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. 2020 Jan 8;48(D1):D1063-D1068.
doi: 10.1093/nar/gkz925.

AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana

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Free PMC article

AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana

Matteo Togninalli et al. Nucleic Acids Res. .
Free PMC article

Abstract

Genome-wide association studies (GWAS) are integral for studying genotype-phenotype relationships and gaining a deeper understanding of the genetic architecture underlying trait variation. A plethora of genetic associations between distinct loci and various traits have been successfully discovered and published for the model plant Arabidopsis thaliana. This success and the free availability of full genomes and phenotypic data for more than 1,000 different natural inbred lines led to the development of several data repositories. AraPheno (https://arapheno.1001genomes.org) serves as a central repository of population-scale phenotypes in A. thaliana, while the AraGWAS Catalog (https://aragwas.1001genomes.org) provides a publicly available, manually curated and standardized collection of marker-trait associations for all available phenotypes from AraPheno. In this major update, we introduce the next generation of both platforms, including new data, features and tools. We included novel results on associations between knockout-mutations and all AraPheno traits. Furthermore, AraPheno has been extended to display RNA-Seq data for hundreds of accessions, providing expression information for over 28 000 genes for these accessions. All data, including the imputed genotype matrix used for GWAS, are easily downloadable via the respective databases.

Figures

Figure 1.
Figure 1.
Detailed association view. This view shows detailed information about the alleles and the allelic distribution of phenotypic values for a selected association. The association table gives individual information about each sample, the allele and phenotype value as well as all associated meta-information (e.g. geographic coordinates). All plots can be adjusted dynamically and data can be exported in CSV format directly within the browser (https://aragwas.1001genomes.org/#/study/262/associations/5_18592588).
Figure 2.
Figure 2.
KO-trait association detected between AT1G57570 and days of seed dry storage required to reach 50% germination (DSDS50) reported by (1). (A) Predicted natural knockout alleles identified in (35). (B) Boxplots showing DSDS50 for accessions with functional (black) versus KO alleles (orange) of AT1G57570. The vertical lines mark the medians while the boxes indicate the interquartile ranges (IQR) between the 25th and 75th quantiles, and the whiskers mark no >1.5 IQR. More broadly, there was a tendency for significant KO allele associations to have positive beta coefficients. Bar plots show the relative frequency of positive and negative beta (β) coefficients across all traits tested (***P < 2 × 10−16, *P < 0.05, Chi-squared tests), for (C) all associations regardless of significance and for associations subsetted by varying significance thresholds: (D) P < 0.05, (E) P < 0.01, (F) P < 0.001, (G) P < 1 × 10−4, (H) P < 2.4 × 10−5 (threshold after Bonferroni correction) (I) permutation-based significance thresholds.

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References

    1. Atwell S., Huang Y.S., Vilhjálmsson B.J., Willems G., Horton M., Li Y., Meng D., Platt A., Tarone A.M., Hu T.T. et al. .. Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature. 2010; 465:627–631. - PMC - PubMed
    1. Koornneef M., Meinke D.. The development of Arabidopsis as a model plant. Plant J. 2010; 61:909–921. - PubMed
    1. Alonso-Blanco C., Andrade J., Becker C., Bemm F., Bergelson J., Borgwardt K.M., Cao J., Chae E., Dezwaan T.M., Ding W. et al. .. 1,135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. Cell. 2016; 166:481–491. - PMC - PubMed
    1. Sugiyama M., Azencott C., Grimm D., Kawahara Y., Borgwardt K.. Multi-Task feature selection on multiple networks via maximum flows. Proceedings of the 2014 SIAM International Conference on Data Mining, Proceedings. 2014; Society for Industrial and Applied Mathematics; 199–207.
    1. Llinares-López F., Grimm D.G., Bodenham D.A., Gieraths U., Sugiyama M., Rowan B., Borgwardt K.. Genome-wide detection of intervals of genetic heterogeneity associated with complex traits. Bioinformatics. 2015; 31:i240–i249. - PMC - PubMed

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