Initiating genomic selection in tetraploid potato

Elsa Sverrisdóttir, Luc Janss, Stephen Byrne, Torben Asp, Kåre Lehmann Nielsen

Research output: Contribution to conference without publisher/journalConference abstract for conferenceResearch

Abstract

Breeding for more space and resource efficient crops is important to feed the world’s increasing population. Potatoes produce approximately twice the amount of calories per hectare compared to cereals. The traditional “mate and phenotype” breeding approach is costly and time-consuming; however, the completion of the genome sequence of potato has enabled the application of genomics-assisted breeding technologies. Genomic selection using genome-wide molecular markers is becoming increasingly applicable to crops as the genotyping costs continue to reduce and it is thus an attractive breeding alternative.
We have used genotyping-by-sequencing to genotype 762 individuals. The individuals were randomly selected from a population of 5,000 individuals derived from a poly-parental cross generated from 18 tetraploid cultivars and breeding clones (MASPot population). Phenotypic data have been established for six agronomical important traits for the entire population.
We have generated statistical models for genomic prediction and have obtained relatively high predictive power with absolute accuracies of 74%, 56%, 54%, and 21% for starch content, chipping quality, late blight resistance, and yield, respectively. When scaled to the trait heritability, which can also be interpreted as the maximum variance explained by genetic factors, relative prediction accuracies of 116%, 68%, 73%, and 49%, respectively, were obtained. As expected from the limited population size of this study, the within-population predictive power is considerably higher than its out-of-population predictive power. Nonetheless, to validate the prediction model, a test panel of 74 individuals not closely related to the training population were genotyped. Absolute prediction accuracies for starch content, chipping quality, and yield, were 40%, 43%, and 51%, with relative accuracies of 62%, 53%, and 109%, respectively. For late blight resistance, there was no correlation between predicted and observed phenotypic values. This was expected because specific dominant R-genes conferring resistance in the training population were different from the ones expected to be present in the validation population.
We are currently expanding the training set for a better calibration of the prediction model. Taken together, our results suggest that genomic prediction of complex traits, and hence selection of breeding material by genomic selection, can be obtained with good prediction accuracies in tetraploid potato.
Original languageEnglish
Publication date12 Sept 2016
Publication statusPublished - 12 Sept 2016
Event13th Solanaceae Conference: Solgenomics: From Advances to Applications - Davis, United States
Duration: 12 Sept 201616 Sept 2016
Conference number: 13th
http://www.solgenomics2016.ucdavis.edu

Conference

Conference13th Solanaceae Conference
Number13th
Country/TerritoryUnited States
CityDavis
Period12/09/201616/09/2016
Internet address

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