Liriodendron chinense  along a latitudinal transect. We genotyped 276 individuals from 11 populations of L. chinense using 987 AFLP markers. Both frequency-based (Dfdist and BayeScan) and correlation-based (MLM) methods were applied to detect outlier loci. Our analyses recovered both neutral and potentially adaptive genetic differentiation among populations of L. chinense. We found moderate genetic diversity within populations and high genetic differentiation among populations with reduced genetic diversity toward the periphery of the species ranges. Nine AFLP marker loci showed evidence of being outliers for population differentiation for both detection methods. Of these, six were strongly associated with at least one climate factor. Temperature, precipitation, and radiation were found to be three important factors influencing local adaptation of L. chinense. The outlier AFLP loci are likely not the target of natural selection, but the neighboring genes of these loci might be involved in local adaptation. Hence, these candidates should be validated by further studies.Understanding adaptive genetic variation and its relation to environmental factors are important for understanding how plants adapt to climate change and for managing genetic resources. Genome scans for the loci exhibiting either notably high or low levels of population differentiation (outlier loci) provide one means of identifying genomic regions possibly associated with convergent or divergent selection. In this study, we combined Amplified Fragment Length Polymorphism (AFLP) genome scan and environmental association analysis to test for signals of natural selection in natural populations of  Climate change has become a major threat to global biodiversity . There iHowea  Sarg. (Magnoliaceae), commonly known as the Chinese Tulip Tree, is a self-incompatible, highly outcrossing and tall deciduous species . All twigs were wrapped with a damp paper towel and stored at 4°C until DNA extraction was carried out.In 2008, 1-year-old twigs with mature buds were collected from 276 individuals representing 11 populations of Genomic DNA was extracted from buds with the cetyltrimethylammonium bromide (CTAB) method . The quaEcoRI selective primers were labeled with fluorescent dye (6-FAM). Selective PCR products were sized against an internal standard  on an ABI Genetic Analyser 3730 (Applied Biosystems) and analyzed by GeneMarker v2.2.0 (Applied Biosystems). Amplification products were scored for the presence or absence of bands, and non-discernible fragments (clearly identifiable bands with high peaks) were excluded from the analysis. The bands between 50 and 400 bp were scored as present (1) or absent (0). To test the repeatability of AFLP procedure, AFLP analysis was replicated twice for 12 randomly selected individuals, starting from DAN extraction down to capillary electrophoresis of the selective PCR products for each primer combination. AFLP loci with more than one score discrepancy for any primer combination were excluded from subsequent statistical analysis.Amplified fragment length polymorphism analysis was carried out by following the method of PPL) at 5% level corrected for the sample bias, expected heterozygosity within populations , and population genetic differentiation (FST) were computed with AFLP-SURV version 1.0  and south (ZM) population were referred as marginal population.The percentage of polymorphic loci (sion 1.0 . To condK) for interpreting the data without prior information about the number of populations sampled and to which population each individual belonged, we used the individual-based population assignment test implemented in the program STRUCTURE  simulation by sampling after a burn-in period of 50,000 iterations. The admixture model and uncorrelated allele frequencies were chosen for the analysis. The most likely estimate of K was predicted from plots of ad hoc posterior probability models of ΔK. ΔK statistics are more appropriate than the highest LnPr (X|K) method to infer population number  and two central populations  with similar population size. Firstly, Dfdist  was obtained by removing 30% of the highest and lowest single-locus FST estimates according to the recommendation by FST values, supposedly uninfluenced by outlier loci. Coalescent simulations were performed to generate data sets with a null distribution based on 50,000 simulations and infinite island model. Outlier loci were detected by comparing empirical FST values for each locus  against a null distribution of FST values expected from a neutral drift model (simulation distribution). The 0.995 or 0.005 quantiles were chosen to define an envelope within which 99% of the data points are expected to lie . Sixty-three climatic parameters, including mean temperature per year, monthly minimum and maximum temperatures, monthly average temperatures, monthly average precipitation, mean precipitation per year, total radiation each month, and mean radiation per year, were obtained from this database.Climate data, which included thermal, precipitation and total radiation records over the period 1971–2000 from more than 100 weather stations across the geographic range of Q model and the most stringent model of Q + K, Q-values  estimated from STRUCTURE for the neutral data set and/or kinship values  calculated with SPAGeDi  varied from 0.136 to 0.220, with a mean value of 0.174. The central populations had a higher H (0.200) than the average (0.174) across the 11 populations and was higher than that of marginal populations .Thirteen primer pairs resolved a total of 987 unambiguous bands. The FST based on all loci was 0.198. It was 0.171 and 0.571 for neutral and outlier loci, respectively (Table 2). Pairwise FST values at outlier loci between pairs of populations ranged from 0.169 to 0.899, whereas those at neutral loci ranged from 0.066 to 0.309  method to infer population number .The plot of n number . STRUCTUFigure 4). BayeScan analysis identified 43 high-differentiation loci at a threshold of log10 PO > 2.0 (posterior probabilities higher than 0.99), corresponding to 4.36% of all loci , all of which exhibited increased differentiation. A total of 55 loci were identified by either Dfdist or BayeScan analyses, with nine loci were detected by both methods. For two marginal populations and two central populations, Dfdist analysis identified 9 and 10 outlier loci, and BayeScan analysis detected four and nine outlier loci, respectively. One and two outlier loci were detected by both methods for two marginal populations and two central populations, respectively.In the Dfdist analysis, 21 outlier loci (2.13% of AFLPs) were identified as being outside of the 99% null distribution. Among these, 16 exhibited more divergence and five exhibited less divergence than the majority of loci, consistent with divergent and convergent selection, respectively (Q model yielded 114 loci (11.6%) that exhibited a significant association with one or more climatic factors at the significance threshold set to 1.0E-10. Eleven of 21 loci (52.4%) detected with Dfdist were significantly associated with at least one climate factor. Twenty-eight of 43 loci (65.1%) detected by BayeScan were significantly associated with at least one climate factor . Six of nine loci (66.7%) detected by both Dfdist and BayeScan were significantly associated with at least one climatic factor . Based on the most stringent model of Q + K, only one locus (896) was found to be associated with the climate factors. This locus was also detected by Dfdist, BayeScan, and association analysis with the Q model.The GLM test based on a Liriodendron chinense showed an intermediate level of intra-population genetic diversity (Hs = 0.174) as compared with AFLP genetic diversity observed in other endangered tree species . The genetic structure revealed by AFLPs (FST = 0.198) is also largely concordant with the pattern revealed by microsatellites in L. chinense  between the central and marginal populations suggests L. chinense possibly departs from island model assumption and lead to many false positives , which was supported by the fact that fewer outlier loci identified in two marginal populations compared to two central populations when pairwise comparisons were made. Hidden population structure causing correlated allele frequencies can also lead to a high false-positive rate in the detection of selection . In addition, demographic history can produce patterns similar to positive selection, as in cases of severe bottlenecks, allele surfing during population expansion, secondary contact, and isolation by distance  do not directly integrate tests for specific selection pressures  that cause selection , we alsoPinus monticola. Trifolium repens. Through ecological niche modeling, precipitation and temperature of the coldest quarter were found to be the main factors contributing to geographic distribution of L. chinense  database of L. tulipifera, a sister species of L. chinense (The results of this study revealed high levels of genetic differentiation among populations and moderate levels of genetic diversity within populations of chinense .X-HY and NW conceived the ideas; A-HY collected the data; A-HY analyzed the data. The manuscript was written by A-HY, PF, and X-HY.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.


Orobanche cumana is a holoparasitic plant naturally distributed from central Asia to south-eastern Europe, where it parasitizes wild Asteraceae species. It is also an important parasitic weed of sunflower crops. The objective of this research was to investigate genetic diversity, population structure, and virulence on sunflower of O. cumana populations parasitizing wild plants in eastern Bulgaria. Fresh tissue of eight O. cumana populations and mature seeds of four of them were collected in situ on wild hosts. Genetic diversity and population structure were studied with SSR markers and compared to weedy populations. Two main gene pools were identified in Bulgarian populations, with most of the populations having intermediate characteristics. Cross-inoculation experiments revealed that O. cumana populations collected on wild species possessed similar ability to parasitize sunflower to those collected on sunflower. The results were explained on the basis of an effective genetic exchange between populations parasitizing sunflower crops and those parasitizing wild species. The occurrence of bidirectional gene flow may have an impact on wild populations, as new physiological races continuously emerge in weedy populations. Also, genetic variability of wild populations may favour the ability of weedy populations to overcome sunflower resistance mechanisms. Orobanche spp. and Phelipanche spp.) are a group of around 170 holoparasitic plant species mainly distributed in the northern hemisphere. They do not have photosynthetic activity and entirely depend on a host plant for nutrition  and the wild legume Indigofera hirsuta L. Conversely, Olivier et al.  was used as a positive control. In a second experiment, the virulence of the populations was tested on a set of sunflower lines with varying levels of genetic resistance to O. cumana physiological races. Jdanovski 8281 (J8281) is a line incorporating resistance gene Or2 that confers resistance to O. cumana race B , allowing the detection of the number of genetically homogeneous groups (K) that best fit the data in the STRUCTURE analyses including 14 O. cumana populations from Spain and Bulgaria (a) and (b). Figure S2(a) presents population structure with each individual being represented by a single vertical bar divided into colors, with each color representing one gene pool (K) and the length of the colored segment showing the individual's estimated proportion of membership in that cluster, and Figure S2(b) population structure in which each population is represented by its constituent clusters by averaging across individuals the membership coefficients for each cluster within each population.Figure S2: Results from STRUCTURE analyses including 14 K) that best fit the data in the STRUCTURE analyses including 11 O. cumana populations from Bulgaria. Figure S3(a), Mean of Pr(X∣K) (±SD) over 10 runs for each K value. Figure S3(b), Rate of change of the likelihood distribution. Figure S3(c), Absolute values of the second order rate of change of the likelihood distribution. Figure S3(d), DeltaK values with respect to K.Figure S3: Description of the four steps (a), (b), (c), and (d) for the graphical method, according to Evanno [46], allowing the detection of the number of genetically homogeneous groups (


While numerous ancient human DNA datasets from across Europe have been published till date, modern-day Poland in particular, remains uninvestigated. Besides application in the reconstruction of continent-wide human history, data from this region would also contribute towards our understanding of the history of the Slavs, whose origin is hypothesized to be in East or Central Europe. Here, we present the first population-scale ancient human DNA study from the region of modern-day Poland by establishing mitochondrial DNA profiles for 23 samples dated to 200 BC – 500 AD (Roman Iron Age) and for 20 samples dated to 1000–1400 AD . Our results show that mitochondrial DNA sequences from both periods belong to haplogroups that are characteristic of contemporary West Eurasia. Haplotype sharing analysis indicates that majority of the ancient haplotypes are widespread in some modern Europeans, including Poles. Notably, the Roman Iron Age samples share more rare haplotypes with Central and Northeast Europeans, whereas the Medieval Age samples share more rare haplotypes with East-Central and South-East Europeans, primarily Slavic populations. Our data demonstrates genetic continuity of certain matrilineages (H5a1 and N1a1a2) in the area of present-day Poland from at least the Roman Iron Age until present. As such, the maternal gene pool of present-day Poles, Czechs and Slovaks, categorized as Western Slavs, is likely to have descended from inhabitants of East-Central Europe during the Roman Iron Age. Continuity of human occupation in the territory of Central Europe, modern-day Poland in particular, and its relation to the origins of the Slavs have been widely discussed in the archaeological, linguistic and historical literature; however, these questions still remain contentious autochthonous and allochthonous - have predominated. According to the autochthonous hypothesis, territories around Oder and Vistula rivers (in present-day Poland) were continuously inhabited by ancestors of Slavs from the Roman Iron Age (0–400 AD), or perhaps even further back in time from the Bronze Age (3200–600 BC) –1500 AD) allochthonous theory suggests the discontinuity of settlements between Roman Iron Age and Medieval Age in the territory of present-day Poland. Allochthonists hypothesize that the Slavs originated in the Pripet and Middle Dnieper River basins in modern-day Ukraine, from where they migrated to the west and south of Europe in the beginning of 5th century AD and inhabited the lands of present-day Poland, which was previously occupied by Germanic tribes during the Roman Iron Age allochthonous model.Several hypotheses have been advanced regarding the origin and early migrations of Slavs, of which two - Genetic studies on present-day Slavic-speaking populations have also addressed the complex genetic history of the Slavs Linearbandkeramik culture from Germany Ancient DNA (aDNA) provides direct genetic evidence for past demographic events. Mitochondrial DNA (mtDNA) from skeletal remains has been particularly successful in reconstructing the evolutionary history of European populations e.g. . HoweverTherefore, to provide fresh perspectives on the debate of genetic continuity in Central Europe during the last two millennia, and to contribute to the resolution of the complex origin of the Slavs, we present the first population-level ancient mtDNA analysis on samples originating from six archaeological sites in Poland. The studied samples date to the Roman Iron Age, represented by Wielbark and Przeworsk cultures and to the Medieval Age. Our aim is to determine matrilineal genetic structure of ancient populations in the area comprising contemporary Poland, their relationships to one other and to other ancient and modern human populations from Europe, and to investigate potential genetic continuity between populations spanning two millennia.st to the 4th century AD. The Przeworsk culture was present in the Western, Central and Southern Poland from the 3rd century BC to the 5th century AD. Both Wielbark and Przeworsk cultures were dated to the Roman Iron Age based on the archaeological context. Medieval Age (ME) samples comprised 34 human remains recovered from cemeteries in Cedynia (n = 18) and Ostrów Lednicki (n = 16). Detailed information about each sample, the archaeological context of the burial sites and their geographic origins is presented in The skeletal material studied here originated from burial sites located in present-day Poland dating to the Roman Iron Age and the Medieval Age (n = 72) . The RomSampling was performed using disposable gloves, facemasks and body suits to minimize the risk of contamination from modern humans. Two teeth were collected from each individual. All pre-PCR work was conducted in laboratories dedicated exclusively to the analysis of low copy number DNA . The outer surface of the teeth was decontaminated using 0.1 M HCl, followed by drilling of the teeth and treatment of the powder with 0.5% NaOCl 4, 0.8 mg/ml RSA , 200 µM each of dNTPs (Invitrogen), 500 nM of each primer and ddH2O up to 25 µl. The thermocycling conditions were as follows: initial denaturation at 94°C for 4 minutes; 42 cycles of 94°C for 30 seconds, 52°C–60°C depending on the primer pair,  using TOPO TA cloning kit (Invitrogen), following the supplier's instructions. More than twelve bacterial colonies from each cloning experiment were screened for inserts using M13 universal primers. At least four positive clones were sequenced for each case. PCR products were purified with exonuclease I and Fast alkaline phosphatase (Fermentas) and sequenced using BigDye Terminator v3.1 kit and ABI Prism 3130xl Genetic Analyzer (Applied Biosystems), following manufacturer's instructions. Amplicons generated with M13-tailed primers were sequenced in both directions using M13 universal primers.Almost all analyzed fragments, including HVRI, HVR-II and coding region fragments containing diagnostic SNPs were cloned and sequenced. Only fragments comprising nps 16048-16132 and 16307-16403 were amplified with M13-tailed primers and directly sequenced without cloning. Amplicons were cloned into pCR2.1-TOPO vector and transformed into competent post-mortem damages or/and possible contaminations, alignment of mtDNA sequences was performed using BioEdit v.7.0.5.3 (http://www.mbio.ncsu.edu/BioEdit/bioedit.html). Polymorphic positions in HVRI, HVRII and coding region sequences were scored against the rCRS sequence. Haplogroups were assigned following the established hierarchy of mtDNA phylogeny In order to determine consensus sequence and detect In order to compare mtDNA profiles of RoIA and ME samples to modern populations, we compiled a database of published mtDNA diversity in contemporary Poles, Czechs, Slovaks, Belarusians, Ukrainians, Russians (from the European part), Slovenians, Bosnians, Croatians, Bulgarians, Serbs, Germans, Finns, Estonians, Latvians, Lithuanians, Macedonians and Swedes . To deteFor haplotype sharing analysis we considered sequences bounded by np 16043 to 16403 of the HVRI for both aDNA samples in this study and those from modern populations of our database. All matches between haplotypes were scored taking into account their haplogroup affiliation. Because different studies have used different phylogenetic resolution of mtDNA, for haplotype sharing analysis and for MDS we considered the phylogenetic resolution depth reached in our aDNA samples.Haplotype sharing analysis was conducted in order to detect mtDNA haplotypes shared between RoIA and ME samples and modern Europeans. To this end, eighteen contemporary populations representing East-Central, Southeast and North Europe were used in the analysis . SeveralThe presence or absence of a particular haplotype in a given contemporary population was marked as „1” or „0”, respectively, and the total number as well as frequency of ancient haplotypes found in each modern population was calculated. Furthermore, all haplotypes present in RoIA and ME samples were divided into three classes based on their incidence in the comparative modern populations: informative haplotypes, which were found in less than half of the comparative populations; non-informative haplotypes, which occurred in more than half of the comparative populations; and unique haplotypes, which did not have exact matches in contemporary populations. In cases where we reduced sample sizes, we have cross-checked for informative/unique haplotypes if they present in whole samples size.We used the two-tailed z-test to assess statistical significance of shared informative haplotypes between ancient and modern populations FST were calculated using Arlequin v.3.5 STF values using Statistica v.10 StatSoft (2011).MtDNA haplogroup frequencies were used to determine genetic distances between ancient and modern populations. MtDNA haplogroups of comparative modern Slavic groups as well as Iron Age and Middle Age populations from present-day Denmark Reproducible mtDNA sequences were obtained from 23 out of the 38 specimens from Roman Iron Age burial sites , and fropost-mortem ancient DNA damages, of which 99% wereby C>T and G>A transitions All cloned mtDNA inserts showed characteristic All haplotypes identified in RoIA and ME populations belonged to typical West Eurasian mtDNA haplogroups (hg): H, K, U, T, J, W, HV, X, HV0, R0, and N  and 3. THaplogroup (hg) H was the most abundant hg in the RoIA populations . Samples from Rogowo comprised the highest number of individuals (10 out of 12) assigned to hg H, of which three displayed HVRI sequence identical to the rCRS. Three haplotypes, originating from Kowalewko and Gąski burial sites, were assigned to three sub-branches of hg U  . HaplogrHaplogroup (hg) H was also the most frequent hg among the ME samples  . Other fA set of 3595 modern mitochondrial haplotypes, including majority of Slavic populations from regions geographically adjacent to Poland, was used for comparative analysis. Haplotypes shared between ancient and modern populations are presented in p<0.05) of shared informative haplotypes with the RoIA samples compared to other present-day populations  haplotype represents a basal haplotype within the phylogeny of hg W. Eight RoIA haplotypes were infrequent in contemporary populations and were classified as informative . The relulations . Notablyulations . These up<0.05) of informative haplotypes with the ME samples , 16304 (sample K1), 16129-16304 (sample G1) , and oneSTF values showed non-significant differences between the RoIA and the ME samples (p>0.01)  . The RoI(p>0.01) . Corresp(p>0.01) .This is the first large-scale study presenting mtDNA profiles for 43 individuals recovered from Roman Iron Age and Medieval Age burial sites from modern-day Poland. All mtDNA hgs identified in RoIA and ME populations are observed in most modern Slavic populations Haplotype sharing analysis indicates that the RoIA individuals shared the highest number of informative mtDNA haplotypes with present day Poles . Of part–4 kya, making this haplotype one of the youngest sub-branches within hg N The evolutionary age of H5 sub-branches (∼4 kya) Haplotype sharing test revealed that RoIA populations share significantly higher number of haplotypes not only with present-day Poles, and Czechs and Slovaks (Slavic populations), but also with Lithuanians and Latvians . SimilarThe ME populations share significantly higher percentages of haplotypes with modern Poles, Belarusians and Bulgarians (p<0.05) . Shared STF values were not statistically significant (p>0.01). Both populations shared haplotypes belonging to subhaplogroups U3a and T2. Notably, we did not identify mtDNA hg I, occurring at high frequency (13%) in ancient Iron and Middle Age Danish populations Inclusion of ancient Danish samples for comparative analysis was prompted by the fact that these groups as well as those from the other parts of Scandinavia are thought to have descended from Germanic tribes that occupied the territory of modern-day Poland during the Roman Iron Age We note that due to the uniparental inheritance of the mitochondrial genomes and relatively small sample sizes in our study, our observation of the various mtDNA hgs in the ancient populations, both the presence/absence and frequencies, are likely to be prone to stochastic events. Hence, future research including nuclear DNA markers are necessary to further explore the genetic connections between these ancient and modern populations, including the question of a common origin and the extent of admixture, if any, between them.Results of our study indicate genetic continuity of mitochondrial lineages between ancient and modern populations in the territory of contemporary Poland. In particular, presence of sub-clades of hg H5a1 among both RoIA and ME ancient samples and present-day Poles, and the identification of N1a1a2 haplotype in RoIA and contemporary Poles is consistent with the idea of continuity of maternal lineages from at least Roman Iron Age in the region. Our data demonstrates that present-day Western Slavs, among analyzed Europeans, exhibit a mtDNA profile that is more similar to one found among ancient inhabitants of Central Europe. This observation appears to be in concordance with the autochthonous hypothesis. Studies on the genetic profiles of other ancient Slavic populations, especially employing nuclear markers, are necessary for further resolution of the complex origin of the Slavs.Figure S1Alignments of cloned aDNA sequences analyzed in this study. The first lines report the revised Cambridge Reference Sequence (rCRS) with the numbering of the nucleotide positions.(PDF)Click here for additional data file.Table S1Detailed information about all samples used in the study involving their repository names, geographical location, context and references.(XLS)Click here for additional data file.Table S2PCR primers used in the present study.(DOCX)Click here for additional data file.Table S3Modern and ancient populations used in the comparative analysis.(DOCX)Click here for additional data file.Table S4Haplotype sharing analysis.(XLSX)Click here for additional data file.Table S5STF distances by Slatkin's based on haplogroup frequencies (P<0.01).(DOCX)Click here for additional data file.


Melospiza melodia graminea). Inter–island differentiation was substantial (G''ST: 0.14–0.37), with San Miguel Island having the highest genetic divergence and lowest migration rates. Santa Rosa and Santa Cruz Island populations were less diverged with higher migration rates. Genetic signals of past population declines were detected in all of the extant populations. The Channel Island populations were significantly diverged from mainland populations of M. m. heermanni (G''ST: 0.30–0.64). Ten mtDNA haplotypes were recovered across the extant and extinct Channel Island population samples. Two of the ten haplotypes were shared between the Northern and Southern Channel Islands, with one of these haplotypes being detected on the Californian mainland. Our results suggest that there is little contemporary migration between islands, consistent with early explanations of avian biogeography in the Channel Islands, and that song sparrow populations on the northern Channel Islands are demographically independent.The Californian Channel Islands are near–shore islands with high levels of endemism, but extensive habitat loss has contributed to the decline or extinction of several endemic taxa. A key parameter for understanding patterns of endemism and demography in island populations is the magnitude of inter–island dispersal. This paper estimates the extent of migration and genetic differentiation in three extant and two extinct populations of Channel Island song sparrows ( Santarosae, which was inundated into the five present day islands by rising sea-levels 9.6–9 Kya [Santarosae has been as short as 7 km off-shore during the glacial maximum [Isolation, novel ecological pressures and high degrees of endemism have made island populations important model systems for evolutionary and ecological studies . In many.6–9 Kya ,3. AlthoAphelocoma insularis) [Including flora and fauna, there are approximately 140 endemic species or subspecies on the Channel Islands, that range from single-island endemics to endemics found across all islands –7. Amongsularis) .Aphelicoma californica), for more than 150 Kya [Eremophila alpestris insularis) should have lower genetic divergence than taxa that had diverged into several endemic subspecies such as the loggerhead shrike (Lanius ludovicianus anthonyi). Genetic analyses from Channel Island populations of loggerhead shrikes [Early hypotheses on patterns of colonization and subsequent divergence of the Channel Island avifauna were based on morphological divergence and biogeography . Species 150 Kya . Single  shrikes ,12 and h shrikes  were conth century [T. b. leucophyrus) and song sparrow (M.m clementae), and the Santa Barbara Island song sparrow (M. m. graminea) [L. l. anthonyi and L. l. mearnsi have been driven to precariously low population sizes with current estimates of less than 250 and 50 birds respectively [Biogeographic patterns across the Channel Islands have been altered by significant disturbances ranging from widespread wildfires in the Pleistocene to extensive livestock overgrazing during the 19 century ,5,14,15.raminea) ,17. The ectively .M. m. graminea [M.m clementae , M.m. micronyx (San Miguel Island), and M. m. graminea (Santa Barbara Island); these subspecies were recognized on morphological characters [This study focuses on the endemic Channel Island song sparrow which is currently recognized as a threatened, endemic subspecies graminea ,19. The aracters . Based oaracters .Throughout their range, song sparrows are highly polytypic with 25 diagnosable subspecies that range from c. 16–50g in body weight and display a wide variety of migratory and life history behaviors –22. The We first use mitochondrial control region data to examine the patterns of genetic structure between extant  and extirpated (Santa Barbara and San Clemente Islands) populations of the Channel Island song sparrow and several mainland sites. Secondly, we use microsatellite data from the extant populations to: determine contemporary inter-island patterns of gene flow, test for evidence of historic population bottlenecks and to compare the genetic structuring found in other mainland song sparrow populations.This work was approved by the University of British Columbia Animal Care Committee (Permit: A04-0177) and the Institutional Animal Care and Use Committee at the University of California—Santa Barbara (Permit 1-06-701). Fieldwork was conducted under permits from the United States Fish and Wildlife Service (Permit: 10596), California Department of Fish and Game (Permit: SC-008327) and United States National Park Service (Permit: CHIS-00049). Field protocols adhered to all welfare recommendations made by the Ornithological Council .We collected blood samples for genetic analysis from the extant song sparrow breeding populations on San Miguel, Santa Rosa and Santa Cruz Islands  and one Toepad tissue from specimens collected from the extirpated populations on Santa Barbara  and San Clemente Islands  were obtained from the Museum of Vertebrate Zoology (UC Berkeley) and the San Diego Natural History Museum. The San Diego Natural History Museum also provided additional historic samples from the Californian  and Mexican mainland . Accession data is provided in dx.doi.org/10.6084/m9.figshare.1489740.DNA was extracted from 78 contemporary blood samples using GenElute Blood Genomic DNA Miniprep Kit (Sigma–Aldrich). We extracted DNA from the museum toepads in a dedicated laboratory using QIAamp DNA micro kit (Qiagen). Contemporary samples were genotyped at nine microsatellites: Mme1, Mme2, Mme3, Mme7, Mme8, Mme12, Escu1, GF5 and PSAP335 . Mme3 anWe obtained 500 bp of mtDNA sequence from a subset of the contemporary population samples and all of the extirpated population samples. Sample sizes for the sequence data were: Santa Cruz (n = 11), San Miguel (n = 10), Santa Rosa (n = 9), Santa Barbara (n = 11) San Clemente (n = 15) Islands, California mainland (n = 5) and the Mexican mainland (n = 3). All sequences are available in GenBank accession numbers: KT312851-312913.2, 0.2 mm dNTPs (Invitrogen), 2.4 μg/μl BSA, 0.1% Triton X–100 (Sigma–Aldrich), 10 pmol of each primer and 1.0 U of Taq polymerase (Stratagene). The cycling profile was: 95°C for 1 min, 35 cycles of 95°C for 30 sec, 56°C for 30 sec, and 72°C for 45 sec, followed by a final extension for 5 min at 72°C. Sequencing reactions were performed commercially at Macrogen–Korea using Big Dye chemistry and an ABI3730 XL automatic DNA sequencer.In order to deal with the degraded DNA from museum specimens, we designed primers to amplify small (< 300 bp) overlapping segments of the mtDNA control region based on published song sparrow sequences . TemplatST) [Raw sequence data were edited, aligned and concatenated using Geneious v.8.0.5  and collST) .ST [M. m. heermanni populations sampled at the Salton Sea and San Francisco Bay [ST) were performed using the GenAlex 6.5 software [We tested for departures from Hardy–Weinberg equilibrium (HWE) and linkage equilibrium in the contemporary microsatellite data using Genepop v 3.4 , with teST , which cST . Microsaisco Bay ,38, whicsoftware , and sig7 iterations in length with a burn-in of 2×106 iterations and collected estimates every 2,000 iterations to estimate the posterior distribution. We used delta values of 0.15, 0.15 and 0.20 for the migration rates, population allelic frequencies and inbreeding coefficient (FIS), respectively.We estimated migration rates among extant Channel Island populations using BayesAss v 2.3 . We ran 5 iterations for K = 1 to 6. The best K was inferred from posterior probabilities [As a complement to BayesAss, we calculated population assignment probabilities using GeneClass2 . The assbilities  by the ∆bilities ,46. Clumbilities  was usedbilities .Given the dramatic habitat loss on the Channel Islands, we tested for the presence of genetic bottlenecks within the contemporary populations on San Miguel, Santa Rosa and Santa Cruz Islands using the program Bottleneck v. 1.2.02 ,50. We rTen mtDNA haplotypes were observed in 60 samples from Santa Cruz, Santa Rosa, San Miguel, San Clemente and Santa Barbara Islands. The eight samples from the Californian and Mexican mainland yielded seven additional unique haplotypes. Haplotypes 3 and 4 were shared across all islands in the northern and the southern island groups, and haplotype 4 was found in a specimen from Los Angeles . HaplotyGenetic divergence based on sequence differences revealed a closer relationship between the southern Channel Island populations on San Clemente and Santa Barbara, both to each other and to the mainland than to Santa Cruz and Santa Rosa populations . The SanST) was statistically significant for all inter-island comparisons (ST: 0.14), but Santa Rosa and San Miguel populations were more diverged (G''ST: 0.37), and San Miguel and Santa Cruz were highly diverged (G''ST: 0.45). San Miguel sparrows were also the most diverged from mainland populations , which supports the occurrence of historic bottlenecks in each population.M. m. heermanni and are not reciprocally monophyletic. The haplotype network and pattern of genetic divergence between northern and southern Channel Island and mainland populations are consistent with various scenarios of asymmetrical inter-island migration with subsequently low dispersal. Our data, however, could also be consistent with separate mainland colonizations to the northern and southern groups or repeated immigration from the same unsampled mainland source. The phylogenetic signal has likely been affected by drift, given the low diversity found on the smaller islands and the presence of divergent haplotypes on neighbouring islands  and the salt marsh specialist (M. m. pusillula), was much lower (G''ST: 0.22–0.25) than the divergence between M. m. heermanni and the Channel Island subspecies M. m. graminea (G''ST: 0.40–0.64) studied here .Fossil evidence indicates song sparrows were on the islands as long as 25–39 Kya , so a coGenetic estimates of immigration can have substantial relevance to conservation biology by estimating the importance of immigration rates to the persistence of particular populations . DespiteThe pattern of increasing genetic divergence and decreased migration (this study) and allelic diversity along the northern Channel Islands  is consiAimophila ruficeps [Although water barriers are known to limit song sparrow dispersal, other factors such as the dominant northwesterly pattern of wind in the region , biogeogruficeps ). Howeveruficeps .Estimated migration rates  and Bayeth century, extensive livestock grazing and invasive species introduction had substantial impacts on many Channel Island species, so detecting genetic bottlenecks in the song sparrow populations was expected. Although the late Pleistocene wildfires and inundation of Santarosae would have impacted song sparrow population sizes, the genetic bottleneck signal is detectable for 2-4Ne generations after the bottleneck, so our analyses likely reflect more recent history [Population bottlenecks also contribute to high genetic divergence ; for exa history .Non-migratory song sparrows often show high site fidelity and limited natal dispersal –65; therS1 Table(DOCX)Click here for additional data file.


Thymallus thymallus, is particularly complex in its southern distribution area, where the Adriatic evolutionary lineage is endangered by a long history of anthropogenic disturbance, intensive stocking and potentially widespread genetic introgression. We provide mtDNA sequence and microsatellite data of 683 grayling from 30 sites of Adriatic as well as Danubian and Atlantic origin. We apply Bayesian clustering and Approximate Bayesian Computation (ABC) to detect microgeographic population structure and to infer the demographic history of the Adriatic populations, to define appropriate conservation units. Varying frequencies of indigenous genetic signatures of the Adriatic grayling were revealed, spanning from marginal genetic introgression to the collapse of native gene pools. Genetic introgression involved multiple exotic source populations of Danubian and Atlantic origin, thus evidencing the negative impact of few decades of stocking. Within the Adige River system, a contact zone of western Adriatic and eastern Danubian populations was detected, with ABC analyses suggesting a historical anthropogenic origin of eastern Adige populations, most likely founded by medieval translocations. Substantial river-specific population substructure within the Adriatic grayling Evolutionary Significant Unit points to the definition of different conservation units. We finally propose a catalog of management measures, including the legal prohibition of stocking exotic grayling and the use of molecular markers in supportive- and captive-breeding programs.The definition of conservation units is crucial for the sustainable management of endangered species, though particularly challenging when recent and past anthropogenic and natural gene flow might have played a role. The conservation of the European grayling,  Freshwater fish are listed among the most threatened organisms at the European level  suffers from widespread introgression, with few purebred populations persisting , mirrors the negative population trend of this species at the European level . Starting from 2012, the Autonomous Province of Bolzano (Upper Adige River Basin) firstly implemented the management implications formulated in Meraner and Gandolfi  in the west to Livenza and Tagliamento Rivers in the east. The core of this study was the Adige River Basin, situated in the centre of the northern Adriatic Basin  used in this study was obtained by merging tissue collections used in Meraner and Gandolfi  was achieved by merging haplotype information reported in Meraner and Gandolfi (The CR sequence dataset-set (Gandolfi  (sample Gandolfi  and MeraGandolfi  (sample Gandolfi . In addiGandolfi  by adoptGandolfi .N = 683) consisted of a set of reference genotypes reported in Meraner et al. , expected (HE) and observed (HO) heterozygosities, departure from Hardy–Weinberg (HW) expectations .Population structure and genetic introgression of 683 grayling specimens from 30 sampling sites were investigated using STRUCTURE 2.3.2.1  represented by our grayling dataset was estimated using the methodology presented in Pritchard et al. ), is a sensible choice for the number of clusters presented by the dataset  and population-level admixture estimates  were taken from a single run among replicates converging to the selected clustering solution.The most likely number of genetic clusters . Thereby, only individuals with a q-value ≥0.90 for a defined cluster were included in these analyses.Intracluster genetic substructure was analyzed by independently re-running STRUCTURE for each of the inferred genetic clusters  from SES_1, ADI , by pooling individuals from ADI_1, ADI_2, ADI_3, ADI_4, ADI_5, and ADI_6, ISA , by pooling individuals from RIE_1, RIE_2, ISA_1, and AUR_1, and DRA  by pooling individuals from DRA_1, DRA_2 and DRA_3  ISAArecent) assumed a recent origin of ISA (1 ≤ t2recent ≤ 10 generations), subsequent to the onset of stocking measures after 1970; submodel  assumed an intermediate time frame for ISA formation , in accordance with the hypothesis of medieval stocking, while the third submodel assumed natural colonization following an ancient, transalpine river shortcut (Aancient)  , each differing from the others in the time of split of populations ISA and DRA Fig. . Submodens) Fig. .Following the results of the model-based clustering and mtDNA analyses, we applied the following ABC approach Fig. :we firs6 datasets for each of the six scenarios, building reference tables based on a combination of six summary statistics, namely NAL, MGW, FST, LIK, V2P, and DAS . The priors for all demographic and mutation model parameters, namely the time of split or admixture events (tn), the effective population size (NX), the rate of admixture (rXtoY), the mean mutation rate (μSSR), and the mean parameter of the geometric distribution of the length in number of repeats of mutation events (PSSR) had uniform distribution defined by minimum and maximum values. Prior distributions of all parameters are described in Table S2. We applied a conservative mean generation time for grayling of g = 4 years .We evaluated the “goodness-of-fit” of all evolutionary scenarios by using the “model checking” option in DIYABC v.1.0.4 aimed to measure the discrepancy between a combination of a model and its parameter posterior distributions to a “real” dataset  . Overall, phylogenetic analyses confirmed the general pattern presented in Weiss et al. , with seAD haplotypes were found at 15 of 20 northern Adriatic sampling sites, including newly sequenced fry collections from the Adige River  and a maximum for the sample ADI_3_f (A = 11.07), with an across-population mean value of 5.98 (Table HE) ranged from 0.40 at ADD_1 to 0.71 at sampling site ADI_4. Departures from HW expectations were statistically significant after false discovery rate (FDR) correction in 60 of 450 cases (13.3%). Three loci, namely BFRO009, TAR110, and TAR104, showed cumulated significant heterozygosity excess and MICRO-CHECKER results indicated the possible presence of null alleles. Therefore, we tested the effect of these loci on model-based clustering, which is known to be sensitive to HW pattern. We run STRUCTURE either with or without these three loci, setting K = 8 as the most likely number of genetic clusters. Both analyses gave compatible results, and thus, we retained the original dataset based on all 15 microsatellite loci .Overall, number of alleles per locus ranged from five, for marker BFRO007, to 53, for marker TAR110. At the population-level, the number of alleles showed a minimum value for the sample ADD_1 .K = 8 for the statistic “estimated Ln Prob of Data” .STRUCTURE-based assignment analysis detected eight distinct genetic clusters, supported by a plateau phase reached at ta” Fig. A1.Q-value frequencies from 0.92 to 0.99 at single localities : no genetic substructure was revealed within clusters qAD1, qSC, and qSV. In contrast, substantial genetic substructure was found within clusters qAD2, qRH1 as well as qSA. In detail, within qAD2, fish from Sesia (SES_1) were separated from Lower Adda (ADD_2) as well as from Livenza (LIV_1) samples, while within qRH1, Upper Adda samples (ADD_1) were discriminated from Rhine (ATL_1) River samples. Finally, Drava River fish (DRA) were clearly separated from eastern Adige grayling populations  .Ahistorical, with an intermediate prior on time since divergence of ISA from DRA , was highlighted as the most likely scenario , with a median divergence time between ISA and DRA estimated at t2historical = 116 generations and a median admixture rate of the ISA gene-pool into ADI  estimated at 0.174.The evolutionary history of eastern Adige populations and their possible contribution to the distinct western Adige populations through migration and gene flow was investigated by a hierarchical ABC analysis: on a first level of analysis, the most likely evolutionary scenario suggested that the eastern Adige population (ISA) derives from the Drava (DRA), while the western Adige population (ADI) originates from admixture of ISA and a hypothetical ancestral Adriatic grayling population (model [A] with posterior probability = 0.8747 [0.8042 ≤ CI ≤ 0.9453]). We thus selected model (A) and inferred the divergence time of population ISA from DRA as well as the admixture rate of ISA into ADI. Submodel Model checking of both first- and second-level ABC analyses and when applying summary statistics not used for model discrimination supported the selected models as the “best” evolutionary scenarios. In the first-level analysis, the type I error rate was 0.29, and the type II error rate was 0.11, while in the second-level analysis, the type I error rate was 0.08, and the type II error rate was 0.02.Virtually, the same results were obtained repeating the analysis after the exclusion of marker BFRO009, showing significant deviation from HWE (data not shown).T. thymallus  outside the Adige River, with frequencies ranging from 0.19 at Tagliamento River (TAG_1) to a maximum of 0.97 at Sesia River (SES_1) Table . In contSalmo trutta, for which permanent Atlantic captive breeding strains have been established over dozens of generations and stocked across Europe , while downstream sites along the Adige River  were only moderately stocked .The different genetic effect of stocking at single sampling sites, spanning from almost no introgression to the complete collapse of the native population, might be linked to different “immigration rates” of stocked fish , as well as model checking, gave high statistical support for such colonization scenarios, and indicate a historical transalpine origin of grayling inhabiting eastern Adige River stretches  were completely missing. Both STRUCTURE analysis and ABC rejected the hypothesis of a genetic contribution of the Adriatic genetic cluster (qAD1) in eastern Adige. The two analyses instead supported a Danubian origin of eastern Adige populations, with likely limited unidirectional gene flow occurring from eastern to western Adige populations. So forth, eastern Adige populations are, however, unlikely to stem from recent stocking measures. ABC rejected a recent colonization scenario and suggested a divergence time of eastern Adige from Drava populations having occurred several hundreds of years ago. Both posterior probabilities of model selection . Genetic monitoring of young-of-the-year grayling (ADI_2f and ADI_3f; Table sensu Moritz sensu Moritz It is important to underline that there is not a single uniform gene pool of the Adriatic Grayling, but a pronounced microgeographic genetic substructure was demonstrated within this “Evolutionary Significant Unit” (ESU; The situation of MUs is particularly complex within the Adige River basin, where a historical contact zone with substantial geneflow from east to west has to be assumed. Therein, two distinct management units should be defined and conserved: an “Adriatic” gene pool in western and main-stem Adige and a “Danubian” metapopulation in the eastern part of the Adige River. Grayling populations of eastern Adige are most likely of anthropogenic origin and thus do not meet the international criteria of “native” gene pools (Manchester and Bullock


Oncorhynchus are the most widespread salmonid fishes and are among the most important fish species in the world, due to their extensive use in aquaculture and valuable fisheries. Trout that inhabit northwestern Mexico are the southernmost native salmonid populations in the world, and the least studied in North America. They are unfortunately also facing threats to their continued existence. Previous work has described one endemic species, the Mexican golden trout (O. chrysogaster), and one endemic subspecies, Nelson’s trout (O. mykiss nelsoni), in Mexico, but previous work indicated that there is vastly more biodiversity in this group than formally described. Here we conducted a comprehensive genetic analysis of this important group of fishes using novel genetic markers and techniques to elucidate the biodiversity of trout inhabiting northwestern Mexico, examine genetic population structure of Mexican trout and their relationships to other species of Pacific trout, and measure introgression from non-native hatchery rainbow trout. We confirmed substantial genetic diversity and extremely strong genetic differentiation present in the Mexican trout complex, not only between basins but also between some locations within basins, with at least four species-level taxa present. We also revealed significant divergence between Mexican trout and other trout species and found that introgression from non-native rainbow trout is present but limited, and that the genetic integrity of native trout is still maintained in most locations. This information will help to guide effective conservation strategies for this important group of fishes.Salmonid fishes are cold water piscivores with a native distribution spanning nearly the entire temperate and subarctic northern hemisphere. Trout in the genus  Oncorhynchus mykiss nelsoni [O. chrysogaster [O. mykiss, but no formal taxonomic evaluation has been conducted and their taxonomic status is not clear [The first step in construction of an effective conservation strategy is to document the diversity of biological units in the focal taxa and gain an understanding of the evolutionary relationships among them and their close relatives . The tax nelsoni , distribsogaster  from thesogaster  and the sogaster . Other gsogaster ,7–9 and ot clear ,10.O. gilae), Apache (O. apache), Mexican Golden (O. chrysogaster) trout and, presumably, the other groups of trout in the SMO.The fossil record indicates that trout inhabited Mexico during the Pleistocene and the southern-most record for a fish assigned to the family Salmonidae is ~ 20° North latitude, in the Lake Chapala, Jalisco region . Behnke i.e., O. chrysogaster) or a few populations in specific regions . While these studies provided valuable information and some insight into the diversity of trout inhabiting northwestern Mexico, incomplete sampling, small sample sizes, and the low resolution of some of these analyses have left many unresolved questions. Thus, there is a clear need for more information on genetic diversity, population structure and evolutionary relationships  , has exas (sensu ) of trous  has led to establishment of naturalized populations in several drainages where native Mexican trout also occur [O. clarkii lewisi) has been ubiquitous [O. apache and O. gilae trout populations are similarly affected, with both species receiving protection under the United States Endangered Species Act (ESA) due to habitat loss, hybridization and genetic introgression with introduced rainbow trout [O. apache populations have some degree of introgression [O. gilae have been lost due to hybridization [In addition, the practice of introducing exotic hatchery rainbow trout  to document the genetic biodiversity of native trout in northwestern Mexico, 2) evaluate relationships between these trout populations and their potential evolutionary origins, and 3) evaluate the extent of hybridization and genetic introgression from hatchery rainbow trout into native trout in northwestern Mexico. To investigate these questions, we use data from a large number of genetic markers, including both microsatellites and single nucleotide polymorphisms, and analyze samples from all the basins in Mexico in which native trout have been recently documented.Permits for the collections were issued by SEMARNAT  and Permisos de Pesca de Fomento DGOPA 21205/0765, 250406/1606 030506/1677, 240800 213-03/2366, 300801-613-03/1607. The study protocols  were approved by the Saint Louis University Animal Care and Use Committee.2) from trout at 42 localities  and five O. gilae individuals (Gila River population).Also, 147 tissue samples from hatchery rainbow trout were obtained from four hatcheries located in different basins in Mexico where native trout have been reported, and one hatchery located in Guachochi, Chihuahua which is oriented towards native trout conservation (O. mykiss populations (N = 675) from California, USA that represent six Distinct Population Segments (DPSs) [O. mykiss hatchery strains (N = 187) were included in the analyses. Genotype data from five cutthroat trout subspecies—coastal: O. c. clarkii; (N = 47), Yellowstone: O. clarkii bouvieri (N = 20), Bonneville: O. clarkii utah (N = 16), Rio Grande: O. clarkii virginalis (N = 10), and Colorado: O. clarkii pleuriticus (N = 8)—were also incorporated  , and fourporated . All popO. mykiss population structure and interactions among different groups of trout in California, including for the detection of introgression by all major lineages of hatchery rainbow trout [O. clarkii [All individuals were genotyped at 18 microsatellite loci identified in salmonid species: Omy27 , Ssa289 ow trout ,34,35,46 clarkii ,48.2O, 1.5μL 10X PCR buffer (Life Technologies Inc.), 0.9μM MgCl2, 0.6μM dNTPs, 1μM fluorescently labeled oligonucleotide primers, 0.04 U Amplitaq DNA polymerase (Life Technologies) and 4μL template DNA of variable concentration. Thermal cycling conditions are available from the authors upon request. PCR products were electrophoresed on an ABI377 or an ABI3730 Genetic Analyzer. Allele sizes were determined with Genotyper or Genemapper software (Applied Biosystems Inc.) and confirmed by two people independently.PCR was conducted in 15μL volumes with 6.9μL Het al. [et al. [O. mykiss from California, Oregon and Washington [™) assays (Life Technologies) and was carried out in 96.96 Dynamic SNP Genotyping Arrays on an EP1 System (Fluidigm Corporation) using the manufacturer’s recommended protocols.A total of 93 single nucleotide polymorphism (SNP) loci were also genotyped on all samples. These SNPs include loci described by Aguilar and Garza , Campbelet al. , and Aba [et al. . They hashington , as wellThe two classes of genetic markers used have important differences, such as higher polymorphism for microsatellites and a lower mutation rate for SNPs, among others. Such differences could provide distinct and complementary information about the genetic relationships and history of these trout. Therefore, some analyses were performed using only the SNP or microsatellite data. All analyses included all populations, regardless of sample size, except where indicated.HE) and observed (HO) heterozygosities [P(0.95) and 0.99 P(0.99) were calculated using GENETIX 4.05 [AR) by rarefaction to account for sample size differences. A Bayesian model-based clustering analysis of individual ancestry implemented in the program STRUCTURE 2.2 [K = 2–7 were evaluated, with 20 iterations for each value and a burn-in period of 50,000 steps and 150,000 Markov Chain Monte Carlo replicates. The results were reordered and visualized using the software CLUMPP [Within population genetic variation was examined using different estimators. Expected  Pairwise quin 3.5 ; b) Prinquin 3.5 , which iquin 3.5 ; and c) quin 3.5 . Markersquin 3.5  method wK = 2–5, five iterations each) and PCA. These analyses were performed using all the naturally spawning populations from a basin (e.g. Río San Lorenzo) and data from the fish from hatcheries in that basin (e.g. “Piscicultura Vencedores” hatchery) as well as from the hatchery trout strains from the United States. The q-value from this clustering analysis with K = 2 was used as a measure of introgression. Even though samples from hatcheries located in the southernmost basins were not available, introgression from hatchery rainbow trout in the ríos Presidio, Baluarte, and Acaponeta was evaluated based on the results obtained in the analyses described above.Due to evident establishment of non-native hatchery rainbow trout in some of the main drainages of northwestern Mexico , geneticA total of 1,999 trout were successfully genotyped with the microsatellite panel, and 1,985 with the SNP panel. Those individuals that had excessive missing data (≥ 10 missing SNP loci or ≥ 9 missing microsatellite loci) were excluded from analyses .O. clarkii ssp. to 0.413 in Gualala River-Fuller Creek  than in any of the SMO populations  and lowest in the Río Conchos-Río Rituchi population  ranged from 0 to 0.99 and at P(0.99) from 0 to 1, with the highest values again observed in O. mykiss (mean P(0.95) = 0.88; mean P(0.99) = 0.95) and the lowest in NSMO fish (mean P(0.95) = 0.02; mean P(0.99) = 0.05), where all loci were monomorphic in several populations  and percentage of polymorphic SNPs (P(0.95): F1,74 = 859.5, R2 = 0.921, p < 0.001; P(0.99): F1,74 = 591.6, R2 = 0.889, p < 0.001; We observed higher mean pairwise population tellites  and signO. clarkii ssp. appeared to share some recent ancestry with O. chrysogaster, while O. gilae and O. apache shared some recent ancestry with O. mykiss, O. chrysogaster, and NSMO trout  and between SMO and O. mykiss populations.Highly significant genetic differentiation between populations was also documented with the pairwise T values , with thO. mykiss populations, including O. m. nelsoni, all hatchery stocks, as well as populations from the southernmost localities . A fourth cluster (green/blue) included populations from two localities: Río Conchos-Arroyo El Molino and O. chrysogaster from the Río Fuerte-Río Verde. The remaining populations of O. chrysogaster formed a fifth group (light blue), except for populations from two tributaries of the Río Fuerte (arroyos Aparique and San Vicente), which clustered with the O. mykiss group with PC1 and PC2 (O. gilae and O. apache trout defined a sixth group (olive green) and the O. clarkii subspecies (light green) overlapped with two O. chrysogaster populations  with PC1 and PC2  clustered separately from most of the SMO populations and O. clarkii. Trout from the Río Acaponeta, the southern-most population, clustered with trout from Mexican hatcheries within the O. mykiss lineage in both trees. Trout populations from tributaries of the Río Fuerte did not cluster together, but rather were most similar to populations from the ríos Sinaloa and Conchos and, with marginal bootstrap support, the Río San Lorenzo/Río Piaxtla cluster.Several notable features could be identified in the population groupings of both dendrograms . First, O. clarkii from all the other trout species. In addition, strong support was observed for a division between populations from the northern and southern Río Yaqui tributaries (O. chrysogaster), along with the population from Río Conchos-Arroyo El Molino, formed a cluster in both dendrograms. Also consistent with the PCA, strong support was found for a cluster of populations from the ríos San Lorenzo and Piaxtla.All populations from the ríos Casas Grandes, Yaqui and Mayo, as well as two tributaries of the Río Conchos, were separated by a long, well-supported internal branch that was similar to that separating butaries . PopulatO. chrysogaster from the “Centro Acuícola Guachochi”, corresponded to O. mykiss and were closely related to hatchery rainbow trout strains commonly raised in the United States .Here, we again confirm the significant genetic diversity present in trout populations inhabiting northwestern Mexico. Clustering analyses of data from over 100 genetic markers further indicates that there exist at least five major genetic lineages of native trout in Mexico. These clusters originated from at least two, and possibly three, separate colonization events of basins in Northwestern Mexico. The first event gave rise to O. mykiss nelsoni [O. chrysogaster [O. mykiss and not closely related to SMO trout or the other species. This is in agreement with earlier work that originally described Nelson’s trout as a new species  [Salmo irideus [O. mykiss irideus [O. m. nelsoni to steelhead DPS populations from southern California than to any other populations of steelhead or hatchery rainbow trout. This observation strongly suggests that trout in Baja California are the result of a radiation of coastal steelhead through southern California and at least as far south as the Sierra de San Pedro Mártir in Baja California, and not the result of an earlier radiation that gave rise to the trout populations in tributaries of the Gulf of California. Even though there was not strong genetic differentiation of O. m. nelsoni from other O. mykiss with the markers used here, it is important to note that it had the lowest genetic diversity and the highest FST values of all O. mykiss populations studied (NE) and a long period of isolation.The great diversity in the Mexican trout complex has been the subject of a number of previous investigations. Substantial questions have remained, however, about the relationships among Mexican trout populations –9,13,16,sogaster —and bothsogaster . Nelson’sogaster , but itssogaster . The STR irideus , now ref irideus ,69. More studied  Tables, FST estimates were observed between SMO trout populations (mean FST = 0.351–0.684) than between O. mykiss populations (mean FST = 0.244–0.527), which is likely due primarily to small effective population sizes of SMO trout and consequent strong genetic drift, which is consistent with the lower diversity found at both microsatellite and SNP markers. However, polymorphisms, SNPs in particular, are frequently not maintained even in closely related species [O. mykiss.Extremely strong genetic differentiation among Mexican trout populations from the SMO was also observed, not only between basins but also among localities/tributaries within basins. Higher pairwise  species ,70, so iWithin the SMO trout, we found at least four well-differentiated genetic clusters. Trout from the ríos Yaqui, Mayo and Casas Grandes, and the northern Río Conchos tributaries form a genetic cluster that is very divergent from other SMO trout populations and the other trout species, which is concordant with previous work on diversity in Mexican trout using morphological variation , mtDNA ,17 and mO. chrysogaster, formed a single group, with the exception of trout from two tributaries of the Río Fuerte (arroyos San Vicente and Aparique), which were somewhat distinct in all analyses and appear more similar to O. mykiss or populations from the ríos San Lorenzo and Piaxtla. This is likely the result of genetic introgression from hatchery rainbow trout, but could also be due, at least partly, to reduced genetic variation or retention of ancestral polymorphisms. However, there was no evidence of grouping by basin for O. chrysogaster populations, as found by Ruiz-Campos et al. [et al. [Populations from ríos Fuerte, Sinaloa and Culiacán, identified as s et al.  and Cama [et al. , but ratOncorhynchus. Trout from the Río Conchos tributaries Rituchi and Ureyna grouped tightly with Río Yaqui-Río Bavispe trout, which are in close proximity  between native and exotic trout in this stream [Trout populations from the ríos San Lorenzo and Piaxtla formed another strongly supported cluster in all analyses. However, trout from Arroyo La Sidra in the Río San Lorenzo were heavily introgressed by hatchery rainbow trout Figs  and 8, as stream . No intrO. mykiss than to the other SMO lineages. Hybridization between trout from these southern drainages and exotic rainbow trout has been previously reported [O. mykiss from the Pacific coast that was more recent than that which gave rise to the other SMO trout. The ríos Presidio and Baluarte are at the extreme southern edge of the known range of trout in Mexico and they are also likely the first perennial streams that anadromous steelhead venturing south from their current contiguous range would encounter. Distinguishing natural colonization from introgression by introduced hatchery trout will require more detailed analysis.Trout from the ríos Presidio, Baluarte and Acaponeta were more similar to reported ,30. The O. mykiss in every analysis and, more specifically, with hatchery rainbow trout strains. This provides strong evidence that Río Acaponeta trout are descended directly from hatchery rainbow trout or recent migrants as described above, and that if there was formerly a native population related to the other SMO trout, it is completely introgressed.Trout from Río Acaponeta clustered with O. chrysogaster for conservation purposes [O. chrysogaster or any other native SMO lineages. In contrast, they clustered tightly with hatchery rainbow trout, indicating collection from a stream with previously unrecognized hatchery trout stocking and consequent incorrect identification, or introgression from exotic rainbow trout also raised at the hatchery.The Centro Acuícola Guachochi hatchery facility in the state of Chihuahua was originally dedicated to the production of hatchery rainbow trout but, in 2006, started a program to breed and raise purposes . UnfortuThe first documented introduction of non-native trout into Mexican waters was in 1886, when ~33,000 eggs were imported from the Baird Station hatchery on the McCloud River, California, United States . The totO. mykiss ancestry, although it is possible that this is due to a more recent anadromous colonization event.In summary, we present the first comprehensive genetic analysis of trout from northwestern Mexico. We used data from over 100 markers, a combination of SNPs and microsatellites, to clearly delineate at least five distinct species-level genetic lineages in Mexico, corresponding to the two named taxa, Mexican Golden and Nelson’s Trout, and at least three unnamed taxa in the Sierra Madre Occidental region. We further clarified the taxonomic status of trout from northern Baja California, unambiguously identifying them as the southern-most population of the coastal California steelhead lineage. In addition, we identify the taxonomic affiliation of fish from the Atlantic Ocean-draining Rio Conchos basin, finding that they are of mixed origin, with one representing a previously unknown population of, at least partial, Mexican Golden Trout ancestry. The data further allowed us to evaluate the ancestry of trout populations that could have been affected by introgression by imported hatchery rainbow trout. This analysis found that, while there was some evidence of introgression of native trout by these hatchery imports, it was generally restricted to populations in the local vicinity of the hatcheries. However, several populations at the southern-most extent of the range were dominated by S1 FigFive watersheds are indicated: Río Casas Grandes (light green), Río Yaqui (dark green), Río Mayo (olive green), Río Fuerte (blue), and Río Conchos (red).(TIFF)Click here for additional data file.S2 FigFour watersheds are indicated: Ríos Fuerte, Sinaloa and Culiacán (blue), and Río Conchos (red).(TIFF)Click here for additional data file.S1 TableN: total number of samples; Lat: Latitude; Long: Longitude; *: estimated location; DPS: Distinct population segment.(XLSX)Click here for additional data file.S2 TableN: number of individuals successfully genotyped with the microsatellite panel and the SNP panel respectively; Expected (HE) and observed (HO) heterozygosity; allelic richness (AR); percentage of polymorphic loci (P) at frequencies 0.95 and 0.99.(XLSX)Click here for additional data file.S3 TableO. mykiss, O. m. nelsoni, NSMO, O. chrysogaster, SSMO, O. apache, O. gilae, and O. clarkii ssp., Mexican hatcheries, and California hatcheries.Lines indicate breaks for the main groups ((XLSX)Click here for additional data file.S4 TableFST by locus using Weir & Cockerham’s (1984) estimator. WSU: Washington State University; CRITFC: Columbia River Inter-Tribal Fish Commission.Original reference is reported. (XLSX)Click here for additional data file.


Plutella xylostella) is an insect pest well known for its capacity of moving over short to long distances. Here, we used newly isolated microsatellite markers to analyze the genetic structure of nine populations across the Taiwan Strait of China (Taiwan and Fujian). A total of 12,152 simple sequence repeats (SSRs) were initially identified from the P. xylostella transcriptome (~94 Mb), with an average of 129 SSRs per Mb. Nine SSRs were validated to be polymorphic markers, and eight were used for this population genetic study. Our results showed that the P. xylostella populations could be divided into distinct two clusters, which is likely due to the year‐round airflows in this region. A pattern of isolation by distance among the local populations within Fujian was found, and may be related to vegetable transportation. Considering the complexity of the P. xylostella population genetic structure from local and regional to global levels, we propose that developing ecologically sound strategies for managing this pest will require knowledge of the link between behavioral and population ecology and its genetic structure.Movement of individuals through events, such as storms or crop transportation, may affect survival and distribution of insect pests, as well as population genetic structure at a regional scale. Understanding what factors contribute to gene flow in pest populations remains very important for sustainable pest management. The diamondback moth ( The genetic makeup of populations is important in determining their capacity to withstand adverse environments and, if needed, adapt to new conditions , represents a typical pest insect that has the capacity to disperse or migrate over short to long distances , Population genetic studies of DBM have been carried out, but few examined explicitly the factors influencing regional genetic distribution  identify the variables governing the dynamics of gene flow and the P. xylostella population genetic structure using microsatellite markers.Fujian and Taiwan are two subtropical provinces on both sides of the Taiwan Strait where vegetable production, including cruciferous plants, is currently intensifying. Both provinces suffer from frequent infestations of P. xylostella transcriptome and then used the polymorphic loci for the genetic analysis of the P. xylostella populations collected from both sides of the Taiwan Strait.We used selectively neutral molecular markers to study genetic differentiation in DBM, as they are preferred for studying questions of demographic history as well as gene flow (Cooke and Lees P. xylostella transcriptome from the recently published database (DBM‐DB: http://iae.fafu.edu.cn/DBM/)   following the manufacturer's instructions. The relative purity and concentration of the extracted DNA were estimated with NanoDrop ND‐2000 . The DNA was diluted to a final concentration of 20 ng/μl with double‐distilled water.To identify polymorphic SSRs, we used individuals from three P. xylostella transcriptome dataset, we performed PCR reactions to validate the effective primer pairs using the extracted DNA of the P. xylostella larvae from Fuzhou (Fuzhou‐S). The forward primers of the validated primer pairs were linked with a universal primer M‐13 (TGT AAA ACG ACG GCC AGT) at their 5′ ends.Based on a total of 281 primer pairs randomly selected from the P. xylostella strains  to identify polymorphic SSRs. A program developed by Schuelke , sizes of the amplification were detected with ABI 3730 (Applied Biosystems). GeneMapper 4.1 (Applied Biosystems) was used to assign alleles based on the sizes of PCR amplifications. PCR products with an identical size generated by the same pair of primers were considered as an allele. SSR markers that could steadily produce ≥ 2 alleles among the eight individuals were taken to be polymorphic markers.We used eight individuals from the three Schuelke  for PCR FST  of the Taiwan Strait, China Fig. , Table 1DA distance   method (Saitou and Nei θ) was estimated by the equation θ = 4Neμ (where Ne is the long‐term (inbreeding) effective population size, μ is the mutation rate per site and generation), and the mutation‐scaled migration size (M) was estimated by M = m/μ (where m is the migration rate per generation). We gradually increased the numbers in Markov chain settings until smooth histograms were observed and modes were within the 50% credibility intervals. The MCMC‐run consisted of a long chain with 5000 recorded steps, 10 concurrent chains (replicates), and 1000 discarded trees per chain. Static heating scheme was also used with four chains of temperature  with swapping interval of 1.We randomly selected three samples representing different geographic locations, Fuzhou (Northern Fujian), Putian (Southern Fujian), and Yunlin (Taiwan), as cases to estimate the migration rate among populations at the regional level. Population size and migration among populations were analyzed based on Bayesian inference using Migrate 3.6.4 (Beerli and Felsenstein P. xylostella transcriptome (~94 Mb), with an average of 129 SSRs per Mb. Approximately 95% of the complete SSRs were shorter than 30 bp in length, while less than 0.1% were longer than 50 bp. In terms of the SSR composition, the numbers of motif‐ and length‐specific SSRs were unevenly distributed. Monomers were the most abundant motifs with a frequency of 58.0%, followed by the trimers (26.6%), dimers (12.1%), and tetramers (2.6%) .A total of 12,152 SSRs were identified from the P. xylostella strains  were generated for 15 SSR loci, among which six were monomorphic and nine polymorphic with trinucleotide repeats  to 15 (A‐DBM‐16) (Table P < 0.05), but they were not necessarily associated with particular populations and/or loci. Null alleles were detected in 22 of the 81 loci as a result of heterozygote deficiency  Table , suggestB‐DBM‐23 and B‐DBM‐25 exhibited linkage disequilibrium in all nine P. xylostella populations. These two loci were located at scaffold 89 in the published DBM genome  ranged from 0.47 in Wuyishan to 0.58 in Zhangzhou, and the allelic richness ranged from 3.50 in Wuyishan to 5.25 in Xiamen. A total of 23 population‐specific alleles were identified . Therefore, each of the 288 individuals was proportionally assigned to the two clusters . Similar patterns were observed using population‐level phylogenetic analysis , which indicated a high level of movement among populations. The differentiation values between clusters (cluster I vs. cluster II) were generally higher than those within clusters (Table θ) of the sampled populations were similar, and mutation‐scaled migration rates (M) estimated with Migrate showed high gene flow among different geographic regions, with the highest value between Putian (Southern Fujian) and Yunlin (Taiwan) (Table The pairwise rs Table . The mutn) Table .P. xylostella, suggested by the heterozygous nature of the recently published genome of this species . Based on the 281 selected primer pairs, we found that 30 primer pairs could amplify expected sizes in Fuzhou strain, of which 15 SSR loci showed effective bands in all the three P. xylostella strains collected from different countries, while others failed and may be related to the polymorphic flanking regions presented in different P. xylostella strains.Conventional methods of microsatellite identification from partial genomic libraries have proved to be inefficient for some taxa such as Lepidoptera Zhang . Low abuP. xylostella populations.Microsatellites can be under selection as these repeats may have functions such as regulation of gene activities  and could be attributed to gene flows originating from frequent vegetable transportation   Fig. . We belian) Fig. . In Fujian) Fig. . Large nP. xylostella at different developmental stages in these regions . Gene flow mediated by large‐scale movements can also shape genetic variation within populations Freeland . AnotherP. xylostella populations from southern Fujian and Taiwan, and that vegetable transportation among rural and urban centers can enhance the complexity of gene flow. In terms of factors affecting population genetic structure at local to regional scales, this complexity may not always be recognized as an important force shaping population genetic diversity of insect pests. Further studies, using landscape genetics and information‐theoretical selection model may help contribute to disentangle the influence of these various mechanisms in governing the gene flow in DBM from local to regional levels.The diamondback moth is an insect pest worldwide distributed, with short‐ to long‐distance dispersal capability. Our analysis shows that several factors can play a role in defining genetic variation and structure at both local and regional levels. Our results support the fundamental role of air currents in intermixing the None declared.Plutella xylostella populations across the Taiwan Strait based on identification of microsatellite markers” (doi:10.5061/dryad.8k3p5).Microsatellite data file has been accessioned at Dryad (datadryad.org) under the title: “Genetic differentiation of the regional Table S1. Composition, abundance (number), and frequency of SSRs identified from the P. xylostella transcriptome.Click here for additional data file.Figure. S1. Mean  of log‐likelihood values (A) obtained using the program structure, and delatK (B) from 20 independent runs.Click here for additional data file.