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Genetic architecture of grain yield in bread wheat based on genome-wide association studies
Xinjiang Agr Univ, Coll Agron, Urumqi 830052, Xinjiang, Peoples R China.;CAAS, Natl Wheat Improvement Ctr, Inst Crop Sci, 12 Zhongguancun South St, Beijing 100081, Peoples R China..
Xinjiang Agr Univ, Coll Agron, Urumqi 830052, Xinjiang, Peoples R China.;CAAS, Natl Wheat Improvement Ctr, Inst Crop Sci, 12 Zhongguancun South St, Beijing 100081, Peoples R China..
CAAS, Natl Wheat Improvement Ctr, Inst Crop Sci, 12 Zhongguancun South St, Beijing 100081, Peoples R China..
CAAS, Natl Wheat Improvement Ctr, Inst Crop Sci, 12 Zhongguancun South St, Beijing 100081, Peoples R China..
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2019 (English)In: BMC Plant Biology, ISSN 1471-2229, E-ISSN 1471-2229, Vol. 19, article id 168Article in journal (Refereed) Published
Abstract [en]

BackgroundIdentification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits.ResultsA total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90K and 660K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4-725.8Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS.ConclusionsThe loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY.

Place, publisher, year, edition, pages
BioMed Central, 2019. Vol. 19, article id 168
Keywords [en]
GWAS, Marker-assisted selection, Single nucleotide polymorphism, Triticum aestivum
National Category
Genetics and Breeding in Agricultural Sciences
Identifiers
URN: urn:nbn:se:kth:diva-251709DOI: 10.1186/s12870-019-1781-3ISI: 000466981800002PubMedID: 31035920Scopus ID: 2-s2.0-85065221197OAI: oai:DiVA.org:kth-251709DiVA, id: diva2:1316706
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QC 20190520

Available from: 2019-05-20 Created: 2019-05-20 Last updated: 2019-05-29Bibliographically approved

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Zhang, Chi

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