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Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics
BACKGROUND: Trait 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 pa...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547493/ https://www.ncbi.nlm.nih.gov/pubmed/31159731 http://dx.doi.org/10.1186/s12864-019-5812-0 |
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author | Pan, Qingchun Wei, Junfeng Guo, Feng Huang, Suiyong Gong, Yong Liu, Hao Liu, Jianxiao Li, Lin |
author_facet | Pan, Qingchun Wei, Junfeng Guo, Feng Huang, Suiyong Gong, Yong Liu, Hao Liu, Jianxiao Li, Lin |
author_sort | Pan, Qingchun |
collection | PubMed |
description | BACKGROUND: Trait 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. RESULTS: Here, 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. CONCLUSIONS: TAS 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5812-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6547493 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65474932019-06-06 Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics Pan, Qingchun Wei, Junfeng Guo, Feng Huang, Suiyong Gong, Yong Liu, Hao Liu, Jianxiao Li, Lin BMC Genomics Database BACKGROUND: Trait 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. RESULTS: Here, 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. CONCLUSIONS: TAS 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5812-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-03 /pmc/articles/PMC6547493/ /pubmed/31159731 http://dx.doi.org/10.1186/s12864-019-5812-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Database Pan, Qingchun Wei, Junfeng Guo, Feng Huang, Suiyong Gong, Yong Liu, Hao Liu, Jianxiao Li, Lin Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics |
title | Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics |
title_full | Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics |
title_fullStr | Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics |
title_full_unstemmed | Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics |
title_short | Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics |
title_sort | trait ontology analysis based on association mapping studies bridges the gap between crop genomics and phenomics |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547493/ https://www.ncbi.nlm.nih.gov/pubmed/31159731 http://dx.doi.org/10.1186/s12864-019-5812-0 |
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