Current computational methods for prioritizing candidate regulatory polymorphisms

Methods Mol Biol. 2009;569:89-114. doi: 10.1007/978-1-59745-524-4_5.

Abstract

Discovery of DNA sequence variants responsible for human phenotypic variation is key to advances in molecular diagnostics and medicines. Historically, variants that alter the protein-coding sequence of genes have been targeted when attempting to identify a trait's etiology; this is done because the rules governing these regions are generally well-understood and candidate variants can be easily selected. However, the effects of variants on gene regulation are increasingly regarded as being as important as protein-coding variation in uncovering the nature of phenotypic variation. I discuss resources and methodology that have recently been developed to computationally prioritize variants that may alter gene expression.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alleles
  • Binding Sites / genetics
  • Computational Biology*
  • Data Interpretation, Statistical
  • Databases, Genetic
  • Gene Expression Regulation*
  • Gene Frequency
  • Genetic Variation
  • Humans
  • Polymorphism, Genetic*
  • Polymorphism, Single Nucleotide
  • RNA, Untranslated / genetics
  • Software
  • Transcription Factors / metabolism

Substances

  • RNA, Untranslated
  • Transcription Factors