Abstract
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.
Highlights
Genome-wide association studies (GWAS) are rapidly becoming the dominant paradigm for investigating the genetics of natural phenotypic variation
GWAS have primarily been used for human diseases, they have been successful in mapping causal variants in many other organisms, including Arabidopsis thaliana, which is an ideal organism for such studies
The Manhattan plot supports zooming, which can be achieved by a “click, hold, and drag mouse” gesture that defines the area for the zoom action
Summary
Genome-wide association studies (GWAS) are rapidly becoming the dominant paradigm for investigating the genetics of natural phenotypic variation. GWAS have primarily been used for human diseases, they have been successful in mapping causal variants in many other organisms, including Arabidopsis thaliana, which is an ideal organism for such studies. We present GWAPP, a user-friendly and interactive Web application for GWAS in A. thaliana. GWAPP places a strong emphasis on informative and efficient visualization tools for interpreting the GWAS results and provides interactive features that allow for hands-on in-depth analysis. Using efficient implementations of both a Wilcoxon rank sum test and an approximate mixed model (Kang et al, 2010; Zhang et al, 2010), the mapping is performed on-the-fly, with genome-wide scans for ;206,000 single nucleotide polymorphisms (SNPs) and 1386 individuals completed in minutes. GWAPP enables the user to view, select subsets, and choose an appropriate transformation
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