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  Comparing the Statistical Fate of Paralogous and Orthologous Sequences

Massip, F., Sheinman, M., Schbath, S., & Arndt, P. (2016). Comparing the Statistical Fate of Paralogous and Orthologous Sequences. Genetics, 204(2), 475-482. doi:10.1534/genetics.116.193912.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-4744-2 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-4745-F
Genre: Journal Article

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© 2016 by the Genetics Society of America
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 Creators:
Massip, F., Author
Sheinman, M., Author
Schbath, S., Author
Arndt, P.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              

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Free keywords: DNA duplications comparative genomics genome evolution statistical genomics
 Abstract: Since several decades, sequence alignment is a widely used tool in bioinformatics. For instance, finding homologous sequences with known function in large databases is used to get insight into the function of non-annotated genomic regions. Very efficient tools, like BLAST have been developed to identify and rank possible homologous sequences. To estimate the significance of the homology, the ranking of alignment scores takes a background model for random sequences into account. Using this model one can estimate the probability to find two exactly matching subsequences by chance in two unrelated sequences. For two homologous sequences, the corresponding probability is much higher, which allows to identify them. Here we focus on the distribution of lengths of exact sequence matches in protein coding regions pairs of evolutionary distant genomes. We show that this distribution exhibits a power-law tail with an exponent alpha = -5. Developing a simple model of sequence evolution by substitutions and segmental duplications, we show analytically and computationally that paralogous and orthologous gene pairs contribute differently to this distribution. Our model explains the differences observed in the comparison of coding and non-coding parts of genomes, thus providing a better understanding of statistical properties of genomic sequences and their evolution.

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Language(s): eng - English
 Dates: 2016-07-292016-10
 Publication Status: Published in print
 Pages: 8
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: PMID: 27474728
DOI: 10.1534/genetics.116.193912
ISSN: 1943-2631 (Electronic)0016-6731 (Print)
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Title: Genetics
Source Genre: Journal
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Publ. Info: Genetics Society of America
Pages: - Volume / Issue: 204 (2) Sequence Number: - Start / End Page: 475 - 482 Identifier: ISSN: 0016-6731
CoNE: /journals/resource/954925400554