Bonthala Venkata Suresh, Mayes Katie, Moreton Joanna, Blythe Martin, Wright Victoria, May Sean Tobias, Massawe Festo, Mayes Sean, Twycross Jamie
School of Computer Sciences, Jubilee Campus, University of Nottingham, Nottingham, United Kingdom.
School of Biosciences, University of Nottingham Malaysia Campus, Kuala Lumpur, Malaysia.
PLoS One. 2016 Feb 9;11(2):e0148771. doi: 10.1371/journal.pone.0148771. eCollection 2016.
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.
非洲竹芋（Vigna subterranea (L.) Verdc.）是一种非洲豆科植物，是一种具有良好种子营养价值但未得到充分利用的有前景的作物。在一些非洲国家，如博茨瓦纳，夜间的低温胁迫会影响非洲竹芋的生长和发育，导致潜在作物产量损失。因此，在本研究中，我们开发了一种计算流程，使用跨物种微阵列技术（由于非洲竹芋没有微阵列芯片）结合基于网络的分析，来识别和分析与非洲竹芋低温胁迫反应相关的基因和基因模块。利用跨物种基因表达数据对非洲竹芋转录组进行分析，结果分别在次优温度（23°C）和极次优温度（18°C）下鉴定出375个和659个差异表达基因（p<0.01），其中110个基因在两种胁迫条件下共同存在。构建基于最高相互排名的基因共表达网络，然后使用启发式聚类凿算法对其进行划分，结果分别在次优和极次优温度胁迫下鉴定出6个和7个基因模块。次优温度胁迫模块主要富集碳水化合物和脂质代谢过程，而极次优温度胁迫的大多数模块则显著富集对刺激的反应和各种代谢过程。突出了几个可能调节参与刺激反应的下游基因以使植物耐受极次优温度胁迫的转录因子（来自MYB、NAC、WRKY、WHIRLY和GATA类）。所鉴定的基因模块可能有助于培育耐低温胁迫非洲竹芋品种。
