Future demands for increased productivity and resilience to abiotic/biotic stresses of major crops require new technologies of breeding by design(BBD)built on massive information from functional and population genomic...Future demands for increased productivity and resilience to abiotic/biotic stresses of major crops require new technologies of breeding by design(BBD)built on massive information from functional and population genomics research.A novel strategy of breeding by selective introgression(BBSI)has been proposed and practiced for simultaneous improvement,genetic dissection and allele mining of complex traits to realize BBD.BBSI has three phases:a)developing large numbers of trait-specific introgression lines(ILs)using backcross breeding in elite genetic backgrounds as the material platform of BBD;b)efficiently identifying genes or quantitative trait loci(QTL)and mining desirable alleles affecting different target traits from diverse donors as the information platform of BBD;and c)developing superior cultivars by BBD using designed QTL pyramiding or marker-assisted recurrent selection.Phase(a)has been implemented massively in rice by many Chinese research institutions and IRRI,resulting in the development of many new green super rice cultivars plus large numbers of ILs in 30+elite genetic backgrounds.Phase(b)has been demonstrated in a series of proof-of-concept studies of high-efficiency genetic dissection of rice yield and tolerance to abiotic stresses using ILs and DNA markers.Phase(c)has also been implemented by designed QTL pyramiding,resulting in a prototype of BBD in several successful cases.The BBSI strategy can be easily extended for simultaneous trait improvement,efficient gene and QTL discovery and allele mining of complex traits using advanced breeding lines from crosses between a common"backbone"parent and a set of elite parents in conventional pedigree breeding programs.BBSI can be relatively easily adopted by breeding programs with small budgets,but the BBSI-based BBD strategy can be fully and more efficiently implemented by large seed companies with sufficient capacity.展开更多
The development of green super rice varieties with improved nutrient use efficiency(NuUE)is a vital target area to increase yield and make it more stable under rainfed conditions.In the present study, we followed an e...The development of green super rice varieties with improved nutrient use efficiency(NuUE)is a vital target area to increase yield and make it more stable under rainfed conditions.In the present study, we followed an early backcross(BC) breeding approach by using a highyielding and widely adapted Xian variety, Weed Tolerant Rice 1(WTR-1), as a recipient and a Geng variety, Hao-An-Nong(HAN), as a donor.Starting from the BC1F2 generation, the BC population went through one generation of selection under irrigated, low-input, and rainfed conditions, followed by four consecutive generations of screening and selection for high grain yield(GY) under six different nutrient conditions(NPK, 75 N,-N,-P,-NP, and-NPK), leading to the development of 230 BC1F6 introgression lines(ILs).These 230 ILs were evaluated under the same six nutrient conditions for 13 agro-morphological and grain yield component traits in comparison to four checks and parents.Significant trait variations were observed between the treatments and ILs.Positive correlations were identified for GY with biomass, panicle length, flag-leaf area, flag-leaf width, filled grain number per panicle,1000-grain weight, and tiller number under-N,-P,-NP, and-NPK conditions.Out of 230 ILs,12 were identified as promising under two or more nutrient deficiency conditions.The results demonstrated an efficient inter-subspecific BC breeding procedure with a first round of selection under rainfed-drought conditions, followed by four generations of progeny testing for yield performance under six nutrient conditions.The promising ILs can be useful resources for molecular genetic dissection and understanding the physiological mechanisms of NuUE.展开更多
Germplasm conserved in gene banks is underutilized,owing mainly to the cost of characterization.Genomic prediction can be applied to predict the genetic merit of germplasm.Germplasm utilization could be greatly accele...Germplasm conserved in gene banks is underutilized,owing mainly to the cost of characterization.Genomic prediction can be applied to predict the genetic merit of germplasm.Germplasm utilization could be greatly accelerated if prediction accuracy were sufficiently high with a training population of practical size.Large-scale resequencing projects in rice have generated high quality genome-wide variation information for many diverse accessions,making it possible to investigate the potential of genomic prediction in rice germplasm management and exploitation.We phenotyped six traits in nearly 2000 indica(XI)and japonica(GJ)accessions from the Rice 3K project and investigated different scenarios for forming training populations.A composite core training set was considered in two levels which targets used for prediction of subpopulations within subspecies or prediction across subspecies.Composite training sets incorporating 400 or 200 accessions from either subpopulation of XI or GJ showed satisfactory prediction accuracy.A composite training set of 600 XI and GJ accessions showed sufficiently high prediction accuracy for both XI and GJ subspecies.Comparable or even higher prediction accuracy was observed for the composite training set than for the corresponding homogeneous training sets comprising accessions only of specific subpopulations of XI or GJ(within-subspecies level)or pure XI or GJ accessions(across-subspecies level)that were included in the composite training set.Validation using an independent population of 281 rice cultivars supported the predictive ability of the composite training set.Reliability,which reflects the robustness of a training set,was markedly higher for the composite training set than for the corresponding homogeneous training sets.A core training set formed from diverse accessions could accurately predict the genetic merit of rice germplasm.展开更多
Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in ...Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in rice is essential to identify elite genes useful for breeding high grain Zn rice varieties.Here,a meta-analysis of previous RNA-Seq studies involving Zn deficient conditions was conducted using the weighted gene co-expression network analysis(WGCNA)and other in silico prediction tools to identify modules(denoting cluster of genes with related expression pattern)of co-expressed genes,modular genes which are conserved differentially expressed genes(DEGs)across independent RNA-Seq studies,and the molecular pathways of the conserved modular DEGs.WGCNA identified 16 modules of co-expressed genes.Twenty-eight and five modular DEGs were conserved in leaf and crown,and root tissues across two independent RNA-Seq studies.Functional enrichment analysis showed that 24 of the 28 conserved modular DEGs from leaf and crown tissues significantly up-regulated 2 Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways and 15 Gene Ontology(GO)terms,including the substrate-specific transmembrane transporter and the small molecule metabolic process.Further,the well-studied transcription factors(OsWOX11 and OsbHLH120),protein kinase(OsCDPK20 and OsMPK17),and miRNAs(OSA-MIR397A and OSA-MIR397B)were predicted to target some of the identified conserved modular DEGs.Out of the 24 conserved and up-regulated modular DEGs,19 were yet to be experimentally validated as Zn deficiency responsive genes.Findings from this study provide a comprehensive insight on the molecular mechanisms of Zn deficiency response and may facilitate gene and pathway prioritization for improving Zn use efficiency and Zn biofortification in rice.展开更多
The identification of loci and markers associated with milled grain appearance traits is essential for breeding high-yielding and good-quality rice variety.To detect stable loci for these characteristics,grain length(...The identification of loci and markers associated with milled grain appearance traits is essential for breeding high-yielding and good-quality rice variety.To detect stable loci for these characteristics,grain length(GL),grain width(GW),grain length/width(GLW),chalkiness degree(CD),chalky-grain rate(CR)and translucency degree(TD)of 378 rice lines were evaluated in three seasons.These lines were derived from a multi-parent advanced generation intercross(MAGIC)population.展开更多
基金funded by the National Key Research&Development Program of China(2017YFD0100100)Key-Area Research&Development Program of Guangdong Province(2020B020219004)+2 种基金Shenzhen Basic Research Special Project(2020231601)Agricultural Science and Technology Innovation Programthe Cooperation and Innovation Mission(CAAS2021-01)。
文摘Future demands for increased productivity and resilience to abiotic/biotic stresses of major crops require new technologies of breeding by design(BBD)built on massive information from functional and population genomics research.A novel strategy of breeding by selective introgression(BBSI)has been proposed and practiced for simultaneous improvement,genetic dissection and allele mining of complex traits to realize BBD.BBSI has three phases:a)developing large numbers of trait-specific introgression lines(ILs)using backcross breeding in elite genetic backgrounds as the material platform of BBD;b)efficiently identifying genes or quantitative trait loci(QTL)and mining desirable alleles affecting different target traits from diverse donors as the information platform of BBD;and c)developing superior cultivars by BBD using designed QTL pyramiding or marker-assisted recurrent selection.Phase(a)has been implemented massively in rice by many Chinese research institutions and IRRI,resulting in the development of many new green super rice cultivars plus large numbers of ILs in 30+elite genetic backgrounds.Phase(b)has been demonstrated in a series of proof-of-concept studies of high-efficiency genetic dissection of rice yield and tolerance to abiotic stresses using ILs and DNA markers.Phase(c)has also been implemented by designed QTL pyramiding,resulting in a prototype of BBD in several successful cases.The BBSI strategy can be easily extended for simultaneous trait improvement,efficient gene and QTL discovery and allele mining of complex traits using advanced breeding lines from crosses between a common"backbone"parent and a set of elite parents in conventional pedigree breeding programs.BBSI can be relatively easily adopted by breeding programs with small budgets,but the BBSI-based BBD strategy can be fully and more efficiently implemented by large seed companies with sufficient capacity.
基金the Bill & Melinda Gates Foundation (BMGF) for providing a research grant to Z.L.for the Green Super Rice project under ID OPP1130530the Department of Agriculture of the Philippines for providing funds to J.A.under the Next-Gen project.
文摘The development of green super rice varieties with improved nutrient use efficiency(NuUE)is a vital target area to increase yield and make it more stable under rainfed conditions.In the present study, we followed an early backcross(BC) breeding approach by using a highyielding and widely adapted Xian variety, Weed Tolerant Rice 1(WTR-1), as a recipient and a Geng variety, Hao-An-Nong(HAN), as a donor.Starting from the BC1F2 generation, the BC population went through one generation of selection under irrigated, low-input, and rainfed conditions, followed by four consecutive generations of screening and selection for high grain yield(GY) under six different nutrient conditions(NPK, 75 N,-N,-P,-NP, and-NPK), leading to the development of 230 BC1F6 introgression lines(ILs).These 230 ILs were evaluated under the same six nutrient conditions for 13 agro-morphological and grain yield component traits in comparison to four checks and parents.Significant trait variations were observed between the treatments and ILs.Positive correlations were identified for GY with biomass, panicle length, flag-leaf area, flag-leaf width, filled grain number per panicle,1000-grain weight, and tiller number under-N,-P,-NP, and-NPK conditions.Out of 230 ILs,12 were identified as promising under two or more nutrient deficiency conditions.The results demonstrated an efficient inter-subspecific BC breeding procedure with a first round of selection under rainfed-drought conditions, followed by four generations of progeny testing for yield performance under six nutrient conditions.The promising ILs can be useful resources for molecular genetic dissection and understanding the physiological mechanisms of NuUE.
基金funded by National Key Research and Development Program of China(2020YFE0202300)International Postdoctoral Exchange Fellowship Program(Talent-Introduction Program)in 2020.
文摘Germplasm conserved in gene banks is underutilized,owing mainly to the cost of characterization.Genomic prediction can be applied to predict the genetic merit of germplasm.Germplasm utilization could be greatly accelerated if prediction accuracy were sufficiently high with a training population of practical size.Large-scale resequencing projects in rice have generated high quality genome-wide variation information for many diverse accessions,making it possible to investigate the potential of genomic prediction in rice germplasm management and exploitation.We phenotyped six traits in nearly 2000 indica(XI)and japonica(GJ)accessions from the Rice 3K project and investigated different scenarios for forming training populations.A composite core training set was considered in two levels which targets used for prediction of subpopulations within subspecies or prediction across subspecies.Composite training sets incorporating 400 or 200 accessions from either subpopulation of XI or GJ showed satisfactory prediction accuracy.A composite training set of 600 XI and GJ accessions showed sufficiently high prediction accuracy for both XI and GJ subspecies.Comparable or even higher prediction accuracy was observed for the composite training set than for the corresponding homogeneous training sets comprising accessions only of specific subpopulations of XI or GJ(within-subspecies level)or pure XI or GJ accessions(across-subspecies level)that were included in the composite training set.Validation using an independent population of 281 rice cultivars supported the predictive ability of the composite training set.Reliability,which reflects the robustness of a training set,was markedly higher for the composite training set than for the corresponding homogeneous training sets.A core training set formed from diverse accessions could accurately predict the genetic merit of rice germplasm.
基金financially supported by the Chinese Academy of Agricultural Sciences-Agricultural Science and Technology Innovation Programthe Shenzhen Science and Technology Program (Grant No. JCYJ20200109150650397)
文摘Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in rice is essential to identify elite genes useful for breeding high grain Zn rice varieties.Here,a meta-analysis of previous RNA-Seq studies involving Zn deficient conditions was conducted using the weighted gene co-expression network analysis(WGCNA)and other in silico prediction tools to identify modules(denoting cluster of genes with related expression pattern)of co-expressed genes,modular genes which are conserved differentially expressed genes(DEGs)across independent RNA-Seq studies,and the molecular pathways of the conserved modular DEGs.WGCNA identified 16 modules of co-expressed genes.Twenty-eight and five modular DEGs were conserved in leaf and crown,and root tissues across two independent RNA-Seq studies.Functional enrichment analysis showed that 24 of the 28 conserved modular DEGs from leaf and crown tissues significantly up-regulated 2 Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways and 15 Gene Ontology(GO)terms,including the substrate-specific transmembrane transporter and the small molecule metabolic process.Further,the well-studied transcription factors(OsWOX11 and OsbHLH120),protein kinase(OsCDPK20 and OsMPK17),and miRNAs(OSA-MIR397A and OSA-MIR397B)were predicted to target some of the identified conserved modular DEGs.Out of the 24 conserved and up-regulated modular DEGs,19 were yet to be experimentally validated as Zn deficiency responsive genes.Findings from this study provide a comprehensive insight on the molecular mechanisms of Zn deficiency response and may facilitate gene and pathway prioritization for improving Zn use efficiency and Zn biofortification in rice.
基金supported by the earmarked fund for China Agriculture Research System(Grant No.CARS-01)Young Elite Scientists Sponsorship Program by China Association for Science and Technology(Grant No.2020QNRC001)Hunan Academy of Agricultural Sciences Scientific and Technological Innovation Project,China(Grant No.2017JC10)。
文摘The identification of loci and markers associated with milled grain appearance traits is essential for breeding high-yielding and good-quality rice variety.To detect stable loci for these characteristics,grain length(GL),grain width(GW),grain length/width(GLW),chalkiness degree(CD),chalky-grain rate(CR)and translucency degree(TD)of 378 rice lines were evaluated in three seasons.These lines were derived from a multi-parent advanced generation intercross(MAGIC)population.
