Artículos de revistas
Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies
Fecha
2017Registro en:
BMC Genomics, Volumen 18, Issue 1, 2018,
14712164
10.1186/s12864-017-3781-8
Autor
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
Institución
Resumen
© 2017 The Author(s). 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 wa