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Genomic Prediction of Arsenic Tolerance and Grain Yield in Rice: Contribution of Trait-Specific Markers and Multi-Environment Models 被引量:3
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作者 Nourollah AHMADI Tuong-Vi CAO +2 位作者 Julien FROUIN Gareth J.NORTON Adam H.PRICE 《Rice science》 SCIE CSCD 2021年第3期268-278,共11页
Many rice-growing areas are affected by high concentrations of arsenic(As).Rice varieties that prevent As uptake and/or accumulation can mitigate As threats to human health.Genomic selection is known to facilitate rap... Many rice-growing areas are affected by high concentrations of arsenic(As).Rice varieties that prevent As uptake and/or accumulation can mitigate As threats to human health.Genomic selection is known to facilitate rapid selection of superior genotypes for complex traits.We explored the predictive ability(PA)of genomic prediction with single-environment models,accounting or not for trait-specific markers,multi-environment models,and multi-trait and multi-environment models,using the genotypic(1600K SNPs)and phenotypic(grain As content,grain yield and days to flowering)data of the Bengal and Assam Aus Panel.Under the base-line single-environment model,PA of up to 0.707 and 0.654 was obtained for grain yield and grain As content,respectively;the three prediction methods(Bayesian Lasso,genomic best linear unbiased prediction and reproducing kernel Hilbert spaces)were considered to perform similarly,and marker selection based on linkage disequilibrium allowed to reduce the number of SNP to 17K,without negative effect on PA of genomic predictions.Single-environment models giving distinct weight to trait-specific markers in the genomic relationship matrix outperformed the base-line models up to 32%.Multi-environment models,accounting for genotype×environment interactions,and multi-trait and multi-environment models outperformed the base-line models by up to 47%and 61%,respectively.Among the multi-trait and multi-environment models,the Bayesian multi-output regressor stacking function obtained the highest predictive ability(0.831 for grain As)with much higher efficiency for computing time.These findings pave the way for breeding for As-tolerance in the progenies of biparental crosses involving members of the Bengal and Assam Aus Panel.Genomic prediction can also be applied to breeding for other complex traits under multiple environments. 展开更多
关键词 genomic prediction model genomic selection complex trait arsenic tolerance RICE predictive ability
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An Investigation on Tolerance and Accumulation of a Facultative Marine Fungus Aspergillus flavus to Pentavalent Arsenic 被引量:1
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作者 Anjana K.Vala Vipul Davariya R.V.Upadhyay 《Journal of Ocean University of China》 SCIE CAS 2010年第1期65-67,共3页
Tolerance of a facultative marine fungus Aspergillus flavus towards As (V) was tested.Luxuriant growth of the test isolate was observed in culture media with As (V) concentrations of 25 mg L-1 and 50 mg L-1,indicating... Tolerance of a facultative marine fungus Aspergillus flavus towards As (V) was tested.Luxuriant growth of the test isolate was observed in culture media with As (V) concentrations of 25 mg L-1 and 50 mg L-1,indicating its tolerance to the metal.Accumulation rate of arsenic was always higher when exposed to As (V) at 50 mg L-1 than at 25 mg L-1.The study reveals Aspergillus flavus as a promising candidate for environmental bioremediation.Arsenic contents (mg g-1) in the fungus when exposed to 50 mg L-1 As (V) were measured as 11.1773,4.0983,and 8.0000 mg g-1 on day 3,6 and 9,respectively.The highest content was observed initially,i.e.on day 3,followed by a decline and a rise again.These results provide baseline information for further explorations regarding the exploitation of the fungus for arsenic removal. 展开更多
关键词 facultative marine fungi Aspergillusflavus arsenic tolerance BIOACCUMULATION
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Allene oxide synthase 1 contributes to limiting grain arsenic accumulation and seedling detoxification in rice
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作者 Xin Fan Haiyang Tang +5 位作者 Xuan Chen Fanrong Zeng Guang Chen Zhong-Hua Chen Yuan Qin Fenglin Deng 《Stress Biology》 2023年第1期555-571,共17页
Arsenic(As)is a cancerogenic metalloid ubiquitously distributed in the environment,which can be easily accumulated in food crops like rice.Jasmonic acid(JA)and its derivatives play critical roles in plant growth and s... Arsenic(As)is a cancerogenic metalloid ubiquitously distributed in the environment,which can be easily accumulated in food crops like rice.Jasmonic acid(JA)and its derivatives play critical roles in plant growth and stress response.However,the role of endogenous JA in As accumulation and detoxification is still poorly understood.In this study,we found that JA biosynthesis enzymes Allene Oxide Synthases,OsAOS1 and OsAOS2,regulate As accumulation and As tolerance in rice.Evolutionary bioinformatic analysis indicated that AOS1 and AOS2 have evolved from streptophyte algae(e.g.the basal lineage Klebsormidium flaccidum)-sister clade of land plants.Compared to other two AOSs,OsAOS1 and OsAOS2 were highly expressed in all examined rice tissues and their transcripts were highly induced by As in root and shoot.Loss-of-function of OsAOS1(osaos1-1)showed elevated As concentration in grains,which was likely attributed to the increased As translocation from root to shoot when the plants were subjected to arsenate[As(Ⅴ)]but not arsenite[As(Ⅲ)].However,the mutation of OsAOS2(osaos2-1)showed no such effect.Moreover,osaos1-1 and osaos2-1 increased the sensitivity of rice plants to both As(Ⅴ)and As(Ⅲ).Disrupted expression of genes involved in As accumulation and detoxification,such as OsPT4,OsNIP3;2,and OsOASTL-A1,was observed in both osaos1-1 and osaos2-1 mutant lines.In addition,a As(Ⅴ)-induced significant decrease in Reactive Oxygen Species(ROS)production was observed in the root of osaos1-1 but not in osaos2-1.Taken together,our results indicate OsAOS1 modulates both As allocation and detoxification,which could be partially attributed to the altered gene expression profiling and ROS homeostasis in rice while OsAOS2 is important for As tolerance. 展开更多
关键词 Jasmonic acid arsenic tolerance Evolutionary bioinformatics Oryza sativa L. ROS homeostasis
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