大麦测序基因分型进展

Genotyping by Sequencing Advancements in Barley.

作者信息

Rajendran Nirmal Raj, Qureshi Naeela, Pourkheirandish Mohammad

机构信息

Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, VIC, Australia.

International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Estado de Mexico, Mexico.

出版信息

Front Plant Sci. 2022 Aug 8;13:931423. doi: 10.3389/fpls.2022.931423. eCollection 2022.

Abstract

Barley is considered an ideal crop to study cereal genetics due to its close relationship with wheat and diploid ancestral genome. It plays a crucial role in reducing risks to global food security posed by climate change. Genetic variations in the traits of interest in crops are vital for their improvement. DNA markers have been widely used to estimate these variations in populations. With the advancements in next-generation sequencing, breeders could access different types of genetic variations within different lines, with single-nucleotide polymorphisms (SNPs) being the most common type. However, genotyping barley with whole genome sequencing (WGS) is challenged by the higher cost and computational demand caused by the large genome size (5.5GB) and a high proportion of repetitive sequences (80%). Genotyping-by-sequencing (GBS) protocols based on restriction enzymes and target enrichment allow a cost-effective SNP discovery by reducing the genome complexity. In general, GBS has opened up new horizons for plant breeding and genetics. Though considered a reliable alternative to WGS, GBS also presents various computational difficulties, but GBS-specific pipelines are designed to overcome these challenges. Moreover, a robust design for GBS can facilitate the imputation to the WGS level of crops with high linkage disequilibrium. The complete exploitation of GBS advancements will pave the way to a better understanding of crop genetics and offer opportunities for the successful improvement of barley and its close relatives.

摘要

由于大麦与小麦关系密切且拥有二倍体祖先基因组,它被认为是研究谷物遗传学的理想作物。在降低气候变化对全球粮食安全造成的风险方面,大麦发挥着关键作用。作物中目标性状的遗传变异对其改良至关重要。DNA标记已被广泛用于估计群体中的这些变异。随着下一代测序技术的进步,育种者能够获取不同品系内不同类型的遗传变异,其中单核苷酸多态性(SNP)是最常见的类型。然而,由于大麦基因组庞大(5.5GB)且重复序列比例高(80%),全基因组测序(WGS)对大麦进行基因分型面临成本高和计算需求大的挑战。基于限制性酶和目标富集的简化基因组测序(GBS)方案通过降低基因组复杂性实现了经济高效的SNP发现。总体而言,GBS为植物育种和遗传学开辟了新视野。尽管GBS被认为是WGS的可靠替代方法,但它也存在各种计算难题,不过专门设计的GBS流程可克服这些挑战。此外,GBS的稳健设计有助于将高连锁不平衡的作物基因分型提升到WGS水平。充分利用GBS的进展将为更好地理解作物遗传学铺平道路,并为成功改良大麦及其近缘种提供机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c562/9394214/96c94b5c108b/fpls-13-931423-g001.jpg

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