TY  - JA
AU  - JULIANA P.
AU  - Poland,J.A.
AU  - Huerta-Espino,J.
AU  - Shrestha,S.
AU  - Crossa,J.
AU  - Crespo-Herrera,L.A.
AU  - Toledo,F.H.
AU  - Velu,G.
AU  - Mondal,S.
AU  - Kumar,U.
AU  - Bhavani,S.
AU  - Pawan Kumar Singh
AU  - Randhawa,M.S.
AU  - Xinyao He
AU  - Guzman,C.
AU  - Dreisigacker,S.
AU  - Rouse,M.N.
AU  - Yue Jin
AU  - Perez-Rodriguez,P.
AU  - Montesinos-Lopez,O.A.
AU  - Singh,D.
AU  - Rahman,M.M.
AU  - Marza, F.
AU  - Singh,R.P.
TI  - Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics
SN  - 1546-1718
PY  - 2019///
CY  - United Kingdom
PB  - Nature Publishing Group
KW  - Plant breeding
KW  - AGROVOC
KW  - Marker-assisted selection
KW  - Soft wheat
KW  - Genomics
N1  - Peer review; WC; FP3
N2  - Bread wheat improvement using genomic tools is essential for accelerating trait genetic gains. Here we report the genomic predictabilities of 35 key traits and demonstrate the potential of genomic selection for wheat end-use quality. We also performed a large genome-wide association study that identified several significant marker-trait associations for 50 traits evaluated in South Asia, Africa and the Americas. Furthermore, we built a reference wheat genotype-phenotype map, explored allele frequency dynamics over time and fingerprinted 44,624 wheat lines for trait-associated markers, generating over 7.6 million data points, which together will provide a valuable resource to the wheat community for enhancing productivity and stress resilience
T2  - Nature genetics
DO  - https://doi.org/10.1038/s41588-019-0496-6
ER  -