ArticleGenome biology2019
WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Neutral transcriptome rewiring promotes quantitative disease resistance evolvability at the species level.The Plant cell · 2025Article
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- Genomic resources in plant breeding for sustainable agriculture.Journal of plant physiology · 2021Review
- Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits inFrontiers in plant science · 2021Article
- Physical Dormancy Release inPlants (Basel, Switzerland) · 2020Article
- WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants.Genome biology · 2019Article
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Authors and funding
9 authors.
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Abstract
The explosive growth of genomic data provides an opportunity to make increased use of sequence variations for phenotype prediction. We have developed a prediction machine for quantitative phenotypes (WhoGEM) that overcomes some of the bottlenecks limiting the current methods. We demonstrated its performance by predicting quantitative disease resistance and quantitative functional traits in the wild model plant species, Medicago truncatula, using geographical locations as covariates for admixture analysis. The method's prediction reliability equals or outperforms all existing algorithms for quantitative phenotype prediction. WhoGEM analysis produces evidence that variation in genome admixture proportions explains most of the phenotypic variation for quantitative phenotypes.
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