Search

International audience

International audience

Additional file 2: Figure S1. (A) zHp value distribution; (B) Genome-wide zHp values for the three white-layer lines. Figure S2. Pipeline overview for the detection of deleterious and functional variants using population WGS data. Figure S3. Chromosome distribution of transition/transversion (TS/TV) ratio across all sequenced animals. Figure S4. PCA analysis for the sequenced samples in WA, WD, and W1 lines. Figure S5. Population F-statistics. Figure S6. Pearson correlation of SIFT and PROVEAN scores on 13,065 missense mutations. Figure S7. Allele frequency distribution of different classes of variants. Figure S8. Relative position of tolerated and deleterious missense variants (SIFT). Figure S9. Relative position of synonymous, tolerated, and deleterious missense variants (SIFT). Figure S10. Distribution of the ratio of deleterious to tolerated alleles in two classes of recombination rates (2). Figure S11. Missense variants predicted to be highly deleterious (PROVEAN

Additional file 1: Table S1. Statistics per breed. Table S2. Candidate mutations in regions of missing homozygosity. Table S3. Single nucleotide variants (SNV) and indels called. Table S4. Summary of identified variants for each line. Table S5. Call rate and TS/TV for all variants after filtering. Table S6. Functional annotation of variants (VEP). Table S7. Final list of deleterious variants identified in nine different classes. Table S8. Fertility phenotypes for three CXC matings that carry the OFD1 (Y19C) missense mutation.

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., Horticulture Research, 7 (1)

Additional file 2: Figure S1. (A) zHp value distribution; (B) Genome-wide zHp values for the three white-layer lines. Figure S2. Pipeline overview for the detection of deleterious and functional variants using population WGS data. Figure S3. Chromosome distribution of transition/transversion (TS/TV) ratio across all sequenced animals. Figure S4. PCA analysis for the sequenced samples in WA, WD, and W1 lines. Figure S5. Population F-statistics. Figure S6. Pearson correlation of SIFT and PROVEAN scores on 13,065 missense mutations. Figure S7. Allele frequency distribution of different classes of variants. Figure S8. Relative position of tolerated and deleterious missense variants (SIFT). Figure S9. Relative position of synonymous, tolerated, and deleterious missense variants (SIFT). Figure S10. Distribution of the ratio of deleterious to tolerated alleles in two classes of recombination rates (2). Figure S11. Missense variants predicted to be highly deleterious (PROVEAN

Additional file 1: Table S1. Statistics per breed. Table S2. Candidate mutations in regions of missing homozygosity. Table S3. Single nucleotide variants (SNV) and indels called. Table S4. Summary of identified variants for each line. Table S5. Call rate and TS/TV for all variants after filtering. Table S6. Functional annotation of variants (VEP). Table S7. Final list of deleterious variants identified in nine different classes. Table S8. Fertility phenotypes for three CXC matings that carry the OFD1 (Y19C) missense mutation.

[Background]: Peach (Prunus persica (L.) Batsch) is a major temperate fruit crop with an intense breeding activity. Breeding is facilitated by knowledge of the inheritance of the key traits that are often of a quantitative nature. QTLs have traditionally been studied using the phenotype of a single progeny (usually a full-sib progeny) and the correlation with a set of markers covering its genome. This approach has allowed the identification of various genes and QTLs but is limited by the small numbers of individuals used and by the narrow transect of the variability analyzed. In this article we propose the use of a multi-progeny mapping strategy that used pedigree information and Bayesian approaches that supports a more precise and complete survey of the available genetic variability., [Results]: Seven key agronomic characters (data from 1 to 3 years) were analyzed in 18 progenies from crosses between occidental commercial genotypes and various exotic lines including accessions of other Prunus species. A total of 1467 plants from these progenies were genotyped with a 9 k SNP array. Forty-seven QTLs were identified, 22 coinciding with major genes and QTLs that have been consistently found in the same populations when studied individually and 25 were new. A substantial part of the QTLs observed (47%) would not have been detected in crosses between only commercial materials, showing the high value of exotic lines as a source of novel alleles for the commercial gene pool. Our strategy also provided estimations on the narrow sense heritability of each character, and the estimation of the QTL genotypes of each parent for the different QTLs and their breeding value., [Conclusions]: The integrated strategy used provides a broader and more accurate picture of the variability available for peach breeding with the identification of many new QTLs, information on the sources of the alleles of interest and the breeding values of the potential donors of such valuable alleles. These results are first-hand information for breeders and a step forward towards the implementation of DNA-informed strategies to facilitate selection of new cultivars with improved productivity and quality., This work has been funded under the EU seventh Framework Programme by the FruitBreedomics project Nu. 265582: Integrated Approach for increasing breeding efficiency in fruit tree crops. IRTA-CRAG group received financial support from the Spanish Ministry of Economy and Competitiveness, through the “Severo Ochoa Programme for Centres of Excellence in R&D” 2016–2019 (SEV-2015-0533)” and through the project AGL2015-68329-R, and from the CERCA Programme/Generalitat de Catalunya.

Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS) at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM), which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16) which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe), and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs. JU has been partially supported by an Early Stage Research Fellowship of the Institute of Advanced Studies (University of Bologna).

International audience; 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 15 417 SNP markers, clustered in 3 K HaploBlock markers spanning 1 267 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.