Connecting tree-ring phenotypes, genetic associations and transcriptomics to decipher the genomic architecture of drought adaptation in a widespread conifer

Abstract

As boreal forests face significant threats from climate change, understanding evolutionary trajectories of coniferous species has become fundamental to adapting management and conservation to a drying climate. We examined the genomic architecture underlying adaptive variation related to drought tolerance in 43 populations of a widespread boreal conifer, white spruce (Picea glauca [Moench] Voss), by combining genotype-environment associations, genotype-phenotype associations, and transcriptomics. Adaptive genetic variation was identified by correlating allele frequencies for 6,153 single nucleotide polymorphisms from 2,606 candidate genes with temperature, precipitation and aridity gradients, and testing for significant associations between genotypes and 11 dendrometric and drought-related traits (i.e., anatomical, growth response and climate-sensitivity traits) using a polygenic model. We identified a set of 285 genes significantly associated with a climatic factor or a phenotypic trait, including 110 that were differentially expressed in response to drought under greenhouse-controlled conditions. The interlinked phenotype-genotype-environment network revealed eight high-confidence genes involved in white spruce adaptation to drought, of which four were drought-responsive in the expression analysis. Our findings represent a significant step toward the characterization of the genomic basis of drought tolerance and adaptation to climate in conifers, which is essential to enable the establishment of resilient forests in view of new climate conditions.

Keywords: association studies; climate adaptation; dendroecology; gene expression; tree-ring phenotypes; white spruce.

FIGURE 1

Geographical location of the 43 Picea glauca populations and the common garden trial (red star). Mean soil water availability in summer (SMI) for the period 1950–1980 is overlaid on the range‐wide distribution of P. glauca. The sampled populations represent provenances whose seeds were used to establish the common garden trial and are indicated by black circles. Population numbering corresponds to that found in Table S1

FIGURE 2

Flowchart of the analyses and classification of the phenotypic traits in this study. Step 1: narrow‐sense heritability estimates were obtained for 12 phenotypic traits. Step 2: genetic association tests were carried out between gene variants (SNPs) and (i) traits with significant heritability (i.e., all traits except growth resistance [Rs]) in GPA analyses and (ii) climate in a GEA approach. Step 3: drought‐responsive genes (DEGs) were identified by RNA‐sequencing using a likelihood ratio test (LRT) with an FDR of 0.05. The overlap between association approaches revealed eight high‐confidence genes for drought adaptation, four of them being differentially expressed under drought (number in bold and underlined in integrated insights box)

FIGURE 3

Results of genotype–phenotype association (GPA) analyses. Violin plots summarize the kernel densities of the posterior distributions taken from BSLMM analyses for the proportion of genetic variance explained by allelic variants (PVE). The median (black circle) and the standard deviation of the observations (thin line) are presented. Abbreviations for the phenotypic are as follows: H38: height at 38 years; DBH38: stem diameter at breast height at 38 years; WD: wood density; CWT: cell wall thickness; LDr: radial lumen diameter; Rc: growth recovery; Rl: growth resilience; Rr: relative growth resilience; CS‐CWT: climate sensitivity of cell wall thickness to drought; CS‐WD: climate sensitivity of wood density to drought; CS‐LDr: climate sensitivity of radial lumen diameter to drought

FIGURE 4

Results of genotype–environment association (GEA) analyses. Venn diagram showing the numbers of significant SNPs and genes (reported in parentheses and italics), and the intersection between sets detected with the latent factor mixed models (LFMM) and the redundancy analysis (RDA)

FIGURE 5

Distribution of genes carrying significant SNPs classified into different sets. (a) Venn diagrams showing unique and common sets of genes identified using genotype–environment (GEA) and genotype–phenotype (GPA) associations, and transcriptomic methods. (b) Venn diagram illustrating unique and common sets of drought‐responsive genes (DEGs) identified in GEA (GEA_DEGs) and GPA (GPA_DEGs). DEGs were classified into upregulated genes (Up, with log fold change LFC >0) and downregulated genes (Down, with LFC <0)