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Inferring Gene Family Histories in Yeast Identifies Lineage Specific Expansions

Overview of attention for article published in PLOS ONE, June 2014
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Title
Inferring Gene Family Histories in Yeast Identifies Lineage Specific Expansions
Published in
PLOS ONE, June 2014
DOI 10.1371/journal.pone.0099480
Pubmed ID
Authors

Ryan M. Ames, Daniel Money, Simon C. Lovell

Abstract

The complement of genes found in the genome is a balance between gene gain and gene loss. Knowledge of the specific genes that are gained and lost over evolutionary time allows an understanding of the evolution of biological functions. Here we use new evolutionary models to infer gene family histories across complete yeast genomes; these models allow us to estimate the relative genome-wide rates of gene birth, death, innovation and extinction (loss of an entire family) for the first time. We show that the rates of gene family evolution vary both between gene families and between species. We are also able to identify those families that have experienced rapid lineage specific expansion/contraction and show that these families are enriched for specific functions. Moreover, we find that families with specific functions are repeatedly expanded in multiple species, suggesting the presence of common adaptations and that these family expansions/contractions are not random. Additionally, we identify potential specialisations, unique to specific species, in the functions of lineage specific expanded families. These results suggest that an important mechanism in the evolution of genome content is the presence of lineage-specific gene family changes.

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The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 3%
Unknown 30 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 35%
Student > Bachelor 4 13%
Researcher 4 13%
Student > Doctoral Student 3 10%
Student > Master 3 10%
Other 2 6%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 52%
Biochemistry, Genetics and Molecular Biology 6 19%
Environmental Science 1 3%
Psychology 1 3%
Social Sciences 1 3%
Other 0 0%
Unknown 6 19%