Genetic variation and association of molecular markers for iron toxicity tolerance in rice

Pawar, Swapnil; Pandit, Elssa; Arjun, P; Wagh, M.P.; Bal, D; Panda, Sanjib Kumar; Bastia, DN; Pradhan, SK; Mohanty, I. C.

doi:10.5958/2249-5266.2017.00066.2

Cited by 8 publications

(11 citation statements)

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“…Therefore, it is concluded that the panel population used for the study possesses considerable genetic variation for iron toxicity tolerance. Earlier researchers had also confirmed about the existence of genetic variation for Fe-toxicity tolerance in rice [ 23 , 25 , 28 – 31 ].…”

Section: Discussionmentioning

confidence: 91%

“…Same experimental set up for LBI under control and treatment with Fe was maintained with only difference that the control set up was without any Fe stress, whereas the treatment set up was applied with Fe pulse stress of 1000 ppm. As a measure of Fe stress, LBI score ranging from 1 to 9 was assigned to the three youngest fully expanded leaves of each plant on the tenth day of pulse stress following the procedure described in earlier publication [ 23 ].…”

Section: Methodsmentioning

confidence: 99%

“…Reduction in grain yield due to this stress is high in Burundi, Sierra leone, Burkina Faso, Liberia, Togo, Nigeria, Senegal, Srilanka, Philippines, Malaysia, Indonesia, Vietnam, Thailand, Malaysia, Colombia, Benin, Ivory Coast, Niger, Gambia, Guinea, Guinea-Bissau and Liberia [ 21 – 24 ]. This is also a problem in few locations in Kerala, Coastal and hilly zones of Karnataka, Tamil Nadu, valley soils in Odisha and north eastern region of Meghalaya in India [ 17 , 23 , 24 ]. Existence of genetic variation for Fe-toxicity tolerance in rice is reported in many publications [ 17 , 25 – 30 ].…”

Section: Introductionmentioning

confidence: 99%

“…Few quantitative trait loci (QTL) located on different chromosomes have been reported from different mapping populations [ 25 , 28 – 31 ]. The involvement of chromosomal regions between 25 to 30 Mb on chromosome 1 and between 0 and 5 Mb on chromosome 3 were reported for tolerance response to the stress [ 23 , 27 , 28 , 30 ]. Many publications on transporter genes involved in toxicity tolerance have been well reported [ 26 , 32 – 37 ].…”

Section: Introductionmentioning

confidence: 99%

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Population genetic structure and association mapping for iron toxicity tolerance in rice

et al. 2021

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Iron (Fe) toxicity is a major abiotic stress which severely reduces rice yield in many countries of the world. Genetic variation for this stress tolerance exists in rice germplasms. Mapping of gene(s)/QTL controlling the stress tolerance and transfer of the traits into high yielding rice varieties are essential for improvement against the stress. A panel population of 119 genotypes from 352 germplasm lines was constituted for detecting the candidate gene(s)/QTL through association mapping. STRUCTURE, GenAlEx and Darwin softwares were used to classify the population. The marker-trait association was detected by considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) analyses. Wide genetic variation was observed among the genotypes present in the panel population for the stress tolerance. Linkage disequilibrium was detected in the population for iron toxicity tolerance. The population was categorized into three genetic structure groups. Marker-trait association study considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) showed significant association of leaf browning index (LBI) with markers RM471, RM3, RM590 and RM243. Three novel QTL controlling Fe-toxicity tolerance were detected and designated as qFeTox4.3, qFeTox6.1 and qFeTox10.1. A QTL reported earlier in the marker interval of C955-C885 on chromosome 1 is validated using this panel population. The present study showed that QTL controlling Fe-toxicity tolerance to be co-localized with the QTL for Fe-biofortification of rice grain indicating involvement of common pathway for Fe toxicity tolerance and Fe content in rice grain. Fe-toxicity tolerance QTL qFeTox6.1 was co-localized with grain Fe-biofortification QTLs qFe6.1 and qFe6.2 on chromosome 6, whereas qFeTox10.1 was co-localized with qFe10.1 on chromosome 10. The Fe-toxicity tolerance QTL detected from this mapping study will be useful in marker-assisted breeding programs.

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Section: Discussionmentioning

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Population genetic structure and association mapping for iron toxicity tolerance in rice

et al. 2021

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“…The genetic diversity and structure of the population in association mapping will be helpful for detecting marker–trait associations that may be useful for trait enhancement in molecular breeding programs. In order to avoid spurious marker–phenotype association, population structure (Q) with relative kinship (K) analyses are used to check and correct the panel population composition for linkage disequilibrium (LD) mapping analyses [ 21 , 22 , 23 , 24 ]. The association estimates based on both the generalized linear model (GLM) and mixed linear model (MLM) are considered appropriate for mapping complex traits, and have been shown to perform better than other model analysis.…”

Section: Introductionmentioning

confidence: 99%

Detection of Genomic Regions Controlling the Antioxidant Enzymes, Phenolic Content, and Antioxidant Activities in Rice Grain through Association Mapping

Sanghamitra

Barik

Bastia

et al. 2022

Plants

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Because it is rich in antioxidant compounds, the staple food of rice provides many health benefits. Four antioxidant traits in rice grain, viz., catalase, CUPRAC, DPPH, FRAP and peroxidase, were mapped in a representative panel population containing 117 germplasm lines using 131 SSR markers through association mapping. Donor lines rich in multiple antioxidant properties were identified from the mapping population. The population was classified into three genetic groups and each group showed reasonable correspondence with the antioxidant traits. The presence of linkage disequilibrium in the population was confirmed from the estimated Fst values. A strong positive correlation of DPPH was established with TPC, FRAP and CUPRAC. A moderate to high mean gene diversity was observed in the panel population. Eleven significant marker-trait associations for antioxidant traits were mapped, namely, qACD2.1, qACD11.1 and qACD12.2 for DPPH; qCAT8.1 and qCAT11.1 for catalase; qFRAP11.1, qFRAP12.1 and qFRAP12.2 for FRAP; and qCUPRAC3.1, qCUPRAC11.1 and qCUPRA12.1 regulating CUPRAC. Co-localization of the QTLs for qACD11.1, qFRAP11.1 and qCUPRAC11.1 were detected, which may act as antioxidant hotspots regulating DPPH, FRAP and CUPRAC activities, respectively, while qACD12.2 and qFRAP12.1 remained close on the chromosome 12. These detected QTLs will be useful in antioxidant improvement programs in rice.

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Genetic regulation of homeostasis, uptake, bio-fortification and efficiency enhancement of iron in rice

Pradhan

Pandit

Pawar

et al. 2020

Environmental and Experimental Botany

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Genetic variation and association of molecular markers for iron toxicity tolerance in rice

Cited by 8 publications

References 0 publications

Population genetic structure and association mapping for iron toxicity tolerance in rice

Population genetic structure and association mapping for iron toxicity tolerance in rice

Detection of Genomic Regions Controlling the Antioxidant Enzymes, Phenolic Content, and Antioxidant Activities in Rice Grain through Association Mapping

Genetic regulation of homeostasis, uptake, bio-fortification and efficiency enhancement of iron in rice

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