ABSTRACT
This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
Subject(s)
Genome , Mice/genetics , Terminator Regions, Genetic , Transcription Initiation Site , Transcription, Genetic , 3' Untranslated Regions , Animals , Base Sequence , Conserved Sequence , DNA, Complementary/chemistry , Genome, Human , Genomics , Humans , Promoter Regions, Genetic , Proteins/genetics , RNA/chemistry , RNA/classification , RNA Splicing , RNA, Untranslated/chemistry , Regulatory Sequences, Ribonucleic AcidABSTRACT
MOTIVATION: Computational prediction and analysis of transcription regulatory regions in DNA sequences has the potential to accelerate greatly our understanding of how cellular processes are controlled. We present a hidden Markov model based method for detecting regulatory regions in DNA sequences, by searching for clusters of cis-elements. RESULTS: When applied to regulatory targets of the transcription factor LSF, this method achieves a sensitivity of 67%, while making one prediction per 33 kb of non-repetitive human genomic sequence. When applied to muscle specific regulatory regions, we obtain a sensitivity and prediction rate that compare favorably with one of the best alternative approaches. Our method, which we call Cister, can be used to predict different varieties of regulatory region by searching for clusters of cis-elements of any type chosen by the user. Cister is simple to use and is available on the web. AVAILABILITY: http://sullivan.bu.edu/~mfrith/cister.shtml. CONTACT: mfrith@bu.edu; zhiping@bu.edu.
