Coastal plants with simple linear distribution ranges along coastlines provide a suitable system for improving our understanding of patterns of intra-specific distributional history and genetic variation. Due to the combination of high seed longevity and high dispersibility of seeds via seawater, we hypothesized that wild radish would poorly represent phylogeographic structure at the local scale. On the other hand, we also hypothesized that wild radish populations might be geographically differentiated, as has been exhibited by their considerable phenotypic variations along the islands of Japan. We conducted nuclear DNA microsatellite loci and chloroplast DNA haplotype analyses for 486 samples and 144 samples, respectively, from 18 populations to investigate the phylogeographic structure of wild radish in Japan. Cluster analysis supported the existence of differential genetic structures between the Ryukyu Islands and mainland Japan populations. A significant strong pattern of isolation by distance and significant evidence of a recent bottleneck were detected. The chloroplast marker analysis resulted in the generation of eight haplotypes, of which two haplotypes (A and B) were broadly distributed in most wild radish populations. High levels of variation in microsatellite loci were identified, whereas cpDNA displayed low levels of genetic diversity within populations. Our results indicate that the Kuroshio Current would have contributed to the sculpting of the phylogeographic structure by shaping genetic gaps between isolated populations. In addition, the Tokara Strait would have created a geographic barrier between the Ryukyu Islands and mainland Japan. Finally, extant habitat disturbances , migration patterns (linear expansion), and geographic characteristics  have influenced the expansion and historical population dynamics of wild radish. Our study is the first to record the robust phylogeographic structure in wild radish between the Ryukyu Islands and mainland Japan, and might provide new insight into the genetic differentiation of coastal plants across islands. Coastal plants offer several advantages as a suitable system for improving our understanding of patterns of intra-specific distributional history and genetic variation . First, Hordeum marinum  were labeled with the fluorochrome 6-FAM or HEX . Amplification was performed using an initial denaturation step of 15 min at 95°C, followed by 32 cycles of denaturation for 30 s at 95°C, annealing for 90 s at 58°C, and extension for 30 s at 60°C, with a final elongation step at 72°C for 10 min. Amplified products were loaded onto an ABI 3130 autosequencer (Applied Biosystems) using the GeneScan Rox-350 Size Standard (Applied Biosystems) and the POP7 polymer and a 36-cm capillary array, and their sizes were determined using GeneMapper (Applied Biosystems). Departures from Hardy—Weinberg equilibrium (HWE) at each locus were carefully explored using a Markov chain Monte Carlo (MCMC) method implemented in GENEPOP version 4.0.10  values had been accurately estimated for each K , 5958, 5The Kuroshio Current effect is also likely responsible for the genetic admixtures between several mainland populations pops. 8 and 9) and Ryukyu Islands populations. Pops. 8 (in Mie) and 9 (in Kanagawa) are greatly distant from the Ryukyu Islands but are located downstream of the Kuroshio Current, which flows from Ryukyu Islands areas. Accordingly, seeds of wild radish are unavoidably and limitedly transported from the Ryukyu Islands to these populations, promoting gene exchange between these regions. This finding coincides with a previous study that reported genetic similarity in wild radish among one insular population of the Ryukyu Islands and several populations from the western part of the Pacific coastal area (near Mie prefecture) based on the allozyme diversity . In gene and 9 anSecond, the Tokara Strait was thought to have created a boundary between the Ryukyu Islands and mainland Japan. The Tokara Strait is located between Amamioshima and Tanegashima Islands, south of Kyushu  25], an, an25], In contrast to the clear phylogeographic structure detected by microsatellite loci, no geographic distribution pattern of haplotypes was observed in cpDNA variations. The discordance is often associated with the different inheritance modes and evolutionary rates between nuclear and chloroplast genomes. Nuclear genes are biparentally inherited and dispersed, whereas the chloroplast genes are inherited predominantly or entirely from the female parent. They segregate rapidly during vegetative growth, so the low heterozygosity in chloroplast genes is feasibly shaped without recombination . This woEvidence that most populations shared the common cpDNA haplotypes (A and B) across the entire Japanese archipelago  suggestsCakile maritima, Salsola kali, and Halimione portulacoides in the Atlantic clusters [Historical population dynamics of wild radish were reflected by the significant bottleneck effect and IBD pattern. The recent bottleneck in wild radish populations on the islands of Japan is most plausibly explained by frequent submergence caused by the high frequency of habitat disturbances, such as frequent intermittent typhoons, striking wild radish populations. In addition, due to the relatively small geographic size of islands and the past fragmentation during the LGM period, plants in islands show increased sensitivity to genetic drift. The significant correlation between geographical and genetic distances indicates the model of stepwise range expansion in wild radish. It is attributed to the linear arrangement of habitats, with seeds assumed to move in a linear pattern via sea currents, that is, geographically close populations are phylogenetically close. Due to the genetic boundary between the Ryukyu Islands and mainland Japan, migration is restricted or rare, but not impossible, as evidenced from the long floating time and long viability of seeds. In addition, the numerous multidirectional tributaries of sea currents surrounding the Japanese archipelago are also responsible for the expansion of wild radish populations. Our results are consistent with the positive correlation of IBD in wild radish reported by Ohsako et al.  using miclusters .in situ factors could not be determined to be causative, thus it is necessary to perform studies involving reciprocal transplantation and/or sympatric cultivation of wild accessions.Fruits of wild radish comprise a few-seeded capsule with a very solid and water impermeable seed coat containing a large air-filled cavity; these characteristics are essential to enhancing seed buoyancy, promoting seed dispersal by seawater over long distances, and high longevity. Accordingly, sea currents enable frequent gene flow over the wide distribution range of wild radish. However, the Ryukyu Islands and mainland Japan experience different histories and hence produce different selection pressures, and these in turn shape the genetic heterogeneity between local populations by producing different selective forces. Also, these two geographic ranges differ in both abiotic  and biotic  factors, which may generate ecological barriers against gene flow. These two forces work synergistically, producing genetic heterogeneity in natural populations and thus enhance genetic differentiation and preserve the robust phylogeographic structure. This hypothesis does not conflict with the observation of genetic admixture between several mainland populations (pops. 8 and 9) and the Ryukyu Islands, which exhibit great morphological variation, implying that restricted gene flow could not be disturbed by the existing robust geographic pattern of genetic variation. However, abiotic factors (such as vicariance mediated by sea currents) and/or Considering wild radish as a typical coastal plant with high longevity and high dispersibility of seeds via sea currents, it poorly represents phylogeographic structure at local scales. However, our study is the first to record the robust phylogeographic structure in wild radish between the Ryukyu Islands and the adjacent mainland Japan, which might provide new insight into the genetic differentiation of coastal plants across islands. The Kuroshio Current has an important influence on the geographic distribution of genetic variation of wild radish by shaping the genetic gap between isolated populations. In addition, the Tokara Strait is proposed to have been responsible for the genetic isolation between these two clusters. Finally, extant habitat disturbances , migration patterns (linear expansion), and geographic characteristics  have influenced the expansion and historical population dynamics of wild radish.S1 FigFruits of wild radish are capsules (left), however, its spongy pericarp is indehiscent and separate at each locule. Seawater dispersal is usually accomplished in this unit (middle). One seed is enveloped by spongy pericarp in each locule (right).(TIF)Click here for additional data file.S2 Fig(a) Leaf of wild radish from the Ryukyu Islands; (b) Leaf of wild radish from mainland Japan; (c) Stem of wild radish from the Ryukyu Islands; (d) Stem of wild radish from mainland Japan. Wild radish were planted under identical cultivation conditions  in a greenhouse (21°C).(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S5 Fig(TIF)Click here for additional data file.S6 Fig(TIF)Click here for additional data file.S7 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


Petunia species endemic to the South Atlantic Coastal Plain. We employed a phylogeographic approach based on plastid sequences obtained from individuals collected from the complete geographic distribution of Petunia integrifolia ssp. depauperata and its sister group. We used population genetics tests to evaluate the degree of genetic variation and structure among and within populations, and we used haplotype network analysis and Bayesian phylogenetic methods to estimate divergence times and population growth.Quaternary climatic changes led to variations in sea level and these variations played a significant role in the generation of marine terrace deposits in the South Atlantic Coastal Plain. The main consequence of the increase in sea level was local extinction or population displacement, such that coastal species would be found around the new coastline. Our main goal was to investigate the effects of sea level changes on the geographical structure and variability of genetic lineages from a P. integrifolia ssp. depauperata and its sister group (P. integrifolia ssp. integrifolia) was compatible with geological estimates of the availability of the coastal plain. Similarly, the origin of each genetic lineage is congruent with geological estimates of habitat availability.We observed three major genetic lineages whose geographical distribution may be related to different transgression/regression events that occurred in this region during the Pleistocene. The divergence time between the monophyletic group P. integrifolia ssp. depauperata possibly occurred as a consequence of the marine transgression/regression cycles during the Pleistocene. In periods of high sea level, plants were most likely restricted to a refuge area corresponding to fossil dunes and granitic hills, from which they colonized the coast once the sea level came down. The modern pattern of lineage geographical distribution and population variation was established by a range expansion with serial founder effects conditioned on soil availability.Diversification of The online version of this article (doi:10.1186/s12862-015-0363-8) contains supplementary material, which is available to authorized users. The severe climatic oscillations that occurred during the Pleistocene produced major changes in species distribution and consequently in their genetic diversity. These changes strongly impacted the vegetation at different latitudes and longitudes ,2. Some e.g., )Petunia integrifolia is a bee-pollinated species that presents purple flowers [Petunia [P. integrifolia ssp. integrifolia and P. integrifolia ssp. depauperata (Fries) Stehmann and Semir. The former is widespread in the Pampas region , while the latter is endemic to the SACP, from Florianópolis  to Chuí (border between Brazil and Uruguay). Each subspecies represents a different evolutionary lineage based on sequences of the internal transcribed spacers of ribosomal nuclear DNA and plastid DNA [ flowers  and is p flowers ,23 and l[Petunia . Accordi[Petunia , this spstid DNA .Figure 1P. integrifolia ssp. depauperata, looking for geographical patterns of genetic variation and lineage distribution that could have emerged during the Pleistocene. Our main aim was to investigate the effects of sea level changes and the putative role of refuge areas for P. integrifolia ssp. depauperata using sequences from two plastid intergenic spacers. We chose these genetic markers because they have been successfully used in phylogeographic studies in Petunia [Calibrachoa Cerv. [In this work, we used a phylogeographic approach to characterize the genetic diversity of a comprehensive sample of  Petunia ,26-30 anoa Cerv. .P. integrifolia ssp. depauperata, the concatenated alignment resulted in 1120 bp, with 25 variables sites and 19 parsimoniously informative sites, resulting in 26 haplotypes. For P. integrifolia ssp. integrifolia, the concatenated alignment resulted in 1071 bp, with 15 variable sites and seven parsimoniously informative sites, resulting in 13 haplotypes. Variable and informative indels produced the discrepancies between the complete alignment and individual sequence length ranges. Despite the great morphological similarity and their taxonomic status, these two taxa did not share haplotypes, which is surprising because haplotype sharing is widely reported among Petunia species [P. axillaris (Lam.) Britton, Sterns and Poggenb subspecies, which cannot be identified based on these plastid sequences alone [A general characterization of each marker is shown in Table  species ,28. Anotes alone .Table 1P. integrifolia ssp. depauperata was h = 0.77 ± 0.01 and π (%) = 0.13 ± 0.09. All parameters were in accordance with other data obtained for other Petunia species in different surveys, despite the wide difference in geographic distribution range and sample sizes among species. In a previous study including P. integrifolia ssp. depauperata, Longo et al. [P. exserta Stehmann, a species with a restricted geographic distribution, was analyzed using the same genetic markers and a similar sample size and presented only six haplotypes but similar nucleotide diversity [P. axillaris, that together cover a geographic range larger than that of P. integrifolia ssp. depauperata, presented 35 haplotypes, but nucleotide and haplotype diversity values [As described in Table o et al.  found oniversity . The thry values  were cloP. integrifolia were used in the network and phylogenetic analyses  and will be further discussed below. The last haplogroup contains all haplotypes of P. integrifolia ssp. integrifolia individuals (numbers 27 to 39). Haplotype H19 . Only six populations were monomorphic, and 18 haplotypes were exclusives  resulted in an estimate of 66% of the total genetic variance found among populations, while the remaining 34% of total genetic variation was found within populations  . Most of these populations only had haplotypes from the Center Group, but populations 7 and 8 also presented, in low frequency, haplotypes H5 and H14 from the Northern Group, respectively. Populations 9-10 and 12-22 formed Samova’s Group 1 (dashed line). Most of these populations only had haplotypes from the Southern Group, except for population 9 , population 13 , and population 17 . Finally, populations 11 and 23-30 formed Samova’s Group 3 (dotted line). Populations 23-30 only had haplotypes from the Northern Group. The presence of population 11 in SG3, however, is more difficult to explain. This assignment may have occurred because this population had a high frequency of haplotypes H5 and H16 from the Northern Group , despite this population being geographically closer to SG1. However, H5 was already present in another population from SG2 (Pop 7), though with minor frequency. Thus, population 11 may actually be part of SG1, but due to stronger drift or founder effect, a higher frequency of Northern Group haplotypes assigns it to SG3. More genetic markers will be necessary to clarify this issue. Notably, the geographical limits of these groups do not match the known putative actual or historical barriers (rivers or other geographic discontinuities) proposed as drivers of population structure of Calibrachoa heterophylla (Sendtn.) Wijsman from the same geographic distribution [The Samova analysis suggested that three groups K = 3) maximize the genetic structure in the among-group level , whereas Tajima’s D was also negative but marginally non-significant  for P. integrifolia ssp. depauperata. Tajima’s D and Fu’s Fs are classical neutrality tests used to assess population demographic history. Both assume that populations have been in mutation–drift balance for a long period of time [Fu’s  of time . Negativh = 0.27) and a significant Fu’s FS , while the Southern group displayed the lower nucleotide diversity (π = 0.03) and significant and negative values for both neutrality tests  , and vouchers were deposited in the BHCB herbarium, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil. Total DNA was extracted from young leaves carefully collected for genetic analysis. Silica gel dried leaves were frozen in liquid nitrogen and ground to a fine powder, and DNA was extracted with cetyltrimethyl ammonium bromide (CTAB) protocol as described by Roy et al. [A total of 291 individuals of y et al. . This wotrnH-psbA and trnS-trnG intergenic spacers, using the universal primers previously described ([Polymerase chain reaction (PCR) was employed to amplify the non-coding plastid scribed  and aligned manually in GeneDoc [h) and nucleotide (π) diversities [For each marker, both forward and reverse strands were checked using Chromas .The evolutionary relationships between haplotypes were estimated using the median-joining network method  as implPetunia. We found eight published rates that fit these criteria, varying between 1 x 10-9 and 8.24 x 10-9 substitutions per site per year (s/s/y) [-9 as prior. We assumed an offset value of 1 x 10-9 s/s/y, such that the median of the prior was 3.05 x 10-9 s/s/y, allowing rate values of 8.24 x 10-9 s/s/y to be reached with low probability .The dated Bayesian phylogenetic tree of haplotypes was inferred using Beast 1.8.0  with a Y (s/s/y) -63. To tP. integrifolia ssp. integrifolia). We then estimated a reconstruction of the phylogeographic history of the clade. We also explored different choices of prior distributions for migration rates in this model, including a uniform prior and a distance-informed prior, and we found that additional information on geographic distances between locations had little impact on the estimated rates.For the phylogeographic reconstruction, we modeled geography through the discrete phylogeographic diffusion model of  and used8 Markov chain Monte Carlo (MCMC) iterations were performed, sampling every 1000 generations; 10% of iterations were removed as burn-in. Convergence was checked by visual inspection of the independent runs in Tracer 1.6 [For each of the above analyses, two independent runs consisting of 1 x 10acer 1.6  so that acer 1.6  using thacer 1.6  to draw P. integrifolia ssp. depauperata through a spatial analysis of molecular variance. Following this, we used Arlequin to estimate AMOVA and genetic variability statistics for the groups defined by Samova, as described previously.We also used Arlequin to perform an analysis of molecular variance  to quanFs [P. integrifolia ssp. depauperata were also inferred through the Bayesian Skyline Plot  method Sequences are deposited in GenBank (accession numbers available in Additional file


Panthera tigris altaica) has experienced a severe contraction in demography and geographic range because of habitat loss, poaching, and prey depletion. In its historical home in Northeast China, there appears to be a single tiger population that includes tigers in Southwest Primorye and Northeast China; however, the current demographic status of this population is uncertain. Information on the abundance, distribution and genetic diversity of this population for assessing the efficacy of conservation interventions are scarce. We used noninvasive genetic detection data from scats, capture-recapture models and an accumulation curve method to estimate the abundance of Amur tigers in Northeast China. We identified 11 individual tigers  using 10 microsatellite loci in three nature reserves between April 2013 and May 2015. These tigers are confined primarily to a Hunchun Nature Reserve along the border with Russia, with an estimated population abundance of 9–11 tigers during the winter of 2014–2015. They showed a low level of genetic diversity. The mean number of alleles per locus was 2.60 and expected and observed heterozygosity were 0.42 and 0.49, respectively. We also documented long-distance dispersal (~270 km) of a male Amur tiger to Huangnihe Nature Reserve from the border, suggesting that the expansion of neighboring Russian populations may eventually help sustain Chinese populations. However, the small and isolated population recorded by this study demonstrate that there is an urgent need for more intensive regional management to create a tiger-permeable landscape and increased genetic connectivity with other populations.Over the past century, the endangered Amur tiger ( Panthera tigris altaica), a flagship species and a top predator, plays a vital role in maintaining the stability and health of the coniferous and broadleaved mixed forests of Northeast Asia [th century [The Amur tiger . Jilin Province Forestry Bureau and the Forestry Industry Bureau of Heilongjiang Province approved permits for the work conducted. Beijing Normal University conducted this study in collaboration with the administrations of the local protected areas. Scat-collection surveys used non-invasive technology and did not involve direct contact with animals.Pinus koraiensis)—deciduous forest dominated by Korean pine, Manchurian ash (Fraxinus mandshurica), Manchurian walnut (Juglans mandshurica), Mongolian oak (Quercus mongolica), and several species of maple (Acer spp.) and birches (Betula spp.). Because of long-term repeated disturbances , the original vegetation has been almost entirely replaced by secondary forests dominated by Mongolian oaks, shrub land and spruce-fir coniferous forests at higher elevations [Panthera pardus orientalis), black bear (Ursus thibetanus) and brown bear (Ursus arctos), and prey species such as sika deer (Cervus nippon), Siberian roe deer (Capreolus pygargus), and wild boar (Sus scrofa) [The scats were collected from three major tiger nature reserves in east Jilin and Heilongjiang, Northeast China: Hunchun reserve (HC), Laoyeling reserve (LYL) and Huangnihe reserve (HNH) . HC and evations . In addi scrofa) . The for scrofa) .2. Two-member team collected scats were conducted along the line transects for 54 consecutive days between December 2014 and February 2015. The size of scats and associated tracks and scrapes were measured. Each scat was placed in a ziploc bag by hand; disposable gloves were worn at all times while handling scat. The samples were stored in a refrigerator at -20°C until further analysis.Two scat collection approaches were used in this study. The first approach was a routine opportunistic approach where fresh scats were collected along logging roads, dirt roads and forest trails by field staff when they periodically monitored Amur tigers and Amur leopards in the study area from April 2013 to May 2015. The second approach was more systematic: specifically, we collected scats along a predefined transects during the winter of 2014–2015 in HC. To increase sampling efficiency, we established 18 transects that the tigers regularly used based on our long-term camera-trapping data. Each transect was inspected by a team of two trained members at six-day intervals. The total length of transects was 162 km, covering an area of approximately 1000 kmb gene (Cytb) fragment for leopards and a 271-bp fragment for tigers before genotyping. A distinct target band was detected by agarose gel electrophoresis at least twice after being screened three times to identify the species. The tiger-positive samples were genotyped at thirteen nuclear microsatellite loci , which were selected for their highly polymorphic information content, ease of amplification and low error rate determined in previous tiger studies [DNA was extracted from the scats using the QIAamp Fast DNA Stool Mini Kit  as described in Russello et al. . Negativ studies , 23, 29.Polymerase Chain Reaction (PCR) for individual identification was performed at a 15-μl volume containing 7.5 μl KHBE PCR MasterMix , 0.2 μm fluorescently labeled forward primer , 0.2 μm usual reverse primer, 1 μg bovine serum albumin (TaKaRa) and 2 μl DNA template. Amplification was performed in a Applied Biosystems Veriti Thermal Cycler with an initial denaturation at 94°C for 5 min, followed by 45 cycles of 94°C for 1 min, 52–59°C for 30 sec, 72°C for 30 sec, and a final extension at 72°C for 10 min. PCR products were separated using capillary electrophoresis on an ABI 3730XL automatic sequencer . Allele data were obtained using GeneScan-500 LIZ Size Standard and scored on GeneMapper software (version 4.1). Because of the poor quantity of fecal DNA and high genotyping errors, we adopted the multi-tube approach to improve detection accuracy . Every shttp://ms.biomed.cas.cz/MSTools/) was used to compare and identify matching genotypes to consensus genotypes. Fecal samples that matched at a minimum of nine loci were pooled to create consensus genotypes. Probability of identity (PID) was used to test whether the number of loci were adequate for distinguishing unrelated individuals, and siblings were estimated using a corrected equation for small populations in the program GIMLET [Mstools (available at m GIMLET . The smaA), expected heterozygosity (HE), observed heterozygosity (HO) and polymorphism information content (PIC) using FSTAT2.9.3.2 [Genetic diversity for ten microsatellite loci was measured as the mean number of alleles per loci  to draw possible home ranges of some identified individuals using the minimum convex polygon. Geophysical and human infrastructure data in our map were obtained from the China fundamental geographic information dataset.We also used Hawth’s analysis tools in ArcGIS 10.0  of 10 microsatellite loci was 2.60, and the mean expected (HE) and observed (HO) heterozygosity were 0.42 and 0.49, respectively  were inferred to inhabit the study area . Of the 2 = 1.22, df = 1, p = 0.27).GIMET analysis revealed that there was a high capability for distinguishing Amur tiger individuals when multiple loci were used. Despite the fact that several of the tigers may have been siblings, the error rate for incorrectly discriminating between them was as low as 1.15% when 10 loci were used . If the Most of the tigers  were recorded in HC along the border with Russia during multiple surveys . Two fem2 = 2.73, p = 0.91). Based on individual capture history  than a similar study implemented in neighboring Russian reserves (58%) . This inA = 2.60, HE = 0.42), which were consistent with results  obtained in the same area previously [A = 3.33–12.43, HE = 0.59–0.81) [A = 3.20–3.56, HE = 0.58–0.62) [A = 2.39–3.33, HE = 0.52–0.54) [E = 0.26; captive populations: HE = 0.36) in a wide-scale analysis of Amur tigers [Our results based on ten microsatellite loci suggest that Amur tigers show low levels of genetic diversity. The mean number of alleles and expected heterozygosity  , 45, 46.58–0.62) , 47 and Given that a barrier exists blocking movements of tigers between Hunchun-Southwest Primorye and the Sikhote-Alin Mountains, the small and isolated Hunchun-Southwest Primorye population may be at risk of continued genetic drift , 47. The2 suitable habitat in Hunchun of China-southwestern Primorsky of Russia and have to share habitat with at least 80 leopards. Since Amur tigers also have large home ranges  in this region, there is a resulting high overlap of home range size of adult males and the absence of territoriality [Understanding the population dispersal and habitat connectivity is critical for wildlife conservation and management . Historioriality . These rDuring the two year study period, almost all tigers were confined primarily to a narrow area along the border with Russia  in accorOur study provided a robust population estimate of Amur tigers in China using noninvasive genetic sampling techniques. The genetic capture-recapture method estimated a population size of 9–11 tiger individuals, which is similar to the result using the camera-trapping data in 2013 in HC where a population size of 11–13 Amur tigers was estimated . The expHowever, there are two reasons to be concerned about noninvasive genetic sampling methods. First, the abundance estimation may be biased because some individuals may be difficult to detect for behavioral reasons . For insThis study provides a valuable independent population status assessment using genetic data from fecal DNA and demonstrates that noninvasive genetic sampling is an effective technique not only in obtaining estimates of population size but also for obtaining information on genetic diversity in species, such as the Amur tiger, for which limited data are available. This study has also established an important baseline for long-term monitoring programs for this charismatic species using the genetic capture-recapture framework in Northeast China. If repeated over multiple time periods, extensions of this framework allow vital rates to be estimated. These vital rates, in turn, drive changes in abundance.Recovery of small populations of threatened species often relies on rigorous demographic estimates. This isolated small tiger population along the China-Russia border, which is at a viability threshold, is facing serious hurdles to dispersal and conflicts with local people , 26. To S1 Table(DOCX)Click here for additional data file.


Arabidopsis halleri subsp. gemmifera, across the Japanese mainland. We found significant evidence for isolation-by-distance but not for isolation-by-environments. However, at least within the central area, the magnitude of genetic differentiation tended to increase with microhabitat dissimilarity in light conditions and water availability. Furthermore, most populations have been estimated to experience a recent decline in the effective population size. These findings highlight a potential influence of the microhabitat conditions and demographic processes on the local-scale genetic differentiation among natural plant populations.To examine determinants of geographical patterns in population differentiation, we quantified genetic variation of a temperate herb,  Arabidopsis halleri subsp. gemmifera (Brassicaceae). We analysed 19 microsatellite loci, which showed a significant population differentiation and a moderate within-population genetic diversity . Our structure analysis and phylogenetic network did not detect more than two genetic groups across the Japanese mainland but found fine-scale genetic differentiations and admixed patterns around the central area. Across the Japanese mainland, we found significant evidence for isolation-by-distance but not for isolation-by-environments. However, at least within the central area, the magnitude of genetic differentiation tended to increase with microhabitat dissimilarity under light conditions and water availability. Furthermore, most populations have been estimated to experience a recent decline in the effective population size, indicating a possibility of bottleneck effects on the pattern of genetic variation. These findings highlight a potential influence of the microhabitat conditions and demographic changes on the local-scale genetic differentiation among natural plant populations.The genetic structure of a plant species is shaped by environmental adaptation and demographic factors, but their relative contributions are still unknown. To examine the environment- or geography-related differentiation, we quantified genetic variation among 41 populations of a temperate herb,  Current patterns of genetic structure within a single plant species are shaped by demographic (e.g. genetic drift or gene flow) and ecological  factors . At a reIn addition to ample evidence on the genetic structure of plant populations from phylogeographical and landscape studies, there has also been increasing evidence that local environment and geographic scale exert mutually non-exclusive influences on the pattern of genetic structure . For exaThe Japanese archipelago consists of four main islands extending over 2000 km in the southwest–northeast direction and encompassing a wide range of climatic zones, including many floral or vegetation types from warm-temperate, evergreen and broadleaf forests to temperate, deciduous and sub-boreal coniferous forests . No majoArabidopsis halleri subsp. gemmifera (syn. Arabis gemmifera) is distributed throughout Japan and the Russian Far East  and 11 sites far from the Kinki area   and 1 pmol of each primer. The PCR proceeded as follows: 15 min at 95 °C; 30 cycles of 30 s at 94 °C, 90 s at 53 °C, 1 min at 72 °C for multiplex set 1, or 35 cycles of 30 s at 94 °C, 90 s at 58 °C and 1 min at 72 °C for multiplex sets 2 and 3; and a final extension step of 30 min at 60 °C. The PCR products were loaded on an ABI 3130xl Genetic Analyzer with GS 500 LIZ size standard . Genotypes were determined using Gene Mapper version 4.0 software (Applied Biosystems). The genotypic data are provided in Ho), within-population genetic diversity , total genetic diversity (Ht) and the inbreeding coefficient (Gis); and the Fstat version 2.9.3.2  for each locus by using GenoDive. Significances of the genetic differentiation, Gst, were analysed for each locus based on the sum of square of the test statistic with 9999 permutations. Linkage disequilibrium among the 19 loci was also tested with 1000 Markov Chain Monte Carlo (MCMC) iterations with 100 batches, using GENEPOP software version 4.2  was set from 1 to 25 with a 100 000-step burn-in and 300 000 MCMC iterations. Allele frequencies were assumed to be correlated among populations and an admixture model was chosen. This process was repeated 20 times for each K. The probable K value was determined using the ΔK statistic .Secondly, we used a Bayesian clustering and population phylogeny to infer patterns of genetic differentiation. We estimated population gene pools and ancestry using Structure software version 2.3.4  for each pair of sampling sites. The Mesh Climate 2000 database (2) and maximum snow cover (cm) at a 1-km2 scale, and is thus suitable for our sampling scale. We added the altitude of each sampling site to these variables. These variables were summarized by a principal component analysis (PCA) to deal with multicollinearity of the environmental variables. The sum of the first and second principal components (PC1 and PC2) explained 78 and 79 % (respectively for the entire area and the Kinki area) of the total variation in habitat environments represented by the eight variables. PC1 explained ∼54 % of the variation, whereas PC2 explained roughly 25 % of the variation for both the entire area and the Kinki area. PC1 was related to the three temperature variables  as well as the altitude, whereas PC2 was related to the light conditions (radiation and sunshine) and water availability (precipitation and snow cover). This tendency was consistent between the entire study area and the Kinki area  was determined by mean and 95 % CI (i.e. 1.96 × SD) of the resampled distribution.Thirdly, we analysed the relationships of genetic differentiation and environmental dissimilarity or geographical distance. We selected t values . The datdatabase  was usedto G′′st/ − G′′st  package  for the 10[N0]) and log10[N1]), respectively), mutation rate (log10[μ]) and the time since populations started to expand/decline (log10[Ta]). These parameters were allowed to vary among all 19 loci, while their initial values were equal among these loci. The generation time (ga) was set as 2 years because A. halleri subsp. gemmifera is a perennial herb able to bloom during the first year of its life cycle under cultivated conditions . We used uninformative lognormal priors as follows: means of the prior distributions were set to 4, 4, −4 and 5; and SD equal to 4, 4, 1 and 4 for N0, N1, μ and Ta, respectively. Hyper-prior lognormal distributions were set as: mean equal to 6, 6, −4 and 8; SD equal to 2, 2, 0.25 and 2; hyper-prior of mean equal to 0, 0, 0 and 0; hyper-prior of SD equal to 0.5, 0.5, 0.5 and 0.5 for N0, N1, μ and Ta, respectively. Three independent chains of MCMC were run with 40 000 thinned updates and a thinning interval of 20 000 steps . The coda package . Within the entire dataset, there were only five individuals with missing values at more than four loci. Although Site 40 consisted of identical genotypes across the 19 loci, identical genotypes were <10 % in the entire dataset.The AR ranged from 1.00 to 2.02 in all populations  and Hyogo prefectures (Sites 34–37) were clearly assigned to different groups .We observed the largest value of ΔK = 4 for the Kinki area; Fig. In the phylogenetic network Fig. , we founr = 0.34, P < 0.001 with 9999 permutations; Fig. r = –0.13, P = 0.88; r = 0.04, P = 0.30 for PC1 and PC2, respectively; Fig. r = 0.25 ± 0.06, P = 0.03 ± 0.04; PC1, r = –0.13 ± 0.07, P = 0.77 ± 0.16; PC2, r = –0.08 ± 0.14, P = 0.72 ± 0.37: Mean ± 95 % CI by 9999 times subsamplings). On the other hand, within the Kinki area, the genetic differentiation was marginally correlated with the geographical distance .The degree of genetic differentiation showed a significantly positive correlation with the geographical distance  and water availability (precipitation and snow cover), we hypothesize that microhabitat conditions can be a factor in local adaptation. Moreover, ion gaps , and we Mimulus guttatus .The coalescence-based estimation inferred a decline in the effective population size for most sites. Accompanied with the species' life-history discussed above , such a decline of population size could account for significantly positive ulations . AlthougA. halleri subsp. gemmifera seems comparable with those of the temperate deciduous broadleaved trees in Japan, i.e. admixed pattern in central Japan . The underlying genetic structure made it difficult to accurately estimate the demographic processes of highly admixed populations. Thirdly, we should note that our demographic inference has some limitations due to a simplified assumption. In particular, the Msvar estimates assumed the absence of gene flow among local populations . Thus, tA. halleri subsp. gemmifera. We also suggest the possible effects of population decline on the patterns of genetic variation. Our findings therefore highlight a potential impact of ecological and demographic factors on the genetic differentiation at a fine spatial scale. Further investigations (such as common garden experiments) are required for rigorous testing of isolation-by-adaptation in order to understand how local adaptation and geographic isolation interactively affect the pattern of genetic differentiation within a plant species.In summary, this study provides suggestive evidence for microhabitat-related differentiations at a local scale despite the lack of isolation-by-environment across the Japanese mainland in Next Generation World-Leading Researchers , JSPS and by Grant-in-Aid for Scientific Research (S) 26221106, MEXT to H.K.This study was supported by funding Programme for Y.S. performed the experiment and analysed the data. Y.S. and H.K. designed the study and wrote the manuscript.None declared.The following Supporting Information is available in the online version of this article –Figure S1. Pictures of the study sites and plants.Figure S2. Log-likelihood and ΔK values showing the likely number of ancestral populations inferred by the structure analysis (Figure S3. Genepop format of raw genotypic data [SatoKudoh_AhSSR_GENEPOP.txt].


Medical genetics and genomic medicine in Rwanda. The pop12) NISR . Rwanda Vision 2020  covers more than 90% of the population with minimal copayment.Rwanda Health sector suffered from the effect of the genocide, by destruction of health facilities, and health workers have been either killed or fled the country , from Belgium and the National University of Rwanda. This grant allowed the country to support capacity building by providing basic and essential genetic lab equipment such as cytogenetic equipment and molecular laboratory equipment. This service offers genetic counseling and the main causes of referral are congenital malformations, intellectual disability, infertility, and repetitive abortions. The project of the Department also involves genetic teaching to medical doctors, nurses, laboratory technicians, and conducting research directed toward the knowledge of genetic problems in Rwandan patients.The genetic laboratory is located at the University teaching hospital of Butare (CHUB), but outpatient consultations are available in two referral hospitals . Traditional karyotype analysis testing is the only cytogenetic test available, but it is covered by health insurances. Consequently, this allowed the increasing number of individuals seeking genetic service in our department. For example, a survey of genetic disease in 345 Rwandan patients over 40 months (December 2006 to March 2010) referred to University Teaching Hospitals of Kigali and Butare revealed abnormal karyotype in 22.26% and the most frequent abnormality was Down syndrome with an incidence of 18%. A majority of patients presented global developmental delay or intellectual disability  was performed in a cohort of 50 Rwandan patients with intellectual disability and multiple congenital abnormalities with a diagnosis rate of 26% . Of the 1825 samples screened, 97 (5.32%) were positive. Of these, 60 (3.28%) samples were heterozygous for Hb S, and four (0.22%) for Hb C; two (0.11%) newborns were Hb SS homozygotes  in the population. Several studies have proposed that parental PTSD is a strong correlate for the development of PTSD in offspring. A study conducted in a cohort of traumatized Tutsi widows and their children showed that mothers exposed to the genocide as well as their children had lower cortisol and glucocorticoid receptor levels and higher mineralocorticoid receptor levels than nonexposed mothers and their children. Moreover, exposed mothers and their children had higher methylation of the IQCK: c.667 C>G; p.Q223E. Interestingly, morpholino knockdown of the iqck mRNA with human IQCK mRNA rescue experiments demonstrated the functional significance of the p.Q223E mutation with severe midline defects in the zebrafish  through pilot studies, initiation of birth defects registry, implementation of prenatal diagnosis facilities, and the development of advanced molecular cytogenetic techniques such as multiplex ligation‐dependent probe amplification (MLPA) and FISH.Other further perspectives include whole sequencing of more Rwandan patients, especially with neurodevelopmental disorders in order to identify underlying genetics defects in our population.With all advantages of array‐CGH, it would be the first‐line diagnosis test to be employed in our Genetic department in patients with intellectual disability and global developmental delay. However, these analyses are still very expensive because they require expensive platform, reagents, and bioinformatics tools to prioritize candidate genes and copy number variations; therefore, the majority of the patients will not be able to pay for the analysis.Moreover, efforts should be made to train local African scientists and to build resources across Africa for independent human genetics research. Thereby, institutional support and considerable internal and external funding are required.None declared.


Octopus vulgaris Cuvier 1797, is a largely exploited cephalopod species in the Mediterranean Sea and the Atlantic Ocean, as well as along the coasts of Africa, Brazil and Japan, where its taxonomic identity is still debated. The assessment of its genetic structure is a pressing need to correctly manage the resource and to avoid overfishing and collapsing of local stocks. Here we analysed genetic variation and population structure of O. vulgaris using thirteen microsatellite loci in seven sampling localities from the Mediterranean Sea and one from the Atlantic Ocean. We also used a DNA barcoding approach by COI gene fragment to understand the phylogenetic relationships among the specimens here investigated and the ones whose sequences are available in literature. Our results reveal high levels of allelic richness and moderate heterozygosity in all samples investigated, and a pronounced differentiation of the Atlantic and Sicilian specimens. This latter aspect seems to support the isolation of the biota within the Strait of Messina. A certain degree of differentiation was detected among the other geographic samples within the Mediterranean Sea, which is more compatible with an island model than isolation by distance. The occurrence of null alleles affected more genetic diversity indices than population structure estimations. This study provides new insights about the genetic diversity and structure of O. vulgaris in the area of interest, which can be used as guidelines for a fisheries management perspective.The common octopus,  The common view of marine populations as demographically open units has been questioned over the past decades  and evidfic case –6.Among invertebrates, molluscs include sessile, slow walking or fast swimming species characterised by internal or external fertilization and direct or indirect development, living in a wide variety of habitats such as open sea, rocky or sandy bottoms. Several patterns of genetic structure have been identified, from genetic homogeneity ,8 to isoThe concepts of differentiation, population structure and stock boundaries are strictly linked; a stock is commonly defined as “a group of organisms whose demographic/genetic trajectory is largely independent from other such groups” . Since mIn the last few years, the decline of other fishery resources has led to an increase of cephalopod exploitation, especially in Europe , making Octopus vulgaris Cuvier, 1797)   . Howeve, 1797)   and sho5 months , the maj5 months –44. In t5 months ,46 to asAll the analyses have been carried out using preserved or freshly dead specimens collected from local fishermen. No use of live animals has been required for this study and no specific permissions were needed for the sampling activities in all of the investigated areas because our species of interest is commercially harvested (not endangered nor protected) and it was caught in areas where fishing is allowed. A total of 193 individuals were collected in seven localities across the Mediterranean Sea and in one locality in the nearby Atlantic Ocean . Starting from the tissue stored in alcohol, about 25 mg were cut, freed of outer skin and put in distilled water for a while to account for rehydration and alcohol removal. Then, the tissue was chopped in small pieces, put in 1.5 mL tubes and processed following the manufacturer’s instructions. Resulting DNA was quantified by NanoDrop Spectrophotometer  and diluted to the optimal concentration for each downstream application.DNA was extracted using the NucleoSpinO. vulgaris is easily recognisable from other octopus species of the Mediterranean Sea and the nearby Atlantic Ocean, a DNA barcode with a fragment of the COI gene was obtained for five individuals from each geographic sampling locality, using the primers developed by [™ Gel Extraction Kit (Sigma-Aldrich). DNA fragments were sequenced using LCO1490 primer [http://www.mbio.ncsu.edu/bioedit/bioedit.html), together with other sequences of O. vulgaris with known geographical provenance [O. insularis was used as outgroup, due to its phylogenetic closeness to O. vulgaris [Despite loped by . DNA amploped by . PCR pro0 primer  by Big-D0 primer  implemenovenance , 52–60 (ovenance  at the fvulgaris .® Microsatellite PCR kit (Qiagen) at the following conditions: 15 min at 95°C, 35 cycles at 94°C for 30 s, 59°C for 1 min and 30 s, 72°C for 1 min, and a final extension at 60°C for 30 min. Each reaction was conducted in a final volume of 12.5 μL. Forward primers were 5’ labelled with different fluorescent dyes  in t™ Software v1.0 (Life Technologies) and scored as PCR products; in case of ambiguity in assigning sizes, samples were run at different dilutions or re-amplified. Micro-Checker v2.2.3 [Microsatellite peaks were analysed with Peak Scannerr v2.2.3  was usedr v2.2.3  to estimFST-outlier method. The options “Neutral mean FST” and “Force mean FST” were used, to increase the reliability of the estimate of the initial mean FST computed from the empirical dataset. A total of 50,000 simulations were computed, plus 5,000 additional, as suggested by the default settings of the software. To test the power of our microsatellite markers on discriminating individuals using multilocus genotypes, we used the software GENCLONE v2.0 [a) per locus and inbreeding coefficient (FIS) per population were calculated in Arlequin v3.5.1.3 [FIS per locus [e) and observed heterozygosity (Ho) per locus and population were calculated using GENETIX v4.05.2 [Putative loci under selection were detected with LOSITAN , a selecONE v2.0 . Number v3.5.1.3 , while Fer locus  was calcer locus ,69. Priver locus ,71. Expe v4.05.2 . Linkage v4.05.2 ,69; the Hardy-Weinberg equilibrium (HWE) probabilities per locus and population were computed in Genepop on the Web ,69 both Relationships among individuals within each sampling locality were calculated using ML-Relate  both on FST [FST measures deviation from a condition of panmixia and is calculated on allele frequencies, whilst D measures deviation from total differentiation and is more related to genetic distances among populations [FST and Jost’s D estimators. To test if the observed patterns of genetic structure conformed to the isolation by distance model, we correlated population pair-wise’s FST previously calculated with the geographic distance (km) between each pair of sampling locality, using the Mantel test function implemented in XLSTAT . Geographical distances were calculated using Google Earth v7.0 (https://www.google.com/earth/), drawing a curve line moving along the coasts according to the circulation of water masses in the Mediterranean Sea [Genetic differentiation among geographic samples was calculated using Weir and Cockerham’s FST  as impleFST , and JosFST , using tFST  implemenFST . In geneulations . We set nean Sea ,80. We dnean Sea  and few nean Sea .After preliminary results, we decided to perform a discriminant analysis of principal components (DAPC) using the R working package ADEGENET v2.0.0  to clustWe also used GENECLASS2  to assigeb) of a cohort from which a sample is obtained that, in populations with non-overlapping generations , is nearly equal to Ne. For the linkage disequilibrium method, a value of 0.020 was set as the lowest allele frequency used. We used preliminary results of population structure analyses to pool together homogeneous samples before calculating Ne, identifying as homogeneous only the geographic samples that were significantly different from all the others and pooling together the remaining.Contemporary effective population size (Ne) from multilocus diploid genotypes was estimated using both the method based on linkage disequilibrium data  and the O. vulgaris. The 482 bp DNA sequences of the COI region considered in the analysis were identical among all samples from Mediterranean Sea and nearby Atlantic Ocean collected in the present study. Three main clades are present in the ML phylogenetic tree obtained  and one from the Balearic Sea (Spain) which also did not result to be successful at locus oct08. We decided to treat these as missing data and included the samples in subsequent analyses. Genotypes for each individual are provided in A total of 193 unique multilocus genotypes were found over 193 individuals analysed, even after removing loci with missing data.No correlation (Pearson’s) between amount of homozygotes and amount of missing data was found neither across individuals  nor across loci , excluding the occurrence of allelic dropout in the dataset. On the contrary, null alleles were detected at all loci, the most at very low frequencies (< 1%), and few around 10–15% . The impLinkage disequilibrium between loci was only found in two population samples after Bonferroni correction: Croatia, with two couples of loci in linkage , and Strait of Messina, where each locus was in linkage with at least another one . The higo values per locus are affected by the occurrence of null alleles, as attested by the increasing of values after correction  to 32 (oct08) and observed heterozygosity values spanning from 0.187 to 0.731 . HoweverFIS per locus .Fifty-five private alleles were detected , the moser locus  and geoger locus . SignifiSimilarly to the case of HWE, inbreeding estimates corrected for null alleles were still positive (average 0.100 per locus and 0.062 per geographic sample), although lower than those calculated with the original dataset (average 0.275 per locus and 0.244 per geographic sample).r) per population ranged from 5.615 to 8.115, with the lowest value observed in the samples from the Strait of Messina  and between the Adriatic and Ionian specimens, Porto Cesareo and Croatia   . Signifi > 0.05) . No sign > 0.05) .FST did not change significantly using the dataset corrected for null alleles  with the two methods used. Estimations with the LD method varied greatly considering or not the correction for null alleles, with overall wide confidence intervals . The metOctopus vulgaris in the Mediterranean Sea and nearby Atlantic Ocean. Our results identify specimens from Ria Formosa (Atlantic Ocean) and the Strait of Messina (Mediterranean Sea) as distinct populations, as confirmed by the strong and significant differentiation detected with different methods of analysis. Conversely, the genetic differentiation among all the other specimens from the Mediterranean Sea is not straightforward, reflecting in the inability to correctly assign all the individuals to their locality of origin. Samples from the Adriatic and the Ionian Sea are homogeneous and no small-scale differentiation was detected in the Gulf of Naples. Our study also highlights higher levels of allelic richness but lower heterozygosity than other studies on the same species.We used a population genetics approach by microsatellite markers to define population structure and genetic diversity of the common octopus FIS and two loci (Vulg06 and Vulg11) showing homozygotes deficit. Homozygosity excess due to null alleles is generally locus-specific [Significant deviations from Hardy-Weinberg equilibrium (HWE) were detected in all samples analysed. Correcting the dataset for null alleles, 35 locus by locus evaluations that were not in HWE were recovered, with a general reduction of the inbreeding coefficient specific , while iFIS values per population corrected for null alleles agree with expectations, according to a review on 124 invertebrate species, where reproductive traits were related with FIS value [FIS < 0.1 are observed in marine invertebrates with internal copulation or sperm transfer such as cephalopods, whilst higher values (FIS > 0.3) in species with planktonic sperm . In general, our geographic populations showed higher allelic richness but lower heterozygosity than other studies on the same species [FIS values found in our sampling sites could be related to non-random mating within geographic populations, as shown by kinship analysis. On the contrary, an excess of heterozygosis was previously reported for Brazilian populations of O. vulgaris [Our IS value . Authors species ,34,36, w species ,91,92. THigh allelic diversity and low to moderate heterozygosity are contrasting patterns and are difficult to explain. It is possible that the fortuitous migration of individuals among populations  is responsible for high allelic richness and low number of private alleles, while the biology of the species accounts for the degree of homozygosity recorded. Small and intense bottleneck events cause substantial loss of allelic diversity, while diffuse bottlenecks spread over generations provoke the same loss of heterozygosity but a smaller reduction of allelic diversity . On the Our analysis of population structure in the Mediterranean Sea based on microsatellite markers agrees with the analysis conducted by Maltagliati and co-workers  using alo, Na and Ar are indicative of the occurrence of genetic drift. Furthermore, the high frequency of half-sibs detected in this sample strengthen its genetic structure. We are so confident in considering it as a distinct population. Moreover, we suggest the presence of a genetic subgrouping in the basin, supported by both differentiation indices used. Octopuses from the Adriatic and Ionian Sea are not genetically differentiated as well as the ones within the Gulf of Naples. We also found a partial isolation of the central and western basin, with the specimens from Croatia that are significantly different from the ones from Spain and the Gulf of Naples (NA2).Here we detected, in the Mediterranean, a strong isolation of the specimens from Strait of Messina, where the low values of HO. vulgaris, in respect to isolation by distance, as also suggested by [East and West Mediterranean populations appear separated in several marine species, as results of the glacial/post-glacial evolutionary history of the basin and present-day circulation patterns , we alserranean , and witerranean , supporterranean  along thThe occurrence of genotypes that can only be assigned to the population from the Strait of Messina can be probably explained with the peculiar characteristics of the site. This is an area of strong currents generated by the opposition of tidal phases between the Tyrrhenian and Ionian basins . These cPopulation genetic structure has been found in the common octopus also in other geographic areas at different spatial scales –34,36. IIn the context of fishery management, particular attention should be paid on the octopus population of the Strait of Messina. The high number of loci in linkage disequilibrium, the small effective population size and the relatively low allelic richness are signs of genetic erosion in this population. Extensive fishing may have caused a reduction in effective population size through genetic drift and linkage disequilibrium among loci. Further analyses in this area using more individuals and extending the spatial scale could be of help to investigate the extent of such phenomenon.The other homogenous groups from the Mediterranean Sea and the Atlantic Ocean derived by our analyses, show contrasting values of Ne according to the method used for estimation, making difficult to draw inferences.Octopus vulgaris, with some Eledone cirrhosa and E. moschata, from the western and central Mediterranean Sea and the Atlantic coasts of Iberian Peninsula. In particular, the five largest producers are Spain (16470 t), Portugal (10934 t), Italy (9884 t), Greece (2676 t), and France (1744 t). In Italy, 3295 t of O. vulgaris have been caught in 2012 , showing a decline if compared with the previous years. In this scenario, understanding the genetic population structure of O. vulgaris as well as of other exploited species over time become fundamental in order to avoid a reduction of effective population size and consequently erosion of genetic diversity. We hope that the findings of our study will be the starting point for further investigations of genetic structure of the common octopus along its area of distribution.The increasing trend in octopus catches in Europe but also in the world should focus the attention to this issue. According to FAO , EuropeaS1 DatasetFiles collected from public repositories are identified with the relative code in parenthesis.(DOCX)Click here for additional data file.S2 Dataset(XLSX)Click here for additional data file.S1 FigValues at the basis of each branch (node) indicate the percentage of occurrence of such specimens together with the other ones in the bootstrap test (1000 replicates).(PDF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 FigFST).Correlation between geographic distance (km) and pairwise genetic differentiation ((TIF)Click here for additional data file.S4 FigGeographic samples are encompassed by ellipses. See (TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableSignificance determined after Bonferroni adjustment at p < 0.000641.(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 TableAbbreviations are as follows: U = unrelated, HS = half- sibs, FS = full-sibs, PO = parent/offspring. In italics are values corrected for null alleles.(DOCX)Click here for additional data file.S5 TableAsterisks indicate the p value of each pair-wise comparison: * p < 0.05; ** p < 0.01; *** p < 0.001; ns = not significant. In bold values significant after Bonferroni correction at p < 0.0017672. See (DOCX)Click here for additional data file.S6 TableValues in italics refer to the dataset corrected for null alleles.(DOCX)Click here for additional data file.


Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs ( A fundamental goal of ecology is to understand how environmental variation influences species persistence, abundance, and gene flow Cushman, . LandscaFunctional connectivity, the degree to which the environment impedes or facilitates the movement of individuals among resource patches  affect dispersal by influencing the production and survival of migrants  in the high mountain wetlands of the Northern Rocky Mountains in Larimer County Colorado. Across the species range, boreal chorus frogs breed in primarily ephemeral wetlands with emergent vegetation in spring and summer. Individuals then disperse to wet meadows to forage during the summer and early fall  and Colorado State University Institutional Animal Care and Use Committee (# 09107A02).n = 322 individuals, Table 2) and were visited 1–3 times with the goal of obtaining 30 samples  to select sites, augmented by sites used in the Spencer study Spencer, . Of the n = 322, loci = 12, Lemmon et al., ps  is modeled as a response of three type of independent variables: spatial distribution , at-site  characteristics representing production of flow and between-site  characteristics describing resistance to flow  but global estimate of all independent variables  assume spatial autocorrelation  and (b) between-wetland environmental predictors (c), and by (c) spatio-temporal wetland connectivity predictors (c). Our spatio-temporal wetland connectivity predictors are quantified using three wetland networks: (1) a spatial network, to evaluate connectivity of 18 occupied wetlands; (2) a temporal network, to evaluate effects of annual fluctuations in hydroperiod; and (3) a stepping-stone network, to evaluate the effect of all 128 potential wetlands in the study area on genetic connectivity. All candidate models within 2 ΔAIC  within-habitat  where the sensitivity of land cover types between wetlands was analyzed at multiple spatial scales, measured as bandwidths along each network edge [30 (minimum resolution), 60, 120, and 240 m buffers, Murphy et al., Wetland characteristics are expected to control the number of potential migrants. Therefore, we included within-wetland (node) variables potentially important for recruitment: peripheral habitat (ratio of meadow to forest), run-off (impervious surfaces), water accumulation potential (compound topographic index), precipitation timing (precipitation ratio), site accessibility (relative slope position), and conductivity . These functional connectivity metrics quantify the functional capacity of the landscape to inhibit or facilitate movement and, consequentially, gene flow . We classified observed wetland permanence . The resulting stepping-stone network is the sum of the 18 sampled breeding wetlands and 110 wetlands located within the study region and were considered potentially suitable for intermediate habitat, for 128 nodes. We considered all selected wetlands to be neutral to snowpack variation for the stepping-stone network. We calculated functional connectivity predictors as described in the spatial-breeding network only for our 18 sampled, occupied wetlands to quantify the effect of neighboring wetland habitat on functional connectivity on our focal sites.To evaluate the effect of neighboring wetlands on × = 14.16) and heterozygosity from 0.212 to 0.788 (× = 0.483) by locus , 84% of non-significant values were sites with less than 700 meters separation. Pairwise GST values ranged from 0 to 0.370. Dps also indicated genetic structure in our study area, ranging from 0.312 to 0.943 (× = 0.553).All 11 microsatellite loci were polymorphic, with between 7 and 26 alleles per locus  included distance between sites (distance) with within-site moisture  and between-site resistance . In the stepping-stone network, functional connectivity quantities  for all 18 sampled sites were low  but variable. The Connector metric did not contribute to overall wetland connectivity (PC < 0.01%) for any wetlands in any of the three types of networks.Considering only wetland connectivity metrics in predicting genetic distance, we found that the presence of stepping-stone wetlands (stepping-stone network) was the highest contributor to the top models explaining genetic connectivity Table . PercentP. maculata over space and time, including climatic fluctuations to address the potential impact of climate warming on the genetic structure of populations. We found that complex interactions among covariates , have distinct and potentially critical roles in controlling genetic connectivity in boreal chorus frogs.Understanding how spatio-temporal variation in habitat composition and configuration influences species dispersal, colonization success, and gene flow is critical to predicting species demographic dynamics in changing landscapes. Variability in the state of environmental conditions on which many species depend may have significant consequences on individual development, population dynamics, and genetic diversity , a greater capacity to hold water (measured as compound topographic index), and presence in all years . Indeed, based on ΔAIC model results, surface relief and precipitation were moisture predictors that explained genetic connectivity independently better than other individual predictors Table . These mP. maculata genetic connectivity: topography and moisture. Habitat and landscape controls on functional connectivity are crucial factors that facilitate species persistence and genetic diversity (Funk et al., Two between-wetland characteristics influenced P. maculata, the presence of stepping stone wetlands possibly improves the probability of dispersal success and gene flow among occupied wetlands and is likely important when there is high topographic between-wetland resistance. This result demonstrates the importance of the underlying habitat spatial heterogeneity compared to fluctuations of critical environmental factors potentially influencing population dynamics of a dispersal-limited species.The stepping-stone wetland connectivity metrics were considered most important in explaining genetic connectivity despite a much lower magnitude in values relative to the spatial-breeding and temporal-breeding networks. While Euclidean distance alone was not a significant predicator in any of the best models, the presence of wetland habitat between the 18 occupied wetlands was a significant factor. Therefore, wetland spatial heterogeneity likely interacts with fluctuating environmental characteristics to affect amphibian genetic connectivity. Stepping-stone habitat improves a given habitat's probability of connectivity regardless of that habitat's area (Saura and Rubio, P. maculata and that high snowpack results in consistent inter-annual habitat availability for frogs. Thus, high snowpack is associated positively with gene flow. Because chorus frogs produce large numbers of propagules and show little parental investment, more wetland should facilitate greater production and increased colonization success (Corn, Our results indicate that winter snowfall is essential to the amount and quality of wetland that is available to ss Corn, , especiass Corn, .We argue that fluctuating environmental conditions in heterogeneous landscapes have a potential role in structuring spatially-explicit populations, and could be important drivers of metapopulation dynamics. Theoretically, a classic metapopulation structure is defined by interbreeding subpopulations linked by dispersal and extinction-colonization dynamics (Smith and Green, Bicyclus expressed coupled genetic and physiological plasticity in seasonally-fluctuating environments (Brakefield, The effects of environmental controls on metapopulation dynamics are not limited to amphibians (Johst et al., P. maculata and other dispersal-limited pond-breeding species. We also expect that similar fluctuations may be observed in different landscapes. Empirical investigations of agricultural or urban environments where land use and climate changes may co-occur, such as other montane (Koscinski et al., Our study used landscape genetic and graph-theoretic connectivity methods to examine how interactions between habitat spatial heterogeneity and climatic variability can influence metapopulation dynamics. The inclusion of fluctuating habitat conditions on species dispersal, colonization, and genetic rescue effects is an essential contribution to advance our understanding of metapopulation ecology. Our work emphasizes the importance in expanding investigations of genetic signatures of populations in dynamic landscapes for multiple species, metapopulations, and metacommunities. Specifically, in a conservation context, these results hold considerable importance in predicting species future responses to human driven land-use and climate change. Considering the likelihood of future climate-driven shifts in precipitation, we expect that fluctuations in habitat availability will continue to affect the metapopulation capacity of Conceived and designed the field work: MM, EM, WF. Performed the experiments: MM. Analyzed the genetic data: SB, BJ, SM, MM. Gravity modeling: MM, PS. Wetland connectivity: MF, AW. Wrote the paper: AW, PS, EM, MM. All authors provided substantial review and comments to written manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Phellodendron amurense Rupr. is a tree species (family Rutaceae) that is endangered due to excessive and illegal harvesting for use in Chinese medicine. Here, we test a general computational method for the prediction of priority conservation areas (PCAs) by measuring the genetic diversity of P. amurense across the entirety of northeast China using a single strand repeat analysis of twenty microsatellite markers. Using computational modeling, we evaluated the geographical distribution of the species, both now and in different future climate change scenarios. Different populations were analyzed according to genetic diversity, and PCAs were identified using a spatial conservation prioritization framework. These conservation areas were optimized to account for the geographical distribution of P. amurense both now and in the future, to effectively promote gene flow, and to have a long period of validity. In situ and ex situ conservation, strategies for vulnerable populations were proposed. Three populations with low genetic diversity are predicted to be negatively affected by climate change, making conservation of genetic diversity challenging due to decreasing habitat suitability. Habitat suitability was important for the assessment of genetic variability in existing nature reserves, which were found to be much smaller than the proposed PCAs. Finally, a simple set of conservation measures was established through modeling. This combined molecular and computational ecology approach provides a framework for planning the protection of species endangered by climate change.Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance is a product not only of habitat suitability in conservation areas but also of efficient protection and management.  Climate change has had a huge impact on the genetic diversity of plant species and has damaged the habitat of wild plants, which continue to decline in large numbers, challenging the survival of some endangered species , native to China, Korea, and Japan  as a vulnerable plant. The ecological protection of P. amurense is therefore considered extremely urgent  suitable for either in situ or ex situ conservation measures. Maxent and Zonation are two models that have been increasingly used by protected area planners and managers for species rehabilitation and habitat conservation , geographical information systems (GIS), species distribution modeling (SDM) such as Maxent, and spatial conservation planning such as Zonation to devise PCAs for We devised conservation strategies to protect genetic diversity using a combination of genetic mapping and computational simulation. First, we established the associations between genetic diversity and habitat suitability to ensure that these measures provide a reasonable basis for assessing ecological processes; second, we assessed current habitat suitability and predicted future suitability under two climate change scenarios  and representing 9.8% of the total area of China  accounts for 27.8% of the national total . In 16 of these plots, approximately 20 samples were taken, and each sample was separated by at least 200 m, in or near the sample plots  as the meshing tool and divided into 30 × 30 km² grids, which were surveyed systematically. Sample plots  of 30 × 30 m² were selected in each study grid, and 3–8 plots were established according to the vegetation conditions of the survey area. Where possible, plots were located in the central region of the grids, and the plot's distance from the edge of the grid was never <15% of the side length of the grid. A GPS system was used to record the populations of 2 at the equator) for the environmental layer input of the SDM. Four bioclimatic variables of 0.5-arc-min spatial resolution – mean annual temperature, mean annual precipitation, temperature seasonality, and precipitation seasonality – were downloaded from the WorldClim data base (http://www.worldclim.org) because they are considered the critical parameters for modeling the geographical distributions of plant species. The bioclimatic variables whose Pearson correlation coefficients with the other variables were between 0.8 and −0.8 were removed to eliminate the negative effect of multicollinearity on the adjustment of the SDM (Escoriza http://srtm.csi.cgiar.org), and we extracted the elevation, aspect, and slope data from the DEM using ArcGIS 10.0 (Esri). Lastly, we obtained land use and land cover (LULC) data from GlobCover V2.3  and used to predict how climate change would alter habitat suitability for P. amurense during these periods. We used the A2 and B2 emission scenarios for the future environmental layer input in Maxent. The A2 scenario represents a highly heterogeneous world with extremely unbalanced development, including self-sufficiency and local protectionism; the study region, therefore, had a large population and high growth rates. Economic development was primarily regionally orientated, with per capita economic growth and technological change being fragmented and slow. The B2 scenario presents a world committed to local solutions to economic, social, and environmental sustainability, and the global population is continuously increasing but at a rate lower than in the A2 scenario. The predicted direction of change was toward environmental conservation and the sustainable development of society. A2 differs from B2 by having larger cumulative concentrations or emissions of carbon dioxide; the result is a different pattern of climate change due to varying anthropogenic emissions of greenhouse gases and other pollutants. Therefore, A2 and B2 were used as high and low emissions scenarios, respectively .Future bioclimatic variables were assessed using HCCPR_HADCM3 analog data , downloaded from the International Centre for Tropical Agriculture  from 16 populations were tested. A set of twenty simple sequence repeats (SSRs) was selected according to polymorphism , 0.3 μL of E00 (10 μmol/L), 0.3 μL of H20 (10 μmol/L), and 0.2 μL of Taq polymerase. The PCR program was denaturation at 94°C for 45 sec, annealing at 50°C for 45 sec, five cycles of extension at 72°C for 45 sec, followed by a final extension step for 10 min at 72°C. The PCR products were stored at 4°C. The PCR amplifications were performed using the GeneAmp PCR 9600 System , and Shannon's index (I); indirect gene flow (Nm) was computed using GenAlEx (PAS) 6.5 for pairwise population differentiation , the average number of effective alleles per population (Ne), the average observed heterozygosity per population (Ho), the average expected heterozygosity per population (He), the fixation index (http://www.cs.princeton.edu/∼schapire/maxent/) was used to model the current and future potential distributions of P. amurense in the SDM. To do this, the function of habitat suitability with maximum entropy was estimated  it has the ability to handle low sample sizes, which drastically impact both the performance and the adjustment of SDM  of 315 s et al.  and Elits et al.  are suits et al. . The jacs et al. . We regas et al. .We used three methods to test the accuracy of the model, namely, AUC, κ, and true skill statistic  to develop conservation plans for maintaining genetic diversity in response to climate change. Zonation is typically used as a spatial conservation prioritization framework for large-scale conservation planning for species, but, here, we adapt the Zonation algorithm to establish protection areas for maintaining the genetic diversity of P. amurense across large spatial and temporal scales. The highest priorities for conservation, namely protected areas for maintaining genetic diversity, were confirmed by identifying the top-ranking cells after computation , as assessed by Maxent values ≥0.5 for each pixel (the input layers for Zonation), were used in the Zonation algorithm to simulate conservation areas in current and future climates. Our goal was to protect the entire current presence distribution of P. amurense from climate change. These maps of the present and the A2 and B2 scenarios  were regarded as the habitat suitability distributions of P. amurense weighted equally for the inputs of Zonation.First, the predicted presence distribution maps of Second, to effectively promote gene flow, we modeled consistent and effective core areas and considered the validity of the future reserves  that were equal to or greater than the threshold value of 0.5 as indicating the presence of a species; in other words, protection is needed for populations with both low and high genetic diversity. Some populations  demonstrated continuously low habitat suitability over time , κ value at 0.767 and TSS value at 0.740; the variable contributions are shown in Table I, Ne, Na, and habitat suitability. There is a positive relationship between He, I, Ne, Na, and habitat suitability, and, from the results of the binary fitting method, genetic diversity noticeably drops when habitat suitability falls below 0.5. Though genetic diversity will drop slightly, the overall trend is stable. The parameters such as Ne, I, and He that showed high correlation coefficients  as assessment criteria for genetic diversity , and values much lower than 0 are suitable for ex situ measures due to an excess of heterozygosity, which could determine the methods of protection from the perspective of gene flow  requires special attention. As shown in Figure F values) are suitable for ex situ conservation, while populations 7, 12, and 16  are most suited to in situ conservation.Moreover, in this study, the value of Nm is 2.089, indicating that gene flow exists between populations  determining the most appropriate method (in situ or ex situ conservation) to protect target populations; (2) analyzing the nature of the relationship between genetic diversity and habitat suitability; (3) delineating protection sites and areas of in situ and ex situ conservation; and (4) incorporating the regions within existing nature reserves.P. amurense, as they were represented by Maxent values, that is, habitat suitability values. Finally, we established areas for the conservation of genetic diversity through the computation of habitat suitability and accounted for the most important ecological processes that will drive species range shifts in the future. The results of this study indicate that this simple and practical modeling method can identify PCAs, which in this case could conserve the genetic diversity of P. amurense with nearly 100 years of validity. For the modeling of protection areas, we considered the current and future potential geographical species distributions and changes in habitat suitability and then selected in situ or ex situ conservation approaches for populations in sites within PCAs. Ultimately, this will effectively protect genetic diversity and increase gene flow and is a methodology that can be applied to any endangered species requiring future conservation planning.Here, a simple evaluation framework has been established for the convenient assessment of genetic diversity, based on the assessment of genetic diversity and habitat suitability, which were positively spatially correlated. This allowed us to simulate PCAs for


Plasmodium falciparum isolates from uncomplicated malaria cases over a ten year period (2003–2013) in Ghana using the polymorphic antigenic marker, merozoite surface protein 2 (msp2).Genotyping malaria parasites to assess their diversity in different geographic settings have become necessary for the selection of antigenic epitopes for vaccine development and for antimalarial drug efficacy or resistance investigations. This study describes the genetic diversity of msp2 for the two major allelic families, FC27 and 3D7, using nested polymerase chain reaction (PCR). The allele frequencies and the multiplicity of infection were determined for the nine sites for five time points over a period of ten years, 2003–2004, 2005–2006, 2007–2008, 2010 and 2012–2013 malaria transmission seasons.Archived filter paper blood blots from children aged nine years and below with uncomplicated malaria collected from nine sites in Ghana were typed for the presence of the markers. A total of 880 samples were genotyped for msp2 gene by resolving PCR products on agarose gels was 14. Both of the major allelic families, 3D7 and FC27 were common in all population samples. The highest multiplicity of infection (MOI) was observed in isolates from Begoro : 3.31 for the time point 2007–2008. A significant variation was observed among the sites in the MOIs detected per infection  for the 2007 isolates and also at each of the three sites with data for three different years, Hohoe, P = 0.03; Navrongo, P < 0.001; Cape Coast, P < 0.001. Overall, there was no significant difference between the MOIs of the three ecological zones over the years (P = 0.37) and between the time points when data from all sites were pooled (P = 0.40).The number of different alleles detected for the msp2 gene in Ghanaian isolates were observed to be profound; however, there was homogeneity throughout the three ecological zones studied. This is indicative of gene flow between the parasite populations across the country probably due to human population movements (HPM).The diversity and variation between isolates detected using the The online version of this article (doi:10.1186/s13071-016-1692-1) contains supplementary material, which is available to authorized users. Malaria parasite genetic diversity creates a great hindrance to vaccine development efforts and enhances antimalarial drug resistance. Genetic diversity occurs as a result of genetic recombinations from numerous allelic polymorphisms exhibited at various genetic loci and also through diversifying selection by immunity , 2. It hmsp2) is a polymorphic antigenic marker that has been used extensively to describe the diversity of parasite populations in many malaria endemic countries. Msp2 gene has two major allelic families, FC27 and ICI/3D7 based on the variable non-repeat sequences as well as the varying sizes of the tandem repeats in the central region [msp1, msp2 and glutamine-rich protein (glurp), which have been endorsed by the WHO for use in distinguishing between recrudescence and new infection in recurrent infections during antimalarial drug efficacy investigations, the msp2 marker is the most polymorphic and therefore the highest discriminatory and informative marker [The merozoite surface proteins 2  transmits the parasite in all 3 ecological zones, A. melas transmit in the coastal savannah zone, A. arabiensis and A. funestus (s.s.) transmits mostly in the Guinea savannah zone of the country. Transmission intensities are high with peaks observed during the wet season. Malaria accounted for 44 % of all outpatient clinic visits in 2013 and 22.3 % of all under-five deaths in Ghana [Ghana is a malaria endemic country with three different ecological zones with either perennial or seasonal transmission of malaria. The northern part of the country has Guinea savannah ecology, middle belt has forest ecology and the southern part has coastal savannah ecology. Seasonal transmission is observed in the northern part whilst the forest and the coastal savannah experiences perennial transmission. The vectors of transmission vary per the ecological zones such that in Ghana . The maiin Ghana .msp2 alleles in P. falciparum isolates from uncomplicated malaria cases collected over ten years (2003–2013) from nine sentinel sites for monitoring antimalarial drug efficacy/resistance in Ghana. Findings from this study will serve as baseline data for future studies on parasite population structure and antimalarial drug resistance surveillance in the country.Information on the diversity of malaria parasites in Ghana is scanty and in the search for an effective vaccine for the African malaria endemic region it is crucial to describe genetically, the parasite population structure over the years. This study therefore determined the genetic diversity of parasites in the country by detecting the presence of The archived samples used for this study were collected in 2003–2013 from nine out of the ten sentinel sites set up by the Noguchi Memorial Institute for Medical Research (NMIMR) and the National Malaria Control Programme (NMCP) for monitoring antimalarial drug resistance in the country. The description of these sites has already been published –22. ThesArchived filter paper blood blots collected from children aged nine years and below with uncomplicated malaria from antimalarial drug resistance surveillance studies conducted in 2003 to 2013 and stored at room temperature were used –22. Thesmsp2 alleles following recommended standardised protocols from the Worldwide Antimicrobial Resistance Network (WWARN) and World Health Organization (WHO) for the identification of parasite populations [msp2 gene are from previously published protocols [Parasite DNA from 880 filter paper blood blot samples was extracted using Qiagen DNA Blood Minikit . Parasite species detection using nested PCR was done following published protocols with minimal changes , 24. Nesulations –12. The rotocols –12  defined as the mean number of genotypes per infection was determined as the quotient of the total number of alleles per locus over the total number of PCR positive samples per locus. Differences in the MOI between time points and the ecological zones were determined by analysis of variance (ANOVA) whilst a difference in MOIs between the sites per time point was determined using Chi-square test and Fisher’s exact test.msp2 alleles, FC27 and 3D7 for five different time points. Of the 880 samples analysed, 52 (6 %) were from 2003 to 2004, 209 (24 %) from 2005 to 2006, 372 (42 %) from 2007 to 2008, 89 (10 %) from 2010 to 158 (18 %) from 2012 to 2013. The contribution from each site to the total number of samples is shown in Table msp2 ranged from 46 to 100 %. It was observed that sensitivity was comparatively higher in the most recently collected samples 2007–2013. Therefore, data analysis was conducted with 711 PCR positive samples, 37 from 2003 to 2004, 136 from 2005 to 2006, 332 from 2007 to 2008, 73 from 2010 to 133 from 2012 to 2013 .Fourteen different alleles were detected for P = 0.370) and between the five time points when the data was pooled (Fisher’s exact test P = 0.405). Except for the isolates from 2007 which showed a significant variation among the sites in the distributions of numbers of alleles of msp2 detected per infection   over the years. A recent genome-wide sequences analysis of isolates from two ecologically distinct areas in Ghana also showed the genetic structure of parasite populations as very similar [The parasite population structure of  the WHO –12. The  similar . The numMsp2 block 3 is known to have a higher polymorphism and therefore provides very useful information in describing the diversity of parasites in a population compared to msp1 and glurp [msp2 gene and the predominant allelic genotypes detected had low to high frequencies which fluctuated at the different time points. This observation of predominant alleles is due to genetic recombinations that result in parasites with particular alleles having high frequencies and consequently a high level of biological fitness [msp2 gene, 3D7 was the predominant allele and this observation has also been made in several African and Southeast Asian countries [msp2 allele in high disease transmission areas.nd glurp , 13. The fitness . These f fitness . These i fitness . Of the ountries , 28–38. ountries . It is emsp2 alleles (FC27 and 3D7) did not vary significantly among the nine populations in 2007 as a result of each local population having similarly wide spectrum of genotypes variation within each of these major types, the observed variation in MOIs estimates could not be due to differences in msp2 allelic diversity locally . Whole genome sequence analyses show that parasite populations in different parts of West Africa have very similar genetic diversity [msp2 alleles as observed in our study over time has also been observed in parasite populations from the Gambia and Brazil [There was generally no significant difference in the MOIs between the different ecological zones and also between time points when data were pooled; however, for the isolates from nine sites in 2007 showed variability in the MOIs. Although the population frequencies of the two iversity , 40, andiversity . As thesiversity , 18. It iversity , 42. Thid Brazil , 43, 44.msp2 gene investigated across the country. The implication of the observed level of genetic diversity in parasite populations in high transmission areas as a result of genetic recombination poses a threat to the identification of antigenic epitopes for malaria vaccine design. Although extensive genetic diversity is a hindrance to vaccine development efforts, for people living in endemic areas, such diversity enhances the encounter with diverse parasite clones which in turn, help with the natural acquisition of immune responses against the multiple clones of the parasite and subsequent protection against disease symptoms.The observation of lack of differences in parasite variants in all three ecological zones may be due to HPM across the country. For people living in the Guinea savannah ecological zone with seasonal transmission, during the dry season which could last for about 6 months, they become migrant workers who move to perennial transmission areas for economic reasons and return to farm their lands before the rains begin. As such they are carriers of parasites from their ecological zone to other zones and also carry parasites of the other zones back to their areas. HPM between rural and urban areas is the norm in the country for trading purposes and for visiting extended families which is an important cultural practice. Therefore, HPM greatly enhances the movement of parasite variants from one place to another which results in variants with minor differences in alleles of the Sequencing the polymorphic regions and microsatellite typing of the genetic locus investigated could provide deeper insight into the variations in gene sequences as detected by other studies , 29, 45,msp2 gene. However, there was minimal variation or homogeneity in parasite populations across the country which may be due to gene flow from the effect of human population movements.There was an immense genetic diversity in the parasite population in Ghana upon investigating the glurp, glutamine rich protein; HPM, human population movements; IPTp, intermittent preventive treatment in pregnancy; IRB, institutional review board; IRS, indoor residual spraying; LLINS, long lasting insecticide-treated nets; MOI, multiplicity of infection; msp1&2, merozoite surface proteins 1 and 2; NMCP, national malaria control programme; PCR, polymerase chain reaction; SMC, seasonal malaria chemoprevention; WHO, World Health Organization; WWARN, worldwide antimicrobial resistance networkACT, artemisinin-based combination therapy; ANOVA, analysis of variance; DNA, deoxyribonucleic acid;