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Novel methods for improved tree breeding

Hallander, Jon (2009). Novel methods for improved tree breeding. Diss. (sammanfattning/summary) Umeå : Sveriges lantbruksuniv., Acta Universitatis Agriculturae Sueciae, 1652-6880 ; 2009:13
ISBN 978-91-86195-60-1
[Doctoral thesis]

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The development and implementation of statistical tools to improve inference in sustainable forest tree breeding are presented here. By combining classical quantitative genetic theory and novel statistical methods, a number of parameters are optimized. The results obtained are compared to those achieved by traditional methods for visualizing improvements to genetic parameters. The methods are tested on both simulated data and on a real Scots pine pedigree. Modeling non-additive gene action using a finite loci model indicates that the development of the additive variance component does not decay initially as the underlying theory predicts. This phenomenon is shown for different sets of genetic components and models. In addition, variable numbers of loci were used so that different numbers of interactions could be captured. To draw inferences about the genetic parameters, a powerful Bayesian Markov chain Monte Carlo method was developed. The method utilizes transformation of the genetic covariance structure to improve computational speed. By combining two different Bayesian Gibbs samplers, a useful hybrid sampler was developed; this was found to enhance convergence statistics and computational speed. A method that finds the number of trees and their respective mating proportions that will maximize genetic gain was implemented and modified to handle a large number of selection candidates. When testing the selection method on a real pedigree an increase in genetic gain of up to 30 % was found compared to traditional methods in which the same restrictions were placed on relatedness. In order to provide a long-term breeding perspective, the selection method was combined with various mating schemes to examine the development of genetic parameters. A modified minimum coancestry mating scheme resulted in a level of genetic gain closest to the theoretically achievable limit while reducing the level of inbreeding in the population.

Authors/Creators:Hallander, Jon
Title:Novel methods for improved tree breeding
Series Name/Journal:Acta Universitatis Agriculturae Sueciae
Year of publishing :2009
Number of Pages:50
ALLI Hallander, J. & Waldmann, P. (2007). The effect of non-additive genetic interactions on selection in multi-locus genetic models. Heredity 98, 1-11. II Waldmann, P., Hallander, J., Hoti, F. & Sillanpää, M.J. (2008). Efficient MCMC implementation of Bayesian analysis of additive and dominance genetic variances in non-inbred pedigrees. Genetics 179, 1101-1112. III Hallander, J. & Waldmann, P. (2009). Optimum contribution selection in large general tree breeding populations with an application to Scots pine. Theoretical and Applied Genetics [online] 1432, 2242. Available from: http://springerlink.com/content/t831115126071v62/fulltext.pdf [Accessed 31st January 2009]. IV Hallander, J. & Waldmann, P. Optimization of selection contribution and mate allocation in tree breeding populations (manuscript).
Place of Publication:Umeå
ISBN for printed version:978-91-86195-60-1
Publication Type:Doctoral thesis
Full Text Status:Public
Agrovoc terms:pinus sylvestris, plant breeding, forest trees, statistical methods, optimization methods
Keywords:Tree breeding, Selection, Optimization, Dominance, Bayesian inference, Genetic gain, Inbreeding, Mate allocation, Scots pine
Permanent URL:
ID Code:1961
Department:(S) > Dept. of Forest Genetics and Plant Physiology
Deposited By: Jon Hallander
Deposited On:16 Mar 2009 00:00
Metadata Last Modified:02 Dec 2014 10:15

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