Dataset Information

Homotypic clusters of transcription factor binding sites are a key component of human promoters and enhancers.

ABSTRACT: Clustering of multiple transcription factor binding sites (TFBSs) for the same transcription factor (TF) is a common feature of cis-regulatory modules in invertebrate animals, but the occurrence of such homotypic clusters of TFBSs (HCTs) in the human genome has remained largely unknown. To explore whether HCTs are also common in human and other vertebrates, we used known binding motifs for vertebrate TFs and a hidden Markov model-based approach to detect HCTs in the human, mouse, chicken, and fugu genomes, and examined their association with cis-regulatory modules. We found that evolutionarily conserved HCTs occupy nearly 2% of the human genome, with experimental evidence for individual TFs supporting their binding to predicted HCTs. More than half of the promoters of human genes contain HCTs, with a distribution around the transcription start site in agreement with the experimental data from the ENCODE project. In addition, almost half of the 487 experimentally validated developmental enhancers contain them as well--a number more than 25-fold larger than expected by chance. We also found evidence of negative selection acting on TFBSs within HCTs, as the conservation of TFBSs is stronger than the conservation of sequences separating them. The important role of HCTs as components of developmental enhancers is additionally supported by a strong correlation between HCTs and the binding of the enhancer-associated coactivator protein Ep300 (also known as p300). Experimental validation of HCT-containing elements in both zebrafish and mouse suggest that HCTs could be used to predict both the presence of enhancers and their tissue specificity, and are thus a feature that can be effectively used in deciphering the gene regulatory code. In conclusion, our results indicate that HCTs are a pervasive feature of human cis-regulatory modules and suggest that they play an important role in gene regulation in the human and other vertebrate genomes.

SUBMITTER: Gotea V

PROVIDER: S-EPMC2860159 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Homotypic clusters of transcription factor binding sites are a key component of human promoters and enhancers.

Gotea Valer V Visel Axel A Westlund John M JM Nobrega Marcelo A MA Pennacchio Len A LA Ovcharenko Ivan I

Genome research 20100402 5

Clustering of multiple transcription factor binding sites (TFBSs) for the same transcription factor (TF) is a common feature of cis-regulatory modules in invertebrate animals, but the occurrence of such homotypic clusters of TFBSs (HCTs) in the human genome has remained largely unknown. To explore whether HCTs are also common in human and other vertebrates, we used known binding motifs for vertebrate TFs and a hidden Markov model-based approach to detect HCTs in the human, mouse, chicken, and fu ...[more]

PMID: 20363979

Similar Datasets

Project description:Despite almost 40 years of molecular genetics research in Escherichia coli a major fraction of its Transcription Start Sites (TSSs) are still unknown, limiting therefore our understanding of the regulatory circuits that control gene expression in this model organism. RegulonDB (http://regulondb.ccg.unam.mx/) is aimed at integrating the genetic regulatory network of E. coli K12 as an entirely bioinformatic project up till now. In this work, we extended its aims by generating experimental data at a genome scale on TSSs, promoters and regulatory regions. We implemented a modified 5' RACE protocol and an unbiased High Throughput Pyrosequencing Strategy (HTPS) that allowed us to map more than 1700 TSSs with high precision. From this collection, about 230 corresponded to previously reported TSSs, which helped us to benchmark both our methodologies and the accuracy of the previous mapping experiments. The other ca 1500 TSSs mapped belong to about 1000 different genes, many of them with no assigned function. We identified promoter sequences and type of sigma factors that control the expression of about 80% of these genes. As expected, the housekeeping sigma(70) was the most common type of promoter, followed by sigma(38). The majority of the putative TSSs were located between 20 to 40 nucleotides from the translational start site. Putative regulatory binding sites for transcription factors were detected upstream of many TSSs. For a few transcripts, riboswitches and small RNAs were found. Several genes also had additional TSSs within the coding region. Unexpectedly, the HTPS experiments revealed extensive antisense transcription, probably for regulatory functions. The new information in RegulonDB, now with more than 2400 experimentally determined TSSs, strengthens the accuracy of promoter prediction, operon structure, and regulatory networks and provides valuable new information that will facilitate the understanding from a global perspective the complex and intricate regulatory network that operates in E. coli.

Project description:Transcription factor binding site (TFBS) identification plays an important role in deciphering gene regulatory codes. With comprehensive knowledge of TFBSs, one can understand molecular mechanisms of gene regulation. In the recent decades, various computational approaches have been proposed to predict TFBSs in the genome. The TFBS dataset of a TF generated by each algorithm is a ranked list of predicted TFBSs of that TF, where top ranked TFBSs are statistically significant ones. However, whether these statistically significant TFBSs are functional (i.e. biologically relevant) is still unknown. Here we develop a post-processor, called the functional propensity calculator (FPC), to assign a functional propensity to each TFBS in the existing computationally predicted TFBS datasets. It is known that functional TFBSs reveal strong positional preference towards the transcriptional start site (TSS). This motivates us to take TFBS position relative to the TSS as the key idea in building our FPC. Based on our calculated functional propensities, the TFBSs of a TF in the original TFBS dataset could be reordered, where top ranked TFBSs are now the ones with high functional propensities. To validate the biological significance of our results, we perform three published statistical tests to assess the enrichment of Gene Ontology (GO) terms, the enrichment of physical protein-protein interactions, and the tendency of being co-expressed. The top ranked TFBSs in our reordered TFBS dataset outperform the top ranked TFBSs in the original TFBS dataset, justifying the effectiveness of our post-processor in extracting functional TFBSs from the original TFBS dataset. More importantly, assigning functional propensities to putative TFBSs enables biologists to easily identify which TFBSs in the promoter of interest are likely to be biologically relevant and are good candidates to do further detailed experimental investigation. The FPC is implemented as a web tool at http://santiago.ee.ncku.edu.tw/FPC/.

Dataset Information

Homotypic clusters of transcription factor binding sites are a key component of human promoters and enhancers.

Publications

Homotypic clusters of transcription factor binding sites are a key component of human promoters and enhancers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets