SSREnricher: a computational approach for large-scale identification of polymorphic microsatellites based on comparative transcriptome analysis
SSREnricher: a computational approach for large-scale identification of polymorphic microsatellites based on comparative transcriptome analysis
复制标题
SSREnricher：一种基于比较转录组分析的大规模多态微卫星识别计算方法
DOI：
10.7717/peerj.9372
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发表时间：
2020-07-02
期刊：
影响因子：
2.7
通讯作者：
Du, Zongjun
中科院分区：
文献类型：
--
作者：
Luo, Wei;Wu, Qing;Du, Zongjun
微卫星（SSR）标记是动植物遗传分析和分子选择育种中最常用的标记。然而，目前可用的方法来开发SSR是相对耗时和昂贵的。最重要的因素之一是多态性SSR的频率较低。本研究开发了一个软件SSREnricher，该软件包括SSR挖掘、序列聚类、序列修改、富集多态性SSR序列、假阳性去除和结果输出以及多序列比对等6个核心分析程序。在该软件上运行转录组序列后，可以鉴定出大量的多态性SSR。验证实验表明，几乎所有的标记（>90%），被鉴定为推定的多态性标记确实是多态性的。SSREEnricher方法检测到的多态性位点频率显著高于传统方法和HTS方法（P < 0.05）。该软件包可在GitHub（https：//github.com/byemaxx/SSREnricher）上公开访问。
Microsatellite (SSR) markers are the most popular markers for genetic analyses and molecular selective breeding in plants and animals. However, the currently available methods to develop SSRs are relatively time-consuming and expensive. One of the most factors is low frequency of polymorphic SSRs. In this study, we developed a software, SSREnricher, which composes of six core analysis procedures, including SSR mining, sequence clustering, sequence modification, enrichment containing polymorphic SSR sequences, false-positive removal and results output and multiple sequence alignment. After running of transcriptome sequences on this software, a mass of polymorphic SSRs can be identified. The validation experiments showed almost all markers (>90%) that were identified by the SSREnricher as putative polymorphic markers were indeed polymorphic. The frequency of polymorphic SSRs identified by SSREnricher was significantly higher (P < 0.05) than that of traditional and HTS approaches. The software package is publicly accessible on GitHub (https://github.com/byemaxx/SSREnricher).