Bioinformatics and mutations leading to exon skipping

Methods Mol Biol. 2012;867:17-35. doi: 10.1007/978-1-61779-767-5_2.

Abstract

Our knowledge about human genes and the consequences of mutations leading to human genetic diseases has drastically improved over the last few years. It has been recognized that many mutations are indeed pathogenic because they impact the mRNA rather than the protein itself. With our better understanding of the very complex mechanism of splicing, various bioinformatics tools have been developed. They are now frequently used not only to search for sequence motifs corresponding to splicing signals (splice sites, branch points, ESE, and ESS) but also to predict the impact of mutations on these signals. We now need to address the impact of mutations that affect the splicing process, as their consequences could vary from the activation of cryptic signals to the skipping of one or multiple exons. Despite the major developments of the bioinformatics field coupled to experimental data generated on splicing, it is today still not possible to efficiently predict the consequences of mutations impacting splicing signals, especially to predict if they will lead to exon skipping or to cryptic splice site activation.

Publication types

  • Review

MeSH terms

  • Animals
  • Computational Biology / methods*
  • Databases, Genetic
  • Exons
  • Genetic Predisposition to Disease / genetics
  • Humans
  • Mutation*
  • RNA Splice Sites
  • RNA Splicing*
  • RNA, Messenger / genetics*
  • Software

Substances

  • RNA Splice Sites
  • RNA, Messenger