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
When exposed to cadmium(Cd),rice(Oryza sativa L.)suffers a loss in biomass as well as an increased concentration of Cd within the plant.When looking for genes that can reduce Cd accumulation or increase Cd tolerance,t...When exposed to cadmium(Cd),rice(Oryza sativa L.)suffers a loss in biomass as well as an increased concentration of Cd within the plant.When looking for genes that can reduce Cd accumulation or increase Cd tolerance,the wild relatives of rice are under-utilised resources.In this study,a rapid hydroponic screening system was established using known tolerant and sensitive O.sativa accessions,and found that 10μmol/L Cd concentration appeared to be the optimum for screening Cd tolerance of rice cultivars.展开更多
Rice is often grown as multiple seasons in one year,alternating between flooded and upland systems.A major constraint,introduced from the flooded system,is a plough pan that may decrease rooting depth and productivity...Rice is often grown as multiple seasons in one year,alternating between flooded and upland systems.A major constraint,introduced from the flooded system,is a plough pan that may decrease rooting depth and productivity of follow-on upland rice.Roots penetrating the plough pan under flooded rice system can leave a legacy of weaker root growth pathways.Deeper rooting rice cultivars could have a bigger impact,but no direct evidence is available.To explore whether a deep rather than a shallow rooting rice cultivar grown in a flooded cropping cycle benefited deeper root growth of follow-on rice in an upland,reduced tillage cropping cycle,a simulated flooded paddy in greenhouse was planted with deep(Black Gora) and shallow(IR64) rooting cultivars and a plant-free control.Artificial plough pans were made in between the topsoil and subsoil to form different treatments with no plough pan(0.35 MPa),soft plough pan(1.03 MPa) and hard plough pan(1.70 MPa).After harvest of this ‘first season’ rice,the soil was drained and undisturbed to simulate zero-tillage upland and planted rice cultivar BRRI Dhan 28.The overall root length density(RLD),root surface area,the numbers of root tips and branching of BRRI Dhan 28 did not vary between plough pan and no plough pan treatments.Compared with the shallow rooting rice genotype,the deep rooting rice genotype as ‘first season’ crop produced 19% greater RLD,34% greater surface area and 29% more branching of BRRI Dhan 28 in the subsoil.In the topsoil,however,BRRI Dhan 28 had 28% greater RLD,35% greater surface area and 43% more branching for the shallow rather than deep rooting genotype planted in the ‘first season’.The results suggested that rice cultivar selection for a paddy cycle affects root growth of a follow-on rice crop grown under no-till,with benefits to subsoil access from deep rooting cultivars and topsoil proliferation for shallow rooting cultivars.展开更多
文摘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.
基金financial support from the School of Biological Sciences,University of Aberdeen in UK for funding this study.
文摘When exposed to cadmium(Cd),rice(Oryza sativa L.)suffers a loss in biomass as well as an increased concentration of Cd within the plant.When looking for genes that can reduce Cd accumulation or increase Cd tolerance,the wild relatives of rice are under-utilised resources.In this study,a rapid hydroponic screening system was established using known tolerant and sensitive O.sativa accessions,and found that 10μmol/L Cd concentration appeared to be the optimum for screening Cd tolerance of rice cultivars.
基金funded by the Commonwealth Scholarship Commission in the UK。
文摘Rice is often grown as multiple seasons in one year,alternating between flooded and upland systems.A major constraint,introduced from the flooded system,is a plough pan that may decrease rooting depth and productivity of follow-on upland rice.Roots penetrating the plough pan under flooded rice system can leave a legacy of weaker root growth pathways.Deeper rooting rice cultivars could have a bigger impact,but no direct evidence is available.To explore whether a deep rather than a shallow rooting rice cultivar grown in a flooded cropping cycle benefited deeper root growth of follow-on rice in an upland,reduced tillage cropping cycle,a simulated flooded paddy in greenhouse was planted with deep(Black Gora) and shallow(IR64) rooting cultivars and a plant-free control.Artificial plough pans were made in between the topsoil and subsoil to form different treatments with no plough pan(0.35 MPa),soft plough pan(1.03 MPa) and hard plough pan(1.70 MPa).After harvest of this ‘first season’ rice,the soil was drained and undisturbed to simulate zero-tillage upland and planted rice cultivar BRRI Dhan 28.The overall root length density(RLD),root surface area,the numbers of root tips and branching of BRRI Dhan 28 did not vary between plough pan and no plough pan treatments.Compared with the shallow rooting rice genotype,the deep rooting rice genotype as ‘first season’ crop produced 19% greater RLD,34% greater surface area and 29% more branching of BRRI Dhan 28 in the subsoil.In the topsoil,however,BRRI Dhan 28 had 28% greater RLD,35% greater surface area and 43% more branching for the shallow rather than deep rooting genotype planted in the ‘first season’.The results suggested that rice cultivar selection for a paddy cycle affects root growth of a follow-on rice crop grown under no-till,with benefits to subsoil access from deep rooting cultivars and topsoil proliferation for shallow rooting cultivars.
