195 research outputs found
Prevalence of intramammary infections in heifer around calving in 40 dairy herds in the West of France
No full textInheritance studies of apple scab resistance and identification of Rvi14, a new major gene that acts together with other broad-spectrum QTL
No full textScab, caused by the fungal pathogen Venturia inaequalis, is the most common disease of cultivated apple (Malus domestica). The fungal races 6 and 7 have now overcome the major resistance gene Vf, which is widely used in apple breeding programmes. New breeding strategies to achieve durable resistance are thus necessary. The aim of this study was to determine the genetic basis of quantitative resistance of the apple cultivar ‘Du¨lmener Rosenapfel’, known to be scab resistant under different environmental conditions. An F1 progeny derived from the cross between the susceptible cultivar ‘Gala’ and ‘Du¨lmener Rosenapfel’ was tested in a greenhouse with a multi-isolate inoculum of V. inaequalis.
Rvi14, a new major gene that conditions a chlorotic-type reaction, was mapped on linkage group (LG) 6 in a genomic region not known to be involved in disease resistance. A further three quantitative trait loci (QTL) for resistance were identified. One co-localized with Rvi14 on LG6, whereas the remaining two were detected on LG11 and LG17, in genomic regions already reported to carry broad-spectrum QTL in other genetic backgrounds. Since a selective genotyping approach was used to detect QTL, an expectation-maximization (EM) computation was used to estimate the corrected QTL contributions
to phenotypic variation and was validated by entire progeny genotyping
Towards a physical map of the locus conferring resistance against the rosy apple aphid Dysaphis plantaginea from the cultivar ‘Florina’
No full textCultivated apples (Malus x domestica) are susceptible to several pests including rosy apple aphid (Dysaphis plantaginea, Passerini) which causes severe economic damages. After the phenotypic characterization of two segregating F1 progenies deriving from the resistant cultivar 'Florina', a single resistance gene (denoted Dp-fl) has been postulated. Dp-fl was mapped at the bottom of linkage group 8 of 'Florina', close to SSR CH01h10. Recently, several Single Nucleotide Polymorphisms (SNPs) located downstream from this SSR have been identified and mapped. The two closest SNP markers flanking the Dp-fl gene have restricted the physical interval containing the resistance gene to approximately 330 kb. In the present work, these two flanking SNPs were used for the screening of a 'Florina' BAC library. The aim of this work was to identify a minimum tiling path of BAC clones spanning the Dp-fl locus to identify the putative candidate genes. So far, the first steps of the screening have been successfully completed and six BAC clones have been identified. Sequencing of the BACs is in progress. Once the full sequence of the Dp-fl region will be completed, important knowledge will be gained for both understanding the functional mechanism underlying the resistance and directly targeting the gene in marker-assisted breeding
Development and test of 21 multiplex PCRs composed of SSRs spanning most of the apple genome
No full textA series of 21 multiplex (MP) polymerase chain reactions containing simple sequence repeat (SSR) markers spanning most of the apple genome has been developed. Eighty-eight SSR markers, well distributed over all 17 linkage groups (LGs), have been selected. Eighty-four of them were included in 21 different MPs while four could not be included in any MPs. The 21 MPs were then used to genotype approximately 2,000 DNA samples from the European High-quality Disease-Resistant Apples for a Sustainable agriculture project. Two SSRs (CH01d03 and NZAL08) were discarded at an early stage as they did not produce stable amplifications in the MPs, while the scoring of the multilocus (ML) SSR Hi07d11 and CN44794 was too complex for large-scale genotyping. The testing of the remaining 80 SSRs over a large number of different genotypes allowed: (1) a better estimation of their level of polymorphism; as well as of (2) the size range of the alleles amplified; (3) the identification of additional unmapped loci of some ML SSRs; (4) the development of methods to assign alleles to the different loci of ML SSRs and (5) conditions at which an SSR previously described as ML would amplify alleles of a single locus to be determined. These data resulted in the selection of 75 SSRs out of the 80 that are well suited and recommended for large genotyping projects
Combining genetic resources and elite material populations to improve the accuracy of genomic prediction in apple
No full textGenomic selection is an attractive strategy for apple breeding that could reduce the length of breeding cycles. A possible limitation to the practical implementation of this approach lies in the creation of a training set large and diverse enough to ensure accurate predictions. In this study, we investigated the potential of combining two available populations, i.e., genetic resources and elite material, in order to obtain a large training set with a high genetic diversity. We compared the predictive ability of genomic predictions within-population, across-population or when combining both populations, and tested a model accounting for population-specific marker effects in this last case. The obtained predictive abilities were moderate to high according to the studied trait and small increases in predictive ability could be obtained for some traits when the two populations were combined into a unique training set. We also investigated the potential of such a training set to predict hybrids resulting from crosses between the two populations, with a focus on the method to design the training set and the best proportion of each population to optimize predictions. The measured predictive abilities were very similar for all the proportions, except for the extreme cases where only one of the two populations was used in the training set, in which case predictive abilities could be lower than when using both populations. Using an optimization algorithm to choose the genotypes in the training set also led to higher predictive abilities than when the genotypes were chosen at random. Our results provide guidelines to initiate breeding programs that use genomic selection when the implementation of the training set is a limitation
Catalogue d'un choix de beaux livres, provenant de la bibliothèque de M. E. M. de C.
No full text[Vente (Livres). 1884-12-19. Paris][Collection (Livres). M. E. M. de C.. 1884]Appartient à l’ensemble documentaire : VenteEST2Avec mode text
Review on apple genetics and breeding programmes and presentation of a new European initiative to increase fruit breeding efficiency
No full textCultivar fingerprinting and SNP-based pedigree reconstruction in Danish heritage apple cultivars utilizing genotypic data from multiple germplasm collections in the world
No full textHeirloom Danish apple cultivars are historically and pomologically important, part of the cultural heritage, and have valuable adaptation to regional climate conditions. However, lack of information about their genetic identity and pedigree relatedness with other cultivars hampers proper cultivar identification, germplasm curation, genebank management, and future regional breeding efforts. Many Danish apple cultivars are maintained in the national collection “The Pometum”, maintaining around 850 apple accessions. Additional material is maintained in public or private Danish collections. However, no information exists regarding genotypic duplicates between these collections and germplasm collections in other countries, pedigree inferences across collections, and genotypically unique accessions at the genebank level. To provide such information, 976 accessions from Denmark were genotyped with simple sequence repeat (SSR) markers and the Illumina Infinium 20K single nucleotide polymorphism (SNP) array. The resulting genotypic data were compared to large databases of genotypic data from germplasm collections in multiple countries to identify genotypic duplicates and conduct pedigree reconstruction. The germplasm maintains 305 unique genotypic profiles which were not found in other germplasm collections. The study exposed previously unknown synonyms, accessions not true-to-type, and novel pedigree relationships involving accessions from multiple collection sites. The most frequent parents of Danish germplasm were ‘Hvid Vinter Pigeon’ and ‘Cox’s Orange Pippin’ whereas ‘Reinette Franche’ was the most common grandparent. The accession-level information will benefit germplasm curation, cultivar identification, genebank management, and future breeding efforts, and shed new light on cultivar history and origi
Construction of an integrated consensus map of the Apple genome based on four mapping populations
No full textAn integrated consensus genetic map for apple was constructed on the basis of segregation data from four genetically connected crosses (C1¿=¿Discovery × TN10-8, C2¿=¿Fiesta × Discovery, C3¿=¿Discovery × Prima, C4¿=¿Durello di Forli × Fiesta) with a total of 676 individuals using CarthaGene® software. First, integrated female¿male maps were built for each population using common female¿male simple sequence repeat markers (SSRs). Then, common SSRs over populations were used for the consensus map integration. The integrated consensus map consists of 1,046 markers, of which 159 are SSR markers, distributed over 17 linkage groups reflecting the basic chromosome number of apple. The total length of the integrated consensus map was 1,032 cM with a mean distance between adjacent loci of 1.1 cM. Markers were proportionally distributed over the 17 linkage groups (¿ 2¿=¿16.53, df¿=¿16, p¿=¿0.41). A non-uniform marker distribution was observed within all of the linkage groups (LGs). Clustering of markers at the same position (within a 1-cM window) was observed throughout LGs and consisted predominantly of only two to three linked markers. The four integrated female¿male maps showed a very good colinearity in marker order for their common markers, except for only two (CH01h01, CH05g03) and three (CH05a02z, NZ02b01, Lap-1) markers on LG17 and LG15, respectively. This integrated consensus map provides a framework for performing quantitative trait locus (QTL) detection in a multi-population design and evaluating the genetic background effect on QTL expression
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