TY - JOUR
T1 - Genome-wide association mapping of agronomic and morphologic traits in highly structured populations of barley cultivars
AU - Wang, Minghui
AU - Jiang, Ning
AU - Jia, Tianye
AU - Leach, Lindsey
AU - Cockram, James
AU - Waugh, Robbie
AU - Ramsay, Luke
AU - Thomas, Bill
AU - Luo, Zewei
N1 - Funding Information:
This study was supported by research grants for the ‘Association Genetics of UK Elite Barley’ project, which was funded by BBSRC and RERAD as part of the Sustainable Arable LINK programme with industrial support from HGCA, KWS (UK), LS Plant Breeding, Syngenta Seeds, Groupe Limagrain, Secobra UK, Svalof Weibull, Perten Instruments AB, The Maltsters Association of Great Britain, The Scotch Whisky Research Institute and Campden BRi. ZWL is also supported by the Leverhulme Trust (RCEJ1471) of UK, NSFC (31071084) and The Basic Research Program (2012CB316505) of China.
PY - 2012/2
Y1 - 2012/2
N2 - Abstract Genome-wide association study (GWAS) has become an obvious general approach for studying traits of agricultural importance in higher plants, especially crops. Here, we present a GWAS of 32 morphologic and 10 agronomic traits in a collection of 615 barley cultivars genotyped by genome-wide polymorphisms from a recently developed barley oligonucleotide pool assay. Strong population structure effect related to mixed sampling based on seasonal growth habit and ear row number is present in this barley collection. Comparison of seven statistical approaches in a genome-wide scan for significant associations with or without correction for confounding by population structure, revealed that in reducing false positive rates while maintaining statistical power, a mixed linear model solution outperforms genomic control, structured association, stepwise regression control and principal components adjustment. The present study reports significant associations for sixteen morphologic and nine agronomic traits and demonstrates the power and feasibility of applying GWAS to explore complex traits in highly structured plant samples.
AB - Abstract Genome-wide association study (GWAS) has become an obvious general approach for studying traits of agricultural importance in higher plants, especially crops. Here, we present a GWAS of 32 morphologic and 10 agronomic traits in a collection of 615 barley cultivars genotyped by genome-wide polymorphisms from a recently developed barley oligonucleotide pool assay. Strong population structure effect related to mixed sampling based on seasonal growth habit and ear row number is present in this barley collection. Comparison of seven statistical approaches in a genome-wide scan for significant associations with or without correction for confounding by population structure, revealed that in reducing false positive rates while maintaining statistical power, a mixed linear model solution outperforms genomic control, structured association, stepwise regression control and principal components adjustment. The present study reports significant associations for sixteen morphologic and nine agronomic traits and demonstrates the power and feasibility of applying GWAS to explore complex traits in highly structured plant samples.
UR - http://www.scopus.com/inward/record.url?scp=84860329104&partnerID=8YFLogxK
U2 - 10.1007/s00122-011-1697-2
DO - 10.1007/s00122-011-1697-2
M3 - Article
C2 - 21915710
AN - SCOPUS:84860329104
SN - 0040-5752
VL - 124
SP - 233
EP - 246
JO - Theoretical And Applied Genetics
JF - Theoretical And Applied Genetics
IS - 2
ER -