Home About Browse Search
Svenska


Quantitative genetics and genomic selection of Scots pine

Calleja-Rodriguez, Ainhoa (2019). Quantitative genetics and genomic selection of Scots pine. Diss. (sammanfattning/summary) Umeå : Sveriges lantbruksuniv., Acta Universitatis agriculturae Sueciae, 1652-6880 ; 2019:36
ISBN 978-91-7760-390-0
eISBN 978-91-7760-391-7
[Doctoral thesis]

[img]
Preview
PDF - Published Version
1MB

Abstract

The final objective of tree improvement programs is to increase the frequency of favourable alleles in a population, for the traits of interest within the breeding programs. To achieve this, it is crucial to decompose the phenotypic variance accurately into its genetic and environmental components in order to obtain a precise estimation of genetic parameters and to increase genetic gains. The overall aim of this thesis was to increase the accuracy of genetic parameter estimation by incorporating new quantitative genetics models to the analysis of multiple traits in multiple trials of Scots pine, and to develop a genomic selection protocol to accelerate genetic gain. Factor analysis was incorporated to multivariate multi-environment analyses and it allowed to evaluate up to 19 traits simultaneously. As a result, precise patterns of genotype-by-environment interactions (G  E) were observed for tree vitality and height; moreover, it was possible to detect the main driver of the G  E: differences in temperature sum among sites. Traditional quantitative trait loci (QTL) analysis of phenotypic data was compared with the detection of QTL with estimated breeding values (EBV) for the first time in a three generation pedigree and, as outcome, it was noticed that if a QTL was associated to a EBV and to a phenotypic trait, the proportion of variance explained by the QTLEBV was higher than the QTL-phenotype. Additionally, several QTL were detected across several ages, which may make them suitable as candidates for early selection. Genomic selection (GS) could aid to reduce the breeding cycle by shortening the periods of progeny field testing, and consequently increasing genetic gains per year. Genomic predictions, including additive and non-additive effects through different prediction models were compared with traditional pedigree-based models; it was seen an overestimation of genetic parameters for pedigree-based models, even larger when nonadditive effects could not be discerned from additive and residual effects. Prediction accuracies and abilities of the genomic models were sufficient to achieve higher selection efficiencies and responses per year varying between 50-90% by shortening 50% the breeding cycle. For the selection of the top 50 individuals, higher gains were estimated if non-additive effects are incorporated to the models (7 – 117%).

Authors/Creators:Calleja-Rodriguez, Ainhoa
Title:Quantitative genetics and genomic selection of Scots pine
Series/Journal:Acta Universitatis agriculturae Sueciae (1652-6880)
Year of publishing :2019
Depositing date:29 April 2019
Volume:2019:36
Number:2019:36
Number of Pages:67
Papers/manuscripts:
NumberReferences
IAinhoa Calleja-Rodriguez*, Bengt Andersson Gull, Harry X. Wu, Tim J. Mullin, and Torgny Persson (2019). Genotype-by-environmental interactions and the dynamic relationship between tree vitality and height in Northern Pinus sylvestris. Tree Genetics & Genomes. doi: 10.1007/s11295-019-1343-8 (in press).
IIAinhoa Calleja-Rodriguez, Zitong Li, Henrik R. Hallingbäck, Mikko J. Sillanpää, Harry X. Wu, Sara Abrahamsson, and Maria Rosario García-Gil* (2019). Analysis of phenotypic- and Estimated Breeding Values (EBV) to dissect the genetic architecture of complex traits in a Scots pine three-generation pedigree design. Journal of Theoretical Biology, 462, pp. 283-292.
IIIAinhoa Calleja-Rodriguez, Jin Pan, Tomas Funda, Zhi-Qiang Chen, John Baison, Fikret Isik, Sara Abrahamsson, and Harry X. Wu* (2019). Genomic prediction accuracies and abilities for growth and wood quality traits of Scots pine, using genotyping-by-sequencing (GBS) data (submitted to G3: Genes, Genomes, Genetics).
IVAinhoa Calleja-Rodriguez, Zhi-Qiang Chen, Mari Suontama, Jin Pan and Harry X. Wu* (2019). Including non-additive genetic effects in genomic prediction of growth and wood quality traits in Pinus sylvestris. (Manuscript)
Place of Publication:Umeå
Publisher:Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences
ISBN for printed version:978-91-7760-390-0
ISBN for electronic version:978-91-7760-391-7
ISSN:1652-6880
Language:English
Publication Type:Doctoral thesis
Article category:Other scientific
Full Text Status:Public
Agris subject categories.:F Plant production > F30 Plant genetics and breeding
K Forestry > K10 Forestry production
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 404 Agricultural Biotechnology > Genetics and Breeding
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 404 Agricultural Biotechnology > Plant Biotechnology
Keywords:Scots pine, genotype-by-environment, multiple variables, factor analysis, quantitative trait locus, genomic predictions, non-additive effects, Bayesian LASSO, Bayesian ridge regression, GBLUP
URN:NBN:urn:nbn:se:slu:epsilon-p-99801
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-99801
ID Code:16094
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Genetics and Plant Physiology
Deposited By: SLUpub Connector
Deposited On:29 Apr 2019 13:50
Metadata Last Modified:30 Apr 2019 06:17

Repository Staff Only: item control page

Downloads

Downloads per year (since September 2012)

View more statistics

Downloads
Hits