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利用简化基因组测序(GBS)技术进行栽培燕麦的基因组发现研究。

Using genotyping-by-sequencing (GBS) for genomic discovery in cultivated oat.

作者信息

Huang Yung-Fen, Poland Jesse A, Wight Charlene P, Jackson Eric W, Tinker Nicholas A

机构信息

Eastern Cereal and Oilseed Research Centre, Agriculture and Agri-Food Canada, Ottawa, Ontario, Canada.

Department of Plant Pathology, Kansas State University, Manhattan, Kansas, United States of America.

出版信息

PLoS One. 2014 Jul 21;9(7):e102448. doi: 10.1371/journal.pone.0102448. eCollection 2014.

Abstract

Advances in next-generation sequencing offer high-throughput and cost-effective genotyping alternatives, including genotyping-by-sequencing (GBS). Results have shown that this methodology is efficient for genotyping a variety of species, including those with complex genomes. To assess the utility of GBS in cultivated hexaploid oat (Avena sativa L.), seven bi-parental mapping populations and diverse inbred lines from breeding programs around the world were studied. We examined technical factors that influence GBS SNP calls, established a workflow that combines two bioinformatics pipelines for GBS SNP calling, and provided a nomenclature for oat GBS loci. The high-throughput GBS system enabled us to place 45,117 loci on an oat consensus map, thus establishing a positional reference for further genomic studies. Using the diversity lines, we estimated that a minimum density of one marker per 2 to 2.8 cM would be required for genome-wide association studies (GWAS), and GBS markers met this density requirement in most chromosome regions. We also demonstrated the utility of GBS in additional diagnostic applications related to oat breeding. We conclude that GBS is a powerful and useful approach, which will have many additional applications in oat breeding and genomic studies.

摘要

新一代测序技术的进步提供了高通量且经济高效的基因分型替代方法,包括简化基因组测序(GBS)。结果表明,这种方法对于多种物种的基因分型是有效的,包括那些具有复杂基因组的物种。为了评估GBS在栽培六倍体燕麦(Avena sativa L.)中的实用性,研究了来自世界各地育种项目的七个双亲子代作图群体和不同的近交系。我们研究了影响GBS单核苷酸多态性(SNP)分型的技术因素,建立了一个结合两个生物信息学流程进行GBS SNP分型的工作流程,并为燕麦GBS位点提供了命名法。高通量GBS系统使我们能够在燕麦一致性图谱上定位45,117个位点,从而为进一步的基因组研究建立了位置参考。利用这些多样性品系,我们估计全基因组关联研究(GWAS)每2至2.8厘摩需要一个标记的最低密度,并且GBS标记在大多数染色体区域满足了这一密度要求。我们还证明了GBS在与燕麦育种相关的其他诊断应用中的实用性。我们得出结论,GBS是一种强大且有用的方法,它将在燕麦育种和基因组研究中有许多其他应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0923/4105502/3971bdaf1c2c/pone.0102448.g001.jpg

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