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Genomic Prediction of Arsenic Tolerance and Grain Yield in Rice: Contribution of Trait-Specific Markers and Multi-Environment Models

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Rice science 2021年第3期28卷 268-278页

作者： Nourollah AHMADI Tuong-Vi CAO julien frouin Gareth J.NORTON Adam H.PRICE Institute of Genetic Improvement and Adaptation of Mediterranean and Tropical Plants French Agricultural Research and International Cooperation OrganizationMontpellier F-34398France University of Montpellier National Research Institute for AgricultureFood and EnvironmentFrench Agricultural Research and International Cooperation OrganizationMontpellier SupAgroMontpellier 34090France School of Biological Sciences University of AberdeenAberdeen AB243UUScotland

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 *** selection is known to facilitate rapid selection of superior genotypes for complex *** 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 *** 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 ***-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%,*** 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 *** findings pave the way for breeding for As-tolerance in the progenies of biparental crosses involving members of the Bengal and Assam Aus *** prediction can also be applied to breeding for other complex traits under multiple environments.

关键词： genomic prediction model genomic selection complex trait arsenic tolerance rice predictive ability

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Genome-Wide Association Study of Nitrogen Use Efficiency and Agronomic Traits in Upland Rice

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Rice science 2021年第4期28卷 379-390,I0027-I0034页

作者： Tatiana Rakotoson Julie Dusserre Philippe Letourmy julien frouin Isabelle Ramonta Ratsimiala Noronirina Victorine Rakotoarisoa Tuong-Vi CAO Kirsten Vom Brocke Alain Ramanantsoanirina Nourollah Ahmadi Louis-Marie Raboin National Center for Applied Research on Rural Development Regional Research Station AntsirabeAntsirabe 110Madagascar Faculty of Sciences University of AntananarivoAntananarivo 101Madagascar Higher Education Institute of Antsirabe Vakinankaratra University of AntananarivoAntsirabe 110Madagascar Agroecology and Sustainable Intensification of Annual Crops Research Unit French Agricultural Research Centre for International Development(CIRAD)Avenue AgropolisMontpellier 34398France Genetic Improvement and Adaptation of Mediterranean and Tropical Plants Research Unit(UMR AGAP) CIRADAvenue AgropolisMontpellier 34398France UMR AGAP Highland Production Systems and Sustainability in Madagascar Platform in PartnershipCIRADAntsirabe 110Madagascar University of Montpellier/CIRAD Montpellier 34398France

Genome-wide association study(GWAS)was performed for 16 agronomic traits including nitrogen use efficiency(NUE)and yield-related components using a panel of 190 mainly japonica rice varieties and a set of 38390 single nucleotide polymorphism(SNP)*** panel was evaluated under rainfed upland conditions in Madagascar in two consecutive cropping seasons with two contrasted nitrogen input *** another set of five grain traits,we identified previously known genes(GW5,GS3,Awn1 and Glabrous1),thus validating the pertinence and accuracy of our datasets for GWAS.A total of 369 significant associations were detected between SNPs and agronomic traits,gathered into 46 distinct haplotype groups and 28 isolated *** association signals were identified for the complex quantitative trait NUE,however,larger number of quantitative trait loci(QTLs)were detected for its component traits,with 10 and 2 association signals for nitrogen utilization efficiency and nitrogen uptake efficiency,*** detected association signals co-localized with genes involved in nitrogen transport or nitrogen remobilization within 100 *** present study thus confirmed the potential of GWAS to identify candidate genes and new loci associated with agronomic ***,because of the quantitative and complex nature of NUE-related traits,GWAS might have not captured a large number of QTLs with limited effects.

关键词： genome-wide association study nitrogen use efficiency agronomic trait upland rice

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湖南烟溪病圃稻瘟病菌的有性态及微卫星标记的遗传多样性分析

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中国水稻科学 2004年第3期18卷 262-268页

作者：沈瑛 julien frouin 何月秋 Claudia KAYE 肖放 Jean Loup NOTTEGHEM 刘二 Didier THARREAU 中国水稻研究所法国国际农艺研究和发展中心法国蒙贝利埃34398 云南农业大学云南省植物病理重点实验室云南昆明650201 湖南省农业科学院植物保护研究所湖南长沙410125 法国生物和植物病理大学法国蒙贝利埃34060

用 2对稻瘟病菌的两性能育菌株 (交配型 1.1和交配型 1.2 )测定了来自湖南烟溪病圃上的 4年 12 4个稻瘟病菌株的交配型 ,用微卫星分子标记分析其中 10 5个菌株的遗传多样性及其亲缘关系。12 4个菌株中 ,2 8个为交配型 1.1,39个为交配型 ... 详细信息

用 2对稻瘟病菌的两性能育菌株 (交配型 1.1和交配型 1.2 )测定了来自湖南烟溪病圃上的 4年 12 4个稻瘟病菌株的交配型 ,用微卫星分子标记分析其中 10 5个菌株的遗传多样性及其亲缘关系。12 4个菌株中 ,2 8个为交配型 1.1,39个为交配型 1.2 ,5 7个不育 ,分别占供试菌株的 2 2 .5 8%、31.4 5 %和 4 5 .97% ;在 0 .6 7相似性的基础上 ,7对微卫星引物扩增出的标记可将 10 5个菌株区分为 6个系谱群。

关键词：稻瘟病菌有性态微卫星标记两性菌株交配型遗传多样性真菌水稻

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