Large-scale assessment of genetic structure to assess risk of populations of a large herbivore to disease

Chronic wasting disease (CWD) can spread among cervids by direct and indirect transmission, the former being more likely in emerging areas. Identifying subpopulations allows the delineation of focal areas to target for intervention. We aimed to assess the population structure of white-tailed deer (Odocoileus virginianus) in the northeastern United States at a regional scale to inform managers regarding gene flow throughout the region. We genotyped 10 microsatellites in 5701 wild deer samples from Maryland, New York, Ohio, Pennsylvania, and Virginia. We evaluated the distribution of genetic variability through spatial principal component analysis and inferred genetic structure using non-spatial and spatial Bayesian clustering algorithms (BCAs). We simulated populations representing each inferred wild cluster, wild deer in each state and each physiographic province, total wild population, and a captive population. We conducted genetic assignment tests using these potential sources, calculating the probability of samples being correctly assigned to their origin. Non-spatial BCA identified two clusters across the region, while spatial BCA suggested a maximum of nine clusters. Assignment tests correctly placed deer into captive or wild origin in most cases (94%), as previously reported, but performance varied when assigning wild deer to more specific origins. Assignments to clusters inferred via non-spatial BCA performed well, but efficiency was greatly reduced when assigning samples to clusters inferred via spatial BCA. Differences between spatial BCA clusters are not strong enough to make assignment tests a reliable method for inferring the geographic origin of deer using 10 microsatellites. However, the genetic distinction between clusters may indicate natural and anthropogenic barriers of interest for management.

Evaluating the use of statistical and machine learning methods for estimating breed composition of purebred and crossbred animals in thirteen cattle breeds using genomic information

Introduction: The ability to accurately predict breed composition using genomic information has many potential uses including increasing the accuracy of genetic evaluations, optimising mating plans and as a parameter for genotype quality control. The objective of the present study was to use a database of genotyped purebred and crossbred cattle to compare breed composition predictions using a freely available software, Admixture, with those from a single nucleotide polymorphism Best Linear Unbiased Prediction (SNP-BLUP) approach; a supplementary objective was to determine the accuracy and general robustness of low-density genotype panels for predicting breed composition. Methods: All animals had genotype information on 49,213 autosomal single nucleotide polymorphism (SNPs). Thirteen breeds were included in the analysis and 500 purebred animals per breed were used to establish the breed training populations. Accuracy of breed composition prediction was determined using a separate validation population of 3,146 verified purebred and 4,330 two and three-way crossbred cattle. Results: When all 49,213 autosomal SNPs were used for breed prediction, a minimal absolute mean difference of 0.04 between Admixture vs. SNP-BLUP breed predictions was evident. For crossbreds, the average absolute difference in breed prediction estimates generated using SNP-BLUP and Admixture was 0.068 with a root mean square error of 0.08. Breed predictions from low-density SNP panels were generated using both SNP-BLUP and Admixture and compared to breed prediction estimates using all 49,213 SNPs (representing the gold standard). Breed composition estimates of crossbreds required more SNPs than predicting the breed composition of purebreds. SNP-BLUP required ≥3,000 SNPs to predict crossbred breed composition, but only 2,000 SNPs were required to predict purebred breed status. The absolute mean (standard deviation) difference across all panels <2,000 SNPs was 0.091 (0.054) and 0.315 (0.316) when predicting the breed composition of all animals using Admixture and SNP-BLUP, respectively compared to the gold standard prediction. Discussion: Nevertheless, a negligible absolute mean (standard deviation) difference of 0.009 (0.123) in breed prediction existed between SNP-BLUP and Admixture once ≥3,000 SNPs were considered, indicating that the prediction of breed composition could be readily integrated into SNP-BLUP pipelines used for genomic evaluations thereby avoiding the necessity for a stand-alone software.

Genome-scale phylogeography resolves the native population structure of the Asian longhorned beetle, Anoplophora glabripennis (Motschulsky)

Human-assisted movement has allowed the Asian longhorned beetle (ALB, Anoplophora glabripennis (Motschulsky)) to spread beyond its native range and become a globally regulated invasive pest. Within its native range of China and the Korean peninsula, human-mediated dispersal has also caused cryptic translocation of insects, resulting in population structure complexity. Previous studies used genetic methods to detangle this complexity but were unable to clearly delimit native populations which is needed to develop downstream biosurveillance tools. We used genome-wide markers to define historical population structure in native ALB populations and contemporary movement between regions. We used genotyping-by-sequencing to generate 6102 single-nucleotide polymorphisms (SNPs) and amplicon sequencing to genotype 53 microsatellites. In total, we genotyped 712 individuals from ALB's native distribution. We observed six distinct population clusters among native ALB populations, with a clear delineation between northern and southern groups. Most of the individuals from South Korea were distinct from populations in China. Our results also indicate historical divergence among populations and suggest limited large-scale admixture, but we did identify a restricted number of cases of contemporary movement between regions. We identified SNPs under selection and describe a clinal allele frequency pattern in a missense variant associated with glycerol kinase, an important enzyme in the utilization of an insect cryoprotectant. We further demonstrate that small numbers of SNPs can assign individuals to geographic regions with high probability, paving the way for novel ALB biosurveillance tools.

An accurate assignment test for extremely low-coverage whole-genome sequence data

Genomic assignment tests can provide important diagnostic biological characteristics, such as population of origin or ecotype. Yet, assignment tests often rely on moderate- to high-coverage sequence data that can be difficult to obtain for fields such as molecular ecology and ancient DNA. We have developed a novel approach that efficiently assigns biologically relevant information (i.e., population identity or structural variants such as inversions) in extremely low-coverage sequence data. First, we generate databases from existing reference data using a subset of diagnostic single nucleotide polymorphisms (SNPs) associated with a biological characteristic. Low-coverage alignment files are subsequently compared to these databases to ascertain allelic state, yielding a joint probability for each association. To assess the efficacy of this approach, we assigned haplotypes and population identity in Heliconius butterflies, Atlantic herring, and Atlantic cod using chromosomal inversion sites and whole-genome data. We scored both modern and ancient specimens, including the first whole-genome sequence data recovered from ancient Atlantic herring bones. The method accurately assigns biological characteristics, including population membership, using extremely low-coverage data (as low as 0.0001x) based on genome-wide SNPs. This approach will therefore increase the number of samples in evolutionary, ecological and archaeological research for which relevant biological information can be obtained.

Population assignment tests uncover rare long-distance marine larval dispersal events

Long-distance dispersal (LDD) is consequential to metapopulation ecology and evolution. In systems where dispersal is undertaken by small propagules, such as larvae in the ocean, documenting LDD is especially challenging. Genetic parentage analysis has gained traction as a method for measuring larval dispersal, but such studies are generally spatially limited, leaving LDD understudied in marine species. We addressed this knowledge gap by uncovering LDD with population assignment tests in the coral reef fish Elacatinus lori, a species whose short-distance dispersal has been well-characterized by parentage analysis. When adults (n = 931) collected throughout the species' range were categorized into three source populations, assignment accuracy exceeded 99%, demonstrating low rates of gene flow between populations in the adult generation. After establishing high assignment confidence, we assigned settlers (n = 3,828) to source populations. Within the settler cohort, <0.1% of individuals were identified as long-distance dispersers from other populations. These results demonstrate an exceptionally low level of connectivity between E. lori populations, despite the potential for ocean currents to facilitate LDD. More broadly, these findings illustrate the value of combining genetic parentage analysis and population assignment tests to uncover short- and long-distance dispersal, respectively.

Estimating the contribution of Greenland Halibut (Reinhardtius hippoglossoides) stocks to nurseries by means of genotyping-by-sequencing: Sex and time matter

Identification of stocks and quantification of their relative contribution to recruitment are major objectives toward improving the management and conservation of marine exploited species. Next-generation sequencing allows for thousands of genomic markers to be analyzed, which provides the resolution needed to address these questions in marine species with weakly differentiated populations. Greenland Halibut (Reinhardtius hippoglossoides) is one of the most important exploited demersal species throughout the North Atlantic, in particular in the Gulf of St. Lawrence, Canada. There, two nurseries are known, the St. Lawrence Estuary and the northern Anticosti Island, but their contribution to the renewal of stocks remains unknown. The goals of this study were (a) to document the genetic structure and (b) to estimate the contribution of the different identified breeding stocks to nurseries. We sampled 100 juveniles per nursery and 50 adults from seven sites ranging from Saguenay Fjord to offshore Newfoundland, with some sites sampled over two consecutive years in order to evaluate the temporal stability of the contribution. Our results show that after removing sex-linked markers, the Estuary/Gulf of St. Lawrence represents a single stock which is genetically distinct from the Atlantic around Newfoundland (F ST = 0.00146, p-value = .001). Population assignment showed that recruitment in both nurseries is predominantly associated with the St. Lawrence stock. However, we found that the relative contribution of both stocks to the nurseries is temporally variable with 1% contribution of the Newfoundland stock one year but up to 33% for the second year, which may be caused by year-to-year variation in larval transport into the Gulf of St. Lawrence. This study serves as a model for the identification of stocks for fisheries resources in a context where few barriers to dispersal occur, in addition to demonstrating the importance of considering sex-linked markers and temporal replicates in studies of population genomics.

Power of a dual-use SNP panel for pedigree reconstruction and population assignment

The use of high-throughput, low-density sequencing approaches has dramatically increased in recent years in studies of eco-evolutionary processes in wild populations and domestication in commercial aquaculture. Most of these studies focus on identifying panels of SNP loci for a single downstream application, whereas there have been few studies examining the trade-offs for selecting panels of markers for use in multiple applications. Here, we detail the use of a bioinformatic workflow for the development of a dual-purpose SNP panel for parentage and population assignment, which included identifying putative SNP loci, filtering for the most informative loci for the two tasks, designing effective multiplex PCR primers, optimizing the SNP panel for performance, and performing quality control steps for downstream applications. We applied this workflow to two adjacent Alaskan Sockeye Salmon populations and identified a GTseq panel of 142 SNP loci for parentage and 35 SNP loci for population assignment. Only 50-75 panel loci were necessary for >95% accurate parentage, whereas population assignment success, with all 172 panel loci, ranged from 93.9% to 96.2%. Finally, we discuss the trade-offs and complexities of the decision-making process that drives SNP panel development, optimization, and testing.

Evaluation of the Precision of Ancestry Inferences in South American Admixed Populations

Ancestry informative markers (AIMs) are used in forensic genetics to infer biogeographical ancestry (BGA) of individuals and may also have a prominent role in future police and identification investigations. In the last few years, many studies have been published reporting new AIM sets. These sets include markers (usually around 100 or less) selected with different purposes and different population resolutions. Regardless of the ability of these sets to separate populations from different continents or regions, the uncertainty associated with the estimates provided by these panels and their capacity to accurately report the different ancestral contributions in individuals of admixed populations has rarely been investigated. This issue is addressed in this study by evaluating different AIM sets. Ancestry inference was carried out in admixed South American populations, both at population and individual levels. The results of ancestry inferences using AIM sets with different numbers of markers among admixed reference populations were compared. To evaluate the performance of the different ancestry panels at the individual level, expected and observed estimates among families and their offspring were compared, considering that (1) the apportionment of ancestry in the offspring should be closer to the average ancestry of the parents, and (2) full siblings should present similar ancestry values. The results obtained illustrate the importance of having a good balance/compromise between not only the number of markers and their ability to differentiate ancestral populations, but also a balanced differentiation among reference groups, to obtain more precise values of genetic ancestry. This work also highlights the importance of estimating errors associated with the use of a limited number of markers. We demonstrate that although these errors have a moderate effect at the population level, they may have an important impact at the individual level. Considering that many AIM-sets are being described for inferences at the individual level and not at the population level, e.g., in association studies or the determination of a suspect's BGA, the results of this work point to the need of a more careful evaluation of the uncertainty associated with the ancestry estimates in admixed populations, when small AIM-sets are used.

Using multiple natural tags provides evidence for extensive larval dispersal across space and through time in summer flounder

Dispersal sets the fundamental scales of ecological and evolutionary dynamics and has important implications for population persistence. Patterns of marine dispersal remain poorly understood, partly because dispersal may vary through time and often homogenizes allele frequencies. However, combining multiple types of natural tags can provide more precise dispersal estimates, and biological collections can help to reconstruct dispersal patterns through time. We used single nucleotide polymorphism genotypes and otolith core microchemistry from archived collections of larval summer flounder (Paralichthys dentatus, n = 411) captured between 1989 and 2012 at five locations along the US East coast to reconstruct dispersal patterns through time. Neither genotypes nor otolith microchemistry alone were sufficient to identify the source of larval fish. However, microchemistry identified clusters of larvae (n = 3-33 larvae per cluster) that originated in the same location, and genetic assignment of clusters could be made with substantially more confidence. We found that most larvae probably originated near a biogeographical break (Cape Hatteras) and that larvae were transported in both directions across this break. Larval sources did not shift north through time, despite the northward shift of adult populations in recent decades. Our novel approach demonstrates that summer flounder dispersal is widespread throughout their range, on both intra- and intergenerational timescales, and may be a particularly important process for synchronizing population dynamics and maintaining genetic diversity during an era of rapid environmental change. Broadly, our results reveal the value of archived collections and of combining multiple natural tags to understand the magnitude and directionality of dispersal in species with extensive gene flow.

Transatlantic invasion routes and adaptive potential in North American populations of the invasive glossy buckthorn, Frangula alnus

BACKGROUND AND AIMS

Many invasive species severely threaten native biodiversity and ecosystem functioning. One of the most prominent questions in invasion genetics is how invasive populations can overcome genetic founder effects to establish stable populations after colonization of new habitats. High native genetic diversity and multiple introductions are expected to increase genetic diversity and adaptive potential in the invasive range. Our aim was to identify the European source populations of Frangula alnus (glossy buckthorn), an ornamental and highly invasive woody species that was deliberately introduced into North America at the end of the 18th century. A second aim of this study was to assess the adaptive potential as an explanation for the invasion success of this species.

METHODS

Using a set of annotated single-nucleotide polymorphisms (SNPs) that were assigned a putative function based on sequence comparison with model species, a total of 38 native European and 21 invasive North American populations were subjected to distance-based structure and assignment analyses combined with population genomic tools. Genetic diversity at SNPs with ecologically relevant functions was considered as a proxy for adaptive potential.

KEY RESULTS

Patterns of invasion coincided with early modern transatlantic trading routes. Multiple introductions through transatlantic trade from a limited number of European port regions to American urban areas led to the establishment of bridgehead populations with high allelic richness and expected heterozygosity, allowing continuous secondary migration to natural areas.

CONCLUSIONS

Targeted eradication of the urban populations, where the highest genetic diversity and adaptive potential were observed, offers a promising strategy to arrest further invasion of native American prairies and forests.

Genetic connectivity and inter-population seed dispersal of Banksia hookeriana at the landscape scale

BACKGROUND AND AIMS

Landscape genetics combines approaches from population genetics and landscape ecology, increasing the scope for conceptual advances in biology. Banksia hookeriana comprises clusters of individuals located on dune crests (geographical populations) physically separated by uninhabitable swales, with local extinctions common through frequent fire and/or severe drought.

METHODS

A landscape genetics approach was used to explore landscape-scale genetic connectivity and structure among geographical populations of B. hookeriana on 18 physically separated dunes located within a heterogeneous landscape of 3 x 5 km. These geographical populations were separated by approx. 0.1 to >1 km of unsuitable intervening swale habitat. Using 11 highly variable microsatellite loci, we utilized a Bayesian approach to identify genetic discontinuities within and between these geographical populations. Population allocation tests were then used to detect inter-dune seed dispersal inferred from assignment of individuals to a source population other than that from which they were collected.

KEY RESULTS

For the modal number of genetically distinct clusters (n = 17 genetic populations), two coincided with the geographical (dune) populations, eight spanned two to four geographical populations, and the remaining seven were spread among various parts of the sampled dunes, so that most geographical populations were spatially defined mosaics of individuals (subpopulations) belonging to two or more genetic populations. We inferred 25 inter-dune immigrants among the 582 individuals assessed, with an average distance between sink and source dunes of 1.1 km, and a maximum of 3.3 km.

CONCLUSIONS

The results show that genetic structure in an apparently strongly spatially structured landscape is not solely dependent on landscape structure, and that many physically defined geographical populations were genetic mosaics. More strikingly, there were physically separated individuals and groups of individuals that were part of the same genetically defined populations. We attribute this mismatch between spatially and genetically defined population structure to the varying closeness of the dunes and the ability of seeds to disperse long distances.

Differentiation among Spanish sheep breeds using microsatellites

Genetic variability at 18 microsatellites was analysed on the basis of individual genotypes in five Spanish breeds of sheep--Churra, Latxa, Castellana, Rasa-Aragonesa and Merino--with Awassi also being studied as a reference breed. The degree of population subdivision calculated between Spanish breeds from F(ST) diversity indices was around 7% of total variability. A high degree of reliability was obtained for individual-breed assignment from the 18 loci by using different approaches among which the Bayesian method provided to be the most efficient, with an accuracy for nine microsatellites of over 99%. Analysis of the Bayesian assignment criterion illustrated the divergence between any one breed and the others, which was highest for Awassi sheep, while no great differences were evident among the Spanish breeds. Relationships between individuals were analysed from the proportion of shared alleles. The resulting dendrogram showed a remarkable breed structure, with the highest level of clustering among members of the Spanish breeds in Latxa and the lowest in Merino sheep, the latter breed exhibiting a peculiar pattern of clustering, with animals grouped into several closely set nodes. Analysis of individual genotypes provided valuable information for understanding intra- and inter-population genetic differences and allowed for a discussion with previously reported results using populations as taxonomic units.