TY - JOUR
T1 - Prediction of gene activity in early B cell development based on an integrative multi-omics analysis
AU - Heydarian, Mohammad
AU - Luperchio, Teresa Romeo
AU - Cutler, Jevon
AU - Mitchell, Christopher J.
AU - Kim, Min Sik
AU - Pandey, Akhilesh
AU - Sollner-Webb, Barbara
AU - Reddy, Karen
PY - 2014
Y1 - 2014
N2 - An increasingly common method for predicting gene activity is genome-wide chromatin immuno-precipitation of 'active' chromatin modifications followed by massively parallel sequencing (ChIP-seq). In order to understand better the relationship between developmentally regulated chromatin landscapes and regulation of early B cell development, we determined how differentially active promoter regions were able predict relative RNA and protein levels at the pre-pro-B and pro-B stages. Herein, we describe a novel ChIP-seq quantification method (cRPKM) to identify active promoters and a multi-omics approach that compares promoter chromatin status with ongoing active transcription (GRO-seq), steady state mRNA (RNA-seq), inferred mRNA stability, and relative proteome abundance measurements (iTRAQ). We demonstrate that active chromatin modifications at promoters are good indicators 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 the differential abundance of proteins. However, we found that many genes whose promoters have non-differential but active chromatin modifications also displayed changes in abundance of their cognate proteins. As expected, this large class of developmentally and differentially regulated proteins that was uncoupled from chromatin status used mostly post- transcriptional mechanisms. Strikingly, the most differentially abundant protein in our B-cell development system, 2410004B18Rik, was regulated by a posttranscriptional mechanism, which further analyses indicated was mediated by a micro RNA. These data highlight how this integrated multi-omics data set can be a useful resource in uncovering regulatory mechanisms. This data can be accessed at: https://usegalaxy.org/u/thereddylab/p/prediction-of-gene-activity-based-on-an-integrative-multiomics- analysis.
AB - An increasingly common method for predicting gene activity is genome-wide chromatin immuno-precipitation of 'active' chromatin modifications followed by massively parallel sequencing (ChIP-seq). In order to understand better the relationship between developmentally regulated chromatin landscapes and regulation of early B cell development, we determined how differentially active promoter regions were able predict relative RNA and protein levels at the pre-pro-B and pro-B stages. Herein, we describe a novel ChIP-seq quantification method (cRPKM) to identify active promoters and a multi-omics approach that compares promoter chromatin status with ongoing active transcription (GRO-seq), steady state mRNA (RNA-seq), inferred mRNA stability, and relative proteome abundance measurements (iTRAQ). We demonstrate that active chromatin modifications at promoters are good indicators 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 the differential abundance of proteins. However, we found that many genes whose promoters have non-differential but active chromatin modifications also displayed changes in abundance of their cognate proteins. As expected, this large class of developmentally and differentially regulated proteins that was uncoupled from chromatin status used mostly post- transcriptional mechanisms. Strikingly, the most differentially abundant protein in our B-cell development system, 2410004B18Rik, was regulated by a posttranscriptional mechanism, which further analyses indicated was mediated by a micro RNA. These data highlight how this integrated multi-omics data set can be a useful resource in uncovering regulatory mechanisms. This data can be accessed at: https://usegalaxy.org/u/thereddylab/p/prediction-of-gene-activity-based-on-an-integrative-multiomics- analysis.
KW - B cell lymphocyte
KW - Immuno-precipitation
KW - Multi-potent progenitors
KW - Post-transcriptional mechanisms
KW - RNA-seq analysis
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UR - http://www.scopus.com/inward/citedby.url?scp=84894557469&partnerID=8YFLogxK
U2 - 10.4172/jpb.1000302
DO - 10.4172/jpb.1000302
M3 - Article
C2 - 25544807
AN - SCOPUS:84894557469
SN - 0974-276X
VL - 7
SP - 50
EP - 63
JO - Journal of Proteomics and Bioinformatics
JF - Journal of Proteomics and Bioinformatics
IS - 2
ER -