Affiliations 

  • 1 School of Computer Sciences, Jubilee Campus, University of Nottingham, Nottingham, United Kingdom
  • 2 Plant and Crop Sciences, Biosciences, Sutton Bonington Campus, Loughborough, Leicestershire, United Kingdom
  • 3 Advanced Data Analysis Centre, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire, United Kingdom
  • 4 Deep Seq, School of Life Sciences, University of Nottingham, Medical School, Queen's Medical Centre, Nottingham, United Kingdom
  • 5 School of Biosciences, University of Nottingham Malaysia Campus, Kuala Lumpur, Malaysia
  • 6 Crops For the Future, Jalan Broga, 43500 Semenyih, Malaysia
PLoS One, 2016;11(2):e0148771.
PMID: 26859686 DOI: 10.1371/journal.pone.0148771

Abstract

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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.