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Genetic architecture of grain yield in bread wheat based on genome-wide association studies.
BMC Plant Biol. 2019 Apr 29; 19(1):168.BP

Abstract

BACKGROUND

Identification 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.

RESULTS

A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. 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 714.4-725.8 Mb 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.

CONCLUSIONS

The 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.

Authors+Show Affiliations

College of Agronomy, Xinjiang Agricultural University, Urumqi, 830052, Xinjiang, China. Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.College of Agronomy, Xinjiang Agricultural University, Urumqi, 830052, Xinjiang, China. Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China. International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, 12 Zhongguancun South Street, Beijing, 100081, China.Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China. International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, 12 Zhongguancun South Street, Beijing, 100081, China.Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China. Sino-Russia Agricultural Scientific and Technological Cooperation Center, Heilongjiang Academy of Agricultural Sciences, 368 Xuefu Street, Harbin, 150086, Heilongjiang, China.School of Chemical Science and Engineering, Royal Institute of Technology, Teknikringen 42, SE-100 44, Stockholm, Sweden.Institute of Cotton Research, Chinese Academy of Agricultural Sciences (CAAS), 38 Huanghe Street, Anyang, 455000, Henan, China.Crop Research Institute, Anhui Academy of Agricultural Sciences, 40 Nongke South Street, Hefei, 230001, Anhui, China.Crop Research Institute, Anhui Academy of Agricultural Sciences, 40 Nongke South Street, Hefei, 230001, Anhui, China.Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China. xiaxianchun@caas.cn.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31035920

Citation

Li, Faji, et al. "Genetic Architecture of Grain Yield in Bread Wheat Based On Genome-wide Association Studies." BMC Plant Biology, vol. 19, no. 1, 2019, p. 168.
Li F, Wen W, Liu J, et al. Genetic architecture of grain yield in bread wheat based on genome-wide association studies. BMC Plant Biol. 2019;19(1):168.
Li, F., Wen, W., Liu, J., Zhang, Y., Cao, S., He, Z., Rasheed, A., Jin, H., Zhang, C., Yan, J., Zhang, P., Wan, Y., & Xia, X. (2019). Genetic architecture of grain yield in bread wheat based on genome-wide association studies. BMC Plant Biology, 19(1), 168. https://doi.org/10.1186/s12870-019-1781-3
Li F, et al. Genetic Architecture of Grain Yield in Bread Wheat Based On Genome-wide Association Studies. BMC Plant Biol. 2019 Apr 29;19(1):168. PubMed PMID: 31035920.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Genetic architecture of grain yield in bread wheat based on genome-wide association studies. AU - Li,Faji, AU - Wen,Weie, AU - Liu,Jindong, AU - Zhang,Yong, AU - Cao,Shuanghe, AU - He,Zhonghu, AU - Rasheed,Awais, AU - Jin,Hui, AU - Zhang,Chi, AU - Yan,Jun, AU - Zhang,Pingzhi, AU - Wan,Yingxiu, AU - Xia,Xianchun, Y1 - 2019/04/29/ PY - 2018/10/06/received PY - 2019/04/16/accepted PY - 2019/5/1/entrez PY - 2019/5/1/pubmed PY - 2019/6/14/medline KW - GWAS KW - Marker-assisted selection KW - Single nucleotide polymorphism KW - Triticum aestivum SP - 168 EP - 168 JF - BMC plant biology JO - BMC Plant Biol VL - 19 IS - 1 N2 - BACKGROUND: Identification 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. RESULTS: A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. 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 714.4-725.8 Mb 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. CONCLUSIONS: The 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. SN - 1471-2229 UR - https://www.unboundmedicine.com/medline/citation/31035920/Genetic_architecture_of_grain_yield_in_bread_wheat_based_on_genome_wide_association_studies_ L2 - https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-019-1781-3 DB - PRIME DP - Unbound Medicine ER -