Demographic history and conservation genomics of caribou (Rangifer tarandus) in Québec

Abstract

The loss of genetic diversity is a challenge many species are facing, with genomics being a potential tool to inform and prioritize decision-making. Most caribou (Rangifer tarandus) populations have experienced significant recent declines throughout Québec, Canada, and are considered of concern, threatened or endangered. Here, we calculated the ancestral and contemporary patterns of genomic diversity of five representative caribou populations and applied a comparative population genomics framework to assess the interplay between demographic events and genomic diversity. We first calculated a caribou specific mutation rate, μ, by extracting orthologous genes from related ungulates and estimating the rate of synonymous mutations. Whole genome re-sequencing was then completed on 67 caribou: from these data we calculated nucleotide diversity, θ_π and estimated the coalescent or ancestral effective population size (N_e), which ranged from 12,030 to 15,513. When compared to the census size, N_C, the endangered Gaspésie Mountain caribou population had the highest ancestral N_e:N_C ratio which is consistent with recent work suggesting high ancestral N_e:N_C is of conservation concern. In contrast, values of contemporary N_e, estimated from linkage-disequilibrium, ranged from 11 to 162, with Gaspésie having among the highest contemporary N_e:N_C ratio. Importantly, classic conservation genetics theory would predict this population to be of less concern based on this ratio. Interestingly, F varied only slightly between populations, and despite evidence of bottlenecks across the province, runs of homozygosity were not abundant in the genome. Tajima's D estimates mirrored the demographic models and current conservation status. Our study highlights how genomic patterns are nuanced and potentially misleading if viewed only through a contemporary lens; we argue a holistic conservation genomics view should integrate ancestral N_e and Tajima's D into management decisions.