Dissertation

Integration of Genomics and Classical Quantitative Genetics in the Improvement of Growth Traits and Disease Resistance in Pinus Taeda L

Lauer, Edwin Gaston

2021

Overview

Conifer breeding is one of the purest applications of quantitative genetics, since there are few qualitative traits distinguishable to the human eye. From the standpoint of a casual observer, a conifer progeny test appears as a homogeneous forest planted at regularly spaced intervals. The subtlety of trait variation and the environmental plasticity of tree growth requires consistent recording of phenotypic measurements across multiple environments. Optimal selection decisions can only be made after quantitative genetic analysis, either through traditional pedigree-based linear mixed models (ABLUP) or through genome-wide regression models (GBLUP). The first chapter is an overview of quantitative genetic methods in conifer improvement, with a focus on the application of genomic markers for reducing the breeding cycle.Second, a multi-environmental trial was analyzed using ABLUP for the purpose of estimating genetic parameters and understanding patterns of genotype-by-environment (GxE) interaction. The trial consisted of 324 maternal half-sib families planted in five test series across 37 locations in the southeast United States. Tree height and diameter were analyzed using multiple variance/covariance matrices for the GxE effect. Models were compared on the basis of model fit. Heritability of family means ranged between 0.63 and 0.90 for both height and diameter. Average additive genetic correlations among sites were 0.70 and 0.61 for height and diameter, respectively, suggesting the presence of some genotype by environment interaction. Pairs of sites with the lowest additive genetic correlations were located at opposite ends of the latitude range.Third, a trait dissection study was conducted to understand the genetic architecture of disease resistance to fusiform rust. Two full-sib families, each with 1000 progeny, were challenged with a complex inoculum consisting of 150 pathogen isolates of Cronartium quercuum f. sp. fusiforme. High-density linkage mapping revealed three major-effect QTL distributed on two linkage groups. All three QTL were validated using a population of 2057 cloned pine genotypes in a six-year-old multi-environmental field trial. As a complement to the QTL mapping approach, bulked segregant RNAseq analysis revealed a small number of candidate genes harboring SNP significantly associated with disease resistance. The results of this study showed for the first time that in P. taeda, a small number of major QTL can provide effective resistance against genetically diverse mixtures of an endemic pathogen. These QTL vary in their impact on disease liability and exhibit additivity in combination.The final chapter is a study of genomic prediction using a clonally propagated training population. In this study, a clonally replicated population (n=2063) was used to train a genomic prediction model. The model was validated both within the training population and in a separate population (n=451). The prediction abilities from random (20% vs 80%) cross validation within the training population were 0.56 and 0.78 for height and stem form, respectively. Removal of all full-sib relatives within the training population resulted in ~50% reduction in their genomic prediction ability for both traits. The average prediction ability for all 451 individual trees was 0.29 for height and 0.57 for stem form. The degree of genetic similarity(full sib family, half sib family, unrelated) between the training and validation sets had a strong impact on prediction ability for stem form but not for height.

• Publisher: ProQuest Dissertations & Theses
• Subject: Cloning / Forestry / Genes / Genetics / Genomes / Genomics / Genotype & phenotype / Haplotypes / Phylogenetics / Plantations / Quantitative genetics / Timber / Trees / Wood sciences
• ISBN: 9798759926665