Ursus thibetanus) have a widespread distribution in mountain landscapes, and are considered vulnerable globally, but are low-priority species for conservation in Nepal. Habitat fragmentation, illegal hunting, and human-bear conflict are the major threats to Asiatic black bears across their global range. Having an adequate level of genetic variation in a population helps with adapting to rapidly changing environments, and thus is important for the long-term health of bear populations. Accordingly, we conducted non-invasive surveys of bear populations in the Annapurna Conservation Area (ACA) to elucidate genetic diversity, genetic structure, and the phylogenetic relationship of Asiatic black bears from this region of Nepal to other subspecies. To assess levels of genetic diversity and population genetic structure, we genotyped eight microsatellite loci using 147 samples, identifying 60 individuals in an area of approximately 525 km2. We found that the Asiatic black bear population in the ACA has maintained high levels of genetic diversity (HE = 0.76) as compared to other bear populations from range countries. We did not detect a signature of population substructure among sampling localities and this suggests that animals are moving freely across the landscape within the ACA. We also detected a moderate population size that may increase with the availability of suitable habitat in the ACA, so bear-related conflict should be addressed to ensure the long-term viability of this expanding bear populations. Primers specific to bears were designed to amplify a 675 bp fragment of the mitochondrial control region from the collected samples. Three haplotypes were observed from the entire conservation area. The complete mitochondrial genome , the first obtained from wild populations of the Himalayan black bear (U. t. laniger), was also sequenced to resolve the phylogenetic relationships of closely related subspecies of Asiatic black bears. The resulting phylogeny indicated that Himalayan black bear populations in Nepal are evolutionary distinct from other known subspecies of Asiatic black bears.Asiatic black bears ( Ursus thibetanus has a broad geographic distribution across south and southeast Asia, China, Russia, Korea, and Japan .–14.12–14Genetic information can be used to better understand the population response of bears to human-induced landscape changes even in the absence of detailed ecological and biological data. Large mammals such as bears often occur at low densities, requiring expansive and continuous landscapes to maintain viable populations . Small, U. t. laniger) inhabits the mountain range in Nepal.Recent records indicate that the wild populations in Nepal are presumably undergoing rapid changes in population size –24. EndaHair and fecal samples from bears were collected non-invasively, without capturing or handling any animals. The study permits were granted by the Department of National Parks and Wildlife Conservation (DNPWC), Ministry of Forest and Soil Conservation (MoFSC), Government of Nepal, Kathmandu (Letter No. 490-22/09/2015) and National Trust for Nature Conservation (NTNC)/ACAP, Pokhara, Nepal (Letter No. 546-04/07/2016).2) established in Nepal, representing 22% of the protected areas in the country. Within the ACA, the forest, which is the preferred habitat of Asiatic black bears, comprise 1,160 km2 (15%) from the southern mid-altitude to the north high-altitude mountain region [Schima-Castanopsis, Pinus roxburghii, Quercus spp., Acer spp., Pinus wallichiana, Abies spectabilis, Betula utilis, Aurndinaria spp., and Rhododendron spp. ACA forests support several endangered species: Himalayan black bears (U. t. laniger), red panda (Ailurus fulgens), musk deer (Moschus chrysogaster), and clouded leopards (Neofelis nebulosa) in the study site and snow leopards (Panthera unica), Tibetan brown bears (U. actor pruinosus), and Himalayan wolves (Canis lupus chanco) in the upper Himalayan region. Traditionally, the people of in this region have been highly dependent on natural resources, particularly the mountain forests [This study was carried out in the southern middle and high mountain forests of the ACA . The ACAn region . The for forests , which h2) over the six units and in the adjoining cropland. We opportunistically collected fecal samples from the agricultural land locating adjacent the bear habitats. The grids were selected based on accessibility, geographic representation, and forest type to better represent the bear population for genetic assessment. We walked along animal trails, villagers’ routes, and mountain ridges to cover the different habitats of bears. If bear signs were observed, the search for fresh feces was intensified as these yield higher-quality DNA [Intensive sampling was conducted in six management units of the ACA during the rainy (July-September) and autumn (October-December) seasons of 2015 and 2016. Four and two of the management units were located in the middle and high mountain regions of the ACA, respectively. We searched for fecal and hair samples within 21 grids  for fecal samples and the Wako DNA Extractor FM Kit  for hair samples according to the manufacturers’ instructions. We included negative controls and processed DNA samples under sterile conditions to avoid cross-contamination.U. americanus [U. arctos [U. t. japonicus [ID), and having a high value (> 0.5) of polymorphic information content (PIC) [Amelogenin gene with the primers SE47/SE48 for molecular sexing of individual Asiatic black bears [For the microsatellite analysis in this study, 27 loci were initially tested using 16 fecal samples to determine genotypes; 11 loci from ericanus –41, 10 l. arctos , and 6 laponicus . The print (PIC) . We usedck bears –46. SampEach sample that was successfully amplified in the first multiplex set of three loci was genotyped two additional times to control for genotyping errors. Poor-quality DNA from fecal samples could lead to the misidentification of individuals and biased estimates –48, and We amplified the left variable region of the mitochondrial control region (CR)/D-loop (approximately 675 bp) of all identified individuals using the bear-specific primer pairs 11H2 and 11L2, and BED 1–2 and BED 3–3 . AmplifiA), effective no of alleles (NE), observed heterozygosity (HO), expected heterozygosity (HE) and Unbiased expected heterozygosity (uHE)) and Wright’s inbreeding coefficient (FIS) [ID, the probability of identity of siblings (PIDSibs), PIC, and the null allele frequency (Fnull) of each locus, were calculated using CERVUS version 3.0.7 [Samples that matched at all eight loci were pooled to create individual genotypes using GIMLET version 1.3.3 . Geneticnt (FIS)  were calnt (FIS) . The Harnt (FIS) . Bonferron 3.0.7 . The GPSPairwise relatedness values (r) were calculated for all individual bears using the estimator developed by Queller and Goodnight  in GenALSequences were visually inspected for errors, multiple peaks, and heteroplasmy using FinchTV version 1.4.0 (Geospiza Inc.), and aligned with Clustal W  in MEGA http://popart.otago.ac.nz) to investigate the possible relationships between CR haplotypes of Asiatic black bears and haplotypes generated from Nepal. Phylogenetic trees were prepared using maximum likelihood (ML) and Bayesian inference (BI) with the programs RAxML version 8.2.10 [The complete mitogenome and the haplotypes sequences of six subspecies of Asiatic black bears were obtained from the GenBank . The Japn 8.2.10 , CIPRES n 8.2.10 , respectn 8.2.10 , using cn 8.2.10  to verifn 8.2.10  in the pn 8.2.10 . No gammn 8.2.10 . A maximID (> 0.250) and lower PIC (< 0.5) values than the other loci. Following amplification, we selected 8 of the 19 polymorphic loci with high amplification success, also taking into account their ease of use in multiplex PCR and readability of their allelic peaks  for the eight microsatellite loci ranged from 5 to 10, and averaged 7.6, which was higher than the effective numbers of alleles (4.4). MU23 and MU50 were highly polymorphic with 10 alleles whereas G10B and UamB5 were the least polymorphic with 5 alleles (O) and expected (HE) heterozygosity were 0.798 and 0.760, respectively. No significant deviation from HWE (P > 0.306) or LD was detected between pairs of the eight microsatellite loci (P > 0.07). Three pairs had slight deviations that were not statistically significant after Bonferroni corrections (P > 0.02). The cumulative PID and PIDSibs were 3.17 × 10−09 and 5.5 × 10−04, respectively, which indicated that the power of the markers selected was more than sufficient to discriminate among individuals. Similarly, PIC averaged 0.727, and ranged from 0.617 to 0.816. The value of FIS was -0.041, indicating no signs of inbreeding among populations. The negative value of FIS also indicates an excess of heterozygous individuals in the region, a finding supported by the lower proportion (< 0.1) of null alleles.The number of alleles  of the ACA that included both forests and surrounding farmlands.From the 97 samples that were successfully genotyped, we identified 60 individuals, of which 20 were sampled multiple times . Two indThe average pairwise relatedness value for 1,770 pairs among 60 individuals was less than 0.05 , which suggests that individuals were highly unrelated to one another. Models with and without LOCPRIOR showed that no individual was assigned with high posterior probability (q ≥ 0.7) to any of the two clusters at K = 2 . IndividU. t. laniger using hair and fecal samples, although a mitogenome of U. t. laniger was previously sequenced from an old skin found in a monastery near the Nepal-Tibet border [U. t. mupinensis  was successfully sequenced. We sequenced three haplotypes that were distinguished by two transition substitutions of adenine (A) and guanine (G) and a repeated-number variation at a T-repeat site . Haplotyt border . VNTRs lpinensis .U. t. laniger from the ACA of Nepal formed a monophyletic clade with U. t. thibetanus and with respect to other reported Asiatic black bear subspecies. A similar tree topology was obtained using mitogenomes (excluding the VNTRs of the CR) and the dataset of 12 protein-coding and 2 rRNA genes  in Kluane [This study revealed that there is no any evidence to suggest that the genetic diversity and geneflow of Himalayan black bears in Annapurna region of Nepal are inadequate, and we did not detect any evidence of inbreeding in the population. We found no significant differences between observed and expected heterozygosity, low levels of relatedness among bear individuals, and a lack of population substructure. The average expected heterozygosity was similar to that found in Indian 0.72 ) and Rus  and Rusn Kluane . As thesn Kluane , the genNo evidence of population substructure was found among the ACA populations, indicating a high degree of admixture throughout the conservation area. Our results are similar to those reported for the population in Dachigam National Park in northwest India . The resGlobally, habitat fragmentation and degradation are major causes of population decline and species extinction , which a2) was less than previous estimates from the national parks of the western Himalayas (17 bears/100 km2) and Thailand (8–29 bears/100 km2) [2 and 8–9 bears/100 km2, respectively [Available data indicate that there are approximately 500 black bear individuals in Nepal . From th100 km2) –84, whicectively . Our anaSampling in this study was mainly opportunistic and geographically biased, and individual bears were not found repeatedly due to the large geographic distances. Although collecting fecal samples from agricultural land and the nearby bamboo forest during the rainy season was relatively manageable, it was difficult to obtain high-quality DNA due to the high levels of moisture in the samples . We recoU. t. gedrosinus. In previous studies, the lack of phylogenetic resolution for Asiatic black bears was primarily due to the low level of variation in the much shorter sequences of cytochrome b or the CR. Previous studies also placed the Japanese subspecies (U. t. japonicus) as the basal group to all other U. thibetanus subspecies [U. t laniger. However, the geographical origin of this individual is unknown. Based on the largest mtDNA dataset available from Asiatic black bears, our mitogenome-based phylogeny provides strong evidence that U. t. laniger is the most basal of all black bear subspecies on the Asian continent. The Japanese black bear was estimated to have diverged from continental black bears approximately 1.48 Mya [U. t. laniger diverged from other lineages of U. thibetanus at 475 Ka BP [U. t. ussuricus also clustered into a single clade [This is the first study using genetic and geographic data from the mitogenome sequences from six subspecies and two Asiatic black bears of unknown origin. The only subspecies that was not represented in our phylogeny was bspecies , 87. In bspecies  branched1.48 Mya  and the 75 Ka BP . Individle clade , 72.U. t. laniger in the ACA that is considered ancient with respect to all other mainland Asiatic black bears subspecies [U. t. mupinensis as basal to all other U. thibetanus in their Clade A. Although the sequences used in Choi et al. [U. t. mupinensis in our phylogenetic tree was placed monophyletic to the other subspecies of U. thibetanus but the U. t. laniger sequences were the basal group. Our phylogenetic analyses inferred from mitogenomes of two unknown and six known subspecies suggesting that whole mitogenomes (without the VNTRs of the CR) were more informative and provide a high resolution for Asiatic black bear phylogeny. The CR and cytochrome b genes are not sufficiently informative to resolve phylogenetic relationships in Asiatic black bears, particularly among such closely related subspecies. Although the left domain of CR is considered the most appropriate region to use in constructing phylogenetic trees [U. t. japnonicus and U. t. ussuricus from China [U. thibetanus and U. malayanus in northern Cambodia [Our mitogenome analysis strongly supports previous finding of a monophyletic lineage of bspecies , 11 and bspecies  that plai et al.  were froic trees , we did om China , and U. Cambodia  have beeCambodia .U. t. laniger from the Himalayan region based on the specimen from the Mustang district monastery [U. t. laniger from India and Pakistan also formed a well-supported clade with other continental bear subspecies using the amplicon sequence of cytochrome b [Our phylogenetic analyses demonstrated that lineages of the Himalayan black bears in Nepal are ancient and genetically distinct from lineages of other subspecies of Asiatic black bears from the main continent . Our results corroborate the findings of previous studies of onastery . Mitogenchrome b .U. t. laniger is likely distributed throughout the western Himalayan mountain range from Nepal to Pakistan, including the northwest India. Further sampling along the eastern Himalayas in Nepal, India, Bhutan, and Myanmar may help to more clearly define the distribution range of U. t. laniger and U. t. thibetanus in the east. We found no evidence of a habitat overlap between the Tibetan brown bear (U. a. pruinosus), the sloth bear (U. ursinus), and U. t. laniger in ACA. The brown bear has been sporadically recorded in the northern part of the ACA and sloth bears inhabit southern Chitwan National Park of the Chitwan-Annapurna landscape [Based on our results, we propose that andscape .U. t. laniger) from Nepal is genetically distinct and belongs to an ancient lineage of continental Asiatic black bears. We were also able to count the minimum number of bears in the ACA population from non-invasive samples. The genetic analyses revealed that no management interventions are currently needed to maintain genetic diversity in the population, but human-bear conflict has to be addressed for long-term survival of the bears. Our study indicates that community-based conservation in the ACA may have contributed to the viability of the bear population here, with low levels of population substructuring. Still, our results were based on samples collected within a single conservation area. Additional non-invasive studies on evolutionary lineage, population status, genetic diversity, and genetic structure should be conducted over the entire mountain landscape of Nepal with sufficient sample replicates to represent this widespread species. This is the first genetic assessment of Asiatic black bears in Nepal and the information herein should be incorporated in Nepal’s national assessment, and when revising the IUCN status and conservation action plan for Asiatic black bears.Our intraspecific phylogeny demonstrates that the wild population of Himalayan black bears (S1 Text(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableAnalysis were carried out based on 16 fecal samples which later identified 8 unique genotypes.(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 TableEach K was performed 5 iterations and a mean value was estimated. The lowest value of Ln likelihood and the low variance of Ln likelihood suggest that the true value of K = 1, implying that Himalayan back bears of ACA are one breeding population and that there is gene flow between northern high mountains and southern mid hills.(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S1 FigThe mean of estimated Ln probability of data is higher when population sub cluster K = 1. Y axis values are fixed from -1600 to -1670 for clear presentation of graph.(DOCX)Click here for additional data file.S2 FigU. t. japonicus (AB863014) was used as an outgroup. Only bootstrap values over 50% and BPP over 0.5 are shown. Sequences are identified by the subspecies name, origin and country name, followed by the GenBank accession number . The position of mitogenome haplotypes from U. t. laniger generated in this study is shown in bold face.The numbers at the nodes of the branches indicate bootstrap supporting values in percentage (BP) and Bayesian posterior probabilities (BPP) based on maximum likelihood and Bayesian analyses, respectively. The mtDNA sequence of (DOCX)Click here for additional data file.S3 FigThe numbers denoted at the node are the bootstrap values based on Neighbor joining/Maximum parsimony methods, respectively. Only the values greater than 50% are shown. Sequences are identified by the subspecies name, origin and country name, followed by the GenBank accession number . The mitogenome generated in this study is marked in bold face.(DOCX)Click here for additional data file.


Rst values between most of pairwise locations  and 86% of individuals were assigned to their sampled colony, suggesting philopatry. STRUCTURE detected three main genetic clusters according to geographical locations: i) Peru; ii) North of Chile; and iii) Central-South of Chile. The Humboldt penguin shows signal population expansion after the Last Glacial Maximum (LGM), suggesting that the genetic structure of the species is a result of population dynamics and foraging colder water upwelling that favor gene flow and phylopatric rate. Our findings thus highlight that variable markers and wide sampling along the species distribution are crucial to better understand genetic population structure in animals with high dispersal ability.The upwelling hypothesis has been proposed to explain reduced or lack of population structure in seabird species specialized in food resources available at cold-water upwellings. However, population genetic structure may be challenging to detect in species with large population sizes, since variation in allele frequencies are more robust under genetic drift. High gene flow among populations, that can be constant or pulses of migration in a short period, may also decrease power of algorithms to detect genetic structure. Penguin species usually have large population sizes, high migratory ability but philopatric behavior, and recent investigations debate the existence of subtle population structure for some species not detected before. Previous study on Humboldt penguins found lack of population genetic structure for colonies of Punta San Juan and from South Chile. Here, we used mtDNA and nuclear markers (10 microsatellites and RAG1 intron) to evaluate population structure for 11 main breeding colonies of Humboldt penguins, covering the whole spatial distribution of this species. Although mtDNA failed to detect population structure, microsatellite loci and nuclear intron detected population structure along its latitudinal distribution. Microsatellite showed significant  Larus dominicanus [Spheniscus magellanicus [Sterna hirundinacea [Pelecanus thagus [Aptenodytes forsteri, [Pygoscelis adelia [P. antarticus Chinstrap penguin [In species with high dispersal ability and no geographical barriers in their distribution, it is expected found low genetic population structure. For instance, weak or no population genetic structure has been frequently recorded for seabird species along the Atlantic coast of South America , along s thagus ), and arorsteri, , 7; Adéls adelia ; P. anta penguin ). Theref penguin ,11, the  penguin , and/or  penguin .The upwelling hypothesis has been proposed to explain reduced or lack of population genetic structure in seabird species specialized in food resources available at cold-water upwellings, which are regularly influenced by largescale climatic events . For insAnother hypothesis to explain reduced population genetic structure is the effect of Pleistocene glaciations, which is frequently proposed for seabirds from South America  and fromGene flow among populations derives from contemporary and historical factors. However, detecting population genetic structure in species with large effective population size is a challenge, since variation in allele frequencies is masked by genetic drift that is inversely proportional to population size . There iSpheniscus humboldti) is an HCS specialist, widely distributed along the Pacific coast of South America, from La Foca Island  in Peru to Metalqui Island  in Chile [ca. 32,000 to 36,982 breeding adults, and the Humboldt Penguin is listed as Vulnerable by International Union for Conservation of Nature (IUCN) due to population size reductions attributed to exploitation or habitat alteration, as well as the effect of ENSO events [Penguins are monogamous seabirds, with intense biparental care, philopatric behavior, high capacity of dispersion, and specialist diet . The Humin Chile . There ain Chile . On the in Chile . The curO events , 39.Migration rates among colonies are not well known, however there is evidence of individuals from Pan de Azucar colony migrating over 600 km, and birds from Puñihuil were found over 1,000 km northwards from their original colonies , 41. In The present study aims to evaluate population genetic structure of the Humboldt penguin, testing upwelling and glaciation hypotheses to explain lack or reduced population structure as previously proposed for this species, and to investigate the potential contribution of choice of molecular markers for population genetic structure of the species along the HCS. To achieve these goals, we (1) characterize the genetic diversity and geographical structure across the entire species range, (2) determined the effects of historical climate changes over the species demography, and (3) evaluated if there is sex-biased philopatry and dispersal, bringing light to the questions about low structure recorded on several seabird´ species.This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Animals at research of the National Council of Animal Experiments from Brazil and Bioethics Guideline from CONICYT  del Chile. The protocol was approved by the Committee on the Ethics of Animal Experiments of the Pontificia Universidade Catolica from Minas Gerais (Protocol Number: 27–2016) and by the Committee on the Ethics of Animal Experiments of the Pontificia Universidad Catolica del Chile. Samples were obtained under Subpesca—Corporación Nacional Forestal del Chile (CONAF), Direccíon General Florestal y de Fauna Silvestre (DGFFS) of the Peruvian Nation Protected Areas Agency (SERNANP 001088) and .Blood samples for genetic analysis were collected during penguin breeding seasons between 2005 and 2013. We collected a total of 487 samples from adult Humboldt penguins from 11 breeding colonies distributed along its entire distribution range in Peru and Chile . Penguin2 and P8 [Taq buffer, 200 μM of each dNTP, 3.5 mM MgCl2, 0.5 μM of each primer, and 0.5 U of Taq DNA polymerase. Amplifications were performed with an initial step at 94°C for 4 min, 53–55°C for 30 s, and 1 min at 72°C, followed by 40 cycles of 30 s at 92°C, 50°C for 30 s, and 45 s at 72°C, followed by a final extension of 7 min at 72°C. The PCR amplifies regions of the CHD1 gene found on the sex chromosomes [Sex was determined by Polymerase chain reaction (PCR), using primer pairs P2 and P8 , prepareomosomes . Gender Spheniscus [Taq buffer, 200 μM of each dNTP, 0.5 μM of each primer, and 0.5 U of Taq DNA polymerase. Amplifications were performed with an initial step at 95°C for 4 min and 37 cycles of 30 s at 94°C, 30 s at annealing temperature according to each locus  considering a Euclidean distance.Possible correlations between the indices of genetic differentiation and geographic distances between all pairs of colonies were tested using the Mantel test, which was performed with Mantel Non-parametric Test Calculator v.2.0  using 10K-means and model selection to identify genetic cluster [Bayesian clustering analyses was performed to estimate the optimal number of genetic clusters (K) using STRUCTURE v2.3.3 . To test cluster . For thi cluster  was usedAssignment of each individual to their reference putative population was evaluated for microsatellite data using GeneClass , employiDeviations from mutation/drift equilibrium were tested with the program BOTTLENECK , 61. ThrTaq buffer, 200 μM of each dNTP, 1.0 μM of each primer, and 0.5 U of Taq polymerase. Amplifications were performed with an initial step at 94°C for 2 min and 35 cycles of 30 s at 94°C, 40 s at 62°C and 90 s at 72°C, followed by final extension of 10 min at 72°C. PCR products were cleaned by precipitation using 20% Polyethylene Glycol with 2.5M NaCl. Sequences were obtained on an ABI 3500.The mtDNA Control region was amplified with primers D-loop C and D . The PCRRAG-1 (Recombination activating gene 1) was amplified with primers RAG17 and RAG22 . The PCRwww.technelysium.com.au). The alignments were adjusted by manually in Bioedit v.5.06 [Sequences were visualized using ChromasLite 2.1 (t v.5.06 . A Bayest v.5.06  was usedt v.5.06 .www.fluxus-technology.com) with median joining method [Descriptive analyses, including haplotype diversity (h), nucleotide diversity (π), and theta (θ), were done in DNAsp v.5.10.01 . We usedg method  to draw g method  and Fu’sg method  statistig method . We seleg method .−3 substitution/site/myrs to RAG1 [http://beast.bio.ed.ac.uk/Tracer) [We used AIC as implemented in the software JModeltest , to sele to RAG1 . To eval/Tracer) . To chec/Tracer) .The Humboldt penguin showed high genetic diversity for all markers in all colonies. For microsatellites, the number of alleles found in each locus ranged from eight (locus Sh2Ca58) to 23 (both Sh2Ca40), averaging 15.89 over all loci . Privateo = 0.66) and the maximum from Tilgo (Ho = 0.76).The analyses performed by Microchecker showed evidence for null alleles at locus M1-11 in seven breeding colonies  and out of Hardy-Weinberg Equilibrium (HWE), thus it was excluded from population analysis. Loci Sh2Ca58, Sh2Ca12 and Sh2Ca9 were also excluded from population analysis due genotype proportions deviating from H-W expectations . Thus, td = 0.906) and high nucleotide diversity (π = 0.008). A RAG1 fragment of 876 bp from 54 individuals showed 23 haplotypes, also high haplotype diversity (Hd = 0.876) and nucleotide diversity (π = 0.002). These patterns of high genetic diversity were also observed in all colonies analyzed , compared to 98.36% within and only 1.64% among populations for mtDNA (p = 0.10), and 78.51% within and 21.49% among populations for RAG1 (p < 0.001).K = 2, being one included Pan de Azucar and Isla Grande de Atacama and another included all remaining locations, despite into second group Punta San Juan was slight differentiation  of Humboldt penguins: 1) Punta San Juan, Peru, 2) Pan de Azucar and Isla Grande de Atacama and 3) the remaining locations . Despitentiation . No isolST values for microsatellite were observed between the majority of pairwise locations, mainly between the groups detected by STRUCTURE, with significant RST values ranging between Punta San Juan and the remaining locations of 0.011 to 0.088, or among Pan de Azucar and Isla Grande and remaining locations of 0.001 to 0.158; and within the third group higher values were found between Algarrobo and the remaining locations (0.059 to 0.158), except Pupuya and Chiloé  and Pan de Azucar  only with D-loop region (Signatures of bottlenecks were detected at Pupuya (IAM p = 0.01), Pajaros , Choros , Chañaral , Pan de Azucar , and Punta San Juan  . Furtherp region . Corrobop region . Skylinep region .Our study reveals that the Humboldt penguin exhibits a clear population genetic structure along the Pacific coast of the South America, as observed in other previous studies on Humboldt penguins . HoweverLontra feline) exhibit higher genetic differentiation from populations from Peru compared to those distributed along Chile [Engraulis ringens), the Araucanian herring (Strangomera bentincki), the Silverside (Odontesthes regia), the Common hake (Merluccius gayi), the Inca scad (Trachurus murphyi), the Garfish (Scomberesox saurus scombroides), and the South American pilchard (Sardinops sagax) [Although some endemic seabirds from the Humboldt Current show weak population genetic structure, such as Peruvian pelicans ; Peruviang Chile . Despiteng Chile : these ang Chile . Thus, Hng Chile  to suppls sagax) . Therefos sagax) , reducinThe population genetic structure can be explained by the species philopatric behavior that reduces gene flow. Philopatry was confirmed by assignment test based on microsatellites for all colonies of Humboldt penguins, showing individuals assignment the population origin above 86% . EcologiPygoscelis papua) maintained large effective population sizes in Antarctica and the Scotia Arc followed by an expansion [The evolutionary history, such as isolation, expansion or retraction of populations, affects the population genetic structure and the genetic diversity of a species. In the present study in the Humboldt penguin, the D-loop and RAG1 analyses showed a stability and recent coalescence . Thus, it is possible that, during the glaciation when Pacific coast experienced a change in its productivity, leading to an intense reduction of the global population of the Humboldt penguin, followed by an expansion of the population after the LGM. However, the population expansion was observed only in neutrality tests to D-loop region and in network , Fig 4. xpansion , 84, 85,xpansion , 87. Thexpansion .Penguin species have demonstrated, in general, high genetic diversity, as detected here for the Humboldt penguin, and recorded for the Magellanic penguin , 88, theOur study shows that the population structure in the Humboldt penguin can be better investigated and understood by increasing the number of markers and the sampling effort to cover the whole species’ distribution. Low sampling may not reflect real allele frequencies of the global population, showing a simplification of the genetic structure. This study of the Humboldt penguins’ population genetic structure revealed three major regions: 1) Punta San Juan in Peru, with clear genetic differences from the Chilean colonies, 2) Pan de Azucar and Isla Grande de Atacama in the North of Chile, which need a special attention as the most genetically differentiated colonies and 3) the breeding colonies from the Central-South of Chile.Based on our results, following recommendations arise in relation to conservation initiatives. It is important to expand population genetic studies to cover other breeding colonies in Peru, to better understand the relationship between the population of Punta San Juan and the other two genetic groups detected in Chile. Chañaral and Choros are part of the Humboldt Penguin National Reserve, but the other islands (Tilgo and Pajaros)- should also be considered into this system to maintain genetic diversity and a more integral form of population management.Rattus rattus and R. norvegicus, and feral dogs) that predate on unattended eggs and chicks [The Humboldt Penguin suffers from the impacts of several factors, such as the interaction with industrial fisheries , the pressure from alien species Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableSignificant values (P<0.05) are in bold. Population reference: CHI (Chiloé), PUP (Pupuya), ALG (Algarrobo), CAC (Cachagua), TIL (Tilgo), PAJ (Pajaros), CHO (Choros), CHA , GRA (Isla Grande), AZU (Pan de Azucar), PSJ (Punta San Juan).(DOCX)Click here for additional data file.S4 TableSignificant values (P<0.05) are in bold. Population reference: CHI (Chiloé), PUP (Pupuya), ALG (Algarrobo), CAC (Cachagua), TIL (Tilgo), PAJ (Pajaros), CHO (Choros), CHA , GRA (Isla Grande), AZU (Pan de Azucar), PSJ (Punta San Juan).(DOCX)Click here for additional data file.S5 TablePopulation reference: CHI (Chiloé), PUP (Pupuya), ALG (Algarrobo), CAC (Cachagua), TIL (Tilgo), PAJ (Pajaros), CHO (Choros), CHA , GRA (Isla Grande), AZU (Pan de Azucar), PSJ (Punta San Juan).(DOCX)Click here for additional data file.S6 TableCAC (Cachagua), TIL (Tilgo), PAJ (Pajaros), CHO (Choros), CHA , GRA (Isla Grande), AZU (Pan de Azucar), PSJ (Punta San Juan).(DOCX)Click here for additional data file.S7 TablePopulation reference: CHI (Chiloé), PUP (Pupuya), ALG (Algarrobo), CAC (Cachagua), TIL (Tilgo), PAJ (Pajaros), CHO (Choros), CHA , GRA (Isla Grande), AZU (Pan de Azucar), PSJ (Punta San Juan).(DOCX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.S1 FigPopulation reference: CHI (Chiloé), PUP (Pupuya), ALG (Algarrobo), CAC (Cachagua), TIL (Tilgo), PAJ (Pajaros), CHO (Choros), CHA , GRA (Isla Grande), AZU (Pan de Azucar), PSJ (Punta San Juan).(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S4 Fig(DOCX)Click here for additional data file.S1 Dataset(TXT)Click here for additional data file.


The pneumococcal enzyme-linked immunosorbent assay (ELISA) measures IgG antibodies in human serum, and it is an important assay that supports licensure of pneumococcal vaccines. The immune correlate of protection, 0.35 µg/ml of IgG antibodies, was determined by the ELISA method. Pfizer has developed a new Luminex-based assay platform to replace the ELISA. These papers describe the important work of (i) validating the Luminex-based assay and (ii) bridging the immune correlate of protection (0.35 µg/ml IgG) to equivalent values reported by the Luminex platform. This article describes the results of a study designed to bridge the World Health Organization (WHO) pneumococcal enzyme-linked immunosorbent assay (ELISA) platform to the validated Luminex-based 13-plex direct immunoassay (dLIA) platform developed by Pfizer, Inc. Both assay platforms quantify serotype-specific serum IgG antibodies (in micrograms per milliliter) against an international reference standard serum. The primary goal of this study was to determine if the dLIA is a suitable replacement for the ELISA to support clinical vaccine studies that include the evaluation of immune responses to serotypes 1, 3, 4, 5, 6A, 6B, 7F, 9V, 14, 18C, 19A, 19F, and 23F. Serum samples were selected from four pivotal 13-valent pneumococcal conjugate vaccine  clinical trials on the basis of their serotype-specific IgG concentrations by ELISA. In these studies, subjects were immunized either with 13vPnC or with 7-valent pneumococcal conjugate vaccine . There were 1,528 of 1,574 selected samples with sufficient remaining volume for reanalysis in the dLIA. A comparison of assay results from the dLIA and ELISA platforms showed clear and robust linear quantitative relationships across all 13 serotypes. In addition, lower IgG antibody concentrations in preimmunization samples were measured in the dLIA, thus allowing better differentiation between preimmunization and low-titer postimmunization samples. Overall, the results showed that the established population-level protective threshold IgG concentration, 0.35 µg/ml of serotype-specific serum IgG antibodies, is appropriate for use for data generated using the dLIA platform developed by Pfizer, Inc., for 10 serotypes: serotypes 1, 3, 4, 6A, 7F, 9V, 14, 18C, 19F, and 23F. On the basis of the extensive bridging analyses, however, the use of dLIA cutoff values of 0.23, 0.10, and 0.12 µg/ml is recommended for serotypes 5, 6B, and 19A, respectively. This adjustment will ensure that the consistency of the established population-level protective threshold IgG concentration is maintained when switching from the ELISA to the dLIA platform. The results of this bridging study demonstrate that the 13-plex dLIA platform is a suitable replacement for the WHO reference ELISA platform.IMPORTANCE The pneumococcal enzyme-linked immunosorbent assay (ELISA) measures IgG antibodies in human serum, and it is an important assay that supports licensure of pneumococcal vaccines. The immune correlate of protection, 0.35 µg/ml of IgG antibodies, was determined by the ELISA method. Pfizer has developed a new Luminex-based assay platform to replace the ELISA. These papers describe the important work of (i) validating the Luminex-based assay and (ii) bridging the immune correlate of protection (0.35 µg/ml IgG) to equivalent values reported by the Luminex platform. Over the past 20 years, the pneumococcal capsular polysaccharide (PnPS) enzyme-linked immunosorbent assay (ELISA) platform has been used to measure levels of serotype-specific serum IgG antibodies to evaluate both established and experimental pneumococcal conjugate vaccine (PCV) formulations. PnPS-specific serum antibodies offer protection against invasive pneumococcal disease (IPD), and in 2003, ELISA data sets from three pivotal efficacy studies in infants were used to establish a population-level protective serum IgG threshold concentration of 0.35 µg/ml –4. Vacci–5–The World Health Organization (WHO) Expert Committee on Biological Standardization endorsed this threshold IgG concentration for infant studies in a comprehensive guidance document for PCV manufacturers –9. Howev–12–An examination of the percentage of vaccine responders reaching IgG concentrations of ≥0.35 µg/ml is historically based on the WHO reference ELISA platform, and the WHO Expert Committee has provided guidance on acceptable bridging strategies for manufacturers that use an alternative assay platform for clinical evaluations . Accordil-lysine (PLL)-conjugated PnPS to fluorescent Luminex microspheres. Each PnPS-PLL conjugate is coupled to spectrally distinct microspheres, which are pooled for the multiplex assay procedure. The targeted coupling of PnPS-PLL-conjugated antigens to microspheres reduces the presence of CWPS on the solid support, which improves the overall specificity of the assay. Furthermore, the dLIA platform uses less serum than the ELISA, which is important for infant studies, where serum volumes are limited.Pfizer has developed a Luminex-based direct immunoassay (dLIA) platform to replace the WHO reference ELISA platform. The dLIA platform has been validated for the 13 PnPS serotypes found in 13vPnC. Both platforms quantify serotype-specific serum IgG antibodies against an international reference standard with known IgG concentrations . HoweverThis bridging study was designed to evaluate the performance of the multiplex dLIA platform and compare it to the performance of the WHO reference ELISA. Furthermore, the study was performed to provide the data to support the use of the dLIA platform as a suitable replacement for the ELISA to support clinical PCV studies. Serum samples were chosen from four pivotal 13vPnC clinical trials in the United States, Germany, and Japan in which subjects received the 7vPnC vaccine or the 13vPnC vaccine , 15, 19.The quantitative relationships between the WHO reference ELISA platform and the multiplex dLIA platform were evaluated by Deming regression of log-transformed IgG values for each serotype. In a limited number of cases, there was insufficient residual serum volume to generate a full set of 13 dLIA results. In those cases, the ELISA result did not have a paired dLIA result and was not used in the regression analysis. The total proportion of missing data was less than 1.31% for all serotypes. Data-derived dLIA threshold values corresponding to the WHO ELISA 0.35 µg/ml benchmark were computed for each serotype from the corresponding linear model. The CI values for the slopes of the Deming regression curves were generally within 2% to 4% of the corresponding slope estimates for serotypes 1, 4, 6A, 6B, 7F, 9V, 14, 18C, 19A, 19F, and 23F, which indicates a strong linear relationship between the ELISA and dLIA IgG results. The CI of the slope for serotype 3 was within 5% of the estimated slope for the primary data set and was within 6.5% for the secondary data set. For serotype 5, the CI of the slope was within 4% of the estimated slope for the primary data set and within 6% for the secondary data set. Note that the CI based on the secondary data set is wider than that based on the primary data set because the primary data set has a larger sample size as well as a larger spread of data.y axis versus the ELISA results on the x axis based on the primary and secondary data sets, respectively. The dashed reference line represents the y = x concordance line corresponding to a theoretical perfect match between the two assay platforms. The solid line represents the fitted Deming regression curve based on the primary data set. The vertical line ascending from the x axis to the fitted regression curve represents 0.35 µg/ml on the x axis (ELISA), and the horizontal line extending from this point on the fitted regression curve to the y axis represents the corresponding IgG concentration on the y axis (dLIA). For example, a value of 0.35 µg/ml on the x axis (ELISA) corresponds to a value of 0.29 µg/ml on the y axis (dLIA) for serotype 1 on the primary data set , was selected for this analysis since it included serum samples collected prior to the first immunization . Serum pBoth assay platforms showed a separation between the immunized and unimmunized populations, as expected. However, the results show a further separation between the dLIA and ELISA platforms for the unimmunized population, and this observation is consistent for all 13 serotypes and both arms of the study. The RCDC plots of the dLIA results are shifted to the left of the RCDC plots derived from the ELISA platform for the preimmunization population, which indicates that the dLIA platform measures lower levels of serum IgG antibodies in the unimmunized subjects. These results suggest that the dLIA platform is more specific than the ELISA and is therefore better able to differentiate the immunized and unimmunized populations.P values were combined for each serotype using Fisher’s method for combining P values , 6B (0.10 µg/ml), and 19A (0.12 µg/ml) in order to maintain the proportion of vaccine responders observed by ELISA. The 0.35 µg/ml benchmark is an appropriate dLIA cutoff value for serotype 6A despite the moderate location shift of the Deming regression line relative to the scale. This result is largely due to the fact that the regression curve crosses the theoretical Advances in the newer immunoassay methodologies have led to improvements in assay sensitivity and specificity and dynamic range, as well as to changes in IgG measurements compared to the older ELISA platform. A careful assessment of the dLIA platform developed by Pfizer, Inc., against the WHO ELISA using clinical samples from completed clinical vaccine studies has led to the selection of well-justified dLIA threshold values that preserve the percentage of vaccine responders observed in historical 13vPnC clinical trials. Our data support 0.35 µg/ml as the cutoff value for the dLIA platform developed by Pfizer, Inc., for serotypes 1, 3, 4, 7F, 9V, 14, 18C, 19F, and 23F. Lower threshold values should be used for serotypes 5 (0.23 µg/ml), 6B (0.10 µg/ml), and 19A (0.12 µg/ml) in order to maintain the proportion of vaccine responders that were observed by ELISA in completed clinical studies. This report provides well-justified threshold IgG concentrations for the dLIA platform developed by Pfizer, Inc., that correspond to the 0.35 µg/ml benchmark of the WHO reference ELISA platform.A total of 1,574 archived serum samples were selected from 13vPnC and 7vPnC clinical trials conducted in infants and toddlers for reanalysis by the dLIA method based on the remaining sample volume and the serotype-specific IgG concentration by the WHO reference ELISA. Serum samples from four completed trials from the United States, Germany, and Japan were included , 15, 19.The WHO reference ELISA was performed as described previously using the international reference standard serum, 89SF, to calculate all ELISA results , 24, whiThe dLIA procedure was performed as described elsewhere in this issue  using thThe primary goal of this study was to determine if the dLIA platform is a suitable replacement for the WHO reference ELISA. There were three main objectives. The first objective was to evaluate the linear relationship between the IgG antibody concentrations measured by the ELISA and dLIA. The second objective was to assess the performance of the multiplex dLIA platform in differentiation of pre- and postimmunization populations. The third objective was to provide a well-justified IgG concentration for each serotype assessed by the dLIA platform that corresponds to the 0.35 µg/ml efficacy threshold concentration established through the WHO ELISA.The primary endpoint for this bridging study was to derive serotype-specific serum IgG antibody concentrations, as determined by ELISA and multiplex dLIA platforms. The assay results were subjected to log transformation for analysis. All references to log transformation in this report correspond to the common logarithm with base 10. Statistical analyses were performed using SAS proprietary software version 9.2 (TS2M3).A linear relationship was expected between the two platforms for postimmunization samples, since the two are similar in their underlying approaches. The methodology described by Tan and Iglewicz, also known as errors-in-variables regression or Deming regression, constitutes the basis for this analysis , 25. ThiThe alternative efficacy threshold IgG concentrations for the dLIA were evaluated against the 0.35 µg/ml benchmark by calculating the proportion of vaccine responders in each study population according to serotype and threshold value. To compare the proportions of responders, two-by-two tables were produced for each of 14 serum panels, namely, A1, A2, A3, A4, B1, B2, B3, B4, C1, C2, C3, C4, D2, and D4 see  for the These serum panels are representative of their corresponding underlying immunized populations at two key time points: 1 month after the infant immunization series (visit 4) and 1 month after the toddler dose . A two-by-two table was produced for each potential dLIA cutoff value and for each serotype and each serum panel.P value was used as an indicator of how well the proportion of responders by dLIA matched the proportion of responders by ELISA (MQ = (n12 − n21)2/(n12 + n21), where n12 and n21 were the counts of two mismatched cells  in the two-by-two table. When both n12 and n21 are zero, McNemar’s test is not well defined. However, for our purpose, this scenario implies a perfect match between the ELISA and dLIA platforms. We use definitions of MQ = 0 and exact P value = 1 for such cases.For each two-by-two table, McNemar’s test was performed and its exact by ELISA . The McNP values of the McNemar’s test for each alternative threshold value (P value corresponding to the 0.35-µg/ml cutoff value is 0.25 or greater, it would indicate that the 0.35-µg/ml cutoff value should be maintained for the dLIA platform. However, if the combined P value corresponding to the established 0.35 µg/ml benchmark is ~0.05 or smaller but the combined P value corresponding to the data-derived cutoff value is ≥0.25, it would indicate that the data-derived cutoff value is better justified.Fisher’s method was used to combine the 7 or 14 exact ld value . For eac


The study aim was to determine whether the range and distribution of all, and proportions of specific, land covers/uses within European cities are associated with city-specific mortality rates.233 European cities within 24 countries.Aggregated city-level all-cause and age-group standardised mortality ratio for males and females separately and Western or Eastern European Region.The proportion of specific land covers/uses within a city was related to mortality, displaying differences by macroregion and sex. The land covers/uses associated with lower standardised mortality ratio (SMR) for both Western and Eastern European cities were those characterised by ‘natural’ green space, such as forests and semi-natural areas . Dense housing was related to a higher SMR, most prominently in Western European cities .There is pressure to build on urban natural spaces, both for economic gain and because compact cities are regarded as more sustainable, yet here we offer evidence that doing so may detract from residents’ health. Our study suggests that urban planners and developers need to regard retaining more wild and unstructured green space as important for healthy city systems. This was a large international study of 233 cities within 24 countries.We used high-quality, internationally comparable land cover/use data from the European Urban Atlas.We were able to examine the impact of land covers/uses both collectively (via landscape metrics) and individually.Previously validated city-level standardised mortality ratio (SMR) data were spatially joined with contemporaneous land cover/use data.Although associations between land covers/uses and SMRs were described, we have no information on how the individuals used or were exposed to the land covers/uses.In 2014, 54% of the world’s population lived in urban environments; this is set to rise to 66% by 2050.The physical extent, design and composition of cities are important components of the urban system and are associated with the health and well-being of residents.This study is about ‘what is on the ground’ in a city, which we refer to as land cover/uses. Land cover refers to what the surface actually is, for example, forests, concrete or water. Land uses are the purposes for which humans use the land, such as airports or roads. Urban land cover/use can influence health via multiple mechanisms including the promotion or inhibiting of healthy behaviours,Evidence suggests that land cover/use exerts an independent influence on residents, over and above residents’ own characteristics. For example, the density of settlement and transport networks have been associated with variation in mortality risk across a number of English cities.The study aim was to determine whether the range and distribution of all, and proportions of specific, land covers/uses within European cities is associated with the city-specific mortality rate. Previous research found that a city’s wider macroregion  was an important determinant of mortality rate, and moderator of association between environment and health,Is the range and distribution of land covers/uses within a city associated with city-level mortality rates?Which, if any, specific land covers/uses are associated with city-level mortality rates?How do these between associations vary with sex and by macroregion?2 resolution.The 2006 Urban Atlas provided pan-European comparable land cover/use data collected and digitised from satellite data for urban areas.10.1136/bmjopen-2019-033623.supp1Supplementary data2) for each land cover/use by city, using an extension for ArcMap GIS called Patch Analyst.We calculated the total area  for males and females separately, calculated for 233 European cities by Richardson et al,The SMR, land cover/use and GDP data were matched at city level. The final dataset included 233 cities (within 24 countries). The cities were allocated to either Western or Eastern-Central bloc macroregion, following Richardson No patients were involved in the development of the research question, design and implementation of the study or interpretation of the results.First, linear regression models assessed associations between the landscape metrics and city SMR data, adjusting for city GDP. Next, models for specific land covers/uses were built. Preliminary analyses suggested that associations between the specific land cover/use measures and SMR were not linear, so the former were categorised. To do this, the proportion of the total area covered by each land measure was calculated within each city, and then classified into quintiles. This process was carried out separately for each macroregion. We categorised the data into quintiles rather than apply polynomial terms in order to aid interpretation and therefore help guide policymakers.all land covers/uses, together with Wald statistics. Third, we graph marginal means from the adjusted regression models for associations identified in universal or partially universal  was associated with lower SMRs for males, but in Eastern cities this protective association was present for females only  was associated with higher SMRs in the Eastern cities, with the greatest adverse association quintiles 4 and 5. Western European cities with higher proportions of land classified as residential and discontinuous low-density urban fabric had higher SMRs, particularly for cities in quintile 5  showed some association with lower SMR, while SMRs were higher for Western European cities with a greater residential proportion and low-density discontinuous cover . Specifically, our most consistent finding was that presence of more ‘relatively wild’ green spaces, such as agricultural, semi-natural areas and wetlands and forests was associated with lower SMRs, an association observed across sexes and macroregions and relatively strongly. The health benefits of contact with nature are very well established from both experimental and observational studies.green urban areas, the proportion of which was relatively consistently associated with higher mortality. At first, this seems like a directly contradictory finding, but it is important to be clear what kinds of spaces are classified as ‘green urban areas’ in the Urban Atlas. Large urban parks are not classified solely as ‘green urban areas’ and will be separated into their designated components, for example, if a park contains a botanical garden, zoo or national trust gardens, these areas will be classified as an industrial or commercial areas; blue spaces within parks will be defined as waters; any space which can be used for sport or containing sport facilities  will be defined as sports or leisure facilities. In this land use classification, ‘green urban areas’ are relatively small and manicured ‘in-fill’ green spaces within residential and commercial developments. Their association with greater mortality is not unprecedented in the literature. Previous work found that the total amount of green space within American cities was associated with higher mortality rates, suggesting that the indicator was capturing sprawling cities, however this study was unable to distinguish between the green space type.green urban areas’ in European cities were associated with reduced reported life satisfaction for its city residents.Overall, we observed that higher proportions of natural spaces and less dense or non-residential land cover/use was associated with lower mortality. For example, greater proportions of lower density settlement . Residential settlements with ‘green views’ command a premium price. Furthermore, a central message of contemporary urban planning is that dense and/or compact cities are ‘sustainable’. Yet, the literature already hints that compact cities characterised by high-density residential areas have both benefits and disadvantages for their residents. The environmental benefits, owing to the reduced carbon emissions required in intraurban transport and service, have been well described,This was a large international study of 233 cities within 24 countries. We were able to use high-quality, internationally comparable land cover/use data from the European Urban Atlas for each city to assess the configuration and quantity of these within each city. By including a large number of cities and countries with differing economic position, we believe our results can be generalised to similar cities globally. We were able to dissect the impact of land covers/uses both collectively (via landscape metrics) and individually. We surpass some previous research by including a very large range of land covers/uses, rather than studying the impact of just one or two.Although we described associations between land covers/uses and SMRs, we have no information on how the individuals used or were exposed to the land covers/uses that we included in our analysis, for example, if they live in a part of the city without that particular land use, and were unable to distinguish between land covers and land uses. This may be most pertinent for the most socioeconomically deprived individuals who may have a smaller activity space and therefore the affordances of the city-wide environment on their mortality may be limited. Data were aggregated to the city level and therefore may be subjected to both the ecological fallacy and modifiable areal unit problem. The development of the sample cities may also have changed considerably during individuals’ life courses and the individual may not have always resided in that city, thus impacting on SMRs. As this was an ecological study and only measured land cover/use at one point in time and therefore unable to determine causality. We explored the possible effects of cultural and economic differences in land covers/uses by analysing our cities by macroregion, however we did not explore the different cultural meanings for each city to be able to ascertain if culturally affirming landscapes were health beneficial. The mortality indicator we used for the study was a city-level population-level measure and therefore we were unable to explore inequality in mortality by socioeconomic status.We found that the proportion of specific land covers/uses within cities is associated with mortality rates there, but that these associations varied by macroregion and by sex. There is great pressure to build on wild green space for economic gain and sustainability, and to promote compact cities as sustainable. Our study suggests that urban planners and developers need to regard retaining more wild and unstructured green space as important for healthy city systems, and that they should reconsider the push for dense and compact cities.


Choristoneura fumiferana), in Quebec (Canada). AMOVA, cluster analysis, isolation by distance, and sPCA were used to characterize spatio‐temporal genomic variation using 1,370 SBW larvae sampled over four years (2012–2015) and genotyped at 3,562 SNP loci. We found evidence of overall weak spatial genetic structure that decreased from 2012 to 2015 and a genetic diversity homogenization among the sites. We also found genetic evidence of a long‐distance dispersal event over >140 km. These results indicate that dispersal is the key mechanism involved in driving population synchrony of the outbreak. Early intervention management strategies that aim to control source populations have the potential to be effective through limiting dispersal. However, the timing of such interventions relative to outbreak progression is likely to influence their probability of success.Spatial synchrony is a common characteristic of spatio‐temporal population dynamics across many taxa. While it is known that both dispersal and spatially autocorrelated environmental variation  can synchronize populations, the relative contributions of each, and how they interact, are generally unknown. Distinguishing these mechanisms and their effects on synchrony can help us to better understand spatial population dynamics, design conservation and management strategies, and predict climate change impacts. Population genetic data can be used to tease apart these two processes as the spatio‐temporal genetic patterns they create are expected to be different. A challenge, however, is that genetic data are often collected at a single point in time, which may introduce context‐specific bias. Spatio‐temporal sampling strategies can be used to reduce bias and to improve our characterization of the drivers of spatial synchrony. Using spatio‐temporal analyses of genotypic data, our objective was to identify the relative support for these two mechanisms to the spatial synchrony in population dynamics of the irruptive forest insect pest, the spruce budworm ( Distinguishing between these two processes can help us to better understand the spatial dynamics of population irruptions and is needed to develop effective early intervention strategies to mitigate the negative effects of pest outbreaks.Spatio‐temporal analysis of geo‐referenced molecular markers offers a powerful tool to assess the relative weight of the two processes and to infer population dynamics over extensive geographic and temporal scales. This objective is nonetheless challenging because both the epicenter process and the Moran effect can lead to similar spatial genetic patterns when an outbreak is at or near its peak. Given the temporal contingency of outbreaks and the genetic patterns within and among populations, spatio‐temporal approaches to analyzing spatial genetic structure are required to assess the relative strength of these two processes in driving spatial synchrony. Here, we illustrate the hypothesized development of synchronous spatial genetic structure under these two processes.The upper panel illustrates the development genetic structure under the epicenter hypothesis, and the lower panel illustrates the development genetic structure under the Moran effect, in a chronological order from the initiation of the outbreak to the peak phase (from left to right). Panel a1 (“epicenter”) shows three distinct populations, one of which is increasing in population density and spatial extent. The other two populations remain at a low density. In this case, we expect genetic structure to manifest as a gradient extending from the source population  and significant isolation by distance. This rapidly spreading epicenter population can then subsume the other sites, effectively swamping out their genetic variation (d1) and leading to eventual panmixia (panel e1).In contrast, panel a2 (“Moran effect”) shows three distinct populations that are each increasing in density and extent, presumably in response to regionally synchronous environmental conditions. Because each population's growth is independent and does not rely on dispersal from other populations, we expect the development of patchy genetic differentiation . Boundaries between populations become less clear as the outbreak progresses as a result of both the spatial expansion of the populations and dispersal among them (panel d2), leading to high levels of genetic admixture between populations (panel e2) and eventual panmixia. Genetic diversity at panmixia due to the Moran effect is (panel e2) expected to be higher than that due to the epicenter hypothesis (e1), due to the genetic contributions of multiple, versus a single, populations.Using this framework, collection and analysis of spatial genetic data from multiple years can be used to distinguish between the processes underlying outbreak synchrony. However, successful identification of the dominant process requires that sampling occurs early enough during the outbreak, before panmixia is reached. After panmixia is reached , the genetic legacy of the previous outbreak collapse may no longer be detectable. The specific rate at which these historical legacies in spatial genetic structure fade is likely a function of multiple demographic parameters such as effective population size, dispersal capacity, and genetic diversity within the population of interest. The precise roles of these factors remain to be further investigated.Choristoneura fumiferana Clemens) provides an excellent example of spatially synchronous population dynamics. The SBW is a univoltine native lepidopteran that periodically outbreaks (every ~35 years) and defoliates large areas (>106 ha) of balsam fir  Mill) and spruce (Picea spp.) forests in North America  during outbreaks  exposure to a common regional disturbance , 14 locations in 2013 (n = 420), 17 locations in 2014 (n = 260), and 10 locations in 2015 (n = 163). In 2012, sites were selected to cover all the outbreak patches. Not all sites were identical from one year to the next. Some sites were discarded due to low larvae density or trouble accessing the site, but close  replacement sites were selected when possible. When substitute sites were selected, we considered the original and the substitute site to be a single site through time  from all defoliated zones to ensure that all individuals were associated with their site and the possibility of migrants from outside the study area would not affect the results. Many sites were sampled successively in all years, whereas some were sampled for only a single year Figure . Larvae 2.2PstI‐MspI GBS libraries (96 plex) were prepared by the Institut de Biologie Intégrative et des Systèmes (IBIS) at Université Laval  using the protocol of Poland, Brown, Sorrells, and Jannink  <.4 were removed as advised by Browning and Browning  <5% were removed to exclude putative sequencing errors and keep only the most informative SNPs  and expected  heterozygosity, rarefied allelic richness , and total number of alleles  using the hierfstat R package  was computed within each year also using hierfstat.For each site and for each year, we calculated observed . We first created multiple principal components (PC) using a matrix of allele occurrence  using Jombart,  and thenJombart, .2.5adonis of the vegan package  and time (year of sampling) on patterns of genetic variation, we conducted a permutation‐based multivariate analysis of variance using the function As the number of sites and the number of individuals sampled per site varied among years, we performed a rarefied bootstrap to standardize for the minimum number of sites per year and the minimum number of individuals per site to ensure that there was no bias due to the unbalanced sampling. We subsampled the data keeping only 10 sites per year and 8 individuals per site and performed the AMOVA. We repeated this procedure 9,999 times.2.6adegenet  was used to identify the most probable number of clusters (K) present in the data. DAPC provides membership probabilities to these clusters for each individual, which we examined for geographic structure.If populations are not connected, their growth will be independent as it does not rely on dispersal from other populations. In this case, we expect individuals to cluster into genetic groups that correspond to geographic provenance. We searched for genetic groups using discriminant analysis of principal components (DAPC) implemented in the Jombart,  package Jombart, . For eac2.7mantel.randtest function of the ade4  of spatial autocorrelation  . These SNPs were identified using 1,228 individual larvae  that satisfied the missing genotype criterion . Most SNPs  had at least one missing genotype which was then imputed  were discarded when filtering for MAF and LD. Of the remaining SNPs, 4.1% (182) deviated from HWE in more than 15% of the sampling sites. About 16% (691) of the remaining SNPs were detected as potentially under selection and removed. In total 3,562 SNPs met our strict selection criteria and were retained for final analysis.Sequence processing through the fast‐GBS pipeline  was 0.172 (±0.013) and average expected heterozygosity (He) was 0.211 (±0.011), with a mean allelic richness per locus (Ar) of 1.738 (±0.033). The total number of alleles  was 6,774 (±274), and the inbreeding coefficient (Fis) was 0.166 (±0.028). He, Ho, Ar, n.all, and Fis varied through time  but significant (p < 10–3). The two clusters initially identified in 2012 were no longer present from 2013 to 2015; instead, K = 1 had the greatest support . However, the first positive eigenvalue, which represents global spatial genetic structure, decreased in magnitude from 2012 to 2015 compared to the other eigenvalues , we quantified temporal changes in spruce budworm spatial genetic structure and estimated gene flow through space and time. Our goal was to use spatial genetic information to better understand the relative importance of dispersal to spatial outbreak synchrony . Although He was spatially clustered in 2012, from 2013 to 2015 He became increasingly homogeneously distributed.The decline in the strength of spatial genetic structure from 2012 to 2015 Figure  and S4 a4.2Rapid change in SBW genetic composition on the south shore between 2012 and 2014 indicates long‐distance dispersal and successful establishment; that is, the eggs laid by dispersing females successfully hatched Figure . PreviouLong‐distance dispersal is common in Lepidoptera Showers,  and has 4.3The application of population genetic approaches to the study of cyclic species is challenging because of frequent deviations from theoretical predictions due to highly variable population dynamics and dependence on ecological context . Time‐structured data thus offer a new dimension of information that enables identification and better understanding of demographic changes. Such temporal analysis can also highlight the risks of failing to consider temporal variability when inferring population demographic parameters  on the basis of a static assessment of spatial genetic structure. Temporal investigations of the spatial genetic structure of cyclic and noncyclic species could be instructive in improving our understanding of how their dynamics are influenced by changes in functional connectivity, that is, by changes in their habitat conditions, an increasingly important issue given the fast environmental changes induced by global warming and the loss and fragmentation of habitat , which indicates that SBW moths can not only travel large distances (e.g., Greenbank et al., In Quebec, SBW populations are currently well connected and exhibit genetic panmixia. Such panmixia poses a challenge to forest managers seeking to contain the spread of SBW outbreaks from Quebec into other areas, such as Atlantic Canada. Early intervention strategies (Pureswaran et al., Our ability to distinguish between different drivers of outbreak synchrony will vary depending on the characteristics of the species being studied. For example, our approach may be sensitive to species‐specific factors such as effective population size, generation time, dispersal capacity, outbreak frequency, and landscape heterogeneity, as all of these factors influence the spatial distribution of genetic variation (Gauffre et al., None declared.  Click here for additional data file.


Animal models for neurodevelopmental disorders (NDD) generally rely on a single genetic mutation on a fixed genetic background. Recent human genetic studies however indicate that a clinical diagnosis with ASDAutism Spectrum Disorder (ASD) is almost always associated with multiple genetic fore- and background changes. The translational value of animal model studies would be greatly enhanced if genetic insults could be studied in a more quantitative framework across genetic backgrounds.We used the Collaborative Cross (CC), a novel mouse genetic reference population, to investigate the quantitative genetic architecture of mouse behavioral phenotypes commonly used in animal models for NDD.Classical tests of social recognition and grooming phenotypes appeared insufficient for quantitative studies due to genetic dilution and limited heritability. In contrast, digging, locomotor activity, and stereotyped exploratory patterns were characterized by continuous distribution across our CC sample and also mapped to quantitative trait loci containing genes associated with corresponding phenotypes in human populations.These findings show that the CC can move animal model studies beyond comparative single gene-single background designs, and point out which type of behavioral phenotypes are most suitable to quantify the effect of developmental etiologies across multiple genetic backgrounds.The online version of this article (10.1186/s13229-018-0252-2) contains supplementary material, which is available to authorized users. Recent studies show that genetic risk factors for neurodevelopmental disorders (NDD) such as autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) segregate in the general population. They influence continua of behavioral and developmental traits –4. TheseThis notion also has implications for animal studies into the biology of NDD. So far, animal models for NDD are generally designed to study the impact of a single genetic mutation in a fixed genetic background. Indeed, they have provided crucial insights into NDD biology and have transformed the landscape of treatment development . HoweverOver the past century, a great deal of methods and resources has been optimized to study the genetic basis of quantitative physiological and neurobehavioral traits in animal model populations –12. In aWe here tested the potential of the Collaborative Cross (CC), a mouse genetic reference population, and establish a quantitative framework to study the impact of etiological factors on neurobehavioral and ASD-like trait distributions. The CC is a panel of mouse recombinant inbred lines (RI lines) with a unique level of genetic diversity derived from five classical laboratory strains and three wild-derived mouse inbred lines Fig. a 25]. T. T25]. TWe investigated neurobehavioral phenotypes in 53 Collaborative Cross RI lines available at Tel Aviv University (TAU), Israel. The CC lines were initially bred at three different locations from eight common founder strains . These iGenome structures of CC lines were derived from SNPs array data from the Mouse Universal Genotyping Array   and MegaSocial interaction and short- and long-term memory in a social context were measured during the social discrimination task, as performed previously , 37. FirOn day 3 of the experiment, mouse behaviors including locomotor activity, exploratory patterns, digging, and grooming were assessed, while animals were exposed to four novel objects in a 26.5 × 17 × 11.4-cm arena with wood chip bedding. Digging and grooming behaviors were manually recorded using The Observer XT . Locomotor trajectories were recorded using an overhead camera connected to a PC with video tracking software  using LOWESS smoothing. These trajectories were then used to calculate the total distance moved and to investigate exploratory patterns. Stereotyped exploratory patterns were quantified as previously reported by Bonasera et al.  and as iK in which the phenotypic variance-covariance matrix V is modeled as I is the identity matrix and Narrow-sense heritability was calculated using kinship matrix K, based on reconstructed genomes . Narrow-sense heritability was estimated using a mixed model applied to the phenotype and kinship matrix 2) including epistatic but not dominant effects was estimated using the proportion of phenotypic variance explained by differences in CC lines in a one-way ANOVA . W. W27]. WWe first tested the influence of the genetic variation in these 53 CC lines on basic mouse behavioral traits and quantified digging and locomotor activity. The total population consisted of 285 male CC mice with 5–6 mice on average per CC line. We observed substantial continuous variation for these traits across the tested population Fig. a, top anTo compare these basic mouse behavioral traits with general physical traits, we quantified brain weight and body weight and observed strong variation across CC lines Figs. d, e. PaiNext, we analyzed behavioral traits commonly studied to establish face validity with human ASD and found continuous variation in social interaction, short-term, and long-term social discrimination Fig. a across In search for mouse behavioral traits related to ASD with stronger genetic influences, we reverted to the BTBR mouse inbred strain to find candidate phenotypes that may yield more genetic contrast in the CC lines. Following the variation in digging and grooming behavior in our CC population, we hypothesized that ASD phenotypes relating to lower order repetitive behavior might show stronger genetic control. The BTBR mouse inbred strain has a wide variety of natural genetic variation compared to other mouse laboratory inbred strains  and is commonly used as a mouse model for ASD with predominant abnormalities in behavioral inflexibility and repetitiveness –18, 43. Following the characterization of stereotyped exploratory patterns during novelty exposure in BTBR mice, we tested this phenotype in our population of CC mice. We found that this readout was continuously distributed with substantial variation Fig. d and wasHrh3 . High ASD-ranked genes within this QTL included brain-specific angiogenesis inhibitor 3 (Bai3), a member of the BAI subfamily of adhesion G-protein-coupled receptors (GPCRs). These GPCRs regulate synapse development and plasticity and are implicated in various neurological and psychiatric disorders [As further proof of principle, we also investigated whether QTLs for basic behavior and brain phenotypes . Finallpression –60.These results showed that CC recombinant inbred lines can complement existing genetic or inbred animal models for neurodevelopmental disorders. The current sample of CC inbred lines showed a population distribution of phenotypic variability for multiple NDD traits, and we identified QTLs that harbor genes strongly associated with corresponding NDD phenotypes in humans. Overall, the results indicated that CC lines can be used to study the quantitative impact of genetic manipulations and environmental perturbations on the basis of controlled genetic background variability.The obtained results in this CC population highlight that the choice of behavioral phenotypes is crucial to mimic trait dynamics and genetic associations observed in population studies . First, Once these criteria have been met, translational value may be indicated by the intersection of human neurodevelopmental risk genes with genetic associations of homologous genes in mouse populations. The current set CC lines appeared insufficient to resolve genetic loci at a single-gene level. We were, however, able to identify multiple QTLs and show that several genes in the identified QTLs are implicated in normal and abnormal brain development and are enriched for genes that are associated with ASD.Bai3. This gene has been associated with predisposition for schizophrenia and addiction and is considered a potential target for pharmacological intervention [In this study, we identified two QTLs for locomotor activity on chromosomes 1 (23.484–29.342 Mb) and 12 (16.824–26.491 Mb). We found that the locus on chromosome 1 was enriched for high ASD-ranking genes and that the highest ASD-ranking gene in this QTL was rvention –49, 61. rvention ). For exrvention , includirvention , of DBA/rvention , and of rvention . We alsorvention  and a lorvention . The varAtxn1 that plays a critical role in neural proliferation and cortical development [Hmgb4, which regulates the expression of neuronal differentiation markers.We identified two QTLs for brain weight unrelated to body weight on chromosomes 4 and 13. Both loci contained genes known to be involved in brain development, including elopment , 53, as Htr2C gene, which is known to cause repetitive behavior symptoms in a gene knockout model [The X-chromosome was highly associated with digging behavior in CC mice, which was indicated by three QTLs for this behavior on this chromosome. While these loci contained many genes, this association is an interesting observation because many genetic neurodevelopmental disorders are X-linked. Moreover, in mice, the X-chromosome has been implicated in autistic-like symptoms in a study that derived behavioral QTLs from intercrossing C57BL/6J and the BTBR mice . We obseut model . We did ut model . Moreoveut model  for sociWe identified a gene coding for H3 receptor in a QTL for repetitive behavior patterns. Manipulation of this receptor has been shown to alter repetitive behavior expression both in an anatomical model as in a pharmacological model –46. For Taken together, our findings highlight the potential to use the CC population to assess the quantitative impact of genetic manipulations and pharmacological compounds on behavioral dimensions across different genetic backgrounds, e.g., as a genetic reference population. The use of CC for NDD studies can be expanded into more targeted experiments, for example, by heterozygous crosses between CC lines and gene knockout lines , or by CQuantitative, population-based approaches in animal modeling are needed to complement models based on single genetic mutations in a single background. Our results provide a starting point for modeling the quantitative nature of NDD using a genetic reference population and demonstrate a unique potential of CC lines for future studies into mouse models of neurodevelopmental disorders.Additional file 1:Figure S1. Haplotype-based and broad-sense heritability estimates in CC mice. Figure S2. Phenotypic correlations in CC mice. Figure S3. Quantification of stereotyped exploratory patterns in C57BL/6J and BTBR mice. Figure S4. Characterization of genes in QTL by predicted ASD implication. Table S1. Quantitative trait loci (QTLs) for neurobehavioral traits in CC mice. Table S2. Human homologous genes in QTLs derived from CC mice. (DOCX 8519 kb)


Festuca ovina L., in Xinjiang, China. A total of 100 individuals from 10 populations were analyzed using six amplified fragment length polymorphism (AFLP) primer pairs. A total of 583 clear bands were generated, of which 392 were polymorphic; thus, the percentage of polymorphic bands (PPB) was 67.24%. The total and average genetic diversities were 0.2722 and 0.2006 (0.1686–0.2225), respectively. The unweighted group method with arithmetic mean (UPGMA) tree, principal coordinates analysis (PCoA) and Structure analyses revealed that these populations or individuals could be clustered into two groups. The analysis of molecular variance analysis (AMOVA) suggested that most of the genetic variance existed within a population, and the genetic differentiation (Fst) among populations was 20.71%. The Shannon differentiation coefficient (G’st) among populations was 0.2350. Limited gene flow (Nm = 0.9571) was detected across all sampling sites. The Fst and Nm presented at different levels under the genetic barriers due to fragmentation. The population genetic diversity was significant relative to environmental factors such as temperature, altitude and precipitation.Glaciation and mountain orogeny have generated new ecologic opportunities for plants, favoring an increase in the speciation rate. Moreover, they also act as corridors or barriers for plant lineages and populations. High genetic diversity ensures that species are able to survive and adapt. Gene flow is one of the most important determinants of the genetic diversity and structure of out-crossed species, and it is easily affected by biotic and abiotic factors. The aim of this study was to characterize the genetic diversity and structure of an alpine species,  Glaciation and mountain orogeny are the main factors that shape landscapes and change climate, and they have been linked to recent diversification and speciation events ,2. They High genetic diversity is fundamental for the ability of a species to survive and develop . It is oFestuca (Poaceae), with its approximately 100 species, is one of the most prevalently used grass genera, presenting a wide cosmopolitan distribution in the world [Festuca ovina L. is a perennial, cool-season and outbreeding grass aggregate with considerable agricultural and ecological importance [n = 4x = 14 and tetraploid 2n = 4x = 28 [Festuca ovina L. survives well in various habitats, which range from acid soils, coastal dunes and cliffs to cold deserts and heavy metal soils. Moreover, this species is abundant in Eurasia, ranges from the Arctic to the warm temperate zone, and is even found in outlying areas further south [Festuca ovina L. is often used as a constructive species, turf grass, hay or grazing grass due to its multi-tillers and nutritional value , and it also presents considerable ecological resistance to sandstorms and soil erosion in some alpine and desert areas [F. ovina and Stipa purpurea are the dominate species of Temperate steppe in Xinjiang, China, while a large number of Leymus, Potentilla and deleterious Leguminosae plants have invaded, expanded and occupied the dominant position in degraded ecosystem because of global climate changes, overexploitation, overgrazing and pollution [F. ovina community indicate high volatility and vulnerability and the population size is gradually decreasing, causing genetic erosion that seriously impedes the sustainable development of the region’s ecological security and local animal husbandry.The genus he world . Among tportance ,24. Its  4x = 28 . Due to er south ,26. Festrt areas ,26. Geneollution ,28. The F. ovina. Actually, the heterogeneity of landscapes triggered by orogenic movements has formed many special habitats [The Tianshan Mountains in Xinjiang of China and Central Asia are three parallel fold mountains that present a typical case of glaciation and orogenic movement ,30. Theyhabitats ,35. Manyhabitats ,36. The habitats ,38. It ihabitats ,40.F. ovina individuals from 10 populations found in Xinjiang. The aims were to (1) characterize the level of genetic diversity and the distribution of genetic variation within and among F. ovina populations; (2) calculate the gene flow and differentiation among populations at different scale and fragmented patterns; and (3) discuss the influence of environmental factors on population genetic diversity and structure. As a consequence, this study supplies a basis for the collection and protection of germplasm resources.In this study, AFLP was used to investigate the genetic diversity and structural patterns of 100 wild In this study, the six selected AFLP primer pairs generated 583 clear bands that corresponded to an average of 97.17 per primer pair . Among tF. ovina populations are listed in The genetic diversities of 10 F. ovina populations  among 10 ulations . The genF. ovina, a UPGMA (unweighted pair-group method with arithmetic means) clustering analysis at the species level was conducted  was performed on the entire dataset of 100 individuals. The results showed that these individuals were divided into two groups . The indF. ovina populations  was conducted to further evaluate the partitioning of genetic differentiation among and within ulations . The resF. ovina populations was carried out using Monmonier’s maximum difference algorithm. This analysis revealed three likely barriers against gene flow     to altitude, and weak correlation to annual precipitation . No significant correlation was found between Ho and annual mean temperature, longitude or latitude. The percent of polymorphic loci (PPL) was also weakly correlated to altitude , and not related to annual mean temperature, annual precipitation, longitude or latitude.Pearson’s correlation analyses showed that the Nei’s genetic diversity (Hj) of  < 0.01) a, indica < 0.01) b, and we < 0.01) c. While Fescue accessions was assessed using a DNA bulking strategy and AFLP, revealed an average NPB (number of polymorphic bands) of 41 and a PPB of 85.4%. Higher PIC values, such as 0.2715 (0.1534–0.3842) for genomic SSRs (simple sequence repeat) and 0.2224 (0.0760–0.4289) for EST-SSRs (expressed sequence tag-simple sequence repeat), than those of tall fescue were revealed by Tehrain et al. [Festuca pratensis Huds.) populations and Nordic cultivars, which revealed a lower genetic diversity (Hj = 0.1412) [F. ovina populations, which corresponded well to the Shannon differentiation coefficient of G’st = 0.2512. The study by Majidi et al. [F. ovina populations. This low observed value of genetic diversity was possibly caused by different molecular markers or DNA strategies . Alternatively, habitat fragmentation could be the explanation. Since the formerly panmictic population became fragmented, random genetic drift over time has led to both genetic differentiation among, and loss of heterozygosity within the fragmented population [F. ovina, resulting in decreased fitness and reduced population size and thereby causing the observed low genetic diversity [Genetic diversity is considered the consequence of long-term evolution and represents the evolutionary potential of a species to survive in various environments ,41. Thusn et al. . Generaln et al. . In mostn et al. . A molec 0.1412) . Typical 0.1412) . The toti et al.  revealedi et al.  showed di et al. . Converspulation . In the r = −0.85, p < 0.01) or Shannon diversity index . For out-crossing species, wind, insects and animals are essential pollinators that guarantee gene flow within and among populations, these factors also determine the seed distribution of F. ovina [r = 0.5657, p < 0.01)  was weakly negatively correlated with annual precipitation   as the latitude and longitude increasing, which affect the distribution and development of plant species. Whereas the longitude and latitude didn’t impact on genetic diversity of F. ovina populations in this study, these were probably limited by the scarcity of specimens, and further research with more sampling sites would confirm it.Evidence for lower genetic diversity at higher altitudes was found based on Pearson’s correlation analysis between geographic altitude and Nei’s genetic diversity  b, and iteratures ,31. Thos < 0.01) c, partlyF. ovina populations comprised two clusters, and FO-04 and FO-09 were isolated from adjacent populations  has an important impact on population genetic structure, evolutionary biology, conservation biology, and ecology . High leF. ovina populations  were sampled from Xinjiang, China in 2010 (n = 2x = 14).A total of 10 wild  in 2010 . Individ in 2010 . A singl® ND-1000 Spectrophotometer  and diluted to 100 ng/μL for AFLP analysis.For each individual, genomic DNA was extracted from an aggregate of 3–5 fresh leaf tissues (approximately 80 mg) using a plant DNA extraction kit  according to the manufacturer’s instructions. The DNA concentration was quantified using a NanoDrop2, 2 mM dNTP, 40 ng of each of EcoRI primer and MseI primer, 1 U Taq polymerase, and 5.0 µL pre-amplified template DNA. The fragments amplified in the latter step were subjected to capillary electrophoresis using an ABI 3500 . GeneMarker  was used to treat the fluorescent AFLP fragments for each individual sample.The AFLP procedure was performed according to Sorkheh et al. . A preliEach band in the AFLP fingerprint pattern was considered a separate putative locus, and the bands clearly indicating AFLP amplification as 1 (presence) or 0 (absence) in a readable range (between 50 and 400 bp) were used to generated the binary matrices. The following parameters were calculated using EXCEL 2013 software : total number of bands (TNB), number of polymorphic bands (NPB), percentage of polymorphic bands (PPB) and polymorphism information content . The ShFirst, Nei’s genetic distance (GD) of the population was calculated using AFLP-SURV v1.0  with 10,To further study the genetic differentiation (Fst) within and among populations, analysis of molecular variance (AMOVA) was conducted at different levels using the R package “vegan” . The ShaTo examine the level of significance, the Pearson correlation between genetic diversity and environmental factors  was estimated using the R package “ade4”   with 100F. ovina was relatively low. Population genetic diversity was decreased with increasing elevation, and it was also weakly related to temperature and precipitation but not correlated to latitude or longitude. Restricted gene flow was observed at different spatial scales, whereas genetic differentiation due to fragmentation was also detected between adjacent populations.The results of this study demonstrate that environmental conditions in different habitats are major factors influencing the hereditary characteristic of species. The genetic diversity of