencing and application toward developing alternate therapeutic strategies. Systematic examination identified a novel siRNA target, si143, confirmed to induce TGS as the silencing mechanism. TGS was prolonged with virus suppression >12 days, despite a limited ability to induce post- TGS. Epigenetic changes associated with silencing were suggested by partial reversal by histone deacetylase inhibitors and confirmed by chromatin immunoprecipitation analyses, which showed induction of H3K27me3 and H3K9me3, reduction in H3K9Ac, and recruitment of argonaute-1, all characteristic marks of heterochromatin and TGS. Together, these epigenetic changes mimic those associated with HIV-1 latency. Further, robust resistance to reactivation was observed in the J-Lat 9.2 cell latency model, when transduced with shPromA and/or sh143. These data support si/shRNA-mediated TGS approaches to HIV-1 and provide alternate targets to pursue a functional cure, whereby the viral reservoir is locked in latency following antiretroviral therapy cessation.
Project description:BACKGROUND: Chromatin immunoprecipitation (ChIP) experiments are now the most comprehensive experimental approaches for mapping the binding of transcription factors (TFs) to their target genes. However, ChIP data alone is insufficient for identifying functional binding target genes of TFs for two reasons. First, there is an inherent high false positive/negative rate in ChIP-chip or ChIP-seq experiments. Second, binding signals in the ChIP data do not necessarily imply functionality. METHODS: It is known that ChIP-chip data and TF knockout (TFKO) data reveal complementary information on gene regulation. While ChIP-chip data can provide TF-gene binding pairs, TFKO data can provide TF-gene regulation pairs. Therefore, we propose a novel network approach for identifying functional TF-gene binding pairs by integrating the ChIP-chip data with the TFKO data. In our method, a TF-gene binding pair from the ChIP-chip data is regarded to be functional if it also has high confident curated TFKO TF-gene regulatory relation or deduced hypostatic TF-gene regulatory relation. RESULTS AND CONCLUSIONS: We first validated our method on a gathered ground truth set. Then we applied our method to the ChIP-chip data to identify functional TF-gene binding pairs. The biological significance of our identified functional TF-gene binding pairs was shown by assessing their functional enrichment, the prevalence of protein-protein interaction, and expression coherence. Our results outperformed the results of three existing methods across all measures. And our identified functional targets of TFs also showed statistical significance over the randomly assigned TF-gene pairs. We also showed that our method is dataset independent and can apply to ChIP-seq data and the E. coli genome. Finally, we provided an example showing the biological applicability of our notion.
Project description:Epstein-Barr virus (EBV) oncoprotein EBNA3C is indispensable for primary B-cell transformation and maintenance of lymphoblastoid cells outgrowth. EBNA3C usurps two putative cellular pathways-cell-cycle and apoptosis, essentially through modulating ubiquitin-mediated protein-degradation or gene transcription. In cancer cells, these two pathways are interconnected with autophagy,-a survival-promoting catabolic network in which cytoplasmic material including mis/un-folded protein aggregates and damaged organelles along with intracellular pathogens are degraded and recycled in lysosomal compartments. Studies have shown that tumor viruses including EBV can manipulate autophagy as a survival strategy. Here, we demonstrate that EBNA3C elevates autophagy, which serves as a prerequisite for apoptotic inhibition and maintenance of cell growth. Using PCR based micro-array we show that EBNA3C globally accelerates autophagy gene transcription under growth limiting conditions. Reanalyzing the ENCODE ChIP-sequencing data (GSE52632 and GSE26386) followed by ChIP-PCR demonstrate that EBNA3C recruits several histone activation epigenetic marks (H3K4me1, H3K4me3, H3K9ac, and H3K27ac) for transcriptional activation of autophagy genes, notably ATG3, ATG5, and ATG7 responsible for autophagosome formation. Moreover, under growth limiting conditions EBNA3C further stimulates the autophagic response through upregulation of a number of tumor suppressor genes, notably cyclin-dependent kinase inhibitors-CDKN1B (p27Kip1) and CDKN2A (p16INK4a) and autophagy mediated cell-death modulators-DRAM1 and DAPK1. Together our data highlight a new role of an essential EBV oncoprotein in regulating autophagy cascade as a survival mechanism and offer novel-targets for potential therapeutic expansion against EBV induced B-cell lymphomas.