Mytilus are known to change their geographic distribution despite being sessile animals. In addition to natural dissemination at larval phase—enhanced by intentional or accidental introductions and rafting—they can spread through hybridization and introgression with local congeners, which can create mixed populations sustaining in environmental conditions that are marginal for pure taxa. The Mytilus species have a wide distribution in coastal regions of the Northern and Southern Hemisphere. In this study, we investigated the inter-regional genetic differentiation of the Mytilus species complex at 53 locations in the North Atlantic and adjacent Arctic waters and linked this genetic variability to key local environmental drivers. Of seventy-nine candidate single nucleotide polymorphisms (SNPs), all samples were successfully genotyped with a subset of 54 SNPs. There was a clear interregional separation of Mytilus species. However, all three Mytilus species hybridized in the contact area and created hybrid zones with mixed populations. Boosted regression trees (BRT) models showed that inter-regional variability was important in many allele models but did not prevail over variability in local environmental factors. Local environmental variables described over 40% of variability in about 30% of the allele frequencies of Mytilus spp. For the 30% of alleles, variability in their frequencies was only weakly coupled with local environmental conditions. For most studied alleles the linkages between environmental drivers and the genetic variability of Mytilus spp. were random in respect to “coding” and “non-coding” regions. An analysis of the subset of data involving functional genes only showed that two SNPs at Hsp70 and ATPase genes correlated with environmental variables. Total predictive ability of the highest performing models (r2 between 0.550 and 0.801) were for alleles that discriminated most effectively M. trossulus from M. edulis and M. galloprovincialis, whereas the best performing allele model (BM101A) did the best at discriminating M. galloprovincialis from M. edulis and M. trossulus. Among the local environmental variables, salinity, water temperature, ice cover and chlorophyll a concentration were by far the greatest predictors, but their predictive performance varied among different allele models. In most cases changes in the allele frequencies along these environmental gradients were abrupt and occurred at a very narrow range of environmental variables. In general, regions of change in allele frequencies for M. trossulus occurred at 8–11 psu, 0–10 °C, 60%–70% of ice cover and 0–2 mg m−3 of chlorophyll a, M. edulis at 8–11 and 30–35 psu, 10–14 °C and 60%–70% of ice cover and for M. galloprovincialis at 30–35 psu, 14–20 °C.Large-scale climate changes influence the geographic distribution of biodiversity. Many taxa have been reported to extend or reduce their geographic range, move poleward or displace other species. However, for closely related species that can hybridize in the natural environment, displacement is not the only effect of changes of environmental variables. Another option is subtler, hidden expansion, which can be found using genetic methods only. The marine blue mussels  Coastal ecosystems are highly complex and driven by multiple environmental factors. Local patterns represent the interplay of historical evolutionary processes  combined with separate and interactive effects of local environmental gradients on species  ,2. TheseMytilus species, has a wide distribution in coastal regions of the Northern Hemisphere [Mytilus complex includes three incompletely isolated species of marine mussels, Mytilus edulis , Mytilus trossulus  and Mytilus galloprovincialis . Recent research on the distribution of the species complex evidently reflects a history of inter- and trans-oceanic dispersal, secondary contact and hybridization, besides the distribution effect brought about by human activities [M. trossulus in the Pacific and invaded the Arctic Ocean from the Pacific Ocean around 3.5 million years ago (mya) through the Bering Strait [M. edulis in the Atlantic. Since then M. edulis has spread to large parts of the Atlantic, and due to apparent low gene flow the populations of M. edulis on each side of the Atlantic are genetically distinct [M. edulis and M. galloprovincialis [M. trossulus reinvaded the Arctic Ocean [M. trossulus/M. edulis hybrid zones along North American and European coasts [M. trossulus is considered as the cold-water adapted species, M. edulis resides in temperate areas and M. galloprovincialis tolerates higher temperatures and has the most southerly native distribution of these three species in Europe in the Mediterranean and Black Sea. Moreover, M. galloprovincialis has successfully invaded temperate waters in other geographic areas such as South Africa, North and South America, Asia and Australia [The blue mussel complex, misphere ,16,17,18misphere . The Myttivities ,24,25,26g Strait ,28,29. Ddistinct ,31. An aincialis ,28,32,33incialis . Betweenic Ocean ,35. Fromn coasts ,21,36. Iustralia ,39,40,41M. edulis has been reported in the northern part of the Atlantic and European seas from the White and Barents Sea to the Atlantic coast of southern France and M. galloprovincialis is in the Mediterranean Sea, Black Sea and along the Atlantic coastline of Western Europe, including the British northern islands [M. trossulus was limited to the North Pacific, eastern Canada and the Baltic Sea [Today the species are in contact in several places in the North Atlantic with both co-occurrence and interbreeding ,42,43,44 islands ,45,46,47ltic Sea , but morltic Sea ,26,48,49Mytilus spp. have large inter-regional genetic differentiation, but it is poorly known if and how much this variation is correlated with local environmental conditions. In general, three important local environmental gradients have been recognized in intertidal hard bottom areas inhabited by Mytilus spp.: wetness, exposure to wave action and salinity [Mytilus spp. and reported salinity among the most important environmental drivers in the North Atlantic and Arctic regions. However, other authors indicate temperature and food concentration as prime environmental factors affecting distribution and geographic range of Mytilus populations [As seen above salinity . The wetsalinity ,51. Thissalinity , differesalinity ,54, heavsalinity  and salisalinity ,36. Telesalinity  recentlyulations ,58,59.Mytilus species complex in the North Atlantic and Arctic at different geographical scales and to quantify if and how much environmental variables explain the genetic diversity of Mytilus spp. Our models included regions as well as key environmental variables known to drive the local variability of Mytilus spp. When the between-region variability is important in the models then this suggests that the genetic patterns of Mytilus spp. are highly due to the historical colonization of different regions [Mytilus spp. is not random but is stronger for those alleles at genes opposing to alleles that are located in the non-coding regions.The aims of this study are to provide a basic genetic knowledge on the current distribution ranges of the  regions . On the  regions ,2 we expMytilus spp. samples, consisting of 1204 individuals of mixed ages and size 5–50 mm were collected from 43 localities in North America and Europe, including the arctic and subarctic regions. Eleven samples were obtained from North America ; fourteen were obtained from arctic and subarctic regions of Europe ; seven from British Isles and Ireland; four from the Baltic Sea; four from the Atlantic coast of Europe; and three from the Mediterranean and Azov Seas. Forty-three samples consisted of 17 to 40 (mainly about 30) individuals, while two samples from Spitsbergen and Mont Saint-Michel consisted of 4 individuals , identified in Bach et al. [M. trossulus. Two populations, Indian River, Delaware (IRD) from the Atlantic coast of North America and Loire (LOI) from the Atlantic coast of North Europe, provided reference samples of M. edulis [M. galloprovincialis [ividuals . DNA wash et al.  were use. edulis . Populatincialis . A few sincialis , BAR, ONincialis ) were geincialis ,37,38,62Mytilus individuals were genotyped using the Sequenom MassARRAY iPLEX genotyping platform [M. trossulus, M. edulis and M. galloprovincialis individuals from Europe and North America [M. edulis, M. trossulus, M. galloprovincialis) [Mytilus collected from geographic regions including Europe, North and South America and New Zealand. Assays were designed for 79 SNPs.SNPs identified in the present study and in earlier work ,24,25 weplatform . Putativ America ,24,25,62ncialis) ,24 and wOP) and minor allele frequency (MAF). Fifty-one samples consisting of at least 11 individuals were used. Expected (EH) and observed heterozygosity (OH) in each population was calculated using the whole SNP data set. The statistical significance of inbreeding coefficient ISF (>0) was tested by 10,000 permutations of alleles between individuals. Departures from Hardy–Weinberg equilibrium (HWE) were tested by exact test and significance was determined by Markov chain Monte Carlo simulations. Pairwise analysis was used to calculate mean pairwise STF values defining population differentiation. STF values at individual SNPs were calculated using the AMOVA function. Permutation testing with 1000 iterations was used to calculate p-values for mean STF and locus-by-locus STF values. Arlequin was also used to detect loci under selection. The neutral distribution of STF was simulated with 30,000 iterations at a 95% confidence level.Arlequin v.3.5.1.2  was applα = 0.05) to control for multiple testing [M. edulis, M. galloprovincialis and M. trossulus). For a pair of diploid loci, no assumption was made about the gametic phase in double heterozygotes. STF distance measures in the Newick format, obtained in POPTREEW [M. trossulus  used in HI analysis were chosen.The false discovery rate (FDR-BY) was applied to the significance threshold  were estimated by computing likelihood over 10 runs for values of K ranging from 1 to the study number of populations plus 3. At the plateau of the graph curve (plot of likelihood against K), the value of K captures the main structure of the populations. The best-fit number of genetic clusters was determined by calculating the logarithmic probability (LnP(K) and using the ΔK method [Two methods were carried out to characterize population structure. In the first method clustering analysis was carried out with STRUCTURE v. 2.3.3 software ,72. STRUK method . ThreshoK method . IndividK method . A MonteK method ), implemK method , was useK method . Each dohttps://power.larc.nasa.gov/data-access-viewer/ and percent total cloud amount from http://daac.ornl.gov/ [http://worldclim.org/version2 [https://www.nodc.noaa.gov/cgi-bin/OC5/woa18/woa18.pl. Average swell height was obtained from the Global Atlas of Ocean Waves at http://www.sail.msk.ru/atlas/ and tide height from AVISO+ Satellite Altimetry Data at https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/global-tide-fes/description-fes2014.html. The product Sea surface height amplitude due to non-equilibrium ocean tide at M2 frequency—FES2014b was used. Sea ice concentration (expressed as a mean percentage of ocean area covered by sea ice) was obtained from the Goddard Space Flight Center, Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer and the Defense Meteorological Satellites Program Special Sensor Microwave/Imager passive microwave data (https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=981).Regional-scale proxies for weather and local environment were obtained from different online databases. A mean climatology for wind speed at 50 m above the surface of the earth was obtained from rnl.gov/ . This clrnl.gov/ . Solar eversion2 . Sea wata was obtained from the Ocean Color Climate Change Initiative dataset, Version 3.1, European Space Agency, available online at http://www.esa-oceancolour-cci.org [https://www.nodc.noaa.gov/OC5/woa13/woa13data.html. The spatial and temporal resolution of datasets, data range and units are shown in Mytilus samples are shown in These original data were re-gridded by the National Snow and Ice Data Center from their original 25-km spatial resolution and EASE-Grid into equal angle Earth grids with quarter degree spatial resolutions in latitude/longitude . Water c-cci.org . NutrienMytilus spp. that vary tens of degrees in the South-North and East-West direction. Thus, the grain of environmental variables is sufficiently detailed relative to the grain of study.As data were originating from multiple sources, the environmental datasets have different temporal range. Here, these climatological time series are used to characterize typical environmental conditions  of the regions of interest over a very long period of time. In the context of this study, some differences in timing among environmental datasets do not pose any significant problems as regional climatological averages are expected to change over the centuries and millennia rather than a few years. In addition, the environmental datasets also had different spatial resolution from 0.04 to 2°. However, in the current study we focused on large spatial patterns  of r < 0.3. Temperature was negatively correlated with ice cover (r = −0.87), but this value did not severely distort model estimations and subsequent prediction [Multicollinearity can be an issue with any spatial modeling algorithm when deciding which environmental variables are of ecological interest. Thus, prior to modeling, multicollinearity was checked with a Pearson correlation analysis in order to exclude highly correlated variables from the model. Most variables were only weakly intercorrelated at ediction .Mytilus spp. were explored using the boosted regression trees technique (BRT). Besides environmental variables shown in Mytilus spp. are mostly due to the historical colonization of different regions by Mytilus spp. On the other hand, when environmental variability strongly modulates the local genetic structure independent of regional variability then local adaptation processes are expected to be very important.The relationships between different environmental variables and allele frequencies of The BRT is a technique that combines the strength of machine learning and statistical modeling; it avoids starting with a data model and rather uses an algorithm to learn the relationship between the response and its predictors . The preThe BRT iteratively develops a large ensemble of small regression trees constructed from random subsets of the data. Each successive tree predicts the residuals from the previous tree to gradually boost the predictive performance of the overall model. The final BRT model is a linear combination of many trees  that can be thought of as a regression model where each term is a tree. Although BRT models are complex, they can be summarized in ways that give powerful ecological insight ,88. R paUsing BRT requires specification of the learning rate and number of fitted trees parameters. Decreasing (slowing) the learning rate increases the number of fitted trees required, and in general a smaller learning rate (and larger number of fitted trees) are preferable, conditional on the number of observations and time available for computation. The usual approach is to estimate the optimal number of trees with an independent test set or with cross validation (CV), using deviance reduction as the measure of success. We used 10-fold CV and learning rate 0.01 to estimate the optimal number of trees for each analysis with 20,000 trees as the limit. This strategy guaranteed that the rule-of-thumb of at least 1000 trees used was followed for each analysis. Typically, the number of trees used was larger than 5000. Relative importance of predictors should only be considered in the context of the model’s total predictive ability. To assess this, an adjusted count pseudo-R-squared was calculated for each model M as follows. First the prediction inaccuracy of model M was calculated as the frequency of incorrect predictions based on the CV predicted values of model M. Then the null model prediction inaccuracy was calculated as the frequency of the incorrect predictions of an intercept-only model. The ratio of the two inaccuracies can be interpreted as the relative prediction inaccuracy of model M and thus the pseudo-R-squared calculated as one minus the ratio is the relative prediction accuracy of model M.Mytilus spp. are stronger when the respective alleles are located in the coding regions, we ran ANOSIM analysis to examine differences in the patterns of variation in genetic variability between the "coding" and "non-coding" regions. Prior to analysis, a Bray-Curtis similarity matrix was calculated using raw data (untransformed) of the BRT modeling results . Environmental variables responsible for the observed genetical differences were identified by the SIMPER analysis. The ANOSIM and SIMPER analyses were performed using the PRIMER 7 software [In order to assess if linkages between environmental drivers and the genetic variability of software .Mytilus mussels [Genotype results obtained with seventy-nine candidate SNPs were collated for 1469 mussels from 53 samples. For 11 SNPs, the assay did not provide an acceptable quality score, and two were monomorphic in all samples. Sixty-six were polymorphic. Of these 66 SNPs, 54 could be scored in all 53 samples and the remaining 12 could be scored in a subset of 16 samples. SNP annotation is presented in  mussels ,24,25,62Mytilus spp. populations. Only five pairs of loci out of a total of 2145 were in highly significant linkage disequilibrium (p < 0.001). Four were found between SNPs localized in the same fragment  and concerned M. galloprovincialis and M. edulis populations. The remaining pair consisted of different gene fragments (BM201C vs. BM203B) and concerned only M. galloprovincialis populations. STF values at individual SNP markers ranged from 0.01 to 0.85. Deviation from expectation of neutrality based on a null distribution of FST values was identified in 41 SNPs which had STF values significantly different from zero by outlier tests carried out for all studied populations (Very little linkage disequilibrium between pairs of 66 markers was found in the three groups of ulations .Po) ranged from 37.04% to 88.9% among populations  and from the Atlantic coast of Europe (NLOO). The highest levels of polymorphism were found in Norway (Bergen BRN) and in the Baltic Sea (STC). There are also high levels of polymorphism in the Arctic and Subarctic populations , where hybridization between M. edulis and M. trossulus also occurs, with 77–85% of the SNPs being polymorphic .The level of polymorphic SNPs (ulations . The lowymorphic . Among pP < 0.05) after FDR-BY correction was observed in the population from Loch Etive, and in the Arctic and Subarctic populations from North Russia , Newfoundland and northwest Greenland (Maarmorilik Fjord), reaching values from 40% to 58% of SNPs (Ho) for 54 loci among 50 populations was in general lower than expected (He) in most of the populations. The greatest difference can be seen in the populations from North Russia , Newfoundland (PBAY), Maarmorilik fjord (GLL) and in the Loch Etive (LET) population, where Ho is about half the value of He. The highest values of Ho were observed in the populations from Atlantic coast of Spain, especially from the Camarinal (CAM), Scotland Hebrides (STA), Danish Straits (STC) and the lowest at populations from Russia White (KER) and Barents Sea (DLZ). The highest gene diversity and differences within population can be observed in populations from Bergen (BRG), Loch Etive (LET), Newfoundland (PBAY) and Danish Straits (STC), where many hybrids were also present  show a significant excess of homozygotes in 29 populations. Very large (>0.6) values of ISF for 30% to 50% of the loci were observed in populations from Russia , Newfoundland (PBAY), Maarmorilik fiord (GLL) and in the Loch Etive (LET) population, where hybridization between M. edulis and M. trossulus occurs. In a few cases, ISF had values of 1, indicating the existence of two alternative homozygotes without any heterozygotes, mainly in populations from Russia in the White Sea and Barents Sea  (Most SNP loci were in Hardy–Weinberg equilibrium (HWE) in the vast majority of the study populations. The largest fraction of SNPs that were not in HWE  .STF distance matrix . The tree shows three separate groups which contain individuals of M. edulis: first, the populations from North America , second, North European populations , and third, populations originating from the Atlantic coast of Europe . In addition, one clade was composed of Scotland M. edulis/M. galloprovincialis populations. Populations of Atlantic and Mediterranean M. galloprovincialis formed two separate groups. Pairwise STF values were significant after FDR-BY correction between most of the pairs of populations (M. trossulus from North America (SAV) and M. edulis from Netherlands (NLOO)  whereas three groups of populations, M. edulis from America, M. edulis from Atlantic coast of Europe and Atlantic M. galloprovincialis, were mostly homogeneous (STF ranging from 0 to 0.006).The NJ tree showing the genetic relationships of 50 samples  was constructed based on the e matrix . Besidesulations . The greM. edulis population structure. Analysis was performed for 54 SNP and 25 samples of M. edulis from North America, Scandinavia, Arctic and Western Europe  value suggests further subdivision into four clusters with M. edulis splitting into two distinct groups: American and European populations  from seven populations of M. galloprovincialis  were properly assigned to the original taxon. Only five individuals from the Atlantic coast (BID and VIG) were considered potentially admixed . Single individuals from British Isles populations  were also assigned to the M. galloprovincialis cluster (q > 0.8), whereas from 30% to 90% of individuals from the British Isles, especially from Hebrides Scotland  showed very high levels of admixture and were ambiguously assigned to M. galloprovincialis and M. edulis, with genome admixture values q from 0.2 to 0.8. Additionally, single individuals  from Baltic Sea (BIA), North Europe , Spitsbergen (SPI) and North America (SNS) were assigned to two clusters, mainly M. edulis and M. galloprovincialis, and rarely M. trossulus and M. galloprovincialis (BIA).In STRUCTURE using M. trossulus and M. edulis taxa in 30 selected populations, comprising the 4 groups of populations: North America (13 populations), North Russia (7 populations), Scandinavia and Loch Etive (6 populations) and Baltic Sea (4 populations). Three populations from France (LOI), USA (IRD) and from Greenland (SAV) provided references of pure M. edulis and M. trossulus (q) for each individual by considering 54 allele frequencies, both species-specific and shared. The algorithm with the ΔK method [K = 2) indicating M. trossulus and other Mytilus taxa . M. galloprovincialis was ignored in further analysis because only a few individuals from the analyzed populations were considered potentially admixed with M. galloprovincialis   .M. trossulus (species-specific) were chosen to detect hybrid individuals by calculating the HI score  and Greenland  showed a high diversity. HI varied from 0.37 in Greenland populations to 0.85 in a population from Nova Scotia (KKA), and HIV (variance of HI) reaches 0.43 in the PBAY population. Most individuals were identified as pure M. trossulus or pure M. edulis using both Structure and NewHybrids. The others were identified as hybrids with q- value about 0.5, however F1 and F2 hybrids could not be distinguished using the Structure analysis method. By contrast NewHybrids revealed F1 hybrids in these 4 populations with a probability mostly over 0.9. The percentage occurrence of F1 hybrids varied from 12% (PBAY) to 24% (GLD) of individuals. F2 hybrids were not identified, while only a single backcross to M. trossulus was found.A total of 16 SNP markers with alleles having high frequency in pure HI score  and usinM. edulis. In two others  all individuals were identified as pure M. trossulus or M. edulis. In the remaining 4 populations, Structure revealed a small number of hybrids in proportion ranging from 0.03 to 0.12. NewHybrids revealed from 0.03 to 0.09 F1 hybrids with a probability over 0.99 and a single M. trossulus backcross. The values of HI varied from 0.02 , through 0.28  to 0.82  . Structure analysis showed pure M. edulis ranging from 0.86 to 1.0 in frequency with a few hybrids identified in populations from Bodø . NewHybrids with a probability mostly over 0.8 revealed single F1, F2 hybrid (0.03) and M. edulis backcrosses (0.03–0.17) as shown in M. trossulus and M. edulis taxa with HI reaching above 0.5. In Bergen, the percentage of hybrids reached 0.5. However, NewHybrids analysis with high probability revealed all hybrid categories in the population from Bergen and F1 hybrid and M. trossulus backcrosses in populations from Loch Etive. Populations from the Baltic Sea had low diversity with HI ranging from 0.63 to 0.72. Most of the populations showed a unimodal hybrid swarm with varying amounts of M. trossulus characteristic alleles . Only the Danish Straits population (STC) represented an admixture of the two taxa with only a single M. edulis individual and no F1 hybrids (Among seven populations from North Russia only one from White Sea (ONE) was identified as pure alleles) . Except  hybrids .Mytilus spp. (2 between 0.41 and 0.79) were for BM101A, BM113A, BM11A, BM12A, BM17B, BM202A, BM202B, BM203D, BM21B, BM21C, BM26B, BM54A, BM62A, BM67C, BM92B. Interestingly, these alleles did the best at discriminating M. trossulus from M. edulis and M. galloprovincialis or M. edulis from M. trossulus and M. galloprovincialis , whereas the best performing allele model (BM101A) did the best at discriminating M. galloprovincialis from M. edulis and M. trossulus (see result section above)  . In addia and ice cover contributed over 10% (sometimes nearly 40%) of the variability of allele frequencies. Overall, the predictive power of models only weakly reflected whether the variable region was included into the model or not . Thus, judging from the correlative evidence only, historical evolutionary processes do not dominate over selection between environments.As expected, inter-regional variability was important in many allele models, especially those explaining over 40% of variability in allele frequencies . HoweverM. trossulus occurred at 8–11 psu, 0–10 °C, 60–70% of ice cover and 0–2 mg m−3 of chlorophyll a, for M. edulis at 8–11 and 30–35 psu, 10–14 °C and 60–70% of ice cover, and for M. galloprovincialis at 30–35 psu, 14–20 °C . Thus, for the studied alleles the linkages between environmental drivers and the genetic variability of Mytilus spp. was random in respect to “coding” and “non-coding” regions.When quantifying the strength of associations between allele frequencies and the environment in alleles located in “coding” or “non-coding” regions  the allele models of “non-coding” regions had higher component of inter-regional variability (7.8%) compared to those of “coding” regions (3.2%) whereas the effect of salinity was stronger for coding alleles (4.2%) than for non-coding alleles (3.4%). However, the observed differences were not statistically significant  are in Canada. In the literature, M. edulis populations are described to be distributed along the American continental coast from Delaware Bay (38.5° N) and north [M. trossulus are found from the Gulf of Maine (44° N) and north [M. edulis  where these two species form a hybrid zone [M. trossulus, which was found to be more related to the North Pacific M. trossulus populations than the North Atlantic as for GLL and GLD [M. trossulus in the Atlantic [M. edulis is again located father south  from that of M. trossulus . From our data, as well as from the literature [M. edulis is distributed mostly discontinuously along the coasts of Europe up to the very distribution border in the Pechora Sea , the Bergen area in Western Norway (BER), and harbor areas in the White (CHU) and Barents (KOL) Seas in Russia. Several more M. trossulus outposts in the White and Barents Seas, all from harbor areas, were also reported [M. trossulus could be more widespread in Western Norway [M. trossulus was found together with M. edulis. The northernmost population of M. trossulus in Europe – BAR is at 69° N. Only M. edulis populations were found in Iceland  and on Spitsbergen . Thus, taking into account only geographic distribution, it could be difficult to postulate that M. trossulus is a more cold-water adapted species compared to M. edulis. Therefore, analyses directly based on correlation between species distributions and temperature and other environmental proxies rather than simply latitude was performed in this study to understand what contemporary factors actually control biogeographical distribution of Mytilus species.According to our data the east coast of the USA is dominantly inhabited by nd north , while Mnd north . Along tnd north ,91,92. Itebrates ). Along rid zone . The nor and GLD . At leasAtlantic ,26,35. Oterature ,20,48, i69.5° N, ,20), thereported . Single n Norway  and in Nn Norway . In eachM. trossulus are not genetically homogenous, but are subdivided into two clusters, Baltic populations and all other settlements. Distinctness of the Baltic mussel is primarily explained by its mixed nature due to the strong introgression of M. edulis genes , indicates either relatively long (thousands rather than hundreds of years) vicariance [M. edulis . M. edulis populations are subdivided into three clusters, the American and West European are most distinct, but internally quite homogenous, while North European (admixed) is heterogeneous and intermediate between the other two. The Danish Straits have been proposed as a border between the West- and the North European clusters [M. edulis in Europe was revealed only in recent SNP-based research , the region was colonized both from Europe and from America. Subsequent gene flow homogenized mitochondrial diversity, but not the nuclear diversity through Europe. Indeed, mussels are prone to differential mitochondrial DNA introgression. For example, the Baltic populations, although being dominated by M. trossulus nuclear genes, are virtually fixed for mitochondrial haplotypes of M. edulis [M. galloprovincialis populations have been reported partly introgressed with M. edulis mitochondrial haplotypes [clusters . The macesearch  and along the Atlantic coast of Iberian Peninsula (the Atlantic lineage). The complex contact zones with M. edulis in southern France [M. galloprovincialis from Scotland could be defined as ‘pure’ , while the presence of M. galloprovincialis alleles was considerable in mixed populations with M. edulis from Scotland , but negligible (<5%) in other samples. The results of our study correspond to the results of the recent study by Simon and co-authors [M. galloprovincialis in Atlantic Europe and its hybridization with M. edulis. They discovered invasive populations of the Mediterranean lineage in multiple French harbors up to Le Havre north (49.5° N) and confirmed earlier records [M. galloprovincialis) in Norway in the Ålesund area and Lofoten Iles (68° N). Each time M. galloprovincialis were found to hybridize with native mussels  and were being introgressed with their genes. In its turn, the reference natural Scottish M. galloprovincialis population was different because it represented the Atlantic lineage introgressed with the North European M. edulis genes. Further Simon et al. [M. galloprovincialis presence in the Arctic was overestimated considerably at the individual and population levels. The overestimation has been generated by using Atlantic M. galloprovincialis introgressed with M. edulis alleles as a reference sample, which reduced the actual diagnostic power of SNPs used by Mathiesen et al [M. galloprovincialis genes to the genetic composition of Spitsbergen M. edulis populations was confirmed, which is in line with our observations. Occurrence of the Mediterranean mussel in Northern Europe well illustrates its long-known ‘superficial’ abilities as an invasive species, but also questions the prognostic power of species-distributions models  predictM. trossulus or M. edulis taxa and a low frequency of hybrid mussels, mainly F1 and single M. trossulus backcrosses, were found in the arctic and subarctic region in Russia and America  indicated high admixture of two taxa and a bimodal hybrid zone. This type of hybrid zone largely consists of genotypes resembling the parental forms, with only few intermediates [M. trossulus and M. edulis mussels coexist and hybridize present a completely different population structure. Pure taxa plus all hybrid categories were found in Norway and a large number of hybrids in other locations like Scotland and Baltic Sea [HI was very low , pointing to a unimodal hybrid swarm. In Scotland and Norway, we observed intermediate genotypic distributions that consist of a slightly more even mixture of parental and hybrid genotypes. A characteristic feature of the Scandinavian and Arctic mussels with M. edulis genomes is admixture of American and European clusters  that are not directly exposed to the warm Gulf Stream of the Atlantic Ocean were not characterized by such large M. galloprovincialis introgression. Dias et al. [M. galloprovincialis alleles throughout the northwest and northeast of mainland Scotland and the Shetland Islands.According to our data pure Azov Sea ,21, whers et al. , using oM. edulis, M. trossulus and M. galloprovincialis and their hybrids. We expected that interregional differences would account for a large part of the genetic variability of Mytilus spp., but within region environmental variability would strongly modulate the genetic differentiation [Mytilus spp. [M. trossulus from M. edulis and M. galloprovincialis. These alleles did not involve the functionally important genes, which products can affect resistance to stress and tolerance to changes in environmental variables [In order to evaluate the role of environmental conditions in shaping local genetic structure we quantified correlative links between key environmental drivers and the genetic variability of the three species ntiation ,51. Our lus spp. ,107,108.ariables .Mytilus spp. [Mytilus species-complex possesses a high degree of phenotypic plasticity, different species show differences in physiological responses to environmental conditions. In general, M. trossulus is the northernmost species, tolerant to cold waters, but also brackish waters, and is often found in areas which have been ice-covered in previous ice ages. M. edulis inhabits the cold, but temperate waters, but can also occur in brackish waters. The European southern range of M. edulis on the Atlantic coast overlaps with M. galloprovincialis, which is a temperate marine warm water species inhabiting more exposed locations in the south European/Mediterranean Seas, e.g., [Earlier literature suggests that salinity and temperature drive the patterns of hard bottom intertidal species including lus spp. . Althougs, e.g., ,98.M. trossulus and M. edulis. The strong effect of salinity was also expected as salinity varied over a large range in the study area. Several studies have documented that M. trossulus tolerates lower salinity better than M. edulis both as adult [M. trossulus genes, which are more tolerant to low salinities [M. trossulus in the entrance area of the Baltic Sea, but a strong introgression of M. edulis in the Baltic Sea proper such that no pure M. trossulus genotypes were identified. The segregation of M. trossulus in the brackish Baltic Sea and in lowered saline central Greenland fjords impacted by a freshwater input from snow melt and glacial input  is in contrast to the western Atlantic clade  and the North Greenland (SAV) where M. trossulus is found at more open wave-exposed coasts. Similarly, Riginos and Cunningham [M. edulis dominates in sheltered areas of low salinity and M. trossulus on wave-exposed open coasts in the Western Atlantic.This study identified salinity as the primary driver for at least the distribution of as adult ,49,110 aas adult ,112. An linities ,113,114.nningham  have conMytilus spp., but to lesser extent than salinity. Relationship between temperature and intertidal animals are complex. During submergence intertidal organisms mostly experience a stable water temperature whereas during emersion when exposed to air they often experience much warmer or colder climate. The wetness gradient  defines the realized effect of temperature on intertidal organisms. In our modeling, however, solar irradiance, tidal and wave regime had only marginal effects on the variability in the studied allele frequencies.In the present study, temperature was also found as an important driver of the spatial patterns of genetics of M. edulis for example require summer temperatures of a minimum of 4 °C [M. edulis are favored over M. trossulus [M. trossulus that often occurs in ice covered areas. While M. edulis has been shown to start their spawning in late spring, M. trossulus generally starts later in the summer [M. trossulus to dominate areas with longer-lasting sea ice. Popovic and Riginos [Mytilus taxa in Northern Hemisphere and demonstrated that M. galloprovincialis inhabits waters characterized by much higher mean surface temperature in comparison with M. edulis and M. trossulus. M. galloprovincialis has physiological and metabolic adaptations to higher sea water temperature in comparison with M. edulis and M. trossulus [Mytilus hybrid zones, we expected that the taxa specific alleles would be correlated to some extent with the functional genes related hereto . Mytilus spp. attach to their substrate by byssus threads and studies have shown differences in preferences to wave action between Mytilus species [M. trossulus tended to induce changes in Hsp levels at lower temperatures than the warmer-adapted M. galloprovincialis [Mytilus.Adult  of 4 °C . On the rossulus . Similare summer ,117, pav Riginos  summarizrossulus ,121,122. species ,52. In aMytilus taxa has been performed by Malachowicz and Wenne [Mytilus specimens from natural environments. Their study performed on 24 individuals of Mytilus congeners collected from natural environments differing in temperature suggested a positive temperature-dependent selection as a factor influencing molecular divergence between warm and cold tolerant Mytilus taxa. Among thermotolerant candidate genes exhibiting differentiated expression were mentioned genes of oxidative stress response and cytoskeletal stabilization, including Hsp. The authors concluded that expression and sequence divergence can be correlated at the multigene level. Changes in transcriptome expression have been observed after exposure of M. edulis from the Gulf of Maine to increased temperature, CO2 induced acidification, and lowered food concentrations under laboratory experimental conditions [M. edulis and M. galloprovincialis larvae in response to elevated temperature [M. edulis [M. edulis population northward by 350 km of Cape Hatteras has been a sign of serious displacements of populations, which should be expected as a consequence of global climate changes [M. edulis and M. galloprovincialis populations in Europe in response to climate changes in the North Atlantic area has been also predicted by an individual-based model [Finding differences at the level of genotype/allele dependent gene expression in response to environmental variables requires a candidate gene approach and transcriptome analysis. Mantle transcriptome comparison among nd Wenne . While Fnd Wenne  demonstrnd Wenne  used tranditions . Those cperature . Differe. edulis . A contr changes . A northed model .Mytilus spp. display high plasticity to environmental changes, studies on ecological effects of introgression and hybridization points to significant differences in fitness, including less resilience in hybrids and backcrosses compared to parental species [While climate reconstructions have demonstrated that the Earth has experienced oscillations in both warming and cooling periods over the past several millennia , the cur species ,62,129. Mytilus mussels from over 50 locations using single nucleotide polymorphisms. We found three main groups of populations representing M. edulis, M. trossulus and M. galloprovincialis as well as nine clades with a strong evidence of geographic structure and different admixture level. Populations of M. trossulus from North America and North Russia grouped separately from introgressed M. trossulus/M. edulis Baltic Sea and other populations from Europe  and Greenland. Three separate groups of M. edulis populations were found: pure American, American and European admixed in Scandinavia and Arctic and pure European. In addition, a separate group was composed of admixed Scotland M. edulis/M. galloprovincialis populations. As expected, populations of Atlantic and Mediterranean M. galloprovincialis formed two separate groups.We studied the genetics of Amphi-Atlantic and Arctic populations of Mytilus taxa hybridize in the contact area and create hybrid zones. Hybridization and introgression with local congeners result in mixed populations. The mixed populations are mainly bimodal in the Arctic and Subarctic region in Russia and America for M. trossulus and M. edulis taxa. However, in other European populations intermediate genotypic distributions between M. trossulus and M. edulis (Scotland and Norway) or M. edulis and M. galloprovincialis  were observed. Finally, the hybridization zone can take the unimodal form as in the inner Baltic, creating a hybrid swarm.All three Mytilus spp. Importantly, the linkage between environmental variables and the frequency of most alleles was not affected whether alleles were located in the coding or non-coding regions.Correlative species distribution models are frequently applied as a sophisticated tool to improve our understanding of the relationship between environment and biota. Here, we applied boosted regression trees modeling technique to evaluate the role of environmental conditions in shaping local genetic structure of However, in a more targeted analysis based on functional genes, two SNPs at Hsp70 and ATPase genes showed linkage with environmental variables. In addition, inter-regional variability was important in many allele models, but this source of variability did not prevail over variability in local environmental variables.a concentration were the greatest predictors among different allele models in the studied populations of Mytilus. In most cases changes in the allele frequencies along these environmental gradients were abrupt and occurred at a very narrow range of environmental variables. The few established functions between environmental gradients and the genetics of Mytilus spp. provide good starting conditions to understand how local environment would potentially shape species distributions and help us forecast future scenarios.Among the studied environmental variables salinity, water temperature, ice cover and chlorophyll


Although domestic cavies are widely used in sub-Saharan Africa as a source ofmeat and income, there are only a few studies of their population structure andgenetic relatedness. This seminal study was designed with the main objective toassess the genetic diversity and determine the population structure of cavypopulations from Cameroon to guide the development of a cavy improvementprogram. Sixteen microsatellite markers were used to genotype 109 individualsfrom five cavy populations . Twelvemarkers worked in the five populations with a total of 17 alleles identified,with a range of 2.9 to 4.0 alleles per locus. Observed heterozygosity (from0.022 to 0.277) among populations was lower than expected heterozygosity (from0.42 to 0.54). Inbreeding rates between individuals of the populations andbetween individuals in each population were 59.3% and 57.2%, respectively,against a moderate differentiation rate of 4.9%. All the tested loci deviatedfrom Hardy-Weinberg equilibrium, except for locus 3. Genetic distances betweenpopulations were small (from 0.008 to 0.277), with a high rate of variabilityamong individuals within each population (54.4%). Three distinct genetic groupswere structured. This study has shown that microsatellites are useful for thegenetic characterization of cavy populations in Cameroon and that thepopulations investigated have sufficient genetic diversity that can be used tobe deployed as a basis for weight, prolificacy and disease resistanceimprovement. The genetic of diversity in Southern Cameroon is wide andconstitute an opportunity for cavy breeding program. Caviaporcellus L.) exist that serve for meat consumption, income generationand manure production in mixed crop-livestock systems . However, in numerous sub-SaharanAfrican countries considerable populations of domestic cavies . Except for two development projects Hardouin , howeverSince 2001, the use of cavies has been promoted by the Ministry of Livestock,Fisheries and Animal Industries in Cameroon as part of short-cycle livestock speciestargeted to meet the national demand for animal proteins .Domestic cavies are widely reared and consumed in Cameroon  region, and Mémé and Fako in the Southwest region ofCameroon. The Littoral and Southwest administrative regions of Cameroon, aunimodal agro-ecological zone, are located between 2°6' and6°12' north, 8°48' and 10°30' east,with elevations from 0 to 4095 m a.s.l. This region occupies an area of 4.5million ha, of which 282,000 ha (6.3%) are cultivated with agricultural crops.The climate is typically equatorial: with an average annual rainfall of 2500 to4000 mm, air humidity of 85 to 90%, and mean monthly temperature between 22 and29°C FAO .A total of 109 blood samples were collected from adult cavies of about fourmonths of age.To select within the five populations, the snowball method wasused , according to the manufacturer’sinstructions and air dried.For the total DNA extraction, twenty 1.5 mm punches of the FTA Card blood spotswere added to 1 ml of 100 mM Tris pH 8, 0.1% SDS and the supernatant was removedafter 30 min of agitation. A total volume of five hundred µl of 1.5 Mguanidinium thiocyanate was added, and after 10 min of vortexing all thesupernatant was removed. The discs were then washed three times with 500µl of triple distilled water, with 10 min of centrifugation between eachwash. Then, 50 µl triple distilled water was added to the discs and themixture placed in a water bath and heated to 90 °C for 20 min. After 30min of cooling, DNA was recovered by centrifugation and stored at20°C.Caviaporcellus were evaluated , 200 μM of each dNTP, and 0.4 U of DreamTaq DNA polymerase(Fermentas). PCR conditions were: 95°C for 3 min, followed by 35 cyclesof 30 sec at 94°C for template denaturation, 30 sec at 60°C primerannealing and 60 sec at 72°C for primer extension, followed a finalprimer extension step at 72 °C for 20 min. PCR products were analyzedusing 1.5% agarose gel electrophoresis.Sixteen microsatellite markers previously reported for the species The data was captured using the GenScan ® collection software (AppliedBiosystems) and the allelic data analyzed using the GeneMapper ® softwareversion 4.1 (Applied biosystems). A total 103 data points were achieved out ofthe expected 109 data point giving an overall success rate of 94.5 % .The datawas compiled into a spreadsheet as a standard GeneMapper output file and used insubsequent analysis.Allele scoring was done using GeneMapper software V4.1 Timothy . The obsthnumber of population, Bayesian probabilistic group assignment was done usingSTRUCTURE software . K values analyzed ranged from to 1-5and each one was simulated five times. Correlated allele frequency with mixingmodel was used for runs with 100,000 iteration following a 10,000 burn-inperiod. The Delta K method described by Evanno et al.  while Wouri had the greatest number (4.00).Poutougnigni et al.  andWikoCavia magna and Cavia aperea. The high rate ofinbreeding (0.60) observed in the studied populations could help explain the lowrates of observed and expected heterozygosity. On the other hand, the largestdeviation from expected heterozygosity  was lower than that reported by Burgos-Paz et al. (In the whole studied populations, the expected heterozygosity was high than theobserved heterozygosity. The same observation have been done by Wikondi et al. and Poutz et al. .C. aperea, but deviation in theloci cavy1, 5 and 10 in C. magna. Burgos-Paz et al. (Except for locus cavy 3, all studied loci deviated from Hardy-Weinbergequilibrium in the general population. These results differ from those obtainedby Kanitz et al. , who obsz et al.  record aThe deviation from the equilibrium in this study can be explained by the factthat in Cameroon, the average size of a cavy population is 18 per household(Ngou Ngoupayou et al. 1995; Yiva et al. The high rate of molecular variance observed between individuals from differentpopulations and between individuals of the same population have been alreadyreported as well by Wikondi et al.  and PoutThe five populations in this study were structured into three distinct geneticgroups. Evolutionary theory of populations can help explain these groups.According to Mohamed et al. ,the genA low level of genetic structure as observed in this study and a high rate ofinbreeding has been reported from several production systems. This could beattributed to nonrandom mating and selection (e.g., Granevitze et al. The results of this study show that existing microsatellites developed for cavypopulations in South America are useful tools for the genetic characterization ofcavy populations in sub-Saharan Africa. They indicate that the studied populationsfrom southern Cameroon have a satisfactory genetic diversity that can be used as abasis for conservation of and selection from this small livestock species to improveproductivity. Future studies should expand to include cavy populations from northernand northwestern regions of Cameroon as well as those from other African countries.This may help not only to identify useful pockets of less related genetic diversityfor improvement but also clarify the possible evolution of domestic cavy on theAfrican continent.


Aedes albopictus is an indigenous primary vector for dengue and Zika viruses in China. Compared with its insecticide resistance, biology and vector competence, little is known about its genetic variation, which corresponds to environmental variations. Thus, the present study examines how Ae. albopictus varies among different climatic regions in China and deciphers its potential dispersal patterns.Ae. albopictus populations collected from three climatic regions of China were investigated with 11 microsatellite loci and the mitochondrial coxI gene.The genetic variation and population structure of 17 ne value increasing from the temperate region (3.876) to the tropical region (4.144). Twenty-five coxI haplotypes were detected, and the highest diversity was observed in the tropical region. The mean Ho value (ca. 0.557) of all the regions was significantly lower than the mean He value (ca. 0.684), with nearly all populations significantly departing from HWE and displaying significant population expansion . Two genetically isolated groups and three haplotype clades were evaluated via STRUCTURE and haplotype phylogenetic analyses, and the tropical populations were significantly isolated from those in the other regions. Most genetic variation in Ae. albopictus was detected within populations and individuals at 31.40 and 63.04%, respectively, via the AMOVA test, and a relatively significant positive correlation was observed among only the temperate populations via IBD analysis . Recent dispersions were observed among different Ae. albopictus populations, and four major migration trends with high gene flow (Nm > 0.4) were reconstructed between the tropical region and the other two regions. Environmental factors, especially temperature and rainfall, may be the leading causes of genetic diversity in different climatic regions.Of 44 isolated microsatellite markers, 11 pairs were chosen for genotyping analysis and had an average PIC value of 0.713, representing high polymorphism. The number of alleles was high in each population, with the Ae. albopictus populations across different climatic regions, and environmental factors, especially temperature and rainfall, may be the leading causes of genetic variation.Continuous dispersion contributes to the genetic communication of  Aedes (Stegomyia) albopictus, also known as the Asian tiger mosquito, is an epidemiologically critical vector for its transmission of several arboviruses, including dengue virus (DENV), Zika virus (ZIKV), chikungunya virus and filarial nematodes, such as Dirofilaria immitis [Aedes aegypti, the primary vector for DENV and ZIKV, Ae. albopictus is generally considered to be a less efficient vector due to its less anthropophilic behavior and inferior adaptation to urban domestic environments [Ae. aegypti. Meanwhile, combined with its strong ecological plasticity, global trade, such as the transportation of used tires and “lucky bamboo,” has also accelerated the global spread of this species from its original Southeastern Asian distribution to every continent except Antarctica [ immitis –4. Comparonments . Howevertarctica . Currenttarctica .Ae. albopictus has population dynamics and vector competence that are also greatly influenced by environmental conditions [Ae. albopictus populations, mainly based on their influence on mosquito abundance, survival, size, fecundity and competence for certain arboviruses [Ae. albopictus populations associated with various environmental conditions [Ae. albopictus in certain regions and providing necessary information for subsequent mosquito control.Natural environmental variation is responsible for fluctuations in insect population dynamics, distribution and biology, including population number, intensity and feeding behavior . An imponditions , 10. Numoviruses –15. Howenditions –18, althAe. albopictus and facilitate its breeding and dispersal throughout the country [Ae. albopictus from its original environment to a new environment facilitates the manifestation of new phenotypes and the increase of mutated alleles in frequency, and thriving international travel and trade provide essential routes for the continuous introduction of arboviruses from other countries, especially those in Southeast Asia, where Ae. albopictus originated [Ae. aegypti and Ae. albopictus among these regions [Ae. aegypti (an invasive species distributed only in the southern area of China), Ae. albopictus is an indigenous Chinese mosquito, ranging from Dalian in the north to Hainan in the south [With the advent of urbanization in China, the natural environment was altered tremendously; more people have moved from rural areas to cities, and trade has increased between cities and rural areas. All these processes create suitable habitats  for  country –22. Meaniginated , thus pu regions . In conthe south , 26. Morhe south , 28. ItsAe. aegypti and Ae. albopictus, where it helps them occupy diverse niches and respond quickly to evolutionary challenges [Ae. albopictus have been successfully isolated and employed in Ae. albopictus population studies on a global scale, and they continue to be a popular choice of genetic marker [Ae. albopictus microsatellites, the mitochondrial coxI gene has frequently been used for mosquito barcoding and invasive species monitoring because of its conservation and high accuracy when distinguishing sequence variation at the interspecies level and its usefulness in investigating population dispersal routes of mosquitoes [High genetic variation is ubiquitous in vector populations, especially in invasive vectors, such as allenges . Microsaallenges . To datec marker , 31–33. squitoes –38.Ae. albopictus and decipher the potential dispersal patterns of Ae. albopictus among different climatic regions, a total of 17 Ae. albopictus populations were collected and examined via 11 microsatellite loci and the coxI gene. The results provide information for the future control of Ae. albopictus in China.To evaluate how environmental factors affect genetic diversity and dispersal patterns of All mosquitoes were sampled from the three main climatic regions of China, including tropical, subtropical and temperate regions. The annual accumulated temperature and precipitation for the tropical region is > 8000 ℃ and 1500–2000 mm, respectively, with the lowest monthly average temperature being 15–24 ℃. These data for the subtropical region are between 4500 and 8000 ℃ and > 1000 mm, respectively, with the lowest monthly average temperature being 0–15 ℃. These data for the temperate region are between 3000 and 4500 ℃ and 700 mm, respectively, with the lowest monthly average temperature being – 8 to 0 ℃ , 40.Ae. albopictus larvae were sampled from 17 geographically diverse sites across three environmentally distinct regions of China from June to August 2018; all the sampling site information is described in Fig. In the present study, ca. 600 Ae. albopictus by magnetic-bead enrichment and PCR screening, and all markers were found to be highly polymorphic via denatured polyacrylamide gel electrophoresis (D-PAGE). A set of 11 microsatellite loci was employed for genotyping the 17 Ae. albopictus populations. Detailed microsatellite primer information is listed in Table Referring to Chambers et al. , microsacoxI sequence polymorphism was investigated among 497 individuals . Briefly, DNA amplification of a 550-bp fragment of coxI was performed on a T100 Thermal Cycler  with the following primer set: 5′-GGAGGATTTGGAAATTGATTAGTTC-3′ (F-coxI) and 5′-CCCGGTAAAATTAAAATATAAACTTC-3′ (R-coxI) in a 50 µl reaction mix containing 10 µl PCR reaction buffer , 4 µl dNTPs , 1 µl primers  and 0.5 µl PrimeSTAR HS DNA polymerase . The PCR amplification program was set as follows: pre-denaturation at 94 °C for 3 min, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 54 °C for 45 s and elongation at 72 °C for 1 min, with a final elongation at 72 °C for 10 min. All the PCR products were detected and separated by 2% agarose gel electrophoresis. The target fragments for coxI were then cut from the gel under UV light and purified with the GenElute™ PCR Clean-Up Kit . Each purified PCR product was then cloned into the pCR™2.1 vector with a TA Cloning™ Kit  and selected by bacteria liquid PCR with the T7 promoter primers. Finally, at least 20 positive clones for each PCR product were sequenced on both strands using an ABI 3730XL automatic sequencer .As described by Bonacum et al. , coxI sea and ne, were assessed with Cervus version 3.0.7 [K method of Evanno et al. [K value; the parameters were set as follows: (1) K ranged from 1 to 20 with ten iterations for each K value; (2) an admixture model was chosen with a Markov chain Monte Carlo algorithm run for 100,000 iterations and 1,000,000 repetitions. The optimal K value was calculated via Structure Harvester: http://taylor0.biology.ucla.edu/structureHarvester/ and depicted with Distribut version 1.1. The DAPC analysis was performed on the microsatellite date of each population with the R packages “Adegenet 2.1.3” [ST value for each population were evaluated with the AMOVA test via Arlequin version 3.5.2.2 [The microsatellite data were processed with GeneMapper v.4.0 . All markers were tested for polymorphism by determining their polymorphism information content (PIC) values via PIC-Calc 0.6 , and theon 3.0.7 . The Ho,on 3.0.7 . Departuon 3.0.7 . Additioon 3.0.7  and the o et al.  were empt 2.1.3” , and thet 2.1.3” , respect 3.5.2.2 .ne, Shannon index, Hd, H and π) and environmental factors  were described via principal component analysis (PCA) and multiple factor analysis (MFA) with the R package “FactoMineR” [The haplotypes of all the populations were screened by DnaSP version 6.0 , and thetoMineR” .Ae. albopictus, 11 pairs of which were highly polymorphic and were therefore chosen for microsatellite genotyping analysis  in each Ae. albopictus population was very high, and the mean na value in each climatic region ranged from 6.909 to 8.091 without a significant difference. In contrast, the effective number of alleles (ne) ranged from 3.501 to 4.525, and the ne value increased from the temperate region (3.876) to the tropical region (4.144). The mean value of observed heterozygosity (Ho) for all the climatic regions was ca. 0.557, which was significantly lower than the expected heterozygosity (He) (ca. 0.684). The FIS value of each climatic region ranged from 0.266 to 0.359, and the Ae. albopictus populations significantly departed from HWE, except in two locations, SHJD and KZXZ  revealed that nearly all the populations from the temperate and subtropical regions displayed significant population expansion with p values < 0.05, while no significance was observed among all the tests for the Ae. albopictus populations from the tropical region after Bonferroni correction  based on an analysis of the coxI sequences. The haplotype indices  changed dramatically across Ae. albopictus populations from different climatic regions  ranging from 0.014  to 0.190 . The average number of nucleotide differences (k) ranged from 0.067  to 0.929 , and the number of polymorphic sites ranged from 1 to 5 across all the populations. Overall, the tropical Ae. albopictus populations showed the highest diversity, with mean values of Hd, π and k reaching 0.657, 0.156 and 0.763, respectively, whereas the temperate populations showed the lowest diversity.In all, a total of 25 Ae. albopictus populations were adequately allocated to two clades with significant genetic differences, and the best K value, as determined via the ΔK method of Evanno et al., was also equal to two . Meanwhile, the pairwise FST values between populations ranged from 0.008  to 0.141 . Genetic differentiation was significant between all the sampled populations after Bonferroni correction (p < 0.05) except for five pairs of FST values among the subtropical populations NNXZ, NJTH, NJDX, KZXZ and temperate populations ZGND, BHBG, QDDX and HBSD , while no such evidence was observed in the other two regions  of Clade III was the most frequent haplotype and was distributed from the tropical to the temperate region with an increasing trend. Nearly all the other haplotypes derived from H1 with one or two mutations, with Clade I mainly distributed in the tropical region and Clade II mainly distributed in the southern subtropical region , and unimodal mismatch distributions were observed among the different Ae. albopictus populations  and included five haplotypes (H2–H3 and H5–H7) that were distributed in only the southern subtropical region. Clade III was an admixture group containing all the remaining 14 haplotypes, 2 of which were observed in the tropical region and four in the climatic regions  and two environmental factors  contributed equivalently to the first axis of the PCA, explaining up to 95.2% of the variation; the exception was the environmental factor latitude, which contributed more to the second axis, with a proportion of 17.5%. Combining these results with hierarchical clustering via MFA, all 17 Ae. albopictus populations were clustered into three groups, of which cluster II and cluster III were closely related to each other. When environmental factors were regarded as the major influencing factors, the molecular diversity indices  of the populations in the tropical region were significantly higher than those in the other regions  from Guangdong Province , H19 (22.1%) from Yunnan  and Hainan provinces , and H30 (10%) from Hainan Province ; likewise, Zhang et al. also detected 25 haplotypes across China, and 48% (12 out of 25) of these haplotypes were detected in only tropical and subtropical regions. Both studies corroborate our findings that the haplotype diversity of the tropical and subtropical regions is higher than that of the temperate region. Continuous dispersal from neighboring Southeast Asian countries may be the reason for the higher diversity of the Ae. albopictus populations in the tropical and subtropical regions and that the origins of the Ae. albopictus populations of these two regions may be different. Furthermore, the mismatch analysis results revealed recent population dispersal among the different climatic regions, which is the main reason for the universal distribution of the remaining haplotypes. As an important and rapidly adapting insect, Ae. albopictus has biological characteristics that are strongly influenced by environmental conditions [Ae. albopictus; when this mosquito migrates from a tropical region to a temperate region, it needs time to adapt to the new environment, especially to survive during the winter period, which causes diapause in Ae. albopictus [Ae. albopictus, the activity of host-seeking females was positively affected by temperature and rainfall [Ae. albopictus populations from different climatic regions.In the present study, nearly 44% (11 out of 25) of these 25 detected haplotypes were observed only in the tropical and subtropical regions. The same result for Chinese g et al. , 75. Guo and H30 % from Harainfall . The PCAFST values between populations were significant, the values were not high, which indicates potential anthropogenic exchange between the populations. A study by Schmidt et al. [Ae. albopictus collected from 12 sample sites in Guangzhou also found that human transportation networks, particularly shipping terminals, influenced the genetic structure of Ae. albopictus populations. With the development of China, the rapid expansion of high-speed rail, aircraft routes and highways between different climatic regions has not only facilitated trade among different cities but also accelerated the spread of mosquitoes. Accordingly, only two genetically separated clades were observed among these populations, and molecular variations within populations and individuals were found to contribute to the genetic differentiation between these populations. As a global invasive species, Ae. albopictus has developed several strategies to cope with a broad range of temperatures and adapt to local thermal conditions [p value of the Mantel test.Corresponding to the results of Kotsakiozi and Manni et al. , 77, whit et al.  of the gnditions , 71, whinditions , 77–83. Ae. albopictus in different climatic regions will help in the selection of appropriate mosquito control strategies, and since dengue fever continues to break out in Southern China every year, monitoring the potential migration routes of Ae. albopictus can also predict the potential transmission routes of this virus and help prevent its further spread.Overall, strong dispersal patterns were observed in Southern China, and frequent dispersals have occurred from the tropical and subtropical regions to the temperate region. Monitoring the population structure and potential migration routes of Ae. albopictus populations across different climatic regions of China. All 17 Ae. albopictus populations were genetically structured into two isolated clades, in accordance with their locality or region of origin, and three major haplotype clusters were observed via phylogenetic analysis of coxI. These results suggest different evolutionary histories in changing environments, especially differences in temperature and rainfall. Meanwhile, four major migration trends were observed among the different climatic regions with high gene flow; these trends contribute to the similarity of the Ae. albopictus populations.The present study systematically evaluated the genetic variation, population structure and haplotype-based phylogenetic relationships of Additional file 1: Table S1. Sampling information of 17 Ae. albopictus populations collected from three different climatic regions of China.Additional file 2: Table S5. Genetic diversity of 11 microsatellite loci developed for Ae. albopictus based on samples (n = 502) collected from three different climatic regions of China.Additional file 3: Figure S1. Linkage disequilibrium analysis at each pair of Loci across all 17 Ae. albopictus populations.Additional file 4: Table S2. Heterozygosity tests of all 17 Ae. albopictus populations based on SMM model.Additional file 5: Table S3. Haplotype diversity of 17 Ae. albopictus populations based on coxI collected from three different climatic regions of China.Additional file 6: Table S4. Population differentiation estimation of the FST value  and Geographic distance  among all 17 Ae. albopictus populations.Additional file 7: Figure S2. Isolation by distance analysis of all 17 Ae. albopictus populations.Additional file 8: Figure S3. Historical demography analysis of Ae. albopictus inferred from mtDNA coxI sequences.Additional file 9: Figure S4. Migration analysis of all 17 Ae. albopictus populations inferred from microsatellite data.


Rattus tanezumi is a common domestic rat and host of the bubonic plague pathogen in China and Southeast Asia (SEA). The origin, genetic differentiation and dispersal of R. tanezumi have received increasing attention from researchers. The population genetics of R. tanezumi based on its mitochondrial cytochrome b gene have been studied to explain the origin, relationships and dispersal of populations. In this study, we captured a total of 229 rats; morphological and molecular biological identification cytochrome oxidase subunit I (COI) confirmed 131 R. tanezumi individuals collected from 6 provincial areas, and their Cytb gene sequences were analyzed. The results showed that the population in Mohan (MH), Yunnan, had the highest genetic diversity, while that in Ningde (ND), Fujian, had the lowest. Tajima’s D statistic for all populations was negative and nonsignificant, indicating the possible expansion of R. tanezumi populations. Low gene flow occurred between the Zhangmu (ZM) R. tanezumi population and other populations, and the genetic differentiation among them was high. Furthermore, our analyses revealed the ZM lineage was the oldest lineage among the groups and diverged ~1.06 Mya, followed by the Luoyang (LY) lineages (~0.51 Mya) and Yunnan lineage (~0.33 Mya). In southeastern Yunnan, the Jinshuihe (JSH) and MH populations were more closely related to the populations in southeastern China (Fuzhou (FZ), ND, Quanzhou (QZ), Nanchang (NC)) and inland areas (Chongqing (CQ), LY) than to those in other areas of Yunnan (Jiegao (JG) and Qingshuihe (QSH)), indicating that R. tanezumi may have spread from southeastern Yunnan to the interior of China. In summary, R. tanezumi may have originated in ZM and adjacent areas, spread to Yunnan, and then spread from the southeast of Yunnan inland or directly eastward from ZM to inland China. Rattus tanezumi belongs to Mammalia, Rodentia, Muridae, and Rattus and is distributed throughout most parts of East and Southeast Asia (SEA). R. tanezumi is a common commensal rat in China, where it is also known as the roof rat [R. tanezumi is a medium-sized rat, presents a more slender profile than Rattus norvegicus, and has agile movement and strong climbing abilities. R. tanezumi often inhabits roofs, wall gaps, and ceilings, thus causing damage to family living areas [R. tanezumi has expanded significantly because of environmental changes, transportation development, and climate change associated with urbanization [R. tanezumi inhabiting scrap ships imported from North Korea for the first time. Trains from Tibet to Chongqing were also found to harbor R. tanezumi. Additionally, a stable population of this rat was detected in Linfen City, Shanxi Province, in 1989 [R. tanezumi has been expanding. This species is now found in 13 counties of Shanxi Province in areas such as Yuncheng, Changzhi, Jinzhong, Taiyuan, Xinzhou, etc., and its distribution extends into the urban and rural areas of Shanxi. In March 2017, members of this species were caught in the almond forest next to the walnut village of Fenxi County [R. tanezumi has a wide range of activities, it can move back and forth between indoors and outdoors. Traces of its activities are found everywhere, which facilitates the spread of gastrointestinal diseases. These rats harbor ectoparasites, such as mites, and internal parasites, such as protozoa, trematodes, and nematodes. This species is a reservoir host for bacteria, rickettsia, and viruses. R. tanezumi can spread infectious diseases, such as plague (Yersinia pestis), leptospirosis (Leptospira), ascariasis, endemic typhus, and hemorrhagic fever with renal syndrome (Hantaan virus).roof rat . R. taneng areas . This rang areas . In recenization –6. In 20 in 1989 . The disR. tanezumi provides important data for the analysis of the evolutionary potential and future fate of R. tanezumi and helps reveal the causes and processes underlying R. tanezumi migration and expansion [Rattus sp. with DNA barcoding using cytochrome oxidase I (COI) sequences or tree-based methods using D-loop, cytochrome b and COI sequences.The level of genetic diversity within a species is a result of long-term evolution. Decreased genetic diversity leads to a decline in the ability of organisms to adapt to their environment and survive . Speciesxpansion . The mitxpansion , 12. In xpansion  reliablyCytb genes have a moderate evolutionary rate in the mitochondrial genome [Cytb genes are not severely affected by the saturation effect, and the levels of phylogenetic and genetic differentiation are more suitable for analyzing the differences among species and genera [Cytb gene in animal mitochondria is considered to be a good indicator of the degree of genetic differentiation between related species and within species [Cytb gene sequence and showed that the Nile tilapia population in the lower reaches of the Beipan River had rich genetic diversity.l genome , and a sd genera , 16. The species , 18. Yi  species  studied R. tanezumi populations. For example, Zhao et al. [R. tanezumi that river barriers have almost no effect on the genetic pattern of this species. Guo et al. [R. tanezumi in mainland China was the result of shipping transportation, which led to the subsequent expansion from coastal areas into Central China along the Yangzi River. Furthermore, the linkages between populations in Tibet and Sichuan, revealed by analyzing microsatellite markers and mitochondrial DNA sequences point, to a modern-era introduction via the Chuan-Zang highway rather than the Tea Horse Ancient Road.With the development and application of molecular biology, molecular marker technology has been increasingly applied to the genetic study of o et al.  demonstro et al.  suggesteCytb as a molecular marker for 11 geographical populations of R. tanezumi to study their genetic differentiation, gene communication and phylogenetic tree. Based on the results of these analyses, we aimed to explain the origin, relationship and dispersal of these populations. The degrees of genetic differentiation and genetic diversity of different geographical populations were analyzed, their ecological adaptability was clarified, and their population dynamics were discussed to provide information for the development of effective control strategies for R. tanezumi.This study selected mitochondrial This study was approved by the Animal Welfare Provision of the Chinese Academy of Inspection and Quarantine (CAIQ). Approval for the capture of and experimentation on the animals was obtained from CAIQ .R. tanezumi in China  in 6 provinces covering the range of in China . SamplesRats were selected and transported to the laboratory individually. Compressed carbon dioxide in a gas cylinder was used to euthanize the rats. The captured rats were dissected to obtain their liver tissue, which was collected and stored in 95% ethanol at -80°C until DNA extraction according to the handbook of the Blood/Cell/Tissue Genomic DNA Extraction Kit (TIANGEN).Cytb gene (1140 bp) was amplified using primers  and COI (750 bp) was amplified using primers  in a thermocycler. The total volume of the amplification system included 50 μL: 1 μL of template DNA, 1 μL of each primer (10 μM), and 25 μL of Premix Taq (TaKaRa Taq Version 2.0 plus dye), and RNase-Free water to a final volume of 50 μL, which was then mixed. We used a standard 3-step amplification protocol: 95°C for 3 min; 35 cycles of 95°C for 30 s, 50°C (Cytb)/55°C (COI) for 30 s, and 72°C for 90 s (Cytb)/60 s (COI); 1 cycle of 72°C for 10 min and then held at 4°C. PCR amplification products were subjected to 1.0% agarose gel electrophoresis, Goldview staining and UV gel imager detection. Sequencing was performed by Invitrogen Biotechnology Co., Ltd. Sequences were manually edited in Sequencher v5.3 and aligned with ClustalX 2.0 [MtDNA sequence generation DNA extracted from all samples was used as a template; the complete D statistic. Partial deletion of positions with missing data was performed when calculating pairwise nucleotide-based metrics (nucleotide diversity and pairwise number of nucleotide differences). To characterize the population structure of R. tanezumi, we performed an analysis of molecular variance (AMOVA) of all samples in Arlequin v3.5. We visualized the spatial patterns of mtDNA diversity by computing a TCS haplotype network [Cytb genes.We used DnaSP v6  and MEGA network  in PopARCytb using the optimal partitioning scheme inferred above. Two independent Markov Chain Monte Carlo (MCMC) analyses composed of 4 Metropolis-coupled chains each (the default) were used to estimate the posterior distributions of the tree topologies, with both analyses run for 1,000,000 generations, sampling every 1000 generations, and discarding the first 25% of samples as burn-in. The convergence of all parameters was assessed in Tracer v1.6.0 [We inferred phylogenies for all samples in a Bayesian framework. First, we used jModelTest 2.1.7 to identify optimal substitution models as the most general model identified by either the Akaike Information Criterion (AIC) or the hierarchical likelihood ratio test. We conducted Bayesian phylogenetic inferences in MrBayes v3.2.3  and BEASr v1.6.0  by visuaMus and Rattus is somewhat speculative, most current research suggests it occurred early in the evolution of Murinae but was not basal in the divergence of the clade. We used the recommendations of 14 Mya  and 10.4 Mya (based on records of the extinct genus Karnimata [Rattus) as upper and lower demarcations, respectively, for the middle 95% of the normally distributed prior divergence. In accordance with all recent molecular and morphological interpretations, the R. tanezumi clade was enforced relative to that of the vole.We used the minimum and maximum time constraints of the mouse–rat divergence from  to calibarnimata , 34, whiR. tanezumi individuals were confirmed among the 229 collected rats, and the nucleotide sequence length was approximately 1120 bp. Overall, the polymorphisms in the Cytb region were high, with 126 segregating sites defining 34 haplotypes (π = 0.0098) in Yunnan but lowest for the ND population (π = 0.0000) in Fujian. Significant differences were not observed in the neutral detection of Tajima’s D statistic  for all geographical populations.Through morphological and molecular biology (COI) identification and alignment analysis of these sequences, 131 plotypes . The nucFst was between 0.00000 and 0.99207. The gene flow Nm was between 0.00 and 51.74. The Fst and Nm values between FZ and ND were 0.00741 and 33.50, respectively, while the Fst and Nm between QZ and ND were 0.33333 and 0.50, respectively. The Fst values between the R. tanezumi population of ZM and other geographic populations were greater than 0.80, whereas the Nm values were smaller than 0.50. The Fst and Nm between FZ and NC, FZ and LY, and FZ and CQ were 0.04884 and 4.87, 0.00486 and 51.74, and 0.00635 and 39.13, respectively. The Fst and Nm between QZ and NC, QZ and LY, and QZ and CQ were 0.20486 and 0.97, 0.09764 and 2.31, and 0.22222 and 0.88, respectively. The Fst of ND and NC, ND and LY, ND and CQ was 0.18107, 0.00000 and 0.00000, respectively. The Fst and Nm between MH and JSH were 0.02541 and 10.09, those between MH and QSH were 0.00604 and 41.67, and those between MH and JG were 0.11466 and 1.93, respectively. The Fst and Nm values between JG and JSH were 0.14863 and 1.43, and those between JG and QSH were 0.05163 and 4.59, respectively.R. tanezumi populations, we considered the R. tanezumi populations in these two regions as a group, and similarly grouped the JSH, MH and QSH populations; thus, we divided the 11 R. tanezumi populations into 8 groups. The AMOVA results , and the percentage of variation among populations within groups was 1.50%.Due to the close geographical location and high degree of gene exchange between the FZ and ND  results  showed tR. tanezumi clade consisted of 63 unique haplotypes. There were fifteen unique Yunnan R. tanezumi haplotypes, of which five haplotypes were either shared with or differed by only a single mutation from SEA haplotypes and were removed from ZM R. tanezumi haplotypes  of the total individuals. Two peripheral star-like clusters are present in the R. tanezumi network . The combined data set of carefully screened sequences derived from all available sequences in GenBank along with our current data resulted in a robust maximum likelihood phylogenetic analysis of 78 Cytb gene sequences. The trees estimated by ML and Bayesian inference from the R. tanezumi Cytb dataset had the same topology , at approximately 0.52 Mya, followed by the Philippines, at 0.33 Mya, and Yunnan , at about 0.31 Mya; finally R. tanezumi from the rest of China, Japan, South Africa, Madagascar, and Bangladesh diverged 0.27 Mya. With the exception of a subset of individuals from ZM that were closely related to populations from Nepal and Pakistan, which belonged to the R. rattus III clade . ZM Port is located in the southern foothills of the Himalayas, and it is the largest border trade center port in Tibet. The trade routes radiate to Tibet and neighboring provinces and regions and to Nepal and neighboring countries and regions. The main channel for economic and cultural exchange between China and the South Asian subcontinent is the largest open port. The port has a dense population flow, frequent trade activity, good weather, and obvious traces of rodent activity. The climate type in Yunnan is complex, and the terrain is high in the north and low in the south. Due to the influence of topography and different weather systems, the zonal distribution of temperature in the province frequently presents unique phenomena, such as "hot in the north and cool in the south". Moreover, the distribution of precipitation seasonally and regionally is extremely uneven. Therefore, four regions in Yunnan Province were selected from north to south . The geography of Fujian is characterized by mountains and sea, and it has a forest coverage rate of 65.95%, ranking first in the country. FZ, ND and QZ are all coastal cities with suitable temperatures, and they host large populations of R. lose, R. norvegicus and R. tanezumi. The inland cities of CQ, LY and NC have developed road and railway transportation networks and abundant transportation means, which may represent a method for the abnormal spread of R. tanezumi.In the past, H) and nucleotide diversity (π) are two important indicators of genetic diversity [R. tanezumi populations of Yunnan showed a pattern of high haplotype diversity and high nucleotide diversity, indicating that a large and stable population had evolved over a long period of time or that secondary contact occurred between different populations [R. tanezumi in Yunnan, indicating that the Cytb genes of R. tanezumi had a high rate of polymorphism, which suggested that they had strong survivability in changing environments. This characteristic might be related to various factors, such as their biological characteristics. In contrast, the genetic diversity of the populations in the present research showed that the ND population, LY population and Tibet populations had lower genetic variability , hemorrhagic fever (H. virus) and leptospirosis (Leptospira). As a result, Tajima’s D statistics of all populations were negative and not significant. A negative D value indicated that there was a slight deleterious mutation in the purifying selection or separation of the R. tanezumi population, which may also be caused by population expansion [D and Fu & Li’s tests on the D-loop and COI genes of 12 R. tanezumi populations and found recent demographic expansion of these populations, which was consistent with our findings. COI is a widely used DNA barcoding method that shows sufficient resolution and stability in biological species and is suitable for species identification. Therefore, we used the COI gene to identify the species of the rats we captured. The Cytb gene evolution rate is moderate, and the gene contains a large amount of genetic information and is particularly suitable for analyzing the genetic evolution among individuals of the same species. Cytb is more suitable for the construction of phylogenetic trees to study the geographic distribution of species [R. tanezumi populations with different mitochondrial genes.Tajima’s xpansion , 42. Guoxpansion  performe species –47. We sFst and Nm analyses of R. tanezumi populations from 11 regions . The reason might be that the ZM port provided a connection to Nepal and Pakistan, and the relatively close distance was conducive to the spread of the R. tanezumi population. Similarly, the R. tanezumi population in Yunnan was closely related to those in Thailand, Laos, the Philippines, Indonesia, Myanmar and Bangladesh. In southwestern Yunnan, most of the JG R. tanezumi samples were closely related to those from QSH and were relatively geographically close to each other, which was consistent with the close genetic exchange between the two groups of R. tanezumi shown in R. tanezumi has become obvious in North China, such as in Shanxi and Qinghai [R. tanezumi. Although the geographical locations of ZM and LY are far apart, we speculate that R. tanezumi might have dispersed between them. Some of the populations of R. tanezumi in FZ, ND, QZ, NC, LY and CQ were closely related, which roughly confirmed the results indicated by the haplotype network diagram. In southeastern Yunnan, the populations of R. tanezumi in JSH and MH were more closely related to the populations in southeastern China  and inland areas (CQ and LY) than to those in other areas of Yunnan, showing that R. tanezumi might be more inclined to spread from the southeast of Yunnan to the interior of China.Zhou  used fous et al.  revealedn et al.  and Lackn et al. . And we  Qinghai , 55, whiCytb gene in these lineages initially diverged about 1 Mya, with the earliest at 1.06 Mya in ZM, followed by R. rattus I/R. tanezumi divergence approximately 0.8 Mya. We discovered R. tanezumi populations in ZM that had differentiated earlier than those in other regions of China. It could be assumed that ZM and the adjacent area of SEA could be regarded as the origin of R. tanezumi. Interestingly, the differentiation time of R. tanezumi in LY was earlier than those in Yunnan and other regions. There are likely many mechanisms for the eastward spread of R. tanezumi from ZM to inland China. One possibility that all the R. tanezumi caught in LY were caught at the airport, and R. tanezumi in other areas spread to LY through transportation modes, such as airplanes.Hal postulated that beginning in the early Pliocene (~5 Mya), a combination of emergent small islands and changing sea levels led to changes in the spread of rodents . Dating R. tanezumi may have originated in ZM and adjacent areas, spread to Yunnan, and then spread from the southeast of Yunnan inland or directly eastward from ZM to inland China. The dispersal route needs further study. R. tanezumi may have also spread through transportation networks, such as highways and railways. Our study and that of Robins et al. [Cytb, thus are subject to intrinsic biases related to maternal inheritance and organelle location [In summary, s et al.  are baselocation , 58, reslocation . Firstlylocation –61, and location , 63. TheS1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S1 File(TXT)Click here for additional data file.