Carcinus aestuarii , across the Mediterranean Sea. Recently, marked divergence between two highly separated haplogroups (genetic types I and II) of C. aestuarii was discerned across the Siculo-Tunisian Strait, suggesting an Early Pleistocene vicariant event. In order to better identify phylogeographic patterns in this species, a total of 263 individuals from 22 Mediterranean locations were analysed by comparing a 587 basepair region of the mitochondrial gene Cox1 (cytochrome oxidase subunit 1). The examined dataset is composed of both newly generated sequences (76) and previously investigated ones (187).Recently, population genetic studies of Mediterranean marine species highlighted patterns of genetic divergence and phylogeographic breaks, due to the interplay between impacts of Pleistocene climate shifts and contemporary hydrographical barriers. These factors markedly shaped the distribution of marine organisms and their genetic makeup. The present study is part of an ongoing effort to understand the phylogeography and evolutionary history of the highly dispersive Mediterranean green crab, Our results unveiled the occurrence of a highly divergent haplogroup (genetic type III) in the most north-eastern part of the Mediterranean Sea. Divergence between the most distinct type III and the common ancestor of both types I and II corresponds to the Early Pleistocene and coincides with the historical episode of separation between types I and II. Our results also revealed strong genetic divergence among adjacent regions (separating the Aegean and Marmara seas from the remaining distribution zone) and confirmed a sharp phylogeographic break across the Eastern Mediterranean. The recorded parapatric genetic divergence, with the potential existence of a contact zone between both groups in the Ionian Sea and notable differences in the demographic history, suggest the likely impact of paleoclimatic events, as well as past and contemporary oceanographic processes, in shaping genetic variability of this species.Our findings not only provide further evidence for the complex evolutionary history of the green crab in the Mediterranean Sea, but also stress the importance of investigating peripheral areas in the species’ distribution zone in order to fully understand the distribution of genetic diversity and unravel hidden genetic units and local patterns of endemism.The online version of this article (10.1186/s12862-018-1167-4) contains supplementary material, which is available to authorized users. In the marine environment, genetic variability and population genetic structure of a species are shaped by both contemporary and historical marine barriers, such as narrow and shallow water passages between landmasses , salinitPalaeoclimatic and palaeogeographical evolution of the Mediterranean, primed by sea-level low stands during glacial periods of the Pleistocene and the consequent shift in abiotic  and biotic factors , prompted population isolation and divergence, following local events of extinction and recolonization. This in turn enhanced the formation of intraspecific genetic units within various marine taxa, due to historical or contemporary hydrographic barriers to gene flow , 5. The In this context, the phylogeography of Mediterranean species underwent a common set of processes resulting from fragmentation within glacial refugia, range expansions via postglacial colonisation, and secondary contact zones among historically divergent lineages , 15–18.Carcinus aestuarii  , represents a good model to test the impact of current and historical marine barriers on population subdivision and genetic structuring across various marine biogeographic boundaries in the Mediterranean Sea. This species is a very common inhabitant of estuaries and lagoons of the Mediterranean Sea and has also been reported from the southern Black Sea [The Mediterranean green crab, lack Sea , 20. It lack Sea , 21. Thelack Sea , 23.C. aestuarii specimens into several regions outside their native range, such as to the Canary Islands [Owing to maritime commerce and ballast transport, several reports have pointed out to the accidental introduction of  Islands , Tokyo B Islands  and Sout Islands , 26.C. aestuarii, the particular ecological specialization of this species to estuarine and brackish-water habitats in the Mediterranean could be considered as important factor susceptible of generating significant phylogeographic patterns, owing to limited connectivity among estuarine populations. Restricted gene flow is highly expected in estuarine and brackish-water taxa owing to larvae retention within their natal estuary . In . In C. ary  sequences were obtained from 76 specimens collected from seven sites across the Eastern Mediterranean Basin, stretching across the Greek and Turkish coasts. This newly generated dataset of sequences was merged with previously examined data by Ragionieri and Schubart [In light of these considerations, it will be interesting to re-examine population genetic structure in a highly dispersive decapod species, like Schubart  and DeliSchubart  for phylCarcinus aestuarii were included in the present phylogeographic study, of which 76 were newly analyzed, and the remaining 187 had been previously investigated [C. aestuarii were collected from seven locations stretching across the Greek (Lefkada and Alexandroupolis) and Turkish coasts   or the Nh), number of polymorphic sites (Nps), haplotype diversity , nucleo , an  and nonsynonymous substitutions (dN) [0: dN = dS) depends on the tested alternative hypothesis (HA): (a) lack of neutral evolution (dN is different from dS:dN ≠ dS), (b) positive selection (dN > dS) or (c) purifying selection (dN < dS). A two-tailed test was implemented to reject neutral evolution, while one-tailed tests were used to check for positive and purifying selection, respectively. The variance of the difference between synonymous and nonsynonymous substitutions was computed using the bootstrap method (1000 pseudoreplicates). Analyses were conducted using the Nei and Gojobori [To test in how far natural selection is operating on the n 7.0.18 . Codon-bons (dN) . The relGojobori  procedurC. aestuarii. Based on the outcome of the TCS analysis, we also examined the distribution pattern of the discerned divergent haplotypes (or Cox1 haplogroups) across the surveyed geographic region.A statistical parsimony network, constructed with the software TCS version 1.21  under thGST) and ordered haplotypes (NST). Estimation and comparison of these parameters was based on the methods described by Pons and Petit [NST is significantly higher than GST, it usually indicates the presence of phylogeographic structure [Based on the particular pattern of evolutionary relationships among Cox1 haplotypes (yielding various differentiated haplogroups that were restricted to specific geographic regions), we assessed the relationship between phylogeny and the geographical distribution of the recorded haplotypes by measuring levels of population subdivision, using both unordered . Subsequently, the entire intraspecific dataset  was used for the divergence estimate, applying a specifically determined clock rate of the examined genetic marker for the genus Carcinus [In order to elucidate the evolutionary history of Carcinus .C. aestuarii and its Atlantic sister species C. maenas , highlighting variation in rates among branches, final analyses were run enforcing a relaxed molecular clock model. Uncertainty on the divergence time was modelled using a normal prior with a standard deviation of 55,000 years [In a first analysis, we considered the closure of the Strait of Gibraltar at the beginning of the Messinian Salinity Crisis  as calinas see , 62). Di. DiC. aenas  was useMyr  simulations were run for 100 million steps and sampled every 1000 steps. The corresponding outputs were reviewed in TRACER version 1.5  for robuΦST . For both kinds of analyses, the resulting significant values were calculated from 10,000 permutations. B-Y FDR correction [C. aestuarii was also examined (by means of two-level AMOVAs) under various biogeographic hypotheses, testing the significance of population structure among Mediterranean basins (Western Mediterranean vs. Eastern Mediterranean), or among defined regions within basins (Algerian Basin vs. Afro-Sicilian Basin vs. Adriatic Sea vs. Ionian Sea vs. Aegean Sea vs. Sea of Marmara). Partitioning of C. aestuarii genetic variation was also assessed based on the outcome of haplotype network (among the main groups of populations defining each haplogroup) and pairwise comparisons of genetic differentiation, as well as the MDS plot.Overall population genetic differentiation  as wellquencies ) and FSTrrection  was thenrrection , based orrection  for pairrrection . The staC. aestuarii. The software was run with 100 random initial conditions for 10,000 iterations, with number of tested groups (K) ranging from 2 to 8.The spatial analysis of molecular variance (SAMOVA) approach, implemented in SAMOVA version 1.0 , withoutD [Fs [R2 [D and Fs indices were estimated in ARLEQUIN, while R2 statistic was calculated in DnaSP. The examination of deviation from neutrality by all three indices was based on 1000 coalescent simulations. A scenario of population expansion is likely supported by significantly negative D and Fs values as well as significant R2 . The Harpending’s raggedness index rg [C. aestuarii according to the population expansion model implemented in ARLEQUIN. A total of 10,000 replicates allowed testing the significance of the rg index. The four above mentioned parameters  were applied to each examined population, the overall dataset, as well as the genetically differentiated geographic groups (as inferred mainly by SAMOVA).Three neutrality tests  were usindex rg  was alsoCarcinus by Marino et al. [Since deviations from neutrality are usually caused by changes in effective population size, we also applied Bayesian Skyline plots (BSP)  to exploo et al. , was impo et al. . Two indo et al.  and summC. aestuarii were included in the analyses. Of these, 76 were newly obtained, proofread and aligned. The resulting alignment had to be trimmed to a length of 587 basepairs. A total of 97 nucleotide sites were variable, of which 58 were parsimony-informative. Nearly 40% of the examined sequences were unique and allowed the identification of 106 haplotypes  and nucleotide (π = 0.0211 ± 0.0009) diversities  for all examined populations (except Benikhiar), as well as for the total dataset , as no significant positive selection was detected for all investigated populations of C. aestuarii as well as for the whole dataset  , and IIC. aestuarii across the Eastern Mediterranean Basin. Indeed, type II sequences were only found in Tunisian  and Libyan (Tripoli and Mosrata) populations. On the other hand, type III sequences were mostly found in specimens from Greece  and Turkey  and GST (0.121) revealed that the NST value is significantly higher than the GST value (P < 0.05), inferring significant relationship between phylogeny and the geographical distribution of haplotypes, and indicating the existence of marked phylogeographic structure within the examined material.While type I sequences proved to be present in almost all examined populations, the genetic distinctiveness of the other two haplogroups hints at the existence of a remarkable regional geographic structure within ey Figs.  and 3a tey Figs.  and 3b aAll three recorded Cox1 types occur in the Eastern Mediterranean Fig. . This clC. aestuarii and C. maenas as calibration point and ii) a Birth-Death prior and uncorrelated lognormal relaxed clock, divergence among type III and the monophyletic group composed of types I and II was estimated to occur approximately around 1.54 Mya . Using a strict molecular clock with a species-specific mutation rate of 3.86% per Myr , and assuming a GTR model of sequence evolution and a coalescent tree prior, involving all the intraspecific data of C. aestuarii, the estimated time of the split between Cox1 type III and both types I and II was relatively younger .The outcome of Bayesian phylogenetic analysis, as implemented in BEAST, confirmed the results inferred from the TCS parsimony procedure, yielding a noticeable separation between the highly differentiated type III and the monophyletic group composed of both types I and II. Assuming i) a 5.59 Myr split (see ) betweeno et al.  for CarcC. aestuarii based on Tajima-Nei distances  and haplotype frequencies . This differentiation was more pronounced based on nucleotide divergence (more than 61% of the variation among populations). Pairwise comparisons of genetic differentiation, estimated from nucleotide divergence and haplotype frequencies, also yielded significant differences for most comparisons and revealed, in particular, a clear genetic distinctiveness of the populations of Alexandroupolis, Izmir Bay, Enez Dalyan Lagoon, Dardanelles Strait, Prince’s Islands and Bosphorus Strait, after B-Y FDR correction  by means of a Mantel Test, supporting an isolation by distance hypothesis to better explain the population separation.The one-level AMOVA gives evidence for strong and highly significant genetic differentiation among the examined populations of on Table . The outon Table , suggestΦCT = 0.164, P < 0.05; FCT = 0.082, P < 0.01), a significant and more pronounced genetic separation within C. aestuarii  was also revealed when testing differentiation among Mediterranean sub-basins . It also explained most of the population genetic structure of C. aestuarii  was highest with two hierarchical groups ), the selected significant grouping of K = 2 (corresponding to the highest partitioning of variance among groups) matches perfectly the results inferred from the outcomes of pairwise comparisons of genetic differentiation and MDS plots. Besides, the concordance in the outcome of the two different approaches defining the population structure pattern (with (AMOVA) or without (SAMOVA) a prior structure parameter) consolidate the hypothesis that most of population genetic structure within C. aestuarii is explained assuming two hierarchical groups. Accordingly, this perfect agreement between results of different analyses assures the correct delineation of population structure and verifies and confirms the choice of the SAMOVA grouping of K = 2. Such pattern of genetic differentiation highlights the existence of a barrier to gene flow between two delineated (and adjacent) geographic groups within C. aestuarii in the Eastern Mediterranean Basin. The first group, harbouring mainly types I and II, covered mostly the North African coast as well as the Adriatic and Ionian seas; while the second group, including exclusively type III specimens, characterized the Aegean and Marmara seas.Population genetic structure was examined by means of two-level AMOVA, testing for partitioning of genetic variation under alternative biogeographic hypotheses . Our results showed significant genetic structure under these various grouping schemes Table . Indeed,D, 4 by the Fu’s Fs, and 5 by the Ramos-Onsins and Rozas’s R2 test; Table D and Fs tests have little power to detect departure from neutrality, when sample size is small , more weight should be put on the outcome of the R2 test, which is more powerful than either D or Fs tests in case of small sample sizes. Hence, population expansion can be roughly inferred for five populations ; whereas it is uncertain in all the remaining cases. The negative and significant value of Fu’s FS test, together with the small and non-significant value of Harpending’s raggedness index rg, also revealed significant deviations from neutrality for the whole dataset (Table D and Fu’s Fs), associated with small and non-significant values of the Harpending’s raggedness index, for group 1  and group 2 .Overall, the applied neutrality tests revealed significant deviations from mutation-drift equilibrium for a total of twelve populations  showed a relatively sudden and recent increase of effective population size over time, following a short phase of size decrease, preceded by quite a stationary period  in the most north-eastern part of the Mediterranean Sea, in addition to two haplogroups (types I and II) previously described by Deli et al. [C. aestuarii from the Greek population of Navarino (Peloponnesus) and briefly discussed in Ragionieri and Schubart [C. aestuarii and stressing a sharp phylogeographic break across the Eastern Mediterranean.The results of the present study provide new and interesting insights into the genetic composition of i et al. . Type IISchubart  but the C. aestuarii exhibits complex population structure across its distribution range. Earlier investigations by Ragionieri and Schubart [The existence of these two genetically and geographically differentiated groups confirmed the assumption and previous results that Schubart  and DeliSchubart  showed mSchubart  providedC. aestuarii could be the footprint of a complex evolutionary history of the species within the Mediterranean Sea. Type III represents the most distinct haplogroup with high levels of nucleotide divergence. We suggest it to be a genetic isolate that might have survived different episodes of Pleistocene climate changes. During the Quaternary glacial periods, sea level regressions limited the biotic exchange through the Strait of Gibraltar [The remarkable coexistence of all three Cox1 types  in the Eastern Mediterranean, being regionally differentiated, allowed us to advance the hypothesis that such particular pattern of mitochondrial diversity within ibraltar  and the ibraltar . These hibraltar . This coibraltar , 94. Earibraltar  allowed C. aestuarii with type III mtDNA in the Sea of Marmara and the adjacent Aegean Sea potentially suggests that this isolated haplogroup could have originated in the Black Sea and subsequently dispersed into the Aegean. In this context, we hypothesize that the highly divergent Cox1 type III could be the result of historical isolation mediated by the closure of the Bosphorus Strait during Pleistocene climate shifts [C. aestuarii echoes a similar explanation of the discerned phylogeographic pattern in other marine invertebrate from the Black Sea and Aegean Sea, i.e., the bivalve Mytilus galloprovincialis  into the Aegean (via the Black Sea water current), following the onset of connection between both basins. A similar scenario was also proposed for the littoral prawn Palaemon elegans genetic type III, with a potential Black Sea origin [Pachygrapsus marmoratus confined to the Black Sea. The authors stressed on the importance of the biogeographic barrier between the Aegean and Black seas, susceptible of disrupting dispersal and gene flow for many marine species during past and present times and triggering intraspecific diversification in the Mediterranean.The particular geographic concentration of e shifts . These pe shifts , could hlis (see ). Based lis . This lineage must be relatively tolerant to brackish waters, considering that it recently invaded the Baltic Sea . Similarly, Luttikhuizen et al. [Crangon crangon might also have survived in the Black Sea in brackish waters with salinities of less than 7 ppt.This likely scenario is reinforced by the fact that the Black Sea was repeatedly isolated from the Mediterranean Sea during Pleistocene glaciations and diluted with fresh water during those periods . Svitoch valence ), it can valence  previousn et al.  argued tC. aestuarii within the Eastern Mediterranean, following episodes of historical isolation between the Aegean Sea and the Eastern Mediterranean, as has been reported in several studies [The marked genetic divergence between both geographically delineated groups (harbouring different Cox1 types) could reflect the impact and likely involvement of historical processes  in shap studies , 39–45. D, Fu’s FS, and Ramos-Onsins and Rozas’s R2) for both divergent genetic groups of C. aestuarii (delineated by SAMOVA) showed significant values, indicating significant deviation from neutrality due to historical factors (such as a population bottleneck or sudden expansion) and contemporary processes . Notably, significant negative D and FS values  were retrieved for both geographic groups. Such patterns clearly indicate that these genetic entities have undergone demographic expansion and refer to a loss of equilibrium among mutation, gene flow and genetic drift [C. aestuarii, highlighted by more recent expansion event in group 1  than that recorded in group 2 . Notably, while both demographic events were found to precede the Last Glacial Maximum  on pattern of genetic diversity evolution. In addition to the observed temporal variation, marked spatial differences in the demographic history of the Mediterranean green crab also have been noticed. While a pattern of sudden population growth was detected for group 1 (composed mainly by types I and II), the species exhibited a pattern of slight and progressive increasing population size in the Aegean Sea and the Sea of Marmara (group 2 harbouring exclusively type III). We may therefore hypothesize that these spatial differences could likely stem from the potential impact of Pleistocene climate fluctuations  on the availability of favourable abiotic conditions . In this context, we may attribute the less magnitude of expansion event, recorded in the Aegean and Marmara seas (group 2), to the lack of suitable habitat availability for C. aestuarii which could have probably led to population expansion limitation. Indeed, during glacial cycles of the Pleistocene, particularly during the Middle Pleistocene and the last glacial period, the Aegean Sea experienced massive sea-level regression that probably caused half of its area to become land [C. aestuarii owing to the limited areas of the Aegean and Marmara seas.The three applied neutrality tests , the teome land , 107. MoCerastoderma glaucum in the Eastern Mediterranean, highlighting a major phylogeographic break in mitochondrial Cox1 gene sequences between a group of Ponto-Caspian-Aegean Sea haplotypes and those to the west of the Peloponnese peninsula in the Mediterranean. This remarkable pattern of genetic break, within the Eastern Mediterranean, has also been recorded in crustaceans. Notably, Shemesh et al. [Chthamalus montagui between the western-central Mediterranean Sea and Aegean-Black seas. Gene flow restriction between western and eastern Mediterranean populations was shown to be mainly linked to the hydrographic isolation of the Aegean Sea, and found to be more marked than that associated with the Siculo-Tunisian Strait [Alternatively, the recorded pattern of parapatric genetic divergence among the two adjacent groups, with the potential existence of contact zone among both groups in the Ionian Sea, suggest the impact of particular past and present oceanographic patterns (such as marine currents and gyres) across the Eastern Mediterranean. Accordingly, we assume that the recorded pattern of population structure could be mainly caused by the potential effects of the hydrographic isolation of the Adriatic-Ionian and Aegean seas , 5 on lah et al.  and lateh et al.  revealedn Strait .C. aestuarii across the Eastern Mediterranean could also be triggered by historical isolation events resulting in strong bottlenecks. Such isolation events could include Pleistocene hydrographical shifts that allowed repeated isolation and separation of the Aegean Sea from the remaining Eastern Mediterranean [Genetic divergence within erranean . The conerranean –111, whierranean , 45, 112C. aestuarii, selection on mtDNA haplotypes is another important factor that should be taken into consideration. For instance, the significant genetic patterns, linked to geography within the examined Mediterranean coasts, may strongly suggest that gene flow is not only limited by fluctuating events and neutral processes (as suggested by the observed significant pattern of isolation by distance), but also by environmental factors, i.e., hydrological factors  or differential selection (affecting fitness). Reduced dispersal among populations can lead to genetic subdivision of populations and may facilitate local adaptation [C. aestuarii in the Eastern Mediterranean. A significant correlation between sea surface temperature and mitochondrial haplotypes has been already recorded in marine species, i.e., the walleye pollock Theragra chalcogramma in the North Pacific [C. aestuarii, this hypothesis remains questionable and would need to be verified.In addition to the previously discussed impact of palaeoecological history as well as past and present oceanographic processes on shaping the genetic variability and population structure of the green crab aptation . The impaptation , 115. Thaptation . The seaaptation . Hence,  Pacific . NeverthC. aestuarii throughout its distribution range: During glaciations periods of the Early Pleistocene, dropping sea levels led to the restriction of biotic exchange across the Gibraltar and Siculo-Tunisian straits. The Eastern Mediterranean Basin was more affected by these environmental shifts and experienced desiccation episodes of greater or lesser importance in different parts [C. aestuarii from Pleistocene refugia in different parts of the distribution area, might have shaped the current genetic diversity and population genetic structure, such as observed by us. Indeed, in an earlier study by Deli et al. [Overall, the results of the present investigation, along with those already obtained for more western populations of the Mediterranean green crab , 35, allnt parts . Hence, i et al. , a seconC. aestuarii, the two discerned geographic groups deserve to be better investigated. In this sense, analysis of nuclear markers (such as microsatellite loci) in areas where both genetic groups occur is required to confirm this particular divergence pattern. It should be noted that the use of such additional markers may provide changes in phylogeographic patterns and consequent interpretations, as reported by Avise [Our study provides new and important insights into the evolutionary history of a highly dispersive benthic decapod crustacean in the Mediterranean Sea. Notably, results of this investigation allow unravelling a sharp phylogeographic break in the Eastern Mediterranean (matching the well-known and reported sharp genetic break between the Aegean Sea and the remaining Mediterranean) and elucidating historical and contemporary processes susceptible of driving such complex phylogeographic structure. Our finding also stress the importance of investigating peripheral areas in the species’ distribution zone to fully understand the distribution of the genetic diversity and unravel hidden genetic units and local patterns of endemism. Lastly, regardless the mechanism involved in shaping pattern of genetic structure of by Avise , yet stiAdditional file 1:Table S1. Geographic distribution of the 106 haplotypes of C. aestuarii recorded at the 22 sampling sites within the Mediterranean Sea. (DOCX 44 kb)


A unique genetic background in an isolated population like that of Finland offers special opportunities for genetic research as well as for applying the genetic developments to the health care. On the other hand, the different genetic background may require local attempts to develop diagnostics and treatment as the selection of diseases and mutations differs from that in the other populations. In this review, we describe the experiences of research and health care in this genetic isolate starting from the identification of specific monogenic diseases enriched in the Finnish population all the way to implementing the knowledge of the unique genetic background to genomic medicine at population level. Isolated populations may have a unique genetic background as, by chance, the founder population has initially had a certain assortment of gene variants which, again by chance, may have developed towards enrichment of some of the variants and disappearance of some others. As the population size is small, the possible bottleneck events like epidemics, wars, or hunger have a more profound effect on the gene pool when compared to larger populations. The isolation may be cultural as in the case of Ashkenazi Jews or geographical with Faroe Islands as an example. In case of Finland, both geographical isolation due to the very Nordic position of the country and cultural isolation due to religious and language boundaries have caused enrichment of some disease-causing gene variants and losses of others , Norio et al.  realizedWhen this was understood, the concept of the Finnish disease heritage started to form. The criterion for a disease to be included in the list was that it should be more prevalent in Finland than elsewhere. However, there never was a strict rule defining how much more prevalent the disease had to be. This kind of rule would have actually been impossible as the epidemiology of rare diseases was and still is poorly known in most countries, including Finland, due to among other things, underdiagnosis. So some diseases maybe were included in the list with too loose criteria and some others were excluded with no good reason. In addition, two of the diseases are inherited in X-linked manner and two are autosomal dominant; for those diseases, the population history does not give similar logical explanation.The diseases on the present official list can be grouped according to the main manifestations. Of them, 11 are progressive central nervous system diseases beginning usually in childhood, 5 are prenatally or neonatally fatal malformation syndromes, 5 are ophthalmological disorder, and 4 manifest with growth deficiency. Many feature multiple symptoms, for instance, Rapadilino patients are small, have several malformations and dysmorphic features and they also have increased risk for some types of malignancies  is an extreme example of the counter part of the Finnish disease heritage: the diseases that have an exceptionally low prevalence in Finland. When PKU had been characterized, a search was organized among all institutions for mentally retarded in Finland at a time when it was a common practice to care for mentally retarded patients in institutions Palo . About aIn the case of most diseases of the Finnish disease heritage, there were no clues about the pathogenesis which would have helped in trying to identify the genetic defect behind the diseases. Aspartylglukosaminuria (AGU) was an exception as it was known from previous studies that the gene for the enzyme aspartylglucosaminidase (AGA) which is deficient in AGU is located in the long arm of chromosome 4   and positioned on the latest genomic build  in most of the Finnish monogenic diseases. This obviously facilitated genetic diagnostic already at the time, when sequencing whole genes was beyond normal clinical diagnostics. Details of the mutational background of the diseases can be found at There have been enthusiastic efforts for elucidating the pathogenetic mechanisms of the diseases of the Finnish disease heritage but, understandably, the main part of the work has happened in Finland. A lot is known about the pathogenesis of already most of these diseases and the research is ongoing. However, the pharmacological industry has not been as eager in searching for treatments and starting clinical trials as in the case of “more common rare diseases.” At present, there are several ways to treat the symptoms of these diseases, including special diets , organ transplantation  or orthopaedic treatments (diastrophic dysplasia # 222600). Treatment based on specific orphan drugs is still lacking in all of them. In case of especially the progressive encephalopathies, such treatment if started early enough might dramatically change the future of the patients.On the other hand, pharmaceutical companies show increasing interest in the advantages the genetic profile of an isolated population such as Finland may offer for research of more common diseases. For example, studies of loss-of-function variants and complete gene knockouts, which are enriched in the population, have provided information with potential therapeutic implications for cardiovascular diseases  expensive tests. In Finland, the aim has been and still is that health care services should be available to everybody in as equal a way as possible.As new and very expensive treatments are being developed to many hereditary disorders, this might affect the possible decision to start national carrier screening. The public health care could either see the cost of treatments too high and promote carrier screening or, on the other hand, consider that possibility to treatment accentuates the difficult ethical questions related to carrier screening, making it a less acceptable option.There are few examples of populations with as favorable possibilities for carrier screening for (some) of the recessive disorders as the Finnish population. The molecular genetics of the diseases of the Finnish disease heritage are well studied and documented .Ministry of Social Affairs and Health (STM) in Finland aims to increase the role of genomics in promoting the health and well-being of Finnish population STM . FinlandUtilization of genetic risk information in predictive medicine requires preceding research to identify genetic loci and eventually genetic variants that associate with the risk of the complex diseases. Typically, study samples need to comprise of tens or even hundreds of thousands of individuals to find more common genetic variants with modest effects on multifactorial diseases. Isolated populations seem to offer substantial advantage for this research; a reduced allelic heterogeneity, and relatively high frequencies of loss-of-function variants and other deleterious mutations facilitate studies of clinically meaningful low-frequency variation .Of the 5.5 million inhabitants of Finland today, nearly 40% lives in cities. Especially, young people move to cities for higher education and/or employment. This means that the parents of today’s and future children less often originate from the same regional isolates in the rural areas. In addition, in the recent years, the immigration has greatly increased so that today one in ten of people aged 25 to 44 and living permanently in Finland are of foreign background (Statistics Finland This development means that in coming decenniums, the prevalence of the autosomal recessive diseases belonging to the Finnish disease heritage is likely to diminish even though the founder mutations will remain in the population of Finnish origin. Similarly, the variants associated with common multifactorial diseases will slowly become less homogeneous. However, a considerable part of the population still represents genetically typical Finns and even continues living in the regional isolates. So the health care has to flexibly respect and implement the experience of the Finnish genetic research but be prepared to also take into account the different needs of the genetically distinct parts of the population Valle . For genRecognition of Finnish population as a genetic isolate increased interest to genetic studies and was also reflected in national research funding some 20 years ago in Finland. Understanding and utilizing the unique genetic profile of Finns has since led researchers to identify specific diseases of the Finnish disease heritage, to find associations between genetic variants and common diseases in the Finnish population, and finally to provide valuable data on sequence variants in Finns for both researchers and clinicians . When reIncluding genetic diversity in studies searching for associations between genome and diseases may facilitate but also impede research unless the allelic heterogeneity is considered in the analysis. The genetic profile of a disease may differ between populations which could weaken the power to detect associations and lead to failed attempts in replicating the results in other study samples. On the other hand, as the disease-associated genes and variation in them may be different in different populations, utilizing the diverse genetic profiles valuably contributes to the overall quest of piecing together information on the complex biological pathways leading to diseases.The new possibilities of genomic medicine, where genetic information from research and clinical sequencing directly promotes the health of individuals, require detailed knowledge of the genetic profile of the population in question. To reduce inequality in genetic screening and treatment opportunities between populations and ethnicities, back ground data of genetic diversity and its meaning needs to be collected and utilized.


Bambusa mizorameana to other five Dendrocalamus species by clustering into a single group, while Dendrocalamus manipureanus segregated from the cluster indicating its genetic divergent character. Except for Schizotachyum fuchsianum, the three Schizotachyum species viz., S. dullooa, S. pergracile and S. munroi exhibited close genetic affinity by grouping into a single minor clade. Principal coordinates analysis (PCoA) showed distribution of different bamboos species in the plot in accordance to unweighted pair-group method with arithmetic average (UPGMA) cluster analysis. Genetic relationship of 15 different bamboos as revealed from the dendrogram and PCoA analysis reasonably conformed to traditional system of classification though slight disagreement existed. This is the first report on the successful use of ISSR markers in the phylogenetic and genetic variation studies of 15 important bamboos of the region including the endemic bamboo species of B. mizorameana, B. manipureana, D. sikkimensis and D. manipureanus.The classification of bamboos based on floral morphology and reproductive characters is very hard due to erratic flowering behavior and unusually long reproductive cycle. The application of reliable and effective DNA molecular markers is highly essential to address this problem. In the present investigation, inter-simple sequence repeats (ISSR) markers were employed to study phylogenetic relationship of 15 different bamboos of North-East India. The 10 ISSR primers generated 116 polymorphic loci or scorable bands with average of 11.6 bands per primer. The genetic similarity coefficient ranged from 0.41-0.76 showing high genetic polymorphism among different bamboo species. The phylogenetic tree constructed based on genetic similarity matrix revealed genetic proximity of endemic  Bamboos are one of the most important forest trees having more than 1000 different uses . BecausePhyllostachys bamboos and other four genera within the sub tribe Bambusinae [The traditional method of classification has many shortcomings which can be replaced by new molecular approaches . Many ecmbusinae  and 18. mbusinae  and 20. mbusinae . The dismbusinae . Though mbusinae -25, theiBambusa tulda, B. nutan, B. mizorameana, B. vulgaris, B. manipureana, Schizotachyum dullooa, S. pergracile, S. munroi, S. fuchsianum, Dendrocalamus giganteus, D. hamiltonii, D. sikkimensis, D. hookeri, D. longispathus and D. manipureanus) have been selected for the present study. Presently the grouping of these bamboos is mostly performed using the traditional classification system. The more sophisticated molecular marker approach has not been effectively utilized to establish genetic and phylogenetic relationship of the local bamboos. The present investigation was carried out with an aim to determine the genetic diversity and relationship between the 15 different bamboos of North-East India using ISSR markers. The North-East India harbors rich bamboo resources as it contributes more than 60% of bamboos in India. 15 important bamboos of the region  method with some modifications [oC for 15-20 minutes in hot water bath before being subjected to centrifugation at 12000rpm for 5 minutes. The supernatant was collected and treated with chloroform: isoamylalcohol (24:1) followed by another centrifugation at 13000 rpm for 1-2 minutes. The pellet obtained after 7.5M ammonium acetate treatment was washed several times with 70% ice cold ethanol and dried before being resuspended in sterile DNase free double distilled water. The DNA solution was incubated at 65oC for 20 minutes to destroy any DNase which may be present in it. The extracted DNA solution was finally stored at 4oC for subsequent analysis. DNA quality and quantity were determined through spectrophotometry at 260 and 280 nm respectively. The purity and integrity of DNA was tested by performing 1.0% agarose gel electrophoresis and comparing the intensity of the resultant bands with 1kb DNA ladder . The DNA samples obtained after extraction process were finally diluted to 50ng/µl and stored at-20oC for ISSR marker analysis.ications . The leaISSR amplification: Out of the 21 ISSR primers initially screened, 10 ISSR primers  were selected based on production of clear, reproducible and scorable bands. The amplification was carried out in a total volume of 25µl containing 20ng of genomic DNA, 2.5µl of 10X PCR buffer containing 15mM MgCl2, 0.2mM dNTPs, 1 unit Taq polymerase  and 20ng of ISSR primers . The ISSR amplification cycles consisted of an initial DNA denaturation at 94oC for 4 mins followed by 45 cycles of denaturation at 94oC for 1 min, annealing at 40oC for 1min and 2mins extension at 72oC with a final extension at 72oC for 10 mins. Thermal cycler  was used for DNA amplification and amplified fragments generated were separated on 1.5% (w/v) agarose gel using 1 X TBE buffer. The gel with the separated fragments was stained with ethidium bromide (0.5µg/ml) and finally visualized and photographed under Gel Documentation system . A 1kb DNA ladder  was used to determine the size of unknown DNA fragments on the agarose gel. The amplification reactions of ISSR primers were performed twice to ensure the reproducibility of the banding pattern.Data analysis: Distinct and well resolved bands were scored as present (1) or absent (0) for each ISSR reaction. The data obtained were utilized to compile binary data matrix and the intensity of band was not considered while scoring. The genetic similarity matrix between 15 different bamboo species was calculated according to Nei and Li [i and Li . These si and Li  using uni and Li . The 10 ISSR primers selected from the 21 initially screened ISSR primers produced a total of 116 scorable bands or loci with average of 11.6 bands per primer . The sizDendrocalamus hamiltonii and D. sikkimensis (0.76), D. hookeri and D. longispathus (0.75), Bambusa nutans and B. manipureana (0.72) and Schizotachyum pergracile and S. munroi (0.63), while low genetic affinity was observed between Schizotachyum pergracile and Dendrocalamus longispathus (0.41), S. dullooa and D. manipureanus (0.44), D. hamiltonii and S. pergracile (0.46) and D. hookeri and S. pergracile (0.46). The genetic similarity index between 15 different bamboo species derived from Nei and Li’s coefficient  ranged fSchizotachyum , while the remaining 12 bamboos were grouped into other major cluster. Interestingly S. fuchsianum was placed separately from the first cluster which indicated its less genetic affinity with other three Schizotachyum bamboos. S. fuchsianum exhibited lower genetic similarity with S. dullooa (0.57), S. pergracile (0.55) and S. munroi (0.53) as compared to similarity coefficient recorded between S. dullooa and S. pergracile (0.62), S. munroi and S. pergracile (0.63) and S. dullooa and S. munroi (0.61). The dendrogram generated based on similarity matrix obtained from differential banding profile of ISSR primers revealed two major clusters . The firDendrocalamus bamboos included in the study, 5 were grouped in the same subcluster divulging closer genetic identity between them. This finding affirmed their placing under the same genus Dendrocalamus as per the traditional system of classification (The 12 bamboos placed under one major cluster were further grouped into different subclusters. Out of the 6 fication .D. manipureanus was genetically more divergent from other Dendrocalamus species as it was placed separately by segregating from the group. The total segregation of D. manipureanus from other members of Dendrocalamus indicated the more likely polyphyletic origin of the genus Dendrocalamus. Ghosh et al. [D. manipureanus and their segregation from D. latiflorus. The general morphological features of D. hookeri and D. longispathus are closely similar so it is difficult to differentiate their natural stands [Dendrocalamus bamboos into a single minor clade supporting their close phenotypic and genetic relationship. Similar explanation can be made for D. giganteus and D. sikkimensis which exhibited identical morphological features and were placed in same group. D. giganteus was also placed in same subcluster with D. hamiltonii. Basumatary et al. [D. giganteus and D. hamiltonii in the same cluster. Many similar phenotypic characters are shared between D. giganteus and D. longispathus with their erect culms which are about 14-25m tall and 10-12cm in width with prominent nodes and internodes [Dendrocalamus bamboos showed considerable genetic divergence with similarity index of 0.58 recorded between them and occurring in different minor clades in the dendrogram. Ramanayake [D. longispathus and D. giganteus when RAPD analysis was performed to estimate their phylogeny. The lone h et al.  using AFl stands . The deny et al.  while stternodes . But theBambusa species viz., B. vulgaris, B. nutans and B. manipureana were grouped in same subcluster depicting genetic proximity between them. Sun et al. [Bambusa nutans and B. vulgaris while studying phylogenetic relationship using RAPD markers. B. tulda was however segregated from the group indicating lesser genetic affinity with other 3 members of Bambusa. This result was in contrast to previous report of close genetic affinity between B. tulda and B. vulgaris by Loh et al. [B. tulda and B vulgaris when they recorded Jaccards’s similarity coefficient of only 0.224 using ISSR markers. Genetic similarity matrix analysis revealed B.mizorameana to be more genetically closed to D. hookeri and D. longispathus than to other Bambusa species. This is reflected in phylogenetic tree with B. mizorameana clustering in same group with D. hookeri and D. longispathus rather than with other Bambusa species. The 3 n et al.  also reph et al.  when theh et al.  also revB. mizorameana under Bambusa and suggested the appropriateness of B.mizorameana to be included within the genus of Dendrocalamus. There is still a requirement of in-depth assessment for the accurate classification of two endemic bamboos of B. mizorameana andD. manipureanus. This is because the normal traditional classification system of bamboos is largely based on morphological and vegetative characters which need to be further validated with the application of other sophisticated and more informative DNA markers [The present phylogenetic study showed reservation in the positioning of  markers .Dendrocalamus species from the rest represented by Schizotachyum and Bambusa species. The two dimensional PCoA plot showed the first principal coordinate accounting for 19.19% while the second coordinate produced 14.39% of the total genetic variation. PCoA analysis revealed each bamboo species forming a separate plot and all the species were distributed in agreement with the UPGMA cluster analysis . The 15 B. mizorameana, B. manipureana, D. sikkimensis and D. manipureanus.The phylogenetic relationship established between 15 bamboo species of North-East India using ISSR markers was quite reasonably conformed to traditional system of classification though some slight discord existed. This minor disagreement with classical approach was also previously observed in genetic relationship study of other bamboo species , 15, 37.


Trypanosoma congolense “forest type”, with the ultimate goal of understanding its transmission dynamics between tsetse flies and domestic animals. Blood samples were collected from pigs, sheep, goats and dogs in five villages in Fontem, South-West region of Cameroon. In these villages, tsetse were captured, dissected and their mid-guts collected. DNA was extracted from blood and tsetse mid-guts and specific primers were used to identify T. congolense “forest type”. All positive samples were genetically characterized with seven microsatellite markers. Genetic analyses were performed on samples showing single infections of T. congolense “forest type”. Of the 299 blood samples, 137 (46%) were infected by T. congolense “forest type”. About 3% (54/1596) of tsetse fly mid-guts were infected by T. congolense “forest type”. Of 182 samples with T. congolense “forest type”, 52 were excluded from the genetic analysis. The genetic analysis on the 130 remaining samples revealed polymorphism within and between subpopulations of the target trypanosome. The dendrogram of genetic similarities was subdivided into two clusters and three sub-clusters, indicating one major and several minor genotypes of T. congolense “forest type” in tsetse and domestic animals. The low STFvalues suggest low genetic differentiation and no sub-structuration within subpopulations. The same T. congolense genotypes appear to circulate in tsetse and domestic animals.Despite the economic impact of trypanosome infections, few investigations have been undertaken on the population genetics and transmission dynamics of animal trypanosomes. In this study, microsatellite markers were used to investigate the population genetics of  AATs cause high mortality, abortion, significant reductions in milk and meat production, and delay in sexual maturity, along with low calving rates and loss of draught power. These diseases are associated with considerable losses in livestock production [African trypanosomiases are parasitic infections caused by pathogenic protozoa of the Trypanosomatidae family. Trypanosomes are cyclically transmitted to animals by tsetse flies. In 37 sub-Saharan African countries, African animal trypanosomiases (AATs) represent an important factor that limits cattle breeding in an area of about 9 million kmoduction . The totoduction .Trypanosoma congolense, Trypanosoma vivax and Trypanosoma brucei brucei [T. congolense, trypanosomes of the subgenus Nannomonas contain also T. simiae which is found in a wide range of ungulate hosts. The use of biochemical and molecular methods subdivided trypanosomes of the subgenus Nannomonas into two clades [T. congolense clade, contains T. congolense associated with savannah and forest and another distinct group or T. congolense kilifi, which was found around the Kenyan coast [T. simiae clade, contains T. simiae, T. godfreyi-like, T. simiae tsavo and T. godfreyi [The main pathogenic trypanosomes of livestock are i brucei . In addio clades . The firan coast ,16,21. Tan coast . The secgodfreyi .T. congolense has been shown to be the most prevalent trypanosome species infecting cattle [T. congolense infections requires investigations aiming to better understand the population genetics of trypanosomes. Such investigations could help to comprehend the spread of genotypes responsible for specific pathophysiological traits such as drug resistance or different clinical manifestations. Previous studies have shown that isolates of T. congolense exhibit different clinical phenotypes in the infected hosts [T. congolense induce acute disease and high mortality, while the less virulent strains cause benign and chronic infections [In sub-Saharan Africa, g cattle ,28,41,42ed hosts . For insfections . AlthougT. brucei and different epidemiological pictures of HAT in west and central Africa [T. brucei in tsetse flies and different animal species. They also revealed common genotypes circulating in both tsetse flies and different animal species [T. congolense revealed predominant clonal reproduction within T. congolense “forest type” [T. congolense “savannah type” [T. congolense in tsetse flies and different animal species [T. congolense circulating in tsetse flies and domestic animals of Fontem in southern Cameroon [T. congolense isolates circulating both in tsetse flies and different animal species of the same tsetse-infested area. Such investigations could help to understand the transmission dynamics as well as the circulation of trypanosome genotypes between hosts  or villages. In this context, reviewing and reanalyzing published data of the same tsetse-infested area could enable us to understand the transmission dynamics and the circulation of trypanosome genotypes, and also to improve our knowledge on the genetics of trypanosomes.During the last few decades, several genetic markers including Amplified Fragment Length Polymorphism (AFLP) ,35, Randl Africa ,33,36,37 species , highligst type” ,40, and ah type” . Microsa species ,38,40. HT. congolense “forest type” were retrieved from data of two studies published by Simo et al. [T. congolense genotypes between hosts  or different villages of Fontem.In this study, single infections of o et al. ,40. The For this study, verbal authorizations were obtained from inhabitants, and from traditional and administrative authorities in each village before beginning the study. Thereafter, verbal consent was obtained from each owner before sample collection.Glossina palpalis palpalis has been reported as the main vector of trypanosomes in this locality [This study was carried out in the Fontem  region located in the Lebialem, Manyu and Koupe-Manengouba Divisions of Cameroon. This is a forested region with a tropical humid climate. The topography is made up of hills and valleys through which several high-speed rivers flow ,31,34. Dlocality .et al. [Domestic animals were sampled in five villages  of Fontem in July 2006 and June 2007. Before sampling, the objective of the study was explained to local authorities and inhabitants of each village. After their approval, inhabitants were asked to catch and/or keep their domestic animals. All domestic animals that had spent at least 3 months in the study zone were selected. All details concerning the animals sampled and the blood collection procedures were described by Simo et al. ,40.et al. [Tsetse flies were sampled during two entomological surveys conducted in November 2006 and April 2007. These entomological surveys were performed in the same five villages  where domestic animals were sampled. During each survey, pyramidal traps  were setet al. .et al. [DNA was extracted from blood samples using the “DNeasy Tissue kit” (Qiagen) as described by Simo et al. . InitialFor the tsetse fly mid-guts, the Chelex method was used to extract DNA . BrieflyT. congolense “forest type” were used [et al. [T. congolense “forest type” were selected and subjected to subsequent analyses.For this identification, specific primers (TCF1/2) for ere used . The amp [et al. . All samT. congolense originating from tsetse flies and domestic animals were genetically characterized at seven microsatellite loci, as previously described by Morrison et al. [et al. [T. congolense is a diploid organism and must have one allele (homozygote) or two alleles (heterozygote) after the resolution of the amplified products of each microsatellite locus.The samples positive for n et al. . For eac [et al. ,40. The T. congolense “forest type” was assessed through Wright's F-statistics [STF values were evaluated. STFis a measure of deviation from random distribution of individuals between subpopulations . STF measures the genetic differentiation between subpopulations. Here, we considered as a subpopulation all samples of T. congolense “forest type” originating from the same host  or the same village . STFis a convenient measure of differentiation among the different subpopulations of a data set. The STFestimator is around 0 under the null hypothesis of random distribution of genotypes across subpopulations. The estimator displays positive values, up to 1, in case of genetic differences. Wright's F-statistics were estimated using Weir and Cockerham's unbiased estimators [STF, the estimator was Ө and its significance was tested through 10,000 permutations of individuals between subpopulations.For these analyses, samples with multiple genotypes or showing more than two alleles were excluded. Therefore, only single genotypes or samples showing no more than two alleles were taken into account for the analysis of population genetic structure. Due to the low amplification rate of the TCM3 and TCM5 markers, the data generated for these two microsatellite markers were not considered for genetic analyses. In addition, data for TCM4 were also not considered because no polymorphism was observed. Therefore, only data generated by four microsatellite markers were used for population genetics studies. The genetic structure within and between subpopulations of atistics . For thitimators  in Fstattimators . For FSTFstat 2.9.4 software. The test was performed through 10,000 permutations within subsamples.To get an overall idea of individual distribution across the hosts, unrooted NJTREEs were computed with MEGA 3.1 software  using thGlossina palpalis palpalis were sampled in five villages  of Fontem. The 299 domestic animals included 173 pigs, 60 sheep, 48 goats and 18 dogs  infected by this trypanosome   . The 54 T. congolense “forest type”-positive samples. Results of these two markers were not considered during genetic analyses. The remaining five markers  generated good results with amplification rates above 80%. However, TCM4 generated no polymorphism  for all samples and consequently was not also considered during subsequent analyses. Excluding results for three microsatellite markers  enabled us to perform the genetic analyses on data generated at four microsatellite loci.For this characterization, seven microsatellite markers were used. No samples were amplified by TCM3, while TCM5 amplified less than 20% of T. congolense “forest type”-positive samples , 36 different alleles were identified: 30 and 6 in single and mixed genotypes, respectively. Specific alleles such as 136 bp for TCM2, 138 bp and 173 bp for TCM1, and 208 bp, 218 bp, 233 bp for TCM7 were observed only in mixed genotypes  with single genotypes of T. congolense “forest type” were finally considered for population genetics studies. Thirteen T. congolense “forest type” circulating both in tsetse flies and all domestic animals  were observed. These alleles can be considered as minor alleles belonging to minor genotypes of T. congolense “forest type”. They include 189 bp and 217 bp of TCM2, 190 bp, 194 bp and 198 bp of TCM1, 195 bp and 200 bp of TCM6, and 169 bp and 180 bp of TCM7. Considering single genotypes only, it was found that 15 alleles were observed in T. congolense “forest type” identified in flies, against 27 in animals. The number of alleles circulating in animals is 1.8 times higher (27/15) than the value obtained for parasites found in tsetse flies.High allelic frequencies above 40% were observed for some alleles of  animals . ConsideT. congolense “forest type” circulating in animals and 1.478 for parasite identified in tsetse flies. No significant difference (p = 0.936) was observed between these values. The genetic diversity index evaluates the degree of varieties of genes in a given population. Its value was 0.569 for T. congolense “forest type” circulating in animals and 0.540 for parasites identified in tsetse flies. No significant difference (p = 0.148) was observed between these values. With the overall value of 0.554, some variation in the genetic diversity indexes was observed across loci  are mainly found in sub-cluster 1. Sub-cluster 2 contains samples from pigs (59.52%) and tsetse flies (26.19%). Samples from sheep are predominantly found in sub-clusters 2 and 3. The genotypes circulating in pigs are found in various clusters and sub-clusters , the STF values were generally very low and not significant between hosts . They therefore reflect the low genetic distances between strains of T. congolense “forest type” circulating in tsetse and domestic animals of Fontem.The villages . Despiteen hosts . These rT. congolense “forest type” has shown some genetic polymorphism between T. congolense “forest type” circulating in tsetse flies and domestic animals of different villages of Fontem. Samples showing more than two alleles or samples with mixed genotypes of T. congolense “forest type” were excluded from population genetics studies because the genetic information for each individual trypanosome could not be obtained. Some alleles involved in these infections (probably minor genotypes) were not taken into account and consequently, the real genetic variability of T. congolense “forest type” was underestimated in the studied areas. Non-consideration of wild animals, known as hosts for trypanosomes and as a source of blood meals for tsetse flies [T. congolense “forest type”. Irrespective of the microsatellite marker used, the majority of alleles identified in tsetse flies and domestic animals were selected for population genetics studies. The resulting genotypes are probably the major ones circulating in the studies areas. The identification of T. congolense “forest type” in tsetse flies and domestic animals confirms previous results [This study on the genetic structure of se flies , is anot results ,29,34.T. congolense strains. Another reason explaining this discrepancy is the bottleneck observed during the establishment and migration of trypanosomes in tsetse fly. This bottleneck enables few parasites to complete their developmental cycle in tsetse flies while the tsetse immune response kills most trypanosomes during the first days after a blood meal.For population genetics studies performed with data generated at four microsatellites loci, 27 alleles were identified in domestic animals and only 15 in tsetse flies. These results indicate a high level of genetic variability within strains circulating in animals, compared to those found in tsetse flies. They are in line with previous observations reporting that the full level of trypanosome diversity is only apparent when the parasites circulating in tsetse flies are examined ,40. The T. congolense “forest type” was not affected by the difference observed in the number of alleles identified between trypanosomes circulating in tsetse flies and domestic animals.The absence of significant differences between values for allelic richness as well as the genetic diversity index suggests that the genetic variability between strains of T. brucei s.l.  in the same villages [T. congolense circulate both in tsetse and domestic animals. This is strengthened by the clustering of several genotypes from animals with those from tsetse flies  identified in different hosts  with those observed for villages , it appese flies . The ide village .T. congolense “forest type” can be subdivided into two main clusters, separate analyses of each of these populations did not reveal such results [T. congolense “forest type” that circulate in tsetse flies and mammalian hosts. Analysis of such a mixture enabled a better understanding of the genetic diversity of trypanosomes as well as the genetic structure of these parasites. The genotypes belonging to the same cluster or sub-cluster of the dendrogram can be considered as closely related strains or closely related genotypes. The identification of several genotypes within the same cluster highlights some genetic polymorphisms between strains of T. congolense “forest type” as reported previously by Simo et al. [T. congolense strains were from various hosts. This high genetic polymorphism can be explained by several minor genotypes circulating in tsetse flies and different domestic animals. The very low allelic frequency is in favor of minor T. congolense genotypes circulating in different villages  of  results ,40. The o et al. ,40. No cvillages . Resultsive size . In tsetive size . Such stive size . Some miSTF between villages with no statistical significance indicate an absence of sub-structuration by village. They suggest identical genotypes or closely related genotypes circulating in tsetse fly and different animals or between the villages of Fontem. This is highlighted by samples of various villages clustering together in different clusters and sub-clusters of the dendrogram , but statistically significant, suggesting some genetic differences between strains circulating in tsetse flies and sheep, as previously reported for T. brucei [STF values between hosts  were very low and not significant, indicating an absence of sub-structuration by host. In previous studies, MacLeod etal. [T. brucei circulating in the same hosts and the same villages, Simo et al. [T. brucei, our data on T. congolense “forest type” suggest that each host cannot be considered as a separate entity during population genetics studies. Our results suggest that for the genetic characterization of T. congolense “forest type”, sampling in one village or in one animal species could provide information on the population genetic structure of parasites circulating in the studied areas. Results obtained in pigs strengthen this hypothesis because trypanosome genotypes originating from pigs were widely distributed in the dendrogram. The genetic characterization of strains circulating in pigs could therefore provide information on the genetic variability of T. congolense “forest type” circulating in tsetse flies and animals of this region. This is in line with what has been reported for T. brucei [STF confirm the wide distribution of strains as observed in the dendrogram. They suggest that the same genotypes or closely related genotypes circulate between villages or different hosts, without any genotype genuinely committed to a village or a particular host. This wide distribution of similar genotypes indicates the transmission of identical strains in these tsetse-infested areas. To interrupt disease transmission in such areas, similar control strategies could be implemented with the use of identical control tools like drugs and vector-control tools. With these generalized control strategies, there is a high risk for the development and spread of resistant strains in different villages. In this type of context, control operations must be followed up by continuous characterization of trypanosome isolates in order to detect emerging resistant and more pathogenic strains early that could jeopardize control efforts.Between subpopulations of . brucei . Despited etal.  reportedo et al.  reported. brucei . ResultsT. congolense “forest type” between villages or different hosts. These results suggest no association between a genotype or closely related genotypes of T. congolense “forest type” to a specific host or village. They suggest that the same genotypes or genotype families circulate in tsetse flies and various domestic animals. They indicate an absence of sub-structuration between subpopulations of T. congolense “forest type” according to hosts or villages. The data generated here made it possible to understand the transmission dynamics as well as the spread of different genotypes of T. congolense “forest type”.The results of this study enable us to improve our knowledge on the transmission dynamics of


Poicephalus robustus) are negatively affected by the removal of eggs and chicks for the pet trade.Illegal trade in rare wildlife species is a major threat to many parrot species around the world. Wildlife forensics plays an important role in the preservation of endangered or threatened wildlife species. Identification of illegally harvested or traded animals through DNA techniques is one of the many methods used during forensic investigations. Natural populations of the South African endemic Cape Parrot (P. robustus) are assessed for their utility in forensic casework. Using these 16 loci, the genetic diversity of a subset of the captive Cape Parrot population was also assessed and compared to three wild Cape Parrot populations.In this study, 16 microsatellite markers specifically designed for the South African endemic Cape Parrot (It was determined that the full 16 locus panel has sufficient discriminatory power to be used in parentage analyses and can be used to determine if a bird has been bred in captivity and so can be legally traded or if it has been illegally removed from the wild. In cases where birds have been removed from the wild, this study suggests that a reduced 12 locus microsatellite panel has sufficient power to assign confiscated birds to geographic population of origin.The level of genetic diversity observed within the captive Cape Parrot population was similar to that observed in the wild populations, which suggests that the captive population is not suffering from decreased levels of genetic diversity. The captive Cape Parrots did however have double the number of private alleles compared to that observed in the most genetically diverse wild population. This is probably due to the presence of rare alleles present in the founder population, which has not been lost due to genetic drift, as many of the individuals tested in this study are F1–F3 wild descendants. The results from this study provide a suit of markers that can be used to aid conservation and law enforcement authorities to better control legal and illegal trade of this South African endemic. The illegal wildlife trade includes the buying and selling of any wildlife product that has been captured alive, poached, and used as food, medicine, pets, and trophies . The illCaptive breeding of exotic birds is a plausible alternative to sourcing wild animals, and it has been shown to be a viable practice . BreedinMolecular forensic methods are widely used to identify suspected illegally obtained wildlife or wildlife products . One of Several factors need to be considered when selecting a microsatellite panel for forensic studies. The quality of the data obtained from a set of markers should be assessed by considering the occurrence of genotyping errors such as null alleles and missing data, which can lead to biased estimations of genetic diversity and false parentage assignments . AdditioPID; PE; PID and PE estimates are well-established methods for assessing the ability of molecular markers to distinguish between individuals  estimate , the proividuals .Poicephalus robustus) is a locally endangered parrot species found in the South African mistbelt forests  or CITES as endangered or threatened. Recent genetic work has, however, shown that the Cape Parrot should be elevated to species status .The South African endemic Cape Parrot . All sampling procedures followed the criteria laid out by this committee.Samples were collected from 76 captive Cape Parrots . This inn = 14). Biopsies of 5 mm × 5 mm were collected from each carcass and stored in absolute ethanol at −20 °C.Whole blood was collected from 45 captive Cape Parrots using Whatman™ FTA™ Elute cards  and was stored at room temperature in a dark cool storage area. Seventeen samples were whole blood stored in absolute ethanol at −20 °C. Samples were also collected from deceased birds provided by two breeding facilities  was performed following the manufacturer’s protocols. The DNA extraction from the tissue and whole blood stored in absolute ethanol was performed with the NucleoSpin® Tissue kit , following the manufacturer’s protocols. All DNA extracts were stored at −20 °C. DNA quantity was established via NanoDrop® ND-1000 Spectrophotometer  analysis.To assess any genetic differences between captive-bred and wild Cape Parrots, 85 genotypes from wild Cape Parrot populations were taken from Prob06, Prob15, and Prob26; multiplex 2: Prob30 and Prob36; multiplex 3: Prob18, Prob25, and Prob31; multiplex 4: Prob01, Prob09, and Prob17; multiplex 5: Prob23 and Prob28; multiplex 6: Prob29, Prob34, and Prob35). In-silico testing of all multiplexes was done prior to PCR amplification to test for the presence of primer dimers and hairpin structures using the program AutoDimer v1  was used for all genotype scoring. We reamplified 20% of the data set to check for genotype consistency.PID and probability of exclusion  were estimated in GenAlEx  were estimated using Genepop v4.2 (The expectation maximization (EM) algorithm for detection of null allele frequencies was used as implemented in the software program FreeNA . To asse GenAlEx  to evalupop v4.2 .PID and PE2 estimates , number of private alleles (PA), observed heterozygosity (HO) and unbiased expected heterozygosity (uHE) estimated in GenAlEx, inbreeding coefficient (FIS) using Genepop v4.2  were estimated to assess if the captive population constitutes a separate genetic unit using GenAlEx. Bonferroni correction was implemented to all p-values to correct for problems with multiple testing . The data set contained less than 1 missing data, with a mean null allele frequency over all loci and samples of 0.039. The per locus null allele frequencies ranged from 0 to 0.186 . The mean number of alleles per locus varied greatly among loci, ranging from 1.75 (Prob36) to 17 (Prob17) alleles. A large difference in Ar values was observed across the loci, with values ranging from 2 (Prob36) to 22 (Prob17). Seven loci showed high levels of heterozygosity . Fourteen of the 16 loci were moderately to highly informative, with values ranging from 0.415 (Prob29) to 0.888 (Prob17). Only two loci (Prob35 and Prob36) were identified as uninformative  to 0.591 (Prob36). A combined PID over all 16 loci was calculated as 1.831E−13 following the product rule. The PE2 ranged from 0.658 (Prob17) to 0.032 (Prob36), with the combined PE2 at 0.995. It was observed that the PID and PE2 values improved as the number of loci analyzed increase , following Bonferroni correction (p < 0.003). Of the 120 per locus comparisons made during the linkage disequilibrium (LD) analysis, more than half of the locus pairs showed signs of LD (52.5%).For this study, 76 captive Cape Parrots were successfully genotyped across 16 microsatellite loci. Loci were amplified across a range of DNA template concentrations, with low template concentration (2–5 ng/μl) successfully amplifying with minimal signs of allelic dropout . The replicate genotypes did not show any signs of discrepancies. Co-amplification of each multiplex was also highly successful, with the most amplification failures (4 of 76) observed for the locus with the largest bp size . The nine-locus panel also showed a lower success rate at identifying the correct sires and dams, with 73.7% of sires and 96.8% of dams correctly identified with high probability (p > 0.75). All known dams were correctly identified using the seven larger panels. Although the seven larger panels had similar assignment success rates (parent pair assignment success = 83.9%), the full 16 locus panel had overall higher mean probability rates making this panel most suited for use in future parentage analyses.All eight microsatellite panels showed very low combined us panel . These vus panel . The ninFH12 and FH32) that were incorrectly assigned, were sampled from the Eastern Cape but assigned to the captive (FH12) and KZN (FH32) populations. The assignment probabilities of these individuals did, however, differ only slightly between the actual population of origin and the assigned population . The highest assignment success was achieved with the six larger microsatellite panels (16 loci to 11 loci), with 83.33% of the specimens correctly assigned . The 12 pulation .p < 0.003). The average number of alleles observed for the captive data set was higher than that observed in the wild population . The Ar estimates provide a more accurate estimation, with no significant difference observed among the captive and wild per locus Ar estimates (p < 0.003). The captive data set did, however, have the highest number of private alleles (PA = 21), which was almost double that of the highest value observed among the wild populations . All private alleles occurred at low frequencies, with private allele frequencies for the captive data set ranging from 0.007 to 0.100 and frequencies for the southern wild population ranging from 0.008 to 0.133. No significant differences were observed between the captive vs wild per locus observed HO, unbiased expected uHE and FIS comparisons.The genetic diversity estimates for the captive data set, using 16 microsatellite loci, were largely similar to that observed for the wild Cape Parrot populations . SignifiHO for the captive data set was only slightly lower than that observed for the three wild populations , with an uHE comparable to that observed for the south and central wild populations . A low positive FIS value was observed for the captive data set indicating only slight inbreeding (FIS = 0.054), with low heterozygote deficiency. Low genetic differentiation was found only between the captive data set and the south population . No significant genetic differentiation was observed between the captive and north populations  or the captive and central populations , following a Bonferroni correction (p = 0.003). The global FST value calculated for the captive and three wild populations did not significantly differ from zero . AMOVA indicated that 92% of the observed genetic variance occurred within individuals, with 5% of the genetic variance between individuals and only 3% among the populations.The Prob15 was previously reported as Z-linked in Cape Parrots . The failure to assign a parent, or assignment of a parent with low probability, can be linked to the occurrence of amplification errors during PCR causing allelic dropout, null alleles, stuttering, or polymerase slippage  all had a success rate of 83.33%. The average assignment probabilities of the correct assignments did however differ, with the 12 locus panel outperforming the rest . The twod to KZN . The prod to KZN , and theGypaetus barbatus) population, with a higher level of genetic diversity in the captive population when compared to that observed in the wild population. This was linked to founder individuals, who are still present in the breeding population, carrying rare alleles and thereby passing these alleles down to their offspring (The majority of the genetic differentiation estimates showed little to no genetic difference between the captive data set and the three wild Cape Parrot populations. Similar AMOVA results were observed in a study focusing purely on the genetic variation among the wild Cape Parrot populations . A clearffspring . It is tffspring . These iThe captive and wild birds are also subjected to different environmental forces, which can lead to genetic adaptation to captivity . The difThe assessment of the 16 microsatellite loci tested in the current study identified the full 16 locus panel as the best set of markers for use in parentage analysis. Such analyses should be performed on traded birds suspected of being illegally harvested from the wild. It is therefore important to have a database of all legally owned Cape Parrots and a complete studbook for future use. Using this set of loci, birds suspected of being illegally harvested from the wild can be traced to the region of origin through implementation of the partial Bayesian approach in GeneClass2 for individual assignment analysis. The 12 locus microsatellite panel is most appropriate for this analysis. It is, however, recommended to increase the reference data sets, for both the wild and captive populations, thereby increasing the accuracy of the individual assignment analysis using the assignment methods implemented in GeneClass2. This recommendation is based on the low level of differentiation observed between the wild and captive populations. The use of additional highly polymorphic loci could improve these results . The higThe results from this study will help conservation and law enforcement authorities to better police and identify cases of illegal trafficking in South Africa’s only endemic parrot. The information obtained here also highlights the genetic distinctiveness of the captive population, and the effect these birds will have on wild populations should be considered before any future reintroductions plans are made.10.7717/peerj.2900/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.2900/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.2900/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj.2900/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj.2900/supp-5Supplemental Information 5Click here for additional data file.


Prionace glauca, Linnaeus 1758) is one of the most abundant epipelagic shark inhabiting all the oceans except the poles, including the Mediterranean Sea, but its genetic structure has not been confirmed at basin and interoceanic distances. Past tagging programs in the Atlantic Ocean failed to find evidence of migration of blue sharks between the Mediterranean and the adjacent Atlantic, despite the extreme vagility of the species. Although the high rate of by-catch in the Mediterranean basin, to date no genetic study on Mediterranean blue shark was carried out, which constitutes a significant knowledge gap, considering that this population is classified as “Critically Endangered”, unlike its open-ocean counterpart.The blue shark  amplified from 207 and 170 individuals respectively, collected from six localities across the Mediterranean and two from the North-Eastern Atlantic.Although no obvious pattern of geographical differentiation was apparent from the haplotype network, Φst analyses indicated significant genetic structure among four geographical groups. Demographic analyses suggest that these populations have experienced a constant population expansion in the last 0.4–0.1 million of years.The weak, but significant, differences in Mediterranean and adjacent North-eastern Atlantic blue sharks revealed a complex phylogeographic structure, which appears to reject the assumption of panmixia across the study area, but also supports a certain degree of population connectivity across the Strait of Gibraltar, despite the lack of evidence of migratory movements observed by tagging data. Analyses of spatial genetic structure in relation to sex-ratio and size could indicate some level of sex/stage biased migratory behaviour. Prionace glauca, Linnaeus 1758; BS henceforth) is one of the most abundant epipelagic sharks that is found in all oceans from 60°N to 50°S , extensive tag-recapture surveys carried out from 1962 to 2000, indicated that North Atlantic BS form a single stock and that trans-Atlantic migratory movements were quite frequent, likely favoured by the oceanic current system . FocusinThe primary aims of this study is to test the null hypothesis of panmixia between North Atlantic and Mediterranean BS, by comparing the mtDNA genetic variation of two gene regions, the control region (CR) and the Cytochrome b (Cytb) among four population samples collected in the North-Eastern and South-Eastern North Atlantic and in the Western and Eastern Mediterranean. Given the female philopatry observed in other carcharhiniformes , mtDNA mN = 91 males, N = 101 females and N = 22 unsexed)  and Western areas . North Atlantic BS were caught from the North Eastern Atlantic Ocean off the coasts of Portugal  and Celtic Sea  . A totalunsexed) . The BS unsexed) : juvenilhttps://fishreg.jrc.ec.europa.eu/web/medbluesgen/sampling-data.A unique and transparent sampling documentation tool was developed within the project, in order to render data public. This tool can be used by everyone as an interactive map visiting the website: ® Spin Tissue Kit, Invitek  and the Wizard® Genomic DNA Purification Kit  following the manufacturers’ protocols.Individual fin clips or skeletal muscle tissue samples were collected and preserved in 96% ethanol and kept at −20 °C until laboratory analyses. DNA extraction was carried out using the InvisorbPrionace glauca available in GenBank were retrieved and aligned using ClusterW algorithm implemented in MEGA ver.7.0  and cytochrome b (Cytb) genes were designed. Homologous complete CR and Cytb sequences of  ver.7.0 . Primer  ver.7.0 , minimizm = from 50 °C to 60 °C) according to PCR cycling conditions described by The designed primer pairs  were tested using a temperature gradient to identify the most suitable melting temperatures , 3 µL of MgCl2 , 2 µL of dNTPs , 2.5 µL  of each primer, 0.25 µL  of Taq polymerase and 2 µL of template DNA(10–20 ng). The temperature profile included an initial denaturation at 94 °C for 2 min, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 60 °C for 30 s, elongation at 72 °C for 30 s and a final elongation step at 72 °C for 5 min. PCR amplicons were sequenced using the external service provider MACROGEN® Europe.Once the optimal melting temperature was identified, the PCR thermal profile was adjusted and the PCR reactions were performed for both markers in a final volume of 50 µL containing 31.75 µL of distilled sterile HThe CR and Cytb nucleotide sequences obtained were validated with the homologous gene sequences deposited in the GenBank with the BLASTn search implemented in the NCBI website , and aliNh), the number of polymorphic sites (S), the haplotype (h) and nucleotide diversity (π) with associated standard deviation (stdev).Given the high potential of geographical dispersal of the species, sequence data were grouped according to the four geographical areas: EMED, WMED, SNEATL and NNEATL . The sofhttp://www.cibiv.at/ greg/haploviewer).Haplotype relationships were inferred using the dnaml program of the PHYLIP package version 3.6  implemenST with the associated p-values were calculated using the software Arlequin ver 3.5.2.2  analysis implemented in the software BEAST v.1.8.2 , using tN = 192; 2 test: 10.256 P2tail = 0.001; P1tail = 0, d.f. 1) while in the two Mediterranean BS groups a weak and not significant predominance of males was observed . Sized BS (N = 209) were composed by 63 juvenile, 82 young and 64 large individuals  were deposited in GenBank under the accession numbers MG515900–MG516106 and MG545732–MG545901 for Cytb and control region, respectively.A total of 207 and 170 BS individuals were sequenced for Cytb (762 bp) and CR (747 bp), respectively. Haplotype sequences , according to three areas (NEATL (NNEATL+SNEATL) vs WMED vs EMED; AMOVA3), and according to two areas (NEATL (NNEATL+SNEATL) vs MED (WMED+EMED), for both dataset. However, the grouping that best described the partitioning of genetic variance is when the different sampling locations are subdivided into four areas showing the lowest partition of molecular variance among populations within group.The AMOVA  revealedST values among the four geographical areas were significant except that between the two Atlantic groups  that became non-significant after the Bonferroni correction for multiple tests  in both markers, is dated back to 1.24 Mya and 0.94 Mya using Cytb and control region, respectively.Both BSP analyses suggested a constant population size increase of Mediterranean and North–eastern Atlantic BS, starting more recently in the Mediterranean than in the North–eastern Atlantic . Previous studies carrying out AMOVA on the Atlantic BS using the control region variation, showed a significance variance among groups formed by the North Atlantic BS collected from Portugal and Azores and by the South African  while the sub-adult and juvenile BS frequent in the Adriatic and Ionian Seas. The great abundance of juvenile BS in the Adriatic Sea seemed to confirm the nursery role of this area for BS . The bioScyliorhinus canicula, and the velvet belly lanternshark, Etmopterus spinax  a greater understanding of the genetic diversity, spatial population structure and gene flow in this species will be achieved, which will enable us to devise more effective strategies for the management of this increasingly exploited ocean predator.This work sheds new light on the understudied BS of the Mediterranean Sea, and emphasizes the need of conducting further population genetic surveys on this population. With ongoing efforts, ; Y, young (TL = 120–180 cm); L, large (TL ≥ 180 cm). NATL: North-eastern Atlantic; WMED: Western Mediterranean; EMED: Eastern Mediterranean.Click here for additional data file.10.7717/peerj.4112/supp-5Table S2South North East Atlantic, SNEATL; North North East Atlantic, NNEATL; West-Mediterranean/Balearic, BALE; South Tyrrhenian Sea, TYRR; Calabria Ionian Sea, IONI; Central Adriatic Sea, CADR; Aegean Sea & Eastern Ionian Greece.Click here for additional data file.10.7717/peerj.4112/supp-6Table S3Click here for additional data file.10.7717/peerj.4112/supp-7Table S4p = 0.0166).*Values that resulted not significant after the Bonferroni correction for multiple tests (a-level of significance after Bonferonni correction: Click here for additional data file.10.7717/peerj.4112/supp-8Supplemental Information 1Click here for additional data file.10.7717/peerj.4112/supp-9Supplemental Information 2Click here for additional data file.