Merluccius productus) inhabits upwelling regions in the California Current ecosystem from the Gulf of California to the Gulf of Alaska. In this study, we examined mitochondrial DNA (mtDNA) and microsatellite variation to estimate levels of genetic differentiation of M. productus in relation to the role of oceanographic features as potential barriers to gene flow. Samples were obtained from nine sites spanning a large part of the geographic range of the species, from Puget Sound, Washington to Costa Rica. The microsatellite results revealed three genetically discrete populations: one spanning the eastern Pacific coast, and two apparently resident populations circumscribed to the Puget Sound and the northern Gulf of California . Cytochrome b sequence data indicated that isolation between the Puget Sound and northern Gulf of California populations from the coastal Pacific were recent phenomena . Oceanographic data obtained from the Gulf of California support the hypothesis that permanent fronts within the region, and strong gradients at the entrance to the Gulf of California act as barriers to gene flow. A seascape genetics approach found significant genetic–environment associations, where the daytime sea surface temperature and chlorophyll concentrations were the best predictive variables for the observed genetic differentiation. Considering the potential causes of genetic isolation among the three populations, e.g. spawning areas in different latitudes associated with upwelling processes, oceanographic barriers, asymmetric migration and specialized diet, oceanographic barriers appear to be a likely mechanism restricting gene flow.Determining the relative influence of biotic and abiotic factors on genetic connectivity among populations remains a major challenge in evolutionary biology and in the management and conservation of species. North Pacific hake ( A lare.g., –11) emphe.g., –14. Howe results ,15 Seasc results ,17.M. productus represents a single species distributed from Washington State to Costa Rica. Four populations or stocks have been proposed in this region based upon morphology, behavior and life history traits [M. productus [M. hernandezi [North Pacific hake, also known as Pacific whiting, has a temperate demersal distribution largely restricted to continental shelves and slopes from 45 to 500 m deep . A receny traits –23. One y traits ,20. Two y traits ,20,21. Ty traits . Recentlroductus , there irnandezi –26.i.e. weak isolation-by-distance) reported for some Atlantic and Pacific hake species along coasts [M. merluccius [M. hubbsi [M. bilinearis [M. productus [https://oceancolor.gsfc.nasa.gov). A seascape genetics approach compared genetic heterogeneity between resident and coastal stocks in relation to oceanographic conditions. Finally, we used mtDNA sequence variation to estimate divergence times among these populations.The highly migratory behavior of hake is apparently reflected in broad-scale genetic panmixia or subtle genetic differentiation  issued the permissions for sample collection, and for the North American hake the authorities who issued permission for sample collection were the states of Alaska, Washington, Oregon and California. The species that supporting this study species is not endangered or protected species in according to Comisión Nacional para el Conocimiento y Uso de la Biodiversidad México (CONABIO) We analyzed data obtained in previous studies ,23 consih) and nucleotide (π) diversity, were estimated using Arlequin 3.5 [Mitochondrial DNA sequences were edited and aligned using the ClustalW program implemented in MEGA 6 . Best-fiquin 3.5 .AR) for each locus and location for random subsamples of nineteen genes, the minimum sample size (CR) in the study with HP-RARE v1.0 [Microsatellite data were examined for scoring errors and null alleles using FreeNA . DeviatiARE v1.0 . This meARE v1.0  for moreST outlier approach [ST vs. He to identify loci with unusually high or low FST values [ST , 99.5%confidence intervals and a false discovery rate (FDR) of 0.05 assuming infinite alleles and stepwise mutation models.We used the Fapproach ,48 impleapproach  to detecT values . For thiST = 0.05  = 750), FST = 0.01  and FST = 0.001 . All simulations were performed for eight populations (sample sites). In all cases, 1,000 replicates were run and the percentage of significant outcomes (α = 0.05) for a range of predefined FST values was interpreted as the power of the tests for detecting that level of differentiation. Pairwise sample FST values for both mtDNA (ϕST) and microsatellites (FST) were estimated with Arlequin 3.5 [Simulations in POWSIM v 4.0  were usequin 3.5  using 10quin 3.5 .http://phage.sdsu.edu/~jensen/) [http://clumpak.tau.ac.il/index.html).Mitochondrial DNA and microsatellites data were analyzed for hierarchical population structure with an analysis of molecular variance (AMOVA) using four grouping strategies: (A) assuming all localities as different populations; (B) pooling coastal localities from PS to SBC, with NGC and CR as different populations; (C) pooling all coastal samples and assuming PS and NGC as two different populations; and (D) pooling coastal samples with PS, NGC and CR considered as separate populations. An isolation-by-distance (IBD) analysis was performed on the microsatellite data. Shoreline distances (km) between sampled populations were estimated using Google Earth 4.3 and plotted against pairwise genetic distance . IBD regjensen/)  with 10,jensen/)  implemenjensen/) . To estijensen/) ,57. GrapMigration rates among populations were estimated using microsatellite data with Migrate-n 3.6.5 . We condr) and the simulated sums of squared deviation (SSD). Tajima’s D [Fs [A haplotype genealogy for mtDNA data was obtained using Haploview v4.2 . Inferenjima’s D , and Fu’’s D [Fs  neutraliDivergence times were estimated using BEAST v1.8.0 . We usedThe presence of fronts and hydrographic gradients in the Gulf of California was determined during winter, the main spawning season of hake in that region . Mean FeIn order to relate patterns of genetic variation with environmental heterogeneity, a seascape genetics approach was developed following Selkoe et al.  and Henr2 for each location . In total, oceanographic data from 32 sites were analyzed . Day time (SSTd) and night time (SSTn) sea surface temperatures, PAR , POC (Particulate Organic Carbon), water turbidity (measured as the diffusion attenuation coefficient at 490 nm), and CHL  were obtained from satellite data for each site. Values were extracted from 4-km spatial resolution layers  using SeaDAS v7.4 [2). Averages were estimated for the time of sample collections and the seasonal occurrence of larvae in the study areas. Variables were tested for autocorrelation using Spearman non-parametric correlation tests implemented in PAST [Geographic coordinates of each sampling site   using Cah = 0.858) and low nucleotide diversity (π = 0.003). The NGC sample contained the most haplotypes (20) and the EU sample the lowest number (2), likely due to small sample size  were 350, 393, and 449 base pairs (bp) in length, respectively, resulting in concatenated fragment of 1192 bp. Mitochondrial DNA variation indicated a relatively high degree of global haplotype diversity . Frequencies between 0.01 and 0.10 occurred in 53.1% of the samples, and 43.8% had nulls at < 0.01. Two microsatellite loci developed for European hake (Mmer4 and Mmer20) showed null alleles at frequencies of 0.01 and 0.130, which occurred at almost all localities (Table C in AR = 12.27) and moderately high observed (Ho = 0.85) and expected heterozygosities (He = 0.94). The lowest and highest mean Ho values  were not significantly different , whereas the lowest and highest mean He (0.86 and 0.94) differed significantly . Allelic richness (AR) and number of private alleles (AP) were lowest in the PS sample , while samples from SBC (13.23AR) and the NGC (4.23 AP) had significantly higher values   . LOSITANST = 0.01 with 100% certainty, and with 93% and 95% certainty for FST = 0.001 using Chi-square and Fisher’s exact tests, respectively  was largely panmictic; the SBC sample showed some marginally significant differences from coastal samples, while those from PS and the NGC generally showed significant genetic differentiation from all other locations  while minimizing variance within groups (FSC = 0.602).The AMOVA analysis  indicateA dominant haplotype  was detected in all locations except the NGC and CR. The distinctiveness of hake from the NGC was strongly supported by a haplotype network with 17 private haplotypes separated by three mutational steps from all other locations . Three hBarrier analysis of mtDNA data indicated three potential boundaries within the geographic distribution, all with high bootstrap support. The first was found between PS and the PC locations and the second between these coastal stations and the NGC. A third boundary separated CR from all other northern locations .CT = 0.031; AMOVA results for microsatellite data showed that genetic differentiation among groups was slightly higher when comparing four groups (D) PS, PC, NGC and CR   pattern was evident in the microsatellite data , showing frontal zones to the south and north.February climatology data from the Aqua-MODIS satellite showed considerable differences in SSTd across the Gulf of California, ranging from ~ 25.5 the Gulf . In parthe north . The lowThe transect crossing the frontal zone south of the MAR  showed tTwo oceanographic variables, SSTd and CHL, showed no significant autocorrelation (Table H in M. productus in this study (0.86) exceeded those reported for M. paradoxus [M. albidus [M. australis [M. bilinearis [M. capensis [M. gayi [He = 0.85 to 0.94), comparable to those reported for M. merluccius (0.70–0.96 [M. bilinearis (0.88–0.91) and M. hubbsi (0.84 to 0.87) [The levels of genetic diversity observed with both molecular marker classes were comparable to those reported for other hake species. Mean haplotype diversity of aradoxus ,79, M. a albidus , M. austustralis , M. bililinearis  and M. ccapensis  and was [M. gayi . Similar.70–0.96 –84), M. M. productus and other hakes showing genetic structure indicating both migratory and resident population components [While it is unsurprising to find broad-scale panmixia or weak IBD structure in marine fishes with high dispersal capabilities, there is increasing genetic evidence that some gadoid species (cods and hakes) can colonize different ecosystems, allowing them to adapt and evolve independently ,36. In tmponents ,23,28,29However, there were some discrepancies displayed in the present study between the marker classes. The mtDNA analysis consistently revealed two genetic groups: one at NGC, which was differentiated from all other locations and the other encompassing all sites along the Northeast Pacific coast, including PS. The microsatellite data separated PS as a third distinct population. Estimated divergence times from CYTB sequences , suggestM. bilinearis (Atlantic hake) or another apparently extinct species that entered the Pacific Ocean at the closing of the isthmus of Panama, subsequently speciating into the northern (M. productus) and southern hake (M. gayi) about 1 myr ago in the Mid-Pleistocene [M. asutralis and the clade of Pacific hake ancestral to M. gayi and M. productus was recent (290 kyr) and that of M. gayi and M. productus exceptionally so . The small sample size  from CR produced estimates greater than that but without statistical support. The SBC population (dwarf stock) was considered as an independent stock [Microsatellite results indicate at least three genetically discrete populations exist: two resident stocks (NGC and PS) and the contiguous Pacific coast from Washington State to Costa Rica . Resultsnt stock  but our Studies reporting mesoscale oceanographic features as causal agents for population isolation in the Gulf of California rarely provide concurrent oceanographic data to explain observed genetic structure in different marine species ,33,34,95The efficacy of barriers to gene flow between species with different life history strategies  has been extensively studied inside Gulf of California. Multiple patterns of genetic structure have been reported, including a) panmixia , b) IBD Previous oceanographic surveys ,99, studMultiple studies have reported significant genetic–environmental association in marine fish ,11,106. M. productus. An alternative explanation is that physical barriers that impede genetic flow, such as gradients and oceanographic fronts, are the sufficient to create the observed genetic differentiation of populations living in local heterogeneous environments.Although we found a significant genetic–environment association between PS and NGC hake, the explanation of how these variables keep resident stocks isolated is not simple. We interpreted results from two marker classes  in a neutral population genetics framework. The mitogenome is generally assumed to evolve under neutral or nearly neutral selection . Recent ST outliers in some comparisons among the genetic groups  and four months , were selected for coincidence of hake on the spawning grounds and duration of the planktonic larval stage. Hake are dependent upon upwelling ecosystems (http://cobi.org.mx/wp-content/uploads/2013/10/Reporte-Merluza-lowres-200913.pdf). North Pacific hake from the NGC should be considered a distinct population for assessment and management purposes, since oceanographic barriers in this region likely create some degree of isolation, as indicated for PS hake in the Salish Sea ecosystem [M. hernandezi [Pacific hake is considered a potential fishery resource in Mexican water . Resultscosystem ,23. The cosystem ,88,89. Icosystem . The currnandezi –26 suggernandezi , since aS1 TableMerluccius spp. used to estimate divergence times. Table C. Estimates of null allele frequencies using the FreeNA program (Chapuis & Estoup 2007). Table D. Test of Hardy-Weinberg disequilibrium by locus. A. Probability test. B test when H1 = Heterozygote deficit. Significant values (in red) after Bonferroni correction. Table E. Linkage disequilibrium test. P-value for A pairwise comparison of locus by location and B locus pairs across all locations. Table F. Loci under selection estimated by the random value method FST. Table G. Statistical power analysis for microsatellite data to detect genetic differentiation by using POWSIM v 4.0  [Merluccius productus obtained with BEAST [Table A. Collection dates and geographical coordinates of sampling sites. Table B. Genbank accession numbers for CYTB sequences of lm 2006) . Proportth BEAST . Numbers(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S1 FigFig A. Isolation by distance relationship. Scatter plot of pairwise genetic distance (linearized FST) vs geographic distances of eight microsatellite loci for Merluccius productus showing significant correlation between geographic and genetic distance. Fig B. General patterns of estimates of migration rates between Merluccius productus populations. A. Average estimates of migrants per generation with range in parentheses. Arrows indicates direction of gene flow. B. Depiction of migration rates, with line thickness proportional to migration rate. PC Pacific coast, PS Puget Sound and NGC northern Gulf of California.(DOCX)Click here for additional data file.


It is becoming increasingly difficult to keep information about genetic ancestry separate from information about health, and consumers of genetic ancestry tests are becoming more aware of the potential health risks associated with particular ancestral lineages. Because some of the proposed associations have received little attention from oversight agencies and professional genetic associations, scientific developments are currently outpacing governance regimes for consumer genetic testing.We highlight the recent and unremarked upon emergence of biomedical studies linking markers of genetic ancestry to disease risks, and show that this body of scientific research is becoming part of public discourse connecting ancestry and health. For instance, data on genome-wide ancestry informative markers are being used to assess health risks, and we document over 100 biomedical research articles that propose associations between mitochondrial DNA and Y chromosome markers of genetic ancestry and a wide variety of disease risks. Taking as an example an association between coronary heart disease and British men belonging to Y chromosome haplogroup I, we show how this science was translated into mainstream and online media, and how it circulates among consumers of genetic tests for ancestry. We find wide variations in how the science is interpreted, which suggests the potential for confusion or misunderstanding.We recommend that stakeholders involved in creating and using estimates of genetic ancestry reconsider their policies for communicating with each other and with the public about the health implications of ancestry information.The online version of this article (doi:10.1186/s12920-016-0240-3) contains supplementary material, which is available to authorized users. While genetic ancestry tests marketed to consumers do not currently claim to provide information about disease risk, it is becoming increasingly difficult to keep information about ancestry separate from information about health. In this article, we consider the recent and unremarked upon growth in genetic tests and biomedical studies linking markers of genetic ancestry to various diseases and medical conditions. These developments are becoming part of public discourse connecting ancestry and health, but because genetic testing companies, oversight agencies, and professional genetic associations have largely treated health and ancestry genetic tests as independent and distinct, little guidance is available to help consumers understand and interpret the reported connections between genetic ancestry and disease risk. Consequently, when such findings circulate in the public realm, consumers learn that there may be health risks tied to their genetic ancestry even though companies do not report those associations. There is therefore potential for confusion or misunderstanding that is problematic for both consumers and the scientific community. We argue that the various stakeholders in genetic ancestry testing need to reconsider what they communicate about the health implications of ancestry information, both to the public and to each other, in order to effectively bridge the gap that currently exists in policies and consumer guidance regarding genetic tests for ancestry and health.Genetic ancestry tests were first marketed directly to consumers in 2000, for the purpose of reconstructing genealogies and investigating personal genetic heritage. They quickly became the most popular of all consumer genetic testing services, and more than three million individuals have reportedly purchased these tests to date , 2. OverHowever, recent developments demonstrate that the boundary between ancestry-related and health-related genetic testing is more porous than previously suggested , and it This blurring of the line between genetic ancestry and health accentuates the gaps that currently exist in policy and in the available guidance for consumers because little attention has been given to the health implications of genetic ancestry testing. However, as others have noted, it may become common for consumers to share their ancestry test results or ancestry-related estimates of disease risk with their physicians, expecting such information to inform their healthcare decisions and improve their quality of care , 14. It Thus, it is critical that we recognize and address the increasingly porous boundary between genetic tests for ancestry and health because (1) genetic ancestry tests can provide information that has consequences for health decision-making, (2) test-takers may have unrealistic expectations about the scientific and medical certainties offered by the tests they have purchased, (3) many physicians are not prepared to interpret and apply the genetic test results that their patients may bring into the clinic, and (4) better guidance for consumers is needed to ensure that health-related information from genetic ancestry tests is interpreted and applied in valid ways. This is especially important because, as we show in the next section, scientific and biomedical studies have been drawing ever more connections between ancestry and health, and there is evidence that these connections are beginning to affect consumer interpretations of their genetic ancestry test results.Genetic ancestry plays an important role in contemporary biomedical science. Medical genetic studies, for instance, commonly use ancestry inferences derived from autosomal markers  to control for population stratification, a practice that underpins the now routine reporting of population-specific or ancestry-specific estimates of disease risks and drug response in genetic epidemiology , 22. FarOver the last decade, hundreds of biomedical studies have been published that suggest that certain mitochondrial DNA (mtDNA) and Y chromosome variants (and the haplogroups defined by those variants) are associated with an increased risk of disease and other health complications . These vP-values that have not been corrected for multiple comparisons), so some of the reported haplogroup-disease associations are almost certainly false positives. Other researchers have also drawn attention to these problems [It is important to note that the quality of studies reporting associations between mtDNA/Y chromosome haplogroups and disease susceptibility is quite variable. Some haplogroup-disease associations are supported by multiple independent studies with rigorous statistical designs, but many others are not. The biomedical literature includes a large number of studies that suffer from small sample sizes, inappropriate controls for population stratification, and/or problematic statistics  than other British men, with haplogroup I being the most significant predictor of CAD after HDL cholesterol and lipid-lowering treatment [NHS Choices, after the study was published — albeit to argue that this information was not of immediate use for tackling CAD in the UK because, among other reasons, “men are unlikely to know their specific haplogroup, so are unlikely to know whether they may be at increased risk of CAD” [Lancet study  in online forums , and a Principal Scientist at 23andMe blogged about the study, expressing skepticism about the study’s conclusions and offering an alternative analysis using his company’s data  and health risks? How can those who communicate about the relevant science  achieve maximum clarity regarding the potential health implications of genetic ancestry (or the lack of them), and make effective use of the published critiques of the putative links between uniparental haplogroups and health risks , 28? ShoThe ASHG or another respected professional genetics society should organize a roundtable to bring the various stakeholders together to produce authoritative guidance that will inform and benefit consumers, and help create a set of standards for the industry to follow. This guidance should make clear what we can and cannot know from genetic ancestry testing, and provide guidance regarding the accuracy and reliability of associations between genetic markers and health risks. Industry representatives, consumer advocates, policy and legal advisors, biomedical researchers, social scientists, and regulators should all be involved in drafting this guidance.Consumer advocates, scientific organizations, companies, science journalists, and government agencies should play a role in making this information available to consumers.Genetic ancestry testing companies should report only associations between genetic markers and diseases/medical conditions that have been scientifically validated. They should also provide information about the limitations of their tests  and incMedical schools and continuing medical education (CME) programs should discuss the potential health implications of genetic ancestry information so that physicians can help their patients to interpret and contextualize their genetic testing results.Policy-makers and government agencies may wish to reconsider current oversight regimes for direct-to-consumer genetic testing in light of the increasingly porous boundaries between tests for health and ancestry.To help address the issues raised here, we make five recommendations for stakeholders in consumer genetic testing to consider:Our recommendations are aimed at encouraging novel and timely interventions into ongoing debates about direct-to-consumer genetic tests, especially since the US FDA, European Commission, ASHG, and high-profile ancestry testing companies are all considering scientific, ethical, and regulatory issues regarding health-related genetic testing. Now is the time to start bridging the gap in our current approaches to health and ancestry genetic testing.


Carcinus maenas) in eastern North America. Green crab populations in eastern North America are associated with two independent invasions, previously shown to consist of distinct northern and southern ecotypes, with a contact zone in southern Nova Scotia, Canada. Using a RAD‐seq panel of 9,137 genomewide SNPs, we detected 41 SNPs (0.49%) whose allele frequencies were highly correlated with environmental data. A principal components analysis of 25 environmental variables differentiated populations into northern, southern, and admixed sites in concordance with the observed genomic spatial structure. Furthermore, a spatial principal components analysis conducted on genomic and geographic data revealed a high degree of global structure (p < .0001) partitioning a northern and southern ecotype. Redundancy and partial redundancy analyses revealed that among the environmental variables tested, winter sea surface temperature had the strongest association with spatial structuring, suggesting that it is an important factor defining range and expansion limits of each ecotype. Understanding environmental thresholds associated with intraspecific diversity will facilitate the ability to manage current and predict future distributions of this aquatic invasive species.Genetic‐environment associations are increasingly revealed through population genomic data and can occur through a number of processes, including secondary contact, divergent natural selection, or isolation by distance. Here, we investigate the influence of the environment, including seasonal temperature and salinity, on the population structure of the invasive European green crab ( Green crab are highly tolerant of a wide range of temperatures and salinities, encompassing a 25°C range in sea surface temperatures in their native range and a range in salinity tolerance of 4–52‰ in adults   and unmeasured environmental variables as latent factors. We set K = 2 based on the results of previous discriminant analyses of principal components (DAPC) and STRUCTURE . We used the R function Jombart, . We usedadegenet to evaluate environmental similarity among our sample locations using all environmental variables. We then used redundancy analyses (RDA) and partial redundancy analyses (pRDA) to account for the geographic autocorrelation of each site for both the outlier and nonoutlier locus allele frequencies using vegan to select which environmental variables best explain the genetic structure. Analyses of variance  were used to assess the significance of each environmental parameter within the RDA. The ordistep function, a stepwise permutational ordination method, was used with 1,000 permutations to evaluate the environmental variables and create a model which best explained the spatial distribution of our genotype data.Next, we used a principal components analysis (PCA) in FST values as the response value and least‐cost distances calculated in marmap as the explanatory variable using the MRM function with 10,000 permutations in the ecodist R package  relationship as a null hypothesis to a genetic‐environment association controlling for geographic distances using multiple regression on distance matrices  for each locus and recombination rate r (0.5).We used the R package  Palumbi , where d2.5blastn algorithm and queried multiple databases including SWISSPROT and NCBI nucleotide/protein collections with an E‐value cutoff of 1e−4 and otherwise default parameters.We attempted gene ontology using Blast2GO 3.3.5 .Of the 9137 SNPs analyzed from Jeffery, DiBacco, Van Wyngaarden et al. , LFMM cl3.2r2 = .635, p = .003; Figure A PCA of all environmental parameters at each sampling location resulted in the clustering of sampling locations that mirrored the genetically determined northern, admixed, and southern population clusters found by Jeffery, DiBacco, Wringe et al.  Figure . The top3.3p = .001) and little local structure (p = 1.0) as noted by the extreme positive eigenvalue that explained 66% of the observed structure  were significantly associated  and nonoutlier SNP genotype distribution  selected by the ordistep function . Subsequent analyses of variance revealed that WinSST was the only significant predictor of both the nonoutlier and outlier variation . Variance partitioning based on the outlier RDA models revealed that the environment explains 43.95% and geography explains 9.35% of the variation in genetic structure, with the remaining variance explained by the interaction between environment and geography.The relationship between WinSST and observed population‐genetic structure was also highlighted by the redundancy analysis, which revealed WinSST to be the most significant environmental variable associated with the outlier  largely driven by inter‐regional comparisons. However, an MRM model including winter sea surface temperature had a stronger relationship with pairwise FST values  suggestive of this environmental variable's role in possibly constraining gene flow.Using multiple regression on distance matrices, we observed a significant isolation‐by‐distance relationship among populations (3.4SD) from the southernmost sites, while the cline width was estimated to be 299.22 ± 666.88 km based on outlier allele frequencies. The 10 clinal nonoutlier loci estimated the cline center at 955 ± 145.83 km and a cline width of 477.07 ± 793.07 km. Neither the cline centers (p = .62) or the cline widths (p = .56) were significantly different between nonoutlier and outlier loci when correcting for sample size. Nonoutlier loci estimated the standard deviation of parent‐offspring distance to be 82.31 ± 127.71 km (mean ± SD). The standard deviation of parent‐offspring distance was estimated to be 138.50 ± 319.95 km based on the clinal environmental outliers.Twenty‐four of 41 outliers (58.5%) were considered clinal based on their log‐likelihood distribution, while only 10 of the randomly selected 100 nonoutlier loci (10%) were considered clinal Figure . The cen3.5Portunus trituberculatus at an e‐value of 1.6e−20. TLRs are cell‐surface receptors which aid in the innate immune system  from the decapod 4Here, we present results consistent with the environmentally associated distribution of secondary contact punctuated by an environmental gradient among two independent invasions of green crab along the coast of eastern North America. Our multivariate analyses reveal winter sea surface temperature to be the best predictor of spatial structure after accounting for multicollinearity among environmental predictors. Similarly, multiple regression on distance matrices revealed a stronger isolation‐by‐environment relationship than a simple isolation‐by‐distance relationship, suggesting that the environment is more of a constraining influence on gene flow than geographic distance among populations  recently introduced (<60 years) into the native habitat of the California Tiger salamander , form a strong hybrid zone with F1 hybrids showing increased fitness relative to either pure parent species     are rare, and to our knowledge, no studies exist that integrate genomic data and fine‐scale environmental data in an invasive species with multiple invasions  are most affected by this minimum temperature. Reproductive timing varies across the invasive range, with mating typically occurring in the summer or early fall  along a similar range in eastern North America. However, this clinal model assumes balance between natural selection and dispersal rate, which may not be at equilibrium in the highly dynamic green crab system. Similarly, changes in linkage disequilibrium and allele frequencies over time will inevitably alter the estimated cline width, and therefore, we consider our model an approximation of contemporary rates of dispersal.The same model was recently implemented by Van Wyngaarden et al.  to studyThe single clinal outlier locus that aligned to a reference sequence corresponded to a Toll‐like receptor (TLR) gene which is part of the innate immune system (Li et al., 4.4Understanding the broad‐ and fine‐scale environmental factors that influence an invasive species’ distribution on a temporal scale and at different life stages is necessary to model the range expansion and ecological or economic impacts of that species over time (Cosham et al., 4.5Although we were able to detect genetic‐environment associations between a small proportion of outlier loci and season temperatures, we cannot conclude which processes have led to this observation without data from the crabs’ native range, a well‐annotated genome, and a comprehensive understanding of the temporal dynamics of the green crab system. As mentioned, it is likely green crab in their native range are adapted to a range of ocean temperatures from North Africa to Norway, and may show both genetic variation and plasticity in thermal tolerances. The recent introductions of different lineages to North America, and even more recent secondary contact between lineages, appear to simply reflect the native population structure, and a clinal gradient in structure is maintained by a corresponding gradient in temperature, in particular winter bottom temperature. Data from populations in the native range at different latitudes could aid in determining how seasonal minima, such as winter bottom temperature, might also constrain population structure in a naturally replicated system (see Schmidt et al., 4.6The population structure of two green crab ecotypes and hybrid populations in the Northwest Atlantic Ocean is driven on a broad scale by a gradient in seasonal temperature minima, leading to reduced gene flow and constraints in the ranges of two distinct ecotypes which evolved along a latitudinal gradient in Europe. Winter sea surface temperature was observed to show the strongest relationship with crab genetic spatial structure, suggesting that the continued expansion of the separate ecotypes is limited by the minimum temperature each year. This broad understanding of how the environment limits the genetic spatial structure of invasive green crab can be implemented in models predicting the spread and impacts of this species over time, and allow for projections of range expansion under climate change scenarios.https://doi.org/10.5061/dryad.bq27d.Data for this study are available from the Dryad Digital Repository:  Click here for additional data file.


Parrotia subaequalis is an endangered palaeoendemic tree from disjunct montane sites in eastern China. Due to the lack of effective genomic resources, the genetic diversity and population structure of this endangered species are not clearly understood. In this study, we conducted paired-end shotgun sequencing (2 × 125 bp) of genomic DNA for two individuals of P. subaequalis on the Illumina HiSeq platform. Based on the resulting sequences, we have successfully assembled the complete chloroplast genome of P. subaequalis, as well as identified the polymorphic chloroplast microsatellites (cpSSRs), nuclear microsatellites (nSSRs) and mutational hotspots of chloroplast. Ten polymorphic cpSSR loci and 12 polymorphic nSSR loci were used to genotype 96 individuals of P. subaequalis from six populations to estimate genetic diversity and population structure. Our results revealed that P. subaequalis exhibited abundant genetic diversity  and high genetic differentiation , and characterized by a low pollen-to-seed migration ratio (r ≈ 1.78). These genetic patterns are attributable to its long evolutionary histories and low levels of contemporary inter-population gene flow by pollen and seed. In addition, lack of isolation-by-distance pattern and strong population genetic structuring in both marker systems, suggests that long-term isolation and/or habitat fragmentation as well as genetic drift may have also contributed to the geographic differentiation of P. subaequalis. Therefore, long-term habitat protection is the most important methods to prevent further loss of genetic variation and a decrease in effective population size. Furthermore, both cpSSRs and nSSRs revealed that P. subaequalis populations consisted of three genetic clusters, which should be considered as separated conservation units. Parrotia C. A. Mey. (Hamamelidaceae) contains just two extant species, Parrotia persica (DC.) C. A. Mey. and P. subaequalis (Hung T. Chang) R.M. Hao & H.T. Wei , deciduous tree  with bisexual and wind-pollinated flowers that turn into woody capsules, dispersed by gravity and water  on the hillsides and along canyons in subtropical China, where it is presently found in only about 8 known populations from disjunct/montane sites in Anhui, Jiangsu, Zhejiang and Henan provinces of eastern China   and low within-population diversity 0.11 for Nei's gene diversity. However, the dominant nature of ISSR markers precludes estimating small-scale spatial genetic structure and inbreeding coefficient FIS as well as inferring evolutionary/demographic history which are necessary to guide management practices aiming at avoiding inbreeding and assessing future risk of erosion of diversity  datasets are less expensive and more efficient  Table , respectP. subaequalis individuals. Firstly, a total of 3 μg of the purified genomic DNA was used for each library construction. Short-insert (500 bp) paired-end libraries were generated in accordance with the Illumina standard protocol. Two libraries with different indexes were then pooled together and sequenced in one lane of HiSeq 2500 platform  at Beijing Genomics Institute . For each individual, about 2.5 Gb of raw data were obtained with pair-end 125 bp read length.Two next-generation sequencing (NGS) DNA libraries were prepared using the low-coverage shotgun sequencing of the whole genome of two P. subaequalis were assembled into whole chloroplast genomes using a combination of both reference guide and de novo assembly approaches  using CLC-quality trim program clc assembly cell package (http://www.clcbio.com/products/clc-assembly-cell/). Then, for the reference-based mapping, we aligned the trimmed reads to the reference chloroplast genome of Liquidambar formosana Hance (KC588388Genbank ID: ) using bowtie software  under the following parameters: minimum contig length = 200 bp, bubble size = 98 bp, deletion and insertion costs = 3, mismatch cost = 2, length fraction = 0.9, and similarity fraction = 0.8. All the assembled contigs were aligned and ordered with respect to the reference cp genome of L. formosana through blast. Lastly, the top-quality reads were again mapped to the draft cp genomes to yield the complete cp genomes of two P. subaequalis individuals that were visualized in geneious v10.0.5 (http://www.geneious.com). To confirm accuracy, the four junctions between LSC/IRs and SSC/IRs of the two cp genomes of P. subaequalis were validated via specific primers as described previously .Gene annotation of the two cp genomes of misa perl script  and Vitis vinifera (FM179380Genbank ID: ) as references. After filtering the cp- and mitochondria-contained contigs, potential polymorphic nSSRs were identified using CandiSSR  within the cp genomes, we applied the P. subaequalis cp genome using mafft v7. The sequence divergence for a specific region between two cp genomes was quantified as the nucleotide variability (Pi) and estimated using dnasp v5.10  > 0 and an aligned length > 200 bp were extracted to explore the divergence hotspot regions in http://sourceforge.net/projects/primer3/files/primer3/) with the following parameters: 18–25 base pairs (bp) in length, PCR product size of 100–300 bp, annealing temperature of 50°-65°C, and a GC content of 40–60%. After that, according to our potential polymorphic SSRs selection principles, we finally selected 20 chloroplast and 30 nuclear candidates of polymorphic SSRs primer pairs to do the further trials  polPrimer pairs were initially screened for amplification success and effectiveness using one randomly selected individual. The polymorphism of each locus was performed then by selecting 12 individuals from six representative geographically distant populations . PCR amplifications were performed on a GeneAmp9700 DNA Thermal Cycler  following the standard protocol of the AmpliTaq Gold 360 Master PCR kit  in a final volume of 15 μL, which contained 1 μL of template DNA, 7.5 μL AmpliTaq Gold 360 Master Mix , 5.5 μL of deionized water, and 0.5 μL of forward and reverse primers (10 μM). And the procedure of PCR was 5 min initial denaturation at 95°C, 35 cycles of 45 s at 95°C, 30 s annealing at optimal primer temperature Tables , S8 and Fragment lengths of PCR products were analyzed on an ABI 3730XL DNA Analyzer  with GeneScan LIZ 500 as an internal reference (Applied Biosystems). Electrophoresis peaks scoring and alleles identification were assayed by using GeneMarker v2.2.0 . All primer sequences obtained from this study were submitted to GenBank Tables , S8. In NA) and unbiased haploid diversity index (hd) using the program GenAlEx v6.41 , the number of effective alleles (NE) using program contrib v1.02  implies that genealogically closely related haplotypes are geographically close to each other, indicating the presence of phylogeographical structure . Analysis of molecular variance (AMOVA) was performed to partition the total genetic variance among populations using the arlequin v3.11 , allelic richness (AR), expected heterozygosity (HE), observed heterozygosity (Ho), total genetic diversity (HT), average genetic diversity within populations (HS) and polymorphism information content (PIC) were calculated by using cervus v2.0  by using structure v2.3.4  to determine the maximum value of posterior probability of the data [lnp(D)]  that corresponds to the change of lnp(D) between consecutive K values  was identified as the one that maximized lnp(D) and/or ΔK. Analysis of molecular variance (AMOVA) was performed to partition the total genetic variance among populations using the arlequin v3.11.For each nSSR locus, the number of alleles  and geographic distance among sampling locations (isolation-by-distance effect) using a Mantel test  using a modified form of an equation of Ennos -1)−2(1/RST(c)-1)]/(1/RST(c)-1), where mp and ms correspond to the pollen migration rate and the seed migration ratio, RST(n) is the nuclear RST and RST(cp) is the cytoplasmic RST.We tested for a correlation between pairwise population genetic distance  and P. subaequalis (SJD), respectively. The de novo assembly generated 359,167 contigs with an N50 length of 554 bp for P. subaequalis (TX) and 274,639 contigs with an N50 length of 580 bp for P. subaequalis (SJD) . Four junction regions in each chloroplast genome were validated using PCR-based sequencing  were produced for ng Table . These sP. subaequalis were 159,280 bp  and 159,324 bp in length   with a length of 26,211 in TX and 26,212 bp in SJD, separated by one large single-copy (LSC) region of 87,927 bp in TX and 87,968 bp in SJD and a small single-copy (SSC) region of 19,031 bp in TX and 18,932 bp in SJD. The gene map is shown in Figure atpF, ndhA, ndhB, petB, petD, rpl2, rpl16, rpoC1, and rps16) and six tRNA genes  had a single intron, while three protein-coding genes  possessed two introns : 985 bp; P. subaequalis (SJD): 985 bp; L. formosana: 1,609 bp).The whole cp genome sequences of two ns Table . All theP. subaequalis were calculated for the 40 regions showing single-nucleotide polymorphisms (SNPs). The overall average Pi value was 0.00144. For 20 protein coding regions, Pi values ranged from 0.00015 (ycf2) to 0.00407 (psaC), among which psaC, rps4, cemA, petD, ycf1, ndhD, ndhG, ndhI, and ndhA regions showed remarkably higher Pi values (Pi > 0.00144). For the 17 intergenic spacer, Pi-values ranged from 0.00055 (ycf1-trnN) to 0.00369 (ccsA-ndhD), of which matK-trnK, trnT-psbD, trnS-psbZ, psbZ-trnG, psaJ-rpl33, rps18-rpl20, and ccsA-ndhD regions with Pi values exceeding the average value. Besides, for the three intron regions, Pi-values varied between 0.00094 (intron ndhA) and 0.00136 (intron rpoC1)  values in the two cp genomes of ) Figure .P. subaequalis cp genomes. The mononucleotide A/T repeat units were found to be the most abundant, with 49 in P. subaequalis (TX) and 54 in P. subaequalis (SJD)  and P. subaequalis (SJD) contained 71 and 78 SSRs, respectively, of which 30 were potential polymorphic cpSSRs (Table NA) per locus varied from 2 to 6, while the the unbiased haploid diversity (Hd) per locus ranged from 0.392 to 0.752 , 20 dinucleotide , 4 trinucleotide , 8 tetranucleotide , and 3 pentanucleotide  repeats were detected within the two D) Table . Most SSD) Table . The cp Rs Table . Based oRs Table . FinallyRs Table  were genP. subaequalis candidates of polymorphic nSSR loci with an average length of 17 bp were detected in the nuclear genome. Among these loci, di-nucleotide repeats (DNRs) were the most abundant repeat type , followed by tri- , tetra- , penta-  and hexa-nucleotide repeats  (Table v > 5%), while significant linkage disequilibrium was observed between PasN24 and PasN14. These three loci were excluded from subsequent analyses. Four of the remaining 12 loci deviated significantly from HWE expectations (P < 0.001) in some populations  as a result of heterozygote deficiency. In total, the 12 polymorphic SSRs yielded 64 alleles with an average of 5.33 alleles and a range of 2 to 14 alleles (NA) per locus. Besides, the observed (HO) and expected (HE) heterozygosity per locus over all populations ranged from 0.073 to 0.990 (with an average of 0.520) and from 0.071 to 0.868 (with an average of 0.558), respectively   Table . Followi%) Table  were genHcp = 0.832 at species level. The haplotypic diversity per population (Hcp) ranged from 0.520 (SJD) to 0.862 (HBS), with an average of 0.713 , indicating the existence of a marked phylogeographical structure at this scale. The AMOVA partitioned genetic variation into 65.45% among six populations and 34.55% was contributed by differences within populations  among loci was 0.478, with a range of 0.067–0.740; while the total genetic diversity over all populations (HT) ranged from 0.071 to 0.865 and averaged 0.559 , being lowest in population HBS  and highest in population TX  = 0.331, P < 0.001). The hierarchical AMOVA revealed that 16.39% of the total variation was attributed to differences among six populations and that 83.61% was contributed by differences within populations . Using the nSSR-derived RST(n) value of 0.331 across the six populations surveyed, and their corresponding value for cpSSR markers, RST(cp) = 0.652, the pollen/seed migration ratio (r) was calculated as 1.78, indicating a slightly higher level of pollen flow as compared to seed flow. structure yielded the highest likelihood when samples were clustered into three groups (K = 3). However, all individuals were clearly assigned to non-empty groups when K values ranged from 2 to 4  and the nine genes . These regions of the cp genome can be further used to evaluate maternally inherited genomic diversity for phylogeographic and population genetic studies of P. subaequalis. Moreover, based on a comparative analysis of two cp genomes of P. subaequalis, we identified a total of 30 candidates of polymorphic cpSSR loci, for which 20 primer sets were designed to evaluate their amplification and polymorphism in the initial screening with the 12 individuals from the six populations. Of the 20 primer pairs, 10 yielded clear and polymorphic amplification products, confirming that plastome assembly from low coverage genomic sequencing is an ideal method for the development of cpSSR markers. Notably, the 10 polymorphic SSR markers could also be amplified in other five Hamamelidaceae species, indicating that they could be used as cross-species markers within Hamamelidaceae.In the last decade, next-generation high-throughput sequencing technologies have allowed producing genomic resources in a rapid and cost-effective way Mardis, . Here, is Figure . The cp s Figure . The genP. subaequalis to construct the sequencing library, based on the two assembled sequences, we identified a total of 576 candidate polymorphic SSRs by means of the program CandiSSR. In agreement with previous reports from many other plant taxa  were proved to be polymorphic among 96 individuals from the six populations. Such high success ratios indicate that the application of next-generation sequencing (NGS) technologies for SSRs development is possible to develop large numbers of polymorphic SSR markers. For population genetic analyses in P. subaequalis, 13 loci seem to provide a good resource to explore population genetic diversity and structure (see below). Our tests of interspecies transferability of the 15 SSRs from P. subaequalis to other five Hamamelidaceae species yielded transfer success rates of 47% (7) for all species, suggesting an intermediate level of cross-species transferability.Genomic SSRs have traditionally been isolated by hybridizing repeat-enriched molecular probes in genomic libraries  as compared to other Chinese endemic flowering plant taxa presented in previous studies by using similar markers  is at the lower end of the range reported for 93 seed plant species  (0.652) estimated for P. subaequalis, its correspondingly low r estimate likely implies restricted pollen flow in a low-seed disperser rather than a significant role of seed flow in a species for which pollen dispersal is limited. In fact, nSSR-derived RST(n) value of 0.331 suggest a substantial amount of population isolation. Therefore, the reduced levels of contemporary intersite gene flow via pollen and seed agrees well with the second assumption. The above results also accord with field observations indicating that (1) the small (ca 4–5mm) seeds from the two-seeded capsules are ballistically dispersed for a short distance (≤ 18 m)  is comparable to average nSSR-based HS  in endemic species (HS = 0.42), as reviewed by Nybom  are more likely due to the historical random loss of alleles, possibly following habitat fragmentation, rather than inbreeding. Likewise, historical processes such as long-term isolation and/or habitat fragmentation may have also contributed to the geographic differentiation of P. subaequalis  and SJD (K = 4) were assigned to a separate cluster, respectively  of genomic DNA from two individuals of P. subaequalis. Our results revealed that P. subaequalis exhibits abundant genetic diversity  and high genetic differentiation; e.g., cpSSRs: RST(cp) = 0.652; nSSRs: RST(n) = 0.331], and is characterized by a low pollen-to-seed migration ratio (r ≈ 1.78). These genetic patterns are attributable to its long evolutionary histories and reduced levels of contemporary intersite gene flow via pollen and seed. In addition, lack of isolation-by-distance pattern, together with the strong population subdivision in both marker systems, suggests that long-term isolation, and/or habitat fragmentation as well as genetic drift may have also contributed to the geographic differentiation of P. subaequalis. Therefore, long-term habitat protection is the most important means to prevent further losses of genetic variation and a decrease in effective population size. Moreover, the three genetic clusters of P. subaequalis revealed by both cpSSRs and nSSRs should be considered as separate conservation units in any program, allowing for the long-term preservation of its genetic resources.We further used 10 polymorphic cpSSR and 12 polymorphic nSSR loci to investigate the genetic diversity and population structure for six populations sampled across the range of Y-YZ, Y-XQ, and Z-SW conceived the study; Y-YZ analyzed the data and wrote the manuscript; ES and Z-PY helped to collect samples; Y-YZ and ES performed the experiment; Z-PY and Q-FG provided useful suggestions on the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In the past decade, the ability to generate whole-genome sequences has provided geneticists with a view of the astonishing breadth of genetic variation. This, in theory, means we should be able to identify the specific differences in DNA sequence that lead to an inherited phenotype, including disease states. But this wealth of new information has revealed perhaps the most fundamental challenge for geneticists since Mendel. While we understand that phenotypes are influenced by genetic variation, we do not yet know how to interpret individual genome sequences, and, therefore, we cannot predict which genetic variants are linked to which phenotypes. Indeed, the term “missing heritability” was coined to highlight the fact that in natural populations the genes or genetic elements associated with complex traits explain only a small proportion of the phenotypic variation in these traits.In stark contrast, controlled crosses of model organisms have generated a wealth of information about the genetic basis of phenotypes. From broad associations of genomic regions with traits, to individual polymorphisms that act by well understood mechanisms, geneticists have been remarkably successful in revealing the impact of genetic variation on phenotype. Applications as diverse as targeted drug therapy and dramatic improvements in agricultural output have been enabled by our understanding of genetics. But it remains a significant challenge to transfer this understanding to natural populations.To bridge the gap between natural populations and experimental systems, experimental systems need to incorporate more of the complexity of natural populations. This has given rise to a burst of creativity in the design of genetic reference populations. The basic idea is simple: combine the strength of the experimental system, where the genetic composition can be replicated, with the genetic diversity of the target population. Rather than choose two inbred lines or two phenotypically divergent individuals as founders of a genetic reference panel (recombinant inbreds), choose eight, or 25. Using multiple lines as founders of a set of inbred lines whose haplotypes can be replicated has been referred to as Interconnected populations multi-parent, advanced-generation inter-cross design, Complex Cross, and multi-parental RIL. We are choosing to refer to this broad set of genetic reference panels as multi-parent populations (MPP).GENETICS and G3 in 2012 . Systematic monitoring of progress with the mouse collaborative cross has provided a window into the impact of drift on the genomes . The first set of papers describing these strains was published in Arabidopsis , sunflower . These issues of GENETICS and G3 feature MPPs of sorghum  rely on data sharing. One of the benefits to working with a reference panel is the ability to leverage data collected in different ways, for different purposes. Our journals have long had policies for reagent and data sharing that reflect the values of our community, and this is evident in these articles on MPPs. Each MPP paper in these issues has the Data availability section that is standard for all GSA publications, as well as a one-page guide to the data that makes it easier to browse the data behind the papers.G3 and GENETICS have designed a specialwebresourceforMPPs. Papers are organized in a special collections page, with subheaders that help navigate the growing literature. Our journals have long partnered with model organism databases FlyBase, SGD, WormBase, and others, and we now incorporate news, blogs, tips, and protocols directly on our webpage to help geneticists interested in MPPs get a handle on this topic. Tweet your insights to #MPP #GSAjournals, and use MPP as a keyword of your MPP papers to enable text search engines to collate this literature. The GSA journals are committed to creating a community platform that spans species and disciplines, yet remains focused on common research questions. We thank the authors, referees and editors for making this resource a reality!In recognition of the ongoing importance of MPPs for understanding fundamental questions in genetics,


E 0.035) than for other breeds (HE 0.209–0.284). Analyses of genetic structure with > 15K linkage disequilibrium-pruned SNPs showed four distinct genetic clusters. Pairwise FST values between Lundehund and the candidate breeds were highest for Icelandic Sheepdog, followed by Buhund and Norrbottenspets. We assessed the presence of outlier loci among candidate breeds and examined flanking genome regions (1 megabase) for genes under possible selection to identify potential adaptive differences among breeds; outliers were observed in flanking regions of genes associated with key functions including the immune system, metabolism, cognition and physical development. We suggest crossbreeding with multiple breeds as the best strategy to increase genetic diversity for the Lundehund and to reduce the incidence of health problems. For this project, the three candidate breeds were first selected based on phenotypes and then subjected to genetic investigation. Because phenotypes are often paramount for domestic breed owners, such a strategy could provide a helpful approach for genetic rescue and restoration of other domestic populations at risk, by ensuring the involvement of owners, breeders and managers at the start of the project.Genetic rescue, outcrossing with individuals from a related population, is used to augment genetic diversity in populations threatened by severe inbreeding and extinction. The endangered Norwegian Lundehund dog underwent at least two severe bottlenecks in the 1940s and 1960s that each left only five inbred dogs, and the approximately 1500 dogs remaining world-wide today appear to descend from only two individuals. The Lundehund has a high prevalence of a gastrointestinal disease, to which all remaining dogs may be predisposed. Outcrossing is currently performed with three Nordic Spitz breeds: Norwegian Buhund, Icelandic Sheepdog, and Norrbottenspets. Examination of single nucleotide polymorphism (SNP) genotypes based on 165K loci in 48 dogs from the four breeds revealed substantially lower genetic diversity for the Lundehund (H Genetic rescue–augmentation of genetic variation in depauperate populations–has occurred by means of natural experiments or initiated by humans, and appears to have resulted in favourable outcomes at least in the short term e.g. –4). By p. By p4])Fratercula arctica, hereafter puffins). The Lundehund population underwent at least two severe bottlenecks in the 1940s and 1960s where each event appears to have left only five inbred individuals [IS) equal to 0.87 based on 26 microsatellite loci genotyped in 125 Lundehund individuals. The Lundehund is no longer used to hunt puffins, a species now considered vulnerable on the Norwegian mainland . However, the Lundehund exhibits a number of unique morphological features associated with its historical function. These include enhanced neck and shoulder joint flexibility, polydactyly  and “sealable” ears, which together with small body size appear to have permitted easier access to, and mobility in, the steep coastal cliffs where the puffins nest [The endangered Norwegian Lundehund (henceforth Lundehund) is undergoing genetic rescue and provides a constructive example as a model system, because dog genomic resources are readily available and comparatively inexpensive, and the demographic history of dogs is relatively well-known. The Lundehund breed is a small Spitz from coastal Norway where it was traditionally used to hunt Atlantic puffins  suggest that approximately 30% of Lundehund individuals die from a type of gastroenteropathy known as intestinal lymphangiectasia, commonly known as IL. The high prevalence of gastrointestinal disease is believed to be an example of inbreeding depression [Lundehund individuals are reported to have a high prevalence of gastroenteropathy, a disease of the stomach and intestines –16, whicpression . AlthougPolydactyly, a signature Lundehund trait, has been investigated across taxa for possible negative effects on health and development in vertebrates by means of pleiotropic effects whereby one gene influences two or more apparently unrelated phenotypic traits . HoweverThe selection of breeds and individuals for outcrossing, and the procedures for managing the breeding plans, is a balance between infusing new genetic variation relatively quickly, and careful monitoring to ensure that what remains of the original genetic variability is not swamped. Moreover, the breeding program aims to ensure that morphological, behavioural and other breed characteristics are conserved as much as possible. Outcrossing is currently ongoing and breeding has been undertaken/planned with all three candidate breeds. The objective of this study is to investigate 1) the population genetic structure and differentiation among the Lundehund and candidate breeds for outcrossing, and 2) the occurrence of outlier loci among breeds, the presence of which may indicate selection on genes in flanking regions and thus adaptive differences among breeds that, over time, could benefit Lundehund recovery and preservation. Humans have likely performed selective breeding in the Lundehund and candidate breeds according to their historical role in e.g. herding and hunting, including the unique adaptations to puffin hunting found in the Lundehund. Selective breeding by humans may be expected to produce outlier loci among breeds. However, as all four breeds originate from relatively similar Nordic environments we do not expect such differences to represent naturally selected traits that carry a risk of being maladaptive in crossbred individuals. The main aim of the outlier analyses is to help clarify whether there may be signs of standing genetic variation from adaptation or artificial selection among the candidate breeds, indicating that each breed could contribute unique and potentially adaptive genetic variation to the depauperate Lundehund genome. Importantly, the bottlenecks experienced by the Lundehund may have augmented the probability of finding outliers between this breed and the candidate breeds owing to genetic drift. However, if outlier SNPs near genes believed to be associated with health and survival occur among all four breeds, or pairwise between candidate breeds, this would appear to support the inclusion of multiple candidate breeds in the programme to augment Lundehund genetic variation and evolutionary potential.http://lundehund.no/index.php/krysningsprosjektet) based on morphology, behaviour, shared history and (assumed) high genetic relatedness to the Lundehund breed. However, the individuals in this study were not expected to contribute directly to the breeding program.We genotyped 48 dogs including 17 Lundehund and individuals from three candidate breeds for crossbreeding: 10 Norwegian Buhund (henceforth Buhund), nine Icelandic Sheepdogs, and 12 Norrbottenspets, a breed originating from northern Fennoscandia and Russian Karelia and named after the Norrbotten province in northern Sweden. The three candidate breeds to be used for crossbreeding have been chosen by the Norwegian Lundehund Club . Individual call rates were ≥ 0.98, except for one Icelandic Sheepdog with call rate 0.91. Subsequently, we imported the data into PLINK [E) and observed heterozygosity (HO), missingness (missing genotype rate), polymorphism (P) and identity-by-descent (IBD) within and among breeds. Next we screened the data across all breeds with criteria of minor allelic frequency 0.01  and genotyping success rate 0.98 . We then removed sex-linked SNPs  and pruned the data for markers in linkage disequilibrium (LD) with PLINK command—indep 50 5 2, where 50 is the size of the sliding window, 5 is the number of SNPs shifted in each step, and 2 is the variance inflation factor (VIF), which is a measure of multicollinearity where two or more predictor variables in a multiple regression are highly correlated. The VIF is 1/(1-R2) where R2 represents the multiple correlation coefficient for a SNP simultaneously regressed on all other SNPs. The PLINK guidelines recommend using a VIF from 1.5 to 2.0 for small sample sizes to avoid removing too many SNPs.Collection of Norrbottenspets and Buhund samples was approved by the Animal Ethics Committee at the State Provincial Office of Southern Finland (ESLH-2009-07827/Ym-23 and ESAVI/6054/04.10.03/2012). Icelandic Sheepdog blood samples were collected by a veterinarian, and Lundehund individuals were sampled by non-invasive buccal swabs. Blood or buccal swab samples were genotyped with the Canine HD Bead Chip (Illumina) with 172 115 SNPs, and we performed quality screening in GenomeStudio (Illumina) following the program guidelines .We calculated pairwise FST  among br2 = 0.95 in SNPs 50 kb apart [http://www.ncbi.nlm.nih.gov/genome?term=canis%20lupus%20familiaris) for genes under possible selection. Subsequently, we examined the data in LOSITAN [Subsequently, we examined the data with BayeScan  to identkb apart . For out LOSITAN –28 to evversus SNP position in sliding windows for every 20 and 100 SNPs within each chromosome with 95% confidence intervals. Next, we excluded the Lundehund and plotted the Norrbottenspets, believed to be the most genetically diverse, versus the two other candidate breeds. We subsequently examined expected and observed heterozygosity for each of the four breeds.Finally, we explored genetic diversity along the chromosomes to detect potential islands of divergence. In this assessment we used all chromosomes including the X-chromosome. We calculated the Pearson correlation coefficient for allele frequencies between the Lundehund and each of the three candidate breeds, and plotted the mean the coefficient We obtained profiles containing 165 293 (165K) SNPs and, after application of filters for genotyping success and minor allele frequency, 119 920 high-quality SNPs remained. Subsequent pruning for loci in linkage disequilibrium and exclusion of sex-linked SNPs resulted in a data set of 15 648 autosomal unlinked loci. Genetic diversity was substantially lower for the Lundehund than for the other breeds . The NorThe cross-validation errors for the ADMIXTURE results were lowest for K = 2  appeared to be genetically closer, with FST-values of 0.128 and 0.211, respectively, although small sample sizes prevent a full comparison for some breeds. In contrast, another breed from Norway, the Norwegian Elkhound (here represented by the grey variety) is genetically more distant from Lundehund than several breeds originating from outside Norway.Pairwise Fparisons . Based oLRRTM1 (chromosome 17), which was observed in the flanking region for an outlier SNP in the pairwise test for Buhund–Norrbottenspets, has previously been related to a rare phenotype in mice associated with avoiding confined space [POC1A (chromosome 20) has been connected to bone formation, short stature and facial dysmorphism in humans [GLB1 (chromosome 23) was observed in the flanking region of an outlier in the test across all four breeds as well as in two pairwise tests ; mutations in this gene have been linked to metabolic diseases and hypermobile joints [BayeScan results across all four breeds and from pairwise comparisons highlighted 18 outlier SNPs , ten of ed space . POC1A  whereas two SNPs, BICF2P663203 (chromosome 10) and BICF2P993491 (chromosome 17), had probability values of 0.72 and 0.86, respectively. Both of the latter two SNPs had been identified in BayeScan tests incorporating all four dog breeds.Although the genetic findings from the abovementioned studies have no known direct link to the Lundehund or the candidate breeds, the among-breed variation observed in the outlier tests appears relevant to the conservation breeding program, considering Lundehund history, human-directed selection, current breed standard, and health concerns. The LOSITAN results for all individuals were consistent with BayeScan in identifying the 18 SNPs as outliers under divergent selection, with the probability of the sample FGenetic polymorphism values and mean ROH lengths per individual revealed a similar pattern . Furtherversus other breeds revealed extensive regions without allelic diversity. These areas are marked in grey colour below plots  . For theow plots  whereas ow plots . These rST value between Lundehund and the Norrbottenspets was also lower than for other candidate breeds. In addition, ADMIXTURE results for K = 5–6 showed high within-breed variation in the Norrbottenspets, which seems consistent with the breed having an open stud book.Our results of low genetic diversity and high levels of inbreeding in the Lundehund are consistent with findings from earlier studies with a range of genetic markers –14. FurtAlthough the Buhund and the Icelandic Sheepdog show relatively high within-breed relatedness and low genetic variation when compared with the Norrbottenspets, earlier studies suggest that the crossing of two groups with a high degree of inbreeding can provide substantial positive effects of genetic rescue, especially in the short term . ImportaST estimates between Lundehund and other breeds, sample size differences could have affected the results as only few individuals were available for certain breeds. Additionally, the extent to which higher FST values imply that breeds have a genuinely different genetic composition caused by deliberate selection and/or genetic drift, or whether high values primarily reflect a lack of variation in the Lundehund, should be considered. Higher variation within breeds such as the Norrbottenspets could also have resulted in lower FST values in comparisons between this and other breeds, including the Lundehund. The FST estimates should therefore be interpreted with some caution. Notably, in preliminary ordination analyses by means of multidimensional scaling across 13 Nordic Spitz breeds  are often paramount for domestic breed owners and managers, such an approach could provide a helpful blueprint for genetic rescue and restoration of other domestic populations at risk by ensuring the active involvement of breeders and managers at the start of the project and taking advantage of their knowledge in the selection of candidate breeds for subsequent genetic investigation.LEPREL1 (chromosome 34) and NOD1 (chromosome 14) that were highlighted in a recent investigation of gastrointestinal disease in the Lundehund [We strongly advocate that animals from this genetic rescue project are genotyped  and that resources are devoted to following the project closely including phenotyping of animals. The Lundehund cross-breeding initiative has the potential to become an illustrative model of the potential of genetic rescue in domestic species. This project can serve as a model for how to use genomic information to guide breeding decisions in breeds that are genetically depauperate, and help illuminate the genetic architecture of complex diseases. Specifically, individuals resulting from the current outcrossing project may offer an opportunity for a future case-control study comparing disease-affected dogs with individuals showing good lifetime health records. This approach could be used for further investigation of undehund  and the undehund .GLB1 gene on chromosome 23 related to metabolism and hypermobile joints might represent a trade-off, whereby selection for hypermobile joints could have negative metabolic consequences by means of pleiotropic effects. The cross-breeding offspring from this project will likely show phenotypic variation for e.g. polydactyly and gastrointestinal health. These individuals can therefore contribute beyond the genetic rescue of an endangered breed toward case-control studies of phenotypic traits critical for vertebrate (including human) survival and health, thus improving our understanding of inbreeding, natural selection, and evolution.We recommend further research for the observed genes associated with characteristics that are part of the current breed standard  and may have implications for animal health. Although these genes are not, at present, considered to have direct implications for the Lundehund or the breeding program, future research could examine the possibility that the S1 FileTable A—Pairwise FST-values for the Lundehund and a selection of other Nordic Spitz breeds. Table B—SNPs with ID, chromosome and position (bp) from CanFam2 found as outliers.Figure A—ADMIXTURE cross-validation error values for K (population clusters) from 1–6. Figure B—ADMIXTURE results for n = 41 Nordic dogs with 15 648 single nucleotide polymorphism loci and K = 2–6 population clusters.Figure C—The genomic location of runs of homozygosity (ROH) shared by at least 2/3 of individuals within each breed.Figure D—Pearson correlation coefficient between allele frequencies along the chromosome for the Lundehund and the candidate breeds.Figure E—Expected and observed heterozygosity along the chromosome for the Lundehund and the candidate breeds.(DOCX)Click here for additional data file.


Chorthippus binotatus binotatus) from the biogeographically complex region of southeast Iberia. First, we examined geographical patterns of genetic structure and employed an approximate Bayesian computation (ABC) approach to compare different plausible scenarios of population divergence. Second, we used a landscape genetic framework to test for the effects of (1) Late Miocene paleogeography, (2) Pleistocene climate fluctuations, and (3) contemporary topographic complexity on the spatial patterns of population genetic differentiation. Genetic structure and ABC analyses supported the presence of three genetic clusters and a sequential west‐to‐east splitting model that predated the last glacial maximum . Landscape genetic analyses revealed that population genetic differentiation was primarily shaped by contemporary topographic complexity, but was not explained by any paleogeographic scenario or resistance distances based on climate suitability in the present or during the LGM. Overall, this study emphasizes the need of integrating information on ancient and contemporary landscape composition to get a comprehensive view of their relative importance to explain spatial patterns of genetic variation in organisms inhabiting regions with complex biogeographical histories.Understanding the processes underlying spatial patterns of genetic diversity and structure of natural populations is a central topic in evolutionary biogeography. In this study, we combine data on ancient and contemporary landscape composition to get a comprehensive view of the factors shaping genetic variation across the populations of the scrub‐legume grasshopper ( During c. 12 Mya) configured a mosaic of islands (hereafter Betic Islands) at the confluence of European and African continental platforms. The rotation of the Betic Islands toward the Iberian Peninsula, in combination with sedimentation processes, resulted in their fusion to the continent and the configuration of a continuous emerged landscape that is currently conformed by the Prebetic, Penibetic, and Subbetic mountain ranges of southeast Iberia  in Europe, during which vast portions of land were free of permanent ice at elevations below 2,500 m.a.s.l.  (Orthoptera: Acrididae) is a winged Orthoptera with a 1‐year generation time  form scattered vegetation patches located at moderate to high elevations . This fact restricts the distribution of the scrub‐legume grasshopper to the different mountain ranges of the region   climate suitability and stability, and contemporary topographic complexity (TC). Finally, we (3) tested the hypothesis predicting more genetic diversity in populations from areas with high past and present climate suitability and stability since the LGM.Here, we used the scrub‐legume grasshopper as model system to analyze the contribution of contemporary  and historical  factors on shaping spatial patterns of genetic diversity and structure across the populations of the species from southeast Iberia. In particular, we first (1) examined geographical patterns of genetic structure and employed an approximate Bayesian computation (ABC) framework to compare different plausible scenarios of population divergence   Table . This al2.2We extracted genomic DNA from a hind leg of each individual using a salt extraction protocol  using the so‐called ENA method implemented in the program freeNA  with a burn‐in period of 200,000 steps and a run length of 1,000,000 Markov chain Monte Carlo cycles. The number of genetic clusters (K) best fitting the data set was defined using log probabilities [Pr(X|K)]  was estimated using the deviance information criterion (DIC) values and stabilization of the Q matrix of posterior probabilities  genetic distances  to examine the partitioning of the genetic variation among and within regions and populations as defined by five population grouping hypotheses. Populations were pooled according to their historical location in the three different paleogeographical Late Miocene scenarios   Scenario III, sequential splitting model from east to west: Group C split from groups A and B at t2, and these two groups split at t1; (4) Scenario IV, splitting model from central to peripheral populations: Group B split from groups A and C at t2, and these two groups subsequently split at t1 , model checking, and estimation of the posterior distribution of all parameters under the best supported model were performed as described in Ortego, Noguerales, Gugger, and Sork  to create vector layers for emerged lands based on geological models from Martín et al. (c. 1 km) resolution that were finally used as inputs in circuitscape .To test the possible effect of the complex geological history of the study region on contemporary patterns of genetic differentiation, we considered three paleogeographic scenarios: Early Tortonian (12.0–11.6 Mya), Late Tortonian (8.0–7.3 Mya), and Earliest Messinian (7.2–7.0 Mya)  resolution . Then, we used the Jackknife of regularized training gain procedure implemented in maxent to retain the variables with the maximum contribution to the model. We discarded the worst and highest correlated predictors among the whole set of variables, conducted a new model with the remaining variables, and repeated this backward process until the final model only retained the best explanatory and less correlated variables  using the maximum entropy presence‐only algorithm implemented in c. 21 Kya), we projected contemporary species–climate relationships to the LGM using two atmospheric circulation models: the Community Climate System Model .To obtain the distribution of scrub‐legume grasshopper during the LGM  resolution and used as input in circuitscape (see below for details).We investigated the role of contemporary TC as a potential factor shaping patterns of genetic differentiation in our study populations. We calculated the surface ratio index for each cell from a present‐day digital elevation model using “DEM Jenness,  in arcgiJenness, . Calcula2.5.4circuitscape 4.0 , an approach that allowed us to identify the optimal ratio of landscape resistance between both landscape elements that best fit our data on genetic differentiation  against all pairwise resistance distance matrices representing the nine different IBR/IBD scenarios. We used a backward procedure to select final models, eliminating nonsignificant variables from an initial full model including all explanatory predictors. We tested the significance of the remaining variables again until no additional term reached significance  standardized for sample size was calculated for each population using hp‐rare  obtained from the probabilities of population membership to each genetic cluster inferred by structure analyses  to 1 . We used generalized linear models  and an information‐theoretic model selection approach to analyze AR and GADMIX , LGM climate suitability (HSLGM), and climate suitability stability (HSSTA). Models for GADMIX included HSSTA as independent variable. Longitude and latitude were included as additional covariates in models for both AR and GADMIX to take in account possible geographical clines of genetic diversity and admixture  were significantly higher than zero after sequential Bonferroni correction . The populations from Ronda, Parapanda, and Tejeda, located at the westernmost portion of the study area, exhibited the highest levels of genetic differentiation with the rest of populations. Analyses in structure showed a best supported number of clusters for K = 2 according to the ΔK method. The first cluster included the Western populations, whereas the second cluster included the remaining populations located in the east part of the study area. However, log probabilities [Ln Pr (X|K)] steadily increased from K = 2 to K = 5  was also congruent with the results from Bayesian clustering analyses  for scenario II, suggesting good model fit. Type I and II errors were .394 and .372, respectively, and RMAE values were moderate in most cases (Table t2) , whereas these two groups split ~42,000 years ago (t1)  (Table Ne) indicated no important demographic changes after the different splitting events  had the highest posterior probability based on both direct and logistic regression‐based estimates, and its 95% confidence interval did not overlap with those obtained for others scenarios that showed much lower support Table . Observees Table . Considees Table , the wes3.3The variables included in the final CNM were temperature seasonality (BIO4), mean temperature of the driest quarter (BIO9), precipitation of the driest month (BIO14), and precipitation of the warmest quarter (BIO18). This model had a very high value of area under the curve , indicating overall good performance. The predicted distribution of scrub‐legume grasshopper in the present Figure a is cons3.4Ps < .006)   yielded qualitatively analogous results (data not shown).Tejeda and Ronda populations are currently located in areas that were not likely to form emerged lands during Early and Late Tortonian, and for this reason, they were excluded from landscape genetic analyses. Thus, we performed MMRR analyses using the 17 populations presumably located on permanently emerged lands since the late Miocene in order to make our landscape genetic analyses comparable across all tested scenarios and time periods. Considering these 17 populations, only resistance distances based on contemporary TC and IBD were significantly associated with genetic differentiation 6) Table . However Table . ts Table , but mod3.5GK = i, 5]ADMIX ADMIX [ index and AR were also correlated . Model selection results showed that AR was not significantly associated with longitude, latitude, or HSCUR, HSLGM, or HSSTA at any analyzed spatial scale  was not significantly associated with longitude, latitude, or HSSTA at any analyzed spatial scale , when the scrub‐legume grasshopper probably showed a distribution similar to that in the present. We did not find support for the hypothesis predicting more genetic diversity in populations from areas with higher past and current climate suitability and stability since the LGM. Unlike other organisms from temperate regions whose distributions were confined to isolated refugia during glacial or interglacial periods  and the LIG (c. 120 Kya)  and t1  were very broad. In addition, it must be also considered that diyabc does not accommodate gene flow after divergence , an endemic taxon from the Pyrenees belonging to the same species complex than the scrub‐legume grasshopper  due to the large distance to the mainland and/or the absence of optimal habitats given the warmer climate and the forest‐like vegetation prevailing during the Late/Middle Miocene (c. 23–14 Mya) (Jimenez‐Moreno, Fauquette, & Suc, Our landscape genetic analyses showed that resistance distances based on contemporary TC provided the best model fit, indicating that gene flow is primarily shaped by physical features of the landscape Wang, . This suOverall, this study shows that contemporary TC is the main landscape factor predicting spatial patterns of population genetic differentiation in the scrub‐legume grasshopper. Future studies analyzing the complete distribution range of the species and considering current and past distributional data for all host plant taxa can provide new insights into the consequences of ancient and contemporary landscape changes on the evolutionary and demographic history of this specialist grasshopper. Our study emphasizes the need of integrating spatial data of ancient and contemporary landscape composition to get a comprehensive view of their relative importance in explaining genetic variation of organisms inhabiting regions with a complex biogeographical history.None declared. Click here for additional data file.


Giardia duodenalis is a flagellated intestinal protozoan responsible for infections in various hosts including humans and several wild and domestic animals. Few studies have correlated environmental contamination and clinical infections in the same region. The aim of this study was to compare groups of Giardia duodenalis from clinical and environmental sources through population genetic analyses to verify haplotype sharing and the degree of genetic similarity among populations from clinical and environmental sources in the metropolitan region of Campinas. The results showed high diversity of haplotypes and substantial genetic similarity between clinical and environmental groups of G. duodenalis. We demonstrated sharing of Giardia genotypes among the different populations studied. The comparison between veterinary and human sequences led us to identify new zoonotic genotypes, including human isolates from genetic assemblage C. The application of a population genetic analysis in epidemiological studies allows quantification of the degree of genetic similarity among populations of Giardia duodenalis from different sources of contamination. The genetic similarity of Giardia isolates among human, veterinary, and environmental groups reinforced the correlation between clinical and environmental isolates in this region, which is of great importance for public health. It is frequently found in areas with inadequate water and sewage treatment systems and poor hygiene practices, although it has also been responsible for waterborne outbreaks in developed countries . Genetic assemblages A and B are usually associated with human infections, although these groups have also been identified in various domestic, wildlife, and marine animal species , a daycare center (DC), a veterinary clinic, and the Zoonosis Surveillance Unit of the city of Campinas (VET). The sequences of environmental samples came from rivers, urban streams, sewage effluent, and hospital sewage (ENV). Table S4 presents the reference sequences obtained from NCBI that were used to confirm the genotypes of the sequences. Tables S5, S6, S7, S8, S9, S10, and S11 present all sequences used in this study and include information regarding genetic assemblages, GenBank accession numbers, and specific sites of collection.2.2This study used public sequences deposited in the GenBank database. No clinical information was obtained from the isolates, and no specific permissions were required.2.3tpi), 753 bp from the beta‐giardin gene (bg), and 218 bp from the glutamate dehydrogenase gene (gdh), were obtained from GenBank. These genes have been widely used in studies on Giardia, which is beneficial for comparisons between different sources. These are single‐copy loci that are unlinked in the genome of G. duodenalis  and environmental sequences.After the identification of haplotype variability in the bg gene were not considered in the population hierarchical analysis due to a sampling bias that prevented comparison with other groups. In the second hierarchical analysis of the distribution of genetic diversity between populations, the RIV  and SEW (samples from sewage) groups were analyzed both separately and together with all other environmental samples (ENV Group).In this study, a group of isolates was considered a set of samples from the same genetic assemblage with the same origin or collection site. Groups with less than five isolates at each locus were not considered in the genetic diversity and hierarchical analyses. Sequences of the 3G. duodenalis isolates from the metropolitan region of Campinas from both clinical and environmental sources were analyzed at three different gene loci. The genetic loci tpi, bg, and gdh provided 175, 106, and 71 sequences, respectively. These sequences originated from 198 isolates, which were separated into the following groups: HC, for sequences obtained from a hospital; DC, for sequences obtained from a daycare center; VET, for sequences obtained from veterinary isolates; and ENV, for environmental sequences. For the analysis of haplotype diversity and genealogical relationships, the ENV group was divided into the RIV group, for sequences obtained from rivers and urban streams and the SEW group, for sequences originating from sewage  of all sequences. Notably, the HP01tpi and HP02tpi haplotypes were detected in hospital, daycare center, and sewage sequences from the city of Campinas. The HP01tpi haplotype was also identified in a sequence obtained from a dog  of all sequences  of all sequences. Three haplotypes were detected at multiple sites and are highlighted as follows: the HP01 bg and HP06bg haplotypes were detected in both clinical sequences and the Atibaia River, and the HP08bg haplotype was found both in dogs and sewage sequences , respectively. These results are shown in Table The haplotype diversity of each group was also evaluated in this study. It was determined that all populations exhibited a high level of genetic diversity, which reflects the large number of haplotypes presented in Table 3.4The groups were compared using AMOVA to determine the variability among and within certain groups. In the established hierarchy, the initial decision was to compare the group of hospital samples (HC group) and the group of samples obtained from children at a daycare center (DC group). The descriptive data for the AMOVA analysis are provided in Table tpi locus, there was no significant variation between the groups, but for the gdh locus, the variation between the HC and DC groups  showed significant differences.Regarding the groups that originated from genetic assemblage B, contrasting results were found between the HC and DC groups at the two markers used. For the tpi locus. The results of this comparison showed that there were no significant variations between these groups; thus, these groups could be considered similar  were compared with those obtained from environmental isolates (ENV). The results for both genetic assemblages (A and B) indicated that these groups (HC and DC × ENV) were very similar, with no significant genetic variation being observed between them for both genetic assemblages. These results are shown in Table At the second hierarchical level, the 4Giardia spp.  or two (SEW) molecular markers, which narrowed the possibility of comparisons with other groups. This finding may be a consequence of the low success rates of the amplification and sequencing reactions in these groups at this locus. Numerous factors, such as the DNA extraction methods or PCR inhibitors used and whether single‐copy or multi‐copy genes are targeted, influence the successful amplification of DNA , which compromises comparisons with the other groups.The high level of haplotype diversity identified in this study was determined through analysis of the diversity of haplotypes and their proportion in a population. This result, although initially unexpected for a parasite that reproduces clonally, probably reflects the dynamism of the metropolitan region, which comprises more than 3 million inhabitants as well as metropolitan hospitals, some of the most reputable universities of the country, and an international airport, all of which may influence how widespread several genotypes are in this region. The river group (RIV) presented low haplotype diversity  may be susceptible to the same contamination events in this metropolitan region.Genetic similarity between the hospital and daycare center (HC × DC) groups was observed for both assemblages (A and B), which demonstrates a robust correlation between the isolates of this parasite and both hosts. Children, and particularly those who attend daycare centers, primary schools, and orphanages, are highly susceptible to infection by G. duodenalis from genetic assemblage C that are shared between humans and dogs. This result, which has also been reported in previous studies  also showed high genetic similarity for both comparisons (genetic assemblages A and B). Many environmental sequences presented genotypes that are commonly detected in humans. Although 5Giardia duodenalis from different sources of contamination. Our results showed that in the metropolitan region of Campinas, there is high diversity of haplotypes and substantial genetic similarity between clinical and environmental groups of G. duodenalis, which could be quantitatively demonstrated. The sharing of Giardia genotypes between human, veterinary, and environmental groups reinforced the correlation between clinical and environmental isolates in this region and allowed us to identify new zoonotic genotypes, which is of great importance for public health.The application of a population genetic analysis in epidemiological studies opens up new possibilities allowing quantification of the degrees of genetic similarity between populations of The authors have no conflicts of interest. Click here for additional data file.