Landscape limits gene flow and drives population structure in Agassiz's desert tortoise (Gopherus agassizii).
Sci Rep
; 8(1): 11231, 2018 07 25.
Article
de En
| MEDLINE
| ID: mdl-30046050
ABSTRACT
Distance, environmental heterogeneity and local adaptation can strongly influence population structure and connectivity. Understanding how these factors shape the genomic landscape of threatened species is a major goal in conservation genomics and wildlife management. Herein, we use thousands (6,859) of single nucleotide polymorphism markers and spatial data from hundreds of individuals (n = 646) to re-evaluate the population structure of Agassiz's desert tortoise (Gopherus agassizii). Analyses resolve from 4 to 8 spatially well-defined clusters across the range. Western, central, and southern populations within the Western Mojave recovery unit are consistent throughout, while analyses sometimes merge other recovery units depending on the level of clustering. Causal modeling consistently associates genetic connectivity with least-cost distance, based on multiple landscape features associated with tortoise habitat, better than geographic distance. Some features include elevation, soil depth, rock volume, precipitation, and vegetation coverage, suggesting that physical, climatic, and biotic landscape features have played a strong evolutionary role restricting gene flow between populations. Further, 12 highly differentiated outlier loci have associated functions that may be involved with neurogenesis, wound healing, lipid metabolism, and possibly vitellogenesis. Together, these findings have important implications for recovery programs, such as translocations, population augmentation, reproduction in captivity and the identification of ecologically important genes, opening new venues for conservation genomics in desert tortoises.
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Tortues
/
Adaptation biologique
/
Flux des gènes
/
Animaux sauvages
Type d'étude:
Prognostic_studies
Limites:
Animals
Langue:
En
Journal:
Sci Rep
Année:
2018
Type de document:
Article
Pays d'affiliation:
Canada