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Elucidation and analyses of the regulatory networks of upland and lowland ecotypes of switchgrass in response to drought and salt stresses.
Zuo, Chunman; Tang, Yuhong; Fu, Hao; Liu, Yiming; Zhang, Xunzhong; Zhao, Bingyu; Xu, Ying.
Affiliation
  • Zuo C; College of Computer Science and Technology, Jilin University, Changchun, China.
  • Tang Y; Computational Systems Biology Lab, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA, United States of America.
  • Fu H; Noble Research Institute, LLC., Ardmore, OK, United States of America.
  • Liu Y; North Automatic Control Technology Institute, Taiyuan, China.
  • Zhang X; Department of Crop and Soil Environmental Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.
  • Zhao B; Department of Crop and Soil Environmental Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.
  • Xu Y; Department of Horticulture, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.
PLoS One ; 13(9): e0204426, 2018.
Article in En | MEDLINE | ID: mdl-30248119
ABSTRACT
Switchgrass is an important bioenergy crop typically grown in marginal lands, where the plants must often deal with abiotic stresses such as drought and salt. Alamo is known to be more tolerant to both stress types than Dacotah, two ecotypes of switchgrass. Understanding of their stress response and adaptation programs can have important implications to engineering more stress tolerant plants. We present here a computational study by analyzing time-course transcriptomic data of the two ecotypes to elucidate and compare their regulatory systems in response to drought and salt stresses. A total of 1,693 genes (target genes or TGs) are found to be differentially expressed and possibly regulated by 143 transcription factors (TFs) in response to drought stress together in the two ecotypes. Similarly, 1,535 TGs regulated by 110 TFs are identified to be involved in response to salt stress. Two regulatory networks are constructed to predict their regulatory relationships. In addition, a time-dependent hidden Markov model is derived for each ecotype responding to each stress type, to provide a dynamic view of how each regulatory network changes its behavior over time. A few new insights about the response mechanisms are predicted from the regulatory networks and the time-dependent models. Comparative analyses between the network models of the two ecotypes reveal key commonalities and main differences between the two regulatory systems. Overall, our results provide new information about the complex regulatory mechanisms of switchgrass responding to drought and salt stresses.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Gene Expression Regulation, Plant / Droughts / Salt Stress / Panicum Type of study: Health_economic_evaluation / Prognostic_studies Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2018 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Gene Expression Regulation, Plant / Droughts / Salt Stress / Panicum Type of study: Health_economic_evaluation / Prognostic_studies Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2018 Document type: Article Affiliation country: China
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