Mapping QTLs for drought tolerance in an F2:3 population from an inter-specific cross between Gossypium tomentosum and Gossypium hirsutum

Zheng, Jinfeng; Oluoch, G.; Khan, Muhammad Kashif Riaz; Wang, X. X.; Cai, Xiaoyan; Zhou, Zhongli; Wang, C. Y.; Wang, Y. H.; Li, X. Y.; Liu, F.; Wang, K. B.

doi:10.4238/gmr.15038477

Cited by 35 publications

(28 citation statements)

References 25 publications

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“…A population comprising 188 F 2:3 , obtained from a hybrid crossed between Gossypium hirsutum and Gossypium tomentosum, was used to identify drought-related QTLs under field conditions [113]. Overall, 67 QTLs were identified under drought conditions, which were distributed on chromosomes 5, 8, 9, and 16.…”

Section: Molecular Genetic Basis and Qtls For Drought Tolerance In Comentioning

confidence: 99%

Insights into Drought Stress Signaling in Plants and the Molecular Genetic Basis of Cotton Drought Tolerance

Mahmood

Khalid

Abdullah

et al. 2019

Cells

235

141

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Drought stress restricts plant growth and development by altering metabolic activity and biological functions. However, plants have evolved several cellular and molecular mechanisms to overcome drought stress. Drought tolerance is a multiplex trait involving the activation of signaling mechanisms and differentially expressed molecular responses. Broadly, drought tolerance comprises two steps: stress sensing/signaling and activation of various parallel stress responses (including physiological, molecular, and biochemical mechanisms) in plants. At the cellular level, drought induces oxidative stress by overproduction of reactive oxygen species (ROS), ultimately causing the cell membrane to rupture and stimulating various stress signaling pathways (ROS, mitogen-activated-protein-kinase, Ca2+, and hormone-mediated signaling). Drought-induced transcription factors activation and abscisic acid concentration co-ordinate the stress signaling and responses in cotton. The key responses against drought stress, are root development, stomatal closure, photosynthesis, hormone production, and ROS scavenging. The genetic basis, quantitative trait loci and genes of cotton drought tolerance are presented as examples of genetic resources in plants. Sustainable genetic improvements could be achieved through functional genomic approaches and genome modification techniques such as the CRISPR/Cas9 system aid the characterization of genes, sorted out from stress-related candidate single nucleotide polymorphisms, quantitative trait loci, and genes. Exploration of the genetic basis for superior candidate genes linked to stress physiology can be facilitated by integrated functional genomic approaches. We propose a third-generation sequencing approach coupled with genome-wide studies and functional genomic tools, including a comparative sequenced data (transcriptomics, proteomics, and epigenomic) analysis, which offer a platform to identify and characterize novel genes. This will provide information for better understanding the complex stress cellular biology of plants.

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Section: Molecular Genetic Basis and Qtls For Drought Tolerance In Comentioning

confidence: 99%

Insights into Drought Stress Signaling in Plants and the Molecular Genetic Basis of Cotton Drought Tolerance

Mahmood

Khalid

Abdullah

et al. 2019

Cells

235

141

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“…A number of QTLs associated with drought tolerance traits have been identified in plants such as barley (Fan et al 2015), Oryza sativa (Mardani et al 2013), Zea mays (Lu et al 2010), and wheat (Fleury et al 2010). QTL mapping for drought tolerance traits has been reported in which SSR markers have been used to develop the genetic map (Zheng et al 2016). Howerver, the use of genotypic data derived from GBS has not been reported yet in a segregating backcross population (BC 2 F 2 ) derived from interspecific backcross between Gossypium hirsutum and G. tomentosum, though the same techniques have been used to explore salt tolerance in intraspecific an F 2:3 population in upland cotton (Qi et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Identification of QTLs and candidate genes for physiological traits associated with drought tolerance in cotton

Magwanga

Kirungu

et al. 2020

J Cotton Res

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Background: Cotton is mainly grown for its natural fiber and edible oil. The fiber obtained from cotton is the indispensable raw material for the textile industries. The ever changing climatic condition, threatens cotton production due to a lack of sufficient water for its cultivation. Effects of drought stress are estimated to affect more than 50% of the cotton growing regions. To elucidate the drought tolerance phenomenon in cotton, a backcross population was developed from G. tomentosum, a drought tolerant donor parent and G. hirsutum which is highly susceptible to drought stress. Results: A genetic map of 10 888 SNP markers was developed from 200 BC 2 F 2 populations. The map spanned 4 191.3 centi-Morgan (cM), with an average distance of 0.104 7 cM, covering 51% and 49% of At and Dt sub genomes, respectively. Thirty stable Quantitative trait loci (QTLs) were detected, in which more than a half were detected in the At subgenome. Eighty-nine candidate genes were mined within the QTL regions for three traits: cell membrane stability (CMS), saturated leaf weight (SLW) and chlorophyll content. The genes had varied physiochemical properties. A majority of the genes were interrupted by introns, and only 15 genes were intronless, accounting for 17% of the mined genes. The genes were found to be involved molecular function (MF), cellular component (CC) and biological process (BP), which are the main gene ontological (GO) functions. A number of miRNAs were detected, such as miR164, which is associated with NAC and MYB genes, with a profound role in enhancing drought tolerance in plants. Through RT-qPCR analysis, 5 genes were found to be the key genes involved in enhancing drought tolerance in cotton. Wild cotton harbors a number of favorable alleles, which can be exploited to aid in improving the narrow genetic base of the elite cotton cultivars. The detection of 30 stable QTLs and 89 candidate genes found to be contributed by the donor parent, G. tomentosum, showed the significant genes harbored by the wild progenitors which can be exploited in developing more robust cotton genotypes with diverse tolerance levels to various environmental stresses. Conclusion: This was the first study involving genome wide association mapping for drought tolerance traits in semi wild cotton genotypes. It offers an opportunity for future exploration of these genes in developing highly tolerant cotton cultivars to boost cotton production.

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“…RuBP was estimated in response to apparent mesophyll conductance (AMC) as follows [3]: (1). And WUE was also calculated as follows [10,17]: (2). Then the corresponding F 4 plants were harvested and subsequently air-dried to evaluated ear weight (EW), grain weight per ear (GW), and 100-kernel weight (KW).…”

Section: Field Experiments and Trait Evaluationmentioning

confidence: 99%

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

Zhao

Zhang

2020

Preprint

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BackgroundMaintaining photosynthetic capacity 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 F4 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 CO2 concentration (Ci), transpiration rate (Tr), ribulose 1,5-biphosphate carboxylase activity (RuBP), and water use efficiency (WUE) under drought-stressed and well-watered environments.ResultsFor 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.ConclusionsPhotosynthetic 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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Mapping QTLs for drought tolerance in an F2:3 population from an inter-specific cross between Gossypium tomentosum and Gossypium hirsutum

Cited by 35 publications

References 25 publications

Insights into Drought Stress Signaling in Plants and the Molecular Genetic Basis of Cotton Drought Tolerance

Insights into Drought Stress Signaling in Plants and the Molecular Genetic Basis of Cotton Drought Tolerance

Identification of QTLs and candidate genes for physiological traits associated with drought tolerance in cotton

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

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