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

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 a...

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Autores principales: Togninalli, Matteo, Seren, Ümit, Freudenthal, Jan A, Monroe, J Grey, Meng, Dazhe, Nordborg, Magnus, Weigel, Detlef, Borgwardt, Karsten, Korte, Arthur, Grimm, Dominik G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145550/
https://www.ncbi.nlm.nih.gov/pubmed/31642487
http://dx.doi.org/10.1093/nar/gkz925
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author Togninalli, Matteo
Seren, Ümit
Freudenthal, Jan A
Monroe, J Grey
Meng, Dazhe
Nordborg, Magnus
Weigel, Detlef
Borgwardt, Karsten
Korte, Arthur
Grimm, Dominik G
author_facet Togninalli, Matteo
Seren, Ümit
Freudenthal, Jan A
Monroe, J Grey
Meng, Dazhe
Nordborg, Magnus
Weigel, Detlef
Borgwardt, Karsten
Korte, Arthur
Grimm, Dominik G
author_sort Togninalli, Matteo
collection PubMed
description 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.
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spelling pubmed-71455502020-04-13 AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana Togninalli, Matteo Seren, Ümit Freudenthal, Jan A Monroe, J Grey Meng, Dazhe Nordborg, Magnus Weigel, Detlef Borgwardt, Karsten Korte, Arthur Grimm, Dominik G Nucleic Acids Res Database Issue 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. Oxford University Press 2020-01-08 2019-10-23 /pmc/articles/PMC7145550/ /pubmed/31642487 http://dx.doi.org/10.1093/nar/gkz925 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Issue
Togninalli, Matteo
Seren, Ümit
Freudenthal, Jan A
Monroe, J Grey
Meng, Dazhe
Nordborg, Magnus
Weigel, Detlef
Borgwardt, Karsten
Korte, Arthur
Grimm, Dominik G
AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana
title AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana
title_full AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana
title_fullStr AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana
title_full_unstemmed AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana
title_short AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana
title_sort arapheno and the aragwas catalog 2020: a major database update including rna-seq and knockout mutation data for arabidopsis thaliana
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145550/
https://www.ncbi.nlm.nih.gov/pubmed/31642487
http://dx.doi.org/10.1093/nar/gkz925
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