Increasing concern is directed towards genetic diversity of domestic animal populations because strong selective breeding can rapidly deplete genetic diversity of socio-economically valuable animals. International conservation policy identifies minimizing genetic erosion of domesticated animals as a key biodiversity target. We used breeding records to assess potential indications of inbreeding and loss of founder allelic diversity in 12 native Swedish dog breeds, traditional to the country, ten of which have been identified by authorities as of conservation concern. The pedigrees dated back to the mid-1900, comprising 5–11 generations and 350–66,500 individuals per pedigree. We assessed rates of inbreeding and potential indications of loss of genetic variation by measuring inbreeding coefficients and remaining number of founder alleles at five points in time during 1980–2012. We found average inbreeding coefficients among breeds to double–from an average of 0.03 in 1980 to 0.07 in 2012 –in spite of the majority of breeds being numerically large with pedigrees comprising thousands of individuals indicating that such rapid increase of inbreeding should have been possible to avoid. We also found indications of extensive loss of intra-breed variation; on average 70 percent of founder alleles are lost during 1980–2012. Explicit conservation goals for these breeds were not reflected in pedigree based conservation genetic measures; breeding needs to focus more on retaining genetic variation, and supplementary genomic analyses of these breeds are highly warranted in order to find out the extent to which the trends indicated here are reflected over the genomes of these breeds. Similarly, strategies for safeguarding the genetic diversity of such species should be developed and implemented over this time period .Domestic animals are often bred under strong selection that focuses on a few specific traits, and this type of breeding is considered to result in loss of genetic biodiversity both in the form of entire breeds–typically old, traditional, local ones–and in variation within breeds . IncreasFood producing animals have been the main targets for conservation actions , but horThe domestic dog renders increased socio-economic importance due to its many roles in modern society. Dogs of different breeds are used for human therapy, sports activities, herding, hunting, medical research, identifying biological material, companionship, as well as in police, customs, military, rescue, and security work, , 12, 13.At the same time, recent research indicates that within breed genetic diversity is rapidly depleted , 16, 17 In this study, we used extensive pedigree data provided by the Swedish Kennel Club comprising the past few decades to assess rates of inbreeding and loss of intra-breed variation measured in terms of number of founder alleles , 23 in 1www.skk.se; a kennel club is a nationwide organization which works and cares for purebred dogs in a country). SKC was founded in 1889 and their computerized studbook database was created in 1975–76. The database comprises pedigrees of almost all dog breeds kept in Sweden and approximately 90 percent of pedigree dogs in Sweden are included in these records .Pedigree data for the 12 Swedish domestic dog breed populations used in this study was obtained from the Swedish Kennel Club  and reviewed these plans to find out whether 1) retention of genetic variation is an explicit breeding goal for the separate breeds, 2) whether disease control programs for genetic diseases/disorders are considered for the breed. The strategic breeding plans are produced by breeding clubs associated to the SKC, and SKC has requested breeding clubs to produce and continuously revise such plans for each breed since around year 2000. We downloaded and used the plans that applied in 2012 from the SKC website .Ten of the 12 breeds have been classified as of Swedish national conservation concern , 24 Tab. The datTo monitor potential temporal trends we analyzed levels of inbreeding and loss of founder allele variation (see below) at five points in time including dogs alive on December 31 in the years of 1980, 1990, 2000, 2006, 2012, respectively. To determine the number of live dogs at the five points in time we had to make assumptions about the longevity of dogs. This is because the SKC studbooks do not include information on date of death of separate individuals. We assumed that each dog lives for 12 years after its date of birth. For example, a dog born on January 1, 1999 was assigned a date of death on January 1, 2011. Thus, our analysis of dogs alive in e.g. December 31, 2000 includes animals born between January 1, 1989 and December 31, 2000. Using this definition the number of living individuals as of December 31, 2012 ranged from 149 (Gotland hound) to 17,483 (Swedish elkhound).The SKC pedigrees include individuals of other countries if such individuals have descendants in the Swedish populations. Thus, when a dog is imported, or when a Swedish dog is mated to a dog abroad, pedigree information a few generations back that include dogs with foreign registration numbers are included in the Swedish studbooks. We have always excluded such dogs among those classified as alive since these dogs do not exist within the Swedish populations. We only included dogs with a Swedish registration number as being alive and dogs with foreign registration numbers that should be alive according to the maximum age of 12 years criterion have been marked as dead, while they do not belong to the Swedish population. A complete date of birth is required for the applied pedigree software (see below) and we therefore assigned suitable dates of birth to individuals lacking this data  based on existing information (i.e. birth dates of parents and/or offspring in the studbook). We used the mPed software  to perfoF) and mean kinship (MK) quantify probabilities of identity by descent (IBD) of such alleles, within and between individuals, respectively [fge) [fge is the number of equally contributing founders from which no random loss of alleles has occurred that represent the same amount of variation as that retained in the living population. fge should be compared to the true number of founders; difference results from loss of founder alleles and uneven genetic contribution of separate founders to presently living individuals [Pedigree analysis was used to assess inbreeding and loss of genetic variation in relation to the population founders over the time period monitored. A founder is an individual unrelated to all other individuals in the pedigree except for its descendants; at any random locus, it carries two hypothetical, unique founder alleles. The coefficient of inbreeding (ectively . Geneticly [fge) . fge is ividuals .Ne) defined in two ways: 1) as per generation average effective population size over the analysis time span, and 2) as “current effective population size” of the living population based on the number of living males and females that have produced offspring using the equation Ne = 4NmNf/(Nm+Nf) where Nm = number of live males that have reproduced and Nf = number of living females that have reproduced [We used the Population Management x software (PMx)  to obtaiproduced .To evaluate potential differences in the parameters assessed over time within breeds we used analyses of variance tests (ANOVAs) performed with MS Excel and R 2.12.2. The latter software was also used for Kruskal-Wallis tests. Two-factor ANOVAs were performed in MS Excel. Because of the unbalanced data sets with large differences in number of observations per breed and point in time, we used two-factor ANOVAs without replication. MS Excel was also used for t-tests and linear regression analyses.The size, depth (number of generations), and number of founders of the full pedigrees as of December 31, 2012 varies greatly for separate breeds . The numF) over the studied breeds increase over the five points in time from 0.033 in 1980 to 0.066 in 2012, exceeding the level of first cousin mating (F>0.0625) in both 2006 and 2012 . Similarly, there is no correlation between F and the number of founders at any of the points in time , suggesting that, contrary to what might be expected, the number of founders or the population size does not explain inbreeding levels. For the Gotland hound, census numbers have been consistently low over the study period with the number of animals regarded as alive never exceeding 180. Similarly, the number of founders is very low for this particular breed (maximum of 15 in 1990) and average levels of inbreeding is also highest in this breed with average F = 0.10 in 2012. Breeds like the Swedish lapphund and the Swedish vallhund, however, reach almost as high average F—0.09—in spite of pedigree sizes of several thousand individuals, census sizes of well over 1000, and over 50 founders. Similarly, the Swedish elkhound and the Drever have pedigrees comprising over 50,000 dogs, with over 10,000 defined as alive in 2012 but average F is over 0.07.The recent rates of inbreeding that we were able to monitor with the existing pedigree data is relatively extensive and the average coefficient of inbreeding  and point in time . This analysis included all five points in time and only the nine breeds for which results from all time points are available  and among points in time .Inbreeding increases over time as expressed by a significant linear relationship between time and average inbreeding coefficient per breed , but significant differences between the three time points  are lacking . The Hamilton hound lacks results from the full five point time series . The observation of differences in inbreeding levels between breeds and between time points is supported also when quantifying inbreeding in terms of MK or as average Ne over generations (data not shown).Breed differences persist also over the final part of our time series, 2000–2012 (e series  but has b) in the range 0.001–0.004, and all P-values <<0.001. These observations are consistent for the Gotland hound, Swedish white elkhound and the Danish-Swedish farmdog both with and without the 1980 data.When analyzing each breed separately there is a weak but consistent increase of inbreeding over time within all breeds  with linLoss of genetic variation measured as number of remaining founder alleles over the monitored time period is extensive. In 2012 the proportion of remaining founder alleles ranges from 0.13 (Hamilton hound) to 0.49 (Danish-Swedish farmdog) with an average over breeds of 0.29. This suggests that on average 70 percent of the genetic variation measured by this pedigree based parameter has been lost over a c. 5 decade period representing around 8 generations . The range of fge among live dogs in 2012 is 3.3–11.5 with the Gotland hound representing the lowest values and the Swedish white elkhound the largest  and between breeds . Similar variation in proportion of remaining founder alleles exists over the last part of the period , and is observed also when retention of genetic variation is measured as the number of fge per founder. Two-factor ANOVAs without replication for fge over 1980–2012 gives between breeds F8,32 = 7.39 (P<0.0001) and between points in time F4,32 = 6.69 (P<0.001). The same test gives equivalent results for fge over 2000–2012 .There is a highly significant negative trend over time in the proportion of remaining founder alleles, but the variation among breeds is quite large .The Swedish lapphund exhibits prcd-PRA—an eye disease that results in blindness. The defect is caused by a single autosomal, recessive allele . The SKCF, MK, fge). The removal did not affect average inbreeding among remaining animals , and neither was mean kinship (MK = 0.085 versus 0.084) or fge (5.95 versus 5.93) among remaining animals affected.We analyzed the effect on the conservation genetic status of the Swedish lapphund population of removing not only type C dogs but also type B dogs (heterozygous carriers) from the population. We proceeded as follows: from the population of animals classified as alive (using the assumption 12 years as the maximum age) as of December 31, 2012 we removed type B and C dogs. This resulted in removal of 34 percent of the population. We then assessed the variables studied , mean kinship (MK = 0.089 versus 0.084), or fge (5.63 versus 5.67).We also analyzed the Swedish lapphund pedigree in regard to an additional hereditary defect that occurs in the population—hip dysplasia. This defect is also considered hereditary , and we F = 0.040 versus 0.041 with and without removal, respectively), mean kinship (MK = 0.044 in both cases) or fge (11.31 versus 11.32). For the Swedish white elkhound average inbreeding with and without removal were F = 0.018 in both cases, mean kinship was MK = 0.043 versus 0.044 with and without removal of HD affected dogs, and fge was 11.43 versus 11.49.The same pattern regarding conservation genetic effects of removing dogs affected with hip dysplasia (HD) were observed in the Danish-Swedish farmdog and Swedish white elkhound populations. Excluding HD affected dogs  for Danish-Swedish farmdogs did not affect average inbreeding among live animals in 2012  increases over this period and in 2012 averages for separate breeds are in the range Inbreeding  over generations is slightly above the critical level of 50 [Ne is below this level.Effective population size  and has long been applied within the context of maintaining endangered wild animal species in zoos [Genomic marker-based measures have been suggested to outperform pedigrees , 42, but in zoos . A recen in zoos .fge/number of founders = 3.31/12 = 0.276) which is much higher than for any of the other breeds. Similarly, current Ne/N is highest (0.16) for the Gotland hound and the proportion of remaining founder alleles is around 50 percent which is the highest retention observed .With respect to the situation for the 12 breeds investigated in the present study current breeding goals are not well met with respect to retention of pedigree measured genetic variation. An exception is the Gotland hound which is numerically very small but where several quantities indicate that breeding has been carried out well from a conservation perspective. The ratio of remaining founder genome equivalents to the number of founders is almost 30 percent for this breed . This recommendation is not met for 8 of the 12 breeds where average F of the living population exceeds 0.0625 at one or more points in time, and the upper range is practically always well above F = 0.0625  implying a per generation Ne ≥100. This criterion is violated for all breeds over the full study period.The Swedish Kennel Club recommends that mating resulting in = 0.0625 . SimilarNe/N , and we therefore describe them briefly here. The FAO categories include Extinct, Critical, Critical-maintained, Endangered, Endangered-maintained, Not at risk, and Unknown. The category Extinct is met when the breed no longer exists or when only individuals of one sex remain. Critical is met if i) the total number of breeding females is less than or equal to 100 or ii) the total number of breeding males is less than or equal to five; or iii) if the overall population size is less than or equal to 120 and decreasing and the percentage of females being bred to males of the same breed is below 80 percent.The FAO criteria for threat classification  have beei) the total number of breeding females is greater than 100 and less than or equal to 1,000 or ii) the total number of breeding males is less than or equal to 20 and greater than five; or iii) if the overall population size is greater than 80 and less than 100 and increasing and the percentage of females being bred to males of the same breed is above 80 percent; or iv) if the overall population size is greater than 1,000 and less than or equal to 1200 and decreasing and the percentage of females being bred to males of the same breed is below 80 percent. The classification as Critical-maintained or Endangered-maintained implies that the category Critical or Endangered is met but that active conservation programs are in place. Category Not at risk refers to when none of the threatened criteria are met, e.g. the total number of breeding females and males are greater than 1,000 and 20, respectively, or if the population size is greater than 1,200 and the overall population size is increasing.The Endangered category implies that There are obvious shortcomings of the FAO classification system (as of any such system). For instance, no direct genetic parameters are included . HoweverThere is an ongoing discussion of potential conservation genetic effects of imposing selective breeding aiming at removing hereditary disorders in these breeds. Animals with a diagnosed defect can, in many cases, still be used in breeding. For example, dogs with diagnosed hip dysplasia can be used in breeding although the SKC and breed clubs often recommend that they are not. Similarly, animals that are known carriers of the allele that causes progressive retinal atrophy (PRA) can be used in breeding if they are mated to documented (through genotypic screening) non-carriers. Dogs homozygous for the PRA-allele cannot be used in breeding. One reason for allowing the use of carriers in breeding is because if those animals are selected against this would result in extensive loss of genetic variation.Previous studies on wild animals bred in captivity for conservation purposes have shown that evaluation of effects of selective removal of animals carrying single deleterious alleles must be carried out on a case by case basis. For instance, removing high probability carriers of a single allele causing blindness in a captive wolf population did not affect retention of overall founder genetic variation. In contrast, removal of high probability carriers of an allele causing albinism in a captive brown bear population could not be done without substantial loss of genetic variation ..Our present results indicate that selective removal of affected animals can often be carried out without further loss of founder genetic variation. For the present breeds this seems to be the case for hip dysplasia in the Swedish lapphund, the Swedish white elkhound, and the Danish-Swedish farmdog and also for progressive retinal atrophy in Swedish lapphund.MK rankings are included when selecting animals for breeding. Further, a larger portion of existing dogs should be used in breeding. For the breeds of the present study current census sizes imply that future increase of inbreeding and loss of genetic variation has the potential to be miniscule if more dogs are used in breeding and extreme variation in offspring production between separate dogs are avoided. We note that both software applied here (PMx and mPed) are freely available and genetic monitoring using pedigree data is a cost effective method to improve breeding from a conservation perspective. It is important, however, that supplementary genomic studies are conducted for these and other dog breeds in order to find out, e.g., how well the pedigree measurements reflect genomic inbreeding and levels of genetic variation.In order to reduce the rate of loss of genetic variation and increase of inbreeding that has been documented in many dog breeds we recommend that conservation genetic criteria such as http://www.cbd.int/sp/). Thus, we urge for continued monitoring of these populations including the use of genomic tools. We also stress the importance of documenting dates of death of separate dogs in the SKC database to provide an opportunity of obtaining as correct a picture as possible with respect to the conservation genetic situation.Our present analysis does not cover much of the period 2010–2020 during which the Strategic Plan of the Convention of Biological Diversity applies and where a specific Target referring to genetic diversity of domestic species applies Click here for additional data file.


Ustilago hordei genome was mined for microsatellite distribution and their application in defining population structure and genetic variation. To dissect the molecular variation and genetic structure of U. hordei, 59 fungal isolates representing two distinct agro-ecological zones of India were analyzed by employing simple sequence repeats (SSRs). Using bioinformatic approaches, a total of 100,239 and 137,442 microsatellites were identified from 20.13 and 26.94 Mb of assembled genomic sequences of Uh364 and Uh4857-4 isolates of U. hordei, respectively. Penta-nucleotides (31.29 and 29.75%) followed by tri-nucleotide (28.27 and 29.88%) were most prevalent in both the genomes. Out of them, 15 polymorphic microsatellites showing conservancies in both the genomes were selected for exploring population genetic structure of U. hordei. An average of two alleles per microsatellite marker was generated with band size ranging from 180 to 850 bp. Polymorphic information content (PIC) varied between 0.095 and 0.37. Fifty-nine isolates were distributed in two distinct groups with about 65% genetic similarity according to UPGMA clustering and population structure analysis (K = 2). Gene flow analysis (Nm = 1.009) reflected moderate gene flow among the analyzed population. An analysis of molecular variance (AMOVA) displayed high level of genetic variation within population (87%) and low variation among populations (13%). Linkage disequilibrium (LD) analysis indicated positively significant but relatively low standardized index of association (SIA) value in both the population sets (SIA = 0.181), advocating a state of LD with epidemic population structure. In conclusion, the newly developed neutral SSR markers are highly polymorphic within U. hordei and will be useful for revealing evolutionary history and providing deep insight into the population dynamics of U. hordei in India as well as facilitating developing management strategies for CS of barley.Barley covered smut (CS) pathogen  Ustilago hordei, is one of the most important diseases of barley (Hordeum vulgare L.). It is a seed- and soil-borne disease and fungal inocula survive in the form of teliospores on the external surface of seeds and in the soil  incited by biotrophic fungus, the soil . Usuallythe soil . At the the soil . The typthe soil . The memthe soil . CS disethe soil . Seed trthe soil . Howeverthe soil , intimidUstilago segetum tritici (Tilletia indica (Ustilago scitaminea (Ustilago maydis (Phytophthora infestans (Fusarium udum (Fusarium pseudograminearum (Colletotrichum gloeosporioides (U. hordei (U. hordei (Uh4857-4 and Uh364) is available in National Center for Biotechnology Information (NCBI) data bank1. Therefore, in the present study, attempts have been made to explore this genomic resource for identification, characterization, and development of microsatellites markers. Further, efforts have been put to characterize U. hordei isolates collected from diverse barley-growing regions of North India by validating polymorphic SSR markers and to identify various factors that determine U. hordei population structure.Traditionally, variations among fungal pathogens have been studied by analyzing the cultural characteristics, morphology, sporulation, virulence, mating type, plant–fungus physiological and biochemical interactions, and disease response on differential hosts . Unfortu tritici , Tilletia indica , Ustilagitaminea , Ustilago maydis , Phytophnfestans , Fusariuium udum , Fusariuminearum , and Colorioides . So far,. hordei  and no cU. hordei isolates (Uh4857-4 and Uh364) available in the NCBI (see text footnote 1) database were screened for SSR motifs  containing streptomycin sulfate (0.05 g L–1) and incubated for 30 min at 25 ± 2°C. Later, 100 μl of the teliospore spore suspension of each serial dilution (up to 10–5) was smeared on PDA medium for teliospore germination. Single germinating teliospore was transferred to slants containing 50% PDA , incubated at 25 ± 2°C for 3 days and stored at 4°C for further use.The single teliospore isolation method of McCluskey and Mills (1990) with minor modifications was adopted to raise the culture of U. hordei isolate was grown in liquid potato-dextrose broth (50 ml) in a conical flask (250 ml) at 25 ± 2°C with shaking at 150 rpm. After 7 days, fungal mycelium was harvested and immediately ground into a fine powder in liquid nitrogen for DNA extraction according to the procedure adopted by Each ® Green Master Mix (Promega), 0.5 pmol of each forward and reverse primer  to determine the best annealing temperature (Ta). For each SSR primer set, PCR was performed in 10 μl of total volume containing GoTaqe primer , and 25 H), and Shannon’s information index (I). The polymorphic information content (PIC) value for each SSR marker was calculated using the formula mentioned by K) was selected by testing K = 1 to K = 15 using five independent runs of 25,000 burn in period length at fixed iterations of 100,000. The optimum K-value was standardized by following the methodology of The gels were scored for the presence or absence of prominent and reproducible amplicons. Each amplicon was designated as a locus with two alternative alleles. The data of SSR amplification in different isolates were transformed into a binary data matrix as discrete variables (0 = absence and 1 = presence). The cluster analysis was performed with the NTSYS version 2.1 program  based onU. hordei, respectively  and plain (PZ) terrains. The polymorphism data for each locus are mentioned in To determine the allelic diversity among  primers  revealede) and expected heterozygosity (He) across all 15 loci in the whole population were varied from 1.3221 to 2.8792 and 0.0997 to 0.4904, respectively  was observed in the PZ population, while a lower value (1.066) was recorded in the HZ population (e) and effective alleles (Ne), the HZ population showed the least values  relative to the PZ population . Similarly, unbiased gene diversity (uHe) was the least in the PZ population (uHe = 0.5271) compared to the HZ population (uHe = 0.5903). The polymorphic loci (%) were varied from 86.67 (HZ) to 100% (PZ), with an average of 93.34% ; however, genetic variation among populations was low (13%). Pairwise comparison between HZ and PZ populations reflected very low but significant genetic distance values (P < 0.001). The average and constant level of gene flow (Nm = 1.009) was noticed between HZ and PZ populations. Pairwise comparison of HZ and PZ showed a genetic identity of 0.198 levels  grouped into cluster II, representing Punjab, Haryana, Rajasthan, and Uttar Pradesh states.U. hordei isolates, excluding loci with null alleles, demonstrated a strong signal with a single clear peak at K = 2  and a VD-value higher than the L-value was observed, advocating a state of LD  that deviated from zero in the case of both HZ and PZ populations . When iste of LD .U. hordei (Uh4857-4 and Uh364) have been released in 2013 and 2018, respectively, but, still these have not been elucidated for distribution, abundance, and frequency of microsatellite motifs. To the best of our knowledge, the present investigation provides the first comprehensive information about the microsatellite distribution and their comparison between assembled genomes of both the U. hordei isolates. Further, 15 new microsatellite markers were developed for analyzing the genetic differentiation and population structure of 59 isolates of U. hordei collected from barley field representing two different terrains (HZ and PZ) in India. In earlier reports, a small number of microsatellites developed from U. hordei genome have been utilized for analyzing the genetic variability between the isolates of U. hordei in China  in the barley sampling fields and by the observation that two different barley-growing terrains were clustered in the same lineages. Therefore, the PZ population was most likely migrated into the HZ in recent times.In the current investigation, two terrains, i.e., HZ and PZ, were chosen because they are geographically distinct from one another, differ greatly in size, and are subject to different barley cultivation and management practices. The results of the present study revealed low but significant genetic differentiation in ficients . The lowU. hordei populations (P < 0.001), whereas the rest (87%) was due to variations within population. Similarly, low variation (16%) among population of U. maydis and comparatively more variation (84%) within U. maydis population were observed in Mexico  between the U. hordei population (geographic distance between populations of 150–800 km). Therefore, migration plays a more important role than genetic drift in the case of the present study. It is also a well-established fact that in the sampling sites, the teliospores of CS fungus are proficient for travel by wind and human interventions, resulting in minimizing the genetic differences among populations. Moreover, there is also the possibility that the genetic differences in the U. hordei population may be influenced by environmental conditions, geography, and cultivation of different types of barley cultivars. Overall, it seems that gene flow mediated processes as a consequence of anthropogenic activities, such as movement and exchange of infected plant material responsible for causing significant variation among a pathogen population.An AMOVA based of microsatellite markers revealed that 13% of the total molecular variance belonged to variation among n Mexico . On paraU. hordei is a seed- and soil-borne fungus. LD analysis conducted to explore the extent of recombination within U. hordei population indicated positively significant but relatively low SIA value deviating extensively from zero in both the population sets. This clearly indicated a state of LD in both PZ and HZ populations, which might be due to the presence of epidemic isolates . These results are in line with the earlier reports of U. hordei population. Moreover, Bayesian clustering and UPGMA analysis based on polymorphic SSR markers also divided U. hordei population into two distinct genetic clusters. However, 23.72% isolates were found as admixture. These observations were similar to the earlier findings of U. hordei belonging to Tibetan areas of China. Structure analysis in the present study revealed two clusters (K = 2 with microsatellite data) and pointed toward the existence of significant structure in U. hordei populations. The population structure is composed of sub-groups formed as a result of admixture of isolates representing PZ isolates in HZ cluster and thereby highlighting a common origin source for U. hordei populations or the role of migration and gene flow among U. hordei populations.There are several reports that describe low level of genetic variation in basidiomycetes fungi . SimilarU. hordei isolates from barley fields of India. Despite geographical barriers (HZ and PZ), the observed genetic variations in the U. hordei population suggest frequent exchange of planting materials and dispersal of inocula among the barley growing regions. Migration of U. hordei isolates between barley-growing regions appeared accidental through movement of infected materials or though barley breeding linked processes. Overall, this study provides baseline information that can be further utilized to dissect evolutionary history and pathogen biology for in-depth analysis of disease dynamics, plant–fungus interactions, and development and deployment of resistant varieties and evolve effective disease management module. Moreover, genomic resources generated from this study can be used to develop novel specific primers for identification and molecular characterization of U. hordei.The microsatellite markers generated in the current investigation are very useful to decipher the genetic variability and population structure of https://www.ncbi.nlm.nih.gov/genome/?term=ustilago+hordei.Publicly available datasets were analyzed in this study. This data can be found here: PK and SK conceived and designed the work, and drafted the manuscript. PK, SK, and PJ performed the sampling survey. RK, RT, PK, AS, and PS conducted the experiments. RT, PJ, and AS performed the data analysis. SK and GS performed the final editing and proofing of the manuscript. All authors approved the submitted version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


NE)  and gene diversities (HE)  were high. None of the breeds deviated significantly from the Hardy-Weinberg equilibrium. There was no sign of significant population bottleneck for all the breeds. The inbreeding estimates (FIS) of the breeds were low . Analysis of molecular variance showed 0.6% of the total genetic variation among breeds, 1.9% among individuals and 97.5% within individuals. The global FIT, FST, and FIS estimates for the population were 0.025, 0.006 and 0.019 respectively. The analysis of population structure failed to distinguish subpopulations in traditional horses and this was supported by a high genetic exchange among the breeds. Overall, the results of this study suggest a rich genetic diversity in the traditional horse despite a very low genetic differentiation among the breeds in Bhutan.The genetic variability and population structure of three Bhutanese traditional horse breeds were assessed through genotyping of 74 horses  for 29 microsatellite DNA loci. Altogether, 282 alleles were detected across 29 polymorphic loci. The allelic diversity ( The horse is one of the most widely distributed livestock species across the globe owing to their utility in transportation and extensive use in trade and warfare in the past. For landlocked Bhutan characterized by rugged terrain and harsh climatic conditions, the highly adapted traditional horses played an unfailing role in country’s trade. The traditional horses were decsribed as intelligent, enduring and good performers in challenging environment in reports of British expeditions to Bhutan . Apart fThe estimated horse population of 13,900 ,5. On thThe overall horse population in the country has declined at an alarming rate (over 40% in a span of five years) and the risk of reduction to a critical number is immenint . The curThe genetic diversity of traditional Bhutanese horses has not been assessed using standard microsatellite DNA markers till date. Therefore, our study evaluated their genetic diversity and population structure using a set of 29 DNA microsatellite markers. The findings from the current study fills in important information gap and contribute in the strengthening of conservation and effective management of traditional horse genetic resources in the country.The study proposal including the ethical clearance was granted by the Research Committee, National Biodiversity Centre, Serbithang. The procedure of DNA sampling by pulling of hairs was considered non-invasive and a technique requiring minimal animal handling. The approval was granted vide NBC/BRD/7/2015-2016/2469 dated January 15th, 2016.2, 2.5 μg proteinase K2, PCR reaction buffer 3) at 60˚C for 1 hour and then heated to 97˚C in a thermal cycler for 1 hour. The extracts were then stored at 4°C and the stored solution was used directly for the PCR procedure.Hair samples were plucked from the mane region of horse representative of three traditional breeds . A purposive sampling was undertaken to cover around 15–20% of the breed populations , and 35 Yuta horses from 16 major Yuta horse rearing Gewog (sub-districts) of Bhutan . In all We used a set of 29 highly polymorphic microsatellite loci  which weNA) and number of effective alleles (NE), observed (HO) and expected (HE) heterozygosity, and analysis of molecular variance (AMOVA). Polymorphism information content (PIC) of each locus was quantified using Cervus software version 3.0.7 [The relatedness among the genotyped animals was examined using Coancestry software version 1.0.1.8  to rule on 3.0.7 . Furtheron 3.0.7  in FSTATon 3.0.7 . The exaon 3.0.7 , 20 fromon 3.0.7  was applDA) between a pair of breeds was estimated and used to produce a neighbor-joining tree in POPTREEW [P<0.05 as the significance level. The genetic bottleneck test was reconfirmed through a Mode shift indicator test based on qualitative descriptive allele frequency distribution.The Nei’s genetic distance  and effective number (NE) of alleles, observed (HO) and expected (HE) heterozygosities of the breeds, and polymorphism information content (PIC) values are presented in NA ranged from 5.67 (TKY294) to 12 (ASB17) with an average of 8.06 across the population. By breed, the highest mean NA and NE estimates were in Yuta followed by Boeta and the least in Sharta. Across the breeds and loci, the NE ranged from 1.85  to 8.94 . The mean heterozygosity estimates (HE and HO) were similar in all the breeds.The observed (FIS) estimate was low  and not significantly different from zero (p <0.05). There was no significant deviation from Hardy-Weinberg equilibrium following sequential Bonferroni correction. The total genetic variation was mainly within individual variation (97.5%) (p<0.05), and 1.9% (p = 0.056) and 0.6% (p<0.05) among individuals and among the breeds respectively from the analysis of the molecular variance.The coefficient of inbreeding . According to the test, a population which experienced a bottleneck exhibits a significant heterozygosity excess. This result was supported by mode-shift indicator test in which all the breed population at equilibrium shows a normal “L” shaped allele frequency distribution . AltogetFST) among the breeds was low. The F-statistics obtained by jackknifing over loci was FIT (0.025), FST (0.006) and FIS (0.019). The genetic differentiation between breeds based on Nei’s unbiased genetic distance (DA) and population differentiation (FST) between breed pairs (The genetic differentiation (ed pairs  suggest ed pairs K = 3 (FST was high (45.6) with highest between Boeta and Yuta (73.9) followed by Sharta-Yuta (32.3) and the least (30.6) in Boeta-Sharta pairs.The examination of population structure of Bhutanese traditional horse breeds through STRUCTURE program suggested a lack of definite structure  althoughK = 3 . This suHO 0.74, HE 0.75, FIS 0.02)  [NA 4.3; HO 0.59; HE 0.6) [NA 6.3, HO 0.66, HE 0.65) [NA 4.2; HO 0.70; HE 0.649) [The high PIC values of all 29 microsatellite loci used in this study showed that the markers were suitable for genetic evaluation of Bhutanese traditional horse breeds. Overall, the high genetic diversity of the traditional horse population as assessed through standard diversity indices are optimistic for the resilience to environmental changes in future. In general, the adjusted genetic diversity of Bhutanese traditional horses for the common loci was high and comparable to American horses’ study involving 50 breeds  (mean nuIS 0.02)  and fiveHO 0.72)  for 24 c HE 0.6) , Kiso hoHE 0.65)  and MiyaE 0.649) .There was no evidence of a genetic bottleneck in all traditional breeds. A recent genetic bottleneck is an important aspect to consider for conservation because it results in a loss of genetic variability, inbreeding, and expression of undesirable recessive alleles, and therefore reduce survival rates. As such the population of the horse in the country has not declined drastically until the last decade . It is iThe Yuta horses were considered as inbred in the recent past (based on phenotypic observations) ,5. The cFST) in this study corresponds to the previously reported estimates both within subpopulations of a breed as wells as between breeds. The FST estimates for the subpopulations of the Nordestino horse was 0.005 [FST as low as 0.001 (Guizou and Luoping horses) [The levels of genetic differentiation (as 0.005  and Thoras 0.005 . Among t horses) , 0.002 ( horses)  are repoThe lack of population structure and high gene flow among the traditional breeds in this study also suggests the potential interbreeding among the breeds. Further, the absence of salient distinguishing phenotypes among the traditional breeds ,6 supporIn summary, this study suggests the traditional horse breeds of Bhutan are genetically less differentiated. Nonetheless, a high individual genetic diversity provides an optimistic outlook for the survival of the declining traditional horse population with appropriate management interventions.S1 Fig(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLS)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S1 Text(TXT)Click here for additional data file.S2 Text(TXT)Click here for additional data file.S3 Text(TXT)Click here for additional data file.S4 Text(TXT)Click here for additional data file.S5 Text(TXT)Click here for additional data file.


Signal transducers and activators of transcription (STATs) mediate essential signaling pathways in different biological processes, including immune responses, hematopoiesis, and neurogenesis. Among the STAT members, STAT3 plays crucial roles in cell proliferation, survival, and differentiation. While STAT3 activation is transient in physiological conditions, STAT3 becomes persistently activated in a high percentage of solid and hematopoietic malignancies , thus contributing to malignant transformation and progression. This makes STAT3 an attractive therapeutic target for cancers. Initial strategies aimed at inhibiting STAT3 functions have focused on blocking the action of its activating kinases or sequestering its DNA binding ability. More recently, the diffusion of proteomic-based techniques, which have allowed for the identification and characterization of novel STAT3-interacting proteins able to modulate STAT3 activity via its subcellular localization, interact with upstream kinases, and recruit transcriptional machinery, has raised the possibility to target such cofactors to specifically restrain STAT3 oncogenic functions. In this article, we summarize the available data about the function of STAT3 interactors in malignant cells and discuss their role as potential therapeutic targets for cancer treatment. Intracellular signal transduction allows for the transmission of extracellular stimuli from the cell surface to a variety of intracellular targets to modulate the biological functions of a cell. Signal Transducers and Activators of Transcription (STATs) represent a family of latent cytoplasmic transcription factors involved in several pathways activated by both extrinsic and intrinsic signals that ultimately lead to the expression or repression of target genes involved in cell proliferation, apoptosis, inflammatory response, and angiogenesis .The STAT family comprises seven members , which share conserved domains, such as the N-terminal coiled-coil domain, the DNA binding domain, a linker, the Src-homology 2 (SH2) domain, and the C-terminal transactivation domain [Typically, STAT3 activation is triggered by the binding of cytokines and growth factors to their related receptors. For example, members of the IL-6 family of cytokines are potent activators of STAT3, mediating their signal through the pleiotropic gp130 receptor subunit that recruits and triggers the activation of the Janus kinase (JAK)2 by transphosphorylation . JAK2 caBesides tyrosine and serine phosphorylation, STAT3 functions in cancer cells can also be elicited by the fine tuning of other post-translational modifications (PTMs), such as methylation ,19, ubiqTargeting STAT3 is an appealing anti-cancer strategy and the multi-step process of STAT3 activation allows multiple points for inhibiting its oncogenic functions. Upstream kinases, such as JAKs, are among the STAT3 pathway components that have been targeted for cancer therapy. Such kinases tyrosine-phosphorylate STAT3, thus increasing its nuclear shuffling and transcriptional activity . HoweverBecause STAT3 mediates distinct biological effects by interacting with specific cooperating proteins, another strategy to inhibit oncogenic STAT3 functions might be the identification of tumor-specific STAT3 critical cofactors. In certain human cancers, the expression of critical oncogenes is driven by large regulatory elements, called super-enhancers, which are more densely bound chromatin regulators, transcriptional coactivators, and cofactors compared with their normal counterparts . Thus, dIn this review, we summarize the role of STAT3-interacting proteins in malignant cells and discuss their potential as therapeutic targets for cancer treatment.In the last 20 years, several studies have identified and characterized a wide range of STAT3-interacting proteins in malignant cells able to modulate the activity of this transcription factor in a positive or negative manner in different cell compartments .Such molecules, which can be considered, in all respects, potential valuable targets for cancer therapy, are summarized in STAT3 interactors can positively regulate STAT3 activity in different cell compartments via a variety of mechanisms.In a study in 2003, Sato et al. described a role for Heat-shock protein 90 (Hsp90) in regulating IL-6 functions via STAT3 . Hsp90 iStress-induced phosphoprotein 1 (STIP1) acts as an adapter molecule that directs HSP90 to HSP70–client protein complexes in the cytoplasm, thus modulating their chaperone activity . High leThe murine homolog of the human breast tumor kinase (BRK) substrate (BKS), also known as Signal transducing adaptor protein-2 (STAP-2), was seen to be a further critical STAT3-interacting protein playing an important role in BRK-dependent STAT3 activation . STAP-2 The Fibroblast growth factor receptor (FGFR) family consists of Tyrosine Kinase Receptors involved in several biological functions and plays important roles for the progression and development of several cancers . Using aThe 14-3-3 proteins are a family of molecules that interact with other proteins through serine/threonine-phosphorylated residues and function as adapter or scaffold proteins in different signaling pathways . In partCancer/testis antigens (CTAs) are tumor-associated antigens that are typically expressed only in adult testis but inappropriately reactivated in a variety of human cancers . Song anIn order to bind the DNA and act as a transcription factor, STAT3 needs to translocate into the nucleus. Therefore, another possibility to modulate the STAT3 signaling pathway is to target proteins involved in STAT3 nuclear import. Although tyrosine phosphorylation is required for STAT3 to bind to specific DNA target sites, Liu and co-workers elegantly demonstrated that STAT3 nuclear import occurs constitutively through interaction with specific import carriers, namely importins, and independently of tyrosine phosphorylation . In partConsistently with the evidence that several tumor viruses are associated with STAT3 activation ,92, MuroThe same authors identified a new STAT3 activator, namely ADP-ribosylation factor like 2 (ARL2), which is able to mediate STAT3 transcriptional activity upon interaction with the binding partner binder of ARL2 (BART) . In vitrAnother important STAT3 interaction partner is represented by the RNA-binding protein Y14. In 2008, Ohbayashi et al. demonstrated that Y14 binds to STAT3 through the C-terminal region in the presence or absence of cytokine-induced STAT3 activation . KnockdoPAS domain containing 1 (PASD1) is a newly identified CTA demonstrated to interact with STAT3 in the nucleus by Xu and co-workers . In HeLaProline-, glutamic acid-, and leucine-rich protein-1 (PELP1) is an estrogen receptor coactivator identified as a STAT3-interacting protein by Manavathi et al. . PELP1 oMDR1, NANOG, VEGF) [Proteins interacting with STAT3 can modulate its activity independently of phosphorylation. In this context, a good example comes from Jun activation domain-binding protein 1 (JAB1). Nuclear JAB1 positively regulated unphosphorylated STAT3 DNA-binding activity through protein–protein interaction in the human colon cancer cell line Colo205 . ConversG, VEGF) . FurtherGrn gene [Granulins are glycosylated peptides derived from the cleavage of the precursor protein progranulin (88 kDa), which is encoded by the Grn gene . GranuliGrn gene ,97,98,99Grn gene . In suchGrn gene .CR6-interacting factor 1 (CRIF1), also known as GADD45GIP1, is a key regulator of cellular growth described to be involved in DNA damage and oxidative phosphorylation in the mitochondria ,101. Usic-Myc gene [Besides its conventional role in promoting oncogenic responses through the ERK MAPK cascade and the activation of STAT family members , EpidermMyc gene . InteresSTAT3 distribution and functional status in cancer cells can be modulated by acetylation. This makes components of the acetylation machinery possible therapeutic targets.Yuan and coworkers demonstrated that STAT3 interacted with the Histone acetyltransferase (HAT)p300/CREB-binding protein (CBP) complex in Hela and MCF-7 cells and it was acetylated on a single lysine residue, Lys 685, in response to cytokine treatment . STAT3 aEvidence of the crucial role of Lys 685 acetylation on STAT3 activity was given in parallel by another group in HepG2 cells . In suchGupta et al. uncovered the role of HDAC3 in regulating STAT3 activity in Diffuse large B-cell lymphoma (DLBCL) . They shBesides its canonical function as transcription factor, STAT3 plays a distinct role in the mitochondria, where it supports Ras-dependent malignant transformation , promoteUpstream activation by cytokines, growth factors, or oxidative stress phosphorylates STAT3 in Ser727, which seems crucial for STAT3 mitochondrial function . AlthougMackenzie and coworkers demonstrated the importance of targeting mitochondrial STAT3 in pancreatic cancer . They shDephosphorylation and proteolytic degradation or impairment of DNA-binding ability have been shown to participate in the negative regulation of STAT3 functions .While SOCS proteins interact with JAKs, thus reducing their tyrosine kinase activity, other inhibitors called PIAS (protein inhibitor of activated STAT) bind to activated STAT dimers and block their DNA binding activity . The firSince then, several proteins have been identified as STAT3 interactors with negative effects on STAT3 functionality. One of the first-described STAT3 binding partners with repressive activity in cancer cells is TIP60 , a protein involved in DNA damage repair, cell death apoptosis, histone acetylation, and the modulation of gene expression upon association with a number of transcription factors ,114,115.Mcl-1 [Type I interferon (IFN) induces the expression of pro-apoptotic genes and has been used in the clinical treatment of a number of tumors ,119,120.Mcl-1 .Hypermethylated in cancer 1 (HIC1) is a tumor suppressor gene that is frequently deleted or epigenetically silenced in a variety of human cancers . STAT3 wThe ubiquitin-ligase Fbw7 acts as a tumor suppressor, tagging a large number of proto-oncogenes for proteasomal degradation . RecentlIn 2013, Chang’s group identified a novel gene encoding a protein named STAT3 Interacting Protein as a Repressor (SIPAR) . They obIcardi et al. uncovered the role of Sin3 transcription regulator homolog A (Sin3a) as a repressor of STAT3 transcriptional activity . Sin3a dZhang et al. identified GRIM-19  as a specific STAT3 binding partner in different breast cancer cell lines  . FunctioMitochondrial STAT3 also interacts with Cyclophilin D (CypD) to regulate the mitochondrial permeability transition pore (MPTP) . DeletioThe transcription factor STAT3 is activated downstream of cytokines and growth factors to elicit different and sometimes contrasting effects under both physiological and pathological conditions. Inappropriate/persistent STAT3 activation is reported in a variety of clinical tumor samples, where it seems to drive multiple pro-oncogenic functions. Consistently, blockade of STAT3 in cultured cancer cells was found to inhibit cell proliferation, induce apoptosis, and stimulate immune responses. For that, STAT3 is widely considered as an oncogene and an attractive therapeutic target, although recent evidence have proved its ability to suppress malignant cell onset and/or progression in particular tumor backgrounds . Thus faIn recent years, proteomics-based approaches have shed light on STAT3 interactors and their effects on physiologic and neoplastic STAT3 functions. In particular, analysis of STAT3-containing complexes has allowed us to identify novel STAT3-binding proteins which can modulate the oncogenic activity of the transcription factor via its subcellular localization, DNA binding ability, and recruitment of transcriptional machinery. Outlining the role of such proteins might increase our knowledge about the functional regulation of STAT3 and reveal targetable elements in its signaling pathway that have previously been undervalued. This may allow a tumor-cell- and tissue-specific targeting of STAT3 while sparing healthy cells. Moreover, a comprehensive characterization of the STAT3 structural domains involved in these protein–protein interactions would permit a more selective inhibition of a cohort of STAT3 target genes with oncogenic but not physiologic functions in order to restrain therapy-related side effects.Like STAT3, the transcription factor NF-κB is aberrantly activated in many types of cancers, where it regulates, among others, genes involved in tumor cell proliferation, migration, and invasion . ImportaIn conclusion, therapeutic strategies aimed at targeting specific STAT3 interactors are likely to have potential to restrain STAT3-mediated cancer progression with limited detrimental effects on normal cells. However, studies that demonstrate their anti-tumor efficacy and lack of toxicity in relevant preclinical animal models of human cancer are lacking and urgently needed in order to better understand the feasibility of such a therapeutic approach in cancer patients.


Aedes aegypti invaded Madeira Island in 2005 and was the vector of the island’s first dengue outbreak in 2012. We have studied genetic variation at 16 microsatellites and two mitochondrial DNA genes in temporal samples of Madeira Island, in order to assess the origin of the invasion and the population structure of this mosquito vector. Our results indicated at least two independent colonization events occurred on the island, both having a South American source population. In both scenarios, Venezuela was the most probable origin of these introductions, a result that is in accordance with the socioeconomic relations between this country and Madeira Island. Once introduced, Ae. aegypti has rapidly expanded along the southern coast of the island and reached a maximum effective population size (Ne) in 2012, coincident with the dengue epidemic. After the outbreak, there was a 10-fold reduction in Ne estimates, possibly reflecting the impact of community-based vector control measures implemented during the outbreak. These findings have implications for mosquito surveillance not only for Madeira Island, but also for other European regions where Aedes mosquitoes are expanding.Historically known as the yellow fever mosquito,  The Asian tiger mosquito, Aedes albopictus, was first recorded in the European continent in Albania, in 19792. Since then, this mosquito invaded most of central and western Europe and become established in 27 countries3. Coincidently, epidemics of chikungunya and dengue have been reported over the last 20 years, notably in Italy 5, France 7 and Croatia (2010)8. Another mosquito species responsible for arbovirus transmission is Aedes aegypti, previously present in Europe until mid-20th century and re-established in Madeira and in the Black Sea region3.Arbovirus transmission is becoming an increasing public health threat in Europe, mainly due to the establishment of invasive mosquito vectors and importation of arboviruses by viremic travelersAe. aegypti was first reported in 2005, in the vicinity of Funchal city. Since then, this mosquito has subsequently expanded its distribution throughout the southern coast of the island10, being detected in Santa Cruz (East) in 2008 and in Paúl do Mar (West) in 2012 12.In the Portuguese island of Madeira, 14. This scenario increases the risk of exportation of both Ae. aegypti and viremic individuals to Europe12. In fact, the dengue epidemic in Madeira was responsible for 78 imported cases that were notified in 13 different countries, the majority corresponding to tourists that had travelled to the island during the outbreak15. To mitigate the risk of importation/exportation of virus and vectors, local health authorities perform vector control activities at the International Airport and at the Funchal harbour, and coordinate an island-wide integrated Madeira Dengue Surveillance System (MDSS), responsible for the detection of imported cases.Madeira is a famous touristic destination, mostly for Europeans, with daily flights from/to several European countries and regular stops of cruise ships14. Coincidently, phylogenetic analysis and an importation index based on the air-travel interconnectivity with dengue-endemic countries revealed Venezuela as the most likely country of origin for the circulating DENV-1 in the island16. In addition, previous studies showed that Ae. aegypti from Madeira is able to transmit dengue, chikungunya and Zika viruses18, pinpointing the potential risk of local arbovirus transmission.Despite its insular condition, Madeira has a considerable risk of importing exotic vectors and pathogens from tropical regions. This is mainly due to the strong socio-economic relations that the island maintains with South American countries, such as Brazil and Venezuela19, microsatellites20, and Single Nucleotide Polymorphisms21, provided evidence for a South American origin of the introduced Ae. aegypti population in Madeira. However, these analyses did not have sufficient resolution to precisely pinpoint the geographic origin and colonization dynamics of the Ae. aegypti Madeira population, mainly because (i) a single sample from the island was used; (ii) some of the most important putative source populations were not included. Moreover, these studies did not provide information about the dynamics of the colonization of this mosquito in the island.Previous genetic analyses involving different markers such as mitochondrial DNA, knockdown resistance associated genesAe. aegypti samples from different localities of Madeira island collected at different time-points, as well as from additional sites in South America. In addition, genetic data were integrated with global genetic data available for this species in order to address the following questions:Ae. aegypti in Madeira island?What is the population genetic structure and demographic history of Are these populations the result of a single or multiple mosquito introductions?Ae. aegypti was introduced?What is the most likely country of origin of the source populations from which In this study, we analyzed microsatellites and mtDNA genes in Fis values, indicative of heterozygote deficits. Most heterozygote deficits were detected at a single locus, AC4, which accounted for 15 out of the 48 significant tests. Micro-checker results suggested that locus AC4 had a high probability of having null alleles in all but Fx05L and PM14A samples (Supplementary Table Forty-eight out of 246 (19.5%) exact tests of Hardy-Weinberg proportions were significant  to 6.6 (88AT1) and mean He from 0.081 (AC7) to 0.789 (88AT1) . In Paúl do Mar, no significant differences in He were found between 2013 and 2014 . The proportion of unrelated individuals obtained by ML-RELATE was above 70% in all samples except for Santa Cruz. This sample had the highest frequency of related individuals (41%) with a high proportion of full sibs (15%) and backcrosses (20%).Microsatellite polymorphism in He across temporal samples from Madeira was significantly different from those of the Brazilian samples  but comparable to the sample of Caracas, Venezuela .The overall mean AR and He and AR were largely similar between larval and adult samples collected in the same locality and year  was less polymorphic, estimates of Ne) increased overtime, from a minimum of 3.4 in 2005 to a maximum of 657.0 in 2012, the year of the dengue epidemic .Significant departures from mutation-drift equilibrium were detected by heterozygote tests only under the TPM model Table . There wK values (K = 2 to K = 4) are shown in Fig. ΔK can be seen in Supplementary Fig. K = 3 clusters scenario, population partitioning corresponds to the geographic localities sampled, with distinct genetic clusters for Santa Cruz, Paúl do Mar and Funchal. The K = 4 scenario maintains the geographic substructuring but separates the samples from Funchal into two different genetic backgrounds. This genetic partitioning within Funchal was not confirmed by the DAPC analysis . All Madeiran individuals were homogenously assigned to the Ae. aegypti aegypti group. When the analysis was repeated without the African samples, the best value of K was equal to four  of 0.00317. Partial ND4 sequences were analyzed from 191 mosquitoes . However, microsatellite genetic diversity of this 2005 sample (Fx05L) is comparable to other Ae. aegypti island27 and mainland populations29. Furthermore, MDE tests did not provide evidence of a population contraction associated with a founder event mediated by only a few individuals. This may reflect a higher evolution rate of microsatellites, with mutation rates30 around 10−4–10−3, or that the size of the founding population was still sufficient to maintain a representative gene pool of this species.The lower mtDNA genetic diversity of Ae. aegypti in Funchal, possibly by maritime transportation. Funchal is the capital and the major urban centre of the island, where the international harbour is located. It was in Funchal that the first Ae. aegypti specimens were collected in October 20059. In agreement, Funchal displays the highest genetic diversity for both mtDNA and microsatellites and the largest Ne estimates recorded in Madeira, suggesting a longer established population. After the introduction, Ae. aegypti rapidly expanded eastwards and westwards of Funchal, reaching Santa Cruz in 200810 and Paúl do Mar in 201212. Again, genetic data supports an earlier colonization of Santa Cruz, judging from the higher haplotype diversity when compared to Paúl do Mar, with a single haplotype. The lower Ne estimates also agree with subsequent colonisations of those two localities after the initial introduction of Ae. aegypti in Funchal. This expansion was most probably human-mediated, through road transportation along the only highway that connects most of the southern part of the island. In fact, the pronounced island’s topography is likely to act as a natural barrier to active dispersal of this mosquito and this may be the reason why Ae. aegypti has not yet established in the northern part of the island. The influence of human movement in shaping genetic diversity, structure and differentiation was also observed on other Ae. aegypti insular populations as in the Antilles islands31 and in the Pacific region32.Both genetic and historical evidence support an initial introduction of 33. While this haplotype was only detected in 2014, we cannot exclude an earlier introduction due to the lack of sample availability from previous years in this locality.Concatenated mtDNA sequences revealed the presence of two highly divergent haplotypes separated by 23 mutation steps (COI_1/ND4_1 and COI_2/ND4_2). These two haplotypes were detected in the initial sample of Funchal 2005, providing evidence that the initial colonization was made by at least two different maternal lineages. However, the presence of a unique mtDNA haplotype (COI_3/ND4_4) in Santa Cruz may suggest one additional introduction on the island. Santa Cruz is a county where the International Airport of Madeira is located, providing an opportunity for airplane-mediated transportation of mosquitoes, an occurrence that has been previously detectedAe. aegypti in Madeira. All Madeira samples grouped in a distinct genetic cluster together with specimens from Venezuela, mainly from Caracas. Moreover, the most frequent mtDNA haplotype in Madeira (COI_1/ND4_1) is the same haplotype found in all Caracas specimens sequenced in this study. A Venezuelan origin of Ae. aegypti in Madeira is not surprising given that Madeira has an important emigrant community living in Caracas34. During summer, there is extensive movement between Caracas and Madeira because of holidaying by the migrant community. Coincidently, the only direct flight connecting Madeira and South America is between Funchal and Caracas16.Both Bayesian clustering and DAPC analyses suggest a South American origin of Ae. aegypti also agrees with the insecticide susceptibility profile of Ae. aegypti in Madeira. This population was found to be resistant to three different insecticide classes and resistance was associated with knockdown resistance (kdr) mutations F1534C and V1016I and elevated expression of detoxification enzymes35. Similarly, insecticide resistance studies in Ae. aegypti from Venezuela revealed high frequencies of F1534C and V1016I kdr mutations and increased activity of glutathione-S transferases, esterases and mixed-function oxidases37, the same profile as that observed in Madeiran Ae. aegypti.A Venezuelan origin of In addition to a Venezuelan origin, at least one introduction may have derived from Brazil. There were 7 individuals from São Sebastião, Brazil, which grouped in the Madeira/Caracas genetic cluster and 21 individuals from Madeira with genetic ancestry closest to the Brazilian/Colombian cluster. Moreover, the phylogenetic tree indicates that haplotype COI_2/ND4_2 groups in a clade in sequences from Brazil but not from Venezuela. However, this may simply reflect that the number of specimens sequenced from Venezuela was too low to capture all the haplotype diversity. Therefore, we cannot exclude the possibility of haplotype COI_2/ND4_2 also being present in Venezuela but not sampled.-Ne in Funchal consistently increased overtime from the first sample time-point in 2005 until reaching its highest value in 2012. Coincidently, 2012 was the year of the dengue epidemic on the island38. Such an increase in Ne agrees with the rapid expansion of this mosquito vector on the island. The precise ecological conditions driving this expansion are not fully understood but the mild temperate climate suitable for sustaining a mosquito population throughout the year coupled with an extensive availability of breeding sites (flower pots)13 in urban and rural areas may have facilitated adaptation and subsequent population expansion on the island14.Estimates of LD41. Interestingly, estimates of Fs-Ne did not show any trend of temporal variation. While two-sample estimates are sensitive to population fluctuations, these methods are influenced by the initial (T0) genetic variation of the population, since Ne is retrieved from an unbiased estimate of allelic variance43. Therefore, the initial low microsatellite polymorphism of the Madeiran Ae. aegypti population may have affected the sensitivity of Fs-Ne in detecting population contractions. Coincidently, Fs-Ne samples of Funchal in the order of the hundreds are within the average values obtained in a previous study analyzing a global dataset for Ae. aegypti44.The utility of genetic markers in assessing the impact of vector control on the mosquito population has been tested previously, with varying degrees of successNe significantly decreased in 2013 and 2014. Heterozygosity tests and mode-shift allele detected a recent bottleneck during this period. These results suggest that the vector control measures implemented after the dengue outbreak were effective in reducing Ae. aegypti densities. It should be emphasized that vector control during the dengue outbreak of Madeira was predominantly based on community-based larval source reduction, enforced by a strong communication campaign led by the local health authorities12. Given the high insecticide resistance of Ae. aegypti on the island, alternative non-insecticidal methods are essential to contain the mosquito population and, subsequently, prevent arbovirus transmission. In this context, larval source reduction is a valid option for Madeira. This method is also recommended by the World Health Organization as a primary vector control tool for Ae. aegypti45.After the 2012 outbreak, estimates of Ae. aegypti has recently arrived in Madeira and rapidly expanded its population size to levels able to sustain transmission of an arbovirus epidemic. The Venezuelan origin is coherent with the socioeconomic relations of this insular territory with that country and highlights the importance of monitoring mosquito populations at points of entry such as international harbours and airports. This study also provided evidence for the effectiveness of non-insecticidal vector control methods. The relatively small effective size of this island vector population may also be regarded as advantageous for the implementation of vector control tools that rely on genetically modified mosquitoes46.To conclude, Ae. aegypti in the island  were reared to adults under insectary conditions. Adults were identified to species using morphological keyset al.48 for the other Madeira samples. DNA of the individuals from Brazil and Venezuela were extracted using a Chelex100® Molecular Biology Grade resin (Bio-rad Laboratories) protocol according to the manufacturer’s protocols.Genomic DNA was extracted using the NZY tissue gDNA isolation kit  for the 2005 Madeira sample, and with the protocol of Collins 51 and are described in Supplementary Table A total of 16 microsatellites were genotyped by fragment size analysis of polymerase chain reaction amplified products. Primer sequences and PCR conditions followed previously published protocolset al.20, available in VectorBase (Project ID: VBP0000138). This database has genotypes for 12 of the 16 microsatellites genotyped in a total of 3,566 individuals from 78 countries representing Asian, African and American Ae. aegypti populations. In order to calibrate inter-lab allele scoring, 20 individuals from Gloria-Soria et al.20, kindly provided by the Jeffrey Powell laboratory at Yale University, were analysed at GHTM and the genotypes were compared with the original scorings.The genotypes obtained were integrated into the microsatellite genotypic database of Gloria-Soria The genotypes obtained for the samples here analysed are available in VectorBase (Project ID: VBP0000303).He) and the inbreeding coefficient (Fis) were estimated using GENEPOP52. The same software was used to perform exact tests of departure from Hardy-Weinberg proportions and of linkage disequilibrium (LD) among pairs of loci. Estimates of allele richness (AR) were obtained for each population by the statistical rarefaction approach implemented in HP-RARE53. The software Micro-checker 2.2.354 was used to test for the presence of null alleles  at each locus/sample.Expected heterozygosity (Ne) were made: single-sample estimates based on the linkage disequilibrium method55; and two-sample temporal estimates, based on the F-statistic of Jorde & Ryman56. Calculations were performed using NeEstimator v257. Because rare alleles may bias linkage disequilibrium Ne estimates, alleles with frequency below 0.05 at each locus were removed from the analysis.Two estimates of current effective population size (58. Expected heterozygosity estimates assuming mutation drift equilibrium (MDE) were calculated from the number of alleles and sample size under two mutation models, considered more suitable for microsatellites: the stepwise mutation model (SMM) and a two-phased model (TPM) with 30% multistep mutations (variance = 30%). Although the SMM has been considered as better suited for the type of mutation process most frequent in microsatellites (i.e. DNA slippage59), there is evidence that intermediate mutation models such as the TPM with increasing proportions of multistep mutations are less prone to detect false positives60. Wilcoxon tests were used to assess significance between observed and MDE-expected heterozygosities, as recommended for analysis with less than 20 loci61. In addition, the allele frequency distribution method was also used60. Under MDE, an L-shaped allele frequency distribution is expected, whereas a shifted distribution due to loss of low-frequency alleles is consistent with a recent bottleneck62.Evidence of recent population perturbations was assessed by heterozygosity tests as implemented in BOTTLENECK version 1.2.0263. For each pair of individuals, log-likelihood estimates are calculated for four pedigree classes: unrelated, half-siblings, full-siblings and parent-offspring.In order to assess the degree of relatedness among individuals, the maximum-likelihood method implemented in ML-RELATE was used64, in order to assess within-island population subdivision and to determine the most likely source populations of Ae. aegypti in Madeira. In a first analysis, only Madeira island samples were used. Subsequently, the Madeira island genotypes were analysed with the continental sample dataset of Gloria-Soria et al.20. Twenty independent runs were made for each value of K, which varied from one to 10 for within island analysis, including source population determination, and from one to five at the subspecies/species level. Each run was conducted with a burn-in of 100,000 iterations and 500,000 replicates, assuming an admixture model with correlated allele frequencies. The optimal number of clusters was determined following the guidelines of Pritchard et al.64 and the delta K statistic of Evanno et al.65, using STRUCTURE HARVESTER version 0.6.9466. The information from the outputs of each K was aligned by the Greedy method implemented in CLUMPP67.Bayesian clustering analysis was performed using the software STRUCTURE version 2.3.4.68, was used to visualize patterns of genetic differentiation among individual mosquitoes belonging to different genetic clusters in a two-dimensional plot. This analysis was performed with the samples from Madeira and a subset of candidate source populations selected from the Bayesian clustering analysis.Discriminant Analysis of Principal Components (DAPC), as implemented by ADEGENET69.Whenever multiple tests were performed, the nominal significance level (α = 0.05) was adjusted by the sequential Bonferroni procedure24 and protocols19. In addition to Madeira individuals, mtDNA sequences for 21 individuals from Caracas, Venezuela, were also obtained to compensate for the scarcity of sequences available in Genbank for this country. Sequences were aligned and manually corrected using BioEdit v7.0.570. For each gene, haplotype diversity (Hd), nucleotide diversity (π) and the Tajima and Fu and Li neutrality tests were computed by DNAsp v5.1071.The mitochondrial genes COI and ND4 were analysed by direct sequencing from amplified products, corresponding to 764 bp and 351 bp, respectively, using previously published primers72.In order to infer the relationships between haplotypes in Madeira, haplotype networks were constructed for concatenated COI-ND4 sequences using a median-joining algorithm as implemented in the NETWORK software73 was used to generate a phylogenetic tree based on the COI-ND4 concatenated haplotypes, obtained from sequences produced in this study and others retrieved from GenBank .The BEAST v1.8.4 softwareSupplementary InformationTable S3


The objectives of this study were to (1) simultaneously estimate genetic parameters for BW, feed intake (FI), and body weight gain (Gain) during a FI test in broiler chickens using multi-trait Bayesian analysis; (2) derive phenotypic and genetic residual feed intake (RFI) and estimate genetic parameters of the resulting traits; and (3) compute a Bayesian measure of direct and correlated superiority of a group selected on phenotypic or genetic residual feed intake. A total of 56,649 male and female broiler chickens were measured at one of two ages (Posterior means of heritability for BW, FI and Gain were moderately high and estimates were significantly different between males and females at the same age for all traits. In addition, the genetic correlations between male and female traits at the same age were significantly different from 1, which suggests a sex-by-genotype interaction. Genetic correlations between The results of the multivariate Bayesian analyses in this study showed that genetic evaluation for production and feed efficiency traits should take sex and age differences into account to increase accuracy of selection and genetic gain. Moreover, for communicating with stakeholders, it is easier to explain results from selection on  Genetic improvement of body weight (BW) and feed efficiency (FE) traits has received major consideration in the poultry industry due to their economic and environmental implications. Body weight is the live weight of birds at a given age, while feed efficiency is the ability of birds to convert kg of feed into kg of body weight gain. Among the different ways of measuring FE in poultry, residual feed intake (RFI) is a popular partial measure of FE due to its phenotypic independence of production traits, the presence of considerable variation in RFI among birds and the moderately high heritability of the trait . ClassicPrediction of RFI has been largely based on phenotypic regression of feed intake on measures of production from multiple regression analysis. This is called phenotypic RFI since direct consideration has not been given to underlying genetic regressions in the computation of RFI and it is not genetically independent of production traits. Kennedy et al.  derived n traits .Jensen et al.  extendedThus, the objectives of this study were to (1) simultaneously estimate genetic parameters for body weight, feed intake, and body weight gain in broiler chickens from a multi-trait Bayesian analysis; (2) derive phenotypic and genetic RFI and estimate genetic parameters for these traits; and (3) compute a Bayesian measure of direct and correlated superiority of a group selected on phenotypic or genetic residual feed intake.Data from 16 selection rounds (SR) for growth rate of broiler chickens, which were reared under strict bio-secure environmental conditions, were collected using procedures by Cobb-Vantress. In total, 56,649, male and female broilers with phenotypic data were available. For the first 10 SRs, body weight was recorded at Preliminary univariate and bivariate restricted maximum likelihood estimation (REML) analyses were conducted to determine whether BW, FI and Gain in males and females at the two ages should be considered as the same trait or separate traits. The REML results showed that genetic parameters were significantly different between sexes  and at the two ages  variance parameters of the 12-trait model, 3000 samples were saved for post-Gibbs analysis. Posterior means of breeding values and co (variance) components were computed as the average of samples after the burn-in period. The boa package in the R program was used to evaluate convergence of co (variance) parameters . Functioi et al. . Phenotyument}bG . For exaThe distribution of i et al. .The Bayesian measure of the direct and correlated genetic superiority of a group of selected birds was calculated as the difference between the mean of the predicted breeding values in the selected population and the mean of the population corrected for genetic trend. Unlike the classical selection index calculations, it is possible to make probability statements on the expected response to selection in the Bayesian analysis and their posterior standard deviations can be derived easily. This gives an expression of superiority of the selected group in each sample from the posterior distribution. The mean of the selected group for trait i et al.  as:6\docDescriptive statistics of the data are in Table The posterior mean and posterior standard deviations (PSD) of genetic variance, residual variance, and heritability for the 12 original traits and the eight derived traits of RFI are in Table Unlike BW traits, the heritability estimates of FI, Gain, entclass1pt{minimaThe posterior means of the genetic correlations between the 12 traits included in the multivariate model are in Table Posterior means of genetic correlations between BW and FI were moderate 0.49–0.63) for males and females at both ages. Genetic correlations between BW and Gain were also moderate (0.30–0.50) for males and females at both ages, except for the low genetic correlation (0.25) between BW and Gain for males at  for maleGenetic and phenotypic correlations between production traits and the two RFI definitions are in Table  0 Table . SimilarThe same holds true for genetic and phenotypic correlations between the two RFI definitions and Gain. Posterior means of genetic correlations between 2) Table . Similar 0 Table .Estimates of genetic and phenotypic correlations between FI and the two RFI definitions are in Table Table Table We used a Bayesian method to analyze genetic parameters for production and feed efficiency traits for male and female broiler chickens recorded at two different ages, to derive phenotypic and genetic RFI, and to estimate a Bayesian measure of direct and correlated superiority of a group of animals selected on feed efficiency traits. The Bayesian method allows posterior means of the two RFI definitions to be derived simultaneously within the model, with their posterior standard deviations, while integrating over all unknown model parameters, including “fixed” and dispersion parameters.Different authors have estimated genetic parameters for BW of males and females at different ages of broiler chickens and reported heritability estimates ranging from 0.20 to 0.53 , 10–12. In general, the different heritability estimates of BW for males and females and the lower than 1 genetic correlations of BW between males and females at the two ages suggest that there is sex-by-genotype interaction for BW and that the genetic background of BW might be partly different in male and female broiler chickens. Similarly, heritability estimates of BW at the two ages and the genetic correlations of BW between the two ages suggest that there is an age-by-genotype interaction for BW and that the genetic background of BW in broiler chickens changes between the two ages. Therefore, genetic evaluation of BW in broiler chickens should take sex and age differences in to account, otherwise assuming genetic correlations of 1 between sexes and ages and average heritability estimates across sexes and ages may decrease the accuracy of selection and genetic gain. One can argue that the genetic correlations are too high to make such a conclusion, however, they are significantly different from 1, thus male and female records as well as records at the two ages cannot simply be considered as the same trait. Instead, phenotypes on male and females and at the two ages should be considered as separate traits in order to maximize the accuracy of predicted breeding values. Considering male and female records and records at the two ages as separate traits will of course cost extra computation time, but this is negligible compared to the very expensive selection experiments and the potential improvement in accuracy and genetic gain.The heritability estimates of FI and Gain for males and females at the two ages were moderate (0.26–0.38) but lower than those reported by Aggrey et al. , i.e. 0.The significantly different heritability estimates of FI and Gain in males and females and the genetic correlations between sexes, which differed significantly from 1, suggest that the genetic background of these traits might be partially different in males and females. Similarly, the significantly different heritability estimates for FI and Gain at the two ages and the genetic correlations of the traits between the two ages, which differed significantly from 1, suggest that there is an age-by-genotype interaction between these traits. Moreover, it suggests that the genetic background of FI and Gain might differ partly between the two ages. Therefore, models for the genetic analysis of the two traits should consider the sex and age in order to increase accuracy of selection and genetic gain. The moderate genetic correlation (0.30–0.50) within production traits (BW and Gain) and between BW and FI (0.49–0.63), as well as the high genetic correlation between FI and Gain (0.82–0.89) in the current study, is not surprising since higher BW and Gain might require higher feed intake and vice versa. Case et al.  reportedPrevious studies have reported low to moderate heritability estimates 0.10–0.49) for phenotypic RFI for male and female broiler chickens at different ages  for phen, 18. In (0.20 0.0) and \doy et al.  noted a i et al.  conditioThe non-zero estimates of the genetic correlations 0.04–0.32) between 2 betweeny et al.  reportedThe estimate of the genetic variance of FI was considerably and significantly higher than the estimate for either Estimates of genetic correlations between FI and y et al. , who stanegative . In our  Nichols  noted th Nichols  reportedOur results show that direct selection on one of the 12 traits included in the model results in a positive correlated response on the other traits, including a positive correlated response in FI (results not shown), which is not desirable. The observed positive correlated responses for the traits in our study is a reflection of the moderate to high positive genetic correlations between them. The Bayesian analysis suggested that direct selection for low y et al. , who notSuperiority of the selected group was slightly but not significantly lower when selection was for y et al.  who repoy et al.  noted thOur results show that selection for FE based on Genetic parameters were estimated simultaneously for feed intake, body weight, and body weight gain using a multi-trait Bayesian analysis. The heritability estimates of the traits were moderately high but significantly different between males and females at the same age. Moreover, estimates of the genetic correlation for BW, FI and Gain between males and females at the same age were significantly different from 1, which suggests that these traits are influenced by a sex-by-genotype interaction in addition to direct genetic and maternal permanent environmental effects. Similarly, the different heritability estimates for BW, FI and Gain between the two ages within sexes and estimates of genetic correlations of BW, FI and Gain between the two ages within sexes show that there is an age-by-genotype interaction for these traits. In our study, heritability estimates for


Symplocarpus nipponicus, a member of the Araceae family, is an endangered plant in several prefectures in Japan. For the conservation of this wild species, we investigated the morphology, life cycle, and genetic diversity of three wild populations. By fixed-point observation over several years, we found that it takes at least four years for the plant to set the inflorescences consisting of spadices and spathes, and another two years for it to set mature seeds. To examine the genetic diversity in the wild population, we developed 11 novel microsatellite markers and investigated the genetic variation in three populations in Kyoto Prefecture: Ayabe, Hanase, and Momoi. The Ayabe population carried less genetic variation than the other two areas, suggesting the isolation of the habitat and thus a higher risk of extinction. Our results provide basic knowledge of the ecological aspects of S. nipponicus, as well as molecular techniques for the assessment of its genetic diversity, and thus are useful for the conservation of this endangered species. Symplocarpus is the genus of perennial plants in the family Araceae, including three species found in Eastern Asia , one in North America [S. foetidus (L.) Salisb. ex W.P.C. Barton], and one in the Far East of Russia [S. egorovii N. S. Pavlova & V. A. Nechaev]  ,2,3. AmoNechaev] ,3. The flinators . The phyhe genus ,5. InterS. nipponicus is an endangered plant species in several prefectures in Japan, and is classified as critically endangered (CR) in Kyoto Prefecture. The habitats are seriously limited, and the procession of inbreeding within a population may be causing the loss of genetic diversity, which is an important factor to recognize how a particular population is endangered [Symplocarpus, phylogenetic analyses with chloroplast DNA variation have been reported as shown above, although they sometimes cannot distinguish the intraspecific variation [S. nipponicus and assessed the intraspecific genetic diversity of three populations in Kyoto Prefecture.dangered . There adangered . The difdangered . In Sympariation ,5. Here,S. nipponicus, we traced the development of the natural population in Ayabe. They grow in the understory of the forest comprising of trees such as Cercidiphyllum japonicum and Cryptomeria japonica on wet slopes, where the penetration of sunlight through the canopy is limited  and observed heterozygosity (OH) of each marker ranged from 0.133 to 0.585, and from 0.102 to 0.243, respectively  phylogram were small in Ayabe, but relatively large in Hanase  and endangered (EN), Saitama, Tokyo, Yamanashi, Aichi, Kyoto, and Tottori; vulnerable (VU), Hiroshima; and near threatened (NT), Ibaragi, Tochigi, Toyama, Ishikawa, and Fukui (search system of Japanese red data: http://jpnrdb.com/index.html). Since this species grows in dim fields in the woods, we can consider several reasons for its endangerment: regional development for residence, the afforestation of C. japonica that could have changed the ecosystem around the habitat, or recent climate change such as global warming. Also, significant deviation from the Hardy–Weinberg equilibrium in Ayabe and Momoi suggests that there are some modes of non-random mating such as inbreeding and population subdivision within these populations.We unveiled the life cycle and genetic variation of S. nipponicus takes more than four years to set flowers, since they germinate from seeds. During vegetative growth for a couple of years, they may accumulate photosynthesized carbohydrates in roots, and afterwards, they enter the reproductive phase to set seeds. The plant germinates in autumn, expands leaves in spring, and generates inflorescence consisting of dark purple spathe and spadix , Hanase , and Momoi  in Kyoto Prefecture were used . Total DNA was extracted from a leaf by DNeasy Plant Mini kit . Microsatellite-enriched libraries were constructed from the total DNA of an individual from Ayabe using (CA)15 or (GA)15 biotin-labeled oligonucleotide  [S. nipponicus.Leaf tissues of 62 individuals were collected from three habitats  and non-fluorescent reverse primer. The PCR products were analyzed with a CEQ8000XL DNA sequencer  for scoring the fragment size of each locus. Finally, 11 primer pairs were selected as polymorphic microsatellite markers. The expected and observed heterozygosity (EH and OH), fixation index (ISF) in each population, and Hardy–Weinberg equilibrium test were calculated by Genepop version 4.2 [AN) in each population, and AN, EH, OH and ISF for each locus were analyzed by GenAlEx 6.5 [http://www.bioinformatics.org/project/?group_id=84) based on Nei’s AD genetic distance [K value (ranging from 1 to 5). The length of each run was 1,000,000 iterations following 100,000 burn-ins. Delta K [K value.PCR was performed with KAPA Taq EXtra PCR Kit  under the following conditions: initial denaturation at 94 °C for 1 min, 30 cycles of 94 °C for 30 s, 50 °C for 30 s, and 72 °C for 1 min, and the final extension at 72 °C for 5 min. Twelve primer sets that were successful in the PCR were selected for the genotyping of sion 4.2 . The numAlEx 6.5 . PhylogeAlEx 6.5  using Podistance . Populatdistance ,20. Mark Delta K  was adop