Skim exome capture genotyping in wheat

Authors: Wang, Hongliang; Bernardo, Amy; St Amand, Paul; Bai, Guihua; Bowden, Robert; Guttieri, Mary; Jordan, Katherine

Submitted to: The Plant Genome
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/29/2023
Publication Date: 12/20/2023
Citation: Wang, H., Bernardo, A.E., St. Amand, P.C., Bai, G., Bowden, R.L., Guttieri, M.J., Jordan, K. 2023. Skim exome capture genotyping in wheat. The Plant Genome. 16(4). Article.e20381. https://doi.org/10.1002/tpg2.20381.
DOI: https://doi.org/10.1002/tpg2.20381

Interpretive Summary: One of the most limiting factors of genetics and breeding research for crop improvement is cost. Costs for generating sequencing reads continue to decrease as technology develops, allowing for a more comprehensive understanding of the genetic makeup of various crops and breeding material. However, the wheat genome is very large (16Gb) and complex (~85% repetitive material), limiting what information can be gained for wheat that can be accomplished in smaller, less complex staple crops with existing genomic platforms. With this in mind, we developed a new method called skim exome capture (SEC), which combines the strengths of existing sequencing and genotyping technologies, that allows for targeted sequencing of the genic regions of wheat. This results in a more informative snapshot of the wheat genome at a reduced cost per sample compared to traditional re-sequencing and capture approaches. We present data that show this new approach is repeatable and can be scaled to the desired price point to generate meaningful genotypic data that can be used in downstream breeding applications, such as, genome-wide association studies or genomic selection that can help produce better adapted wheat varieties.

Technical Abstract: Next-generation sequencing (NGS) technology advancements continue to reduce the cost of high-throughput genome-wide genotyping for breeding and genetics research. Skim sequencing, which surveys the entire genome at low coverage, has become feasible for quantitative trait locus (QTL) mapping and genomic selection in various crops. However, the genome complexity of allopolyploid crops like wheat still poses a significant challenge for genome-wide genotyping. Targeted sequencing of the protein-coding regions (i.e., exome) reduces sequencing costs compared to whole genome re-sequencing and can be used for marker discovery and genotyping. We developed a method called skim exome capture (SEC) that combines the strengths of these existing technologies and produces targeted genotyping data while decreasing the cost on a per-sample basis compared to traditional exome capture. Specifically, we fragmented genomic DNA using a tagmentation approach, then enriched those fragments for the low-copy genic portion of the genome using commercial wheat exome baits and multiplexed the sequencing at different levels to achieve desired coverage. We demonstrated for a library of 48 samples, ~7-8x target coverage was sufficient for high-quality variant detection. For higher multiplexing levels of 528 and 1,056 samples per library, we achieved an average coverage of 0.76x and 0.33x, respectively. Combining these lower coverage SEC sequencing data with genotype imputation using a customized wheat practical haplotype graph database (PHG) that we developed, we identified hundreds of thousands of high-quality genic variants across the genome. The SEC method can be used for high-resolution QTL mapping, genome-wide association studies, genomic selection and other downstream applications.