Chinook salmon native to North America are spreading through South America’s Patagonia and have become the most widespread anadromous salmon invasion ever documented. To better understand the colonization history and role that genetic diversity might have played in the founding and radiation of these new populations, we characterized ancestry and genetic diversity across latitude (39–48°S). Samples from four distant basins in Chile were genotyped for 13 microsatellite loci, and allocated, through probabilistic mixture models, to 148 potential donor populations in North America representing 46 distinct genetic lineages. Patagonian Chinook salmon clearly had a diverse and heterogeneous ancestry. Lineages from the Lower Columbia River were introduced for salmon open-ocean ranching in the late 1970s and 1980s, and were prevalent south of 43°S. In the north, however, a diverse assembly of lineages was found, associated with net-pen aquaculture during the 1990s. Finally, we showed that possible lineage admixture in the introduced range can confound allocations inferred from mixture models, a caveat previously overlooked in studies of this kind. While we documented high genetic and lineage diversity in expanding Patagonian populations, the degree to which diversity drives adaptive potential remains unclear. Our new understanding of diversity across latitude will guide future research. Furthermore, different introduction vectors delivering distinct genetic lineages in different regions can result in a mosaic of populations with varying genetic diversity and evolutionary potential2. We investigated self-sustaining Chinook salmon [Oncorhynchus tshawytscha ] populations, currently part of a rapid colonization that is sweeping through Patagonia, the binational region of Chile and Argentina at the southern cone of South America. Specifically, we measured genetic diversity and evaluated the most likely phylogenetic origins of four self-sustaining populations spread over a wide geographical range that received multiple distinct introductions from different kinds of artificial propagation.Multiple independent introduction events can lead to shifts in genetic variation relative to native source populations, potentially boosting invasiveness and potential for rapid local adaptation3; yet successful naturalization has been rare. Self-sustaining adfluvial (migrating between lake and river) Chinook salmon populations have been established in the North American Great Lakes4, but anadromous (migrating between the sea and river) populations outside their native range exist only in New Zealand’s South Island and in Patagonia3. The phylogenetic ancestry of New Zealand Chinook salmon was tracked to introductions in the early 1900s from the Sacramento River fall run , most likely Battle Creek, California5. When studied about 30 salmon generations later, a number of phenotypic traits had evolved apparently in response to local environmental conditions6, offering increased local fitness7. The monophyletic ancestry and known history of introduction in New Zealand greatly facilitated that research7. This rapid evolution in New Zealand underscores the potential of Chinook salmon to adapt to new environments, yet it begs the question of why successful introductions have been rare elsewhere.Beginning in the 1870s, Chinook salmon, native to North America and the North Pacific Ocean, were deliberately introduced into innumerable rivers in all continents except AntarcticaPatagonian Chinook salmon are much less studied than New Zealand Chinook salmon. Patagonian populations are younger than those in New Zealand but much more widespread. The ancestral origin of these populations is unclear, but out of the many introduction attempts beginning in the late 1800s, two relatively recent experimental commercial open-ocean ranching operations were most likely the sources of the introduced populations (Table 8. The other open-ocean ranching operation took place further south in the Magellan region (51°S) during the period 1982–1989 using University of Washington Hatchery fall-run broodstock, Puget Sound, Washington, as well as the progeny of adult fish returning to Chiloé Island11.For the purpose of this study, we distinguish two classes of artificial propagation. In open-ocean ranching, returning adults are spawned artificially in fish hatcheries and the juveniles are released to grow at sea. These free-ranging fish may be harvested at sea but especially in a terminal fishery of maturing adults homing back to the stream of release. The second class is floating net-pen aquaculture. In this case, fish are held captive from hatching until harvest or reproduction (see below). One open-ocean ranching operation took place on Chiloé Island (42°S) during the period 1978–1982 using primarily Cowlitz River Hatchery spring-run brood stock from the Lower Columbia River, Washington, U.S.A.12. The stocks utilized, also poorly documented, were relatively diverse, as ova importations came at least from Washington, Oregon, Vancouver Island, and from New Zealand 13. In contrast to open-ocean ranching, net-pen aquaculture was mostly concentrated in Chile’s Lake District region (42°S)12. Therefore, in contrast to New Zealand, Patagonian Chinook salmon represent a potentially polyphyletic assemblage, offering new and interesting research avenues to study colonization dynamics and contemporary evolution. A summary of Chinook salmon introductions to Patagonia is presented in Table By 1988, Chilean salmonid propagation shifted entirely from open-ocean ranching to net-pen aquaculture in captivity. Despite the captive design, fish escaped in the thousands every year and many of those escapes were poorly documented14. The accuracy and precision of mixture analysis using the GAPS baseline is substantial with either conditional or unconditional Bayesian methods17 , producing novel genotypes not accurately attributable to any single source population. Founding effects and drift are not easily accounted for, but neither are they likely to fundamentally confound our analysis. When considering microsatellites or other neutral markers, it is unlikely that founding and drift would result in a Patagonian population looking more like an unrelated population than the true population of origin. Such a result would require parallel patterns of allele frequency convergence at multiple highly polymorphic loci. The problem of interbreeding is more serious. It was unclear to us how the Rannala and Mountain20 CML mixture algorithm would treat individuals of mixed origin. Simulations and sensitivity analysis helped us answer that question, and M-BC allowed an independent evaluation of CML mixture analysis in this unusual application of stock identification of introduced and naturalized populations.We analysed the genetic diversity and population structure of Chinook salmon in four western Patagonia basins. We then compared these to native North America populations, and finally estimated ancestry and lineage distribution in regions that differed in their history of artificial propagation by open-ocean ranching and net-pen aquaculture. For estimation of ancestry, we used two different classes of genetic mixture analysis, conditional maximum likelihood (CML) and model-based clustering (M-BC). We took advantage of a large, interagency, microsatellite baseline as our known-origin reference against which we compared fish from Patagonia. The international Genetic Analysis of Pacific Salmonids (GAPS) consortium assembled a comprehensive genetic baseline for coast-wide fishery management of mixed-stock fisheriesData quality and genotyping success were high, with an average of 12 out of 13 microsatellite loci scored per individual fish. We removed from the analysis 9 Toltén individuals that gave no reliable genotypes (collected as decomposing carcass samples), leaving 87 individual Patagonian Chinook salmon for our study.Ots213 and OtsG474 departed significantly from neutral expectation (FST outlier test) in Patagonian and North American populations, respectively, and were removed from further population genetic analyses due to potential directional selection. These loci were retained for genetic mixture analysis, which is generally robust to departures from neutrality. Oki100 and Ots208b also departed from neutral expectation in Patagonian populations, but were only marginally significant and so were retained. Pairwise allele frequency differences were not significant between sample collection locations within river basins in Patagonia, even including all loci  and were therefore pooled for population-level analyses. The analyses we present here are based on those river-basin-level aggregates of collections that are intended to represent separate populations, though because our samples are small, we scrutinized that assumption in several ways. For example, mean FIS value for Patagonian populations  was substantially larger than estimates from the North America baseline populations .HS = 0.83, SD = 0.024) was essentially identical to the average of all North American baseline populations  and close to the populations identified as likely founders  was not significantly different from that observed in all North American populations  nor in the putative founders . The 259 alleles observed in Patagonia included more than half of the 490 observed in North America, from the Yukon River in the Bering Sea to Central Valley California—most of the native species range21. Within Patagonia, overall genetic diversity did not differ significantly among river basins, as inferred from heterozygosity and allelic richness . Similarly, pairwise FST values were large among Patagonian populations , especially considering the relatively narrow range of genetic differentiation among the putative source populations  relative to all of North America .Between Patagonian river basins, allele frequencies were highly significantly different . Petrohué was similar to Baker and Aysén, whereas Toltén, the northern-most population, was the most distinct of the four.Contingency testing, pairwise Results: Simulated mixed-origin founding). Hence, in order to emphasize major contributing lineages and avoid over-interpretation, we focused on putative contributors with c. 10% or greater allocation from any source to any single Patagonian population  were identified by CML mixture analysis as possibly represented in Patagonia Figs . Despiteion Fig. . Seven pThe estimated number of lineages that contributed to our South American populations was higher in the north (Toltén and Petrohué) than in the south of our study area (Aysén and Baker) Fig. . West CaWhereas the two northern river basins 39°–42°S) appeared highly polyphyletic, the two southern basins (45°–48°S) were nearly monophyletic, attributing nearly all of their ancestry to the closely related lower Columbia River, West Cascade spring and Willamette River spring lineages. Despite small sample sizes and apparent mixed ancestry, we found general agreement between modelled stock composition estimates and the proportions of individual fish assignments  or reference populations  . Both at the reporting group and population-level, individual fish that did show affinity to multiple source lineages, were invariably associated with the same sources to which other fish in the same collection assigned with high probability. For example, Petrohué and Toltén had individuals that assigned with relatively high probability to North Oregon Coast, West Cascade spring and fall, Interior Columbia Basin summer/fall, and South Puget Sound fall; however other presumed mixed-origin individuals split their assignment probability among those same sources.The ancestries of most fish were readily identifiable though CML mixture analysis. Most assigned with high probability to one of the baseline reporting groups . Interior Columbia Basin summer/fall received about half of these misassignments, whereas the rest were distributed among 14 other unrelated reporting groups. This level of misassignment observed in simulated fish was much higher than the normal level of misassignment observed between closely related reporting groups in North America . Any criterion would be somewhat arbitrary, but for the empirical dataset there seemed to be a break between 0.08 and 0.1, and we knew that values below 0.08 could be relatively strongly influenced by the spurious assignments we revealed in the simulation.Our simulation study confirmed the general utility of CML mixture analysis for individual assignment and proportional allocation despite admixture, but also showed the potential for misleading results, even when individuals assign with high probability. Therefore, we interpreted our empirical results of CML mixture analysis of real fish with caution when the estimated proportional contribution of a reporting group approached the level of misassignment we observed in the simulation . Only five fish, collected in the Petrohué basin, assigned with high probability to another Puget Sound fall-run hatchery stock, Soos Creek (from which University of Washington brood stock was derived), but none were similar to our contemporary sample from University of Washington Hatchery fall-run stock.Simulated mixed-origin founding).Central Valley California was also a suspected source of Patagonian Chinook salmon, however, our results offered very little support for that conclusion at the locations we sampled. Only two fish assigned to Central Valley populations, one to Tuolumne River and the other to Stanislaus River. It was unclear if those two fish demonstrated true Central Valley ancestry or spurious assignments resulting from admixture (see above Methods) included 31 of the GAPS baseline populations21 from seven reporting groups . These reporting groups contributed most (84.13%) of the combined posterior probability in the reporting group-level CML mixture analysis  in the North American populations showed a peak in delta log likelihood at K = 3 and K = 5 , or a combination of West Cascade spring and Willamette River spring runs (Q4). Aysén fish mostly showed affinity with West Cascade spring/fall runs (Q3), but also some possible Willamette River spring (Q4) and little South Puget Sound fall and Whidbey Basin influence (Q5). In Petrohué, West Cascade spring/fall and Willamette River (Q3 and Q4) lineages were still important, but a substantial increase of all other lineages was apparent, particularly South Puget Sound fall and Whidbey Basin (Q5). This trend towards more diverse ancestry in the north of the Patagonian range persisted in Toltén where fish showed affinity to all five ancestral lineages inferred by the M-BC analysis (Q1 to Q5), and by extension the seven lineages distinguished in phylogeographic analysis of Chinook salmon in the native range21. Thus, the ancestry of Patagonian Chinook salmon populations was strongly spatially structured  We used the most inclusive baseline dataset possible, including all potential North American donor lineages. Previous studies have been more or less limited by the number of reference lineages available for particular genetic markers. The GAPS microsatellite baseline is the most extensive of its kind and is ideally suited for this application. (2) To our knowledge, ours is the first study of its kind to take into account the potential for spurious allocation of admixed genotypes. Other studies have addressed genetic drift in introduced populations18, but not admixture between divergent lineages. We suggest that admixture may be more problematic than genetic drift, and simulations of mixed-origin founding offered a cautionary note on potentially misleading results. Our observations are relevant to many studies that seek to characterize small genetic contributions from multiple founding lineages26. (3) Our study included naturalized populations both within and outside salmon aquaculture zones. This helped clarify the poorly documented role of net-pen aquaculture on Chinook salmon introduction to Chilean Patagonia. Thus, our study provides important new insight into the ancestry and history of colonization of Patagonian Chinook salmon.Our study is distinguished from previous molecular studies of Patagonian Chinook salmonFIS values within basins. Recognizing limited power for detecting a Wahlund Effect, we also tried to draw inference from CML individual assignment probabilities. Fewer intermediate assignments (split probabilities between reference groups) were observed than expected for a (simulated) mixed-origin population at equilibrium. If real, such a result and the possibly low heterozygosity might indicate assortative mating of two or more genetically distinct lineages within a river basin. Alternatively, strong out-breeding depression27 or insufficient time since introductions could result in fewer than expected mixed-origin and heterozygous individuals. A companion study to ours used the same Patagonian samples and an intensive genome scan of 11,759 single nucleotide polymorphisms (SNPs)25. That study compared results to those from selected North American populations that our study had identified as potential founders. Average FIS values for Patagonia populations were an order of magnitude higher for SNPs than for microsatellites. Yet SNPs estimated similar FIS values between North and South America. This was in contrast to our observation of a two-fold higher FIS in Patagonia. Resolution of these discrepancies and elucidation of specific population structure will require larger, and spatially stratified samples within and among river basins and across multiple generations.Mating structure is critical to our understanding of potential for adaptation and persistence of introduced lineages in Patagonia. Even though allele frequencies led us to pool within-river-basin samples into putative populations, we did find some evidence of heterozygote deficits including non-significant yet elevated 25. Initially, we assumed high genetic diversity, i.e., heterozygosity and allelic richness, was a result of mixed ancestry. Previous studies have made similar conclusions24. CML mixture analysis and M-BC both estimated more founding lineages in the two northern Patagonian sites. Surprisingly, however, populations with the greatest number of founding lineages showed no higher levels of heterozygosity or allelic richness. Nor was there spatial structure for heterozygosity or allelic diversity, as was evident for lineage diversity. It would seem almost axiomatic that a diversity of founders would introduce more alleles relative to monophyletic populations, yet, as mentioned above, other factors might be confounding a clear association between lineage diversity and genetic diversity.Our genetic CML mixture analyses strongly suggested a diverse array of founding lineages in Patagonia. Moreover, the number of founding lineages was clearly higher in northern Patagonia than in the south, and yet this latitudinal trend was uncorrelated with standard measures of genetic diversity. Overall, population genetic diversity measured by heterozygosity and allelic richness was higher than expected in Patagonia—nearly identical to North American populations. Both of these surprising results were consistent with those from the companion SNP study of the same Patagonian populations16. However, our simulation of mixed-origin founding revealed some spurious genetic allocation not previously reported in studies that used this approach26. The CML simulation showed us that mixed origin (admixed) individuals usually assign to the true donors, however, some individuals will assign to unrelated populations, sometimes with high assignment probability. Note, however, that the probability values are conditional on available baseline references. A high assignment probability might simply mean that no other reference population could likely have produced a given genotype. This is relevant, for example, to studies that assume a probability threshold  for accurate assignment, and especially to those with incomplete baseline datasets. While a probability threshold such as 0.8 is clearly useful in conventional genetic mixture applications17, in a mixed-origin founding application, it is almost certainly the case that some high-probability individual assignments are attributable to the misassignment phenomenon that we demonstrated through simulation. Apparently, introgression between donor populations results in unique genotypes that assign arbitrarily to other, unrelated populations. To avoid falsely implicating potential donor lineages we set a lower threshold for genetic contribution below which putative ancestry was viewed with caution and some skepticism. Based on review of both simulated and empirical data, we used a threshold of 10% estimated genetic contribution to any single population in Patagonia. It was not that we rejected as potential contributors lineages below 10%, rather we were less confident in identifying those as founders.A principal challenge in this study was to distinguish the genetic signal of true ancestry from the noise created by mixed-origin, introgressed populations. In our CML mixture analysis we expected some misassignments between related populations. The patterns of misassignment in the North American reference baseline .Despite this caveat, our findings clearly confirm the importance of entrepreneurial attempts to establish Chinook salmon open-ocean ranching programs in Chile during the late 1970s and 1980s. In particular, the West Cascade spring and fall lineages, introduced from the Lower Columbia River, were likely associated with the enterprises suspected to have initiated the invasion. In 1978 Domsea Pesquera Chile Ltda.  began yearly stockings of Chinook salmon in a small stream on Quinchao Island, Curaco de Vélez, Chiloé (42°S). Three strains of Chinook salmon were introduced: Cowlitz River spring run, Bonneville Hatchery fall run, and University of Washington Hatchery fall run, in decreasing number of individuals released10. Here, Salmones Antártica S.A., initiated stockings first in Río Santa María (1982) and then in Río Prat (1983–1989) using University of Washington Hatchery fall-run and the newly established Chilean-based brood stocks  from Petrohué River assigned to Soos Creek Hatchery.Subsequent open-ocean ranching experiments in the Magellan region 51°S) utilized the University of Washington Hatchery fall-run stock°S utiliz24, but owing to the low resolution of those analyses , those results deserve further scrutiny. Other investigators, using SNPs and a more extensive baseline31, found little evidence to support South Puget Sound ancestry, although they still suggested a possible contribution of University of Washington Hatchery stock based on its supposed origin from lower Columbia River lineages, which do appear as major contributors to Patagonian populations19. Our results provided no support whatever for that interpretation. The GAPS baseline shows no similarity between Lower Columbia River populations and the most recent sample from University of Washington Hatchery stock—or indeed any other Puget Sound populations. University of Washington Hatchery brood stock is genetically distinct with 80% correct assignment of known-origin fish in a leave-one-out self-assignment test. Moreover, all University of Washington Hatchery fish assign correctly to the South Puget Sound fall run lineage . Further study is obviously needed in the Magellan region where the University of Washington Hatchery brood stock was introduced.Previous studies have inferred ancestral affiliation from the University of Washington Hatchery based on mitochondrial DNAPatagonian Chinook salmon unrelated to the West Cascade spring and fall lineages (hereafter non-WC) accounted for almost half of the fish (45.8%), mostly taken from north of parallel 45°S. The phylogenetic origins of non-WC fish were tracked to 14 diverse and geographically widespread lineages in North America. This seemingly hyperdiverse assemblage is at least partly explained by spurious individual assignments, especially those related to mixed ancestry (consistent with our simulations). However, much of this diversity appears due to accidental escapes from thriving Chilean net-pen salmonid aquaculture operations in the 1990s that imported ova from diverse sources.32. Data gathered from insurance companies alone12 led to an estimate of one million salmon and trout escaping every year, primarily from net-pen aquaculture. Although Chinook salmon farming has always been marginal in Chile relative to other species , sustained Chinook salmon farming in leaky rearing facilities certainly contributed propagules to the wild32. We estimate that with one million escaped salmon and trout per year, adjusting for the contribution of Chinook salmon to annual harvest33, c. 100,000 farmed sub-adult Chinook salmon might have escaped between the onset of modern salmonid farming (1988) and the date of our sampling (early 2004). During this period, numerous aquaculture companies were established in Chile, propagating Chinook salmon brood stocks to meet increasing demand. Aedo13 assembled the fragmentary record of importations and concluded that ova originated at least from Washington, Oregon, Vancouver Island, and New Zealand , but specific stocks mostly went undocumented  to another population in the Atlantic slope . The population closer to the Lake District region (Pacific slope) showed affinity to more lineages than the population in the Atlantic slope19. Thus, escapes from net-pen aquaculture activity in the Lake District region have augmented the genetic diversity initially introduced by open-ocean ranching operations24, this study. Similarly, the introgression of cultured rainbow trout genes into pre-existing, naturalized, rainbow trout populations in Patagonia, has also been demonstrated34.Although sparse, this information could explain the incidence of Patagonian genotypes related to multiple lineages of the West Coast of U.S.A. Furthermore, the spatial distribution of non-WC fish was concentrated in the north (Toltén and Petrohué), consistent with more intensive propagule pressure of distinct lineages farmed in this region. In fact, during the 1990s, most aquaculture activity (and escapes) was concentrated in the Lakes District region (41–43°S), within 200 km of the Petrohué River. Toltén River (39°S), being a few hundred kilometres further north, might have received colonists dispersing naturally from the Lake District region, escapees from inland hatcheries, or deliberate stockings. Both Toltén and Petrohué are located in well-populated regions easily accessible by paved roads. In sharp contrast, our more remote southern study sites (45–50°S) experienced only incipient aquaculture activity (Aysén River) or none at all (Baker River). Here, accidental escapes or unreported deliberate stockings were less likely, and natural dispersion alone seems the most likely source of founders, especially in the remote and isolated Baker River basin. Other studies have come to similar conclusions by comparing one Chinook salmon population in the Pacific slope of Patagonia .An apparent lack of Central Valley ancestry was similar to the findings of one previous molecular study18. A number of possibilities could explain this interesting pattern: (1) As discussed above, higher propagule pressure of distinct lineages escaping from fish farms might have resulted in higher lineage diversity in northern sites compared to remote southern localities that lacked farms (propagule pressure hypothesis). (2) Most dispersing colonists moved northwards in our study area such that those colonizing Aysén and Baker rivers were derived from stockings in the Magellan region of West Cascade spring and fall ancestry, whereas those colonizing Petrohué and Toltén rivers were derived from fish farms in the Lake District region (propagule+dispersion hypothesis). This pattern would resemble natural ocean migration patterns of Washington and Oregon stocks towards the north in the North Pacific, although it is unclear how the fish would respond to magnetic stimuli of the southern hemisphere. (3) Deliberate stockings initiated the first wave of invasion that eventually reached Aysén and Baker rivers, either from the north or south. Previous establishment of West Cascade spring and fall lineages might have inhibited the expansion of farmed lineages from the north (density-dependent hypothesis). At present, it is hard to gauge the relative importance of these processes, and it is conceivable that each contributed to the observed pattern of lineage distribution.Notable patterns of lineage distribution are emerging at a continental scale. Northern study sites (Toltén and Petrohué) showed unexpectedly high lineage diversity, including substantial estimated contributions from five or more lineages . By contrast, southern study sites (Aysén and Baker) revealed a striking dominance of three closely related lineages from the Lower Columbia River . Similar diversity was also found in the Santa Cruz River draining to the Atlantic Ocean in Argentinian Patagonia19, this study, high phenotypic plasticity and rapid adaptive evolution observed in Chinook salmon introduced to New Zealand7, as well as adaptation to environmental conditions inferred for Patagonian populations36, are all features that suggest high adaptive potential of Chinook salmon in Patagonia. Lower-than-expected levels of heterozygosity, if confirmed and maintained over generations, could indicate reproductive isolation between sympatric lineages, which would help maintain lineage identity. Whether this happens is crucial to the evolutionary trajectory of the species in its new range. Lineages could either evolve adapting genetically to local conditions7 or they could interbreed and recombine, potentially resulting in new phenotypic variation with unpredictable evolutionary outcomes. Chinook salmon may exert strong ecological impacts in freshwater, estuarine and marine ecosystems35, and different evolutionary outcomes will directly affect these impacts owing to considerable phenotypic variation among lineages.Complex invasion dynamics and distinct patterns of genetic diversity are likely to have profound evolutionary consequences in the continuing range expansion of Chinook salmon in Patagonia. High genetic diversity, as measured by high allelic and lineage richness35. Fish sample collections were approved by Chilean Subsecretaría de Pesca del Ministerio de Economía, Fomento y Reconstrucción in accordance to their guidelines and regulations .Chinook salmon populations were sampled in the fall of 2004 from rivers in the four Andean basins of Toltén, Petrohué, Aysén and Baker (39–48°S), all draining to the South Pacific through Chile Fig. . The res37. We used the GAPS Chinook salmon microsatellite markers following the GAPS consortium conventions for standardization of genotypic data14. We calculated allelic and genotypic frequencies as well as diversity metrics allelic richness, AR , and expected heterozygosity, HS, estimated with FSTAT v2.9.339. Fixation indices FST and FIS were represented by Weir and Cockerham’s38 multilocus estimators, θ and f, calculated with FSTAT v2.9.339. FST was used to evaluate relationships among populations (see below) whereas FIS was used to evaluate departures from Hardy-Weinberg-Castle (HWC) expectations for genotypic proportions within putative populations40. We also tested for composite linkage disequilibrium by using the Markov chain Monte Carlo (MCMC) method implemented in the program GENEPOP v4.241. Before proceeding with our population genetic analyses, we tested for loci that departed from neutral expectation in order to avoid loci that might bias our parameter estimates and genetic distance estimates . We used the FST outlier approach42 implemented in the LOSITAN software package43. Genetic differences among the South American river basins were analysed in more detail utilizing pairwise FST values and leave-one-out jackknife self-assignment among introduced populations in order to characterize genetic differences among the introduced Patagonian populations. Because our sample sizes were small, we were especially cautious of non-significant results because we had little power to reject null hypotheses, even when false. However, where we did observe statistical significance, we generally trusted our results as biologically meaningful, despite small sample sizes.DNA was extracted from individual fish tissue samples by using silica-based purification . Genomic DNA samples were amplified for 13 highly polymorphic microsatellite loci and genotyped by using an Applied Biosystems Incorporated (ABI) 3100 Genetic Analyzer and ABI’s Genescan and Genotyper software (v3.7), according to established methods14 to represent as closely as possible historical phylogeographic lineages in North American Chinook salmon. Specifically, we used a slight modification of the dataset analysed by Moran et al.21. We added the following populations because they were identified previously as potential sources of Patagonian Chinook salmon , which is the level of inference in essentially all our interpretations. The mean probability across individuals for membership to a particular lineage was taken as an approximation of overall genetic ancestral contribution to the population . Simulation studies helped us evaluate the strength of those assumptions under conditions of mixed ancestry. The CML analysis was used as a first approximation to help narrow the range of contributing lineages to just the major contributors. A reduced set of populations and lineages was then further analysed by M-BC.Two different methods were used to explore the likely ancestry of introduced Chinook salmon populations in Chile, conditional maximum likelihood (CML) and model-based clustering (M-BC). As a first approximation of genetic similarity and potential ancestry, we used the Rannala and Mountain26, its validity in that application has not to our knowledge been demonstrated. As a test of the algorithm’s sensitivity to the presence of mixed-origin founding, we simulated a new population derived from large and equal numbers of individuals from two of our North American baseline populations. These were specific populations that appeared to be associated with the introduction to Patagonia . That simulated founding involved the creation of an ideal population (at mutation/drift equilibrium) with intermediate allele frequencies to the Cowlitz River and Puget Sound source populations. We then drew 1000 individuals from that new, mixed-origin population, and we estimated the posterior probability distributions for those simulated individuals, the same as we did for the real Patagonian fish. We sought to determine whether the admixed genotypes would assign with high probability to one or the other source population, or split their probability of assignment between the two source populations. These novel genotypes might even assign to other, unrelated populations in the large coast-wide North American baseline (where “assignment” simply reflects the maximum a posteriori probability of membership to population or reporting group). We needed to know the extent to which potentially spurious assignments might affect our analysis of the Patagonian populations. As a benchmark for misassignment in the North American reference populations, we conducted a leave-one-out, jackknife analysis for comparison of a posteriori probability distributions between simulated mixed-origin fish and real fish, from both North and South America . The 10% value was selected based on an apparent break in the composition estimates. We also inferred from simulations that allocations of less than 10% might be due at least in part to spurious assignment of mixed-origin fish (see Methods: Simulated mixed-origin founding).Based on the results of our CML mixture analysis we conducted a more focused model-based cluster analysis (M-BC) of the introduced fish relative to the putative source populations using computer program Structure v2.3.4i.e., α, F, divergence among populations Di,j, and the likelihood estimate). We used an admixture model, including location information45, with allele frequencies correlated among populations46. We assumed population specific FST values, and updated allele frequencies by using baseline individuals only, thus treating Patagonian samples as having unknown origins. Multiple MCMC chains (10) were constructed for each value of K . We modelled values of K from two to nine for the North American populations. The most appropriate K value was selected based on likelihood and ∆K47, as well as optimal discrimination of putative North American source populations. Structure output was processed with the STRUCTURE HARVESTER computer program48, and plotted in the R computing environment version 3.3.149.For the M-BC analysis, we conducted 110,000 MCMC realizations per chain, discarding the first 10,000 iterations as a burn in. Apparent convergence of diagnostic parameters was observed within the first 10,000 iterations (Supplementary Information


Tursiops truncatus, is widely distributed along the western coast of South America. In Ecuador, a resident population of bottlenose dolphins inhabits the inner estuarine area of the Gulf of Guayaquil located in the southwestern part of the country and is under threat from different human activities in the area. Only one genetic study on South American common bottlenose dolphins has been carried out to date, and understanding genetic variation of wildlife populations, especially species that are identified as threatened, is crucial for defining conservation units and developing appropriate conservation strategies. In order to evaluate the evolutionary link of this population, we assessed the phylogenetic relationships, phylogeographic patterns, and population structure using mitochondrial DNA (mtDNA). The sampling comprised: (i) 31 skin samples collected from free-ranging dolphins at three locations in the Gulf of Guayaquil inner estuary, (ii) 38 samples from stranded dolphins available at the collection of the “Museo de Ballenas de Salinas,” (iii) 549 mtDNA control region (mtDNA CR) sequences from GenBank, and (iv) 66 concatenated sequences from 7-mtDNA regions  obtained from mitogenomes available in GenBank. Our analyses indicated population structure between both inner and outer estuary dolphin populations as well as with distinct populations of T. truncatus using mtDNA CR. Moreover, the inner estuary bottlenose dolphin (estuarine bottlenose dolphin) population exhibited lower levels of genetic diversity than the outer estuary dolphin population according to the mtDNA CR. Finally, the estuarine bottlenose dolphin population was genetically distinct from other T. truncatus populations based on mtDNA CR and 7-mtDNA regions. From these results, we suggest that the estuarine bottlenose dolphin population should be considered a distinct lineage. This dolphin population faces a variety of anthropogenic threats in this area; thus, we highlight its fragility and urge authorities to issue prompt management and conservation measures.The common bottlenose dolphin,  Tursiops truncatus has not been well-defined, suggesting different lineages in this species  from the Australian continent  based on osteological and genetic data (The common bottlenose dolphin (hereafter bottlenose dolphin) is widely distributed in pelagic and coastal waters, including sounds, bays, and estuaries . The ecotic data . The coatic data  while thtic data ; howevertic data . The offtic data , whereastic data . Additiotic data . Converstic data .Although the bottlenose dolphin is widely present along the entirety of the western coast of South America , only onIn the Gulf of Guayaquil inner estuary, two photo identification studies were carried out in the 1990s focusing on the behavioral ecology, social organization, and social structure of the bottlenose dolphin population , 1997. TThe bottlenose dolphins in the Gulf of Guayaquil inner estuary reside in an area characterized by high biological productivity. During the cold, dry season, the Humboldt Current and superficial subtropical water mass promote outcrops of high-nutrient waters with increased biological productivity . There aThe bottlenose dolphin population of the Gulf of Guayaquil inner estuary (hereafter referred to as the estuarine bottlenose dolphin) is one of the most vulnerable populations due to human population increase and coastal development activities . This haT. truncatus populations elsewhere based on analyses of several mitochondrial DNA (mtDNA) regions. The genetic study was conducted using: (i) a 392 bp fragment of mtDNA control region (mtDNA CR) to estimate the genetic diversity of the bottlenose dolphin of the Gulf of Guayaquil; (ii) 397 bp mtDNA CR sequences to assess population divergence, phylogeographic patterns, and phylogeny between the estuarine bottlenose dolphins and bottlenose dolphin populations elsewhere; and (iii) 7-mtDNA regions  to determine phylogenetic relationships including distinct T. truncatus populations and all species inside the genus Tursiops. To our knowledge, this is the first genetic study carried out with bottlenose dolphins in the Gulf of Guayaquil. The results will be discussed in terms of conservation. The estuarine bottlenose dolphin is Ecuador’s most vulnerable dolphin population because of anthropogenic threats, so understanding population boundaries is essential to improving local management strategies and ensuring the short-term conservation of the bottlenose dolphin in the area.The aim of this study is to assess the evolutionary link of the estuarine bottlenose dolphin in the Gulf of Guayaquil with The Gulf of Guayaquil, the largest estuary on the southeast Pacific coast, is located in southwestern Ecuador (3°S and 81°W)  Stevens. The entThe weather in the study area is characterized by two seasons: one warm, rainy from January to May, and the cold, dry from June to November . Rainfaln = 14) and inner  estuary of the Gulf of Guayaquil, Galápagos Islands (n = 1), and Santa Rosa, Peru (n = 1). The other stranded samples (n = 8) were collected in different undefined locations from the Gulf of Guayaquil. Occipital condyle and mandible bone powder were gathered based on the technique reported by We included 38 museum samples, which are available from the “Museo de Ballenas de Salinas”  collection in the Salinas city. The samples belong to the mentioned museum according to the patent of wildlife management granted by the Department of Salinas, Ministry of Environment of Ecuador (patent number FAU-0002-DPSE/VS). Of 38 museum samples, one was a skin sample (Ttr_1) from a Galápagos free-ranging dolphin, and 37 (Ttr_2–Ttr_37 and Ttr_69) were obtained from stranded dolphins (eight skin and 29 bone samples). Stranded samples were collected from different years  and locations, including the outer  from the Gulf of Guayaquil inner estuary  from free-ranging dolphins at three different sites  was isolated using a modified proteinase K digestion protocol and two chloroform: isoamyl alcohol (24:1) extractions followed by ethanol precipitation . We extrn = 69) with a duplex polymerase chain reaction (PCR) amplification using two sets of primers, ZFX0582F and ZFX0923R . PCR thermo-cycling conditions consisted of an initial denaturation step at 95 °C for 5 min, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 51 °C for 45 s, and extension at 72 °C for 45 s with a final extension step at 72 °C for 10 min. Gender was determined by the banding pattern on a 2.5% agarose gel, stained with ethidium bromide, and visualized under ultraviolet light.We identified the sex of all free-ranging and stranded dolphins , we amplified 7-mtDNA regions , cytochrome oxidase I and II, (COI and COII), cytochrome b (Cyt b), and the mtDNA CR) designed on the basis of the T. truncatus mitochondrial genome. The details of each set of primers are listed in For all samples . This sequence was chosen because it represents the coastal ecotype mitogenome from the eastern Pacific Ocean (h), and nucleotide diversity (π) with Arlequin v.3.5 , and the outer estuary dolphins, represented by three communities . On a broad geographic scale, population genetic differentiation was evaluated in both the inner and outer estuary dolphin populations from the Gulf of Guayaquil in addition to global populations. In the analyses, we incorporated 432 mtDNA CR sequences from different geographic regions made available in the GenBank. We implemented an analysis of molecular variance (AMOVA) to compute significance with 10,000 permutations (FST), haplotype frequency and genetic distance (φST) via Arlequin v.3.5  using jModelTest v.2.1.4 software  different geographic locations and the number of net nucleotide substitutions per site between populations (Ad) using Tamura–Nei model via MEGA 6 software . The details of mtDNA CR haplotypes and their corresponding GenBank accession number are summarized in We constructed two phylogenetic trees to infer the phylogenetic relationships of the Gulf of Guayaquil bottlenose dolphins based on Bayesian inference using MrBayes v.3.2.2 . A singln = 40). We aligned all concatenated sequences obtained with 66 concatenated sequences from 7-mtDNA regions available in the GenBank (65 belonging to different species of Tursiops and one as outgroup). The 65 concatenated sequences from 7-mtDNA regions belong to T. truncatus (n = 59), T. aduncus (n = 4), Burrunan dolphin . The details of the mtDNA regions and their corresponding GenBank accession number are summarized in S. bredanensis (accession number JF339982.1). We aligned all sequences using CLUSTAL W implemented in MEGA 6 software  values using Tracer v.1.6 software  to ensurn = 29) and four skin samples could not be amplified. The five stranded samples were identified as four females and one male. In estuarine bottlenose dolphins, molecular sex determination showed a sampling bias in favor of males (22) over females (9) (sex ratio 2.4:1). The details are summarized in Of the 29 bone samples included in the study, 13 samples could not be amplified for mtDNA CR . Sex wasn = 40), 450 (n = 13), and 350 bp (n = 3), which were truncated to 392 bp. The sequences shorter than 392 bp were excluded from all analyses. A total of 48 samples were analyzed for the genetic diversity of Gulf of Guayaquil dolphin populations. Overall, haplotype diversity (h) and nucleotide diversity (π) were h = 0.7154 ± 0.0676 and π = 0.1510 ± 0.0826, respectively. mtDNA CR genetic diversity was higher in the outer estuary population than in the inner estuary population . However, the analysis of genetic distances (φST) did not indicate differences between locations . On a broad geographic scale, the analyses indicated a genetic structuring among populations  and genetic distances . Pairwise FST and φST comparisons confirmed significant differences among estuarine bottlenose dolphin population and other bottlenose dolphin populations; whereas, the outer estuary population was significantly different from the majority of the dolphin population  and the average divergence (XYd) values showed a divergence (Ad = 0.015 and XYd = 0.030) between both outer and inner estuary populations. At the same time, the population divergence analyses revealed a high divergence between the estuarine bottlenose dolphin population and all other populations. The Ad values varied between 0.023 and 0.047 and the XYd values varied between 0.034 and 0.052. Additionally, the analyses of population divergence did not indicate divergence between the outer estuary population and some bottlenose dolphin populations, particularly with Gulf of California populations. The Ad values varied between 0.001 and 0.038 and XYd values varied between 0.022 and 0.044 , (ii) 16S rRNA of 562 bp (n = 47), (iii) ND1-ND2 of 897 bp (n= 40), (iv) COI of 837 bp (n = 40), (v) COII of 738 bp (n =40), (vi) Cyt b of 436 bp (n = 47), and (vii) CR of 715 bp (n = 45). In Overall, we obtained a 5,237 bp concatenated consensus sequence of 7-mtDNA regions: (i) 12S rRNA-16S rRNA of 1,050 bp  were clustered with the single coastal haplotype from the Gulf of California (accession number KF570389.1), whereas two haplotypes  were clustered with the sequences of the pelagic population from Western Atlantic Ocean as well as with sequences of the coastal populations from the Black Sea, and the Mediterranean Sea   (Orcinus orca (T. aduncus (n = 31)  . The gen= 0.697) . The low= 0.697) . Similarπ = 0.9) . The lowπ = 0.9) ; (ii) a π = 0.9) ; (iii) yπ = 0.9) ; or (iv)π = 0.9) . Low nucπ = 0.9) . For insnus orca  and T. a aduncus . However 31) see .FST = 0.231, P < 0.05). The pattern of genetic differentiation among bottlenose dolphins inhabiting adjacent habitat types has been seen previously in populations of T. truncatus . This is because of the high intraspecific diversity and low interspecific divergence observed in this subfamily (T. truncatus (KF570386.1). The Galápagos Islands dolphin populations were formerly described as an offshore ecotype based on morphological data  from different geographic regions made available in the GenBank database with 53 CR region sequences of this study.Click here for additional data file.10.7717/peerj.4589/supp-2Supplemental Information 2The database includes 28 Ecuadorian haplotypes and 66 concatenated sequences from 7-mtDNA regions available in the GenBank.Click here for additional data file.10.7717/peerj.4589/supp-3Supplemental Information 3Tursiops truncatus, NA: not available, CR: control region, COI: cytochrome oxidase I, COII: cytochrome oxidase II, Cyt b: cytochrome b. F: female, M: male, a) genetic diversity b) population structure and genetic divergence, c) phylogeographic analysis, d) mtDNA CR phylogenetic analysis, e) 7-mtDNA regions phylogenetic analysis. * skin biopsy from free-ranging dolphin, + genes/regions that were excluded from the analyses, - did not amplify.All bone powder was collected on January 19, 2013. Acronyms: Ttr: Click here for additional data file.10.7717/peerj.4589/supp-4Supplemental Information 4COI: cytochrome oxidase I, COII: cytochrome oxidase II, Cyt b: cytochrome b, ND1-ND2: NADH dehydrogenase subunit I-II.Acronyms: bp: base pair, Ta: Temperature annealing, mM: milimolar, CR: control region, Click here for additional data file.10.7717/peerj.4589/supp-5Supplemental Information 5The table includes the accession numbers and sequences geographic location. Number of samples by haplotype (n). Acronyms: Hap: Haplotype, C: coastal, O: Offshore, P: pelagic, U: unknown.Click here for additional data file.10.7717/peerj.4589/supp-6Supplemental Information 6The table includes the accession numbers, haplotype name, sequences geographic location, and ecotypes. Number of samples by haplotype (n). Acronyms: E: Ecotype, C: coastal, P: pelagic, O: offshore, U: unknown.Click here for additional data file.10.7717/peerj.4589/supp-7Supplemental Information 7The table includes the accession numbers, sequences geographic location, ecotypes, and the species. Acronyms: C: coastal, P: pelagic, U: unknown.Click here for additional data file.10.7717/peerj.4589/supp-8Supplemental Information 8Tursiops truncatus, * samples excluded from genetic diversity, population structure, and genetic divergence analyses.Number of samples by haplotype (n). Acronyms: Hap: Haplotype, Ttr: Click here for additional data file.10.7717/peerj.4589/supp-9Supplemental Information 9Tursiops truncatus, CR: Control region, COI: cytochrome oxidase I, COII: cytochrome oxidase II, ND1-ND2: NADH dehydrogenase subunit I-II, Cyt b: cytochrome b.The table includes the accession numbers of the sequences which are similar to the sequences found in the present study. 100% of similarity is in bold. 95% of similarity is in red. Acronyms: H#: number of haplotype; Hap: Haplotype, Ttr: Click here for additional data file.10.7717/peerj.4589/supp-10Supplemental Information 1012S rRNA, 16S rRNA, and tRNAs), Protein-coding genes .Total number of sequences (n), base pair (bp), polymorphic sites (S), non-coding (Click here for additional data file.


The genetic diversity and relationships among ethnic minority populations of southwest China were investigated using seven polymorphic restriction enzyme sites in the β-globin gene cluster. The haplotypes of 1392 chromosomes from ten ethnic populations living in southwest China were determined. Linkage equilibrium and recombination hotspot were found between the 5′ sites and 3′ sites of the β-globin gene cluster. 5′ haplotypes 2 (+−−−), 6 (−++−+), 9 (−++++) and 3′ haplotype FW3 (−+) were the predominant haplotypes. Notably, haplotype 9 frequency was significantly high in the southwest populations, indicating their difference with other Chinese. The interpopulation differentiation of southwest Chinese minority populations is less than those in populations of northern China and other continents. Phylogenetic analysis shows that populations sharing same ethnic origin or language clustered to each other, indicating current β-globin cluster diversity in the Chinese populations reflects their ethnic origin and linguistic affiliations to a great extent. This study characterizes β-globin gene cluster haplotypes in southwest Chinese minorities for the first time, and reveals the genetic variability and affinity of these populations using β-globin cluster haplotype frequencies. The results suggest that ethnic origin plays an important role in shaping variations of the β-globin gene cluster in the southwestern ethnic populations of China. According to the 2010 population census, excluding the Han, who forms the majority of the Chinese population, there are 55 other officially recognized ethnic minority populations accounting for 8.49% of the Chinese national population. More than 30 Chinese ethnic minorities inhabit in southwest China, most of them inhabit only in the region, such as Thai, Achang, Deang, and Tibetan. Due to the plateau and mountainous geographic features of the region, these populations have adapted the distinctive natural environment including climate, high altitude and epidemic infectious diseases, also experienced founder effect resulted from regional geographic isolation. Therefore, ethnic minority populations of southwest China present abundant diversity and distinction on their historic origins, languages, cultures, and genetic characteristics. Many studies have focused on understanding the genetic structures and relationships in these ethnic populations using microsatellite, mitochondrial DNA (mtDNA) and Y chromosome markers1225The value and power of β-globin gene cluster markers in resolving origins, migration and evolutionary relationships within human populations worldwide have been well demonstrated789101113In the present study, we examine for the first time the allelic and haplotypic characteristics of the β-globin gene cluster in 10 ethnic minority populations, mainly from southwestern China. This study also integrated these results with those data previously published for Chinese and other world populations, and evaluated the genetic variability and relationship among the ethnic Chinese populations.We used a likelihood-ratio test of Arlequin software to evaluate linkage disequilibrium between a pair of loci in the studied populations from southwest China. Pairwise linkage disequilibrium (LD) were observed among the loci HincII 5′ ε, HindIII G γ, HindIII Aγ, HincII 5′ Ψβ and HincII 3′ Ψβ at the 5′ end of the β-globin gene cluster, as well as between AvaII β and Hinf I 3′ β loci at the 3′ end of the cluster. But LD was not observed between loci of the 3′and the 5′ ends of the cluster . These s5) possible 5′ haplotypes were observed in the southwestern minority populations, but only haplotype 2, 5, 6 and 9 reached frequencies greater than 0.02. Haplotypes 25 (+++++) and 26 (++−+−) have never been described before this study. Seven haplotypes, 3, 17, 19, 20, 27, 28 and 29, were identified for the first time in Chinese populations with low frequencies as in other populations elsewhere. Haplotype 2 (+−−−−) was the most and 6 (−++−+) was the second most prevalent in the minorities of southwestern China with frequencies range of 0.570–0.779 and 0.035–0.174, respectively. The distribution patterns of common haplotypes 2, 6 and 5 in the southwestern minorities are generally consistent with that in other world populations. However, haplotype 2 was somewhat less frequent in Achang and Deang, and haplotype 5 was absent in Khmus. Achang participants had a significantly higher frequency of haplotype 4 (0.125), which is only slightly less frequent than that in African populations (0.152).The haplotypes derived from the five polymorphic sites of the 5′ β-globin cluster from the 10 southwestern minority groups and other populations are reported in The distribution of the β-globin gene cluster haplotype showed geographic variation. The Chinese populations from the southwest and from north are distinguished by the distribution of haplotype 9 (−++++). Haplotype 9 is the third most prevalent haplotype with frequency of 2.2–8.5% in the southwest Chinese populations, but it is absent or very rare (<1%) in all other populations elsewhere . On the We also measured genetic variability of Chinese populations using heterozygousity and Gini-Simpson index (GSI). We found that heterozygousity and GSI of Achang, Deang and Khmus are much higher than that of all other Chinese populations except Oroqens from northern China, and are comparable with African. This suggests that the populations with longer history have higher levels of genetic variability.We identified 3′ haplotypes based on the presence (+) and absence (−) of AvaII and Hinf I restriction sites . We founT) of the southwestern Chinese population is 52.5%, of which 88% may be ascribed to genetic variation within populations. The level of heterozygosity observed in the southwestern Chinese is higher than that in northern Chinese, but the correction for gene differentiation coefficient (GST′) is lower in southwest Chinese (2.5%) than in northern Chinese (3.7%), indicating less interpopulation differentiation among the southwest populations. The lowest GST′ were observed in northern Chinese Han (0.5%) and Thai (0.7%) subpopulations, while high degree of interpopulation differentiation was observed in Tibetan (GST′ = 1.2%), indicating genetic heterogeneity among different Tibetan subpopulations from different inhabitation regions. Likewise, when the northern Han were analyzed together with southern Han (Han), the GST′ was significantly increased, suggesting high differentiation between south and north Chinese Han populations.The measures of genetic diversity in Chinese ethnic populations and other world populations are presented in Using pairwise Fst (F-statistics) and exact test of non-differentiation based on 5′ haplotype frequencies, the most significant differences and greatest genetic heterogeneity were observed in inter-ethnic comparisons of the Chinese populations  and 2. KThe β-globin gene cluster haplotypes have been largely shown as important and useful for investigating genetic variability, origin, migration and evolutionary relationships between populations worldwide. Our present study is the first report characterizing the β-globin gene cluster haplotypes in southwestern Chinese minorities, and reveals genetic variation and relationships in these ethnic populations. We found the allelic and haplotypic characterization of the β-globin gene cluster, and the significant differences in genetic variability, characteristics and distribution patterns of the haplotypes among the study populations. Our results demonstrate that current haplotypic variation of the β-globin gene cluster in Chinese ethnic populations mirrors their ethnic origin and linguistic classifications.Our finding reveals the distribution characteristics of β-globin gene cluster haplotype in ethnic minority populations of southwest China. In the southwestern Chinese minorities, 5′ haplotype 2, 6, 9 and 5 are more prevalent overall, while haplotypes 12 and 4 are less common but not rare . Haploty810121415161016The origin of β-globin gene cluster haplotypes in the populations of southwest China has not been explored. The haplotypes 2, 5 and 6 are considered primitive and first-order haplotypes as they are separated from each other by at least two genetic events, mutation or recombination. The origin of the rest of the haplotypes is derived from the first-order types by recombination8Our results show linkage disequilibrium between the five sites within the 5′ region of the β-globin gene cluster and between the other two sites within the 3′ terminal, whereas linkage equilibrium was observed between 5′ and 3′ haplotypes as a result of the recombination hotspot between the two regions , Fig. 1.1111E, HBB codon 26 G > A) reported in the Achang, Deang and Jingpo minority populations living in the region23E gene was found exclusively linked to haplotype 9 and FW2 in southwestern Chinese minorities in our previous studyHBB gene βA (HbAA) was linked to 5′ haplotypes 2, 6, 9, 5  in the Achang, Deang and Khmus from southwestern China was found to be much greater than that of other Chinese populations with the exception of Oroqens . Deang iOur study explores how ethnic minority populations of southwest China are related to each other and other populations. Our findings demonstrate that genetic affinities among ethnic Chinese populations show ethnic and linguistic patterns. Some studies using microsatellite and mitochondrial DNA (mtDNA) markers have found distinct genetic divergence between southern and northern Chinese populations, and have argued that northern populations are derived from southern Chinese populations1512When genetic relationships between world populations were analyzed using haplotypic frequencies, the majority of Chinese ethnic groups were clustered together and close to other Asia and Amerindian populations as expected . As a re91016In conclusion, the β-globin haplotype is useful for elucidating genetic variation, affinity and ethnic origin of human populations. Here we have shown that the distribution of β-globin haplotypes is significantly heterogeneous in minority populations of southwest China, the distribution pattern is significantly different with that of populations in other regions of China. Moreover, we have demonstrated that the genetic affinity of Chinese population show ethnic and linguistic patterns. The genetic heterogeneity and differentiation presented in the southwest Chineses ethnic populations deepen our understanding of their ethnic history and gene flow. The diversity of the β-globin gene cluster in Chinese populations is mainly attributed to ethnic origin. Meanwhile, admixture, geographic isolation and genetic recombination are important factors accounting for the genetic variations observed. Overall, our findings provide new comparable data for revealing genetic diversity and the relationships of Chinese populations, and once again, and show that the β-globin gene cluster can provide a large amount of substantial information on elucidating human history and evolution.HBB) mutations were excluded based on hematologic and molecular genetics analyses for thalassemia. A total of 1392 chromosomes with normal β-globin genotype HbAA (βA) from 696 individuals were examined in the present study.Ten ethnic minority groups belonging to six Chinese nationalities: Achang, Deang, Khmus , Jingpo, Thai (named Dai in Chinese) and Tibetan from south-to-west China regions including Yunnan, Tibet and Qinghai provinces, were studied. The chosen groups well represent ethnic populations of southwest China as they inhabit only in the region, with different historic origins and cultures. The sample size was chosen to satisfy the needs of genetic statistics. It varied with size and sample availability of the different ethnic groups. The sampling, geographic location and linguistic affiliation of the populations are presented in There are seven polymorphic restriction sites in the β-globin gene cluster: HincII 5′ ε, HindIII G γ, HindIII Aγ, HincII 5′ Ψβ, HincII 3′ Ψβ, AvaII β and Hinf I 3′ β ; these s27http://www.personal.psu.edu/nxm2/dispan2.htm, copyright 1993 by Tatsuya Ota and the Pennsylvania State University) was used to measure genetic diversity parameters HT (the average heterozygosity for the entire population), Hs (the average heterozygosity within populations) and GST (gene differentiation coefficient). The haplotype frequencies in the present study were integrated with those from other populations in China and around the world using data from previous reports810111314151720ST′ was used as a correction of GST affected by the number of examined populationsAllele frequencies for different restriction sites were calculated using a direct counting method. The Hardy-Weinberg equilibrium, estimation of haplotype frequencies of the β-globin gene cluster, linkage disequilibrium between pairs of loci, pairwise Fst (F-statistics) and the exact test of population differentiation, were evaluated using the population genetics analysis software Arlequin V3.5.229How to cite this article: Sun, H. et al. β-globin gene cluster haplotypes in ethnic minority populations of southwest China. Sci. Rep.7, 42909; doi: 10.1038/srep42909 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Tamarix austromongolica and Tamarix chinensis, to understand the role of the Yellow River and Pleistocene climate in shaping their distribution patterns. The most common chlorotype, chlorotype 1, was found in all populations, and its divergence time could be dated back to 0.19 million years ago (Ma). This dating coincides well with the formation of the modern Yellow River and the timing of Marine Isotope Stages 5e-6 (MIS 5e-6). Bayesian reconstructions along with models of paleodistribution revealed that these two species experienced a demographic expansion in population size during the Quaternary period. Approximate Bayesian computation analyses supported a scenario of expansion approximately from the upper to lower reaches of the Yellow River. Our results provide support for the roles of the Yellow River and the Pleistocene climate in driving demographic expansion of the populations of T. austromongolica and T. chinensis. These findings are useful for understanding the effects of geological events and past climatic fluctuations on species distribution patterns.The geological events and climatic fluctuations during the Pleistocene played important roles in shaping patterns of species distribution. However, few studies have evaluated the patterns of species distribution that were influenced by the Yellow River. The present work analyzed the demography of two endemic tree species that are widely distributed along the Yellow River,  At that time, the Yellow River basin was only composed of some disconnected lakes4. The uplift of the Tibetan Plateau and river erosion, especially during the Gonghe Movement (0.15 Ma) in the late Pleistocene, greatly promoted the connection of these lakes causing the retrogressive erosion of the Yellow River and downcutting of the river valley in Sanmen Gorge5. Consequently, the Yellow River evolved into a long river flowing from west to east6. The river might have acted as an abiotic physical barrier to gene flow8, or it may have geographically facilitated movement and channels of dispersal, which has been observed in Rosa roxburghii9, Rhododendron ripense10 and Terminalia franchetii11, for which frequent gene flow resulted in the genetic homogenization of populations.The uplift of the Qinghai-Tibet Plateau (QTP) dramatically changed the topography of Asia, and the direction of flow of the Yellow River system from west to east is closely tied to this uplift. The Yellow River appeared about 1.7 Ma during phase C of the Qingzang Movement12. This was especially true during the Mid-Pleistocene Transition (MPT), which lasted from approximately 1.25 million to 700 thousand years ago, and was a period during which the total amount of ice in ice sheets increased globally14. The climatic fluctuation in China during the Pleistocene, although not as severe as that in Europe and North America, still occurred during the alternation between glacial and interglacial periods16. In China, loess sequences in central China indicated that major shifts occurred toward cooler and drier climates at about 2.4 Ma, 1.2 Ma, and 0.5 Ma, while less pronounced shifts were dated to 1.65 Ma, 0.8 Ma, and 0.2 Ma18. Furthermore, marine δ18O records also showed similar shifts19. Three ice core records from the Qinghai-Tibet Plateau revealed that late glacial stage conditions were apparently colder, wetter, and dustier than Holocene conditions20. Additionally, lacustrine sporopollen records indicated that wetter conditions progressed from western China to the east during the early Pleistocene21. These climatic changes can influence the distribution of species because the distributions of some species migrated during glacial periods, and the species survived in refugia, after which many species then re-colonized some areas during the postglacial period24; alternatively, other species persisted and adapted to the changed conditions26, while others became extinct27.The Pleistocene was a time during which dramatic climatic and temperature shifts occurredTamarix austromongolica and Tamarix chinensis are endemic tree species in China28; T. austromongolica is naturally distributed in the upper reaches of the Yellow River, from Qinghai to the ravine region between Shanxi and Shaanxi provinces; T. chinensis, however, mainly occurs in the lower reaches of the Yellow River. The most obvious features of these species include drought, saline, and alkaline tolerance; they are also water tolerant. The small, short-lived seeds in particular require a moist surface soil, short-term precipitation, or may drift with water in the early stage of germination29, which is different from other desert shrubs. As two species that are widely distributed along the coast of the entire Yellow River, T. austromongolica and T. chinensis are very closely related species30. Furthermore, Tamarix is an ancient genus occurring in ancient times in the Mediterranean region31. Therefore, these two species can serve as good candidates for investigating the influence of the Yellow River and paleoclimate on patterns of species distribution.Tamarix species. To better understand the distribution of these two species, we evaluated the following: (1) the relationship between the divergence time of chlorotypes and the paleoclimate, formation, and evolution of the Yellow River; (2) the demographic history of two Tamarix species using genetic data and species distribution models.In this study, we sampled 45 populations along the Yellow River to infer the effects of geological events and climate change during the Pleistocene on two Two cpDNA fragments from a total of 382 individuals and nDNA ITS fragments of 45 populations and two out-group individuals were sequenced. The total length of cpDNA sequences was 1640 bp, with 11 chlorotypes identified by nine nucleotide substitution sites and two indels. These 11 chlorotype sequences were submitted to the GenBank database under accession numbers KY621817-KY621842. Chlorotype C10 was unique to population GYJ. The Chlorotype C1 was shared by all of populations, which indicates high migration rates among populations. Interestingly, C2 was found in populations GLZ and SDH, in different species and at different geographical distance between the two populations. The details of chlorotype distribution for each locality are shown in Fig. Based on chlorotypes, we constructed a Median-joining network. One chlorotype (C1) was found in 363 of 382 individuals from the 45 populations and represented the central node of this network; the networks containing clades with characteristic star-like topologies showed that populations that have experienced population expansion. The aligned sequences of ITS in 45 populations were 686 bp; 56 ribotypes see Fig.  were fou−3  indicated that only 0.80% of this variation was observed among is Table , whereasT. austromongolica and T. chinensis at 1.85 Ma (95% HPD = 0.70–3.23), which was observed in the GYJ population in this study, suggesting that plants of the genus Tamarix first reached Gansu when migrating from a secondary differentiation center of Xinjiang. The divergence time of C5  was 1.23 Ma (95% HPD = 0.45–2.13). Chlorotype C1 is the most widely distributed in the Yellow River basin, and its divergence was 0.19 Ma (95% HPD = 0–0.54), which is approximately consistent with the time of MIS 5e-6 and formation of the modern Yellow River, suggesting that climate fluctuations promoted the divergence of chlorotypes of Tamarix.In the time-calibrated chlorotype tree Fig. , all chlT. austromongolica have experienced recent demographic expansion based on cpDNA sequences  of  Ma Fig. , and theons Fig. . The EBSize Fig. ; this chets Fig. .Figure 3Tamarix plants in the lower reaches of the Yellow River came from the upstream giving this scenario more support.Considering the three scenarios tested with cpDNA sequences, DIYABC analysis software indicated that scenario 2 was the best-supported scenario Fig. , with a 2) was obviously larger than that from the last glacial maximum (LGM) prediction  and the last interglacial  predictions; similar patterns were identified for all suitable areas (P > 0.05)  values; AUC values for these curves varied from 0.941 to 0.971. For both species, the most suitable area climatically (0.54 < P < 1) from the current prediction  Fig. . ObviousTamarix species analyzed here; the percentages of their contributions were 26.8%, 16.7% and 16.4%, respectively. This finding showed that wet habitats and temperate zones were probably the main factors that limit the distribution of Tamarix species over time when compared with the effects of other variables.Results from the analysis of variable contributions indicated that three environmental variables, namely, mean temperature of coldest quarter, isothermality, and precipitation of wettest month, were the main climatic factors affecting the current distribution of the two 34. T. austromongolica and T. chinensis are perennial species with strong tolerance and adaptability; these species blossom and bear fruit 2–3 years after germination. Therefore, both species produce numerous seeds in spring, summer, and autumn. Population growth rates are also influenced by the rates of migration; the small seeds of Tamarix species have white hairs on one end that enable long-distance wind or water dispersal35, resulting in rapid increases in populations and dispersal along the entire river if environmental conditions are suitable.The most important factors that shape the distribution and demography of populations are natural increases in population size (the number of births minus the number of deaths), net migration, and environmental factors, such as water supply and climate conditions36, and the divergence time of C5 (1.23 Ma) coincided with the Kunlun-Yellow River Tectonic Movement. Therefore, our data provide biological evidence for the approximate geological age of the Yellow River. Based on the divergence time of chlorotype C1 (0.19 Ma), the demographic histories of T. austromongolica and T. chinensis could be traced back to 0.15 Ma and 0.02 Ma, respectively. As mentioned earlier, the Gonghe Movement started from around 0.15 Ma, which resulted in a substantial uplift of the QTP and promoted the formation of modern Yellow River38; therefore, it appears that the expansion of these two species was closely matched to the formation of the modern Yellow River.The divergence time of C10 in the GYJ population was dated to 1.85 Ma. The paleo-magnetic dating of Liupanshan loess, near the GYJ population, showed the first grade Yellow River terraces reached to 1.8 MaT. chinensis began around 0.02 Ma. T. austromongolica and T. chinensis are morphologically similar, and both species flower from May to October. Previous studies showed that these two species are closely related phylogenetically31; therefore, we speculate perhaps T. chinensis is a species that evolved and diverged from T. austromongolica along the Yellow River, which could explain why the species expanded relatively late. Overall, the valleys of the Yellow River are not only known as cradles of China’s ancient civilization but also provide moist habitat for seed germination and plant growth. Clearly, the Yellow River has been revealed to be the main driving force for demographic expansion of T. austromongolica and T. chinensis.It is not easy to interpret why the expansion of 39, such as mammals40, other vertebrates41, insects42, and plants43; however, the responses of different species to these changes have been diverse and depended on their habitat suitability and environmental requirements44. For example, neotropical savanna tree species experienced the greatest expansion during the LIG and a retraction during the LGM45. Two tropical tree species, Erythrophleum ivorense and E. suaveolens, experienced demographic bottlenecks during the last glacial period46, whereas a temperate tree frog species, Hyla sarda, underwent range expansion mostly during the last glacial phase47.These two species experienced demographic expansion during the late Pleistocene, which was a period of multiple glacial-interglacial cycles and dramatic environmental changes. Numerous studies have suggested that environmental changes associated with the Pleistocene climate  played roles in determining both the origin and distribution of living organismsT. austromongolica and T. chinensis are temperate species endemic to China; although this region was not directly affected by extensive ice sheets, it also experienced severe climatic change throughout the Quaternary. Also, during the LGM, the low thermal conditions in the Eurasian continent produced temperatures that were 4 °C–16 °C lower than today48. These low temperatures affected the distribution and evolution of plants50, such as the temperate tree Pteroceltis tatarinowii51 and the cool-temperate deciduous tree Quercus mongolica52, which retreated southward and then re-colonized the previously northern region post-glacially. Ostryopsis davidiana, which is a temperate deciduous shrub species in northern China, maintained multiple refugia in the northern and southern regions of the Qing Mountains rather than having survived only in the south53.T. austromongolica and T. chinensis experienced demographic expansion during the late Pleistocene. The EBSP analysis and predictions of paleo-distribution models under past climatic conditions consistently suggested that the populations of these two species not only survived but also experienced a period of range expansion. One interpretation of this is that Tamarix is a temperate deciduous species and shows a strong tolerance to cold and drought55, with killing temperatures for T. ramosissima, T. chinensis, and hybrids ranging from −33 °C to −47 °C56; this type of adaptation was probably important during past range expansions of these populations.Unlike previous studies, we found that −3; meanwhile, Hd of the GLZ and NMDK sites were 0.56 and 0.60, respectively, and the populations from the lower reaches seemed to have lower values. Population genetic theory predicts that colonization can result in a decrease in genetic diversity, known as the founder effect, and there is a loss of diversity in newly established populations due to a small number of founders59.Our genetic data showed that the haplotype diversity value for the entire dataset averaged 0.11, while nucleotide diversity averaged 0.057 × 10et al. studied the molecular biogeography of Lactuca serriola. They found that significantly lower genetic diversity characterized the newly colonized parts of the range of this species when compared with historical populations; this confirmed the importance of founder effects60. Similar results have been reported in Geranium carolinianum; genetic diversity patterns across China have revealed that reduced diversity has resulted from successive founder events during range expansion61. However, in contrast, long-distance dispersal maximized the evolutionary potential for invasive European starlings (Sturnus vulgaris) because multiple introductions associated with successful dispersal strategies may lead to relatively high genetic diversity, especially when introductions occurred from different regions62.Various researchers have experimentally investigated the effects of recent colonization events on genetic diversity in both herbs and birds. Recently, D’Andrea 63; low genetic diversity in introduced populations may lower their abilities to adapt and hence increase the risk of extinction in novel environments. Thus, to maintain adaptive potential and minimize the risk of extinction, the founder populations with relatively high levels of genetic diversity need to be conserved.Taken together, different introductions and dispersal strategies contributed different amounts of genetic diversity through the introduction of different numbers of individuals or individuals carrying different amounts of diversity. It is well known that genetic diversity is linked to adaptive potentialT. austromongolica and T. chinensis, responded to climatic fluctuations in the Pleistocene and prehistorical geological events affecting the Yellow River. Based on a wide geographic range of samples and by combining information on cpDNA and nDNA sequences, we dated the divergence time of chlorotypes to the Pleistocene and reconstructed the demographic expansion history of T. austromongolica and T. chinensis throughout the Yellow River valley based on EBSP, a distribution model, and ABC analyses. The results suggested that the populations of these two species experienced a period of range expansion. Additionally, the occurrence of the expansion of these two species was closely matched to the formation of the modern Yellow River.The main goal of the present study was to understand how the two widespread East Asian temperate deciduous tree species, T. austromongolica and 235 individuals in 24 populations of T. chinensis, during September 2015 to September 2016, across eight provinces along the Yellow River. Of these locations, SFY and SWS were located along the Fenhe River, the second largest tributary of the Yellow River. Additionally, in Shandong Province, T. chinensis is common in alkaline and saline soil areas along the coasts of the Bohai Sea; as a result, the sample points here are denser geographically than those of other samples. Moreover, two individuals of Myricaria bracteata and Myricaria paniculata were collected in Gansu and Qinghai, for use as outgroups in the analysis. Samples of fresh leaves were dried using silica gel; the location of each population, including longitude, latitude and elevation, were recorded with a GPS unit. Table A total of 382 individuals were sampled from 45 populations including 147 individuals of 21 populations of TrnL-F64, rps1665 and ITS66 were selected; DNA amplifications were performed in a gradient PCR system  with the following cycling conditions: 95 °C (5 min); 38 cycles of 95 °C (30 s), 56 °C (30 s), 72 °C (1 min 50 s), and then 72 °C (10 min); conditions only differed based on the annealing temperatures (58 °C for rps 16). We carried out PCR amplification in 20 μL reaction volumes for each individual; PCR products were checked on 1.5% agarose gels and purified with the TaKaRa MiniBEST Agarose Gel DNA Extraction Kit ; all PCR products were subsequently sequenced on an ABI 3730 DNA Sequence Analyzer at the Beijing Genomics Institute , sequencing with forward and reverse primers in all individuals. Sequences trnL-F (KJ729796.1) and rps16 (KJ729745.1) of Reaumuria soongarica were downloaded from the US National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/).Total genomic DNA was extracted using a Plant Genomic DNA Extraction Kit  according to the manufacturer’s protocol and stored at −20 °C. 67. Haplotype diversity (Hd) and nucleotide diversity (π) inferred from cpDNA sequences within populations were all done in DnaSP. The genealogical topologies of chlorotypes and ribotypes were constructed using the program Network Version 5.0 with a median-joining model.Sequence contig was done using Seqman with the DNAstar program ; all the variance sites were carefully checked optically in Chromas. For nDNA ITS sequences, if double peaks occurred in the same position and the weakest signal reached 1/3 of the strongest signal, we considered the site to be heterozygous, and inferred their phases using the PHASE algorithm in DnaSP 5.1068 and Arlequin ver3.569; the significance of AMOVA was tested based on 1000 permutations.To determine whether the populations were structured, genetic differentiation among and within populations was calculated using STRUCTURE 2.3.4Tamarix, Kräusel70 believed that Tamarix records in Egypt were from the Lower Oligocene. Researchers in China72 found Tamarix fossils from Gansu Province dated to the Oligocene Baiyanghe Fm and Huoshaogou Fm; all these showed the Tamarix plant appeared before the Oligocene. Tamaricaceae and Frankeniaceae formed the closest sister clade with this node dated to 43–30 Ma73; Zhang et al. estimated an age of about 70 Ma in the light of woody families origin74. Tank et al. suggested an age for this clade of 49.7 Ma75 and ca 53.8 Ma in Magallón et al.76. Ultimately, 53.8 Ma was chosen cautiously as the family root for our molecular dating.Regarding the fossil record of 77; the best fit nucleotide substitution model (GTR+G) was selected with Modeltest Version 3.778 in conjunction with PAUP* Version 4.0b1079, Model selection was conducted based on Bayesian Information Criterion. Relaxed clock log-normal was implemented and the mutation rate of 0.9 × 10−9 substitutions per site per year for cpDNA noncoding regions was used to calibrate the tree80. We ran the Markov chain Monte Carlo (MCMC) chain for 10 million generations, with a sampling every 1,000 generations. We used Tracer software to visualize and check for convergence to a stationary distribution and for high effective sampling size values (ESSs > 200); the first 10% of trees were discarded as burn-in in TreeAnnotator Version 2.3.2, and the resulting trees were drawn in FigTree Version 1.4.2.To relate genetic differentiation found among chlorotypes to Pleistocene events, the divergence time was estimated using BEAST Version 2.3.281 with parametric bootstrapping (1000 replicates) to estimate population expansion.We used Tajima’s D and Fu’s Fs to infer historical demographic processes. We also conducted mismatch distribution analyses based on both SSDs and the Raggedness indexTamarix with the EBSPs82 in BEAST 2.3.2. We applied a general time-reversible substitution model and strict clock rate 0.9×10−9substitutions per site per year; the weights for EBSP operators and the initial value were adjusted to improve MCMC mixing. We used a scale factor of 0.5 for cpDNA because only the female cpDNA contributes to the effective population size, and then the MCMC chain was run for 10,000,000 iterations.To investigate the potentially relatively complex effects of population size dynamics, we retraced the demographic history of Tamarix along the Yellow River, further analysis of the evolutionary paths of T. austromongolica and T. chinensis was inferred from an ABC using DIYABC software Version 2.1.083. Two groups were defined based on T. austromongolica and T. chinensis species, and three evolutionary scenarios were developed and tested: (a) scenario 1, in which T. austromongolica and T. chinensis of size N1 and N2 have diverged t generations in the past from an ancestral population of size N1 + N2; (b) scenario 2, in which T. austromongolica derived from ancestral population at t2, T. chinensis derived from T. austromongolica at t1; (c) scenario 3, in which T. chinensis derived from ancestral population at t2, T. austromongolica derived from T. chinensi at t1. We generated 3, 000 000 simulated datasets per scenario and chose uniform prior distributions for effective population sizes. To confirm the validity of using ABC to analyze our data, a posterior probability of scenario was assessed and finally obtained the best-supported scenario for comparison.To identify source populations and the colonization patterns of T. austromongolica and T. chinensis in the past climate based on habitat suitability, ecological niche modeling was conducted with the Maximum Entropy algorithm 84. Except for our 45 sampling sites, 15 reliable distribution sites were selected for prediction from the National Specimen Information Infrastructure . The latitude and longitude of each T. austromongolica and T. chinensis collection site in MaxEnt are given in Supplementary Table www.worldclim.org); these 19 variables included temperature and precipitation and together are considered particularly pertinent to species distributions. The random test percentage was set to 25%, and the maximum number of iterations was set to 1000. To assess the quality of the generated distribution models, a value representing the AUC was performed.To predict the area of distribution for supplementary material


The results of population genetic study manifested that Uyghur had close relationships with those contiguous populations, such as Xibe and Hui groups. In a word, these autosomal short tandem repeat loci were highly informative in Uyghur group and the multiplex PCR system could be used as a valuable tool for forensic caseworks and population genetic analysis.We investigated the allelic frequencies and forensic descriptive parameters of 23 autosomal short tandem repeat loci in a randomly selected sample of 1218 unrelated healthy Uyghur individuals residing in the Xinjiang Uyghur Autonomous Region, northwest China. A total of 281 alleles at these loci were identified and their corresponding allelic frequencies ranged from 0.0004 to 0.5390. The combined match probability and combined probability of exclusion of all loci were 5.192 × 10 The Uyghur ethnic group, the fourth largest ethnic minority of China, primarily lives in northwest China’s Xinjiang Uyghur Autonomous Region. Previous population genetic studies –3 indicaShort tandem repeats (STRs) have been publicly recognized as vital genetic markers in forensic sciences. In order to achieve better performances in forensic applications, especially in some mutation events of parentage testing, we need more genetic markers with high polymorphisms. Meantime, we should obtain population genetic data of these markers as much as possible before putting them into actual forensic cases. In this study, we investigated the allelic frequencies and forensic descriptive parameters of autosomal multi STR loci in Uyghur group using HuaXia Platinum PCR Amplification system, which included 23 autosomal STR loci and two sex associated markers (Y-chromosome insertion and deletion and Amelogenin). Furthermore, we evaluated genetic relationships between studied Uyghur group and other reference populations –17 from p = 0.05/23≈0.0022); only D3S1358 violated Hardy-Weinberg equilibrium. The match of probability (MP) ranged from 0.0123 at Penta E locus to 0.2003 at TPOX locus with the average of 0.0692. The probability of exclusion (PE) ranged from 0.2862 at TPOX locus to 0.8102 at Penta E locus with the average of 0.5969. The mean values of discrimination power (DP), polymorphic information content (PIC), observed heterozygosity (Ho) and expected heterozygosity (He) were 0.9380, 0.7776, 0.7957 and 0.8048, respectively; and the highest values of DP, PIC, Ho and He were also found at Penta E locus, the least observed at TPOX locus. The combined match probability (CMP) and combined probability of exclusion (CPE) of 23 STR loci were 5.192×10-29 and 0.9999999996594, respectively.The results of allelic frequencies and forensic descriptive parameters for 23 STR loci were presented in Table p-value) were obtained with the method of analysis of molecular variance (AMOVA). After applying Bonferroni correction to multiple tests (p = 0.05/238≈0.00021), the least differentiations were found between Uyghur group and Uyghur1, Hui and Xibe groups at the same 14 loci, with significant differences at 0, 1 and 3 loci, respectively. By contrast, more significant differences were observed between Uyghur group and African American and Caucasian populations, with significant differences at 13 loci. Among all the compared loci, the most population diversity locus was found at TH01 with significant difference between Uyghur and 16 reference populations, the least found at TPOX with only 2 reference populations.As shown in Table Fst) genetic distances between Uyghur group and other 17 reference populations were generated by the Genepop v4.0.10 [The pairwise fixation index  using the ‘R’ package (http://www.r-tutor.com/category/r-packages). The similar population distributions were observed in the MDS plot: Chinese populations and Asian population were located in the right part; Mexican and African American were located in the left part; Spanish, Caucasian, Portuguese and Hispanics were located in the middle of the plot.A principal component analysis (PCA) plot was drawn using allelic frequencies of 14 shared loci of Uyghur group and 17 previously published populations by MVSP v3.1 software . As demoBy using neighbor-joining method, two phylogenic trees were constructed by the software PHYLIP v3.6 Figure  and MEGA–29 and 0.9999999996594, respectively, which indicated the panel could be a robust and valid tool for individual identification and parentage testing in forensic caseworks.HWE announces that a large random-mating population without selecting, mutating or migrating is thought to be in HWE. For populations in HWE, allelic frequencies and genotype frequencies usually remain constant from generation to generation –21. SincIf the loci with significant differences in allelic frequencies between pairwise populations are too many, it means that their genetic relationships are long distance and vice versa. Comparisons of genetic differentiations between Uyghur group and other reference populations based on 14 overlapping STR loci indicated the Uyghur had closer genetic relationships with some Chinese populations than those from different continents. By investigating inter-population differentiations based on allelic frequencies using AMOVA method, the two Uyghur groups showed no significant differences at these loci, and the significant differences were found between the studied Uyghur and Hui group at only TH01 locus; Xibe group at CSF1PO, TH01, D13S317 loci, revealing the short distances between Uyghur and Hui, Xibe groups. Deng  et al. rFst is a measure of genetic differentiation between compared populations which is used frequently in population genetics. The pairwise populations whose Fst is small usually show similar allelic frequency distributions; on the contrary, they show greatly different. In this study, the relative small Fst values were observed between Uyghur group with its adjacent populations such as Hui and Xibe groups, which indicated they had tight genetic relationships.Fst values, respectively. The results of PCA and MDS analysis indicated that the populations with closer geographical distances had more intimate relationships. Besides, results obtained once again showed that Uyghur is a Eurasian population. In order to further evaluate genetic relationships among these populations, we constructed two phylogenic trees. The results obtained from phylogenic trees were basically in agreement with above genetic relationship analysis. In addition, previous studies also reported the similar results as following. Shen et al. constructed a phylogenic tree between Uyghur group and other reported populations based on allelic frequencies of HLA-B locus, revealing that Uyghur group had close genetic relationships with the Xibe and Hui groups [Rst at 17 Y-STR loci [The genetic relationships between Uyghur group and 17 reference populations were revealed by the PCA and MDS figures based on allelic frequencies of the same 14 STR and population pairwise i groups . A dendri groups . Bian etSTR loci . The cloSTR loci  indicateWe gathered blood samples from 1218 unrelated healthy individuals of Uyghur ethnic minority in northwest China’s Xinjiang Uyghur Autonomous Region after receiving their written informed consents. Each individual whose family has been living in the region for at least three generations didn’t intermarriage with other ethnic groups. All experiment procedures were in agreement with the ethical committee of Xi'an Jiaotong University Health Science Center, China. Under the instructions of Walsh et al, we obtained genomic DNA of each sample with the Chelex-100 method .®-600 LIZ® Size Standard v2.0. The loading mixture was first denatured at 95°C for 3 min, followed by cooling at 4°C for 3 min immediately. The results of STRs typing were identified by the GeneMapper ID 3.2 software . Deionized water and control DNA from human cell line 9948 were typed as negative and positive control, respectively.All loci were co-amplified using HuaXia Platinum PCR Amplification kit in GeneAmp 9700 PCR system  under the producer’s specification. Thermal cycler conditions were as described below: pre-denaturation at 95°C for 1 min, followed by 27 cycles of 94°C for 3 s, 59°C for 16 s, 65°C for 29 s, and a final extension for 5 min at 60°C. The whole PCR reaction could be finished in 1 hour. Separation of amplified products was performed by capillary electrophoresis on the ABI 3130xl Genetic Analyzer  following the instructions in 11 µl reactions which consist of 1 µl PCR product or allelic ladder and the mixture of 9.6 µl Hi-Di Formamide and 0.4 µl GeneScanhttp://cmpg.unibe.ch/software/arlequin3). On the basis of 14 overlapping STR loci, Fst values of pairwise populations were calculated with the Genepop v4.0.10. A PCA of eighteen populations was plotted by MVSP v3.1 software which could perform a variety of ordination and cluster analyses. A MDS plot was illustrated based on Fst values via the ‘R’ packages. Two phylogenic trees were constructed based on the allelic frequencies of the same 14 STRs by PHYLIP v3.6 software and DA distances (obtained from the DISPAN program) by MEGA v5 software, respectively.We calculated allelic frequencies, MP, PE, DP, and PIC using the corrected PowerStats v1.2 . We eval