Penicillium marneffei to have extensive spatial genetic structure at local and regional scales, and although there has been some genetic evidence that a sexual cycle is possible, this haploid fungus is thought to be genetically, as well as morphologically, asexual in nature because of its highly clonal population structure. Here we use comparative genomics, experimental mixed-genotype infections, and population genetic data to elucidate the role of recombination in natural populations of P. marneffei. Genome wide comparisons reveal that all the genes required for meiosis are present in P. marneffei, mating type genes are arranged in a similar manner to that found in other heterothallic fungi, and there is evidence of a putatively meiosis-specific mutational process. Experiments suggest that recombination between isolates of compatible mating types may occur during mammal infection. Population genetic data from 34 isolates from bamboo rats in India, Thailand and Vietnam, and 273 isolates from humans in China, India, Thailand, and Vietnam show that recombination is most likely to occur across spatially and genetically limited distances in natural populations resulting in highly clonal population structure yet sexually reproducing populations. Predicted distributions of three different spatial genetic clusters within P. marneffei overlap with three different bamboo rat host distributions suggesting that recombination within hosts may act to maintain population barriers within P. marneffei.Molecular genetic approaches typically detect recombination in microbes regardless of assumed asexuality. However, genetic data have shown the AIDS-associated pathogen  Penicillium marneffei, an endemic AIDS-associated pathogen in Southeast Asia. Previous studies have shown that P. marneffei has a pattern of extreme clonality despite the ability to disperse across wide distances and the presence of mating type genes that are required for sexual recombination. In this study we used genetic markers, comparative genomics, experimental data, and spatial models to determine the influence of sex on P. marneffei populations, and we found that although there was substantial evidence of sexual recombination, most of the recombination in natural populations was limited to sexual neighborhoods, amongst genetically similar and spatially close individuals. Based on the results of experiments and spatial models we found support for sex occurring in bamboo rats that are known to harbor P. marneffei and the pathogens sexual neighborhoods. Our study suggests that the high levels of effective clonality and endemicity found in P. marneffei may have more to do with specific host interactions than with an innate inability to generate population genetic diversity through sexual recombination.Fungal pathogen populations show patterns ranging from globally recombining to endemic and clonal. Among the most genetically and spatially restricted fungi is the highly clonal pathogen  Cryptococcus neoformans, Coccidioides sp., Histoplasma capsulatum and Penicillium marneffei. These fungi are maintained in natural environmental reservoirs that might contribute to structured populations via local adaptation, and they are thought to be largely clonal. However, fungi have many different mating systems that encompass asexual propagation t7hrough multiple forms of sexual and parasexual recombination, and clonal structure may be arrived at via very different mechanisms Hypotheses of globally continuous populations and strict clonality in putatively asexual microbial pathogens are rarely supported MAT) in order to undergo sexual reproduction. If no mating partners are present, then sexual reproduction does not occur and the fungus reproduces asexually . In this case, the relative capacities of fungal lineages to disperse and co-occupy environmental niches can drive population-level recombination rates. If strains of opposite mating type do not equally penetrate environments then species recombination rates may be reduced to levels nearing complete asexuality Penicillium marneffei shows extensive spatial genetic structure at local and regional scales across Thailand P. marneffei, this haploid fungus is thought to be genetically, as well as morphologically, asexual within these populations Heterothallic mating systems in fungi require physical contact between two isolates containing opposite mating types at the mating-type locus (P. marneffei genome show evidence of sex? 2) How are populations of P. marneffei genetically structured? 3) Can population structure be reconciled with sex? 4) Do spatial or host factors correlate with population structure and sex? We use comparative genomics to identify genes linked to mating and genomic signatures of mutation bias associated with meiosis, and we experimentally detect recombination in vivo. We expand our collection of population genetic data across southeast Asia to include mating type data and 34 isolates from bamboo rats in India, Thailand and Vietnam, and 273 isolates from humans in China, India, Thailand, and Vietnam. Together these data form a mosaic that reveals some physical and genetic underpinnings of mating in P. marneffei that are linked to patterns of genetic diversity across its known endemic range.In this study, we use comparative genomics, experimental approaches, and population genetic data to identify the role of sexual recombination in maintaining spatial and genetic structure in this infection. We attempt to answer 4 specific questions: 1) Does the A. fumigatus), NZ_ABAR00000000 (P. marneffei), and NZ_ABAS00000000 (T. stipitatus). We screened transposon families for substitution bias by making BLAST based alignments to determine the dominant form of a functional integrase gene in each family. We counted the type of substitution based on differences of alleles as low as 70% identical to the dominant intact type. We compared gene sequences of the genomic region between slaB and apnB (the genes that flank the MAT idiomorph in related fungi) of strains FRR2161 and FRR3842.We used 84 sexual cycle genes  to blastP. marneffei from humans and vertebrate hosts (bamboo rats), covering the known global range of the fungus. Our study obtained 273 epidemiologically unlinked human isolates of P. marneffei from HIV-AIDS patients covering the time-period 1959 to 2005. Of these isolates, 258 were georeferenced to either the broad geographical region of collection or the patients home address. The remaining 15 isolates were recovered from patients whose infections were diagnosed in non-endemic regions, and no accurate geographical origin could be assigned. In addition to human isolates of P. marneffei, we obtained 34 isolates from the bamboo rats species Rhizomys pruinosis (n = 3), R. sumatrensis (n = 13), R. sinensis (n = 1) and Cannomys badius (n = 17). We also include the type isolate for P. marneffei Segretain et al. ATCC 18224, CBS 388.87, isolated from R. sinensis in 1959 et al.We acquired 307 isolates of MAT1-1 α box and MAT1-2 high mobility group idiomorphs was determined using the PCR protocol detailed by Woo et al.The presence within each of isolate of the P. marneffei. We used the package adegenet and its dependencies in R to conduct spatial PCA and DAPC analyses P. marneffei genetic clusters. We measured distributional overlap using Schoener's D and a resampling approach D based on resampling of R. sumatrensis and Cannomys  were mixed in a 1∶1 ratio to form the inoculum (S9). Serial dilutions of homogenized saline samples were plated (no later than 6 hours after they were removed from the mice) on Sabouraud agar. Colonies were counted after 4 days in 27°C. Individual colonies used for DNA extraction and subsequent genotyping as before Five co-housed outbred CD-1 male mice (16–18 g) were inoculated intranasally with 10All the clinical studies from which isolates are available were approved by the Wellcome Trust ethics committees at the study sites, in the UK and by the regulatory authorities of the countries involved. All patients or their next of kin gave written informed consent and all patient data are anonymised. This work strictly complied with the animal regulations and guidelines under UK law and was approved by Imperial College's Ethical Review Process (ERP) Committee and the British Home Office. All murine work was carried out in a Biosafety level 3 secure animal facility under licensed approval from the British Home Office.P. marneffei of genes known to be involved in sexual development in fungi. First, comparing between strains FRR2161 and FRR3842 revealed that the region between genes slaB and apnB resembled other fungal mating type idiomorphs. A region of complete dissimilarity was flanked by regions that were nearly identical between the strains , a process by which some fungi silence genes involved in mobile genetic element function by preferentially mutating repeated sequences within their genomes, is associated with meiosis P. marneffei transposon family Ty-1 with a skew towards G to A and C to T transitions . We also detected significant ‘global’ genetic structure  but no ‘local’ genetic structure (negative correlation) using spatial principal coordinate analysis Microsatellite allelic diversity was high overall and within localities . With thulations . Phylogeulations . Using dulations . As expeet al.−6 and 2.50×10−5 mutations per generation P. marneffei between 3×10−5 and 2.50×10−4, a rate about half that observed in wild yeast M), which represents the minimum number of recombination events necessary to explain alleles failing the four gamete test P. marneffei, but similar to previous results the inferred levels of clonality remain among the highest observed for fungi Linkage disequilibrium was high throughout the sample with an overall of 0.113 . We deteP. marneffei showed a distribution of mating types that was significantly skewed (p = 0.02 or p = 0.04 when clone corrected) from a ratio of 1∶1 in favour of an overabundance of MAT1-1 alleles, but some local populations were skewed towards MAT1-2 alleles  generations. Alternatively, in a completely sexual population without selection associated with a mating type, MAT alleles would be maintained at frequencies near 0.5 with very limited variance because all individuals in each generation will possess MAT alleles according to a binomial distribution, and there is no opportunity for drift beyond a single generation. MAT allele counts can be used to represent the reduction in effective population size caused by drift in MAT ratios MAT allele frequency depends on population size and the frequency of sex. Based only on the differences in MAT allele frequencies between clusters and an intrinsic restriction on sex, P. marneffei would have an intrinsic upper bound of sexual recombination frequency at less than 4.5% given a modest population size of 1000. This small level of sex could explain the highly skewed ratio of MAT alleles in Cluster 3 and still accommodate the 1∶1 ratio in Cluster 1 while avoiding any fixation of MAT alleles. However, if the intrinsic sexual recombination rate explained the distribution of MAT alleles it would predict equal frequencies of clone detection across populations. Instead, percent clonality tracks the MAT allele skew, suggesting that sexual recombination in Cluster 3 is reduced relative to Cluster 1  of the recombinant genotype . This observed range overlap supports a host specific effect on P. marneffei population structure.The scale of recombination determines the efficacy of adaptation and the adaptive potential of populations. Although recombination across large distances allows generation of greater genetic diversity and more rapid spread of advantageous alleles, it disrupts locally advantageous combinations reducing local ecological genetic correlation. When sex is limited to small geographic distances it can reinforce local adaptation, and when limited to smaller genetic distances can reinforce genomic coadaptation. Together these effects can promote ecological speciation  1 and 3 . HoweverP. marneffei  Spatially restricted dispersal keeps individuals in contact with only closely related individuals; 2) Genetic incompatibility between dissimilar individuals restricts sex to genetically similar individuals; 3) Local adaptation restricts the ability of dissimilar genotypes to penetrate habitats ensuring mating between genetically similar individuals. All three are likely to be partially correct. Although the genetic evidence shows spatial limitations to effective dispersal, the physical dispersal of airborne conidia is not likely to be a limiting factor, and four genetically identical clones are dispersed across distances over 800 km. We have little information about the effect of genetic similarity on mating success in P. marneffei, but genetic restrictions on successful recombination are present in some plant pathogens Asexual spores are common P. marneffeiP. marneffei despite abundant asexual reproduction in the lab suggests that there is a selective advantage for sex not associated with the advantages of greater adaptive potential provided by outcrossing. One major consequence of sexual clonality is release from Muller's Ratchet compared to asexuality P. marneffei in the subgenus Biverticillium, outcrossing has not been shown to occur, but self-fertility is common Previous work has focused on the consequences of selectively neutral loss of sex in P. marneffei might withstand stress by mating when it would otherwise not survive. If that were the case, recombination in P. marneffei might be clustered in space or time where or when stress occurs. Unfortunately, little is known about the natural ecology of P. marneffei, and any conditions that might allow mating to occur are unknown. Isolates are commonly recovered from bamboo rats, yet the epizoology of the fungus is poorly known including unknown routes of infection and unknown course and outcomes of the zoonosis. In other dimorphic fungi including Histoplasma and Blastomyces, mating in natural populations is also poorly known, but in these species it mating has long been studied outside of the host and at lower temperatures in vitro P. marneffei.Another compelling scenario favouring sex recognises the opportunity presented by mating itself for dramatic shifts in morphology and physiology. A predominant view in the fungal literature is that sex occurs in otherwise mostly clonal fungi in response to stressful conditions P. marneffei has some parallels with other fungal and non-fungal eukaryotic pathogens Leishmania brasiliensisLeishmania results in sexual neighbourhoods of pathogen genotypes with high differentiation at multiple spatial scales Plasmodium falciparum, high inbreeding has been linked to faster emergence of drug resistance in some low infection intensity regions, but inbreeding has also emerged as a general property of P. falciparum populations regardless of infection intensity Toxoplasma gondii and Sarcocystis neurona, ‘clonal’ emergence is enabled by high rates of selfing and results in spatially structured populations Candida albicans, also undergoes same-sex mating that can facilitate inbreeding and the ability to accelerate evolution via sex within clonal populations C. neoformans, multiple ecological niches where recombination between strains with opposite mating type occurs have been found C. neoformans globally is likely to occur between strains of the same mating type, and although there is as yet no indication of what factors alter the probability of this kind of inbreeding across natural populations, it may have facilitated the global emergence of a single mating type and highly clonal populations Cryptic mating and inbreeding in Figure S1DAPC cluster analysis.(PDF)Click here for additional data file.Figure S2Dispersal kernel effects on spatial genetic correlation.(PDF)Click here for additional data file.Figure S3Simulated and observed spatial genetic correlation.(PDF)Click here for additional data file.Figure S4Distribution of markers and within contig recombination.(PDF)Click here for additional data file.Figure S5Detection of putative recombinant isolates.(PDF)Click here for additional data file.Table S1P. marneffei.Mating associated genes detected in (PDF)Click here for additional data file.Table S2Linkage disequilibrium.(PDF)Click here for additional data file.Text S1P. marneffei – bamboo rat species overlap.Analysis of (PDF)Click here for additional data file.Text S2In vitro and in vivo co-inoculation.(PDF)Click here for additional data file.


Bacopa monnieri L.) accessions were evaluated using random amplified polymorphic DNA (RAPD) and inter simple sequence repeats (ISSR) markers. During RAPD analysis, amplification of genomic DNA of the 15 accessions by 22 primers generated 197 fragments, of which 187 were polymorphic with an average of 8.95 bands per primer. The amplified products varied in size from 2,200 to 250 bp. Twenty-five selected ISSR primers produced 284 bands across 15 accessions, of which 270 were polymorphic with an average of 10.80 bands per primer. The PIC value ranges from 0.363 to 0.908 for RAPD primers, while 0.419 to 0.836 in case of ISSR. The size of amplified bands ranged from 2,800 to 240 bp. Similarity index values ranged from 0.16 to 0.95 (RAPD), 0.18 to 0.98 (ISSR) and 0.179 to 0.945 for pooled ISSR and RAPD markers data. Mantel test revealed the similar distribution pattern of the polymorphism between RAPD and ISSR markers and the correlation co-efficient (r) was 0.71384. The results indicated that both of the marker systems RAPD and ISSR, individually or combined can be effectively used in determination of genetic relationship among B. Monnieri accessions collected from different parts of Central India. It could be concluded that the information of genetic similarities and diversity among Brahmi accessions is necessary for their conservation and breeding programs.Genetic variations of 15 Brahmi ( Bacopa monnieri (L.) Penn. commonly known as ‘Neera-Brahmi’ of family Scrophulariaceae is a small prostrate herb that grows wild in marshy and damp places near water logs throughout India. B. monnieri (Brahmi) has been used for centuries as a traditional Ayurvedic medicine to enhance memory and to prepare popular ayurvedic preparations like ‘Brahmirasayanam’ and ‘Brahmighritam’ , Department of Science and Technology, Government of India . The continuous exploitation of B. monnieri from the natural habitat has now resulted in the depletion of natural population. The present status of the plant attracted attention of biotechnologists to conserve this important medicinal herb. Morphological traits display continuous phenotypic range and work as quantitative traits dominated by multigenes  were collected from various locations of Central India and maintained at Biotechnology Centre, Jawaharlal Nehru Agriculture University, Jabalpur, India.A total of 15 accessions , 10× PCR buffer with 2.5 mM MgCl2 and 200 μM of each dNTP mixture , 15 pmol of 10-mer RAPD and ISSR primers . Each sample was amplified in a reaction mixture containing 50 ng genomic DNA, Pij)2, where Pij is the frequency of the ith pattern revealed by the jth primer summed across all patterns revealed by the primers  values were calculated for each RAPD and ISSR primer according to the formula: PIC = 1 − Σ and plant type (spreading or semi-erect) were used to identify B. monnieri accessions , stem (thickness and color), leaf size  for DNA amplifications through PCR, out of which only 22 primers responded to all the accessions  was recorded between BM-7 and BM-4, while the lowest similarity value (0.16) between BM-14 and BM-13 (data not shown). Cluster analysis was performed on the basis of similarity co-efficient generated from RAPD profiles. The cluster analysis divided all the Brahmi genotypes under study into two major groups Fig. . Major gThe genetic structure of plant populations reflects the interactions of many different processes such as the long-term evolutionary history of the species , mutation, genetic drift, mating system, gene flow, and selection Slatkin . All of B. monnieri with RAPD markers. High levels of polymorphism found in the present investigation reveal that RAPD markers as a suitable tool for genetic diversity studies. This study will pave the way for detailed research to understand all the aspects of this divergence. RAPD has been successfully utilized for the identification of medicinal plants , which indicates a good fit among RAPD and ISSR marker systems. Cluster analysis performed from combining data of both markers generated a dendrogram separating the genotypes into two clusters. Cluster I further divided into two sub clusters. First sub cluster contained four Brahmi accessions, namely, BM-1, BM-2, BM-4 and BM-8. Within the second sub cluster comprising nine accessions , BM-12 was very closely related to BM-13 (0.945) followed by BM-9 (0.941). Cluster II comprised only two accessions BM-11 and BM-14 with a genetic similarity index of 0.838. The dendrograms generated by both approaches individually (RAPD and ISSR) were in strong agreement with each other as well as with combined (RAPD-ISSR) approach. Two major groups were obtained and most of the related accessions were found to be grouped together  also supports the similar clustering patterns as both spreading plant type have medium leaf size, dark green leaf color with thin green stem.The similarity co-efficients of the 15 Brahmi accessions based on RAPD and ISSR markers ranged from 0.945 to 0.179 among all the genotypes. Accessions BM-13 and BM-12 showed the highest similarity index (0.945), while the lowest (0.179) between BM-14 and BM-7 Table  test andher Fig.  found twB. monnieri with molecular approaches revealed that accessions collected from nearby locations fell into different clusters and those from geographically different locations fell in the same cluster. Occasionally, some of the accessions from nearby geographical locations fell in the same cluster. These results imply that multiplicity of factors including the geographical locations were responsible for the selection of genotypes that got naturalized at the sites of collections. Similar results have been reported earlier for several plant species (Gupta et al. The cluster analysis of 15 accessions of It was also observed from this study that some accessions were collected from the similar climatic zone does not exhibit similar morphological characteristics. This suggests that morphologic divergence observed cannot solely be attributed to environmental variations but possibly to a genetic restructuring evolved in the populations. However, to test this hypothesis, it would be necessary to collect extensive morphologic data and subject them in the evaluation of the distribution of variability.In general, the molecular classifications more or less follow morphological classification. However, in our study, discrepancy exists between morphological characteristics and molecular data. This might be most likely the result of the primary stages of Brahmi breeding, during which most cultivars and varieties derived from open pollination, artificial selection, and are maintained by vegetative propagation. In similar studies in olive (Hagidimitriou et al. It can be concluded that RAPD and ISSR markers may be a more useful tool for the identification of Brahmi than morphological characters. The present findings can help the genetic variation analysis among different accessions of Brahmi. On the basis of the findings of the present study, we can conclude that Central India is a good source of genetic variability. However, detailed study is desirable to understand all the aspect related to variations. Hence, further information will be necessary on patterns of gene flow within and between population and its effects on reproductive and demographic processes, to assess its impact on population viability. The accessions showed a considerable level of genetic diversity, indicating a high genetic variability in the population. The genetic variability in a gene pool is normally considered as being the major resource available for breeding programs.


Escherichia coli infecting two populations of wild elephants: one in Amboseli National Park and another in Samburu National Reserve, Kenya. If E. coli transmission is strongly influenced by elephant social structure, E. coli infecting elephants from the same social group should be genetically more similar than E. coli sampled from members of different social groups. However, we found no support for this prediction. Instead, E. coli was panmictic across social groups, and transmission patterns were largely dominated by habitat and host traits. For instance, habitat overlap between elephant social groups predicted E. coli genetic similarity, but only in the relatively drier habitat of Samburu, and not in Amboseli, where the habitat contains large, permanent swamps. In terms of host traits, adult males were infected with more diverse haplotypes, and males were slightly more likely to harbor strains with higher pathogenic potential, as compared to adult females. In addition, elephants from similar birth cohorts were infected with genetically more similar E. coli than elephants more disparate in age. This age-structured transmission may be driven by temporal shifts in genetic structure of E. coli in the environment and the effects of age on bacterial colonization. Together, our results support the idea that, in elephants, social structure often will not exhibit strong effects on the transmission of generalist, fecal-oral transmitted bacteria. We discuss our results in the context of social, environmental, and host-related factors that influence transmission patterns.Social structure is proposed to influence the transmission of both directly and environmentally transmitted infectious agents. However in natural populations, many other factors also influence transmission, including variation in individual susceptibility and aspects of the environment that promote or inhibit exposure to infection. We used a population genetic approach to investigate the effects of social structure, environment, and host traits on the transmission of  Social structure is thought to play a profound role in the transmission of both directly and environmentally transmitted infectious agents To date, most support for socially structured transmission of infectious agents comes from theoretical models Escherichia coli to test the influence of social structure, environment, and host traits on patterns of bacterial transmission in wild African savannah elephants, Loxodonta africana . African elephants live in fission-fusion societies where individuals belong to predictable social groups, but the strength of associations between individuals and groups can vary depending on ecological conditions In this study, we used population genetic information on E. coli is an enteric commensal and an occasional pathogen in many vertebrates. It is transmitted between hosts through both direct physical contact and the ingestion of fecal-contaminated food and water E. coli is a common model organism to study patterns of bacterial transmission in wildlife because it is easy to sample individual E. coli isolates from fecal samples E. coli reproduce clonally, and recombination–i.e., the exchange of genes or gene segments with other bacteria–is usually too low to obscure its clonal structure and transmission patterns E. coli may lend insight into the spread of other, more harmful fecal-oral transmitted microbes, such as Salmonella sp. E. coli transmission patterns E. coli than more distantly connected hosts E. coli than members of different households E. coli than members of different groups E. coli infects many vertebrate species; hence, its population structure may often not be heavily influenced by the social structure of a single host species E. coli can persist for several days to several years in water, sediment, and soil E. coli is a member of the gut microbiome, and host age and ecological interactions among bacteria may influence which isolates establish in a given host Prior studies have found that host social structure can be correlated with E. coli transmission among wild elephants. We examined the role of social structure in the context of several other factors that may also influence E. coli transmission, including aspects of the habitat, host sex, and host age. We inferred patterns of transmission using the population genetic structure of E. coli isolated from elephants living in two populations: the Amboseli ecosystem in southern Kenya, and the Samburu-Laikipia ecosystem in central northern Kenya. Although both populations occupy areas with a similar climate, they differ in that the Amboseli population has a permanent swamp in their core habitat, while the Samburu population does not. We addressed two main questions: 1) Do host social structure and patterns of habitat use predict the population genetic structure of E. coli? And 2) what other aspects of individual hosts or their environments are important in shaping the population genetic structure of E. coli? If social structure influences E. coli transmission, we predicted that: a) E. coli infecting elephants from the same family should be genetically more similar than E. coli infecting members of different families, and b) the degree of range overlap would predict the degree of E. coli genetic similarity between families. In terms of host traits, we tested whether male elephants, which have larger ranges than females and possible differences in immune function, harbored genetically more diverse or potentially more pathogenic E. coli than female elephants. Finally, we explored age-related effects on patterns of E. coli infection, and specifically tested the prediction that elephants more similar in age are infected with genetically more similar E. coli, compared to elephants more different in age.Our main objective was to test whether host social structure plays a detectable role in shaping patterns of All protocols were noninvasive and adhered to the guidelines approved by the Institutional Animal Care & Use Committee (IACUC) of the University of Notre Dame. In Kenya, permission to conduct research was granted by the Kenyan government through research permit number NCST RRI/12/1/MAS/118/4.2), in southern Kenya, and the Samburu-Laikipia ecosystem , which lies about 390 km to the north of Amboseli, in central northern Kenya. Elephant migration between these parks is probably currently rare, given the level of urban development between these locations. Both populations have been subject of long-term research; elephants in Amboseli have been monitored continuously for over 40 years, while elephants in Samburu have been monitored continuously for over 15 years Study subjects were wild elephants living in the Amboseli ecosystem  of each group within the protected areas and the percent of spatial overlap between ranges in the protected areas were estimated using GPS locations of sightings of family members collected over a five-year period prior to E. coli sampling (March 2005 to March 2010 in Amboseli and January 2006 to December 2011 in Samburu). We chose a five-year span to maximize the number of sightings for each family (To test whether host occupancy patterns influenced the transmission of h family . Elephan2) of each family’s range in swamp habitat, and the percent overlap among pairs of families in swamp habitat (Samburu lacked swamp habitat).From these GPS data, we used a kernel density estimator in BIOTAS software (Version 2.0a.3.8) to calculate a “protected area range” for each family from 95% of GPS locations by eliminating 5% of the locations that were spatial outliers . To miniE. coli was cultured from fecal samples collected from known elephants during intensive 1-month sampling efforts during July 2010 in Amboseli and June 2011 in Samburu (E. coli might be most likely to be found). Samples were typically collected within 10 minutes of defecation, and we avoided all sections of the fecal sample that may have made contact with the ground. Samples were kept at ambient temperature for 1 to 4 hours until we cultured and collected individual E. coli isolates from each sample. Specifically, we lit a candle in the workspace to create an up-draft. We then lightly touched the surface of the fecal sample with a flame-sterilized metal loop to collect a small amount of feces (an amount barely visible to the naked eye), and streaked the loop onto individual MacConkey agar plates (MacConkey agar is selective for gram negative bacteria and indicates the presence of lactose fermentation). Samples were incubated at 37°C for 12–24 h to allow colonies to grow. We collected one fecal sample per individual, and for each fecal sample, we used sterile toothpicks to collect 4 to 10 putative E. coli colonies . After collection, each putative E. coli colony was transferred to its own tube, containing 95% ethanol. We refer to these preserved colonies as “isolates”. Each putative E. coli isolate was stored at room temperature for up to four weeks prior to genetic analysis. Samburu . When meE. coli isolate using seven multi-locus sequence typing (MLST) loci adk (adenylate kinase), fumC (fumarate hydratase), gyrB (DNA gyrase) icd (isocitrate dehydrogenase), mdh , uidA (beta-glucuronidase) and ClpX (caseinolytic protease × homolog) E. coli. We extracted DNA from 2 to 4 individual E. coli isolates per Amboseli elephant and 4 E. coli isolates per Samburu elephant. DNA was extracted using DNAeasy (Qiagen tissue kit) following the manufacturer’s instructions. We amplified each MLST marker using the polymerase chain reaction (PCR) conditions described in E. coli .We genotyped each putative E. coli isolate. An E. coli isolate with a distinct concatenated sequence is henceforth referred to as a “haplotype”. Prior research has shown that E. coli haplotypes can belong to one of four major phylogenetic groups, referred to as A, B1, B2, and D E. coli Reference Collection (ECOR) consisting of 72 sequences with known phylogroup membership We concatenated the sequences from each MLST gene for each E. coli and hence our ability to detect transmission patterns. We calculated nucleotide diversities and Tajima’s D in Arlequin (Version 3.5.1.3) We examined basic patterns of genetic diversity, demographic history, and recombination rates since these forces might influence the population structure of E. coli population genetic structure, we used analysis of molecular variance (AMOVA) in Arlequin to partition genetic variance in E. coli sampled from adult female and juvenile elephants within and between host populations, family groups and individual hosts. Measuring the population genetic structure of bacteria can be challenging because the clonal structure may vary depending on the rate of recombination. Hence, we performed AMOVA and calculated FST using two different measures of genetic distance, each with their own assumptions. First, to account for evolutionary distance between haplotypes caused by mutations and recombination events, we calculated genetic distance based on the ClonalFrame analysis. Specifically, we measured “patristic distance” or the total branch lengths between each pair of isolates calculated from a 50% consensus evolutionary tree, assuming uniform nucleotide substitution and recombination using a Bayesian analysis in ClonalFrame. This approach to inferring transmission assumes that genetically more similar haplotypes share more recent common ancestors and more recent transmission events. Second, we measured “haplotype distance” by performing AMOVA using classic haplotype frequency-based measures of genetic variance, which ignore phylogenetic distance between haplotypes. This measure of genetic distance, which is based on the proportion of shared haplotypes, may be better at capturing patterns of transmission when evolutionary rates are high.To test the influence of host social structure on E. coli genetic similarity between family groups. As in the AMOVA’s above, E. coli isolates sampled from adult males were excluded from these analyses. Mantel tests were used to assess the correlation between matrices of the percent of range overlap and matrices of genetic differentiation (FST) based on patristic distance and haplotype distance between E. coli sampled from different family groups. In Amboseli we also conducted a second analysis using percent range overlap in swamps alone.We next tested whether range overlap in protected areas influenced E. coli genetic and phylogroup structure. First, using samples from Samburu only, we tested whether independent adult males  were infected with more diverse E. coli than adult females. Specifically, we performed a regression analysis with host sex and age as predictor variables and average nucleotide diversity among E. coli isolates from within a host as the dependent variable. When a covariance analysis showed that age was not an important predictor of E. coli nucleotide diversity within individuals, but sex was, we carried out an independent sample t-test between genetic distances of E. coli isolates from adult male and adult female hosts.We next performed three analyses to understand the associations between host traits (sex and age) and E. coli phylogroup. To test whether the proportion of isolates belonging to a given phylogroup changed as a function of host age and sex, we used the number of E. coli isolates belonging to a phylogroup from each individual elephant as the response variable and the total number of E. coli isolates obtained from that individual host as an offset variable. The use of the offset variable allowed us to model counts of each phylogroup as proportions. We used host sex and age as fixed factors, and host population as a random factor. The effect of age and sex on the proportion of isolates for some phylogroups did not vary by host population (e.g. A and B1). For these phylogroups, we instead ran a generalized linear model (GLM) that retained all the fixed factors but without including population as a random factor.Second, we used generalized linear mixed modeling (GLMM) to test whether host age or sex influenced the tendency for individuals to be infected with each phylogroup. We expected males to be more often infected with phylogroups associated with greater pathogenic potential (phylogroups B2 and D). We constructed a Poisson GLMM for each E. coli, as compared to animals more disparate in age. Specifically, we used Mantel tests to correlate pairwise matrices of difference in age with matrices of genetic distance between E. coli isolates sampled from that pair of elephants.Third, we tested the prediction that same-aged elephants are infected with genetically more similar strains of E. coli using 210 E. coli isolates from 85 adult female and juvenile Amboseli elephants, and 143 E. coli isolates from 36 Samburu elephants  was found within and between individual elephants living in the same population. Indeed, individual hosts tended to contain diverse haplotypes; for instance, within-host nucleotide diversities were around 1%, and the average number of pairwise nucleotide differences between isolates sampled from the same host was 30.8±25.1 in Amboseli and 24.4±18.8 in Samburu . In Amboseli, elephant families had considerable overlap with swamp, which constituted, on average 70% of a family’s range within this protected area . In terms of range overlap between families, the mean ± SD percent overlap in swamp was 27.86% ±22.87% (range: 0.95% to 80.84%).To test whether range overlap in protected areas was correlated with E. coli genetic similarity between families. We found mixed support for this prediction. In Amboseli, the percent of range overlap was not correlated with E. coli genetic similarity, whether we tested this relationship for complete ranges , or only for range overlap in swamp . However, we did observe a significant relationship between range overlap between families and genetic similarity of E. coli in Samburu .We expected that higher range overlap in protected areas would be associated with greater E. coli than adult females. In support, we found that adult males were infected with genetically more diverse strains than females as measured by nucleotide diversity . One explanation for these results is that age might predict a host’s probability of infection with a given phlyogroup, perhaps through age-specific patterns of susceptibility We also examined the correlation between ulations . SpecifiE. coli infecting wild elephants. We found little evidence for socially structured transmission; instead, the population genetic structure of E. coli was heavily influenced by processes occurring in the environment and at the level of individual hosts. Below we discuss our results, starting with the effects of habitat on patterns of E. coli transmission.Social organization and behavior can influence the transmission of both directly E. coli from members of their own family group than members of other families. Instead, E. coli isolates sampled from members of the same family were not genetically more similar compared to E. coli from different families, and families did not represent major barriers to E. coli gene flow.Many researchers have hypothesized that exposure to infectious disease is an important evolutionary cost of group living E. coliE. coli transmission are more common in some species than others. During rainy periods, elephants aggregate in large groups and have physical contact between members of different families, especially during play or mating, which may promote between-group transmission. In addition, elephants have high range overlap around water sources, which may serve as environmental reservoirs for E. coli and promote between-group transmission. By contrast, aspects of human behavior may make E. coli transmission within households much more common than between households, such as high rates of physical contact between family members, hand washing, cooking and eating at home, and the use of toilets and latrines.These results differ somewhat from prior studies on other social species, including giraffes, baboons, gorillas, and humans, which found that individuals with more frequent social contact were more likely to be infected with more similar strains of E. coli phylogroups vary in their prevalence across host species and abiotic environments, and the likelihood of socially structured transmission may depend on phylogroup identity. For instance, nearly 70% of isolates from the elephants in our study were attributed to phylogroup B1, a commensal form that is known to be environmentally ubiquitous, to infect a wide variety of animals, and to have high turnover within hosts Second, differences in study design may have led to higher rates of within- versus between-group contact rates in prior studies compared to our study. For instance, in the studies on baboons and gorillas, researchers chose social groups with non-overlapping home ranges, which should reduce the probability that individuals would encounter fecal contamination from non-group members E. coli transmission used the BOX-PCR method of Cesaris et al. E. coli in giraffes. Studies on E. coli infecting gorillas and humans used a similar approach called repetitive-element PCR E. coli genome, which may lend more power to distinguish relationships among strains. Future studies may find it valuable to compare results from these two methods of E. coli genotyping.Fourth, differences in genotyping methods may also explain why our results differed from some prior studies. In particular, two prior studies that found effects of social structure on E. coli from members of their own family than from members of other families, we observed some support for socially structured transmission via habitat overlap While our results indicate that elephants were not more likely to be infected by E. coli persistence times E. coli transmission between elephant groups.Another possible explanation for these mixed results is that differences in habitat moisture and the degree of habitat overlap between elephant family groups favored socially structured transmission via range overlap in Samburu, but not in Amboseli. Specifically, in Samburu, the habitat was drier, and the elephant groups exhibited a greater degree of range overlap than in Amboseli. These two forces may act in concert to increase the strength of socially structured transmission; harsh habitat may reduce E. coli . Hence, despite possible support for socially structured transmission, these results are far from conclusive about the role of social behavior in the transmission of E. coli between elephant groups.One final observation on socially structured transmission via range overlap: while we observed support for this hypothesis in Samburu, it is as yet unclear whether the patterns of transmission we observed between elephant groups were driven by socially mediated factors  or were instead driven by the fact that these elephant groups used the same areas and so were exposed to the same environmental sources of E. coli populations was structured within and between individual hosts, not family groups or host populations. This population structure–i.e., high gene flow between geographically distinct populations, but strong genetic differentiation between hosts–is typical of E. coli. For instance, researchers often find high levels of E. coli gene flow between host populations separated by large geographic distances E. coli is structured within and between individual hosts Most of the genetic variation in E. coli populations. In particular, E. coli is a normal member of the gut microbiome, and the process of microbiome assembly–including bacterial colonization, interactions among bacterial species, and interactions with the host’s genome and immune system–may influence which E. coli haplotypes occur in a given host E. coli populations in individual hosts: host sex and age. With respect to sex, we found that adult males were infected with more genetically diverse E. coli and were more likely to be infected with strains from phylogroup D than were adult females. This result is based on a relatively small sample size, and it should be interpreted with caution. Moreover, phylogroup proportions are not independent of each other; however, we observed no other significant relationships between sex and phylogroup proportions, suggesting that sex is the primary predictor of phylogroup D. If true, one explanation for this result is that adult male elephants range more widely than adult females, which may expose males to more diverse E. coli strains. Indeed, similar effects have been described for other infectious agents E. coli infection E. coli infection patterns E. coli infection are common across vertebrate species.For the elephants in Amboseli and Samburu, most individuals were infected with multiple, genetically diverse haplotypes, which often differed in identity and frequency from the haplotypes found infecting other members of their family or population. These patterns suggest that processes occurring at the level of individual hosts, as opposed to families or host populations, are most important in influencing the structure of E. coli populations. Specifically, elephants born around the same time were infected with genetically more similar E. coli than pairs of elephants further apart in age. This pattern occurred for pairs of elephants drawn from the same host population, as well as for pairs drawn from the two different populations . One explanation for these effects is that they are caused by age-related changes in gut morphology or immune function leading to differences in the composition of phylogroups in younger versus older elephants. While this explanation is possible, it is not well supported by our data, as we found few changes in phylogroup composition as a function of age.We also found effects of host age on E. coli infection reflect temporal structure in environmental E. coli. Specifically, individual hosts may be infected with E. coli when in the first few months of life, and while individuals are continually exposed to E. coli throughout life, most of these later strains may fail to establish E. coli within hosts and in the environment E. coli was sampled from several locations in a lake repeatedly for several days or years, there was strong genetic similarity among isolates collected on the same day or the same year across different locations separated by distances of 50 kilometers, as compared to E. coli collected on different days or years in the same location E. coli populations infecting animal hosts E. coli population structure have typically been explored over the scale of weeks or months, not decades. Given that elephant births are often seasonally clustered, and habitat and rainfall conditions can vary markedly between birth cohorts over their first years of life, these variations may affect transmission during the early acquisition of E. coli. That said, the time scale over which we observed temporal patterns on E. coli communities is surprising, given that B1 strains, which were the most common in our study, are among the most transient members of the gut. It is possible that B1 phylogroups behave differently in elephants as compared to other hosts. However, our results require further confirmation to see if they will be upheld. We encourage future researchers to test for similar temporal patterns within host populations.Instead, we think our results are more consistent with the idea that age-related patterns of E. coli transmission in wild elephants. Instead, transmission patterns were dominated by host habitat and aspects of individual hosts, such as individual sex and age. Strong patterns of socially mediated transmission may be limited to infectious agents with high host specificity, transmitted only via physical contact between hosts, and to hosts with social structures that minimize habitat overlap and contact between different group members. Generalist infectious agents that can be transmitted through the environment, such as E. coli, are common in wildlife, and they may be some of the most important from an evolutionary and a management perspective. In the future, we encourage researchers to incorporate multiple aspects of hosts and their environment, as well as social contacts, to gain the greatest insight into transmission patterns.Social structure is often proposed to be an important conduit for the transmission of directly and environmentally transmitted infectious agents. However, our results indicate that social structure plays, at most, a weak role in Figure S1Nucleotide diversity in E. coli as a function of host sex. Boxplots depict nucleotide diversity in E. coli infecting individual elephants as a function of host sex. This analysis was performed on adult animals from Samburu NR only.(TIF)Click here for additional data file.Figure S2The distribution of E. coli phylogroups groups as a function of host age. Plot depicts a cross-sectional analysis of the proportion of each phylogroup type found infecting elephant hosts of different ages. Relationships demonstrate that unclassified E. coli isolates increased in older age groups.(TIF)Click here for additional data file.Table S1E. coli isolates genotyped per family group, and the number of GPS sightings per family group.Sample information, including the number of elephant hosts per family group, the number of (DOCX)Click here for additional data file.Table S2E. coli isolates assigned to different phylogroups in Amboseli and Samburu. Unassigned isolates did not cluster with any known ECOR sequences.Percent of (DOCX)Click here for additional data file.Table S3E. coli sequences.Basic evolutionary parameter estimates for concatenated (DOCX)Click here for additional data file.


Banksia menziesii (Proteaceae), a widely distributed Western Australian tree of significance in local ecological restoration programs. An analysis of molecular variance (AMOVA) of 100 amplified fragment length polymorphism (AFLP) markers revealed significant genetic differentiation among populations (ΦPT = 0.18). Pairwise population genetic dissimilarity was correlated with geographic distance, but not environmental distance derived from 15 climate variables, suggesting overall neutrality of these markers with regard to these climate variables. Nevertheless, Bayesian outlier analysis identified four markers potentially under selection, although these were not correlated with the climate variables. We calculated a global R-statistic using analysis of similarities (ANOSIM) to test the statistical significance of population differentiation and to infer a threshold seed collection zone distance of ∼60 km  and 100 km (outlier markers) when genetic distance was regressed against geographic distance. Population pairs separated by >60 km were, on average, twice as likely to be significantly genetically differentiated than population pairs separated by <60 km, suggesting that habitat-matched sites within a 30-km radius around a restoration site genetically defines a local provenance seed collection zone for B. menziesii. Our approach is a novel probability-based practical solution for the delineation of a local seed collection zone to minimize negative genetic impacts in ecological restoration.An increasingly important practical application of the analysis of spatial genetic structure within plant species is to help define the extent of local provenance seed collection zones that minimize negative impacts in ecological restoration programs. Here, we derive seed sourcing guidelines from a novel range-wide assessment of spatial genetic structure of 24 populations of  Ecological restoration – the process of assisting the recovery of an ecosystem that has been degraded, damaged, or destroyed – is a rapidly emerging scientific discipline . Ideally the markers should capture the main sources of neutral and non-neutral population genetic variation – local adaptation, genetic drift, gene flow, and mutation – and the interactions between these sources. Given the complexity of these genetic objectives, there is no ideal single molecular marker technique. However, the polymerase chain reaction (PCR)-based multi-locus DNA fingerprinting technique amplified fragment length polymorphism (AFLP) is perhaps the most suitable marker to meet these objectives. AFLP efficiently delivers information for many markers from across the genome, and typically at least some of these markers detect signatures of natural selection and can strongly influence the overall patterns of genetic differentiation detected . Banksia menziesii is a key species used in the ecological restoration of disturbed and degraded sites across the Swan Coastal Plain (SCP), a region of high species diversity within the South-West Australian Floristic Region (SWAFR), an international biodiversity hotspot  estimate population genetic diversity and differentiation parameters, (ii) provide genetic guidelines for local provenance seed sourcing for the establishment of ecologically restored populations that have high evolutionary potential and are genetically integrated with existing local populations, and (iii) more generally, define a threshold distance that has biological significance, beyond which there are potentially negative restoration consequences from collecting seed for restoration. Additionally, we employ a population genomics approach to look for signatures of natural selection in the markers we have employed, through the identification of molecular marker outliers as well as associations between markers and environmental data obtained for each site.Here, we seek to delimit local provenance seed-source zones in an iconic Western Australian species, Banksia menziesii is a dominant over-story species, widespread along the deep sandy soils of the SCP  within populations, and overall, using GenAlEx v6.5b3  and Shannon's diversity index . Significance of pairwise population differentiation was also determined by permutation testing, and by comparison to the global R-statistic  to 1  (Chapman and Underwood R) and linear geographic distance visually, and by a Mantel test (with 9999 iterations) in Genalex v6.5b3. Sampling locations were plotted using GPS points on OziExplorer (http://www.oziexplorer.com) to generate accurate geographic distances (km) between each pair of locations.An analysis of pairwise population similarities was used to test for significant differences between all pairs of populations, using the ANOSIM  function in Primer V6 (Clarke and Gorley http://www.diva-gis.org/).Climate data  were obtained from the Australian Bureau of Rural Sciences Natural Resources Data Library. These data were then extrapolated to sample population coordinates with Diva geographic information system (http://manteltester.berlios.de/), which uses the Zt software tool  of the residuals of a null model  that are specific to each population and to each locus. The method uses a hierarchical Bayesian approach to estimate the posterior probabilities of two alternative models, one including the effects of selection and one excluding it. The results are expressed as posterior odds (PO), which indicate for each locus the ratio of posterior probability of the selection model against the neutral model and interpreted as different levels of evidence of selection according to Jeffreys scale. We used a threshold of PO >100 (“decisive”) for a marker to be considered under selection. This corresponds to a posterior probability of >0.99 for the model accounting for selection. BayeScan was run with 20 pilot runs with a burn-in of 50,000 followed by 50,000 iterations each, a sample size of 5000, a thinning interval of 10, and an FIS set at a mean of 0.05 based on known data for complete outcrossing in B. menziesii  = −2) means that 1% of corresponding outlier markers  are expected to be false positives. We then conducted simple and partial Mantel tests, as outlined above, on individual markers identified by the Bayesian allele frequency test.To detect signatures of natural selection on individual genetic markers, a Bayesian approach generalized from the method of Beaumont and Balding  was implii Scott . In addiB. menziesii plants sampled from 24 locations across the geographic range of the species, of which 79 were polymorphic (Table I) ranged between 0.12 and 0.21 (mean = 0.16). AMOVA partitioned 82% of the total variation among individuals within populations (Table PT = 0.18), which was significantly different from zero .MDS ordination of the genetic data showed an arrangement of populations that was largely associated with geographic proximity Fig. . A notabR of 0.39, which was significantly different from 0 (P < 0.001). Approximately half (149/276) of all pairwise population tests were significant at P < 0.001 as determined by 999 random permutations. There was a significant positive correlation between genetic distance (as measured by R) and geographic distance . The global R of 0.39 intersected the line of best fit through these points that corresponded to a geographic distance of ca. 60 km  generated an R > 0.39. This result was similar when calculated for the 0–20 km and 0–30 km distance classes. Beyond 60 km, there were 158 pairwise population comparisons, of which 49 (31%) generated an R < 0.39, and 109 (69%) generated an R > 0.39. Beyond 150 km, these values were 12% and 88%, respectively.ANOSIM for all markers generated a global Simple Mantel tests showed significant relationships between all pairs of distance matrices Table . PartialFST values that were 2–3 times those of non-outliers, with strongly positive alpha coefficients (1.5–2.3), “decisive” posterior probabilities (log10PO >2), and a FDR of <0.01% (log10q <−4.0) , one positive (G55 and B93) and one negative (G74 and B93). An MDS ordination of genetic dissimilarity from these four markers (not shown) largely reflected that generated from all markers  between these two genetic dissimilarity matrices.Four markers were identified as significant outliers by BayeScan analysis, with log10q <−.0  genetic distance (as measured by R based on these four markers) against geographic distance resulted in a weaker positive correlation  than for all markers combined  was found between the SCP populations and non-SCP populations  Fig. . The souB. menziesii. In particular, we used the relationship between the R-statistic  and geographic distance, to infer a biologically significant threshold seed collection distance. Beyond this threshold distance we suggest that there are potentially negative consequences from collecting seed for ecological restoration, although this ultimately requires experimental confirmation. This objective materially enhances the generic seed collecting guideline extremes of composite provenancing , which corresponded to a geographic distance of 60 km, or equivalently a 30-km radius around a restoration site. The unique strength of this analysis is that it enabled us to assign probabilities of genetically matching pairs of populations at various distance classes, depending on the proportion of points falling below and above the global R. Within 60 km, 66% of all population pairs fell below the global R, and 34% above. Beyond 60 km, 31% of all population pairs fell below the global R, and 69% above. Consequently, the probability of genetically matching population pairs  by chance when separated by >60 km is half that for populations separated by <60 km. Importantly, the proportion under 60 km does not change for the smaller distance classes of 30 km, nor 20 km. In contrast, above 150 km, there is only a 1 in 10 chance of genetically matching population pairs.For 79 variable AFLP markers in R values, from ∼0 to almost 0.8. For example, Bold Park is a 437 Ha remnant of coastal bushland in the western suburbs of metropolitan Perth that was declared an A-class reserve in 1998 and has been the subject of the most extensive ecological restoration effort in the Perth metropolitan area (BGPA B. menziesii for restoration. For these populations, R = 0.65. The relatively weak genetic similarity between populations in Bold Park and Kings Park has been observed in many other species (e.g., Krauss and He R and geographic distance remains when specifically comparing Bold Park to all other sites, with R > 0.39 for 63% of population pairs separated by >60 km, and 42% of population pairs separated by <60 km.However, even within 60 km, there was a large range in pairwise population rea BGPA . GeograpThis example serves to demonstrate the need to qualify the genetically determined threshold seed collection zone distance of 60 km with the recommendation that habitat and climate matching of the restoration site and potential seed-source populations within the threshold distance should be conducted wherever possible to increase the probability of matching genetically adapted seed-source populations with those in or around the restoration site (McKay et al. Four markers were identified as outliers, and therefore candidates for positive selection. None of these markers, however, were associated with the climate variables assessed here, and overall they were only weakly associated with geographic distance. The weaker association with geographic distance and the higher threshold distance, compared to analyses with all markers, suggests an underlying, yet undefined, complexity of selection driving variation at these markers, and that seed sourcing decisions made purely on the basis of geographic distance may have greater error for these putatively non-neutral than putatively neutral markers. This conclusion serves to emphasize the importance of habitat matching where possible within the defined threshold geographic distance based on overall marker variation. Detection of the variation at these outlier markers by chance alone seems unlikely given the attention to this issue by the BayeScan analysis through the robust FDR (Fischer et al. R-statistic threshold for significance of genetic distance of AFLP markers enables the quantification of probabilities of genetically matching populations as a function of geographic distance. This then establishes a solid quantitative framework for the testing of biological significance of the genetic marker results through the use of reciprocal transplant experiments (O'Brien et al. In conclusion, our novel consideration of the


Pterostichus oblongopunctatus F. (Coleoptera: Carabidae), in a fragmented and metal-polluted landscape to assess the consequences of human-induced changes on the population genetic structure. Genotypic variation at five microsatellite loci was screened in 309 beetles from 21 sample locations around zinc-and-lead smelter in southern Poland. Low levels of genetic differentiation among sampling sites were observed, suggesting high gene flow among populations. A negative correlation was found between levels of genetic differentiation and habitat patch size. No significant effects of metal pollution, in terms of genetic bottlenecks and genetic differentiation, were observed. Analyses revealed weak genetic clustering that is loosely tied to the geographic position of the sampled populations. Several tests of sex-biased dispersal were conducted. Most of them indicated male-biased dispersal. Differing levels of dispersal between females and males resulted in sex-specific spatial genetic patterns. Genetic differentiation was significantly correlated with geographical distance for males, but not for females, who were more diverged locally. Also, the effect of habitat patch size was sex-dependent, supporting the finding of different dispersal patterns between the sexes. This study demonstrated the application of microsatellite markers to answer questions regarding complex interactions between population structure and physical properties of the landscape. In the study system, migration appears to be sufficient to override potential effects of environmental pollution as well as habitat fragmentation. This investigation of population genetic structure indicated, for the first time, male-biased dispersal in carabid beetles.Ground beetles are an integral and functionally important part of many terrestrial ecosystems. Habitat change often influences population genetic structure of carabid beetles. In this study, genetic variation, population differentiation, and sex-specific dispersal patterns were studied in the forest ground beetle,  Anthropogenic disturbance may drive species to extinction or to local adaptation. Extinction probability and micro-evolutionary processes are strongly linked to the organism's mobility, especially in fragmented landscapes . CarabidCarabus violaceus was affected by the presence of major roads in the study area. Brouat et al. , from fragmented and polluted habitats in southern Poland. Molecular data were used to test several hypotheses. Firstly, overall high dispersal rate of the species was expected, because the animals are relatively small and macropterous, thus potentially can disperse by flight. High migration rates are usually associated with low levels of genetic population structuring. Bottlenecks, founder effects, and evolution by drift were not likely to occur. Secondly, because the species can be reasonably expected to be promiscuous or polygynous, male-biased migration is expected. In genetic terms, it can be expressed as a higher proportion of shared alleles between sampling sites in males than in females, due to more frequent migration events in males. Finally, if overall dispersal rate is high, effects of habitat fragmentation and pollution on population genetic structure can be expected to be weak or absent. That means that there should be no correlation between genetic diversity and patch sizes or contamination levels. Response to habitat fragmentation and pollution can also be sex-dependent, with the more mobile sex showing greater genetic homogeneity over the study area.This paper examines population genetic structure of the forest carabid, P. oblongopunctatus is common to woodlands in the Palearctic region, occurring in both deciduous and coniferous forests . All sampling sites were dominated by Scots pine, Pinus sylvestris L.  forest with a small number of other tree species, including oak, birch and rose. The sites chosen represent a broad range of metal pollution, with zinc, cadmium, and lead being the most important pollutants. The contamination levels at the sampling sites are reported as zinc concentration in the soil humus layer (To assess the geographic distribution of genetic variation within and among populations of us layer  because us layer . Four sowww.perkinelmer.com). Ten sampling sites showing extremely high levels of metal accumulation were located in close vicinity of the zinc-and-lead miningmetallurgic complex in Bolesław near Olkusz . Tissues were dried at room temperature, ground in a 1.5 ml Eppendorf tube with a small pestle, and incubated in 500 µl 10% Chelex and 5 µl proteinase K (20 mg/ml) at 55° C for 3 h. Five microsatellite loci  were analyzed using primers and methods described by Lagisz and Wolff  chord distance using POPULATIONS v.1.2.14 (Langella 2004). Confidence in tree topology was assessed by bootstrapping over loci  and the phylogenetic tree was visualized in TREEVIEW 1.6.6 .F, the probability that two genes share a common ancestor within a population. A Markov Chain Monte Carlo simulation with 100,000 iterations was computed, and the first 10% of the output was discarded in order to avoid bias resulting from the starting conditions. Two independent runs were carried out to check the convergence of the posterior probabilities of the models. F-values were checked for convergence by comparing the means and time-series standard errors for the two runs. The number of migrants per generation (M) was estimated as (1 - F)/(4F) /(4F) .cmAI and cvAI), ISF and STF. The assignment index c), according to the method described by Rousset . Forest patch sizes ranged from 0.03 to 20.7 km2 . The sma Rousset .STF) distance among populations. Counter-intuitively, its presence means that populations are inter-connected by gene flow and that the level of isolation is proportional to geographical distance. Isolation-by-distance was investigated using spatial autocorrelation analysis with SPAGEDI v.1.1 . The significance of each Moran's I , with sTo quantify the effects of habitat fragmentation and environmental pollution on genetic diversity a partial Mantel test was applied for all samples and for females and males separately . PartialK (ΔK)  . SamplinSTF and ISF, using FSTAT software . The average pollution levels and patch sizes were compared between the clusters with ANOVA to determine if these environmental variables may be reflected in the clustering pattern. Finally, the samples were pooled within each cluster, and tests for sex-biased dispersal were repeated in the same way as described earlier.Clusters determined for the total population were compared for differences in mean number of alleles, observed heterozygosity, gene diversity, All five microsatellite loci investigated were polymorphic within and among populations with the exception of locus Pob3 in the population DRK and Pob5 in the population OSI  in 8 out of 105 analyses: 2 cases for locus Pob4 and 6 for locus Pob5. Hardy-Weinberg deviations were not restricted to particular sampling sites. In all 8 cases, the observed heterozygosity was lower than expected, which was probably notcaused by null alleles because no null homozygote genotypes were observed. There was a difference in genotype distribution between the sexes, especially in the most variable locus, Pob5, where observed heterozygosity levels were generally lower in males than in females (data not shown). Deviation from Hardy-Weinberg equilibrium may indicate significant immigration, drift, selection and/or non-random mating.within = 1.40781, dfwithin = 597, Vamong = 0.1011, dfamong = 20, F = 3.1127, p < 0.0001). Locus by locus AMOVA showed that locus Pob5 is responsible for the largest part of the total genetic variation observed between the sites. For this locus, the variation among the sampling sites amounted to 21%. Loci Pob1, Pob4, and Pob14 also reflected significant differentiation, but to a smaller extent . Population pairwise estimates of STF were less than zero in 12 cases, which were set to 0.0. The mean pairwise values for all sampling sites varied between 0.02 and 0.10.The analysis of molecular variance (AMOVA) revealed statistically significant genetic structuring among the sampling sites: genetic variation within sampling sites amounted to 93.3%, whereas variation among the sampling sites was 6.7%  and males (n = 147). The STF values obtained were 0.082 for females and 0.066 for males. Although males appeared to be less genetically differentiated between populations than females, difference in STF values between the sexes was not significant . The comparison of calculated ISF indices gave a significant difference between sexes , with males showing higher homozygosity levels . Also, the assignment test showed that mean assignment index (cmAI) was low for males (-0.275) and high for females (0.250), and the difference between them ation test, p = 0.474, all tests one-was significant . At the same time, the variance among individuals in assignment indices (cvAI) was lower for females (4.90) than for males (6.36), but the difference was not significant . In summary, all calculated values that may reflect sex-biased dispersal supported a pattern that suggests a higher migration rate of males, although not all tests were statistically significant.In order to assess if there was sex-biased dispersal in the studied species, fixation indices over all loci were calculated separately for females  and negative for 10.2 to 21.0 km . This result also reflects high migration rates between neighboring sampling sites. However, when data for females and males were analyzed separately with a Mantel test, correlation between geographic and genetic distance was significant for males  and insignificant for females .Similarly, significant isolation by distance was shown when pairwise r = -0.153, p = 0.028) was observed in partial Mantel tests calculated over all samples. However, when analyses were performed for two sexes separately, genetic diversity of females was related to forest patch size , whereas for males this relationship was insignificant   .ΔK, the rate of change in the log probability of the data between successive potential numbers of clusters , therefore the two-cluster model was more likely than the single-cluster model. However, the revealed clustering pattern was weak, reflecting small genetic differentiation among the sampling sites. High proportions of admixed individuals were observed at all sites with assigned membership seldom exceeding 80%. Several sites showed approximately equal proportions of individuals assigned to different clusters, and they were thus classified as “unclustered.” The results were plotted on a map to evaluate the geographical relationships of the sites in different genetic clusters. The first cluster was composed mostly of relatively uncontaminated sites located in the eastern part of the study area. At the same time, five out of eight sites falling into the second cluster were grouped around the smelter site, generally more to the west than the first cluster . However, values of ISF were distinct (p = 0.0003), indicating dissimilarities in inbreeding levels between the clusters (ISF = -0.06 and 0.021). While sites in the western cluster were generally located closer to the smelter than those sites forming the eastern cluster, the difference in the mean zinc concentrations in the soil between the clusters was not statistically significant . The test for dissimilarities in mean patch size also gave a non-significant result .The genetic variation, expressed as the mean allelic richness and gene diversity was significantly lower  in the eastern cluster  than in the western cluster  . At the STF: p = 0.0855; ISF: p = 0.0295; cmAI: p = 0.0855; cvAI: p = 0.0855, permutation tests), reflecting increased test power. These results support the conclusion on the prevalence of male-biased dispersal.The samples from different sites were pooled together by assignment to genetic clusters and re-analyzed for signatures of sex-biased dispersal. These tests revealed the same pattern, namely, that males are the more dispersive sex, as earlier tests on unpooled samples, when 21 sampling sites were treated as separate populations. The p-values were either higher or the same for all of the tests (P. oblongopunctatus were linked by high levels of gene flow within and between habitat patches.The data on genetic differentiation among the sampling sites provided support for the first hypothesis stated in the introductory section of this paper. Low levels of genetic population structuring were expected based on the relatively high mobility of macropterous ground beetles . Only 6.P. oblongopunctatus populations. It is unclear what kind of habitat should be considered as hostile for this species and what the threshold distance is that separates two patches of suitable habitat.The lack of detailed ecological information on the organism's dispersal and gapcrossing ability made it difficult to assess and include in analyses the actual degree of geographic isolation experienced by P. oblongopunctatus and if the presence of such barriers explained the low Moran's I values observed in the first class of geographic distance (0–3.6 km, This may have affected the results of this study, as some of the sampling sites assumed to be independent may function as one habitat patch, while others, considered as belonging to one woodland area should be treated as separated patches. Moreover, the presence of additional barriers, such as local roads and water bodies, may have had a significant influence on genetic differentiation of neighboring populations . AdditioEvidence was found for sex-specific patterns of population genetic structure. Allele frequencies observed in males were more similar among sampling sites than allele frequencies in females. Isolation-by-distance was evident for males, but not for females in the study area, indicating lower migration rates of females. These findings are supported by the results of a set of analyses for sex-biased dispersal based on several genetic parameters. It is possible that females usually move only for very short distances, i.e. mainly within habitat patches. In that case, isolation-by-distance could potentially be observed in females only at a much smaller geographic scale than used in the present study. However, based on available data, rare long-distance migration events cannot be ruled out for females, as such rare migrants are unlikely to be sampled from populations. While females appear to be the philopatric sex, males seem to disperse more often at the scale represented by our study, presumably searching for females during the reproductive period in early spring . Males aDispersal mostly by one sex may not be sufficient to fully homogenise allele frequencies among subpopulations, so small differences in allele frequencies between the sexes can still prevail as observed in the present study . That maThe study revealed negative correlation between geographic distance and genetic differentiation, indicating higher migration rates between neighboring sampling sites than between more distant sites. However, this autocorrelation was statistically significant only for males and not for females. Significant isolation-by-distance detected for males indicated a higher migration rate for this sex. This result is in-line with the detected sex-biased dispersal. It is possible that landscape features, like geographical distance, habitat discontinuity, and patch size and/or quality, differently affect mobility of males and females. More dispersive males tend to homogenise the genetic structure of populations, regardless of patch size, while presumably more sedentary females tend to differentiate more among sampling locations, but still may have potential to occasionally colonise small and isolated habitatislets.P. oblongopunctatus. It is known that pollutants may exercise directional selection on populations, but the effect of such a selection on population genetic structure in natural conditions is difficult to demonstrate (P. oblongopunctatus showed that animals collected from polluted areas have reduced fecundity (P. oblongopunctatus (The results also demonstrated that levels of environmental pollution as encountered in the study sites have no detectable effect on population genetic structure of onstrate . Earlierecundity , toleranecundity , and altecundity  in compaunctatus .It is possible that contaminant stress did not induce a genetic change in exposed populations because the period of selection has been too short and/or the markers surveyed are not closely linked to genes involved in the development of resistance. The data presented shows no sign of significant genetic bottlenecks in these populations. Animals captured for this study from the most contaminated sites could represent either permanent local populations or recent immigrants. Thus, it is possible that lack of genetic differences between populations from contaminated and clean sites may simply result from intensive recolonisation of polluted sites after the levels of contaminants influx decreased during the last two decades. Significant gene flow between unpolluted and polluted areas is also likely to impair development of local genetic adaptation in the latter, thus preventing differentiation.Population structuring pattern derived from Bayesian clustering analysis was more powerful than neighbour-joining clustering analysis and revealed two clusters of sampling sites. The general structuring was still weak, and the proportion of admixture was high at all sites, further supporting the prediction of a high dispersal rate of the species. The results of this study suggest the presence of a genetic cluster across the eastern part of the study area. The second cluster, containing populations located more to the west, and generally closer to the source of pollution is characterized by lower overall genetic diversity in comparison to the eastern cluster. Lower genetic divergence between the sampling sites and higher admixture levels within the sites forming the second cluster suggest higher dispersal rates in that area. However, there was no clear link between pollution level or habitat patch size and clustering pattern, which is also in-line with the results from the environmental correlations analyses.Interestingly, when clustering was performed on the data from both sexes separately, the pattern observed in the females only was almost identical to that of the total data set. Isolation-by-distance, observed in males, but not in females, can make defining discrete genetic units problematic  and therOur study illustrates how microsatellite markers can be used to reveal population genetic structure and sex-biased dispersal of a carabid beetle in a framework of an anthropogenically changed landscape. As expected, overall high dispersal rate of the species and low levels of genetic population structuring were detected. High gene flow among the sampling sites and genetic population clusters explains weak or no effects of habitat fragmentation and pollution on population genetic structure. Male-biased dispersal was demonstrated, as predicted from the species' biology.


Ursus americanus. We tested whether dispersal increases with population density in both sexes. Fine-scale genetic structure was investigated in each of four sampling areas using Mantel tests and spatial autocorrelation analyses. Our results revealed male-biased dispersal pattern in low-density areas. As population density increased, females appeared to exhibit philopatry at smaller scales. Fine-scale genetic structure for males at higher densities may indicate reduced dispersal distances and delayed dispersal by subadults.Although the dispersal of animals is influenced by a variety of factors, few studies have used a condition-dependent approach to assess it. The mechanisms underlying dispersal are thus poorly known in many species, especially in large mammals. We used 10 microsatellite loci to examine population density effects on sex-specific dispersal behavior in the American black bear,  Natal dispersal, defined as the movement of an individual from its birth site to the place where it might reproduce , has beeA milestone in the study of dispersal has been provided by Density-dependent dispersal has been found to occur in natural populations , where tUrsus americanus) is a generalist, opportunist, and solitary species distributed over a wide range of population densities in North America. Although it has often been reported that most subadult males disperse from their natal area whereas most females settle in or adjacent to it , red maple (Acer rubrum), yellow birch , and American beech (Fagus grandifolia). Four sampling areas were distributed throughout the region in areas with different densities of bears (2) is part of the Pontiac Zone (hereafter named Pontiac), for which an estimate of 1.0–1.2 bears/10 km2 was observed. The second sampling area (1000 km2) was located in the Lady Smith-Cawood area (hereafter named LadyCawood), for which the bear density level was low (<1 bear/10 km2). The third sampling area (500 km2), referred to as Bois-Francs, has been characterized by a relatively high bear density, namely 2.2 bears/10 km2. The fourth sampling area (500 km2) is part of the Papineau-Labelle Wildlife Reserve (hereafter named Papineau-Labelle), known for its high density of bears (5.5 bears/10 km2). With the exception of Papineau-Labelle  and low-density area with ≤1.2 bears/10 km2 . All sampling areas were distributed in a relatively large homogeneous landscape  5 × 5-km cells. One station was built within each cell, except for two cells (four for LadyCawood) per area that contained five stations. The average distance between each of the 140 stations and the nearest one was 3.22 km (SD = 0.90 km), and Universal Transverse Mercator (UTM) geographic coordinates were recorded for all stations using Global Positioning System (GPS). We visited each station on a weekly basis, removed hair samples, sterilized barbed wire, and refreshed the food lure as necessary. All hairs collected on the same side of the barbed wire defined a sample, and all samples were preserved dry at room temperature into individual paper envelops until DNA extraction. A total of 411 hair samples were collected at 249 stations, that is, 175 hair samples at 72 stations for Pontiac, 90 at 56 stations for LadyCawood, 107 at 66 stations for Bois-Francs, and 89 at 55 stations for Papineau-Labelle .In order to minimize genotyping errors, we conducted a pilot study to determine allelic dropouts , and false alleles   associatDNA extraction from hair samples was carried out using the DNeasy Protocol for Animal Tissues  with minor modifications. Up to 10 guard hair roots as available were cut off and placed into 1.5-mL centrifuge tubes containing 180 µL of ATL buffer. Twenty microlitres of proteinase K (20 mg/mL) and 30 µL of DTT (100 mg/mL) were added to each tube before incubating at 37°C overnight. The remaining steps of the DNA extraction followed exactly those described in the DNeasy Tissue Kit Handbook (Qiagen Inc.), except for the last procedure in which the elution volumes were adjusted for each sample according to the hair category to which it belonged: 60 µL (category 1), 70 µL (category 2), 75 µL (category 3), 80 µL (category 4), or 100 µL (category 5), as in the pilot study.2, primers, and Taq polymerase were optimized for each locus, as well as the annealing temperature during the PCR cycles . Additional amplifications to correct for negative PCRs and ambiguous results were performed as necessary.All samples were genotyped at 10 microsatellite loci using sets of primers developed from black and brown bear samples: G1D, G10L ; G10H, GR cycles . The ampR cycles , ran on 2), 1.8 µL of dNTP (2.5-mM each), 1.8 µL of each SE47 and SE48 primers (10 µM each), 2.5 µL of BSA (1.0 mg/mL), 1.2 U of Taq polymerase (1.0 U/µL), and 5.0 µL of template DNA. The amplification consisted of an initial denaturation step of 9 min at 95°C, followed by 70 cycles of 30 sec at 94°C, 30 sec at 60°C, and 1 min at 72°C, completed by a 5-min final elongation step at 72°C. Ten microlitres of each PCR product were run on a 2.5% agarose gel and negative controls were used during the whole process.Sex identification was carried out twice for each sample using the protocol of identity 1.0 , The program tity 1.0  was used were computed between pairs of sampling areas with fstat. To test differentiation among populations, we used the exact G-test on allelic frequencies . Sampling areas showing nonsignificant or weak genetic differentiation were then combined into a single genetic group for the calculation of reference allele frequencies.quencies  as impleijr, following R2) was calculated for each comparison using the program SpaGedi 1.2g  to be calculated across multiple sets of individuals (rc). Based upon the natural dichotomy of the bear population density levels and the highly similar genetic patterns among some sampling areas as revealed by the Mantel tests (see results), we carried out spatial genetic autocorrelation analyses across (1) Pontiac and LadyCawood sampling areas, and (2) Bois-Francs and Papineau-Labelle sampling areas. These associations are hereafter referred to as low-density and high-density areas, respectively. For each type of comparison, we first defined distance classes as a trade-off between the spatial resolution and the number of pairs in each class: 1 km, 4 km, 7 km, 10 km, 15 km, and 30 km. The first distance class (1 km) contained only comparisons between individuals with identical spatial coordinates. To avoid the bias described above, our interest here was exclusively in the detection of positive spatial autocorrelation in the second distance class (4 km), as expected under philopatry  or dispersal across short distances . Because we also wanted to assess the influence of the second distance class size chosen on the interpretation of the results, we also performed the same analyses but modifying only the second distance class as follows: every 1 km from 4 to 10 km, successively. Results are presented as correlograms (plots of rc as a function of distance), with 95% confidence interval about rc estimated by 1000 bootstraps. Positive spatial genetic structure was declared when the probability P to achieve a value greater than or equal to the observed rc was less than 0.05, as determined through 10,000 random permutations of the individual genotypes among the geographic locationsBecause we were also interested in obtaining a detailed picture of how relatedness between two individuals changed with the distance separating their mean locations, we further investigated the fine-scale genetic structure using a spatial genetic autocorrelation technique implemented in the software enalex 6 . This teenalex 6 . In ordePositive PCR frequency ranged from 94.0% to 99.1% for the five DNA content-based categories . Both ADidentity 1.0 (dropout (L_base= 6 loci). Genotyping errors were thus reasonably minimal in our dataset. The overall probability of identity among siblings (PID(sib)) was 2.131 × 10–5  except for locus MU23 . Given the weak signal of inbreeding at this locus and the fact that nine of 10 loci did suggest random mating in the whole sample, we did not reject that locus from the dataset. Global FIS value was 0.015, also not significant (P= 0.45). When tested for each locus in each sampling area, significant departure from Hardy–Weinberg equilibrium was found at only two loci . Given this proportion is expected to occur by chance alone (2/40 = 0.05), we concluded that the assumption of Hardy–Weinberg equilibrium was respected in each sampling area. Fifteen pairs of loci deviated significantly (α= 0.05) from linkage equilibrium, a number slightly over the one expected by chance alone (15/180 = 0.083). Because these deviations did not involve twice the same pair of loci and might result from the existence of more than one genetic group in the whole study area , all loci were assumed to be statistically independent and were retained for genetic structure analyses.The total number of alleles per locus varied between nine and 20, with an average of 11.5 . ObserveFST coefficients between sampling areas were all significantly different from zero . The main divergence was observed between Papineau-Labelle and the three other areas (range: 0.029–0.032). In contrast, the FST values between the other three sampling areas were very weak, averaging 0.005 (range: 0.004–0.009). We thus concluded that there were two major genetic groups in the dataset, namely Papineau-Labelle  and the one composed of remaining individuals (n= 110) located in Pontiac, LadyCawood, and Bois-Francs . In contrast, spatial autocorrelation analyses of all individuals and male genotypes located in high density areas revealed significantly positive rc value within the 4-km distance class . rc values that declined but remained significant beyond the distance class size of 8 km.Spatial autocorrelation analysis of females located in the low-density areas revealed significantly positive Myotis bechsteinii, Ovis aries, Ursus arcticus  may also be delayed under high-density conditions. For several species of mammals, an increase in population density means an increase in competition for space and food , resulti density , as did  density . For mal density . More im2)   and wellIn summary, and contrary to our initial hypothesis, our results suggest a negative density-dependent dispersal pattern in the American black bear in our study area, as previously reported in brown bear i.e.,  as well