Integrated QTL detection for key breeding traits in multiple peach progenies

José R. Hernández Mora (1) , Diego Micheletti (2) , Marco Bink (3) , Eric van de Weg (4) , Celia Cantín (5) , Nelson Nazzicari (6, 7) , Andrea Caprera (7) , Maria Teresa Dettori (8) , Sabrina Micali (8) , Elisa Banchi (2) , José Antonio Campoy-Corbalan (9) , Elisabeth Dirlewanger (9) , Patrick Lambert (10) , Thierry Pascal (10) , Michela Troggio (2) , Daniele Bassi (11) , Laura Rossini (11, 7) , Ignazio Verde (8) , Bénédicte Quilot-Turion (10) , Francois Laurens (12) , Pere Arus (1) , Maria José Aranzana (1)

1 Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB-UB
2 Research and Innovation Centre
3 Technology & Services
4 Plant Breeding
5 Fruit CentreParc Cientific i Tecnològic Agroalimentari de Lleida (PCiTAL)
6 Research Centre for Fodder Crops and Dairy Productions
7 PTP Science Park
8 Centro di Ricerca per la Frutticoltura
9 BFP - Biologie du fruit et pathologie
10 GAFL - Génétique et Amélioration des Fruits et Légumes
11 DiSAA
12 IRHS - Institut de Recherche en Horticulture et Semences

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.

Mots clés: Peach QTL; Pedigre-based Analysis; PBA; FlexQTLTM; Peach breeding; fishery management; genetic variability

Mots clés: détection qtl; gestion des pêches; génotype végétal; pépinière fruitière; pédigrée; prunus persica; phase reproductrice; variabilité génétique

Domaines: Biologie végétale

José R. Hernández Mora, Diego Micheletti, Marco Bink, Eric van de Weg, Celia Cantín, et al.. Integrated QTL detection for key breeding traits in multiple peach progenies. BMC Genomics, 2017, 18 (1), ⟨10.1186/s12864-017-3783-6⟩. ⟨hal-01533858⟩