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PMID: 21695233 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Testing the ortholog conjecture with comparative functional genomic data from mammals.

PLoS computational biology ·Vol. 7 ·No. 6 ·2011-06-00 ·Pages e1002073

Nehrt NL, Clark WT, Radivojac P, Hahn MW

Abstract

A common assumption in comparative genomics is that orthologous genes share greater functional similarity than do paralogous genes (the "ortholog conjecture"). Many methods used to computationally predict protein function are based on this assumption, even though it is largely untested. Here we present the first large-scale test of the ortholog conjecture using comparative functional genomic data from human and mouse. We use the experimentally derived functions of more than 8,900 genes, as well as an independent microarray dataset, to directly assess our ability to predict function using both orthologs and paralogs. Both datasets show that paralogs are often a much better predictor of function than are orthologs, even at lower sequence identities. Among paralogs, those found within the same species are consistently more functionally similar than those found in a different species. We also find that paralogous pairs residing on the same chromosome are more functionally similar than those on different chromosomes, perhaps due to higher levels of interlocus gene conversion between these pairs. In addition to offering implications for the computational prediction of protein function, our results shed light on the relationship between sequence divergence and functional divergence. We conclude that the most important factor in the evolution of function is not amino acid sequence, but rather the cellular context in which proteins act.

MeSH Terms
Animals Comparative Genomic Hybridization Evolution, Molecular Gene Dosage Gene Expression Profiling Genes Humans Mice Oligonucleotide Array Sequence Analysis Proteins/genetics
Chemicals
Proteins
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Nehrt Nathan L
School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA.
Clark Wyatt T
Radivojac Predrag
Hahn Matthew W
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Article Info
Journal
PLoS computational biology
Abbr.
PLoS Comput Biol
ISSN
1553-7358
Published
2011-06-00
Epub
2011-00-09
Pages
e1002073
Language
English
Region
United States
NLM ID
101238922
PMCID
PMC3111532
Subset
IM
Corrections
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