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Genomic consequences of selection and genome-wide association mapping in soybean

Overview of attention for article published in BMC Genomics, September 2015
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Title
Genomic consequences of selection and genome-wide association mapping in soybean
Published in
BMC Genomics, September 2015
DOI 10.1186/s12864-015-1872-y
Pubmed ID
Authors

Zixiang Wen, John F. Boyse, Qijian Song, Perry B. Cregan, Dechun Wang

Abstract

Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits. To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified. These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
France 1 1%
Brazil 1 1%
Unknown 95 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 23 23%
Researcher 22 22%
Student > Ph. D. Student 22 22%
Student > Doctoral Student 5 5%
Student > Bachelor 4 4%
Other 9 9%
Unknown 13 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 61 62%
Biochemistry, Genetics and Molecular Biology 15 15%
Unspecified 1 1%
Mathematics 1 1%
Immunology and Microbiology 1 1%
Other 2 2%
Unknown 17 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 September 2015.
All research outputs
#17,772,019
of 22,826,360 outputs
Outputs from BMC Genomics
#7,568
of 10,654 outputs
Outputs of similar age
#180,058
of 266,946 outputs
Outputs of similar age from BMC Genomics
#225
of 283 outputs
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