Genetic Distance Measures Research Articles

Evaluation of the R package 'resistancega': A promising approach towards the accurate optimization of landscape resistance surfaces.

Understanding how landscape features affect gene flow has implications for numerous fields including molecular and evolutionary ecology. Despite this, modelling landscape resistance surfaces has remained a significant challenge. The R package resistancega was developed to provide a framework for optimizing landscape resistance surfaces. In this study, we assessed ResistanceGA's ability to recover the true resistance surface under a variety of scenarios, including when the underlying surface: (a) had different levels of spatial autocorrelation and (b) was transformed into a resistance surface using different functional transformations. These scenarios were evaluated with regard to varying sample size and varying levels of variance in the measure of genetic distance. We also assessed the ability of ResistanceGA to identify the true resistance surface among alternative correlated surfaces. In univariate simulations, correlation between the true and optimized resistance surfaces remained high with increased variance in genetic distance, but only when sample size was moderate to high (≥50). Model selection error was also driven by sample size with low type I error when simulations had moderate to high sample sizes, even with moderate to high variance in genetic distance and correlated alternative surfaces. ResistanceGA also performed well in multivariate simulationsbut had more difficulty identifying the true data generating surfaces when genetic data were simulated using an agent-based approach (especially with individual-based genetic data). Overall, our simulations highlight the ability of ResistanceGA to accurately optimize resistance surfaces but also underscore challenges in optimizing landscape resistance surfaces, especially with highly stochastic individual-based data.

A novel quantitative framework for riverscape genetics.

Riverscape genetics, which applies concepts in landscape genetics to riverine ecosystems, lack appropriate quantitative methods that address the spatial autocorrelation structure of linear stream networks and account for bidirectional geneflow. To address these challenges, we present a general framework for the design and analysis of riverscape genetic studies. Our framework starts with the estimation of pairwise genetic distance at sample sites and the development of a spatially structured ecological network (SSEN) on which riverscape covariates are measured. We then introduce the novel bidirectional geneflow in riverscapes (BGR) model that uses principles of isolation-by-resistance to quantify the effects of environmental covariates on genetic connectivity, with spatial covariance defined using simultaneous autoregressive models on the SSEN and the generalized Wishart distribution to model pairwise distance matrices arising through a random walk model of geneflow. We highlight the utility of this framework in an analysis of riverscape genetics for brook trout (Salvelinus fontinalis) in north central Pennsylvania, USA. Using the fixation index (FST ) as the measure of genetic distance, we estimated the effects of 12 riverscape covariates on geneflow by evaluating the relative support of eight competing BGR models. We then compared the performance of the top-ranked BGR model to results obtained from comparable analyses using multiple regression on distance matrices (MRM) and the program STRUCTURE. We found that the BGR model had more power to detect covariate effects, particularly for variables that were only partial barriers to geneflow and/or uncommon in the riverscape, making it more informative for assessing patterns of population connectivity and identifying threats to species conservation. This case study highlights the utility of our modeling framework over other quantitative methods in riverscape genetics, particularly the ability to rigorously test hypotheses about factors that influence geneflow and probabilistically estimate the effect of riverscape covariates, including stream flow direction. This framework is flexible across taxa and riverine networks, is easily executable, and provides intuitive results that can be used to investigate the likely outcomes of current and future management scenarios.

Ancient Origins of the Global Variation in Economic Preferences

This paper shows that contemporary population-level heterogeneity in risk aversion, time preference, altruism, positive reciprocity, negative reciprocity, and trust partly traces back to the structure of the migration patterns of our very early ancestors. To document this pattern, we link differences in preferences between populations to the length of time elapsed since the ancestors of the respective groups broke apart from each other, as proxied by genetic and linguistic distance measures. Preference differences are significantly increasing in ancestral distance in both cross-country regressions and within-country analyses across groups of migrants.

Beyond the landscape: Resistance modelling infers physical and behavioural gene flow barriers to a mobile carnivore across a metropolitan area.

Urbanization affects key aspects of wildlife ecology. Dispersal in urban wildlife species may be impacted by geographical barriers but also by a species' inherent behavioural variability. There are no functional connectivity analyses using continuous individual-based sampling across an urban-rural continuum that would allow a thorough assessment of the relative importance of physical and behavioural dispersal barriers. We used 16 microsatellite loci to genotype 374 red foxes (Vulpes vulpes) from the city of Berlin and surrounding rural regions in Brandenburg in order to study genetic structure and dispersal behaviour of a mobile carnivore across the urban-rural landscape. We assessed functional connectivity by applying an individual-based landscape genetic optimization procedure. Three commonly used genetic distance measures yielded different model selection results, with only the results of an eigenvector-based multivariate analysis reasonably explaining genetic differentiation patterns. Genetic clustering methods and landscape resistance modelling supported the presence of an urban population with reduced dispersal across the city border. Artificial structures (railways, motorways) served as main dispersal corridors within the cityscape, yet urban foxes avoided densely built-up areas. We show that despite their ubiquitous presence in urban areas, their mobility and behavioural plasticity, foxes were affected in their dispersal by anthropogenic presence. Distinguishing between man-made structures and sites of human activity, rather than between natural and artificial structures, is thus essential for better understanding urban fox dispersal. This differentiation may also help to understand dispersal of other urban wildlife and to predict how behaviour can shape population genetic structure beyond physical barriers.

An optimized genomic VCF workflow for precise identification of Mycobacterium tuberculosis cluster from cross-platform whole genome sequencing data

Whole-genome sequencing (WGS) data allow for an inference of Mycobacterium tuberculosis (Mtb) clusters by using a pairwise genetic distance of ≤12 single nucleotide polymorphisms (SNPs) as a threshold. However, a problem of discrepancies in numbers of SNPs and genetic distance measurement is a great concern when combining WGS data from different next generation sequencing (NGS) platforms. We performed SNP variant calling on WGS data of 9 multidrug-resistant (MDR-TB), 3 extensively drug-resistant tuberculosis (XDR-TB) and a standard M. tuberculosis strain H37Rv from an Illumina/NextSeq500 and an Ion Torrent PGM. Variant calls were obtained using four different common variant calling tools, including Genome Analysis Toolkit (GATK) HaplotypeCaller (GATK-VCF workflow), GATK HaplotypeCaller and GenotypeGVCFs (GATK-GVCF workflow), SAMtools, and VarScan 2. Cross-platform pairwise SNP differences, minimum spanning networks and average nucleotide identity (ANI) were analysed to measure performance of the variant calling tools. Minimum pairwise SNP differences ranged from 2 to 14 SNPs when using GVCF workflow while maximum pairwise SNP differences ranged from 7 to 158 SNPs when using VarScan 2. ANI comparison between SNPs data from NextSeq500 and PGM of MDR-TB and XDR-TB showed maximum ANI of 99.7% and 99.0%, respectively, with GVCF workflow while the other SNP calling results showed lower ANI in a range of 98.6% to 95.1%. In this study, we suggest that the GVCF workflow showed the best performing variant caller to avoid cross-platform pairwise SNP differences.

Assessment of genetic diversity of upland rice (Oryza sativa L.) genotypes from North Eastern Hill Region of India

Genetic diversity among 30 upland rice genotypes (Oryza sativa L.) was evaluated using morphological and SSR markers. Roger’s distance was calculated for all the data sets as a measure of genetic distance between accessions. The distance matrices were used to generate a dendrogram based on the UPGMA method. The minimum genetic distance based on morphological marker was 0.04 which was found between Megha Rice-1 and Megha Rice-2. The maximum genetic distance was 0.75 observed between Aizawng New and Majinlu, Aizawng New and Mima-Mitong-Jang, Mibisa and Chakhao Poireiton, Chakhao Poireiton and Vepvu Tsuk with an average of 0.395. The number of alleles per SSR marker varied from 2 to 8, with an average number of 4.286 alleles per locus. Polymorphism information content (PIC) values ranged from 0.062 to 0.799 per locus with an average of 0.425. The minimum and maximum genetic distances based on Roger’s distance, were found to be 0.00 (Bhalum-1 and Bhalum-2) and 0.84 (Aizawng New and Mibisa), respectively. In cluster analysis, morphological and molecular marker-based genetic distance grouped the local landraces together with the improved lines and Gene Bank lines. Correlation analysis between morphological data and molecular data revealed a very poor association (r = 0.051 at p = 0.271). The diverse genotypes revealed from morphological-based dendrogram were the following pairs viz., Aizawng New and Majinlu, Aizawng New and Mima-Mitong-Jang, Mibisa and Chakhao Poireiton, Chakhao Poireiton and Vepvu Tsuk, Buh Pui (Tuirel) and Chakhao Poireiton, Marow and Chakhao Poireiton, Kba Tlang and Majinlu, Lokhumo (Tall) and Chakhao Poireiton. While Aizawng New and Mibisa, IC 583129 and Mibisa, Bhalum-1 and Mibisa, Bhalum-2 and Mibisa, Marow and Mibisa pairs were identified as the diverse genotypes based on molecular dendrogram which may be used as parent for hybridization during further rice improvement.

Limited influence of landscape on the genetic structure of three small mammals in a heterogeneous arid environment

AbstractAimThe complexity and biologically challenging nature of arid landscapes can generate high inter‐ and intra‐species diversity, although these biomes remain poorly studied. We investigated whether prominent geomorphic features in an Australian arid landscape had similar influences on patterns of intra‐specific genetic diversity of three small mammals with different distribution and life history traits. Specifically, we tested (a) whether mountain ranges harbour high diversity and act as refugia, (b) the extent to which ephemeral river systems pose barriers to gene flow or (c) whether environmental differences explain genetic structure in these species.LocationThe topographically complex Pilbara bioregion of the Australian arid zone.TaxaTwo rodents, the Western pebble‐mound mouse, Pseudomys chapmani and the Sandy inland mouse, Pseudomys hermannsburgensis and a dasyurid, Ningaui timealeyi.MethodsWe used maximum parsimony networks of mitochondrial haplotypes and spatially‐explicit Bayesian clustering analysis of microsatellite genotypes to identify historical and contemporary genetic structure in each species. Based on measures of individual diversity and genetic distance, we distinguished ‘hotspots’ and ‘coldspots’ (>1.5 standard deviations from the mean) of genetic diversity and genetic connectivity and assessed their concordance with landscape features. The influence of environmental dissimilarity on observed genetic differentiation was evaluated using generalized dissimilarity modelling.ResultsPatterns of genetic diversity and connectivity were complex, with few consistent patterns across species. Both microsatellite and mitochondrial diversity were high across species, with limited spatial genetic structure. Rivers had the most influence on genetic patterns but were not consistently identified as barriers. Environmental dissimilarity amongst sampling sites had low explanatory power.Main ConclusionsLimited genetic structure in each of the three species suggests that the structurally complex Pilbara landscape remains relatively permeable to species with high dispersal capacity. Additionally, population responses to boom‐bust cycles in arid environments are likely to obscure spatial genetic patterns.

GENETIC VARIATION OF WILD Musa acuminata COLLA FROM INDONESIA

Indonesia is the center of origin and diversity of Musa acuminata Colla, one of the progenitors of cultivated bananas today. However, the genetic variation of wild M. acuminata has not been studied extensively, thus this study aimed to assess the genetic variation of the Indonesian wild M. acuminata based on 10 RAPD (Random Amplified Polymorphic DNA) and 10 ISSR (Inter Simple Sequence Repeats) markers. The genetic properties of 17 populations of wild M. acuminata were analyzed by Popgene 1.32 based on Nei’s unbiased measures of genetic identity and genetic distance. Of the 443 DNA bands produced, 425 (95.94%) were polymorphic. Cluster analysis of the combined data of RAPD and ISSR produced a dendrogram which separated the population of M. acuminata (A genome) from M. balbisiana (B genome), but not from M. schizocarpa (S genome). Nei’s genetic distance of the 17 populations of wild M. acuminata ranged from 0.3676 to 0.1634. The highest genetic distance was observed between M. acuminata var rutilifes (from East Java) and M. acuminata var sumatrana (from West Sumatra). The percentages of polymorphic loci among the 17 populations of M. acuminata ranged from 9.93% to 39.73%. Nei’s gene diversity (h) ranged from 0.041 to 0.1418. M. acuminata var malaccensis population was the most diverse among the researched 17 M. acuminata. The high level of genetic diversity of the wild M. acuminata from Indonesia emphasizes the need for conservation and preservation of the natural population and its use in the banana breeding program.

Fertility and Modernity

We investigate the historical dynamics of the decline in fertility in Europe and its relation to measures of cultural and ancestral distance. We test the hypothesis that the decline of fertility was associated with the diffusion of social and behavioral changes from France, in contrast with the spread of the Industrial Revolution, where England played a leading role. We argue that the diffusion of the fertility decline and the spread of industrialization followed different patterns because societies at different relative distances from the respective innovators (the French and the English) faced different barriers to imitation and adoption, and such barriers were lower for societies that were historically and culturally closer to the innovators. We provide a model of fertility choices in which the transition from higher to lower levels of fertility is the outcome of a process of social innovation and social influence, whereby late adopters observe and learn about the novel behaviors, norms and practices introduced by early adopters at the frontier. In the empirical analysis we study the determinants of marital fertility in a sample of European populations and regions from 1830 t0 1970, and successfully test our theoretical predictions using measures of genetic distance between European populations and a novel data set of ancestral linguistic distances between European regions.

The molecular clock and evolutionary timescales.

The molecular clock provides a valuable means of estimating evolutionary timescales from genetic and biochemical data. Proposed in the early 1960s, it was first applied to amino acid sequences and immunological measures of genetic distances between species. The molecular clock has undergone considerable development over the years, and it retains profound relevance in the genomic era. In this mini-review, we describe the history of the molecular clock, its impact on evolutionary theory, the challenges brought by evidence of evolutionary rate variation among species, and the statistical models that have been developed to account for these heterogeneous rates of genetic change. We explain how the molecular clock can be used to infer rates and timescales of evolution, and we list some of the key findings that have been obtained when molecular clocks have been applied to genomic data. Despite the numerous challenges that it has faced over the decades, the molecular clock continues to offer the most effective method of resolving the details of the evolutionary timescale of the Tree of Life.

Microsatellite-Based Genetic Diversity among Egyptian Sheep Breeds

Sheep represent one of the most important domestic animals in Egypt, where meat and coarse wool production are the basic breeding objectives for Egyptian sheep. Therefore, evaluation of genetic diversity of sheep breeds is necessary for implementing the most suitable breed-region conservation programs. Animals from the three major Egyptian sheep breeds (Ossimi, Rahmani and Barki) were genotyped for 14 microsatellite markers. All loci tested were highly polymorphic. Various measures of genetic variation were calculated. The total observed number of alleles per microsatellite ranged from 6 to 12 for markers MAF65 and OarHH47, respectively. Estimates of effective number of alleles were between 3.11 for TGLA53 and 6.12 for OarHH47. The mean of polymorphism information content was 0.73. Overall gene diversity for all microsatellites analyzed was 0.66, 0.69 and 0.75 for Ossimi, Rahmani and Barki, respectively. For all breeds studied, estimates of observed heterozygosity were significantly lower than the expected heterozygosity. Average observed and expected heterozygosity estimates were 0.55 and 0.67, respectively. Significant departures from Hardy-Weinberg Equilibrium (HWE) due to heterozygote deficiency were observed for all the markers analyzed. The three breeds revealed significant deviation from HWE. The overall indicator of population subdivision (FST) was calculated to be 0.071; pointing out that about 7% of genetic diversity is due to genetic variation between breeds. Estimates of total inbreeding (FIT) and within-breed inbreeding (FIS) coefficients were 0.187 and 0.118, respectively. The estimates of pair-wise genetic differentiation were 0.039, 0.051 and 0.056 for Ossimi-Rahmani, Barki-Rahmani and Ossimi-Barki pairs, respectively. Measures of genetic distance between pairs of sheep breeds ranged from 0.423 to 0.615 for Rahmani-Ossimi and Barki-Ossimi sheep breed pairs. The results obtained in this study may be useful in sustainable breeding programs of Egyptian sheep breeds.

Spatial genetic structure in American black bears (Ursus americanus): female philopatry is variable and relatedto population history.

Previously, American black bears (Ursus americanus) were thought to follow the pattern of female philopatry and male-biased dispersal. However, recent studies have identified deviations from this pattern. Such flexibility in dispersal patterns can allow individuals greater ability to acclimate to changing environments. We explored dispersal and spatial genetic relatedness patterns across ten black bear populations-including long established (historic), with known reproduction >50 years ago, and newly established (recent) populations, with reproduction recorded <50 years ago-in the Interior Highlands and Southern Appalachian Mountains, United States. We used spatially explicit, individual-based genetic simulations to model gene flow under scenarios with varying levels of population density, genetic diversity, and female philopatry. Using measures of genetic distance and spatial autocorrelation, we compared metrics between sexes, between population types (historic and recent), and among simulated scenarios which varied in density, genetic diversity, and sex-biased philopatry. In empirical populations, females in recent populations exhibited stronger patterns of isolation-by-distance (IBD) than females and males in historic populations. In simulated populations, low-density populations had a stronger indication of IBD than medium- to high-density populations; however, this effect varied in empirical populations. Condition-dependent dispersal strategies may permit species to cope with novel conditions and rapidly expand populations. Pattern-process modeling can provide qualitative and quantitative means to explore variable dispersal patterns, and could be employed in other species, particularly to anticipate range shifts in response to changing climate and habitat conditions.

Microsatellite based Genetic Variation among the Buffalo Breed Populations in Pakistan.

IntroductionEight microsatellite loci were used to define genetic diversity among five native water buffalo breeds in Pakistan.Material and MethodsBlood samples (10 mL) from 25 buffaloes of each of the Nili, Ravi, Nili-Ravi, Kundhi, and Azi-Kheli breeds were collected aseptically from the jugular vein into 50 ml Falcon tubes containing 200 µl of 0.5 M EDTA. The phenol-chloroform method was used to extract DNA and the regions were amplified for microsatellite analysis. The eight microsatellite markers ETH10, INRA005, ILSTS029, ILSTS033, ILSTS049, ILSTS052, ETH225, and CSSM66 were analysed.ResultsThe effective number of alleles across all loci was as usual lower than the observed values with a mean value of 2.52 alleles per locus. The overall allele frequency varied from 0.0041 for alleles B, I, and J over respective loci ILSTS052, INRA005, and ILSTS029 to 0.80 for allele H over locus ILSTS029. The average observed and expected heterozygosity values across all polymorphic loci in all studied buffalo breeds were 0.43 and 0.53, respectively. The overall value for polymorphic information content of considered microsatellite markers was 0.53, suggesting their appropriateness for genetic diversity analysis in buffalo. The mean Fis value was 0.13 and all loci except ILSTS049 were found significantly deviated from HWE, most likely due to non-random breeding. The five buffalo populations were genetically less diverse as indicated by a small mean Fst value (0.07). The average gene flow (Nm) indicative for population migration was calculated as 3.31. Nei’s original measures of genetic distance (Ds) revealed ancient divergence of the Nili and Azi-Kheli breeds (Ds = 0.1747) and recent divergence of the Nili and Ravi breeds (Ds = 0.0374).ConclusionThese estimates of genetic diversity were seen to coincide with phenotypic differentiation among the studied buffalo breeds. The present study reports the first microsatellite marker-based genetic diversity analysis in Pakistani buffalo breeds, and might facilitate similar studies in other livestock breeds of Pakistan.

Assessing genetic diversity of wild southeastern North American Vaccinium species using microsatellite markers

Wild species representatives from Northwestern, Central and Southern Florida, and neighboring U.S. states were collected in multiple United States Department of Agriculture (USDA) exploration expeditions and are being preserved at the USDA, Agricultural Research Service, National Clonal Germplasm Repository in Corvallis, Oregon. Germplasm from these southeastern regions of North America is particularly vulnerable to loss in the wild due to encroachment of human development in key habitats and biotic and abiotic stresses from climate change. Fourteen simple sequence repeats (SSRs), previously developed from the highbush blueberry (Vaccinium corymbosum) cultivar ‘Bluecrop’, were used to estimate genetic diversity and genetic differentiation of 67 diploid individuals from three species, including 19 V. elliottii, 12 V. fuscatum, and 35 V. darrowii accessions collected throughout the species’ ranges. Results from our analyses indicated that the samples from each species could be reliably resolved using genetic distance measures with ordination and neighbor joining approaches. In addition, we estimated admixture among these species by using Bayesian assignment tests, and were able to identify a mis-labeled accession of V. darrowii ‘Johnblue’, two mis-classified accessions (CVAC 735.001 and CVAC 1223.001), and four accessions of previously undescribed hybrid origin (CVAC 734.001, CVAC 1721.001, CVAC 1741.001, and Florida 4B CVAC 1790). Allele composition at the 14 SSRs confirmed that Florida 4B CVAC 1790, the donor of low chilling for the southern highbush blueberry, was the critical parent of US 74. Genetic diversity assessment and identification of these wild accessions are crucial for optimal germplasm management and expand opportunities to utilize natural variation in breeding programs.

Determination of genetic relatedness from low-coverage human genome sequences using pedigree simulations.

We develop and evaluate methods for inferring relatedness among individuals from low-coverage DNA sequences of their genomes, with particular emphasis on sequences obtained from fossil remains. We suggest the major factors complicating the determination of relatedness among ancient individuals are sequencing depth, the number of overlapping sites, the sequencing error rate and the presence of contamination from present-day genetic sources. We develop a theoretical model that facilitates the exploration of these factors and their relative effects, via measurement of pairwise genetic distances, without calling genotypes, and determine the power to infer relatedness under various scenarios of varying sequencing depth, present-day contamination and sequencing error. The model is validated by a simulation study as well as the analysis of aligned sequences from present-day human genomes. We then apply the method to the recently published genome sequences of ancient Europeans, developing a statistical treatment to determine confidence in assigned relatedness that is, in some cases, more precise than previously reported. As the majority of ancient specimens are from animals, this method would be applicable to investigate kinship in nonhuman remains. The developed software grups (Genetic Relatedness Using Pedigree Simulations) is implemented in Python and freely available.

Tracking the Genetic Stability of a Honey Bee (Hymenoptera: Apidae) Breeding Program With Genetic Markers.

A genetic stock identification (GSI) assay was developed in 2008 to distinguish Russian honey bees from other honey bee stocks that are commercially produced in the United States. Probability of assignment (POA) values have been collected and maintained since the stock release in 2008 to the Russian Honey Bee Breeders Association. These data were used to assess stability of the breeding program and the diversity levels of the contemporary breeding stock through comparison of POA values and genetic diversity parameters from the initial release to current values. POA values fluctuated throughout 2010-2016, but have recovered to statistically similar levels in 2016 (POA(2010) = 0.82, POA(2016) = 0.74; P = 0.33). Genetic diversity parameters (i.e., allelic richness and gene diversity) in 2016 also remained at similar levels when compared to those in 2010. Estimates of genetic structure revealed stability (FST(2009/2016) = 0.0058) with a small increase in the estimate of the inbreeding coefficient (FIS(2010) = 0.078, FIS(2016) = 0.149). The relationship among breeding lines, based on genetic distance measurement, was similar in 2008 and 2016 populations, but with increased homogeneity among lines (i.e., decreased genetic distance). This was expected based on the closed breeding system used for Russian honey bees. The successful application of the GSI assay in a commercial breeding program demonstrates the utility and stability of such technology to contribute to and monitor the genetic integrity of a breeding stock of an insect species.

GENETICS CHARACTERS INTRAPEDIGRYS TYPES OF CARPATHIAN BREED BEES

GENETICS CHARACTERS INTRAPEDIGRYS TYPES OF CARPATHIAN BREED BEES

Individualism and Corruption: A Cross‐Country Analysis

While the role of cultural norms in determining corruption is well‐explored in the empirical literature, the relationship between a specific aspect of culture, that is, individualism versus collectivism, and corruption is rather unexplored. This paper investigates the relationship between individualism/collectivism and corruption in a large cross‐section of countries. To establish causality, the paper uses an index of historical prevalence of infectious diseases and a measure of genetic distance between the population in a country from that in the United States to instrument the individualism/collectivism variable. We find that more individualistic countries have lower levels of corruption (perception). This relationship is robust to the inclusion of a rich set of control variables and to the use of alternative measures of corruption.

Multiple introductions of Sirex noctilio (Hymenoptera: Siricidae) in northeastern North America based on microsatellite genotypes, and implications for biological control

The invasive woodwasp Sirex noctilio (Hymenoptera: Siricidae) has been moved from Eurasia into regions in the Southern Hemisphere, where extensive tree mortality has occurred in pines (Pinus spp.) introduced for forestry. More recently this woodwasp was found in northeastern North America, where pines are native, and it is a species of concern due to the economic importance of pines. Understanding the genetic diversity of North American S. noctilio points to new areas of inquiry, particularly regarding the ability of parasitic nematodes to sterilize woodwasps, which could provide control methods in the US and/or Canada. We investigated the genetic diversity of 924 S. noctilio from nine populations from New York and Pennsylvania (US), Ontario (CA), and Queensland (AU) using nine microsatellite loci. To avoid inflating the number of populations estimated by Bayesian inference, we measured the full-sibling relationships of woodwasps within 13 trees and removed all but one member of each full-sib family from the genetic analysis, resulting in a final sample size of 741 S. noctilio. Within a tree, on average 39% of woodwasps did not have a full sibling, and there were 5.6 families with at least two full-sibling members per tree. The mean family size across trees was 1.9 when single offspring (i.e., no full siblings) were included. Given the short time span since invasion, variation within North American S. noctilio is likely due to differences among founding genotypes. Genetic analyses support the hypothesis that at least two separate introductions occurred. Within North America, genetic distance measures were greatest between a site in southwestern Ontario and all other sites, suggesting that this population could represent a separate introduction event. Two methods of Bayesian clustering also support this idea; they detected 4 or 5 distinct genetic clusters with little admixture between the southwestern Ontario site and other North American populations. The wasps from Australia, where biological control with nematodes has been successful, showed low genetic diversity and clustered with the southwestern Ontario population in one out of two Bayesian analyses. Within the Ontario subset of samples, high woodwasp activity level (i.e., attack and mortality of trees) was associated with one genetic cluster more strongly than another. Population variation should be taken into account in studies of S. noctilio spread and management within North America.

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples.

The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis). In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples) and computational (petabytes of sequence data) issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances) or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST) scheme). When analyzing empirical data (whole-genome sequence data from 18,997 Salmonella isolates) there are features (e.g., genomic, assembly, and contamination) that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.