Sample identification and pedigree reconstruction in Wolverine (Gulo gulo) using SNP genotyping of non-invasive samples

Translating genomic advances into biodiversity conservation

A key action of the new Global Biodiversity Framework is the maintenance of genetic diversity in all species to safeguard their adaptive potential. To achieve this goal, a translational mindset, which aims to convert results of basic research into direct practical benefits, needs to be applied to biodiversity conservation. Despite much discussion on the value of genomics to conservation, a disconnect between those generating genomic resources and those applying it to biodiversity management remains. As global efforts to generate reference genomes for non-model species increase, investment into practical biodiversity applications is critically important. Applications such as understanding population and multispecies diversity and longitudinal monitoring need support alongside education for policymakers on integrating the data into evidence-based decisions. Without such investment, the opportunity to revolutionize global biodiversity conservation using genomics will not be fully realized.

Species-specific SNP arrays for non-invasive genetic monitoring of a vulnerable bat

Genetic tagging from scats is one of the minimally invasive sampling (MIS) monitoring approaches commonly used to guide management decisions and evaluate conservation efforts. Microsatellite markers have traditionally been used but are prone to genotyping errors. Here, we present a novel method for individual identification in the Threatened ghost bat Macroderma gigas using custom-designed Single Nucleotide Polymorphism (SNP) arrays on the MassARRAY system. We identified 611 informative SNPs from DArTseq data from which three SNP panels (44-50 SNPs per panel) were designed. We applied SNP genotyping and molecular sexing to 209 M. gigas scats collected from seven caves in the Pilbara, Western Australia, employing a two-step genotyping protocol and identifying unique genotypes using a custom-made R package, ScatMatch. Following data cleaning, the average amplification rate was 0.90 ± 0.01 and SNP genotyping errors were low (allelic dropout 0.003 ± 0.000) allowing clustering of scats based on one or fewer allelic mismatches. We identified 19 unique bats (9 confirmed/likely males and 10 confirmed/likely females) from a maternity and multiple transitory roosts, with two male bats detected using roosts, 9 km and 47 m apart. The accuracy of our SNP panels enabled a high level of confidence in the identification of individual bats. Targeted SNP genotyping is a valuable tool for monitoring and tracking of non-model species through a minimally invasive sampling approach.

A simulation-based evaluation of methods for estimating census population size of terrestrial game species from genetically-identified parent-offspring pairs

Estimates of wildlife population size are critical for conservation and management, but accurate estimates are difficult to obtain for many species. Several methods have recently been developed that estimate abundance using kinship relationships observed in genetic samples, particularly parent-offspring pairs. While these methods are similar to traditional Capture-Mark-Recapture, they do not need physical recapture, as individuals are considered recaptured if a sample contains one or more close relatives. This makes methods based on genetically-identified parent-offspring pairs particularly interesting for species for which releasing marked animals back into the population is not desirable or not possible (e.g., harvested fish or game species). However, while these methods have successfully been applied in commercially important fish species, in the absence of life-history data, they are making several assumptions unlikely to be met for harvested terrestrial species. They assume that a sample contains only one generation of parents and one generation of juveniles of the year, while more than two generations can coexist in the hunting bags of long-lived species, or that the sampling probability is the same for each individual, an assumption that is violated when fecundity and/or survival depend on sex or other individual traits. In order to assess the usefulness of kin-based methods to estimate population sizes of terrestrial game species, we simulated population pedigrees of two different species with contrasting demographic strategies (wild boar and red deer), applied four different methods and compared the accuracy and precision of their estimates. We also performed a sensitivity analysis, simulating population pedigrees with varying fecundity characteristics and various levels of harvesting to identify optimal conditions of applicability of each method. We showed that all these methods reached the required levels of accuracy and precision to be effective in wildlife management under simulated circumstances (i.e., for species within a given range of fecundity and for a given range of sampling intensity), while being robust to fecundity variation. Despite the potential usefulness of the methods for terrestrial game species, care is needed as several biases linked to hunting practices still need to be investigated (e.g., when hunting bags are biased toward a particular group of individuals).

Microsatellite Characterization and Panel Selection for Brown Bear (Ursus arctos) Population Assessment

An assessment of the genetic diversity and structure of a population is essential for designing recovery plans for threatened species. Italy hosts two brown bear populations, Ursus arctos marsicanus (Uam), endemic to the Apennines of central Italy, and Ursus arctos arctos (Uaa), in the Italian Alps. Both populations are endangered and occasionally involved in human-wildlife conflict; thus, detailed management plans have been in place for several decades, including genetic monitoring. Here, we propose a simple cost-effective microsatellite-based protocol for the management of populations with low genetic variation. We sampled 22 Uam and 22 Uaa individuals and analyzed a total of 32 microsatellite loci in order to evaluate their applicability in individual identification. Based on genetic variability estimates, we compared data from four different STR marker sets, to evaluate the optimal settings in long-term monitoring projects. Allelic richness and gene diversity were the highest for the Uaa population, whereas depleted genetic variability was noted for the Uam population, which should be regarded as a conservation priority. Our results identified the most effective STR sets for the estimation of genetic diversity and individual discrimination in Uam (9 loci, PIC 0.45; PID 2.0 × 10-5), and Uaa (12 loci, PIC 0.64; PID 6.9 × 10-11) populations, which can easily be utilized by smaller laboratories to support local governments in regular population monitoring. The method we proposed to select the most variable markers could be adopted for the genetic characterization of other small and isolated populations.

Diversity of the MHC class II DRB gene in the wolverine (Carnivora: Mustelidae: Gulo gulo) in Finland

The wolverine (Gulo gulo) in Finland has undergone significant population declines in the past. Since major histocompatibility complex (MHC) genes encode proteins involved in pathogen recognition, the diversity of these genes provides insights into the immunological fitness of regional populations. We sequenced 862 amplicons (242 bp) of MHC class II DRB exon 2 from 32 Finnish wolverines and identified 11 functional alleles and three pseudogenes. A molecular phylogenetic analysis indicated trans-species polymorphism, and PAML and MEME analyses indicated positive selection, suggesting that the Finnish wolverine DRB genes have evolved under balancing and positive selection. In contrast to DRB gene analyses in other species, allele frequencies in the Finnish wolverines clearly indicated the existence of two regional subpopulations, congruent with previous studies based on neutral genetic markers. In the Finnish wolverine, rapid population declines in the past have promoted genetic drift, resulting in a lower genetic diversity of DRB loci, including fewer alleles and positively selected sites, than other mustelid species analyzed previously. Our data suggest that the MHC region in the Finnish wolverine population was likely affected by a recent bottleneck.