Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program

Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.Instituto de Recursos BiológicosFil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: Cappa, Eduardo Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Klutsch, Jenifer G. University of Alberta; Department of Renewable Resources; CanadaFil: Sebastian-Azcona, Jaime. University of Alberta; Department of Renewable Resources; CanadaFil: Ratchiffe, Blaise. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; CanadáFil: Xiaojing, Wei. University of Alberta; Department of Renewable Resources; CanadaFil: Da Ros, Letitia. University of British Columbia. Faculty of Forestry. Department of Wood Science; CanadáFil: Yang, Liu. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; CanadáFil: Chen, Charles. Oklahoma State University. Department of Biochemistry and Molecular Biology; Estados UnidosFil: Benowicz, Andy. Alberta Agriculture and Forestry. Forest Stewardship and Trade Branch; CanadáFil: Sadoway, Shane. Blue Ridge Lumber Inc.; CanadáFil: Mansfield, Shawn D. University of British Columbia. Faculty of Forestry. Department of Wood Science; CanadáFil: Erbilgin, Nadir. University of Alberta; Department of Renewable Resources; CanadaFil: Thomas, Barb R. University of Alberta; Department of Renewable Resources; CanadaFil: El-Kassaby, Yousry A. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; Canad

Intraspecific Variation in Pinus Pinaster PSII Photochemical Efficiency in Response to Winter Stress and Freezing Temperatures

As part of a program to select maritime pine (Pinus pinaster Ait.) genotypes for resistance to low winter temperatures, we examined variation in photosystem II activity by chlorophyll fluorescence. Populations and families within populations from contrasting climates were tested during two consecutive winters through two progeny trials, one located at a continental and xeric site and one at a mesic site with Atlantic influence. We also obtained the LT50, or the temperature that causes 50% damage, by controlled freezing and the subsequent analysis of chlorophyll fluorescence in needles and stems that were collected from populations at the continental trial site

Multiple-trait analyses improved the accuracy of genomic prediction and the power of genome-wide association of productivity and climate change-adaptive traits in lodgepole pine

Abstract Background Genomic prediction (GP) and genome-wide association (GWA) analyses are currently being employed to accelerate breeding cycles and to identify alleles or genomic regions of complex traits in forest trees species. Here, 1490 interior lodgepole pine (Pinus contorta Dougl. ex. Loud. var. latifolia Engelm) trees from four open-pollinated progeny trials were genotyped with 25,099 SNPs, and phenotyped for 15 growth, wood quality, pest resistance, drought tolerance, and defense chemical (monoterpenes) traits. The main objectives of this study were to: (1) identify genetic markers associated with these traits and determine their genetic architecture, and to compare the marker detected by single- (ST) and multiple-trait (MT) GWA models; (2) evaluate and compare the accuracy and control of bias of the genomic predictions for these traits underlying different ST and MT parametric and non-parametric GP methods. GWA, ST and MT analyses were compared using a linear transformation of genomic breeding values from the respective genomic best linear unbiased prediction (GBLUP) model. GP, ST and MT parametric and non-parametric (Reproducing Kernel Hilbert Spaces, RKHS) models were compared in terms of prediction accuracy (PA) and control of bias. Results MT-GWA analyses identified more significant associations than ST. Some SNPs showed potential pleiotropic effects. Averaging across traits, PA from the studied ST-GP models did not differ significantly from each other, with generally a slight superiority of the RKHS method. MT-GP models showed significantly higher PA (and lower bias) than the ST models, being generally the PA (bias) of the RKHS approach significantly higher (lower) than the GBLUP. Conclusions The power of GWA and the accuracy of GP were improved when MT models were used in this lodgepole pine population. Given the number of GP and GWA models fitted and the traits assessed across four progeny trials, this work has produced the most comprehensive empirical genomic study across any lodgepole pine population to date.Forestry, Faculty ofNon UBCForest and Conservation Sciences, Department ofWood Science, Department ofReviewedFacultyResearcherOthe

Genotypic variation in traits linked to climate and aboveground productivity in a widespread C4 grass:Evidence for a functional trait syndrome

Examining intraspecific variation in growth and function in relation to climate may provide insight into physiological evolution and adaptation, and is important for predicting species responses to climate change. Under common garden conditions, we grew nine genotypes of the C4 species Panicum virgatum originating from different temperature and precipitation environments. We hypothesized that genotype productivity, morphology and physiological traits would be correlated with climate of origin, and a suite of adaptive traits would show high broad-sense heritability (H2). Genotype productivity and flowering time increased and decreased, respectively, with home-climate temperature, and home-climate temperature was correlated with genotypic differences in a syndrome of morphological and physiological traits. Genotype leaf and tiller size, leaf lamina thickness, leaf mass per area (LMA) and C : N ratios increased with home-climate temperature, whereas leaf nitrogen per unit mass (Nm) and chlorophyll (Chl) decreased with home-climate temperature. Trait variation was largely explained by genotypic differences (H2 = 0.33-0.85). Our results provide new insight into the role of climate in driving functional trait coordination, local adaptation and genetic divergence within species. These results emphasize the importance of considering intraspecific variation in future climate change scenarios