NOGGIN gene - causing neither brachydactyly nor fibrodysplasia ossificans progressiva. This study highlights that a given genetic variation should not be considered pathogenic unless supported by functional analyses.We identified an amino acid change (p.G92E) in the Bone Morphogenetic Protein antagonist NOGGIN in a 22-month-old boy who presented with a unilateral brachydactyly type B phenotype. Brachydactyly type B is a skeletal malformation that has been associated with increased Bone Morphogenetic Protein pathway activation in other patients. Previously, the amino acid change p.G92E in NOGGIN was described as causing fibrodysplasia ossificans progressiva, a rare genetic disorder characterized by limb malformations and progressive heterotopic bone formation in soft tissues that, like Brachydactyly type B, is caused by increased activation of Bone Morphogenetic Protein signaling. To determine whether G92E-NOGGIN shows impaired antagonism that could lead to increased Bone Morphogenetic Protein signaling, we performed functional assays to evaluate inhibition of BMP signaling. Interestingly, wt-NOGGIN shows different inhibition efficacies towards various Bone Morphogenetic Proteins that are known to be essential in limb development. However, comparing the biological activity of G92E-NOGGIN with wt-NOGGIN, we observed that G92E-NOGGIN inhibits activation of bone morphogenetic protein signaling with equal efficiency as wt-NOGGIN, supporting that G92E-NOGGIN does not cause pathological effects. Genetic testing of the child's parents revealed the same amino acid change in the healthy father, further supporting that p.G92E is a neutral amino acid substitution in NOGGIN. We conclude that p.G92E represents a rare polymorphism of the  Xenopus laevis embryos caused excessive head development NOGGIN (NOG) is a secreted homodimeric protein. The name originates from the observation that high doses of NOG injected into ACVR1), a BMP type I receptor, in all classically affected individuals worldwide ACVR1 at position c.G617A leading to the amino acid change p.R206H is an activating mutation Imbalance between agonists, antagonists and receptors can result in BMP linked disorders. As NOG is especially important in bone development and function, NOG mutations are linked to several skeletal diseases that are characterized either by joint fusions and/or malformations of the phalanges ACVR1 mutations in FOP, defects in the BMP signaling pathway had been hypothesized to be responsible for FOP as BMPs regulate multiple steps in development and can induce heterotopic osteogenesis BMP4, and no mutations in BMP4 could be found in FOP patients NOG, a potent extracellular BMP antagonist, was also considered a candidate gene for FOP NOG expression in a negative feedback loop Previous to the identification of De novo mutations in the NOG gene in FOP patients were reported, including the same guanine to adenine substitution at nucleotide 275 leading to the amino acid change p.G92E that we identified in our patient NOG mutations in FOP NOG mutations have also been reported NOG.NOG activity assays have been successfully established to investigate the functional activity of NOG mutations in BDB2 patients rd to 5th digits with a rudimentary finger nail of 4th digit. Missing middle and distal phalanges and a hypoplastic proximal phalanx of the 4th finger as well as hypoplastic middle and distal phalanges of digits III and V were demonstrated by a hand radiograph  of the right hand and a negative family history Fig. 1. ROR2 and NOG. Sequencing revealed no mutation in the ROR2 gene, but a heterozygous substitution c.G275A, p.G92E in the NOG gene. Analysis of the healthy parents showed that the unaffected father also carried this substitution. Patient follow-up at the age of 4 years revealed that apart from the unilateral brachydactyly the boy was healthy and did not subsequently show any signs of FOP.The patient was tested for mutations in two candidate genes for BDB, The single residue substitution in p.G92E is located within an apparently highly flexible segment of the human NOG protein called the polyglycine loop that comprises amino acid residues 89–95 in vitro chicken micromass system to test whether this amino acid change might alter NOG function and potentially cause brachydactyly or FOP. Using a previously established assay for BMP-induced chondrogenesis in micromass cultures We investigated the G92E-NOG amino acid change in the We further investigated the ability of wt-NOG and G92E-NOG to inhibit the activity of a set of BMPs which are co-expressed during limb development NOG missense mutations in FOP, a rare but fatal genetic disorder, has been a matter of intense discussion for nearly a decade The clinical relevance of ROR2, whereas BDB2 is the result of mutations in NOG. As the patient described here presented with unilateral atypical BDB-like phenotype, sequencing of ROR2 and NOG was performed, revealing the nucleotide substitution c.G275A in the NOG gene resulting in the amino acid change p.G92E. A search through the Human Gene Mutation Database indicated that G92E-NOG is currently not associated with any type of brachydactyly but with FOP.We identified G92E-NOG in a 22-month-old patient with an atypical unilateral brachydactyly phenotype and in his healthy father. Brachydactylies represent a group of skeletal disorders characterized in general by shortened digits in hand and feet due to abnormalities in the developmental process of phalanges or metacarpals/metatarsals NOG and FOP, whereas Xu et al. excluded such a linkage between NOG and FOP and could not identify mutations of the NOG gene in a large cohort of FOP patients NOG published by Semonin et al. were subsequently challenged to be technical PCR errors due to the use of a nested PCR approach ACRV1 as the genetic cause of FOP in 2006, additional questions regarding the validity of NOG mutations in FOP were raised In 2000, Lucotte and colleagues reported a genetic linkage between NOG gene leading to p.G92E was described for two patients with FOP of Spanish origin. Of note, one of the patients was also positive for the p.R206H mutation in ACVR1, raising the question of the likelihood that two “pathogenic” mutations causing a genetic disorder as rare as FOP would be found in a single patient The nucleotide substitution c.G275A in the NOG gene previously described to be a cause of FOP Our patient with unilateral atypical BDB-like phenotype and his healthy farther were positive for the amino acid change c.G275A, p.G92E in the From a structural standpoint, the substitution in p.G92E is situated in the most flexible portion of the NOG protein, a segment not interpretable from the electron density maps of the 3D-structure determination Further, using experimental assays for BMP signaling, we did not identify differences between wild-type and mutant NOG protein to inhibit control chicken micromass cells Fig. 3. NOG. His malformation is more likely caused by an isolated local disruption of embryonic vessels during early development. Polygenic or multifactorial developmental disturbances rather than single gene germline mutations are thought to be the cause of many unilateral limb defects, especially with respect to hereditary monogenic types of brachydactylies as these generally manifest bilaterally http://evs.gs.washington.edu/EVS) 25 of 10129 alleles  are listed containing the G92E exchange The absence of differences between G92E-NOG and wt-NOG in our functional tests supports that the observed unilateral atypical BDB-like phenotype in our patient is not due to the polymorphism in NOG mutations described to cause FOP are evaluated through experimental tests. The necessity of such functional assays for the evaluation of putatively disease causing mutations was recently underlined by several studies. For example, genome information of Dr. James Watson by next-generation sequencing technology identified 20 mutations associated with increased disease risks without becoming manifest in the apparently healthy carrier Our analysis raises important issues with respect to genetic counseling. Since the G92E amino acid change in NOG is reported to be pathogenic for FOP in many databases, such as the Human Gene Mutation Database, parents could be wrongly informed that their child has a FOP causing mutation when, in fact, a neutral polymorphism has been identified. In our opinion it is imperative that this fact becomes common knowledge and noted in the relevant database, and further that other Clinical investigations have been conducted according to the principles expressed in the Declaration of Helsinki. Ethical approval of the study was given by the ethical board Charité. Written informed consent for genetic testing was received from all analyzed individuals or by parents on behalf of their child.ROR2) and NOG as well as the flanking intronic sequences were amplified by standard PCR protocols. The primer sequences and PCR conditions for the molecular testing were previously published  as a reference.Genomic DNA was extracted from peripheral blood samples by standard methods. The coding regions of tyrosine kinase-like orphan receptor 2 gene  BMP2, GDF5 and Bmp7 were cloned into RCAS(BP)A. Wild-type (wt)-NOG and G92E-NOG were cloned into RCAS(BP)B to allow co-expression of NOG with different BMPs. Cloning into retroviral vectors, production of viral supernatant in DF1 cells and concentration of viral particles was performed as described previously Mouse Chicken micromass cultures were primary isolated from limb buds of day 4.5 chicken embryos and performed as previously described Western Blot analysis was performed as previously described


Below we highlight some recent papers that use evolutionary biology to address questions of applied importance.s 109, no. 51: 20960–20965.doi:10.1073/pnas.1212536109.Sutter, D. A. H., C. D. Suski, D. P. Philipp, T. Klefoth, D. H. Wahl, P. Kersten, S. J. Cooke, and R. Arlinghaus. 2012 Recreational Fishing Selectively Captures Individuals with the Highest Fitness Potential. Proceedings of the National Academy of ScienceMicropterus salmoides) selectively bred over three generations for either high (HV) or low (LV) vulnerability to angling as a model system, we show that the trait “vulnerability to angling” positively correlates with aggression, intensity of parental care, and reproductive fitness. Our study constitutes experimental evidence that recreational angling selectively captures individuals with the highest potential for reproductive fitness. Our study further suggests that selective removal of the fittest individuals likely occurs in many fisheries that target species engaged in parental care. As a result, depending on the ecological context, angling-induced selection may have negative consequences for recruitment within wild populations of largemouth bass and possibly other exploited species in which behavioral patterns that determine fitness, such as aggression or parental care, also affect their vulnerability to fishing gear.Fisheries-induced evolution and its impact on the productivity of exploited fish stocks remains a highly contested research topic in applied fish evolution and fisheries science. Although many quantitative models assume that larger, more fecund fish are preferentially removed by fishing, there is no empirical evidence describing the relationship between vulnerability to capture and individual reproductive fitness in the wild. Using males from two lines of largemouth bass , to identify the overall structure and potential adaptive features of the dispensable and core components of the genome. We also performed population genetic analyses on the core genome of the species aimed at understanding the demographic history, and impact of selection shaping its genetic variation. The maximum gene content divergence among strains was approximately 23%, with the majority of strains diverging by 5% to 15%. The core genome consisted of 1490 genes and the pan-genome approximately 3296. Maximum likelihood analysis of the synonymous site frequency spectrum (SFS) suggested that the S. mutans population started expanding exponentially around 10,000 years ago , approximately coincidental with the onset of human agriculture. Analysis of the replacement SFS indicated that a majority of these substitutions are under strong negative selection, and the remainder evolved neutrally. A set of 14 genes was identified as being under positive selection, most of which were involved in either sugar metabolism or acid tolerance. Analysis of the core genome suggested that among 73 genes present in all isolates of S. mutans but absent in other species of the mutans taxonomic group, the majority can be associated with metabolic processes that could have contributed to the successful adaptation of S. mutans to its new niche, the human mouth, and with the dietary changes that accompanied the origin of agriculture.http://mbe.oxfordjournals.org/content/early/2012/08/31/molbev.mss198.short.Joseph, S. J., X. Didelot, J. Rothschild, H. J. C. de Vries, S. A. Morré, T. D. Read, and D. Dean. Population Genomics of Chlamydia Trachomatis: Insights on Drift, Selection, Recombination, and Population Structure. 2012Molecular Biology and Evolution. Chlamydia trachomatis has made this organism a World Health Organization priority for vaccine development. However, there is no gene transfer system for Chlamydia to help identify potential vaccine targets. To accelerate discoveries toward this goal, here we analyzed the broadest diversity of C. trachomatis genomes to date, including 25 geographically dispersed clinical and seven reference strains representing 14 of the 19 known serotypes. Strikingly, all 32 genomes were found to have evidence of DNA acquisition by homologous recombination in their history. Four distinct clades were identified, which correspond to all C. trachomatis disease phenotypes: lymphogranuloma venereum ; noninvasive urogenital infections (Clade 2); ocular trachoma (Clade 3); and protocolitis . Although the ancestral relationship between clades varied, most strains acted as donor and recipient of recombination with no evidence for barriers to genetic exchange. The niche-specific LGV and trachoma clades have undergone less recombination, although the opportunity for mixing with strains from other clades that infect the rectal and ocular mucosa, respectively, is evident. Furthermore, there are numerous occasions for gene conversion events through sequential infections at the same anatomic sites. The size of recombinant segments is relatively small (∼357 bp) compared with in vitro experiments of various C. trachomatis strains but is consistent with in vitro estimates for other bacterial species including Escherichia coli and Helicobacter pylori. Selection has also played a crucial role during the diversification of the organism. Clade 2 had the lowest nonsynonymous to synonymous ratio (dN/dS) but the highest effect of recombination, which is consistent with the widespread occurrence of synonymous substitutions in recombined genomic segments. The trachoma Clade 3 had the highest dN/dS estimates, which may be caused by an increased effect of genetic drift from niche specialization and a reduced effective population size. The degree of drift, selection, and recombination in C. trachomatis suggests that the challenge will remain to identify genomic regions that are stable and cross protective for the development of an efficacious vaccine.The large number of sexually transmitted diseases and ocular trachoma cases that are caused globally each year by http://www.biomedcentral.com/1471-2148/12/237Zhao, K., Y. Ishida, T. K. Oleksyk, C. A. Winkler and A. L. Roca. 2012. Evidence for selection at HIV host susceptibility genes in a West Central African human population BMC Evolutionary Biology 2012 12:237. HIV-1 derives from multiple independent transfers of simian immunodeficiency virus (SIV) strains from chimpanzees to human populations. We hypothesized that human populations in west central Africa may have been exposed to SIV prior to the pandemic, and that previous outbreaks may have selected for genetic resistance to immunodeficiency viruses. To test this hypothesis, we examined the genomes of Biaka Western Pygmies, who historically resided in communities within the geographic range of the central African chimpanzee subspecies (Pan troglodytes troglodytes) that carries strains of SIV ancestral to HIV-1.We found protective alleles or evidence for selection in the Biaka at a number of genes associated with HIV-1 infection or progression. Pygmies have also been reported to carry genotypes protective against HIV-1 for the genes CCR5 and CCL3L1. Our hypothesis that HIV-1 may have shaped the genomes of some human populations in West Central Africa appears to merit further investigation.Kause, Antti, and JørgenØdegård. 2012. The Genetic Analysis of Tolerance to Infections: a Review. Frontiers in Genetics 3:252. doi:10.3389/fgene.2012.00262.Tolerance to infections is defined as the ability of a host to limit the impact of a given pathogen burden on host performance. Uncoupling resistance and tolerance is a challenge, and there is a need to be able to separate them using specific trait recording or statistical methods. We present three statistical methods that can be used to investigate genetics of tolerance-related traits. Firstly, using random regressions, tolerance can be analyzed as a reaction norm slope in which host performance (y-axis) is regressed against an increasing pathogen burden (x-axis). Genetic variance in tolerance slopes is the genetic variance for tolerance. Variation in tolerance can induce genotype re-ranking and changes in genetic and phenotypic variation in host performance along the pathogen burden trajectory, contributing to environment-dependent genetic responses to selection. Such genotype-by-environment interactions can be quantified by combining random regressions and covariance functions. To apply random regressions, pathogen burden of individuals needs to be recorded. Secondly, when pathogen burden is not recorded, the cure model for time-until-death data allows separating two traits, susceptibility, and endurance. Susceptibility is whether or not an individual was susceptible to an infection, whereas endurance denotes how long time it took until the infection killed a susceptible animal (influenced by tolerance). Thirdly, the normal mixture model can be used to classify continuously distributed host performance, such as growth rate, into different sub-classes , which allows estimation of host performance reduction specific to infected individuals. Moreover, genetics of host performance can be analyzed separately in healthy and affected animals, even in the absence of pathogen burden and survival data. These methods provide novel tools to increase our understanding on the impact of parasites, pathogens, and production diseases on host traits.Attard, C. R. M., Beheregaray, L. B., Jenner, K. C. S., Gill, P. C., Jenner, M.-N., Morrice, M. G., Robertson, K. M. and Möller, L. M. 2012. Hybridization of Southern Hemisphere blue whale subspecies and a sympatric area off Antarctica: impacts of whaling or climate change? Molecular Ecology, 21: 5715–5727.doi: 10.1111/mec.12025Balaenoptera musculus) have two recognized Southern Hemisphere subspecies that show differences in geographic distribution, morphology, vocalizations, and genetics. During the austral summer feeding season, the Antarctic blue whale (B. m. intermedia) is found in polar waters and the pygmy blue whale (B. m. brevicauda) in temperate waters. Here, we genetically analyzed samples collected during the feeding season to report on several cases of hybridization between the two recognized blue whale Southern Hemisphere subspecies in a previously unconfirmed sympatric area off Antarctica. This means the pygmy blue whales using waters off Antarctica may migrate and then breed during the austral winter with the Antarctic subspecies. Alternatively, the subspecies may interbreed off Antarctica outside the expected austral winter breeding season. The genetically estimated recent migration rates from the pygmy to Antarctic subspecies were greater than estimates of evolutionary migration rates and previous estimates based on morphology of whaling catches. This discrepancy may be due to differences in the methods or an increase in the proportion of pygmy blue whales off Antarctica within the last four decades. Potential causes for the latter are whaling, anthropogenic climate change or a combination of these and may have led to hybridization between the subspecies. Our findings challenge the current knowledge about the breeding behavior of the world's largest animal and provide key information that can be incorporated into management and conservation practices for this endangered species.Understanding the degree of genetic exchange between subspecies and populations is vital for the appropriate management of endangered species. Blue whales  on intraspecific genetic variation. In this review, we highlight the importance of incorporating neutral and nonneutral genetic diversity when assessing the impacts of GCC, for example, in studies that aim to predict the future distribution and fate of a species or ecological community. Specifically, we address the following questions: Why study the effects of GCC on intraspecific genetic diversity? How does GCC affect genetic diversity? How is the effect of GCC on genetic diversity currently studied? Where is potential for future research? For each of these questions, we provide a general background and highlight case studies across the animal, plant, and microbial kingdoms. We further discuss how cryptic diversity can affect GCC assessments, how genetic diversity can be integrated into studies that aim to predict species' responses on GCC and how conservation efforts related to GCC can incorporate and profit from inclusion of genetic diversity assessments. We argue that studying the fate of intraspecific genetic diversity is an indispensable and logical venture if we are to fully understand the consequences of GCC on biodiversity on all levels.2 in a coastal dinoflagellate bloom: implications for interspecific competitive interactions and community structure. Evolution. doi: 10.1111/evo.12029Tatters, A. O., Schnetzer, A., Fu, F., Lie, A. Y.A., Caron, D. A. and Hutchins, D. A. 2013. Short- versus long-term responses to changing COpCO2  in an “acidified” ocean will affect phytoplankton community structure, but manipulation experiments with assemblages briefly acclimated to simulated future conditions may not accurately predict the long-term evolutionary shifts that could affect inter-specific competitive success. We assessed community structure changes in a natural mixed dinoflagellate bloom incubated at three pCO2 levels  in a short-term experiment (2 weeks). The four dominant species were then isolated from each treatment into clonal cultures, and maintained at all three pCO2 levels for approximately 1 year. Periodically , these pCO2-conditioned clones were recombined into artificial communities, and allowed to compete at their conditioning pCO2 level or at higher and lower levels. The dominant species in these artificial communities of CO2-conditioned clones differed from those in the original short-term experiment, but individual species relative abundance trends across pCO2 treatments were often similar. Specific growth rates showed no strong evidence for fitness increases attributable to conditioning pCO2 level. Although pCO2 significantly structured our experimental communities, conditioning time and biotic interactions like mixotrophy also had major roles in determining competitive outcomes. New methods of carrying out extended mixed species experiments are needed to accurately predict future long-term phytoplankton community responses to changing pCO2.Increasing Ambrosia artemisiifolia) in stressful and benign environments. Molecular Ecology. doi: 10.1111/mec.12179Hodgins, K. A., Lai, Z., Nurkowski, K., Huang, J. and Rieseberg, L. H. 2013. The molecular basis of invasiveness: differences in gene expression of native and introduced common ragweed (Ambrosia artemisiifolia) is an annual weed native to North America and has been introduced to Europe where it has become invasive. Using a custom-designed NimbleGen oligoarray, we examined differences in gene expression between five native and six introduced populations of common ragweed in three different environments , as well as two different time points. We identified candidate genes that may contribute to invasiveness in common ragweed based on differences in expression between native and introduced populations from Europe. Specifically, we found 180 genes where range explained a significant proportion of the variation in gene expression and a further 103 genes with a significant range by treatment interaction. Several of these genes are potentially involved in the metabolism of secondary compounds, stress response and the detoxification of xenobiotics. Previously, we found more rapid growth and greater reproductive success in introduced populations, particularly in benign and competitive (light stress) environments, and many of these candidate genes potentially underlie these growth differences. We also found expression differences among populations within each range, reflecting either local adaptation or neutral processes, although no associations with climate or latitude were identified. These data provide a first step in identifying genes that are involved with introduction success in an aggressive annual weed.Although the evolutionary and ecological processes that contribute to plant invasion have been the focus of much research, investigation into the molecular basis of invasion is just beginning. Common ragweed (Novy, A., Flory, S.L. and Hartman, J. M. 2012 Evidence for rapid evolution of phenology in an invasive grass. Journal of Evolutionary Biology.doi: 10.1111/jeb.12047Microstegium vimineum. In environmentally controlled growth chambers, we grew plants from seeds collected from multiple latitudes across the species' invasive range. Flowering time and biomass were both strongly correlated with the latitude of population origin such that populations collected from more northern latitudes flowered significantly earlier and at lower biomass than populations from southern locations. We suggest that this pattern may be the result of rapid adaptive evolution of phenology over a period of less than 100 years and such changes have likely promoted the northward range expansion of this species. We note that possible barriers to gene flow, including bottlenecks and inbreeding, have apparently not forestalled evolutionary processes for this plant. Furthermore, we hypothesize that evolution of phenology may be a widespread and potentially essential process during range expansion for many invasive plant species.Evolutionary dynamics of integrative traits such as phenology are predicted to be critically important to range expansion and invasion success, yet there are few empirical examples of such phenomena. In this study, we used multiple common gardens to examine the evolutionary significance of latitudinal variation in phenology of a widespread invasive species, the Asian short-day flowering annual grass


Passer montanus).Although the negative effects of roads on the genetics of animal populations have been extensively reported, the question of whether roads reduce gene flow in volant, urban bird populations has so far not been addressed. In this study, we assess whether highways decreased gene flow and genetic variation in a small passerine bird, the tree sparrow (Passer montanus) sampled at 19 sites within Beijing Municipality, China, using 7 DNA microsatellites as genetic markers.We assessed genetic differences among tree sparrows (FST) among tree sparrows from different urban sites. Birds sampled at urban sites had similar levels of genetic diversity to those at rural sites. There was, however, evidence of some weak genetic structure between urban sites. Firstly, there were significant genetic differences (FST) between birds from opposite sides of the same highway, but no significant FST values between those from sites that were not separated by highways. Secondly, birds from eleven urban sites had loci that significantly deviated from the Hardy–Weinberg equilibrium but no such deviation was found in birds from rural sites.AMOVA showed that genetic variation between sites, between urban and rural populations, and between opposite sides of the same highway, were very weak. Mantel tests on all samples, and on urban samples only, indicated that the age and number of highways, and the number of ordinary roads, were uncorrelated with genetic differences (We cannot, therefore, conclusively reject the hypothesis that highways have no effect on the gene flow of tree sparrow populations. Furthermore, since the significance of these results may increase with time, we suggested that research on the influence of highways on gene flow in urban bird populations needs to be conducted over several decades. The ecological effects of roads have long been identified Passer montanus).Previous research on the influence of roads on gene flow in animal populations has focused on flightless species More specifically, we test the following predictions:Genetic differences between tree sparrows at different sites are positively correlated with the number, or age, of multilane highways between sampling sites.Genetic differences between samples from opposite sides of the same highway are greater than those between samples from the same side of a highway.Urban tree sparrows display greater inter-site genetic differentiation and lower genetic diversity than rural tree sparrows.The tree sparrow is a relatively sedentary species that occurs in a variety of habitats throughout China We collected blood samples from tree sparrows at 14 sites in urban Beijing which has a dense road network with six concentric ring highways and ten intercity highways . We alsoAll samples were collected with the permission of the Beijing Forestry Bureau. Experimental procedures conformed to the relevant Chinese laws and had the approval of Hainan Normal University's Animal Research Ethics Committee see also . In addiDNA samples were extracted from blood samples following the procedure described by Griffith et al. FST values were used to estimate genetic differentiation between populations. FST values were calculated in Arlequin 3.0. Three hierarchical analyses of molecular variance variance among groups, 2) variance among individuals within group, 3)variance within individuals. The significances of all F statistics values were tested via 16000 permutations.Pairwise multilocus e AMOVA;  using diFST, geographical distance, number of highways, highway age and number of roads between sample sites were tested using a Mantel test carried out in Fstat. Because urban highways have much more traffic than those in rural areas, highways would be expected to be a greater barrier to gene flow in urban than rural tree sparrow habitat. To determine if this was the case we performed two Mantel tests: one on all samples, and a second on urban samples only. By means of a permutation procedure, the significance of the partial regressions between the pairwise FST values and the following four matrices were tested: geographical distance as measured on a map, number of highways, total age of highways in years and number of roads.The correlation between The observed and expected heterozygosities were estimated for each locus from each sample site. Significant departures from the Hardy–Weinberg equilibrium were detected applying tests which were carried out with 1000000 steps in the Markov chain and 5000 dememorization steps P = 0.459, Ho: P = 0.622, He: P = 0.559). However, eleven of the 14 urban sites had heterozygosity values significantly different from those expected under Hardy–Weinberg equilibrium (P<0.05)  . No such(P<0.05) .P<0.05 level, 15 (8.7%) were significant at the P<0.01 level and 3 (1.8%) were significant at the P<0.001 level  were significant at the 01 level . Therefo01 level .FST values and geographical distance, highway age, number of highways or the total number of roads between pairs of sample sites (P values for urban samples were lower than those for all samples,and all determination values of urban samples were higher than those for all samples (Mantel tests on all samples, and on urban samples only, revealed no significant partial regressions between pairwise le sites . On the  samples .As expected, the distance between sampling sites was too small for significant genetic differentiation among tree sparrows; the results of the Mantel test provide good support for the fact that there was no correlation between genetic differentiation and geographical distance. The Mantel test also indicated that there was no correlation between genetic variation and the number of highways, common roads and highway age. In addition, the AMOVA results also indicated very weak genetic variation between sites, between urban and rural populations, or between opposite sides of the same highway. Indeed, the data show that the genetic diversity of urban tree sparrows was not significantly different from those found at rural sites. These results do not, therefore, support the hypothesis that highways, or ordinary roads, significantly limit the dispersal of tree sparrows.P values and higher determination values when applied to urban samples than when applied to all samples, which suggests that highways have a greater effect on gene flow between urban than rural sites. These results suggest that highways, and especially urban highways, have a weak, but detectable, effect on gene flow in tree sparrow populations in Beijing.There was, however, some evidence to the contrary. We did find significant genetic differences between birds from 20% of sites, all of which were on opposite sides of the same highways, while no significant differences were found when sites were from the same side of the highway. This suggests that highways may be responsible for a weak genetic structure in urban tree sparrow populations. Furthermore, although we did not find any significant difference in the genetic diversity of urban and rural tree sparrow populations, we did find significant deviation from the Hardy–Weinberg equilibrium in some urban tree sparrow loci but no such deviation in birds from rural sites. This suggests that urban tree sparrows may be more inbred than those at rural sites. Meanwhile, the Mantel test returned lower There are several possible explanations for these results. The first is that tree sparrows can fly over roads, including highways. The second is population density. Gauffre et al. Therefore, we cannot conclusively reject the hypothesis that highways do not restrict gene flow in urban tree sparrow populations. A time series analysis should be done to test whether the effects of highways on the genetic structure of Beijing's tree sparrow population will increase with time. Future research on the influence of highways on gene flow in bird populations will need to be conducted over several decades to obtain more conclusive results.


F-statistics revealed significant differences between the majority of the populations that were sampled. Bayesian cluster analyses using both prior information and no prior information on sampling location revealed the presence of two distinguishable genetic pools - namely, the Northern (Group 1) and Southern (Group 2) regions of Iceland. Furthermore, the random permutation of different allele sizes among allelic states revealed a significant mutational component to the genetic differentiation at four microsatellite loci , and supported the proposition of a historical origin behind the observed variation. The estimated time of divergence, using two different ABC methods, suggested that the observed genetic pattern originated from between the Last Glacial Maximum to the Younger Dryas, which serves as additional evidence of the relative immaturity of Icelandic fish populations, on account of the re-colonisation of this young environment following the Last Glacial Maximum. Additional analyses suggested the presence of several genetic entities which were likely to originate from the original groups detected.Due to an improved understanding of past climatological conditions, it has now become possible to study the potential concordance between former climatological models and present-day genetic structure. Genetic variability was assessed in 26 samples from different rivers of Atlantic salmon in Iceland , using 15 microsatellite loci.  For decades, several types of genetic markers have been used to define populations' boundaries in a multitude of species. An alternative approach has only been recently developed due to better understanding of past climatological conditions . Indeed, contemporary genetic patterns are known to be the result of both present-day and historical factors Although phylogeography studies related to anadromous fish such as the Atlantic salmon Although the complex biological cycle of the Atlantic salmon has been determined to be the primary source of potential genetic signal, another major factor that could have been the origin of the present-day genetic pattern in the Atlantic salmon is the geological and climatological history of the North Atlantic Ocean. Past geological and climatological history has, indeed, been shown to be at the origin of genetic structure and patterns of several land or marine organisms The objective of the present study was, therefore, to investigate the genetic structure of Atlantic salmon collected from 26 Icelandic rivers using 15 neutral markers, and to assess whether the genetic pattern observed could be attributed to the climatological history of Iceland.Animal Welfare number 15/1994, article 14” et al.A total of 2,352 salmon parr were sampled by electro fishing from 400–500 m stretches at 26 rivers in 2002 ) and 2004  , Table 1HO) and expected (HE) heterozygosities and F-statistics HS, average expected heterozygosity) of individual samples. The significance of pairwise STF  was calculated in ARLEQUIN 3.5.1.3 STF values. To detect loci under directional selection we used the program LOSITAN STF values and an estimate of p-value for each locus.Samples from early life stages contain only the genetic material of successful breeders -often of a single year- and may be biased towards particular families F value for the implemented F-model for correlated allele frequencies which can be used in a historical inference et. alK populations represented in our sample have each undergone independent drift away from ancestral allele frequencies at rates parameterized by F1, F2, F3…Fk respectively”. These F1 to Fk values can be used to make evolutionary inferences  was performed using Arlequin vs. drift on the genetic pattern detected, we performed the allele-size randomization test FST = RST, where RST is a stepwise mutation model (SMM)-based measure of genetic differentiation informed by microsatellite allele size variance. This is analogous to FST, and unbiased with respect to any differences in sample size between populations or any differences in variance between loci. When mutations contribute little to genetic differentiation, estimates of differentiation using FST and RST should show similar results. On the other hand, if stepwise-like mutations have contributed significantly to divergence, RST should demonstrate a larger differentiation than that of FST. Potential historical signatures in the genetic data were therefore assessed by permutating allele sizes at each microsatellite locus among allelic states  to simulate distribution of RST values (ρRST) with 95% confidence intervals (CI).To assess the potential impact of mutation simulation) simulates many multilocus data sets with characteristics similar to the observed data set; the second step (rejection) compares the simulated data set to the observed data set and retains simulations that are arbitrarily close to the observations whilst rejecting others; the final step (estimation) then estimates posterior distributions of parameters through locally weighted linear regression on the summary statistics associated with the retained simulations t generations in the past from an ancestral population of size N1+N2, assuming a stepwise mutation model with no indel mutations and a mutation rate μ = 10−4. In the first step, 1,000,000 datasets were simulated, and 1% of the simulated data sets that most closely fit the observed data were used to inform the posterior distribution of parameter values. The uniform prior distributions used in the DIYABC analyses ranged from 0–20,000 for both N1 and N2 and 0–50,000 for t. Secondly, the time of divergence was approximated using the popABC software A that splits at time T in the past to give two populations of size N1 and N2. Since the time of splitting, immigration occurs at rates m1 and m2, where immigrants into one population are drawn from the other population. The mean of mean mutation rate among loci was assumed to 5×10−4, normally distributed with a standard deviation of 5×10−4. A mean mutation rate of 5×10−4 is commonly assumed in demographic models To further clarify evolutionary history, the time of divergence was approximated using two different ABC approaches. First, the time of divergence was approximated using the Approximate Bayesian Computation (ABC) implemented in DIYABC v1.0.4.46 Salmo trutta), salmon, and hybrids thereof et al.A total of 324 individuals  were discarded due to sibling effects within the sampling, ranging from 40 in Litla Laxa (12) to none in Laxa Dolum (10) . A totalHS) and allelic richness (AR), ranged from 0.630–0.730 and 6.78–9.23, respectively (Only one sample deviated from HWE (i.e. the river Hvita Efst (6) ); this wectively .FST value of 0.057 was observed on a sample level. The degree of genetic differentiation between sampling locations, as estimated by FST, ranged between 0.006 and 0.140  was two, both with (Ln P(D)±S.D = −95402±462) and without location information (Ln P(D)±S.D = −95725±922) , with and without location information, are presented in FST) was 0.072 between the two groups  . The fir725±922)  green. T725±922)  yellow. analysis . Branchealysis A. The cluo groups .In addition, when the genetic diversity of Group 1 and Group 2 were compared, no significant trend was observed, although the gene diversity (Hs) and allelic richness (Ar) tended to be slightly higher in Group 1 than in Group 2, .RST were significantly larger than the 95% CI range of the ρRST values at four microsatellite loci , suggesting a mutational component to genetic differentiation. RST was also larger than the ρRST values at SSsp2210, but not significantly. When considering the two groups detected with the Bayesian method, the overall estimate of RST was also significantly larger than the 95% CI range of the ρRST values  to 17.8 kyr BP (five years generation time). In the popABC approach the time of divergence was estimated as 17,454 . Other parameters estimated by the popABC are available in In the case of the DIY ABC approach, the simulations were based on the scenario of two populations that were diverged STF compared to other samples is 0.027 lower. Removing siblings also caused the genetic distance between the two samples from the Blanda river system to drop from significant to non-significant.An accurate result from population genetic analyses requires a random, independent sample from each population of interest. However, within a population the genetic patterns can differ among demographic groups, and attention to this factor is important in order to attain an accurate conclusion regarding population genetic structure Understanding the distribution and connectivity of populations has been one of the major challenges of recent decades, and has been recognised as a necessity for biodiversity conservation The Atlantic salmon exhibits a complex biological cycle involving stages that inhabit both marine and freshwater environments. Several genetic studies have demonstrated its propensity to form distinct and reproductively isolated populations et al.et al.STF value between salmon populations in Iceland was 0.14 found between Kalfa (7) and Laxa Adaldal (9). Kalfa appeared to be a very unique sample and was highly differentiated from all other samples with a minimum STF value of 0.075. If we excluded this sample, the STF value range in this study was 0–0.116 and was very similar to what was observed within salmon populations in the UK A distance phylogenetic tree and was geographically relevant, suggesting the effect of restricted gene flow was due to isolation by distance. The consequent predicament was a question of the extent to which to pursue the hierarchical analysis. In this case, we stopped at the second and third level, as we concluded that this sufficiently described the eight geographically major stock units of Iceland. Restricted gene flow can, of course, continue to act within some of the eight major genetic groups, but further subdivision (e.g. the within river structure of the Olfus river system) can be determined using the pairwise STF comparison  exists within populations, such that genetic drift is the only force acting upon the population. With time, genetic drift will increase the population F-value, as was demonstrated by Group 2 having a higher F-value than Group 1. One possible interpretation of these results is that Group 2 was possibly colonized from Group 1 When considering neutral genetic markers the F-value in the south, do not provide any direct support for an initial colonisation in the north but are nevertheless consistent with the ice-cap retreat model in Iceland (and that the northern region was deglaciated first). When considering the deglaciation model of Iceland it is highly probable that pioneer salmon colonized the northern region before the southern region. The first available habitat for salmon in Iceland after the LGM is located in the Northwest region (Breiðafjörður) approximately 17.5 ka BP. From there suitable habitats were consecutively formed as the progression of deglaciation went north and east. The estimated time of divergence (DIYABC and popABC) demonstrated the existence and timing of subdivision between the northern and southern populations, and suggested that pioneer salmon were arriving in Iceland at a time when the only viable habitats were in the northern region (Breiðafjörður). Therefore, when we considered the available deglaciation model for Iceland, the presented genetic results seemed to be consistent with an initial settlement of Atlantic salmon in the northern region of Iceland.The genetic analyses, i.e. the existence of two main genetic clusters and the higher The proposed order of settlement offers the possibility of three settlement scenarios: First, that the colonizing salmon inhabit the northern region and subsequently colonize the south. Second, that the colonizing salmon inhabit the north of Iceland and a second colonization event from the same population of origin occurs in the southern area. Third, that the colonizing salmon inhabit the north of Iceland and a second colonization event from a different refugium occurred in the southern area. Although we cannot distinguish between the suggested three settlement scenarios, our results suggest that the glaciation event in Iceland has imprinted the present day genetic structure of Atlantic salmon.AAlthough a three cluster scenario suggesting a colonization process consisting of multiple events cannot be completely ruled out, the current analysis better support the two cluster scenario. The additional within-river groups detected within each original group (Group 1 and Group 2) during our three levels of hierarchical structure analysis, and confirmed by the consensus neighbour joining tree of pairwise DThe rivers Ellidaa (25), Leirvogsa (11), and Langa (23) seemed to be misplaced in these ice-free environment re-colonisation events; however, a closer inspection of Icelandic volcanic history and of contemporary human activity offered explanations for these anomalies.The lava field, Leitárhraun, was formed in a volcanic eruption 5,200 years ago Regarding Leirvogsa (11), the river was probably inaccessible for salmon in its original state as there were cascades near the estuary. However, after the cascades were artificially made accessible to enhance rod fishery, the river became known for its sea-run brown trout. Today, Leirvogsa (11) is a river with a healthy salmon population since the river became stocked with parr and smolts originating from Ellidaa (25).In Langa, (23) there are two waterfalls at the estuary - Sjávarfoss and Skuggafoss - that were possibly impassable for salmon. Skuggafoss waterfall proved especially difficult for salmon to pass until a fishway was built in the 1950s The present study has yielded two important findings. Initially, that microsatellite loci revealed a significant genetic signal amongst the populations collected at 26 rivers distributed across the country, a result which suggested a restricted gene flow common to the sampled populations. Secondly, that the time of divergence between the two primary genetic groups detected was highly consistent with the ice-cap retreat model in Iceland, and that further analyses provide overwhelming evidence of a historical component to the observed genetic differentiation. The individual analysis of population structure strongly supports the presence of two genetically distinct groups, with a general trend of higher genetic variability in the northern areas in relation to that of the southern regions, thus substantiating the expectation of the existence of higher genetic variability in the potential initial area of colonization. The rivers Ellidaa (25), Leirvogsa (11) and Langa (23), however, do not seem to fit this re-colonisation route hypothesis, although the volcanic history of Iceland and the history of human activity for the previous 60 years could be attributed responsibility for the displacement of these rivers in the presented salmon histories. In addition, the additional variation observed within each predominant group (Group 1 and Group 2) was likely due to more recent events of colonisation or population isolation, subsequent to the recolonisation event after the LGM. We therefore conclude that the observed genetic pattern at microsatellite loci for the Atlantic salmon in Icelandic rivers serves as additional evidence of the relative immaturity of Icelandic fish populations, on account of the re-colonisation of this relatively young environment following the Last Glacial Maximum.http://doi.org/10.5061/dryad.60kk5.Data available from the Dryad Digital Repository: Table S1Microsatellite loci characteristics assessed as repeat motif (RM), number of alleles (n), allelic richness (Ar), allelic size range (size range), gene diversity  and overall FST and RST.(DOCX)Click here for additional data file.Table S2Pairwise FST values  and their corresponding p-values for 0.01 significance level  for all sample pairs, as calculated in Arlequin.(DOCX)Click here for additional data file.Table S3Hierarchical analysis of variance (AMOVA) among samples of Atlantic salmon grouped into the two a priori groups detected with STRUCTURE. The variance among groups relative to the total variance, the variance among samples within groups and the variance among samples relative to the total variance are presented. The source of variation from among groups, among samples within groups, and within samples is given as a percentage for each comparison. All F-values were highly significant (P<0.0001).(DOCX)Click here for additional data file.Table S4The estimation from popABC with 95% confidence interval in parenthesis for splitting time (T), effective population sizes  and migration rates .(DOCX)Click here for additional data file.Figure S1A PCA plot based on the FST values. The two clusters of populations represent the two genetic clusters referred to throughout the text (Group 1 and Group 2).(DOCX)Click here for additional data file.Figure S2A graphical output of the LOSITAN analysis for the two primary populations were heterozygosity (He) is on the x-axis and the STF value is on the y-axis. All loci fall within the simulated confidence area for neutral loci (grey area).(DOCX)Click here for additional data file.Figure S3Clustering assignment of 26 salmon populations with STRUCTURE for K =  with and without location information respectively. Individuals are represented by a single vertical column divided into K colours. Each colour represents one cluster, and the length of the coloured segment corresponds to the individual's estimated proportion of membership in that cluster.(DOCX)Click here for additional data file.


Alytes obstetricans), in four Swiss regions where the species has suffered variable levels of subpopulation extirpation. We also quantified the effects of several geographic factors on genetic structure and used a model selection approach to ascertain which of the variables were important for explaining genetic variation. Although subpopulation pairwise FST-values were highly significant even over small geographic scales, neither any of the geographic variables nor loss of subpopulations were important factors for predicting spatial genetic structure. The absence of a signature of subpopulation loss on genetic differentiation may suggest that midwife toad subpopulations function as relatively independent units.Genetic diversity is crucial for long-term population persistence. Population loss and subsequent reduction in migration rate among the most important processes that are expected to lead to a reduction in genetic diversity and an increase in genetic differentiation. While the theory behind this is well-developed, empirical evidence from wild populations is inconsistent. Using microsatellite markers, we compared the genetic structure of populations of an amphibian species, the midwife toad ( The maintenance of population genetic diversity is of crucial importance for long-term population persistence Frankham  ReducingThe global decline of amphibians has resulted in the loss of amphibian populations over a matter of decades, but declines are not homogeneously distributed , Bern , Lucerne , and St. Gallen  and 74 subpopulations of A. obstetricans were detected from 1981 to 1993  and declines have been moderate  than in BL and BE. There are only three reports of colonization of new subpopulations . Relatively more subpopulations of s Hewitt , hence wBarandun . BreedinA. obstetricans subpopulations. In LU, we sampled two clusters of subpopulations of which the southernmost was located at the distribution border. Subsequent analyses confirmed that, although no known populations exist between the southern and northern cluster, these clusters could still be treated as one population 13, (GATA)7, (GTAT)7, (ACAG)7, and (GCGT)7 oligonucleotide repeats  using We extracted DNA from tail clips using the BioSprint 96 DNA Blood Kit , following the protocol for tissue extraction. Polymerase chain reactions (PCR) were performed with fluorescent-labeled primers in three separate multiplexes Table . Each weMicrosatellite loci were tested for the presence of null alleles, stuttering and allelic dropout of larger alleles using MICROCHECKER  were calculated using GENETIX 4.05.2 , we ran the programs ONeSAMP  in all ponds where data on two cohorts was available. This analysis tested whether reproduction among cohorts was strongly skewed towards a few parental individuals , we assumed that our measures of genetic diversity with all samples from a subpopulation pooled were representative. We next calculated global FST-values per region and pairwise FST-values of subpopulations within regions as a measure of genetic population structure among and within regions and tested the significance of pairwise FST within regions with an exact test with 1000 permutations -transformed FST values and log-transformed Euclidian distances  based inference framework  were correlated , and the same was true for He and Ho (r = 0.89). We calculated a mean subpopulation FST as the mean of all pairwise FST values of a subpopulation to all other subpopulations within the same population.Severity of subpopulation loss was classified as “none,” “moderate,” or “strong” Table . We extrOur independent variables, all defined above, were (1) severity of subpopulation loss, (2) elevation, (3) location close to a stream, and (4) geographic isolation within a population. We used an intercept-only model as the null model. We included one main effect per model only. Population was defined as a random effect to accommodate non-independence of the sub-populations in all models . Locus Alyobs20 was monomorphic in all studied subpopulations and excluded from further analyses. We found no deviations from HW equilibrium after Bonferroni correction and very little and inconsistent linkage at few markers in few subpopulations. With the application of a conservative significance level of P = 0.001, 24 signatures of linkage were found in a total of 4730 comparisons (11 markers times 43 subpopulations); linked markers were found in 8 of the 43 subpopulations. This is further indication that the (possible) presence of siblings in the genotype data did not negatively affect our results  and the overall, global FST was 0.352. Pairwise FST values among subpopulations within populations ranged from 0.035 to 0.534  and all were significantly different from zero. IBD was highly significant when the entire data set was included in a single analysis  but within populations IBD was not significant for BE , BL , and LU , and only marginally so for SG  but still considerable amounts of variation around 20% each occurred among subpopulations within populations and among populations Table .e, suggesting that none of the explanatory variables explained variation in He well  were small and levels of genetic variation were very low. Moreover, private alleles were common in subpopulations, supporting our estimates of small breeding population sizes (Nb). Additionally, we identified strong genetic differentiation among subpopulations even across small geographical scales. Distances of less than 500 m were associated with significant pairwise FST-values.We predicted that we would find differences in subpopulation and population genetic structure and diversity that correlated with population declines and connectivity. Specifically, we expected to see differences among subpopulations attributable to different population decline histories and habitat variables expected to influence amphibian dispersal. Although these factors varied among the four regions, we detected no evidence that variation in genetic structure and diversity was influenced by any geographical or historical factor population loss, even if declines have been ongoing for a sufficient amount of time for genetic signatures of decline to manifest.Matocq and Villablanca  and ShorA. obstetricans subpopulations in Switzerland are generally composed of relatively few breeding adults  of subpopulations appears to be the most promising conservation strategy. Larger subpopulations are less prone to environmental and demographic stochasticity and have a higher chance of long-term persistence. Increasing the number of subpopulations, for example, by the creation of new breeding sites, would also benefit long-term survival of populations. However, given the low dispersal rate and the resulting low chance for natural colonizations to occur, conservation management of


Cryptobranchus alleganiensis alleganiensis) is a large, fully aquatic paedamorphic salamander. Many populations are experiencing declines throughout their geographic range, yet the genetic ramifications of these declines are currently unknown. To this end, we examined levels of genetic variation and genetic structure at both range-wide and drainage  scales. We collected 1,203 individuals from 77 rivers throughout nine states from June 2007 to August 2011. Levels of genetic diversity were relatively high among all sampling locations. We detected significant genetic structure across populations . We identified two genetically differentiated groups at the range-wide scale: 1) the Ohio River drainage and 2) the Tennessee River drainage. An analysis of molecular variance (AMOVA) based on landscape-scale sampling of basins within the Tennessee River drainage revealed the majority of genetic variation (∼94–98%) occurs within rivers. Eastern hellbenders show a strong pattern of isolation by stream distance (IBSD) at the drainage level. Understanding levels of genetic variation and differentiation at multiple spatial and biological scales will enable natural resource managers to make more informed decisions and plan effective conservation strategies for cryptic, lotic species.Conservation genetics is a powerful tool to assess the population structure of species and provides a framework for informing management of freshwater ecosystems. As lotic habitats become fragmented, the need to assess gene flow for species of conservation management becomes a priority. The eastern hellbender ( Rivers are complex, dynamic systems that shape aquatic ecosystems at the landscape scale through a combination of biotic and abiotic processes. A central theme in stream conservation biology involves assessing spatial and temporal patterns of genetic variation within species inhabiting streams distributed across landscapes While numerous investigators have assessed the genetic diversity and structure of fish and macroinvertebrate species within and among lotic systems Cryptobranchus alleganiensis alleganiensis is a large, long-lived, aquatic salamander which is confined to lotic dispersal. Hellbenders exhibit a strictly North American distribution, currently ranging from New York, across the Midwest to Missouri, and through several southern states to northern Georgia The eastern hellbender Cryptobranchus alleganiensis bishopi phylogeography utilizing mtDNA and microsatellite markers, have divided the species range into eight reciprocally monophyletic groups with negligible gene flow among groups st average = 0.40; Recent studies of eastern and Ozark hellbender To provide the resolution needed for making informed conservation and management decisions for eastern hellbenders, our goal in this research was to perform exhaustive sampling across the range of the eastern hellbender and to use these samples to detect genetic signatures of reduced population size , delineate genetically distinct populations, and provide baseline data for conservation efforts Permits to collect tissue samples included the Indiana Department of Natural Resources (#09-0161), North Carolina Division of Wildlife Resources (#NC-2010ES286), Pennsylvania Fish & Boat Commission (#019-755-578), Georgia Wildlife Resources Division (#29-WBH-10-184), Tennessee Wildlife Commission (#3564), National Park Service Great Smoky Mountains NP (#GRSM-2010-SCI-0031), and Purdue University Animal Care and Use committee (#UNG-895).Eastern hellbenders were sampled across major watersheds throughout their current geographic range. We collected a minimum of 25–50 samples per watershed across several streams within major river basins of the Ohio, Tennessee, Mississippi, and Susquehanna River basins . GeneticSB1 and NCSB2) and three within Georgia  to ensure sufficient power to detect genetic structure. This sampling regime allowed us to examine genetic variation at multiple hierarchical scales: within the Tennessee River Basin overall, within and between basins (Georgia and North Carolina), within and among sub-basins within basins , and within and among stream reaches nested within sub-basins.To assess hierarchical patterns of genetic structure across stream networks embedded within a specific drainage, we used those hellbender samples obtained within the Tennessee River drainage. This river drainage was chosen due to the presence of stable populations and ability to collect minimal sample sizes of 15–20 adults per stream reach. This drainage-scale study consisted of three hierarchal levels: basins, sub-basins, stream reaches  and generally followed the sample design of Finn et al. 2007 Genomic DNA was extracted from all samples using a standard phenol-chloroform protocol p), observed (Ho), and expected heterozygosites (He) across all loci in GENEPOP is values were calculated and tested for significant deviations from Hardy-Weinburg equilibrium (HWE) averaged across populations in FSTAT We estimated standard metrics of genetic diversity for each stream reach including allelic richness (A), number of private alleles  using 1,000 randomizations in FSTAT  based on the minimization of Hardy Weinberg and linkage disquilibrium (HWE) within clusters K, 1–100) in the dataset. The maximum K of 100 was set to account for the potentially large number of clusters that might exist among the 77 distinct rivers. Our maximum K was adjusted to 10 after determining the highest likelihood values for K were under 10. To infer the actual number of clusters supported by our dataset, we used the ΔK method of Evanno et al. 2005 K and qualitatively examined increases in variance after the “true” K was reached according to Pritchard et al. K = 1 to10) as well as a final run at the inferred K (K = 2), consisting of 1,000,000 iterations after a burn in of 100,000 to ensure stabilization of our MCMC . STRUCTURE was run under the uncorrelated alleles model to prevent overestimation of K given our sample design , Fsb (divergence among sub-basins within basins), Fsrsb (divergence among stream reaches within sub-basins), and Fis . GPS coordinates of individual captures were used to determine geographic distance between individual sample locations. This analysis provides an additional measure of genetic distance to describe the relationship between geographic and genetic distance at the scale appropriate for hellbender life history.To investigate levels of philopatry and vagility of eastern hellbenders within individual streams, we tested for isolation by stream distance (IBSD) at the drainage scale. For this analysis the linear stream distance between sample locations in kilometers was compared to stream Fst values. STREAMTREE allowed us to qualitatively compare results from the ISBD analysis. This software determines a coefficient of determination (R2) to infer fit of the data to the STREAMTREE model of stream hierarchy in which gene flow is confined to a one-dimensional space utilizing watershed specific topology to aid in identification of stream barriers in the absence of strong isolation by distance pattern To test whether genetic structure reflected the topography of streams and identified stream sections that contributed the most to genetic differentiation, we used STREAMTREE K were set similar to STRUCTURE; initially 1–10. The poisson maximum was set to 360, while the Poisson-Veroni tessellation was set to 1,080 (which is at least three times our sample size) as per Guillot et al. 2005 KK is unknown K under the correlated allele model To infer the number of distinct genetic clusters at the drainage scale, we used STRUCTURE  and GENELAND is values, the majority were slightly negative, non-significant values indicating some level of heterozygosity excess (high genetic variation) observed across populations. However most Fis values observed were close to zeroA total of 1,203 tissue samples were collected from 77 discrete stream reaches  and successfully genotyped across 12 tetranucleotide microsatellite markers. Fourteen thousand two hundred and ninety-nine of 14,436 potential genotypes (99.05%) were obtained across all loci and individuals. Estimates of genetic variation were surprisingly high among stream reaches . Estimates of Jost's D were consistent with Fst values.Pairwise FK method of Evanno et al. 2005 .The highest degree of genetic variation was partitioned within streams (93.6–98.35%) . The lev2 = 0.852), indicating that stream-reach distances and watershed topology correlated well with the corresponding genetic distance matrix (6 = 0.0056).There was strong fit of the data to the STREAMTREE model , cluster 2 (GASB1), and cluster 3 (GASB2 & GASB3). GENELAND results were identical to STRUCTURE for clusters 1 and 2, but partitioned cluster 3 into an additional cluster composed of a single stream reach within GASB3.The number of distinct genetic clusters within the drainage scale varied slightly among the clustering programs. STRUCTURE detected 3 distinct genetic clusters: cluster 1  and exhibited similar levels of allelic richness . When tast values between populations were congruent with geographic proximity, i.e., geographically proximate rivers and connected rivers within the same watersheds yielded lower Fst values. The moderately low Fst values between geographically proximate populations were somewhat unexpected as eastern hellbenders are very sedentary and highly philopatric While most of the eastern hellbender stream reaches (populations) sampled within and among drainages were significantly genetically differentiated, overall we found strikingly lower levels of genetic variance partitioning than have been reported in previous studies K = 2) consistently, regardless of iteration or burn in length, using ΔK Evanno et al. 2005 K) with significantly higher assignment probabilities. Latch et al. 2006 st = 0.03–0.05), which overlaps well with the range of most (i.e. 92% above 0.03) of our values range-wide.We identified two major genetic populations at the range-wide scale using Bayesian methods, the Ohio River drainage and Tennessee River drainage. STRUCTURE identified these two distinct clusters . The percent of genetic variation partitioned among drainages (∼1.2%–3.7%) and within sub-basins (∼0.5%–2.8%) were both relatively low . st and linear stream distance  indicates some effect of localized dispersal among nearby populations. Reported patterns of genetic signal relative to stream hierarchy vary across taxa. For example, there is a clear scaling-up effect of genetic variance partitioning among sub-basins in species with some degree of terrestrial dispersal ((Desmognathus quadramaculatus) conforms well to predictions of higher variance within stream reaches  possibly due to high levels of overland dispersal The significant genetic structuring detected at higher watershed scales (among basins and within sub-basins of the Tennessee River drainage) should not be discounted as it indicates individual drainages and larger hydrologic features are important in contributing to landscape level genetic sub-structure. Alternatively, a lack of structuring at higher hierarchical levels (i.e. sub-basin) may indicate insufficient time for structure to accrue at this spatial scale given the relatively short time frame following glacial retreat and significant paleo-river reconfiguration in this region ispersal . Indeed,SB3) into an additional cluster composed of a single stream reach. This same sub-basin indicated some degree of differentiation (limited gene flow) from other Georgia stream reaches within the same Basin in the PCA analyses. One stream segment in this sub-basin occurs in an area separated by a higher elevational gradient and separated by a greater linear stream distance than other stream reaches within GASB1 and GASB2.Interestingly, the results of the drainage scale analysis using STRUCTURE and GENELAND indicate further fine-scale genetic structuring at hierarchical levels (sub-basins), as both programs grouped North Carolina sub-basins together, but differentiated Georgia sub-basins into proper sub-basins. GENELAND, however further divided one Georgia sub-basin , we observed a more linear trend for North Carolina while Georgia genetic differences appear to increase rapidly at short distances then plateau. This difference in pattern may be due to the shorter stream distances and lower levels of genetic differentiation estimates observed within North Carolina sub-basins than those in Georgia or a lack of intermediate sample locations. Alternatively, this nonlinear pattern may be a result of landscape features other than linear distance  influencing genetic differentiation within Georgia sub-basins. Moreover, this nonlinear pattern is supported by the clustering results and may reflect the fine-scale structure of two distinct Georgia sub-basins. When taken together, these results reveal the presence of fine-scale structure at the drainage scale characterized by detectable level of IBSD.Future management of the eastern hellbender across these two major drainages (Ohio and Tennessee Rivers) presents many challenges. Many populations have declined to the point where the only remaining viable management tools are captive propagation and translocations, both of which require understanding of the genetic and biological attributes of source and target populations if they are to be successful. Translocation programs may suffer from low success rates if they fail to incorporate underlying levels of genetic structure Table S1Locus-specific information for range-wide study. Null allele presence  and frequencies for all eastern hellbender populations. The number of alleles observed at each locus is reported along with loci-specific Fis.(DOCX)Click here for additional data file.Table S2st and Jost's D matrix of Representative eastern hellbender populations with minimal sample size of 8.F Pairwise Fst values are below the diagonal, Jost's D values are above. Fst values that are not significant are in bold. Abbreviations as follows; IN , HI1 , HI2 , HI3 , HI4, HI5 , HI6 , HI7 , HI8 , HI9 , HI10 , LT , Elk , Cap , MO1 , MO2 , MO3 , VA1 , WV1, WV2 , PA1 , PA2 , PA3 , PA4 , PA5 , PA6 , PA7 , PA8 , FB1 , FB2 , FB3 , FB4 , Deep , Tuck , FB5 , FB6 , New1 , New2 , New3 , New4 , New5 , FB7 , FB8 .(DOCX)Click here for additional data file.


Phyllastephus debilis) represents the only described bird species within the Eastern Arc/coastal forest mosaic, which is polytypic across an altitudinal gradient: the subspecies albigula (green head) is distributed in the montane Usambara and Nguru Mountains whereas the subspecies rabai (grey head) is found in Tanzanian lowland and foothill forest. Using a combination of morphological and genetic data, we aim to establish if the pattern of morphological differentiation in the Tiny Greenbul (Phyllastrephus debilis) is the result of disruptive selection along an altitudinal gradient or a consequence of secondary contact following population expansion of two differentiated lineages.The Eastern Arc Mountains of Africa have become one of the focal systems with which to explore the patterns and mechanisms of diversification among montane species and populations. One unresolved question is the extent to which populations inhabiting montane forest interact with those of adjacent lowland forest abutting the coast of eastern Africa. The Tiny Greenbul (rabai) and montane  populations in Tanzania. The differences in shape are coupled with discrete differences in the coloration of the underparts. Using multi-locus data gathered from 124 individuals, we show that lowland and montane birds form two distinct genetic lineages. The divergence between the two forms occurred between 2.4 and 3.1 Myrs ago.We found significant biometric differences between the lowland (rabai to albigula, is taking place at three mid-altitude localities, where lowland and montane rainforest directly abut. The extent of this introgression appears to be limited and is likely a consequence of the recent expansion of rabai further inland.Our coalescent analyses suggest that limited gene flow, mostly from the subspecies albigula be elevated to species rank.The clear altitudinal segregation in morphology found within the Tiny Greenbul is the result of secondary contact of two highly differentiated lineages rather than disruptive selection in plumage pattern across an altitudinal gradient. Based on our results, we recommend  The Eastern Arc and coastal forests of East Africa have been identified as a biodiversity hotspot: an area featuring exceptional concentrations of endemic species and experiencing severe habitat loss . The extExtensive field research within the Eastern Arc has taken place over the past 15 years which has led to the description of several new species and the development of novel hypotheses concerning patterns of differentiation among species and populations distributed in East Africa ,8,9. DesPhyllastephus debilis) represents the only described bird species within the Eastern Arc/coastal forest mosaic, which is polytypic across an altitudinal gradient  as well as in the Nguru Mts 130 km further inland  north along the coast into Kenya, and inland along riverine corridors to the foothill forests od the the Uluguru, Nguu and Nguru Mts . The moe frogs, : albigulguru Mts  and to 2Whether disruptive selection across an altitudinal gradient can lead to parapatric speciation is hotly debated, as it requires natural selection to be sufficiently strong to counteract the effects of gene flow e.g. -17]. Alt. Alt17]]rabai, are generally small  with a mouse grey crown, pale grey underparts with bright yellow streaks  contrasting with a very pale grey throat and extensive pale yellow belly. This description also applies to birds from Mt. Kanga (n = 6), the Nguu Mts (n = 2) and the Uluguru foothills , subspecies albigula from the Usambara (n = 6) and Nguru Mts (n = 11) are generally large . Birds of both sexes from the two montane populations of albigula do not differ significantly from each other in any measured morphometric trait , but do differ from lowland birds, with lowland birds being significantly smaller .Specimens of the montane subspecies debilis  are separable from lowland populations (rabai) in morphospace, particularly along PC1 .The first two principal components (PCs) had eigenvalues greater than one and accounted for 77.2% of the total variation . Principal component loadings on PC1 were positive and strongly correlated with weight. Loadings on PC2 were positive and strongly correlated with wing- and tail-length; bill- and tarsus-length loaded evenly on both PC1 and PC2. In agreement with the bivariate results above, the scatterplot  and even the throat and chin are rather grey  leaving only a narrow area on the central belly white. Yellow streaks are variably developed but generally weak and there is always a bright yellow axillary patch which, together with the yellow wing-lining, stands out conspicuously. Thus, the most prominent plumage difference between the rabai and albigula specimens is in the color of the underparts rather than the crown as traditionally described.In plumage characters, the dark olive-green color of the back of rabai, resembles individuals from the adjacent Nguru Mts  in plumage and size . The ZMUC specimen (74473) from Lindi  we sequenced in this study resembled specimens from lowland populations further north on the Tanzanian coast (rabai) in both plumage and size . Only one specimen from Zimbabwe (debilis) could be compared directly with Tanzanian specimens, and differs from the Lindi specimen and most of the other rabai specimens only in having a faint greenish tinge on the crown. The description in Keith et al. ..rabai israbai) and highland  populations. Yet, when individuals from Mt. Kanga were excluded from the analyses, the hypothesis of zero gene flow could no longer be rejected. This pattern suggests that limited gene flow between albigula and rabai takes place on Mt. Kanga. Given that the lowland population likely experienced a demographic expansion, it is likely that Mt. Kanga represents a zone of secondary contact and not the initial area where the two species diverged. Consequently, recurrent gene flow appears to be restricted in space to areas of intermediate habitat. The Isolation with Migration model implemented in IMa has several assumptions that may be violated in empirical data sets, including: no intralocus recombination, no gene flow with an unsampled species/population, no linkage among loci, no selection and no population structure in the ancestral population. Here, we can reasonably reject recombination, selection and linkage among the sampled loci as potential biases. Gene flow with an unsampled species is unlikely, as the Tiny Greenbul has no close extant relatives )albigula, it is important to know if gene flow is occurring between the two populations. Our coalescent-based analyses could not exclude the hypothesis of zero gene flow between the two populations. Our result is consistent with phylogeographic studies of other Eastern Arc Mountain birds where the Usambara-Nguru gap has consistently been recovered as the major phylogeographic break among clades ,30,31albArthroleptis xenodactylus, from the Usambara and Nguru Mts  althougST 1.5.4 ,60 with ST 1.5.4  to estimST 1.5.4  and the TRUCTURE V2 [n = 80) for which: 1) all three nuclear loci could be satisfactorily phased, and 2) sequences of the three nuclear loci were available. We compared the optimal number of populations estimated by STRUCTURE and the probability of each individual being assigned to each population across analyses. We assumed an admixture model with correlated allele frequencies and let alpha vary among populations. We ran 2*106 iterations (burnin: 2*105 iterations) from K = 1 to K = 5. The number of clusters (populations) was estimated using ΔK [We used SCTURE V2  to inferusing ΔK .OFAD V1.03 [PLITSTREE V4.0 [TRUCTURE analyses. We used uncorrected-p distances as input for POFAD and made use of the standardized matrix for network reconstruction.We used PAD V1.03  and SPLIREE V4.0  to buildEAST, [albigula, debilis and rabai). Species tree approaches implement the coalescent to estimate a species tree based on the individual gene trees; this approach has been shown to outperform the traditional concatenation approaches in that incomplete lineage sorting is explicitly taken into account. We defined each subspecies as a 'species'. We used all individuals for which full phase information was available and assumed a strict molecular clock model for all loci and made used of the best-fit model for each partition, as determined with DT_MODSEL[We used the species tree approach  implemeEAST, ,60, to eDT_MODSEL. Thus, eAYESIAN PHYLOGENY AND PHYLOGEOGRAPHY V2.0  and the age of the root in the species tree (τ0), whereas the other divergence time parameters were assigned a Dirichlet prior [[We made use of the software BPP v2.0, ,68) to epop1 (4Nepop1μ), θpop2 (4Nepop2μ), θpopA (4NepopAμ), t , m1  and m2 . We defined inheritance scales to reflect the difference in modes of inheritance among the loci used: 0.25 for the mtDNA locus, 0.75 for the Z-linked locus and 1.0 for the two autosomal loci. We used an HKY model of nucleotide substitution for the mtDNA and an infinite-sites model for each of the three nuclear loci. Parameters and genealogies were sampled every 100 steps for the 5 and 10 million step runs. To assess convergence we monitored the extent of autocorrelation, parameter trend lines and the effective sample size (ESS) throughout the run and we also compared the results between three independent runs.We used the Markov chain Monte Carlo method implemented in the program IMa  to fit t-8 substitutions/site/year (s/s/y) for mtDNA , and th-9 s/s/y . This trin HYPHY ,73.albigula versus rabai, 2) albigula versus rabai with individuals collected on Mt Kanga excluded (see results), 3) rabai versus debilis, and 4) albigulaNguru versus albigulaUsambara.We performed four pairwise comparisons: 1) http://www.worldclim.org/current and compiled using DIVA-GIS v7.2 [Current bioclimatic data  were collected from WORLDCLIM GIS v7.2 . The cliGIS v7.2 .J Fuchs performed the laboratory work, carried out the genetic and bioclimatic analyses and drafted the manuscript. J Fjeldså participated in the design of the study, took the biometric and plumage data and drafted the manuscript. RB participated in the design of the study, performed the biometric and some genetic analyses and drafted the manuscript. All authors read and approved the final manuscript.Scatterplot of the principal component scores derived from five morphological measures. Scatterplot of the principal component scores derived from five morphological measures for P. debilis. Code Key: red (1) lowland rabai, green (2) montane albigula from the Usambara Mts, and blue (3) montane albigula from the Nguru Mts).Click here for fileHaplotype network obtained from each nuclear loci. Haplotype network obtained from each nuclear loci using TCS. Color codes are: P. d. rabai (green), P. d. debilis (red) and P. d. albigula (blue). Circle size is proportional to haplotype frequency. Note that the scale is different for each locus.Click here for fileTRUCTURE algorithmAssignment of individuals to genetic clusters using the S. Assignment of individuals to genetic clusters using the STRUCTURE algorithm for K = 3 , K = 4 , K = 5 .Click here for filerabai and albigulaBayesian Skyline Plot of the mitochondrial data sets for the subspecies . Bayesian Skyline Plot of the mitochondrial data sets for the subspecies rabai and albigula.Click here for fileList of samples used and Genbank Accession Numbers. List of samples used and Genbank Accession Numbers.Click here for fileList of loci sequenced and primers used for PCR amplification and sequencing. List of loci sequenced and primers used for PCR amplification and sequencing.Click here for file


Streptococcus mutans. In addition, we constructed a chimeric protein by cutting the C-terminal domain of the ADP-Glc PPase from Escherichia coli and pasting it to the entire S. mutans UDP-Glc PPase. Both proteins were fully active as UDP-Glc PPases and their kinetic parameters were measured. The chimeric enzyme had a slightly higher affinity for substrates than the native S. mutans UDP-Glc PPase, but the maximal activity was four times lower. Interestingly, the chimeric protein was sensitive to regulation by pyruvate, 3-phosphoglyceric acid and fructose-1,6-bis-phosphate, which are known to be effectors of ADP-Glc PPases from different sources. The three compounds activated the chimeric enzyme up to three-fold, and increased the affinity for substrates. This chimeric protein is the first reported UDP-Glc PPase with allosteric regulatory properties. In addition, this is a pioneer work dealing with a chimeric enzyme constructed as a hybrid of two pyrophosphorylases with different specificity toward nucleoside-diphospho-glucose and our results turn to be relevant for a deeper understanding of the evolution of allosterism in this family of enzymes.In bacteria, glycogen or oligosaccharide accumulation involves glucose-1-phosphate partitioning into either ADP-glucose (ADP-Glc) or UDP-Glc. Their respective synthesis is catalyzed by allosterically regulated ADP-Glc pyrophosphorylase  or unregulated UDP-Glc PPase (EC 2.7.7.9). In this work, we characterized the UDP-Glc PPase from  Other specific NDP-sugar PPases complement the metabolic scenario for the production of the multiple mono-, oligo-, and poly-saccharides in the cell, which are found as free components or covalently bound to proteins and lipids  , which has a wide buffering range (from pH 6.0 to pH 10.0), and tricine  SmuGalU and the chimeric SmuGalU-Δ294EcoGlgC enzyme were determined by gel filtration using a Tricorn 5/200 column . A Gel Filtration Calibration Kit-High Molecular Weight  with protein standards including thyroglobulin (669 kDa), ferritin (440 kDa), aldolase (158 kDa), conalbumin (75 kDa) and ovoalbumin (44 kDa) was used. The column void volume was determined using a dextran blue loading solution .The molecular mass of the i (after hydrolysis of PPi by inorganic pyrophosphatase) by the highly sensitive colorimetric method previously described [2, 1.5 mM UTP, 0.2 mg/mL bovine serum albumin, 0.5 mU/μL yeast inorganic pyrophosphatase and a proper enzyme dilution. Assays were initiated by the addition of Glc-1P in a total volume of 50 μL. Reaction mixtures were incubated for 10 min at 37 °C and terminated by adding the Malachite Green reactive [i was measured at 630 nm with an ELISA EMax detector (Molecular Devices) and using (sodium PPi) as standard.Synthesis of UDP-Glc was assayed by following the formation of Pescribed . The stareactive . The comOne unit (U) of enzyme activity is equal to 1 μmol of product formed per minute under the respective assay conditions specified above.versus substrate (or effector) concentration (mM), and kinetic constants were determined by fitting the data to the Hill equation as described elsewhere [nH), the maximal velocity (Vmax), and the kinetic constants that correspond to the activator, substrate or inhibitor concentrations giving 50% of the maximal activation (A0.5), velocity (S0.5) or inhibition (I0.5). All kinetic constants are the mean of at least three sets of data, which were reproducible within ±10%.Kinetic assays were performed using specified concentrations and conditions for all reaction mixture components. Saturation curves were performed by assaying the respective enzyme activity at saturating level of a fixed substrate and different concentrations of the variable substrate. The experimental data were plotted as enzyme activity (U/mg) lsewhere . FittingC. glutamicum in complex with magnesium and UDP-Glc , the apo structure of the UDP-Glc PPase from H. pylori , the structure of the ADP-Glc PPase from A. tumefaciens (PDB code 3brk), and the structure of potato tuber ADP-Glc PPase in complex sulfates in the putative regulatory site. In this way, the coordinates of the UDP-Glc PPases provide the structural information to build the S. mutans domain of the chimeric enzyme (N-terminus), and the ADP-Glc PPases the information needed to build the E. coli domain of the chimeric (C-terminus). The A. tumefaciens structure is particularly good for this, since it is a bacterial enzyme like E. coli, but the potato tuber structure provides information about where the sulfate ligands will go. Similarly, the C. glutamicum was used to place the product UDP-Glc in the model. The reliability of the model was evaluated using the programs Verify3D [Modeling of the chimeric enzyme was performed using the program Modeller 9v1 . For thaVerify3D . All theE. coli ADP-Glc PPase to the entire UDP-Glc PPase from S. mutans produces a chimeric protein with UDP-Glc PPase activity sensitive to allosteric activation by specific metabolites. To the best of our knowledge this is the first report on allostery by binding of small molecules to a UDP-Glc PPase (even more in an NDP-Glc PPase distinct of ADP-Glc PPase) from prokaryotic or eukaryotic origin [E. histolytica enzyme that responds to regulation after modification by oxidants and reducing agents of critical cysteine residues [Herein, we present results that strongly support that fusion of the C-terminal domain of c origin . Previouc origin –46; and residues .39 is important in the interaction with Fru-1,6-bisP with E. coli ADP-Glc PPase [32 from A. tumefaciens ADP-Glc PPase (similar to Lys39 in the E. coli enzyme), Arg33, and Arg45 are involved in allosteric effector binding [E. coli ADP-Glc PPase N-terminal domain in the activation of the enzyme [E. coli and A. tumefaciens ADP-Glc PPases indicated that the C-terminal region was critical in determining the affinity and specificity to effectors [N- and C-terminal domains are interconnected in the response of the enzyme to the allosteric effectors. In this context, our results with the chimeric enzyme SmuGalU-Δ294EcoGlgC support this model, since we clearly demonstrated that the presence of a single C-terminal domain causes sensitivity to an allosteric activator to a previously non-allosteric UDP-Glc PPase.ADP-Glc PPases are allosteric enzymes catalyzing the key step in glycogen and starch synthesis in bacteria and plants, respectively ,2. Many lc PPase –49. In a binding . In thise enzyme . In addie enzyme ,51 Howevffectors ,22. ThisSmuGalU-Δ294EcoGlgC is a novel feature acquired by the S. mutans UDP-Glc PPase after being transformed (by domain fusion) in the hybrid enzyme. The latter strongly supports the functional allosteric regulatory role of the C-terminal domain found in ADP-Glc PPase. Results also support the view that such a domain can be modularly fused to add allosteric properties to different PPases. It is tempting to speculate that evolution followed a similar strategy to modify one enzymes of such type (with specificity toward ADP-Glc), elongating the protein to trigger allosteric regulation in a general way. Later, critical changes in the C regulatory domain would confer specificity for different allosteric effectors within ADP-Glc PPases. We do not know the mechanism by which the N-terminal domain is activated in presence of the C-terminal domain and the proper activator, but our experiments indicate that the catalytic domain of NDP-Glc PPases may have an intrinsic property to have their activity modulated in presence of certain interactions, even when they are not natively regulated. In this case, the presence of a foreign domain triggers the allosteric properties.It has to be remarked that the activation pattern exhibited by chimeric