Accuracy and responses of genomic selection on key traits in apple breeding

The application of genomic selection in fruit tree crops is expected to enhance breeding eficiency by increasing prediction accuracy,increasing selection intensity and decreasing generation interval.The objectives of this study were to assess the accuracy of prediction and selection response in commercial apple breeding programmes for key traits.The training population comprised 977 individuals derived from 20 pedigreed fllsib families.Historic phenotypic data were available on 10 traits related to productivity and fruit external appearance and genotypic data for 7829 SNPs obtained with an llumina 20K SNP array.From these data,a genome-wide prediction model was built and subsequently used to calculate genomic breeding values of five application fllsib families.The application families had genotypes at 364 SNPs from a dedicated 512 SNP array,and these genotypic data were extended to the high-density level by imputation.These five families were phenotyped for 1 year and their phenotypes were compared to the predicted breeding values.Accuracy of genomic prediction across the 10 traits reached a maximum value of 0.5 and had a median value of 0.19.The accuracies were strongly affected by the phenotypic distribution and heritability of traits.In the largest family,significant selection response was observed for traits with high heritability and symmetric phenotypic distribution.Traits that showed non-significant response often had reduced and skewed phenotypic variation or low heritability.Among the five application families the accuracies were uncorrelated to the degree of relatedness to the training population.The results underline the potential of genomic prediction to accelerate breeding progress in outbred fruit tree crops that still need to overcome long generation intervals and extensive phenotyping costs.

An integrated approach for increasing breeding efficiency in apple and peach in Europe

Despite the availability of whole genome sequences of apple and peach,there has been a considerable gap between genomics and breeding.To bridge the gap,the European Union funded the FruitBreedomics project(March 2011 to August 2015)involving 28 research institutes and private companies.Three complementary approaches were pursued:(i)tool and software development,(ii)deciphering genetic control of main horticultural traits taking into account allelic diversity and(iii)developing plant materials,tools and methodologies for breeders.Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding,development of new,dense SNP arrays in apple and peach,new phenotypic methods for some complex traits,software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis(PBA).This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies(GWAS)on several European genebank collections.FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities.Through FruitBreedomics,significant progresses were made in the field of apple and peach breeding,genetics,genomics and bioinformatics of which advantage will be made by breeders,germplasm curators and scientists.A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public.This review covers the scientific discoveries made in this major endeavour,and perspective in the apple and peach breeding and genomics in Europe and beyond.

Apple whole genome sequences:recent advances and new prospects

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.

A high-density, multi-parental SNP genetic map on apple validates a new mapping approach for outcrossing species

Quantitative trait loci(QTL)mapping approaches rely on the correct ordering of molecular markers along the chromosomes,which can be obtained from genetic linkage maps or a reference genome sequence.For apple(Malus domestica Borkh),the genome sequence v1 and v2 could not meet this need;therefore,a novel approach was devised to develop a dense genetic linkage map,providing the most reliable marker-loci order for the highest possible number of markers.The approach was based on four strategies:(i)the use of multiple full-sib families,(ii)the reduction of missing information through the use of HaploBlocks and alternative calling procedures for single-nucleotide polymorphism(SNP)markers,(iii)the construction of a single backcross-type data set including all families,and(iv)a two-step map generation procedure based on the sequential inclusion of markers.The map comprises 15417 SNP markers,clustered in 3 K HaploBlock markers spanning 1267 cM,with an average distance between adjacent markers of 0.37 cM and a maximum distance of 3.29 cM.Moreover,chromosome 5 was oriented according to its homoeologous chromosome 10.This map was useful to improve the apple genome sequence,design the Axiom Apple 480 K SNP array and perform multifamily-based QTL studies.Its collinearity with the genome sequences v1 and v3 are reported.To our knowledge,this is the shortest published SNP map in apple,while including the largest number of markers,families and individuals.This result validates our methodology,proving its value for the construction of integrated linkage maps for any outbreeding species.