ArticleBMC genomics2019
Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Genome-phenome association prediction using weighted deep matrix factorization with a multisource graph attention network.Quantitative biology (Beijing, China) · 2026Article
- An epidemiological knowledge graph extracted from the World Health Organization's Disease Outbreak News.Scientific data · 2025Article
- An ontology-based knowledge graph for representing interactions involving RNA molecules.Scientific data · 2024Article
- Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences.Database : the journal of biological databases and curation · 2023Review
- Genomic analysis of a new heterotic maize group reveals key loci for pedigree breeding.Frontiers in plant science · 2023Article
- PlantGSAD: a comprehensive gene set annotation database for plant species.Nucleic acids research · 2022Article
- Contrasting Water Withholding Responses of Young Maize Plants Reveal Link Between Lipid Peroxidation and Osmotic Regulation Corroborated by Genetic Analysis.Frontiers in plant science · 2022Article
- Will Plant Genome Editing Play a Decisive Role in "Quantum-Leap" Improvements in Crop Yield to Feed an Increasing Global Human Population?Plants (Basel, Switzerland) · 2021Review
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Authors and funding
8 authors.
Funding
Abstract
backgroundTrait ontology (TO) analysis is a powerful system for functional annotation and enrichment analysis of genes. However, given the complexity of the molecular mechanisms underlying phenomes, only a few hundred gene-to-TO relationships in plants have been elucidated to date, limiting the pace of research in this "big data" era.
resultsHere, we curated all the available trait associated sites (TAS) information from 79 association mapping studies of maize (Zea mays L.) and rice (Oryza sativa L.) lines with diverse genetic backgrounds and built a large-scale TAS-derived TO system for functional annotation of genes in various crops. Our TO system contains information for up to 18,042 genes (6345 in maize at the 25 k level and 11,697 in rice at the 50 k level), including gene-to-TO relationships, which covers over one fifth of the annotated gene sets for maize and rice. A comparison of Gene Ontology (GO) vs. TO analysis demonstrated that the TAS-derived TO system is an efficient alternative tool for gene functional annotation and enrichment analysis. We therefore combined information from the TO, GO, metabolic pathway, and co-expression network databases and constructed the TAS system, which is publicly available at http://tas.hzau.edu.cn . TAS provides a user-friendly interface for functional annotation of genes, enrichment analysis, genome-wide extraction of trait-associated genes, and crosschecking of different functional annotation databases.
conclusionsTAS bridges the gap between genomic and phenomic information in crops. This easy-to-use tool will be useful for geneticists, biologists, and breeders in the agricultural community, as it facilitates the dissection of molecular mechanisms conferring agronomic traits in an easy, genome-wide manner.
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