Maize Research Center, Beijing Academy of Agricultural and Forest Sciences (BAAFS)/Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing, 100097, China.
Provincial Key Laboratory of Agrobiology, Institute of Crop Germplasm and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, Jiangsu, China.
BMC Bioinformatics. 2021 Sep 8;22(1):429. doi: 10.1186/s12859-021-04351-w.
With the broad application of high-throughput sequencing and its reduced cost, simple sequence repeat (SSR) genotyping by sequencing (SSR-GBS) has been widely used for interpreting genetic data across different fields, including population genetic diversity and structure analysis, the construction of genetic maps, and the investigation of intraspecies relationships. The development of accurate and efficient typing strategies for SSR-GBS is urgently needed and several tools have been published. However, to date, no suitable accurate genotyping method can tolerate single nucleotide variations (SNVs) in SSRs and flanking regions. These SNVs may be caused by PCR and sequencing errors or SNPs among varieties, and they directly affect sequence alignment and genotyping accuracy.
Here, we report a new integrated strategy named the accurate microsatellite genotyping tool based on targeted sequencing (AMGT-TS) and provide a user-friendly web-based platform and command-line version of AMGT-TS. To handle SNVs in the SSRs or flanking regions, we developed a broad matching algorithm (BMA) that can quickly and accurately achieve SSR typing for ultradeep coverage and high-throughput analysis of loci with SNVs compatibility and grouping of typed reads for further in-depth information mining. To evaluate this tool, we tested 21 randomly sampled loci in eight maize varieties, accompanied by experimental validation on actual and simulated sequencing data. Our evaluation showed that, compared to other tools, AMGT-TS presented extremely accurate typing results with single base resolution for both homozygous and heterozygous samples.
This integrated strategy can achieve accurate SSR genotyping based on targeted sequencing, and it can tolerate single nucleotide variations in the SSRs and flanking regions. This method can be readily applied to divergent sequencing platforms and species and has excellent application prospects in genetic and population biology research. The web-based platform and command-line version of AMGT-TS are available at https://amgt-ts.plantdna.site:8445 and https://github.com/plantdna/amgt-ts , respectively.
随着高通量测序的广泛应用及其成本的降低，简单重复序列（SSR）测序（SSR-GBS）已广泛应用于解释不同领域的遗传数据，包括群体遗传多样性和结构分析、遗传图谱的构建以及种内关系的研究。迫切需要开发准确和高效的 SSR-GBS 分型策略，为此已经发布了几种工具。然而，迄今为止，尚无合适的准确基因分型方法能够耐受 SSR 和侧翼区域中的单核苷酸变异（SNV）。这些 SNV 可能是由 PCR 和测序错误或品种间的 SNP 引起的，它们直接影响序列比对和基因分型的准确性。
本研究报告了一种新的集成策略，称为基于靶向测序的精确微卫星基因分型工具（AMGT-TS），并提供了一个用户友好的基于网络的平台和 AMGT-TS 的命令行版本。为了处理 SSR 或侧翼区域中的 SNV，我们开发了一种广泛匹配算法（BMA），该算法可以快速准确地实现具有 SNV 兼容性的超高深度覆盖和高通量分析的 SSR 分型，并对分型读取进行分组，以进行进一步的深入信息挖掘。为了评估该工具，我们在八个玉米品种中测试了 21 个随机采样的基因座，并对实际和模拟测序数据进行了实验验证。与其他工具相比，我们的评估表明，AMGT-TS 可以实现极其准确的基因分型，具有单碱基分辨率，适用于纯合和杂合样本。
该集成策略可以基于靶向测序实现 SSR 的精确基因分型，能够耐受 SSR 和侧翼区域中的单核苷酸变异。该方法可以方便地应用于不同的测序平台和物种，在遗传和群体生物学研究中有很好的应用前景。AMGT-TS 的基于网络的平台和命令行版本可在 https://amgt-ts.plantdna.site:8445 和 https://github.com/plantdna/amgt-ts 上获取。
