Briefings in Functional Genomics Advance Access originally published online on June 4, 2009
Briefings in Functional Genomics 2009 8(4):215-230; doi:10.1093/bfgp/elp014
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This article appears in the following Briefings in Functional Genomics and Proteomics issue: Special Issue: Non-Coding Regulatory Regions in Genomes [View the issue table of contents]
Special Issue Papers |
Identifying regulatory elements in eukaryotic genomes
Corresponding author. Ivan Ovcharenko, Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health (NIH), Bethesda, MD, USA. Tel: (301) 435-8944; Fax: (301) 480-2290; Zip Code: 20894; E-mail: ovcharei{at}ncbi.nlm.nih.gov
Proper development and functioning of an organism depends on precise spatial and temporal expression of all its genes. These coordinated expression-patterns are maintained primarily through the process of transcriptional regulation. Transcriptional regulation is mediated by proteins binding to regulatory elements on the DNA in a combinatorial manner, where particular combinations of transcription factor binding sites establish specific regulatory codes. In this review, we survey experimental and computational approaches geared towards the identification of proximal and distal gene regulatory elements in the genomes of complex eukaryotes. Available approaches that decipher the genetic structure and function of regulatory elements by exploiting various sources of information like gene expression data, chromatin structure, DNA-binding specificities of transcription factors, cooperativity of transcription factors, etc. are highlighted. We also discuss the relevance of regulatory elements in the context of human health through examples of mutations in some of these regions having serious implications in misregulation of genes and being strongly associated with human disorders.
Keywords: transcriptional regulation, enhancers, silencers, tissue-specific regulatory elements, population variation, non-coding diseases, computational analysis of regulatory element sequence composition