Distinguishing regulatory DNA from neutral sites.

Laura Elnitski, Ross C. Hardison, Jia Li, Shan Yang, Diana Kolbe, Pallavi Eswara, Michael J. O'Connor, Scott Schwartz, Webb Miller, Francesca Chiaromonte

Research output: Contribution to journalArticlepeer-review

100 Scopus citations

Abstract

We explore several computational approaches to analyzing interspecies genomic sequence alignments, aiming to distinguish regulatory regions from neutrally evolving DNA. Human-mouse genomic alignments were collected for three sets of human regions: (1) experimentally defined gene regulatory regions, (2) well-characterized exons (coding sequences, as a positive control), and (3) interspersed repeats thought to have inserted before the human-mouse split (a good model for neutrally evolving DNA). Models that potentially could distinguish functional noncoding sequences from neutral DNA were evaluated on these three data sets, as well as bulk genome alignments. Our analyses show that discrimination based on frequencies of individual nucleotide pairs or gaps (i.e., of possible alignment columns) is only partially successful. In contrast, scoring procedures that include the alignment context, based on frequencies of short runs of alignment columns, dramatically improve separation between regulatory and neutral features. Such scoring functions should aid in the identification of putative regulatory regions throughout the human genome.

Original languageEnglish (US)
Pages (from-to)64-72
Number of pages9
JournalGenome research
Volume13
Issue number1
DOIs
StatePublished - Jan 2003

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

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