Fishing may induce neutral and adaptive evolution affecting life-history traits, and molecular evidence has shown that neutral genetic diversity has declined in some exploited populations. Here, we theoretically study the interplay between neutral and adaptive evolution caused by fishing. An individual-based eco-genetic model is devised that includes neutral and functional loci in a realistic ecological setting. In line with theoretical expectations, we find that fishing induces evolution towards slow growth, early maturation at small size and higher reproductive investment. We show, first, that the choice of genetic model (based on either quantitative genetics or gametic inheritance) influences the evolutionary recovery of traits after fishing ceases. Second, we analyse the influence of three factors possibly involved in the lack of evolutionary recovery: the strength of selection, the effect of genetic drift and the loss of adaptive potential. We find that evolutionary recovery is hampered by an association of weak selection differentials with reduced additive genetic variances. Third, the contribution of fisheries-induced selection to the erosion of functional genetic diversity clearly dominates that of genetic drift only for the traits related to maturation. Together, our results highlight the importance of taking into account population genetic variability in predictions of eco-evolutionary dynamics. Anthropogenic activities do not only affect population dynamics in the wild, but can also have evolutionary consequences. Harvesting, habitat fragmentation, pollution and many other pressures affect the genetic composition of populations through selection for certain trait values or through altered rates of genetic drift , additive genetic variance is, along with neutral genetic variance, expected to increase logistically with effective population size, because of weaker drift and an increased number of mutations . Their genotypes comprise a set of neutral loci, to study neutral evolution, and a set of functional loci, to investigate the combination of neutral and adaptive evolution of life-history traits. Functional loci code for the life-history traits of individuals and thus, together with plastic responses of traits to environmental variation, affect the life-history processes of growth, maturation, reproduction and mortality, which jointly determine population dynamics. Ultimately, individual fitness, controlling the production of offspring to which genetic material is transmitted, is determined by an individual's functional loci and environment. The latter is altered by fishing, the emerging population dynamics through density dependence, and environmental stochasticity affecting resources are available for growth and recruitment.Below we describe in turn the genetics of neutral markers and life-history traits, phenotypic expression, the associated individual-level life-history processes from which population dynamics emerge, and the measures of population genetic diversity used to monitor evolutionary dynamics  and the fusion of two randomly picked gametes creates a diploid offspring.To assess genetic drift, each individual carries 30 neutral loci. Genetic diversity at each neutral locus is represented by 10 possible allelic states distributed in the population, which mimics allelic diversity at microsatellite markers . We denote by zx,k,1(i) and zx,k,2(i) the two alleles at a given locus Lf. For simplicity, loci coding for the same trait has the same number of possible alleles. To translate these integers into two allelic values Ax,k,1(i) and Ax,k,2(i), we assume an initial minimum and maximum genotypic value, Ax,min and Ax,max, respectively, for each trait x in the population  of trait x is then given by the sum of allelic values across locifor g, α, χ, y, and s) deviate from their genotypic values, reflecting micro-environmental variation and nonadditive genetic effects (dominance and epistasis). This variation is described by an expression noise ɛx with x for individual i is then obtained from the following generic equation,ɛx(i) is randomly drawn, once per lifetime, from a normal distribution with mean 1 and a standard deviation specific to each trait x  is also affected by population-level density dependence,B(t) is the population biomass in year t and 1/ρ is the total population biomass at which density dependence halves the juvenile growth rate.Besides expression noise, the juvenile growth rate i in year t is characterized by its five life-history traits , α(i), χ(i), y(i) and s(i)); its age a, its length ℓ and its age at maturation am(i). Together, these determine the four annual life-history processes: somatic and gonadic growth, maturation, reproduction and mortality.An individual w as wβ, where β denotes the production exponent. Juveniles allocate all energy available to somatic growth, whereas adults start by allocating all energy to somatic growth and switch to allocating all energy to gonadic growth after a fraction p of the productive season. p is given byα(i) and χ(i) lie between 0 and 1  of the productive season to somatic growth; this proportion then decreases geometrically with an annual ratio χ(i) as the individual ages. This is consistent with von Bertalanffy adult growth.Energy allocation between growth and reproduction is described following Quince et al.'s  biphasicβ of 2/3  equals 0; after maturation, it is a function of body length at the end of each productive season,γ is the ratio of the wet-weight energy density of somatic tissue to gonad tissue. The gonado-somatic index (GSI) is defined as the ratio between gonadic weight and somatic weight, Γ = G/w.Before maturation, the gonad weight y and slope s. The maturation probability is then given by the logistic equationp50 = y(i) + s(i)a is individual i 's length at 50% maturation probability. The parameter δ is determined by the PMRN envelope width ω,p) = ln (p/(1 – p)), and pup and plow are the upper and lower probability bounds, respectively, for which the PMRN envelope width is defined.We model sexual maturation using probabilistic maturation reaction norms .Maturation is modelled as a stochastic process of Bernoulli trials, taking place if a number randomly drawn from a uniform distribution between 0 and 1 is smaller than Q = G/wegg. From this, the total number of newborns in each year, N0, is determined by a Beverton–Holt recruitment function (Beverton and Holt ɛR(t) is normally distributed , equalling the proportion So far, we have only defined the number of newborns in each year. Each newborn is assigned two parents, selected in proportion to their gonad size through a stochastic process of Bernoulli trials. The adult having the largest gonad weight is determined in each year. Then, an individual is randomly drawn (with replacement) and a number is randomly drawn from a uniform distribution between 0 and this maximal gonad weight. If this number is less than the drawn individual's gonad weight, this individual will be selected as a parent. Hence, the higher an individual's fecundity, the more likely it is to become a parent. The random draws continue until enough parents have been selected. Individuals selected as parents are then randomly combined into pairs for each recruit. Therefore, on average, each individual d0 originates from diseases, senescence, or any stochastic source of mortality unrelated to body size. Second, size-dependent predation generates mortality decreasing with body size according toThree different sources of natural mortality are considered. First, a constant mortality cs is the maximum instantaneous predation mortality rate and ℓs is the size at which the predation mortality is decreased by the factor 1/e. Third, a growth-dependent mortality,cg denoting the minimum instantaneous growth-dependent mortality rate and g0 the growth rate at which the growth-dependent mortality is increased by the factor e, accounts for the trade-off between growth and survival. Such a trade-off can originate physiologically when faster growth is achieved at the expense of less energy being available for maintenance  = 1 − exp T). As for maturation and reproduction, individual mortality is modelled as a stochastic process of Bernoulli trials and occurs if a number randomly drawn from a uniform distribution between 0 and 1 is lower than D.where We follow the effect of fishing on neutral and functional genetic diversity using three genetic diversity indices.Ne using the temporal method  is the frequency of allelic state l at locus k at time t, and t1 and t2 are two sampling years, the effective population size is then obtained aswhere ΠT is the generation time in years, and N1 and N2 are the population sizes at times t1 and t2, respectively  of any trait x(i) for each individual i, the population's mean genotypic value VA(x) are directly calculated from the population composition in each year, and the heritability h2(x) is obtained asKnowing the genotypic value k,l(t) is the frequency of allelic state l at locus k at time t.To assess the relative contributions of genetic drift and selection imposed by fishing on the evolution of life-history traits, we estimate the expected heterozygosity over neutral loci on the one hand eqn  and overExpected heterozygosity will decrease as variability in allele frequencies, and thus genetic diversity, decreases owing to genetic drift and/or selection. Both evolutionary forces affect functional diversity, while neutral heterozygosity depends only on genetic drift, and thus constitutes a baseline allowing detecting the effects of selection whenever functional heterozygosity differs from this baseline.S(x) are estimated in each year by inverting the breeder's equation R(x) = h2(x)S(x), where heritability h2(x) is estimated as described above and the selection response R(x) is computed as the difference in mean trait value between the new cohort and the population that produced it. Mean-standardized selection differentials are also calculated, by multiplying selection differentials with the trait's mean and dividing by its variance  with parameters taken from the literature or, when not available, fixed to values yielding plausible emergent properties and patterns; for more details, see TableWe model a population resembling North Sea cod  = Ag(i), and its randomly attributed age a, while neglecting density dependence and expression noise, so that ℓ = ℓ0 + Ag(i)a.The initial population is comprised of 220 000 juveniles. For each individual, alleles at each neutral and functional locus are randomly drawn from a uniform distribution between 1 and 10 . Juveniles are initially given a random age between 2 and 6 years old, to avoid the high mortality at younger ages . For each juvenile H takes values from 0.2 to 1 . Effective population sizes after recovery are larger when fishing intensities are higher  = −0.32, P = 0.74; χ: t(98) = 0.83, P = 0.41; y: t(98) = −2.21, P = 0.03; s: t(98) = −1.5, P = 0.14), except for growth selection differentials (g: t(98) = 98.1, P < 2.2 × 10−16), which are positive with a mean of 0.1  = −3.46, P < 0.001; α: t(99) = −13.41, P < 2.2 × 10−16; χ: t(99) = −5.3, P < 10−6; y: t(99) = −38.9, P < 2.2 × 10−16; s: t(99) = −8.1, P < 10−11). The initial decrease is followed by an increase for the PRMN intercept and slope  = 3.04, P = 0.003; Fig.α: t(99) = 2.6, P = 0.01; Fig.After fishing, selection differentials increase and slightly exceed preharvest values for all traits Fig.A–D excepMean-standardized selection differentials Fig.F, which Before harvesting, the dynamics of additive genetic and phenotypic variances of all traits are steady, indicating the absence of selection Fig.A–E. Heri2 in genetic variance for the highest fishing mortality  per generation under genetic drift  the influence of environmental variability on recruitment  are required to reduce it by 2% when Ne = 3000, which is the lowest Ne value observed in our model under strong fishing intensity. It is therefore unlikely that in large marine fish populations, fisheries-induced genetic drift significantly reduces functional genetic variation.In our results, losses of genetic variability due to pure genetic drift  are extremely weak, which is as expected at the observed range of effective population sizes: given that heterozygosity decreases by the factor 1−1/2We also find that differences between the temporal trends of neutral and functional expected heterozygosity increase when fisheries-induced changes in the mean genotypic values of life-history traits are larger: the loss in genetic variability at neutral and functional loci is almost equal for most traits, except for the PMRN intercept. Therefore, strong stabilizing selection obviously occurs for the latter, whereas for the other four traits, losses in functional genetic diversity remain very small and equivalent to losses in neutral genetic diversity.It also interesting to consider whether the observed fisheries-induced evolutionary responses of mean genotypic life-history trait values are due to selective pressures or genetic drift or a mixture of both. As the observed directions of these evolutionary responses are adaptive , they are most likely due to fisheries-induced selection. Moreover, genetic drift modifies allelic frequencies randomly, thus equally leading to beneficial or detrimental changes in individual fitness, which would tend to counteract the effects of selection. This further supports the interpretation that the evolutionary dynamics of at least the mean genotypic values of life-history traits are due to fisheries-induced selection, in agreement with new experimental results using guppies as model species (Van Wijk et al. Besides these considerations, the co-variation observed between heterozygosity of neutral and functional loci suggest that the temporal dynamics of neutral genetic diversity might possibly be a useful surrogate of the temporal dynamics of functional genetic diversity (Merilä and Crnokrak Drosophila melanogaster (e.g. Robertson −9 per locus per generation; Li Two main results of our study are that the observed losses in additive genetic variance and functional allelic diversity are permanent, prevailing even after fishing is stopped, and that the resulting loss in evolutionary potential impedes the genetic recovery of life-history traits. Long-term selection has been shown to deplete additive genetic variance in animal models such as Our results show the importance of managing genetic impacts of fishing on exploited populations. First, fisheries-induced evolution may be detrimental for a stock's productivity, as population biomass does not fully recover to its prefishing level after fishing is stopped . This isMitigating fisheries-induced genetic drift is important for reducing the potential risk of inbreeding and its impact on evolutionary potential. Although conflicting empirical results emerge from different estimates of effective population size (but see meta-analysis by Pinsky and Palumbi Regarding the reduction of functional diversity due to fisheries-induced adaptive evolution, our findings for the PMRN intercept highlight the importance of mitigating selection on maturation imposed by fishing gears, both to limit changes in mean genotypic and phenotypic values of life-history traits, and to avoid losses of evolutionary potential. A theoretical study on Arctic cod has shown that fishing with a dome-shaped size-selectivity curve could mitigate the evolution of mean age and size at maturation (Jørgensen et al.


Anopheles darlingi is the main malaria mosquito vector in the Amazonia region. In spite of being considered a riverine, forest-dwelling species, this mosquito is becoming more abundant in peri-urban areas, increasing malaria risk. This has been associated with human-driven environmental changes such as deforestation.A. darlingi from seven localities along the Madeira River, Rondônia (Brazil), collected in the early and late periods of the rainy season.Microsatellites were used to characterize A. darlingi; the other (subpopulation B) was associated with the early rainfall period and is probably more adapted to drier conditions by exploiting permanent anthropogenic breeding sites. Results suggest also a pattern of asymmetric introgression, with more subpopulation A alleles introgressed into subpopulation B. Both subpopulations (and admixed mosquitoes) presented similar malaria infection rates, highlighting the potential for perennial malaria transmission in the region.Two genetically distinct subpopulations were detected: one (subpopulation A) was associated with the late rainfall period and seems to be ecologically closer to the typical forest A. darlingi adapted to different periods of rainfall may promote a more perennial transmission of malaria throughout the year. These findings, in a context of strong environmental impact due to deforestation and dam construction, have serious implications for malaria epidemiology and control in the Amazonian region.The co-occurrence of two genetically distinct subpopulations of  Anopheles darlingi is a major malaria mosquito vector in the Americas. It is of particular importance in the Amazon basin where most malaria cases occur in South America[Plasmodium malaria parasites. Anopheles darlingi is typically described as a lowland, riverine, forest-dwelling species[ America,2. This  species. However species,3-6. Mor species.A. darlingi being a species complex has been raised by many authors. Charlwood[A. darlingi from central Amazon and further north (Venezuela and Guyana). However, several isozyme and DNA-based studies reported levels of genetic differentiation consistent with a monotypic species throughout the species' range[A. darlingi did not provide support for speciation within the taxon[A. darlingi populations over broad geographical ranges  but mainly due to isolation by distance[Due to its intrinsic diversity the question of harlwood found chs' range-11. Alths' range-14, comphe taxon. Nucleardistance-17.A. darlingi distribution and abundance[A. darlingi populations is seasonal and dependent upon the availability of larval habitats[vice versa[Precipitation is considered to be the main ecological variable influencing bundance. The annhabitats. In rivehabitats, and urbice versa,20. In dice versa,21.A. darlingi may result in changes in the seasonality patterns of this mosquito with implications for malaria transmission. Such is the case of the region of Porto Velho, in Rondônia state, Brazil. This city lies along the Madeira River, an important tributary of the Amazona River. A major environmental disturbance is expected in this region due to the construction of two hydroelectric power dams along the river, with a planned total flooded area of 380 sq km, which will likely impact local mosquito populations.Variable density peaks may be the result of seasonal fluctuations of the same population or the consequence of the presence of two differentially adapted subpopulations of the same species. In both cases, there is a growing concern that the increased anthropogenic influence in riverine, forested habitats of A. darlingi from the region of Porto Velho (RO). Results suggest a season-dependent genetic partition, with two distinct mosquito subpopulations that display similar Plasmodium infection rates.In the present study, microsatellite loci were used to analyse genetic variation of Amazonian ca. 436,000 inhabitants) is the capital city of the state of Rondônia (Brazil), which lies along the shores of Madeira River in the western part of the Amazonian forest, close to the border with Bolivia. Most of the human population lives on the right bank of the Madeira River, while the left bank is sparsely populated with small farms and settlements created by the National Institute of Colonization and Agrarian Reform. The state is one of the most affected by deforestation in Brazil[Anopheles darlingi abundance is seasonal and follows the rainfall regime. During the rainy season, human-biting mosquito densities reach a peak in March-April, with over 30 bites per human per hour, whereas in the dry season biting rates fall to nearly zero[Porto Velho  corresponding to the end of the rainy season and when e region; OctoberNyssorhynchus[Anopheles darlingi specimens were preserved individually in tubes with 70% isopropyl alcohol.Collected mosquitoes were morphologically identified to species using the identification keys of the subgenus of orhynchus. AnophelDNA was extracted from each mosquito (whole body) using 5% Chelex solution (BioRad), according to the manufacturer's recommendations and eluted in 200 μl of double-distilled water.et al.[et al.[2, 200 μM dNTPs, 0.5 μM of each primer, 0.5 U of Taq polymerase and 1 μl of DNA template. Cycling conditions included an initial denaturation at 94°C for 5 min, followed by 30 cycles at 94°C for 30 sec, annealing  and the species-specific nucleotide sequences of the 18S rRNA genes of Plasmodium falciparum (5’-CAATCTAAAAGTCACCTCGAAAGATG-3’) and Plasmodium vivax (5’-CAATCTAAGAATAAACTCCGAAGAGAAA-3’)[The detection of GAAA-3’). Each 15He) allele richness (Rs) and private allele richness (Ps) were calculated in FSTAT v 2.9.3.2[Estimates of expected heterozygosity . The number of genetic clusters (K) was inferred using the ΔK statistic[K (20 runs) was compiled by the Greedy method implemented in CLUMPP software[Tq) of 0.80 following the recommendations of Vaha and Primmer[The genetic structure of the stimates and by astimates, both avstimates was alsotatistic with thetatistic. The infsoftware. Individ Primmer.5 iterations. Individual assignment to classes was based on a posterior probability threshold, Tq > 0.5.The Bayesian method implemented in NewHybrids was usedIn order to detect recent population perturbations, Wilcoxon signed-ranks tests of heterozygosity were performed with BOTTLENECK 1.2.02. CalculaA. darlingi were analysed in this study. Of these, 158 were collected in the early rainfall period whereas 282 were collected in the late rainfall period . Significant departures from H-W equilibrium were detected at loci ADC107n  and ADC29 (in 11 samples) suggesting the presence of null alleles  to 44 (ADC01). Exact tests of LD showed one significant association for the pair ADC29-ADC110 in the sample of Amazonas, early rainfall period (He) and allelic richness (Rs) per locality and sampling period are presented in Table Rs over loci ranged from 9 to 10. The mean He over loci ranged from 0.142 in Jaci Paraná to 0.838 in Santo Antônio . The largest difference in He between sampling periods was found in the most inland sample of Jaci Paraná, with an estimate of 0.142 in the early rainfall and 0.794 in the late rainfall.Estimates of expected heterozygosity (K = 2), hereafter denoted as subpopulations A and B . When these individuals were excluded and subpopulations A and B were analysed separately, each consisted of a single genetic cluster (best K = 1). There was no particular association between these subpopulations and any of the localities sampled . When all individuals were included significant FST was obtained in two (P2 and P9) out of the eight loci analysed  were removed from the analysis , and six out of eight loci showed a significant FST  ranged from 0 to 0.036 in subpopulation A  was confirmed by a significant estimate of global Furthermore, the component of variance between sampling periods was higher than that among sampling sites within each subpopulation when admixed individuals were excluded, showing 2.87% of genetic variation between sampling periods, 14 times higher than the non-significant percentage of variation among populations within subpopulation , mean private allele richness (Wilcoxon signed-ranks test: P = 0.575) or expected heterozygosity (Wilcoxon signed-ranks test: P = 0.735).Table Since only two individuals were assigned to subpopulation A in early rainfall sampling period, heterozygosity tests implemented in BOTTLENECK were performed on three samples: subpopulation A , subpopulation B  and subpopulation B . Wilcoxon tests revealed a significant deficit of heterozygotes indicative of recent population expansion in subpopulation A while all other tests were non-significant , Vila Candelária  and Teotônio . Infection rates were comparable between the two sampling periods: 3.2% (five out of 158) in the early and 3.9% (11 out of 282) in the late rainfall . Plasmodium falciparum was the predominant species, occurring in 14 (87.5%) of the positive mosquitoes. There was also one mosquito  infected with P. vivax and one P. falciparum/P. vivax mixed infection .Of the total mosquito DNA samples analysed (N = 440), 16 (3.6%) were positive for A. darlingi genetic subpopulation, overall Plasmodium infection rate was higher in subpopulation A (4.6%) when compared to subpopulation B (3.0%) or admixed individuals (3.0%) but this difference was non-significant (Fisher’s exact test: P = 0.692). For subpopulation B and admixed individuals, it was possible to compare infection rates between seasons but no significant differences were found (Table P = 0.430).Concerning each tion A 4.% when coA. darlingi near Porto Velho (RO), two genetically differentiated subpopulations associated with different seasonal sampling periods were detected. Subpopulation A is almost exclusively found during or at the end of the rainy season. However, subpopulation A was less abundant in the inland locality (Jaci Paraná) where it appeared to be replaced by subpopulation B earlier in the rainy season than in riverine localities. In this sense, subpopulation A seems to be ecologically closer to a typical forest/riverine A. darlingi population that displays the highest mosquito density after the peak of rainfall[A. darlingi reaches its late rainy season peak. A previous mtDNA-based study conducted in the same region also reported a seasonal difference in the mosquito population of Portuchuelo, a riverine village ca. 30 km northeast of Porto Velho, but no seasonal mtDNA differences were found in the other localities analysed[FST estimates among samples at smaller distances (up to 80 km) were comparable with the FST estimates within subpopulations obtained in this study. However, none of these microsatellite-based studies compared samples from the same locality at different seasons.In Amazonian, suburban, riverine populations of rainfall. In contanalysed. Other sanalysed-17. In tA. darlingi densities decline to residual values[Two hypotheses can be proposed to explain the observed pattern of seasonal genetic variation. The genetic differences between sampling periods may reflect drastic fluctuations in the effective population size of a single genetic entity caused by the transition between rainy and dry seasons. This would agree with the marked seasonal variation in mosquito abundance reported for this region, where during the dry season l values. If thisA. darlingi. Subpopulation A would represent a subpopulation more dependent of the rainfall regime, probably adapted to exploit temporary larval habitats in forested, riverine, flooded areas. The bio-ecology of this subpopulation would thus be closer to the typical A. darlingi. This would agree with its predominance at the end of the rainy season, where a signal of population expansion was detected and the decline over the dry season as evidenced by its near absence from collections at the early rainfall period. On the other hand, subpopulation B would correspond to a subpopulation more adapted to the dry season, in agreement with its predominance in collections at the onset of the rains. This subpopulation could have derived from the typical subpopulation A through adaptation to more permanent anthropogenic larval habitats, in urban and semi-urban settings. This would result in the maintenance of a resident A. darlingi population in urban areas during the dry season with a relatively stable effective population size. In the urban and suburban localities sampled, this population should thus be the first to peak at the start of the rainy season while subpopulation A would peak later in the rainy season when the availability of temporal larval habitats is highest in the forest/riverine flooded areas surrounding these localities.The other hypothesis assumes the occurrence of two genetically distinct and partially isolated subpopulations of A. darlingi is large, ranging from typical natural breeding sites such as the margins of slow flowing streams, river arms and lagoons, to more human-dependent sites such as irrigation canals, flooded crop fields and mine excavation pools. Such diversity in larval ecology may set a ground for genetic divergence driven by ecological adaptation at the larval stage. This was the case of the recent radiation of the malaria vector Anopheles coluzzii  within voidance. In addiollution-49. ThesA. darlingi is a stable condition or if it was a sporadic/transient observation. The complete genome sequence of A. darlingi has been published recently[A. darlingi in the region.Further studies involving additional mosquito surveys in the region of Porto Velho are required to validate the proposed hypotheses. These studies will also allow verifying if the observed pattern of seasonal genetic partitioning within recently. This reThe vast majority of individuals within subpopulation A were classified as pure-bred while the genetic background of subpopulation B was more admixed, with 48% of individuals classified as hybrids. The different proportions of admixture within subpopulations suggest a pattern of asymmetric introgression, with more subpopulation A alleles being introgressed into subpopulation B. This pattern is consistent with the hypothesis of the presence of a resident subpopulation (subpopulation B) in the urban setting that is seasonally exposed to a genetically distinct subpopulation (subpopulation A) promoting local hybridization during the rainy season. It remains to be determined which factors may determine the unbalanced genetic exchange between subpopulations A and B.Culex pipiens[A. gambiae[Asymmetric introgression is not an uncommon event in mosquitoes. Similar findings have been reported between closely related taxa in x pipiens,51 and A. gambiae. These p. gambiae. While t. gambiae, this re. gambiae,53.FST estimates, there were two loci (P2 and P9) that displayed the highest differentiation between subpopulations. These loci may be located near genomic regions under divergent selection that may harbour genes associated with phenotypic differences between the subpopulations that may promote sympatric divergence with gene flow[From the locus specific ene flow,55. It iene flow and theyA. darlingi appears to be adapting to human modified habitats by deviating its breeding preferences into more permanent larval habitats, which may lead to an increased persistence during the dry season. This adaptation may have important consequences in regional malaria transmission patterns. Both subpopulations were found infected with malaria parasites at comparable rates, with the highest values occurring at the end of the rainy season, in accordance with the seasonal patterns of malaria transmission intensity characteristic of the Amazonian region[A. darlingi. The co-occurrence of both subpopulations in this region may thus promote a more perennial transmission of malaria throughout the year, with obvious implications for malaria epidemiology and control.The findings of this study suggest that n region. HoweverA. darlingi populations in this malaria endemic region.Several studies have demonstrated that deforestation and human colonization of deforested areas have a strong impact in mosquito populations, with an increase in larval breeding and human-biting activity,57,58 thA. darlingi adapted to different periods of rainfall may promote a more perennial transmission of malaria throughout the year. These findings in a context of strong environmental impact due to deforestation and dam construction preclude serious implications for malaria epidemiology and control in the Amazonian region.The co-occurrence of two genetically distinct subpopulations of mtDNA: Mitochondrial DNA; INMET: Instituto Nacional de Meteorologia; PCR: Polimerase Chain Reaction; rRNA: Ribosomal ribonucleic acid; dNTPs: Deoxynucleoside triphosphate; SMM: Stepwise Mutation Model; TPM: Two Phase Model; He: heterozygosity, heterozygosity (He) allele richness (Rs) and private allele richness (Ps).The authors declare that they have no competing interests.All the authors collaborated on the work presented in this study. AFA and PEMR defined the research theme; LHSG was responsible for the mosquitoes collection; AFA designed the methods, performed the experiments and interpreted the results; JLV performed some of the experiments; AFA, PS, JP, and PEMR analysed the data and drafted the manuscript. All authors read and approved the final version of the manuscript.Title: Repeats and primer sequences of the microsatellite loci designed for A. darlingi. Description: Microssatelites used to genotype Anopheles darlingi, Locus position, numer of repeats, primer sequence , Tm of the reaction and fluorechrome of each loci used.Click here for fileTitle: Estimates of pairwise genetic differentiation among localities in A. darlingi pure subpopulation (without admixed): A) subpopulation A, B) subpopulation B. Description: Pairwise genetic differentiation of grouped subpopulations A and B excluding admixture individuals.Click here for fileTitle: Relative distribution of each genetic lineage revealed by STRUCTURE per locality/semester. Description: A table showing the distribution of subpopulation A, subpopulation B and admixture population at different collection sites and period.Click here for fileTitle: Apportionment of molecular variance measured among populations of Anopheles darlingi from all samples, or between populations from the two semesters. Description: Molecular variance of samples considering subpopulation A and subpopulation B.Click here for fileTitle: Summary of BOTTLENECK tests. Description: List of Bottleneck tests at Subpopulations A and B at each period of collection.Click here for file


Schistosoma mansoni infections in this region, little is known about its colonization history.Anthropogenic environmental changes may lead to ecosystem destabilization and the unintentional colonization of new habitats by parasite populations. A remarkable example is the outbreak of intestinal schistosomiasis in Northwest Senegal following the construction of two dams in the ‘80s. While many studies have investigated the epidemiological, immunological and geographical patterns of cox1) and nine nuclear DNA microsatellite markers. Phylogeographic and population genetic analyses revealed the presence of (i) many genetically different haplotypes at the non-recombining mitochondrial marker and (ii) one homogenous S. mansoni genetic group at the recombining microsatellite markers. These results suggest that the S. mansoni population in Northwest Senegal was triggered by intraspecific hybridization (i.e. admixture) between parasites that were introduced from different regions. This would comply with the extensive immigration of infected seasonal agricultural workers from neighboring regions in Senegal, Mauritania and Mali. The spatial and temporal stability of the established S. mansoni population suggests a swift local adaptation of the parasite to the local intermediate snail host Biomphalaria pfeifferi at the onset of the epidemic.Parasites were collected at several time points after the disease outbreak and genotyped using a 420 bp fragment of the mitochondrial cytochrome c oxidase subunit 1 gene (S. mansoni parasites are very successful in colonizing new areas without significant loss of genetic diversity. Maintaining high levels of diversity guarantees the adaptive potential of these parasites to cope with selective pressures such as drug treatment, which might complicate efforts to control the disease.Our results show that  Schistosoma parasites successfully colonize new regions following the construction of water schemes for power production or agricultural purposes. Here we investigated the colonization history of the human parasite Schistosoma mansoni in Northwest Senegal following the construction of two dams in the ‘80s. Parasites were collected at several time points following the disease outbreak and their genetic profile was characterized using molecular markers. Our results showed that many genetically different parasites must have been introduced at the onset of the epidemic, which complies with the extensive immigration of infected seasonal agricultural workers from neighboring regions in Senegal, Mauritania and Mali. Furthermore, we showed that parasite transmission occurred over a large geographic distance, which implies that new alleles, like resistance alleles, could spread rapidly in this system. These new insights demonstrate how colonization following anthropogenic environmental changes may lead to genetically diverse parasite populations within a short time span. High genetic diversity is often linked with a stronger potential to cope with selective pressures such as drug treatment, which may complicate efforts to control the disease. Environmental change and increasing movements of people, plants and animals have led to species introductions and proliferations into new areas. The colonization, establishment and success of introduced species depend on various biotic and abiotic factors –4. In thSchistosoma mansoni that per generation cycles through a human final host and a snail intermediate host of the species Biomphalaria pfeifferi . Se. Secox1 S. mansoni infection in Assoni among children aged 6–14 years was initially 100% in 2006 (i.e. before treatment), but decreased to 50% in 2013 after three treatment rounds  with praziquantel to those children that were diagnosed positively for S. mansoni infection [The second genetic dataset, hereafter referred to as DMS1, comprised parasites that were genotyped at nine microsatellite markers , and that were either miracidia collected within the framework of this study or adult worms provided by SCAN  see Tab. The Sennfection . Similarnfection .S. mansoni genotypes from miracidia that were collected in the village Kokry-Bozo in 2007 in Southwest Mali within the framework of the study of Gower and colleagues [S. mansoni infection in Kokry-Bozo at the time of sampling was 88% [CA11-1, S9-1, SMD25, SMD28, SMD89, SMDA28) were shared among the study of Gower and colleagues [The third genetic dataset, hereafter referred to as DMS2, includes the same genotypes as DMS1, but complemented with previously published lleagues . Main lo was 88% . Samples was 88% . The genlleagues  and our lleagues  for binnGenomic DNA extractions of lab-derived adult worms and naturally collected miracidia were performed with the Nucleospin Tissue kit (Macherey Nagel) following the manufacturer’s instructions. For miracidia, 3 mm discs containing the whole miracidium were excised from the FTA cards and for worms the whole sample was used as DNA source .cox1 gene (450 bp) were obtained using primers Asmit-1 and Schisto-3' [2, 0.2 mM dNTPs and 0.8 μM of each primer. PCR conditions were the following: denaturation for 3 min at 95°C, followed by 35 cycles of 45 s at 94°C, 45 s at 49°C, 45 s at 72°C with a final extension of 10 min at 72°C. PCR products were visualized on a 1% agarose gel to check for amplicons, and subsequently purified and sequenced using a Big Dye Chemistry Cycle Sequencing Kit v1.1 in a 3130 Genetic Analyser (Applied Biosystems). The forward primer Asmit-1 was used and complemented with sequencing reverse primer Schisto-3' when sequence quality was poor.Sequences of the mitochondrial histo-3' ,45 in 25S. mansoni parasites  were genotyped using nine microsatellite loci in a single multiplex reaction  as desc, SMDA28 . All PCRcox1 sequences were manually edited and aligned using MUSCLE [http://www.geneious.com/). Species identity was confirmed using BLAST (http://blast.ncbi.nlm.nih.gov/).All g MUSCLE  as implecox1 fragment (DSEQ) was quantified per region, per village and per year in DNA-SP v5.10.1 [h [Π). Based on the commonly used mutation rate of 10−8 mutations per site per year for mitochondrial DNA [Genetic diversity at the  v5.10.1  by estim.10.1 [h , the numrial DNA , we assuhaplotype and used to construct a network with the function haploNet. The number of sequences that represented a given haplotype was logarithmically transformed to narrow high and small values, and used to determine the size of its corresponding pie diagram. A first network included all sequences from the DSEQ dataset. A second network included only sequences from Senegal and Mali.Genealogical relationships between all sequences were explored by constructing two haplotype networks based on statistical parsimony  in the pFIS was estimated by f [f was tested using 10,000 permutations and corrected for multiple testing using Bonferroni corrections. Analyses were done per village, year and region.First, the genetic diversity of parasite populations was quantified by estimating the proportion of heterozygous individuals , the expected proportion of heterozygous individuals assuming Hardy-Weinberg Equilibrium  and the number of alleles corrected for sample size . Ho and Hs were estimated in GENETIX v4.05  while ARted by f  in GENETK populations that are each characterized by a set of allele frequencies. Individuals could be assigned to two or more populations if their genotypes indicate that they are admixed. As K is unknown, the model is run multiple times, each time with a different K-value (from 1–10). Sampling locations (i.e. village) were included in the model as a prior (LOCPRIOR = 1), as they can assist clustering when the amount of genetic markers is low [6 MCMC chains, initiated by 105 burn-in steps. All jobs were run parallel on multiple cores using the R package ‘ParallelStructure’ [K value was identified by the maximum LnP(D), which is the log likelihood of the observed genotype distribution in K clusters.Second, the ancestry of individual parasites was inferred using a Bayesian Markov Chain Monte Carlo (MCMC) clustering analysis as implemented in STRUCTURE v2.2.3 . The pros is low . Note ths is low . Five reructure’ . The optThird, population genetic structure was visualized by exploring the distribution of genotypes of DMS1 and DMS2 in hyperspace using a Factorial Correspondence Analysis (FCA) as implemented in GENETIX and results were visualized using the R software. FCA visualizes genotypic (dis)-similarities among individual parasites.FST analogue θ [θ between villages were visualized with classical multidimensional scaling (CMDS) plots using the R software. Only populations with at least 10 genotypes were kept in order to minimize bias due to low sample size.Fourth, genotypic (dis)-similarities were studied among groups of parasites by estimating the alogue θ . This wacox1 sequences of which 121 were generated in this study  to 152 in Nder  differed from each other but were in common with Northwest Senegal, of which one was also found in Assoni . Haplotype diversity of all parasites found in Northwest Senegal  was high compared to other regions in Africa, ranging from 0.543 in Niger (N = 160) to 0.927 in Tanzania (N = 44). Haplotype diversity was 1.000 in Mali, but the sample size was very low (N = 3). In Richard Toll, haplotype diversity in 1993 (N = 8) and 1994 (N = 30) was equal to 0.929 and 0.772 respectively, comparable to other regions in Africa (Π = 0.0081) was similar to other populations in Africa. Only parasites sampled in Zambia and Coastal Kenya showed higher levels of nucleotide diversity  containing parasites from Coastal Kenya, Tanzania and Uganda  . Parasitd Uganda . The secd Uganda .S. mansoni in Northwest Senegal  were similar to the diversity in Assoni in Southeast Senegal , but slightly lower compared to Kokry-Bozo in Southwest Mali  (Parasite population genetic diversity as estimated by unbiased expected heterozygosity (Hs), observed heterozygosity (Ho) and allelic richness (AR) was rather uniform across all villages sampled in Northwest Senegal , with th = 3.31) .K = 4 for DMS1 and for K = 3 for DMS2; the log likelihood decreased thereafter for larger values of K. For DMS1, parasites from almost all villages sampled in Northwest Senegal were assigned to one genetic cluster, with the exception of parasites from Ndombo (1997) and Mbodjene (2007)  . In addie (2007) . For DMSe (2007) .Factorial Correspondence analysis (FCA) for DMS2 revealed that most of the parasites from Northwest Senegal sampled in several villages from 1993 to 2007 always clustered together and differed strongly from parasites sampled in Assoni in 2011  and Kokry-Bozo in 2007  . For DMSFST between regions for DMS2 were 0.064 (p < 0.001) between Southwest Mali and Northwest Senegal, 0.056 (p < 0.001) between Southwest Mali and Southeast Senegal and 0.044 (p < 0.001) between Northwest Senegal and Southeast Senegal. FST between villages and shows that parasite populations from Kokry-Bozo (2007), Assoni (2011), Ndombo (1997) and Mbodjene (2007) were almost always significantly differentiated from the other samples when genotypes were permuted among villages. In contrast, genetic differentiation among the other samples in Northwest Senegal was mostly low and often insignificant  led to a massive outbreak of intestinal schistosomiasis, a debilitating and neglected disease that had not been reported before in the region. The rate and intensity at which the epidemic expanded over Northwest Senegal was devastating: within a few years, villages . Here, wS. mansoni was high, both at the mitochondrial and at the nuclear level. A total of 20 different cox1 haplotypes (out of 103 described across Africa) were identified in Northwest Senegal emerge successfully into new regions [These results highlight the success of this parasite in extending its geographic range without notable loss of genetic diversity. Maintaining genetic diversity allows the parasite to quickly adapt to a new environment or a new host, or to counteract selective pressures such as drug treatment ,66. Such regions , and whyFST, Factorial Correspondence Analysis and STRUCTURE analysis revealed the presence of three genetic populations in Northwest Senegal: one dominant S. mansoni population that is present in almost all villages and at all times, and two smaller populations in Ndombo 1997 and in Mbodjene 2007 , or that they are the result of intraspecific hybridization (admixture) among multiple introduced parasite populations (scenario 2). Admixture among different introductions might produce recombinant genotypes that are characterized by a unique genetic profile if these genotypes were extensively shuffled, which will furthermore erode the genetic signal of the native range [cox1 haplotypes were found within a single village  than the result of a single introduction (scenario 1). Unfortunately, our sampling in the native range is too restricted to reliably discriminate among both scenarios. Analyses of genetic structure indicated that the samples from Southeast Senegal and Southwest Mali represent separate genetic groups  Thc groups  and 4, sc groups . AdditioSchistosoma mansoni genetic diversity in 1993–1994 from Richard Toll is of the same order of magnitude as 14 years later  than in combination with Cameroonian S. mansoni  [S. mansoni prevalence (44%) in B. pfeifferi snails at the onset of the epidemic [S. mansoni to its intermediate snail host B. pfeifferi in Northwest Senegal. This could have led to priority effects in S. mansoni, lowering the establishment success of subsequent invasions and ensuring the temporal and spatial stability of the dominant S. mansoni population in Northwest Senegal [In light of the dynamic nature of a disease outbreak, it is remarkable that parasite genetic diversity remained relatively stable in space and time. r Tables  and 3 anr Tables . These rund ones . Experimination) . This waepidemic . Altoget Senegal ,78.S. mansoni parasites from Mbodjene (2007) in the Lampsar region were significantly differentiated from most other samples in the vicinity of Richard Toll. Likewise, the B. pfeifferi population sampled close to this locality was genetically different from the other two populations near the Lampsar River and the populations around Richard Toll [S. mansoni in a certain region. At the molecular level, this could comply with the hypothesis of a matching phenotype model where the interactions between parasite antigens and host immune receptors during the early stages of the infection determine the success or failure of the infection [An interesting finding is that ard Toll . This confection .S. mansoni population suggest a swift local adaptation of the parasite to its intermediate snail host B. pfeifferi at the onset of the epidemic. Further research using samples from different localities in Senegal, Mali and Mauritania will help to pinpoint the putative source population(s) of this disease outbreak.This study is the first to reconstruct a recent epidemic of human intestinal schistosomiasis using mitochondrial and nuclear markers, revealing the evolutionary consequences of such a rapid colonization. The occurrence of many different haplotypes as revealed by the non-recombining mitochondrial marker indicated that multiple introductions occurred, while the recombining microsatellite markers pointed to the presence of mainly one widespread homogeneous population. We argue that admixture among multiple introductions generated a homogenous parasite population with a distinct genetic signature. The spatial and temporal stability of the established S1 DataS. mansoni samples that were genotyped at nine microsatellite markers. DMS2 can be found in excel tab 2 and contains 758 S. mansoni samples that were genotyped at six microsatellite markers. Loci are coded in 6 digits .DMS1 can be found in excel tab 1 and contains 542 (XLSX)Click here for additional data file.


Streptococcus thermophilus with high exopolysaccharide production were isolated from traditional Chinese fermented dairy products. The exopolysaccharide and viscosity of milk fermented by these 19 isolates were assayed. The strains of Streptococcus thermophilus zlw TM11 were selected because its fermented milk had the highest exopolysaccharide content (380 mg/L) and viscosity (7716 mpa/s). Then Streptococcus thermophilus zlw TM11 was combined with Lactobacillus delbrueckii subsp. bulgaricus 3 4.5 and the combination was named SH-1. The quality of the yogurt fermented by SH-1 and two commercial starter cultures  were compared. It was shown that the exopolysaccharide content of yogurt fermented by SH-1 was similar to that of yogurt fermented by YF-L711 and significantly higher than YO-MIX 465 (p < 0.05). In addition, the yogurt fermented by SH-1 had the lowest syneresis (8.5%) and better texture and sensory than the samples fermented by YO-MIX 465 and YF-L711. It manifested that the selected higher exopolysaccharide production starter SH-1 could be used as yogurt starter and reduce the amount of adding stabilizer, which can compare with the imported commercial starter culture. 19 Yogurt has been an integral part of everyday diet for centuries, rising as the second most popular snack among children in the world . TexturaStreptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus are the mainly strains used in the yogurt starter culture and used for yogurt production. Unfortunately, some of strains of Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus did not produce EPS or produce only low yields of EPS, which may affect the end products quality [ quality –14. Pres Streptococcus thermophilus. The aim of this work was to select the starter culture with higher exopolysaccharide production to improve the yogurt quality and develop our own authority yogurt starter culture. The selected higher exopolysaccharide production starter will reduce the amount of additives addition and can be comparable with the imported starter culture.In China, there are many traditional fermented dairy products. Therefore, screening LAB from natural sources has been one of the powerful means to obtain strains for the food industry. We have already screened LAB from Chinese traditional fermented dairy products and some properties have been characterized in our previous work , 16. In The commercial yogurt starters, YO-MIX 465 and YF-L711, were obtained from Danisco and Chr. Hansen (Denmark). The whole cow raw milk was purchased from supermarket . Skim milk was purchased from Nestle Company, Heilongjiang, China. All the chemicals used in this paper were of analytical grade. Streptococcus thermophilus were screened from traditional Chinese fermented dairy products. The above 19 isolates were inoculated into the sterilized  reconstituted skim milk (12%), respectively. The inoculate rate was 2% and incubated at 42°C until pH attained to 4.7. The fermented samples were cooled at 4°C for 12 h. Then the content of exopolysaccharide and viscosity in fermented milks were detected. The Streptococcus thermophilus, which produced higher exopolysaccharide and had higher viscosity, was selected. The pH of each sample was determined directly using a digital pH meter  calibrated with standard buffer solutions. Three replicates were performed.19 Streptococcus thermophilus with higher exopolysaccharide production was combined with Lactobacillus delbrueckii subsp. bulgaricus 3 4.5, which was screened from Chinese traditional fermented dairy products and identified by Biolog identification system and analysis of 16S rDNA gene sequence. The direct vat starter (DVS) SH-1 which was composed by these two stains (the fermented characteristic about the combined starter culture was reported in our previous work [The selected7 CFU/mL measured by spread plate count method and incubated at 42°C until the pH reached 4.6 (about 4 to 4.5 h). Then yogurt samples were put into the refrigerating chamber (4°C) for 12 h to detect the EPS production, appearance viscosity, texture, syneresis, and sensory of yogurts. Each test has three replications.Raw fresh cow milk consisted of 3.14% protein, 3% fat, lactose 4.92%, and 11.81% total solids, was analyzed by MilkoScan FT1 (Denmark), and then preheated to 65°C and homogenized. The homogenized milk was pasteurized at 65°C for 30 minutes and cooled to 42°C and portioned to three equal batches. The batches were inoculated with about 3 mg/L starter cultures  that were determined by the initial viable counts of yogurt. The initial viable counts of each batches were about 10EPS was isolated from the fermented sample, according to a modified method of Lin and Chien . The ferViscosity measurement was carried out at 4 ± 1°C by Brookfield Programmable DV-E Viscometer  equipped with S63 spindle at 20 rpm.The texture of yogurt was determined by penetration measurements . The instrument was adjusted to the following conditions: cylindrical probe, probe diameter: 35 mm; penetration speed: 1.0 mm/s; penetration distance, 20 mm into surface. The software used was Exponent . 100 mL of yogurt sample was analyzed in each cup. Four parameters were evaluated, the firmness (g) , defined as the force necessary to attain a given deformation; the cohesiveness (g/s) (adhesive force), defined as forces of internal bonds, which keep the product complete; the viscosity (g); and the adhesiveness (g/s) ; the work is necessary for overcoming the force of attraction between the area of foodstuff and other solids coming to contact with them.Syneresis index of different yogurt samples was determined according to the methodology proposed by Farnsworth et al.  with modTwenty trained panelists  were asked to evaluate the sensory attributes of yogurt. The ratings were presented on a 9-point hedonic scale ranging from 9 (“like extremely”) to 1 (“dislike extremely”). Yogurt sensory parameters were evaluated by thickness, smoothness, fermented odor, finished flavor, and taste quality. To minimize bias, all groups were three digits coded. The yogurts were served to panelists after the cooling process. Result was given on averages of the three trials for each type of yogurt .α = 0.05. Data were expressed as mean values ± standard deviation (S.D.). For analyzing the relationship of exopolysaccharide production and viscosity of fermented milk, the correlate bivariate analysis was used to determine the correlation coefficient. All experiments were performed in duplicate and repeated three times.Statistical analyses were performed using SPSS 14.0 software . Significant differences among treatments were tested by ANOVA followed by Tukey's test with a level of significance at  Streptococcus thermophilus isolated from traditional Chinese fermented dairy products were assayed. In  Streptococcus thermophilus zlw TM11, the exopolysaccharide and viscosity were significantly higher than that of the other strains (p < 0.05). The relationship of exopolysaccharide production and viscosity of fermented milk was analyzed by SPSS software correlate bivariate analysis. The results showed that the correlation coefficient between exopolysaccharide production and viscosity was 0.841 (p < 0.01). It suggested the strains producing higher exopolysaccharide might contribute to the higher viscosity of fermented milk. Guzel-Seydim et al. [ Streptococcus thermophilus zlw TM11 were selected to combine with Lactobacillus delbrueckii subsp. bulgaricus 3 4.5. The combination was named SH-1 and was used as starter to make yogurt.The exopolysaccharide production and the viscosity of fermented cow milk produced by the 19m et al. , 22. Thep < 0.05) and had no significant difference with YO-MIX 711 (p > 0.05). Starter YO-MIX 711 had the higher exopolysaccharide production and also had higher viscosity in fermented milk compared with YO-MIX 465, although there was no significant difference for the fermented milk viscosity (p > 0.05). It was verified in the result of The exopolysaccharide content in each yogurt samples was showed in p < 0.05). For YF-L711, the firmness (36.70 g) and cohesiveness had no significantly different with YO-MIX 465 (p > 0.05). While viscosity (18.63 g) and adhesiveness were significantly lower than YO-MIX 465 fermented yogurt (p < 0.05). The content of exopolysaccharide in YF-L711 fermented yogurt was a little higher than that of YO-MIX 465 fermented yogurt, though no significant difference (p > 0.05) was observed. It was inferred that a little increase of exopolysaccharide might have great effect on viscosity and adhesiveness.The textures properties of the yogurts fermented by different starter cultures were showed in Many researchers reported that the exopolysaccharide could improve the texture of yogurt, because exopolysaccharide produced by LAB interacts with the free water in the gel-like structure , 23, 24.p > 0.05). Among them, starter SH-1 had the highest exopolysaccharide content (423 mg/L), corresponding to the lowest whey separation (8.51%). For commercial starters YO-MIX 465 and YF-L711, the syneresis was 10.70% and 12.12%, respectively. It seemed that the higher content of exopolysaccharide would contribute to the lower whey separation. Similar results had also been reported by other studies [The syneresis of samples fermented by different starters was showed in content 43 mg/L, c studies , 26. Thup > 0.05). As regards to the fermented odor, the starter SH-1 was no better than YO-MIX 465 and YF-L 711. The results of sensory evaluation indicated that the selected starter SH-1 had the potential to replace the imported commercial starter.The scores for sensory characteristics of the yogurt samples were presented in The starter culture type affected the qualities of yogurt samples. The selected starter SH-1 had the similar content of exopolysaccharides to the commercial starter YF-L 711 and significantly higher than YO-MIX 465. The higher exopolysaccharides could provide better texture of yogurt and lower whey separation. On the other hand, the sensory evaluation of yogurt using selected culture SH-1 was better than or similar to the other commercial starter cultures, except for the fermented odor which was a little lower than the other two commercial starters. These implied that our own authority starter SH-1 could produce the yogurt with similar or better quality compared with the commercial starters.


Macaca fascicularis) is one of the most commonly used nonhuman primates in academic and industry settings, yet population genetic research has revealed significant substructure throughout the species distribution that may confound studies. Cynomolgus monkeys introduced to Mauritius specifically have previously been thought to maintain the least genetic heterogeneity of all cynomolgus monkeys, although recent work, including work from our lab, suggests macaques from Mauritius too may harbor cryptic substructure.Nonhuman primates are commonly used in biomedical research as animal models of human disease and behavior. Compared to common rodent models, nonhuman primates are genetically, physiologically, behaviorally and neurologically more similar to humans owing to more recent shared ancestry and therefore provide the advantage of greater translational validity in preclinical studies. The cynomolgus macaque  contains supplementary material, which is available to authorized users. Macaca mulatta) and the long-tailed macaque (M. fascicularis), also commonly known as the crab-eating or cynomolgus macaque.Nonhuman primates are commonly used in scientific research as animal models of human behavior and disease. Although their use in research is overshadowed by the availability of less expensive and more abundant animal models such as rodents and zebrafish with easier husbandry, these animal models do not always provide the best translational medicine when trying to elucidate human pathologies. Nonhuman primates represent an alternative to these animal models and provide distinct advantages owing to their phylogenetic proximity to humans that lends itself to greater genetic, physiological, neurological, and behavioral similarities , 2. HistDespite a number of advantages to using nonhuman primates in biomedical research, there are distinct disadvantages that make studies in these animals difficult. Captive nonhuman primates harbor greater genetic heterogeneity, as these animals are outbred relative to laboratory strains of rodents, which is complicated by another distinct disadvantage which is that studies are often comprised of much smaller sample sizes inherent in the increased costs required for acquisition and husbandry . BecauseThe cynomolgus macaque is one of the most commonly used models in biomedical research , 15. Theth century [Cynomolgus macaques originated in Southeast Asia and maintain a wide subtropical distribution ranging from Vietnam, Cambodia, Thailand and Malaysia to island populations in Indonesia, the Philippines and, more recently, Mauritius. Animals used in research are sourced from many of these locations and, while subpopulation differences are still minimally studied, potentially important genetic differences between populations are already recognized , 22. Mau century . Recent  century  or more  century . Cynomol century . On the  century , 27.With many cynomolgus macaques used in research sourced from Mauritius, here we utilized a pseudogenomic approach to investigate population homogeneity in this group of macaques. Although previous work has found little genetic heterogeneity , recent Previous work  found a M. mulatta, M. cyclopis, and M. fuscata  and Y-chromosome DNA (YDNA), we tested whether the 32 animals from the Goswami et al. study  clusterea Figure . This anSRY and TSPY sequence data of 102 individuals  , was also performed to analyze the data. This methodology uses an approach conceptually similar to Principal Component Analysis (PCA) with a focus on minimizing sources of within group variation . k-means) Figure A. As wit2 Figure B or K of2 Figure C it is pRegardless of whether there are two or three subpopulations, moderate admixture  is observed and suggests either reproductively isolated populations with hybrid zones or historic isolation that no longer exists. Previous work on Mauritian cynomolgus macaques has suggested genetic substructure with a putative northern and southern population based on microsatellite loci . UnfortuImportantly, it seems that despite this population substructure most animals are significantly admixed and the structure may be decaying. Unlike other subpopulations of cynomolgus macaques, such as those from the various “continental” and “insular” location, or the Indian-origin and Chinese-origin rhesus, the two subpopulations of Mauritian macaques appear largely admixed. This can be envisioned similarly to the Collaborative Cross of laboratory mouse strains , ChineseThe underlying cause of this apparent population stratification remains unknown. An ecological separation remains possible, but there is little evidence to support this hypothesis and the likelihood of it causing pervasive genome wide effects in such a relatively short time seems minimal. What may be more likely given the relatively recent introduction of macaques to Mauritius by mariners is that these data may suggest either two or three independent founding events and/or, knowing that significant genetic structure exists among cynomolgus macaques outside of Mauritius , foundinAnimal models are an important component of preclinical biomedical research and critical to the translational success of new drugs and therapies. Just as the importance of cryptic substructure in human studies became increasingly recognized, so too now do we recognize its importance in animal models. In laboratory mice and rats, animals are almost always inbred and genetically identical, but non-human primates are outbred and can harbor genetic variation often exceeding that seen in humans. Moreover, an increasing number of studies have identified segregating common variation with explicit functional effects on many of the characteristics under study in these animals. It is important, therefore, that the genetic substructure of populations be taken into account.Cynomolgus macaques are among the most widely used of non-human primate model species, particularly in industry, and among cynomolgus macaques those sourced from Mauritius are particularly prevalent. Moving into the post-genomic era, it has become increasingly possible to tease apart the complex demographic history and extant genetic difference among this population. Although there are no obvious or otherwise documented phenotypic  differences among these subpopulations of cynomolgus macaques on the island of Mauritius, given the results of our study it is entirely possible that observed phenotypic variability among Mauritian cynomolgus macaques , 42, 43 Here we demonstrate at least two, and possibly three, subpopulations of cynomolgus macaques on Mauritius. We propose that this stratification is suggestive of either an unknown and previously unrecognized barrier to gene flow, or the remains of genetic substructure among Mauritian cynomolgus macaques following distinct founding events and/or founding individuals approximately 500 years ago. This effort has served to not only elucidate the natural history of cynomolgus macaques on Mauritius, but to also better inform studies that use these animals.Blood draws for the isolation of genomic DNA for animals housed at the NEPRC were done during routine preventative health care by trained veterinary phlebotomists within the NEPRC Division of Veterinary Resources. All animals were maintained in accordance with the guidelines of the Harvard Medical School Standing Committee on Animals and the Guide for Care and Use of Laboratory Animals of the Institute of Laboratory Animal Resources, National Research Council. Blood draws from animals obtained from Cynologics Ltd.  and Bioculture Mauritius Ltd.  were collected at the respective sources in accordance with their standard operating procedures.The two primary suppliers of cynomolgus macaques from Mauritius are Bioculture Mauritius and Cynologics. These animals are captured and subsequently resold or bred by secondary distributors such as Charles River Laboratories  and Primate Products . The 32 cynomolgus macaque genomic DNAs used in the Goswami et al.  study weSRY (sex-determining region) and TSPY (testis-specific protein) genes were targeted for amplification and analysis. The SRY gene (~600 bp) was amplified using primers SW2 and SW3B from Whitfield et al. [TSPY gene (~2250 bp) was amplified using primers TSPY-A and TSPY5R from Tosi et al. [PCR, sequencing and analysis of the mtDNA and Y chromosome were performed on the 32 Goswami et al.  cynomolgd et al.  and the i et al. . Due to PCR product purification was performed using ExoSAP-IT  and was outsourced to Functional Biosciences, Inc.  for sequencing where Sanger sequencing reactions are performed using BigDye V3.1 on ABI 3730xl instruments. The PCR primers were used for sequencing the mtDNA region. Sequencing primers, however, were used from Tosi et al.  for the Papio sp.) sequence was included in each alignment as an outgroup for phylogenetic analysis. Each alignment was run in jModelTest v2.1.1 [Sequence reads were assembled and cleaned-up using CodonCode Aligner v4.1.1 . Two alignments were created for phylogenetic analysis, one for the mtDNA sequence data and one for the Y chromosome data, using ClustalW . Sequenct v2.1.1 , 50 and t v2.1.1 , with thA panel of SNPs was generated to determine population substructure in a manner analogous to that which had been previously developed for the differentiation of Indian-origin and Chinese-origin rhesus macaques . Our SNPWe further selected SNPs based on their anticipated ability to differentiate between the two putative populations identified previously, prioritizing SNPs that displayed the greatest difference in minor allele frequencies (ΔMAF). This approach maximizes the information content of the SNPs and allows for the achievement of significant results with the use of fewer SNPs. Finally, any given SNP can be the result of demography or selection. We prioritized supposed neutral, demographic SNPs, but did not exclude SNPs possibly under selection as these too could be informative. However given that SNPs under selection may obscure signals of demography we prioritized non-genic SNPs followed by synonymous SNPs and then nonsynonymous SNPs. 110 SNPs were selected based on these criteria.Assay design and SNP genotyping using Sequenom iPLEX technology were outsourced to the Biomedical Genomics Center at the University of Minnesota. Four assay pools  were created for multiplexing. DNA samples were divided across three 96-well plates and duplicates were placed on each plate to ensure consistency in genotype calls. All DNA samples underwent quality control analysis prior to genotyping. 96 SNPs (divided evenly across the multiplexes) resulted in successful assays with >97% call rates and were used for future analyses  and then analyzed using k values from 1 to 10 with k-means to identify the optimal number of clusters. DAPC then constructs synthetic variables, discriminant functions, based on linear combinations of alleles harboring the greatest between-group variation and smallest within-group variation [A Discriminant Analysis of Principle Components (DAPC) was also performed using the 4-2 in R , 54–56. ariation . This meAll supporting data are included as additional files to this manuscript.Additional file 1: Table S1: Animals used in the mtDNA phylogenetic analysis to confirm that animals in the Goswami et al.  study deAdditional file 2: Table S2: Animals used in the YDNA phylogenetic analysis to confirm that animals in the Goswami et al.  study deAdditional file 3: Figure S1: Subpopulation inference after Evanno et al. , STRUCTUAdditional file 4: Figure S2: Subpopulation inference after Evanno et al. , defaultAdditional file 5: Figure S3: Subpopulation inference after Evanno et al. , defaultAdditional file 6: Figure S4: Inferred ancestry of individuals from STRUCTURE distinguishing animal source/dealer. Inferred ancestry with K = 2. Animals in red are derived from Cynologics and animals in blue are from Bioculture Mauritius. (PDF 37 KB)Additional file 7: Table S3: SNPs included on the panel of 96 used to evaluate population substructure of cynomolgus macaques on Mauritius. Table also includes SNP location information including chromosome number and position, gene, gene region, and the flanking sequence. (XLSX 18 KB)


Uniformity of eggs is an important aspect for retailers because consumers prefer homogeneous products. One of these characteristics is the color of the eggshell, especially for brown eggs. Existence of a genetic component in environmental variance would enable selection for uniformity of eggshell color. Therefore, the objective of this study was to quantify the genetic variance in environmental variance of eggshell color in purebred and crossbred laying hens, to estimate the genetic correlation between environmental variance of eggshell color in purebred and crossbred laying hens and to estimate genetic correlations between environmental variance at different times of the laying period.We analyzed 167,651 and 79,345 eggshell color records of purebred and crossbred laying hens, respectively. The purebred and crossbred laying hens originated mostly from the same sires. Since eggshell color records of crossbred laying hens were collected per cage, these records could be related only to cage and sire family. A double hierarchical generalized linear sire model was used to estimate the genetic variance of the mean of eggshell color and its environmental variance. Approximate standard errors for heritability and the genetic coefficient of variation for environmental variance were derived.The genetic variance in environmental variance at the log scale was equal to 0.077 and 0.067, for purebred and crossbred laying hens, respectively. The genetic coefficient of variation for environmental variance was equal to 0.28 and 0.26, for purebred and crossbred laying hens, respectively. A genetic correlation of 0.70 was found between purebred and crossbred environmental variance of eggshell color, which indicates that there is some reranking of sires for environmental variance of eggshell color in purebred and crossbred laying hens. Genetic correlations between environmental variance of eggshell color in different laying periods were generally higher than 0.85, except between early laying and mid or late laying periods.Our results indicate that genetic selection can be efficient to improve uniformity of eggshell color in purebreds and crossbreds, ideally by applying combined crossbred and purebred selection. This methodology can be used to estimate genetic correlations between purebred and crossbred lines for uniformity of other traits and species.The online version of this article (doi:10.1186/s12711-016-0212-2) contains supplementary material, which is available to authorized users. Animal products require a certain level of homogeneity. In some cases, homogeneity or uniformity has benefits for product processing, e.g. meat , and retSelection for more uniform brown eggs requires the presence of genetic variation in the uniformity of this trait. For several other traits, there is empirical evidence for the existence of genetic variance in environmental variance  and during three periods in crossbred hens . Purebred hens were individually housed, whereas crossbred hens were housed as paternal half-sibs in group cages that contained between four and 17 hens. Eggshell color was measured with a reflectometer (Minolta) using three parameters: L* measures lightness , a* measures hue as a function of the red–green scale  and b* measures hue as a function of the blue–yellow scale  . The thrThe main aim was to estimate the genetic correlation between The genetic analysis of  (DHGLM) , 17. Herr et al. , a sire r et al.  for crosi et al. , a Gammacument}i . Fellekid et al. . The resr et al. . The resred from . The sirervation . The adjr et al. . The veci et al. , withoutRun linear mixed model for Calculate where and where r et al.  where thRun a four-variate linear mixed model on Update Iterate steps 3 and 4 until convergence.The algorithm for the iterations was as follows , 18:Run −3 and 1 × 10−2 for the iterations 51 to 100. In addition, individual parameters showed only minor changes (<5 %). Therefore, we considered that the algorithm converged after 100 iterations.The algorithm was run for 100 iterations and parameters showed small changes. The sum of the relative squared differences in estimated values of all variance components between the current and the previous iteration was between 3 × 10In Eq. mentclass2pt{minimmentclass2pt{minimmentclass2pt{minimAs described earlier, the definition of mentclass2pt{minimnce see “” sectionIn order to compare our results with data in the literature, we calculated two additional genetic parameters based on the estimated variance components, i.e. the heritability of t}GCVVe) . The \doelection . The \doument}VE . The calument}VE , 22, forument}VE . The \doStandard errors of mentclass2pt{minimEggshell color was approximately normally distributed with small skewness and kurtosis Table ; Fig. 1.The variance components for eggshell color itself are in Table t test, approximate test assuming normality of the test statistic [The genetic correlation between purebred and crossbred eggshell color was equal to 0.86 Table , which itatistic ). In purIn purebreds, we investigated the genetic correlations between different laying periods in purebred laying hens Table . The genThe results of simulations to test the effect of different definitions of is zero “”.Table 6In this study, we estimated the genetic variance in To the best of our knowledge, this paper reports the first estimates of genetic variance for  species . The her studies , 18, 24.rvations . With rervations . When peument}VE . The herument}VE . This sis of EBV . Thus, ws of EBV , 28. TheFor crossbreds, we used the sire model adjustment  to accouvariance . In thisThe genetic analysis that considered the different laying periods as separate traits revealed that except for the early laying period, eggshell color and its y models , 30 coulBased on the simulations in purebreds, we concluded that the genetic correlation between uals. In , a genetTo the best of our knowledge, this is the first time that genetic correlations between purebred and crossbred laying hens for ing goal . In our Designs to estimate tiaansen  was useds larger , 31. WheIn this study, the DHGLM methodology was used to estimate the genetic correlation between us study , we invetiaansen  can be uThe estimates of genetic variance for election , but alsentclass1pt{minimaIn addition to selection on uniformity in the pure lines, uniformity at the producer level could be achieved by selecting sires and dams as parents for the crossbreds on their EBV for  The genetic coefficients of variation for Approximate standard errors for nd Walsh . Because a ratio , 21, we nd Walsh , where \The denominator of When using the variance of a product in equation A1.18b in Lynch and Walsh :5\documeSimilar to Eq. Combining Eqs. Subsequently, the sampling variance of nd Walsh , assuminThe standard error of Numerical analysis showed that The standard error of nd Walsh :11\documPurebred hens were in individual hen cages and crossbred hens were in multiple-hen cages. This difference in housing led to a difference in the definition of We assumed that the within-individual variance was partly determined by its additive genetic effect After some rearranging of Eq. Equation Assuming that the proportion of Equation


Myrica rubra Sieb. & Zucc.) is an important subtropical evergreen fruit tree in southern China. Generally dioecious, the female plants are cultivated for fruit and have been studied extensively, but male plants have received very little attention. Knowledge of males may have a major impact on conservation and genetic improvement as well as on breeding. Using 84 polymorphic SSRs, we genotyped 213 M. rubra individuals  and compared the difference in genetic diversity between the female and the male populations.Chinese bayberry  and Female dominated (80). The well-known cultivars ‘Biqi’ and ‘Dongkui’, and the landraces ‘Fenhong’ are derived from three different gene pools. Female population had a slightly higher values of genetic diversity parameters  than the male population, but not significantly different. The SSR loci ZJU062 and ZJU130 showed an empirical Fst value of 0.455 and 0.333, respectively, which are significantly above the 95 % confidence level, indicating that they are outlier loci related to sex separation.Neighbour-joining cluster analysis separated M. rubra in China, with wide genetic diversity coverage; and the two representative cultivars ‘Biqi’ and ‘Dongkui’, and one landrace ‘Fenhong’ in three female subpopulations. This research provides genetic information on male and female Chinese bayberry and will act as a reference for breeding programs.The male and female populations of Chinese bayberry have similar genetic diversity in terms of average number of alleles and level of heterozygosity, but were clearly separated by genetic structure analysis due to two markers associated with sex type, ZJU062 and ZJU130. Zhejiang Province China could be the centre of diversity of The online version of this article (doi:10.1186/s12864-015-1602-5) contains supplementary material, which is available to authorized users. Myrica rubra) is an evergreen fruit tree native to southern China and other Asian countries [Myrica species in China, only M. rubra is commercially cultivated in Zhejiang, Jiangsu, Fujian and Guangdong, and is also grown in the Yunnan, Guizhou and Hunan provinces [Chinese bayberry  belongs to the s plants -9, with  members ,10-12. T6 belongs members , also soM. rivas-martinezii and M. faya [Genetic diversity, cultivar identification and the geographic origin of Chinese bayberry have been studied using molecular markers ,6,13, bu M. faya . SSRs ar M. faya -22.Actinidia chinensis (kiwifruit), which revealed putative X/Y sex-determining chromosomes[Myrica species. Here we report, for the first time, the genetic diversity of male plants of Chinese bayberry compared with the female plants, using 84 SSR markers. This information will be useful in the conservation of these diverse individuals and for direct application in the new initiative of the Chinese bayberry cross-breeding program.Molecular markers linked to sex determination have been reported in a few dioecious fruit crops. A microsatellite (GATA)n revealed sex-specific differences in papaya , and SCAromosomes. HoweverHo value was lower than the expected (He), which ranged from 0.19 to 0.88, . Shannon’s information index (I) for each locus ranged from 0.47 to 2.36, with a mean of 1.48.The 84 SSRs used in this research were polymorphic in both female and male samples, amplifying a total of 876 alleles, with an average of 10.43 alleles per locus. . Apart from the differences between them, these results also illustrate that the female and male of Chinese bayberry have abundant genetic diversity.The Na, Ne, Ho, and Hs of the male and female populations in 84 SSR loci are shown in Table M. rubra accessions were evaluated for population stratification. The assumed number of populations was set from K = 1 to 10. According to the method of Evanno [The 213 f Evanno , the accSTRUCTURE was then run for each of the subpopulations as a first step. The Male Dominated population of plants Fig. . The firThe Female-dominated population was further structured into two groups Fig. . The ‘BiBased on AMOVA analysis, most variation (81.55 %) was detected within individual accessions, with only 11.00 % attributed to variation among the six subpopulations Table . The oveM. adenophora, M. nana, and M. cerifera fell into the G2, G3 and G4 groups, respectively, as outgroups. G1 contained all the M. rubra accessions, and can be divided into two subgroups: SG1 and SG2. Ninety-one male plants were assigned to SG1, and five major subgroups clustered in SG2, assigned 101 accessions and clustered according to the sex type and geographical origin in the dendrogram, also consistent with the structure-based membership assignment. The other accessions clustered into several small groups, with males and females assigned to distinct groups. Of the 98 male accessions, 91 were assigned to male group SG1, four to SG2-5, and three to the female groups, one to SG2-1, and two to SG2-2. ‘W2011-1’, collected from a female plant with male inflorescences, was close to ‘Dingaomei’ in SG2-3. The two cultivars ‘Biqi’ and ‘Dongkui’, and the landrace ‘Fenhong’, were split into different subgroups, suggesting a different origin.Using a neighbour-joining (NJ) tree enabled a clear division of the 216 accessions into four main groups: G1, G2, G3 and G4  significantly above the 95 % confidence level by FDIST2 analysis Fig. , respectWhen we exclude the two SSR markers associated with sex, the phylogenetic tree  reported by Xie, where 123 cultivars were analysed with 14 SSRs [M. rubra [The female and male accessions contributed equally to the variability, with a mean gene diversity value, M. rubra . HeterozBayesian clustering analysis has been proven to be powerful tools to evaluate the genetic structure of fruit tree populations. A nested clustering strategy has also been used to assign individuals to populations, for example in apple  and peacM. rubra. ‘Biqi’ and ‘Fenhong’ would be old landraces, possibly sharing one or a number of common ancestors. However, this remains to be further elucidated.Also using STRUCTURE as the first step, most Zhejiang landraces clustered together  are clustered with those from Zhejiang Provinces (Zaoqimimei and Sanjiaaowumei) in SG2-2, indicating gene flow occurred frequently among these two provinces [Phylogenetic analysis grouped rovinces ,6. Zhejirovinces . The lanrovinces , a phenorovinces ,6,17.In general, males from geographically closer locations had higher genetic similarities than those from more distant locations, however, the three male plants of Y2012-1, Y2012-2 and Y2012-151 were clustered in SG2-1 and SG2-2, close to female plants collected from the same location, which indicates that these plants may be progeny of the female plants. Though few male accessions are clustered with female accessions, we would speculate that the male and female populations essentially have similar genetic diversity but distinct background associated with sex.Melandrium album) [Rumex acetosa [h chromosome (HSY) were sequenced, with the results supporting the model of early sex chromosome evolution [M. rubra and other related species have not been reported [Dioecious plants with separate male and female individuals are found in only 6 % of the 240,000 angiosperm species, and probably evolved recently from hermaphrodite ancestors . Myricacm album) -33 and R acetosa ,35. Rece acetosa , and thevolution . Sex detreported . The SSRreported ,16,17.M. rubra. The genetic diversity of the two cultivars ‘Biqi’ and ‘Dongkui’ and the landrace ‘Fenhong’ makes them an excellent source of variability for Chinese bayberry breeding programs. We also identified two SSR markers putatively associated to sex segregation in the two populations.Analysing male and female genotype data, we were able to estimate the genetic diversity of Chinese bayberry and demonstrate the rich diversity of the population. Phylogenetic cluster and population structure analyses revealed the sex trait effect on genetic structure stratification, and that Zhejiang Province could be the centre of diversity of M. rubra) and three related species  were sampled. For M. rubra, 113 females, 98 males, one monoecious plant (C2010-4), as well as W2011-1 from a female plant with a male branch were used to evaluate genetic diversity and population structure. Among these collections, the male population was collected from five provinces in China, and half of the Yuyao and Cixi accessions from trees planted in avenues located in different areas of Zhejiang Province, with these male trees collected from different regions in Ningbo, Zhejiang Province. Of the female population, 34 were from the China Bayberry Germplasm Repository (CBGR), Yuyao, Zhejiang Province, China, and 62 were local landraces , and PCR products, with four different colour labelling, were then mixed with the internal size standard LIZ500 (ABI) and separated by capillary electrophoresis in an ABI 3130 Genetic Analyzer . Allele size was estimated with the GeneMapper v4.0 software . The genotypes of 216 accessions were deposited in Dryad (doi: 10.5061/dryad.7qc88).A total of 84 primers pairs , the effective number of alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), genetic diversity (Hs), Shannon’s information index (I) and Wright’s fixation index (F = 1-Ho/He) were calculated using GenAlEx 6.4 [SSR data were scored as two alleles per locus distinguished by their size. We did not found multi-locus cases. The number of alleles , using Arlequin v3.5 software . PrincipM. cerifera’ as outgroup.Cluster analysis was conducted using the Neighbour-joining algorithm as implemented in TREECON ver.1.3 b . Genetic


Neoverruca are abundant near deep-sea hydrothermal vents of the northwestern Pacific Ocean, and are useful for understanding processes of population formation and maintenance of deep-sea vent faunas. Using next-generation sequencing, we isolated 12 polymorphic microsatellite loci from Neoverruca sp., collected in the Okinawa Trough. These microsatellite loci revealed 2–19 alleles per locus. The expected and observed heterozygosities ranged from 0.286 to 1.000 and 0.349 to 0.935, respectively. Cross-species amplification showed that 9 of the 12 loci were successfully amplified for Neoverruca brachylepadoformis in the Mariana Trough. A pairwise FST value calculated using nine loci showed significant genetic differentiation between the two species. Consequently, the microsatellite markers we developed will be useful for further population genetic studies to elucidate genetic diversity, differentiation, classification, and evolutionary processes in the genus Neoverruca.Barnacles of the genus  Neoverruca [Imbricaverruca [Neoverruca has no fossil record, the first appearance of close, but extinct ancestors is in the Mesozoic Era [Neoverruca is a very primitive barnacle. Presently, the genus Neoverruca contains only one described species, Neoverrucabrachylepadoformis. Based on morphology, individuals in the Okinawa Trough and Izu-Ogasawara Arc are distinct from N. brachylepadoformis in the Mariana Trough, located south of the Izu-Ogasawara Arc [et al. [Neoverruca sp., and investigated population structure, focusing on mitochondrial cytochrome oxidase c subunit I (COI). They discovered significant genetic differentiation between the two regions. Further population genetic analysis of this species using high-resolution genetic markers will be needed for detailed estimation of genetic diversity and structure. Therefore, microsatellite markers have been developed for further population genetic studies of Neoverruca sp. We isolated and characterized novel polymorphic microsatellite loci for Neoverruca sp. using next-generation sequencing and investigated cross-species amplification for N.brachylepadoformis collected from the Mariana Trough. Furthermore, we estimated the extent of genetic differentiation between Neoverruca sp. and N.brachylepadoformis using developed microsatellite loci, since Watanabe et al. [Larval dispersal in ecosystems such as deep-sea hydrothermal vents is essential for maintenance of benthic populations and for establishment of new colonies. For vent-endemic benthos, planktonic gametes or larvae provide the only means of migration between hydrothermal vents . Howeveroverruca  and Imbraverruca . The foraverruca ,5. Thougzoic Era ,6. Hencewara Arc ,5. WatanNeoverruca sp., and assembled each read pair. We used assembled 736,240 sequences longer than 100 bp  for simple sequence repeat identification. Sequence repeats were used for microsatellite detection and primer design. Ninety-six primer pairs were designed for screening amplifiable microsatellite loci . Twelve of these loci were successfully amplified and subsequently analyzed in Neoverruca sp., although Nsp_11 and Nsp_80 were not amplified in two and one individual(s), respectively. The number of alleles per locus ranged from 2 to 19 (p < 0.05).We obtained 291,118,462 bp  of raw sequence data from genomic DNA of  2 to 19 . Values Neoverruca sp., nine were successfully amplified in N. brachylepadoformis. Three loci, including Nsp_11 and Nsp_23, which showed high polymorphism in Neoverruca sp., were hardly amplified in N. brachylepadoformis. The number of individual N. brachylepadoformis that showed successful amplification at these nine loci was 14 to 19 (out of 19) .Of the 12 loci isolated and characterized from t of 19) . These nt of 19) . Values FST implied significant differentiation between Neoverruca sp. and N. brachylepadoformis. This differentiation is consistent with divergent patterns in molecular phylogenetic trees previously constructed for the COI haplotype [In this study, the number of useful loci and the significance of the pairwise aplotype . Using ni.e., between the Okinawa Trough and the Izu-Ogasawara Arc, which influences the formation and maintenance of populations within these species. Furthermore, these markers are expected to help elucidate genetic diversity, differentiation, classification, and evolutionary processes in genus Neoverruca. They may even be useful in clarifying the taxonomic diversification concerning this genus.Further population genetic studies using these markers will enable us to elucidate the level of present and historical dispersal and recruitment between these areas, Neoverruca sp. was collected at the Iheya Depression  in the Okinawa Trough during cruise of R/V “Kaiyo” (Cruise No. KY11-02 Leg. 2), using the remotely operated vehicle (ROV) “Hyper-Dolphin” (Dive No. HPD#1245). Specimens were preserved in ethanol, and genomic DNA was isolated using proteinase K and phenol-chloroform extraction. DNA was further purified using ethanol precipitation and a QIAquick PCR purification kit . Extracted DNA was sequenced as 300 bp paired end reads using a MiSeq sequencer , according to manufacturer’s instructions. Sequencing adapters were trimmed with fastq-mcf in ea-utils version 1.1.2-537 [For isolation of whole genomic DNA, Neoverruca sp. collected at the Iheya North field  with aforementioned procedures and conditions. These specimens were collected at the Alice Springs field  were calculated with GenAlEx version 6.5 [N. brachylepadoformis. In addition, the number of alleles, expected and observed heterozygosity, and deviation index from Hardy-Weinberg equilibrium were also calculated in N. brachylepadoformis. To estimate the level of genetic differentiation between populations of Neoverruca sp. and N. brachylepadoformis, pairwise FST was calculated using GenAlEx focusing cross-species amplifiable loci. The test for statistical significance was based on 999 random permutations.For successfully amplified microsatellite loci, the number of alleles, expected and observed heterozygosity, and deviation index from Hardy-Weinberg equilibrium (sion 6.5 . The sofsion 6.5  performesion 6.5 ,14,15 unNeoverruca sp. to estimate the processes of population formation and maintenance. In addition, nine of the primers can amplify microsatellites in N. brachylepadoformis. These markers are expected to help elucidate genetic diversity, differentiation, classification, and evolutionary processes in the genus Neoverruca.Twelve microsatellite loci developed in this study were successfully amplified and should have utility for further population genetics of