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Elsa Sverrisdóttir, Department of Chemistry and Bioscience will defend her thesis on: "Initiating Genomic Selection in Tetraploid Potato"
04.05.2017 kl. 13.00 - 16.00
"Initiating Genomic Selection in Tetraploid Potato"
The world’s population is growing rapidly, and by 2050 it is estimated that it will reach its maximum at almost 10 billion people, more than doubling the food demand. Breeding for more space and resource efficient crops is therefore more important than ever, especially since most fertile areas are already intensively cultivated. Potato is the world’s most important non-grain food crop and produces approximately twice the amount of calories per hectare compared to cereals. It is one of the most space-efficient food crops and is thus of central importance for global food security.
Potato breeding faces several difficulties, leading to slow breeding gain. The traditional “mate and phenotype” breeding approach is costly and time-consuming, consisting of 10-15 years of hard work, where as much as a million seedlings are screened before a cultivar can successfully be introduced to the market. Molecular breeding has the potential to speed up the breeding process significantly, and the completion of the potato genome sequence has greatly facilitated 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, which makes it an attractive breeding alternative.
The overall objective of this thesis was to evaluate the potential of and initiate a genomic selection breeding programme in tetraploid potato. Genotyping-by-sequencing was used to genotype a large number of individuals from three panels, and genomic prediction models were generated for starch content, dry matter, chipping quality, yield, and late blight resistance.
Overall, the results of this study suggest that genomic prediction of important agricultural traits, and hence selection of breeding material by genomic selection, can be obtained with good accuracies within tetraploid potato. The most optimal prediction accuracies were obtained when predicting within the same population, while predictions across populations were significantly lower. However, when combining all populations, maximal prediction accuracy could be obtained for all populations simultaneously, suggesting a promising approach for establishing a broad-application prediction model for the implementation of genomic selection in tetraploid potato breeding programmes.
Professor, Søren Kjærsgaard Rasmussen, Department of Plant and Environmental Sciences, KU, Denmark
Department of Chemistry and Bioscience, AAU, Section of Biotechnology
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