Next generation berries - implementing genome wide selection approaches
Genomic selection is one of the most advanced methods of plant breeding and uses information from a densely phenotyped training population along with marker information to predict the genome-wide contribution of genetic variants to a panel of agronomically important traits. Crucially it is a method that works extremely well with highly quantitative traits (which most traits in strawberry are). This method allows the prediction of plant performance using only genetic data, allowing selection to be made at the early seedling stage, rather than in the field.
As part of CP094, a PhD studentship that finished in October 2015, a population was phenotyped over the course of three years for a number of plant architecture, fruit quality and disease resistance traits and markers were identified controlling these traits. This information is perfect for training genomic selection models. Using this data, this studentship would test a range of genomic selection models for their efficacy at predicting plant performance and disease resistance traits. Using the SNP data from the Affymetrix SNP array and the forthcoming strawberry genome, the student will also develop reliable SNP markers for screening on the strawberry germplasm, to facilitiate the genomic selection process.
Source: AHDB Horticulture