Genetic dissection of high temperature stress tolerance using photosynthesis parameters in QTL introgressed lines of rice cv. Improved White Ponni

Vivitha, P.; Raveendran, M.; Vijayalakshmi, C.; Vijayalakshmi, D.

doi:10.1007/s40502-018-0408-2

Cited by 12 publications

(11 citation statements)

References 11 publications

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“…Further, to overcome the limitations of chromosomal mapping, while performing large scale mutagenesis, Kumar and Jain (2018) light on recent forward and reverse genetics approaches to develop combined stress tolerance in crop plants. Similarly, using reverse genetics approach, Kaur et al (2018) isolated and characterized the heat stress responsive transcript Hsp17.9 from the Khejri tree, which grows under extreme environments, while Vivitha et al (2018) unfold the transcript abundance of photosynthetic related parameters in rice. Authors Kishor et al (2018) and Tanwar et al (2018) discuss the current genome editing strategies including CRISPR/Cas9 for genetic improvement of peanut and algae.…”

mentioning

confidence: 99%

Stepping forward and taking reverse as we move ahead in genetics

Pareek

Arora

Dhankher

2018

Ind J Plant Physiol.

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mentioning

confidence: 99%

Stepping forward and taking reverse as we move ahead in genetics

Pareek

Arora

Dhankher

2018

Ind J Plant Physiol.

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“…To recognize the genetics of leaf photosynthesis under HS, RILs of rice cv. Improved White Ponni (IWP) introgressed with two QTLs (qHTSF 1.1 and qHTSF 4.1) directing spikelet fertility were grown under HS [117]. Notably, the introgression lines (ILs) showed: improved photosynthetic rates, PSII efficiency, stomatal closure, and reduced transpiration rate.…”

Section: Genomics: Helps To Reveal the Stressresponsive Mechanismsmentioning

confidence: 99%

“…Based on physiological responses, introgressed QTLs can be used for the development of HS-tolerant rice cultivars [117]. Similarly, fine mapping of the introgressed QTL (qHTB1-1QTL) at the booting phase confers the HS tolerance using ILs in rice [118].…”

Section: Genomics: Helps To Reveal the Stressresponsive Mechanismsmentioning

confidence: 99%

Can omics deliver temperature resilient ready-to-grow crops?

Raza

Tabassum

Kudapa

et al. 2021

Critical Reviews in Biotechnology

141

110

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Plants are extensively well-thought-out as the main source for nourishing natural life on earth. In the natural environment, plants have to face several stresses, mainly heat stress (HS), chilling stress (CS) and freezing stress (FS) due to adverse climate fluctuations. These stresses are considered as a major threat for sustainable agriculture by hindering plant growth and development, causing damage, ultimately leading to yield losses worldwide and counteracting to achieve the goal of "zero hunger" proposed by the Food and Agricultural Organization (FAO) of the United Nations. Notably, this is primarily because of the numerous inequities happening at the cellular, molecular and/or physiological levels, especially during plant developmental stages under temperature stress. Plants counter to temperature stress via a complex phenomenon including variations at different developmental stages that comprise modifications in physiological and biochemical processes, gene expression and differences in the levels of metabolites and proteins. During the last decade, omics approaches have revolutionized how plant biologists explore stress-responsive mechanisms and pathways, driven by current scientific developments. However, investigations are still required to explore numerous features of temperature stress responses in plants to create a complete idea in the arena of stress signaling. Therefore, this review highlights the recent advances in the utilization of omics approaches to understand stress adaptation and tolerance mechanisms. Additionally, how to overcome persisting knowledge gaps. Shortly, the combination of integrated omics, genome editing, and speed breeding can revolutionize modern agricultural production to feed millions worldwide in order to accomplish the goal of "zero hunger." ARTICLE HISTORY

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“…, and WUE (μmol CO2/mol H2O) were measured in the corresponding populations and parents, using a portable photosynthesis system, namely LI-6400 XT (LI-COR Inc. Lincoln, Nebraska, USA). Specifically, Pn, Gs, Ci, and Tr were measured at a light intensity of 1,500 μmol m -2 s -1 photosynthetic active radiation (PAR), a leaf temperature of 30 ℃ and a constant CO2 concentration of 380±5 μmol CO2 mol -1 in the sample chamber provided with buffer volume [13]. All measurements for each treatment were made on the fully expanded leaves between 9:00 and 11:00 a.m. on sunny days to avoid effects of photo-inhibition and were repeated at least 5 times using different plants.…”

Section: Field Experiments and Trait Evaluationmentioning

confidence: 99%

“…Using identified molecular markers and quantitative trait loci (QTLs) for photosynthetic-related traits under different watering treatments in marker-assisted selection (MAS) breeding is a promising way to maximize the productivity of maize grown in droght land. Until now, genetic studies on wheat (Triticum aestivum L.) [10], rice (Oryza sativa L.) [11][12][13], sunflower (Helianthus annuus L.) [14], rapeseed (Brassica napus L.) [15], cotton (Gossypium spp) [16][17] etc. for photosynthetic-related traits have been extensively conducted using QTL mapping during drought, high temperature, salt and alkali stresses.…”

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confidence: 99%

Genetic dissection of photosynthetic performances in maize under drought-stressed and well-watered environments

Zhao

Lü

Bai

et al. 2019

Preprint

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Background: Maintaining photosynthetic capacities is a critical function that allows maize ( Zea mays L.) to adapt to drought stress. The elucidation of genetic controls of photosynthetic performances, and tightly linked molecular markers under water stress are thus of great importance in marker-assisted selection (MAS) breeding. Meanwhile, little is known regarding their genetic controls under drought stress. Two F 4 populations were developed to identify quantitative trait loci (QTLs) and dissect the genetic variation underlying six photosynthetic-related traits, namely, net photosynthetic rate (Pn), stomatal conductance (Gs), intercellular CO 2 concentration (Ci), transpiration rate (Tr), ribulose 1,5-biphosphate carboxylase activity (RuBP), and water use efficiency (WUE) under drought-stressed and well-watered environments. Results: For two populations, we detected 54 QTLs under drought-stressed and well-watered environments by single-environment mapping with composite interval mapping (CIM), approximately 81.8~100 % QTLs displayed non-additive effects, and 43 of the 54 QTLs were identified under drought-stressed environment. We also dissected 54 QTLs via joint analysis of all environments with mixed-linear-model-based composite interval mapping (MCIM), 24 QTLs involved in QTL × environment interactions (QEIs), approximately 87.5 % QEIs were identified under drought-stressed environments, as well as 14 pair epistasis exhibited dominance-by-additive/dominance (DA/DD) effects under constracting environments. We further identified 8 constitutive QTLs (cQTLs) across two populations by CIM/MCIM under multiple environments. Remarkably, bin 1.07_1.10 (cQTL2), bin 6.05 (cQTL5), bin 7.02_7.04 (cQTL6), bin 8.03 (cQTL7), and bin 10.03 (cQTL8) exhibited 5 pleiotropic cQTLs that were consistent with phenotypic correlations among all photosynthetic-related traits. Additionally, 17 candidate genes were validated in above cQTLs. Conclusions: Photosynthetic performances in maize were predominantly controlled by non-additive and QEIs effects, where more QEIs effects occurred in drought stress. 8 cQTLs affecting six photosynthetic-related traits could be useful for genetic improvement of these traits via QTL pyramiding, corresponding 5 QTLs clusters indicated tight linkage or pleiotropy in the inheritance of these traits, and 17 candidate genes involved in leaf morphology and development, photosynthesis, and stress reponse coincided with above corresponding cQTLs.

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Genetic dissection of high temperature stress tolerance using photosynthesis parameters in QTL introgressed lines of rice cv. Improved White Ponni

Cited by 12 publications

References 11 publications

Stepping forward and taking reverse as we move ahead in genetics

Stepping forward and taking reverse as we move ahead in genetics

Can omics deliver temperature resilient ready-to-grow crops?

Genetic dissection of photosynthetic performances in maize under drought-stressed and well-watered environments

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