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Combining genetic resources and elite material populations to improve the accuracy of genomic prediction in apple

Cazenave, Xabi and Petit, Bernard and Lateur, Marc and Nybom, Hilde and Sedlak, Jiri and Tartarini, Stefano and Laurens, Francois and Durel, Charles-Eric and Muranty, Hélène (2021). Combining genetic resources and elite material populations to improve the accuracy of genomic prediction in apple. G3. 12 :3 , jkab420
[Research article]

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Abstract

Genomic selection is an attractive strategy for apple breeding that could reduce the length of breeding cycles. A possible limitation to the practical implementation of this approach lies in the creation of a training set large and diverse enough to ensure accurate predictions. In this study, we investigated the potential of combining two available populations, i.e., genetic resources and elite material, in order to obtain a large training set with a high genetic diversity. We compared the predictive ability of genomic predictions within-population, across-population or when combining both populations, and tested a model accounting for population-specific marker effects in this last case. The obtained predictive abilities were moderate to high according to the studied trait and small increases in predictive ability could be obtained for some traits when the two populations were combined into a unique training set. We also investigated the potential of such a training set to predict hybrids resulting from crosses between the two populations, with a focus on the method to design the training set and the best proportion of each population to optimize predictions. The measured predictive abilities were very similar for all the proportions, except for the extreme cases where only one of the two populations was used in the training set, in which case predictive abilities could be lower than when using both populations. Using an optimization algorithm to choose the genotypes in the training set also led to higher predictive abilities than when the genotypes were chosen at random. Our results provide guidelines to initiate breeding programs that use genomic selection when the implementation of the training set is a limitation.

Authors/Creators:Cazenave, Xabi and Petit, Bernard and Lateur, Marc and Nybom, Hilde and Sedlak, Jiri and Tartarini, Stefano and Laurens, Francois and Durel, Charles-Eric and Muranty, Hélène
Title:Combining genetic resources and elite material populations to improve the accuracy of genomic prediction in apple
Series Name/Journal:G3
Year of publishing :2021
Volume:12
Number:3
Article number:jkab420
Number of Pages:16
Associated Programs and Other Stakeholders:Z - SLU - Library > Odla mera
ISSN:2160-1836
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Agricultural Science
URN:NBN:urn:nbn:se:slu:epsilon-p-115088
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-115088
Additional ID:
Type of IDID
DOI10.1093/g3journal/jkab420
ID Code:27269
Faculty:LTV - Fakulteten för landskapsarkitektur, trädgårds- och växtproduktionsvetenskap
Department:(LTJ, LTV) > Department of Plant Breeding (from 130101)
Deposited By: SLUpub Connector
Deposited On:07 Mar 2022 16:25
Metadata Last Modified:08 Mar 2022 05:04

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