WGCCRR: a web-based tool for genome-wide screening of convergent indels and substitutions of amino-acids

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Bioinformatics advances Pub Date : 2024-05-24 DOI:10.1093/bioadv/vbae070
Zheng Dong, Chen Wang, Qingming Qu
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Abstract

Genome-wide analyses of protein-coding gene sequences are being employed to examine the genetic basis of adaptive evolution in many organismal groups. Previous studies have revealed that convergent/parallel adaptive evolution may be caused by convergent/parallel amino acid changes. Similarly, detailed analysis of lineage-specific amino acid changes has shown correlations with certain lineage-specific traits. However, experimental validation remains the ultimate measure of causality. With the increasing availability of genomic data, a streamlined tool for such analyses would facilitate and expedite the screening of genetic loci that hold potential for adaptive evolution, while alleviating the bioinformatic burden for experimental biologists. In this study, we present a user-friendly web-based tool called WGCCRR (Whole Genome Comparative Coding Region Read) designed to screen both convergent/parallel and lineage-specific amino acid changes on a genome-wide scale. Our tool allows users to replicate previous analyses with just a few clicks, and the exported results are straightforward to interpret. In addition, we have also included amino acid indels that are usually neglected in previous work. Our website provides an efficient platform for screening candidate loci for downstream experimental tests. It is available at: https://fishevo.xmu.edu.cn/.
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WGCCRR:基于网络的全基因组聚合嵌合和氨基酸替换筛选工具
蛋白质编码基因序列的全基因组分析被用来研究许多生物群体适应性进化的遗传基础。以往的研究表明,趋同/平行适应性进化可能是由趋同/平行氨基酸变化引起的。同样,对特定品系氨基酸变化的详细分析也显示出与某些特定品系性状的相关性。然而,实验验证仍然是衡量因果关系的最终标准。随着基因组数据可用性的不断提高,用于此类分析的简化工具将促进并加快筛选具有适应性进化潜力的基因位点,同时减轻实验生物学家的生物信息学负担。在本研究中,我们介绍了一种基于网络的用户友好型工具,名为 WGCCRR(全基因组编码区比较读取),旨在全基因组范围内筛选会聚/平行和品系特异性氨基酸变化。我们的工具让用户只需点击几下就能复制以前的分析,导出的结果也易于解释。此外,我们还加入了在以往工作中通常被忽略的氨基酸嵌合体。我们的网站为下游实验测试筛选候选基因位点提供了一个高效的平台。网址:https://fishevo.xmu.edu.cn/。
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