TTX) toxicity of the Rough‐Skinned Newt (Taricha granulosa) in regions of allopatry with its TTX‐resistant predator, the Common Garter Snake . In sympatry, geographic patterns of phenotypic exaggeration in toxicity and toxin‐resistance are closely correlated in prey and predator, implying that reciprocal selection drives phenotypic variation in coevolutionary traits. Therefore, in allopatry with TTX‐resistant predators, we expect to find uniformly low levels of newt toxicity. We characterized TTX toxicity in northwestern North America, including the Alaskan panhandle where Ta. granulosa occur in allopatry with Th. sirtalis. First, we used microsatellite markers to estimate population genetic structure and determine if any phenotypic variation in toxicity might be explained by historical divergence. We found northern populations of Ta. granulosa generally lacked population structure in a pattern consistent with northern range expansion after the Pleistocene. Next, we chose a cluster of sites in Alaska, which uniformly lacked genetic divergence, to test for phenotypic divergence in toxicity. As predicted, overall levels of newt toxicity were low; however, we also detected unexpected among‐ and within‐population variation in toxicity. Most notably, a small number of individuals contained large doses of TTX that rival means of toxic populations in sympatry with Th. sirtalis. Phenotypic variation in toxicity, despite limited neutral genetic divergence, suggests that factors other than reciprocal selection with Th. sirtalis likely contribute to geographic patterns of toxicity in Ta. granulosa.Species interactions, and their fitness consequences, vary across the geographic range of a coevolutionary relationship. This spatial heterogeneity in reciprocal selection is predicted to generate a geographic mosaic of local adaptation, wherein coevolutionary traits are phenotypically variable from one location to the next. Under this framework, allopatric populations should lack variation in coevolutionary traits due to the absence of reciprocal selection. We examine phenotypic variation in tetrodotoxin ( Coevolution occurs across a heterogeneous landscape of reciprocal selection, where species interactions and their fitness consequences vary from one location to the next Thompson . ReciproTaricha granulosa) in allopatry with its toxin‐resistant predator, the Common Garter Snake , to test the hypothesis that phenotypic variation in a coevolutionary trait is limited in the absence of reciprocal selection with a natural enemy. Taricha granulosa and other congeners possess tetrodotoxin (TTX), a lethal neurotoxin that deters most predators. However, multiple species of garter snake, including Th. sirtalis, independently evolved resistance to the toxin , factors other than reciprocal selection with Th. sirtalis likely contribute to variation in toxicity.We expect selection in the absence of a TTX‐resistant predator to favor reduced toxicity, particularly if TTX production comes at a physiological cost or trade‐off, as is predicted for increasing trait values in arms races Vermeij . AlternaTaricha granulosa were sampled in April and May of 2004. We sampled from ponds in Bella Coola, British Columbia  and on coastal islands of the Alaskan panhandle, including Revillagigedo, Wrangell, Mitkoff, and Prince of Wales islands  to collect a 5 mm diameter dorsal skin punch for the TTX assay. In addition to the northern samples, we also collected genetic data from from a population of Ta. granulosa at Ledson Marsh in Sonoma County, California. These samples were used in the analysis of geographic population structure to provide a comparison of genetic variation with a population located in the southern portion of the range of Ta. granulosa , expected heterozygosity (HE), and number of alleles (NA) in ARLEQUIN 3.5.1.3 . A total of six microsatellite loci – Tgr01, Tgr02, Tgr04, Tgr06, Tgr10, and Tgr14 – were amplified by adapting protocols from Jones et al. . Microsaion Holm . Next, wFST values between sampling sites. Statistical significance was obtained by permuting the samples 1000 times, and P‐values were adjusted with a sequential‐Bonferroni correction. We chose to use FST, as opposed to RST because it tends to produce more accurate estimates of genetic subdivision when population structure is weak (as expected in Alaskan populations) and when the sample sizes and number of loci are limited  by sampling location and (2) by the presence/absence of detectable TTX. We used the R package “adegenet” to test for the presence of isolation by distance (IBD) by plotting pairwise FST/(1 ‐ FST) against the logarithm of pairwise geographic distance , implemented in STRUCTURE v. 2.3.4 . STRUCTURE HARVESTER  of the 10 runs for each value of the most probable K (K = 2) were averaged using CLUMPP v. 1.1.2 . We then estimated dorsal skin concentration of TTX (mg/cm2 of skin), along with whole animal toxicity (mg) based on each individual's total skin area. TTX is uniformly distributed throughout the dorsal skin and dorsal levels of TTX are strongly predictive of toxicity in other skin regions  and the proportion of detectably toxic newts. We then used Mantel tests and Redundancy Analysis (RDA) to test for correlations between phenotypic divergence, neutral genetic divergence, and geographic distance, and then used permutation‐based methods to assess significance.To test for among‐site differences in TTX toxicity, we used a nonparametric Kruskal‐Wallis test. We also used a multiple logistic regression to test for among‐site differences in the proportion of newts with any detectable TTX . We included sex in the model to account for potential differences in toxicity among males and females ; however, FST was lower when British Columbia was excluded from the analysis . Even when Alaskan individuals were grouped by island (rather than by sampling location), FST was still low . Alternatively, when Alaska individuals were grouped according to their presence/absence of detectable TTX, we found a nonsignificant FST value . The test for IBD revealed a significant positive correlation between genetic differentiation and geographic distance , but this relationship disappeared when Bella Coola was removed from the analysis .Measures of population differentiation generally revealed low levels of genetic subdivision among northern sites, particularly within Alaska. Nearly all the pairwise ro Table . Almost K) and LnPr(X|K) supported a value of K = 2. All Alaska individuals showed a high membership probability to one cluster, while British Columbia individuals predominantly grouped into another. To avoid overlooking fine scale population structure in Alaskan sites, we also ran a STRUCTURE analysis excluding individuals from British Columbia. The LnPr(X|K) values indicated K = 1 as the most likely number of clusters and the bar plot of K = 2 (not shown) identified all individuals across all populations as roughly equally admixed, indicating a lack of population structure.The STRUCTURE analysis revealed a similar pattern of population structure Fig. . Both thχ2 = 44.62, P < 0.001, df = 7) and whole animal toxicity . The logistic regression also revealed a significant effect of collection site on the proportion of newts with detectable TTX . Sex and the sex*population interaction were not significant predictors in the model. We found large differences in the proportion of toxic newts across short geographic distances in Alaska, for example, the Pat's Lake site was devoid of newts with detectable levels of TTX, but only 15 km away at the Highbush site (on the same island), 94.7% of newts possessed detectable levels of TTX, with a mean toxicity of 0.2554 mg , but not in the RDA. This pattern likely reflects the fact that the proportion of toxic newts at a given site can change drastically over short geographic distances.The Mantel tests and RDA produced similar results, so here we only report Mantel test results Table . We did Ta. granulosa generally lacked geographic population structure, particularly in Alaska. As predicted, overall population levels of newt toxicity were low outside the geographic range of TTX‐resistant predators. However, we found unexpected among‐ and within‐site variance in toxicity, which suggests that natural selection by resistant predators does not fully explain phenotypic variation in toxicity. First, we assess biogeographic structure in northern populations as context for interpreting geographic patterns of newt toxicity.Northern populations of Ta. granulosa in British Columbia and Alaska had reduced levels of genetic diversity. Estimates of pairwise FST, the AMOVA, and the STRUCTURE analysis all suggest an overall lack of population structure in northern populations, particularly within Alaska. Jones et al.  also has been proposed as a northern refugium for flora and fauna during the height of Pleistocene glaciation , a monophyletic group that includes Ta. granulosa , a stoat (Mustela erminea), a muskrat (Ondatra zibethicus), and a bobcat (Lynx rufus)  in Oregon are capable of preying on the eggs of Ta. granulosa, and appear to harbor some degree of resistance to TTX  Brodie . Adult nTa. granulosa in allopatry with Th. sirtalis suggests that factors other than the coevolutionary interaction with resistant predators contribute to geographic patterns of phenotypic variation in toxicity. External factors, such as abiotic conditions, may affect the ability of newts to sequester or synthesize TTX. For example, marine taxa are generally thought to obtain TTX through the food chain or a bacterial symbiont, and high individual and regional variation in toxicity has been cited as evidence of an exogenous source of TTX in puffer fish  and the red‐spotted newt  appeared to result in a loss of toxicity (Yotsu‐Yamashita et al. The variance in toxicity of Ta. granulosa has some heritable genetic component that is susceptible to drift because southern populations have apparently evolved extreme toxicity in response to escalatory reciprocal selection with Th. sirtalis (Hanifin et al. Variation in toxicity in Alaska could also result from increased variance in TTX synthesis genes and genetic drift in the absence of selection for exaggerated toxicity. This alternative may be less likely, given the lack of neutral genetic variation and subdivision in Alaskan sites. The incongruence between phenotypic variation and the lack of neutral microsatellite variation suggests that among‐site variance in toxicity is not solely due to neutral drift. Admittedly, we cannot rule out the importance of genetic drift because the genetic basis of TTX synethesis is unknown. Presumably TTX toxicity in Ta. granulosa in allopatry with TTX‐resistant predators. However, we also found evidence for among‐ and within‐population variation in toxicity, a pattern that appears to be inconsistent with neutral genetic population structure. The limited number of samples and microsatellite markers in this study may restrict our power to detect microgeographic population structure in Alaska, thus our results should be interpreted with caution. Nevertheless, estimates of FST, tests for IBD, and the STRUCTURE analysis all suggest an overall pattern of limited population stucture among the geographic cluster of sites in Alaska, which decreases the likelihood that our population comparisons of TTX toxicity are confounded by deep phylogenetic divergence.As predicted, levels of toxicity were generally low in populations of Ta. granulosa in allopatry with Th. sirtalis represents a critical step in inferrering how exogenous forces might influence coevolution in sympatry. These data emphasize that reciprocal selection is likely not the sole determinant of geographic patterns of toxicity in Ta. granulosa. Focusing only on phenotypic variation in sympatric populations would otherwise lead to a myopic interpretation of coevolutionary dynamics. The coevolutionary process occurs across space and time, which inevitability span variable ecologial and abiotic conditions. Factors unrelated to the interaction, like environmental conditions (Johnson et al. Characterizing toxicity of None declared.


Schistosoma mansoni and urinary schistosomiasis caused by Schistosoma haematobium are endemic in Ethiopia. Although schistosomes look morphologically uniform, there is variation in infectivity, egg productivity and virulence due to variation in their genetic make. Knowing the genetic diversity and population structure of S. mansoni isolates will enable to understand and consider the possible variability in terms of infectivity, egg productivity and virulence.Human intestinal schistosomiasis caused by Schistosoma mansoni isolates from four endemic areas of Ethiopia was assessed using previously published 11 polymorphic microsatellite loci. Miracidia were hatched from eggs of S. mansoni collected from stools of human subjects residing in Kemissie, Wondo Genet, Ziway and Sille-Elgo villages. DNA was extracted from single miracidium and PCR was run following standard protocol. Allelic polymorphism and population genetic structure was analyzed using different software.Between 2010 and 2011, genetic diversity and population structure of FST values ranged from 8.5 to 11.5, 3.46–20.8, 0.66–0.73 and 3.57–13.63 %, respectively. All analyzes on population genetic structure reveals strong genetic structuration corresponding to the four sampled villages. At infrapopulation level (i.e. different hosts) the mean number of alleles per locus, allelic richness, expected heterozygosity in Hardy–Weinberg equilibrium and FIS values ranged from 3.09 to 7.55, 1–1.96, 0.59–0.73 and 0.1763–0.4989, respectively. Mean estimated genetically unique adult worm pairs within hosts ranged from 66 to 92 % revealing the occurrence of infection of a single host with genetically unique multiple S. mansoni strains. The data also indicated the occurrence of genetic variation within inter- and intra-hosts.At a population level (i.e. different villages), the mean number of alleles per locus, allelic richness, expected heterozygosity in Hardy–Weinberg equilibrium and pairwise S. mansoni isolates of Ethiopia. These results are quite different from previous studies demonstrating that it is difficult to generalize schistosome transmission patterns because epidemiological situation tends to vary. These are important factors to be considered in relation with morbidity, drug resistance or vaccine development.High level of genetic diversity and significant population differentiation characterized the  Schistosoma mansoni is endemic in Ethiopia. Varying in distribution and magnitude of disease burden, S. mansoni is widely distributed throughout the country and hence is a major public health problem [Human intestinal schistosomiasis caused by  problem –3.S. mansoni, a snail of the genus Biomphalaria. Once it has penetrated the snail, the miracidium transforms into a mother sporocyst which produces multiple daughter sporocysts through asexual reproduction. These in turn produce cercariae which are released into water and are infective to human hosts, thus completing the life cycle.Schistosomes reproduce sexually reproduction in their definitive hosts  and this type of reproduction allows for reassortment and the perpetuation of parasite genotypic diversity. The eggs laid by the adult female worms pass in the host’s faeces and each will hatch in water to release a miracidium. These free-swimming larvae must find and penetrate an appropriate freshwater snail, in the case of S. mansoni is considered morphologically uniform, it is known that strains from the same or different geographical locations have shown differences in egg production, infectivity, pathogenicity and susceptibility to chemotherapy [S. mansoni parasites [S. mansoni in northern Senegal using nine microsatellite markers revealed a random distribution (panmixia) of parasite genetic variation among villages and hosts, confirming the concept of human hosts as ‘genetic mixing bowls’ for schistosomes [Schistosoma parasites, and establish whether movement of humans from refugia or non-treated areas introduces new parasites into local populations [Schistosoma mansoni (two published and six unpublished) microsatellite datasets collected from individual schistosome-infected school-children showed that S. mansoni populations were more diverse in East than West African schools, but heterozygosity levels did not vary significantly with geography [Schistosoma mansoni and Schistosoma haematobium populations from different countries in sub-Saharan Africa, indicative of isolation by distance [S. mansoni so far. Our previous epidemiological survey performed on three villages from northern, central and southern Ethiopia shows considerable variation in terms of prevalence and intensities of infections [Schistosoma mansoni infection among the study participants in Kemissie, Wondo Genet and Sille-Elgo was 89.6, 59.9, and 31.6 %, respectively. The highest and geometric mean of egg per gram of stool for Kemissie, Wondo Genet and Sille-Elgo was, 5208 and 346, 8472 and 252, 3960 and 91, respectively [S. mansoni observed across these villages, in this present study it was hypothesised that there will be substantial difference in genetic diversity between isolates of Ethiopian S. mansoni populations.Although otherapy . These carasites . Study ostosomes . Though stosomes –8. Thus stosomes . Moreoveulations , 11. A meography . Geneticdistance . In othedistance . AlthougSchistosoma mansoni endemic areas namely: Wondo Genet about 261Km south of Addis Ababa, located at 07°05′35″N, 038°36′66″E at an altitude of 1755 m above sea level, Ziway about 164Km away from the capital Addis Ababa, located at 07°56′37″N, 038°43′25″E at an altitude of 1642 m above sea level, Sille-Elgo about 525Km away southwest of Addis Ababa located at about 05°28′39″N, 037°26′02″E at an altitude of 1188 m above sea level, and Kemissie about 305 km northeast of Addis Ababa located at 10°43′30″N, 039°04′20″E at an altitude of 1450 m above sea level. Work permission was obtained from local administrative officers, health offices and school principals.The study was conducted in four geographically distant Schistosoma mansoni infection. Among those found with high intensity of Schistosoma mansoni infection, stool specimens were collected for the second time to harvest egg and hatch miracidia. Each single miracidium was used to determine genetic diversity and population structure of Schistosoma mansoni isolates from the four endemic study areas.From 2010 to 2011 a cross sectional parasitological study was conducted in the four study areas in order to determine the prevalence and intensity of Schistosoma mansoni eggs. Stool specimens were collected from 16 S. mansoni positive subjects in Sille-Elgo, 30 subjects in Wondo Genet, 30 subjects in Kemissie and15 subjects from Ziway, totaling 91. The stool specimens were kept in 0.85 % saline in vial and transported in ice box to the Medical Parasitology Laboratory of Aklilu Lemma Institute of Pathobiology, Addis Ababa University, to harvest miracidia.Small plastic sheets were distributed to voluntary study participants and sizable stool specimens were collected and examined using Kato-Katz method (41.7 mg template) . InfectiIn order to stimulate hatching of miracidia, stool samples were homogenized with saline and sieved through tiered sieve of 425, 180 and 140 μm mesh size and kept for about 20 min in dark in order to allow the eggs to settle in the bottom of the flask. The supernatant was poured and the eggs were put in 250 ml flask filled with aged water. The flasks were exposed to artificial light in order to initiate hatching. The flasks were covered with black carbon paper and aluminum foil. This induces the positive phototropic and negative geotropic characteristics of the miracidia which results in their accumulation on the top of the flask [Schistosoma mansoni miracidia was done following Beltran et al. [DNA extraction from n et al.  protocolSchistosoma mansoni population structure of the Ethiopian isolates. To maximize efficiency and minimize cost, these PCRs were performed in three multiplexes [P value to 0.000227 and there was no linkage disequilibrium detected.Previously published 11 polymorphic microsatellite markers, namely SMDA28, SMC1, SMDO11 and AF325698 , R95529,tiplexes . The PCRtiplexes . All locIn this study, miracidia from all the patients within a single study site were treated as a population while all miracidia in a single host are treated as infrapopulation.FIS (inbreeding coefficient) for each population and pairwise FST  were also calculated following the method of Weir and Cockerham [FIS and FST values from zero was tested using a permutation test. All F statistics were carried out using FSTAT 2.9.3.2 [t-test is used to compare two sample means where there is a one-to-one correspondence (or pairing) between the samples while Friedman’s test was used for ordinal data or an interval-scale variable that is not normally distributed [The allele frequencies were calculated using the program MICROSATELLITE TOOLKIT (software available upon request). Both the expected and observed heterozygosities were also calculated using MICROSATELLITE TOOLKIT and their statistical significance tested using the chi-square test at α̍ =0.05. FSTAT was used to test for deviations from Hardy-Weinberg equilibrium using exact tests, testing the hypothesis that observed diploid genotypes are the product of random union of gametes. An exact test for linkage disequilibrium between pairs of loci was performed using the FSTAT. Mean estimates of ockerham . Deviati 2.9.3.2 . Isolatitributed . Genetictributed  and bayetributed . Full-sitributed .S. mansoni were treated with Praziquantel at a dose of 40 mg/Kg body weight.The study was ethically approved by the Institutional Research and Ethics Committee of the Department of Microbial, Cellular and Molecular biology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia and by the National Research Ethics Review Committee of Federal Republic of Ethiopia Ministry of Science and Technology, P.O. Box 2490, Addis Ababa, Ethiopia. Informed verbal consent was obtained from all adults. For school age children younger than 18, informed verbal consent was obtained from their parents through health extension workers and school principals. In addition, the children also gave their assent. All study participants found positive for Schistosoma mansoni positive individuals  a total of 288 were successfully genotyped for 11 loci and analyzed at population level.Out of the 379 miracidia collected from 41 χ2 = 10.941 at 3DF; P = 0.012).One hundred sixty four alleles were scored in all of the four populations for all of the 11 loci examined. There was no null allele detected. Individually a total of 127, 123, 102 and 94 alleles for all of the 11 loci were counted for Kemissie, Wondo Genet, Sille-Elgo and Ziway, respectively. The number of alleles scored for each locus ranged from 4 to 22 (SMC1-SMDO11) with a mean value of 8.5 in Ziway; from 3 to 25 (SMD28-SMDO11) with a mean value of 11.5 in Kemissie; 4–22 (SMC1-SMDO11) with a mean value of 11.2 in Wondo Genet and, 3–23 (SMD28-SMDO11) with a mean value of 9.3 in Sille-Elgo for the 11 loci. The number of alleles in all of the four populations ranged from 8 to 34 (SMD28-SMDO11) with a mean value of 14.9 . However, Wilcoxon rank test indicated that Sille-Elgo had the lowest allelic richness with significant deference from both Kemissie and Wondo Genet (P < 0.05).Allelic richness was calculated based on minimum sample size of 29 diploid individuals , 43DF, P = 0.000) .Paired ity  to 13.63 % (between Ziway and Kemissie) .The Schistosoma mansoni isolates in this study was determined by both Principal Component Analyses (PCA) using Genetix software [Spatial genetic structuration or distribution of software  and Bayesoftware . The firTwenty four infrapopulations were analyzed for the number of alleles counted. The scored number of alleles in individual study subjects which were represented by five or more miracidia also had shown variation Table . The numSchistosoma mansoni isolates at individual host level ranged from 1 to 1.96 for each locus .Allelic richness of us Table . For allt-test showed statistically significance deviations between the observed and expected heterozygosity (t(18.091), 23DF, P = 0.000). At the infrapopulation level all the FIS are positive. Fourteen on 24 values are significantly different from zero.For the 24 infrapopulations a total of 247 miracidia were analyzed at 11 loci level for their heterozygosity Table . It was Colony analysis in Kemissie revealed an estimated total of 37 genetically unique adult worm pairs, representing 88 % of the pairs Table . Twenty S. mansoni genetic polymorphism was observed as evidenced by a large number of alleles detected in each population and infrapopulation. Variation in the number of alleles counted from a single host at the 11 loci level suggests that the degree of heterozygosity is highly variable among the study subjects. In a Kenyan study a relatively higher value, compared to the current study, was reported [S. mansoni isolates can also be attributed to coinfections by multiple genotypes from genetically different cercariae. Schistosome genetic diversity within molluscan host populations has been characterized in previous studies [In the current study high level of reported . In a coreported  reported studies . These pS. mansoni isolates of Sille-Elgo compared to the others. Similar finding was reported in a Kenyan study [The large geographical distance separating the four study sites is likely to limit contacts between populations, thus promoting schistosome population differentiation among them. Allelic richness scored was higher for Kemissie followed by Wondo Genet, Ziway and Sille-Elgo. The nonparametric Friedman test showed that there is no significant difference in allelic richness among the four populations. However, Wilcoxon rank test indicated that Sille-Elgo had the lowest allelic richness, showing low genetic variation of an study . It is ian study . HoweverFIS value for all loci in the four populations is significantly greater than zero, indicating heterozygote deficiency. However, Sille-Elgo and Ziway had less than zero value at the SMDA28 and SMBR10 loci, respectively, indicating heterozygote excess. A study in Brazil reported a bit similar result to our finding [Fis values has been measured, in both population (i.e. village) and infrapopulation (i.e. human) levels [Fis values at infrapopulation level may be a consequence of sib transmission (i.e. person visiting the same transmission site frequently). This sib transmission is particularly true for children compared to adults [Fis values we observed. In context of strong sib transmission a significant genetic structure would be expected as we have observed in our study. In Van den Broeck et al. [In the current study there was statistically significant difference between the expected and observed heterozygosities showing significant departure from Hardy–Weinberg equilibrium. The  finding  showed n) levels . The auto adults . Becausek et al.  study thFst calculation, PCA or Bayesian approach) show a clear and significant genetic differentiation, supporting distinctions among the four populations, thus implying that there is restricted gene flow among the schistosomes under study [S. mansoni population [S. mansoni population was not associated with isolation by distance. Guadeloupe island [S. mansoni population was not associated with isolation by distance which in agreement with our finding. As described by Agola et al. [All the methods we used in this study  and for the larval stages within the intermediate host  both collected at the same transmission site was conducted by Theron and colleagues [S. mansoni strains is in favor of the current finding where multiplicity of infection occurred in human hosts based on sibship determination. Colony analysis in Kemissie revealed an estimated total of 37 genetically unique adult worm pairs, with a mean of 88 % and 26 shared worm pairs among eight individuals. Similarly, there were an estimated total of 36 genetically unique adult worm pairs, with a mean of 73 %, and 19 worm pairs shared among the four individuals in Sille-Elgo. In Wondo Genet there were an estimated total of 32 genetically unique adult worm pairs, with a mean of 92 %, and 15 worm pairs shared among the nine individuals. In Ziway, a total of 24 genetically unique adult worm pairs with a mean of 66 % were observed and there were 4 worm pairs shared among the three individuals. This result showed high levels of infection of single host with genetically different multiple strains of S. mansoni isolates.The estimation of genetically unique adult worm pairs within a single host proves the occurrence of infections with genetically different lleagues . The resBiomphalaria and Bulinus), including Ethiopia could be the source of high genetic differentiation and structuration. Therefore, further investigation of S. mansoni isolates in different localities and also its interaction with host snails is recommended to determine the phylogeography of S. mansoni isolates of Ethiopia. The human behavior effect in S. mansoni population structuration and if there are other reservoir hosts that can have effect on the S. mansoni population structure should be investigated.The study revealed that the schistosome isolates from the four study sites in Ethiopia have highly polymorphic allele counts and are genetically structured. These results are quite different from previous studies demonstrating that it is difficult to generalize schistosome transmission patterns because epidemiological situation tends to vary. These are important factors to be considered in relation with morbidity, drug resistance or vaccine development. The presence of a rich snail fauna in East Africa (about half a dozen species of


Aedes fluviatilis is a neotropical mosquito species thought to be a potential vector of Yellow Fever viruses and can be infected with Plasmodium gallinaceum in laboratory. A better understanding of its genetic structure is very important to understand its epidemiologic potential and how it is responding to urbanization. The objective of this study was to survey the transferability of microsatellites loci developed for other Aedes to Ae. fluviatilis.Ae. fluviatilis 40 pairs of primers known to flank microsatellite regions in Aedes aegypti, Aedes albopictus and Aedes caspius, and found eight loci that amplified consistently. The number of alleles per locus ranged from 2 to 15, and the expected heterozygosity ranged from 0.09 to 0.85.We tested in Ae. fluviatilis. This finding opens avenues for cost-effective optimization of high-resolution population genetic tools.We found that several microsatellite primers successfully transferred to  Aedes fluviatilis   iz, 1904) . These mz, 1904) . Femaleslinaceum –7.Ae. fluviatilis is adapted to the urban environment [Previous studies showed that ironment , 9. ConsMicrosatellites or Simple Sequence Repeats (SSR) are molecular markers commonly used for population genetics studies, they are repetitive non-codon DNA regions composed by 1 to 6 base pairs in tandem, present in eukaryotic and prokaryotic genomes and are very useful to analyze the genetic structure of mosquitoes , 11. HowAe. fluviatilis of microsatellite primers previously developed for Aedes aegypti, Aedes albopictus and Aedes caspius.Transferability of microsatellite loci between close taxa have been successfully performed before , 13, redAe. aegypti, Ae albopictus or Ae. caspius were tested in nine Ae. fluviatilis’ populations composed of 30 female mosquitoes each, comprising a total of 270 individuals, collected in urban parks throughout the city of São Paulo [Forty microsatellite primers originally designed for ão Paulo . DNA sam™ dye  and examined under UV light.PCR reactions were performed as in Huber et al. , PorrettHO), expected heterozygosity (HE), deviations from Hardy-Weinberg equilibrium and assessment of linkage disequilibrium were calculated in Genepop (v4.2 http://genepop.curtin.edu.au/) [After incorporation of the fluorescent dye , PCR products were diluted (1:7) by mixing 3 μL of each product with 21 μL of ultra-pure water for a final volume of 30 μL. A second dilution was performed with 2 μL of the previous dilution suspended in 8.925 μL of formamide HIDI  and 0.075 μL of molecular weight marker GeneScan 500 ROX  for a final volume of 11 μL. The samples were sent to the Centro de Estudos do Genoma Humano da Universidade de São Paulo and processed in the automatic sequencer ABI 3730 . Fragment analyzes were performed on the software Gene Marker . The allele number, observed heterozygosity (edu.au/)  and ArleAe. fluviatilis, which corroborates the results of Bello & Becerra [Ae. caspius in Ae. taeniorhynchus. The 8 microsatellite primer pairs that successfully transferred to Ae. fluviatilis  (Table Aedes mosquitoes are often less polymorphic than loci developed for other Culicidae genera (e.g. Culex quinquefasciatus and Anopheles funestus) [Our results show that several primers were successfully transferred to  Becerra  that sucunestus) –24.TableAe. fluviatilis, two alleles were found most frequently in the populations examined. Tests for Hardy-Weinberg equilibrium were made for the 8 functional microsatellite loci (Table HE values were higher than the HO values in 5 of 8 conducted tests (Table Ae. fluviatilis genetic structure studies although additional populations should be tested. Both Albtri20 and Albtri33 were monomorphic in one of the nine populations. The other loci were moderately polymorphic and potentially very useful in future population genetics analyses of this species.The number of alleles ranged from 2 to 15 per locus per population, the allele sizes were different from the alleles found in original manuscripts, except for locus OchcB5. Although locus Albtri3 had a high number of alleles per locus in F-statistics values [Null alleles, which occur when mutations in the primer regions prevent primers from annealing, are commonly found in studies using microsatellite markers . Their ps values . Althougs values , 23, 25.s values .Ae. aegypti, Ae. albopictus and Ae. caspius to Ae. fluviatilis demonstrate that loci developed for a few species can be recast for population genetic studies of less well studied species. This finding may open a new range of genetic structure studies of poorly known and/or neglected mosquitoes, e.g. secondary epidemiological importance species as well as a cost-effective genetic population accessible tool.Cross-species microsatellite loci transferability from


Mugil cephalus, has been farmed in semi-intensive ponds with tilapia and carps in Egypt for years. The current study used the fluorescent amplified fragment length polymorphism (F-AFLP) technique to search for genetic differences between the populations of M. cephalus in the northern region of Egypt and to detect the gene flow between sampled locations and the homogeneity within M. cephalus genetic pool in Egypt.The gray mullet, To fulfill the study objectives 60 (15/location) samples were collected from four northern coast governorates of Egypt . Three replicates of bulked DNA (5 samples/replicate) for each location were successfully amplified using the standard AFLP protocol using fluorescent primers. DNA polymorphism, genetic diversity, and population structure were assessed while positive outlier loci were successfully detected among the sampled locations. Based on the geographical distribution of sampling sites, the gene flow, the genetic differentiation, and correlations to sampling locations were estimated.e) for all bulked samples combined together was 1.42. The expected heterozygosity under Hardy–Weinberg assumption (He) for all bulked samples combined together was 0.28. Bulked samples from Damietta yielded the lowest ne (1.35) and the lowest He (0.23) when inbreeding coefficient (FIS) = 1. Bulked samples from Kafr El-Sheikh scored the highest ne (1.55) and the highest He (0.37). Bulked samples from Alexandria scored 1.40 for ne and 0.26 for He, while bulked samples from Port Said scored 1.39 for ne and 0.26 for He. The observed bulked samples formed three sub-population groups, where none is limited to a certain sampling location. A high differentiation among locations was detected, however, is not fully isolating the locations. Gene flow was 0.58. Positive outliers loci (117) were detected among the four sampled locations while weak significant correlation  was found for the distance between them.A total of 1890 polymorphic bands were scored for all locations, where 765, 1054, 673, and 751 polymorphic bands were scored between samples from Alexandria, Kafr El-Sheikh, Damietta and Port Said, respectively. The effective number of alleles (nM. cephalus in Egypt.Even though this species is cultivated in Egypt, the wild population is still present and by the current study a flow of its genes is still exchanged through the northern coast of Egypt. Which contribute to the cultivated populations leading to heterogeneity in its genetic pool and consequently affects the production consistency of  Mugil cephalus Linnaeus, is commonly referred to as the striped, gray, or black mullet /2.”An AMOVA test was used to measure the changes in the pairwise differentiation of the ocations . Gene flPartial Mantel test between the geographical distance and AFLP all loci data set for both data and log data showed no significant correlation, along with the AFLP outlier data against the geographical data. However, weak significant correlation  was found between log (AFLP outlier) matrix against geographical distance matrix.M. cephalus is economically a very important fish because it has high market value and has been cultivated successfully by fish farmers [M. cephalus with many aims, however, less were concerned by its population structure and genetic diversity as it is mainly farmed. Even though, wild populations are still present and by the current study, a flow of its genes are still exchanged through the northern coast of Egypt, thus contribute to the cultivated populations.In Egypt, mullet fish especially  farmers . Severale) was 0.28, which reflects the low diversity level of M. cephalus genetic pool from the sampled locations. The structure program implements a model-based clustering method for inferring population structure using molecular data consisting of unlinked markers. The method was introduced by Pritchard et al. [et al. [M. cephalus in the northern coast of Egypt. Such conclusion was further tested and proved by AMOVA.The AFLP technique permits a genome-wide scan of the genetic variability with a high number of variable markers. Therefore, there is a relative good chance to detect markers under selection either directly or because they are located near a gene under selection. The high reading output and the extensive statistical refining were expected to reflect more clearly the genetic variability of the studied samples. The mean expected heterozygosity under Hardy–Weinberg assumption  by Bonin et al. [loci they screened exhibited elevated altitudinal differentiation. Another recent example was presented by Magdy et al. [Funaria hygrometrica Hedw.) in which the genome scanning successfully detected loci under selection that were strongly correlated with the gradient of environmental factors in Sierra Nevada mountains. Because local adaptation and directional selection should have locus-specific effects of reducing genetic variability within populations and increasing differentiation between populations, loci that are outliers for these characteristics are strong candidate regions for involvement in adaptation to the certain environment.For example, the study of the genetic frame of adaptation to a gradient of altitude in the common frog , a very stringent significance criterion of 99.5% was applied, and simulations were set up to the maximum number allowed by the program. Since a high number of reasonable size bands between 150 and 600 bp were found, the loci under selection detected here should prove to have a good reliability.This study is the first report on the detection of candidate r et al.  noted thm) is a major factor influencing the genetic structure and differentiation among populations. Gene flow was 0.58, the detection of gene flow shows that the genetic differentiation among locations is not absolute. In other words, a complete reproductive isolation between the sampled locations is not the case. Wright [m>1, the homogenization is the result. When Nm<1, the locations can be strongly differentiated. According to these criteria, strong genetic differentiation exists among the studied locations.The AMOVA produces estimates of variance components and F-statistics analogs . In our . Wright  proposedTo elucidate the genetic bases of adaptation to different environments represents a goal of central importance and interest in evolutionary biology . Testingloci are likely located in non-coding DNA, some of the outlier loci may only exhibit the signature of selection because they are linked to the actual target [loci, the genome scan of M. cephalus still offers a window to unravel the genetic basis of fish adaptation without known phenotypes and whole genome sequences. Nowadays, the AFLP primers that were used to amplify the identified outlier loci can be used to construct a reduced representation library of the M. cephalus genome using next-generation sequencing technology [As the detected AFLP l target . Althougchnology .MM has carried out the experimental work in the MAR laboratory and then he prepared the manuscript, while ME has checked the manuscript and polished English language. All authors read and approved the final manuscript.


Screening of BMIC lines with a library of STAT3 inhibitors identified one inhibitor to significantly reduce tumor formation. Meta-analysis identified the oncomir microRNA-21 (miR-21) as a target of STAT3 activity. Inhibition of miR-21 displayed similar reductions in BMIC self-renewal and migration as STAT3 knockdown. Knockdown of STAT3 also reduced expression of known downstream targets of miR-21. Our studies have thus identified STAT3 and miR-21 as cooperative regulators of stemness, migration and tumor initiation in lung-derived BM. Therefore, STAT3 represents a potential therapeutic target in the treatment of lung-to-brain metastases.Brain metastases (BM) represent the most common tumor to affect the adult central nervous system. Despite the increasing incidence of BM, likely due to consistently improving treatment of primary cancers, BM remain severely understudied. In this study, we utilized patient-derived stem cell lines from lung-to-brain metastases to examine the regulatory role of STAT3 in brain metastasis initiating cells (BMICs). Annotation of our previously described BMIC regulatory genes with protein-protein interaction network mapping identified STAT3 as a novel protein interactor. STAT3 knockdown showed a reduction in BMIC self-renewal and migration, and decreased tumor size  Metastases are the most common neoplasm to affect the adult central nervous system, occurring at a rate ten times greater than that of primary neural cancers . Brain mThe metastatic progression of cancer involves several extremely complex but poorly understood stages. Identification and characterization of the pathways and molecules that regulate this process will thus be crucial to our understanding and subsequent treatment of BM. Several genes have been implicated in the regulation of metastases. We have identified a list of candidate genes as being significantly overexpressed in BM, as compared to primary brain and lung tumors . A protein vitro and in vivo as a promising therapeutic avenue for cancer treatment, and several molecules have been identified to block STAT3 activation  and then concatenated into the single list comprising all the unique TF:target pairs. We used mirDIP [Both STAT3 and hsa-mir-21 are very potent regulators of expression targeting wide range of genes. To identify their targets and relationships among them, we collated data from multiple independent sources. Knowledge of human transcription factors (TF) and their respective targets was obtained from four different databases, namely: ChEA  database , ITFP 8  on September 15th 2014. Level 3 gene or miRNA expression data, as well as de-identified patient clinical data, was used for our analysis.All TCGA data was obtained through the TCGA data portal (We calculated Pearson distance between miR-21 and all the Genes/miRNAs to identify features that were inversely co-expressed with miRNA-21 in lung adenocarcinoma samples. The top 250 inversely co-expressed genes/miRNAs are included as Survival analysis was completed in R and survival curves were graphed using Graphpad Prism 5.n values listed in figure legends. Student’s t-test analyses and 2-way ANOVA analysis were performed using GraphPad Prism 5. P < 0.05 was considered significant.Replicates from at least three samples were compiled for each experiment, unless otherwise specified in figure legends. Respective data represent mean ± SD with


Emydura macquarii krefftii), using range-wide sampling  and analysis of mitochondrial sequences (∼1.3-kb control region and ND4) and nuclear microsatellites (12 polymorphic loci). A range of phylogeographic , demographic , and population genetic analyses  were implemented to differentiate between competing demographic  and biogeographic (arid corridor vs. drainage divide) scenarios. Genetic data reveal population genetic structure in Krefft's river turtles primarily reflects isolation across drainage divides. Striking north-south regional divergence  2.08–8.16 Ma) was consistent with long-term isolation across a major drainage divide, not an adjacent arid corridor. Ancient divergence among regional lineages implies persistence of northern Krefft's populations despite the recurrent phases of severe local aridity, but with very low contemporary genetic diversity. Stable demography and high levels of genetic diversity are inferred for southern populations, where aridity was less extreme. Range-wide genetic structure in Krefft's river turtles reflects contemporary and historical drainage architecture, although regional differences in the extent of Plio–Pleistocene climatic aridity may be reflected in current levels of genetic diversity.The influence of Pleistocene climatic cycles on Southern Hemisphere biotas is not yet well understood. Australia's eastern coastal margin provides an ideal setting for examining the relative influence of landscape development, sea level fluctuation, and cyclic climatic aridity on the evolution of freshwater biodiversity. We examined the impact of climatic oscillations and physical biogeographic barriers on the evolutionary history of the wide-ranging Krefft's river turtle ( Climatic cycles over the past several million years have driven important evolutionary changes in the world's biota. However, research has focused largely on the Northern Hemisphere where land-based glaciation was extensive. Widespread glaciations never occurred in Australia, which instead experienced cycles of severe aridity that also profoundly influenced current patterns of biodiversity  currently experience the most severe seasonal aridity of anywhere along Australia's east coast. The degree of aridity experienced here was probably even more extreme during glacial maxima (Williams 2), immediately to its south. These basins may be particularly ancient  describe population genetic structure and connectivity in E. m. krefftii at multiple spatial scales, including within and among individual drainage basins as well as regionally across its whole distribution; and (2) differentiate between competing biogeographic (arid corridor vs. drainage divide) and demographic  hypotheses. If the Burdekin Gap has presented an important historical barrier for Krefft's turtles, regional genetic divergence is expected among populations either side of the Burdekin lowlands. Alternatively, if the Burdekin–Fitzroy drainage divide has been a significant historical barrier, regional genetic divergence is expected across the Burdekin's southern drainage boundary. Similarly, if E. m. krefftii survived local climatic perturbation in northern refugia, (a) northern populations are expected to be genetically differentiated from southern populations; and (b) to potentially show signals of historical bottlenecks and/or recent demographic expansion. By contrast, if northern populations are the result of recent range expansions from southern refugia, we would expect (a) steady northwards decrease in genetic diversity; and (b) less pronounced genetic structure moving northwards. In either case, southern populations are expected to have been demographically more stable.To examine the relative importance of a major drainage divide versus a historical arid corridor as barriers to movement of freshwater animals in eastern Australia, we investigated range-wide genetic structure in Krefft's river turtle, E. m. krefftii across 18 locations in 11 drainage basins, representing the native distribution of this subspecies in eastern coastal Australia  for comparison. Tissues were obtained from existing collections through collaborations with other researchers, or during targeted field work. In the field, turtles were caught by seine net, baited trap or by hand while snorkeling. A small section of skin was removed from the forelimb of each turtle and preserved immediately in 95% ethanol, later stored at −20°C. Genomic DNA was extracted from tissues using a modified salting-out protocol described previously  and NADH dehydrogenase subunit 4  using primers and protocols described previously . ND4 sequences were translated and examined for premature stop codons that may indicate the presence of nuclear mitochondrial (numt) DNA paralogues, and sequence chromatograms were inspected visually for ambiguous nucleotide signals that may indicate co-amplification of mitochondrial DNA and numts. Finally, regions were aligned with published sequences from a range of turtle species to verify amplification of the correct mitochondrial region. No evidence of numts was found, and CR and ND4 sequences were concatenated for further analysis.We investigated historical population structure and identified major genetic lineages within E. m. krefftii and related subspecies) were assessed with a minimum spanning network, computed in ARLEQUIN 3.5 , number of polymorphic sites (Np), haplotype diversity (h), nucleotide diversity (π), and average number of nucleotide differences (k).Measures of mtDNA diversity within major E. m. krefftii, as well as among related subspecies, were estimated for ND4 sequences using mean uncorrected p-distances in MEGA 5  and observed (HO) and expected (HE) heterozygosities for each sample location, drainage and region in ARLEQUIN. Private alleles were identified using GENALEX. Allelic richness (AR) was also calculated for each population, region and overall in FSTAT 2.9 , performed in ARLEQUIN . AMOVA were performed at two spatial scales: regional (among northern and southern regions and among drainages within regions) and drainage (among drainages and among locations within drainages).Population genetic structure within and across drainage boundaries was quantified using pairwise linearized K) best represented within the microsatellite data. All samples were utilized, including those from the Herbert (n = 2) and Alligator Ck (n = 8) drainages. Ten independent simulations were run for each value of K from one to 10, using 5 million MCMC replications with an initial “burn-in” of 1 million, found to be appropriate in pilot runs. An admixture model with correlated allele frequencies was assumed, and sampling locations were used as prior information (LOCPRIOR model), which improves clustering performance for datasets where the signal of genetic structure may be weak, without biasing the outcome  of STRUCTURE runs was assessed in the program CLUMPP 1.1.2  for each population using individual multilocus microsatellite data, on the basis that recent immigrants and their offspring display genotypic disequilibrium relative to the population in which they were sampled. The approach does not assume migration–drift equilibrium, but because prior limits are placed on m (0–0.33), is powerful only when migration is low (m < 0.1) and population divergence is moderate–high . Based on recommendations by Faubet et al. . This approach follows that of Hodges et al.  was applied. Two independent MCMC chains were each run for 200 million generations, sampling every 20,000 steps. Trace convergence was assessed in TRACER and replicate runs combined using LOGCOMBINER 1.8.0 (10% “burn-in”). TREEANNOTATOR 1.8.0 was used to produce the maximum clade credibility tree, visualized in FIGTREE 1.3.1 (available from http://tree.bio.ed.ac.uk/software/figtree).A timeframe for divergence between northern and southern mitochondrial lineages Fig.  was estis et al. , who sucE. m. krefftii clades. Fu's FS (Fu D (Tajima r) were calculated, using 2000 bootstrap replicates to assess significance. Significant SSD or r values indicate that an expansion model is rejected by the data.Neutrality statistics and mismatch distributions were performed on mtDNA data to test for signatures of population expansion within major 's FS Fu  is one oD Tajima  in ARLEQD Tajima  against D Tajima . To testMicrosatellite data were used to investigate the possibility of recent genetic bottlenecks using tests for heterozygosity excess implemented in BOTTLENECK 1.2.02  [GenBank: KF181795–KF181853]. Twenty-nine ND4 haplotypes were identified among 647 individuals (59 variable sites across 837 bp) [GenBank: KF181854–KF181885]. The haplotypic network, based on concatenated sequences, distinguished three divergent clades within E. m. krefftii  and E. m. nigra (Fraser Is), were nested within the southern E. m. krefftii clade and were closely related to haplotypes from the Burnett and Mary Rivers, respectively. E. m. emmotti (Cooper Ck) was distinct, separated by 38 mutational changes from the northern E. m. krefftii clade. ND4 evolutionary distances are presented in Table E. m. krefftii clades (2.23–3.03%) to be considerably greater than that between the southern E. m. krefftii clade and E. m. nigra (0.83%) or E. m. macquarii (0.64%). The upstream Burnett clade was as divergent from the southern clade (2.31%) as from the other subspecies (range 2.35–2.83%), giving no indication of a potential historical relationship. Greatest within-clade divergence was seen within the southern clade (0.53%), compared with the northern (0.19%) or upstream Burnett (0.16%) clades.For the remaining subspecies, only a single haplotype was identified per subspecies among the five sampled individuals. Their relationships with Hd = 0.940, π = 0.662). The northern clade shared just three common haplotypes across 200 individuals . Deviations from HWE were detected at six loci . There was no evidence of scoring error due to stuttering or large allele dropout at any locus, although tests for homozygote excess in MICRO-CHECKER suggested null alleles at locus Ekref15 and Ekref12 in the Fitzroy R subcatchment and Normanby R populations, respectively. There was no evidence for linkage disequilibrium. As there was no consistent evidence for null alleles or deviation from HWE for any particular locus or sampling location, and as analyses with and without these data did not alter the interpretation, the entire dataset was retained and examined.AR, HO, and gene diversity among regions were all statistically significant (P < 0.05). For the southern locations collectively, 48 (40%) private alleles were detected, compared with eight (10%) in the northern locations. Most individual drainages also contained private alleles .As for mtDNA, stark differences were found in measures of genetic diversity among regions and some sampling locations at microsatellites Table . Values E. m. krefftii. Pairwise FST values among drainages were all highly significant after correction for multiple comparisons , suggesting drainage basins are the most local unit of population structure. Only three comparisons were significant after correction: Burnett downstream vs. upstream (FST 0.008), Burdekin Bowen R vs. Suttor R (FST 0.016), and Burdekin Bowen R vs. Burdekin R (FST 0.015). Distinctiveness of the upstream Burnett R population, as supported by mtDNA , compared with within regions . AMOVA analyses also revealed significant hierarchical population structure (Table P = 0.012), and 9.9% to variation among drainages within regions (P = 0.000). A drainage-level analysis attributed 15.9% of genetic variation to among drainages (P = 0.000), with a small but significant 0.7% (P = 0.000) attributed to among locations within drainages.Microsatellites revealed a considerable level of genetic differentiation across the range of ns Table . HoweverDNA Fig. , was notE. m. krefftii. A primary division between two genetic clusters . However, because m represents the fraction of migrants in a population, and sample size for the northern lineage was roughly half that of the southern lineage, migration has been greater southwards across the Burdekin–Fitzroy drainage divide (from the northern lineage into the southern lineage). Individual posterior probabilities of migrant ancestry identified seven individuals as potential migrants (nonmigrant probability < 0.90). All had second-generation migrant probabilities between 0.14 and 0.97 (first-generation migrant probabilities were negligible) and were sampled from headwater locations adjacent the Burdekin–Fitzroy drainage divide. Northern lineage migrants were sampled from Theresa Ck , and the Pioneer and Proserpine drainages (n = 1 each), while a single southern lineage migrant was sampled from the Burdekin's Suttor R. Locations of cross-drainage dispersal are the same as those identified from the mtDNA haplotype network and microsatellite clustering analyses, although only the Suttor R individual exhibited an mtDNA haplotype from the opposite lineage.Five replicate BAYESASS runs produced highly consistent results and very low estimates of E. m. krefftii mitochondrial lineages originated (diverged) approximately 4.73 million years ago (Ma), in the early Pliocene . Earliest divergence within the southern lineage was estimated at 1.28 Ma (95% HPD: 0.54–2.20 Ma), and for the northern lineage 0.74 Ma (95% HPD: 0.22–1.42 Ma), both within the Pleistocene.Coalescent-based analyses in BEAST estimate northern and southern E. m. krefftii. Estimates of demographic parameters and neutrality tests for major mtDNA clades are presented in Table D and FS were negative for most lineages, suggesting population expansion, only the D statistic in the Far North clade was significant. However, significant r and SSD values indicated a sudden expansion model could not be conclusively rejected in any case  analyses to differentiate between alternative scenarios of demographic change. However, preliminary results from both methods indicated the current dataset lacks resolution for estimating historical demographic parameters, and results are not presented here.E. m. krefftii. Three divergent mtDNA clades were identified within E. m. krefftii, and a strongly hierarchical population structure was evident across its extensive range. Data enabled differentiation between competing biogeographic (arid corridor vs. drainage divide) and demographic  hypotheses related to the impact of cyclic aridity on the east Australian freshwater fauna. These hypotheses are addressed in detail below in relation to the current genetic data.Australia presents a unique opportunity to study the impact of episodic Pleistocene aridity on current biodiversity in the absence of widespread glaciation. In the present study, fine-scale geographic sampling and analyses of mtDNA and nuclear microsatellites were used to describe genetic structure and diversity in the widespread Krefft's river turtle, E. m. krefftii lineages in the vicinity of the Burdekin drainage. The disjunction is geographically congruent with genetic “breaks” observed in codistributed taxa, hypothesized to reflect a terrestrial climatic barrier termed the Burdekin Gap. Fine-scale sampling of E. m. krefftii throughout the Burdekin and adjacent catchments, however, revealed the genetic disjunction to be inconsistent with this hypothesis. Turtle populations sampled within the Burdekin drainage but separated by the Gap were closely related genetically at mtDNA and microsatellite data. Low, but significant, FST values among Burdekin locations for microsatellites (range 0.011–0.016) suggest only weak restrictions on dispersal, consistent with distance, a large waterfall  and Fitzroy  basins are by far the largest and oldest systems on Australia's eastern seaboard, having expanded westwards during the Palaeogene , while populations either side of the Burdekin Gap are distinct only at the intraspecific level within E. irwini , with weak or no differentiation among locations within drainages . Hierarchical relationships among drainages were also evident, especially from analyses in STRUCTURE  has been linked to geological evidence for a recent confluence of these river systems, severed by rising sea levels only ∼12,000 years ago . Closer relatedness of one Burdekin haplotype, found in six individuals sampled from the Suttor R close to the Fitzroy boundary, to Fitzroy haplotypes may also indicate historical crossing of the drainage divide. Despite the limited haplotype sharing among drainages, complex relationships among southern haplotypes also imply periodic cross-drainage dispersal followed by isolation and divergence. Isolation by drainage divides coupled with occasional cross-drainage dispersal may be important in generating considerable genetic diversity observed across the whole Elseya sp., swamp-adapted Chelodina sp., and Emydura indistinguishable from living E. m. krefftii, indicate diverse aquatic habitat here before establishment of Pleistocene cyclic aridity  predate evidence for widespread aridity in eastern Australia around 1.5 Ma  and other relict Gondwanan lineages , especially, implies enduring aquatic habitat , and swift recolonization once freshwater connections re-established. An ability to move overland and abandon drying habitat in search of permanent waterbodies potentially further facilitated their survival during periods of climatic harshness in the Burdekin region, when many other freshwater taxa clearly were extirpated.Many Northern Hemisphere species, including freshwater fishes and turtles, show clear signatures of genetic bottlenecks and range reductions into isolated glacial refugia, followed by dramatic demographic and range expansion since the end of the last ice age  is within the range typically observed among congeneric chelonian species  is warranted. Such an analysis may prove especially revealing, as E. macquarii is one of few very widespread species inhabiting south-eastern Australia shown to be genetically structured. Although biogeographically complex and relatively well-studied, historical relationships and dispersal patterns among major freshwater biogeographic regions in this area remain poorly resolved (Unmack Range-wide investigation of morphological and genetic variation in d Unmack .E. m. krefftii, primarily reflects isolation by drainage divides, with evidence of occasional overland dispersal. We found little evidence that an arid corridor is responsible for structuring Krefft's turtles along Australia's east coast, and newly identify a significant biogeographic barrier in the form of an ancient drainage divide between the geographically extensive Burdekin and Fitzroy basins. Although E. m. krefftii apparently persisted despite severe local aridity associated with the Burdekin Gap through multiple glacial cycles, habitat instability and increased genetic drift may be responsible for very low contemporary genetic diversity compared with southern populations. Our study highlights the importance of fine-scale geographical sampling in evaluating the role of biogeographic barriers and demonstrates the utility of integrating mitochondrial sequences and sensitive nuclear datasets for inferring evolutionary history.Range-wide genetic structure and molecular diversity in a widespread freshwater turtle, E. macquarii complex may be a valuable model taxon for unraveling biogeographic complexity in south-eastern Australia for freshwater taxa, and may help to answer several long-standing questions regarding historical patterns of freshwater connectivity and dispersal in this region.The broader


Tamias striatus) in conjunction with spatially explicit habitat attribute data to evaluate the realized permeability of various landscape elements in a fragmented agricultural ecosystem. To accomplish this we 1) used logistic regression to evaluate whether land cover attributes were most often associated with the matrix between or habitat within genetically identified populations across the landscape, and 2) utilized spatially explicit habitat attribute data to predict genetically-derived Bayesian probabilities of population membership of individual chipmunks in an agricultural ecosystem. Consistency between the results of the two approaches with regard to facilitators and inhibitors of gene flow in the landscape indicate that this is a promising new way to utilize both landscape and genetic data to gain a deeper understanding of human-altered ecosystems.Human-altered environments often challenge native species with a complex spatial distribution of resources. Hostile landscape features can inhibit animal movement , while other landscape attributes facilitate gene flow. The genetic attributes of organisms inhabiting such complex environments can reveal the legacy of their movements through the landscape. Thus, by evaluating landscape attributes within the context of genetic connectivity of organisms within the landscape, we can elucidate how a species has coped with the enhanced complexity of human altered environments. In this research, we utilized genetic data from eastern chipmunks ( Fragmentation of natural landscapes by anthropogenic attributes, such as agriculture, urbanization, and transportation infrastructure, alters the manner in which animals utilize remnant native habitats , 2]. In. In2]. IOf particular concern in fragmented ecosystems is the concept that a long-term reduction in genetic diversity and impediments to gene flow can inhibit future adaptation of species . Howevera priori groupings and genetic patterns can be analyzed at the individual scale. Another benefit of using landscape genetics for fragmentation studies is its ability to disentangle multiple influences on gene flow because genetic variation is often influenced by multiple factors that operate at different spatial . T. T13]. T spatial –18 and t spatial , 20]..a prioriLandscape genetic models often depend on accurate definition of the functional biological extent of populations, particularly in management and conservation efforts , 22]. U. U22]. Uq-values or posterior probabilities) inferred from Bayesian algorithms within landscape genetic models. These genetic variables can act as response variables in statistics that evaluate how landscape parameters influence genetic variation. For example, several studies have utilized genetic surfaces based on ancestry coefficients from Bayesian clustering programs to investigate how specific landscape features  impacted gene flow , ) in the basin are highly fragmented with the largest tracts confined to major drainages where floodplains or locally steep topography prohibits agriculture . I. I2) of iculture . Possibl2 study cells from late May to early August in 2001, 2002, 2003, respectively. Prior to each field season, all 30 X 30 m pixels in each cell were classified into 1 of 5 land cover categories , and then sampled according to a stratified-random design. To capture the variation within the study area, trapping grids were placed in sampling sites based on land cover so that natural land cover types  were disproportionally represented as compared to urban and agriculture . We randomly chose sampling sites  within patches of habitat by randomly selecting pixels of an appropriate habitat according to the predefined proportions stated above within each study cell (n = 35). Forest site selection had an additional step because they were also stratified according to forest patch size , and then were selected according to their log10 area within the three size categories. In total, a maximum of 45 sampling sites were selected per study cell in a summer , a, a2 studa summer . A full a summer .Each sampling site within a cell contained a grid of Fitch live traps (2001), Sherman live traps (2003), or a mixture of both (2002) spaced 15 m apart. Grid dimensions varied by trap year and patch size. Grids in 2001 were primarily 3 traps x 3 traps, with a few 7x7 grids where forest patch sizes were large enough to accommodate this arrangement. In 2002 and 2003, 5x5 grids were used whenever space allowed; otherwise 4x4 or 3x3 grids were used. If a forest patch was not large enough for a 3x3 grid, it was not sampled. Habitat corridors were identified as treed and non-treed land cover features less than 30 m wide and were fitted with 5x2 grids. Simultaneous trapping for raccoons was conducted at the edges of the trap grids to limit disturbance by raccoons to the small mammal traps.Traps were baited with black-oil sunflower seeds. A pre-bait period with traps locked open occurred for 3 days, followed by a 5-day trap-check session, during which traps were checked twice daily. Each site had one trapping session. All animals were handled according to procedures approved by the Purdue Animal Care and Use Committee under protocol #01–024. Ear clips were taken from each individual using sterile scissors, and treated with ferric subsulfate in cases of excess bleeding. Animals were then released, and all tissues were stored in at -80°C prior to DNA extraction.Taq DNA polymerase (NEB) and 2X Thermopol reaction buffer 2SO4, 10 mM KCl, 2 mM MgSO4, 0.1% Triton X-100; NEB). Primer concentrations were adjusted so that intensities of the final products per multiplex reaction were approximately equal  in in34] ink. Five independent runs were performed to ensure consistency in the estimation of k. If there were inconsistencies between runs , we added additional runs with 400,000 iterations . Finally, Geneland may produce empty populations in addition to occupied populations, a phenomenon known as ‘ghost populations’ )a priori assignment of cost values is needed. Instead, regression coefficients derived from models developed in independent landscapes like our study could also be used to parameterize resistance surfaces. Once developed, genetically informed individual-based models could be used for a variety of purposes such as comparison to other parameterization  or optimization Click here for additional data file.S2 TableR), and FIS with the upper and lower 95% confidence intervals are listed per locus and sample cell. Bold FIS values indicate a significant deficiency of heterozygotes.Sample size (N), number of alleles (Na), observed (Ho) and expected heterozygosity (He), allelic richness (A(DOCX)Click here for additional data file.S3 TableST values were calculated for each study cell as well as pair-wise FST values between all putative clusters within a study cell. All but one FST between putative clusters were significantly different from zero.Global F(DOCX)Click here for additional data file.S1 FigWe recorded a positive relationship between geographic and genetic distance, consistent with IBD .(TIF)Click here for additional data file.


Mhc-DQB1 loci in 119 wild rhesus macaques from five geographically isolated populations in western Sichuan, China, and compared the levels of MHC variation and differentiation among populations with that previously observed at neutral microsatellite markers.Rhesus macaques living in western Sichuan, China, have been separated into several isolated populations due to habitat fragmentation. Previous studies based on the neutral or nearly neutral markers  showed high levels of genetic diversity and moderate genetic differentiation in the Sichuan rhesus macaques. Variation at the major histocompatibility complex (MHC) loci is widely accepted as being maintained by balancing selection, even with a low level of neutral variability in some species. However, in small and isolated or bottlenecked populations, balancing selection may be overwhelmed by genetic drift. To estimate microevolutionary forces acting on the isolated rhesus macaque populations, we examined genetic variation at Mamu-DQB1 alleles were identified in 119 rhesus macaques in western Sichuan, China. These macaques exhibited relatively high levels of genetic diversity at Mamu-DQB1. The Hanyuan population presented the highest genetic variation, whereas the Heishui population was the lowest. Analysis of molecular variance (AMOVA) and pairwise FST values showed moderate genetic differentiation occurring among the five populations at the Mhc-DQB1 locus. Non-synonymous substitutions occurred at a higher frequency than synonymous substitutions in the peptide binding region. Levels of MHC variation within rhesus macaque populations are concordant with microsatellite variation. On the phylogenetic tree for the rhesus and crab-eating macaques, extensive allele or allelic lineage sharing is observed betweenthe two species.23 Mhc-DQB1 genes in these macaques. Balancing selection plays an important role in sharing allelic lineages between species, but genetic drift may share balancing selection dominance to maintain MHC diversity. Great divergence at neutral or adaptive markers showed that moderate genetic differentiation had occurred in rhesus macaque populations in western Sichuan, China, due to the habitat fragmentation caused by long-term geographic barriers and human activity. The Heishui population should be paid more attention for its lowest level of genetic diversity and relatively great divergence from others.Phylogenetic analyses confirm the apparent trans-species model of evolution of the  MHC genes are well-known examples of genes of adaptive significance and are particularly relevant to conservation[How genetic variation is maintained within populations of endangered species is a central issue in evolutionary and conservation biology. Diversiervation. Consequervation, and theervation-11, but ervation,13. In pervation,14. Geneervation. The smaervation. The loservation. An impoervation,19. ClarMacaca mulatta) is mainly found throughout most of southern Asia crossing eastern Afghanistan, Bangladesh, Bhutan, northern and central India, central and southern China, Lao PDR, Myanmar, Nepal, northern Pakistan, northern Thailand, and Vietnam, and is a endangered species due to the sharp reduction in the number throughout its wider distribution in recent years. This species is listed in CITES Appendix II, Schedule III of the Bangladesh Wildlife (Preservation) Act (1974), Schedule I of Part I of the Indian Wildlife (Protection) Act (amended up to 2002), and Category II of the Chinese Wildlife Protection Act (1989). According to Jiang[M. mulatta lasiotis, which was isolated from the other five subspecies by human activities and natural barriers (Yangtze River) and has been fragmentized in western Sichuan mainly due to the special topography in this region  and the northern section of Hengduan Mountains, is the global biodiversity hotspots. Affected by the Pliocene uplifting of the QTP, western Sichuan formed a complex and diverse topography with high mountains and deep valleys. The region, from southwest to northeast, has four major mountains, namely, Liangshan, Xiangling, Qionglai, and Mingshan and four large rivers, namely, Jinshajiang, Yalongjiang, Daduhe, Mingjiang and Jialingjiang Figure . Additioion) Act 974, ScheAona-DQB1 alleles were identified that separated the two lineages Aona-DQB1*22 and Aona-DQB1*23 in a group of 19 unrelated owl monkeys (Aotus nancymaae)[Mhc-DQB gene in each of a random panel of 60 non-pedigreed cynomolgous macaques (Macaca fascicularis), resulting in the detection of 23 Mafa-DQB1 alleles that had not previously been published and confirmed the trans-species model of evolution of the Mhc-DQB lineages, in which a group of major allele lineages is shared by different species of non-human primates in the phylogeny. Qiu et al.[MhcMamu-DQB1 alleles in 105 Chinese rhesus macaques by cloning and sequencing, illustrating a marked allelic polymorphism at DQB1 in these monkeys. Notably, in recent years more MHC class II DQB alleles have been identified and characterized in two closely related monkeys, rhesus and cynomolgous macaques, due to their common use as experimental animal models in biomedical research.The rhesus macaque, cynomolgus macaque, common marmoset and owl monkey are non-human primates that are often used as experimental model animals for biomedical research, such as transplantation studies and vaccine development against measles, Ebola, or other infectious diseases including acquired immune deficiency syndrome (AIDS),28. For ncymaae); Otting ncymaae) sequenceu et al. identifiDQB1 locus in five isolated populations of rhesus macaques in western Sichuan, China; 2) to estimate the degree of genetic differentiation among or within populations; 3) to determine the relative roles of microevolutionary forces such as balancing selection or genetic drift in populations; and 4) to confirm the trans-species model of evolution of Mhc-DQB1 lineages between rhesus and cynomolgous macaques.The above work provided us with the inspiration and base to explore the genetic variation patterns of rhesus macaques in western China based on MHC genes with adaptive significance because of their role in pathogen resistance. The aims of this study included the following: 1) to investigate polymorphism levels of MHC class II Mamu-DQB1 gene, and then cloning and sequencing of the second exon of the Mamu-DQB1 gene were conducted for the samples representing the 49 genotypes. Consequently, 23 Mamu-DQB1 alleles were identified in Sichuan rhesus macaques (Table Mamu-DQB1 sequence obtained was 274 bp (excluding primers) in length and spanned the complete sequence of exon 2. No more than two alleles were detected in each individual, and no stop codon or insertion/deletion was observed in Mamu-DQB1. By blast searches in the IPD-MHC Database (http://www.ebi.ac.uk/ipd/mhc/), the 23 allelic sequences were found to be completely identical to some designated alleles, showing that these alleles also existed in other rhesus macaque individuals in previous study.A total of 119 rhesus macaque individuals in western Sichuan were typed into 49 genotypes through the polymerase chain reaction (PCR) and single-strand conformation polymorphism (SSCP) analysis based on the polymorphism of the second exon of the Mamu-DQB1 alleles varied substantially in five different geographical populations  of the 119 monkeys; the next most common frequency was Mamu-DQB*1503, which was detected in 30 (12.61%) of these monkeys. The third frequency was Mamu-DQB*1703, which was detected in 29 (24.37%) of these monkeys. Three of the five geographical populations had their unique alleles. Mamu-DQB*1502, Mamu-DQB*1601, Mamu-DQB*170601, Mamu-DQB*1804, and Mamu-DQB*1819 were found only in the Hanyuan population, Mamu-DQB*061301 and Mamu-DQB*1818 were found only in the Danba population, and Mamu-DQB*0607 was found only in the Jiulong population. Mamu-DQB*0614 was found in all populations at different frequency from 1.79% to 21.43%. Mamu-DQB*061301 was detected only in one individual.The number and frequency of the s Table . The high), nucleotide diversity (π), expected heterozygosity (He) and allelic richness (AR) were calculated  region, and there were at least 20 nucleotide variations on average in each population. The Hanyuan population exhibited the highest genetic diversity: 15 allele haplotypes were observed in 28 animal individuals. The Heishui population exhibited the lowest genetic diversity: only 7 allele haplotypes were observed in 30 animal individuals. Surprisingly, the inbreeding coefficient (Fis) in the Hanyuan population was also the highest, whereas it was lowest in Heishui population.In order to estimate genetic diversity of the rhesus macaques in western Sichuan based on the adaptive marker, several genetic diversity parameters such as haplotype diversity . As is evident from the tree, the majority of Mhc-DQB1 alleles tended to cluster together according to lineage group rather than species or sample origins, revealing a trans-species model of evolution. Twenty-three Mamu-DQB1 alleles were classed into five lineages: DQB1*06, *15, *16, *17, and *18, of which lineage DQB1*06 and *18 were most dominant . Almost all previously reported major Mamu-DQB1 lineages were detected , except for DQB1*24 lineages that were not found in the western Sichuan macaques examined in this study. It is worth noting that rhesus macaques shared only 14 identical alleles with crab-eating macaques on the phylogenetic tree, but there were 10 alleles to be detected in this study  for all sites, antigen-binding sites (ABS), and non-antigen binding sites (non-ABS) were calculated (Table ω = 1.458), whereas the lowest ω ratio value was found in non-ABS and less than one (ω = 0.976), but these values did not significantly deviate from the neutral expectation in the Z-test (p > 0.05). To better understand the substitution pattern of Mamu-DQB1 exon 2 sequences, 46 Mamu-DQB1 exon 2 sequences from the previous studies were added to our sequence data to expand our analysis . These results indicated that the ABS of Mamu-DQB1 exon 2 sequences had been subjected to a strong balancing selection, but the selection signal was not significant in the Mamu-DQB1 exon 2 sequences of western Sichuan rhesus macaques.To analyze the selective pressure on FST) . To further assess the genetic differentiation among populations, the pairwise comparison FST and gene flow (Nm) values among populations were calculated . However, there is not a significant correlation between microsatellite sites and Mamu-DQB1 heterozygosity per population . No significant correlation to pairwise FST between microsatellite sites and Mamu-DQB1 . The FST values of Mamu-DQB1 showed higher divergence among populations when compared with microsatellite loci (except for the Danba-Hanyuan and Danba-Xiaojin populations), and all of the FST values (except for that of the Danba-Xiaojin population) at the Mamu-DQB1 locus were higher than 0.05, indicating that divergence existed among populations, especially between the Heishui and Jiulong populations, which had the largest FST. Overally, the population difference was more obvious at the Mamu-DQB1 locus than the microsatelites: six FST values from the Mamu-DQB1 locus were far larger than that of the microsatellites in ten pariwise population comparisons  and He values than any other populations  that are present at considerably higher frequencies in this population. Nevertheless, it is possible that there are additional MHC alleles that were not detected in Heishui population because of its smaller sample size.The high level of polymorphism usually observed in MHC genes is likely to be maintained by balancing selection, driven largely by exposure to a diversity of pathogens-11. In ts Table , exhibitHC genes-42, thusDRB, but not at DQB locus[Fis) at the Mamu-DQB1 locus  compared to synonymous (dS) substitutions (ω = dN /dS) is the most common measure used to detect balancing selection acting on protein-coding genes. Polymorphisms within the ABS of MHC genes are thought to be maintained by balancing selection imposed by pathogens/parasites. Fast-evolving parasites may adapt to the most common host genotype and escape presentation of their antigens to the adaptive immune system of the host[Mamu-DQB1 exon 2 sequences had been subjected to a strong balancing selection, but the selection signal was not significant in the Mamu-DQB1 exon 2 sequences of western Sichuan rhesus macaques. This may well be caused by genetic drift acting differently on the different populations, e.g., the Heishui population may has been subject to a genetic drift, leading to a low level of genetic diversity. Alternatively, this may also be due to the smaller sample size surveyed here.Balancing selection is expected to preserve high levels of polymorphisms at MHC loci by retaining alleles during species diversification events,47. The the host. In thisMhc-DQB1 allele sequences from rhesus and cynomolgus macaques tended to cluster together according to allelic lineages rather than species or sample origins, leading to the sharing of allelic lineages by different species. The result clearly confirmed the trans-species model of evolution of the Mhc-DQB1 lineages. In particular, 14 Mamu-DQB1 alleles matched exactly with the Mafa-DQB1 alleles, suggesting that they may have occurred because of trans-species conservation after the divergence of the rhesus and cynomolgus macaque 1.8–2.0 million years ago (mya)[DQA1, DPB1, and DRB1[Under balancing selection, some allelic lineages exhibit unusual longevity that predates speciation events, leading to “trans-species polymorphisms” (TSP) used to describe polymorphisms among species. In an ego (mya),53,28. Ago (mya). The all and DRB1. HoweverFst was moderate (0.14712)  is the transfer of genes from one population to another. Generally, if Nm < 1, genetic drift will result in substantial local differentiation; if Nm > 1, gene flow between populations is higher and the extent of genetic differentiation is smaller. When Nm > 4, gene exchange is more frequent and genetic differentiation is much smaller[Nm were larger than 1 (1.533–6.175). Especially, the values of Nm among three populations  were even larger than 4, suggesting that gene exchange was more frequent among the three populations.AMOVA of the five populations indicated that variations mainly occurred among populations and that the erate 0.1712 , Hanyuan (n = 28), Danba (n = 14), Xiaojin (n = 27), and Heishui (n = 30), located in western Sichuan, China  amplification of Mamu-DQB1, all PCRs were performed in a reaction volume of 10 μl, containing 5 μl of 2X ES Taq MasterMix , 0.3 μl (10 pm/μl) of each DQB1 primer, roughly 20 ng template DNA, and distilled, deionized H2O to 10 μl. All PCR amplifications were carried out using a MyCyclerTM Thermal Cycler , with the first step at 94°C for 5 minutes, 30 cycles of 94°C for 30 seconds, 62°C for 25 seconds, 72°C for 45 seconds, and a final extension at 72°C for 10 minutes. Products were examined with 1% agarose gel electrophoresis and visualized under ultraviolet light.A pair of specific primers (Mamu-DQB1F 5’–GCCTGACTGACTGGACGGTGATTC-3’ and Mamu-DQB1R 5’-GGGGCGACAACGCTCACCTC-3’) were used to amplify an approximately 317-bp DNA fragment containing the complete second exon of the DQB1 exon 2 by SSCP analysis. Two μl of the PCR sample was mixed with 8 μl of the denaturating buffer  before heating for 10 min at 98°C. The samples after denaturation were immediately cooled in ice water at least 10 min, then loaded in a 2-mm-thick 12% acrylamide gel (no glycerol contained) and were electrophorized in 0.5X TBE at 130 V (15 h) at room temperature. The resulting bands were visualized by silver staining. PCR products that showed the same SSCP pattern were counted and typed.All positive PCR amplification products were screened for polymorphisms in Escherichia coli DH5α-competent cells to the incubated ligation mixture, and then we put this on ice for 30 minutes, heat-shocked the cells at 42°C for 52 seconds in a water bath, immediately put this on ice for at least 3 minutes, and added 800 μl 37°C LB media. This mixture was then incubated at 37°C with shaking at approximately 150 rpm for 80 min, and recovery cells were mixed with 7 μl IPTG and 40 μl X-Gal, then 160 μl of the mixture was plated onto LB/ampicillin plates and incubated at 37°C overnight (14–16 hours). After blue⁄white selection, a number of positive clones were picked and grown, and 10–12 clones were chosen and sequenced by the sequencing company . To avoid errors arising from PCR-based recombination, apart from the optimization of the PCR program, we have taken several measures to determine a real sequence: 1) a sequence must be detected in at least 2 animal individuals; and/or 2) if a sequence was found in only one animal individual, it must be confirmed by at least 2 independent PCRs.Representative samples from each population were amplified with a reaction volume of 50 μl by PCR; the product was fractionated by electrophoresis in 18% agarose gels and purified using a Gel Extraction Kit . Purified pieces of DNA were then cloned using the pMD19-T Vector kit . Briefly, ~2–3 μl of each positive purified DNA was added into each mixture containing 2.5 μl of Solution I and 0.5 μl of pMD19-T Vector. The mixtures were incubated at 16°C for 40 min. For transformation, we added 25 μl of π) and haplotype diversity (h) were calculated using DnaSP (Version 5)[He) and observed (Ho) heterozygosities, pairwise FST and genetic flow (Nm) among populations were estimated with GenAlEx 6.5[FIS) and allelic richness (AR) per population were calculated with the FSTAT program, version 2.9.3[The sequences obtained from this study were initially adjusted using DNAStar software . Multiple sequence alignments were created using the Clustal W program in DAMBE software. Nucleotrsion 5). AllelicAlEx 6.5. Inbreedon 2.9.3. AllelicdN) and synonymous (dS) substitution rates at Mamu-DQB1 amino acid sites were calculated according to the Nei–Gjobori method in Mega 5.05[Z-test for selection was used to evaluate whether dN was significantly greater than dS for entire sequences. The ABS and non-ABS were distinguished based on HLA-DQB1 structure[Mhc-DQB1 allelic sequences using Mega 5.05, based on the neighbor-joining method with Kimura 2-para model. The reliability of the neighbor-joining tree was estimated by bootstrapping, in which 1000 bootstrap pseudosamples were used. To expand our data and compare with the closely related species, an additional 46 Mamu-DQB1, 85 Mafa-DQB1 (Macaca fascicularis), and 2 Aona-DQB1 (Aotus nancymaae) alleles were also retrieved from the Immuno Polymorphism Database. Thus, a total of 156 Mhc-DQB1 gene sequences including 23 sequences identified in this study were used in the phylogenetic analysis, and Aona-DQB1 was used as an out-group. Information for all these sequences is shown in Additional fileNon-synonymous  using the Arlequin version 3.1 package. This paThe data sets supporting the results of this article are available in the Dryad repository, doi:10.5061/dryad.h8b93.The authors have declared that no competing interests.H-LX conceived the study and helped to draft the manuscript; Y-FY and Q-XD performed the experiments and wrote the manuscript; JL, Q-YN and M-WZ analyzed the data. All authors read and approved the final manuscript.Mhc-DQB1 alleles of different primate species used in this study A total of 156 Mhc-DQB1 alleles from three primate species  were used in this study, including 69 Mamu-DQB1, 85 Mafa-DQB1 and 2 Aona-DQB1 alleles. Alleles detected in this study are shown in bold. IPD Acc No. is accession number in the IPD-MHC Database (http://www.ebi.ac.uk/ipd/mhc/).Click here for file