Genomic insights into the genotype-environment mismatch and conservation units of a Qinghai-Tibet Plateau endemic cypress under climate change

Abstract

Habitat loss induced by climate warming is a major threat to biodiversity, particularly to threatened species. Understanding the genetic diversity and distributional responses to climate change of threatened species is critical to facilitate their conservation and management. Cupressus gigantea, a rare conifer found in the eastern Qinghai-Tibet Plateau (QTP) at 3000-3600 m.a.s.l., is famous for its largest specimen, the King Cypress, which is >55 m tall. Here, we obtained transcriptome data from 96 samples of 10 populations covering its whole distribution and used these data to characterize genetic diversity, identify conservation units, and elucidate genomic vulnerability to future climate change. After filtering, we identified 145,336, 26,103, and 2833 single nucleotide polymorphisms in the whole, putatively neutral, and putatively adaptive datasets, respectively. Based on the whole and putatively neutral datasets, we found that populations from the Yalu Tsangpo River (YTR) and Nyang River (NR) catchments could be defined as separate management units (MUs), due to distinct genetic clusters and demographic histories. Results of gradient forest models suggest that all populations of C. gigantea may be at risk due to the high expected rate of climate change, and the NR MU had a higher risk than the YTR MU. This study deepens our understanding of the complex evolutionary history and population structure of threatened tree species in extreme environments, such as dry river valleys above 3000 m.a.s.l. in the QTP, and provides insights into their susceptibility to global climate change and potential for adaptive responses.

Keywords: King Cypress; Qinghai–Tibetan Plateau; climate change; conservation units; genomic vulnerability; local adaptation.

FIGURE 1

Geographic distribution of sampled Cupressus gigantea populations. (a) “The King Cypress”—the largest specimen of C. gigantea at Nyingchi, is estimated to be more than 3000 years old. (b) The geographic distribution of wild C. gigantea samples under the background of habitat suitability. (c) The location of the Qinghai–Tibet Plateau. Pie chart shows the ancestral composition of each population with K = 2 inferred from ADMIXTURE based on dataset Ⅰ, which contains all SNPs

FIGURE 2

Population structure and phylogenetic inference of Cupressus gigantea. (a–b) Structure results, with different colors indicating different genetic backgrounds based on dataset Ⅰ (a) and dataset Ⅱ (b). (c–e) Results of the principal component analysis using dataset Ⅰ (c), dataset Ⅱ (d), and dataset Ⅲ (e). (f) A maximum‐likelihood phylogenetic tree based on 4DTv sites using dataset Ⅰ

FIGURE 3

Demographic history of Cupressus gigantea. (a) Schematic diagram of demographic scenario modeled in FSC2. Estimated effective population sizes and divergence times are indicated. The numbers next to the arrows indicate the per generation migration rate between populations. (b) The detailed population demographic history of YTR, NR, and all C. gigantea individuals (ALL) over the past 10 million years based on the Stairway Plot method. The inferred effective size N_e of the C. gigantea population is plotted from present time (0) to the past. Thick lines represent the median, and thin light lines represent the 95% pseudo‐CI defined by the 2.5% and 97.5% estimates from the SFS analysis. The periods of the Xixiabangma Glaciation, the Naynayxungla Glaciation, the Guxiang Glaciation, and the Baiyu Glaciation are highlighted with gray vertical bars

FIGURE 4

Prediction of genomic mismatch under future climate change for two shared socioeconomic pathways (SSPs) in 2100 based on the whole SNPs (a, b) and environment‐associated SNPs (c, d). Red and blue indicate high and low genomic mismatch, respectively. The circles represent the locations of Cupressus gigantea populations used in our study