Genomic prediction for dry matter and chipping quality in tetraploid potato

Elsa Sverrisdóttir, Ea Høegh Riis Nielsen, Heidi Øllegaard Johnsen, Hanne Grethe Kirk, Torben Asp, Luc Janss, Glenn J. Bryan, Kåre Lehmann Nielsen

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

Abstract

Potato is one of the most space-efficient food crops and is of vital importance for global food security. The traditional “mate and phenotype” breeding approach is costly and time-consuming; however, genomic selection using genome-wide molecular markers is becoming increasingly applicable to crops
and is thus an attractive breeding alternative.
Genotyping-by-sequencing was used to genotype a large number of individuals from three panels. The main panel, the MASPOT population, consisted of 762 individuals derived from a larger population generated from biparental crosses of 18 tetraploid parents. Additionally, two test panels were established, one panel consisting of breeding clones from the same breeding station as the MASPOT population, named Test panel DK, and one panel from a breeding station in the UK, named Test panel UK.
Genomic prediction models were generated for dry matter and chipping quality. High cross-validated prediction accuracies of 0.72-0.82 were obtained for dry matter within each population, while prediction accuracies for chipping quality varied from 0.17 to 0.79. Similar prediction accuracies were obtained when combining the panels in one large training population, while across-population predictions were low or moderate.
Overall, the results suggest that genomic prediction and hence selection of breeding material can be obtained with good accuracies within tetraploid potato. Although the most optimal prediction accuracies were obtained when predicting within the same population, the results from combining training populations with genotypes from different populations suggest a promising approach for establishing a broad-application prediction model for the implementation of genomic selection in tetraploid potato breeding programmes.
Original languageEnglish
Publication date3 Sep 2017
Publication statusPublished - 3 Sep 2017
EventXIV Solanaceae and 3rd Cucurbitaceae Joint Conference: Solcuc2017 - Valencia, Spain
Duration: 3 Sep 20176 Sep 2017
http://solcuc2017.org/

Conference

ConferenceXIV Solanaceae and 3rd Cucurbitaceae Joint Conference
CountrySpain
CityValencia
Period03/09/201706/09/2017
Internet address

Cite this

Sverrisdóttir, E., Nielsen, E. H. R., Johnsen, H. Ø., Kirk, H. G., Asp, T., Janss, L., ... Nielsen, K. L. (2017). Genomic prediction for dry matter and chipping quality in tetraploid potato. Abstract from XIV Solanaceae and 3rd Cucurbitaceae Joint Conference, Valencia, Spain.
Sverrisdóttir, Elsa ; Nielsen, Ea Høegh Riis ; Johnsen, Heidi Øllegaard ; Kirk, Hanne Grethe ; Asp, Torben ; Janss, Luc ; Bryan, Glenn J. ; Nielsen, Kåre Lehmann. / Genomic prediction for dry matter and chipping quality in tetraploid potato. Abstract from XIV Solanaceae and 3rd Cucurbitaceae Joint Conference, Valencia, Spain.
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abstract = "Potato is one of the most space-efficient food crops and is of vital importance for global food security. The traditional “mate and phenotype” breeding approach is costly and time-consuming; however, genomic selection using genome-wide molecular markers is becoming increasingly applicable to cropsand is thus an attractive breeding alternative.Genotyping-by-sequencing was used to genotype a large number of individuals from three panels. The main panel, the MASPOT population, consisted of 762 individuals derived from a larger population generated from biparental crosses of 18 tetraploid parents. Additionally, two test panels were established, one panel consisting of breeding clones from the same breeding station as the MASPOT population, named Test panel DK, and one panel from a breeding station in the UK, named Test panel UK.Genomic prediction models were generated for dry matter and chipping quality. High cross-validated prediction accuracies of 0.72-0.82 were obtained for dry matter within each population, while prediction accuracies for chipping quality varied from 0.17 to 0.79. Similar prediction accuracies were obtained when combining the panels in one large training population, while across-population predictions were low or moderate.Overall, the results suggest that genomic prediction and hence selection of breeding material can be obtained with good accuracies within tetraploid potato. Although the most optimal prediction accuracies were obtained when predicting within the same population, the results from combining training populations with genotypes from different populations suggest a promising approach for establishing a broad-application prediction model for the implementation of genomic selection in tetraploid potato breeding programmes.",
author = "Elsa Sverrisd{\'o}ttir and Nielsen, {Ea H{\o}egh Riis} and Johnsen, {Heidi {\O}llegaard} and Kirk, {Hanne Grethe} and Torben Asp and Luc Janss and Bryan, {Glenn J.} and Nielsen, {K{\aa}re Lehmann}",
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Sverrisdóttir, E, Nielsen, EHR, Johnsen, HØ, Kirk, HG, Asp, T, Janss, L, Bryan, GJ & Nielsen, KL 2017, 'Genomic prediction for dry matter and chipping quality in tetraploid potato', XIV Solanaceae and 3rd Cucurbitaceae Joint Conference, Valencia, Spain, 03/09/2017 - 06/09/2017.

Genomic prediction for dry matter and chipping quality in tetraploid potato. / Sverrisdóttir, Elsa; Nielsen, Ea Høegh Riis; Johnsen, Heidi Øllegaard; Kirk, Hanne Grethe; Asp, Torben; Janss, Luc; Bryan, Glenn J.; Nielsen, Kåre Lehmann.

2017. Abstract from XIV Solanaceae and 3rd Cucurbitaceae Joint Conference, Valencia, Spain.

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

TY - ABST

T1 - Genomic prediction for dry matter and chipping quality in tetraploid potato

AU - Sverrisdóttir, Elsa

AU - Nielsen, Ea Høegh Riis

AU - Johnsen, Heidi Øllegaard

AU - Kirk, Hanne Grethe

AU - Asp, Torben

AU - Janss, Luc

AU - Bryan, Glenn J.

AU - Nielsen, Kåre Lehmann

PY - 2017/9/3

Y1 - 2017/9/3

N2 - Potato is one of the most space-efficient food crops and is of vital importance for global food security. The traditional “mate and phenotype” breeding approach is costly and time-consuming; however, genomic selection using genome-wide molecular markers is becoming increasingly applicable to cropsand is thus an attractive breeding alternative.Genotyping-by-sequencing was used to genotype a large number of individuals from three panels. The main panel, the MASPOT population, consisted of 762 individuals derived from a larger population generated from biparental crosses of 18 tetraploid parents. Additionally, two test panels were established, one panel consisting of breeding clones from the same breeding station as the MASPOT population, named Test panel DK, and one panel from a breeding station in the UK, named Test panel UK.Genomic prediction models were generated for dry matter and chipping quality. High cross-validated prediction accuracies of 0.72-0.82 were obtained for dry matter within each population, while prediction accuracies for chipping quality varied from 0.17 to 0.79. Similar prediction accuracies were obtained when combining the panels in one large training population, while across-population predictions were low or moderate.Overall, the results suggest that genomic prediction and hence selection of breeding material can be obtained with good accuracies within tetraploid potato. Although the most optimal prediction accuracies were obtained when predicting within the same population, the results from combining training populations with genotypes from different populations suggest a promising approach for establishing a broad-application prediction model for the implementation of genomic selection in tetraploid potato breeding programmes.

AB - Potato is one of the most space-efficient food crops and is of vital importance for global food security. The traditional “mate and phenotype” breeding approach is costly and time-consuming; however, genomic selection using genome-wide molecular markers is becoming increasingly applicable to cropsand is thus an attractive breeding alternative.Genotyping-by-sequencing was used to genotype a large number of individuals from three panels. The main panel, the MASPOT population, consisted of 762 individuals derived from a larger population generated from biparental crosses of 18 tetraploid parents. Additionally, two test panels were established, one panel consisting of breeding clones from the same breeding station as the MASPOT population, named Test panel DK, and one panel from a breeding station in the UK, named Test panel UK.Genomic prediction models were generated for dry matter and chipping quality. High cross-validated prediction accuracies of 0.72-0.82 were obtained for dry matter within each population, while prediction accuracies for chipping quality varied from 0.17 to 0.79. Similar prediction accuracies were obtained when combining the panels in one large training population, while across-population predictions were low or moderate.Overall, the results suggest that genomic prediction and hence selection of breeding material can be obtained with good accuracies within tetraploid potato. Although the most optimal prediction accuracies were obtained when predicting within the same population, the results from combining training populations with genotypes from different populations suggest a promising approach for establishing a broad-application prediction model for the implementation of genomic selection in tetraploid potato breeding programmes.

M3 - Conference abstract for conference

ER -

Sverrisdóttir E, Nielsen EHR, Johnsen HØ, Kirk HG, Asp T, Janss L et al. Genomic prediction for dry matter and chipping quality in tetraploid potato. 2017. Abstract from XIV Solanaceae and 3rd Cucurbitaceae Joint Conference, Valencia, Spain.