Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates.Genomics-assisted breeding utilizes genomic and phenotypic information to increase the sele...Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates.Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs,and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions.Here we present an apple reference population:the apple REFPOP,a large collection formed of 534 genotypes planted in six European countries,as a unique tool to accelerate apple breeding.The population consisted of 269 accessions and 265 progeny from 27 parental combinations,representing the diversity in cultivated apple and current European breeding material,respectively.A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95.Based on the genotypic data,linkage disequilibrium was low and population structure was weak.Two well-studied phenological traits of horticultural importance were measured.We found marker–trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date,respectively.With decreasing SNP density,the detection of significant marker–trait associations varied depending on trait architecture.Regardless of the trait,10,000 SNPs sufficed to maximize genomic prediction ability.We confirm the suitability of the apple REFPOP design for genomics-assisted breeding,especially for breeding programs using related germplasm,and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era.展开更多
In 2010,a major scientific milestone was achieved for tree fruit crops:publication of the first draft whole genome sequence(WGS)for apple(Malus domestica).This WGS,v1.0,was valuable as the initial reference for sequen...In 2010,a major scientific milestone was achieved for tree fruit crops:publication of the first draft whole genome sequence(WGS)for apple(Malus domestica).This WGS,v1.0,was valuable as the initial reference for sequence information,fine mapping,gene discovery,variant discovery,and tool development.A new,high quality apple WGS,GDDH13 v1.1,was released in 2017 and now serves as the reference genome for apple.Over the past decade,these apple WGSs have had an enormous impact on our understanding of apple biological functioning,trait physiology and inheritance,leading to practical applications for improving this highly valued crop.Causal gene identities for phenotypes of fundamental and practical interest can today be discovered much more rapidly.Genome-wide polymorphisms at high genetic resolution are screened efficiently over hundreds to thousands of individuals with new insights into genetic relationships and pedigrees.High-density genetic maps are constructed efficiently and quantitative trait loci for valuable traits are readily associated with positional candidate genes and/or converted into diagnostic tests for breeders.We understand the species,geographical,and genomic origins of domesticated apple more precisely,as well as its relationship to wild relatives.The WGS has turbo-charged application of these classical research steps to crop improvement and drives innovative methods to achieve more durable,environmentally sound,productive,and consumer-desirable apple production.This review includes examples of basic and practical breakthroughs and challenges in using the apple WGSs.Recommendations for“what’s next”focus on necessary upgrades to the genome sequence data pool,as well as for use of the data,to reach new frontiers in genomics-based scientific understanding of apple.展开更多
Pedigree information is of fundamental importance in breeding programs and related genetics efforts.However,many individuals have unknown pedigrees.While methods to identify and confirm direct parent–offspring relati...Pedigree information is of fundamental importance in breeding programs and related genetics efforts.However,many individuals have unknown pedigrees.While methods to identify and confirm direct parent–offspring relationships are routine,those for other types of close relationships have yet to be effectively and widely implemented with plants,due to complications such as asexual propagation and extensive inbreeding.The objective of this study was to develop and demonstrate methods that support complex pedigree reconstruction via the total length of identical by state haplotypes(referred to in this study as“summed potential lengths of shared haplotypes”,SPLoSH).A custom Python script,HapShared,was developed to generate SPLoSH data in apple and sweet cherry.HapShared was used to establish empirical distributions of SPLoSH data for known relationships in these crops.These distributions were then used to estimate previously unknown relationships.Case studies in each crop demonstrated various pedigree reconstruction scenarios using SPLoSH data.For cherry,a full-sib relationship was deduced for‘Emperor Francis,and‘Schmidt’,a half-sib relationship for‘Van’and‘Windsor’,and the paternal grandparents of‘Stella’were confirmed.For apple,29 cultivars were found to share an unknown parent,the pedigree of the unknown parent of‘Cox’s Pomona’was reconstructed,and‘Fameuse’was deduced to be a likely grandparent of‘McIntosh’.Key genetic resources that enabled this empirical study were large genome-wide SNP array datasets,integrated genetic maps,and previously identified pedigree relationships.Crops with similar resources are also expected to benefit from using HapShared for empowering pedigree reconstruction.展开更多
基金supported by the project RIS3CAT(COTPAFRUIT3CAT)financed by the European Regional Development Fund through the FEDER frame of Catalonia 2014–2020 and by the CERCA Program from Generalitat de Catalunya.
文摘Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates.Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs,and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions.Here we present an apple reference population:the apple REFPOP,a large collection formed of 534 genotypes planted in six European countries,as a unique tool to accelerate apple breeding.The population consisted of 269 accessions and 265 progeny from 27 parental combinations,representing the diversity in cultivated apple and current European breeding material,respectively.A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95.Based on the genotypic data,linkage disequilibrium was low and population structure was weak.Two well-studied phenological traits of horticultural importance were measured.We found marker–trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date,respectively.With decreasing SNP density,the detection of significant marker–trait associations varied depending on trait architecture.Regardless of the trait,10,000 SNPs sufficed to maximize genomic prediction ability.We confirm the suitability of the apple REFPOP design for genomics-assisted breeding,especially for breeding programs using related germplasm,and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era.
文摘In 2010,a major scientific milestone was achieved for tree fruit crops:publication of the first draft whole genome sequence(WGS)for apple(Malus domestica).This WGS,v1.0,was valuable as the initial reference for sequence information,fine mapping,gene discovery,variant discovery,and tool development.A new,high quality apple WGS,GDDH13 v1.1,was released in 2017 and now serves as the reference genome for apple.Over the past decade,these apple WGSs have had an enormous impact on our understanding of apple biological functioning,trait physiology and inheritance,leading to practical applications for improving this highly valued crop.Causal gene identities for phenotypes of fundamental and practical interest can today be discovered much more rapidly.Genome-wide polymorphisms at high genetic resolution are screened efficiently over hundreds to thousands of individuals with new insights into genetic relationships and pedigrees.High-density genetic maps are constructed efficiently and quantitative trait loci for valuable traits are readily associated with positional candidate genes and/or converted into diagnostic tests for breeders.We understand the species,geographical,and genomic origins of domesticated apple more precisely,as well as its relationship to wild relatives.The WGS has turbo-charged application of these classical research steps to crop improvement and drives innovative methods to achieve more durable,environmentally sound,productive,and consumer-desirable apple production.This review includes examples of basic and practical breakthroughs and challenges in using the apple WGSs.Recommendations for“what’s next”focus on necessary upgrades to the genome sequence data pool,as well as for use of the data,to reach new frontiers in genomics-based scientific understanding of apple.
基金Funding for this research was in part provided by the Niedersächsisches Ministerium für Wissenschaft und Kultur through the EGON project:“Research for a sustainable agricultural production:Development of organically bred fruit cultivars in creative commons initiatives”,the USDA NIFA Specialty Crop Research Initiative projects,“RosBREED:Enabling marker-assisted breeding in Rosaceae”(2009-51181-05808)“RosBREED 2:Combining disease resistance with horticultural quality in new rosaceous cultivars”(2014-51181-22378),USDA NIFA Hatch project 1014919,and State Agricultural Experiment Station-University of Minnesota Project MIN-21-040.Part of the 20K Infinium SNP data came from the FruitBreedomics project no 265582:“Integrated approach for increasing breeding efficiency in fruit tree crops”50,which was co-funded by the EU seventh Framework Programme.
文摘Pedigree information is of fundamental importance in breeding programs and related genetics efforts.However,many individuals have unknown pedigrees.While methods to identify and confirm direct parent–offspring relationships are routine,those for other types of close relationships have yet to be effectively and widely implemented with plants,due to complications such as asexual propagation and extensive inbreeding.The objective of this study was to develop and demonstrate methods that support complex pedigree reconstruction via the total length of identical by state haplotypes(referred to in this study as“summed potential lengths of shared haplotypes”,SPLoSH).A custom Python script,HapShared,was developed to generate SPLoSH data in apple and sweet cherry.HapShared was used to establish empirical distributions of SPLoSH data for known relationships in these crops.These distributions were then used to estimate previously unknown relationships.Case studies in each crop demonstrated various pedigree reconstruction scenarios using SPLoSH data.For cherry,a full-sib relationship was deduced for‘Emperor Francis,and‘Schmidt’,a half-sib relationship for‘Van’and‘Windsor’,and the paternal grandparents of‘Stella’were confirmed.For apple,29 cultivars were found to share an unknown parent,the pedigree of the unknown parent of‘Cox’s Pomona’was reconstructed,and‘Fameuse’was deduced to be a likely grandparent of‘McIntosh’.Key genetic resources that enabled this empirical study were large genome-wide SNP array datasets,integrated genetic maps,and previously identified pedigree relationships.Crops with similar resources are also expected to benefit from using HapShared for empowering pedigree reconstruction.
