ArticleNucleic acids research2017
AraPheno: a public database for Arabidopsis thaliana phenotypes.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- On the genetic origins of phenotypes in genome-wide association studies: the SAFE-hBMC bioinformatics · 2026Article
- Lightweight plant phenotypic feature extraction via transferable attention head pruning in Vision Transformers.Frontiers in plant science · 2026Article
- The effectiveness of large language models with RAG for auto-annotating trait and phenotype descriptions.Biology methods & protocols · 2025Article
- The benefits of permutation-based genome-wide association studies.Journal of experimental botany · 2024Article
- Genome-wide association studies identify loci controlling specialized seed metabolites in Arabidopsis.Plant physiology · 2024Article
- Epiallelic variation of non-coding RNA genes and their phenotypic consequences.Nature communications · 2024Article
- Crop-GPA: an integrated platform of crop gene-phenotype associations.NPJ systems biology and applications · 2024Article
- Comparison of machine learning methods for genomic prediction of selected Arabidopsis thaliana traits.PloS one · 2024Article
- networkGWAS: a network-based approach to discover genetic associations.Bioinformatics (Oxford, England) · 2023Article
- A cryptic natural variant allele of BYPASS2 suppresses the bypass1 mutant phenotype.Plant physiology · 2023Article
- AraDiv: a dataset of functional traits and leaf hyperspectral reflectance of Arabidopsis thaliana.Scientific data · 2023Article
- Analysis of Arabidopsis non-reference accessions reveals high diversity of metabolic gene clusters and discovers new candidate cluster members.Frontiers in plant science · 2023Article
- Predicting Gene Regulatory Interactions Using Natural Genetic Variation.Methods in molecular biology (Clifton, N.J.) · 2023Article
- HeliantHOME, a public and centralized database of phenotypic sunflower data.Scientific data · 2022Article
- Prioritized candidate causal haplotype blocks in plant genome-wide association studies.PLoS genetics · 2022Article
- Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributions.Bioinformatics (Oxford, England) · 2022Article
- From genotype to phenotype in Arabidopsis thaliana: in-silico genome interpretation predicts 288 phenotypes from sequencing data.Nucleic acids research · 2022Article
- cis-prenyltransferase 3 and α/β-hydrolase are new determinants of dolichol accumulation in Arabidopsis.Plant, cell & environment · 2022Article
- A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species.Frontiers in plant science · 2022Article
- Global Genetic Heterogeneity in Adaptive Traits.Molecular biology and evolution · 2021Article
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7 authors.
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No grant is acknowledged in the PubMed record.
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.
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