Genetic diversity and distribution pattern responses of Picea asperata

Picea asperata Mast. as a kind of keystone coniferous plant, lives in alpine and subalpine regions of Southwest China and takes on very important ecological and economic tasks there. But with the increasingly serious global climate events, the living environment for P. asperata is getting into great trouble. In this situation, explaining the inherent connection between species distribution and environmental elements is a main part of ecological study. This kind of understanding not only can help us to know about the genetic variety, but also helps us to think about the variety of living organisms.

We employed transcriptome sequencing to analyze 54 P. asperata individuals from 11 natural populations and combined with environmental variables to assess population structure and genetic diversity. Species distribution modeling (MaxEnt) was applied to predict habitat shifts under current and future climate scenarios (SSP1-2.6, SSP5-8.5), while redundancy analysis (RDA) and latent factor mixed model (LFMM) identified key environmental factors that drive genetic variation.

ADMIXTURE analysis indicated that the optimal number of clusters was K = 1, and P. asperata exhibited low nucleotide diversity (π = 0.003508). Stairway Plot analysis revealed a historical bottleneck followed by gradual population recovery. TreeMix analysis indicated ongoing gene flow among populations, consistent with low pairwise F _ST values. MaxEnt projections predicted an expansion of suitable habitats under future climates, particularly under the high-emission SSP5-8.5 scenario. Both RDA and LFMM identified December wind speed (Wind12) and precipitation of the warmest quarter (Bio18) as the environmental factors most strongly associated with genomic differentiation. Functional annotation and GO enrichment further uncovered candidate genes involved in stress responses, including ERD1, ARR1, and IBR1.

The study reveals low genetic diversity in P. asperata. Stairway Plot analysis detected a bottleneck during the Quaternary glaciations. MaxEnt projections indicate habitat expansion under future climates, while GEA analyses identify December wind speed (Wind12) and the warmest quarter (Bio18) as key drivers of genomic differentiation. To safeguard the adaptive potential of P. asperata, we recommend strengthening in situ conservation, maintaining existing habitat connectivity, assisting the migration of germplasm carrying key adaptive alleles, and establishing comprehensive germplasm repositories.