Whole-genome analysis of gene conversion events

Chih Hao Hsu, Yu Zhang, Ross Cameron Hardison, Webb Miller

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

2 Scopus citations

Abstract

Gene conversion events are often overlooked in analyses of genome evolution. In a conversion event, an interval of DNA sequence (not necessarily containing a gene) overwrites a highly similar sequence. The event creates relationships among genomic intervals that can confound attempts to identify orthologs and to transfer functional annotation between genomes. Here we examine 1,112,202 paralogous pairs of human genomic intervals, and detect conversion events in about 13.5% of them. Properties of the putative gene conversions are analyzed, such as the lengths of the paralogous pairs and the spacing between their sources and targets. Our approach is illustrated using conversion events in the beta-globin gene cluster.

Original languageEnglish (US)
Title of host publicationComparative Genomics - International Workshop, RECOMB-CG 2009, Proceedings
Pages181-192
Number of pages12
DOIs
StatePublished - Dec 1 2009
Event7th International Workshop on Comparative Genomics, RECOMB-CG 2009 - Budapest, Hungary
Duration: Sep 27 2009Sep 29 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5817 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Workshop on Comparative Genomics, RECOMB-CG 2009
CountryHungary
CityBudapest
Period9/27/099/29/09

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Hsu, C. H., Zhang, Y., Hardison, R. C., & Miller, W. (2009). Whole-genome analysis of gene conversion events. In Comparative Genomics - International Workshop, RECOMB-CG 2009, Proceedings (pp. 181-192). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5817 LNBI). https://doi.org/10.1007/978-3-642-04744-2_15