Large-scale genomic selection of wheat

Biology revolutionized agriculture in the XXth century. It’s easy to forget that cultivation of wheat – the most popular crop in the world – was entirely different before the Green Revolution in the 1960s. One of the main research centers behind that transformation, CIMMYT (International Maize and Wheat Improvement Center), finished a new study, which merges artificial selection with the latest technological discoveries in fields of genomic sequencing and bioinformatics.

Scientists made use of a fresh reference genome for bread wheat. They compared almost 80,000 genetic markers, coupled with phenotypic data, derived from over 44,000 lines of the plant. In result, they developed 35 genomic prediction models for important traits, such as protein content, grain yield, or days to maturity. Researchers also prepared various genetic analyses of wheat varieties from different parts of the world, as well as performed GWAS (genome wide association study) for another 50 characteristics of wheat.

Prediction models from the study can be used to speed-up artificial selection, avoid extensive field testing, and provide cost-effective selection programs for developing countries. Moreover, CIMMYT hopes to integrate the results into a new genomic selection tool for wheat.

CIMMYT provides detailed data under the Nature publication address:

Lead quote: Carlos Guzmán.
Publication: Juliana, P., Poland, J., Huerta-Espino, J., Shrestha, S., Crossa, J., Crespo-Herrera, L., … & Bhavani, S. (2019). Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics. Nature genetics, 1-10.

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