Meanwhile, we find genotypic penetrance to be historically stable with respect to depression. Our findings help inform our understanding of how the genetic and environmental landscape of American society has changed over the past century, and have implications for research which models gene-environment (GxE) interactions, as well as polygenic score calculations in consortia studies that include multiple birth cohorts.This study evaluates changes in genetic penetrance—defined as the association between an additive polygenic score and its associated phenotype—across birth cohorts. Situating our analysis within recent historical trends in the U.S., we show that, while height and BMI show increasing genotypic penetrance over the course of 20 This study evaluates changes in polygenic penetrance—defined as the association between a polygenic score (PGS) and its associated phenotype—across recent birth cohorts in the United States. The answer to this question informs our understanding of how the genetic and environmental landscape of American society has changed over the past century, and offers suggestive evidence for the selective influence of environment on genetic expression. Our findings also have important implications for PGS calculations in consortia studies that include multiple birth cohorts. This inquiry would not have been possible even a decade ago, before the development of PGS techniques to predict complex phenotypesth century in the U.S. Because the economic, social, and physical environments underwent dramatic changes during this period, it is likely that the association between a PGS and its related phenotype has also evolved as a consequence346789th century birth cohorts, education and heart disease exhibit the opposite trend. In contrast, the association between depression and its underlying genetic architecture remained stable over the same period.In the present paper, we exploit this opportunity by asking whether the associations between PGS and several phenotypes have changed over the course of the 20yi = f + εi), a complete analysis would require that we first know the partial derivatives of the unknown function f. Absent a specified model of f, many scholars, particularly in the social sciences, have attempted to inductively model gene-environment correlations (rGE) and interactions (GxE). Starting with the seminal paper in this area of scholarshipAdditive heritability (for which PGS penetrance is a proxy), independently of how it is measured, is contingent on the social structure. Indeed, heritability is not a fixed parameter across time and place but is always a ‘local perturbation analysis'th century, the underlying genotype signifying a greater propensity to smoke exerted a more pronounced influence on behavior.A few exceptions to this trend include studies that deploy nationally-representative, genome-wide data with controls for principle components in order to address population stratification on the genetic side while econometrically exploiting natural experiments on the environmental side to assure exogeneity of environment16Other research shows a similar historical shift in genomic influence on physical characteristics, with increasing associations between genetic architecture and BMI in recent decades for US adults18Some have argued that these changes reflect the relative increase of genetic over social factors as determinants of complex behavioral traits like smoking, rather than a true increase in the causal association between genetic polymorphisms and phenotypes. This distinction is important because it emphasizes genetic penetrance rather than expression, per se. That is, the social and historical context can, at times, mask small genetic associations because the environment may be ‘pushing’ the phenotype, which limits our ability to observe penetranceth century among U.S. adults. Respondents were born between 1919 and 1955 and, on average, went on to complete over 13 years of education. Nearly 40% of the respondents self-reported heart disease. Baseline associations between the five traits and their respective polygenic scores . Details about inclusion in the sample and selective attrition can be found in the c scores  are signWe interacted the PGS for each trait with birth year to predict the corresponding phenotypes in 18One potential explanation for these trends in PGS penetrance could be due to changes in the genetic variation in the population that could result from differential fertility and/or genetic assortative mating2223The twentieth century witnessed massive shifts in the social and nutritional environment of the United States. The change from an agrarian society to an industrial and post-industrial one has well documented effects on population healthAs nutritional deprivation receded as a restraining force on genetic expression, height and weight could more “accurately” reflect underlying genetic potential as measured by common SNPs. Meanwhile, educational “abundance” had the opposite effect: with the steady expansion of schooling we find that rather than constraints on the full extent of ability being lifted to reveal increasing genetic penetrance, we observed declining genetic prediction among more recent cohorts. During this time, secondary schooling became nearly universal and post-secondary education more common, yet the genetic signal was weakened. Thus, in some cases—like height and BMI— environmental barriers can act to suppress genetic effects, while in others (such as education) such obstacles can act to accentuate genetic associations. This may be a useful dichotomous classification scheme to apply to cohort analysis of genetic influence on other phenotypes going forward.Phenotypes were computed based on RAND Fat Files, version N (which covers data collection up until 2012). We examined:Education: Total years of educational attainment.BMI: Mean BMI over all available waves.Height: Max height over all available waves.Heart Disease: Whether a respondent ever reports heart problems (rXheart).Depression: Mean CESD score over all available waves. This variable had a skewed distribution, so it was transformed via the logarithm (after adding one to everyone’s mean).Sample descriptives are shown in Table S1.Polygenic Scores (PGSs) were first suggested in 2007 as flexible tools for quantifying the genetic contribution to a phenotype313233n) of the number of reference alleles x  at that SNP multiplied by the score for that SNP 6789where SNPs with relatively large p-values will have small effects (and thus be down weighted in creating the composite), so we do not impose a p-value threshold. Loadings were summed across the SNP set to calculate the polygenic score. The score was then standardized to have a mean of 0 and SD of 1 for ease of interpretation . Genetic analyses were done using the second-generation PLINK softwareHuber-White correction for the non-independence of spousal pairs does not change results see .How to cite this article: Conley, D. et al. Changing Polygenic Penetrance on Phenotypes in the 20th Century Among Adults in the US Population. Sci. Rep.6, 30348; doi: 10.1038/srep30348 (2016).


The word “Ctenomyidae” is misspelled in the article title. The correct title is: Genetic pool information reflects highly suitable areas: the case of two parapatric endangered species of tuco-tucos (Rodentia: Ctenomyidae). The correct citation is: Galiano D, Bernardo-Silva J, Freitas TROd (2014) Genetic Pool Information Reflects Highly Suitable Areas: The Case of Two Parapatric Endangered Species of Tuco-tucos (Rodentia: Ctenomyidae). PLoS ONE 9(5): e97301. doi:10.1371/journal.pone.0097301There is an error in the fifth sentence of the first paragraph of the “Genetic data” segment of the Methods section. The correct sentence is: For C. lami, 27 locations were sampled, and the data are presented by the authors based on the four karyotypic blocks proposed for the species .There are errors in the first two sentences of the second paragraph of the “Genetic data” segment of the Methods section. The correct sentences are: Briefly, the geographical genetic structure of C. minutus was characterized by examining 276 individuals over the entire distributional range and using information from cytochrome oxidase I gene and control region sequences. For C. lami, a total of 166 specimens were sampled, using information from the same mitochondrial DNA markers.The authors would like to add the following sentence to the Acknowledgments section: “We are grateful to Carla M. Lopes for suggestions of corrections to the published version of the manuscript.”


Maximizing crop yield while at the same time minimizing crop failure for sustainable agriculture requires a better understanding of the impacts of plant breeding on crop genetic diversity. This review identifies knowledge gaps and shows the need for more research into genetic diversity changes under plant breeding.Modern plant breeding has made a profound impact on food production and will continue to play a vital role in world food security. For sustainable agriculture, a compromise should be sought between maximizing crop yield under changing climate and minimizing crop failure under unfavorable conditions. Such a compromise requires better understanding of the impacts of plant breeding on crop genetic diversity. Efforts have been made over the last three decades to assess crop genetic diversity using molecular marker technologies. However, these assessments have revealed some temporal diversity patterns that are largely inconsistent with our perception that modern plant breeding reduces crop genetic diversity. An attempt was made in this review to explain such discrepancies by examining empirical assessments of crop genetic diversity and theoretical investigations of genetic diversity changes over time under artificial selection. It was found that many crop genetic diversity assessments were not designed to assess diversity impacts from specific plant breeding programs, while others were experimentally inadequate and contained technical biases from the sampling of cultivars and genomes. Little attention has been paid to theoretical investigations on crop genetic diversity changes from plant breeding. A computer simulation of five simplified breeding schemes showed the substantial effects of plant breeding on the retention of heterozygosity over generations. It is clear that more efforts are needed to investigate crop genetic diversity in space and time under plant breeding to achieve sustainable crop production.The online version of this article (doi:10.1007/s00122-015-2585-y) contains supplementary material, which is available to authorized users. Plant breeding since the early 1900s has made a profound impact on food production and will continue to play a vital role in the world food security Borlaug . HoweverEfforts have been made over the last three decades to assess crop genetic diversity using molecular marker technologies. These assessments have generated considerable knowledge about the extent and nature of genetic diversity present in conserved and/or actively utilized germplasm of various crops  Why diversity assessments have often not revealed diversity reduction from modern plant breeding? (2) Does plant breeding truly reduce crop genetic diversity? (3) How much is known theoretically about genetic diversity changes under artificial selection? and (4) What research is needed to fill the knowledge gap in this area of study? We have organized the review to address these questions with our arguments and thoughts.Over the last three decades, concerns have been expressed about crop uniformity Duvick  and therFu  reviewedvan de Wouw et al.  reviewedRauf et al.  reviewedIt is clear that no consensus has been reached on the overall impact of modern plant breeding on crop genetic diversity. The temporal patterns of crop genetic diversity are largely inconsistent with our perception that modern plant breeding reduces crop genetic diversity Gepts  and are Plant breeding since 1900s has had a profound impact on food production through developing and deploying new cultivars on a worldwide basis Borlaug . New culCrop breeding has been largely aimed at the improvement of yield, adaptation, resistance to biotic and abiotic stresses, and end-use quality. However, breeding objectives have changed over the years beyond yield improvement. New cultivars need to be developed with the capacity to achieve high yields in reduced chemical-input systems and with the genetic diversity needed to maintain yield stability under fluctuating climatic conditions . Genetic variation among populations, reflected in the differences in allele and genotype frequencies, is frequently measured using several different metrics. They are (1) Fst and analogs; (2) genetic distance such as Nei’s D; and (3) sequence divergence  schemes over many generations  due to genetic drift alone isq0 is the initial allele frequency, N is the population size, and t is the generation (Hedrick q = 0.1 or 0.4) is predicted to reduce over generations in a population of size (N = 20 or 50). These predictions were empirically confirmed with some Drosophila experiments  over generations of artificial selection with a finite population (see the Eq. (5) of Silvela s, 1 + sh, 1 for AA, Aa, aa genotypes), we can formulate his derived heterozygosity as below:s is the selection coefficient, and h is the level of dominance.The single-locus theory of selection in a finite population was formulated by Kimura in q = 0.4) in a smaller population (N = 20) will be reduced over generations, but could be increased in a larger population (N = 50). However, the expected heterozygosity for a favorable allele of low frequency (q = 0.1) in a small population can be maintained or increased over generations, depending on the type of alleles (or the level of dominance h). Both the population size and selection coefficient work in the same direction to enhance the heterozygosity changes (either decrease or increase) over generations. Generally, heterozygosity for a neutral allele in a small population will be reduced over generations, but those for a selective allele can be increased or decreased, depending on the initial frequency and type of alleles.To understand the changes of expected heterozygosity over generations of directional selection in a finite population, Eq.  was specHowever, a little is known about the heterozygosity changes in a multi-locus system with linkage, epistasis, and inbreeding , weakly recessive , strongly recessive , weakly additive , strongly additive , weakly dominant , and strongly dominant . Two progeny sizes  were used. Thus, there were 14 combinations for each breeding scheme.For the breeding scheme Self, the simulation started with a parental generation of two unrelated individuals for each replicate. For this pair of parents, one of the four initial alleles at each locus was randomly designated as having a selective disadvantage as a homozygote; the other three alleles had no disadvantage and were selectively equivalent. From each mating, progeny of given size were generated. For each progeny, the genotype was determined, locus by locus, by randomly choosing one of two gametes  from each of two parents to form a zygote. For each genotype, the numbers of homozygotes and heterozygotes of alleles were counted over loci, from which the relative genetic value of a progeny for the trait of interest was determined using Eq. , in combFor the other breeding schemes, the same procedures as in Self were applied, but they differed in the use of two parental individuals heterozygous for all the loci to form two full-sib families and the selection of the two progeny with the largest genetic values for the trait as the parents of the next generation from each full-sib family, as described in the breeding schemes above. The simulations were done with an R script , while decreased the genetic diversity with reduced heterozygosity (Table S2). For example, the parental heterozygosity approached zero after seven successive selfings Fig. b. Third,Concerns about crop uniformity and the possible risk of crop failure Ullstrup  have conFirst, a standardization of crop genetic diversity assessments should be sought to avoid technical biases identified in this review and applied for more informative assessment of genetic diversity dynamics FAO . It is tSecond, continuous assessments on crop genetic diversity using advanced genomic techniques are needed to facilitate the effective monitoring of newly released cultivars and on-farm crop diversity. This could be done with an assay of cultivars released over time from specific breeding programs and quantification of diversity changes. More emphasis should be given to the assessments of crop genetic diversity at the breeding program and farm levels, and less on country or world scale. More can be learned from the temporal diversity analysis of long-term public and commercial breeding programs such as the Illinois long-term maize selection experiment and Pioneer Hi-Bred International maize improvement program. Empirical assessments of genomic response to artificial selection like those in animal breeding


Odocoileus hemionus), we combined genetic and ecological data to (i) examine correlations between genetic differentiation and migration timing, (ii) screen for mitochondrial haplotypes associated with migration timing, and (iii) test whether nuclear heterozygosity was associated with condition. Migration was related to genetic differentiation  and mitochondrial haplogroup. Body fat was related to heterozygosity at two nuclear loci (with antagonistic patterns), one of which is situated near a known fat metabolism gene in mammals. Despite being focused on a widespread panmictic species, these findings revealed a link between genetic variation and important phenotypes at a fine scale. We hypothesize that these correlations are either the result of mixing refugial lineages or differential mitochondrial haplotypes influencing energetics. The maintenance of phenotypic diversity will be critical to enable the potential tracking of changing climatic conditions, and these correlates highlight the need to consider evolutionary mechanisms in management, even in widely distributed panmictic species.The relationship between genetic variation and phenotypic traits is fundamental to the study and management of natural populations. Such relationships often are investigated by assessing correlations between phenotypic traits and heterozygosity or genetic differentiation. Using an extensive data set compiled from free-ranging mule deer ( Understanding variation in phenotypic traits related to fitness in wild populations is fundamental to the study of evolution and ecology. Such traits can be related to genetic variation at relatively fine spatial scales, and knowledge of these relationships can provide insight into important eco-evolutionary processes such as inbreeding depression, local adaptation, population structure, and speciation  divergence have been identified across taxa and appear to be relatively robust (Shafer and Wolf Cervidae) are an ecologically important group of ungulate that have been the focus of numerous investigations into the relationship between genetic variation and phenotypic traits. Da Silva et al. (Capreolus capreolus L.) survival was correlated with MLH; likewise, red deer (Cervus elaphus L.) birth weight, neonatal survival, and lifetime breeding success increased significantly with heterozygosity , and genetic data to (i) examine whether genetic differentiation was correlated with migration timing, (ii) screen for specific mitochondrial haplotypes associated with migration timing, and (iii) test whether heterozygosity (multilocus and single locus) was associated with body mass and fat. We discussed the results in light of the phylogeographic history of mule deer and the metabolic role of the mitochondrion and highlight the importance of considering evolutionary processes in the management of this species.We captured adult >1 year old) female mule deer using helicopter net gunning in four winter range study areas in the Piceance Basin of Northwestern Colorado . We assumed an admixed model with correlated allele frequencies , we constructed a minimum-spanning tree among haplotypes using sensu Shafer and Wolf Both migration and body condition are phenotypic traits that are important to the fitness of mule deer. However, only condition can be thought of as a proxy for fitness. Thus, we used two separate analytical frameworks to examine genetic correlations with these traits. For migration, we examined the relationship between mitochondrial haplotypes and genetic differentiation to determine whether there was a genetic component to the timing of migration . Migration was demarcated as the time period during which deer travelled between their winter and summer home ranges. Home ranges were determined by outlining a minimum convex polygon around all locations that occurred prior to directed movement, without return, away from the summer or winter range areas.After GPS radio collars were recovered and data were downloaded, we calculated the initiation and termination dates of spring and fall migration  in r| > 0.7) and age was standardized r3.0.1  and the dates of spring and fall migrations. For this analysis, we corrected the Julian date of migration to the earliest date among all individuals. The resulting data represented a count of the number of days since the earliest arriving or leaving migrant had terminated or initiated their migration. These data were analyzed using negative binomial regression (see Appendix S3 for model formulation). We included covariates for the mtDNA haplogroup to which each deer was assigned  as well as a covariate for the age of the animal and binary covariates indicating winter range study area . Before models were run, correlations among covariates were examined to assess collinearity  between each individual's migration termination or initiation dates leaving us with four matrices representing differences in migration timing for spring and fall. The relationships between relatedness indices (QG and coancestry) and migratory behavior (dates) were evaluated in g2, where a value of zero means no variance in inbreeding  using the HFC framework. We fit hierarchical  models in a Bayesian framework. The presence or the absence of a relationship was determined by examining the posterior probability distributions of each coefficient to determine the probability that either MLH or heterozygosity at any single locus was related to condition. In all models, we included covariates for either MLH or SLH, the age of the animal, a binary variable for if the data came from a March capture (both mass and fat are expected to be lower in March), and binary variables indicating which of the four winter range areas the deer was captured in . We tested between models with solely a linear effect or a quadratic effect of age using the deviance information criteria , while beta regression was used because it is proper for dependent variables ranging between 0 and 1 as percent body fat does. Because there were multiple condition measures for certain deer , for both analyses, we allowed the intercept to vary by individual, estimating a population-level intercept , with all other coefficient values fixed. See Appendix S3 for details of model parameters and convergence assessment. To assess the fit of the models, we calculated residuals  and plotted them against the fitted values to examine any potential patterns in residuals.http://datadryad.org/resource/doi:10.5061/dryad.3vc1b). All markers were in Hardy–Weinberg Equilibrium, and there was no evidence of linkage (diversity statistics by loci are presented in Appendix S2). The structure-based analysis of the microsatellites suggested a single, homogenous population was most likely . Based on winter range, FIS values were as follows: NR = −0.05 (P = 0.02), NM = −0.02 (P = 0.16), RG = −0.03 (P = 0.07), and SM = 0.01 (P = 0.31). The mol_coan analysis produced a matrix of pedigree-like coefficients for all individuals; we note the one suspected mother–daughter pairing had a coefficient of 0.50, suggesting the results were indeed reflective of pedigree data. We sequenced the mitochondrial control region in a subset of animals (n = 81). For comparison with data from Latch et al. . Deer ranged in age from yearlings to more than 11 years old, with a median age of 5.5 years old (See Appendix S5). All 134 deer were genotyped at 17 loci producing a data set that was 99% complete ; however, MLH was a poor predictor of both body mass and fat in all models (Appendix S5 Table 2), while heterozygosity at individual loci was strongly related to condition measures , both primers colocalized with 100% identity to a region with the closest known gene being that of TBC1D1. Interestingly, this gene regulates cell growth and differentiation and has been shown to influence fat metabolism in mice and humans , a slight disruption of co-adapted alleles that are linked to fat metabolism could explain the negative correlation between this locus and fat . This is predicted to outcome when locally adapted lineages mix, and it has been recently suggested for grizzly bears in an area where they are subject to large-scale human-assisted migration  is the most likely to be genuine. However, given the concern over spurious HFCs, we must still consider the possibility of Type I errors . The potential for type I errors is of particular concern when detecting local effects and examining multiple models  in this species. These results have potential management implications for mule deer, which are under substantial human pressure from a multitude of stressors (Sawyer et al.


However, they share an association with the dead wood (saproxylic) habitat. Spatial patterns of intraspecific genetic diversity partly conform to topography-based divisions that circumscribe five ‘microgeographic regions’ at Tallaganda. In synthesizing population processes and past events that generated contemporary spatial patterns of genetic diversity in these forest floor invertebrates, we highlight cases of phylogeographic congruence, pseudo-congruence, and incongruence. Finally, we propose conservation-oriented recommendations for the prioritisation of areas for protection.The interaction between physiogeographic landscape context and certain life history characteristics, particularly dispersal ability, can generate predictable outcomes for how species responded to Pleistocene (and earlier) climatic changes. Furthermore, the extent to which impacts of past landscape-level changes ‘scale-up’ to whole communities has begun to be addressed via comparative phylogeographic analyses of co-distributed species. Here we present an overview of a body of research on flightless low-mobility forest invertebrates, focusing on two springtails and two terrestrial flatworms, from Tallaganda on the Great Dividing Range of south-eastern Australia. These species are distantly-related, and represent contrasting trophic levels ( With a basic understanding of species’ biology and landscape history, the analysis of present-day spatial patterns of genetic diversity can yield insights into past evolutionary processes . PhylogeGeographic areas that retained multiple refuges and were not extensively glaciated during Pleistocene climatic cycles are excellent natural laboratories for studying impacts of past climate change on regional biota. This is because each refuge area represents a semi-independent replicate from which phylogeographic inferences can be drawn, thereby permitting a greater appreciation of inherent variability in species’ responses . Substani.e., those that depend on dead wood microhabitats such as rotting logs) are exceptionally useful for detecting fine-scale geographic patterning resulting from long-acting processes such as climatic cycles, because viable populations can persist in isolated refugia too small to support vertebrates [Limited dispersal ability facilitates historical inference ,33, and tebrates ,36,37,38tebrates , and logtebrates ). Even ftebrates , which ftebrates , encompatebrates , and ofttebrates .in situ over long periods within local, stable refuges that repeatedly served as centres for the retention of biodiversity. Some support for the latter scenario is provided by biogeographic and phylogeographic studies of moist-forest-dependent amphibians, reptiles and invertebrates from the Great Dividing Range of south-eastern Australia [In contrast to the boreal landscapes of Europe and North America , Australustralia ,53,54,55c. 100 km (north-south) by 3–17 km (east-west) forested region is bounded to the east and west by the ancient Shoalhaven and Murrumbidgee valleys, and to the north by the Lake George basin, all of which supported grassland rather than forest throughout the Pleistocene and to the present [c. 19 glacial-interglacial cycles of the Pleistocene [Tallaganda, comprising Tallaganda State Forest and National Park, Badja State Forest, and parts of Gourock and Deua National Parks, lies on the Gourock Range—a physiographically isolated section of the Great Dividing Range. This  present ,57. Duriistocene ,59, moisistocene .Because the Great Dividing Range has a long history of geological stability , land forms have been preserved . This toTwo overarching questions have been pertinent throughout the invertebrate comparative phylogeography research program at Tallaganda: to what extent does topography, particularly drainage networks, predict spatial-genetic patterns within species, and did historical climatic cycles promote the similar responses among distantly-related species? These broader questions are being addressed via the following set of four spatially and/or temporally explicit predictions that are applicable to, and testable in, all members of the forest floor community at Tallaganda.Prediction 1: Given the long-term stability of Tallaganda’s topography, five a priori regions delineated partly on the basis of drainage divisions will harbour distinct gene pools of low mobility forest floor invertebrates  have been clearly characterised. One represents a new genus and species in the subfamily Pseudachorutinae, and the other is a new species of Acanthanura in the subfamily Uchidanurinae (Acanthanura sp. herein). Both are unusually large (often >5 mm long), dorsoventrally-flattened, and graze on plasmodial slime moulds found inside moist, well-decomposed, large-diameter rotting logs [ing logs . They arFlatworms: The two species of flatworm, Artioposthia lucasi and Caenoplana coerulea , the Harolds Cross and Badja Regions are the most genetically diverse ( (6 loci ), each b diverse . Further diverse , their pAcanthanura sp. is divided into five distinct genetic clusters , boundary overlap analyses revealed slight but significant differences in the spatial locations of genetic breaks [priori region found to contain haplotypes from more than one major mtDNA clade. In particular, Acanthanura sp. has three well-supported major clades in the Eastern Slopes Region, and all are relatively early-branching in the outgroup-rooted tree [Acanthanura sp. are also early-branching and clearly the most phylogenetically distinct, suggesting that this lineage is of considerable age under neutral assumptions.NA clade ,76). Thec breaks . SequencFlatworms. Mitochondrial DNA sequences from Artioposthia lucasi reveal deep phylogeographic structure, with most sequences forming clades with non-overlapping spatial distributions, each restricted to Harolds Cross, Eastern Slopes or Badja Region [Artioposthia lucasi Eastern Slopes genetic group is similar to that of the a priori landscape model for Tallaganda, and also as expected, haplotypic diversity was quite high  glacial-interglacial cycles of the Pleistocene.Notwithstanding challenges in estimating absolute divergence times from molecular data ,79,80, Dighlands ). Indeedighlands ,76. Furtighlands  as abovecoerulea . AlthougThere is strong evidence for multiple, recurrent impacts of Pleistocene climatic cycles on phylogeographic structure of the two springtail species ,74,76, aAcanthanura sp. [a priori palaeoclimatic landscape model for Tallaganda may have broad utility for predicting patterns of local endemism in other wet-adapted saproxylic invertebrates.Set in the context of topographically heterogeneous, low- to moderate-elevation landscapes on the Great Dividing Range, Tallaganda seems to have harboured several moist forest refuges that supported viable populations of saproxylic invertebrates—refuges that were most likely retained in sheltered gullies ,57. As pnura sp. ). Indeednura sp. . There inura sp. , suggestex situ sources cannot be ruled out. However, our phylogeographic inferences have provided some indications of within-region refugia. For example, relatively deep sequence divergences among Badja Region mtDNA haplotypes seen in Pseudachorutinae sp. [Artioposthia lucasi [Atraxsutherlandi [Acanthanura sp. [Acanthanura sp. range expansion events originating within Badja Region [ex situ sources of genetic diversity seems particularly plausible for the highland water skink Eulamprus tympanum, which shows a marked phylogeographic break at the same geographic location as the aforementioned invertebrates, but it is not restricted to Tallaganda and has sufficient dispersal capabilities to permit relatively rapid recolonisation from moderate- to high-elevation southern refuges [Caenoplana coerulea [Badja Region is particularly notable both in terms of its uniqueness, and the abrupt transition between it and the more northern genetic populations seen in several of the taxa studied. This microgeographic region was predicted to have been treeless steppe during periglacial activity owing to its low elevation , and givinae sp. ,74, Artia lucasi , the funherlandi ,84, and nura sp. , are incnura sp. ,47,48. Fa Region  indicate refuges . Similarcoerulea .Acanthanura sp., the Pikes Saddle refuge(s) may have been particularly favourable over recent periods, as indicated by this region’s inferred role as a major source of migrants into the neighbouring Eastern Slopes Region [Acanthanura sp., of which it harbours a highly distinctive lineage [Euperipatoides rowelli from Anembo Region [Phylogeographic data indicate that Harolds Cross and Pikes Saddle Regions retained pockets of moist forest in the Pleistocene that acted as sources for local recolonisation following climatic amelioration ,77. In ts Region . Althoug lineage . Morpholo Region ,86 also We have highlighted cases of congruence in spatial patterns of genetic diversity seen among co-distributed invertebrates at Tallaganda  and appai.e., Harolds Cross Region) haplotypes as late branching. If we assume that phylogenetic sister lineages are likely to be geographic neighbours , then these contrasting patterns may indicate different geographic origins and spatial progressions of lineage emergence along the north-south axis of Tallaganda. There are also differences between members of the same taxon pair. In the springtails, Acanthanura sp. haplotypes from Pikes Saddle and Badja Regions are nested together in a well-supported monophyletic clade, yet no such higher-level relationship can be seen among Pseudachorutinae sp. haplotypes sampled from those same regions, based on the maximum likelihood estimate of the gene tree. That said, the latter phylogeny contains many short internodes, making the tree somewhat unstable, to the extent that topological congruence with the Acanthanura sp. tree cannot be rejected [Indications that similar spatial-genetic patterns may have emerged via different underlying processes come from a qualitative comparison of the topologies of outgroup-rooted mtDNA gene trees . For exarejected .Ne) over time for springtails and flatworms reveal subtly different demographic histories among co-occurring populations  and Artioposthia lucasi (yellow) show parallel moderate declines, whereas Pseudachorutinae sp.  seems to have been relatively constant  was sampled within the geographic range of purebreds, rather than at the centre of the contact zone itself. Overall, contemporary migration and among-population gene flow in Pseudachorutinae sp. and Acanthanura sp. appears to be limited, such that effective migrants are probably too few to counteract the effects of genetic drift. The role of incomplete pre- or post-mating isolating mechanisms in shaping genetic structures of the two springtail species requires further investigation.The locations of genetic contact zones do not coincide with marked environmental gradients, and so it is possible that the relatively narrow, abrupt phylogeographic breaks detected in the two springtail species persist via some level of endogenous selection. Tension zones are maintained by the opposing forces of selection against hybrids and dispersal of individuals . Thus, wet al. [Cryptocercus punctulatus from the southern Appalachians—a biogeographic landscape with a qualitatively similar palaeoclimatic history and topographic complexity as Tallaganda. For this rotting-log-adapted invertebrate, the absence of contemporary physical or ecological barriers to dispersal that coincide with contact zones implicates partial or complete reproductive isolation [Caledia captiva in south-eastern Queensland, Australia. At that site, F2 progeny were found to be completely inviable owing to arrested development during embryogenesis, and the high level of mortality was ascribed to the production of novel imbalanced recombinant genotypes in the F1 generation. Endogenous selection has also been proposed to account for fine-scale contact zones among subspecies of the neanurid Collembolon Monobella grassei in the eastern Pyrenees [Euperipatoides rowelli shows severe developmental abnormalities at one well-characterised hybrid zone [Reproductive isolating mechanisms that developed during long-term separation in montane forest refugia can preserve the signature of more ancient divergences following secondary contact. For example, Nalepa et al.  reportedsolation . While tsolation  identifisolation  identifiPyrenees , and at rid zone .et al. [A solid foundation of empirical research is central to mitigating negative anthropogenic impacts on genetic diversity . Saproxyet al.  showed tet al. ,15.comprehensive, adequate and representative’ (CAR) reserve system was established as a framework for sustainable forest management. The Regional Forest Agreement for southern New South Wales [i.e., 80 to 100-year) logging cycles, temporal continuity of large-diameter rotting logs cannot be assured [i.e., National Parks, Nature Reserves and Flora Reserves) are ‘representative’ of extant floristic biodiversity is also questionable, even at a coarse level of classification. For example, the Messmate-Brown Barrel forest league  is poorly represented in the reserve system. Conversely, the Scribbly Gum-Stringybark-Silvertop Ash (mainly dry sclerophyll forest types), and the Snowgum league (a limited range of cold-tolerant species with 10–20 metre canopies) are proportionately overrepresented at Tallaganda . Temporal continuity of large-diameter rotting log recruitment can be promoted by leaving some commercially over-mature trees standing, and using longer logging rotation cycles. Importantly, these measures need not compromise the ability of commercial forestry operations to generate an economic return on timber harvesting [Natural forest dynamics and ecological processes might be maintained in production forests if ‘low-impact’ management practices are adopted. Spatial connectivity of dead wood can be promoted by allowing fallen logs to decay rvesting . Indeed,rvesting ,105. Adarvesting ,108.a priori catchment-based microgeographic regions were detected. Partly concerted responses to Pleistocene glacial-interglacial cycles may be attributable to inherent features of species’ biology  together with a common landscape experience, underpinned by a shared reliance on cool and moist rotting log microhabitats.The identification of centres of biodiversity in distantly-related, co-distributed members of the same ecological community has conservation applications, particularly for prioritisation of areas for protection. Species with characteristics such as low mobility, high ecological specialisation, and long-term occupation of a region, are well-suited for inferring local landscape history via the genetic signatures of past range expansion and contraction, population divergence, and gene flow. Saproxylic invertebrates may be exceptional in their ability to recover fine-scale signal given that viable populations may persist in small forest refuges—refuges too small to support most vertebrates during Pleistocene ice ages. At Tallaganda, marked fine-scale population sub-structuring, large intraspecific divergences, and strong spatial associations between ancient phylogeographic breaks plus contemporary population boundaries with


Bactris gasipaes var. gasipaes) and two wild populations (Bactris gasipaes var. chichagui), their relationships and genetic structures. Two hundred plants of these 8 races were used and 18 plants of the two wild populations, one from the Magdalena River, Colômbia, and the other from the Xingu River, Pará, Brazil. Eight primers were used to generate RAPD markers, of which 124 markers with 101 polymmorphic. The observed heterozygosity was 0.38, with 93% polymorphism, both slightly greater than in earlier studies. The "gene flow medium" was 1.12 among the races of peach palm, which is explained by the distance between most breeds analyzed. These values are significantly larger than those of [Molecular markers were used to examine the genetic variability of eight landraces of peach palm (


Gobio) are widespread in Central Europe, the taxonomy of this group and the distribution of its species are still unexplored in detail. The aims of our study are to ascertain taxonomic composition and distribution of the former Gobio gobio superspecies in the inner area of the Carpathian Basin. Since the presence of cryptic species is suspected in this area, we examined the taxonomic and phylogenetic relationships of Central European Gobio taxa by sequencing the mitochondrial DNA control region (mtCR). Additionally, we characterized the genetic structure of 27 stream-dwelling gudgeon populations of this area by Amplified Fragment Length Polymorphism (AFLP). Results of mtCR analysis proved the presence of three species already known as G. obtusirostris (dominant in NW-Hungary), G. gobio (sporadic) and G. carpathicus (sporadic). Additionally, the analysis revealed the existence of one doubtful taxon, G. sp1 (dominant in NE-Hungary), and a new isolated haplogroup (dominant in SW-Hungary). Although Network analysis showed significant detachment among haplogroups, their genetic distances were quite small. Therefore Bayesian phylogenetic analysis showed weak nodal support for the branching pattern both for newly described haplotypes, and for the already accepted species. AFLP data showed distinct population structure and a clear pattern of isolation was revealed by distance of stocks. At the same time, level of separation was not affected by the altitudinal position of sites. Moreover we found three major clusters of populations which were separated according to hydrographic regions, and corresponded to the findings of mtCR analysis. Our results suggest the on-going speciation of gudgeons in the Carpathian Basin, however the separation of haplogroups seems to only be an intermediate phase. The discovered natural pattern seems to be only slightly influenced by anthropogenic impacts. Additionally our results put into question the suitability of the recently accepted within Gobio genus taxonomy.Although stream-dwelling gudgeons (Cyprinidae, genus:  Freshwaters are exceedingly diverse ecosystems, but at the same time they are extremely sensitive to habitat degradation and pollution With the increasing use of molecular techniques, it has become evident that many species formerly believed to have widespread geographical distribution can in fact be divided into numerous more or less discrete entities -so called cryptic or sibling species by Mayr Gobioninae subfamily (Fam: Cyprinidae), the common gudgeon Gobio gobio Linnaeus (1758), was known as the most widely distributed lentic gudgeon species in West Eurasia Gobio gobio was considered a common species in the waters of the Carpathian Basin for a long time G. gobio and suggested the occurrence of the Danube gudgeon, Gobio obtusirostris Valenciennes (1842) in the western region of the basin, and the Carpathian gudgeon, Gobio carpathicus Vladykov (1925) in the drainage system of River Tisza. Furthermore, Mendel et al. Gobio sp1) from the catchment of River Tisza, but the taxonomic position of this newly described taxon has not yet been firmly established. It is also important to note that the findings of Kottelat and Freyhof Gobio species to date, it included only a very limited number of samples from the Carpathian Basin and furthermore all of those samples originated from the edges of this region. The above mentioned Gobio taxa  are morphologically very similar G. gobio and the related species The type species of the G. gobio superspecies in the inner Carpathian Basin. Specifically, we (i) examine the taxonomic and phylogenetic relationships of Gobio taxa and the presence of cryptic species, and (ii) characterize the genetic structure of gudgeon populations with special attention paid to the effects of hydrological distance and elevation as possible forces facilitating genetic separation.This study aims to ascertain taxonomic composition and distribution of the former To unravel the taxonomic relationships of stream-dwelling gudgeons inhabiting the central area of the Carpathian Basin we use the same methodology and molecular marker  as was used by Mendel et al. Gobioninae subfamily is protected in Hungary. Electrofishing in protected areas and any procedure (collection and storage of tissue samples) to be applied to protected species are subject to authorisation in Hungary. Fin tissue collection and storage were approved by the National Inspectorate for Environment, Nature and Water, Hungary . Fish collected for this study were narcotized using clove oil. After fin tissue sampling, when they regained consciousness, they were returned to the wild. Field studies did not involve fish that were endangered .This study was carried out following relevant national and international guidelines pertaining to the care and welfare of fish. Collections were made by electrofishing, partially from sampling sites which are located within protected areas. Moreover, each species within the 2 catchment area). The structure of this drainage system is dendritic, with the Tisza River forming the central axis. All the studied watercourses connected to the middle section of the River Tisza All sampling sites were situated in the inner area of the Carpathian Basin, which belongs to the drainage system of the Danube River. Based on its topographic characteristics, the Hungarian part of Middle Danubian hydrosystem can be divided into two larger catchments and ten smaller sub-catchments  and 2. TGobio genus show notable phenotypic plasticity, we investigated only adult (>60 mm standard length) specimens characterised by Gobio gobio- like morphological features, such as dispersedly spotted dorsal and caudal fins, and with no epithelial crests on the scales situated on the predorsal region of the body Fish samples were collected between 2009 and 2012 by electrofishing from 27 sites across five sub-catchments of the Danube River and five sub-tributaries of the Tisza River , Fig. 1.Fin clips of 241 specimens were sampled and stored in 96% ethanol at −20°C until DNA extraction. DNA was isolated with a DNeasy Blood and Tissue kit , using 10–20 mg of fin tissue as per the manufacturer’s instructions. Quality and quantity of the extracted DNA were verified using a NanoDrop 2000c Spectrophotometer .CCCAAAGCAAGTACTAACGTC) and CR851 (TGCGATGGCTAACTCATAC) (2 (25 mM), 0.2 µl dNTPs (10 mM), 0.3 µl of each primer (20 µM), 2.0 µl template DNA, and 17.8 µl purified and distilled water in a final volume of 25 µl. Reactions were performed in a MJ Research PTC-200 Peltier Thermal Cycler under the following conditions: 95°C for 1 min, followed by 37 cycles of 94°C for 45 s, annealing at 52°C for 30 s, and an extension temperature of 72°C for 45 s, followed by a final extension at 72°C for 8 min. PCR products were purified from 1% agarose gel using the Millipore Ultrafree-DA DNA extraction kit. PCR products were sequenced on an ABI 3730XL sequencing machine by MWG-Biotech AG (http://www.mwg-biotech.com). Sequences were edited manually and aligned using the program Geneious 5.4 DNA of 168 out of 241 individuals (111 from the Danube River and 57 from the Tisza River catchments) were used for the amplification of the mitochondrial control region (mtCR). The sequences of mtCR were amplified by polymerase chain reaction (PCR) using the primers CR159 (CTCATAC) . PCRs weGACTGCGTACCAATTCA 3′), 0.5 µM Mse-C primer (5′ GATGAGTCCTGAGTAAC 3′) and 5 µL diluted, digested, ligated DNA. The PCR was started at 94°C for 2 min followed by 20 cycles of 94°C for 30 sec, 56°C for 1 min, 72°C for 1 min and a final elongation at 72°C for 7 min. Selective PCR was performed in a final volume of 20 µL containing AmpliTaqGold 360 Master Mix, 0.1 µM fluorescently labelled Eco-ACT primer (5′ 6FAM GACTGCGTACCAATTCACT 3′), 0.25 µM Mse-CTT primer (5′ GATGAGTCCTGAGTAACTT 3′), 2 µL PCR product from the pre-selective PCR. Cycling conditions of the touchdown PCR were as follows: enzyme activation at 94°C for 2 min followed by 13 cycles for 30 sec at 94°C, for 30 sec at 65°C and decreased by 0.7°C in each cycle, and for 1 min at 72°C, then 23 cycles for 30 sec at 94°C, for 30 sec at 56°C and for 1 min at 72°C, followed by 5 min at 72°C. Digestion, ligation and PCRs were carried out in a Gene Amp PCR System 9700 (Applied Biosystems). Fragment analysis was performed on an ABI 3130 sequencer  and data were analysed with Peakscanner v1.0 (Applied Biosystems). Electropherograms were automatically analysed with tinyFLP To verify the results of the mitochondrial CR sequencing, a complementary method, Amplified Fragment Length Polymorphism (AFLP), was carried out; which is a reproducible, PCR-based molecular genetic method Gobio haplotypes , Romanogobio banaticus (GenBank a.n.: EF427393), Sarcocheilichthys variegatus (GenBank a.n.: NC004694), Rhodeus ocellatus kurumeus (GenBank a.n.: AB070205). Thus the lenght of aligned sequence set was 666 bp. Bayesian phylogenetic analysis was conducted by Markov chain Monte Carlo method (B/MCMC), and it was performed in MrBayes 3.2 To construct the phylogenetic tree, the (652 bp long) sequence set analyzed in the Network analysis was aligned against further haplotypes used as outgroup taxa of varying putative phylogenetic depths  and fixation index, as a measure of population differentiation (Fst) from AFLP markers, were computed using the Bayesian ABC4F software is and Fst values of the studied populations (where N≥8) were compared with the altitude of the sampling sites by Spearman rank correlations. We calculated the membership probabilities of each individual for the different a priori groups  based on retained discriminant functions using cross-validation with Discriminant Analysis of Principal Components (DAPC) Higher level differentiation of Gobio gobio (100% similarity with the specimen: EU131542) and G. carpathicus (100% similarity with the specimen: EU131559) respectively. From the North Danubian region only three and from the Tisza River catchment a total of five haplotypes were displayed. The Middle and South Danubian regions were the richest in haplotypes. Moreover nine out of the 10 haplotypes found were unique to these regions , 55 as G. sp1 described by Mendel et al. G. gobio (haplogroup ‘D’) and two as G. carpathicus (haplogroup ‘F’)  , Table 4irostris . The resirostris  were simThe mean of the estimated Ln probability values from STRUCTURE analysis of the final matrix strongly increased between K = 1 and K = 3 and then consolidated at higher K values . The comis, Fst are given for each population where N≥8 in For population genetic analyses, data were used of those 21 populations  where N≥8. The average number of bands per specimen was 40.5±9.4 (ranging between 16.0 and 62.0). Base population genetic features as: P. loci %, UHe, Fis, and Fst) were not significantly correlated (p<0.05) with the altitudinal position of the sites.Within population genetic distance (GD), pairwise Φpt and pairwise Unbiased Nei Genetic Distances data are displayed in According to the results of Mantel tests, hydrological distances correlated significantly and positively both with Unbiased Nei genetic distances  and with the pairwise Φpt values  of the selected (N≥8) populations.Gobio species in the inner Carpathian Basin Gobio reveal high diversity, both taxonomically and from the population genetic standpoint, within this relatively small and well-connected catchment area. At the same time, the presence of more cryptic species is indicated and the fine-scale separation of the identified genetic lineages between sub-catchments supports the existence of ecological barriers and on-going speciation in Hungarian drainage systems.Our results only partially support the earlier assumptions of the taxonomic composition and distribution of Gobio haplotypes found in the inner Carpathian basin can be classified into the north European clade and all except one haplotype (G. gobio) belong to the north-eastern European subclade described by Mendel et al. , a doubtful taxon (G. sp1) and an additional, distinct haplogroup were distinguished from the study area.All of the G. carpathicus occurred in the Tisza River catchment, this area was dominated by the haplotypes of G. sp1 (G. gobio in the Carpathian Basin (in Cuhai-Bakony-ér). Furthermore, haplotypes of G. obtusirostris proved to be dominant only in the North Danubian region. A distinct, but highly diverse haplogroup (haplogroup ‘B’) was dominant in the Middle and South Danubian regions  haplotypes also occurred in the Middle Danubian region, their presence was restricted to only those sites that were in the vicinity of fish ponds and/or where trout  stocking occurred G. obtusirostris introductions with gamefish (trout) stocking and thus a secondary, anthropogenic contact between the phylogenetically separated haplogroups.Although some specimens characterised by CR01 (G. obtusirostris (1.31%±0.31%) and from G. sp1 (1.61%±0.17%), as an interspecific genetic divergence among some already accepted gudgeon species such as G. skadarensis and G. carpathicus (1.29%±0.18%) or G. skadarensis and G. ohridanus (1.38%±0.17%) , and did not clearly support the recently accepted within-genus taxonomy. Our results indicate that the reproductive isolation of these entities may have only began in the geohistorical recent past, presumably in the middle Pleistocene. Contrary to the findings of the Network analysis, Bayesian phylogenetic computations in most cases query the species level differentiation within the Gobio genus. This premise is supported by the fact that in the case of other fish species, e.g. topmouth gudgeon - Pseudorasbora parva , stone loach - Barbatula barbatula , and grayling - Thymallus thymallus , a similar or higher degree of differentiation among haplogroups is considered to be not more than subspecies level detachment G. insuyanus is the only taxon which fulfils the above mentioned criteria (Haplogroup ‘B’ showed similar genetic distances from the %±0.17%) . These dcriteria .is Fst, and GD) did not show significant differences among subdrainage basins. Moreover, none of these variables showed significant correlation with the altitudinal position (as a possible marker for population isolation due to differences in the habitat use of fish) of the sampling sites. In the case of basic population genetic parameters, the local environmental conditions and the degree of hydrographic isolation are likely to be more important than either the altitudinal position or the taxonomic arrangement of the inhabiting specimens.The values of basic population genetic parameters  may be attributed to the role of Danube River. At the other Danubian Regions the population structure was much more differentiated. For the Middle Danubian Region, notable differences were found among closely situated sites. Results of the mtCR analyses revealed the existence of a different haplotype (CR01) in addition to the assumed “native” haplotype group from this area  hybridisation Results of STRUCTURE analysis are in accordance with the results of mtCR sequence analyses. Both inferred the existence of three larger clusters/haplogroups within the Carpathian Basin. Furthermore, both analyses indicated the transitional position of Cluster 2/haplogroup ‘B’ between the Cluster 1/haplogroup ‘A’ and the Cluster 3/haplogroup ‘C’. The two specimens identified as analysis  which maGobio stocks were simultaneously changed by the growing hydrographical distances. This natural pattern is just slightly diminished by anthropogenic impacts.Mantel test results revealed a clear pattern of isolation by hydrographical distance. Taxonomic and population genetic differences of the studied Gobio “species” form an extremely diverse and variable group. At the same time explanation of the phylogenetic relationships and within-genus taxonomic features are still partly unresolved. Our results showed that because of the casual immigration and/or the accidental introductions, and the sympatric occurrences, the location of the collection site is not a convenient feature to discriminate these “species” occurring in Hungarian waters.Consequently, the genetic analyses confirmed the results of former analyses, which were based on mainly morphologic/morphometric variables Gobio entities form a relatively young phylogenetic group and that the genetic differences among them are not strong enough in most cases for species level differentiation. Moreover, considering the possibilities of interspecific and intergeneric hybridisation, the recent taxonomic partitioning of the Gobio genus needs re-evaluation. However, the discovered genetic diversity is probably very vulnerable. Since the separation of haplogroups seems to be only an intermediate phase of an on-going speciation and stream-dwelling gudgeons have specific environmental needs and a restricted habitat area at present, habitat alteration and accidental stocking may easily damage the integrity of haplogroups. Consequently, conservation actions should be implemented to preserve the exceptional diversity of this fish group.Our results indicate that these cryptic


Oxyria sinensis, a perennial plant endemic to the HHM. Sixteen chloroplast haplotypes were identified and were clustered into three phylogenetic clades. The age of the major clades was estimated to be in the Pleistocene, falling into several Pleistocene glacial stages and postdating the formation of the Mekong-Salween Divide. Range expansions occurred at least twice in the early and middle Pleistocene, but the spatial genetic distribution rarely changed since the Last Glacial Maximum. Our results suggest that temporary mountain glaciers may act as barriers in promoting the lineage divergence in O. sinensis and that subsequential range expansions and secondary contacts might reshape the genetic distribution in geography and blur the boundary of population differentiation created in the earlier glacial stages. This study demonstrates that Pleistocene climatic change and mountain glaciers, rather than the Mekong-Salween Divide, play the primary role in shaping the spatial genetic structure of O. sinensis.The formation of the Mekong-Salween Divide and climatic oscillations in Pleistocene were the main drivers for the contemporary diversity and genetic structure of plants in the Himalaya-Hengduan Mountains (HHM). To identify the relative roles of the two historical events in shaping population history of plants in HHM, we investigated the phylogeographic pattern of  Inferring the evolutionary causes that drive genetic diversity of a population over time and space has been one of the central topics in phylogeography12The Himalaya-Hengduan Mountains (HHM) have been recognized as one of the worldwide global biodiversity “hotspots”45679101012Sinopodophyllum hexandrumTaxus wallichianaTerminalia franchetii was believed to be geographically structured by the paleo-drainage re-arrangements rather than the modern drainage systems, highlighting the role of historical geologic events in shaping contemporary genetic distribution131992123249102627According to the geological hypothesis, a continuous population might have been broken into spatially isolated subpopulations when new mountains formed during the uplifts of the QTP approximately 40 million years ago (Mya). Those isolated subpopulations eventually evolved into genetically distinct lineages via the accumulation of genetic differences and via adaptation to the local environment. This hypothesis has been strongly supported by the geological, ecological and recent genetic evidence. The HHM serve as the southeast boundary of the QTP and include numerous northwest-southeast high mountains with deeply incised valleys and rivers resulting from the extensive uplift movement of the QTP starting 40 Mya910in situ263132112614234351010In contrast to the geological hypothesis, the climatic hypothesis attributes population genetic diversification and species diversity mainly to Pleistocene glacial cycling. Specifically, it is hypothesized that Pleistocene glaciers may have isolated populations into glacial refugia and promoted population differentiation and intra-specific diversification without apparent geological breaks291Oxyria sinensis Hemsley (Polygonaceae), which diverged from its sole sister species O. digyna in the genus Oxyria between 12 and 14 Mya19O. sinensis. Thus, in this study, we specifically aimed to test how the Mekong-Salween Divide formation and/or Pleistocene glacial-interglacial fluctuations affected the population history of O. sinensis.The two contrasting hypotheses to explain the causes of the high biodiversity in the HHM region have each been supported by a number of studies. However, they are not necessarily incompatible with each other. The effects of both historical events  may be tracked through the genomic imprinting of extant species in phylogeographic studies. Interestingly, up to now, most phylogeographic studies have focused on plants with shallow lineages, and the evolutionary history of these lineages primarily reflects the effects of Pleistocene climate changes3435O. digyna, O. sinensis is endemic to southwest China, with a center in the Hengduan Mountains, westward extension to the southeast Himalaya, and eastward extension to the east edge of the QTP (east QTP). There is a clear break in the distribution at the Mekong-Salween Divide, where the Mekong-Salween Divide appears to segregate O. sinensis into west and east populations  reveal the genetic diversity and geographic structure of contemporary O. sinensis populations; 2) reconstruct the demographic history of O. sinensis; 3) estimate the evolutionary consequences of the two historical events and assess their relative roles in shaping the contemporary genetic pattern of O. sinensis; and 4) infer the locations of the refugia in the Last Glacial Maximum (LGM) and regions of over-represented diversity that can help in the conservation and management of biodiversity in the HHM region.In contrast to the worldwide distribution of ulations . TypicalmatK haplotypes from 477 individuals in 38 populations . Clade A appeared to be a widely distributed clade, consisting of 8 unique haplotypes that were widespread throughout the region. Broadly, Clade B contained 5 haplotypes, including an unresolved haplotype H6 . After excluding the H6, Clade B was exclusively distributed in the east QTP. The H6 mainly occurred in the Hengduan Mountain region. Clade C contained three haplotypes, all of which occurred only in the Himalaya. The minimum-spanning network of these haplotypes produced a similar grouping pattern (The distinct  pattern .O. sinensis and O. digyna was approximately 13.79 Mya (95% HPD: 7.54–24.63 Mya) in the Miocene. This estimate is well consistent with an estimate based on the fossil record (12–14 Mya)27The estimated divergence time between GST = 0.611; NST = 0.662) was high. The high population differentiation was also supported by AMOVA and BARRIER analyses, as reflected by the distinct haplotype composition among the three geographic groups or the predicted phylogeographic groups. However, NST was not significantly higher than GST (P > 0.05), indicating a nonsignificant phylogeographic structure. This might be due to the discontinuous distribution of the shared dominant haplotypes  across different geographic regions. Furthermore, BARRIER predicted that a major phylogeographic structure existed between the HHM and the east QTP (HT = 0.791), contrasting the low degree of within-population diversity (HS = 0.308). The haplotype diversity (he) within populations varied from 0.000 to 0.833  showed a multimodal mismatch distribution  were reconstructed for the present and the LGM  and the Maximum glacial stage (0.6–0.8 Mya) in the early and/or middle Pleistocene3044304546O. sinensis. The Himalaya harbored three haplotypes on the basal clade, representing the eldest refugium. A number of populations which harbor high genetic diversity and abundant unique haplotypes were potential refugia during the cooling stages  indicate high population differentiation across the entire distribution of O. sinensis, but no significant phylogeographic structure was found based on a comparison of GST and NST (P > 0.05). The high geographic genetic differentiation primarily reflects the composition of the distinct haplotypes among the three geographic groups or the phylogeographic disjunction between the HHM and east QTP identified from BARRIER. The nonsignificant phylogeographic signal most likely occurred because of the discontinuous distribution of the common haplotypes  across different geographic regions. We detected the signatures of repeated regional expansions based on a combination of multiple statistical analyses, including Fu’s Fs and Tajima’s D statistics, BSPs, and hierarchical mismatch distribution. BSPs indicated that the population size had increased dramatically since 0.5 Mya  could be recognized as distinct genetic units, and merit further conservation recognition from a management perspective. Secondly, we found that the Himalaya harbor the highest genetic diversity, whereas the Hengduan Mountains harbor moderate diversity. This poses an urgent need that is of the highest priority for the conservation management. These locations include the Himalaya (populations 1–3), the central Hengduan Mountains , the south Hengduan Mountains , and the east QTP . In addition, we should note that only a few field samples were obtained in the Himalaya, implying a rather small natural population and a potential loss of genetic diversity of O. sinensis suggests that Pleistocene refugial isolation may have driven lineage divergence at spatio-temporal timescales and that later interglacial range expansions blurred the phylogeographic boundaries created in the early Pleistocene. Our results provide one of the few detailed maternal evolutionary histories of endemic plants with deep lineages and give important insight into the origin and maintenance of genetic diversity in a global biodiversity “hotspot” region.For plants originated in the Miocene on the QTP, their genetic structure could have been affected by the geological changes due to uplifts of QTP and glacial-interglacial oscillations during the Pleistocene since their speciation. Our phylogeographic analysis of Oxyria sinensis is a dioecious perennial herb endemic to the Himalaya-Hengdua Mountains (HHM) that can reproduce sexually via seeds and asexually via rhizomesO. sinensis were collected from 38 populations across its entire range between 2008 and 2011  following the manufacturer’s protocol. We amplified the chloroplast Muturase K (matK) gene using polymerase chain reactions (PCR), with a primer pair of matKAF  and matK8R . The PCR reactions were performed in a 25 μL reaction volume, containing 1.5 μL genomic DNA, 50 mM Tris-HCL, 1.5 mM MgCl2, 250 μg/mL bovine serum albumin (BSA), 0.5 mM dNTPs, 0.2 μM of each primer, and 0.75 units of Taq polymerase. Programmed amplification parameters were as follows: 4 min denaturation at 94 °C, then 35 cycles of 50 sec denaturation at 94 °C, 50 sec annealing at 53 °C, and 1 min 30 sec extension at 72 °C, and a final extension of 7 min at 72 °C. PCR products were purified before sequencing to remove excess primers and deoxynucleotide triphosphates using a TIAN quick Midi Purification Kit . Sequencing reactions were performed using ABI Prism Sequencing Ready Reaction Kit with the same primers as PCRs, and analyzed on the ABI 3730 genetic analyzer (Applied Biosystems).Genomic DNA was extracted from 20 mg of dried leaf tissue from each matK gene from a closely related Oxyria species (O. digyna)40O. sinensis sequences. All sequences generated in this study have been deposited in GenBank under accession numbers KJ159010–KJ159025.DNA sequences were aligned using CLUSTAL XmatK haplotypes and divergence times were jointly estimated through a Bayesian Markov Chain Monte Carlo approach implemented in BEAST v.1.7.2Oxyria is unknown, we used a range of mutation rates from 1.01 × 10−9 to 2.9 × 10−9 substitution/site/year (s/s/y) that are believed valid for chloroplast DNA of angiosperms overall575860ln likelihood scores. The GTR + I model was chosen and applied to all Bayesian inferences. Three independent Markov Chain Monte Carlo (MCMC) runs were performed, with each run starting a random tree for 200,000,000 generations, and sampled for every 1000 generations. Convergence of three independent runs was evaluated using Tracer v.1.5 (http://evolve.zoo.ox.ac.uk/), with an effective sample size (ESS) for all parameters larger than 100. The results in log files of multiple runs were combined using LogCombiner v.1.5.4http://beast.bio.ed.ac.uk/TreeAnnotator/). The tree was plotted using FigTree v.1.31 (http://tree.bio.ed.ac.uk/software/figtree/) and further graphically modified for publication using graphic design software CorelDRAW X6 .The genealogical relationships among matK haplotypes of O. sinensis using TCS 1.21To explore the genealogical relationships and their phylogeographic pattern, we also constructed the parsimonious networks for all HS) and among populations (HT), and two population differentiation parameters, GST and NST, were computed using the program PERMUT with 1000 permutationshttp://www.pierroton.inra.fr/genetics/labo/Software/PermutCpSSR). Geographic structure and genetic differentiation within and between geographical regions were statistically tested through analyses of molecular variance (AMOVA)HE) and nucleotide diversity (π) for geographic populations were also calculated using ARLEQUIN.The average haplotype diversity within populations (Demographic dynamics through time were inferred using Bayesian skyline plots (BSPs) in BEAST. The BSPs employ a coalescent approach to estimate the effective population size and its changes over piecewise coalescent intervalsDFS testt, in years) was estimated from the mutation rate (u) and number of generations since expansion (τ), using Rogers and Harpending’sut. The mutation rate u was calculated from the DNA substitution rate (μ), sequence length (k) and the generation time (g) of O. sinensis using the formula u = 2μkg. A generation time of 2 years and an average cpDNA mutation rate of 2 × 10−9 s/s/y were assumed5758Historical population expansions were tested using mismatch distribution analysis implemented in ARLEQUIN. The mismatch analysis compares the observed frequency distribution of pairwise differences among haplotypes with the expected from those under the parametric demographic expansion model. A uni-modal distribution of pairwise haplotypes difference is expected if a population has undergone a recent expansion, whereas a multimodal distribution suggests a population in equilibriumBARRIER v2.2O. sinensis. Environmental conditions including 19 bioclimate variables were downloaded from the WorldClim database (http://www.worldclim.org). Bioclimate layers were obtained in the 2.5 arc-minute resolution for the present and the LGM . Climate data from two general circulation model (GCM) simulations from the Community Climate System Model (CCSM)74Species niche modeligng (SDM) was conducted to examine the influence of Pleistocene climate changes on the geographic distribution of O. sinensis were compiled from our field study and the Chinese Virtual Herbarium . We obtained 205 hits by searching “Oxyria Sinensis” in the CVH (last visit on 10/10/2014), representing historical collections from 1906 to present. Exact geographic information was obtained from 81 records, i.e., the longitude and latitude coordinates were recorded by collectors. For those without geographical coordinates, we mapped their locations to the nearest county. After removing duplicates, we obtained 64 additional unique records from CVH. After merging the CVH and this study, a total of 102 records were included and subjected to the SDM.Distribution records of Biomod2” (http://cran.r-project.org/web/packages/biomod2/index.html) packages in R v. 3.0 (http://www.R-project.org/). For the MAXENT method, Maxent v 3.3.3khttp://www.cs.princeton.edu/~schapire/maxent/. Because all three methods require presence-absence data and O. sinensis lacks true absences records, we randomly generated 10,000 background pseudo-absence points. All three SDM modeling approaches were combined to construct the realized distribution model using an ensemble forecasting (EM) techniques to account for prediction uncertainty among different algorithms and outperform single models78We applied three algorithms to build the SDM – one regression methods: generalized linear models (GLM) and two machine learning methods: random forests (RF) and maximum entropy (MAXENT). Models were created for each algorithm to predict the effects of topography on species distribution. All three algorithms were implemented in “To evaluate model predictive performance, we randomly split the original dataset into two subsets, using 70% (training dataset) to calibrate each model and 30% (testing dataset) for model evaluation. We repeated the processes 30 times to obtain robust estimates of the SDM. The accuracy of the model performance was evaluated using three indices: the receiver operational characteristic (ROC), the True Skill Statistic (TSS) and Cohen’s Kappa (KAPPA). The ROC curve plots with true positive rate of model simulation as a function of the false positive rateO. sinensis. To compare the similarity of niches (or niche overlap) between the two ecological layers, we computed Schoener’s DI statistics82http://www.diva-gis.org/) and R 3.0.We obtained the projections for the LGM by applying the realized models fitted to the present conditions of How to cite this article: Meng, L. et al. Refugial isolation and range expansions drive the genetic structure of Oxyria sinensis (Polygonaceae) in the Himalaya-Hengduan Mountains. Sci. Rep.5, 10396; doi: 10.1038/srep10396 (2015).


Bcl-2, Bcl-xL, VEGF, cyclin D2, and E2F-1. By inhibiting the STAT3 signaling, SC99 induced MM cell apoptosis which could be partly abolished by the ectopic expression of STAT3. Furthermore, SC99 displayed potent anti-MM activity in two independent MM xenograft models in nude mice. Oral administration of SC99 led to marked decrease of tumor growth within 10 days at a daily dosage of 30 mg/kg, but did not raise toxic effects. Taken together, this study identified a novel oral JAK2/STAT3 inhibitor that could be developed as an anti-myeloma agent.The oncogenic STAT3 signaling pathway is emerging as a promising target for the treatment of multiple myeloma (MM). In the present study, we identified a novel STAT3 inhibitor SC99 in a target-based high throughput screen. SC99 inhibited JAK2-STAT3 activation but had no effects on other transcription factors such as NF-κB, and kinases such as AKT, ERK, and c-Src that are in association with STAT3 signaling pathway. Furthermore, SC99 downregulated the expression of STAT3-modulated genes, including  Mcl-1, Bcl-2, survivin [D-cyclins, E2F-1) [Signal transducer and activator of transcription 3 (STAT3) is an oncogenic transcription factor widely expressed in many tissues and plays an important role in regulating cellular activities. Being activated by a panel of stimuli, including cytokines, such as interleukin-6 (IL-6) , 2, and survivin –6, and c, E2F-1) , 8. In a, E2F-1) .+ bone marrow cells of primary MM patients [STAT3 is overexpressed in a broad range of cancers including hematological malignancies, including leukemia , lymphompatients  and the patients , includipatients . Currentpatients . A recenpatients .D-type cyclins including cyclin D1, D2 and D3 are key members in regulating cell cycle progress. Cyclin D2 (CCND2) was reported in more than 50% of MM cell lines and primary patient cells  and is aTo find out small molecule compounds that inhibit STAT3 activation and CCND2 transactivation, a luciferase reporter system driven by the CCND2 promoter containing a STAT3 response element was stably established in NIH3T3 cells and was applied to screen a Maybridge chemical library composed of 56000 compounds with unknown functions as described previously , from whTo investigate the effect of SC99 on the constitutive activation of STAT3, five MM cell lines with highly activated STAT3 were treated with SC99 (10 μM) or DMSO, followed by immunoblotting analyses against p-STAT3. As shown in Figure STAT3 activation leads to STAT3 dimerization and further is translocated to the nuclei where it exerts its transcriptional activity . To evalThere are 7 members in the STAT3 family, of which STAT1, STAT3 and STAT5 are associated with oncogenesis, to exclude the effects of SC99 on STAT1 and STAT5, MM cells were treated with SC99 for 24 hrs followed by immunoblotting analysis. It turned out that SC99 dose-dependently suppressed STAT3 phosphorylation, but had no effects on the p-STAT1 or p-STAT5 level Figure . TherefoSTAT3 is a transcription factor and it must enter nuclei to exert its activity after its activation. The above experiments showed that SC99 potently inhibited STAT3 activation, to further evaluate whether SC99 affected STAT3 nuclear translocation, an immunofluorescent assay was performed. Starved OPM2 cells were pre-treated with DMSO or SC99 followed by IL-6 stimulation for 20 min because IL-6 can trigger STAT3 phosphorylation and nuclear import . The immSeveral important signaling pathways are in association with STAT3 activation, including MAPK/ERK , PI3K/AKJAK2 is a key kinase activating STAT3, we therefore evaluated the effect of SC99 on JAK2. As shown in Figure To further evaluate whether SC99 could interfere with the JAK2 molecule, a computer modeling was performed. The results showed that SC99 was well docked into the ATP-binding pocket of JAK2 in which SC99 formed strong and stable hydrogen bond . On the 14th day, SC99 significantly slowed down tumor growth with a p value < 0.01 , penicillin (100 units/mL) and streptomycin (100 μg/mL) in an incubator humidified with 95% air and 5% COPrimary bone marrow samples were collected from the Department of Hematology, the First Affiliated Hospital of Soochow University, with the approval from the Institutional Review Board of Soochow University. Informed consent was obtained in accordance with the Declaration of Helsinki. Mono-nuclear cells were isolated by Lympholyte® Cell Separation  .A STAT3 luciferase construct (p-STAT3-luc) driven by a quadrupled STAT3 response element was obtained from Beyotime Biotechnology Institute . A cyclin D2 luciferase reporter plasmid was established in pGL4 vector (Promega) driven by a fragment of cyclin D2 promoter containing or lacking a STAT3 response element . A NF-κBThe plasmid p-STAT3.Luc was stably introduced into NIH3T3 cells which was used to screen Maybridge Chemicals  using a protocol as described previously under the robot assistance , 34, 35.SC99 is chemically named 2-(2-(3-chloro-4-fluorophenyl)hydrazono)-3-(4-chlorophenyl)-3-oxo-pro panenitrile. SC99 and its analogs were synthesized from 4-(trifluoro-methyl)benzoamine and 2-(2-thiopheneSulfonyl) acetonitrile. The detailed method was available in Specific luciferase constructs were transiently introduced into HEK293 cells using 25 KD polyethylenimine  as described previously . LuciferTo determine cell apoptosis, MM cells treated with SC99 were stained with Annexin V-fluorescein isothiocyanate (Annexin V-FITC) and propidium iodide  according to the manufacturer's instruction. Stained cells were analyzed on a flow cytometer . To determine cell cycle, MM cells after SC99 treatment was stained with PI and subsequent analysis on the flow cytometer as described previously .STAT3, total RNA was prepared from U266 cells and used for the synthesis of the first strand cDNA in a cDNA reaction system . The STAT3 gene was then cloned into a pcDNA3.1 vector with a Myc or a Flag tag using primers: 5′-CCCAAGCTTATGGCCCAATGGAATCAGCTACAG -3′ (Forward primer) and 5′-CATCTCGAGTCACATGG GGGAGGTAGCGCACT-3′ (Reverse primer). STAT3 siRNA was designed and provided by Genepharm Co. Ltd, Suzhou, China.To clone LigPrep module. The structure of JAK2 (PDB ID: 3UGC) was used as the initial structure. All crystallographic water molecules were removed, hydrogen atoms were added, and the structure was submitted to restrained minimization to relieve steric clashes using the OPLS2005 force field within the Protein Preparation Wizard in Schrodinger. The minimization was terminated when the root-mean-square deviation (RMSD) reached a maximum value of 0.3 Å. For the grid generation and ligand docking procedures, the default settings were used and the Glide module in the Schrodinger was employed for molecular docking [The structure of SC99 was constructed in Schrodinger (version 09) and then preprocessed with the  docking –39.2 (CCND2) was purchased from Santa Cruz Biotechnology, Inc. ; antibodies against Bcl-2, Bcl-xL, Caspase-3, STAT3, p-STAT3(Tyr705), c-Src, p-Src, JAK2, p-JAK2, E2F-1, AKT, p-AKT, ERK, p-ERK, mTOR, p-mTOR, and PARP were purchased from Cell Signaling Technology . Antibodies against VEGF, β-actin, α-tubulin, anti–mouse immunoglobulin G (IgG) and anti–rabbit IgG horseradish peroxidase conjugated antibody were purchased from R&D Systems . Anti-Myc antibody and GAPDH was purchased from Sigma .Cells after SC99 treatment were prepared for immunoblotting according to our previous method , 40. A sThe basic protocol for the analysis of p-STAT3 subcellular location was referred to our previous protocol . Briefly5/mL) from primary MM patients or healthy donors, a colony forming unit assay was performed as described previously [To assess clonogenic growth in bone marrow cells (6.25 × 10eviously . Cells teviously .Two MM xenograft models were established with human MM cell line JJN3 and OPM2, respectively, as described previously . Thirty vs. control cells or animals was determined by using the Student's t test. The minimal level of significance was P < 0.05.Statistical significance of differences observed in drug-treated


Rhizophora racemosa, a widespread species in the region. Genetic diversity was low to moderate and genetic differentiation between nearly all population pairs was significant. Bayesian clustering analysis, PCoA, estimates of contemporary migration rates and identification of barriers to gene flow were used and complemented with estimated dispersal trajectories of hourly released virtual propagules, using high-resolution surface current from a mesoscale and tide-resolving ocean simulation. These indicate that the Cameroon Volcanic Line (CVL) is not a present-day barrier to gene flow. Rather, the Inter-Bioko-Cameroon (IBC) corridor, formed due to sea level rise, allows for connectivity between two mangrove areas that were isolated during glacial times by the CVL. Genetic data and numerical ocean simulations indicated that an oceanic convergence zone near the Cameroon Estuary complex (CEC) presents a strong barrier to gene flow, resulting in genetic discontinuities between the mangrove areas on either side. This convergence did not result in higher genetic diversity at the CEC as we had hypothesized. In conclusion, the genetic structure of Rhizophora racemosa is maintained by the contrasting effects of the contemporary oceanic convergence and historical climate change-induced sea level rise.Mangroves are seafaring taxa through their hydrochorous propagules that have the potential to disperse over long distances. Therefore, investigating their patterns of gene flow provides insights on the processes involved in the spatial genetic structuring of populations. The coastline of Cameroon has a particular geomorphological history and coastal hydrology with complex contemporary patterns of ocean currents, which we hypothesize to have effects on the spatial configuration and composition of present-day mangroves within its spans. A total of 982 trees were sampled from 33 transects (11 sites) in 4 estuaries. Using 11 polymorphic SSR markers, we investigated genetic diversity and structure of  Ng et al. [et al. [Rhizophora species. Null alleles are relatively common in microsatellite analysis [Moderate genetic diversity was observed in the red mangroves of the Cameroonian coastline and there was a general trend of genetic diversity parameters, decreasing from north to south. This may indicate that the relatively smaller populations in the Lokoundje (Kribi site 10) and Ntem  estuaries, located on the south of this coastline, have lower effective population sizes. Genetic diversity is directly proportional to effective population size , 107. Se species , 111. Geanalysis  and theyanalysis . SignifiRhizophora propagules have quicker establishment chances and longer viability periods [The highest genetic diversity was observed in the BERI (site 8), BEK (site 3), and TIK (site 5) populations and this could be due to propagule supply from upstream populations into these seaward populations (BERI and BEK) . These t periods . Despite periods , low see periods . Hence, Rhizophora racemosa populations of the Rio Del Rey Estuary and those of the Cameroon Estuary complex. In contrast, our study illustrates how ocean features such as convergence zones in coastal areas can greatly influence the overall genetic structure in a particular region. The isolation by distance signals observed is likely isolation by resistance posed by the presence of an oceanic convergence zone, which was found to be an effective barrier to gene flow, hampering the exchange of propagules between populations at both sides of this barrier. Contrary to expectation, the convergence of two ocean currents did not result in higher genetic diversity at the Cameroon Estuary complex, likely as a result of ineffective overall dispersal.We found sufficient evidence to conclude that climate change-induced SLR in the recent past has created a corridor for gene flow between S1 FigSelecting the best K value using the Evanno method of delta K (a) and Ln(P) (b).(TIF)Click here for additional data file.S2 FigThe convergence zone of the two currents offshore of the Cameroon Estuary complex is clearly revealed.(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S1 Table(DOC)Significant migration rates are highlighted in bold. (DOCX)Click here for additional data file.S2 Table(DOC)(DOCX)Click here for additional data file.S3 Table(DOC)(DOCX)Click here for additional data file.


Esox lucius), based on the analysis of nearly 3000 individuals from 40 sampling sites using 22 microsatellites along the Lake Ontario – St. Lawrence River system (750 km) that locally presents diverse degrees of interannual water level variation. Genetic structure was globally very weak (FST = 0.0208) but spatially variable with mean level of differentiation in the upstream section of the studied area being threefold higher (FST = 0.0297) than observed in the downstream sector (FST = 0.0100). Beside interannual water level fluctuation, 19 additional variables were considered and a multiple regression on distance matrices model  revealed that water masses  and man-made dams  reduced genetic connectivity. Local level of interannual water level stability was positively associated to the extent of genetic differentiation . As water level variation impacts on yearly quality and localization of spawning habitats, our study illustrates how temporal variation in local habitat availability, caused by interannual water level fluctuations, may locally decrease population genetic structure by forcing fish to move over longer distances to find suitable habitat. This study thus represents one of the rare examples of how environmental fluctuations may influence spatial variation in the extent of population genetic structure within a given species.A growing number of studies have been investigating the influence of contemporary environmental factors on population genetic structure, but few have addressed the issue of spatial patterns in the variable intensity of factors influencing the extent of population structure, and particularly so in aquatic ecosystems. In this study, we document the landscape genetics of northern pike ( Landscape genetic studies have mostly focused on long-term processes that structure populations , are flowing side by side in SLR corridor with very limited mixing area so that those water masses lead to very contrasting fish habitat conditions CSL . Moreove, are floEsox lucius), one of the most widely distributed freshwater species in the northern hemisphere, is one of the most widely distributed in this system and largely influenced by the amount of shallow habitats at different stages of its life history. It is mainly sedentary and the raw data were treated with DATA COLLECTION v3.1.1. (Life Technologies) Genotypes were resolved using GENEMAPPER v.4.1 (Life Technologies).Genomic DNA was extracted from fins clips preserved in 95% ethanol using a salt extraction method  and observed (HO) heterozygosity with GENETIX v.4.05.2  and private allelic richness (Apr) over all loci standardized for smallest sample size (N = 20) with HP-RARE . We also assessed the stability of genetic structure as a function of sampling period (prior and during spawning period). Given the results of both AMOVAs (see Results section), temporal samples were pooled for further analyses.FST values were computed with GENETIX v.4.05.2  were plotted as a function of the shortest waterway geographic distance between sites . Thirdly, to assess the relative contribution of the retained variables to the model, a multiple regression on distance matrices model  as available environmental data were not sufficiently detailed for the LO region, and also because of the large sampling gap of 150 km between the upper and lower SLR, which is an important caveat for landscape genetics analysis  within each window. Mean pairwise FST values and mean interannual water level variation coefficients were plotted as a function of downstream waterway distance (from site 2) for each window. Moreover, mean pairwise FST values were plotted as a function of mean interannual water level variation coefficients for each window for both upstream (Ontario sector) and downstream (Quebec sector) of the Moses-Saunders regulation dam. Spearman correlation coefficients were assessed. When not mentioned otherwise, analyses where computed with R software . Mean FIS on all loci was low  and Hardy-Weinberg and linkage disequilibrium tests detected no consistent pattern (Table S2).Compared with other studies conducted in freshwater fishes, genetic diversity was modest and comparable among sampling sites . With a second AMOVA, significant but very weak variation was found between sampling periods relative to spatial structuring . Given this, temporal samples were pooled for further analyses.The AMOVA between 2009 and 2010 samples revealed variation between years which was 10 times smaller than the extent of spatial genetic structure . Pairwise FST values ranged between −0.0037 and 0.1123 (Table S6). The four annexes were the most divergent sites . IBD relationship was significant  but moderate for the whole study area . However, genetic divergence increased more steeply with waterway geographic distance within the Ontario sector  than within the Quebec sector  and waterway distance better explained the genetic distance within the former sector  than the latter sector .Given its geographic scale, the global extent of genetic structure across the whole study area (more than 750 km) was weak . Accordingly, global FST values were three times higher in the Ontario sector than in Quebec sector considering annexes  and excluding annexes .The spatial variation in patterns of IBD was also reflected by the geographic distribution of the first 20 barriers inferred by BARRIER , spring water conductivity  and interannual water level stability  were significantly correlated with pairwise FST values  exhibits low water level variability mainly due to natural lake topography, while the St. Lawrence River (SLR), narrower and fed by many important tributaries, exhibits high water level variations. Downstream Moses-Saunders regulation dam  we observed that interannual water level variation was negatively correlated to the extent of population genetic structure. Yearly localization and quality of spawning habitat were previously modeled as a function of annual water levels within lower SLR by Mingelbier et al. . This reSuch temporal habitat variability, in addition to habitat degradation and fragmentation from human activities, may impact the temporal stability and the extent of population structure, especially in areas that are more affected by water level variations. At a given locality, the more water levels vary interannually, the more suitable spawning habitats do not spatially coincide between years. It implies that depending on annual water level, available spawning habitat location and quality will vary from year to year. Consequently, adult northern pike ready to spawn may be unable to return to their previously suitable natal site which could be completely exundated during that year. In such a case, they would possibly seek an alternative suitable spawning area. This would hypothetically limit adult northern pike's ability to return to spawn at their natal site and, consequently, would impede the maintenance of a pronounced local population genetic structure. Genetic differentiation varied negatively as a function of interannual water level fluctuation that decreased from upstream to downstream, which may partly explain the weak population genetic structure in the Quebec sector (lower SLR). In the Ontario sector (LO and upper SLR), the much lower interannual water level variability may have favored the development of a stronger genetic structure because of a higher probability of homing to natal sites.Salmo trutta, Ostergaard et al. Gambusia holbrooki), when severe episodic drying events happens in the Everglades in Florida, individuals from different populations intermix in deep-water refuges during dry years where only patches of habitat are available  versus downstream (Quebec sector) part of our study area.Perca flavescens, Leclerc et al. Northern pikes tolerate a wide range of environmental conditions, but they choose their spawning habitat according to several environmental factors, including vegetation type and density, current velocity, water temperature, water depth, turbidity, and dissolved oxygen concentration , and much higher than populations of the Quebec sector (lower SLR) (FST = 0.005). Baltic Sea is an almost enclosed water body which does not experience major interannual water level variability as it is the case for the lower SLR, and this could partly explain the weaker genetic structure observed in this study. More generally, at a large geographic scale, low levels of population genetic structure have been reported for northern pike in connected habitats  and eight populations in Quebec sector (lower SLR). Thus, because the extent of genetic variance between sample groupings defined by BARRIER was significant and because it was about 10 times more pronounced than between sampling sites within them, we consider these groupings as the most likely genetically distinct pike populations in the study area. Even if these groupings are weakly differentiated, we propose them as populations units as our results refuted panmixia and the extent and pattern of genetic structure of these populations varied significantly and non-randomly as a function of landscape features. It is also important to remember that strong genetic connectivity may nevertheless translate into relatively weak demographic connectivity  which would allow increasing the precision  of estimations of genetic parameters for a better resolution of magnitude of genetic differentiation and connectivity (Allendorf et al.