SummaryPopulus trichocarpa is widespread across western North America spanning extensive variation in photoperiod, growing season and climate. We investigated trait variation in P. trichocarpa using over 2000 trees from a common garden at Vancouver, Canada, representing replicate plantings of 461 genotypes originating from 136 provenance localities.We measured 40 traits encompassing phenological events, biomass accumulation, growth rates, and leaf, isotope and gas exchange-based ecophysiology traits. With replicated plantings and 29 354 single nucleotide polymorphisms (SNPs) from 3518 genes, we estimated both broad-sense trait heritability (H 2 ) and overall population genetic structure from principal component analysis.Populus trichocarpa had high phenotypic variation and moderate/high H 2 for many traits. values reflected trait correlation strength with geoclimate variables. The population genetic structure had one significant principal component (PC1) which correlated with daylength and showed enrichment for genes relating to circadian rhythm and photoperiod. Robust relationships between traits, population structure and geoclimate in P. trichocarpa reflect patterns which suggest that range-wide geographical and environment gradients have shaped its genotypic and phenotypic variability.

SummaryIn order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS).We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29 355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions.We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P < 1.7 9 10 À6). Markers were found across 19 chromosomes, explained 1-13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes).The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.

SummaryEstablishing links between phenotypes and molecular variants is of central importance to accelerate genetic improvement of economically important plant species. Our work represents the first genome-wide association study to the inherently complex and currently poorly understood genetic architecture of industrially relevant wood traits.Here, we employed an Illumina Infinium 34K single nucleotide polymorphism (SNP) genotyping array that generated 29 233 high-quality SNPs in c. 3500 broad-based candidate genes within a population of 334 unrelated Populus trichocarpa individuals to establish genomewide associations.The analysis revealed 141 significant SNPs (a ≤ 0.05) associated with 16 wood chemistry/ ultrastructure traits, individually explaining 3-7% of the phenotypic variance. A large set of associations (41% of all hits) occurred in candidate genes preselected for their suggested a priori involvement with secondary growth. For example, an allelic variant in the FRA8 ortholog explained 21% of the total genetic variance in fiber length, when the trait's heritability estimate was considered. The remaining associations identified SNPs in genes not previously implicated in wood or secondary wall formation.Our findings provide unique insights into wood trait architecture and support efforts for population improvement based on desirable allelic variants.

Stomata are essential for diffusive entry of gases to support photosynthesis, but may also expose internal leaf tissues to pathogens. To uncover trade-offs in range-wide adaptation relating to stomata, we investigated the underlying genetics of stomatal traits and linked variability in these traits with geoclimate, ecophysiology, condensed foliar tannins and pathogen susceptibility in black cottonwood (Populus trichocarpa). Upper (adaxial) and lower (abaxial) leaf stomatal traits were measured from 454 accessions collected throughout much of the species range. We calculated broad-sense heritability (H(2) ) of stomatal traits and, using SNP data from a 34K Populus SNP array, performed a genome-wide association studies (GWAS) to uncover genes underlying stomatal trait variation. H(2) values for stomatal traits were moderate (average H(2) = 0.33). GWAS identified genes associated primarily with adaxial stomata, including polarity genes (PHABULOSA), stomatal development genes (BRASSINOSTEROID-INSENSITIVE 2) and disease/wound-response genes (GLUTAMATE-CYSTEINE LIGASE). Stomatal traits correlated with latitude, gas exchange, condensed tannins and leaf rust (Melampsora) infection. Latitudinal trends of greater adaxial stomata numbers and guard cell pore size corresponded with higher stomatal conductance (gs ) and photosynthesis (Amax ), faster shoot elongation, lower foliar tannins and greater Melampsora susceptibility. This suggests an evolutionary trade-off related to differing selection pressures across the species range. In northern environments, more adaxial stomata and larger pore sizes reflect selection for rapid carbon gain and growth. By contrast, southern genotypes have fewer adaxial stomata, smaller pore sizes and higher levels of condensed tannins, possibly linked to greater pressure from natural leaf pathogens, which are less significant in northern ecosystems.

Genetic mapping of quantitative traits requires genotypic data for large numbers of markers in many individuals. For such studies, the use of large single nucleotide polymorphism (SNP) genotyping arrays still offers the most cost-effective solution. Herein we report on the design and performance of a SNP genotyping array for Populus trichocarpa (black cottonwood). This genotyping array was designed with SNPs pre-ascertained in 34 wild accessions covering most of the species latitudinal range. We adopted a candidate gene approach to the array design that resulted in the selection of 34 131 SNPs, the majority of which are located in, or within 2 kb of, 3543 candidate genes. A subset of the SNPs on the array (539) was selected based on patterns of variation among the SNP discovery accessions. We show that more than 95% of the loci produce high quality genotypes and that the genotyping error rate for these is likely below 2%. We demonstrate that even among small numbers of samples (n = 10) from local populations over 84% of loci are polymorphic. We also tested the applicability of the array to other species in the genus and found that the number of polymorphic loci decreases rapidly with genetic distance, with the largest numbers detected in other species in section Tacamahaca. Finally, we provide evidence for the utility of the array to address evolutionary questions such as intraspecific studies of genetic differentiation, species assignment and the detection of natural hybrids.

SummaryThe increasing ecological and economical importance of Populus species and hybrids has stimulated research into the investigation of the natural variation of the species and the estimation of the extent of genetic control over its wood quality traits for traditional forestry activities as well as the emerging bioenergy sector. A realized kinship matrix based on informative, high-density, biallelic single nucleotide polymorphism (SNP) genetic markers was constructed to estimate trait variance components, heritabilities, and genetic and phenotypic correlations.Seventeen traits related to wood chemistry and ultrastructure were examined in 334 9-yr-old Populus trichocarpa grown in a common-garden plot representing populations spanning the latitudinal range 44°to 58.6°. In these individuals, 9342 SNPs that conformed to HardyWeinberg expectations were employed to assess the genomic pair-wise kinship to estimate narrow-sense heritabilities and genetic correlations among traits.The range-wide phenotypic variation in all traits was substantial and several trait heritabilities were > 0.6. In total, 61 significant genetic and phenotypic correlations and a network of highly interrelated traits were identified.The high trait variation, the evidence for moderate to high heritabilities and the identification of advantageous trait combinations of industrially important characteristics should aid in providing the foundation for the enhancement of poplar tree breeding strategies for modern industrial use.

BackgroundQTL cloning for the discovery of genes underlying polygenic traits has historically been cumbersome in long-lived perennial plants like Populus. Linkage disequilibrium-based association mapping has been proposed as a cloning tool, and recent advances in high-throughput genotyping and whole-genome resequencing enable marker saturation to levels sufficient for association mapping with no a priori candidate gene selection. Here, multiyear and multienvironment evaluation of cell wall phenotypes was conducted in an interspecific P. trichocarpa x P. deltoides pseudo-backcross mapping pedigree and two partially overlapping populations of unrelated P. trichocarpa genotypes using pyrolysis molecular beam mass spectrometry, saccharification, and/ or traditional wet chemistry. QTL mapping was conducted using a high-density genetic map with 3,568 SNP markers. As a fine-mapping approach, chromosome-wide association mapping targeting a QTL hot-spot on linkage group XIV was performed in the two P. trichocarpa populations. Both populations were genotyped using the 34 K Populus Infinium SNP array and whole-genome resequencing of one of the populations facilitated marker-saturation of candidate intervals for gene identification.ResultsFive QTLs ranging in size from 0.6 to 1.8 Mb were mapped on linkage group XIV for lignin content, syringyl to guaiacyl (S/G) ratio, 5- and 6-carbon sugars using the mapping pedigree. Six candidate loci exhibiting significant associations with phenotypes were identified within QTL intervals. These associations were reproducible across multiple environments, two independent genotyping platforms, and different plant growth stages. cDNA sequencing for allelic variants of three of the six loci identified polymorphisms leading to variable length poly glutamine (PolyQ) stretch in a transcription factor annotated as an ANGUSTIFOLIA C-terminus Binding Protein (CtBP) and premature stop codons in a KANADI transcription factor as well as a protein kinase. Results from protoplast transient expression assays suggested that each of the polymorphisms conferred allelic differences in the activation of cellulose, hemicelluloses, and lignin pathway marker genes.ConclusionThis study illustrates the utility of complementary QTL and association mapping as tools for gene discovery with no a priori candidate gene selection. This proof of concept in a perennial organism opens up opportunities for discovery of novel genetic determinants of economically important but complex traits in plants.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1215-z) contains supplementary material, which is available to authorized users.

BackgroundGenomic selection (GS) in forestry can substantially reduce the length of breeding cycle and increase gain per unit time through early selection and greater selection intensity, particularly for traits of low heritability and late expression. Affordable next-generation sequencing technologies made it possible to genotype large numbers of trees at a reasonable cost.ResultsGenotyping-by-sequencing was used to genotype 1,126 Interior spruce trees representing 25 open-pollinated families planted over three sites in British Columbia, Canada. Four imputation algorithms were compared (mean value (MI), singular value decomposition (SVD), expectation maximization (EM), and a newly derived, family-based k-nearest neighbor (kNN-Fam)). Trees were phenotyped for several yield and wood attributes. Single- and multi-site GS prediction models were developed using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) and the Generalized Ridge Regression (GRR) to test different assumption about trait architecture. Finally, using PCA, multi-trait GS prediction models were developed. The EM and kNN-Fam imputation methods were superior for 30 and 60% missing data, respectively. The RR-BLUP GS prediction model produced better accuracies than the GRR indicating that the genetic architecture for these traits is complex. GS prediction accuracies for multi-site were high and better than those of single-sites while multi-site predictability produced the lowest accuracies reflecting type-b genetic correlations and deemed unreliable. The incorporation of genomic information in quantitative genetics analyses produced more realistic heritability estimates as half-sib pedigree tended to inflate the additive genetic variance and subsequently both heritability and gain estimates. Principle component scores as representatives of multi-trait GS prediction models produced surprising results where negatively correlated traits could be concurrently selected for using PCA2 and PCA3.ConclusionsThe application of GS to open-pollinated family testing, the simplest form of tree improvement evaluation methods, was proven to be effective. Prediction accuracies obtained for all traits greatly support the integration of GS in tree breeding. While the within-site GS prediction accuracies were high, the results clearly indicate that single-site GS models ability to predict other sites are unreliable supporting the utilization of multi-site approach. Principle component scores provided an opportunity for the concurrent selection of traits with different phenotypic optima.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1597-y) contains supplementary material, which is available to authorized users.