Mishra Pragya, Singh Nisha, Jain Ajay, Jain Neha, Mishra Vagish, G Pushplatha, Sandhya Kiran P, Singh Nagendra Kumar, Rai Vandna
National Research Centre on Plant Biotechnology, Indian Agriculture Research Institute, New Delhi, India.
Banasthali University, Tonk, Rajasthan.
Bioinformation. 2018 Mar 31;14(3):123-131. doi: 10.6026/97320630014123. eCollection 2018.
Rice, a staple food crop, is often subjected to drought and salinity stresses thereby limiting its yield potential. Since there is a cross talk between these abiotic stresses, identification of common and/or overlapping regulatory elements is pivotal for generating rice cultivars that showed tolerance towards them. Analysis of the gene interaction network (GIN) facilitates identifying the role of individual genes and their interactions with others that constitute important molecular determinants in sensing and signaling cascade governing drought and/or salinity stresses. Identification of the various cis-regulatory elements of the genes constituting GIN is equally important. Here, in this study graphical Gaussian model (GGM) was used for generating GIN for an array of genes that were differentially regulated during salinity and/or drought stresses to contrasting rice cultivars (salt-tolerant [CSR11], salt-sensitive [VSR156], drought-tolerant [Vandana], drought-sensitive [IR64]). Whole genome transcriptom profiling by using microarray were employed in this study. Markov Chain completed co-expression analyses of differentially expressed genes using Dynamic Bayesian Network, Probabilistic Boolean Network and Steady State Analysis. A compact GIN was identified for commonly co-expressed genes during salinity and drought stresses with three major hubs constituted by Myb2 transcription factor (TF), phosphoglycerate kinase and heat shock protein (Hsp). The analysis suggested a pivotal role of these genes in salinity and/or drought stress responses. Further, analysis of cis-regulatory elements (CREs) of commonly differentially expressed genes during salinity and drought stresses revealed the presence of 20 different motifs.
水稻作为一种主食作物,经常遭受干旱和盐胁迫,从而限制了其产量潜力。由于这些非生物胁迫之间存在相互作用,因此识别共同和/或重叠的调控元件对于培育对这些胁迫具有耐受性的水稻品种至关重要。基因相互作用网络(GIN)分析有助于确定单个基因的作用及其与其他基因的相互作用,这些基因是感知和信号传导级联中控制干旱和/或盐胁迫的重要分子决定因素。识别构成GIN的基因的各种顺式调控元件同样重要。在本研究中,使用图形高斯模型(GGM)为一系列在盐胁迫和/或干旱胁迫下差异表达的基因生成GIN,这些基因来自对比的水稻品种(耐盐[CSR11]、盐敏感[VSR156]、耐旱[Vandana]、干旱敏感[IR64])。本研究采用微阵列进行全基因组转录组分析。使用动态贝叶斯网络、概率布尔网络和稳态分析对差异表达基因进行马尔可夫链共表达分析。在盐胁迫和干旱胁迫期间,为共同共表达的基因鉴定了一个紧凑的GIN,其中三个主要枢纽由Myb2转录因子(TF)、磷酸甘油酸激酶和热休克蛋白(Hsp)构成。分析表明这些基因在盐胁迫和/或干旱胁迫反应中起关键作用。此外,对盐胁迫和干旱胁迫期间共同差异表达基因的顺式调控元件(CRE)分析揭示了20种不同基序的存在。