Genetic engineering of indica rice with AtDREB1A gene for enhanced abiotic stress tolerance View Full Text


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Article Info

DATE

2019-01

AUTHORS

Gunturu Manju Latha, K. V. Raman, John Milton Lima, Debasis Pattanayak, Ashok K. Singh, Viswanathan Chinnusamy, Kailash C. Bansal, K. R. S. Sambasiva Rao, Trilochan Mohapatra

ABSTRACT

Drought and cold stresses are major abiotic stresses that affect rice productivity. Therefore, enhancing tolerance to these stresses is necessary for sustaining rice productivity. Overexpression of the AtDREB1A gene has been shown to confer tolerance to both drought and cold stresses in diverse plant species. Hence, we genetically engineered indica rice cv. Pusa Sugandh 2 with AtDREB1A gene under the transcriptional control of stress responsive AtRD29A promoter. The transformants were confirmed for the stable integration of transgene in the rice genome by using PCR, RT-PCR and Southern blot analyses. Two single copy transgenic events (T3) and non-transgenic (NT) plants grown in pots were subjected to drought and cold stresses for 14 days. Transgenic plants exhibited enhanced tolerance to both drought and cold stresses as compared with NT plants. Transgenic plants maintained significantly higher leaf relative water content (LRWC), chlorophyll content, total sugars and proteins, but lower canopy temperature as compared with NT plants. Microarray analysis of AtDREB1A transgenic rice line (TL4) subjected to drought stress at reproductive stage led to the identification of 256 differentially expressed genes (DEGs), of which 201 were upregulated under drought stress. Interestingly, ~ 38% of the up-regulated genes coded proteins for chloroplast structure and function, which is a unique finding of this study. About 47% of the DEGs were enriched with CRT/DRE cis-regulatory elements in their promoters. Of these CRT/DRE cis-element containing genes, 50% genes coded for chloroplast function suggesting that these genes might be the direct targets of DREB1A TF. Up-regulation of TFs ZFP179 and NF-YC1, which are positive regulators of stress tolerance and downregulated TFs HOX22 and OsNAP, which are negative regulators of stress tolerance might have contributed to the enhanced drought tolerance of AtDREB1A transgenic plants. In addition, AtDREB1A-mediated orchestration of genes for chloroplast function appeared to have played an important role in not only providing carbon requirements of plants for survival and growth, but also helped minimize photo-inhibition and ROS accumulation in chloroplast under drought stress. Thus, stress-inducible overexpression of AtDREB1A in rice is a useful strategy to enhance drought and cold tolerance in the major staple food crop of the world. More... »

PAGES

1-16

References to SciGraph publications

  • 2010-03-08. Gene Regulation During Cold Stress Acclimation in Plants in PLANT STRESS TOLERANCE
  • 2017-09. Heterologous expression of PDH47 confers drought tolerance in indica rice in PLANT CELL, TISSUE AND ORGAN CULTURE (PCTOC)
  • 2016-10. Overexpression of RSOsPR10, a root-specific rice PR10 gene, confers tolerance against drought stress in rice and drought and salt stresses in bentgrass in PLANT CELL, TISSUE AND ORGAN CULTURE (PCTOC)
  • 2016-04. Heat and hydrolytic enzymes treatment improved the Agrobacterium-mediated transformation of recalcitrant indica rice (Oryza sativa L.) in PLANT CELL, TISSUE AND ORGAN CULTURE (PCTOC)
  • 2005-12. Expression of a carrot 36 kD antifreeze protein gene improves cold stress tolerance in transgenic tobacco in FORESTRY STUDIES IN CHINA
  • 2014-06. Stress-inducible expression of AtDREB1A transcription factor greatly improves drought stress tolerance in transgenic indica rice in TRANSGENIC RESEARCH
  • 2016-07. Ectopic expression of AtICE1 and OsICE1 transcription factor delays stress-induced senescence and improves tolerance to abiotic stresses in tobacco in JOURNAL OF PLANT BIOCHEMISTRY AND BIOTECHNOLOGY
  • 2017-10. Physiological role of rice germin-like protein 1 (OsGLP1) at early stages of growth and development in indica rice cultivar under salt stress condition in PLANT CELL, TISSUE AND ORGAN CULTURE (PCTOC)
  • 2015. The Omics of Cold Stress Responses in Plants in ELUCIDATION OF ABIOTIC STRESS SIGNALING IN PLANTS
  • 1999-03. Improving plant drought, salt, and freezing tolerance by gene transfer of a single stress-inducible transcription factor in NATURE BIOTECHNOLOGY
  • 2013-05. Abiotic stress responsive rice ASR1 and ASR3 exhibit different tissue-dependent sugar and hormone-sensitivities in MOLECULES AND CELLS
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    http://scigraph.springernature.com/pub.10.1007/s11240-018-1505-7

    DOI

    http://dx.doi.org/10.1007/s11240-018-1505-7

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    https://app.dimensions.ai/details/publication/pub.1109779222


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