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Connectedness among test series in mixed linear models of genetic evaluation for forest trees


In forest tree species with large natural ranges, there are usually several to many separate breeding populations, each designed to capture elite material suited to a particular geographic region. Separate test series are often dedicated to each population. Because the aim is to optimise gain in the meta-population, it is important to ensure that test series are linked so that individuals can be compared across test series as well as within. Computer simulation was used to determine the most efficient strategy for obtaining linkage. The average accuracy of a genetic value contrast between individuals in the same and in different test series was used as the criterion for assessing the optimal level of linkage. Accuracy is a function of the elements of the inverse coefficient matrix for a mixed linear model within a best linear unbiased prediction framework (BLUP). Material used to link test series was either common test families, common check-lots such as seed orchard bulks, or families generated by inter-crossing parents from different test series. Use of common test families was the most efficient strategy for the scenarios tested, which included having 50 parents crossed to produce 50 test families in each of three populations. For a low-heritability scenario, the amount of linkage material, relative to test material, needed to be 8 and 12 %, for progeny and parents, respectively, in order for a contrast between individuals in different test series to have equivalent accuracy as a contrast between individuals in the same test series. Other strategies were less efficient in terms of the amount of linkage material needed to obtain this equivalency.

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The authors gratefully acknowledge the financial support received from the Swedish Association for Forest Tree Breeding (grant number 219). They would like to thank the helpful support given by the Southern Tree Breeding Association, particularly Dr. Tony McRae and Mr Peter Cunningham.

Data Archiving Statement

Data for this project were generated using computer simulation. Primary data comprised simulated pedigrees, mating patterns and allocation of trees to test series, replicate and blocks numbers. Secondary data were then generated and comprised sparse matrices containing the coefficient matrix for the mixed model equations. Inverting these matrices derived accuracies and prediction error variances. Primary and secondary data currently exist on the first author’s computer and can be provided to a third party repository database if required.

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Correspondence to Richard J. Kerr.

Additional information

This article is part of the Topical Collection on Breeding

Communicated by R. Burdon

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Kerr, R.J., Dutkowski, G.W., Jansson, G. et al. Connectedness among test series in mixed linear models of genetic evaluation for forest trees. Tree Genetics & Genomes 11, 67 (2015).

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  • Connectedness
  • Genetic evaluation
  • BLUP
  • Genetic progress