Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression

Abstract

The identification of regulatory regions is one of the most important and challenging problems toward the functional annotation of the human genome. In higher eukaryotes, transcription-factor (TF) binding sites are often organized in clusters called cis-regulatory modules (CRM). While the prediction of individual TF-binding sites is a notoriously difficult problem, CRM prediction has proven to be somewhat more reliable. Starting from a set of predicted binding sites for more than 200 TF families documented in Transfac, we describe an algorithm relying on the principle that CRMs generally contain several phylogenetically conserved binding sites for a few different TFs. The method allows the prediction of more than 118,000 CRMs within the human genome. A subset of these is shown to be bound in vivo by TFs using ChIP-chip. Their analysis reveals, among other things, that CRM density varies widely across the genome, with CRM-rich regions often being located near genes encoding transcription factors involved in development. Predicted CRMs show a surprising enrichment near the 3′ end of genes and in regions far from genes. We document the tendency for certain TFs to bind modules located in specific regions with respect to their target genes and identify TFs likely to be involved in tissue-specific regulation. The set of predicted CRMs, which is made available as a public database called PReMod (http://genomequebec.mcgill.ca/PReMod), will help analyze regulatory mechanisms in specific biological systems.

Promoter regions of many neural- and nutrition-related genes have experienced positive selection during human evolution

“…These studies, limited to individual genes, very recent positive selection, or highly conserved regions, strengthen the motivation for a systematic assessment of whether cis-regulatory sequences of many neural-or nutrition-related genes bear signatures of positive selection during human evolution. Because cis-regulatory sequences are scattered, short, and imprecise, most have not yet been mapped precisely, but several lines of evidence indicate that most are near transcription start sites 12,19,20 . Accordingly, we surveyed regions immediately upstream (5 ) from transcription start sites and identified associations of functional categories and expression domains with evidence of positive selection on these regions.…”

“…These regions contain many, perhaps most cis-regulatory sequences in the genome 12,19,20 . The chosen intronic sequences of a gene are the coding-region introns, excluding the first intron, which often contains cis-regulatory sequences [19][20][21] , the ends of each intron, which contain splicing signals 22 , and the centers of large introns, which may often contain cis-regulatory sequences 19 . These sequences are generally among the least constrained in the genome 3,23,24 , so they are a plausible neutral standard accounting for regional variation in mutation and recombination rates.…”

Screening and regulatory network analysis of survival-related genes of patients with colorectal cancer

“…Multiple transcription factor binding sites usually constitute cis-regulatory modules (CRM). Studies have shown that CRM-enriched regions are associated with growth-related transcription factors, and growth-related transcription factors also play an important role in the occurrence and de-velopment of tumors [4]. Therefore, genes with more binding sites for the above 25 transcription factors may be more important in the development of colorectal cancer, as well as the survival time of patients with colorectal cancer.…”

618 Five vertebrate ChIP-seq reveals the evolutionary dynamics of transcription factor binding

“…Many comparative genomics approaches assume that a multi-species alignment of a high quality motif is indicative of functionality (19)(20)(21)(22)(23)(24)(25). Our analysis of experimentally determined in vivo occupancy of two TFs in multiple vertebrates revealed apparent limitations to this model and a number of other insights about the complex relationship between genetic sequence, transcription factor binding, and genome regulation.…”