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Unraveling the molecular basis of oxidative stress management in a drought tolerant rice genotype Nagina 22

Overview of attention for article published in BMC Genomics, October 2016
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Title
Unraveling the molecular basis of oxidative stress management in a drought tolerant rice genotype Nagina 22
Published in
BMC Genomics, October 2016
DOI 10.1186/s12864-016-3131-2
Pubmed ID
Authors

Chandra Prakash, S. V. Amitha Mithra, Praveen K. Singh, T. Mohapatra, N. K. Singh

Abstract

Drought stress tolerance for crop improvement is an important goal worldwide. Drought is a complex trait, and it is vital to understand the complex physiological, biochemical, and molecular mechanisms of drought tolerance to tackle it effectively. Osmotic adjustment, oxidative stress management (OSM), and cell membrane stability (CMS) are major components of cellular tolerance under drought stress. In the current study, we explored the molecular basis of OSM in the drought tolerant rice variety, Nagina 22 and compared it with the popular drought sensitive rice variety, IR 64, under drought imposed at the reproductive stage, to understand how the parental polymorphisms correlate with the superiority of Nagina 22 and tolerant bulk populations under drought. We generated recombinant inbred lines (RIL) from contrasting parents Nagina 22 and IR 64 and focussed on spikelet fertility (SF), in terms of its correlation with OSM, which is an important component of drought tolerance in Nagina 22. Based on SF under drought stress and its correlations with other yield related traits, we used superoxide dismutase (SOD), glutathione reductase (GR), and ascorbate peroxidase (APX) activity assays to establish the relationship between SF and OSM genes in the tolerant and sensitive lines. Among the OSM enzymes studied, GR had a significant and positive correlation with single plant yield (SPY) under drought stress. GR was also positively correlated with APX but negatively so with SOD. Interestingly, none of the enzyme-morphology correlations were significant under irrigated control (IC). Through genome-wide SNP analysis of the 21 genes encoding for OSM enzymes, we identified the functional polymorphisms between the parents and identified superior alleles. By using network analysis of OSM genes in rice, we identified the genes that are central to the OSM network. From the biochemical and morphological data and the SNP analysis, the superiority of Nagina 22 in spikelet fertility under drought stress is because of its superior alleles for SOD (SOD2, SODCC1, SODA) and GR (GRCP2) rather than for APX, for which IR 64 had the superior allele (APX8). Nagina 22 can bypass APX8 by directly interacting with SODA. For nine of the 11 genes present in the central network, Nagina 22 had the superior alleles. We propose that Nagina 22 tolerance could mainly be because of SODA which is a reactive oxygen scavenger in mitochondria which is directly associated with spikelet fertility.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 26%
Researcher 8 19%
Student > Bachelor 4 9%
Student > Master 3 7%
Student > Postgraduate 2 5%
Other 2 5%
Unknown 13 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 40%
Biochemistry, Genetics and Molecular Biology 8 19%
Economics, Econometrics and Finance 1 2%
Psychology 1 2%
Medicine and Dentistry 1 2%
Other 0 0%
Unknown 15 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 October 2016.
All research outputs
#20,344,065
of 22,890,496 outputs
Outputs from BMC Genomics
#9,294
of 10,670 outputs
Outputs of similar age
#276,841
of 319,862 outputs
Outputs of similar age from BMC Genomics
#223
of 269 outputs
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