USDA-ARS, Hard Winter Wheat Genetics Research Unit, Center for Grain and Animal Health Research, Manhattan, Kansas, USA.
Plant Genome. 2023 Dec;16(4):e20381. doi: 10.1002/tpg2.20381. Epub 2023 Aug 21.
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 such as wheat (Triticum aestivum L.) 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 that for a library of 48 samples, ∼7-8× target coverage was sufficient for high-quality variant detection. For higher multiplexing levels of 528 and 1056 samples per library, we achieved an average coverage of 0.76× and 0.32×, respectively. Combining these lower coverage SEC sequencing data with genotype imputation using a customized wheat practical haplotype graph database 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.
下一代测序（NGS）技术的进步不断降低了高通量全基因组基因分型的成本，从而应用于育种和遗传学研究。全基因组低覆盖度的简化测序（skim sequencing）已经可以用于各种作物的数量性状位点（QTL）作图和基因组选择。然而，小麦（Triticum aestivum L.）等异源多倍体作物的基因组复杂性仍然对全基因组基因分型构成了重大挑战。与全基因组重测序相比，对蛋白质编码区（即外显子）进行靶向测序可以降低测序成本，并且可以用于标记发现和基因分型。我们开发了一种名为简化外显子捕获（skim exome capture，SEC）的方法，该方法结合了现有技术的优势，在降低每个样本成本的基础上，产生了靶向基因分型数据，与传统的外显子捕获相比。具体来说，我们使用标签化方法对基因组 DNA 进行片段化，然后使用商业小麦外显子诱饵对基因组中低拷贝基因部分进行富集，并在不同水平上进行测序，以实现所需的覆盖度。我们证明，对于 48 个样本的文库，约 7-8×的目标覆盖度足以进行高质量的变异检测。对于更高的 528 和 1056 个样本/文库的多重化水平，我们分别实现了 0.76×和 0.32×的平均覆盖度。将这些较低覆盖度的 SEC 测序数据与我们开发的定制小麦实用单倍型图数据库的基因型推断相结合，我们在整个基因组中鉴定了数十万高质量的基因变异。SEC 方法可用于高分辨率 QTL 作图、全基因组关联研究、基因组选择和其他下游应用。
