A complex interplay of genetic introgression and local adaptation during the evolutionary history of three closely related spruce species

Abstract

As climate change triggers unprecedented ecological shifts, it becomes imperative to understand the genetic underpinnings of species' adaptability. Adaptive introgression significantly contributes to organismal adaptation to new environments by introducing genetic variation across species boundaries. However, despite growing recognition of its importance, the extent to which adaptive introgression has shaped the evolutionary history of closely related species remains poorly understood. Here we employed population genetic analyses of high-throughput sequencing data to investigate the interplay between genetic introgression and local adaptation in three species of spruce trees in the genus Picea (P. asperata, P. crassifolia, and P. meyeri). We find distinct genetic differentiation among these species, despite a substantial gene flow. Crucially, we find bidirectional adaptive introgression between allopatrically distributed species pairs and unearthed dozens of genes linked to stress resilience and flowering time. These candidate genes most likely have promoted adaptability of these spruces to historical environmental changes and may enhance their survival and resilience to future climate changes. Our findings highlight that adaptive introgression could be prevalent and bidirectional in a topographically complex area, and this could have contributed to rich genetic variation and diverse habitat usage by tree species.

Keywords: Adaptation; Introgression; Picea; Population transcriptome.

Fig. 1

Map showing the geographical distribution of sampling locations for Picea asperata (N = 6), P. crassifolia (N = 12), and P. meyeri (N = 3) populations. Photographs of cones of three species were adopted from https://www.cfh.ac.cn/Spdb/spsearch.aspx.

Fig. 2

Phylogenetic relationships and population structure for populations of the three Picea species (P. asperata, P. crassifolia, and P. meyeri). A, Bar plots of population structure. Each vertical bar represents an individual, and the height of each color represents the probability of assignment to that cluster. A maximum likelihood (ML) tree for P. asperata and P. crassifolia as well as P. meyeri, constructed using P. breweriana as an outgroup, is presented above the bar plots. B, Principal component analysis (PCA) plot showing the first two principal components.

Fig. 3

Genetic introgression between Picea asperata, P. crassifolia, and P. meyeri. A, ABBA-BABA analysis of P. asperata, P. crassifolia, and P. meyeri, constructed using P. breweriana as an outgroup. The numbers in the figure represent the number of introgressed alleles between species. Abbreviations: asp, P. asperata; cra, P. crassifolia; mey, P. meyeri; Outgroup, P. breweriana. B, TreeMix analysis results of 21 populations from P. asperata, P. crassifolia, and P. meyeri with P. breweriana as the outgroup. The red arrow represents the direction of gene flow, and the darker the color, the stronger the intensity. C and D, Genomic regions with strong selective sweep signals. Distribution of log₂(θπ ratios) and F_ST values; these were calculated in 10 kb sliding windows in 1 kb steps. Data points located to the left and right of the vertical dashed lines correspond to the top 5% of empirical log₂(θπ ratios) values and data points above the horizontal dashed lines represent the top 5% of the empirical F_ST values. Blue points, orange points, and green points represent genomic regions under selection for P. meyeri, P. asperata, and P. crassifolia, respectively. The highlighted triangles represent introgressed allele under positive selection that are highly correlated with environmental adaptation. C,P. asperata and P. meyeri. D,P. crassifolia and P. meyeri.

Fig. 4

Predicted distribution of three species. A, Predicted distribution of the three species during mid-Holocene and the Last Glacial Maximums. B, Predicted distribution of three species the present periods.