Simultaneous history reconstruction for complex gene clusters in multiple species

Yu Zhang, Giltae Song, Chih Hao Hsu, Webb Miller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Genomic intervals that contain a cluster of similar genes are of extreme biological interest, but difficult to sequence and analyze. One goal for interspecies comparisons of such intervals is to reconstruct a parsimonious series of duplications, deletions, and speciation events (a putative evolutionary history) that could have created the contemporary clusters from their last common ancestor. We describe a new method for reconstructing such an evolutionary scenario for a given set of intervals from present-day genomes, based on the statistical technique of Sequential Importance Sampling. An implementation of the method is evaluated using (1) artificial datasets generated by simulating the operations of duplication, deletion, and speciation starting with featureless "ancestral" sequences, and (2) by comparing the inferred evolutionary history of the amino-acid sequences for the CYP2 gene family from human chromosome 19, chimpanzee, orangutan, rhesus macaque, and dog, as computed by a standard phylogenetic-tree reconstruction method.

Original languageEnglish (US)
Title of host publicationPacific Symposium on Biocomputing 2009, PSB 2009
Pages162-173
Number of pages12
StatePublished - 2009
Event14th Pacific Symposium on Biocomputing, PSB 2009 - Kohala Coast, HI, United States
Duration: Jan 5 2009Jan 9 2009

Publication series

NamePacific Symposium on Biocomputing 2009, PSB 2009

Other

Other14th Pacific Symposium on Biocomputing, PSB 2009
CountryUnited States
CityKohala Coast, HI
Period1/5/091/9/09

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Biomedical Engineering
  • Medicine(all)

Fingerprint Dive into the research topics of 'Simultaneous history reconstruction for complex gene clusters in multiple species'. Together they form a unique fingerprint.

Cite this