As one of the world's most important food crops, potato (Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. non-additive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color.Genomic covariance matrices for additive (G), digenic dominant (D), and additive x additive epistatic (G#G) effects were calculated using 3895 markers, and the numerator relationship matrix (A) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including non-additive effects improved accuracy and/or bias when predicting total genotypic value, for all three traits. When six F1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and will improve selection for breeding value given the substantial amount of non-additive genetic variance in elite germplasm.4
The third most important food crop worldwide, potato (Solanum tuberosum L.) is a tetraploid outcrossing species propagated from tubers. Breeders have long been challenged by polyploidy, heterozygosity, and asexual reproduction. It has been assumed that tetraploidy is essential for high yield, that the creation of inbred potato is not feasible, and that propagation by seed tubers is ideal. In this paper, we question those assumptions and propose to convert potato into a diploid inbred line-based crop propagated by true seed. Although a conversion of this magnitude is unprecedented, the possible genetic gains from a breeding system based on inbred lines and the seed production benefits from a sexual propagation system are too large to ignore. We call on leaders of public and private organizations to come together to explore the feasibility of this radical and exciting new strategy in potato breeding.
New software to make tetraploid genotype calls from SNP array data was developed, which uses hierarchical clustering and multiple F1 populations to calibrate the relationship between signal intensity and allele dosage. SNP arrays are transforming breeding and genetics research for autotetraploids. To fully utilize these arrays, the relationship between signal intensity and allele dosage must be calibrated for each marker. We developed an improved computational method to automate this process, which is provided as the R package ClusterCall. In the training phase of the algorithm, hierarchical clustering within an F1 population is used to group samples with similar intensity values, and allele dosages are assigned to clusters based on expected segregation ratios. In the prediction phase, multiple F1 populations and the prediction set are clustered together, and the genotype for each cluster is the mode of the training set samples. A concordance metric, defined as the proportion of training set samples equal to the mode, can be used to eliminate unreliable markers and compare different algorithms. Across three potato families genotyped with an 8K SNP array, ClusterCall scored 5729 markers with at least 0.95 concordance (94.6% of its total), compared to 5325 with the software fitTetra (82.5% of its total). The three families were used to predict genotypes for 5218 SNPs in the SolCAP diversity panel, compared with 3521 SNPs in a previous study in which genotypes were called manually. One of the additional markers produced a significant association for vine maturity near a well-known causal locus on chromosome 5. In conclusion, when multiple F1 populations are available, ClusterCall is an efficient method for accurate, autotetraploid genotype calling that enables the use of SNP data for research and plant breeding.
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