GWAPP: A Web Application for Genome-Wide Association Mapping in Arabidopsis
GWAPP: A Web Application for Genome-Wide Association Mapping in Arabidopsis
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DOI：
10.1105/tpc.112.108068
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发表时间：
2012-12-01
期刊：
影响因子：
11.6
通讯作者：
Nordborg, Magnus
中科院分区：
文献类型：
--
作者：
Seren, Uemit;Vilhjalmsson, Bjarni J.;Nordborg, Magnus
拟南芥是研究植物遗传学和分子生物学的重要模式生物。它的高度自交性，小尺寸，短世代时间，小基因组大小和广泛的地理分布使其成为了解自然变异的理想模式生物。全基因组关联研究（GWAS）已被证明是一种有效的技术，以确定遗传位点负责的自然变异，在A。thaliana.先前基因分型的种质（天然近交系）可以在不同条件下重复生长，并对不同性状进行表型分析。这些重要的特征极大地简化了性状的关联作图，并允许通过整个A. Thaliana社区为了促进这一点，我们提出了GWAPP，一个交互式的基于Web的应用程序进行GWAS在A。thaliana.使用线性混合模型的有效实现，可以在几分钟内上传并使用混合模型和其他方法绘制1386个公开可用生态型的子集的性状。GWAPP具有广泛的，交互式的，用户友好的界面，包括交互式曼哈顿图和连锁不平衡图。它还通过实现诸如在模型中包含候选多态性作为辅因子等功能来促进探索性数据分析。
Arabidopsis thaliana is an important model organism for understanding the genetics and molecular biology of plants. Its highly selfing nature, small size, short generation time, small genome size, and wide geographic distribution make it an ideal model organism for understanding natural variation. Genome-wide association studies (GWAS) have proven a useful technique for identifying genetic loci responsible for natural variation in A. thaliana. Previously genotyped accessions (natural inbred lines) can be grown in replicate under different conditions and phenotyped for different traits. These important features greatly simplify association mapping of traits and allow for systematic dissection of the genetics of natural variation by the entire A. thaliana community. To facilitate this, we present GWAPP, an interactive Web-based application for conducting GWAS in A. thaliana. Using an efficient implementation of a linear mixed model, traits measured for a subset of 1386 publicly available ecotypes can be uploaded and mapped with a mixed model and other methods in just a couple of minutes. GWAPP features an extensive, interactive, and user-friendly interface that includes interactive Manhattan plots and linkage disequilibrium plots. It also facilitates exploratory data analysis by implementing features such as the inclusion of candidate polymorphisms in the model as cofactors.