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Development of a novel data mining tool to find cis-elements in rice gene promoter regions
BACKGROUND: Information on more than 35 000 full-length Oryza sativa cDNAs, together with associated microarray gene expression data collected under various treatment conditions, has made it feasible to identify motifs that are conserved in gene promoters and may act as cis-regulatory elements with...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2270273/ https://www.ncbi.nlm.nih.gov/pubmed/18302796 http://dx.doi.org/10.1186/1471-2229-8-20 |
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author | Doi, Koji Hosaka, Aeni Nagata, Toshifumi Satoh, Kouji Suzuki, Kohji Mauleon, Ramil Mendoza, Michael J Bruskiewich, Richard Kikuchi, Shoshi |
author_facet | Doi, Koji Hosaka, Aeni Nagata, Toshifumi Satoh, Kouji Suzuki, Kohji Mauleon, Ramil Mendoza, Michael J Bruskiewich, Richard Kikuchi, Shoshi |
author_sort | Doi, Koji |
collection | PubMed |
description | BACKGROUND: Information on more than 35 000 full-length Oryza sativa cDNAs, together with associated microarray gene expression data collected under various treatment conditions, has made it feasible to identify motifs that are conserved in gene promoters and may act as cis-regulatory elements with key roles under the various conditions. RESULTS: We have developed a novel tool that searches for cis-element candidates in the upstream, downstream, or coding regions of differentially regulated genes. The tool first lists cis-element candidates by motif searching based on the supposition that if there are cis-elements playing important roles in the regulation of a given set of genes, they will be statistically overrepresented and will be conserved. Then it evaluates the likelihood scores of the listed candidate motifs by association rule analysis. This strategy depends on the idea that motifs overrepresented in the promoter region could play specific roles in the regulation of expression of these genes. The tool is designed so that any biological researchers can use it easily at the publicly accessible Internet site . We evaluated the accuracy and utility of the tool by using a dataset of auxin-inducible genes that have well-studied cis-elements. The test showed the effectiveness of the tool in identifying significant relationships between cis-element candidates and related sets of genes. CONCLUSION: The tool lists possible cis-element motifs corresponding to genes of interest, and it will contribute to the deeper understanding of gene regulatory mechanisms in plants. |
format | Text |
id | pubmed-2270273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-22702732008-03-20 Development of a novel data mining tool to find cis-elements in rice gene promoter regions Doi, Koji Hosaka, Aeni Nagata, Toshifumi Satoh, Kouji Suzuki, Kohji Mauleon, Ramil Mendoza, Michael J Bruskiewich, Richard Kikuchi, Shoshi BMC Plant Biol Software BACKGROUND: Information on more than 35 000 full-length Oryza sativa cDNAs, together with associated microarray gene expression data collected under various treatment conditions, has made it feasible to identify motifs that are conserved in gene promoters and may act as cis-regulatory elements with key roles under the various conditions. RESULTS: We have developed a novel tool that searches for cis-element candidates in the upstream, downstream, or coding regions of differentially regulated genes. The tool first lists cis-element candidates by motif searching based on the supposition that if there are cis-elements playing important roles in the regulation of a given set of genes, they will be statistically overrepresented and will be conserved. Then it evaluates the likelihood scores of the listed candidate motifs by association rule analysis. This strategy depends on the idea that motifs overrepresented in the promoter region could play specific roles in the regulation of expression of these genes. The tool is designed so that any biological researchers can use it easily at the publicly accessible Internet site . We evaluated the accuracy and utility of the tool by using a dataset of auxin-inducible genes that have well-studied cis-elements. The test showed the effectiveness of the tool in identifying significant relationships between cis-element candidates and related sets of genes. CONCLUSION: The tool lists possible cis-element motifs corresponding to genes of interest, and it will contribute to the deeper understanding of gene regulatory mechanisms in plants. BioMed Central 2008-02-27 /pmc/articles/PMC2270273/ /pubmed/18302796 http://dx.doi.org/10.1186/1471-2229-8-20 Text en Copyright © 2008 Doi et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Doi, Koji Hosaka, Aeni Nagata, Toshifumi Satoh, Kouji Suzuki, Kohji Mauleon, Ramil Mendoza, Michael J Bruskiewich, Richard Kikuchi, Shoshi Development of a novel data mining tool to find cis-elements in rice gene promoter regions |
title | Development of a novel data mining tool to find cis-elements in rice gene promoter regions |
title_full | Development of a novel data mining tool to find cis-elements in rice gene promoter regions |
title_fullStr | Development of a novel data mining tool to find cis-elements in rice gene promoter regions |
title_full_unstemmed | Development of a novel data mining tool to find cis-elements in rice gene promoter regions |
title_short | Development of a novel data mining tool to find cis-elements in rice gene promoter regions |
title_sort | development of a novel data mining tool to find cis-elements in rice gene promoter regions |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2270273/ https://www.ncbi.nlm.nih.gov/pubmed/18302796 http://dx.doi.org/10.1186/1471-2229-8-20 |
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