Genomic Prediction of Autotetraploids; Influence of Relationship Matrices, Allele Dosage, and Continuous Genotyping Calls in Phenotype Prediction

Abstract

Estimation of allele dosage, using genomic data, in autopolyploids is challenging and current methods often result in the misclassification of genotypes. Some progress has been made when using SNP arrays, but the major challenge is when using next generation sequencing data. Here we compare the use of read depth as continuous parameterization with ploidy parameterizations in the context of genomic selection (GS). Additionally, different sources of information to build relationship matrices were compared. A real breeding population of the autotetraploid species blueberry (Vaccinium corybosum), composed of 1,847 individuals was phenotyped for eight yield and fruit quality traits over two years. Continuous genotypic based models performed as well as the best models. This approach also reduces the computational time and avoids problems associated with misclassification of genotypic classes when assigning dosage in polyploid species. This approach could be very valuable for species with higher ploidy levels or for emerging crops where ploidy is not well understood. To our knowledge, this work constitutes the first study of genomic selection in blueberry. Accuracies are encouraging for application of GS for blueberry breeding. GS could reduce the time for cultivar release by three years, increasing the genetic gain per cycle by 86% on average when compared to phenotypic selection, and 32% when compared with pedigree-based selection. Finally, the genotypic and phenotypic data used in this study are made available for comparative analysis of dosage calling and genomic selection prediction models in the context of autopolyploids.

Keywords: Allelic dosage; Autopolyploid; GenPred; Genomic Prediction; Genomic Selection; Relationship Matrices; Shared Data Resources; Shared data; Vaccinium; blueberry.

Figure 1

Linkage disequilibrium decay and heterozygosity for blueberry. Linkage disequilibrium decay estimation using one marker per probe, within scaffolds for (A) diploid, (B) tetraploid and (C) continuous genotype parameterizations. Heterozygosity observed in (D) diploid, (E) tetraploid, and (F) heterozygosity empirically established for the continuous genotypes’ scenario, assuming the limits of 0.058 ≤ X ≤ 0.908.

Figure 2

Relationship between continuous values and the classes assumed in the (A) diploid and (B) tetraploid parameterizations.

Figure 3

Phenotypic predictive abilities. Predictive abilities obtained for (A) seven traits in 2014, and (B) for six traits in 2015 considering different dosage parameterizations (indicated by the numbers 2 or 4, and r for ratio values), and different relationship matrices (indicated by the letters I, A, and G) in the prediction of breeding values of 1,847 blueberry genotypes.

Figure 4

Proposal of GS implementation in the University of Florida blueberry breeding program. UF blueberry breeding program stages and times of selection considering the conventional process (left) compared with the proposed process implementing genomic selection (right).