Population transcriptomic sequencing reveals allopatric divergence and local adaptation in Pseudotaxus chienii (Taxaceae)

Elucidating the effects of geography and selection on genetic variation is critical for understanding the relative importance of adaptation in driving differentiation and identifying the environmental factors underlying its occurrence. Adaptive genetic variation is common in tree species, especially widely distributed long-lived species. Pseudotaxus chienii can occupy diverse habitats with environmental heterogeneity and thus provides an ideal material for investigating the process of population adaptive evolution. Here, we characterize genetic and expression variation patterns and investigate adaptive genetic variation in P. chienii populations.

Despite the strong population structure in P. chienii, genomic data revealed signatures of divergent selection associated with environmental variables. Our research provides SNPs, candidate unigenes, and biological pathways related to environmental variables to facilitate elucidation of the genetic variation in P. chienii in relation to environmental adaptation. Our study provides a promising tool for population genomic analyses and insights into the molecular basis of local adaptation.

We generated population transcriptome data and identified 13,545 single nucleotide polymorphisms (SNPs) in 5037 unigenes across 108 individuals from 10 populations. We observed lower nucleotide diversity (π = 0.000701) among the 10 populations than observed in other gymnosperms. Significant negative correlations between expression diversity and nucleotide diversity in eight populations suggest that when the species adapts to the surrounding environment, gene expression and nucleotide diversity have a reciprocal relationship. Genetic structure analyses indicated that each distribution region contains a distinct genetic group, with high genetic differentiation among them due to geographical isolation and local adaptation. We used FST outlier, redundancy analysis, and latent factor mixed model methods to detect molecular signatures of local adaptation. We identified 244 associations between 164 outlier SNPs and 17 environmental variables. The mean temperature of the coldest quarter, soil Fe and Cu contents, precipitation of the driest month, and altitude were identified as the most important determinants of adaptive genetic variation. Most candidate unigenes with outlier signatures were related to abiotic and biotic stress responses, and the monoterpenoid biosynthesis and ubiquitin-mediated proteolysis KEGG pathways were significantly enriched in certain populations and deserve further attention in other long-lived trees. Conclusions: Despite the strong population structure in P. chienii, genomic data revealed signatures of divergent selection associated with environmental variables. Our research provides SNPs, candidate unigenes, and biological pathways related to environmental variables to facilitate elucidation of the genetic variation in P. chienii in relation to environmental adaptation. Our study provides a promising tool for population genomic analyses and insights into the molecular basis of local adaptation.