Department of Biochemistry and Molecular Biology, University of Nevada, Reno, NV, United States of America.
Nevada Center for Bioinformatics, University of Nevada, Reno, NV, United States of America.
PLoS One. 2021 Mar 8;16(3):e0248213. doi: 10.1371/journal.pone.0248213. eCollection 2021.
Recent plant breeding studies of several species have demonstrated the utility of combining molecular assessments of genetic distance into trait-linked SNP genotyping during the development of parent lines to maximize yield gains due to heterosis. SSRs (Short Sequence Repeats) are the molecular marker of choice to determine genetic diversity, but the methods historically used to sequence them have been burdensome. The ability to analyze SSRs in a higher-throughput manner independent of laboratory conditions would increase their utility in molecular ecology, germplasm curation, and plant breeding programs worldwide. This project reports simple bioinformatics methods that can be used to generate genome-wide de novo SSRs in silico followed by targeted Next Generation Sequencing (NGS) validation of those that provide the most information about sub-population identity of a breeding line, which influences heterotic group selection. While these methods were optimized in sorghum [Sorghum bicolor (L.) Moench], they were developed to be applied to any species with a reference genome and high-coverage whole-genome sequencing data of individuals from the sub-populations to be characterized. An analysis of published sorghum genomes selected to represent its five main races (bicolor, caudatum, durra, kafir, and guinea; 75 accessions total) identified 130,120 SSR motifs. Average lengths were 23.8 bp and 95% were between 10 and 92 bp, making them suitable for NGS. Validation through targeted sequencing amplified 188 of 192 assayed SSR loci. Results highlighted the distinctness of accessions from the guinea sub-group margaritiferum from all other sorghum accessions, consistent with previous studies of nuclear and mitochondrial DNA. SSRs that efficiently fingerprinted margaritiferum individuals (Xgma1 -Xgma6) are presented. Developing similar fingerprints of other sub-populations (Xunr1 -Xunr182) was not possible due to the extensive admixture between them in the data set analyzed. In summary, these methods were able to fingerprint specific sub-populations when rates of admixture between them are low.
最近对几个物种的植物育种研究表明，在亲本系的开发过程中，将遗传距离的分子评估与与性状相关的 SNP 基因分型相结合，以最大限度地提高杂种优势的产量增益是有用的。SSR（短序列重复）是确定遗传多样性的首选分子标记，但历史上用于测序它们的方法繁琐。能够在不受实验室条件限制的情况下以更高的通量分析 SSR，将增加它们在分子生态学、种质保存和世界各地的植物育种计划中的实用性。本项目报告了简单的生物信息学方法，可用于在计算机上生成全基因组从头 SSR，然后对那些提供有关育种系亚种群身份的最多信息的 SSR 进行靶向下一代测序（NGS）验证，亚种群身份影响杂种优势群的选择。虽然这些方法在高粱[高粱（L.）Moench]中进行了优化，但它们是为应用于任何具有参考基因组和来自要表征的亚种群的个体的高覆盖率全基因组测序数据的物种而开发的。对代表高粱五个主要品种（二色、尾穗、杜拉、卡菲尔和几内亚；75 个品系总计）的已发表高粱基因组的分析鉴定出 130,120 个 SSR 基序。平均长度为 23.8bp，95%的长度在 10 到 92bp 之间，适合 NGS。通过靶向测序验证扩增了 192 个测定 SSR 位点中的 188 个。结果突出了来自几内亚亚群 margaritiferum 的品系与高粱所有其他品系的不同，与核和线粒体 DNA 的先前研究一致。提出了有效指纹 margaritiferum 个体的 SSRs（Xgma1 -Xgma6）。由于在分析的数据集之间存在广泛的杂交，因此无法对其他亚种群（Xunr1 -Xunr182）进行类似的指纹开发。总之，当它们之间的杂交率较低时，这些方法能够对特定的亚种群进行指纹识别。
