Egretta eulophotes), a globally vulnerable species, from four breeding populations across China. We assessed the levels of genetic diversity, selection pressure, and population differentiation at seven TLR loci . Using a variety of metrics , our analyses showed that genetic diversity was lower at 4 of the 7 TLR loci in the vulnerable Chinese egret compared to the more common little egret (Egretta garzetta). The selection test indicated TLRs, except for TLR5, were under purifying selection in TLR evolution, suggesting that low TLR genetic diversity in the Chinese egret may be caused by purifying selection. Moreover, analysis of molecular variance indicated low but significant population differentiation among four populations at all of the TLR loci in this egret. However, some comparisons based on fixation index analyses did not show significant population differentiation, and Bayesian clustering showed admixture. Our finding suggested that these four populations of the Chinese egret in China may be considered a single unit for conservation planning. These results, the new report of TLR genetic diversity in a long-distance migratory vulnerable Ardeid species, will provide fundamental TLR information for further studies on the conservation genetics of the Chinese egret and other Ardeids.Toll-like receptor (TLR) genes have recently been employed to assess genetic diversity, as they can be used to infer both demographic history and adaptation to environments with different pathogen pressure. Here, we sampled 120 individuals of the Chinese egret ( Loss of genetic variability and inbreeding depression may consequentially increase extinction risk for threatened species by decreasing reproductive fitness and adaptive potential and increasing disease susceptibility in a changing environment . Thus, uTraditionally, neutral molecular markers (such as microsatellites and mtDNA) have been effectively used to assess genetic variation, with further analysis to provide demographic history and determine population structure –6. HowevTLRs are an ancient family of innate-immunity genes that recognize and bind to a variety of Pathogen-Associated Molecular Patterns (PAMPs). The structure of TLRs consists of three components: the characteristic horseshoe-shaped ectodomain that directly contacts pathogens and leads to most variations, a transmembrane domain, and an intracellular Toll-interleukin 1 receptor (TIR) domain that enables downstream signal transmission , 16. As Gallus gallus, NCBI: NC_006091.5) and other avian species. According to Wang’s classification [To date, 10 avian TLR family members have been identified based on their functions and sequences in the Red jungle fowl  is a species of migratory colonial wading bird in the family of Ardeidae that overwinters in the Philippines, Vietnam, Malaysia, Singapore, Indonesia, and Brunei while breeding in Russia, North Korea, South Korea, and China [Egretta garzetta), and other reported avian species; 2) analyze selection in the evolution of TLRs in this egret; and 3) detect population differentiation and population structure for TLRs in the Chinese egret and delineate a conservation unit for this vulnerable species across China. We hypothesize that both SNPs and genetic diversity as indicated by heterozygosity, nucleotides, and haplotypes of toll-like receptor genes in the vulnerable species, the Chinese egret, are lower than those in the more common species, the little egret, due to the purifying/negative selection acting on the TLRs. To our knowledge, this is the new study of TLR genetic diversity in a long-distance migratory vulnerable Ardeid species.The Chinese egret  or little egret (E. garzetta). Blood samples were obtained by puncturing the wing vein and using a syringe to withdraw. The nestlings were immediately returned to the nest after stanching the wound with cotton. Collection of samples (feathers or blood samples of nestlings) was conducted in the morning during the breeding season, and visits to a breeding colony were restricted to a maximum of two hours per day.This research and all procedures involving collection of animal tissue in the wild were approved by the Administration Center for Wildlife Conservation in Fujian Province (FJWCA-1208). The scientific license for access to the study site was issued by the Administration Department of Xiamen Egret Natural Reserve (XMENR-1005). Feathers were plucked and blood samples (~0.5mL) were collected from nestlings (aged around 10 days) of the Chinese egret , Mantoushan , Riyu  and Xiaocaiyu . Samples of little egret were obtained from two sites in China, Xinyang  and Mantoushan . These offshore islands  represent most of the known breeding sites of the Chinese egret across China . To avoiPeasy-T1 Cloning kit , and we obtained the most accurate haplotypes of different TLR genes in this research compared with other studies using software inference. In this study, any individual included in the analysis (and reported in the results) had no missing SNP data.DNA was extracted using the universal Genomic DNA Extraction Kit Ver. 3.0 (TaKaRa) from samples (feathers or blood samples of nestlings). The Leucine Rich Repeats (LRRs) domains of TLR genes were targeted from the genome of the Chinese egret (our unpublished data), and the primer set for amplifying part of the LRRs region  was designed using the online resource Primer-BLAST . Amplifih), the nucleotide diversity (π) among sequences, Watterson’s estimator of the population mutation rate (θw) and the average number of nucleotide differences between alleles (k) were estimated by using DNAsp V6.11.01 [h and π, which were plotted graphically in Microsoft Excel 2016.After we aligned all of the sequences by using MEGA version 7.0 , phylogeV6.11.01 . Deviatihttp://www.datamonkey.org) was used to search for positively selected sites by two methods: SLAC, a fast and conservative method [p values < 0.1 for SLAC and with posterior probabilities > 0.9 for FUBAR were considered as candidates to be under positive selection. In addition, the mixed-effects model of evolution (MEME) was used to test for episodic diversifying selection in the TLRs by using DataMonkey (default α = 0.1 as significance threshold). MEME is an extension of FEL and most appropriate to detect episodic diversifying selection affecting individual codon sites. Pairwise comparison FST (9999 permutations), analysis of molecular variance (AMOVA) (9999 permutations) and Mantel tests were carried out with GenALEx 6.503. The Mantel test was performed based on 9999 permutations to investigate the isolation-by-distance relationship between the estimates of FST/ (1 − FST) and the natural logarithm of geographic distance. Geographical distance (in km) was measured using Google Earth (http://earth.google.com) based on a straight line connecting each pair of sampled populations.DataMonkey , which selects the number of clusters by simultaneously evaluating posterior probability and the Delta K statistic of [http://clumpak.tau.ac.il/) [STRUCTURE 2.3.3  was usedistic of ; the fin.ac.il/) .In this study, seven TLR  sequences were characterized in the vulnerable Chinese egret and the common little egret . The NJ In total, we found 26 (synonymous (s):non-synonymous (ns) = 16:10) and 45 (s:ns = 25:20) SNPs in the Chinese egret and little egret, respectively , and thep<0.01), indicating that TLR3 evolved under balancing selection.All TLR genes showed more synonymous than non-synonymous mutations except for TLR5 (dn/ds = 48.60) (dn/ds of TLR4 and TLR7 could not be estimated by DataMonkey due to less than three unique sequences) . Based oSarothrura ayresi), the African penguin (Spheniscus demersus), and New Zealand robin  and three more common and widespread species (the little egret (Egretta garzetta), the house finch (Carpodacus mexicanus) and the lesser kestrel . Based on seven TLRs  in these five species, we conducted a comparison of mean nucleotide diversity (π) and number of inferred haplotypes (h) (h) ranged from 2 to 20 with a mean h = 6.2, and nucleotide diversity ranged from 0 to 0.0100, with a mean π = 0.0028. Both h and π for the Chinese egret are close to the values for the New Zealand robin but were lower than in the more common species, the little egret, the house Finch and the lesser kestrel (h) in the Chinese egret was lower than in the white-winged flufftail and African penguin, although mean nucleotide diversity (π) was higher than in either species  , Fig 3.  kestrel . We also species .ST = 0.011, p = 0.043 < 0.05), and a high proportion of the total genetic variance was attributable to variations within populations (98.87%). Considering TLR3 and TLR5, low but significant genetic differentiation was present among the four populations at the 0.05 level   among these populations (ST/(1 − FST) value based on estimated molecular distances with the natural logarithm of the geographic distance   . To furtlculated . For allulations . The Man= 0.300) . STRUCTU= 0.300) ; among tclusters .Salmonella enterica in Chinese native chicken breeds [In this study, the Chinese egret had a low level of SNPs in the TLRs compared to the little egret, as in previous studies with other endangered or critically endangered species , 21, 36.n breeds .Our analysis revealed purifying selection acting on TLRs in the Chinese egret except for TLR5. No positively selected sites were detected by either method. Also, no episodic diversifying selected sites were detected under MEME, although episodic positive selection played an important role in the evolution of most avian TLRs . MoreoveSarothrura ayresi), in which genetic diversity was lower than in the common red-chested flufftail (Sarothrura rufai) in South Africa [Four in seven of TLR genetic diversity in the Chinese egret was lower compared to the common little egret in China, except for TLR3, TLR5, and TLR7 . This reh Africa , 54–58.The heterozygosity of TLR3 (Ho = 0.517) in a migratory bird, the Chinese egret, is apparently higher than the heterozygosity of TLR7 (Ho = 0.233), suggesting different pathogen selection pressures between the TLR3 and TLR7 genes . In the The heterozygosity of both TLR3 Ho = 0.517) and TLR7 (Ho = 0.233) in the Chinese egret were higher than in the little egret (TLR3 Ho = 0.110 and TLR7 Ho = 0.117) . In cont7 and TLRST values  for overall TLR loci using molecular distances, and also low but significant FST values (p = 0.020 and 0.037) for TLR3 and TLR5 although, this was not supported by TLR1LB, TLR2A, TLR4, TLR7, or TLR15. Pairwise population analysis indicated that there was no significant genetic differentiation among the four populations, in accord with our previous study [There was low but significant divergence in TLRs among populations, indicating the presence of a comparable level of gene flow among these four Chinese egret populations. This genetic exchange is most likely made by the individual movements among populations meeting in the same breeding, stopover or wintering sites during long-distance migration. AMOVA analysis showed low but significant FIn conclusion, this study reported the TLR genetic diversity in an Ardeid species by assessing seven TLR loci. Our analyses confirmed the hypothesis that both SNPs and the majority of genetic diversity of toll-like receptor genes in the vulnerable species, the Chinese egret, were lower than those in the more common and widely distributed species, the little egret, in accordance with previous reports on other threatened avian species. The selection test indicated TLRs, except for TLR5, were under purifying selection in TLR evolution, suggesting that low TLR genetic diversity in the Chinese egret may be caused by purifying selection. Moreover, among the four populations in this egret, molecular variance analysis showed low but significant genetic differentiation at TLR loci, pairwise population analysis indicated that there was no significant genetic differentiation, and Bayesian analysis revealed the populations had high levels of admixture in structure. Taking account of these three results together as a whole, the four populations of the Chinese egret in China should be considered as a single adaptive unit for conservation. These new results may provide fundamental TLR information for further studies on the conservation genetics of the Chinese egret and other Ardeids.S1 FigThe bootstrap values are displayed at each branch point.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableN Number of samples, Ho mean observed heterozygosity, He mean expected heterozygosity, uHe unbiased expected heterozygosity.*20 samples were randomly sampled from 120 samples three times, and the average value was obtained. (DOCX)Click here for additional data file.S1 Appendix(XLSX)Click here for additional data file.


We investigated this question for 11 taxa across five genera. In this first study analysing and optimizing ex situ genetic diversity across multiple genera, we found that the percentage of extant genetic diversity currently conserved varies among taxa from 40% to 95%. Most taxa are well below genetic conservation targets. Resampling datasets showed that ideal collection sizes vary widely even within a genus: one taxon typically required at least 50% more individuals than another (though Quercus was an exception). Still, across taxa, the minimum collection size to achieve genetic conservation goals is within one order of magnitude. Current collections are also suboptimal: they could remain the same size yet capture twice the genetic diversity with an improved sampling design. We term this deficiency the ‘genetic conservation gap’. Lastly, we show that minimum collection sizes are influenced by collection priorities regarding the genetic diversity target. In summary, current collections are insufficient (not reaching targets) and suboptimal (not efficiently designed), and we show how improvements can be made.Effectively conserving biodiversity with limited resources requires scientifically informed and efficient strategies. Guidance is particularly needed on how many living plants are necessary to conserve a threshold level of genetic diversity in  These collections also help safeguard species from extinction, especially when species' native habitats become uninhabitable. Currently, 14 300 plant species are classified by the International Union for Conservation of Nature Red List as threatened with extinction (greater than 10% chance of extinction in less than 100 years) including 63% of cycads and 40% of conifers, but most plant species have not been assessed. Meanwhile, many millions of populations of mammal species have already disappeared owing to habitat loss [in situ and ex situ conservation approaches is recommended to prevent extinction and ensure that genetic diversity necessary for long-term species survival is maintained [tat loss ,3. A sciintained .https://www.cbd.int/sp/targets/) have committed to ‘preventing genetic erosion’ and ‘safeguarding genetic diversity’. Meanwhile, the United Nations Sustainable Development Goal 2.5 (https://sustainabledevelopment.un.org/) focuses on agricultural biodiversity and food security via seed banks, and the Global Strategy for Plant Conservation  commits to preserving 70% of genetic diversity of crops, wild relatives and other economically or culturally valued species by the year 2020. Actions to date are far from sufficient [in situ and 40% ex situ . Progre species , and witovenance . Thus, mex situ collections of species that are very difficult to conserve ex situ [sensu [There is a particular challenge for  ex situ . While su [sensu )—plants ex situ collection; see also [et al. [Zamia) and showed that less genetic diversity will be captured in the species with a lower frequency of flowering and fewer reproductive individuals. In spite of this foundational work, the question remains open as to what primary factors (such as shared traits within a genus) could lead to quantitatively similar collecting strategies.Standard collection sizes have been established using simple probability equations and are frequently applied to many species  from five genera spanning much of the seed plant tree of life . All are relatively long-lived, threatened species whose seeds cannot be seedbanked owing to inherent seed physiology or ecological factors. Specifically, we:—ex situ collections—how well do ex situ collections, as they are today, represent the wild populations?determine how much genetic diversity has been captured in present-day —could be captured by varying collection sizes, assuming random sampling;resample the wild population genetic datasets to determine how much genetic diversity —calculate minimal collection size needed to capture 70% and 95% of the genetic diversity;—test the influence of genus on the minimum collection needed to capture the genetic diversity and on a new statistic we term the ‘genetic conservation gap’; and—test other factors including species' genetic structure (reflecting fragmentation and gene flow) and allele frequency spectrum (reflecting demographic history).In this paper, we present such a comparative study. We use genetic datasets and resampling algorithms to determine appropriate 2.(a)ex situ as living plants; (ii) they cover a broad phylogenetic range , so our results can be applicable across plant groups; (iii) they represent variation in geographical ranges or numbers of populations; and (iv) all are threatened taxa, and some are critically endangered.We selected our target perennial trees and shrubs , are endemic to the island of Kaua‘i in Hawai‘i. Both are threatened by habitat degradation, non-native herbivores, competition by invasive plants, seed predation by insects and a possible decline or loss of native pollinators. Hibiscus waimeae subsp. hannerae is rarer—approximately 200 adult individuals from three valleys remain and little or no regeneration occurs. Magnolia ashei  is a small deciduous tree with large leaves and flowers that occurs in only 10 counties in Florida (dataset presented in [Magnolia pyramidata (synonym: Magnolia fraseri var. pyramidata) is a medium-sized deciduous tree reported from Texas to South Carolina, though with few occurrences in most states, except southern Alabama and northwestern Florida. Pseudophoenix ekmanii (Arecaceae) is restricted to a small area of the Dominican Republic and threatened by illegal destructive harvesting of sap. Pseudophoenix sargentii, the sister species of P. ekmanii, has the widest distribution of its genus, from Florida to Belize and east to Dominica, yet populations are isolated and locally imperiled. Quercus georgiana (Fagaceae) is a specialist on stone outcrops known from small, fragmented populations in Alabama, Georgia and South Carolina. Quercus boyntonii is a small tree occurring on sandstone outcrops in a few counties in Alabama, making it one of the most range-restricted United States oaks. Quercus oglethorpensis, formally described in 1940, occurs in sparse isolated populations across the southeast, also in granite outcrops. Zamia decumbens (Zamiaceae) is a slow-growing infrequently reproducing cycad from southern Belize, with less than 500 extant plants, while Zamia lucayana is a fast-growing, frequently coning cycad from the Bahamas, with one population of fewer than 1000 plants on a single island (here we expand on the dataset from [We studied taxa from five genera. Two subspecies of ented in ). Magnolset from ).(b)In situ populations were identified via Global Biodiversity Information Facility (GBIF) occurrence data and local collaborator networks. We attempted to sample as many wild populations as possible and to best represent the wild extant genetic diversity. Ex situ locations were identified via Botanic Gardens Conservation International's PlantSearch (https://members.bgci.org/data_tools/plantsearch), Beckman et al. [in situ adult plants and ex situ adult and seedling plants. DNA was extracted using standard methodologies , quantified and diluted. Approximately 10 microsatellites were amplified on each species using PCR and analysed using automated DNA sequencers such as ABI 3730. The software Geneious was used to call alleles and export data to .csv files.n et al.  and pers(c)is currently conserved in gardens, for each species, and how much genetic diversity could be conserved with different collection sizes. All code and five datasets are available at: https://github.com/smhoban/IMLS_Safeguarding/tree/master and https://doi.org/10.5061/dryad.zgmsbcc74 [We performed two sets of calculations on the genetic datasets: how much genetic diversity gmsbcc74 .is currently conserved was to: (i) genotype the in situ and ex situ individuals mentioned above, and (ii) calculate the percentage of in situ alleles  that are represented in the ex situ individuals  for each allele category.The approach for determining how much genetic diversity als see ,18). Thi. Thiis cdegenet’  to tabulcould be conserved under different strategies was: (i) begin with the wild, in situ population genetic dataset; (ii) computationally resample this dataset for different numbers of individuals, representing different possible collection sizes that could have been used; (iii) for each resample, calculate the percentage of alleles in each of these potential ex situ collections, relative to the total in situ dataset; and (iv) assess the relationship between potential collection size versus genetic diversity captured. R scripts and a modified version of the ‘sample.pop’ function from adegenet were used to create subsamples of the wild dataset ranging in size from two through to the total population size for each species. This procedure was repeated 75 000 times for each taxon.The approach for determining how much genetic diversity To summarize the data, compare among taxa and inform a conservationist seeking to optimize their effort, we calculate a measure of ‘sufficiency’, defined as size needed for the collection to reach a minimum target percentage of genetic diversity . We calSufficiency calculations will depend on the frequency of alleles the conservationist decides is ‘important’ ,24. Of cin situ dataset, which, for a population size of 200 diploid individuals, is a frequency of 0.005.Lastly, the conservationist may decide that some very rare alleles are negligible. For example, alleles observed in only one or two individuals have a low chance of persisting. Moreover, some alleles that occur only once or twice in a dataset may be artefacts owing to genotyping error. We therefore tested two plausible assumptions—reduced dataset, where the conservationist is either not interested in extremely rare alleles or believes they may be artefacts, and full dataset, where the conservationist is interested in the value of every allele for its potential adaptive utility. In the reduced dataset, any alleles below a predefined threshold are excluded from consideration. We used a threshold of two alleles in the We tested the influence of ‘genus’ by performing three sets of ANOVAs, for each allele category, for full and reduced datasets, all with the predictor variable being ‘genus’ and the response variable being: (i) the amount of diversity currently conserved, (ii) sufficient size to reach 70% or 95% of alleles, and (iii) genetic conservation gap. An alternative explanatory factor might be the degree of population genetic structure, with theory predicting that more structured populations need, on average, larger collections ,24. Ther3.For each question, we first present results for the reduced dataset, where alleles present in one or two copies are excluded from the analysis , and then results for the full dataset, where all alleles are retained. Across all species, 21% of alleles were present in one or two copies.(a)in situ alleles currently present in ex situ collections is summarized in P. sargentii and Z. lucayana. The percentage of genetic diversity safeguarded in collections is typically lower with the full dataset; only one species has ≥90% of genetic diversity protected overall (Z. lucayana) and none have ≥95%. Genus, population structure (FST) and allele frequency spectra were not a significant explanatory factor for ex situ conservation of any of the allele categories after Benjamani and Hochberg multiple comparison correction. However, the number of plants in current collections is a good predictor for the proportion of low frequency alleles and all alleles, showing a logarithmic relationship (The percentage of tionship .Table 2(b)in situ datasets for a number from two to the total number of individuals, we calculated genetic diversity that could be captured for each potential collection size under optimal sampling, and we then plotted genetic diversity against collection size  captured in existing ex situ collections varies from 40% to 95% for the reduced dataset , and from 28% to 91% for the full dataset . On average, larger collections capture more genetic diversity, though size is not a perfect predictor of diversity captured. Even within genera, some taxa were collected more ‘efficiently’ than others: for example, Q. georgiana safeguards equivalent diversity to Q. boyntonii in less than half the collection size (Hibiscus taxa) have at least 70% of alleles conserved (satisfying Target 9 of the GSPC). However, using the full dataset, no taxa achieve 95% and only three achieve 70%. Of course, the percentage captured depends on the allele category examined  of the other. We also did not find that population structure affected genetic diversity captured in ex situ collections or sample size needed to preserve target diversity. It is likely that biogeographical and demographic history, traits such as the frequency of reproduction and sampling strategy affect ideal sampling for genetic conservation and require a further study. Quercus was the one exception. The minimum size for all three oak species is about 80 (for the reduced dataset). All three are rare, wind-pollinated, habitat specialists, but they have different geographical distributions . Interestingly, sample size to sufficiently capture genetic diversity partially corresponds to allele frequency profiles, which may reflect demographic history, e.g. bottlenecked populations.For the main question, ‘should taxa within a genus, which tend to share many biological traits relevant to genetic diversity and structure, have similar collection sizes for safeguarding genetic diversity see also ). Genus Quercus), the taxonomic breadth of our study illustrates the ‘bounds’ of minimum size for threatened plants. On the optimistic side, results for the reduced dataset suggest that many taxa will require collections from 25 to 82 individuals to capture 95% of all alleles; more conservatively, results for the full dataset suggest 58–207 individuals. The range is dependent on the decision to include or exclude ultra-rare alleles. While some of these alleles may be genotyping errors, probably most are not; genotyping errors in microsatellites are typically 1–5%, while these alleles represent 21% of our observed alleles. In general, if nothing is known about a species' biology, demography or genetics, the sufficient minimum collection size will usually fall between approximately 30 and 200 plants if sampling randomly (though see Caveats below). This is consistent with a recent modelling study [While there is not a general ‘best’ strategy to apply to a particular genus  preserve 70% of diversity . Capturing 70% of rare alleles necessitated protecting 5–15 populations per species in situ. Their study differs from ours in that they studied widespread species, and resampled the number of populations rather than the number of individuals. Nonetheless, they demonstrated little relationship to the mating system, similar to our findings.We know of no other study analysing and optimizing k et al.  estimate(a)most real-world collections will capture significantly less genetic diversity than shown in the tables and plots in this paper—what we present are absolute minimum sample sizes.Two key differences exist between the computational resampling which we used in this study and real-world plant conservation: sampling strategy and collection attrition. These two points mean that et al. [et al. [First, the resampling algorithm chooses individuals randomly and visits all wild populations—an ideal scenario rarely reached in reality. If non-random sampling is used, Hoban & Strand  suggest et al.  and Hoba [et al. .most collections should be larger than the values shown in our figures and tables, probably multiple times larger .Second, our calculations assume that no plants in the collection die over time. However, in reality, some seeds fail to germinate, and living plants experience disease, damage and senescence ,30. If gex situ collection management necessitates further study [There are several considerations beyond the scope of this study. First, we considered rare, perennial woody plant species, and our results probably do not apply to all species. Collections for common species may need tens of thousands to millions of seeds ,28, thouer study , includier study ,36, how er study ,16.(b)ex situ collections are insufficiently safeguarding genetic diversity, and that the appropriate collection size needed to sufficiently and efficiently capture genetic diversity in ex situ collections is unlikely to be similar for taxa in the same genus, with the possible exception of Quercus. Nonetheless, optimal size across all genera is within an order of magnitude . More case studies in other genera are needed to determine the relative importance of each factor  material that has a low conservation value . Of course, redundancy is needed, with some duplicates maintained through the metacollection. Lastly, we identified a heretofore overlooked factor that may be more influential than species biology—decisions about the level and type of genetic diversity to preserve . Discussion and resolution on these questions, by the ex situ community, is needed for the quantitative optimization of ex situ collections.Our study of 11 threatened, perennial taxa demonstrates clearly that most see also ). We als


Candidatus Phytoplasma prunorum’, responsible for European stone fruit yellows disease, was investigated by the application of a combination of statistical approaches to genotype data of the pathogen sampled from cultivated and wild compartments in three French Prunus-growing regions. This work revealed that the prevalence of the different genotypes is highly uneven both between regions and compartments. In addition, we identified a significant clustering of similar genotypes within a radius of 50 km or less, but not between nearby wild and cultivated Prunus. We also provide evidence that infected plants are transferred between production areas, and that both species of the Cacopsylla pruni complex can spread the pathogen. Altogether, this work supports a main epidemiological scenario where ‘Ca. P. prunorum’ is endemic in — and generally acquired from — wild Prunus by its immature psyllid vectors. The latter then migrate to shelter plants that epidemiologically connect sites less than 50 km apart by later providing infectious mature psyllids to their “migration basins”. Such multi-scale studies could be useful for other pathosystems.Inferring the dispersal processes of vector-borne plant pathogens is a great challenge because the plausible epidemiological scenarios often involve complex spread patterns at multiple scales. The spatial genetic structure of ‘ Managing these threats requires an understanding of their epidemiological cycle, particularly the dispersal processes of pathogens in the landscape3. However, deciphering the complexity of plausible epidemiological scenarios poses a great challenge, especially since insects are involved in disease spread. Indeed, most of the vector-borne plant pathogens are transmitted by small piercing-sucking insects of the Hemiptera order, whose dispersal distances are generally only vaguely known, while searching host plants for food resources and/or reproduction4. Added to this question of dispersal distance is the issue of different host plant species that insects can occupy during their life cycle and how they move among them. In this context, a key question that often arises is the role of wild plants as a reservoir of pathogen and/or insect vectors10.Vector-borne pathogens have caused some of the most devastating plant diseases in perennial and annual crops14 and population genetics16, the development of large-scale pattern-oriented approaches to understand the processes that shape the genetic structure of a population is recent21. The basic idea of these approaches is to estimate the distance at which two samples become genetically independent by linking genetic data and spatial information obtained for a set of samples using a combination of geostatistics22 and population or landscape genetics methods23. In particular, approaches used for qualitative data comprise join counts24 and permutation tests to identify distances at which genetic similarity between pairs of individuals is significantly higher than expected by chance28.One of the first difficulties in identifying patterns of disease spread in agricultural landscapes is to determine the optimal scale of the study design. Although the spatial scale of the processes has been a central question for decades in ecologyCandidatus Phytoplasma prunorum’29 and disseminated via planting material30 or the psyllid Cacopsylla pruni 31. The phytoplasma and its psyllid vectors are widespread in Europe, including the major stone fruit production areas where the disease significantly impacts susceptible crops, particularly apricot and Japanese plum trees32. Rigorous sanitary control of nursery plants and insecticide treatments are currently the main disease-control strategies, but despite these measures, ESFY continues to economically impact European fruit growers, raising the question of the origin of contaminations.The present study focuses on a fruit tree disease known as European stone fruit yellows (ESFY), caused by ‘Prunus/psyllid pathosystem33. Two points appear essential in the dynamics of the epidemic: (i) in Europe, the pathogen is often found in wild Prunus34; and (ii) the psyllid vectors are univoltine and migrate twice a year between Prunus and conifers9. In a landscape comprising different plants on which the psyllid vectors can feed, different mutually non-exclusive scenarios of pathogen spread in orchards can be proposed  psyllids carrying the phytoplasma at a sufficient concentration for inoculation , Bas-Rhône (BR) and Valence (VA)] with different agroecological conditions and strongly impacted by the disease. There, we intensively sampled the three main hosts  of the pathogen.The goal of the present work is to improve our understanding of the spatial scale and ecological compartments involved in ESFY epidemics by investigating the spatial genetic structure of ‘Prunus bushes (mainly blackthorn) at various distances from these orchards; and (iii) mature psyllids in these bushes  gene. From the 69 infected orchards, 750 samples tested positive for the phytoplasma, and 553 imp sequences were obtained. In the 15 orchards where a systematic sampling was undertaken, 14.3% of the 1,982 sampled trees tested positive for the phytoplasma  were found to carry the phytoplasma, from which we obtained 99 sequences. Thus, 991 samples were successfully genotyped for the imp gene  plant samples in infected orchards (mainly apricot); (ii) plant samples in wild m’ Table . The preimp genotypes where genotypes I01 and I09 were the most prevalent  reached a frequency above 4%. Thus, only these six major genotypes were considered in the subsequent statistical analyses. Among the 11 other genotypes, I03 had already been described in Germany by Danet et al.35, and I10–310 was recently described in Slovenia by Dermastia et al.36 under the name I34. Nine genotypes  had never been described before , whereas genotypes I13 and I05 widely differ from all the other genotypes . The proportions of the six major genotypes significantly differed between the two species , mainly because of the over-representation of genotype I01 in species B. For the following analysis, the C. pruni complex was considered as a single epidemiological entity because performing distinct analyses for species A and B strongly reduced the statistical power.The psyllid vector In order to explore relationships among genotypes, compartments and regions, we performed a correspondence analysis on the contingency table of genotype frequencies  between compartments  and regions . Consequently, we further studied these interactions by comparing the distributions of genotypes between compartments for each region  between the visually homogeneous compartment profiles with very close values of Simpson’s diversity index D  and strong differences between the values of the diversity index D. The high prevalence of genotype I09 in the bushes and, conversely, the high prevalence of genotype I01 in the orchards contribute to this highly significant genotype dissimilarity  is also reflected by the higher value of the diversity index among psyllids than among bushes or orchards. Within each compartment, the genotypic composition significantly differed according to the growing region , although the proportion of the main genotypes for the orchards was very similar across regions , or specific local psyllid populations as seen with vectors of ‘Ca. P. mali’33. Because phytoplasma prevalence is much lower in psyllids than in bushes at the regional scale, phytoplasma acquisition from blackthorn appears to be inefficient.Several results of our study strengthen previous information on the functioning of the pathosystem. Firstly, we show that the pathogen is highly prevalent in all of the 61 tested bushes, confirming previous reports from other European countriesCa. P. prunorum’. The discovery that C. pruni is actually a complex of two cryptic species38 raised questions about their respective distribution area and vector competence. In the present study, we observed balanced species proportions . However, an additional study is needed to compare the transmission capacities of the two species.Our study also provides new information about the vectors of ‘Prunus, i.e., scenario 4 is necessary to explain this observed pattern. However, this scenario is not sufficient to explain that the genotype composition of ‘Ca. P. prunorum’ is more similar across regions for orchards than for the wild compartments  must also contribute to the long spatial range of the genotype similarity between orchards within each region  adults (scenario 5) are compatible with the persistent transmission mode. Indeed, successive inoculation events within either the orchard or the bush where an infectious vector first landed may explain (together with the planting of infected trees) that pathogen genotypes are spatially clustered within, but not between, compartments. To summarise, this field study supports and refines previous hypotheses derived from laboratory experiments9 by showing (i) that exchanges of infected plants contribute to disease spread between regions , and (ii) that pathogen spread within a region involves acquisition (mainly from wild Prunus) by nymphs and immature adults, a first migration before the summer to one of the regional shelter hubs , a second migration after the winter and (possibly multiple) inoculations within Prunus orchards after an effective latency of eight months. ESFY may therefore be seen as a self-sustaining natural pathosystem that accidentally impacts stone fruit species, particularly in apricot orchards where ESFY is essentially a monocyclic disease . Such an epidemic cycle is an extremely unusual feature for plant diseases and evokes vector-borne zoonoses like Lyme disease or West Nile fever40.No previous study has addressed the key question of the spatial scale of ESFY epidemics. In our study, we unambiguously show a sub-regional structure of the pathogen genotypes and provide new insights into the main drivers of the epidemic. In particular, we demonstrate that the genotype distribution of the pathogen in bushes differs very significantly between the three regions Fig. , which mts Figs.  and 4. Tion Fig. . The obs41, including the origin of contaminations in European orchards. Indeed, this study highlights the prominent role of wild Prunus as an indirect source of infection for apricot trees. Given the endemic nature of this disease in Europe in wild habitats32 and the wide distribution area of the psyllid vectors42, there is little doubt that the disease cycle is similar in most diseased areas. Nevertheless, our study does not rule out the possibility that attractive Prunus orchards could be a significant source of inoculum in some particular situations . Given the current state of knowledge about the pathosystem, once the disease is established in the natural environment, it would be unrealistic to consider eradication at any scale . Disease control should thus focus on the protection of orchards against the psyllid vectors during the key period of their return migration after overwintering, and on the production of healthy plants for planting .These new insights into the pathosystem fill some gaps identified in an EFSA pest risk assessmentCandidatus Phytoplasma spp.’, ‘Candidatus Liberibacter spp.’, Xylella fastidiosa), for which disease management strategies would strongly benefit from insights into the epidemiological role of wild plants or the scale of disease dispersal44. The top-down exploratory approach that we applied here can be relatively easily implemented using a single molecular marker for a clonal organism sampled from wild and cultivated compartments and a robust multi-scale statistical approach involving correspondence and join-count analyses. Further insights may be gained on the complex interaction network among host plants and insect vectors by the use of landscape genetic approaches46 to analyse the genotypes of ‘Ca. P. prunorum’ from insects collected in and at various distances from shelter sites.The approach used in this study could be applied to other pathosystems, especially in the case of plant diseases due to vector-borne bacteria  orchards (Supplementary Table Prunus cerasifera Ehrh.), European plum (Prunus domestica L.), Japanese plum  and peach (Prunus persica (L.) Batsch) trees. Most of the samples were collected from symptomatic trees during the autumn and winter of 2010 and 2011 (Supplementary Table Prunus spinosa L.) or myrobalan bushes around the plots, at up to 30–40 km . Other congeneric species where sometimes caught but C. pruni individuals were easily recognized by the colour of the forewing, which is dark brown at the apex and brown in the remaining part. Soon after identification, we conserved the samples in 96% ethanol until DNA extraction. Phytoplasma-carrying insects collected several years before in the three regions were also included in the analysis  apricot . All the Prunus samples were individually analysed. DNA from plant samples was then purified using the CTAB method48 in 1.5-ml tubes. DNA pellets were diluted in 100 µl of pure water. Total DNA of individual psyllids was purified from whole bodies, and each psyllid DNA sample was assigned to species A or B by amplifying the Internal Transcribed Spacer 2 (ITS2), as previously described37. No individual showed two bands, demonstrating that the sample was devoid of hybrids or contamination between species.The protocol used for the total DNA extraction from plant samples was adapted from Ahrens and SeemüllerCa. P. prunorum’ was detected in the insect and plant samples by using the ESFYf/r primers in a specific and sensitive PCR-based method, as described in Yvon et al.49. We then attempted to sequence the 1,328 positive samples at the immunodominant membrane protein (imp) gene locus, which was shown to be highly variable for ‘Ca. P. prunorum’35 and assumed to be present at a single copy per genome based on the known genome sequence of ‘Ca. P. mali’50, a closely related phytoplasma . DNA amplification performed well for almost all of the psyllid samples, but failed for more than a quarter of the plant samples . Chromatograms were trimmed, assembled, and aligned using the Muscle algorithm, and visually checked under Geneious (version 5.5) (http://www.geneious.com). Sequences were deposited in GenBank  to build a genotype network using the integer neighbour-joining (IntNJ) algorithm, which is well adapted for low-divergence datasets. Each infected individual contained a single imp genotype, except for six cultivated trees in which two different genotypes were found (either from different branches or in different years) and kept for the analysis.To select samples for sequencing, ‘53. A correspondence analysis was performed on the contingency table  the complete model (including the main effects and their interaction) with the model without the interaction. Fisher’s exact tests with simulated p-value (based on 108 replicates) were used to test the homogeneity of the distributions of genotypes between compartments (within each region), and of genotypes between regions (within each compartment).All statistical analyses were performed using R 3.4.024 and permutation tests. This approach is well adapted to an exploratory spatial analysis of epidemiological data because no assumption or prior knowledge of the processes of disease spread is needed 57. The genetic distance between two samples was fixed at 0 if the samples had the same genotype, and at 1 if their genotypes differed. This definition corresponds to the join count between elements of different classes of nominal data24. In cases where two different genotypes were detected in the same tree, their geographical distance was set at 0 (and their genetic distance at 1). In the case of a single compartment with n samples, the geographical distances between the n(n − 1)/2 pairs of samples were first calculated. Then, for each calculated distance d, we computed the average genetic distance Dd between the kd pairs of samples separated by a geographical distance less than or equal to d . The average genetic distance was defined as:hd is the number of pairs of samples with different genotypes among the kd pairs. The confidence intervals  were obtained from N  random permutations of the genotypes of the n samples. We calculated the N average genetic distances within each distance d, and the lower  limit was defined as the genetic distance with rank Nα/2 ) among the N random genetic distances. A significant reduction in genetic diversity at the beginning of the curve  is expected when genotypes are spatially clustered, and the distance at which this reduced genetic diversity becomes non-significant indicates the spatial extent of genetic similarity among samples. Significant genetic distances are interpreted as false positives when non-significant genetic distances are observed at shorter geographical distances . Considering the cumulative number of pairs separated by a distance less than or equal to d, rather than the number of pairs falling in distance classes defined by intervals, provides more powerful tests and more stable curves.In order to assess whether the sampled genotypes were spatially structured within and between compartments, the relationship between genetic and geographical distances was tested at all distances using a geostatistical method based on join countsd is equal to the maximum distance dmax between two samples, we have:When ni is the number of samples with genotype i and the summation is over all the genotypes. Thus, the value of D = 0 if all the samples have the same genotype, and D = 1 if all the samples have different genotypes. Since D when d = dmax. When d < dmax, Dd can be considered as Simpson’s diversity index restricted to the pairs of samples separated by a geographical distance less than or equal to d.andn1 and n2 samples, a similar procedure was applied to the n1n2 pairs consisting of one sample of each compartment with the statistics:hd and kd, except that the two samples belong to two different compartments. However, for the computation of the confidence intervals, only the genotypes of the less structured compartment were randomly permuted to prevent false positive tests caused only by breaking the structure of the most structured compartment by permutation58. When the less structured compartment was also significantly structured, the tests were interpreted conservatively, i.e., interpreting the points bordering the limits of the confidence envelope as not being statistically significant. When d = dmax, the value of ni1 and ni2 are the numbers of samples with genotype i in each of the two groups. D′ = 0 if the two groups have the same unique genotype, and D’ = 1 if the two groups have no common genotype.In the case of two different compartments with Supplementary information.


Odocoileus virginianus (4.19). Heterozygosity was similar to the other studies (0.54) with little evidence of inbreeding. To explain the level of heterozygosity and level of inbreeding within the St. John population, three hypotheses are proposed, including the effect of intrinsic biological traits within the population, a recent infusion of highly heterogeneous loci from North American populations, and a consistent level of immigration from a nearby island. Additional work is needed to further understand the genetic history of the St. John and regional deer populations.This is the first study to document the genetic diversity of the white‐tailed deer population on St. John, US Virgin Islands. The island population was founded by a small number of animals, has very limited hunting or predation, and recently experienced a reduction in size following an extended drought in 2015. DNA samples were collected from hair from 23 anesthetized adult deer  ranging in age from 1 to 8 years (3.36 ± 1.9 years) and also from fecal DNA samples, for a total of 42 individuals analyzed for genetic diversity. The St. John deer data set averaged 4.19 alleles per marker and demonstrates the second lowest number of alleles (A) when compared to other populations of  This is the first study of the genetic profile for the white‐tailed deer population of St. John, Virgin Islands, which was introduced with a very small founder population over 200 years ago. The results show high levels of heterozygosity for an isolated island population. Several ideas for the degree of heterozygosity are proposed. Virgin Islands was from a Danish ship log, where the captain mentions five white‐tailed deer being released on St. Croix during or before 1790  were analyzed using GENEPOP (Ver. 4.2)  for comparison to non‐island populations of white‐tailed deer.Individuals with > 10 genotyped microsatellites (3N = 23) from the entire data set and were used in the final analysis. Some of the fecal samples came from the same individuals, which further reduced our sample from 80 down to 42.For DNA samples collected from hair, a total of 23 adult deer  were sampled, ranging from 1 years to 8 years old (3.36 ± 1.9 years) on the basis of a palpated tooth shape  of all of the comparison populations compared , may have added a significant amount of genetic diversity of deer currently living on St. John.Hypothesis 3A consistent level of immigration from St. Thomas may have resulted in genetic rescue to the St. John deer population.Many species on islands or within small isolated populations that experience bottlenecks can exhibit the effects of inbreeding depression and the subsequent loss of genetic and allelic variation  responsible for preserving allelic diversity with more precision will require additional research and should include a genetic analysis of the source populations, a better understanding of the St. Thomas deer genetic profile, a larger sample of deer sampled, more detail on the history of deer introductions to both St. Thomas and St. John, and a more comprehensive approach to genetic data collection regionally. This paper represents a first study of the genetic composition of this population and is one is a series of papers describing the characteristics of this population of introduced deer to St. John ; data curation (lead); funding acquisition (lead); investigation (lead); methodology (lead); writing‐original draft (lead). Scott A. Taylor: Formal analysis (lead); methodology (lead); software (lead); validation (lead). Jon D. Reuter: Data curation (lead); investigation (lead); methodology (lead); writing‐review & editing (supporting).


Mytilus galloprovincialis in the largest farming areas in Thermaikos gulf, in Northern Greece, and to investigate their temporal and spatial distribution, adding to the knowledge of microcystins presence in Greek Mediterranean mussels.Microcystins are emerging marine biotoxins, produced by potentially toxic cyanobacteria. Their presence has been reported in aquatic animals in Greek freshwater, while data are few in marine environments. Since the climate change induces eutrophication and harmful algal blooms in coastal marine ecosystems affecting the public health, further research on microcystins’ presence in marine waters is required. The aim of this study was to examine the potential presence of microcystins in mussels M. galloprovincialis, in five sampling areas in Thermaikos gulf, in northern Greece, where the 90% of the Greek mussels’ farming activities is located. The isolation of potentially toxic cyanobacteria was confirmed by molecular methods. An initial screening was performed with a qualitative and quantitative direct monoclonal (DM) ELISA and results above 1 ng g−1 were confirmed for the occurrence of the most common microcystins-RR, -LR and -YR, by Ultra High Performance Liquid Chromatography (UHPLC) coupled with a high- resolution mass spectrometer (HRMS) . Microcystin-RR and microcystin-LR were detected, while the intensity of microcystin-YR was below the method detection limit. Most samples that exhibited concentrations above 1 ng g-1 were detected during the warm seasons of the year and especially in spring. Results indicated an overestimation of the ELISA method, since concentrations ranged between 0.70 ± 0.15 ng g−1 and 53.90 ± 3.18 ng g−1, while the confirmation denoted that the levels of microcystins were 6 to 22 times lower.A 4-year microcystins’ assessment was conducted from 2013 to 2016, in farmed Mediterranean mussels M. galloprovincialis, harvested from farms in Thermaikos gulf, in Central Macedonia, Greece. Their presence was linked to potentially toxic cyanobacteria. Bioaccumulation was observed in digestive gland, while the concentrations in muscles were found extremely low. Samples with levels above 1 ng g−1 were observed mostly during spring, confirming the seasonal distribution of microcystins. The comparison of the results by the ELISA and the LC-Orbitrap MS method indicated an overestimation of concentration by the ELISA method.Microcystin-RR and microcystin-LR were detected for the first time in mussel  Microcystis, Anabaena (Dolichospermum), Nostoc, Planktothrix, Chroococcus  MC-RR and [Dha7] MC-LR. On the other hand, the LC-Orbitrap HRMS analysis focused on the most common microcystins MC-LR, MC-RR and MC-YR. Although ELISA is considered a suitable screening method due to its high sensitivity, detection of multi analogues of microcystins, rapid results, low cost and lack of ethical issues [Microcystis aeruginosa cells were added at the abundance of 105 cells mL−1 for 28 days. The microcystins concentrations in the liver were 0.92 µg MC-LR equivalents per g fresh weight measured by ELISA, although no toxins were detected by HPLC/GC-MS [M. galloprovincialis in Adriatic Sea [−1 (ELISA) in mussels’ tissues, although only the desmethylated derivative desMe-MC-RR was confirmed by LC/ESI-Q-ToF-MS/MS at the level of 39 ng g−1. In other mussel samples an overestimation was also observed (1.5 to 6.5 times higher). It was mentioned that ELISA is a useful screening tool, but results should be confirmed by chromatographic analytical methods tandem to mass spectrometry. In another study in McMurdo Ice Shelf station in Antarctica, researchers from New Zealand examined water samples and cyanobacterial mats [Regarding the comparison between ELISA and LC-Orbitrap HRMS, our results indicate an overestimation by ELISA. In particular, during spring the samples above 1 ng gl issues –29, falsLC/GC-MS . It was atic Sea , the MC-ial mats . The conial mats . It was ial mats . It was ial mats  water saM. galloprovincialis, harvested from farms in Thermaikos gulf, in Central Macedonia, in Greece. The presence of potentially toxic cyanobacteria in those areas was confirmed molecularly. Bioaccumulation in digestive gland was observed, while the concentrations in muscles were extremely low. Samples with levels above 1 ng g−1 were observed mostly during spring, confirming the seasonal distribution of microcystins. Moreover, a spatial distribution among sampling areas was noticed, explained by the fluctuations of the rivers runoffs and the nutrients enrichments. The analysis by ELISA and LC-Orbitrap HRMS, revealed overestimation of the first method. In any case, the use of ELISA as screening method is recommended to be followed by chromatographic analytical methods and mass spectrometry as confirmatory methods.In our study microcystin-RR and microcystin-LR were detected for first time in mussel


The yak is a species of livestock which is crucial for local communities of the Qinghai-Tibet Plateau and adjacent regions and naturally owns one more thoracic vertebra than cattle. Recently, a sub-population of yak termed as the Jinchuan yak has been identified with over half its members own a thoracolumbar vertebral formula of T15L5 instead of the natural T14L5 arrangement. The novel T15L5 positioning is a preferred genetic trait leading to enhanced meat and milk production. Selective breeding of this trait would have great agricultural value and exploration of the molecular mechanisms underlying this trait would both accelerate this process and provide us insight into the development and regulation of somitogenesis.Here we investigated the genetic background of the Jinchuan yak through resequencing fifteen individuals, comprising five T15L5 individuals and ten T14L5 individuals with an average sequencing depth of > 10X, whose thoracolumbar vertebral formulae were confirmed by anatomical observation. Principal component analysis, linkage disequilibrium analysis, phylogenetic analysis, and selective sweep analysis were carried out to explore Jinchuan yak’s genetic background. Three hundred and thirty candidate markers were identified as associated with the additional thoracic vertebrae and target sequencing was used to validate seven carefully selected markers in an additional 51 Jinchuan yaks. The accuracies of predicting 15 thoracic vertebrae and 20 thoracolumbar vertebrae with these 7 markers were 100.00 and 33.33% despite they both could only represent 20% of all possible genetic diversity. Two genes, PPP2R2B and TBLR1, were found to harbour the most candidate markers associated with the trait and likely contribute to the unique somitic number and identity according to their reported roles in the mechanism of somitogenesis.Our findings provide a clear depiction of the Jinchuan yak’s genetic background and a solid foundation for marker-assistant selection. Further exploitation of this unique population and trait could be promoted with the aid of our genomic resource. The yak is a species of livestock that is well-adapted to the extreme environment of plateaus and plays an important role in local residents’ lives. Recently, a unique sub-population was identified and referred to as the Jinchuan yak due to its higher meat yield owing to an additional thoracic vertebra . For exaA mature somite, which consists of two compartments: the sclerotome and the dermomyotome, is derived from the presomitic mesoderm (PSM) while vertebrae are derived from the sclerotome compartment . The numThe increased vertebral number has not only been observed in yaks, but also in cattle , sheep  and certBesides increased vertebral number, the Jinchuan yak also possesses other advantageous characteristics including high milk production  and an eA total of 463.64 G bases composed of 1545 million pairs of raw reads were generated on an Illumina HiSeq X Ten sequencing platform. 1522 million pairs of clean reads containing 456.61 G bases remained after filtering  by the principle component 1 (PC1) Fig. . The PC1The slowest decay rate and the highest level of linkage disequilibrium (LD) were observed in the YC population, whereas the rapidest decay rate and the lowest level of LD were observed in the GY population Fig. .Fig. 3DNe) for the YC population which was the smallest compared with the ZC and GY populations. Due to the slow LD decay rate of the YC population, it became less difficult to select loci linked to the causal variants determining the trait of increased vertebral number for selective breeding.This phenomenon can be attributed to the intense artificial selection for the extra thoracic vertebra trait in heavier yaks which may lead to the decline in genetic diversity and increased linkage among loci. This was also likely reflected in the effective population size (The NJ (neighbor-joining) tree split individuals into three groups, which are highlighted with blocks of different colors Fig. . It was However, the large genetic distance within Jinchuan yak suggested a significant genetic diversity exists in the Jinchuan yaks. Considering the genetic distance between Jinchuan yaks, Qinghai-plateau yaks and the outgroup (cattle), it suggested that Jinchuan yaks could be further divided into two subpopulations, which were highlighted with a green block and a yellow block. The genetic distance from the green block to the red block was closer than to the yellow block. And the yellow block was closer to the outgroup cattle than any other blocks were.In light of the previously reported phylogeographical study of domestic and wild yaks based on complete mitochondrial sequences , it was Another interesting observation was that the genetic distances between individuals shown in the NJ tree were similar to the distances between individuals reflected by PCA Fig. , such asThe nucleotide diversity (pi) and population-differentiation statistic (Fst) were calculated using whole genome SNVs. The average pi of each population  was similar to other domestic yaks’ pi that was also calculated from whole genome sequencing data (unselected landraces (D2): 0.00138, Tianzhu white yaks (D1): 0.00137, 36]. The average Fst between Jinchuan yaks and Qinghai-plateau yaks was 0.0415; this was larger than the Fst (0.0213) between D1 and D2 but smaller than that (0.0582) between D1 + D2 and wild yaks , which iTo explore the source of the generation of an extra vertebra and advantageous productive traits of Jinchuan yaks from an evolutionary perspective, selective sweep analysis was conducted between Jinchuan yaks and Qinghai-plateau yaks. Qinghai-plateau yaks were chosen as the control group because they belong to Plateau yak and Jinchuan yaks belong to Valley yak. The genetic distance between them should be relatively far away. The 5 kb regions whose Fst and pi log-ratio were both in the top 5% were regarded as regions under strong selective sweeps. 1393 windows covering 30.8 Mb genomic regions and 4154 windows covering 62.5 Mb genomic regions were chosen for the GY population (which refers to 5 Qinghai-plateau yaks) and the JC population (which refers to 10 Jinchuan yaks), respectively. The size of the regions under selective sweep in the Qinghai-plateau yak was less than half that of the Jinchuan yak. A possible reason for this phenomenon was that the habitat of the Qinghai-plateau yak seldom changed but the habitat of the Jinchuan yak might have undergone a major change. The genes that overlapped with these regions  Table weCOL4A6, COL2A1, COL12A1, MEP1A besides genes whose name beginning with ‘LOC’) were involved in the ‘protein digestion and absorption pathway’, 14 genes  were located in the ‘calcium signaling pathway’, 10 genes  resided in the ‘glutamatergic synapse pathway’. In short, pathways related to two types of functions were significantly enriched: one was related to energy  and the other was related to domestication . For the GY population, only two pathways related to the cell junction were found to be enriched, which were adherens junctions and tight junctions. The regions under strong selective sweep were related to totally different functions in the two populations, which suggested these two populations underwent different adaptive evolution and it was consistent with their different geographical distribution.The genes under strong selective sweep were used to perform enrichment analysis in DAVID for the JC and GY populations. The enriched terms are listed in Table The screening of loci associated with the T15L5 trait started from 498,542 loci harboring population-level genotypes , chromosome 17  and chromosome 7   and goat (Capra hircus) uncovered a fact that the PPP2R2B gene sequence of yak was assembled into two contigs separately. The PPP2R2B genes from cattle and goat are comprised of eleven and ten exons respectively, and the total lengths are 509,525 bp and 478,425 bp. But the length of yak’s PPP2R2B gene is 129,107 bp which is made up of the last eight exons (including introns between these eight exons). The distance between cattle’s first three exons  and the last eight exons  was 184,756 bp and the total length of the last eight exons (including introns between these eight exons) was 128,197 bp. Moreover, the corresponding distances in goat were 188,301 bp (between first two exons (H) and last eight exons (T)) and 130,901 bp . The distant distance between H and T might be the reason for the loss of H in the yak, which may result from artificial annotation and not the intrinsic nature of this gene in yak. The similar lengths and sequences of the last eight exons between yak, cattle, and goat indicated the correctness and reliability of the annotated part of yak. No population-level variants were observed in the head part of yak’s PPP2R2B gene. The reference genome of the latter two species has already reached the chromosome level but the reference genome of yak was still fragmented, which reminded us of the necessity of improving the yak’s reference genome for further understanding the molecular mechanism underlying the yak’s good characteristics.A comparison of the sequences of the PPP2R2B gene from yak, cattle . According to the concordance between the genotypes of 15 resequenced samples obtained from the whole genome resequencing and the target sequencing, 3 loci were excluded. Therefore, 3 extra loci from the 330 candidate loci were chosen. The new ten loci were genotyped in 50 Jinchuan yaks (including the 10 resequencing samples). In summary, 51 extra Jinchuan yaks were genotyped with target sequencing and the evaluation of these 7 loci which appeared in two rounds of target sequencing is presented in Tables The evaluation consisted of two aspects: one was the ability to successfully predict 20 thoracolumbar vertebrae and the other was to predict 15 thoracic vertebrae. First, the loci whose major genotypes differed in two phenotype groups (e.g. the ‘observed 19’ group and the ‘observed 20’ group) were selected. The major genotypes denoted the genotype whose count was the most in one locus. Second, each individual was scored for two phenotypes according to all its selected genotypes and the rule of scoring was: + 3 if the genotype probability > = 0.9; + 2 if the genotype probability > = 0.8 and + 1 for the rest. Third, if the difference of scores between two phenotypes (diff) was greater than a specific value, this individual was considered to be predictable using our loci and its phenotype was specified as the phenotype corresponding to the higher score. Others are specified as unknown. Finally, the efficiency of properly predicting a phenotype was assessed with ‘accuracy of prediction’ and ‘representative capacity’. The accuracy of prediction was defined as the percentage of individuals with a correctly determined phenotype relative to the total individuals who were predicted to be this phenotype. The definition of representative capacity was the percentage of individuals with a correctly determined phenotype relative to the total individuals who were observed to be this phenotype.In the evaluation of the ability of these 7 loci to predict 20 thoracolumbar vertebrae, 6 out of 51 individuals were expected to be 20 thoracolumbar vertebrae and 2 out of 6 were observed to be 20 thoracolumbar vertebrae. Therefore, it indicated the accuracy of predicting 20 thoracolumbar vertebrae was 33.33%. And 2 out of 10 individuals with 20 thoracolumbar vertebrae were identified, which indicated the representative capacity was 20%. When it came to predicting 15 thoracic vertebrae, the accuracy increased to 100.00% but the representative capacity was still 20.00%. One reason that could explain the difference between the accuracies of two conditions was the difference between 19 and 20 vertebrae was smaller than the difference between 14 and 15 thoracic vertebrae. The representative capacity told us the 10 Jinchuan yaks resequenced before only represented around 20.00% of the total genetic diversity of individuals with T15L4/T15L5 traits.The objective of this study was to explore the genetic background of the Jinchuan yak and the possible mechanisms of aberrant somitogenesis according to the whole genome resequencing data in order to find markers which could be used to select individuals with the specific thoracolumbar vertebral formula (T15L5) trait. The representative capacity (20.00%) was satisfying in our view considering our relatively small initial sample size and the use of only 7 markers to predict the trait. In the future, more loci could be included to increase the representative capacity of the genetic diversity at least in theory. After identifying the causal gene(s) or QTLs dominate for this trait, more precise selection could be carried out using the corresponding markers.The predominant type of PP2A is a heterotrimer phosphatase, which consists of a scaffolding subunit A, a regulatory subunit B and a catalytic subunit C , and oneAnother important gene identified in this study that was found to carry numerous mutations was TBL1XR1 , which was both involved in the signaling pathways regulating somite identity and somite number. The relationship between TBLR1 and somite identity originated from the corepressor SMRT . TBLR1 iOvis aries based on sequencing data similar to ours. The functions of these genes did help the species to better adapt to their corresponding environments [When a species evolves under a certain pressure, the areas harboring alleles that help the species better adapt to this pressure would be under strong selective sweep. For example, the windows in which the SOCS2 and GPX3 genes reside were screened out with selective sweep analysis of ronments . In our ronments .The increased vertebral number of yak in a natural condition is believed to be relevant to its adaption to plateau. Investigating the mechanism determining this trait and developing methods selecting such individuals would provide us better understanding of the mechanism regulating this trait and much more production yields. Our work provides a good practice of implementing MAS with the aid of modern NGS-based molecular methods to select yaks with one more thoracic vertebra. The report of the unique somitogenesis of yak and the discussion of possible mechanisms underlying this trait will inspire further exploration concerning the somitogenesis and plateau hypoxia. The interpretation of population genetics characteristics of this unique sub-population of the yak builds a foundation for both selective breeding and evolutionary development. Also, the genomic resources of individuals whose thoracolumbar vertebral formula was confirmed by anatomical observation in our research provide researchers with a reliable foundation to carry out further comparative analysis.In order to explore the genetic characteristics of Jinchuan yaks with one additional thoracic vertebra, five Jinchuan yaks whose thoracolumbar vertebral formula was T15L5 (YC population) were taken as the case group and ten yaks with a normal vertebral number (five Jinchuan yaks (ZC population) and five Qinghai-plateau yaks (GY population) whose thoracolumbar vertebral formula was T14L5) were taken as the control group. Our samples could also be divided into another two groups according to a classical classification, which categorizes them as Plateau yaks (represented by the Qinghai-plateau yak) and Valley yaks  based on their geographic distribution and morphological features. Therefore the genetic characteristics at the population level of the Valley yak relative to the Plateau yak were also explored in this study. All study animals were slaughtered on breeding farms and the number of thoracic and lumbar vertebrae of each yak was determined to confirm its thoracolumbar vertebral formula. Ten Jinchuan yaks and five Qinghai-plateau yaks were from Jinchuan Yak Breeding Cooperative in Reta Village, Maori Township, Jinchuan county, Sichuan province and Qinghai Yushu Plateau Yak Farm in Yushu county, Qinghai province respectively. Whole blood was collected from each animal and used to extract genomic DNA. Pair-end libraries were constructed according to the protocol of the manufacturer  using the extracted genomic DNA. All samples were sequenced on an Illumina HiSeq X Ten sequencing platform.http://broadinstitute.github.io/picard/) to remove duplicates with ‘MarkDuplicates REMOVE_DUPLICATES = true’ and samtools [The raw pair-end reads generated after sequencing were filtered out under the following conditions to generate clean reads: (a) It contained a sequencing adapter; (b) The length of ‘N’ bases in either of a pair-end reads exceeded 10% of the total bases of the corresponding read; or (c) Low quality bases (Q-score < = 5) in either of a pair-end reads that accounted for over 50% of total bases of the corresponding read. The clean reads were then mapped to the yak reference genome (BosGru_v2.0 ) with thsamtools  to removsamtools . ANNOVARsamtools .2) of paired SNVs at certain distances was calculated using PopLDdecay [2 and its corresponding distance.The principle component analysis (PCA) was performed based on the whole genome SNVs of each individual using the program smartpca provided in EIGENSOFT (version 7.2.1) . The squpLDdecay  for eachBos taurus) (NGS data accession ID: ERR035712 - ERR035769), whose whole genome SNVs were obtained according to the same method we used for our samples here, was selected as an outgroup to root the NJ tree.The pairwise (1-IBS) distance (IBS: identity-by-state) matrix between individuals was calculated with whole genome SNVs using PLINK  and usedBoth the nucleotide diversity (pi) of the Jinchuan yak (composed of the ZC and the YC population) and Qinghai-plateau yak (the GY population) and the fixation index (following Weir and Cockerham’s paper ) were caThe yak reference genome (BosGru_v2.0 ) we usedAdditional file 1. The genes that overlapped with regions under strong selective sweeps.Additional file 2. Primers used to amplify the sequences harboring the final seven loci.


Mycobacterium bovis and other members of the Mycobacterium tuberculosis complex (MTC) is a main concern in wildlife populations such as the Eurasian wild boar (Sus scrofa). Tests detecting antibodies against the MTC are valuable for tuberculosis (TB) monitoring and control and particularly useful in suids. The development of accurate, efficient, and non-invasive new tools to detect exposure to MTC would be highly beneficial for improving disease surveillance. This study aimed to determine if antibodies against MTC could be detected in oral fluid (OF) samples by a new ELISA test (IgG detection) from naturally TB-infected wild boar. For this, individual, paired serum and OF samples were collected from 148 live wild boar in two TB-status areas from Spain and quantitatively used to validate the new ELISA test. Antibodies against MTC were widely detected in OF samples, for which a significant positive correlation (r = 0.83) was found with the validated serology test. OF ELISA sensitivity and specificity were 67.3% and 100%, respectively. The results of this work suggest that OF samples have the potential to be used for MTC diagnosis as a further step in TB surveillance and control in suid populations. Based on our results, further research is warranted and could be performed using non-invasive new tools directly in field conditions to detect exposure to MTC.The presence of  Mycobacterium bovis and other close members of the Mycobacterium tuberculosis complex (MTC) .p < 0.05.The data were analyzed using the commercial statistical software SPSS 22 . Correlation analysis between ELISA optical densities (OD) in OF and serum samples was performed using Pearson’s ranked coefficient test. Cohen’s kappa coefficient (κ) was used to calculate the degree of agreement of the OF test (OF ELISA with the standard Serum ELISA). ROC analyses were performed to estimate the AUC by using serology data from known uninfected and MTC-infected wild boar and to determine cut-off values . The cut


Urochloa (syn.—Brachiaria s.s.) is one of the most important tropical forages that transformed livestock industries in Australia and South America. Farmers in Africa are increasingly interested in growing Urochloa to support the burgeoning livestock business, but the lack of cultivars adapted to African environments has been a major challenge. Therefore, this study examines genetic diversity of Tanzanian Urochloa accessions to provide essential information for establishing a Urochloa breeding program in Africa. A total of 36 historical Urochloa accessions initially collected from Tanzania in 1985 were analyzed for genetic variation using 24 SSR markers along with six South American commercial cultivars. These markers detected 407 alleles in the 36 Tanzania accessions and 6 commercial cultivars. Markers were highly informative with an average polymorphic information content of 0.79. The analysis of molecular variance revealed high genetic variation within individual accessions in a species (92%), fixation index of 0.05 and gene flow estimate of 4.77 showed a low genetic differentiation and a high level of gene flow among populations. An unweighted neighbor-joining tree grouped the 36 accessions and six commercial cultivars into three main clusters. The clustering of test accessions did not follow geographical origin. Similarly, population structure analysis grouped the 42 tested genotypes into three major gene pools. The results showed the Urochloa brizantha (A. Rich.) Stapf population has the highest genetic diversity (I = 0.94) with high utility in the Urochloa breeding and conservation program. As the Urochloa accessions analyzed in this study represented only 3 of 31 regions of Tanzania, further collection and characterization of materials from wider geographical areas are necessary to comprehend the whole Urochloa diversity in Tanzania. Urochloa (syn.—Brachiaria s.s.) that consists of about 100 species is among the most widely cultivated tropical forage grass in South America, Australia and East Asia and has been recognized for high yield, nutritional content and wider adaptability to diverse ecological niches  contributed largely by shortage of quality feed particularly during the dry seasons. Though not a tradition, farmers have started growing improved forages to support the emerging livestock sector in the region. Recently, Urochloa genotypes is useful to organize a working collection and to select genotypes for crossing and conservation , Ethiopia. The result of this study would be highly useful in a Urochloa improvement and conservation program.The characterization of genetic diversity of a population is necessary for better use of genetic resources in breeding and biodiversity conservation programs. Therefore, knowledge of genetic diversity of the available germplasm is essential in selecting materials for cultivation or parents for cultivar development. The genetic diversity can be assessed using different tools including DNA markers  were included in this study  according to manufacturer’s instructions. The quality, quantity and integrity of DNA were estimated using the NanoDrop 1000 Spectrophotometer  and visualized in 1% agarose gel (w/v) stained with 0.25X GelRed under ultraviolet light . The DNA was adjusted to the final concentration of 20 ng/μl and stored at – 20 °C until further use.PCR amplification and capillary electrophoresis – A total of 24 SSR markers initially developed for U. ruziziensis Germain & Evrard with the proven transferability to other Urochloa species were used in the study  using the following PCR cycling conditions: initial denaturation at 95 °C for 3 min, followed by 35 cycles of 94 °C for 30 s, annealing at 58/59 °C for 1 min, extension at 72 °C for 2 min and final extension at 72 °C for 20 min and hold at 15 °C. The amplicons were separated in 2% agarose gel stained with 0.25 × GelRed and run for 45 min at 100 V. A cocktail (LH) of 15 μl GeneScanTM500LIZ size standard  and 1 ml Hi-Di-formamide was prepared for capillary electrophoresis. Multiplexed PCR product (1.5 μl) was mixed with 9 μl of LH, denatured at 95 °C for 3 min and snap-chilled on ice for 5 min. The samples were then subjected to capillary electrophoresis at the Segolip Unit of BecA-ILRI HuU.Data analysis – Forty-two Urochloa genotypes consisting five species: U. bovonei (Chiov.) Robyns, U. brizantha (A. Rich.) Stapf, U. jubata  Stapf, U. humidicola (Rendle) Schweick, U. ruziziensis Germain & Evrard and six Urochloa cultivars were grouped into six populations for the genetic diversity study. The descriptive statistics for SSR markers were computed with PowerMarker v.3.25 software (http://www.powermarker.net). The population diversity description, principal coordinate analysis (PCoA) and analysis of molecular variance (AMOVA) were performed using GenAlEx v6.41 ] based on the rate of change in Ln P(D) between successive K. The optimum K value was predicted following the simulation method , number of private alleles (PN) and percentage of polymorphic loci (%PL) across all loci ranged from 0.34–2.74, 0.08–1.53 and 17.19–68.75%, respectively, in the studied populations. The observed heterozygosity (OH) was in the range of 0.17–0.69, with a mean of 0.49. The high-level diversity was observed in U. brizantha population (I = 0.94) and a low-level diversity in U. bovonei population (I = 0.12). The observed heterozygosity was higher than expected for all populations.Genetic distance – The pairwise genetic distance and population matrix of Nei unbiased genetic identity were presented in U. ruziziensis and U. jubata), U. bovonei and commercial cultivar populations were distantly related (3.186), whereas U. brizantha and U. humidicola populations were the most closely related (1.639). Similarly, genetic identity was the highest between U. brizantha and U. humidicola populations (0.194) and the lowest between U. bovonei and commercial cultivar populations (0.041).Analysis of molecular variance – Analysis of molecular variance (AMOVA) of 42 Urochloa genotypes showed that only 3% of the total variation in the population was due to differences among individual accessions. Differences within individual accessions in a population contributed 94% of total variation, and 5% was due to the differences among the Urochloa populations (FST- = 0.05) as evidenced by high level of gene flow estimate (Nm = 4.77).ulations . There wPopulation structure – The principal coordinate analysis (PCoA) bi-plot showed no distinct clustering pattern for 42 Urochloa genotypes studied  grouped in cluster I, whereas most of accessions from U. humidicola, two accessions of U. bovonei and two commercial cultivars (Humidicola and Piata) grouped in cluster II. Three commercial cultivars  and one available accession U. ruziziensis formed the cluster III. Overall topology of the dendrogram indicated the presence of three lineages in the Urochloa populations studied. A similar pattern was observed on Bayesian model-based clustering algorithm implemented in STRUCTURE software. The method of Evanno et al.  compared to previous studies   detected in this study was higher than that reported by Jungmann et al. , Bianca 67–0.95) . The res species .U. brizantha population, whereas U. bovonei and U. ruziziensis populations had lower values , while commercial cultivar, Mulato II, is a product of three-way cross of U. brizantha, U. decumbens and U. ruziziensis. Two species, i.e., U. jubata and U. ruziziensis, were not included in this analysis due to insufficient sample size.Genetic distance is the measure of the allelic substitutions per locus that have occurred during the separate evolution of two populations or species  contribution of within-individual difference to a total variation, whereas among-individual and among-population differences contributed 3 and 5%, respectively. The high level of genetic variation within species observed in our study was similar to that reported for Ruzigrass  among populations and high number of migration (Nm = 4.7) per generation  are polyploid , while most U. humidicola accessions (12 out of 15) were found in cluster II and 3 of 6 commercial cultivars were found in cluster III. Two accessions of U. bovonei and one of U. jubata were found in cluster II, but in different sub clusters. Although U. ruziziensis was found in cluster III, it is a bit far from the rest of accessions (Urochloa accessions compared to six commercial Urochloa cultivars. The SSR markers used in this study were highly informative to assess genetic diversity in Urochloa species. The Urochloa accessions did not cluster according to the geographical regions but clustered by their genetic background. The accessions belonging to U. brizantha were more diverse than those from other four species and commercial cultivars, which can be tapped and used in conservation and breeding programs, especially in developing improved Urochloa varieties and hybrids that can produce high biomass and withstand well to biotic and abiotic environmental conditions. The cultivars and sexual diploid U. ruziziensis from cluster III can be used in future crosses with other accessions from cluster I and II depending on their ploidy to obtain heterosis in the progeny. As the Urochloa accessions analyzed in this study represent only 3 of 31 regions of Tanzania, collecting Urochloa germplasm from a wider geographical area is necessary to catalog the genetic variation of Urochloa in the country.In PCoA, no distinct clusters were observed; however, STRUCTURE and the unweighted neighbor-joining algorithm analyses consistently revealed three major clusters , 4. Cluscessions . This iscessions . However


Brachymystax lenok tsinlingensis is an endangered freshwater fish which is endemic to part of China. To investigate its genetic diversity and population structure, mitochondrial cytochrome b gene and D-loop control region were used to analyze samples from five different locations. Fifteen haplotypes were identified; however, no shared haplotypes were observed among different streams. The analysis of molecular variance (AMOVA) results indicated that 77.38% of total variation was attributed to differentiation between populations, whereas 22.62% from variation within populations. The high genetic differentiation among the populations would provide useful information for building natural reserves and artificially releasing cultured juveniles in the future. Brachymystax lenok tsinlingensis is endemic to several streams of the middle part of the Qinling Mountains, especially in the Heihe, Shitouhe, Xushui and Taibaihe Rivers  will be applied to analyze population genetic diversity and genetic relationships of samples from different locations due to its rapid evolution rates and maternal inheritance  and Baoji   was carried out in 50 μL mix containing 1 X PCR reaction Buffer (including Mg), 0.2 mM dNTP, 1 μM forward and reverse primers, 1.25 units of Taq DNA polymerase (TaKaRa) and about 500 ng of genomic DNA. All PCRs were performed with an initial denaturation of 94 °C for 3 min, followed by 35 cycles of 94 °C for 30 s, annealing temperature of 60 °C for 30 s, 72 °C for 90 s and the final extension of 10 min at 72 °C. PCR products were sent to Shanghai Sangon Biotech Co. Ltd.  for sequencing.Specimens of *9 = 36) . All the*9 = 36) . Mitocho Lalitha . The parcytochrome b sequence and D-loop region into one sequence. Haplotypes (H), haplotype diversity (Hd) and nucleotide diversity (π) were calculated for within and between different geographic population using DnaSP v5 , namely S1, S2, S3-S4 and S5, which referred to four geographical locations  according to this study. To further investigate genetic diversity and genetic distance among populations in different streams, more samples from more streams need to be collected. In conclusion, the findings in this study would be useful for building natural reserves and artificially releasing cultured B. lenok tsinlingensis juveniles in the future.Alignment of 45 concatenated sequences resulted in 2049 sites, of which 64 were variable and parsimony informative. Fifteen haplotypes were identified, but no shared haplotypes were observed among different streams. The haplotype sequences of ocations . Based oClick here for additional data file.