Breeding-assisted genomics: Applying meta-GWAS for milling and baking quality in CIMMYT wheat breeding program

Area of Science:

• Plant genetics
• Agricultural science
• Genomics

Background:

• Genetic studies face challenges with unbalanced datasets, common in multi-year crop and animal breeding.
• Improving bread wheat (Triticum aestivum L.) end-use quality is vital for food security, but testing is costly and limits early selection.

Purpose of the Study:

• To develop and apply a novel meta-genome wide association study (meta-GWAS) approach for identifying marker-trait associations in unbalanced breeding datasets.
• To map processing and end-use quality phenotypes in a large bread wheat breeding program.

Main Methods:

• A meta-genome wide association study (meta-GWAS) was developed, combining GWAS from multi-year, unbalanced breeding nurseries.
• The method was applied to advanced breeding lines (n = 4,095) from the CIMMYT bread wheat breeding program (2009-2014).

Main Results:

• The meta-GWAS successfully identified significant marker-trait associations for processing and end-use quality traits.
• Allele effects and candidate genes were pinpointed, enabling marker-assisted selection.
• The study mapped quality phenotypes in a large, unbalanced dataset.

Conclusions:

• The developed meta-GWAS is a powerful tool for analyzing unbalanced datasets in crop breeding programs.
• This approach enhances the understanding of plant genomes and facilitates 'breeding-assisted genomics' across various crops.
• It enables efficient selection for complex traits like end-use quality in wheat breeding.