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Gramene QTL database: development, content and applications
Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2790302/ https://www.ncbi.nlm.nih.gov/pubmed/20157478 http://dx.doi.org/10.1093/database/bap005 |
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author | Ni, Junjian Pujar, Anuradha Youens-Clark, Ken Yap, Immanuel Jaiswal, Pankaj Tecle, Isaak Tung, Chih-Wei Ren, Liya Spooner, William Wei, Xuehong Avraham, Shuly Ware, Doreen Stein, Lincoln McCouch, Susan |
author_facet | Ni, Junjian Pujar, Anuradha Youens-Clark, Ken Yap, Immanuel Jaiswal, Pankaj Tecle, Isaak Tung, Chih-Wei Ren, Liya Spooner, William Wei, Xuehong Avraham, Shuly Ware, Doreen Stein, Lincoln McCouch, Susan |
author_sort | Ni, Junjian |
collection | PubMed |
description | Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL database contains the largest online collection of rice QTL data in the world. Using flanking markers as anchors, QTLs originally reported on individual genetic maps have been systematically aligned to the rice sequence where they can be searched as standard genomic features. Researchers can determine whether a QTL co-localizes with other QTLs detected in independent experiments and can combine data from multiple studies to improve the resolution of a QTL position. Candidate genes falling within a QTL interval can be identified and their relationship to particular phenotypes can be inferred based on functional annotations provided by ontology terms. Mutations identified in functional genomics populations and association mapping panels can be aligned with QTL regions to facilitate fine mapping and validation of gene–phenotype associations. By assembling and integrating diverse types of data and information across species and levels of biological complexity, the QTL database enhances the potential to understand and utilize QTL information in biological research. |
format | Text |
id | pubmed-2790302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-27903022009-12-08 Gramene QTL database: development, content and applications Ni, Junjian Pujar, Anuradha Youens-Clark, Ken Yap, Immanuel Jaiswal, Pankaj Tecle, Isaak Tung, Chih-Wei Ren, Liya Spooner, William Wei, Xuehong Avraham, Shuly Ware, Doreen Stein, Lincoln McCouch, Susan Database (Oxford) Original Article Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL database contains the largest online collection of rice QTL data in the world. Using flanking markers as anchors, QTLs originally reported on individual genetic maps have been systematically aligned to the rice sequence where they can be searched as standard genomic features. Researchers can determine whether a QTL co-localizes with other QTLs detected in independent experiments and can combine data from multiple studies to improve the resolution of a QTL position. Candidate genes falling within a QTL interval can be identified and their relationship to particular phenotypes can be inferred based on functional annotations provided by ontology terms. Mutations identified in functional genomics populations and association mapping panels can be aligned with QTL regions to facilitate fine mapping and validation of gene–phenotype associations. By assembling and integrating diverse types of data and information across species and levels of biological complexity, the QTL database enhances the potential to understand and utilize QTL information in biological research. Oxford University Press 2009 2009-05-08 /pmc/articles/PMC2790302/ /pubmed/20157478 http://dx.doi.org/10.1093/database/bap005 Text en © 2009 The Author(s). http://creativecommons.org/licenses/by-nc/2.0/uk/ This is Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Ni, Junjian Pujar, Anuradha Youens-Clark, Ken Yap, Immanuel Jaiswal, Pankaj Tecle, Isaak Tung, Chih-Wei Ren, Liya Spooner, William Wei, Xuehong Avraham, Shuly Ware, Doreen Stein, Lincoln McCouch, Susan Gramene QTL database: development, content and applications |
title | Gramene QTL database: development, content and applications |
title_full | Gramene QTL database: development, content and applications |
title_fullStr | Gramene QTL database: development, content and applications |
title_full_unstemmed | Gramene QTL database: development, content and applications |
title_short | Gramene QTL database: development, content and applications |
title_sort | gramene qtl database: development, content and applications |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2790302/ https://www.ncbi.nlm.nih.gov/pubmed/20157478 http://dx.doi.org/10.1093/database/bap005 |
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