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Genomic selection can increase genetic gain per generation through early selection. Genomic selection is expected to be particularly valuable for traits that are costly to phenotype and expressed late in the life cycle of long-lived species. Alternative approaches to genomic selection prediction models may perform differently for traits with distinct genetic properties. Here the performance of four different original methods of genomic selection that differ with respect to assumptions regarding distribution of marker effects, including (i) ridge regression–best linear unbiased prediction (RR–BLUP), (ii) Bayes A, (iii) Bayes Cπ, and (iv) Bayesian LASSO are presented. In addition, a modified RR–BLUP (RR–BLUP B) that utilizes a selected subset of markers was evaluated. The accuracy of these methods was compared across 17 traits with distinct heritabilities and genetic architectures, including growth, development, and disease-resistance properties, measured in a Pinus taeda (loblolly pine) training population of 951 individuals genotyped with 4853 SNPs. The predictive ability of the methods was evaluated using a 10-fold, cross-validation approach, and differed only marginally for most method/trait combinations. Interestingly, for fusiform rust disease-resistance traits, Bayes Cπ, Bayes A, and RR–BLUB B had higher predictive ability than RR–BLUP and Bayesian LASSO. Fusiform rust is controlled by few genes of large effect. A limitation of RR–BLUP is the assumption of equal contribution of all markers to the observed variation. However, RR-BLUP B performed equally well as the Bayesian approaches.The genotypic and phenotypic data used in this study are publically available for comparative analysis of genomic selection prediction models.

Conifers are the predominant gymnosperm. The size and complexity of their genomes has presented formidable technical challenges for whole-genome shotgun sequencing and assembly. We employed novel strategies that allowed us to determine the loblolly pine (Pinus taeda) reference genome sequence, the largest genome assembled to date. Most of the sequence data were derived from whole-genome shotgun sequencing of a single megagametophyte, the haploid tissue of a single pine seed. Although that constrained the quantity of available DNA, the resulting haploid sequence data were well-suited for assembly. The haploid sequence was augmented with multiple linking long-fragment mate pair libraries from the parental diploid DNA. For the longest fragments, we used novel fosmid DiTag libraries. Sequences from the linking libraries that did not match the megagametophyte were identified and removed. Assembly of the sequence data were aided by condensing the enormous number of paired-end reads into a much smaller set of longer “super-reads,” rendering subsequent assembly with an overlap-based assembly algorithm computationally feasible. To further improve the contiguity and biological utility of the genome sequence, additional scaffolding methods utilizing independent genome and transcriptome assemblies were implemented. The combination of these strategies resulted in a draft genome sequence of 20.15 billion bases, with an N50 scaffold size of 66.9 kbp.

Here, we investigated the effect of different heat-wave intensities applied at two atmospheric CO2 concentrations ([CO2]) on seedlings of two tree species, loblolly pine (Pinus taeda) and northern red oak (Quercus rubra). Seedlings were assigned to treatment combinations of two levels of [CO2] (380 or 700 μmol mol−1) and four levels of air temperature (ambient, ambient +3°C, or 7-d heat waves consisting of a biweekly +6°C heat wave, or a monthly +12°C heat wave). Treatments were maintained throughout the growing season, thus receiving equal heat sums. We measured gas exchange and fluorescence parameters before, during and after a mid-summer heat wave. The +12°C heat wave, significantly reduced net photosynthesis (Anet) in both species and [CO2] treatments but this effect was diminished in elevated [CO2]. The decrease in Anet was accompanied by a decrease in F v′/F m′ in P. taeda and ΦPSII in Q. rubra. Our findings suggest that, if soil moisture is adequate, trees will experience negative effects in photosynthetic performance only with the occurrence of extreme heat waves. As elevated [CO2] diminished these negative effects, the future climate may not be as detrimental to plant communities as previously assumed.

• Dissecting the genetic and genomic architecture of complex traits is essential to understand the forces maintaining the variation in phenotypic traits of ecological and economical importance. • Whole-genome resequencing data were used to generate high-resolution polymorphic single nucleotide polymorphism (SNP) markers and genotype individuals from common gardens across the loblolly pine (Pinus taeda) natural range. Genome-wide associations were tested with a large phenotypic dataset comprising 409 variables including morphological traits (height, diameter, carbon isotope discrimination, pitch canker resistance), and molecular traits such as metabolites and expression of xylem development genes. • Our study identified 2335 new SNP × trait associations for the species, with many SNPs located in physical clusters in the genome of the species; and the genomic location of hotspots for metabolic × genotype associations. • We found a highly polygenic basis of quantitative inheritance, with significant differences in number, effects size, genomic location and frequency of alleles contributing to variation in phenotypes in the different traits. While mutation-selection balance might be shaping the genetic variation in metabolic traits, balancing selection is more likely to shape the variation in expression of xylem development genes. Our work contributes to the study of complex traits in nonmodel plant species by identifying associations at a whole-genome level.

Genetically improving constitutive resin canal development in Pinus stems may enhance the capacity to synthesize terpenes for bark beetle resistance, chemical feedstocks, and biofuels. To discover genes that potentially regulate axial resin canal number (RCN), single nucleotide polymorphisms (SNPs) in 4027 genes were tested for association with RCN in two growth rings and three environments in a complex pedigree of 520 Pinus taeda individuals (CCLONES). The map locations of associated genes were compared with RCN quantitative trait loci (QTLs) in a (P. taeda × Pinus elliottii) × P. elliottii pseudo‐backcross of 345 full‐sibs (BC1). Resin canal number was heritable (h² ˜ 0.12–0.21) and positively genetically correlated with xylem growth (rg ˜ 0.32–0.72) and oleoresin flow (rg ˜ 0.15–0.51). Sixteen well‐supported candidate regulators of RCN were discovered in CCLONES, including genes associated across sites and ages, unidirectionally associated with oleoresin flow and xylem growth, and mapped to RCN QTLs in BC1. Breeding is predicted to increase RCN 11% in one generation and could be accelerated with genomic selection at accuracies of 0.45–0.52 across environments. There is significant genetic variation for RCN in loblolly pine, which can be exploited in breeding for elevated terpene content.

The application of quantitative genetics in plant and animal breeding has largely focused on additive models, which may also capture dominance and epistatic effects. Partitioning genetic variance into its additive and nonadditive components using pedigree-based models (P-genomic best linear unbiased predictor) (P-BLUP) is difficult with most commonly available family structures. However, the availability of dense panels of molecular markers makes possible the use of additive- and dominance-realized genomic relationships for the estimation of variance components and the prediction of genetic values (G-BLUP). We evaluated height data from a multifamily population of the tree species Pinus taeda with a systematic series of models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance), using either pedigree- or marker-based information. We show that, compared with the pedigree, use of realized genomic relationships in marker-based models yields a substantially more precise separation of additive and nonadditive components of genetic variance. We conclude that the marker-based relationship matrices in a model including additive and nonadditive effects performed better, improving breeding value prediction. Moreover, our results suggest that, for tree height in this population, the additive and nonadditive components of genetic variance are similar in magnitude. This novel result improves our current understanding of the genetic control and architecture of a quantitative trait and should be considered when developing breeding strategies.

The largest genus in the conifer family Pinaceae is Pinus, with over 100 species. The size and complexity of their genomes (∼20–40 Gb, 2n = 24) have delayed the arrival of a well-annotated reference sequence. In this study, we present the annotation of the first whole-genome shotgun assembly of loblolly pine (Pinus taeda L.), which comprises 20.1 Gb of sequence. The MAKER-P annotation pipeline combined evidence-based alignments and ab initio predictions to generate 50,172 gene models, of which 15,653 are classified as high confidence. Clustering these gene models with 13 other plant species resulted in 20,646 gene families, of which 1554 are predicted to be unique to conifers. Among the conifer gene families, 159 are composed exclusively of loblolly pine members. The gene models for loblolly pine have the highest median and mean intron lengths of 24 fully sequenced plant genomes. Conifer genomes are full of repetitive DNA, with the most significant contributions from long-terminal-repeat retrotransposons. In depth analysis of the tandem and interspersed repetitive content yielded a combined estimate of 82%.

Summary Extramatrical mycelia (EMM) of ectomycorrhizal fungi are important in carbon (C) and nitrogen (N) cycling in forests, but poor knowledge about EMM biomass and necromass turnovers makes the quantification of their role problematic. We studied the impacts of elevated CO2 and N fertilization on EMM production and turnover in a Pinus taeda forest. EMM C was determined by the analysis of ergosterol (biomass), chitin (total bio‐ and necromass) and total organic C (TOC) of sand‐filled mycelium in‐growth bags. The production and turnover of EMM bio‐ and necromass and total C were estimated by modelling. N fertilization reduced the standing EMM biomass C to 57% and its production to 51% of the control (from 238 to 122 kg C ha−1 yr−1), whereas elevated CO2 had no detectable effects. Biomass turnover was high (˜13 yr−1) and unchanged by the treatments. Necromass turnover was slow and was reduced from 1.5 yr−1 in the control to 0.65 yr−1 in the N‐fertilized treatment. However, TOC data did not support an N effect on necromass turnover. An estimated EMM production ranging from 2.5 to 6% of net primary production stresses the importance of its inclusion in C models. A slow EMM necromass turnover indicates an importance in building up forest humus.

Rapidly enhancing oleoresin production in conifer stems through genomic selection and genetic engineering may increase resistance to bark beetles and terpenoid yield for liquid biofuels. We integrated association genetic and genomic prediction analyses of oleoresin flow (g 24 h−1) using 4854 single nucleotide polymorphisms (SNPs) in expressed genes within a pedigreed population of loblolly pine (Pinus taeda) that was clonally replicated at three sites in the southeastern United States. Additive genetic variation in oleoresin flow (h 2 ≈ 0.12–0.30) was strongly correlated between years in which precipitation varied (r a ≈ 0.95), while the genetic correlation between sites declined from 0.8 to 0.37 with increasing differences in soil and climate among sites. A total of 231 SNPs were significantly associated with oleoresin flow, of which 81% were specific to individual sites. SNPs in sequences similar to ethylene signaling proteins, ABC transporters, and diterpenoid hydroxylases were associated with oleoresin flow across sites. Despite this complex genetic architecture, we developed a genomic prediction model to accelerate breeding for enhanced oleoresin flow that is robust to environmental variation. Results imply that breeding could increase oleoresin flow 1.5- to 2.4-fold in one generation.

Pinus taeda is a key timber species, and extensive research has been conducted on its wood formation. However, a comprehensive investigation into the biosynthetic pathways of lignin, cellulose, and hemicellulose in P. taeda is lacking, resulting in an incomplete understanding of secondary cell wall (SCW) formation in this species. In this study, we systematically analyzed transcriptomic data from previously published sources and constructed detailed pathways for lignin, cellulose, and hemicellulose biosynthesis. We identified 188 lignin-related genes and 78 genes associated with cellulose and hemicellulose biosynthesis. An RT-qPCR highlighted 15 key lignin biosynthesis genes and 13 crucial genes for cellulose and hemicellulose biosynthesis. A STEM analysis showed that most essential enzyme-coding genes clustered into Profile 14, suggesting their significant role in SCW formation. Additionally, we identified seven NAC and six MYB transcription factors (TFs) from atypical evolutionary clades, with distinct expression patterns from those of the previously characterized NAC and MYB genes, indicating potentially unique functions in SCW formation. This research provides the first comprehensive overview of lignin, cellulose, and hemicellulose biosynthetic genes in P. taeda and underscores the importance of non-canonical NAC and MYB TFs, laying a genetic foundation for future studies on SCW regulatory mechanisms.