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

Abstract

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.

Genomic evaluation for breeding and genetic management in Cordia africana, a multipurpose tropical tree species

“…In our study, the ssGBLUP models showed a constant increase in additive variance estimates compared to the ABLUP models at all sites, except for the “without inbreeding” scenario at the ILRI site. This is in line with results reported for growth traits in other tree species, for example, Eucalyptus [ 47 , 48 ] , lodgepole pine [ 38 ], white spruce [ 49 ], and loblolly pine [ 50 ]. However, studies on other tree species have reported that models using genomic evaluation (GBLUP or ssGBLUP) show decreased or similar additive variance estimates compared to models using pedigree-based information only for growth and wood quality traits [ 51 – 53 ].…”

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

“…Wood density (WD) from 5 mm increment cores was measured at approximately breast height. See details on core sampling, transportation and analyses in Cappa et al [ 7 ]. Wood density data represents the relative density on an oven-dry weight basis.…”

“…Wood density data represents the relative density on an oven-dry weight basis. Average WD was calculated as the weighted WD of individual tree rings weighted by their ring width, to better represent the density of the whole tree [ 7 ]. Microfibril angle (MFA) was determined by X-ray diffraction on the radial face of the individual growth rings (see Ukrainetz et al [ 73 ] for details).…”

“…The two residual outside slabs of the increment core, retained after the pneumatic processing of the specimens for WD, were used to capture stable carbon isotope ratio (δ 13 C) variation across the lifespan of the tree. A detailed description of how these slabs were processed and analyzed can be found in Cappa et al [ 7 ]. δ 13 C values were normalized and reported relative to the Vienna Pee Dee Belemnite.…”

“…Thus, assessing climate change-related adaptive traits such as drought tolerance and pest and disease resistance and associated secondary (defense) chemical compounds is critical to their incorporation in ongoing breeding activities for improving productivity. While productivity-related traits have been the traditional focus of quantitative genetic analyses of several tree species (including conifer species), some recent progress has been directed towards the selection of climate change-related adaptive traits [ 7 ].…”