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Abstract：
Thousands of sequenced genomes are now publicly available capturing a significant amount of natural variation within plant species; yet, much of these data remain inaccessible to researchers without significant bioinformatics experience. Here, we present a webtool called ViVa (Visualizing Variation) which aims to empower any researcher to take advantage of the amazing genetic resource collected in the Arabidopsis thaliana 1001 Genomes Project (http://1001genomes.org). ViVa facilitates data mining on the gene, gene family, or gene network level. To test the utility and accessibility of ViVa, we assembled a team with a range of expertise within biology and bioinformatics to analyze the natural variation within the well-studied nuclear auxin signaling pathway. Our analysis has provided further confirmation of existing knowledge and has also helped generate new hypotheses regarding this well-studied pathway. These results highlight how natural variation could be used to generate and test hypotheses about less-studied gene families and networks, especially when paired with biochemical and genetic characterization. ViVa is also readily extensible to databases of interspecific genetic variation in plants as well as other organisms, such as the 3,000 Rice Genomes Project ( http://snp-seek.irri.org/) and human genetic variation ( https://www.ncbi.nlm.nih.gov/clinvar/).
摘要：
数以千计的测序基因组现在公开获取植物物种中大量的自然变异；然而，在没有重要生物信息学经验的情况下，研究人员仍然无法获得这些数据中的大部分。这里,我们提出了一个名为ViVa（可视化变异）的webtool，旨在使任何研究人员能够利用拟南芥1001基因组计划（http://1001genomes.org）中收集的惊人遗传资源。ViVa促进了对基因的数据挖掘，基因家族，或基因网络水平。要测试ViVa的实用性和可访问性，我们组建了一个具有生物学和生物信息学专业知识的团队,以分析经过充分研究的核生长素信号通路中的自然变异.我们的分析提供了对现有知识的进一步确认，也有助于产生关于这种经过充分研究的途径的新假设。这些结果强调了如何使用自然变异来生成和测试有关研究较少的基因家族和网络的假设。特别是与生化和遗传特征配对时。ViVa也很容易扩展到植物以及其他生物体种间遗传变异的数据库。例如3,000个水稻基因组项目（http://snp-seek。irri.org/）和人类遗传变异（https://www。ncbi.nlm.nih.gov/clinvar/)。
