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In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean

Sequence-specific DNA-binding transcription factors (TFs) are often termed as ‘master regulators’ which bind to DNA and either activate or repress gene transcription. We have computationally analysed the soybean genome sequence data and constructed a proper set of TFs based on the Hidden Markov Mode...

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Autores principales: Mochida, Keiichi, Yoshida, Takuhiro, Sakurai, Tetsuya, Yamaguchi-Shinozaki, Kazuko, Shinozaki, Kazuo, Tran, Lam-Son Phan
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2780956/
https://www.ncbi.nlm.nih.gov/pubmed/19884168
http://dx.doi.org/10.1093/dnares/dsp023
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author Mochida, Keiichi
Yoshida, Takuhiro
Sakurai, Tetsuya
Yamaguchi-Shinozaki, Kazuko
Shinozaki, Kazuo
Tran, Lam-Son Phan
author_facet Mochida, Keiichi
Yoshida, Takuhiro
Sakurai, Tetsuya
Yamaguchi-Shinozaki, Kazuko
Shinozaki, Kazuo
Tran, Lam-Son Phan
author_sort Mochida, Keiichi
collection PubMed
description Sequence-specific DNA-binding transcription factors (TFs) are often termed as ‘master regulators’ which bind to DNA and either activate or repress gene transcription. We have computationally analysed the soybean genome sequence data and constructed a proper set of TFs based on the Hidden Markov Model profiles of DNA-binding domain families. Within the soybean genome, we identified 4342 loci encoding 5035 TF models which grouped into 61 families. We constructed a database named SoybeanTFDB (http://soybeantfdb.psc.riken.jp) containing the full compilation of soybean TFs and significant information such as: functional motifs, full-length cDNAs, domain alignments, promoter regions, genomic organization and putative regulatory functions based on annotations of gene ontology (GO) inferred by comparative analysis with Arabidopsis. With particular interest in abiotic stress signalling, we analysed the promoter regions for all of the TF encoding genes as a means to identify abiotic stress responsive cis-elements as well as all types of cis-motifs provided by the PLACE database. SoybeanTFDB enables scientists to easily access cis-element and GO annotations to aid in the prediction of TF function and selection of TFs with functions of interest. This study provides a basic framework and an important user-friendly public information resource which enables analyses of transcriptional regulation in soybean.
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spelling pubmed-27809562009-11-23 In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean Mochida, Keiichi Yoshida, Takuhiro Sakurai, Tetsuya Yamaguchi-Shinozaki, Kazuko Shinozaki, Kazuo Tran, Lam-Son Phan DNA Res Full Papers Sequence-specific DNA-binding transcription factors (TFs) are often termed as ‘master regulators’ which bind to DNA and either activate or repress gene transcription. We have computationally analysed the soybean genome sequence data and constructed a proper set of TFs based on the Hidden Markov Model profiles of DNA-binding domain families. Within the soybean genome, we identified 4342 loci encoding 5035 TF models which grouped into 61 families. We constructed a database named SoybeanTFDB (http://soybeantfdb.psc.riken.jp) containing the full compilation of soybean TFs and significant information such as: functional motifs, full-length cDNAs, domain alignments, promoter regions, genomic organization and putative regulatory functions based on annotations of gene ontology (GO) inferred by comparative analysis with Arabidopsis. With particular interest in abiotic stress signalling, we analysed the promoter regions for all of the TF encoding genes as a means to identify abiotic stress responsive cis-elements as well as all types of cis-motifs provided by the PLACE database. SoybeanTFDB enables scientists to easily access cis-element and GO annotations to aid in the prediction of TF function and selection of TFs with functions of interest. This study provides a basic framework and an important user-friendly public information resource which enables analyses of transcriptional regulation in soybean. Oxford University Press 2009-12 2009-11-02 /pmc/articles/PMC2780956/ /pubmed/19884168 http://dx.doi.org/10.1093/dnares/dsp023 Text en © The Author 2009. Published by Oxford University Press on behalf of Kazusa DNA Research Institute. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Full Papers
Mochida, Keiichi
Yoshida, Takuhiro
Sakurai, Tetsuya
Yamaguchi-Shinozaki, Kazuko
Shinozaki, Kazuo
Tran, Lam-Son Phan
In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean
title In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean
title_full In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean
title_fullStr In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean
title_full_unstemmed In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean
title_short In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean
title_sort in silico analysis of transcription factor repertoire and prediction of stress responsive transcription factors in soybean
topic Full Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2780956/
https://www.ncbi.nlm.nih.gov/pubmed/19884168
http://dx.doi.org/10.1093/dnares/dsp023
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