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Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics

Authors :
Daljit Singh
Julio Huerta-Espino
Xinyao He
Sandesh Shrestha
Sridhar Bhavani
José Crossa
Suchismita Mondal
Ravi P. Singh
Felix Marza
Jesse Poland
Mandeep S. Randhawa
Velu Govindan
Fernando H. Toledo
Pawan K. Singh
Matthew N. Rouse
Philomin Juliana
Paulino Pérez-Rodríguez
Yue Jin
Carlos Guzmán
Osval A. Montesinos-López
Leonardo Crespo-Herrera
Susanne Dreisigacker
Uttam Kumar
Mohammad Mokhlesur Rahman
Source :
Nature Genetics. 51:1530-1539
Publication Year :
2019
Publisher :
Springer Science and Business Media LLC, 2019.

Abstract

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. Large-scale genomic analyses in wheat identify regions associated with 50 agronomic traits evaluated in South Asia, Africa and the Americas. This genotype–phenotype map can be used to enhance wheat productivity and stress resilience.

Details

ISSN :
15461718 and 10614036
Volume :
51
Database :
OpenAIRE
Journal :
Nature Genetics
Accession number :
edsair.doi.dedup.....2c8bf5a741ee4241176ee42e73e97a9f
Full Text :
https://doi.org/10.1038/s41588-019-0496-6