Breeding for improved growth, wood quality, and chemistry for southern pines by combining quantitative genetics and association mapping

In the economically important southern pine species, loblolly and slash, the genetic architecture of wood chemistry and stiffness were determined and association genetics was used to identify genes that potentially regulate these economically important traits in loblolly pine.;The in-tree stiffness of juvenile corewood in a progeny trial of 139 families of slash pine Pinus elliottii had moderate level of genetic control with a heritability (h2=0.42) which is generally higher than growth traits, i.e., height and diameter at breast height. No significant genetic correlations were observed between velocity stiffness, DBH and volume growth.;Wood chemistry in the juvenile corewood of a clonally propagated progeny trial of 61 families of loblolly pine Pinus taeda was measured by pyrolysis molecular beam mass spectrometry (pyMBMS). Genetic analysis of all 421 peaks in the spectra identified 32 with significant genetic control. Of these peaks, about half are chemically identified. The chemically identified mass to charge peaks alone or summed together for five and six carbon sugars, lignin and C20 extractives all had low levels of genetic control with a clonal repeatabilities of 0.11--0.16, which are lower than growth traits (height and DBH). Pairwise genetic correlations between peaks showed that known lignin and sugar peak intensities are strongly negatively, genetically correlated; while known carbohydrate and lignin peaks are strongly positively, genetically correlated with others from the same class. In addition, 9 chemically unidentified peaks are strongly correlated with other chemically identified peaks, suggesting the possible chemical class of these peaks. Principal component and wavelet analyses of the spectra show that the genetic variation is better segmented by wavelet than by principal components. Finally, a Metropolis Hastings algorithm was developed and used to search for combinations of 2, 3, 4 and 5 peaks that maximized the heritability. This search algorithm successfully identified many combinations of known peaks within the same class, and also identified combinations of unknown with chemically identified peaks, supporting pairwise genetic correlations.;The performance of a new Bayesian association method that uses a Gibbs sampler to impute missing data (BAMD) was tested using simulated data for structured and unstructured populations and real data from a structured population to identify SNPs known to significantly affect phenotypes that have varying degrees of genetic control.;Association genetic analyses were completed with BAMD to identify significant SNPs for wood property phenotypes. From a set of 2182 genotyped SNPs in a richly structured clonally propagated CCLONES population, 87 significant SNPs were identified for wood chemistry and in-tree velocity stiffness. In-tree wood velocity stiffness is a moderately heritable trait, and 6 SNPs were significant at the 95% level, but an additional 9 were identified at the 90% level.