COL5A1 rs12722 polymorphism is considered to be a novel genetic marker for endurance running performance. It has been postulated that COL5A1 rs12722 may influence the elasticity of tendons and the energetic cost of running. To date, there are no experimental data in the literature supporting the relationship between range of motion, running economy, and the COL5A1 rs12722 gene polymorphism. Therefore, the main purpose of the current study was to analyze the influence of the COL5A1rs12722 polymorphism on running economy and range of motion. One hundred and fifty (n = 150) physically active young men performed the following tests: a) a maximal incremental treadmill test, b) two constant-speed running tests (10 km•h−1 and 12 km•h−1) to determine the running economy, and c) a sit-and-reach test to determine the range of motion. All of the subjects were genotyped for the COL5A1 rs12722 single-nucleotide polymorphism. The genotype frequencies were TT = 27.9%, CT = 55.8%, and CC = 16.3%. There were no significant differences between COL5A1 genotypes for running economy measured at 10 km•h−1 (p = 0.232) and 12 km•h−1 (p = 0.259). Similarly, there were no significant differences between COL5A1 genotypes for range of motion (p = 0.337). These findings suggest that the previous relationship reported between COL5A1 rs12722 genotypes and running endurance performance might not be mediated by the energetic cost of running.The  COL5A1, which encodes a structural protein of the extracellular matrix. These authors observed that the TT genotype was overrepresented in runners with faster performances during the 42.2-km running portion of the Ironman triathlon, suggesting thatCOL5A1 might be a novel genetic marker for endurance running performance.It is well known that athletic performance is dependent on a multifactorial phenotype resulting from a complex interaction between environmental COL5A1 and endurance running performance might be mediated by the energy storage capacity of the connective tissues COL5A1 encodes the α1 (V) chain of type V collagen It is believed that the relationship between COL5A1 rs12722 gene polymorphism. Consequently, it is difficult to determine whether the association previously reported between the COL5A1 gene and endurance performance was due to a reduced running energy cost.Running economy (RE), which has been defined as the energy cost or oxygen uptake for a given submaximal running speed COL5A1 gene polymorphism on RE. In light of past studies that reported a relation between the COL5A1 gene (rs12722) and endurance running performance Therefore, the main objective of the present study was to analyze the influence of the One hundred and fifty (n = 150) physically active men  volunteered to participate in this study. All subjects were medication-free, nonsmokers, and free of neuromuscular disorders and cardiovascular dysfunctions. The subjects had been involved in recreational sports in the past year, but they had not engaged in flexibility and strength training for at least six months before the study. The participants received a verbal explanation about the possible benefits, risks, and discomforts associated with the study and signed a written informed consent before participation in the study. The procedures were in accordance with the Helsinki declaration of 1975, and the study was approved by the Ethics Committee for Human Studies of the School of Physical Education and Sport of the University of São Paulo.All of the subjects were required to visit the laboratory on three occasions separated by at least 72 h over a 2-week period. In the first visit, the subjects were asked to perform mouthwashes for genomic DNA extraction, to perform a sit-and-reach test for ROM measurement, and to fill out a short version of the physical activity questionnaire (IPAQ-short version) to estimate their physical activity levels. In the second visit, anthropometric measurements  were recorded and a maximal incremental treadmill test was performed. A constant-speed, treadmill running familiarization test was conducted at the end of the first and second visits after a 20-min passive recovery. In the third session, the subjects performed two submaximal constant-speed tests. All of the tests were performed at the same time of day in a controlled-temperature room (20–24°C) and 2–3 h after the last meal. All of the subjects were asked to refrain from any exhaustive or unaccustomed exercise for 48 h preceding the test. They also were instructed to wear standard running shoes and asked from taking off nutritional supplements six months before the experimental period.All of the anthropometric measurements were made according to the procedures described by Norton and Olds −1, the velocity was increased by 1 km·h−1 every minute until exhaustion. The participants received strong verbal encouragement to ensure attainment of maximal values. Gas exchange was measured breath-by-breath using a gas analyzer  and was subsequently averaged over 20 s intervals throughout the test. Before each test, the gas analyzer was calibrated according to the recommendations of the manufacturer. Maximal heart rate (HRMAX) was defined as the highest value obtained at the end of the test. Blood samples (25 µl) were collected from the ear lobe one, three, and five minutes after the test to determine the peak blood lactate. Lactate concentrations were measured spectrophotometrically  using a wavelength of 546 nm. −1·min−1 between two consecutive stages, a respiratory exchange ratio greater than 1.1, and a ±10 bpm of the predicted maximal heart rate  The subjects performed a maximal incremental test on a motor-driven treadmill  to determine maximal oxygen uptake −1 and 12 km·h−1 speeds. These intensities corresponded to 78.8±6.7% and 89.7±7.9% of the LW = 10 km·h−1) and high (REHG = 12 km·h−1) intensities. Before the tests, the participants performed a standardized warm-up consisting of a 5 min run at 8 km·h−1 followed by a 5-min of passive recovery. RE was determined by measuring breath-by-breath oxygen uptake for 10 minutes at each running speed. RE was defined by averaging the oxygen uptake values during the last 20 s for each running speed. Recovery time between these two constant-speeds running tests was 10 min.The subjects performed two constant-speed running tests on a treadmill to determine RE. Because it has been reported that a subject who is economical at a given speed will not be necessarily economical at other speeds COL5A1 genotypes on lower limb flexibility because it represents an indirect measure of both hamstring musculotendinous unit length and lumbar ROM Range of motion (ROM) was measured using a sit-and-reach test http://www.ipaq.ki.se/scoring.htm).Because the RE may be influenced by the training status of the subjects COL5A1 rs12722 gene polymorphisms were determined by conventional 2-primer PCR (F: 5′-GCAGTCAGCAGCGTGGGTCTGGTTATCT-3′ and R: 5′-TTTGGGGTGGCACTTGCAGCACT GGTCG-3′). This assay resulted in the amplification of a 637-bp fragment of the COL5A1 gene that includes the polymorphic region. The reaction conditions were as follow: initial hold at 94°C for 3 min, 35 cycles of denaturation at 94°C for 60 s, annealing at 53°C for 60 s and extension at 72°C for 60 s, and a final extension step of 8 min at 72°C. The amplified fragment was subsequently digested using BstUI , following the supplier’s recommendations. The digested products were then separated on a 3% agarose gel. To ensure proper internal control, for each batch of analysis, we used positive and negative controls from different DNA aliquots that were previously genotyped by the same method, according to recent recommendations for replicating genotype-phenotype association studies Cells from the mouthwashes were submitted to an overnight digestion with proteinase K. Nucleotides were separated from the cellular debris by density gradient centrifugation using chloroform. Genomic DNA was then precipitated with isopropyl alcohol, isolated by centrifugation and resuspended in TE buffer. DNA quantification was performed using a spectrophotometer , and the concentration was adjusted to 1 µg/µL for subsequent storage in −20°C. 2 test was used to verify that the genotype frequencies were in Hardy-Weinberg equilibrium. The effects of the COL5A1 genotypes in the analyzed variables were tested using a one-way analysis of variance (ANOVA). The significance level was set at p<0.05. All of the statistical analyses were performed using Statistica 8 .Data normality was assessed using the Kolmogorov-Smirnov test, and all of the variables showed a normal distribution. The results are reported as means and standard deviations (±SD). A X2 test. The genotype frequencies were TT = 27.9%, CT = 55.8% and CC = 16.3%. The genotype distribution of the COL5A1 rs12722 gene polymorphism was similar to the distribution reported in the public databases for Caucasian populations (http://opensnp.org/snps/rs12722). In accordance with the mean values of the IPAQ-SV outcomes, the subjects of the three groups were classified as moderately active COL5A1 gene (p>0.05)  .MAX, and [La]peak between individuals with different COL5A1 genotypes (p>0.05). LW (p = 0.232) (panel A), REHG (p = 0.259) (panel B), and ROM (p = 0.337) (panel C) were not statistical different between the CC , CT , and TT  COL5A1 genotypes groups.COL5A1 gene might be a marker of endurance running performance COL5A1genotypes because the subjects did not perform constant-speed tests to measure the RE. To the best of our knowledge, this is the first study designed to analyze the relationship between a common C to T single-nucleotide polymorphism gene within COL5A1 gene (rs12722) and RE. The major findings of this study show that theCOL5A1 genotypes were not associated with either RE or ROM.Previous findings suggested that the COL5A1 genotypes and RE. Our results showed no significant differences in RELW between individuals with different COL5A1 genotypes. This finding suggests that the superior performance observed in individuals with a TT genotype in the COL5A1gene (rs12722) cannot be explained by a lower energy cost during running at a low percentage of It has been proposed that mechanical properties of connective tissues are responsible for converting elastic energy to kinetic energy free of metabolic cost COL5A1 genotypes were not associated with the energetic cost of running regardless of running intensity. An alternative explanation for the relationship between COL5A1 genotypes and endurance running performance might be the ability to produce force rather than a reduced energetic cost. Recently, Kubo et al. COL5A1 genotypes and endurance running performance.In the present study, we considered that a subject who is economical at low relative running intensity might not be economical at high relative running intensity. Our results demonstrated that COL5A1 rs12722 genotypes could alter the elasticity of tendons i.e. COL5A1 rs71746744) of this gene COL5A1 gene polymorphisms and ROM. Some studies found that the CC genotype was overrepresented in individuals with greater ROM COL5A1 genotypes in a South African cohort were not associated with ROM in young subjects (<35 years). However, these authors found a positive correlation between COL5A1genotypes and ROM in older subjects (>38 years old) COL5A1 genotypes. Taken together, these findings reinforce the suggestion that COL5A1 rs12722 genotypes might interact with age for ROM in physically active subjects It has also been postulated that COL5A1 (rs12722) genotypes (It is important to acknowledge some of the limitations of the present study. First, the subjects in the present investigate on were characterized as physically active, as evidenced by the IPAQ-SV outcomes. This would imply that our subjects might have a lower capacity for endurance exercise than the trained endurance runners that were previously studied enotypes . In addiCOL5A1gene were not associated with RE and ROM. This indicates that the previous relationship reported between COL5A1 genotypes and endurance running performance may not be mediated by the energetic cost of running. Therefore, further studies are needed to examine the causal relationship between COL5A1 gene and endurance running performance.In conclusion, the results of the current study demonstrated that variants within the


Acropora corals . Seven species spawned during both seasons; five only in autumn and one only in spring. The majority of tagged colonies (n = 218) spawned once a year in the same season, but five colonies from three species spawned during spring and autumn during a single year. Reproductive seasonality was not influenced by spatial variation in habitat conditions, or by Symbiodinium partners in the biannual spawner Acropora tenuis. Colonies of A. tenuis spawning during different seasons separated into two distinct yet cryptic groups, in a bayesian clustering analysis based on multiple microsatellite markers. These groups were associated with a major genetic divergence (G”ST = 0.469), despite evidence of mixed ancestry in a small proportion of individuals. Our results confirm that temporal reproductive isolation is a common feature of Acropora populations at Scott Reef and indicate that spawning season is a genetically determined trait in at least A. tenuis. This reproductive isolation may be punctuated occasionally by interbreeding between genetic groups following favourable environmental conditions, when autumn spawners undergo a second annual gametogenic cycle and spawn during spring.Coral spawning on the oceanic reef systems of north-western Australia was recently discovered during autumn and spring, but the degree to which species and particularly colonies participated in one or both of these spawnings was unknown. At the largest of the oceanic reef systems, the participation by colonies in the two discrete spawning events was investigated over three years in 13 species of  Most tropical corals are simultaneous hermaphrodites that reproduce by broadcast spawning, releasing their eggs and sperm into the water column where fertilisation and larval development occur , 2. AlthTemporal reproductive isolation in conspecific colonies may be due to a split-spawning , when coVariation in the time of coral spawning has been attributed to environmental cues such as solar insolation , 25, winAcropora assemblages in a primary mass spawning in autumn and a secondary spawning in spring. Our design included re-sampling individual colonies to determine their capacity to spawn twice a year or in different seasons. Local environmental drivers of reproductive cycles were investigated by sampling from sites across the reef system (separated by m to 10s km) and by identifying the Symbiodinium type hosted by colonies of the most abundant biannual spawner, Acropora tenuis. Additionally, genetic variation was quantified for colonies of A. tenuis from the sampling sites across the reef system to determine the extent of differentiation among sites versus colonies spawning during different seasons.In this study, we investigated cycles of reproduction in biannually spawning corals on an oceanic reef system off Western Australia, and whether spawning seasonality was associated with environmental or genetic variation. Over three years, we surveyed the participation of Acropora species typically contribute around 25% of the total coral cover [The study was conducted at North and South Scott Reef, located approximately 270km from the mainland of north-western Australia , where al cover . Five stAcropora: A. cytherea, A.digitifera, A. florida, A. gemmifera, A. humilis, A. hyacinthus, A. microclados, A. millepora, A. muricata, A. polystoma, A. samoensis, A. spicifera and A.tenuis. Coral colonies typical of the species morphology were targeted and all species identifications were confirmed in situ and with skeletal type specimens by the authors and by D. McKinney [Acropora tenuis), an additional 25 colonies were collected for detailed skeletal analyses by Z. Richards from the Western Australia Museum, which included colonies known to spawn in autumn (n = 16) and spring (n = 9).Reproduction was investigated in 13 abundant species of broadcast spawning McKinney , 33, witn = 50 to 416 colonies per species) were sampled randomly one to five weeks before the spawning in autumn and spring, in 2008, 2009 and 2010. In addition, 218 tagged colonies (n = 11 to 33 per species) were re-sampled prior to each spawning. Three branches were sampled from the central region of each colony to provide an in situ rank of egg development and spawning time based on the size and pigmentation of visible eggs: Score 1, indicated that colonies would spawn within the month; Score 2, indicated colonies would spawn within two months; Score 3, indicated that colonies had recently spawned, or will not spawn for several months. A subset of random colonies was checked in situ after the autumn spawning each year to confirm that mature eggs had been spawned. Sampling was approved by the Western Australian Department of Fisheries under the permit numbers 2008–6 and 14–795.Mature (> 20 cm diameter) colonies  or spring (n = 24) spawners, or as spawning in both seasons (n = 3) according to the field and laboratory observations. Total genomic DNA was extracted and allelic variation measured at five microsatellite loci developed for closely related species which are also polymorphic in A. tenuis: Amil2_10, Amil2_11, Amil_12, Amil_018 [Acr_53 [Tissue samples were collected from the tagged Amil_018  and Acr_ [Acr_53 . MicrosaPopulation genetic statitistics including shared multilocus genotypes and genotype probability (GP), number of alleles, the expected heterozygosity, observed heterozygosity and fixation index at each locus within reproductive season (as defined by the reproductive survey) were calculated with GenAlEx v6 . Shared A. tenuis colonies that spawned in different reproductive seasons was investigated with a Bayesian clustering analysis in STRUCTURE v2.3 [K, in the entire sample without any prior information on spawning time of individual colonies. Mean and variance of log likelihoods and posterior probabilities of the number of clusters (K = 1 to 6) were inferred from multilocus genotypes by running STRUCTURE ten times using the admixture and independent allele frequencies models . The independent allele frequency model was implemented because the genetic differentiation between spawning groups was large, and trial runs with correlated allele frequencies model overestimated K in which individuals lacked strong assignments . Convernts  and is recommended when a small number of markers and individuals are employed [The initial analysis unambiguously identified two distinct clusters, with the majority of individuals assigned to their correct spawning season (as identified by the reproduction survey). A secondary clustering analysis was implemented for employed . For thiFST and with G”ST [G”ST accounts for the high degree of variation within populations, and is the recommended measure of genetic differentiation for inferences of demographic history, particularly when microsatellite markers are used [The level of differentiation between genetic groups identified by STRUCTURE was measured with ith G”ST  in GenAlith G”ST  and exclare used .Symbiodinium type(s) were genotyped from the A. tenuis genomic DNA used in the microsatellite analysis to determine any variation in photosymbiont communities among colonies spawning in different seasons. PCR was used to amplify the Symbiodinium ITS2 rDNA region using the primers ITSintfor2 and ITS2clamp [ITSintfor2 and ITSReverse (without the GC clamp), and re-run on a DGGE and a subset of samples in which bands that matched the original DGGE profiles were sent for sequencing in both directions . Automated sequencing calls of 281 bases were visually checked and consensus sequences were aligned  and compared to available Symbiodinium ITS2 rDNA sequences downloaded from GenBank (http://www.ncbi.nlm.nih.gov/genbank/).TS2clamp  using thTS2clamp . PCRs weTS2clamp . DGGE baAcropora sampled, one spawned only in spring (A. millepora), five spawned only in autumn  and seven spawned in both seasons  (A. tenuis (3), A. cytherea (1) and A. florida (1) contained mature gametes in spring 2008 and again in autumn 2009, but in subsequent years all spawned only during autumn. For most (6 of 7) species of biannual spawners, a similar proportion of colonies spawned in each season. Eggs were present in 29% of the colonies in spring and 51% in autumn, and were either large  and pigmented, indicating they would be spawned within weeks, or small  and unpigmented, indicating they would mature in the next spawning season (in situ observations and gamete development.Of the 13 species of  tenuis) . Most , which AY258485 .A. tenuis colonies, but none of these occurred among colonies collected from the same sampling site. Both of these shared genotypes had a GP > 0.001, and therefore all individuals were included in the analysis. Between two and eight alleles were detected per locus in the two spawning groups along with high levels of heterozygosity in most loci  despite having fewer alleles (A = 3.4 per locus) and less private alleles (PVA = 2), compared with the spring spawners  (Two multilocus genotypes were shared among five pawners: . The autVA = 12) .q ≥ 0.75 in 40 out of 49 colonies . The three individuals that spawned in both seasons also exhibited a degree of mixed ancestry, but all had stronger affinities with the autumn cluster with average q across the ten runs of 0.55, 0.68 and 0.84 . Visual inspection of allele frequencies indicated that these differences were obvious at multiple loci . Th. ThAcropia  than among colonies separated by 1000s of kilometres across Western Australia  may therefore exist only for the colonies whose primary season of spawning is autumn, whereas the spring spawners may not have the same capacity for a second cycle (during autumn) and to pass on newly mutated alleles. This hypothesis is based on evidence from a small sample size at Scott Reef, but is worthy of further investigation with more detailed reproductive and genetic data in coral assemblages where biannual spawning has been documented in both populations and individuals.The combination of reproductive, genetic and environmental data for Scott Reef further support the hypothesis that a colony’s season of spawning is primarily genetically determined, but that significant inter-annual variation in environmental conditions  influence the month of spawning and the capacity to spawn twice a year. Most 98%) tagged colonies at Scott Reef spawned only once a year and consistently in the same season, which was evident in the prodigious genetic differentiation between the autumn and spring spawners of ted from ). Conver% tagged le years , 30. Favle years  and at SPocillopora lineages in north-eastern Australia [n = 244) that were tagged and followed through time, 10% were excluded because their identities could not be confirmed following in situ and skeletal examination at the completion of the study, and differences in expert opinion also existed among other specimens. A detailed morphometric analysis was not conducted and for the many colonies in the random sample identifications were based only on in situ observations. Other studies of coral reproduction and genetics in the Acropora also rely on mostly in situ identification, with more detailed investigation for only a subset of type specimens invariably leading to some errors. Addressing these issues is logistically very difficult (see [Acropora), rather than individual species. Less detailed information is obtained, but the approach if far simpler and supports management actions to protect key periods of reproductive output from human pressures, while also ensuring that reproductive data for incorrectly identified species do not become entrenched in the literature. If, however, the goal of a study is to elucidate the species boundaries in coral assemblages, then detailed reproductive, morphometric and genetic analyses are clearly required over several years.Temporal reproductive isolation and genetic differentiation between conspecific colonies in other studies of corals have suggested the presence of cryptic species –64; for ustralia –67. Consustralia –70, hybrustralia –73 and rustralia , 74, 75.ult , buS1 FigCurrent speed, chlorophyll concentrations, turbidity, and wave heights were quantified only at the Lagoon, Inner East and Inner West sites. Cover (%) of sand is and annual average for the period (2008–2010) of this study. Other parameter values are daily averages divided between summer and winter months, which accounted for the influence of monsoonal storms.(PDF)Click here for additional data file.S2 FigK as a function of K. Lower panel is the assignment probabilities of colonies at K = 2, with colonies that were identified in the reproductive surveys as autumn or spring spawners, and colonies that spawned in both seasons during one year. Values calculated in Clumpak using 10/10 runs, a mean (LnProb) = -501.5, and similarity score = 0.999.Upper panel shows Delta (PDF)Click here for additional data file.S1 TableA), the proportion of expected (HE) heterozygotes, and the fixation index (FIS) calculated for each locus and averaged across loci (All loci) for each reproductive season, and the number of private alleles (PVA) for each reproductive season. Bolded FIS estimates indicate significance at p<0.05 after sequential bonferroni correction.Given are the sample sizes (in brackets after season name), number of alleles ((PDF)Click here for additional data file.S1 Text(PDF)Click here for additional data file.


Hyla wrightorum, the Arizona treefrog, is native to the southwestern United States and Mexico, and an isolated group of populations exists in the Huachuca Mountains and Canelo Hills (HMCH) of southeastern Arizona, USA. Due to concerns about declining observations of the species within the isolated HMCH portion of its range, the HMCH group is currently a candidate for federal protection under the U.S. Endangered Species Act. We present results of a genetic study examining population diversity, structure, and connectivity within the HMCH region. We sampled DNA from H. wrightorum larvae and adults from ten distinct locations, 8 of which were breeding sites and 4 of which were previously undescribed localities for the species. We developed and genotyped 17 polymorphic microsatellite loci and quantified genetic diversity, population differentiation, and landscape influences on population genetic structure. We found evidence of larger than expected effective population sizes, significant genetic differentiation between populations, and evidence of distance being the primary driver of genetic structure of populations with some influence of slope and canopy cover. We found little evidence of recent genetic bottlenecks, and individual-based analyses indicate admixture between populations despite significant genetic differentiation. These patterns may indicate that the breeding sites within the Huachuca Mountains constitute a metapopulation. We suggest that the HMCH region may contain larger and more connected breeding populations than previously understood, but the dynamics of this system and the limited geographic extent of the HMCH group justify current concern for the persistence of the species in this region. Efforts to ensure availability of high-quality breeding habitats and control for local threats such as effects of invasive predators may be critical to the persistence of these unique populations of H. wrightorum.Population attributes such as diversity, connectivity, and structure are important components of understanding species persistence and vulnerability to extinction.  Effective conservation of species vulnerable to extinction throughout some or all of their range requires knowledge of population attributes such as diversity, connectivity, and structure . For decHyla wrightorum , the Arizona treefrog, is an anuran native to the southwestern United States and Mexico and is currently a candidate species for federal protection by the U.S. Fish and Wildlife Service (USFWS) within a subset of its range [Hyla wrightorum is most commonly associated with streams, cienegas (wetlands), and manmade ponds, particularly during the summer monsoon season when intermittent pools are used for breeding [ts range . Hyla wrbreeding –8. The sTaylor, 138, the Abreeding . This dibreeding .Hyla wrightorum populations within the HMCH region are of conservation concern. In the past two decades, confirmed observations have been made at only half (8 of 16) of previously reported locations [H. wrightorum in the HMCH is small compared to the larger two portions of its distribution . In addsbeianus . Contemp species . Taken telopment –17.H. wrightorum in the HMCH region [H. wrightorum may form breeding choruses only one or a few nights in a given year, traditional census and survey efforts may fail to provide reliable information, particularly if populations are in fact in decline [H. wrightorum in the Huachuca Mountains region.These concerns, coupled with the phenotypic, genetic, and geographic uniqueness of this group, have led to candidacy for federal protection of H region . However decline . Genetic decline  and may H. wrightorum in the HMCH region of southeastern Arizona. The objectives of our study were to address current knowledge gaps regarding population genetic diversity, population structure, and effective population sizes (Ne) of this species in the region. To achieve this, we used a combination of population-level and individual-based approaches. Based on current knowledge of the species, we hypothesized small (< 30) effective population sizes for H. wrightorum in the HMCH region. This was based on both small observed breeding choruses for this species [Ne for a sympatric congener . We alss region . Alternaer apart . We alsoH. wrightorum individuals were sampled during the summer monsoon season of 2014. We selected sampling locations using a combination of historical records of H. wrightorum occurrences as well as opportunistic visits to potential habitat (ponds and wetlands) in the known range of the species  at Yale University’s DNA Analysis Facility . Genotypes were analyzed using the software GENEMAPPER 4.1 (Applied Biosystems). Individuals with poor-quality genotype data were processed again through PCR and genotyping, and in a few cases DNA extractions were performed again provided sufficient tissue remained. Individuals with > 25% missing data after three genotyping attempts were discarded from downstream analyses.Whole genomic DNA was extracted using DNeasy 96 Blood & Tissue Kit (QIAGEN) at the Molecular Ecology Research Lab at the University of Washington’s School of Aquatic and Fishery Sciences. Alleles were binned using the program TANDEM . Any all10.6084/m9.figshare.3365293). Microsatellite loci were first screened for linkage disequilibrium or deviations from HWE using adult genotypes to identify any loci that may affect detection of siblings. When full siblings were detected, one sibling was retained from each family in the final dataset.Larval samples can bias population genetics findings by artificially inflating genetic differentiation due to family structure ; therefoHE), observed heterozygosity (HO), allelic richness (AR) rarified to the smallest number of sampled individuals per population, and FIS [FST [G'ST [Dps, a method of measuring genetic differentiation based on proportion of shared alleles [FST [FST, calculated as FST /(1- FST) [FST as linFST. Genetic diversity, global genetic differentiation, and pairwise genetic differentiation metrics were calculated using MSA 4.05 [We calculated genetic diversity estimates of expected heterozygosity  . Here weMSA 4.05 .Ne) for each sampling location and for all individuals combined. Ne for each sampling location was estimated using the linkage disequilibrium method (LDNe) of Waples and Do [Ne estimates, and overall Ne estimates can be downwardly biased if sub-structure exists among populations [Ne that accounts for population structure. We estimated total Ne following Wright [Ne in Holleley et al. [Ne was calculated with mean local Ne estimates and upper and lower 95% jackknifed confidence interval values. A value of 10,000 was used in the case of local Ne estimates with infinite upper confidence values [We estimated effective population size  by first examining log-likelihood and secondarily by visually inspecting α and individual admixture results. This analysis was repeated for genetic clusters in which both K > 1 and n > 1 to identify hierarchical population structure until terminal clusters were described [To evaluate whether individuals sampled at a location likely originated from the local population, we used an individual assignment analysis as implemented in GeneClass2 . We usedtructure . Because species , 44, we K method  in whichkelihood ; α, the kelihood ; and assividuals . We idenescribed . Individescribed .isolation-by-distance (uniform resistance across the landscape); isolation-by-slope , connectivity-by-canopy , and connectivity-by-stream . All spatial data were obtained from publicly available sources and are described in detail in the supporting information, To examine our hypotheses of landscape effects on population genetic structure, we first constructed four landscape connectivity surfaces using CIRCUITSCAPE . CIRCUITDps and linFST) in two ways. First, we first employed a causal modeling framework as implemented in Cushman et al. [We evaluated relationships between landscape resistance and population genetic differentiation  to a null model with only the random effect (sampling location) and an intercept. All analyses were performed in R version 2.14.0 , using a modified version of lme4 [2β calculation as described in van Strien et al. [Additionally, we evaluated relationships between pairwise genetic distance and pairwise landscape resistances using a mixed-effects modeling approach . Throughtatistic . R2β com of lme4  and PBKR of lme4  for R2β n et al. .H. wrightorum individuals at 10 locations for a total of N = 299 individuals, 82 of which were adults . Two locations had insufficient sample sizes for population-level analyses (populations 2 and 5); among the remaining 8 populations, the mean sample size was 36.6 individuals, with a minimum of 19 and a maximum of 50. We retained only 1 full sibling from each family identified, reducing the final sample size to a total of N = 221  or DNA was too degraded for successful genotyping . We found deviations from Hardy-Weinberg expectations at 21 of the 136 sample/locus combinations (15%) prior to application of a Bonferroni correction. However, with a Bonferroni correction applied, we found only 5 instances of significant deviation from HWE , with a jackknifed 95% confidence interval of 401.7 to 30402.4. Population-level Ne averaged 116.7 individuals per population, with a minimum estimate of 32.5 and a maximum estimate of 277.9. Confidence intervals for Ne ranged from 23.1 to infinite values , which may indicate some inbreeding in populations with smaller effective population sizes. Wilcoxon tests for bottlenecks found evidence of a recent bottleneck among individuals at only one location (Site 7), and mode-shift tests found no evidence of bottlenecks  to a second group . This pattern followed a north to south trend, with individuals from centrally located sites assigned to both clusters , and sites 6, 7, 8, and 9, which had a modest to dominant presence of the second group. Hierarchical results for the alternate K = 2 scenario are included in the supporting information, with the only difference from the K = 3 scenario being the inclusion of site 10 in the second group , only Distance was significantly univariately related to Dps . LinFST was not significantly univariately related to any landscape variables . These findings support the expected linear relationship between resistance (of a uniform landscape) and genetic distance in an isolation-by-distance scenario [We found multiple lines of evidence that, of the spatial attributes examined, distance is a primary driver of population structure. We also found evidence that slope and canopy may affect population structure. Of the four Mantel tests examining hypothesized relationships between spatial and landscape variables  and genetic distance Dps and lDps and linFST . Site 4 is a confirmed breeding site (larvae present), and Site 10 is a presumed breeding site (> 20 adults sampled in a breeding chorus). Site 10 extends the known range of contiguous breeding sites in the Huachuca Mountains southeast by roughly 7 km. Additionally, limited observations of H. wrightorum have been reported at a small number of wetland habitats at Rancho Los Fresnos, Sonora, Mexico, south of the Huachuca Mountains [H. wrightorum at three additional breeding locations, all previously undescribed . Many of these ponds were not visited in 2014 due to logistical and time constraints, and many have not been surveyed for this species. Temporal dynamics such as the frequency, timing, and duration of the period during which these ponds are wet versus dry is not known. Future research might aim to quantify the hydrologic dynamics of these ponds, and how they may change in the future, in order to help managers better understand the spatiotemporal variability of available breeding habitat. Additionally,  habitat . These tng sites .FST comparisons, AMOVA results, and evidence of hierarchical structure among populations indicate considerable genetic differentiation between populations, with a significant influence of spatial and/or landscape variables. Individual-based cluster analyses of H. wrightorum most strongly supported a predominant pattern of isolation-by-distance. Additional hierarchical analyses reveal some genetic clusters strongly associated with a certain locality . However, the presence of heterogeneity in assignment of individuals to clusters (Sites 9 and 10) or the lack of support from analyses that did not incorporate sampling location information (Site 3) indicates weak clustering at these locations. Admixture between sites was also supported with the assignment test results. In cases of more complete genetic isolation, we might expect to see near-perfect correlation of cluster assignments with sampling location, as observed in the one of the region’s aquatic macroinvertebrates, Abedus herberti, which requires perennial aquatic habitat [Significant pairwise  habitat .H. wrightorum populations in the HMCH region, which is in contrast to some sympatric pond-breeding anurans, including Anaxyrus cognatus, Scaphiopus couchii, and Spea multiplicata, found to have panmictic population structure across similar spatial scales [H. wrightorum in this study. By contrast, Storfer et al. [Ambystoma mavortium stebbinsi, in the San Rafael Valley and foothills of the HMCH region. They found no support for isolation-by-distance among populations and instead found evidence that genetic drift and small population sizes are responsible for high levels of genetic differentiation among populations. We found that H. wrightorum population structure was most similar to H. arenicolor in the Huachuca Mountains [H. wrightorum’s only congener in the region.Our findings suggest significant genetic structure of l scales , 44. Howl scales –65. Thesr et al.  report mountains , a predoH. wrightorum populations, but additional landscape variables not considered in this study may also explain some portion of H. wrightorum genetic structure. Thus, these findings do not rule out the possibly important role of landscape variables other than distance in connecting populations.Our analyses comparing the relationship between genetic structure and landscape variables of distance, slope, canopy cover, and streams provide additional support for the role of spatial and landscape factors in the genetic structure we observed. Taken together, we found strong support for physical distance as a driver of genetic distance. We also found some support for the role of slope and canopy cover, indicating that populations that are closer together are more highly related, and that flatter, more forested areas may play a role in facilitating gene flow. Correlation between canopy cover and distance highlights the difficulty of interpreting collinear landscape distances . HoweverNe estimates had a high degree of uncertainty as evidenced by wide confidence intervals. This uncertainty may be due in part to migration and other demographic complexities that complicate the estimation of Ne, particularly for metapopulations. Although LDNe is considered one of the most reliable methods for estimating Ne with a single sample in time [Ne due to immigrants creating a larger total pool of parents than a sample with only local breeders [Ne calculated with LDNe due to linkage disequilibrium created by the mixture of multiple gene pools [Ne estimates [Ne values difficult regardless of the method employed, and the Ne estimates in this study should be interpreted with caution.Total and population-level  in time , migratibreeders . Given tne pools . We attene pools  which acstimates . HoweverNe estimates, our results suggest that previous assumptions of consistently small population sizes, with Nc estimates near or below 30 individuals [Ne / Nc ratio that is quite low [Nc of H. wrightorum populations in the study region are larger than the estimated Ne values reported here. Still, concern regarding the size of H. wrightorum populations in the region is warranted. We found small mean family sizes among larval samples, indicating that variance in reproductive success may be modest in this species. Thus, the ratio of Ne / Nc may be closer to 1 than for other amphibians. Mean Ne was less than 100 for the overall estimate and for half the populations we sampled, and the 95% confidence interval of Ne included values < 100 for all populations, as is typical for many pond breeding amphibians [Ne < 100 may indicate these populations are at risk of genetic depletion due to genetic drift and/or inbreeding [Ne and FIS indicates that inbreeding may occur in some populations.Despite uncertainty in our ividuals , likely uite low . Thus, iphibians . Ne < 10Ne, the dynamics of this system and small number of known populations indicate that these populations are of conservation concern. Ne values reported here should be considered in the context of temporal uncertainty, particularly because environmental instability, demography, and other factors that vary through time can influence population dynamics [H. wrightorum in the HMCH region occurs in a largely remote area with little human activity or development, many of the breeding ponds are frequented by cattle. The effects of grazing and other disturbances associated with livestock are currently not known for this amphibian. Predation by the invasive American bullfrog (Lithobates catesbeianus) could significantly reduce the number of adults at breeding ponds—particularly if choruses are small [H. wrightorum population with any evidence of a bottleneck, may have faced decades of predation from bullfrogs that established at a perennial pond just meters away. An intensive bullfrog eradication program began in the area in the early 2000’s [Batrachochytrium dendrobatidis (Bd), a disease associated with the decline and/or extinction of many amphibians worldwide [H. wrightorum [Hyla wrightorum from northern Arizona showed no increase in mortality risk when exposed to Bd in a controlled, experimental setting [Despite genetic connectivity between populations and evidence of higher than expected dynamics . Althougre small . Site 7,y 2000’s , and it orldwide , is docuorldwide  and is kightorum . Hyla wr setting , but theH. wrightorum, and we suggest additional research aimed at quantifying both the habitat requirements of and threats to this species to characterize suitable breeding habitat. Such efforts will help inform efficient and effective management of intermittent ponds to promote the persistence and continued connectivity of H. wrightorum populations within the HMCH region.On a regional scale, climate change will likely bring drier conditions to the southwestern United States  with theS1 Fig(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.S9 Table(DOCX)Click here for additional data file.S10 Table(DOCX)Click here for additional data file.


Height variation is known to be determined by both genetic and environmental factors, but a systematic description of how their influences differ by sex, age and global regions is lacking. We conducted an individual-based pooled analysis of 45 twin cohorts from 20 countries, including 180,520 paired measurements at ages 1–19 years. The proportion of height variation explained by shared environmental factors was greatest in early childhood, but these effects remained present until early adulthood. Accordingly, the relative genetic contribution increased with age and was greatest in adolescence (up to 0.83 in boys and 0.76 in girls). Comparing geographic-cultural regions , genetic variance was greatest in North-America and Australia and lowest in East-Asia, but the relative proportion of genetic variation was roughly similar across these regions. Our findings provide further insights into height variation during childhood and adolescence in populations representing different ethnicities and exposed to different environments. Galton6789Human height is a classic anthropometric quantitative trait for its ease of measurement, approximately normal distribution and relative stability in adulthood, and thus has been the target of extensive research across many fields of science. The study of height has a long standing tradition in genetics; in fact, the field of quantitative genetics was born out of studies of human height in the late 19Beside the genetic factors, a multitude of environmental factors can affect height. They can operate during the whole growth period, but infancy is probably the most sensitive phase regarding external influences111213Although the heritable nature of height has been recognized for more than one hundred years, only a few studies have explored in detail the genetic variation of height during childhood and adolescence. Twin studies have consistently estimated that the heritability of height is lowest (0.2–0.5) in infancy15161516151719201516171819202122Height is also a classic example of a sexually dimorphic trait; on average, men are taller than women in all human populations18192021Further, a greater mean height has been consistently observed in Western populations as compared with East-Asian populationsUsing height measures obtained from 45 twin cohorts in 20 countries participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins), we conducted an individual-based analysis of pooled twin cohorts (i) to analyze the genetic and environmental contribution to variation of height from 1 to 19 years of age; (ii) to explore sex-differences in these contributions over each year of age; and (iii) to assess whether this age pattern varies by geographic-cultural region .Descriptive statistics of height by age and sex for the pooled data  and by geographic-cultural region are presented in Univariate models for height were then conducted separately in the three geographic-cultural regions. Only the estimates of additive genetic factors are presented in Finally, we studied how age modifies the genetic and environmental variances of height by using gene-age interaction analysis, with data pooled across all age groups. The present study of 180,520 paired measurements from 86,037 complete twin pairs in 20 countries revealed that environmental factors shared by co-twins contribute to the inter-individual variation in height from infancy to early adulthood. The relative proportion of common environmental factors was greatest during the first years of life, representing almost half of the variation at age 1, and decreased over childhood and adolescence. The interpretation of these results, however, deserves some caution. It has been questioned whether twin studies are suitable for estimating heritability of height in infancy, since early growth patterns in twins differ considerably from singleton growth patternsThe influence of the shared environment on height variation up to 19 years, which is consistent with previous studies in adolescentset al.A recent and large meta-analysis of twin correlations and variance components for 17,804 traits carried out separately in four age groups  showed that the heritability estimate of height at 12–17 years was considerably greater than at 0–11 years15161820The pattern of total height variation across ages was largely driven by genetic variance. The most consistent result is the increasing genetic variance with age, reaching its peak at around 13 years in girls and 14 years in boys. After that point, even if mean height continued to increase, genetic variance started to decrease in such a way that in late adolescence the magnitude was similar to that before pubertal events start. Adolescence is characterized by the onset of puberty and the occurrence of growth spurts. Although a secular and population-dependent decline has been observed in the age at onset of pubertal growth spurt and peak height velocity since the mid 1900s3013et al.In spite of the largely similar age patterns observed in boys and girls, boys showed somewhat greater heritability estimates and genetic variation, especially in late adolescence. Greater heritability estimates in boys than in girls have previously been reported from birth through 19 yearsComparison between geographic-cultural regions showed that mean height was greatest in Europe, somewhat shorter in North-America and Australia and shortest in East-Asia, but total variance was largest in North-America and Australia. Accordingly, genetic variation was also greatest in North-America and Australia and lowest in East-Asia. However, the relative proportions of additive and environmental variations were more similar in the different geographic-cultural regions. These results are consistent with a previous comparative twin study which found that the mean and variance of height were larger in Caucasian than in East-Asian populations in adolescence, but the heritability estimates were still at the same levelThe study in Caucasian and East-Asian populations showed that approximately 91% of the differences in the total variance between these two population groups was attributable to genetic variancesThe main strength of the present study is the very large sample size of our multinational database of twin cohorts, with height data from 1 through 19 years of age, allowing a more detailed investigation of the genetic and environmental contributions to individual differences in height during childhood and adolescence than in the previous studies. Twin participants are from 20 different countries, thereby making it possible to stratify the analyses by regions representing different ethnicities and environments. Important advantages of individual-based data are better opportunities for statistical modelling and lack of publication bias. However, our study also has limitations. The equal-environment assumption, upon which twin methodology is based, assumes that MZ and DZ twins are equally exposed to environmental factors relevant to the outcome. If equal-environment assumption is violated, it should be seen as differences in variances between MZ and DZ twins, but we did not find such evidence. In the classical twin design phenotypic assortment increases DZ correlations and thus inflates the common environmental component when not accounted for in the modelling. Assortative mating is well recognized for height, and when the potential underestimation of heritability estimates was corrected using a sample of twins and their parentsOur findings provide further insights into height variation during childhood and adolescence in populations representing different ethnicities and exposed to different environments. Worthwhile objectives for future research are to study whether the same genetic and environmental factors contributing to height variation operate throughout time or new genes or new environmental factors start to operate at different ages, and to analyze the heritability of growth in height. Further, a major challenge in future studies with more information on birth and pregnancy related variables is to explore the reasons for the low heritability of height at young ages.In conclusion, environmental factors shared by co-twins exert their strongest influence on height variation in childhood, but these effects remain until the onset of adulthood. Genetic variation in height increased steadily during childhood and reached its peak at around 13 years in girls and 14 years in boys, which may be confounded with genetic variation in pubertal events. Especially in adolescence, there was a trend toward somewhat greater genetic variation in boys than in girls, and part of the genetic variation of height was sex-specific. Genetic variation of height was larger in North-America and Australia and Europe compared with East-Asia, but the relative proportions of genetic and environmental variations between these three geographic-cultural regions were roughly similar. These findings suggest that, in spite of different ethnicities and environmental exposures, genetic factors play a major role on height variation in adolescence and early adulthood, but environmental factors shared by co-twins are also important.All participants were volunteers and gave their informed consent when participating in the study. No experimental data were asked and thus we did not ask ethical approval. Only a limited set of observational variables and anonymized data were delivered to the data management centre at University of Helsinki. The pooled analysis was approved by the ethical committee of Department of Public Health, University of Helsinki, and the methods were carried out in accordance with the approved guidelines.This study is based on the data from the CODATwins project described elsewhereDuring the course of the study, we found that the heritability estimates of height were substantially lower in the Chinese National Twin Registry than in other East-Asian cohorts, as also reported previouslyTo analyze genetic and environmental influences on the variation of height, we used classic twin modelling based on linear structural equationsPrior to conducting the modelling, height values were adjusted using linear regressions and the resulting residuals were used as input phenotypes for the following analyses. Adjustment was carried out for birth year, exact age at the time of the measurement and study cohort within one-year and sex groups in univariate analyses, and for birth year and cohort in gene-environment interaction analyses.The ACE sex-limitation model was selected as a starting point of the univariate modelling based on the following criteria: (i) MZ within-pair correlations were clearly higher than DZ correlations consistent with the influence of genetic effects, (ii) the magnitude of the difference between MZ and DZ correlations (rDZ > 1/2 rMZ) indicated the presence of common environmental effects and (iii) the lower within-pair correlations for OSDZ than for SSDZ twins observed at most ages suggested the presence of sex-specific genetic effects See . PreviouIn order to study how age modifies the genetic and environmental variances of height, we additionally conducted gene–environment interaction modelling using age as an environmental modification factorHow to cite this article: Jelenkovic, A. et al. Genetic and environmental influences on height from infancy to early adulthood: An individual-based pooled analysis of 45 twin cohorts. Sci. Rep.6, 28496; doi: 10.1038/srep28496 (2016).


Culex quinquefasciatus mosquitoes can be found in almost every major city of Brazil and are vectors of filariasis and several arboviruses. Microsatellite markers have been widely used to uncover the genetic structure of various groups of insect populations. The aim of this study was to glimpse the genetic structure of Cx. quinquefasciatus in Brazil.loci.Nine populations were sampled across Brazil (one of them from a laboratory colony - COL) and another one from Argentina and process regarding the variability of six microsatellite loci revealed moderate population genetic structure (mean Fst = 0.12). Dendrograms of genetic distances evidenced two major population clusters, respectively corresponding to the northern and southern populations. The hybrid population Cx. pipiens/quinquefasciatus  and the colony population fell outside the major clusters. Those clusters were substructured and there was a significant correlation between genetic and geographic distances and environmental variables .The analyzed Cx. quinquefasciatus demographical diversity as well as their genetic variations patterns in Brazil so far unknown.Multilocus cluster Bayesian analysis confirmed that populations are mutually distinct, and the set of results point to genetic differences among populations. The presumable low gene flow among them may be due to the large geographic distances (>1000 km) and to the environmental heterogeneity of the sampled areas. The genetic structure observed in this study may lead to the best understanding of  Culex pipiens species complex sharing morphological similarities can be found in urban areas and are responsible for the transmission of several pathogens .,33.primeet al. [et al. [Amplification reactions (PCR) were performed as in Edillo et al.  and Smit [et al. , in an Ahttp://genepop.curtin.edu.au/) [st values were generated to survey the level of genetic structure between populations. Genetic isolation by geographic distances and pairwise multilocus number of migrants (Nm) between populations per generation were estimated in GENEPOP 4.0 utilizing regression of pairwise Fst/(1-Fst) and the geographical distances were shown for a straight-line in kilometers [Cx. quinquefasciatus. The selected parameters incorporate annual trends and environmental characteristics of collection sites  [Fragment sizes were determined with GeneMarker software package (Softgenetics). A parametric t-test was performed for each population, aiming to quantify genetic differentiation. Hardy-Weinberg equilibrium deviations and genetic variation indices were obtained utilizing GENEPOP V4.0 (edu.au/) ,35. Multedu.au/) ; Fst valt Index) . CorrelaThe software Structure 2.3.4  was utilloci. It was observed after Bonferroni correction [is value was 0.34. Out of the 150 possible tests, significant linkage disequilibrium was revealed only between locus ATG-09 and GT-14 in the RBR sample suggesting the loci were not in linkage  for the locus GT-14 and was not found in any other population. COL showed the same phenomenon with A-115 locus, where 28 alleles have 296 bp and can only be found in this population.The COL population was monomorphic, sharing the same allele in most individuals, in the st index (genetic heterogeneity) was used. The Fst mean value was 0.12 indicating moderate genetic structuring, pairwise Fst value comparisons between populations ranged from 0.08 to 0.29 and all of them were statistically significant ) and geographic distance between populations  as well as statistically significant correlation between genetic distance and Environmental Variables   for 10 populations of Cx. quinquefasciatus is presented in Figure The dendrogram of genetic distances based on the allelic variability of the six microsatellite Cx. quinquefasciatus’ populations (delta k = 10)    [The multilocus cluster Bayesian analysis of all 10 population samples together indicate genetic structuration among ) Figure A. A secolue = 2)  . RBR population is located in a remote region of Brazil where urban mobility is mostly by boat or plane, leading to an isolated scenario, which might have increased the genetic differentiation found in that population.Cx. Quinquefasciatus) [Located in the southern branch, the SVI population presented lower genetic variability probably because it is located in the southernmost border of geographic distribution (temperature fluctuations may be limitrophe for sciatus) . ComparaCx. quinquefasciatus/pipiens [Apart from the main dichotomy in the dendrogram, one cannot make deep interpretations regarding the lower clusters up to the present time. Concerning the discrepant samples, COL is a highly inbred and monomorphic laboratory colony and thus appeared to be eccentric; LPL is a hybrid population between /pipiens  and was st correlation showed significant differences among populations and thus low genic flow. The great distances (>1000 of range in km between populations) and distinct biomes might block migratory flows, if there is gene flow it occurs in a smaller geographic scale.Bayesian analysis confirmed the results obtained by the dendrogram and Floci, can be explained by a number of non-mutually excludable factors: Population substructure (Wahlund effect), inbreeding and genetic drift [loci are under selective pressure, although remote, cannot be discarded. Our interpretation of the results is equivalent to those of da Costa-Ribeiro et al. [The deficit of heterozygotes, found in all ic drift . The poso et al. .Cx. quinquefasciatus has a complex population structure and a broad genetic variability. This thought is compatible with the available epidemiological and biological data of the species. Cx. quinquefasciatus mosquitoes can be found in urban habitats where there is a great thermal range, manmade selective pressures and several kinds of available breeding sites, features that can lead to temporal variations of clustering and population differentiation [Aedes aegypti mosquitoes can be disseminated by ground transportation as roads and railways are likely to spread dengue virus beyond the normal reach of mosquitoes but are unlikely to spread dengue virus over large areas [Taken together, our exploratory findings suggest that ntiation . Insectsge areas .Cx. quinquefasciatus vector competence is genetically interconnected to Wuchereria bancrofti causing significant differentiation among populations [Interactions between vector, host and pathogen can change patterns of disease transmissibility resulting in selection, genetic drift and hybridization -45. Paraulations .Population genetic analyses can be useful to enlighten demographic and dispersal trends in mosquitoes, leading to uncovering disease patterns and epidemiological changes in transmission dynamics ,48.Anopheles culicifacies, an important vector of malaria in Southeast Asia.Sunil et al.  found thet al. [Culex tarsalis mosquitoes may have an association in the invasion of North America by WNV. Fonseca et al. [Culex pipiens complex from North America and Europe have distinct epidemiological patterns that can lead to changes in their vectorial capacity, becoming new efficient vectors if introduced into new areas.Kothera et al.  suggest et al.  state tha et al.  showed tCx. quinquefasciatus mosquitoes, as well as their territorial variations and genetic characteristics might help to predict the introduction of this mosquito into new areas that can lead to disease outbreaks, it could also help with the development of new control strategies. Further studies should aim at better understanding of population and demographical dynamics for smaller geographic scales where there is the possibility of migration and a more intense gene flow.The understanding of population structure of


DNA loci) is often measured. However, these loci are selectively neutral  and may not accurately reflect genomewide variation. Variation at functional trait loci, such as the major histocompatibility complex (MHC), can provide a better assessment of adaptive genetic variation in fragmented populations. We compared patterns of microsatellite and MHC variation across three Eastern Massasauga (Sistrurus catenatus) populations representing a gradient of demographic histories to assess the relative roles of natural selection and genetic drift. Using 454 deep amplicon sequencing, we identified 24 putatively functional MHC IIB exon 2 alleles belonging to a minimum of six loci. Analysis of synonymous and nonsynonymous substitution rates provided evidence of historical positive selection at the nucleotide level, and Tajima's D provided support for balancing selection in each population. As predicted, estimates of microsatellite allelic richness, observed, heterozygosity, and expected heterozygosity varied among populations in a pattern qualitatively consistent with demographic history and abundance. While MHC allelic richness at the population and individual levels revealed similar trends, MHC nucleotide diversity was unexpectedly high in the smallest population. Overall, these results suggest that genetic variation in the Eastern Massasauga populations in Illinois has been shaped by multiple evolutionary mechanisms. Thus, conservation efforts should consider both neutral and functional genetic variation when managing captive and wild Eastern Massasauga populations.Genetic diversity is fundamental to maintaining the long‐term viability of populations, yet reduced genetic variation is often associated with small, isolated populations. To examine the relationship between demography and genetic variation, variation at hypervariable loci (e.g., microsatellite  Small, isolated populations face increased risks of extinction due to complex interactions among demographic, genetic, and environmental factors , Piatt County (n = 35), and Cook County (n = 10). Some of the samples were known offspring of adult female Eastern Massasaugas included in this study and were removed from population‐level analyses to minimize bias. Samples were stored in 95% ethanol at −20°C until DNA extraction. Genomic DNA was isolated using DNeasy Blood and Tissue Kits .Tissue samples  were collected from Clinton County , 1 U of GoTaq DNA Polymerase, 200 μmol/L of each dNTP, 1.5 mmol/L of magnesium chloride (MgCl2), 1 μmol/L of each primer, and 50–100 ng of genomic DNA. Cycling conditions were as follows: initial denaturation at 94°C for 2 min; 4 cycles of 94°C for 20 sec, a locus‐specific annealing temperature (Table S1) for 20 sec, and 72°C for 5 sec; 40 cycles of 94°C for 15 sec, the locus‐specific annealing temperature for 20 sec, and 72°C for 5 sec; and a final extension at 72°C for 2 min. Amplicons were electrophoresed on a 1% agarose gel stained with ethidium bromide, visualized under ultraviolet light, and photographed with a digital image system . Successful reactions were analyzed using an ABI Prism 310 Genetic Analyzer . Microsatellite genotypes were determined using GeneMapper v4 (Life Technologies).We analyzed neutral genetic variation at six microsatellite loci: μL volumes containing 1× GoTaq Flexi Buffer (Promega), 1 U of GoTaq DNA Polymerase, 200 μmol/L of each dNTP, 1.5 mmol/L of magnesium chloride (MgCl2), 0.5 μmol/L of each primer, and 50–100 ng of genomic DNA. Cycling conditions were as follows: initial denaturation at 94°C for 5 min, followed by 35 cycles of 94°C for 30 sec, 50°C for 30 sec, and 72°C for 30 sec, and a final extension at 72°C for 7 min. Amplicons were electrophoresed on a 1% agarose gel stained with ethidium bromide, visualized under ultraviolet light, and photographed with a digital image system (Eastman Kodak). Bands of the appropriate size (~215 bp) were excised and combined with 100 μL of water.We used 454 deep amplicon sequencing to sequence a 166‐bp portion of MHC IIB exon 2. This gene fragment includes many of the putative antigen‐binding sites (ABS) predicted based on the human MHC IIB exon 2 protein structure , 1 U of GoTaq DNA Polymerase, 200 μmol/L of each dNTP, 1.5 mmol/L of magnesium chloride (MgCl2), 0.5 μmol/L of each primer, and 50–100 ng of genomic DNA. Cycling conditions were as follows: initial denaturation at 94°C for 5 min, followed by 30 cycles of 94°C for 30 sec, 58°C for 30 sec, and 72°C for 30 sec, and a final extension at 72°C for 7 min.In the second step, liquid from the excised bands of the first round of amplification was used as template for a second round of amplification. Here, each reaction included one of the 35 unique forward primers (Table S3). Each forward primer consisted of the Lib‐L/A adaptor, a unique 10‐bp multiplex identifier (MID), and the template‐specific sequence. Each reaction included the same reverse primer, consisting of the Lib‐L/B adaptor and the template‐specific sequence. Amplifications were performed in 30 Amplicons were visualized as previously described. If a single band of the appropriate size (~300 bp) was observed, the reaction was purified using AMPure beads . Purified amplicons were pooled at approximately equimolar concentrations, based on visual estimation on an agarose gel, and yielded five libraries, with each containing up to 21–35 unique MIDs. Each library was sequenced using Roche GS‐FLX Titanium chemistry on a ⅛ plate region by a commercial sequencing company .We used a stepwise procedure to filter artifacts and define MHC genotypes. First, we pooled the reads (raw sequences) generated from each of the five independent 454 sequencing runs. Reads were removed if they did not contain a perfect match to the forward primer, reverse primer, and one of the supplied MID sequences. Primer and MID sequences were trimmed from each read, and the frequency of each variant (unique sequence) corresponding to each unique MID was calculated using custom scripts in R v3  – the highest frequency at which a particular variant was observed within any single amplicon . Although this approach was originally designed to test for positive selection based on fixed differences among species  and Tajima's D for each population using the “pegas” package in R  microsatellite multilocus heterozygosity and the number of MHC alleles and (2) microsatellite multilocus heterozygosity and MHC nucleotide diversity.We obtained 729,085 reads from five 454 sequencing runs. Of these, 374,399 usable MHC reads were identified, consisting of 751 unique sequence variants. The remaining 354,686 reads were discarded because they (1) did not contain both primer sequences and one of the MID sequences or (2) were not identified as MHC based on BLAST analysis. The number of usable MHC reads per sample was high, but variable  when excluding four samples with poor sequencing depth. Of the 751 unique MHC variants, only 25 had maximum per‐amplicon frequencies ≥0.10 (10%) and were considered putative alleles . While these 25 putative alleles represented less than 5% of the unique variants (25 of 751 variants), they accounted for approximately 75% of the usable MHC reads .Sica‐DAB*01–*04, *07) were previously identified  leading to a frameshift. This sequence occurred in Clinton County, where it was present in >70% of individuals. However, Sica‐DAB*10 likely represents a pseudogene and was excluded from subsequent phylogenetic comparisons and tests of selection. The variation in the number of putative MHC alleles within individuals was not an artifact of read depth because it was not associated with the number of reads within individuals .Of the 25 putative alleles, five alleles (p‐distances ranging from 1.8 to 58.2% (mean ± SD = 36.9 ± 14.9%). We found evidence of positive selection acting on the entire sequence  when compared to the rest of the sequence . Maximum‐likelihood analyses also revealed evidence of positive selection , and model M8 was favored over model M7 . Bayes Empirical Bayes analyses identified six positively selected sites when comparing both sets of nested models: sites 37, 40, 46, 47, 51, 54  nucleotide positions were variable with pairwise Tamura–Nei genetic distances ranging from 0.6 to 57.6% (mean ± SD = 31.9 ± 15.2%). The 24 unique nucleotide sequences translated into 22 unique amino acid sequences , Piatt County (n = 17), Cook County (n = 6). Piatt County showed intermediate levels of rarefied allelic richness and expected heterozygosity compared with Cook and Clinton counties. However, randomization tests revealed significant differences (P < 0.05) only between Cook and Clinton counties, with Clinton County exceeding Cook County in both measures.We obtained genotypes for 134 Eastern Massasaugas from three Illinois counties at six microsatellite loci Table . For allSica‐DAB*03) was nearly ubiquitous, occurring in all but five individuals. We were not able to determine MHC genotypes for ten individuals from Clinton County, so MHC analyses were based on the following sample sizes: Clinton County (n = 79), Piatt County (n = 17), Cook County (n = 6). In each population, Tajima's D was significantly greater than one: Clinton County , Piatt County , Cook County . Eastern Massasaugas possessed between one and 12 MHC alleles, indicating the presence of at least six loci. The mean number of MHC alleles per individual was lowest in Cook County, intermediate in Piatt County, and highest in Clinton County. At the population level, MHC nucleotide diversity was higher in Cook County (π  =  0.216) than in Clinton County (π  =  0.188) or Piatt County (π  =  0.172).We found 18 putative MHC alleles in Clinton County , 11 alleles in Piatt County , and eight alleles in Cook County  or MHC nucleotide diversity .We found no evidence of any relationship between microsatellite and MHC variation within individuals. Multilocus microsatellite heterozygosity was not significantly correlated with MHC allelic richness  and is positively associated with effective population size Frankham . In addiThese Eastern Massasauga populations in Illinois represent a gradient of demographic histories: from relatively stable in Clinton County to declining in Piatt County to likely extirpated in Cook County . We found a general positive relationship between demographic history and microsatellite variation. Despite low statistical power, we found significant differences between Clinton and Cook counties in terms of microsatellite‐rarefied allelic richness and expected heterozygosity. This is likely due to the effects of inbreeding and genetic drift in this small population. Overall, these results are comparable to those reported previously for this species  was associated with reduced parasitism and increased longevity . Although this population is believed to be extirpated at this time, future work should examine other small and declining populations to determine whether this result could be an indication of increased selective pressure as the population declines  Clinton County, (B) Piatt County, and (C) Cook County, Illinois. Shading indicates private alleles.Table S3. Primer sequences used for PCR amplification and 454 sequencing of MHC IIB exon 2 in the Eastern Massasauga. Adaptor sequences are in blue, multiplex identifiers are in red, and template‐specific sequences are in black.Table S4. Summary of replicated MHC IIB exon 2 genotypes (n = 20) determined via 454 sequencing in the Eastern Massasauga.Table S5. Comparison of Eastern Massasauga MHC IIB exon 2 genotypes in three individuals based on cloning and Sanger sequencing and 454 sequencing. Alleles identified by both methods for each individual are highlighted.Table S6. MHC IIB exon 2 genotypes of three Eastern Massasauga mothers and their offspring. The prefix ‘Sica‐DAB*’ is omitted from allele names for brevity. The presence of a given maternal allele in an offspring genotype is indicated with a plus sign (+). Putative paternal alleles  are also listed for each offspring.Figure S1. Eastern Massasauga MHC IIB exon 2 variants with maximum per‐amplicon frequencies above 0.10  were considered putatively true alleles, while those below this threshold were treated as artefacts and excluded from subsequent analyses.Figure S2. The number of MHC IIB exon 2 alleles was not significantly correlated with sequencing depth (number of reads) per individual .Click here for additional data file.


Secale cereale L. accessions using 22 previously published simple sequence repeat (SSR) markers. The plant material included 367 rye accessions comprising historical and contemporary cultivars, cultivated materials, landraces, and breeding strains from the Polish breeding company Danko. The studied accessions represented a wide geographical diversity. Several methods were employed to analyze genetic diversity among the Secale cereale L. accessions and to determine population structure: principal coordinate analysis (PCoA), neighbor-joining (NJ), and Bayesian clustering. We also defined a core collection of 25 rye accessions representing over 93 % of SSR alleles. The results of these analyses showed that accessions from the rye gene bank are clearly divergent in comparison with materials received directly from European breeding companies. Our findings suggest also that the genetic pool of current rye cultivars is becoming narrower during breeding processes. The selected panel of SSR markers performed well in detection of genetic diversity patterns and can be recommended for future germplasm characterization studies in rye.The primary aim of this study was to estimate genetic diversity among The online version of this article (doi:10.1007/s11105-015-0896-4) contains supplementary material, which is available to authorized users. Secale comprises typical representatives of the Mediterranean flora, and its members are widely distributed from Central Europe and the Western Mediterranean through the Balkans, Anatolia, Israel, and the Caucasus to Central Asia. An isolated population also occurs in South Africa. The genus includes annuals, short-lived and long-lived perennials, wild, weedy, and cultivated taxa  is one of the most important cereal crops cultivated in Eastern and Northern Europe. It is characterized by the ability to produce high yields even when grown under environmental stress conditions, i.e., low temperatures, drought, and low soil fertility. The presence of disease resistance genes reduces the need for intensive chemical protection of this crop ; 27 population cultivars, 12 hybrid cultivars, and 26 breeding strains from European breeding companies; and 11 rye accessions from the collection of A. Lukaszewski from the University of California, Riverside (USA). Out of 367 accessions used in this study, 362 were examined previously using DArT markers . Equal amounts of DNA from the 96 plants representing each accession were pooled into one sample. DNA purity and concentration were evaluated using a NanoDrop 2000 spectrophotometer .Forty-two public SSR markers  under conditions specified by the high-stringency protocol of Pillen et al. , 1.5x DreamTaq buffer, 0.2 mM dNTP’s, 0.5 mM MgCln et al. . The ampn et al. . The conFor ease of analysis, we labeled rye accessions according to their geographical origin, source of the seeds, and assignation to one of the heterotic pools. We also conducted separate analyses only for accessions from breeding companies and from PAS BG.Based on the PCR results, a binary matrix was constructed, where the presence of an amplified product was scored as 1 and the absence of a product as 0. Because the templates used in SSR analysis were pooled DNA from 96 plants and more than two alleles per sample were observed, separate bands were treated as individual alleles. The bands were scored as present or absent, and allele frequencies within individual accessions were not established. The number of alleles, number of polymorphic alleles, proportion of polymorphic products , and percentage of frequent (appearing in >50 % of rye accessions) and rare (appeared in <5 % of accessions) alleles were counted. Polymorphic information content (PIC) was calculated according to the formula of Roy et al. .The total number of alleles, number of alleles with a frequency of <5 %, number of private alleles, number of alleles found in more than 25 and 50 % of the accessions from subgroups created based on source of seeds and improvement status, mean diversity, and unbiased diversity were calculated using GenAlEx 6.501  was calculated using Jaccard and Dice coefficients with NTSYSpc 2.1 software Rohlf . CorrelaK) capturing the major structure in the data, a burn-in period of 100,000 Markov Chain Monte Carlo (MCMC) iterations was used, with 100,000 run length and admixture model following the Hardy-Weinberg equilibrium. Five independent runs were performed for each simulated value of K, ranging from 1 to 20. The most likely number of K was determined using the DeltaK method in Structure Harvester  in GenAlEx 6.501.M) algorithm implemented through a modified heuristic algorithm in PowerCore 1.0 was used  (Table h = 0.113), while this value was nearly two fold higher for the collection of A. Lukaszewski (h = 0.218).Analysis of the total allele pattern within groups of accessions sorted according to the source of the seeds and improvement status Table  showed tr = 0.991 and P = 0.001  and cultivars from PAS BG (34 %), especially from Western and Central Europe. Only cultivar Gonello (KWS Lochow) belonged to the P2 population. Breeding strains from the company Danko were the most homogeneous group and were characterized by an inferred ancestry level of >80 %. The P1 population also contained landraces, cultivated materials from European countries, and accession from the A. Lukaszewski collection.Population P2 was comprised mainly of landraces from PAS BG (79 %), while the representation of cultivars and cultivated materials from PAS BG was relatively lower: 8 and 10 %, respectively. The geographical origins of the majority of accessions classified as P2 were Asia, the Balkans, and Southern Europe. The remaining P2 accessions were cultivars and cultivated materials originating from Eastern and Central Europe, and South and North America. Two accessions from the A. Lukaszewski collection originating from North America were also assigned to P2.Accessions characterized by mixed ancestry were mainly from PAS BG (90 %). The geographical origin of accessions with mixed ancestry was very diverse.Several clusters were visible in the NJ dendorgram Figs.  and 3. TTwo groups could be distinguished in the PCoA plot Figs.  and 5. APCoA comparing cultivars and breeding materials showed clear dissimilarity between accessions from the gene bank and from breeding companies. Two separate clusters were visible both in the dendrogram Fig.  and PCoA1) cultivars were dispersed throughout the PCoA plot.In the PCo analysis with labeling according to the assignation to one of the heterotic pools (Petkus or Carsten), the majority of accessions with confirmed Petkus pedigree were closely grouped (Online Resource P < 0.001). The pairwise PhiPT value  was 0.137 and indicated relatively high degree of differentiation between populations P1 and P2. Much greater proportion of variation within than among populations was found for groups of accessions from different sources and with different improvement status: 87 and 13 %, respectively (P < 0.001). When accessions were grouped based on geographical origin, these values were 92 and 8 % (P < 0.001). Pairwise PhiPT values estimated between groups of accessions with different source and improvement status indicated a wide range of genetic differentiation between them ranging from low (0.073) between cultivated materials and landraces from PAS BG to very high (0.275) between breeding strains from Danko and accessions from the A. Lukaszewski collection. In the case of plants grouped according to geographical origin, very low 0.003 PhiPT, indicating little genetic differentiation, was detected between accessions from South America and Northern Europe. The highest genetic differentiation (PhiPT = 0.217) was found between accessions from Western Asia and Central Europe  were selected as core entries. Core collection entries represented all sources and geographical origins .In general, the presented results were largely consistent with those of Bolibok-Brągoszewska et al. . In the In our study, we did not analyze the genetic diversity of rye accessions on a single plant basis. Instead a bulking strategy with 96 plants for each accession pooled into one sample was applied. In consequence of DNA pooling some information is lost, for example, it is not possible to estimate allele frequencies within individual accessions. While this limitation is true for both SSR markers used in the present study and for DArT markers applied earlier  which indicates their high informativeness. The average percentage of polymorphic alleles for the set of 22 markers was also high (93 %). This was predictable because the public markers were not selected randomly, but based on the results of analyses using six diverse rye accessions and 42 SSR markers. The high values of the marker informativeness parameters and the congruency of the results reported here with the results obtained based on over 1000 genome-wide DArT markers  and also from population and hybrid varieties from other breeding companies. Similar results for Gonello were obtained earlier using DArT markers . While this result could be attributed to a mistake in a labeling of seed samples, an alternative explanation may be found in the work of Chebotar et al. , where iAs discussed above, factors such as reproduction or the manner of storage of plant material can greatly influence genetic variation. This may reflect differences in the procedures of plant reproduction employed by gene banks and breeding companies. In the case of open-pollinated plants, it is important to consider regeneration management in ex situ collections, particularly the optimal population size and distance between regeneration plots  and unbiased diversity (uh = 0.118) were the lowest in this germplasm group. Evidence indicating low genetic diversity in Polish rye was previously obtained by Rafalski et al. . Genetic similarity within cultivars from breeding companies and within breeding strains from Danko was relatively high. It is also noteworthy that no unique alleles were observed in accessions obtained from Danko and the values for mean diversity  is one of the major determinants of the population structure in cereals 367 Online Resource 2SSR markers used in preliminary analyses. (PDF 83 kb)Online Resource 3The result of Mantel test showing a strong positive correlation between Jaccard and Dice coefficient. (PDF 541 kb)Online Resource 4GS values (according to the Jaccard coefficient) for pairs of accessions. (PDF 6710 kb)Online Resource 5Delta K values (number of populations assumed) ranging from 1 to 20. (PDF 1347 kb)Online Resource 6Results of Analysis of Molecular Variance. (PDF 34 kb)Online Resource 7PCoA of 367 rye accessions based on 22 SSR markers. Accessions labeled according to their pedigree. (PDF 1369 kb)