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Prediction of gene activity based on an integrated multi-omics approach.

ABSTRACT: An increasingly common method for predicting gene activity is genome-wide chromatin immunoprecipitation of ‘active’ chromatin modifications followed by massively parallel sequencing (ChIP-seq). Using a novel ChIP-seq quantification method (cRPKM), we tested the power of such ChIP-seq strategies to predict relative protein and RNA levels at the pre-pro-B and pro-B differentiation stages in early B cell lymphopoiesis. Using a multi-omics approach that compares promoter chromatin status (ChIP-seq; published in GSE:21978) with ongoing active transcription (GRO-seq; published in GSE:40173), steady state mRNA (RNA-seq), inferred mRNA stability, and relative proteome abundance measurements (iTRAQ), we demonstrate that active chromatin modifications at promoters are a good indicator of transcription and steady state mRNA levels. Moreover, we found that promoters with active chromatin modifications exclusively in one of these cell states frequently predicted differentially expressed proteins. However, we found that many genes whose promoters have non-differential but active chromatin modifications also displayed changes in expression of their cognate proteins. This large class of developmentally and differentially regulated proteins that was uncoupled from chromatin status used mostly post-transcriptional mechanisms. Interestingly, the most differentially expressed protein in our B-cell development system, 2410004B18Rik, was regulated by a post-transcriptional mechanism, which further analyses indicated was mediated by an identified miRNA. These data provide a striking example of how our integrated multi-omics data set can be useful in uncovering regulatory mechanisms.

ORGANISM(S): Mus musculus

PROVIDER: GSE52450 | GEO | 2013/11/19

SECONDARY ACCESSION(S): PRJNA228967

REPOSITORIES: GEO

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Project description:Epigenetic environment of histone H3.3 on promoters revealed by integration of imaging and genome-scale chromatin and methyl-DNA immunoprecipitation information. Chromatin regions with different transcriptional outputs are distinguished by the deposition of histone variants. Histone H3.3 is incorporated into chromatin in a replication-independent manner; yet the relationship between H3.3 deposition, chromatin environment is incompletely understood. We have integrated imaging and genome-scale chromatin and methyl-DNA immunoprecipitation approaches to investigate the genomic distribution of epitope-tagged H3.3 in relation to histone modifications, DNA methylation and transcription. Results: Imaging shows that H3.3, in contrast to replicative H3.1 or H2B, is enriched in chromatin marked by histone modifications of active genes. A genome-wide survey identifies 1,649 H3.3-enriched promoters, only a subset of which is co-enriched in H3K4me3, H3K9me3 and/or H3K27me3, with a preference for H3K4me3, corroborating imaging data. H3.3-enriched promoters are depleted of H3.3 at the TSS in a transcription-independent manner. H3.3 is found predominantly on CpG-rich unmethylated promoters, creating a condition favourable for transcription. In undifferentiated mesenchymal stem cells, H3.3 target genes are linked to signaling and mesodermal differentiation, suggesting that H3.3 may be a mark of lineage priming. Conclusions: A minor fraction of H3.3 is targeted to promoters, which are predominantly CpG-rich, DNA unmethylated and devoid of detectable trimethylated H3K4, K9 and K27. Among H3.3 target promoters co-marked by methylated H3, H4K4me3 is preferred, with or without H3K27me3, arguing that in mesenchymal stem cells H3.3 marks transcriptionally active or potentially active promoters. Key words: Imaging, ChIP-chip, MeDIP-chip, histone H3.3, mesenchymal stem cells ChIP-chip and MeDIP-chip experiments: Performed with two independent biological replicates. Gene expression profiling experiments: Total RNA obtained from H3.3-EGFP transfected or empty-EGFP transfected mesenchymal stem cells compared to untransfected mesenchymal stem cells. Raw expression data linked below as supplementary file (GSE17053_Illumina_non-normalized_data.txt).

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Prediction of gene activity based on an integrated multi-omics approach.

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