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Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies.
Biscarini, Filippo; Nazzicari, Nelson; Bink, Marco; Arús, Pere; Aranzana, Maria José; Verde, Ignazio; Micali, Sabrina; Pascal, Thierry; Quilot-Turion, Benedicte; Lambert, Patrick; da Silva Linge, Cassia; Pacheco, Igor; Bassi, Daniele; Stella, Alessandra; Rossini, Laura.
Afiliación
  • Biscarini F; PTP Science Park, Via Einstein - Loc. Cascina Codazza, Lodi, Italy.
  • Nazzicari N; IBBA-CNR, Via Edoardo Bassini, 15, Milan, 20133, Italy.
  • Bink M; PTP Science Park, Via Einstein - Loc. Cascina Codazza, Lodi, Italy.
  • Arús P; Council for Agricultural Research and Economics (CREA) Research Centre for Fodder Crops and Dairy Productions, Lodi, Italy.
  • Aranzana MJ; Wageningen UR Biometris, Wageningen, The Netherlands.
  • Verde I; Present Address: Hendrix Genetics Research, Technology & Services B.V., P.O. Box 114, Boxmeer NL, 5830AC, The Netherlands.
  • Micali S; IRTA, Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra (Cerdanyola del Vallés), Barcelona, Spain.
  • Pascal T; IRTA, Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra (Cerdanyola del Vallés), Barcelona, Spain.
  • Quilot-Turion B; Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria (CREA) - Centro di Ricerca per la Frutticoltura (CREA-FRU), Via di Fioranello 52, Roma, Italy.
  • Lambert P; Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria (CREA) - Centro di Ricerca per la Frutticoltura (CREA-FRU), Via di Fioranello 52, Roma, Italy.
  • da Silva Linge C; GAFL, INRA, Montfavet, 84140, France.
  • Pacheco I; GAFL, INRA, Montfavet, 84140, France.
  • Bassi D; Università degli Studi di Milano - DiSAA, Via Celoria 2, Milano, Italy.
  • Stella A; Università degli Studi di Milano - DiSAA, Via Celoria 2, Milano, Italy.
  • Rossini L; Università degli Studi di Milano - DiSAA, Via Celoria 2, Milano, Italy.
BMC Genomics ; 18(1): 432, 2017 06 06.
Article en En | MEDLINE | ID: mdl-28583089
ABSTRACT

BACKGROUND:

Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach.

RESULTS:

A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3-5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW0.35, SC0.48, TA0.53, on average) and repeatability (FW0.56, SC0.63, TA0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW0.60, SC0.72, TA0.65, on average).

CONCLUSIONS:

This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the typical long cycles involved in peach productions. All together, these results are very promising for the application of genomic selection to peach breeding programmes.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Genómica / Prunus persica / Frutas Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2017 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Genómica / Prunus persica / Frutas Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2017 Tipo del documento: Article País de afiliación: Italia