To better design association studies for complex traits in isolated populations it's important to understand how history and isolation moulded the genetic features of different communities. Population isolates should not “a priori” be considered homogeneous, even if the communities are not distant and part of a small region. We studied a particular area of Sardinia called Ogliastra, characterized by the presence of several distinct villages that display different history, immigration events and population size. Cultural and geographic isolation characterized the history of these communities. We determined LD parameters in 8 villages and defined population structure through high density SNPs (about 360 K) on 360 unrelated people (45 selected samples from each village). These isolates showed differences in LD values and LD map length. Five of these villages show high LD values probably due to their reduced population size and extreme isolation. High genetic differentiation among villages was detected. Moreover population structure analysis revealed a high correlation between genetic and geographic distances. Our study indicates that history, geography and biodemography have influenced the genetic features of Ogliastra communities producing differences in LD and population structure. All these data demonstrate that we can consider each village an isolate with specific characteristics. We suggest that, in order to optimize the study design of complex traits, a thorough characterization of genetic features is useful to identify the presence of sub-populations and stratification within genetic isolates. Recent advances in array technologies have open up the possibility of economic and rapid genotyping of entire cohort of population samples. The availability of millions of single nucleotide polymorphisms (SNPs) provides a highly dense map across the human genome, which can achieve adequate power for investigating genome variants associated to multifactorial diseases Knowledge of the population structure and LD pattern is essential for study design in order to choose the appropriate approach for gene identification The identification of genetic variants underlying common human diseases are deeply affected by different population structures even if the research is very carefully designed.In whole genome association studies, population stratification influences results when allele frequencies differ among subpopulations that are not represented equally among cases and controls. Undetected population structure can mimic the signal of association and can lead to false positives or to missed real effect Population substructures have been detected in large population groups LD genome mapping is an important parameter for the design of association mapping studies Not all isolates are equal: marker informativity and extent of LD could vary substantially in different isolated populations The central-eastern area of Sardinia called Ogliastra, is characterized by the presence of several distinct villages with different history, immigration events and number of inhabitants We focused our analysis on eight Ogliastra isolated villages using a wide set of about 360000 informative SNPs to determine the extend of genetic variation in this population. Other papers compared genetic features in isolated populations but they either used a limited number of SNPs or single chromosomes or have referred only to partial regions Our aim was to understand how genetic features can be influenced by history and by geographical and cultural isolation in different communities in order to better determine the feasibility and design of genetic analysis for complex traits.Quinque Libri) are also conserved in the same archive.Historic and demographic data demonstrate that Sardinia experienced waves of successive invading populations that pushed the original inhabitants into the most remote and inaccessible areas. The central-eastern Sardinia region, identified as Ogliastra, is clearly one of these refuge areas, geographically and socially secluded for thousands of years from other Sardinia regions due to mountains and deep river valleys. Only after the Second World War, emigration and economic opportunities have changed the population structure of some of these mountain villages leaving in place mostly the older generations of people who still reflect the high level of consanguinity of past inbreeding and who still follow the traditional life styles. To conduct our research we recruited about 9000 voluntary subjects in 8 selected villages: Talana, Urzulei, Baunei, Triei, Seui, Seulo, Ussassai and Loceri . All areThe 8 selected communities share similar demographic features: limited number of founders, high endogamy and consanguinity. We reconstructed their demographic dynamics over the centuries in order to assess their degree of isolation and inbreeding. Six small villages showed similar population growth trend from 1688 to 2001. Baunei and Seui differ because they were two large villages: Seui was one of the most important centers from the 17th century to 1931 because of anthracite and copper mines but today, because of emigration toward Cagliari, is comparable in size to the other small villages .We calculated the level of endogamy characterizing these populations from 1676 to 1975 . EndogamThe endogamy reaches a very high degree in each village from 1676 to 1950 with an average of 80.75% , starting a slow progressive decrease from 1900 to 1950. From 1950, we observe a severe endogamy decline in all villages (average 57.03%) except for Talana (81.28%).th century. Based on kinship coefficients 2 estimates) on 43 individuals originating from other geographical areas of Sardinia.We reconstructed for each village extensive genealogies based on a relational database that includes all the inhabitants personal data starting from the 17People living in the village were invited to take part in the study by invitations sent by mail to every family and through public announcements. All the people participating in the study were healthy individuals and volunteers. The personal data were encrypted and kept separated from genetic and data. The scientific content of the project was extensively explained to all individuals participating in the study that signed informed consent forms in accordance with the Helsinki Declaration. The study was submitted and approved by the Italian Ministry of University and Research (MIUR) following the current Italian legislation.Genomic DNA was extracted from 7 ml of EDTA-treated blood with standard methods. SNPs genotyping for all samples was performed using the Affymetrix GeneChip platform. We utilized the GeneChip® Human Mapping 500 K Array Set that comprises two arrays (the Nsp and Sty arrays) capable of genotyping ∼262000 and ∼238000 SNPs, respectively. We followed the recommended protocol described in the Affymetrix manual. All DNA samples were normalized to 50 ng/µl. Then, 5 µl (250 ng) of dsDNA was digested with the appropriate restriction enzyme and ligated to adapters using T4 DNA ligase. Samples were then PCR amplified using TITANIUM Taq polymerase on an GeneAmp® PCR System 9700 gold plate thermal cycler. PCR products were purified using the Clontech purification kit followed by fragmentation. Samples were then injected into cartridges, hybridized, washed and stained. Mapping array images were obtained using the GeneChip Scanner 3000 7G plus. For quality control (QC), individual arrays not passing the 93% call rate threshold at P = 0.33 with the Dynamic Model algorithm All SNPs physical coordinates refer to the NCBI released annotation update for the human genome (NCBI Build 36.2). Alleles are expressed in the forward (+) strand of the reference.The mean minor allele frequencies (MAF) in our isolated population using the 500 K Array GeneChip® showed an average of 0.187 (±0.003). After the exclusion of monomorphic SNPs, the MAF increased an average of 0.251 (±0.004). We selected only SNPs informative (MAF>0.01) in all villages obtaining a sub-sample of 361980 SNPs (average space 7672 bp).LDMAP program 2http://www.broad.mit.edu/haploview).Two types of pair-wise LD metrics were calculated: Lewontin's standardized deviation coefficient |D'| http://cmpg.unibe.ch/software/arlequin3/). Seventy markers were excluded from the following analysis, as they showed highly significant departure from Hardy Weinberg equilibrium (P<10−5), obtaining 5,192 markers for the following analysis.For population analysis, 500 K were filtered according to inter-SNP distance (about 500 kb) to minimize LD effects, obtaining 5,262 SNPs. We tested Hardy–Weinberg equilibrium with a modified version of the Markov-chain random walk algorithm described in Guo and Thompson To prepare haplotype data, we considered 83 genomic regions with D'>0.7 in all 8 communities, starting from data employed for LD analysis, for a total of 361980 SNPs. Since recombination in X-linked and autosomal portions of the human genome is often concentrated in hotspots separated by DNA regions with little or no recombination We estimated haplotype frequencies using windows of 10 consecutive informative SNPs for each region, spanning an average of 150 kb.Inference of haplotype frequencies were performed employing the software PHASE 2.1 Haplotype data were used to compute genetic distances. Each region was considered as a single polymorphic locus, where each haplotype corresponded to a single allele.ST, a standard measure of genetic differentiation between populations ST is the proportion of the total genetic variance contained in a subpopulation relative to the total genetic variance. Values can range from 0 to 1, and a high value implies a considerable degree of differentiation among populations. The 95% confidence limits for FST were determined by 1000 permutations test. Level of statistical significance was tested by performing 1000 permutations. Both analysis were performed with GENETIX 4.5.02 software http://www.genetix.univmontp2.fr/genetix/genetix.htm).FTo ascertain the proportions of genetic variance due to differences within and between populations, genetic variance was hierarchically apportioned according to geographic criteria through the locus by locus AMOVA  Genetic distances were computed from allele and haplotype frequencies according to Nei http://evolution.genetics.washington.edu/phylip.html.Distances were clustered using the Neighbor – Joining method We performed factor Correspondence Analysis (FCA) using the Genetix 4.5.02 software http://www.unesco.org/webworld/idams/advguide/Chapt6_5.htm. We used this method because Guinand Details of mathematical principles of methods are provided at the following link: We examined correlation between genetic and geographic distance matrices using the Mantel test by a permutation procedure. The permutation allows to examine the empirical null distribution of the correlation coefficient taking into account the auto-correlations of the elements of the matrix http://pritch.bsd.uchicago.edu/structure.html). The model assumes the presence of K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned probabilistically to one cluster or to two or more clusters if their genotypes indicate that they are admixed To infer individual ancestry and population admixture, we carried out analysis of population structure using a model-based clustering method developed in the STRUCTURE 2.2 software We compared the extent of LD for the 8 villages and for a sample originating from other geographical areas of Sardinia. We used a set comprising both commons and informative SNPs in all communities. Moreover, to compare our results to a standard outbred population, we included in our study 60 unrelated samples from 30 HapMap CEU trios. The mean heterozygosity of the markers was 0.345 (SD = 0.011) in the 10 communities selected, ranging from 0.320 (Urzulei) to 0.361 (Seui). The average of minor allele frequency (MAF) was 0.251 (SD = 0.004), ranging from 0.241 (Urzulei) to 0.257 (Seui).The monomorphic SNPs (M-SNPs), in at least one village, were ∼26% of the entire SNPs list. The shared M-SNPs in the eight villages were 31656. The comparison with the HapMap samples showed that 88.5% of the shared M-SNPs were monomorphic also in the CEU population and 10.89% showed a MAF>0 and <0.05. Considering the total number of M-SNPs in each village, we identified a group of village specific M-SNPs that range from the highest values in Urzulei and Talana (5.04% and 4.33% respectively) to the lowest in Seui and Loceri (1.85% and 1.45% respectively).We constructed LD maps for the 10 populations on autosomes. The shortest maps were in Talana, Urzulei, Ussassai, Triei and Seulo, in agreement with their small population size and their secluded position. We found the trend growing from Baunei to Seui and to Loceri. The longest maps were in the Sardinia and in the CEU samples . Similar2 on autosomes in the selected communities. We calculated D' and r2 between all pairs of markers  and the lowest difference between Baunei and Triei (FST = 0.0105). All the comparisons between villages were highly significant (P<0.0001).In order to assess the level of differentiation among the villages we calculated the FST = 0.0260 and FST = 0.0238, respectively. Moreover, these two villages show a great deal of genetic distance between each other (FST = 0.0324).For each village, we computed average Fst resulting from each pairwise comparison. We observed the highest degree of differentiation for Talana and Seulo villages, with FST values pooling villages according to geographic position , we observed a higher FST value in the first group (FST = 0.0200) than in the second (FST = 0.0142).When we computed FST analysis. Results reveal a statistically significant genetic heterogeneity between the two geographic areas (FCT) . Also the heterogeneity among villages within areas (FSC) and among individuals within villages (FST) is highly significant .For AMOVA analysis Population structure was analyzed with the mean of the Mantel Test, which compares coefficient correlation between geographic and genetic distances We plotted results of Factor Correspondence Analysis e probability of the data using the F model favored the assumption of K = 7. To performed STRUCTURE analysis We analyzed features and different aspects of population structure in eight villages of Ogliastra region in the central-eastern area of Sardinia. This region is characterized by high endogamy, low immigration, environmental homogeneity, as well as genetic differentiation from the rest of the island th century to today.In this paper we focus our analysis on eight isolated Ogliastra villages to evaluate LD parameters and effective population structure using a dense whole genome SNPs map. The length of LD map is inversely related to the extent of LD over a given chromosomal segment, therefore shorter LD maps are observed in population isolates compared with more heterogeneous populations. Although the geographic area analyzed in this study was relatively restricted, our results evidence high values of LD parameters and the presence of LD variability across the genome in these communities depending on their historical demography and population structure. The 5 smallest and secluded villages show the shortest LD maps, in agreement with their similar size and isolated condition: from 270 LDU in Talana to 343 LDU in Seulo. We identified intermediate values in Baunei (LDU = 402), a large community with a continuous growth from the 17th century due to the presence of anthracite and copper mines. During the 19th century, Seui became one of Ogliastra main economical centre and the population grew to about 3000 inhabitants from the beginning of the 20th century to the 1960s. Then there was a massive emigration wave toward the main political and economic centre of Sardinia (Cagliari) with a rapid decrease of resident population. Today there are only 1587 inhabitants, and this has influenced LD parameters and current population structure.Seui, on the other hand, has peculiar historical and demographic aspects. This village, which was already an important administrative centre during the Spanish domination of Sardinia (even has a prison dating from the 1640s) has undergone immigration waves starting from the mid-19Finally, Loceri has the lowest LD values because it is not in an isolated geographical position, it is close to the seashore and to Lanusei, an important Ogliastra administrative centre.Its frequent genetic exchanges with other villages are proven by archival data spanning many centuries.Additionally, the extreme features of some villages such as Talana and Urzulei, were evidenced by the analysis of the monomorphic SNPs. The different percentage of specific monomorphic SNPs shows a trend similar to that of different populations, it is consistent with our analyses of LD values and it contributes to evidence the different level of isolation of these villages.ST among villages. Recently various studies have analyzed comparable set of data obtained from European and East Asian Populations ST from a subset of 5,700 SNPs distributed over entire genome, computed with the same method (FST = 0.0029) was lower than our sample (FST = 0.0213). The highest degree of differentiation has been detected between samples from Italy and Sweden (FST = 0.0060). This value is lower than the one detected between Baunei and Triei (FST = 0.0105), which are the least differentiated villages in this study. Salmela et al. ST values in a subset of 6369 SNPs, finding values lower (from 0.0005 to 0.0072) than values observed among Ogliastra villages (0.0105 to 0.0324).The STRUCTURE population analysis confirms the presence of a distinct cluster for each village analyzed, except for Baunei and Triei . Moreover, we observed high values of FOur data suggest a great level of differentiation among Ogliastra villages: even if this result is influenced by the difficulty in detecting micro differentiation in countrywide samples, nevertheless it clearly reveals the high level of population substructure in Ogliastra.In general, our results show a good correlation with the geographical structure of the region, as revealed by the pattern of isolation by distance of the Mantel Test. In particular, Neighbor Joining trees computed from different sets of data (single SNPs and haplotypes) confirmed the Mantel Test results because villages are located in the tree according to their geographic position and relative closeness. Furthermore, the topology of the tree shows two main clusters identifying a Northern and a Southern Ogliastra sub-area. This is confirmed by AMOVA and STRUCTURE analysis at low level of differentiation (K = 2), highlighting the separation of the two sub-areas.Factor Correspondence Analysis and STRUCTURE analysis emphasize that Talana and Urzulei are highly differentiated although separated by limited geographic distance. In addition, Neighbor Joining tree shows the village of Loceri to be in an intermediate position, while correspondence analysis confirms that Triei and Baunei are highly correlated but not identical.Our results, obtained with a large SNPs data set, confirm a high degree of differentiation among villages, leading us to some considerations: not only small areas as Ogliastra should not be considered homogeneous a priori, but even adjacent villages could be not homogeneous.A number of analyses performed in the large and small genetic isolates showed either the presence or absence of substructure. For example, in Hutterites communities we cannot identify distinct subpopulation ST values were 0.02 (95% CI: 0.017–0.022), with many significant differences in the comparison of these villages.In the case of small population isolates, the analysis of 6 South Tyrolean villages performed with microsatellites on Xq13.3, showed the presence of three genetically distinct sub-populations, sharing the alpine environment and lifestyles The information obtained on the genetic differences present among our villages in Ogliastra is potentially useful for the ongoing extensive genetic research in this specific population. Detailed knowledge of the high differentiation in the degree of LD background found in each village will probably be crucial in the analysis of these sub-isolates that represent useful populations for the initial detection of loci/genes with Genome-wide association (GWA) involved in the predisposition to complex traits. Such analysis require a great deal of attention to exclude false positive results as consequence of stratification differences between cases and controls There are potential advantages in the choice of these populations because of reduced environmental complexity and a probably reduced number of disease alleles. Some of the loci are expected to have stronger genetic effects on the disease/trait under analysis. Furthermore, small isolates might contain mutations e/o possible variants that are rare in the population at large, thus allowing the identification of genes that would otherwise be missed One negative aspect could be the limited number of cases in association studies, except for common diseases with high prevalence. In fact our group was able to identify a variant related to the EDA2R gene strongly associated with Androgenetic Alopecia showing an average prevalence of 47% in the 8 villages We also propose that this kind of populations is helpful in the search for variants associated to quantitative traits (QT) related to common disease. In QT loci analyses all individuals phenotyped are useful and even the limited number of inhabitants of one of our villages could be a sufficient cohort for initial association studies. Once a significant association is obtained we can replicate the findings in the other villages. Obviously, it will be important to replicate the findings in a general Sardinian sample and in outbreed populations.To conclude, we underline the influence of history and bio-demography on the genetic features of population isolates and we propose as a first step, the genetic characterization of isolates in order to identify possible sub-populations and stratification. This could lead to the optimization of study design for the choice of the best approach for gene identification in complex traits.


ST value was high , reflecting the degree of differentiation/heterogeneity of seven populations studied for these loci. The cluster analysis and multidimensional scaling of genetic distances reveal two broad clusters of populations, besides Moolu Kurumba maintaining their distinct genetic identity vis-à-vis other populations. The genetic affinity for the three tribes of the Indo-European family could be explained based on geography and Language but not for the four Dravidian tribes as reflected by the NJT and MDS plots. For the overall data, the insignificant MANTEL correlations between genetic, linguistic and geographic distances suggest that the genetic variation among these tribes is not patterned along geographic and/or linguistic lines.The present study was undertaken to determine the extent of diversity at 12 microsatellite short tandem repeat (STR) loci in seven primitive tribal populations of India with diverse linguistic and geographic backgrounds. DNA samples of 160 unrelated individuals were analyzed for 12 STR loci by multiplex polymerase chain reaction (PCR). Gene diversity analysis suggested that the average heterozygosity was uniformly high ( >0.7) in these groups and varied from 0.705 to 0.794. The Hardy-Weinberg equilibrium analysis revealed that these populations were in genetic equilibrium at almost all the loci. The overall G The most remarkable feature of the Indian population structure is the clear division of its population into strictly defined endogamous castes, tribes and religious groups. With the exception of Africa, India harbors more genetic diversity than other comparable global regions. It is generally believed that the tribal people, who constitute 8.2% of the total population (2001 census of India), are the original inhabitants of India. The total number of tribal groups is estimated to be 461, who speak about 750 dialects that belong to one of the four language groups, Austro-Asiatic, Indo-Europeans, Dravidian and Tibeto-Burman.[1et al. reported close genetic affinity for populations from similar linguistic backgrounds.[Studies based on autosomal markers (STRs) have suggested that genetic distances are correlated with geographical distances among the Indian populations.-5 Indeed7kgrounds. The presThe location of the study populations along with the linguistic background and sample sizes are presented in Five to 10 ml of blood was collected in EDTA after informed consent from 160 unrelated individuals belonging to the seven tribal groups. DNA was isolated from the leucocytes by using standard protocols. Twelve dS) and mean heterozygosity for the total sample (HT) {GST = 1- (HS/HT)}, was calculated using the software Dispan.[et al.[www.promega.com/geneticidtools/powerstats/PowerStatsV12.xls) was used to calculate the power of discrimination (PD). Multidimensional scaling analysis based on DA distances was performed with SPSS version 10.0. Mantel correlations for matrix correspondence and partial correlations were obtained between the genetic, geographic and linguistic distance matrices with the software F-Stat version 2.9.3.2 available at http://www2.unil.ch/popgen/softwares/fstat.htm. The geographic distance between places was computed based on geographic coordinates of the place from where the samples were collected. Linguistic distance for the correlation analyses was based on the linguistic trees,[Allele frequencies at each locus were calculated by a simple gene counting method. The Harde Dispan. Pair-wisn.[et al. and a phn.[et al. were conic trees, considerST = 0.051). However, there is considerable heterogeneity in the degree of differentiation at different loci, high (9.8%) in the case of D13S175 and low (2.6%) in the case of D13S170. The PD is an index of the power of a particular locus to discriminate individuals in a population and the results suggest that most of these loci show a high value of this index.Allele frequencies at 12 STR loci among the seven tribal groups showed the presence of the same common alleles and, in a majority of the cases, the most predominant allele was the same, with a variable frequency. The observed heterozygosity at each locus and the average heterozygosity over all the loci for each of the study populations are given in Pair-wise genetic distances between the study populations were computed from the allele frequencies of the 12 loci  and an uST value 0.03) when compared with that among the geographic groups, which is negligible and non-significant. Similar results were obtained when AMOVA was performed based on the linguistic groupings. Genetic differentiation within the Linguistic group was found to be significant compared with the non-significant value for genetic differentiation between the two linguistic groups.AMOVA was performed, grouping the tribes according to the state to test whether geographically closer tribes are also genetically closer . GeneticP = 0.30) nor between genetic and linguistic distances (P = 0.58), respectively, controlling for linguistic and geographic distances.Mantel correlations between genetic distance and geographical or linguistic distances were not significant. The partial Mantel correlation was significant neither between genetic and geographical  among the Indian populations. Based on STR loci, previous studies have reported a relatively high GST value among the Indian populations representing northern, eastern and northeast regions[ST value based on STR, VNTR and other DNA marker loci among the subcastes of Golla from Southern Andhra Pradesh,[ST value calculated for three STR loci common to 23 Indian populations ranged from 3.2% among the Golla sub castes at the local level to 6.7% for all the 23 groups representing different regions of India.[ST value for the tribal populations of the present study is quite high as compared with the other continental populations (GST < 2%) such as Africans, Caucasians and Mongoloids.[These populations show high levels of average heterozygosity (about 74%), suggesting high within-population diversity at these 12 loci. The average Gt regions18 as com Pradesh, Bhargava Pradesh,21 and al Pradesh, The averngoloids.25 This cThe genomic affinities among the groups studied Figures  and 3 in26The analysis of molecular variance reveals that the extent of genetic differentiation among the states or among linguistic families is not significant although the genetic differentiation between populations within the states or within the linguistic family was significant, suggesting that the current geographic and/or linguistic boundaries are not significant determinants of genetic variation in these tribal populations. The political state boundaries in India may not be an actual indication of geographical and/or genetic barriers. MANTEL correlation and partial correlation analysis based on actual geographical distances also did not reveal any significant association between genetic and either linguistic or geographic distance.The results based on just 12 loci might be sometimes misleading as some of the allele frequencies might have been highly affected by stochastic variation considering the limitation of small sample sizes. Nevertheless, these 12 STR loci exhibit a high discriminatory power. The PD is found to be in the range of 0.50-0.96. The high values of PD validate the utility of these markers in forensic identification as well. Further, earlier studies supported the utility of the STR markers in population discrimination both at the local and at the regional levels.28 The la


Glossina fuscipes fuscipes, a riverine species of tsetse, is the main vector of both human and animal trypanosomiasis in Uganda. Successful implementation of vector control will require establishing an appropriate geographical scale for these activities. Population genetics can help to resolve this issue by characterizing the extent of linkage among apparently isolated groups of tsetse.G. f. fuscipes arose from an historical event that divided two divergent mitochondrial lineages. These lineages are currently partitioned to northern and southern Uganda and co-occur only in a narrow zone of contact extending across central Uganda. Bayesian assignment tests, which provided evidence for admixture between northern and southern flies at the zone of contact and evidence for northerly gene flow across the zone of contact, indicated that this structure may be impermanent. On the other hand, microsatellite structure within the southern lineage indicated that gene flow is currently limited between populations in western and southeastern Uganda. Within regions, the average FST between populations separated by less than 100 km was less than ∼0.1. Significant tests of isolation by distance suggested that gene flow is ongoing between neighboring populations and that island populations are not uniformly more isolated than mainland populations.We conducted genetic analyses on mitochondrial and microsatellite data accumulated from approximately 1000 individual tsetse captured in Uganda and neighboring regions of Kenya and Sudan. Phylogeographic analyses suggested that the largest scale genetic structure in Despite the presence of population structure arising from historical colonization events, our results have revealed strong signals of current gene flow within regions that should be accounted for when planning tsetse control in Uganda. Populations in southeastern Uganda appeared to receive little gene flow from populations in western or northern Uganda, supporting the feasibility of area wide control in the Lake Victoria region by the Pan African Tsetse and Trypanosomiasis Eradication Campaign. Glossina fuscipes fuscipes is the most common species of tsetse in Uganda, where it transmits human sleeping sickness and nagana, a related disease of cattle. A consortium of African countries dedicated to controlling these diseases is poised to begin area wide control of tsetse, but a critical question remains: What is the most appropriate geographical scale for these activities? To address this question, we used population genetics to determine the extent of linkage between populations of tsetse confined to discrete patches of riverine habitat. Our results suggest that Uganda was colonized by two distinct lineages of G. f. fuscipes, which now co-occur only in a narrow band across central Uganda. Evidence for interbreeding at the zone of contact and movement of genes from the south to the north suggest that this historical genetic structure may dissolve in the future. At smaller scales, we have demonstrated that exchange of genes among neighboring populations via dispersal is at equilibrium with the differentiating force of genetic drift. Our results highlight the need for investment in vector control programs that account for the linkage observed among tsetse populations. Given its genetic isolation and its location at the far edge of G. fuscipes' range, the Lake Victoria region appears to be an appropriate target for area wide control. Human African Trypanosomiasis, or sleeping sickness, is a vector-borne disease that kills thousands of people each year in sub-Saharan Africa The application of population genetic methods to disease vectors offers insights into facets of ecology, reproduction, dispersal patterns, population dynamics and genetic diversity that can have direct relevance for guiding control programs. At deeper timescales, population genetics can elucidate the historical processes that have influenced the current distribution of vector populations. Over more recent timescales, population genetics can delineate isolated vector populations that may be appropriate targets for local eradication and can identify dispersal routes that must be disrupted to prevent reinfestation of previously cleared zones. Characterization of barriers to gene flow is particularly important in planning the release of genetically modified or sterile vectors where the scale of success will depend on the scale at which the released vectors mate with wild counterparts Glossina fuscipes fuscipes Newstead 1910, which occurs in a peninsular distribution terminating around the shores of Lake Victoria at the far eastern edge of its range  has recently extended its range from a historical focus along the shores of Lake Victoria to several foci extending north into central Uganda T. b. gambiense) found in northwestern Uganda, complicating both the diagnosis and treatment of the disease.In Uganda, the primary vector of both human and animal forms of trypanosomiasis is ange see . Given tGenetic work by Abila et al. G. f. fuscipes is restricted to discrete patches of riverine and lacustrine habitat distributed among large, uninhabitable tracts of pastures and agricultural fields. The extent to which these apparently discrete populations are actually linked by dispersal is unknown, but preliminary work in southeastern Uganda has suggested that even flies from the same watershed may share little mitochondrial variation G. f. fuscipes in Uganda.In Uganda, 2 area. We collected flies from 21 sites across Uganda as well as single sites in Ndere Island, Kenya (ND) and Kurmuk, Sudan . All samples were collected between 2006 and 2009, except for flies from Kigezi (KZ) and Kitgum (KT), which had been collected in 1974 and 1997, respectively, and were obtained from a museum collection stored at the Coordinating Office for the Control of Trypanosomiasis in Uganda.Tsetse were caught in biconical traps  KU; see . S. TorrFlies caught between 2006 and 2009 were extracted using DNeasy kits  following the manufacturer's protocols. Museum specimens were extracted using the DNA-IQ system  in a dedicated ancient DNA laboratory in order to prevent contamination with more abundant sources of modern DNA.G. fuscipesT CAA CAC TTT TTA GGT TTA G – 3′5′ – CC) and COIIR1 (T TCT CTA ATT TCA TCA AGT A – 3′5′ – GG), which consistently amplified just a single sequence. To help insure that this sequence originated from the mitochondrial genome and not a nuclear copy (NUMT), we compared sequences obtained with COIF1/COIIR1 (570 bp) to sequences obtained from the amplification of an ∼1.7 kb fragment  using 50 cycles and an annealing temperature of 51°C. All sequences have been deposited in GenBank (Attempts to amplify fragments of cytochrome oxidase I (COI) and cytochrome b (cytb) genes using primers designed previously for  GenBank .Glossina fuscipesG. pallidipesG. palpalisG. morsitansG. fuscipes. In addition, we developed one new locus (C07b) from the G. fuscipes microsatellite library used by Brown et al. 2, 0.2 mg/mL BSA and 0.5 U AmpliTaq Gold. Flourescently-labeled primers were included at a final concentration of 0.4 µM. When using the m13 amplification system The majority of published microsatellite loci that had been developed for d) and nucleotide diversity (π) using the program DnaSP v5 o) and expected (He) heterozygosity for each population.For mtDNA, we calculated haplotype diversity  within metapopulations and also the variance explained by metapopulations (identified at higher K) within larger metapopulations (identified at lower K) using the program HIERFSTAT In order to further explore the hierarchical relationships among populations, we generated a neighbor-joining tree based on Cavalli-Sforza chord distances. We generated genetic distances using the program MSA v4.05 ST/(1- FST); ST, a frequency based measure, as well as ΦST, which also accounts for the evolutionary relatedness of haplotypes (mtDNA only). For mitochondrial data, we tested each of the two distinct groups of lineages (north and south) identified in a parsimony network, but excluded populations at the zone of contact between these two groups , the number of individuals in an ideal population (subject only to random genetic drift) that would exhibit the same distribution of allele frequencies as actually observed. We calculated Ne using both linkage disequilibrium ; therefore, we explored the stability of estimates using priors of both 5,000 and 10,000 for maximum Ne. We also evaluated all populations for evidence of a recent decline in effective population size using the program BOTTLENECK We performed single sample point estimates of effective population size  and using the sequential Bonferroni method to account for non-independence of multiple tests, we detected no significant tests of linkage disequilibrium among the 55 remaining pairs of loci. Using the generalized binomial procedure implemented in MultiTest v.1.2 han zero . Six popG. f. quanzensis from the DRC. Among samples of G. f. fuscipes, overall haplotype diversity (Hd) was 0.906. Across individual populations, Hd ranged from a high of 0.778 in the Uganda population from Ogur (OG) to a low of 0 in the Kenyan population from Ndere Island  and southern populations , however the latter trend was not evident when the southern group was further parsed into western and southeastern groups.We observed high levels of microsatellite diversity in flies sampled in western Uganda at Arua (AR), Murchison Falls (MF) and Moyo MY; . A regreIsland populations did not exhibit uniformly low diversity. As observed with mitochondrial diversity, Ndere Island flies exhibited the lowest levels of microsatellite variation. Flies from Buvuma Island (BV), on the other hand, exhibited allelic richness and heterozygosity levels on par with neighboring populations from the mainland .G. f. quanzensis and were perfectly partitioned in geographical space (xy = D – 0.5*(Dx+Dy) where D is the mean nucleotide diversity observed between the two clades, and Dx and Dy are the mean nucleotide diversities within group x and group y Drosophila mitochondrial mutation rate of 5.7×10−8 per silent site per year Mitochondrial haplotypes obtained from flies collected across Uganda and Sudan fell into five clades (each consisting of lineages separated by at most two mutations) that were nested within two major groups based on a parsimony network . These tal space . The twos in both the north  and the south ; however, Ramos-Onsins' R2 was only marginally significant in the south .Given that northern and southern flies appear to have evolved independently for an extended period of time, we performed tests of neutrality/population growth for each group separately. Mismatch tests revealed curves typical of expanding populations, particularly in the south . This waST values calculated from microsatellite data revealed significant differentiation among all sampled localities, with the sole exception of Ogur (OG) and Pader  for the effect of population measured within these three metapopulations. Beyond this level of partitioning, individuals continued to exhibit geographically relevant clustering up to K = 11  and Okame (OK) and the large pairwise FST observed between neighboring populations Ndere (ND) and Busime  and Ndere (ND)), we tested whether open water presented a barrier to gene flow beyond that imposed by distance alone. A partial Mantel test implemented in IBDWS revealed a significant effect of island isolation on genetic distance, after controlling for geographical distance ; however, this effect could be explained by the isolation of ND alone. Examining the effect of ND only, a second partial Mantel test revealed a strong effect of island isolation after controlling for geographical distance  and also confirmed the strong relationship between genetic distance and geographical distance in the southeast, after controlling for the effect of ND . Partial Mantel tests involving BV alone provided no evidence for significant isolation of this population beyond that attributable to geographical distance.e based on single point samples provided evidence for relatively large historical effective population sizes in Busime (BU) in southeastern Uganda, and also in several populations from western and northwestern Uganda: Kabunkanga (KB), Kakoga (KK), Murchison Falls (MF) and Moyo , five populations exhibited significant signatures of a population bottleneck under the IAM model, but only one of these  also tested positive for a bottleneck under the TPM model .G. f. fuscipes in Uganda G. f. fuscipes in Uganda appears to reflect an ancient event that divided northern and southern lineages, and in light of evidence for modern gene flow, is likely to be impermanent.Genetic structure in both mtDNA and microsatellites confirmed the presence of two distinct lineages of G. f. fuscipes from dry period refugia. Given the perfect latitudinal partitioning of mitochondrial groups, the two divergent lineages likely expanded into their present distribution via distinct pathways. These paths may have split to the north and south of the Blue and Rwenzori mountain ranges, both of which form a barrier to direct colonization from the west. As evidenced by the distribution of mtDNA haplotypes, these two groups currently meet along a zone of contact extending from Bunghazi (BN) in eastern Uganda to Masindi (MS) in western Uganda. This zone of contact falls to the south of Lake Kyoga, which was formerly proposed as a barrier to gene flow between northern and southern flies The isolation of northern and southern lineages, which appear to have diverged on the order of several hundreds of thousands of years before present, may have been facilitated by habitat fragmentation during extreme drought cycles in East Africa that ended only 70,000 years ago G. palpalis palpalisWolbachia-induced mating incompatibility could also have played a role in driving the northern lineage to relatively high frequency, a possibility currently being investigated. In Junda (JN) and Masindi (MS), the homogeneous nuclear background did not support admixture of northern and southern flies. However, just north of the contact zone, flies captured along the Nile River at Murchison Falls (MF) and along Lake Kyoga at Bugondo (BG) exhibited strong signals of mixed ancestry, confirming our observation in Bunghazi that gene flow between northern and southern lineages is possible and ongoing.At present, evidence for admixture between the northern and southern flies is not uniform along the zone of contact. In Bunghazi (BN), we did not detect any deviation from HWE and almost all flies exhibited a mix of southern and northern ancestry, irrespective of their maternal lineage. In this portion of the contact zone, therefore, no barriers to mating are evident between northern and southern lineages. Given the hybrid dysgenesis observed among cryptic taxa within G. tachinoides and G. submorsitans, can survive for periods of at least 24 hours while submerged in water or saturated soil G. f. fuscipes to disperse in the absence of contiguous tracts of favorable habitat. This warrants consideration when devising vector control strategies.Given the evidence of admixture highlighted above, the genetic differentiation between northern and southern lineages may simply represent a signature of historical allopatric fragmentation that has little bearing on the current movement of genes. However, Bayesian assignment probabilities , which pG. f. fuscipes, albeit at different time scales. In southern Uganda, the slope of the regression of genetic distance on geographic distance was steeper, and at large geographic distances, was driven by the major genetic discontinuity between flies on either side of the gulf in G. f. fuscipes' predicted range (between Kabunkanga (KB) and Nkumba (NA); Whatever the dominant mode of dispersal, analyses of isolation by distance using microsatellites reflected an equilibrium between gene flow and drift in both northern and southern regions. In northern Uganda, the slope of the regression of genetic distance on geographic distance was shallow relative to that observed in southern Uganda, suggesting that the homogenizing influence of gene flow is relatively stronger in the north versus the south. The relatively low genetic divergences observed over large geographic distances may have also been influenced by a recent history of sequential founder events occurring from west to east across northern Uganda, a process that is supported by the significant decline in allelic diversity with longitude across the north. Both scenarios emphasize the vagility of G. f. fuscipes in Uganda appeared to be genetically homogeneous over the 1–5 km2 trapping area that formed our fundamental sampling unit. Although we detected significant deviations from HWE for two loci in a handful of these populations, we did not observe consistent trends in FIS that would provide evidence for any finer scale substructuring of tsetse populations, such as that observed in G. palpalis, a related species of riverine tsetse ST <∼0.1) between most populations separated by less than 100 km. This level of differentiation is similar to the differentiation observed among populations of G. palpalis at similar scales in Burkina Faso and Equatorial Guinea The signal of gene flow obtained from IBD analysis is consistent with estimates of dispersal rates for riverine tsetse, which are on the order of tens of kilometers per year ST values among populations of G. f. fuscipes in Uganda prompted the conclusion that genetic drift is a much stronger force than gene flow and that perhaps dispersal tendencies have been overestimated ST values and little evidence for IBD in mtDNA provided some support for this conclusion, at least among females; however, for microsatellite data, IBD analyses were in accord with higher levels of current gene flow. Even if our microsatellite-based estimates of FST are deemed to be high, modeling has shown that high FST may persist in the face of high gene flow if environmental heterogeneity contributes to a large variance in the size of individual populations e for G. f. fuscipes in Uganda, though subject to large confidence intervals, were variable across populations, indicating that this condition may be met. Interestingly though, with the exception of Okame (OK), a site that has experienced continuous trapping of tsetse over the last several years, we did not find strong evidence for bottlenecks in the majority of populations considered. Our power to detect bottlenecks was likely low, since the transient signal of reduced allelic diversity that is indicative of a bottleneck, is unlikely to persist across multiple demographic cycles in populations with historically low NeG. f. fuscipes in Uganda should account for the movement of tsetse consistent with this gene flow.Previous observation of significant FG. f. fuscipes in Uganda appear to be consistent with high dispersal capacity, though confirmation of this will require the coordination of genetic studies with mark-recapture experiments. Interestingly, open water did not appear to present an unusual barrier to gene flow and we speculate that rivers may serve as a conduit for passive dispersal. Contrary to hypotheses invoking modern geographical barriers, the largest scale genetic structure apparent in Ugandan populations of G. f. fuscipes appears to have arisen from an ancient event that divided northern and southern lineages. Evidence for admixture between these lineages suggests that this structure may be impermanent but future studies should explore the viability of hybrid flies, particularly in light of the northerly-biased gene flow evident across the zone of contact.In conclusion, implied levels of gene flow among populations of Table S1Mitochondrial haplotype information, including frequencies observed across populations and associated GenBank accession numbers.(0.09 MB DOC)Click here for additional data file.Table S2Primer sequences and original source of loci used in this study.(0.06 MB DOC)Click here for additional data file.Table S3G. f. fuscipes. Significance was assessed at p<0.05 (*) and, after Bonferonni correction by locus, at p<0.002 (**).Estimates of FIS at 13 microsatellite loci for populations of (0.09 MB DOC)Click here for additional data file.Table S4G. fuscipes at each locus.Allele frequencies observed across populations of (0.07 MB XLS)Click here for additional data file.Table S5G. f. fuscipes in Uganda, Kenya (ND), Sudan (KU) and the Democratic Republic of Congo .Microsatellite-based FST values  and significance  for all pairwise comparisons between populations of (0.11 MB DOC)Click here for additional data file.Table S6Mitochondrial-based FST values  and significance  for all pairwise comparisons between populations in Uganda, Kenya (ND) and Sudan (KU).(0.10 MB DOC)Click here for additional data file.


Due to its history, with a high number of migration events, the Mediterranean basin represents a challenging area for population genetic studies. A large number of genetic studies have been carried out in the Mediterranean area using different markers but no consensus has been reached on the genetic landscape of the Mediterranean populations. In order to further investigate the genetics of the human Mediterranean populations, we typed 894 individuals from 11 Mediterranean populations with 25 single-nucleotide polymorphisms (SNPs) located on the X-chromosome.A high overall homogeneity was found among the Mediterranean populations except for the population from Morocco, which seemed to differ genetically from the rest of the populations in the Mediterranean area. A very low genetic distance was found between populations in the Middle East and most of the western part of the Mediterranean Sea.A higher migration rate in females versus males was observed by comparing data from X-chromosome, mt-DNA and Y-chromosome SNPs both in the Mediterranean and a wider geographic area.Multilocus association was observed among the 25 SNPs on the X-chromosome in the populations from Ibiza and Cosenza.Our results support both the hypothesis of (1) a reduced impact of the Neolithic Wave and more recent migration movements in NW-Africa, and (2) the importance of the Strait of Gibraltar as a geographic barrier. In contrast, the high genetic homogeneity observed in the Mediterranean area could be interpreted as the result of the Neolithic wave caused by a large demic diffusion and/or more recent migration events. A differentiated contribution of males and females to the genetic landscape of the Mediterranean area was observed with a higher migration rate in females than in males. A certain level of background linkage disequilibrium in populations in Ibiza and Cosenza could be attributed to their demographic background. The X-chromosome has features that make it a good source of information for population genetic studies. The X-chromosome is present in a single copy in males, which makes it possible to determine the X-chromosome haplotypes in men. Compared with autosomes, the X-chromosome has lower recombination rate, lower mutation rate and smaller effective population size resulting in a faster genetic drift. In consequence, both linkage disequilibrium (LD) and population structure in the X chromosome are expected to be stronger than those in autosomes . Two-thiDue to its history with constant migration movements, the Mediterranean area constitutes an challenging region for population genetic studies, both considering the whole area -4 and paIn order to further investigate the genetic characteristics of the populations in the Mediterranean basin, we analyzed 25 SNPs located on the X-chromosome in eleven populations from the Mediterranean area. In addition, two populations from Northern Europe and East Africa were analyzed. We carried out a wider analysis using data from the HapMap website on 21 out of the 25 SNPs used in this study (see Methods for details).We wanted to use the X-chromosome SNPs as multilocus markers. We selected polymorphic X chromosome SNPs with a physical distance of at least 600 kb. Population history such as genetic drift and admixture has an important consequence on the degree of population LD . The levWe studied the informativeness of the markers selected and the sex-biased migration rate and compared the information to that of non-recombinant markers in mtDNA and the Y-chromosome.A total of 1,078 different haplotypes were found in the 13 populations analyzed by means of 25 X-chromosome SNPs. No single haplotype was shared among individuals within or between populations.All the markers were polymorphic in all the populations studied. The minor allele frequency varied between a minimum percentage of 10.3% (X159 marker in the Moroccan population) and a maximum value of around 50.0% (widely found). The mean gene diversity (d) of the 25 markers analyzed was very homogeneous in the 13 populations sampled. They ranged from 0.437 in the Somali population to 0.461 in Iraqis and Tunisians. Taking into account that the maximum level of expected heterozygosity for biallelic markers is 0.5, a high degree of gene diversity was found for the 25 SNPs selected in all the populations analyzed.Among the 300 pairwise comparisons between the 25 SNP markers in the populations, between 10  and 23 pairwise comparisons (Ibiza) showed significant p-values (p < 0.05). However, after Holm-Sidak correction, only two pairwise LD values were significant . Nevertheless, when multilocus tests of associations were performed using all the 25 markers, the null hypotheses of linkage equilibrium were rejected in two populations: Ibiza (p < 0.01) and Cosenza (p < 0.05). Both populations present some peculiarities that may explain the existence of a higher degree of background linkage disequilibrium (see Discussion).st was 0.004 (p = 0.001). When the Moroccans were excluded, the significance level increased to p = 0.05. We also performed a similar statistical analysis in the nine "worldwide" populations (see Methods) by using 21 out of the 25 X-chromosome SNPs  was observed (p < 0.001). No significant difference was found among the three European populations or between the Chinese and the Japanese population, while a high differentiation was observed among the three African populations, especially between Moroccans and Sub-Saharans.Table When a locus by locus AMOVA was performed in the Mediterranean group, only three out of 25 markers showed significant (p < 0.05) variations among the Mediterranean populations , while 17 out of 21 markers were important for the differentiation of the 9 "worldwide" populations: X018, X029, X036, X046, X047, X056, X059, X062, X076, X085, X109, X121, X122, X131, X135, X143 and X165. The markers X004, X142, X159 and X175 were not included in these analyses due to the lack of information in the populations obtained from the HapMap Project. No correlation (data not shown) was found between the mean gene diversity and the level of differentiation among populations, as has been suggested by others [st matrix obtained using 25 or 21 X-chromosome SNPs in the Mediterranean  was made from the pairwise Reynold's Fn Figure  and the n Figure , respectst value) opposite to the others . In the second axis, the Mediterranean populations plus the CEU population (Utah residents with ancestry from northern and western Europe) formed a group between the North-European and African populations. Only the Moroccans showed a slight displacement from the others showing significant Fst values in most of the pairwise comparisons inside the Mediterranean group. The CEU population showed an intermediate position between the North of Europe, represented by the Danish population, and the Mediterranean group. None of the pairwise comparisons between the CEU population and the Mediterranean or Danish populations showed a significant Fst value. For the grouping proposed in Figure In Figure Additionally to the AMOVA analysis, a cluster analysis was performed using the STRUCTURE  softwarest values without finding significant differences using STRUCTURE when the populations analyzed are closely related [Due to the statistical model implemented in STRUCTURE, it is possible to find significant F related . This is related , it coulst/(1-Fst)) and the natural logarithm of the geographical distance (in kilometres) in the Mediterranean area based on the study of 25 X-chromosome SNPs , could be calculated from the slope value (0.001). Considering the 25 biallelic markers analyzed in the present work, the estimated value of 4D μσ2 would be around 935 individuals, which seems to be an underestimated value according to the same author. This data can be interpreted as the result of a high number of migration events in the recent history of the human populations in the Mediterranean basin.We did not find any significant correlation between genetic differentiation . In this study, isolation by distance operated better at large geographic scales than at short distances.The number of estimated migrants was dramatically reduced when a much wider area was considered , a greater female migration rate compared to the male migration rate was still observed. As it has been commented above, the minimum geographic distance between two populations was approximately 954 km and mainly pre-agricultural migration events were then represented in this case.A considerable amount of information based on classical genetic markers ,27,28, ast = 0.004) in 11 Mediterranean populations. The fixation index was significant (p = 0.001) but the p-value increased to p = 0.5 when the Moroccan population was excluded from the analysis. In contrast, a 10 times higher Fst value (p < 0.001) was observed when 9 populations from three continents  were analyzed. Not surprisingly, the strongest genetic differentiation was found among the 3 African populations. It is well known that African populations have a higher level of genetic heterogeneity compared to European or Asian populations [Based on the study of 25 X-chromosome SNPs, we found a low value of population differentiation  and X-chromosome markers were smaller than those obtained from Y-chromosome SNPs. The negative slope obtained from mtDNA data can be explained by the fact that populations geographically close to each other showed a relatively high genetic distance. In accordance with the findings of other authors , the femIn summary, a general genetic homogeneity of the X-chromosome SNPs was observed in a number of populations in the Mediterranean area. The genetic distance between populations in the Middle East and the western part of the Mediterranean area was very low, most likely reflecting the effect of the Neolithic Wave and recent migration events. Only the Moroccan population showed a significant genetic distance from the remaining Mediterranean populations including populations that are geographically close to it, showing the importance of the Strait of Gibraltar as a geographic barrier and supporting the idea of a low impact of the Neolithic demic diffusion and more recent migrations in North-West Africa. In Ibiza and Cosenza populations, interesting differentiations from their neighbouring populations and significant multilocus associations were observed when all the 25 X-chromosome SNPs were analyzed reflecting the particular demographic histories of these populations. A deeper study of LD in these two populations could reveal interesting results for disease association studies.A higher migration rate was observed in females than in males in both the Mediterranean area and in a wider geographic area showing a greater genetic flow mediated by females than males probably both in pre-agricultural and post-agricultural societies. As it was suggested by other authors , patriloWe analyzed a total of 1,078 unrelated males from 13 populations Figure . Eleven For further comparisons, data from males from the International HapMap Project were downloaded Figure : 30 maleTwenty-five X-chromosome SNP markers spaced across the chromosome were selected from the NCBI SNP database. The selected markers provide 300 pairwise comparisons over distances from 0.6 to 145 Mbp. Table A 25-plex PCR reaction was developed in order to amplify all the DNA-fragments with the SNP markers in a single reaction, and a 25-plex minisequencing reaction was also developed. Table n is the number of gene copies, k the number of haplotypes and pi the sample frequency of the ith allele at the locus [ps = 1 - (1 - pi)n-i+1). We used the results obtained from the analysis of 35 biallelic Y-chromosome SNPs carried out on the same set of samples used for the present work (unpublished data and ). We useThe sequences between the nucleotide positions 16,024 and 16,366 were analyzed . Due to The levels of correlations between the different distance matrices obtained from the three groups of markers  were calculated by means of the Mantel test (ARLEQUIN 3.1 software). Because the correlation between genetic distance matrices can be blurred by the geographic distance between populations , we calcCT was primarily responsible for the design of the study, carried out the SNP typing, performed the statistical analysis and elaborated the manuscript. JJS participated in designing the study and the manuscript. AB participated in designing the study and the manuscript, and sent samples from South Italy and Sicily. CBC participated in designing the study and the manuscript, and sent samples from Tunisia. AH participated in designing the study and the manuscript, and sent samples from Morocco. MBD participated in designing the study and the manuscript, and sent samples from Tunisia. MR participated in designing the study and the manuscript, and sent samples from Spain. NM participated in designing the study, analyzing the results and preparing the manuscript. All authors read and approved the final version of the manuscript.


Most genetic studies of population differentiation are based on gene-pool frequencies. Population differences for gene associations that show up as deviations from Hardy-Weinberg proportions (homologous association) or gametic disequilibria (non-homologous association) are disregarded. Thus little is known about patterns of population differentiation at higher levels of genetic integration nor the causal forces.SD. A measure of covariation compares patterns between levels. To show the significance of the observed differentiation among possible gene associations, a special permutation analysis is proposed. Applying this approach to published genetic data on oak, the differentiation is found to increase considerably from lower to higher levels of integration, revealing variation in the forms of gene association among populations.To fill this gap, a conceptual approach to the description and analysis of patterns of genetic differentiation at arbitrary levels of genetic integration  is introduced. Measurement of differentiation is based on the measure Δ of genetic distance between populations, which is in turn based on an elementary genic difference between individuals at any given level of genetic integration. It is proven that Δ does not decrease when the level of genetic integration is increased, with equality if the gene associations at the higher level follow the same function in both populations . The pattern of differentiation is described using the matrix of pairwise genetic distances Δ and the differentiation snail based on the symmetric population differentiation ΔThis new approach to the analysis of genetic differentiation among populations demonstrates that the consideration of gene associations within populations adds a new quality to studies on population differentiation that is overlooked when viewing only gene-pools. Most biological species are subdivided into populations that are more or less strongly connected by gene flow. This facilitates a species' persistence via adaptive differentiation to local conditions, which in turn serves to maintain genetic variation for future adaptational processes. This concept of species is reflected, for example, in meta-population analysis with its special emphasis on extinction-recolonization dynamics (see  for a stvs. diplophase),(1) the developmental stage (chiefly haplophase (2) the genetic traits under consideration at this stage, andgene association in this paper.(3) the ways in which the different states of these genetic traits in the populations are associated to form the genetic types  at this stage, broadly termed genetic integration is used here to designate the combination or arrangement of these elementary objects "gene" into the haplotypes of gametes, into the genotypes at diploid (or polyploid) nuclei of diplophase individuals, or into the cytotypes of mitochondria or plastids, for example. Accordingly, each level of genetic integration usually corresponds to a developmental stage or an organelle that is characterized by special combinations of genes. In general, traits are genetic only if they are inheritable, and the goal of inheritance analysis is to identify genes as the basic units of inheritance. The term The main motivation for this paper was the realization that impacts of particular forces, selective or not, on population differentiation may not be observable at every level of genetic integration. Measurements of differentiation among populations based on gene frequencies, for example, provide no specific insights into the effects of mating systems nor of epistatic interaction on population differentiation. This is due to the fact that gene frequencies refer to the lowest level of genetic integration, namely its absence. This level, which is commonly addressed as a population's gene-pool, is conceived to consist of the set of all individual genes present in the population members for a specified set of genetic traits. Genetic studies of population differentiation are almost always based on this "beanbag" . The purpose of using real data is to show how insights can be gained directly from observations without limitation to particular models, the testability of which may be difficult. It turned out that the large increases in differentiation between levels that were observed in the real data were not producible in numerous simulations of simple selection models, indicating that these models cannot explain the complexity of the real data. Studies of the behavior of this measure using simulated data from increasingly complex models will be the subject of a future paper.In the present paper, a new approach to differentiation analysis is presented that applies a conceptually argued measure of differentiation Δet al. 10] it isProblem"  by linea )SD. This tells us not only that the random generation of gene association never yielded Hardy-Weinberg structures for all loci in all four stands simultaneously. Neither was any other form of homologous association realized simultaneously that leaves differentiation unchanged . Furthermore, all non-homologous associations showed a considerable additional increase in differentiation over the homologous associations, as is seen in the wide separation of the range of differentiation for the single-locus diplophase from the range for the multilocus diplophase. Remarkably, both ranges of differentiation are quite narrow. These results indicate that the increases in differentiation that are realizable by homologous and non-homologous gene association can be tightly restricted by the genic composition of the populations. In such cases, equal differentiation at consecutive integration levels may not be achievable. Thus it appears that differentiation among populations with respect to their forms of gene association may be a normal occurrence. This insight questions the common practice of restricting the measurement of population differentiation to the allelic level (e.g. FST), thereby ignoring the considerable effects of gene association on population differentiation. This analysis is the first of its kind. Therefore, we cannot venture a prediction about whether the above findings on covariation between levels of integration constitute a general trend. It is conceivable, for example, that these findings are mainly determined by the conspicuously large polymorphism characteristic of the microsatellite markers used in this study. Other genetic markers may tell different stories.When comparing the observed differentiation to that producible by gene association in the stands, all 10 000 permutations agreed with the observation by showing much higher differentiation among the single-locus diplophases than among the gene-pools, both for the mean pairwise genetic distance and the symmetric population differentiation ΔThis new approach to the analysis of genetic differentiation among populations demonstrates that the consideration of gene associations within populations adds a new quality to studies on population differentiation that is overlooked when viewing only gene-pools.Proposition 1: P and Q at any L gene loci (L For any two populations ≥ 1) of equal degree of ploidy is not less than the distance between the corresponding gene pools p and q, respectively, that is,where the difference between genetic types  is measured by the elementary genic difference d.Gx or Gy denote the genetic types of the individuals at L gene loci of degree of ploidy N = 1, yielding K = LN genes per individual. For the relative frequencies P(Gx) and Q(Gx) of type Gx in the two populations (by some ordering), denote the frequency structure of the L-locus types as P and Q. Call the ith allele at the l-th locus Ai;l. Term the frequency structure of the gene-types Ai;l in the L-locus gene-pool as p and q. A shift transformation s decomposes the set of all genetic types on the basis of their relative frequencies into three sets: The source types Gx for which P (Gx) > Q(Gx) holds, i.e., that show an excess in the first population with respect to the second; the sink types Gx for which P (Gx) <Q(Gx) holds, i.e., that show a deficit in the first population; and those for which P(Gx) = Q(Gx) holds. In general terms, the excess of type Gx is quantifiable as P (Gx) - min{P (Gx), Q(Gx)} ≥ 0, with equality to 0 if P(Gx) ≤ Q(Gx). Likewise, the deficit of type Gx is quantifiable as Q(Gx) - min{P (Gx), Q(Gx)} ≥ 0, with equality to 0 if P(Gx) ≥ Q(Gx). For all types Gx, s fulfills:Whereas the equality in Proposition 1 follows from the text, proof of the inequality in Proposition 1 depends on a lemma that applies the following notation: For two populations s is the relative frequency among all individuals in population Gx to type Gy.where: Lemma 1: Consider any shift transformation s between the L-locus genetic structures. The genetic distance between the corresponding allelic structures pl) (and ql) is the number of genes of allelic type Ai;l in type Gx.Proof: Note that since an allele Ai;l can be present in both source and sink types, α > 0 and α > 0 can hold simultaneously. It follows that■s > 0 is true only if Gx is a source type and Gy a sink type. Thus α quantifies the total number of Ai;l-genes in the original (source) types of all shifted individuals, divided by the total number of genes at locus l in Population N· population size). Analogously, α quantifies the number of Ai;l-genes in the new (sink) types of all shifted individuals, divided by the same total number of genes. Their difference is the net frequency with which this allele was shifted.Note that Proof of Proposition 1: For any shift transformation s, it follows from Lemma 1 and the definition of the α that:d in the text. Since this holds for any shift transformation, it also holds if s is a minimum shift transformation, in which case ∑x,yd·s = Δ. Therefore, it follows that: The final equality follows from the definition of Ai;l, the expressionIn Proposition 1, equality holds if and only if for each gene-type Gx, Gy. This distinguishes three special groups of genes: Genes Ai;l for which the expression equals zero for all pairs of types Gx, Gy, implying that Ai;l is equally frequent in the two populations and therefore shows no net shift; genes Ai;l for which the expression is ≥ 0 but not ≡ 0 for all x, y, that is, that are never less frequent in source types Gx than in the corresponding sink types Gy, making them source genes; genes Ai;l for which the expression is ≤ 0 but not ≡ 0 for all x, y, making them sink genes.  > 0 and s > 0.)has the same sign for all pairs of types Proposition 2: For any two populations and , the distance between the (multilocus) genetic structures P and Q at any L gene loci (L ≥ 1) of equal degree of ploidy N ≥ 1 is not less than the mean distance between the corresponding single-locus structures Pl) (and Ql) be a shift transformation between the L-locus genotypic structures. Denote the various L-locus types as Gx or Gy, and write each type Gx as the "product" l = 1 and its projection L - 1)-locus type. Denote the single-locus types at locus l as The validity of Proposition 2 for l in the source type Gx and Gy.as the marginal sum of all shifts that involve the type Lemma 2 The difference between the marginal sums for any u equals the net shift  for any shift transformation sl at the locus.Proof: For the l-th locus it holds that:Their difference equals:sl at a locus l, since:The same difference results for any shift transformation ■Even though marginal sums share this property with any shift transformation at the locus, the following lemma shows that marginal sums may not specify a shift transformation.Lemma 3: The marginal sums  of all types  at locus l may shift an amount that is in excess of the amount required of any shift transformation at the locus.Proof: The total amount shifted away from any type l equalsBy the same reasoning, the amount received by These inequalities contradict the equality required of a shift transformation.   ■Lemma 3 shows that the marginal sums may shift too much, and it is easy to construct examples for which this is the case. Excess amounts must be due to the appearance of one or more single-locus types both in two-locus source types and in two-locus sink types. This makes them both sources and sinks in the marginal sums, in violation of the properties of a shift transformation. The three ways in which a type i.e., amount sent away as a source minus the amount received as a sink.The following lemma shows how to eliminate all ambivalent source/sink relationships from the marginal sums without changing the net amount shifted, Lemma 4: The marginal sums  of all types  at locus l can be used to construct a quasi-shift κl(Pl) with the following three properties:Proof by construction: Consider the following algorithm:START: Set u, v.Step 1: If Step 2: If a ≠b, setwhere it follows thatSetRepeat for an additional pair of types that fulfill the condition. If none exist, go to Step 3.Step 3: If a, b, c, subtract M to the "direct route" from i.e., setd is a metric distance, implyingBecause it holds thatfrom which it follows thatSetSTOP.If At each step, u, meaning that no type is both a source and a sink. The net quasi-shift u remains constant throughout the algorithm, equaling κl for locus l for which it holds thatProof: As proven in Lemma 4, for the quasi-shifts and either These three cases can be combined to the expressionκl be a shift transformation between the two L-locus genotypic structures. Denoting the L-locus types as Gx or Gy, their projections to locus l as l as sl(Pl) is the shift transformation constructed in Lemma 4. Since the inequality holds in particular if s is a minimal shift transformation, it follows, as claimed, that    ■where l = 1,...,L specify a minimal shift transformation, i.e., when Equality holds in Proposition 2 whenever the marginal sums for each locus HRG conceived of the approach and drafted the Background and Methods. EG formulated and proved the Theorem, programmed the software, analyzed the data, and drafted the Results and Appendices. Both authors read and approved the final manuscript.


Lasius neglectus, is the most recently detected pest ant and the first known invasive ant able to become established and thrive in the temperate regions of Eurasia. In this study, we aim to reconstruct the invasion history of this ant in Europe analysing 14 populations with three complementary approaches: genetic microsatellite analysis, chemical analysis of cuticular hydrocarbon profiles and behavioural observations of aggression behaviour. We evaluate the relative informative power of the three methodological approaches and estimate both the number of independent introduction events from a yet unknown native range somewhere in the Black Sea area, and the invasive potential of the existing introduced populations.The invasive garden ant, L. neglectus did not separate into clear supercolonial associations, as is typical for other invasive ants.Three clusters of genetically similar populations were detected, and all but one population had a similar chemical profile. Aggression between populations could be predicted from their genetic and chemical distance, and two major clusters of non-aggressive groups of populations were found. However, populations of L. neglectus in Europe likely arose from only very few independent introductions from the native range, and that new infestations were typically started through introductions from other invasive populations. This indicates that existing introduced populations have a very high invasive potential when the ants are inadvertently spread by human transport.The three methodological approaches gave consistent and complementary results. All joint evidence supports the inference that the 14 introduced populations of  Exotic species are a major threat to biodiversity and human welfare, and infestations by invasive species have generally proven difficult and expensive to exterminate -3. The cMyrica faya) to aquatic animals such as the zebra mussel (Dreissena polymorpha) [Solenopsis invicta, the Argentine ant Linepithema humile and the Pharaoh ant Monomorium pharaonis [Invasive species are not limited to specific taxa or habitats and range from terrestrial plants such as the fire tree (ymorpha) . Social ymorpha) . The besharaonis . HoweverLasius neglectus was described in Hungary [L. neglectus is well adapted to cold winters and is currently spreading quickly throughout Europe and Asia with 30 populations known in 2000 and 100 populations identified to date [L. neglectus typically occurs in human-disturbed urban habitats such as parks, greenhouses and gardens [This picture changed in 1990 when the invasive garden ant  to date ), which  to date ,22. L. n gardens .L. neglectus forms large networks of interconnected and mutually tolerant nests, each of which contains multiple queens [L. neglectus [Similar to other invasive ants ,23, L. ne queens . This 'se queens . Supercoe queens . In addie queens -29, and eglectus . It is teglectus ,32.Invasive ants have generally lost the typical mating flights that characterise most ants: they mate inside the nest and found new colonies by nest-budding ,23. For L. neglectus in Europe. We also try to obtain an estimate of how many independent introductions from the native range might have occurred, and how often new populations might have arisen from already existing invasive populations. This type of information is pertinent in the development of efficient biocontrol strategies against the further spread of the invasive garden ant.The geographic extension of invasive ant supercolonies (either continuous or disjunctive) is widely used to reconstruct their invasion history  and reprFST) was on average 0.334  clusters and populations not assigned to clusters was 0.345; pairwise values ranging from 0.108 to 0.551, all significant).As expected for unicolonial ant populations ,39, the F104,334 = 6.27; P < 0.0001). The Warsaw population with the additional single hydrocarbon peak 15* was considerably separated from all other populations, so that all nests of this population had a 100% posterior probability to be correctly assigned to this particular population based on their chemical profiles. In the remaining populations, correct assignments were in the range 35–97%, with a total of 11 out of 68 nests misclassified; see Additional file Gas chromatography-mass spectrometry (GC-MS) analysis of cuticular compounds produced a total of 24 different hydrocarbons, of which 23 were consistently found in each population, and with the remaining single compound (peak 15*) only present in the population from Warsaw, Poland  nor between nests of the same population (n = 179), confirming our genetic results that populations consisted of single supercolonies. In the between-population tests, aggression was detected in none of the replicates (mean 7) in 14% of the 91 independent pairwise combinations of populations , but always occurred in 19% of the combinations. The remaining 67% showed aggression in some replicates, but not in others. However, the variation between population pairs was significantly higher than the variation between replicates . Based on these data, we generated an 'aggression network' , as expected under a scenario of jump dispersal. Also, the chemical distances between populations were not significantly correlated with geographic  or genetic distances . However, the behavioural distance between populations, that is, the pairwise aggression level, was significantly correlated with geographic , chemical  and genetic distance between populations . As it turned out, aggression was lower when populations were geographically closer, chemically more similar and genetically more related  and positively correlated with present population size . We found similar results for correlations of the allelic richness for each population based on the microsatellite analysis, with both year of detection  and population size , as well as a high correlation between allelic richness and chemical within-population variation . Also, the number of polymorphic loci  estimate. As all populations were assumed to have started with a small founder group of a single or very few nests, the present size of a population was also expected to be an indicator of age and both were indeed highly correlated  reconstruct the likely introduction history of Wasmannia auropunctata in the New Caledonia archipelago.The chemical analysis separated the population in Warsaw, Poland, from all other populations, a split that was not detected by genetic analysis, but that was confirmed by aggression data (see below). All other populations showed high similarities in their chemical profile, consistent with a possible joint origin or with similar environmental conditions. A comparable degree of chemical uniformity was found by Errard et al.  when anaL. neglectus populations were very low in our laboratory experiments, which is consistent with the generally high similarities in the genetic and chemical analyses. Remarkably, the observed aggression patterns could be predicted by the genetic and chemical distances between the populations, as well as by their geographic distance. Although Mantel tests do not directly allow testing of the proportions of variance explained by the different predictor variables, the partial correlation coefficients suggest that genetic distance was the best predictor of aggression, followed by chemical and geographic distances. This is in line with other studies showing that aggression is based on chemical recognition cues encoded in the ants' hydrocarbon profiles [Overall aggression levels between profiles ,41 and sprofiles -44. HoweL. neglectus. Only three populations, Bellaterra, Edirne 2 and Warsaw, performed aggression in all replicates towards all other populations  were recently evaluated by Williamson-Natesan [M-ratio was most likely to detect bottlenecks when they lasted for several generations, when the population had recovered and when the pre-bottleneck population sizes (θ) were large. The heterozygosity excess method, on the other hand, was better at detecting bottlenecks when they were recent, less severe and when pre-bottleneck population sizes were small. The low number of detected bottlenecks in the present study could be an artefact of our analysis as many of the young populations of the invasive garden ant, however, have few polymorphic loci, which in itself is an independent indication of genetic bottlenecks, but it compromises the detection power of these programs [It was unexpected that so few populations showed detectable signs of a recent genetic bottleneck, as introduced populations in general show low levels of genetic diversity , which i-Natesan , who conprograms . It is tprograms  on silveL. neglectus are characterised by the lowest chemical variation and genetic diversity in terms of allelic richness (strongest evidence), the number of polymorphic loci and also the detection of genetic bottlenecks. These data and the considerable similarity between introduced populations make a high number of independent introductions from the native range unlikely. As the founder populations of all extant invasive populations were apparently rather similar, the patterns observed are best explained by assuming that younger populations tend to arise as daughter populations from older introduced populations, consistent with the allelic subset pattern discussed above. This implies that L. neglectus experienced serial genetic bottlenecks, which explains the low genetic diversity of young infestations compared with older invasive populations. The higher genetic diversity in the older populations is unlikely to be a result of accumulation of mutations after population founding, as the differences in age are only a few decades. The total evidence available thus allowed us to tentatively infer the most likely chains of ancestry across the investigated 14 populations  tested the suitability of the within-population variation of cuticular hydrocarbons. We found that this chemical variation behaves in a very similar manner to allelic richness and, at least in our study, similarly correlates with both the age and size of populations. Our data showed that the younger populations of s Figure  as a worTo the best of the authors' knowledge, this is the first study to simultaneously implement genetic, chemical and behavioural methodology to assess the affiliation of populations of invasive ants to supercolonies, as similar studies mostly rely on aggression behaviour and genetic analyses. We found that the three approaches revealed consistent but also complementary data and that both genetic and chemical variation within populations can be used as a powerful tool for the detection of founder effects. Still, microsatellites seem to be a more powerful tool to reconstruct introduction histories, as they moreover reveal the possible direction of spread Figure . The cheL. neglectus have likely arisen from other already established invasive populations. This implies that many more infestations of the invasive garden ant are likely to have taken place already, but have remained undiscovered owing to the usual lag phase for invasive species [L. neglectus do expand very fast [Our complementary approach revealed that all extant European populations of the invasive garden ant are probably derived from very few independent introductions out of the hitherto unknown native species range. Even if we do not yet know where the native populations of this new pest ant can be found, the development of highly variable microsatellite markers and the genetic 'barcode' of the introduced sites that we have obtained in this study will allow potential candidates for the native population from which introductions into Europe have occurred to be tested quickly. Our data indicate that most of the younger introductions of  species . Many ofery fast ,20,50 anery fast . We hopeery fast .L. neglectus was collected from 14 populations .DNA was extracted from 30 workers (5 nests and 6 workers/nest) per population, that is, from a total of 420 individuals. From each individual, the mesosoma was crushed in 200 μl of a 5% Chelex solution and boiled at 99°C for 15 min. For each sample six polymorphic nuclear microsatellite loci were amplified, three of them originally developed for L. niger , and thrk') and pairwise genetic distances between populations (FST) were calculated in FSTAT 2.9.3.2 [P-values give the probability of specific populations separating into one or more clusters of populations.The genetic relationship between nestmate workers was assessed by measuring intra-nest regression relatedness using RELATEDNESS v. 5.0.8  in all b 2.9.3.2  using 20 2.9.3.2 . Genetic 2.9.3.2  was usedL. neglectus. The two programs differ in that M RATIO is more likely to detect older bottleneck events than BOTTLENECK. M RATIO exploits the fact that allele distributions tend to shift after a genetic bottleneck and that the number of alleles is expected to decline faster than the overall range size of alleles. The program thus compares the ratio M  to a distribution obtained by simulating 10,000 runs of a population at equilibrium. Based on earlier estimates of the effective population size ne of a L. neglectus population [ne = 5000. The mutation rate was set at μ = 10-4/locus/generation, which is the commonly used mutation rate for microsatellite loci in ants [ne*μ = 2. BOTTLENECK, on the other hand, detects divergences from allelic equilibrium in populations that have undergone a recent decrease in effective population size through estimating across 1000 permutations: (1) any reduction in genetic diversity, that is, a lower number of alleles than expected; and (2) any excess of heterozygosity per locus compared with an equilibrium population. In both software packages the two-phased model (TPM) was chosen as it provided the best fit for the evolution of microsatellite markers [The populations were tested for the occurrence of genetic bottlenecks using both M RATIO  and BOTTpulation ,65 and a in ants ,67, resu markers .The cuticular hydrocarbon profiles of 68 nest samples from the 14 populations  were analysed. Immediately after transportation of the live ants to the laboratory, five ants per nest were placed together in glass vials , and stored at -20°C until solvent extraction. To extract cuticular compounds from the ants, pentane (50 μl) was added after the individuals had been transferred into small glass inserts (200 μl). After 10 min  the ants were removed from the pentane and discarded. The vials were left open at room temperature until all of the pentane had evaporated. The dry extracts were kept frozen (-20°C) until they were analysed using GC-MS.Shortly before GC-MS analysis, the samples were re-diluted in 20 μl of hexane. We injected 2 μl of each extract (split-less and via an auto-sampler) onto the GC-MS (Agilent Technologies 6890N coupled to a 5973N MSD) equipped with a HP-5 column . The initial oven temperature was set at 70°C. After 1 min the oven temperature was increased to 280°C at 20°C/min, after which it was increased further to 340°C at 2°C/min, and kept at this temperature for another 5 min. Other machine settings and characterisation of compounds followed the methods described by Lommelen et al [Lasius species [Cuticular hydrocarbons  were characterised using standard MS databases and diagnostic ions and by determining Kovats indices . The pos species . The finFor all 68 nest samples, the area below each peak was integrated  and the relative proportions of the 24 hydrocarbon peaks were analysed using PCA in STATISTICA 6 (Statsoft) as in D'Ettorre and Heinze  revealinn = 179). In addition, within-nest aggression tests were performed with two workers collected from identical nests . Aggression was never observed between any nests within the same population. We therefore chose one nest per population at random, with which we performed between-population tests. The 14 populations allowed for 91 independent pairwise combinations and each was tested in 7 replicates on average (range 3–12). As the Edirne 3 population behaved identically to the Edirne 1 population in all test trials we did not perform all replicates for Edirne 3. Taken together, a total of 579 aggression tests were carried out.Within the first five weeks after the ants had been collected from the field, aggression tests were carried out in the laboratory between pairs of workers. To test whether single populations consisted of single supercolonies, the five sampled nests were tested in all pairwise combinations . The ants were then put into an 'arena' , and observed for 10 min at an ambient temperature of 22.5 ± 2°C following Giraud et al . The freFST), chemical  and behavioural distance (as proportion of aggressive interactions) were carried out in FSTAT 2.9.3.2 using 2000 randomisations. Two-tailed P-values are reported.Partial Mantel correlation tests using distance matrices from inter-population geographic (in kilometres), genetic  Pairwise genetic distances (FST) between sampled populations of L. neglectus, using the six microsatellite loci  are given for each plot. Mantel tests showed that correlation coefficients were only significant for behavioural distance versus geographic, genetic and chemical distance.ci Table . Bold fis Figure . (d) Pais Figure . (e) ParClick here for fileL. neglectusCuticular hydrocarbon compounds of . Peak number , this posterior probability, as well as the identification of the other population, is given.Click here for file