Evolutionary history reconstruction for mammalian complex Gene clusters

Yu Zhang, Giltae Song, Tomáš Vinař, Eric D. Green, Adam Siepel, Webb Miller

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Clusters of genes that evolved from single progenitors via repeated segmental duplications present significant challenges to the generation of a truly complete human genome sequence. Such clusters can confound both accurate sequence assembly and downstream computational analysis, yet they represent a hotbed of functional innovation, making them of extreme interest. We have developed an algorithm for reconstructing the evolutionary history of gene clusters using only human genomic sequence data, which allows the tempo of large-scale evolutionary events in human gene clusters to be estimated. We further propose an extension of the method to simultaneously reconstructing the evolutionary histories of orthologous gene clusters in multiple primates, which will facilitate primate comparative sequencing studies that aim to reconstruct their evolutionary history more fully.

Original languageEnglish (US)
Pages (from-to)1051-1070
Number of pages20
JournalJournal of Computational Biology
Volume16
Issue number8
DOIs
StatePublished - Aug 1 2009

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics

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    Zhang, Y., Song, G., Vinař, T., Green, E. D., Siepel, A., & Miller, W. (2009). Evolutionary history reconstruction for mammalian complex Gene clusters. Journal of Computational Biology, 16(8), 1051-1070. https://doi.org/10.1089/cmb.2009.0040