Slash pine (Pinus elliottii Engelm.) is an important timber and resin species in the United States, China, Brazil and other countries. Understanding the genetic basis of these traits will accelerate its breeding progress. We carried out a genome-wide association study (GWAS), transcriptome-wide association study (TWAS) and weighted gene co-expression network analysis (WGCNA) for growth, wood quality, and oleoresin traits using 240 unrelated individuals from a Chinese slash pine breeding population. We developed high quality 53,229 single nucleotide polymorphisms (SNPs). Our analysis reveals three main results: (1) the Chinese breeding population can be divided into three genetic groups with a mean inbreeding coefficient of 0.137; (2) 32 SNPs significantly were associated with growth and oleoresin traits, accounting for the phenotypic variance ranging from 12.3% to 21.8% and from 10.6% to 16.7%, respectively; and (3) six genes encoding PeTLP, PeAP2/ERF, PePUP9, PeSLP, PeHSP, and PeOCT1 proteins were identified and validated by quantitative real time polymerase chain reaction for their association with growth and oleoresin traits. These results could be useful for tree breeding and functional studies in advanced slash pine breeding program.

This study aims to understand the genetic basis of key industrial traits in Slash pine (Pinus elliottii Engelm. var. elliottii) to enhance improvement efficiency. Detailed analyses were conducted on inter-family differences, genetic parameters, correlations, and breeding values (BVs) for growth, wood properties, and resin traits of Slash pine planted in Changle Forest Farm of Hangzhou, leading to the identification of elite families. It indicates that growth traits are primarily influenced by environmental effects, while wood properties exhibit a significant impact of genetic effects. The variation in resin traits arises from both genetic and environmental effects. Notably, Beta-pinene exhibits the highest variability and genetic gains among the traits analyzed. The family heritability ranges for growth, wood properties, and resin traits are 0.543−0.794, 0.870−0.885, and 0.285−0.695, respectively. Significant positive correlations are evident between growth and resin traits, while a negative correlation is observed between growth and wood properties. Elite families identified through single-trait and multi-trait combined selection are 8−126 for growth traits, 2−325 and 0−373 for wood properties, and 8−131 for resin traits. The average genetic gains for these elite families are 7.44%, 7.17%, and 8.84%, respectively. These findings provide valuable insights for high-generation breeding of Slash pine and lay a genetic foundation for formulating effective breeding strategies for conifers.

The planting of Pinus elliottii Engelm. has now reached close to three million ha in China. Molecular breeding as part of the improvement program for P. elliottii in southern China has been carried out in recent years. Third-generation sequencing (Pacbio sequencing technology, TGS) was used to obtain the exome of P. elliottii for molecular breeding. A total of 35.8 Gb clean reads were generated using TGS. After removing the redundant reads, we obtained 80,339 high-accuracy transcripts. Significantly, a total of 76,411 transcripts (95.1%) were blasted to public annotation databases. We predicted 65,062 intact coding sequences (CDSs), 8916 alternative splicing events, 1937 long non-coding RNAs, and 22,109 simple sequence repeats (SSRs) based on these obtained transcripts. Using the public databases and the data obtained above, 23 orthologous single-copy genes were identified to analyze the phylogenetic relationships for Pinus firstly including P. elliottii. Many positive selection genes involved in important biological processes and metabolism pathways were identified between P. elliottii and other pines. These positive selection genes could be candidate genes to be researched on the genetic basis of superior performance. Our study is the first to reveal the full-length and well-annotated transcripts of P. elliottii, which could provide reference for short transcriptome sequences in the research of genetics, phylogenetics, and genetic improvement for the non-reference genome species.

Pine resin is one of the best known and most exploited non-wood products. Resin is a complex mixture of terpenes produced by specialized cells that are dedicated to tree defense. Chemical defenses are plastic properties, and concentrations of chemical defenses can be adjusted based on environmental factors, such as resource availability. The slope orientation (south/sunny or north/shady) and the altitude of the plantation site have significant effects on the soil nutrient and the plant performance, whereas little is known about how the slope affects the pine resin yield and its components. In total, 1180 slash pines in 18 plots at different slope positions were established to determine the effects on the α- and β-pinene content and resin production of the slash pine. The near-infrared spectroscopy (NIR) technique was developed to rapidly and economically predict the turpentine content for each sample. The results showed that the best partial least squares regression (PLS) models for α- and β-pinene content prediction were established via the combined treatment of multiplicative scatter correction–significant multivariate correlation (MSC–sMC). The prediction models based on sMC spectra for α- and β-pinene content have an R² of 0.82 and 0.85 and an RMSE of 0.96 and 0.82, respectively, and they were successfully implemented in turpentine prediction in this research. The results also showed that a barren slope position (especially mid-slope) could improve the α-pinene and β-pinene content and resin productivity of slash pine, and the β-pinene content in the resin had more variances in this research.