DNA microsatellite diversity and a set of biological and environmental factors  in two strictly endemic taxa from dolomite outcrops of Sierra Nevada (Helianthemum pannosum and H. apenninum subsp. estevei) and two congeneric widespread taxa (H. cinereum subsp. rotundifolium and H. apenninum subsp. apenninum) that further belong to two different lineages (subgenera) of Helianthemum. We obtained rather unexpected results contrasting with the theory: (a) The narrow endemic taxa showed higher values of genetic diversity as well as higher average values of pollen production per flower and pollen‐to‐ovule ratio than their widespread relatives; and (b) the two taxa of subg. Helianthemum, with larger corollas, approach herkogamy and higher pollen production than the two taxa of subg. Plectolobum, displayed lower genetic diversity and higher values of inbreeding. Altogether, these results disclose how genetic diversity may be affected simultaneously by a large number of intrinsic and extrinsic factors, especially in Pleistocene glacial refugia in mountains where the spatial context harbors a great ecological heterogeneity. On the other hand, differences in mating system and the significant effect of the substrate profile, both being highly diverse in the genus Helianthemum, in the genetic variability illustrate about the importance of these two factors in the diversification and species differentiation of this paradigmatic genus in the Mediterranean and open the field to formulate and test new hypotheses of local adaptation, trait evolution, and habitat diversification.Unraveling the relationships between ecological, functional traits and genetic diversity of narrow endemic plants provide opportunities for understanding how evolutionary processes operate over local spatial scales and ultimately how diversity is created and maintained. To explore these aspects in Sierra Nevada, the core of the Mediterranean Betic‐Rifean hotspot, we have analyzed nuclear  Despite scanty information being available about the building up of biodiversity in such regions, attention is recently being paid to the evolutionary history of species assemblages and lineages by considering phylogenetic relationships for whole floristic datasets  is a monophyletic lineage with about 136 species and subspecies characterized by a complex taxonomy and remarkable life history and functional trait diversity , the other two diversified around the Mediterranean Basin and the Eurosiberian mountains .The genus Helianthemum from Sierra Nevada (southern Spain) that are two pairs of relatives with disparate distribution area  and soil preferences , which moreover represent two different lineages (subgenera) within Helianthemum . The annual average temperature decreases in altitude from 12 to 16°C below 1,500 m to 0°C above 3,000 m a.s.l., and the annual average precipitation is about 600 mm, ranging from less than 250 mm in the lowest parts of the mountain range to more than 700 mm in summit areas. The number of vascular‐plant taxa recorded in Sierra Nevada is 2,353  occupying an area of ca. 2,100 km Lorite, , about 1 Lorite,  and c. 8 Lorite, . This mo Lorite,  benefitt2.2Helianthemum  and H. apenninum subsp. estevei and H. apenninum subsp. apenninum  restricted to dolomitic soils in Sierra Nevada, whereas Helianthemum apenninum subsp. apenninum and H. cinereum subsp. rotundifolium (hereafter referred as H. cinereum) are mostly sympatric taxa (WTs) distributed in C and W of the Mediterranean region with preference for limestone outcrops  and, although the pollination biology of most species remains unknown, flowers are visited by generalist insects, mostly bees and beetles  a limestone (plus mica‐schist) outcrop about 197 km2, where the ETs Helianthemum apenninum subsp. estevei and H. pannosum and the WTs H. apenninum subsp. apenninum and H. cinereum can be found more or less widely distributed, respectively, the interindividual distance of individual conspecific plants ranging from a few centimeters to a few kilometers. In this context, we followed a Trapper sampling scheme  and interindividual distance , 5.95 in H. cinereum (ranging 0.08–17.34), 4.54 in H. apenninum subsp. estevei (ranging 0.05–11.79), and 6.25 in H. apenninum subsp. apenninum (ranging 0.22–22.39). Sampling included fresh leaves immediately dried in silica gel for further DNA extraction, plus 68 flowers and floral buds from 59 individual plants  a mts Table , all thets Table . We also2.3H. cinereum subsp. rotundifolium , 0.5% of BSA, 0.2 μM of the reverse and the M13 universal primers , and 0.07 μM of the modified forward primer with the M13 primer sequence attached at its 5′‐end. We carried out polymerase chain reactions on a MyCycler™ Thermal Cycler  following two PCR profiles published elsewhere  according to the manufacturer's protocol. We checked for transferability to the other three studied taxa a set of 12 microsatellites primer pairs originally developed for 2.4We also collected 125 soil samples at 10–20 cm depth close to each of the 140 sampled plants (except for plants occurring less than 5 m apart). These soil samples were left to dry for 24 hr at room temperature and then passed through a 2‐mm sieve before determining the following physicochemical parameters: texture , pH (at 25°C 1:5), electrical conductivity , percentage of carbonates and organic matter, content of macronutrients (mg/kg of N‐Kjeldahl and P‐Olsen), micronutrients , and assimilable cations . Soil analyses were performed by “Laboratorio Agrama SL” .We also recorded in the field the community neighborhood and composition of each individual sampled plant by recording (a) the number of conspecifics in a 5‐m radius buffer, (b) the distance to the nearest conspecific plant, and (c) the percentage of shrub coverage also in a 5‐m radius buffer following a visual scale with four categories: 1 = 1%–25%, 2 = 26%–50%, 3 = 51%–75%, and 4 = 76%–100%.2.5For each taxon, we averaged the number of stamens and ovules per ovary after dissecting one floral bud from 5 to 21 individual plants under a dissecting microscope totaling 59 flower buds Table . For eac2.62.6.1Na), effective number of alleles (Ne), unbiased Nei's gene diversity (He), and inbreeding coefficient (Fis) with GenAlEx 6.5  in the data set and to assign simultaneously the sampled individuals to each of the inferred clusters. Nonetheless, each of these methods has limitations that can affect the validity of their results. The Bayesian clustering methods infer subtle population structure by minimizing linkage disequilibrium and departures from Hardy–Weinberg equilibrium within each inferred cluster  to 4 (assuming every taxon formed its own cluster). The Bayesian clustering was conducted in Structure 2.3.4 applying a series of five independent runs for each value of K. All runs consisted of 105 iterations of burn‐in period plus a final run length of 106 iterations, and convergence of Markov chains was assessed after the analyses. We assessed the optimal number of clusters with the procedure by Evanno, Regnaut, and Goudet  was estimated with the function find.cluster and identified as the one with the lowest BIC value.To assess the number of independent genetic and evolutionary entities, we inferred the genetic structure by two methodologically contrasting approaches: the Bayesian clustering procedure of Structure . We assessed significance of the averaged correlation coefficients through the construction of 95% confidence intervals by randomly permuting individual location 1,000 times and constructed the correlograms with GenAlEx 6.5.dist and the MRM analyses with the package ecodist  matrix with GenAlEx 6.5 that was subsequently subjected to multiple regression on distance matrices (MRM) analyses against the following environmental matrices: (a) a “neighborhood–composition distance” computed as the pairwise Euclidean distance from the three measures  of neighborhood composition recorded in the field, (b) a “soil distance”, computed by applying a Principal Components Analysis to the standardized soil parameters and then retaining the first two principal components to calculate the pairwise Euclidean distance, and (c) a “geographic distance” computed as the pairwise Euclidean distance among each sampled individuals. All environmental matrices were computed with the function 2.6.3lme4  with the package 33.1Helianthemum taxa of this study are in Supporting Information H. cinereum subsp. rotundifolium were partially transferable to the other three taxa with 11, 7, 7, and 8 loci yielding polymorphic amplified products in Helianthemum cinereum subsp. rotundifolium, H. apenninum subsp. apenninum, H. apenninum subsp. estevei, and H. pannosum, respectively  than in the WTs , even significantly for some measures (Table Fis) were markedly different between subgenera with higher values in both taxa of subg. Helianthemum than in those belonging to subg. Plectolobum.Genetic diversity measures  were higher in the ETs  were not confirmed using the Bayesian Structure analysis because the cluster of H. apenninum was split into two. These two new clusters were not well defined because they had individuals from both subspecies indicating a labile genetic structure between them which can be explained by a very recent divergence or by the persistence of current gene flow. However, both subspecies can be considered as two different entities since the proportion of the individuals assigned to these two clusters were considerably asymmetric between both subspecies , indicative of a recent population decline. We also detected a significant heterozygosity deficiency in H. apenninum subsp. apenninum under both the IAM and TPM models  indicative of a recent population expansion. Either heterozygosity excess or deficiency was not detected in the other two taxa.The program Bottleneck detected significant heterozygosity excess in 3.2Helianthemum apenninum subsp. apenninum showed a significant and positive autocorrelation in the pairwise genetic coefficient at the first distance class (0–1 km), followed by a decline with significant but negative spatial autocorrelation coefficients above 20 km. Helianthemum pannosum showed a significant and positive autocorrelation in the pairwise genetic coefficient at the first distance class (0–1 km) and at 2–4 km. No significant spatial signal was detected in any distance class for the other two taxa. Results of multiple regressions on distance matrices are shown in Table H. apenninum subsp. estevei . The neighborhood–composition distance matrix and the geographic distance matrix were uncorrelated with genetic distance in all cases.Spatial correlograms showed different results among taxa Figure . Heliant3.3Helianthemum (H. apenninum subsp. apenninum and H. apenninum subsp. estevei) had on average flowers with petals about 10 mm in length, 20 ovules per ovary, high pollen production per flower, low pollen‐to‐ovule ratio, and approach herkogamy, whereas those of subg. Plectolobum (H. cinereum and H. pannosum) had almost constantly six ovules per ovary, smaller petals of about 5–6 mm, lower pollen production, higher pollen‐to‐ovule ratio, and reverse herkogamy  the narrow endemic study taxa (ETs) did not show lower values of genetic diversity but even higher, as well as higher average values of pollen production per flower and pollen‐to‐ovule ratio than their widespread relatives (WTs), and (b) the two taxa of subg. Helianthemum, with larger corollas, positive stigma‐anther separation  and higher pollen production than the two taxa of subg. Plectolobum, displayed lower genetic diversity and higher values of inbreeding. These results disclose that genetic diversity may indeed be affected by a large number of factors, some of them acting in opposite directions, and that patterns of genetic diversity cannot be readily predicted from simple proxies  of two pairs of narrow/widespread congeners of 4.1H. pannosum and H. apenninum subsp. estevei) was at least equal or higher than in the WTs , can be the outcome of the successful retention of genetic variation in current populations after the expansion–contraction cycles occurred during the Pleistocene climatic changes and historical population bottlenecks. Contrarily, the lower genetic diversity of H. apenninum subsp. apenninum compared with its narrow endemic relative H. apenninum subsp. estevei can be consequence of a recent expansion favored by the postglacial conditions as it has been described in other widespread and probably young species of Helianthemum such as H. nummularium and H. oelandicum , sandy‐soils , saline‐soils (H. polygonoides), or dolomite  spatial structuring due to the constraints imposed by soil conditions; or (b) the existence of local adaptation  had higher pollen production per flower and higher P/O ratios than their widespread relatives (H. cinereum and H. apenninum subsp. apenninum). This result is likely showing that variation in floral traits is common in Helianthemum, even within populations , effective number of alleles (Ne), and unbiased expected heterozygosity (He), it seems that mixed‐mating systems are promoting survival and contributing to the maintenance, or even to the increase, of the genetic diversity of these two stenochorous taxa. This striking result has also been documented in the Cretan endemic Cyclamen creticum, whose genetic variability is not lower than in its widespread relative C. repandum, being the levels of genetic diversity more influenced by the mating system rather than by the amplitude of the geographic distribution , and higher inbreeding coefficient (Fis) in both taxa of subg. Helianthemum than in those of subg. Plectolobum showing that they are more prone to selfing  have been evaluated as Vulnerable by the Spanish Red List of Endangered Plants (Moreno, H. pannosum and H. apenninum subsp. estevei require ongoing monitoring of their conservation status and it would be advisable the development of appropriate conservation programs to integrate both in situ and ex situ conservation techniques (Volis & Blecher, The two strictly dolomitic endemics in Sierra Nevada here studied ( Moreno,  due to t Moreno, . In our  Moreno, ; however Moreno, . TherefoThe idea and design of the study were developed by R.G.A., J.A., and A.A. Plant material was collected by S.M.S., R.G.A., J.L., J.A., and A.A. The analyses and interpretation of the data were carried out by S.M.H., S.M.S, and R.G.A. Finally, the manuscript was written and discussed between all authors but was led by S.M.H. and A.A. Click here for additional data file.


Taenia hydatigena is a disease of veterinary and economic importance. A considerable level of genetic variation among isolates of different intermediate hosts and locations has been documented. Generally, data on the genetic population structure of T. hydatigena is scanty and lacking in Nigeria. Meanwhile, similar findings in other cestodes like Echinococcus spp. have been found to be of epidemiological importance. Our aim, therefore, was to characterize and compare the genetic diversity of T. hydatigena population in Nigeria based on three mitochondrial DNA markers as well as to assess the phylogenetic relationship with populations from other geographical regions.Cysticercosis caused by the metacestode larval stage of T. hydatigena isolates from Nigerian sheep and goats using three full-length mitochondrial genes: the cytochrome c oxidase subunit 1 (cox1), NADH dehydrogenase subunit 1 (nad1), and NADH dehydrogenase subunit 5 (nad5).In the present study, we described the genetic variation and diversity of cox1-nad1-nad5 sequences indicated that T. hydatigena metacestodes of sheep origin were genetically distinct from those obtained in goats and this was supported by high FST values of nad1, cox1, and concatenated cox1-nad1-nad5 sequences. Genetic variation was also found to be higher in isolates from goats than from sheep.The median-joining network of concatenated T. hydatigena population for the first time in Nigeria using full-length mitochondrial genes and suggests the existence of host-specific variants. The population indices of the different DNA markers suggest that analysis of long mitochondrial DNA fragments may provide more information on the molecular ecology of T. hydatigena. We recommend that future studies employ long mitochondrial DNA sequence in order to provide reliable data that would explain the extent of genetic variation in different hosts/locations and the biological and epidemiological significance.To the best of our knowledge, the present study described the genetic variation of  Taenia infect a wide range of intermediate host species where the metacestode larval stage causes cysticercosis or coenurosis. A few members of this genus such as Taenia solium, T. saginata and T. asiatica are zoonotic and are responsible for taeniosis in humans while others are of veterinary importance.Cestodes belonging to the genus T. hydatigena uses canids (primarily dogs) as definitive hosts. The metacestode larval stage of T. hydatigena infects mostly domestic animals such as goats, sheep and pigs, resulting in cysticercosis; an infection of veterinary importance that causes huge economic loses especially in livestock production as a result of mortality [The tapeworm ortality , condemnortality –5.Taenia hydatigena has a global distribution with a prevalence range of 0.1–32.0%, differing between countries and hosts [nd hosts –6. The end hosts , 5, and nd hosts , 6, 7.T. hydatigena is poorly documented. However, existing reports have demonstrated high infection rates in livestock especially in sheep and goats [T. hydatigena species is lacking. Meanwhile, genetic variation in other cestodes, e.g. Echinococcus granulosus [T. saginata and T. solium mitochondrial genome have also demonstrated intraspecific variation [In Nigeria, cysticercosis due to nd goats –14. Althanulosus –19 has banulosus . Similarariation –24 suggeariation .T. hydatigena. Although a few studies conducted mostly by using partial cox1 and nad1 mitochondrial gene sequences have reported considerable levels of genetic variation among T. hydatigena populations from different geographical regions and hosts [T. hydatigena that could provide better insight on the disease epidemiology.Globally, there exists a dearth of data on the genetic variation of nd hosts , 26–29, Echinococcus [T. hydatigena. Also, some studies have suggested that complete mitochondrial genes such as nad6, nad5, atp6, nad3 and nad2 may have some advantage over the conventional mitochondrial markers like cox1 and nad1 in investigating the molecular ecology of Taenia spp. [T. hydatigena population in Nigeria based on the cox1, nad1 and nad5 mitochondrial genes, compare the genetic variation between the genes, and infer the phylogenetic relationships with T. hydatigena populations from other geographical regions.Further, the limitation of partial gene sequences in inferring the phylogenetic status of taeniids has been largely emphasized for nococcus , 31. Thenia spp. , 32. TheNigeria is a West African country with a population of over 180 million people. It is made up of 36 states and a Federal Capital Territory located in Abuja. These states are further grouped into six geopolitical zones  due to ethnicity and common ancestry. The vegetation cover is majorly rainforest in the south and savannah in the north. Borno State is located in the North-East zone of the country and home to about 4 million small ruminants (sheep and goats)  that aren = 32) analyzed in this study were collected postmortem from goats (n = 24) and sheep (n = 8) in the months of November and December 2018 during routine examination at an abattoir in Maiduguri, Borno State, northeastern Nigeria . All isolates were of liver origin.Isolates , 10 pmol of each primer, 0.5 μl of genomic DNA extract (c.20–200 ng), and RNAse free water up to the final 25 μl volume. The reaction was as follows: initial denaturation at 95 °C for 5 min, followed by 35 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 40 s, and elongation at 72 °C for 60–90 s and a final extension at 72 °C for 10 min. Amplicons were visualized by electrophoresis in 1.5% (w/v) agarose gels in 1× TAE , stained with GelRed™, viewed under UV light and the products sequenced . Primers used for amplifying the complete cox1, nad1 and nad5 genes were designed by Primer Premier 5 software based on the full mitochondrial genome sequence of T. hydatigena (GenBank: NC_012896)  according to the manufacturer’s instructions. PCR was performed in a final 25 µl reaction mixture containing 12.5 μl Premix Ex https://blast.ncbi.nlm.nih.gov/Blast.cgi). Nucleotide and haplotype diversity indices were estimated in DnaSP v6 [cox1, nad1, nad5, and concatenated cox1-nad1-nad5 genes using PopART (http://popart.otago.ac.nz). Pairwise nucleotide difference was calculated using MEGA 7 [ST was calculated using the Arlequin 3.5.2.2 software package [T. hydatigena isolates with other Taenia spp. was carried out based on cox1-nad1-nad5 (4083 bp) concatenated sequences with MrBayes v.3.1.2. The General Time Reversible model with a proportion of invariable sites and a gamma-shaped distribution of rates across sites (GTR + I + G) was used as the best-fit model of sequence evolution as determined by JModelTest [http://taxonomy.zoology.gla.ac.uk/rod/treeview.html) was used to display the phylogenetic tree.Sequences were assembled stepwise with the help of DNAstar v7.1 program and Unipro UGENE v1.29.0 software while making sure that the overlap sequences were identical and then viewed manually for correction of any nucleotide misread followed by alignment in BioEdit v7.2.6 . The ideDnaSP v6 . Median-DnaSP v6  was infeg MEGA 7 . Populatg MEGA 7  and Fu’sg MEGA 7  were calg MEGA 7 . FST was package . The BayodelTest . Markov T. hydatigena. Overall, 29, 24 and 27 isolates were successfully amplified for nad1, cox1 and nad5, respectively. A BLAST search of the resulting nucleotide sequences showed > 99% similarity with T. hydatigena sequences deposited in the GenBank database.All 32 isolates (24 goats and 8 sheep) were identified as cox1 (1620 bp), nad1 (894 bp) and nad5 (1569 bp) mitochondrial nucleotide sequences, we observed 24, 24 and 33 polymorphic sites, respectively for each gene, of which 62.5% (15/24), 75% (18/24) and 36.36% (12/33) were parsimony informative, respectively. The number of haplotypes (Hap) observed was 10, 10, 9 and 9 for nad1, cox1, nad5 and cox1-nad1-nad5 sequences, respectively (Table nad1 gene sequences and constituted 24.13% (7/29) of the total population with 1–7 mutational differences from the other haplotypes  of the total population and made up mostly of sheep isolates ; nad1, 6 amino acid substitutions  and nad5, 8 amino acid substitutions  , followed by nad5 (0.1–1.5%) and cox1 (0.1–0.7%). A high haplotype (Hd) and low nucleotide (π) diversity were observed for all three genes in both intermediate hosts , nad1  and nad5 . Taenia hydatigena population from sheep showed positive Tajima’s D for all genes and was significant for cox1. In contrast, isolates from goats showed negative insignificant Tajima’s D for all genes , resolved most inconsistencies with an overall Hd and π of 0.900 and 0.00358, respectively, and a positively significant Tajima’s D (2.20374) and Fu’s Fs (5.778) for isolates of sheep origin, suggesting the possibility of a balance selection or sudden population contraction. In contrast, a negative (insignificant) Tajima’s D (− 0.85760) and a significantly positive Fu’s Fs (5.873) were observed for isolates from goats. Using the cox1, nad1 and nad5 genes, FST values for pairwise comparison between isolates from goats and sheep were as follows: cox1 , nad1 , nad5 , and cox1-nad1-nad5  suggesting the possibility of genetically differentiated strains.The pairwise nucleotide differences were highest for nad1 0.1–.5%, follnad1 0.1–.5%, follnad1 0.1–.5%, follT. hydatigena cluster  values indicating weak nodal support (< 0.80) for the different haplotypes Fig. . Also, hnad1 sequences of 435 bp (including 29 sequences from this study) . Furthermore, the median-joining network presented two major haplogroups  and European and Asian/Middle Eastern isolates   data from other geographical locations as in this study, we could not employ the full-length mitochondrial genes for comparison. Nonetheless, on trimming, a final dataset of 59 T. hydatigena causes inconceivable damage in livestock production in endemic countries [T. hydatigena in sheep and goats could reach as high as 20–30% [Despite the fact that cysticercosis due to ountries –4, the gountries . In Niges 20–30% , 13 and s 20–30% , causings 20–30% , 43.T. hydatigena isolates from sheep and goats collected from a slaughterhouse in Nigeria based on complete sequences for three mitochondrial genes, cox1, nad1 and nad5, in contrast to the commonly employed partial gene sequences [Meanwhile, mtDNA has been widely employed in investigating the intraspecific variation of metazoans due to the absence of recombination, maternal inheritance, conserved structure, higher mutation rate and a relatively high evolutionary rate –47. Anotequences , 51, 52.cox1 gene while nucleotide diversity was similarly higher in goats and highest for nad1 gene. Overall, the diversity and neutrality indices based on concatenation of all three genes were higher in goats and demonstrated inconsistency with population expansion which suggest the possibility of a bottleneck event in the course of evolution. However, the diversity indices of the individual genes cox1 and nad1 were comparable to estimates from Iranian and Italian (Sardinia) T. hydatigena populations from sheep and goats [T. hydatigena populations of sheep origin [T. hydatigena), smaller area of Palestine, low small ruminant population (about 1.5 million) [T. hydatigena [T. hydatigena, such that a higher prevalence in intermediate hosts, as seen in Italy and Iran, may result in multiple infections (cysts from different intermediate hosts) in definitive hosts favouring sexual reproduction and consequently higher genetic variation within the population.Our analysis of the three mitochondrial genes revealed a considerable degree of genetic variation. Higher haplotype diversity was recorded for goat isolates and was highest for nd goats  but highp origin . In Palemillion)  as well datigena , 51. In datigena . These dT. hydatigena isolates (from both intermediate hosts) could have influenced the outcome of the neutrality and nucleotide diversity indices, the hypothetical existence of host-specific strains which has been reported cannot be completely ruled out [Although the significant differences in the number of examined Nigerian uled out , 54, 55nad1 and nad5 genes but these did not constitute the majority of the population. On concatenation of the three genes, which is believed to be more informative than the individual genes, no centralized haplotype was found. However, two distinct haplotypes were revealed in all sheep isolates. Meanwhile, the formation of a founder haplotype (29.2% of the population) based on partial cox1 (324 bp) gene was reported in a pooled population of T. hydatigena from different countries and hosts [nad1 gene in the latter study did not reveal a centralised haplotype. The same was true for Italian isolates from sheep, goats and wild boars [cox1 fragment (444 bp) and constituted about 55% of the examined population [T. hydatigena isolates from Turkish sheep and goats based on nad1 fragment (471 bp), no centralised haplotype was also observed [Based on the individual genes, the median-joining network featured a centralized haplotype only for nd hosts . Conversld boars . In Palepulation . Howeverobserved . Be thatST values between T. hydatigena populations from sheep and goats, suggesting genetic differentiation. Meanwhile, reports of host specificity have been previously documented between isolates from sheep and goats in Iran [T. hydatigena metacestodes from both hosts were found to be morphologically different. Similarly, analysis of the biochemical components of cysticerci from pigs and goats also suggested genetic differences [ST value. This is in-line with previous FST values suggesting genetic differentiation between sheep and goat isolates from Italy, China and Greece, as well as between pig isolates from Italy, China and Poland [T. hydatigena populations infecting different hosts. Then again, the observed pairwise fixation values and population indices could have been influenced by the small sample size analysed in the present study as sample size has been found to influence estimates of population indices [We observed high F in Iran  and Indi in Iran , such thferences . More sod Poland , which f indices .T. hydatigena as they clustered closely with other T. hydatigena isolates from other regions with relative distances from other Taenia spp.  from T. hydatigena isolates from other geographical regions and hosts revealed a population network that was consistent with population expansion based on the significant negative Tajima’s D and Fu’s F, indicating the presence of rare haplotypes as well as the characteristic star-shaped configuration with a centrally placed haplotype similar to previous observation by Boufana et al. [T. hydatigena. Moreover, the pitfall of short gene sequences in inferring the phylogenetic status and the genetic diversity of cestodes has been emphasized for Echinococcus spp. [T. hydatigena, as the 4083 bp of the mitochondrial genome provided a better resolution as indicated by the phylogenetic network and population indices.Furthermore, analysis of the trimmed a et al. . In the cus spp. . FurtherT. hydatigena isolates in this study. This is because small ruminants (sheep and goats) in Nigerian pastoral communities are mostly raised in the same environment and similar animal husbandry system. Moreover, each geopolitical zone of the country share similar geography (vegetation and climatic conditions), and in this study, the examined ruminants originated from the same state.The influence of geography or animal husbandry practices could not have plausibly explained the genetic differences observed between T. hydatigena in Nigeria for the first time using full-length mitochondrial gene sequences and suggests the possible existence of host-specific strains. The scarcity of complete T. hydatigena mitochondrial cox1, nad1 and nad5 sequences from different geographical regions in the GenBank repository limited a wide-range comparison and interpretation. However, the results suggest that longer DNA fragments or complete mitochondrial genome analysis may provide a better resolution in our understanding of the genetic diversity of T. hydatigena and the possible epidemiological significance.The present study, to the best of our knowledge, described the genetic variation of Additional file 1: Table S1.Taenia hydatigena mitochondrial cox1 gene nucleotide sequence polymorphism and corresponding amino acid changes among haplotypes from sheep and goats. Table S2.Taenia hydatigena mitochondrial nad1 gene nucleotide sequence polymorphism and corresponding amino acid changes among haplotypes from sheep and goats. Table S3.Taenia hydatigena mitochondrial nad5 gene nucleotide sequence polymorphism and corresponding amino acid changes among haplotypes from sheep and goats. Table S4. Characteristics of Taenia hydatigena isolates used in this study. Table S5. Comparison of pairwise fixation values (FST) for Taenia hydatigena isolates from different geographical regions compared to those from Nigeria based on partial nad1 mitochondrial gene sequences.


Glyptostrobus pensilis (Cupressaceae) is a critically endangered conifer native to China, Laos, and Vietnam, with only a few populations remaining in the wild.SSR loci and tested them for amplification success and polymorphism in 16 samples. Ten loci were found to be polymorphic and their genetic diversity was characterized using a total of 83 individuals from three populations in China. A total of 43 haplotypes were present, the effective number of haplotypes varied from 4.55 to 13.36, and the haplotypic richness ranged from 8.04 to 16.00. Gene diversity ranged from 0.81 to 0.97 (average 0.89). The number of alleles per locus and population ranged from one to eight, and the effective number of alleles ranged from 1.00 to 3.90. All polymorphic loci were successfully amplified in the related species Cryptomeria japonica var. sinensis, Taxodium distichum, T. ascendens, and Cunninghamia lanceolata.Using a complete chloroplast genome sequence, we designed 70 cpG. pensilis and related species.These newly developed chloroplast microsatellites will be useful for population genetic and phylogeographic analyses of  Glyptostrobus pensilis (Staunton ex D. Don) K. Koch, the only extant species in the genus Glyptostrobus Endl., is a relict conifer in the family Cupressaceae   D. Don var. sinensis Miq., Taxodium distichum (L.) Rich., T. ascendens Brongn., and Cunninghamia lanceolata (Lamb.) Hook.Chloroplast microsatellites have been widely used to investigate the population genetic structure and phylogeographic history of a range of tree species  for microsatellite loci exhibiting a minimum of eight repeats as these loci are likely to exhibit a higher level of polymorphism  method  and the same PCR protocol as detailed above. PCR products were run on an ABI 3730xL DNA Analyzer adding a GeneScan 500 LIZ internal size standard (Applied Biosystems) to size fragments. The software GeneMarker version 1.9 was used to score the electropherograms of all samples , 0.75 μL of forward primer (10 μM), 0.75 μL of reverse primer (10 μM), 3 μL of 20–50 ng/μL DNA template, and 3 μL of ddHA), number of private haplotypes (P), effective number of haplotypes (Ne), haplotypic richness (Rh), and gene diversity (He). The software GenAlEx6.5 , effective number of alleles (Ne), Shannon's information index (I), and diversity (H).The software Haplotype Analysis version 1.05  that can be used to assess the population genetic and phylogeographic structure of


Models of human migration provide powerful tools to forecast the flow of migrants, measure the impact of a policy, determine the cost of physical and political frictions and more. Here, we analyse the migration of individuals from and to cities in the US, finding that city to city migration follows scaling laws, so that the city size is a significant factor in determining whether, or not, an individual decides to migrate and the city size of both the origin and destination play key roles in the selection of the destination. We observe that individuals from small cities tend to migrate more frequently, tending to move to similar-sized cities, whereas individuals from large cities do not migrate so often, but when they do, they tend to move to other large cities. Building upon these findings we develop a scaling model which describes internal migration as a two-step decision process, demonstrating that it can partially explain migration fluxes based solely on city size. We then consider the impact of distance and construct a gravity-scaling model by combining the observed scaling patterns with the gravity law of migration. Results show that the scaling laws are a significant feature of human migration and that the inclusion of scaling can overcome the limits of the gravity and the radiation models of human migration. Today, human migration is one of the most debated concerns to the general public, governments and international agencies, due to the importance of integration policies, socioeconomic development and well-being. On the one hand, migrants contribute to the prosperity of their destination, to which they provide new skills, norms and community activities, as well as easing the pressures of an ageing population  and can It is therefore not surprising that the study of human migration has attracted the interest of scientists from many disciplines. Some studies investigate the dynamics of specific types of migration, such as international migration , 7, migrMigration between cities, as well as from the countryside to the cities, has attracted particular interest in recent years. Internal migration is indeed the main reason for urban growth  and the migrant as an individual who permanently moves from one location to another, so not considering movements within the same urban area, regardless of their legal status and without positive or negative connotation. Starting from official census data, we analyse the migration fluxes from and to US cities and investigate how these fluxes are influenced by the cities’ population size. Our main finding is that migrants preserve city size, i.e., they prefer to migrate to cities with a similar size to the city of their origin. Moreover, we observe a phase transition where the exponent in our model changes from sublinear to superlinear at a specific population size. Building upon these findings we develop a data-driven scaling model which describes human migration as a two-step decision process, demonstrating that it can partially explain migration fluxes only on the basis of city size. We then consider the impact of distance on a gravity-scaling model of human migration, showing that it performs better than the scaling, gravity and radiation model of human migration. The code of the models is available online: https://github.com/rafaelprietocuriel/Migration.Here, we study human migration in the context of cities and its population . We analcity is considered here as a high population density area with strong economic ties and with a population larger than 50,000 inhabitants. It is based on the metropolitan statistical areas (MSAs) defined by the U.S. Department of Commerce. This gives 385 cities for which the internal migration process is quantifiable . These cities are collectively formed by approximately 268 million inhabitants, so more than 80% of US population. The population size of individual US cities varies broadly from just above 50,000 inhabitants  to nearly 20 million inhabitants (New York City and Los Angeles) while individuals living in towns or rural areas with less than 50,000 inhabitants are considered to be part of the countryside. Using the available data, we analyse the following aspects of city to city migration:Our data source is a census which stores the number of migrants from one metropolitan area to another in the US , where aTo migrate or not);the probability that an individual chooses to migrate (Section Migration to and from other cities);the destination picked by migrants according to the size of their city of origin (Section Migration to and from the countryside);the probability that an individual moves to the countryside (Section Migration to cities from another country).the destination picked by international migrants  outflow migration from i and Xj* as the  inflow migration to j, such that ∑jXij = Xi*; and ∑iXij = Xj*, and Pi denotes the size of the population living in city i, with i and j = 1, 2,…,n.We assume that there are i as Xi*/Pi, which is the frequency of a resident leaving city i. We investigate how this probability depends on city size by fitting a power law equation:α and β are parameters to be determined from the data  which in turn determine the collective frequency of migrating from each city. However, a general pattern in which individuals from smaller cities are more likely to migrate is, nonetheless, detected.Patterns of human migration are quite variable among cities of different sizes and so noise is a relevant issue. One of the key aspects to consider is that 73% of the cities in the US have a population smaller than 500,000 inhabitants, and 50% of the cities have a population smaller than 250,000 inhabitants. Therefore, most of the observations are actually small cities, for which a large variation is expected, as we are comparing, for instance, the number of individuals who move into Yuma, Arizona, a city located in the border between the US and Mexico with the number of individuals who move into Rochester, Minnesota, a city in which the Mayo Clinic forms its core economy. Both cities have approximately the same population but their migration patterns might have different push and pull factors. However, by observing the average small city and comparing its migration patterns to medium-sized or large-sized cities, a different average pattern is observed, and these differences are, in most cases, statistically significant. The scaling equation detects a generalised pattern but it does not mean that all individuals from smaller cities have a higher probability of migrating than individuals from large cities. When Pi ≤ 200, 000) and fit R2 = 0.7101. We find a similar sublinear behaviour when using a different “small city” threshold, for instance, for individuals who used to live in a city with less than 500,000 inhabitants (R2 = 0.8061), less than one million inhabitants (R2 = 0.8554) or other thresholds within that range  when fitting Pi ≥ 5 million, we find a slight superlinear behaviour, as R2 = 0.7163. This behaviour gets more pronounced with a larger threshold, so we find that R2 = 0.5814) with Pi ≥ 8 million and that R2 = 0.5327) with Pi ≥ 10 million (see the section Pi > 5 million) is more likely to move to an equally large city than to move to a small city. Thus, individuals tend to preserve city size when deciding to migrate: an individual from a city with several million individuals is almost twice more likely to move to a city with several million individuals as compared to an individual from a small city and similarly, individuals from the smaller cities are more likely to move to equally small cities.In contrast, we find a superlinear behaviour , we find a sublinear behaviour with R2 = 0.6492) and find a similar sublinear behaviour when using a different population range, for instance, for the influx of individuals who move to a city of less than 500,000 inhabitants (R2 = 0.7429). In general, the impact of the sublinear behaviour gets more pronounced  and similarly if we look at the influx of individuals who moved to a city with more than 10 million inhabitants with R2 = 0.5538). Roughly speaking, 1.7 individuals in every 1, 000 inhabitants of a city with millions of individuals (such as Los Angeles) will have lived in a small city during the previous year, but nearly 20 individuals in every 1,000 in a small city will have lived in a different small city the previous year.In contrast, we find a superlinear behaviour if we look at the influx of individuals who move to a “large city”. For instance, if we analyse the influx of individuals who moved to a city with more than 8 million people, we find a superlinear behaviour with R2 = 0.6199). Thus, results show that an individual who lives in a city with less than 200,000 people is four times more likely to move to the countryside than an individual who lives in a city with 20 million inhabitants, such as Los Angeles or New York City.An individual who lives in a city might decide to migrate to the countryside and this decision is affected by the size of the origin city. By fitting a power law equation  we find R2 = 0.4421). Thus, an individual who currently lives in the countryside is 6 times more likely to move to a city with 200,000 inhabitants or less than to a city with 20 million individuals.Also, an individual who currently lives in the countryside might decide to move to a city and a scaling pattern for the size of their destination follows a sublinear behaviour (R2 = 0.7610) with an even more pronounced pattern for individuals from Africa (R2 = 0.5500) and Americas outside the US (R2 = 0.7036).We find that the destination of international migrants is also affected by the city size of the destination. An individual who arrives in the US from another country is more likely to move to a large city, that is, international migration also exhibits a superlinear behaviour. Larger cities in the US increase their population diversity, measured simply as the proportion of individuals who previously lived outside the US , three tThe inflow of international migrants for every 1,000 inhabitants varies according to the size of their destination. Thus, comparing the whole range of city size, we observe that large cities with millions of people are increasing their percentage of the population from Africa and from Americas outside the US, 32 times and 5 times faster respectively than the smallest cities , whether to migrate to the countryside (sublinear), move to a small city (sublinear), move to a large city (superlinear) and in the destination for international migration (superlinear). To take individuals from the countryside (51 million people) into account within the model, we consider that with a probability We consider a two-step simulation for the dynamics of internal migration observed in the US with individuals moving between different cities or between the countryside and the various cities. We also assume the Markov property so that an individual’s choice to migrate, as well as their destination, are based only on the current location . In the first step, we simulate for each individual, whether they migrate or not, while in the second step we determine the destination of the ones who have chosen to move. Since both steps are affected by the observed scaling laws, we model migration as a decision problem . AssuminThe observed scaling laws of city to city migration allow us to model the migration process by considering the distribution of US population living in different cities (83% of the US population) and the population living in the countryside (17% of the US population) and to consider the corresponding urban dynamics .Undoubtedly, physical distance has an impact on human migration  which islaw of migration, first published by Ernst Georg Ravenstein in 1885, developed looking at migration at county level from and to the UK, Ireland and Scotland, states, among many key issues [The y issues , that thgravity model  [Fij between locations i and j as:a is a constant which needs to be estimated from the data, b is a constant which takes into account the impact of distance and dij is the geographic distance between the two locations which in our case are cities, although the gravity model has been used to estimate the flux of migrants between countries, as for instance [i to j as it predicts from j to i; it assumes a linear impact of the population of each location on the flux; in some cases it predicts more individuals leaving a location than the amount of individuals in the location and other issues  , 23. Theinstance , 39. Altues (see ). There ues The gravity-scaling model takes into account the observed scaling probability that an individual will migrate as well as the preferential migration observed between individuals from small o large cities and the impact that the physical distance has on the migration patterns. The gravity-scaling model gives, in our case, the same results as the scaling model for the migration to and from the countryside and for the inflow of international migrants as the distance between a specific city and the countryside or a continent is not well defined.R2 obtained from the data. To determine the validity of the results of the scaling model and the gravity-scaling model (as measured by how well they fit the observed data), we compare against the commonly used gravity model and the radiation model of human migration. The two parameters of the gravity model  under the same dynamics, both models provide natural departures which could be observed under the same dynamics. For instance, between Houston and Dallas, there were 14,666 migrants and results from the 100 simulations of the gravity-scaling model show that a migration flux between 14,485 and 15,745 is expected under the same dynamics.Power laws correctly describe many aspects of human activity, from the frequency of family names, the wealth of the richest people , the sizOur initial scaling model examined human migration without considering the physical distance between cities, that is, only considering the city size. This stance is supported by the data which indicates that individuals from large cities are more likely to move to other large cities, despite the fact that large cities can be far away from each other and relatively scarce. Our gravity-scaling model considers also the impact of distance and so it could be considered a modified version of the gravity model. The gravity-scaling model has a better fit to the observed data, is not symmetric, does not have a systematic bias (as can be observed in the gravity model) and takes into account scaling .By considering scaling on migration patterns, the commonly used gravity model is considerably improved, highlighting the relevance of city size. A valuable aspect of both the scaling and the gravity-scaling models is that rather than providing a deterministic number for the flux between two cities, they give a procedure to simulate migration providing intervals which could be observed under the same circumstances. Both models begin by taking into account the number of inhabitants of a city and simulate whether individuals move and, if so, where do they move to. Therefore, there is a natural upper limit to the estimated number of individuals who leave that city, as opposed to the gravity model which might, under certain circumstances, estimate more individuals leaving that actually live there.Living in a large city may mean an improved access to education, job opportunities and income, among other “benefits”, but on average and it does not mean better education or income to all; however, the costs of living in a large city is experienced by all its inhabitants. The population living in Kibera, for instance  or Rocinha (the largest favela of Rio de Janeiro) enjoy a limited number of the benefits of living in a large city but they pay the price for longer commuting distances, a higher price for the food and services, pollution, crime rates and more. Thus, although large cities provide certain benefits, more people moving into large cities does not necessarily translate to people enjoying a better standard of living, but might, unfortunately, translate into greater inequality and severe socio-economic problems within the cities.The same applies to people from smaller cities. Take, for instance, the case of Carson City, one of the smallest cities in the US, where nearly twice the amount of people moved to Redding than to Sacramento , even though Sacramento is nearly 100 kilometres closer to Carson City than Redding is and Sacramento is 12 times larger in terms of population size. According to the gravity model, we would expect 20 times more people moving to Sacramento than to Redding since it is larger and closer, but we observe twice the amount of people moved to Redding than to Sacramento; scaling affects migration. Perhaps this is because Redding is a rural environment more similar to Carson City than Sacramento is, although this also warrants further explanation.In terms of migration, not everything can be explained by using only population and distance variables, as used in the models presented here. There are other reasons which create relevant push and pull factors for each city, for instance, Rochester, Minnesota might attract more medical doctors, whilst Ithaca and New Haven might attract more students. Migration is a complex social phenomenon, which begins with individuals deciding whether or not to migrate and develops further when the migrant selects their destination. The mathematical models used here focus on the detection of the patterns which emerge when millions of individuals move from one city to the other.In particular, the scaling model and the gravity-scaling model show a generalised pattern that is observed with noise being a normal and expected part of the model, as they are a simplification of a much more complex reality. Nonetheless, here results show that scaling is a fundamental aspect of the individual decision of moving and the destination picked by those who decide to move.The observed patterns might change and migration to small or large cities might be consequently affected. The current main drivers of migration could subsequently be replaced by other drivers, such as technology, an ageing population, jobs being lost due to automation, climate change, conflicts, fear of crime, water scarcity or other disasters, to name but a few. Cities might have experience positive and negative shocks, which affect their push and pull factors which change how they influence both internal and international migration. The methodology presented here allows different scaling patterns to be detected, through different time intervals, to be applied to international migration or migration from and to the countryside and the detection of quantitative and qualitative changes of human migration.The methodology presented allows different scaling patterns to be detected, through different time intervals, to be applied to international migration or migration from and to the countryside and the detection of quantitative and qualitative changes in human migration.β ∼ 1 the scaling might be negligible.The scaling and the gravity-scaling models are based on current observations of migration but it does not mean that the same pattern has been observed previously, nor does it mean that the same pattern will be observed in the future. However, the methodology presented here allows scaling to be taken into account from and to the countryside, between cities and from international migrants and it goes beyond a static result observed only for a specific time interval and a particular region of the world. It highlights that in the studies of migration patterns, scaling might occur, it does so without assuming that scaling happens. In the case in which the exponent Although distance does play a crucial role in migration, either because of the mental cost of being far from the origin, the lack of information about distant places  or the aThere are still open questions regarding the scaling phenomenon in the case of international migration. Is a person from a large city more likely to move to another country, despite the fact that people from large cities are less likely to migrate? Is the relationship found here, where an individual from a small city is more likely to move to equally small cities, also observed for international migration? Unfortunately, in our dataset there is little information about the origin of international migrants who arrive in the US. However, in terms of their destination we find a strong impact of the city size, which is even more prominent for people who previously lived in Africa or America but outside the US. An individual is less likely to move to a city in which they have less information , which mAlthough the results obtained here are based on data for migration to and from cities in the US, a similar scaling pattern is expected in other countries, so that we predict that an individual from Paris is less likely to move to the countryside than a person from Tours, a smaller French city; a person from Guangzhou is more likely to move to Beijing or Shanghai since both cities have millions of inhabitants, even though they are at 1,200 and 1,900 kilometres away respectively; and Sidney, Melbourne and Brisbane are increasing their international population at a faster rate than the rest of Australia. We predict scaling to be relevant for other types of migration and in other regions of the world, although there might be other drivers, for instance, language, weather, conflicts or government-controlled migration policies.Results of selected estimated parameters according to different thresholds of city size. The estimation of the parameters uses a logarithmic transformation on both sides of


AbstractPampusargenteus is a broadly exploited pelagic fish species, commonly misidentified as Pampusechinogaster. Genetic variation and population structure in Pampusargenteus was studied based on seven microsatellite loci. The observed high average allele number, heterozygosity values, and polymorphism information content of P.argenteus suggested high genetic diversity. No population genetic differentiation was detected based on the results of pairwise Fst, three-dimensional factorial correspondence analysis (3D-FCA) and STRUCTURE analysis, which implied continuous gene flow. Wilcoxon signed rank tests did not indicate significant heterozygosity excess, and recent genetic bottleneck events were not detected. Coupled with previous mitochondrial DNA results, the findings presented here indicate that high gene flow characterizes the current phylogeographic pattern of the species. Pampus Bonaparte, 1834, are mainly distributed in the Indo-West Pacific Ocean and have a rich landing yield in Kuwait, Iran, India, Malaysia, Thailand, China, Korea and Japan  is a broadly exploited pelagic species that has a high economic value because of its highly appreciated taste. Although all species of Pampus are important economical species, the morphological similarity among species of Pampus has resulted in considerable confusion in species-level identification. Pampusargenteus is the most widely distributed species of the genus, and it is usually identified as P.echinogaster  because of the morphological similarities  was regarded as a synonym of P.argenteus by some ichthyologists  are tandemly repeated motifs of 1–6 bases characterized by a high degree of length polymorphism , and theobtained . To furtP.argenteus was collected from the coastal waters of Kuwait, Pakistan, and China from 2010 until 2014 . Seven microsatellite loci developed by 2), 2 μL of dNTPs, 1 μL of fluorescently labeled M13R primer and locus specific primer without tail, 1 μL of locus specific primer with M13 reverse tail, 0.25 μL of Taq polymerase, and 1 μL of genomic DNA (10 ng). All loci were initially screened using the following PCR protocol: 5 min at 94 °C; 35 cycles of 45 s at 94 °C, 45 s at 50~58 °C, and 45 s at 72 °C; and a final step of 15 min at 72 °C. The reactions were then exposed to 72 °C for 45 min and held at 4 °C until further analysis. PCR products were diluted 20 fold with ultrapure Milli-Q water before being further diluted (1 in 5) in formamide containing the LIZ-500 size standard. The samples were separated by capillary gel-electrophoresis on an ABI 3730xl automated sequencer (Applied Biosystems). To score the consistency of microsatellite fragments, nearly 20% of PCR products were restored for replication (Genomic DNA was isolated from muscle tissue by proteinase lication . MicrosaAN), observed heterozygosity (OH) and expected heterozygosity (EH) were estimated using POPGENE 1.32 (PIC) was calculated using the Microsoft Excel Microsatellite Toolkit PageBreak(HWE) and the linkage disequilibrium of each locus  value and assess the Fst values. The 3D-FCA  was performed in Genetix version 4.05  steps were used, with the first 100,000 steps discarded as burn-in. To estimate the most likely number of clusters (K), an ad hoc approach , stepwise mutation model (SMM) and two-phase mutation model (TPM), where 95% single-step mutations and 5% multiple steps mutations with 1000 simulation iterations were set as recommended   to 31 (Par 03)  and the other populations (Xiamen and Sonmiani Bay)  and Taiwan (TW) showed a rather distant genetic relationship with the other four populations.According to the results of the 3D-FCA, the first, second and third principal components can explain 25.91%, 23.08%, and 17.92% of the overall variation, respectively . Obvious differences of proportion in the two inferred clusters were not detected in the five other populations , which suggested that P.argenteus should be in mutation-drift equilibrium (Table The population demography analysis showed no significant heterozygosity excess observed under all three mutation models by the Wilcoxon sign-rank test (um Table . AdditioPageBreakPageBreakAN, heterozygosity values and PIC of P.argenteus were detected by seven microsatellite loci, which is consistent with the mitochondrial DNA results of previous studies (Pampusargenteus presents a considerable yield, indicating a large population size. The wide distribution range of habitats indicates that P.argenteus faces limited natural selection pressure and can accumulate greater genetic variation. Significant excess OH was not observed, which showed that P.argenteus has PageBreaknot experienced bottleneck effect events. Moreover, the selection of loci with high PIC for the analysis can also lead to high genetic diversity.The degree of genetic variation is particularly important for the sustainability and evolution of species, and the strong correlation between genetic diversity and overall fitness has been reported . Populat studies . High geP.argenteus. The Bayesian clustering analysis by STRUCTURE also suggested that the distribution proportions of two inferred clusters were not very different from each other. Similar level of genetic differentiation was detected in mitochondrial DNA (Trachurusjaponicus can be transported over a long distance by the Kuroshio Current along the shelf slope of the East China Sea from areas northeast of Taiwan to the coastal waters of Japan (P.argenteus during its entire life stage could increase the gene flow and weaken the genetic differentiation among geographic populations (Microsatellite markers have demonstrated to be highly sensitive for detecting the population structure of fish . In thisrial DNA . Marine rial DNA . Physicarial DNA . Howeverrial DNA . For exaof Japan . The migulations .P.argenteus populations was detected, and the contemporary genetic structure of the species revealed in this study can preliminarily improve the genetic knowledge and provide a firm basis to guide fishery stock management in the Indo-Pacific Ocean. Unfortunately, only six geographical populations of P.argenteus were collected, which is not sufficient for an even sampling throughout its entire distribution in the Indo-Pacific Ocean. To describe the phylogeographic pattern of P.argenteus, additional representative populations should be collected for further analysis.In conclusion, high genetic homogeneity among six


Maintaining maximum genetic diversity and preserving breed viability in conserved populations necessitates the rigorous evaluation of conservation schemes. Three chicken breeds (Baier Yellow Chicken (BEC), Beijing You Chicken (BYC) and Langshan Chicken (LSC)) are currently in conservation programs in China. Changes in genetic diversity were measured by heterozygosity, genomic inbreeding coefficients, and autozygosity, using estimates derived from runs of homozygosity (ROH) that were identified using SNPs.Ninety DNA samples were collected from three generations for each breed. In the most recent generation, the highest genetic diversity was observed in LSC, followed by BEC and BYC. Inbreeding coefficients based on ROH for the three breeds declined slightly between the first and middle generations, and then rapidly increased. No inbreeding coefficients exceeded 0.1. Population structure assessments using neighbor-joining tree analysis, principal components analysis, and STRUCTURE analysis indicated that no genetic differentiation existed within breeds. LD decay and ROH at different cut-off lengths were used to identify traces left by recent or ancient inbreeding. Few long ROH were identified, indicating that inbreeding has been largely avoided with the current conservation strategy. The observed losses in genetic diversity and occurrences of inbreeding might be consequences of sub-optimal effective population sizes.The conserved Chinese chicken populations have high genomic diversity under the current conservation program (R: F). Furthermore, this study highlights the need to monitor dynamic changes in genetic diversity in conserved breeds over successive generations. Our research provides new insights into genetic diversity dynamics in conserved populations, and lays a solid foundation for improving conservation schemes.The online version of this article (10.1186/s12864-018-4973-6) contains supplementary material, which is available to authorized users. As one of the earliest centers of domestication for chickens, China has the most abundant chicken genetic resources in the world, with 107 indigenous chicken breeds. These breeds play an essential role in the Chinese poultry industry due to the popularity of traditional cuisine. Because these chickens typically exhibit high adaptability to variable environments, strong disease-resistance, and produce high-quality meat and eggs, they are an important breeding resource to meet future market demands . Twenty-An efficient in situ conservation scheme relies on an effective population size, as well as an effective selection and mating strategy . The recResults from a study that compared the effectiveness of these three mating systems suggest that F: R can sustain 90% of genetic diversity in a livestock population for more than 100 years . Other sThe genetic diversity dynamics in successive generations within a conserved population directly reflect the effectiveness of a conservation scheme. DNA markers can be used efficiently to estimate the genetic diversity within and between conserved populations . VariousIn order to investigate the effectiveness of the schemes that are currently used to conserve chicken genetic resources in China, we evaluated the genetic diversity of three conserved indigenous chicken breeds. SNPs, identified using high-throughput DNA sequencing in samples obtained from three generations per breed, were used to estimate diversity and track changes across time. These data can be used to evaluate and improve ongoing conservation efforts.Sample collection procedures strictly followed protocols approved by the Animal Welfare Committee of China Agricultural University .Three Chinese indigenous chicken breeds that have been enrolled in conservation programs were used in this study: Baier Yellow Chicken (BEC), Beijing You Chicken (BYC), and Langshan Chicken (LSC). Different geographical and environmental factors have contributed to the unique characteristics of these breeds. The Baier Yellow chicken, mainly produced in Jiangxi Province, has a distinct appearance with white ears and yellow feathers, beak, and shanks. It is a rare prematurity and egg-type breed. The Langshan chicken is a classic dual-purpose breed that originated in Jiangsu Province. This is one of the oldest breeds and is unusually tall, with long legs and a tail carried at a high angle. The Beijing You chicken is an ancient breed that originated during the Qing Dynasty in Beijing. Known as “royal chickens”, they are valued for their high-quality meat and eggs, and are uniquely marked by a crest on the head, a beard under the lower jaw, and feathers on both shanks –17.These breeds have been managed for optimal conservation as part of the National Chicken Genetics Resources program . Briefly, the conservation goals are that population sizes should be kept constant across generations , and random mating should be enforced within families, with one son kept per sire family and one daughter kept per dam family (R: F). Samples from 270 individuals were collected from NCGR, with three generations per breed and 30 individuals per generation. Samples are identified by breed abbreviation and the last two digits of the year in which samples were obtained . Breed and sampling information is summarized in Table MseI and HaeIII). The initial data set was filtered to exclude low-quality reads, and then aligned to the chicken genome  using BWA (v0.7.8) [All DNA samples were subjected to genotyping by sequencing (GBS) using an Illumina HiSeq 4000 sequencer  after double enzyme digestion ((v0.7.8) . PCR dup(v0.7.8) . Sequenc(v0.7.8) .P-value >10e-6.Quality control procedures were implemented using PLINK 1.90 . SNPs weBefore genetic diversity was estimated, linkage disequilibrium (LD) “pruning” was conducted using PLINK .He), observed heterozygosity (Ho), proportion of polymorphic markers (PN), and allelic richness (AR). He, Ho and PN were calculated using PLINK 1.90 with the default settings. AR estimates were determined using ADZE v1.0 [Nine generation-based sample pools  were used to calculate genetic diversity, as reflected by expected heterozygosity : The estimation of effective population size (Ne) was based on number of sires and dams, following Wright’s model [Ne requires the numbers of males (Nm) and females (Nf) in each population that participated in the R: F program, and is calculated using the equation: F) was calculated using the equation: Inbreeding coefficient based on the mating plan (’s model . ComputaFROH): A run of homozygosity is defined as a region > 100 Kb containing > 50 SNPs. FROH was calculated using PLINK v1.90  and is the fraction of the genome spanned by runs of homozygosity [Inbreeding coefficient based on runs of homozygosity  [To reduce noise due to linkage disequilibrium, SNPs with a pair-wise genotype ris (PCA)  was condis (PCA) . A neighis (PCA)  using this (PCA)  and dispis (PCA) . The genis (PCA) , using ais (PCA) , 31. Tenis (PCA)  was utilis (PCA) , 34. ResST [The unbiased genetic differentiation estimate, FST , was calST  with theGenome-wide nucleotide diversity (π) was computed for each breed using VCFtools v0.1.14  (paramet2) between alleles at two separate SNP loci [P-value >10E-6 were used to calculate r2 with Haploview [LD was evaluated as the correlation coefficient (rSNP loci . Within aploview . Inter-SNe) was estimated according to the random mating model of linkage disequilibrium, using default parameters in NEESTIMATOR v2.01 [Ne estimates for each breed were calculated as the average of the estimates for macrochromosomes (gga1-gga5) [Effective population size (OR v2.01 . Ne estia1-gga5)  (AxelssoRuns of homozygosity (ROH) were identified for each of the 9 sub-populations using PLINK v1.90. The ROH program slides a moving window of 1 Mb across the genome to estimate homozygosity. One heterozygous and five missing calls per window were allowed to avoid false negatives caused by occasional genotyping errors or missing genotypes. The minimum length and SNP counts required for each ROH were 100 kb and 50 SNPs, respectively. Additional statistical significant tests were conducted to detect the differences in genome-wide homozygosity levels among populations with three measures .Gallus_gallus 4.0) for each individual, providing ~8X average genome coverage. 6,950,965 SNPs were identified in the initial screen. 6,234,592 SNPs were excluded because they deviated from Hardy-Weinberg equilibrium , exhibited minor allele frequency ≤ 0.05 , or were located on non-autosomal or small chromosomes . 716,373 SNPs met criteria for inclusion in the final data set. The average physical distance between neighboring SNPs was 1.34 kb, ranging from 1.10 kb on GGA6 to 5.15 kb on GGA25  were subjected to high-throughput DNA sequencing. Two hundred seventy individuals, representing three generations per breed and 30 individuals per generation, yielded 120 Gb of high-quality sequence data. About 99.7% of the reads mapped to the reference genome (Ho (0.2348), He (0.2250), AR (1.235), and PN (0.8130) (Table Ho (0.2379), He (0.2281) and AR (1.238). The highest proportion of polymorphic markers (PN) was observed in BEC07 (82.41%), while BYC15 exhibited the lowest genetic diversity. As expected, BEC and BYC showed decreasing levels of diversity from the initial generation (BEC07/BYC07) to the current generation (BEC15/BYC15). Conversely, LSC displayed increasing diversity with the implementation of a conservation program . LSC exhibited the highest genetic diversity as measured by Ho 0.348, He (250), AR .235, andFES ranged from 0.0789 in BEC to 0.2010 in BYC. As expected, FES values across generations increased as conservation procedures were maintained. In contrast, average FROH tended to be lower than FES, ranging from 0.0511 in BEC to 0.0745 in BYC, and FROH did not exhibit the steady increase that was observed for FES. Maximum inbreeding was observed in BYC15 (FES = 0.2010 and FROH = 0.0925). Correlation between FES and FROH was strongly positive (r2 = 0.76).Estimated inbreeding coefficients varied between breeds and conservation methods. Average Population structures of the three native chicken breeds, comprising 9 conservation sub-populations, were analyzed using PCA, NJ tree, and STRUCTURE. PCA showed that the first two principal components account for 17.77% (PC1) and 15.01% (PC2) of the total variability. Individuals from the 9 sub-populations clearly group into their respective breeds Fig. . The resFigure ST values were calculated using the filtered genotype data , indicating that no obvious genetic differentiation appeared within any breed  and BEC10 vs BEC15 (0.0285).To investigate the extent of population differentiation between different generations within breeds and between breeds, F243 Fig. . FST valeed Fig. . However2) decays to less than half of its maximum value. Short-range LD was always observed in each of the three different generations within same breed  was estimated for autosomal chromosomes gga1 through gga28 based on linkage disequilibrium (Table Ne differed amongst the 9 sub-populations (from 19.33 to 34.85). Within macrochromosomes (gga1–5), BEC07 had the highest estimated Ne (81.52) within a breed, and Ne declined in BEC as conservation continued. In contrast, Ne was lower (55.36) in LSC12 than in LSC10 (70.28) or LSC15 (73.74). Ne estimates for BYC fluctuated, with a high value (75.04) in BYC10 and lower values in BYC07 and BYC15.Effective population size  were identified in the genomes of the 9 sub-populations from all three breeds Table . A genom05 Table . BYC15 h20.1248 = 24.61 kb), followed by BYC07 and BYC10. We speculate that BYC inbreeding might reflect the small effective population size of this breed  . NSEG and KB also showed significant differences (P<0.0001) between generations in BEC and NLS.ROH was then assessed to determine whether any populations exhibited evidence of recent inbreeding. All three generations in BYC had higher ROH values, suggesting that recent inbreeding had occurred in this breed Table . Consisted Table . The ROHThe chicken, one of the first animals to be domesticated, has been subjected to long-term natural selection, artificial selection, and genetic drift for diverse specific traits , 42. A vHo, He), proportion of polymorphic markers (PN), and allelic richness (AR), consistent with previous studies [The majority of studies have estimated genetic variability in Chinese indigenous chickens using microsatellites , 46 or m studies –51. In t studies , suggestThe genetic diversity in all breeds changed no more than 10% between generations , based on whole-genome SNPs for the conserved populations, were far below the required threshold of 50 individuals [Ne according to chromosome size, using the classification proposed by the International Chicken Genome Sequencing Consortium [Ne based on the macrochromosome class (gga1–5). The maximum Ne was 81.52 in BEC07 and the minimum was 41.56 in BEC15 . The results demonstrated that the conserved Chinese chicken populations have sustained high levels of genetic variability under current conservation practices. We also compared successive generations within each breed to characterize trends in genetic diversity, allowing us to assess the effects of conservation over time. Overall, this study demonstrates an efficient strategy for assessing the success a conservation program and for improving conservation and management practices.Additional file 1:Table S1. The distribution of SNPs and average distances between neighboring SNPs. (DOCX 17 kb)Additional file 2:Figure S1. SNP density and distribution across the genome . (TIF 2605 kb)Additional file 3:Figure S2. Fluctuations in genetic diversity among different generations within each breed. (TIF 2872 kb)Additional file 4:Table S2. Genetic differentiation  among the 9 sub-populations in three chicken breeds. (DOCX 25 kb)Additional file 5:Table S3. Differences in measures of homozygosity between individuals among 9 sub-populations in three chicken breeds. (DOCX 27 kb)


Schisandra chinensis, a climber species with a generation time of five years, was investigated using chloroplast DNA (cpDNA), nuclear single copy gene (nSCG), and nuclear single sequence repeats  markers, along with ecological niche modeling (ENM), which predicted a suitable habitat in Korea Peninsula (KP) during the LGM. Private haplotypes and high genetic diversity of both cpDNA and nSCG were mainly found in KP and Changbai Mt. (CB). Although no significant phylogeographic structure was detected in the cpDNA and nSCG, three nSSRs clusters roughly distributed in west (CB and KP), east (north China), and north  regions were found in Structure analysis. The approximate Bayesian computation analysis showed the west cluster diverged at 35.45 kya, and the other two clusters at 19.85 kya. The genetic diversity calculated for each of the three markers showed no significant correlation with latitude. Genetic differentiation of nSSRs was also not correlated with geographic distance. Migrate analysis estimated extensive gene flow between almost all genetic cluster pairs and BOTTLENECK analysis showed that few populations experienced severe bottlenecks. Overall, results indicate that S. chinensis survived the LGM in situ in multiple refugia, which likely include two macrorefugia (KP and CB) and two microrefugia (XR and north China). Extensive postglacial gene flow among the three nSSRs clusters led to uniformly distributed genetic diversity and low genetic differentiation.Temperate conifers and broadleaved mixed forests in northeast China are ideal to investigate the genetic consequences of climate changes during the last glacial maximum (LGM), 29 – 16 kya. As previous studies were focused on tree species with long generation time; here, the evolutionary history of  Quaternary climate changes, especially the last glacial maximum  hindered the precise discrimination of the two different scenarios  Baill, a common climber species with short generation time (about five years) . Then, the correlations between genetic diversity and latitude or IBD were calculated. Historical gene flow was estimated using the maximum-likelihood (ML) algorithm, and whether populations have experienced genetic bottleneck was also estimated.e years) , was choe years) , while ie years) . The genS. chinensis conforms to the single refugium or multiple refugia scenario, and (2) reveal the distribution patterns of genetic diversity and genetic differentiation of S. chinensis and their potential causes.To further understand the influence of the LGM on mixed forests, the present study aimed to (1) determine whether S. chinensis from 20 populations , Beijing, China.We collected 355 individuals of ulations  and fourmatK, ndhA, trnL-trnF, and trnS-trnG .Total genomic DNA was extracted using a Plant Genomic DNA Kit . We amplified and sequenced four chloroplast gene fragments, namely rnS-trnG  for 148 ividuals . The PCR2 with 1000 permutations was used to compare two forms of genetic differentiation (GST and NST) in all populations. The most parsimonious network was inferred using Network 4.6.1.1  from zero was used to test the deviation from Hardy–Weinberg equilibrium in each population. Genotypic disequilibrium was tested for all loci pairs in all populations by randomization, and the obtained P-values (=0.05) were adjusted using the Bonferroni correction. All the above calculations were performed in Fstat 2.9.3 (RS) and private allele richness (PAR) in all populations were calculated in hp-rare 1.0  and latitude were performed in R 3.2.3. Severe population size decreases were detected in BOTTLENECK  tree using Poptree2 (K (K = 1–20) with 1 × 105 initial burn-in, followed by 1 × 106 Markov Chain Monte Carlo (MCMC) steps using an admixture model with correlated allele frequencies. Potential clusters (K) were determined by LnP(D), the change in log-likelihood of the data for each run  between successive K values (FST/(1 – FST) and the natural logarithm of geographic distance. The Mantel test was performed with 9999 permutations in GenAlEx 6.5  of the three scenarios and estimated the parameters of the most possible scenario.To detect population divergence history, all populations were assigned to one of the three gene pools corresponding to its largest proportion of ancestry; population LW  was the Nμ  and M = m/μ  to calculate the effective number of migrants (Nm). We used 10 short chains , three long chains , 20 genealogies, and burn-in of 10,000 initial trees. The starting values for θ and M were estimated from FST values. All individuals were included and the analyses were run three times, independently.The historical gene flow among the nSSRs clusters was estimated using the ML algorithm in Migrate 3.6.8 . We estiS. chinensis as well as those during the LGM and last interglacial (LIG). Fifty-five presence records were obtained from this study (20 sample sites) and from the Global Biodiversity Information Facility3 (35 occurrence locations). Seven climate variables with low correlation (<0.8) were used to model the niche (The maximum entropy modeling technique (MAXENT)  was utilhe niche   nor correlations between HR and latitude  were found. All the newly obtained sequences were uploaded to GenBank (Accessions MH580160–MH580199).Neither significant phylogeographic structure  or when populations with sample size < 10 were excluded   . An IBD K was high for K = 2 or K = 3 (LnP(D) and ΔK were both higher at K = 3 than at K = 2, indicating that three clusters were more likely than two clusters. The three clusters were roughly distributed in the east, west and north regions  and among all three clusters (t1) were estimated as 3.97 × 103 generations with a 95% highest-probability-density interval (HPD) of 0.79 × 103 – 1.20 × 103) and 7.09 × 103 generations (95% HPD: 1.64 × 103 – 12.40 × 103), respectively. The generation time of S. chinensis is assumed to be five years. Therefore, the absolute t2 was 19.85 kya (95% HPD: 3.95 – 60.00 kya) and the absolute t1 was 35.45 kya (95% HPD: 8.20 – 62.00 kya). The mutation rate was estimated as 3.91 × 10−5/locus/generation. The estimated effective population size in west, north, and east clusters were 4.31 × 104, 8.18 × 104, and 7.13 × 105, respectively (Nm) were very high  indicated good accuracy of model predictions. During LGM, both models predicted range contractions. The CCSM4 predicted that the most suitable habitat was located at KP, while MIROC 3.2 indicated the Yellow Sea land bridge and adjacent regions and KP as the most suitable locations. During the LIG, suitable habitats were predicted to be more limited than that at present .S. chinensis, a common climber species in mixed forests, in detail based on multiple genetic markers and potential habitat predictions. Contrary to the southern contraction of mixed forests during the LGM inferred by vegetation reconstructions  was revealed by the different genetic markers and no phylogeographic structure was revealed in either cpDNA and nSCG and in the NJ tree of nSSRs. However, nSSRs Structure analysis indicated that populations could be divided into three clusters  roughly corresponding to their geographic ranges. The DIYABC analysis showed the west cluster diverged before the other two clusters (35.45 kya) and before the LGM, and persisted through the LGM. The divergence time between the north and east clusters (19.85 kya) indicated their divergence was likely triggered by LGM and these two clusters have persisted in situ since the LGM. Thus, the three S. chinensis clusters probably had multiple LGM refugia.Low genetic differentiation  as sources for northward range expansion, latitude . Howeverraiensis . The ABCraiensis , the preby birds , pollen by birds , and theS. chinensis using multiple genetic markers and potential habitat predictions. Divergence times among the three nSSRs clusters showed that S. chinensis persisted in situ through and since the LGM. Two macrorefugia, at KP and CB, were revealed by ENM and high allelic privacy and genetic diversity distributions. Haplotype and nSSRs cluster distributions indicated two possible microrefugia located at XR and north China. Extensive gene flow among clusters resulted in the uniform distribution of genetic diversity and in the absence of an IBD pattern. Short generation time, and seed and pollen movement have facilitated this extensive gene flow. The present study using a common climber species with short generation time is an important complement of previous studies that mainly used tree species with long generation times.A detailed evolutionary history was revealed for https://www.treebase.org/treebase-web/home.html) under submission number 23007 (http://purl.org/phylo/treebase/phylows/study/TB2:S23007).DNA sequences: deposited in Genbank under accessions MH580160–MH580199. All the chloroplast and nuclear sequences were deposited in TreeBASE (H-FW, LB, and J-PG conceived the study. Z-KZ contributed to the sampling. Z-KZ and J-WY collected and analyzed the data. J-WY, LB, and H-FW wrote the manuscript. All authors read and approved the final 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.