Jaroslav Klápště

Geographical and environmental gradients shape phenotypic trait variation and genetic structure in Populus trichocarpa

• Populus 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. H(2) ranged from 0.3 to 0.9 in phenology, 0.3 to 0.8 in biomass and 0.1 to 0.8 in ecophysiology traits. Most traits correlated strongly with latitude, maximum daylength and temperature of tree origin, but not necessarily with elevation, precipitation or heat : moisture indices. Trait H(2) 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.

Genome‐wide association implicates numerous genes underlying ecological trait variation in natural populations of Populus trichocarpa

In 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<1.7×10(-6)). 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.

A 34K SNP genotyping array for Populus trichocarpa: design, application to the study of natural populations and transferability to other Populus species.

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.

Populus trichocarpa cell wall chemistry and ultrastructure trait variation, genetic control and genetic correlations

The 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 Hardy-Weinberg 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.

Breeding without breeding: is a complete pedigree necessary for efficient breeding?

Complete pedigree information is a prerequisite for modern breeding and the ranking of parents and offspring for selection and deployment decisions. DNA fingerprinting and pedigree reconstruction can substitute for artificial matings, by allowing parentage delineation of naturally produced offspring. Here, we report on the efficacy of a breeding concept called “Breeding without Breeding” (BwB) that circumvents artificial matings, focusing instead on a subset of randomly sampled, maternally known but paternally unknown offspring to delineate their paternal parentage. We then generate the information needed to rank those offspring and their paternal parents, using a combination of complete (full-sib: FS) and incomplete (half-sib: HS) analyses of the constructed pedigrees. Using a random sample of wind-pollinated offspring from 15 females (seed donors), growing in a 41-parent western larch population, BwB is evaluated and compared to two commonly used testing methods that rely on either incomplete (maternal half-sib, open-pollinated: OP) or complete (FS) pedigree designs. BwB produced results superior to those from the incomplete design and virtually identical to those from the complete pedigree methods. The combined use of complete and incomplete pedigree information permitted evaluating all parents, both maternal and paternal, as well as all offspring, a result that could not have been accomplished with either the OP or FS methods alone. We also discuss the optimum experimental setting, in terms of the proportion of fingerprinted offspring, the size of the assembled maternal and paternal half-sib families, the role of external gene flow, and selfing, as well as the number of parents that could be realistically tested with BwB.

Association genetics, geography and ecophysiology link stomatal patterning in Populus trichocarpa with carbon gain and disease resistance trade-offs

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 (H2) 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. H2 values for stomatal traits were moderate (average H2 = 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.

Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing

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.

Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions

High-throughput approaches have been widely applied to elucidate the genetic underpinnings of industrially important wood properties. Wood traits are polygenic in nature, but gene hierarchies can be assessed to identify the most important gene variants controlling specific traits within complex networks defining the overall wood phenotype. We tested a large set of genetic, genomic, and phenotypic information in an integrative approach to predict wood properties in Populus trichocarpa. Nine-yr-old natural P. trichocarpa trees including accessions with high contrasts in six traits related to wood chemistry and ultrastructure were profiled for gene expression on 49k Nimblegen (Roche NimbleGen Inc., Madison, WI, USA) array elements and for 28,831 polymorphic single nucleotide polymorphisms (SNPs). Pre-selected transcripts and SNPs with high statistical dependence on phenotypic traits were used in Bayesian network learning procedures with a stepwise K2 algorithm to infer phenotype-centric networks. Transcripts were pre-selected at a much lower logarithm of Bayes factor (logBF) threshold than SNPs and were not accommodated in the networks. Using persistent variables, we constructed cross-validated networks for variability in wood attributes, which contained four to six variables with 94-100% predictive accuracy. Accommodated gene variants revealed the hierarchy in the genetic architecture that underpins substantial phenotypic variability, and represent new tools to support the maximization of response to selection.

Pollination dynamics in a Douglas-fir seed orchard as revealed by pedigree reconstruction

Abstract• Pollination dynamics was studied in a Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) seed orchard using 8 nuclear microsatellite markers and pedigree reconstruction.• The seed orchard consisted of 49 parents (clones). Cone-crop management included bloom delay and supplemental mass pollination (SMP) using 12 internal and 4 external pollen donors.• A random sample of 801 bulk seeds was genotyped for both haploid megagametophyte and corresponding diploid embryo.• Using the parental population’s multilocus genotypes, full pedigree reconstruction generated all the information needed to estimate the maternal, paternal, and parental reproductive success, selfing, pollen contamination, and pollination success of the 4 external pollen donors.• Maternal, paternal, and parental reproductive success varied with 80% of gametes being produced by 23, 45, and 37% of the orchard’s parents, respectively, resulting in a drastically reduced effective population size as compared to the census number (14 vs. 53).• Selfing, pollen contamination, and aggregate SMP success (internal and external) were estimated to be 15.2, 10.4, and 15.0%, respectively.• Full pedigree reconstruction was effective in unraveling the orchard’s pollination dynamics and both female and male reproductive success.

A comparison of genomic selection models across time in interior spruce ( Picea engelmannii × glauca ) using unordered SNP imputation methods

Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3–40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31–0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04–0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.