Skim exome capture genotyping in wheat.

Area of Science:

• Genomics
• Plant Breeding
• Bioinformatics

Background:

• Next-generation sequencing (NGS) costs are decreasing, making genome-wide genotyping feasible for crop research.
• Skim sequencing and exome capture are established methods but face challenges with complex genomes like allopolyploid wheat.
• Existing methods can be costly and may not be optimal for large-scale genotyping in diverse crop species.

Purpose of the Study:

• To develop a cost-effective targeted genotyping method for complex plant genomes.
• To enable high-resolution quantitative trait locus (QTL) mapping and genomic selection in wheat.
• To identify a large number of high-quality genic variants for various downstream applications.

Main Methods:

• Developed skim exome capture (SEC) by fragmenting DNA, enriching low-copy genic regions using wheat exome baits, and multiplexing samples.
• Applied SEC to libraries of 48, 528, and 1056 wheat samples, achieving varying coverage levels (∼7-8×, 0.76×, and 0.32×, respectively).
• Integrated low-coverage SEC data with genotype imputation using a custom wheat practical haplotype graph database.

Main Results:

• Achieved high-quality variant detection with ∼7-8× coverage in smaller sample sets.
• Successfully generated genotyping data at lower coverage (0.76× and 0.32×) for large sample sets (528 and 1056 samples).
• Identified hundreds of thousands of high-quality genic variants across the wheat genome through SEC and imputation.

Conclusions:

• Skim exome capture (SEC) is a cost-effective method for targeted genotyping in complex allopolyploid crops like wheat.
• The SEC method, combined with genotype imputation, facilitates high-resolution QTL mapping, genome-wide association studies, and genomic selection.
• This approach significantly reduces per-sample costs compared to traditional exome capture, making large-scale genetic studies more accessible.