Where to draw the line? Expanding the delineation of conservation units to highly mobile taxa

Development and validation of a GT-seq panel for genetic monitoring in a threatened species using minimally invasive sampling

Minimally invasive samples are often the best option for collecting genetic material from species of conservation concern, but they perform poorly in many genomic sequencing methods due to their tendency to yield low DNA quality and quantity. Genotyping-in-thousands by sequencing (GT-seq) is a powerful amplicon sequencing method that can genotype large numbers of variable-quality samples at a standardized set of single nucleotide polymorphism (SNP) loci. Here, we develop, optimize, and validate a GT-seq panel for the federally threatened northern Idaho ground squirrel (Urocitellus brunneus) to provide a standardized approach for future genetic monitoring and assessment of recovery goals using minimally invasive samples. The optimized panel consists of 224 neutral and 81 putatively adaptive SNPs. DNA collected from buccal swabs from 2016 to 2020 had 73% genotyping success, while samples collected from hair from 2002 to 2006 had little to no DNA remaining and did not genotype successfully. We evaluated our GT-seq panel by measuring genotype discordance rates compared to RADseq and whole-genome sequencing. GT-seq and other sequencing methods had similar population diversity and F ST estimates, but GT-seq consistently called more heterozygotes than expected, resulting in negative F IS values at the population level. Genetic ancestry assignment was consistent when estimated with different sequencing methods and numbers of loci. Our GT-seq panel is an effective and efficient genotyping tool that will aid in the monitoring and recovery of this threatened species, and our results provide insights for applying GT-seq for minimally invasive DNA sampling techniques in other rare animals.

Genetic analysis of harvest samples reveals population structure in a highly mobile generalist carnivore

Delineating wildlife population boundaries is important for effective population monitoring and management. The bobcat (Lynx rufus) is a highly mobile generalist carnivore that is ecologically and economically important. We sampled 1225 bobcats harvested in South Dakota, USA (2014-2019), of which 878 were retained to assess genetic diversity and infer population genetic structure using 17 microsatellite loci. We assigned individuals to genetic clusters (K) using spatial and nonspatial Bayesian clustering algorithms and quantified differentiation (F ST and G ST ″ ) among clusters. We found support for population genetic structure at K = 2 and K = 4, with pairwise F ST and G ST ″ values indicating weak to moderate differentiation, respectively, among clusters. For K = 2, eastern and western clusters aligned closely with historical bobcat management units and were consistent with a longitudinal suture zone for bobcats previously identified in the Great Plains. We did not observe patterns of population genetic structure aligning with major rivers or highways. Genetic divergence observed at K = 4 aligned roughly with ecoregion breaks and may be associated with environmental gradients, but additional sampling with more precise locational data may be necessary to validate these patterns. Our findings reveal that cryptic population structure may occur in highly mobile and broadly distributed generalist carnivores, highlighting the importance of considering population structure when establishing population monitoring programs or harvest regulations. Our study further demonstrates that for elusive furbearers, harvest can provide an efficient, broad-scale sampling approach for genetic population assessments.

How Can Genomics Help or Hinder Wildlife Conservation?

Genomic data are becoming increasingly affordable and easy to collect, and new tools for their analysis are appearing rapidly. Conservation biologists are interested in using this information to assist in management and planning but are typically limited financially and by the lack of genomic resources available for non-model taxa. It is therefore important to be aware of the pitfalls as well as the benefits of applying genomic approaches. Here, we highlight recent methods aimed at standardizing population assessments of genetic variation, inbreeding, and forms of genetic load and methods that help identify past and ongoing patterns of genetic interchange between populations, including those subjected to recent disturbance. We emphasize challenges in applying some of these methods and the need for adequate bioinformatic support. We also consider the promises and challenges of applying genomic approaches to understand adaptive changes in natural populations to predict their future adaptive capacity.

Genomics-informed conservation units reveal spatial variation in climate vulnerability in a migratory bird

Identifying genetic conservation units (CUs) in threatened species is critical for the preservation of adaptive capacity and evolutionary potential in the face of climate change. However, delineating CUs in highly mobile species remains a challenge due to high rates of gene flow and genetic signatures of isolation by distance. Even when CUs are delineated in highly mobile species, the CUs often lack key biological information about what populations have the most conservation need to guide management decisions. Here we implement a framework for CU identification in the Canada Warbler (Cardellina canadensis), a migratory bird species of conservation concern, and then integrate demographic modelling and genomic offset to guide conservation decisions. We find that patterns of whole genome genetic variation in this highly mobile species are primarily driven by putative adaptive variation. Identification of CUs across the breeding range revealed that Canada Warblers fall into two evolutionarily significant units (ESU), and three putative adaptive units (AUs) in the South, East, and Northwest. Quantification of genomic offset, a metric of genetic changes necessary to maintain current gene-environment relationships, revealed significant spatial variation in climate vulnerability, with the Northwestern AU being identified as the most vulnerable to future climate change. Alternatively, quantification of past population trends within each AU revealed the steepest population declines have occurred within the Eastern AU. Overall, we illustrate that genomics-informed CUs provide a strong foundation for identifying current and future regional threats that can be used to inform management strategies for a highly mobile species in a rapidly changing world.

Individual-based landscape genomics for conservation: An analysis pipeline

Landscape genomics can harness environmental and genetic data to inform conservation decisions by providing essential insights into how landscapes shape biodiversity. The massive increase in genetic data afforded by the genomic era provides exceptional resolution for answering critical conservation genetics questions. The accessibility of genomic data for non-model systems has also enabled a shift away from population-based sampling to individual-based sampling, which now provides accurate and robust estimates of genetic variation that can be used to examine the spatial structure of genomic diversity, population connectivity and the nature of environmental adaptation. Nevertheless, the adoption of individual-based sampling in conservation genetics has been slowed due, in large part, to concerns over how to apply methods developed for population-based sampling to individual-based sampling schemes. Here, we discuss the benefits of individual-based sampling for conservation and describe how landscape genomic methods, paired with individual-based sampling, can answer fundamental conservation questions. We have curated key landscape genomic methods into a user-friendly, open-source workflow, which we provide as a new R package, A Landscape Genomics Analysis Toolkit in R (algatr). The algatr package includes novel added functionality for all of the included methods and extensive vignettes designed with the primary goal of making landscape genomic approaches more accessible and explicitly applicable to conservation biology.

Seascape genomics reveals limited dispersal and suggests spatially varying selection among European populations of sea lamprey (Petromyzon marinus)

Sea lamprey Petromyzon marinus is an anadromous and semelparous fish without homing behaviors. Despite being a freshwater, free-living organism for a large part of their life cycle, its adulthood is spent as a parasite of marine vertebrates. In their native European range, while it is well-established that sea lampreys comprise a single nearly-panmictic population, few studies have further explored the evolutionary history of natural populations. Here, we performed the first genome-wide characterization of sea lamprey's genetic diversity in their European natural range. The objectives were to investigate the connectivity among river basins and explore evolutionary processes mediating dispersal during the marine phase, with the sequencing of 186 individuals from 8 locations spanning the North Eastern Atlantic coast and the North Sea with double-digest RAD-sequencing, obtaining a total of 30,910 bi-allelic SNPs. Population genetic analyses reinforced the existence of a single metapopulation encompassing freshwater spawning sites within the North Eastern Atlantic and the North Sea, though the prevalence of private alleles at northern latitudes suggested some limits to the species' dispersal. Seascape genomics suggested a scenario where oxygen concentration and river runoffs impose spatially varying selection across their distribution range. Exploring associations with the abundance of potential hosts further suggested that hake and cod could also impose selective pressures, although the nature of such putative biotic interactions was unresolved. Overall, the identification of adaptive seascapes in a panmictic anadromous species could contribute to conservation practices by providing information for restoration activities to mitigate local extinctions on freshwater sites.