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  How evolution of genomes is reflected in exact DNA sequence match statistics

Massip, F., Sheinman, M., Schbath, S., & Arndt, P. F. (2015). How evolution of genomes is reflected in exact DNA sequence match statistics. Mol Biol Evol, 32(2), 524-535. doi:10.1093/molbev/msu313.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-3AAC-A Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-3AAD-8
Genre: Journal Article

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 Creators:
Massip, Florian1, 2, Author              
Sheinman, Michel1, Author              
Schbath, Sophie2, Author
Arndt, Peter F.1, Author              
Affiliations:
1Evolutionary Genomics (Peter Arndt), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479638              
2UR1077, Unite Mathematiques Informatique et Genome, INRA, domaine de Vilvert, Jouy-en-Josas, France , ou_persistent22              

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Free keywords: Animals Biological Evolution Evolution, Molecular Gene Duplication/genetics Genome/*genetics Genomics/*methods Humans Segmental Duplications, Genomic/genetics Selection, Genetic comparative genomics genome evolution segmental duplication sequence similarities
 Abstract: Genome evolution is shaped by a multitude of mutational processes, including point mutations, insertions, and deletions of DNA sequences, as well as segmental duplications. These mutational processes can leave distinctive qualitative marks in the statistical features of genomic DNA sequences. One such feature is the match length distribution (MLD) of exactly matching sequence segments within an individual genome or between the genomes of related species. These have been observed to exhibit characteristic power law decays in many species. Here, we show that simple dynamical models consisting solely of duplication and mutation processes can already explain the characteristic features of MLDs observed in genomic sequences. Surprisingly, we find that these features are largely insensitive to details of the underlying mutational processes and do not necessarily rely on the action of natural selection. Our results demonstrate how analyzing statistical features of DNA sequences can help us reveal and quantify the different mutational processes that underlie genome evolution.

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Language(s): eng - English
 Dates: 2014-11-132015-02
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1093/molbev/msu313
ISSN: 1537-1719 (Electronic)0737-4038 (Print)
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Title: Mol Biol Evol
Source Genre: Journal
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Publ. Info: Oxford University Press
Pages: - Volume / Issue: 32 (2) Sequence Number: - Start / End Page: 524 - 535 Identifier: -