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Lack of Low Frequency Variants Masks Patterns of Non-Neutral Evolution following Domestication

Overview of attention for article published in PLOS ONE, August 2011
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Title
Lack of Low Frequency Variants Masks Patterns of Non-Neutral Evolution following Domestication
Published in
PLOS ONE, August 2011
DOI 10.1371/journal.pone.0023041
Pubmed ID
Authors

Céline H. Frère, Peter J. Prentis, Edward K. Gilding, Agnieszka M. Mudge, Alan Cruickshank, Ian D. Godwin

Abstract

Detecting artificial selection in the genome of domesticated species can not only shed light on human history but can also be beneficial to future breeding strategies. Evidence for selection has been documented in domesticated species including maize and rice, but few studies have to date detected signals of artificial selection in the Sorghum bicolor genome. Based on evidence that domesticated S. bicolor and its wild relatives show significant differences in endosperm structure and quality, we sequenced three candidate seed storage protein (kafirin) loci and three candidate starch biosynthesis loci to test whether these genes show non-neutral evolution resulting from the domestication process. We found strong evidence of non-neutral selection at the starch synthase IIa gene, while both starch branching enzyme I and the beta kafirin gene showed weaker evidence of non-neutral selection. We argue that the power to detect consistent signals of non-neutral selection in our dataset is confounded by the absence of low frequency variants at four of the six candidate genes. A future challenge in the detection of positive selection associated with domestication in sorghum is to develop models that can accommodate for skewed frequency spectrums.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 3%
United States 1 3%
Australia 1 3%
Unknown 30 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 27%
Student > Ph. D. Student 7 21%
Student > Master 4 12%
Professor 3 9%
Lecturer 2 6%
Other 4 12%
Unknown 4 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 73%
Environmental Science 1 3%
Business, Management and Accounting 1 3%
Social Sciences 1 3%
Unknown 6 18%