Integrating the Bioinformatics and Omics Tools for Systems Analysis of Abiotic Stress Tolerance in Oryza sativa (L.)

  • Pandiyan Muthuramalingam
  • Rajendran Jeyasri
  • Subramanian Radhesh Krishnan
  • Shunmugiah Thevar Karutha Pandian
  • Ramalingam Sathishkumar
  • Manikandan Ramesh


Abiotic stress can inflict limitations on plant growth, developmental processes and also crop productivity. Here we have portrayed advances in omics tools in the view of conservative and contemporary approaches that could be used to unravel abiotic stress tolerance in rice. Under stressful conditions, plants can develop diverse molecular mechanisms to combat stress challenges, while it is not sufficient to protect them. Hence, speculation of this study is essential for understanding how plants react to adverse environmental conditions with the hope of enhancing the tolerance of plants to abiotic stress. It could be addressed by computational biology (bioinformatics); invigorated sequencing approaches in genomics have paved the way for various analytical applications. Focusing on the technological advances, multiple new omics such as the transcriptome, metabolome, hormonome, epigenome, proteome and phenome have emerged. An emphasis was given to systems approaches with respect to abiotic stress. In addition, the availability of rice whole genome information, advancement and development of omics studies has improved to address the identification of unique and combined abiotic stress responsive cellular metabolisms and this enables the interaction between signalling pathways, molecular biological insights along with novel traits and their significance. Thus, this chapter provides the bioinformatics and systems biology aspects of abiotic stress responses by comparing it with the publically available omics and bioinformatics resources which could provide a base for detailed functional studies of stress tolerance in rice.


Rice Abiotic stress Systems biology Omics Modelling Genome Transcriptome Metabolome Proteome Hormonome Phenome 



The author Pandiyan Muthuramalingam (Rc.SO (P)/DBT-BIF/15207/2017 dated February 02, 2018) thanks the DBT-Bioinformatics Infrastructure Facility Scheme, New Delhi, India, for the financial support in the form of fellowship. The authors gratefully acknowledge the use of the Bioinformatics Infrastructure Facility, Alagappa University, funded by the Department of Biotechnology, Ministry of Science and Technology, Government of India grant (No.BT/BI/25/015/2012). The authors also thank RUSA 2.0 [F. 24-51/2014-U, Policy (TN Multi-Gen), Dept of Edn, GoI].


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Pandiyan Muthuramalingam
    • 1
  • Rajendran Jeyasri
    • 1
  • Subramanian Radhesh Krishnan
    • 1
    • 2
  • Shunmugiah Thevar Karutha Pandian
    • 1
  • Ramalingam Sathishkumar
    • 3
  • Manikandan Ramesh
    • 1
  1. 1.Department of Biotechnology, Science CampusAlagappa UniversityKaraikudiIndia
  2. 2.Phytopharma Testing Laboratory, Herbal DivisionT. Stanes & Company LtdCoimbatoreIndia
  3. 3.Plant Genetic Engineering Laboratory, Department of BiotechnologyBharathiar UniversityCoimbatoreIndia

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