Alves Sandy Ingrid Aguiar, Dantas Carlos Willian Dias, Macedo Daralyns Borges, Ramos Rommel Thiago Jucá
Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Laboratory of Simulation and Computational Biology - SIMBIC, High Performance Computing Center - CCAD, Federal University of Pará, Belém, Pará, Brazil.
Front Genet. 2024 Nov 13;15:1474611. doi: 10.3389/fgene.2024.1474611. eCollection 2024.
Microsatellites, also known as SSR or STR, are essential molecular markers in genomic research, playing crucial roles in genetic mapping, population genetics, and evolutionary studies. Their applications range from plant breeding to forensics, highlighting their diverse utility across disciplines. Despite their widespread use, traditional methods for SSR analysis are often laborious and time-consuming, requiring significant resources and expertise. To address these challenges, a variety of computational tools for SSR analysis have been developed, offering faster and more efficient alternatives to traditional methods. However, selecting the most appropriate tool can be daunting due to rapid technological advancements and the sheer number of options available. This study presents a comprehensive review and analysis of 74 SSR tools, aiming to provide researchers with a valuable resource for SSR analysis tool selection. The methodology employed includes thorough literature reviews, detailed tool comparisons, and in-depth analyses of tool functionality. By compiling and analyzing these tools, this study not only advances the field of genomic research but also contributes to the broader scientific community by facilitating informed decision-making in the selection of SSR analysis tools. Researchers seeking to understand SSRs and select the most appropriate tools for their projects will benefit from this comprehensive guide. Overall, this study enhances our understanding of SSR analysis tools, paving the way for more efficient and effective SSR research in various fields of study.
微卫星，也称为简单序列重复（SSR）或短串联重复序列（STR），是基因组研究中必不可少的分子标记，在遗传图谱构建、群体遗传学和进化研究中发挥着关键作用。它们的应用范围从植物育种到法医学，凸显了其在各学科中的多样用途。尽管微卫星标记被广泛使用，但传统的SSR分析方法通常既费力又耗时，需要大量资源和专业知识。为应对这些挑战，已开发出多种用于SSR分析的计算工具，为传统方法提供了更快、更高效的替代方案。然而，由于技术的快速进步和可用选项的数量众多，选择最合适的工具可能具有挑战性。本研究对74种SSR工具进行了全面综述和分析，旨在为研究人员提供一份关于SSR分析工具选择的宝贵资源。所采用的方法包括全面的文献综述、详细的工具比较以及对工具功能的深入分析。通过汇编和分析这些工具，本研究不仅推动了基因组研究领域的发展，还通过促进在SSR分析工具选择中的明智决策，为更广泛的科学界做出了贡献。寻求了解微卫星标记并为其项目选择最合适工具的研究人员将从这份全面指南中受益。总体而言，本研究增进了我们对SSR分析工具的理解，为各研究领域中更高效、更有效的SSR研究铺平了道路。
