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Nucleic Acids Res. 2017 Jan 4;45(D1):D1054-D1059. doi: 10.1093/nar/gkw986. Epub 2016 Oct 24.

AraPheno: a public database for Arabidopsis thaliana phenotypes.

Author information

1
Gregor Mendel Institute of Molecular Plant Biology, Vienna, Austria.
2
Machine Learning and Computational Biology Lab, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
3
Max Planck Institute for Developmental Biology, Tübingen, Germany.
4
Center for Computational and Theoretical Biology, University Würzburg, Würzburg, Germany arthur.korte@uni-wuerzburg.de.

Abstract

Natural genetic variation makes it possible to discover evolutionary changes that have been maintained in a population because they are advantageous. To understand genotype-phenotype relationships and to investigate trait architecture, the existence of both high-resolution genotypic and phenotypic data is necessary. Arabidopsis thaliana is a prime model for these purposes. This herb naturally occurs across much of the Eurasian continent and North America. Thus, it is exposed to a wide range of environmental factors and has been subject to natural selection under distinct conditions. Full genome sequencing data for more than 1000 different natural inbred lines are available, and this has encouraged the distributed generation of many types of phenotypic data. To leverage these data for meta analyses, AraPheno (https://arapheno.1001genomes.org) provide a central repository of population-scale phenotypes for A. thaliana inbred lines. AraPheno includes various features to easily access, download and visualize the phenotypic data. This will facilitate a comparative analysis of the many different types of phenotypic data, which is the base to further enhance our understanding of the genotype-phenotype map.

PMID:
27924043
PMCID:
PMC5210660
DOI:
10.1093/nar/gkw986
[Indexed for MEDLINE]
Free PMC Article

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