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Genome-wide signatures of transcription factor activity: connecting transcription factors, disease, and small molecules.

ABSTRACT: Identifying transcription factors (TF) involved in producing a genome-wide transcriptional profile is an essential step in building mechanistic model that can explain observed gene expression data. We developed a statistical framework for constructing genome-wide signatures of TF activity, and for using such signatures in the analysis of gene expression data produced by complex transcriptional regulatory programs. Our framework integrates ChIP-seq data and appropriately matched gene expression profiles to identify True REGulatory (TREG) TF-gene interactions. It provides genome-wide quantification of the likelihood of regulatory TF-gene interaction that can be used to either identify regulated genes, or as genome-wide signature of TF activity. To effectively use ChIP-seq data, we introduce a novel statistical model that integrates information from all binding "peaks" within 2 Mb window around a gene's transcription start site (TSS), and provides gene-level binding scores and probabilities of regulatory interaction. In the second step we integrate these binding scores and regulatory probabilities with gene expression data to assess the likelihood of True REGulatory (TREG) TF-gene interactions. We demonstrate the advantages of TREG framework in identifying genes regulated by two TFs with widely different distribution of functional binding events (ER? and E2f1). We also show that TREG signatures of TF activity vastly improve our ability to detect involvement of ER? in producing complex diseases-related transcriptional profiles. Through a large study of disease-related transcriptional signatures and transcriptional signatures of drug activity, we demonstrate that increase in statistical power associated with the use of TREG signatures makes the crucial difference in identifying key targets for treatment, and drugs to use for treatment. All methods are implemented in an open-source R package treg. The package also contains all data used in the analysis including 494 TREG binding profiles based on ENCODE ChIP-seq data. The treg package can be downloaded at http://GenomicsPortals.org.

SUBMITTER: Chen J

PROVIDER: S-EPMC3764016 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Genome-wide signatures of transcription factor activity: connecting transcription factors, disease, and small molecules.

Chen Jing J Hu Zhen Z Phatak Mukta M Reichard John J Freudenberg Johannes M JM Sivaganesan Siva S Medvedovic Mario M

PLoS computational biology 20130905 9

Identifying transcription factors (TF) involved in producing a genome-wide transcriptional profile is an essential step in building mechanistic model that can explain observed gene expression data. We developed a statistical framework for constructing genome-wide signatures of TF activity, and for using such signatures in the analysis of gene expression data produced by complex transcriptional regulatory programs. Our framework integrates ChIP-seq data and appropriately matched gene expression p ...[more]

PMID: 24039560

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Project description:Background Walnut is an important economic tree species with prominent economic value and ecological functions. However, in recent years, walnuts have become susceptible to drought stress, resulting in a decline in comprehensive benefits. Therefore, it is necessary to identify the regulatory molecular mechanism associated with walnut response to drought. In many plants, ethylene responsive factor (ERF) gene family plays important roles in response to biotic and abiotic stress, especial drought. Therefore, the identification and characterisation of walnut ERF genes will benefit walnut with regard to the clarification of drought response mechanism as well as the management, production, and quality of plantations. Methods ‘ERF’ was compared against the walnut transcriptome, and the JrERFs with a complete open reading frame (ORF) were identified by ORF Finder. The molecular weights, amino acid residues, and theoretical isoelectric point (pI) were predicted by ExPASy. The distribution of JrERFs in chromosome locations was determined based on walnut genome data from NCBI. The intron-exon structures and conserved domains were analysed using Gene Structure Display Server 2.0 and CD-Search, accordingly. Multi-sequence alignment and a phylogenetic tree were constructed by ClustalX2.1 and MEGA7, respectively. The conserved motifs were acquired using MEME. Total RNA was isolated using the cetyltrimethylammonium ammonium bromide (CTAB) method (Yang et al., 2018). Gene expression was determined by using real-time quantitative polymerase chain reaction (qRT-PCR) analysis and calculated according to the 2−ΔΔCT method (Livak & Schmittgen, 2001). Results A total of 44 JrERFs were identified from the walnut transcriptome, whose ORFs were 450–1,239 bp in length. The molecular weights of the JrERF proteins (consisting 149–412 amino acids) were 16.81–43.71 kDa, with pI ranging from 4.8 (JrERF11) to 9.89 (JrERF03). The JrERFs can be divided into six groups (B1–B6), and among the groups, B6 contained the most number of members. Each JrERF contained 1–6 motifs and each motif comprised 9–50 amino acids. Among the motifs, motif1, motif2, and motif3 were the most abundant. More than 40% of JrERFs were up-regulated continuously when subjected to ethephon (ETH), PEG6000, and PEG6000+ETH treatments. Of all the JrERFs, JrERF11 showed the highest expression. Therefore, we conclude that walnut ERF genes are highly conserved and involved in the regulation of drought response in the presence of ETH. JrERFs are possibly important candidate genes for molecular breeding; hence, the findings of this study provides the theoretical basis for further investigation of ERF genes in walnut and other species.

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Genome-wide signatures of transcription factor activity: connecting transcription factors, disease, and small molecules.

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Genome-wide signatures of transcription factor activity: connecting transcription factors, disease, and small molecules.

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