Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis

Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to l...

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Main Authors:	Bonthala, Venkata Suresh, Mayes, Sean, Moreton, Joanna, Blythe, Martin J., Wright, Victoria, May, Sean, Massawe, Festo, Twycross, Jamie
Format:	Article
Language:	English
Published:	Public Library of Science 2016
Online Access:	http://eprints.nottingham.ac.uk/32811/ http://eprints.nottingham.ac.uk/32811/ http://eprints.nottingham.ac.uk/32811/ http://eprints.nottingham.ac.uk/32811/1/journal.pone.0148771.PDF

id	nottingham-32811
recordtype	eprints
spelling	nottingham-328112018-07-02T09:05:04Z http://eprints.nottingham.ac.uk/32811/ Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis Bonthala, Venkata Suresh Mayes, Sean Moreton, Joanna Blythe, Martin J. Wright, Victoria May, Sean Massawe, Festo Mayes, Sean Twycross, Jamie Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip) coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01) under the sub-optimal (23°C) and very sub-optimal (18°C) temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes) that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties. Public Library of Science 2016-02-09 Article PeerReviewed application/pdf en cc_by http://eprints.nottingham.ac.uk/32811/1/journal.pone.0148771.PDF Bonthala, Venkata Suresh and Mayes, Sean and Moreton, Joanna and Blythe, Martin J. and Wright, Victoria and May, Sean and Massawe, Festo and Mayes, Sean and Twycross, Jamie (2016) Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis. PLoS ONE, 11 (2). e0148771. ISSN 1932-6203 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0148771 doi:10.1371/journal.pone.0148771 doi:10.1371/journal.pone.0148771
repository_type	Digital Repository
institution_category	Local University
institution	University of Nottingham Malaysia Campus
building	Nottingham Research Data Repository
collection	Online Access
language	English
description	Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip) coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01) under the sub-optimal (23°C) and very sub-optimal (18°C) temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes) that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties.
format	Article
author	Bonthala, Venkata Suresh Mayes, Sean Moreton, Joanna Blythe, Martin J. Wright, Victoria May, Sean Massawe, Festo Mayes, Sean Twycross, Jamie
spellingShingle	Bonthala, Venkata Suresh Mayes, Sean Moreton, Joanna Blythe, Martin J. Wright, Victoria May, Sean Massawe, Festo Mayes, Sean Twycross, Jamie Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis
author_facet	Bonthala, Venkata Suresh Mayes, Sean Moreton, Joanna Blythe, Martin J. Wright, Victoria May, Sean Massawe, Festo Mayes, Sean Twycross, Jamie
author_sort	Bonthala, Venkata Suresh
title	Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis
title_short	Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis
title_full	Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis
title_fullStr	Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis
title_full_unstemmed	Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis
title_sort	identification of gene modules associated with low temperatures response in bambara groundnut by network-based analysis
publisher	Public Library of Science
publishDate	2016
url	http://eprints.nottingham.ac.uk/32811/ http://eprints.nottingham.ac.uk/32811/ http://eprints.nottingham.ac.uk/32811/ http://eprints.nottingham.ac.uk/32811/1/journal.pone.0148771.PDF
first_indexed	2018-09-06T12:17:32Z
last_indexed	2018-09-06T12:17:32Z
_version_	1610860465222582272

Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis

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