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高通量 SNP 基因型数据对大麦多样性估计的确定偏差和标记数量的影响。

Effects of ascertainment bias and marker number on estimations of barley diversity from high-throughput SNP genotype data.

机构信息

Division of Plant Sciences, University of Dundee at SCRI, Dundee, UK.

出版信息

Theor Appl Genet. 2010 May;120(8):1525-34. doi: 10.1007/s00122-010-1273-1. Epub 2010 Feb 16.

Abstract

The capability of molecular markers to provide information of genetic structure is influenced by their number and the way they are chosen. This study evaluates the effects of single nucleotide polymorphism (SNP) number and selection strategy on estimates of germplasm diversity and population structure for different types of barley germplasm, namely cultivar and landrace. One hundred and sixty-nine barley landraces from Syria and Jordan and 171 European barley cultivars were genotyped with 1536 SNPs. Different subsets of 384 and 96 SNPs were selected from the 1536 set, based on their ability to detect diversity in landraces or cultivated barley in addition to corresponding randomly chosen subsets. All SNP sets except the landrace-optimised subsets underestimated the diversity present in the landrace germplasm, and all subsets of SNP gave similar estimates for cultivar germplasm. All marker subsets gave qualitatively similar estimates of the population structure in both germplasm sets, but the 96 SNP sets showed much lower data resolution values than the larger SNP sets. From these data we deduce that pre-selecting markers for their diversity in a germplasm set is very worthwhile in terms of the quality of data obtained. Second, we suggest that a properly chosen 384 SNP subset gives a good combination of power and economy for germplasm characterization, whereas the rather modest gain from using 1536 SNPs does not justify the increased cost and 96 markers give unacceptably low performance. Lastly, we propose a specific 384 SNP subset as a standard genotyping tool for middle-eastern landrace barley.

摘要

分子标记的遗传结构信息提供能力受其数量和选择方式的影响。本研究评估了单核苷酸多态性(SNP)数量和选择策略对不同类型大麦种质资源遗传多样性和群体结构估计的影响,这些类型包括品种和地方品种。169 份来自叙利亚和约旦的大麦地方品种和 171 份欧洲大麦品种用 1536 个 SNP 进行了基因型分析。从 1536 个 SNP 中选择了 384 个和 96 个 SNP 的不同子集,这些子集基于其在地方品种或栽培大麦中检测多样性的能力,以及相应的随机选择子集。除了地方品种优化子集外,所有 SNP 集都低估了地方品种种质中的多样性,所有 SNP 子集对品种种质的多样性估计都相似。所有标记子集对两个种质群体的群体结构都给出了定性相似的估计,但 96 个 SNP 集的分辨率值明显低于较大的 SNP 集。从这些数据中,我们推断出,根据种质资源集中的多样性预先选择标记对于获得的数据质量非常有价值。其次,我们建议,适当选择的 384 个 SNP 子集可以很好地结合功率和经济性,用于种质特征描述,而使用 1536 个 SNP 所带来的适度增益并不能证明增加成本是合理的,而 96 个标记的性能则不能接受。最后,我们提出了一个特定的 384 SNP 子集作为中东地方品种大麦的标准基因分型工具。

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