Genetic studies have identified substantial non-African admixture in the Horn of Africa (HOA). In the most recent genomic studies, this non-African ancestry has been attributed to admixture with Middle Eastern populations during the last few thousand years. However, mitochondrial and Y chromosome data are suggestive of earlier episodes of admixture. To investigate this further, we generated new genome-wide SNP data for a Yemeni population sample and merged these new data with published genome-wide genetic data from the HOA and a broad selection of surrounding populations. We used multidimensional scaling and ADMIXTURE methods in an exploratory data analysis to develop hypotheses on admixture and population structure in HOA populations. These analyses suggested that there might be distinct, differentiated African and non-African ancestries in the HOA. After partitioning the SNP data into African and non-African origin chromosome segments, we found support for a distinct African (Ethiopic) ancestry and a distinct non-African  ancestry in HOA populations. The African Ethiopic ancestry is tightly restricted to HOA populations and likely represents an autochthonous HOA population. The non-African ancestry in the HOA, which is primarily attributed to a novel Ethio-Somali inferred ancestry component, is significantly differentiated from all neighboring non-African ancestries in North Africa, the Levant, and Arabia. The Ethio-Somali ancestry is found in all admixed HOA ethnic groups, shows little inter-individual variance within these ethnic groups, is estimated to have diverged from all other non-African ancestries by at least 23 ka, and does not carry the unique Arabian lactase persistence allele that arose about 4 ka. Taking into account published mitochondrial, Y chromosome, paleoclimate, and archaeological data, we find that the time of the Ethio-Somali back-to-Africa migration is most likely pre-agricultural. The Horn of Africa (HOA) occupies a central place in our understanding of modern human origins. This region is the location of the earliest known modern human fossils, a possible source for the out-of-Africa migration, and one of the most genetically and linguistically diverse regions of the world. Numerous genetic studies over the last decades have identified substantial non-African ancestry in populations in this region. Because there is archaeological, historical, and linguistic evidence for contact with non-African populations beginning about 3,000 years ago, it has often been assumed that the non-African ancestry in HOA populations dates to this time. In this work, we find that the genetic composition of non-African ancestry in the HOA is distinct from the genetic composition of current populations in North Africa and the Middle East. With these data, we demonstrate that most non-African ancestry in the HOA cannot be the result of admixture within the last few thousand years, and that the majority of admixture probably occurred prior to the advent of agriculture. These results contribute to a growing body of work showing that prehistoric hunter-gatherer populations were much more dynamic than usually assumed. The timing and extent of migration and admixture are questions that are central to the entire scope of human evolutionary history from the origin of our species to the present day. The most important event underlying human population structure is the origin of anatomically modern humans in Africa and their subsequent migration around the globe Populations in the Horn of Africa  have substantial non-African ancestry However, more recent archaeological research shows that non-African influences in the HOA were limited and transient. Of the early first millennium BCE inscriptions in non-African scripts complete enough to identify a language, only a small proportion are written in a non-African (South Arabian) language - the majority are written in indigenous proto-Ge'ez Archaeological data indicate trade between the HOA and Arabia by at least 8 ka Y chromosome data are also suggestive of at least two episodes of non-African migration into the HOA prior to 3 ka. First, HOA populations carry E-M78 Y chromosomes at high frequencies In order to investigate the discrepancy among the archaeological, historical, mitochondrial, Y chromosome, and genome-wide data for recent vs. more ancient evidence of admixture in the HOA, we generated new genome-wide SNP data for a Yemeni sample and analyzed these new data with publicly available data For these analyses, we generated new genome-wide SNP data using the Illumina 370K array from 61 Yemenis, chosen to represent all geographic regions of the country. These new data were merged with published data from the HOA We first investigated the position and dispersion of HOA populations in the genetic landscape in a multi-dimensional scaling (MDS) analysis of pairwise identity by state (IBS). Consistent with prior analyses of global genome-wide genetic variation In order to better understand the genetic structure of HOA populations, we analyzed the SNP data using the model-based, maximum likelihood ancestry estimation procedure implemented in the ADMIXTURE software There are ten inferred ancestry components (IACs) that are consistent across all three focal K values  and are From K = 10 to K = 12, the changes in ADMIXTURE results occur primarily in the HOA, where two new IACs appear at high frequencies . At K = a priori is unknown. In fact, there is no true K value in most cases because the simultaneous diversification model fit by ADMIXTURE is a poor reflection of human population history. Therefore, rather than take the ADMIXTURE IACs for one of K = 10,11,12 at face value, we used these estimates as hypotheses about the genetic structure of HOA populations and then evaluated these hypotheses in separate analysis.Confident determination of the appropriate K value in an ADMIXTURE-like analysis in most human population genomic studies is problematic because the information required to set K 3f-statistic test, the D-statistic test, and a weighted LD test (K = 10) The HOA African ancestry is very similar to that found in neighboring Nilo-Saharan speaking populations. There is a distinct, differentiated African ancestry in HOA populations (the Ethiopic IAC).And the following hypotheses for the non-African ancestry in the HOA:First, for all focal K values, the ADMIXTURE analysis suggests that many HOA populations have admixture between African and non-African ancestors in their history. To test this, we conducted three formal tests for admixture: the  HOA populations experienced admixture with one or more non-African populations carrying high levels of the Arabian and Maghrebi IACs along with small amounts of the Eurasian IAC.(K = 12) There is a distinct non-African ancestry in the HOA that constitutes most of the non-African ancestry .To evaluate these ADMIXTURE-derived hypotheses, we used the CHROMOPAINTER software The hypothesis that African ancestry in the HOA is not distinct from that found in neighboring Nilo-Saharan speaking populations (hypothesis 1A above) requires a history of homogenizing inter-population migration or relatively recent common origin. In the case of homogenizing gene flow, a correlation between genetic and geographic distance might be expected, with nearby populations more alike than distant populations. We calculated within and between population gene identity  for all the populations included in the 4K partitioned dataset. We then used the between population gene identity estimates among the predominantly Nilo-Saharan ancestry Anuak, Gumuz, South Sudanese, and the African ancestry partition of the Amhara, Ari, Oromo, Somali, and Tygray to test for a relationship between genetic and geographic distance. No significant relationship was recovered  .GT = 0.013, p<0.001). We also fit the HOA data to two population tree models, one without substructure and one with linguistically defined subgroups (−8). Next, we tested for the presence of linguistically delineated subgroups within the Anuak, Gumuz, and South Sudanese. Most southern Sudanese populations speak languages in the Nilotic branch of the Nilo-Saharan language family and the Anuak language is also a Nilotic language GT = 0.024, p<0.001) and the population tree with linguistically defined subgroups  and a micro level  . Population tree models with these groupings are a significantly better fit to the data than a tree without subgroups   . The treThese results support the hypothesis from ADMIXTURE K≥11 of a distinct African ancestry with a long history in differentiated HOA populations (hypothesis 1B above) over the hypothesis from ADMIXTURE K≤10 that African ancestry in the HOA is not substantially differentiated from that found in neighboring populations (hypothesis 1A). In fact, our results suggest a rather more complicated history for these regional populations. Studies of further population samples from ethnic groups in and near the western and southern edges of the Ethiopian escarpment are sure to be interesting.The ADMIXTURE-derived hypothesis that non-African ancestry in the HOA derives from admixture with a population or populations with high levels of the Arabian and Maghrebi IACs and some of the Eurasian IAC (hypothesis 2A above) suggests that HOA populations should have higher levels of shared gene identity with populations with higher proportions of those ancestries. To evaluate this prediction, we examined the relationship between shared gene identity and the ADMIXTURE-estimated proportion of the Arabian, Eurasian, and Maghrebi IACs in MENA population samples for each of the non-African ancestry partitions of the admixed HOA populations using varying intercepts linear models. Only the Maghrebi IAC analysis shows the expected relationship: shared gene identity between HOA and MENA populations increases as the proportion of Maghrebi ancestry increases . ContrarNext, we looked for evidence for extended inter-population gene flow in the correlation of geographic distance and shared gene identity. We found no relationship between geographic and genetic distance within either HOA or MENA populations. We then examined this relationship for HOA populations to North African , Levantine , and Arabian  populations . For NorGT = 0.010, p = 0.066). We then used the ADMIXTURE results to inform subgroup formation. At K = 12, the Amhara, Tygray, Oromo, and Afar all have similar proportions of non-African ancestries that differ from that seen in the Ari and Somali . In addition, the population tree with these geographic subgroups  and the population tree with these subgroups (−16). Finally, putting all of the populations together in an AMOVA analysis, we find significant differences between HOA and MENA subgroups at both a macro level (HOA vs MENA)  and a micro level  . Population tree models for both the simple (HOA vs MENA) and more complex  groups are a significantly better fit to the data than a tree without subgroups  than population groups across the MENA region . All together, these results offer greater support to the hypothesis from ADMIXTURE K≥12 that there is a distinct non-African ancestry in the HOA that is well-differentiated from the non-African ancestry in neighboring Middle Eastern and North African populations (hypothesis 2B).Even though there is strong evidence for admixture between HOA and MENA populations, there is also clearly detectable substructure both within and between the HOA and the Middle East and North Africa. If the majority of the non-African ancestry in the HOA had entered during the last few thousand years (hypothesis 2A above), then population groups should be less differentiated within the HOA then within MENA samples. This expectation is reinforced by the smaller geographic area of sampling within the HOA when compared to the geographic spread of the MENA samples. However, what we observe is that population groups within the HOA are more differentiated (ΦWe used two methods that model the pattern of linkage disequilibrium (LD) expected to result from admixture to estimate the date of admixture for all study populations in which we found statistically significant signals of admixture: ROLLOFF These relatively recent dates are not consistent with our results showing a distinct, differentiated non-African ancestry in the HOA. To be sure, the greater shared gene identity between HOA populations and MENA populations with higher proportions of the Maghrebi IAC  and the In order to seriously entertain the hypothesis that most of the non-African ancestry in the HOA predates the last few thousand years, we must understand why the ROLLOFF and ALDER admixture date estimates are all relatively recent. To do so, we performed simulation tests of ROLLOFF and ALDER in episodic admixture scenarios. To start, we simulated two episodes of admixture, with the first (earliest) episode between 50 and 200 generations ago  and the second (more recent) episode at either 10 or 30 generations ago (300 or 900 years). We found a strong bias towards the most recent admixture date for both ROLLOFF and single-episode ALDER . To inveTo get an intuition for how ROLLOFF and ALDER perform for truly ancient admixture followed by more recent admixture, we simulated 50% admixture between 1,500 and 35,000 years ago, followed by 10% admixture at 900 years ago . As in tIn order to evaluate the hypothesis that there were two or more distinct episodes of non-African admixture in the HOA, with the Ethio-Somali admixture occurring during an earlier episode, we conducted four analyses. First, we looked at the distribution of IACs among HOA populations from the K = 12 ADMIXTURE results. If there have been successive episodes of admixture into a culturally diverse region, we expect that different populations will have different histories of admixture Second, at the time of admixture, there would be a great deal of variation among individuals in the amount of ancestry from introgressing populations. After admixture ends, there will be a decrease in variation among individuals in the amount of admixed ancestry over time FST, effective population size, and divergence time FST values for the ADMIXTURE IACs reflect post-divergence population isolation and could be used to construct a bifurcating population tree that is a good fit for the data. If the population tree model is generally valid, but there has been some post-divergence migration, then the fit of the data to the tree model will not be good and the true divergence date would have been earlier than what we estimate here. When we evaluate the fit of the non-African IACs to a population tree model . The key lines of evidence that support a hypothesis of earlier admixture are that the Ethio-Somali IAC is broadly distributed across almost all ethnic groups in the HOA, consistent with an early entry into the region; that there is less inter-individual variance in Ethio-Somali IAC among individuals within ethnic groups than in Arabian or Eurasian IACs, suggesting that Ethio-Somali admixture predates the Arabian and Eurasian admixture; that the Ethio-Somali IAC is estimated to have diverged from all other non-African IACs by at least 23 ka; and that the Ethio-Somali IAC does not contain the unique Arabian lactase persistence allele that arose about 4 ka. In combination, these data suggest that the Ethio-Somali ancestors admixed with African-origin HOA ancestors sometime after 23 ka, but before the Middle Eastern admixture during the last few thousand years.Agriculture was established in the HOA by at least 7 ka Paleoclimate data offer some information on time ranges when human migration back-to-Africa would be most likely to succeed. During arid periods in North Africa and the Middle East, most plausible routes into Africa experienced desertification, reducing the likelihood of successful migration. In our time frame of interest, there have been two major peaks of aridity in the region, the Last Glacial Maximum (LGM: ∼21.5 ka) and the Younger Dryas (YD: ∼12.5 ka), during which successful human migrations would not have been likely There is abundant archaeological material in the HOA dating to between 5 and 30 ka, but most of the published literature is descriptions of surface surveys or test excavations Like the Ethio-Somali, the Maghrebi IAC in North African populations derives from a early back-to-Africa migration FST value from the ADMIXTURE estimated ancestral allele frequencies is with the Maghrebi  and are all assumed to be in Hardy-Weinberg equilibrium FST among ancestral populations should be interpreted with care.A single prehistoric migration of both the Maghrebi and the Ethio-Somali back into Africa is the most parsimonious hypothesis. That is, a common ancestral population migrated into northeast Africa through the Sinai and then split into two, with one branch continuing west across North Africa and the other heading south into the HOA. For the Ethio-Somali, the lowest Maghrebi , which iMitochondrial M1 and U6 lineages – sub-clades of mitochondrial haplogroups that are otherwise found only in Eurasian populations – are found both in North Africa and the HOA We find that most of the non-African ancestry in the HOA can be assigned to a distinct non-African origin Ethio-Somali ancestry component, which is found at its highest frequencies in Cushitic and Semitic speaking HOA populations . In addiWe close with a provisional linguistic hypothesis. The proto-Afro-Asiatic speakers are thought to have lived either in the area of the Levant or in east/northeast Africa Saliva samples were collected in Yemen in 2007 with informed consent under Western IRB approval, Olympia, WA. Subsequent analysis of anonymized SNP data was approved by the Lehman College IRB.http://dx.doi.org/10.5061/dryad.d9s74) Sixty-four Yemeni, chosen to represent all geographic regions of the country, were selected for SNP genotyping. Genomic DNA was extracted from saliva samples (DNA Genotek Oragene collectors) using the manufacturer's protocol. This DNA was genotyped using the Illumina 370k SNP chip by the University of Florida Interdisciplinary Center for Biotechnology Research Core Facility following the manufacturer's protocols. These new data are available from the Dryad Digital Repository  was performed upon a genome wide matrix of identity by state (IBS) for all individual pairs in the reduced-LD dataset using PLINK After phasing the 260K dataset using the haplotypes inference algorithm implemented in version 2 of the SHAPEIT software Using the 4K partitioned dataset, we evaluated the evidence for gene flow and population structure using Mantel tests, AMOVA, and population tree models. We tested for geographically mediated gene flow using Mantel tests of the correlation between genetic distance as measured by shared gene identity and geographic distance using the implementation in the R ADE4 package eN of 5,000, which is on the lower end of the eN values estimated for relevant HGDP populations FST as a measure of differentiation resulting from the equilibrium between gene flow and genetic drift that is discussed in the main text is Population divergence times of the ADMIXTURE-inferred ancestral populations were estimated using the relationship 3f-statistic, the D-statistic, and a weighted LD statistic 3f test requires a reference population for each, which need not be the actual admixture source. For sub-Saharan Africa reference populations, we used populations that showed very little admixture of ancestral population components in the ADMIXTURE analysis: Mbuti Pygmies, Ju/'hoansi, HapMap3 Yoruba, South Sudanese, and Ari Blacksmith. For non-African reference populations, we used the HapMap3 CEU, Gujarati, and Tuscan populations in addition to Basque, Turkey, and Sardinian. The 3f test was run for all other study populations for all possible pairs of reference populations. A strict Bonferroni correction was applied to control for multiple testing, only Z-scores less than −4 for the most negative 3f statistic for each test population were considered significant. For those populations with significant 3f statistics, the bounds of the admixture proportion were then estimated with the addition of a chimpanzee outgroup. The 3f tests on the 90K and 260K datasets have more power, but return almost exactly the same 3f statistic values , ), where the African reference populations are the same as for the 3f test. Since there is no indication in the literature of any African admixture in the Papuan population, any significantly positive D-statistic was taken as support for admixture between the test population and (a population related to) the Basque. For North African, Middle Eastern, and Eurasian test populations, the unrooted tree tested was , ), where the African reference populations are the same as before. Again, since there is no indication in the literature of any admixture between Papuans and Basque, any significantly positive D-statistic indicates admixture between the test population and an African reference population. A strict Bonferroni correction was applied to control for multiple testing, only Z-scores greater than 4 for the most positive D-statistic for each test population were considered significant. The D tests on the 90K and 260K datasets have more power but recover indistinguishable D statistic values . To verify the admixture date estimates calculated from the main (∼17K SNP) dataset are reliable, we ran ROLLOFF and ALDER on both the 90K and 260K datasets using the HapMap3 Yoruba and CEU as the reference populations. Using the main dataset, we estimate ROLLOFF admixture dates from 2.6–3.7 ka and ALDER admixture dates from 1.1–4.1 ka for admixed HOA population. The verification estimates are not meaningfully different from these, with ROLLOFF admixture dates from 2.6–3.7 ka and ALDER admixture dates from 1.2–3.3 ka for the 260K dataset . The second set of simulations used λ0 equal to 50, 100, 150, 300, 500, 650, 850, 1000, or 1150 generations and λ1 equal to 30 generations. Admixture proportion α0 was 0.50 and admixture proportion α1 was 0.10. Again, three independent replicates were performed for each combination of parameters . Admixture dates were estimated for the simulation data using ROLLOFF and ALDER with the remaining unadmixed CEU and Yoruba individuals as the reference populations. In addition, we reduced the simulated data to the 16,766 SNPs present in the main dataset used to estimate admixture dates for the study populations and estimated admixture dates using ROLLOFF and ALDER for the same set of reference population pairs.In our first set of simulations, we simulated admixture with λFigure S1ADMIXTURE-inferred population average ancestry components for K = 2–20. The Ethiopian-specific Ethiopic ancestry component (dark purple) first appears at K = 11 and is stable from K = 12–20. The back-to-Africa Ethio-Somali ancestry component (green) first appears at K = 12 and is stable from K = 13–20.(EPS)Click here for additional data file.Figure S2Cross-validation error for K = 2–20 from the ADMIXTURE analysis. Ancestry proportions were estimated for K values ranging from 2 to 20, and cross-validation error was calculated for each value of K. The cross-validation error was minimized at K = 12.(TIFF)Click here for additional data file.Figure S3Tests for geographically mediated gene flow within and between HOA and MENA populations. The relationship between shared gene identity and inter-population distance is shown within and between HOA and MENA populations for both straight line distances and distance calculated using a waypoint through Egypt (where appropriate).(EPS)Click here for additional data file.Figure S4ROLLOFF and ALDER estimates of admixture times for simulated episodic admixture. We simulated two instances of admixture between CEU and YRI source populations using the 260K SNP dataset and estimated the time of admixture using ROLLOFF and ALDER. The 260K SNP dataset was also pruned down to ∼17K SNPs (to match the main dataset used in this study) and admixture dates were estimated from this reduced data as well. Loess lines were fit for each set of estimates: ROLLOFF 260K & 17K, ALDER 260K & 17K (thick solid lines). Overall, there is little difference in the estimates from the 260K and 17K simulated datasets. Previous simulation studies have characterized the ROLLOFF estimate of admixture time in episodic admixture scenarios as intermediate between the true dates of admixture; to better understand what this means, we plotted the weighted arithmetic, geometric, and harmonic means of the simulated admixture times (thin dotted lines). The ROLLOFF and ALDER admixture estimates are always heavily biased towards the more recent admixture. (A) The first admixture event was simulated between 50 and 200 generations ago, followed by a second admixture at 10 generations ago. During both episodes, 10% YRI ancestry was admixed. (B) Same as A, but with 25% YRI ancestry at the first (earlier) admixture. (C & D) Same as A and B, but with the second (more recent) admixture at 30 generations ago.(EPS)Click here for additional data file.Figure S5ROLLOFF and ALDER estimates for simulated ancient admixture followed by more recent admixture. same methods were followed as described for (EPS)Click here for additional data file.Figure S6Hierarchical population tree models for the non-African inferred ancestry components. Using the non-African IACs from the K = 12 ADMIXTURE analysis, a series of increasingly structured population tree models were constructed, starting from the unstructured tree (A), continuing through intermediately structured trees (B–D) to a final, fully bifurcating tree model (E). The fit to the data improves significantly with each more structured tree. While the final fully bifurcating is a significantly better fit to the data than any less structured tree, it deviates significantly from a perfect fit to the data.(EPS)Click here for additional data file.Table S1Population samples included in the main 17K, 90K, and 260K SNP datasets.(XLSX)Click here for additional data file.Table S2Results of f3 test for admixture, with estimated bounds of admixture for significantly admixed populations.(XLSX)Click here for additional data file.Table S3Results of D statistic test for admixture.(XLSX)Click here for additional data file.Table S4Results of ALDER test for admixture.(XLSX)Click here for additional data file.Table S5Non-African ancestry proportion estimated for significantly admixed study populations.(XLSX)Click here for additional data file.Table S6Ancestry proportions for each study population from ADMIXTURE ancestry components.(XLSX)Click here for additional data file.Table S7Verification of f3 test results from main (17K SNP) dataset in verification 90K and 260K datasets.(XLSX)Click here for additional data file.Table S8Verification of D statistic test results from main (17K SNP) dataset in verification 90K and 260K datasets.(XLSX)Click here for additional data file.Table S9Verification of ALDER test results from main (17K SNP) dataset in verification 90K and 260K datasets.(XLSX)Click here for additional data file.Table S10Verification of ROLLOFF and ALDER admixture date estimates from main (17K SNP) dataset in verification 90K and 260K datasets.(XLSX)Click here for additional data file.Text S1Affinities of the Ethio-Somali ancestry component. Three different analyses demonstrate that the Ethio-Somali ancestry component that is found at high frequencies in many HOA populations has a non-African origin.(PDF)Click here for additional data file.


Culex pipiens complex includes the most widespread mosquito species in the world. Cx. pipiens is the primary vector of the West Nile Virus (WNV) in Europe and North America. Cases of WNV have been recorded in Italy since 1998. In particular, wet areas along the Po River are considered some of the most WNV affected areas in Italy. Here, we analyzed the genetic structure of ten Cx. pipiens populations collected in the last part of the Po River including the Delta area.The We assessed the genetic variability of two mitochondrial markers, cytochrome oxidase 1 (COI) and 2 (COII), for a total of 1200 bp, and one nuclear marker, a fragment of acetylcholinesterase-2 (ace-2), 502 bp long. The effect of the landscape features was evaluated comparing haplotype and nucleotide diversity with the landscape composition.The analysis showed a high genetic diversity in both COI and COII gene fragments mainly shared by the populations in the Delta area. The COI-COII network showed that the set of haplotypes found was grouped into three main supported lineages with the higher genetic variability gathered in two of the three lineages. By contrast, ace-2 fragment did not show the same differentiation, displaying alleles grouped in a single clade. Finally, a positive correlation between mitochondrial diversity and natural wetland areas was found.Cx. pipiens populations from the Po River Delta contrasts with the low variability of inland populations. The different patterns of genetic diversity found comparing mitochondrial and nuclear markers could be explained by factors such as differences in effective population size between markers, sex biased dispersal or lower fitness of dispersing females. Moreover, the correlation between genetic diversity and wetland areas is consistent with ecosystem stability and lack of insecticide pressure characteristic of this habitat. The mtDNA polymorphism found in the Po River Delta is even more interesting due to possible linkages between the mitochondrial lineages and different biting behaviors of the mosquitoes influencing their vector ability of arboviral infections.The high mitochondrial genetic diversity found in The online version of this article (doi:10.1186/s13071-016-1429-1) contains supplementary material, which is available to authorized users. Culex pipiens complex includes two of the most widespread mosquito species in the world, Cx. pipiens L. (the northern house mosquito) in temperate climates and Cx. quinquefasciatus Say (the southern house mosquito) in tropical and subtropical climates. Although still under debate, two Palaearctic forms or biotypes are usually recognized within Cx. pipiens, the pipiens and the molestus forms [The us forms , 2. The us forms , 4.Cx. pipiens complex are considered to be the primary vectors of the West Nile Virus (WNV) in Europe and North America [Cx. pipiens complex feed on both avian and mammalian hosts. This behavior assigns to mosquitoes of the complex the role of bridge-vector for the transmission of the WNV to birds and mammals, including humans [The mosquitoes of the  America , 6. The  America . The mosg humans , 8. In Ig humans , 10 and g humans . In partg humans , 13. Morg humans .Cx. pipiens complex inhabiting the last part of the Po River. In this area, urban zones are mostly alternated with large cultivated areas, rice paddies and natural wetlands. Here, during summer, Cx. pipiens achieves high population densities, creating much annoyance. Despite its epidemiological relevance, population genetic data for the Cx. pipiens complex in this WNV outbreak area are still lacking. We consider it particularly important to understand the population structure and the distribution patterns of Cx. pipiens in a WNV epidemic area. Genetic variability in local Cx. pipiens populations could underlie biological differences in biting and flight behavior, and in spatial and temporal distribution, with effects on the epidemiological patterns of the WNV infection.This scenario has drawn attention to mosquitoes of the Cx. pipiens complex have been carried out in several European countries using allozymes and mitochondrial markers [Cx. torrentium Martini, morphologically very similar to Cx. pipiens and occurring in sympatry with this species throughout Europe and some parts of Asia [Up to date, some surveys about genetic variability for  markers –17. Thes of Asia , 19.Cx. pipiens complex along the last part of the Po River using both mitochondrial and nuclear markers. In detail, we studied the genetic diversity of cytochrome c oxidase subunit 1 (COI) and the cytochrome c oxidase subunit 2 (COII) in the populations considered. The cytochrome c oxidase fragment has been frequently used to study mosquito species complexes as well as to compare phylogeographic patterns within closely related taxa e.g. [Culex mosquitoes and to identify possible cryptic taxa, we analyzed the acetylcholinesterase-2 gene (ace-2), a protein-coding gene often used for discrimination within the Culex complex species [Cx. pipiens. This information could help to better identify landscape features that may affect the population structure of mosquitoes, mainly in a high-risk area for arbovirus outbreaks.In this study we inferred the genetic structure of the axa e.g. –22 due t species , 23, 24. species , 26 but,2. The Rovigo Province consists of a plain located between the lower portion of the rivers Adige and Po, the two longest Italian rivers. The study region is a wide lowland area with large zones below sea level and a network of embanked rivers and channels.Mosquito collection was carried out in the Province of Rovigo , an area of about 1,500 km2. The Po Delta area is characterized by intensive agriculture  due to its flat topography and the abundance of surface waters for irrigation. Moreover, lagoons and wooded wetland patches, with high biodiversity, are frequent.The eastern part, facing the Adriatic Sea, terminates in the Po River Delta, which covers an area of about 380 kmThe Po Delta is an area located at the crossroads of the most important bird migration routes connecting Europe, the Mediterranean Basin and Africa; moreover, several equine stables are present –30. ThisMosquito specimens were collected twice a month during summer and autumn in 2012. A total of ten geo-referenced sampling sites were chosen for insect collection: nine sites located in the Rovigo Province and one, used as an out-group, located in the Venice Province , tRNA-Leu, and the cytochrome c oxidase subunit 2 (COII) was amplified using the universal primer pairs LCO-1490/HCO-2198 [2, 0.1 mM dNTPs, 0.5 μM for each primer, 0.5 U of Taq polymerase - Promega, 2 μl DNA template). Thermal cycling conditions for the fragment including the 5’ region of the COI were 5 min at 96 °C followed by 4 cycles of 96 °C for 1 min, 47 °C for 1 min, and 72 °C for 1 min, and other 35 cycles of 96 °C for 1 min, 50 °C for 1 min, and 72 °C for 1 min, with a final extension of 72 °C for 5 min; for the fragment including the 5’ region of the COII, PCR conditions were 5 min at 96 °C followed by 35 cycles with a denaturation step of 96 °C for 1 min, an annealing step of 50 °C for 1 min, and an extension step of 72 °C for 1 min, with a final extension of 72 °C for 5 min.DNA was extracted according to a previously described salting-out protocol . A regioHCO-2198  and C1-JHCO-2198 . AmplifiA fragment of the acetylcholinesterase 2 gene (ace-2) was amplified using the primer pairs F1457/B1246 and Acepip/B1246 . The cycPCR products were checked through electrophoresis on 1.0 % agarose gels stained with SYBR® (Invitrogen) and purified using exonuclease and antarctic phosphatase  before sequencing.Sequencing was performed at the BMR Genomics Service  on automated DNA sequencers employing for the mitochondrial markers, the primers LCO-1490 and TK-N-3796 and, for the ace-2 fragment, the primers Acepip and B1246.www.ncbi.nlm.nih.gov) to assess the identity of the sequences. For the COI fragment, the integrated bioinformatics platform Barcode of Life Data (BOLD) System database (www.barcodinglife.org) was also used to identify sequences.Sequences were edited and aligned using MEGA 6.06 . A GenBaA partition homogeneity test was performed for the COI and COII fragments using PAUP* 4.0b10 . HaplotyPhylogenetic relationships among sequences of the COI-COII data set were estimated using the approximate maximum-likelihood (ML) analysis. A GTR + I + G model implemented in PHYML 2.4.4 software  was applD test [D values with a multimodal distribution of pairwise differences, whereas populations that have undergone through a sudden demographic expansion usually show significant negative D values with a unimodal distribution [P values with a parametric bootstrap approach .The demographic history was inferred within each lineage through the Tajima’s D test  and mismD test  using Arribution , 44. TheThe ace-2 haplotypes were reconstructed using a Bayesian statistical method implemented in PHASE 2.1 , 46. TwoThe phylogenetic relationships among the different ace-2 haplotypes were calculated using two methods: the ML and the Bayesian inference methods. The ML tree was obtained following the same methodology reported above for the mitochondrial markers. For the BI analysis of the same data set Mr Bayes 3.1.2  was usedIn order to assess possible correlations between landscape features and genetic diversity for both nuclear and mitochondrial markers, two variables were considered: landscape composition and air distances from the sampling sites to the closest main natural wetlands.www.regione.veneto.it/web/ambiente-e-territorio/quadro-conoscitivo) in QGIS software .The correlation between genetic diversity and landscape composition was evaluated comparing haplotype and nucleotide diversity with different land cover categories, quantified within a 1,000 m radius, around the sampling site coordinates using detailed land-use maps  urban areas, including residential, commercial and industrial areas; 2) rural areas, comprising arable lands with annual crops; 3) tree crops, including poplar plantations and orchards, and 4) wetlands, comprising surface waters and natural wetland areas. The response variables were haplotype and nucleotide diversity, tested separately across the ten sampling sites. The four land cover categories were tested in order to detect possible collinearity between them. The land cover categories that were not correlated were included in the models as explanatory variables.2. These areas were located along the coast and were included in the Delta area or in the Venice Lagoon. All statistical analyses were carried out using R software [The correlation between the distances from the sampling sites to the closest main natural wetlands and genetic variability (haplotype and nucleotide diversity) was tested through a regression analysis. We considered as main natural wetlands those with an area at least 10 kmsoftware .Cx. pipiens complex and representing ten populations  to exclude the presence of nuclear mitochondrial pseudogenes. All of the substitutions, except one, resulted to be synonymous thus not affecting the amino acid sequence. In haplotype 14 of COII fragment, the replacement of a G by an A in pos 22 resulted in the amino acid change G8S. Sequences were deposited in the NCBI database with the GenBank accession numbers reported in Additional file All sequences were translated with Transeq  [Cx. quinquefasciatus [Cx. quinquefasciatus (99–100 %) (i.e. [Cx. pipiens were present in GenBank at the time of writing (July 2015).A comparison with GenBank and BoldSystem databases showed for the COI a similarity > 99 % with members of the molestus , 50, two pipiens  while thed form)  and sequasciatus , 52–54. %) (i.e. ) as for P = 0.28), allowing data to be pooled for further analyses. Diversity indexes ranged between 0 and 0.92 for the haplotype diversity (H) and between 0 and 0.77 % for the nucleotide diversity (π). Populations S07 and S08 showed the significantly highest H values (H = 0.92 and 0.6 respectively) while S02 and S05 showed the lowest (H = 0). Regarding nucleotide diversity, population S07 displayed the highest value together with populations S06, S08 and S09 while populations S02, S05 and S10 showed the lowest variability. The distribution of haplotypes among the ten populations and other summary statistics are shown in Table Partition homogeneity test confirmed that COI and COII fragments bear a homogeneous signal P = 0.8, allowiFst) between analyzed populations showed significant Fst values only for population S07 when compared to all the other populations except for populations S06 and S08 (Table P < 0.05) for all the pairwise comparisons, indicating a non-random distribution of haplotypes among populations.Pairwise genetic distances (08 Table . On the n = 125) of the mosquitoes analyzed. This haplotype was found in all the populations analyzed and in particular it was exclusive in populations S02 and S05  suggesting a past population expansion.Tajima’s r = 0.17, P < 0.01) suggesting that this lineage may have had a relatively stable population size over time.The analysis of mismatch distributions for the three lineages revealed differences among their demographic histories. Mismatch distribution of lineage 1 was unimodal and characterized by small observed mean (0.17 ± 0.01 S.E.M.). In contrast, the mismatch distributions in lineage 2 and lineage 3 were broadly multimodal, with higher mismatch observed means of 5.82 ± 0.39 S.E.M and 4.47 ± 0.21 S.E.M, respectively as expected under a model of relative constant population size . Thus a total of 16 unique alleles of ace-2 gene were identified in the remaining 62 samples. Cloning confirmed the haplotypes found by PHASE whereas the RDP4 software did not detect any statistically significant recombinant among the ace-2 haplotypes. Variable sites were mainly found in intron 2 (15 polymorphic sites out of 312 bp) while only one nucleotide substitution out of 190 bp was found in exon 3, that did not change the inferred amino acid sequence. The sequences were deposited in the NCBI database with the GenBank accession numbers reported in Additional file Cx. pipiens [A subset of 74 individuals of the 158 mosquitoes previously sequenced for the mitochondrial DNA was used for the nuclear analysis. In particular, all the samples showing rare mitochondrial haplotypes and a representative part of the samples with the most frequent haplotype (A1) in the combined data set (COI-COII) were chosen for these analyses. Sequencing of the ace-2 gene yielded a 502 bp fragment with the exon 3 spanning between positions 313–502. Through the analysis carried out with the software PHASE, 12 samples were removed since their alleles could not be correctly assigned ( pipiens .π) showed values between 0.33 and 0.42 for all the populations except for populations S06 and S07, which showed the highest values   and 0.92 (populations S07). Nucleotide diversity  presented a low coverage in almost all the sites, with the exception of S07 and S08 where a high percentage of the latter category was observed   and haplotype (P = 0.0 < 1) diversity. Conversely, no significant correlations were found when considering the nuclear marker diversity.Since an initial analysis showed a significant inverse correlation between rural and urban land categories only the latter was included in the models. The analyses for the mitochondrial diversity showed that only wetland areas category was significantly and positively correlated with 2 = 0.83; P < 0.001) and nucleotide  diversity of each population, that decrease from the main natural wetlands close to the coast to the inner areas in the mainland , with one population (S07) showing also a significant genetic distance from the other populations. A different pattern of variability was found in the ace-2 marker, with all the populations showing homogenous genetic variability values with population S07 displaying the highest nucleotide diversity value (Table ue Table . This ouCx. pipiens complex have been mainly focused on urban and suburban environments and do not include natural habitats. In general, surveillance efforts for potential disease-carrying mosquitoes have necessarily focused on high human population density areas with a greater risk of disease transmission to human populations [The high variability found in the Delta area, with the presence of several rare haplotypes, contrasts with the low genetic diversity found in other areas in previous studies. A lowest genetic variability for COI was found for example in most of the populations analyzed in Germany , 56 and ulations .Cx. pipiens form molestus, mainly linked to human-made environments [Wolbachia producing selective sweeps has been suggested by several authors in order to justify the reduced haplotype diversity in Cx. pipiens [Cx. quinquefasciatus [The haplotypes found in this study are structured in three distinct lineages showing differences in their composition Fig. . Interesronments , 61. The pipiens , 22, 58 asciatus , 63.Cx. pipiens as it has already been suggested for the strong genetic structure found in Cx. torrentium [Cx. quinquefasciatus. However, the morphological analysis excluded that the specimens with these haplotypes could belong to Cx. quinquefasciatus as they presented the divergent dorsal arms of the male genitalia characteristic of Cx. pipiens in contrast to the parallel dorsal arms of Cx. quinquefasciatus [Cx. pipiens and Cx. quinquefasciatus [Cx. quinquefasciatus sequences deposited in GenBank (Fig. The occurrence of three mitochondrial lineages may underlie the existence of cryptic species within rrentium . Noteworasciatus . Moreoveasciatus , confirmank Fig. .Cx. pipiens analyzed is consistent with the diversity found in other studies for this nuclear marker [The high variability found for ace-2 in the populations of r marker , 65 and r marker –68. On tCx. tarsalis [Ochlerotatus sp. [Anopheles sp. [Several studies report discordant patterns between mtDNA and nuclear markers in animals . These itarsalis , Ochleroatus sp.  and Anopeles sp.  hypotheseles sp. , 76. Anoeles sp. , 78. In Culex [Understanding landscape effects on genetic structure could provide insight into biological processes such as metapopulation dynamics and species distribution . In our Culex , 55. In Culex .Cx. pipiens complex, one of the primary WNV vectors, was found using both mitochondrial and nuclear markers. In particular, the mitochondrial diversity was positively correlated to the natural wetland areas close to the Delta Po River. The presence of different haplotypes in the Cx. pipiens complex populations of this area could underlie differences in their biology as it has been already observed for the forms pipiens and molestus [Cx. pipiens complex in delta areas and other natural habitats. In addition, these studies could be coupled with vector competence studies, because of the potential risk of the different forms as vectors of arbovirus.The Delta Po River is on the route of migratory birds that play an important role in the introduction of viruses, such as WNV, into Europe and the Mediterranean Basin . Here, amolestus , 19 thatmolestus , we thin


There are several indigenous ethnic populations along the silk road in the Northwest of China that display clear differences in culture and social customs, perhaps as a result of geographic isolation and different linguistic traditions. However, extensive trade and other interactions probably facilitated the admixture of different gene pools between these populations over the last two millennia. To further explore the evolutionary relationships of the 13 ethnic populations residing in Northwest China and to reveal the features of population admixture, the 9 most-commonly employed CODIS loci  were selected for genotyping and further analysis. Phylogenetic tree and principal component analysis revealed clear pattern of population differentiation between 4 populations living in Sinkiang Uighur Autonomous Region and other 9 populations dwelled in the upper regions of Silk Road. R matrix regression showed high-level gene flow and population admixture dose exist among these ethic populations in the Northwest region of China. Furthermore, the Mantel test suggests that larger percent of genetic variance (21.58% versus 2.3%) can be explained by geographic isolation than linguistic barriers, which matched with the contribution of geographic factors to other world populations. The Northwest region of China has a very complex geography, encompassing mountains, plateaus and basins, as well as some special landscapes, such as the Gobi desert. There are at least 20 ethnic populations and isolated groups that reside in this region. The Han, Hui and Mongolian people are three of the largest ethnic groups in China. The Han ethnic group has a population of more than 1 billion. The Hui and Mongolian ethnic groups each have populations of more than 5 million and are regarded as typical examples of Chinese ethnic minorities The “Silk Road”, which could date back to the Western Han Dynasty, starts geographically from the ancient capital Chang-an, passes through the “Hosi Corridor” and Sinkiang Uighur Autonomous Region and extends into Central Asia, India and finally the Mediterranean region. Previous research has suggested that extensive genetic admixture exists in the Silk Road region Addressing major issues in the field of human genetics requires multiple types of genetic markers and various analytical methods and statistical models and the consideration of geographic, linguistic and social factors Genetic markers on the Y chromosome and on mitochondrial DNA, such as Y-STRs, Y-SNPs and mitochondrial hyper-variable regions I and II, have low recombination rates and lack of recombination respectively, are widely used to address the genetic differentiation between populationsIn this paper, we have selected 13 representative populations (12 different ethnic groups) living in the Northwest region of China, analyzed the statistical distribution of allele frequency at 9 STR loci, and attempted to reconstruct the genetic structure and reveal the respective gene flows. Our analyses also consider geographic and linguistic factors. With these factors in mind, we have quantitatively analyzed the variance components contributed by genetic differentiation, geographic isolation and linguistic differences.We obtained samples of Han individuals residing in Xi'an (N = 84); Hui residing in Ningxia (N = 82); Mongol residing in Inner-Mongolia (N = 94); Uyghur (N = 88), Kazakh (N = 100), Kirghiz (N = 101), and Uzbek (N = 58) who live in Sinkiang Uighur Autonomous Region; Salar (N = 100), Yugur (N = 120) and Baoan (N = 120) who live in Gansu; and Dongxiang (N = 118) and Tu (N = 102) who reside in Qinghai . All indThe study was approved by the Xi'an Jiaotong University Ethics Committee. All participants signed the written informed consent. One of previous study was published using part of these samples Genomic DNA was extracted using the Chelex-100 protocol as described by Walsh et al. and quantified spectrophotometricallyxi2), where x is the estimated frequency of the ith allele in the system. The combined power of exclusion probability of paternity (EPP) and combined probability of matching(PM) for the nine STR systems for each population were calculated as 1-(1-EPP1)*(1-EPP2)…*(1-EPP9) and PM1*PM2*…*PM9, respectively, where EPPn and PMn can be estimated by the Powerstats program Allele frequencies were estimated by gene counting following exact tests of Hardy-Weinberg equilibrium with GenepopA distance was selected to be the genetic measure, as it best reflects the real differentiation among populations; it was calculated by the Dispan program ii is the genetic distance of a particular population from the gene frequency centroid, which can be calculated from allele frequency data, as in the formula i is the average heterozygosity of the ith population, and Ht is equal to the overall mean heterozygosity of the entire population Nei's Dhttp://www.ethnologue.com).The geographic distances were entered as a matrix of the great-circle distances between pairs of populations and were assessed on the basis of population geographic coordinates −8. Furthermore, more than 500 paternity cases and cases of individual identification have been successfully resolved using the 16 Powerplex system, which contains the abovementioned 9 STR loci.A distance with 1000 bootstrap times , with a correlation coefficient of 0.4769 and a 21.58% variance. In contrast, there is no significant difference for Dgen and Dlan, with a low correlation coefficient and variance. When linguistic is kept constant, the partial correlation coefficient for genetics and geography is 0.4516, with high statistical significance (P  = 0.004); conversely, the correlation coefficient is not significant for genetics and language, with a P value of 0.096 and a correlation coefficient value of 0.1230.The results of the Mantel tests are shown in The Northwest region of China was the starting point of the ancient “Silk Road” and served to link Central China in the East to Central Asia, South Asia and even Europe in the West. According to historical records, cultural and commercial communication between the eastern and western was frequent in this region. Moreover, inter-population marriage and genetic exchange among the different populations were very common. It is now quite clear that the Uyghur, Uzbek, Kazakh and Kirghiz populations, which originally lived in Central Asia, migrated into the Sinkiang Uighur Autonomous Region in China in approximately the 5th century, A.D. This is supported by genetic distance we calculated using 13 Northwest Chinese populations and 4 other world populations  [35]–[37There is still no definitive answer regarding the origin of the five ethnic populations living in the Gansu and Qinghai Provinces. Historical records support two hypotheses about the origin of the Tu population. The first and more popular hypothesis proposes that their ancestors were actually from Liaoning Province in the East and that they later migrated into Qinghai and Gansu Provinces in the early 4th century and inter-married with local Mongolian, Tibetan and Han populations The polymorphisms of the nine selected autosomal microsatellite markers have been reported in different populations of the world P value is 0.0004.). Language distance represents an additional contribution to the effect . In our current analysis, we have considered only the geographic coordinates for calculating the geographical distance but have not included the complicated terrain of the Northwest, which is characterized by mountains, deserts and plateaus. In the future, we will establish a more complex and precise mathematical model to quantify the geographic isolation.Populations from different continents that are geographically close are also more similar genetically than predicted by the simple hypothesis that they are from their respective continents In conclusion, our results demonstrate that high–level admixture does exist in the Northwest region of China, which is part of the Silk Road of ancient times. However, the populations living in northern China in Sinkiang Uighur Autonomous Region, which include Uyghur, Kazakh, Uzbek and Kirghiz, are closely clustered, but quite distant from other populations living in Qinghai and Gansu and from the subpopulations of the Han, Hui and Mongol. Those findings reveal that geographic isolation plays a significant role in population differentiation, whereas language differences exert a much smaller influence.Table S1A distance between the 17 populations.Pairwise D(DOCX)Click here for additional data file.


Callosobruchus maculatus that uses different legumes as hosts. We analyzed 180 samples from 42 populations of this stored bean pest from tropical and subtropical continents and archipelagos: Africa, the Middle East, South and Southeast Asia, Oceania and South America. For the mitochondrial genes, there was weak but significant genetic differentiation across continents/archipelagos. Further, we found pronounced differentiation among subregions within continents/archipelagos both globally and within Africa but not within Asia. We suggest that multiple introductions into Asia and subsequent intermixing within Asia have generated this pattern. The isolation by distance hypothesis was supported globally (with or without continents controlled) but not when host species was restricted to cowpeas Vigna unguiculata, the ancestral host of C. maculatus. We also document significant among-host differentiation both globally and within Asia, but not within Africa. We failed to reject a scenario of a constant population size in the recent past combined with selective neutrality for the mitochondrial genes. We conclude that mitochondrial DNA differentiation is primarily due to geographic isolation within Africa and to multiple invasions by different alleles, followed by host shifts, within Asia. The weak inter-continental differentiation is most likely due to frequent inter-continental gene flow mediated by human crop trade.Genetic differentiation can be promoted allopatrically by geographic isolation of populations due to limited dispersal ability and diversification over time or sympatrically through, for example, host-race formation. In crop pests, the trading of crops across the world can lead to intermixing of genetically distinct pest populations. However, our understanding of the importance of allopatric and sympatric genetic differentiation in the face of anthropogenic genetic intermixing is limited. Here, we examined global sequence variation in two mitochondrial and one nuclear genes in the seed beetle  Genetic differentiation can be induced allopatrically by geographic isolation of populations and/or sympatrically by, for example, host-race formation. In crop pests, the trade of crops across the world tends to generate a global mixing of genetic variants in pest populations, whether these were generated and maintained either allopatrically e.g.,  or sympaCallosobruchus (Coleoptera: Chrysomelidae: Bruchinae). Bruchine adults of such species lay eggs on dry seeds of legume crops and larvae burrow into them. Low levels of infestation are difficult to detect because these beetles live inside the seeds as larvae, pupae and pre-emergence adults. Because of the cryptic feeding in grains, world trade of dry beans for human consumption can potentially lead to the effective spread of these beetles.Association with specific host plants may allow the formation of genetically distinct pest host races in some cases Callosobruchus populations In general, flight distance is correlated with body size in animals Callosobruchus maculatus (F.) is a major stored bean pest in sub-Saharan Africa Vigna unguiculata (L.) Walp., but other species of Vigna and other cultivated legumes are also infested by the beetle C. maculatus populations are partially intermixed across agro-ecological zones of Western Africa Callosobruchus maculatus also uses other economically important bean species as hosts, such as V. radiata and V. angularisVicia faba, Cicer arietinum and Cajanus cajanV. subterranea of Afrotropical origin The cowpea is a drought-tolerant food crop for humans and livestock feed that is grown throughout the semi-arid tropics C. maculatus, based on multiple mitochondrial and nuclear gene sequences of 42 populations that use different bean species as hosts. We evaluated these factors by comparing genetic variation between hierarchical spatial scales  and between populations using different host plants. Human-aided dispersal is expected to lead to weak or no differentiation at the spatial scale where anthropogenically mediated gene flow is most frequent. We tested for congruence between the C. maculatus phylogeny and geography on one hand and between the phylogeny and host plant usage on the other. Furthermore, nucleotide sequence variation was compared among populations across five different continents and among those using different host plant species. The isolation-by-distance hypothesis was tested globally and within continents and with host plant controlled.Here, we aimed to study the effects of geographic isolation by limited dispersal ability and genetic differentiation over time, host-plant utilization by formation of distinct host-associated races, and anthropogenic gene flow by trade of crop on the global genetic differentiation of No specific permits were required for the described field studies. No specific permission was required for sampling at any locations and activity. The locations are not privately owned or protected in any way. No activity during the field study involved endangered species or protected species.Callosobruchus maculatus were collected as adults that emerged from randomly selected cultivated beans collected from local markets in various parts of Africa, the Middle East, South and Southeast Asia, Oceania and South America  and two fragments from 28S rRNA. For the PCR and sequencing, we followed the protocol previously described in 5′-ATAATTTTTTTTATAGTTATACC-3′) and COI2-2 COI, and 5′-TAATATGGCAGATTAGTGCATTGGA-3′ and 5′-GAGACCATTACTTGCTTTCAGTCATCT-3′  in combination with 28S-R01 (5′-GACTCCTTGGTCCGTGTTTCAAG-3′) for D2–D3 fragment COI, 51°C for LeutRNA–COII, a constant temperature between 44–52°C for EF-1α, 54°C for 28S-01 and 51°C for 28SD for 40 s, and an extension at 60°C for the mitochondrial genes, 62°C for the EF-1α and at 70°C for the 28S fragments, for 1 min–1 min 10 s. Sequencing was done with BigDye Terminator v3.1 Cycle Sequencing Kit (Life Technologies/Applied Biosystems) on 3730 DNA Analyzer (Applied Biosystems).Whole genomic DNA was extracted from individual beetles using a DNeasy Blood & Tissue Kit . We amplified and sequenced two mitochondrial fragments, Wolbachia may select for mitochondrial haplotypes in infected females through cytoplasmic incompatibility Wolbachia infection using primers fts-Z-f and fts-Z-r for the ftsZ gene coding fragment Callosobruchus chinensis (L.) that were naturally infected with Wolbachia were used as a positive control Because infection by and vertical transmission of the intracellular symbiont Callosobruchus imitator Kingsolver  and C. subinnotatus (Pic)  were used as outgroups , we used a subset of the data with host plant information  or host plants , Cajanus, and Cicer) was tested with a topology-dependent permutation tail probability test (T-PTP) implemented in PAUP*4.0 Beta The congruence of the V. unguiculata, V. angularis, V. radiata, V. subterranea and C. cajan; the other plant species or groups were excluded because of the small sample sizes, α = 0.05 for the mitochondrial genes and α = 0.3 for the nuclear gene, based on our estimation for the C. maculatus dataset.Here, we used populations of which individuals were analyzed either soon after collection or within a relatively brief rearing history in the lab  were positively correlated, by a one-tailed Mantel test based on 2,000 permutations, using the ISOLDE program of Genepop 4.0.10 V. unguiculata as a host to exclude possible effect of host-race formation over distance.As in the previous analyses, we only used populations that were analyzed soon after collection or within a brief rearing history. We assessed spatial genetic differentiation by testing for isolation by distance (IBD) V. unguiculata, with raggedness rSFR2r, significantly negative SF and significantly small R2 values indicate recent sudden population growth. The latter two indices are statistically more powerful than the raggedness index and SF exhibits high statistical power for large sample sizes, while R2 is more powerful for small sample sizes DAs in the previous two sections, we used only populations that were subjected to DNA extraction shortly after collection. Recent past sudden demographic expansion was tested in populations on different continents (Africa and Asia) and in populations using the original host COI, 19 bp for LeutRNA, and 702 bp for COII) for the mitochondrial genes (genbank JX297380–JX297419). The sequence data included no indels and the base composition was AT rich, as is typical for insect mitochondrial sequences. The nuclear EF-1α fragment was sequenced for 81 homozygous individuals. We used 866 bp of this fragment, including insertions and deletions. For the nuclear 28S, the sequenced fragments were 1,452 bp in total (822 bp for the D2–D3 fragment and 630 bp for the D4–D5). There was no sequence variation across C. maculatus individuals in the two fragments of 28S and these were thus discarded from subsequent analyses. We analyzed only the mitochondrial trees because homozygous nuclear EF-1α data was available for limited number of individuals.The total lengths of the sequenced fragments were 1,726 bp , indicating highly significant congruence between the beetle phylogeny and geographic regions. Inclusion of individuals without host information did not alter the significant relationship between geographic location and the C. maculatus phylogeny . Randomization of the host bean groups also changed the length of the C. maculatus phylogenetic tree , indicating that the congruence between the beetle phylogeny and host plant use was as significant as between phylogeny and geography.Randomization of the geographic locations changed the length of the COI  and, out of 91 sequences, 34 haplotypes for LeutRNA–COII . In total, there were 111 different mitochondrial haplotypes . For the EF-1α, out of 69 individuals sequenced, there were 60 different alleles .Out of the 160 individuals sampled recently , there wP = 0.016–0.072). When continents were controlled for, subregional differentiation was significant in Africa but not in Asia . None of these results changed, in terms of our ability to reject null hypotheses, when unequal sample sizes per population were controlled for.The AMOVA indicated genetic differentiation among populations using different host-plant species globally for mitochondrial DNA . HoweverIn contrast to the results based on mitochondrial DNA, the AMOVA of the nuclear gene showed no genetic differentiation among continents. Genetic differentiation among populations using different host plants was significant as in mitochondrial genes but this effect was no longer present when the sample size was controlled for .FST/(1- FST) between pairwise populations were significantly correlated  and SF. We failed to reject a scenario of population stability in the recent past combined with selective neutrality for the mitochondrial genes for global, African or Asian populations and for the populations using either V. unguiculata or other hosts .We aimed to study the relative contribution of factors associated with geography, host plant usage and human-aided dispersal to genetic population structure of the stored bean pest, aculatus . This maC. maculatus subregional populations and suggest that this most likely represents allopatric divergence, because the structure primarily reflects the geographic separation of populations .(TIF)Click here for additional data file.Figure S2Export and import quantities of dry cowpeas (tonnes) in different African and Asian subregions. Data on imports into South Asia were unavailable.(TIF)Click here for additional data file.


Perna perna) across a tropical/subtropical biogeographic transition.Intraspecific variability is seen as a central component of biodiversity. We investigated genetic differentiation, contemporary patterns of demographic connectivity and intraspecific variation of adaptive behavioural traits in two lineages of an intertidal mussel  and eastern  populations, confirming divergence previously detected with mitochondrial (COI) and nuclear (ITS) markers.Gene flow between regions was predominantly east-to-west and was only moderate, with higher heterozygote deficiency where the two lineages co-occur. This can be explained by differential selection and/or oceanographic dynamics acting as a barrier to larval dispersal.Common garden experiments showed that gaping (periodic closure and opening of the shell) and attachment to the substratum differed significantly between the two lineages. Western individuals gaped more and attached less strongly to the substratum than eastern ones.These behavioural differences are consistent with the geographic and intertidal distributions of each lineage along sharp environmental clines, indicating their strong adaptive significance. We highlight the functional role of diversity below the species level in evolutionary trends and the need to understand this when predicting biodiversity responses to environmental change.The online version of this article (doi:10.1186/s12862-015-0366-5) contains supplementary material, which is available to authorized users. The early recognition of functionally significant levels of biodiversity within a species is a central objective of evolutionary biology and biodiversity conservation . This isGiven the recurrent detection of distinct phylogeographic lineages, it is clearly necessary to consider the adaptive significance of intraspecific differences in order to understand the evolutionary potential of a species ,7. ComplThe identification of evolutionarily significant units uniquely based on neutral molecular markers, while overlooking intraspecific patterns of phenotypic divergence, can lead to underrepresentation of locally adapted populations and thus underestimate biodiversity ,11. LocaSpecies with wide distributions over variable environments and large effective population sizes often display marked intraspecific biodiversity with distinct genotypes/populations within a species, resulting from adaptation to local environmental conditions but capable of interbreeding with other ecotypes of the same species e.g. ,14). Mar. Mar14])The southern African coastline covers a wide range of climatic and oceanic conditions and can be divided into three major biogeographic regions: cool-temperate . It is absent from there to central Namibia due to the cold, upwelled waters of the Benguela system  sequences indicate a sharp phylogeographic break on the southeast coast of South Africa  forming a western and an eastern lineage . The weslineages . Manipuldynamics .P. perna populations are influenced by the tropical/subtropical biogeographic transition. First, we adopted a population genetic approach using microsatellite markers, which are unaffected by natural selection, to investigate differentiation and migration patterns of P. perna between populations inhabiting different bioregions. The re-examination of genetic structure in South African P. perna with microsatellites and comparison with previously reported mitochondrial data is critical to assess potential mito-nuclear discordance and contemporary biogeographic conditions. Second, we used a common-garden design to compare fundamental behavioural traits known to affect survival along large  and small (within-shore) scale environmental gradients. In particular, we assessed shell gaping and attachment strength, key attributes affecting tolerance of the two major stresses in intertidal habitats, desiccation and wave action. A common-garden design is necessary to distinguish between adaptive and plastic responses of population subjected to distinct selective pressures. Finally, we compared intertidal elevation  of the two lineages by using in situ temperature profiles to compare intertidal limits of populations from the two bioregions.Here, we examine the hypotheses that contemporary demographic connectivity and functional traits of Mussel collection were performed under permit number RES2014/12 issued by the Department of Agriculture Forestry and Fisheries to the Department of Zoology and Entomology at Rhodes University.Mussels  were collected between February 2010 and May 2013 at six locations in southern Africa  and expected heterozygosity (HE), plus FIS  and Jost’s  were performed under the admixture and the correlated allele frequency model. The most probable value of K was inferred based on the ad hoc criteria L(K) proposed by Pritchard et al. )Temperature offers a more likely explanation as it has direct or indirect effects on attachment. Higher temperatures promote byssal thread production while weakening attachment by accelerating thread deterioration and negatively affecting the curing and moulding of byssal threads ,72. AddiP. perna inhabits shores that are experiencing rapid and geographically uneven environmental changes [This study shows how distinct genetic lineages, partially segregated along a sharp geographic environmental gradient display adaptive responses to different selective pressures.  changes ,76. Our The data set supporting the results of this article is included within the article (Additional file


Mactra chinensis in the East China Sea (ECS). Genetic information was acquired from 501 specimens collected from its main distribution in the region, represented by mitochondrial cytochrome oxidase I (COI) and nine polymorphic microsatellite loci. A shallow and star-like phylogeny was revealed for all COI haplotypes, indicating the origin of populations from a single refugium. Although no divergent lineages existed, population subdivision was detected in both data sets. The most striking pattern was the significant differentiation between populations north and south of a biogeographic boundary—the Changjiang Estuary, suggesting a barrier effect of the freshwater outflow to gene flow. For the northern group, substructure was revealed by COI result as one southernmost population was significant different from other ones. Clear latitude gradations in allele frequencies were revealed by microsatellite analyses, likely influenced by environmental gradient factors such as temperature. Our results demonstrate that genetic subdivision can arise for populations within the ECS despite they have a single origin, and multiple mechanisms including Changjiang River outflow, environmental gradient factors and life-history traits may act in combination in the process.The northwestern Pacific, characterized by unique tectonic and hydrological settings, has greatly intrigued marine phylogeographers. However, current studies mostly focus on the influence of Pleistocene isolation of sea basins in population structure of species in the region, leaving the contribution of other factors  largely unexploited. Here we shed light on the question by investigating phylogeography of the surf clam  Pinpointing mechanisms facilitating marine population subdivision and speciation has long intrigued biogeographers e.g., . For the2, which was likely subjected to amplified sea-level-induced environmental changes through the Pleistocene (The East China Sea (ECS) with the Bohai Gulf and the Yellow Sea  , separating (I) Far East Subregion of North Pacific Region from (II) Sino-Japanese Subregion of Indo-West Pacific Region . Studiesalinity) . Marked alinity) , which malinity) . Howeveralinity) .Mactra chinensis Philippi 1846  as a model organism, employing genetic data from mitochondrial cytochrome oxidase I (COI) and polymorphic microsatellite markers. Mactra chinensis is a temperate bivalve with distribution in the northwestern Pacific, and only occurs naturally in the ECS along Chinese coastline  and a pelagic larval duration (PLD) up to 10 days , 50–100 ng of genomic DNA, 0.25 µM of each primer, 0.2 mM dNTP mix, 2 mM MgCl2 and 5 µL 10× PCR buffer. PCR was carried out on a GeneAmp® 9700 PCR System  based on the conditions in n), haplotype diversity (h) and nucleotide diversity (π) were calculated for each population in the ARLEQUIN 3.5  in each population with the primers LCO-1490 and HCO-2198 . Each poQUIN 3.5 .FCT values (number of groups K: 2 to 8) in SAMOVA 1.0 )  was used to define the best population grouping strategy based on MOVA 1.0 . A hieraMOVA 1.0  was condrrection . The man − FST))  and Eucl − FST)) .D  was individually estimated for two group pairs G1:G2 and G1:G3 because G2 and G3 seemed to derive from G1 separately. Initial runs were analysed to determine the appropriate upper bounds for the migration (m) and divergence time (t). Twenty heated Markov chains were run with a burn-in period of 10 million steps, and all runs were consisted of 100 million steps . Heating parameters (g1 = 0.8 and g2 = 0.9) were used to provide good mixing of the Markov chains. Each procedure was repeated at least for three times with different random seeds. The analyses were considered to converge upon a stationary distribution if the independent runs reported similar posterior distributions  based on following formula: T = t × g/u   used in former studies  . For M. s 1 year . Howevers 1 year . Under ts 1 year . So we aes e.g.,  to shed Microsatellite data were analysed to validate the population structure revealed by mitochondrial COI. In our previous study, we had genotyped eight populations  with nine polymorphic microsatellites . Here weEH) and observed heterozygosity (OH) were calculated for each population using the program MICROSATELLITE ANALYSER  was calculated with FSTAT version 2.9.3 (FST (θ) was calculated in the program MSA  gram MSA . Signifigram MSA . The manCD was calculated and an unrooted neighbor-joining (NJ) tree was generated using the software POPULATIONS v1.2.31 (K ranged from 1 to 12 (sampled populations plus three). For each value, 20 replicates were run using the admixture model, correlated allele frequencies and the prior population information with a burn-in period of 10,000, followed by 100,000 steps. The most appropriate value of K was determined by the statistic ΔK introduced by K by Greedy method implemented in CLUMPP . The number of haplotypes per population ranged from 5 to 10 with an average of 8. Haplotype diversity ranged from 0.533 in ZH to 0.942 in HY, and nuclear diversity ranged from 0.00148 in QH to 0.00390 in PT ; (LY); (PT), referred to hereafter as G1, G2 and G3 correspondingly). Based on this strategy, hierarchical analyses of AMOVA revealed a significant level of geographic structuring among groups . Only 0.43% of the variation was attributed to variation among populations within groups (ΦSC = 0.0124). These results were corroborated with the pairwise ΦST values: genetic structure was indicated as 17 comparisons were significant after Bonferroni corrections . The IBD analysis suggested significantly positive correlation between genetic and geographic distance matrices  was 1.610 (0.908–2.768), while t2 (G1:G3) was 1.354 (0.568–3.328). When applying a mutation rate of 12% myr−1, the real time T1 amounted to 21.4 (12.1–36.8) and T2 was 18.0 (7.5–44.2) kyr  kyr , roughly4.2) kyr .FST tests except one were significant after Bonferroni corrections  were observed between PT and all other populations, suggesting significant genetic differentiation between them.For microsatellites, genetic diversity indices for each population were summarized in rections . ExtremeR2 = 0.705, P = 0.001; K in Structure Harvester was found for K = 2  were recovered with clear gradations in allele frequencies across the northern populations  and repopulated along the ECS coastline quickly. This might represent a common evolutionary scenario for marine species inhabiting the ECS, and similar patterns were revealed in diverse organisms including fishes, molluscs and crustaceans . This sharp genetic discontinuity across the estuary most likely results from the influence of the biogeographic boundary associated with habitat discontinuity: several ocean currents and the Changjiang freshwater outflow meet around the estuary, causing striking physical and ecological gradients that may potentially limit gene flow .Although no northern population was separated in STRUCTURE analyses of microsatellites, two genetic clusters with clear latitudinal clines were discovered, probably reflecting the influence of environmental gradient factors . Populations on both ends may be more likely to diverge from other ones. For example, LY was found with distinct genetic composition as majority of the individuals (81.7%) could be allocated to the pink cluster with membership >80% , compareM. chinensis as a case study, our results indicate that, although derived from a single ancestral population, significant subdivision can arise for intertidal species within the ECS. Genetic discontinuity was observed between distant populations across the Changjiang Estuary but also between adjacent northern populations, reflecting the influence of multiple driving forces including the Changjiang freshwater boundary, habitat discontinuity, environmental gradient factors and life-history traits on shaping the phylogeographic pattern of M. chinensis. Although phylogeographic studies on the NW Pacific have been increasing in recent years, the emerging picture is still far from complete, especially regarding the detailed within-sea evolutionary process (Using the surf clam  process . This st10.7717/peerj.1240/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.1240/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.1240/supp-3Supplemental Information 3Click here for additional data file.


Ne), heterozygosity, fixation index (FST) and runs of homozygosity (ROH) are widely used and help to improve our knowledge about genetic diversity in animal populations. The development of high-density single nucleotide polymorphism (SNP) arrays and the subsequent genotyping of large numbers of animals have greatly increased the accuracy of these population-based estimates.Knowledge of the genetic structure and overall diversity of livestock species is important to maximise the potential of genome-wide association studies and genomic prediction. Commonly used measures such as linkage disequilibrium (LD), effective population size (r2 and D′), Ne, heterozygosity, FST and ROH in five Australian sheep populations: three pure breeds, i.e., Merino (MER), Border Leicester (BL), Poll Dorset (PD) and two crossbred populations i.e. F1 crosses of Merino and Border Leicester (MxB) and MxB crossed to Poll Dorset (MxBxP).In this study, we used the Illumina OvineSNP50 BeadChip array to estimate and compare LD (measured by Ne than MER. Observed heterozygosity in the pure breeds ranged from 0.3 in BL to 0.38 in MER. Genetic distances between breeds were modest compared to other livestock species (highest FST = 0.063) but the genetic diversity within breeds was high. Based on ROH, two chromosomal regions showed evidence of strong recent selection.Compared to other livestock species, the sheep populations that were analysed in this study had low levels of LD and high levels of genetic diversity. The rate of LD decay was greater in Merino than in the other pure breeds. Over short distances (<10 kb), the levels of LD were higher in BL and PD than in MER. Similarly, BL and PD had comparatively smaller This study shows that there is a large range of genome diversity in Australian sheep breeds, especially in Merino sheep. The observed range of diversity will influence the design of genome-wide association studies and the results that can be obtained from them. This knowledge will also be useful to design reference populations for genomic prediction of breeding values in sheep.The online version of this article (doi:10.1186/s12711-015-0169-6) contains supplementary material, which is available to authorized users. The three pure breeds Merino, Poll Dorset, Border Leicester and their crosses (Merino × Border Leicester and Merino × Border Leicester × Poll Dorset) represent more than 90 % of the Australian sheep population.The process of sheep domestication began between 9000 and 11,000 years ago. Over thousands of years, humans have selected sheep for different desirable production traits such as wool, milk and meat. This artificial selection combined with natural adaptation to new environments as sheep were introduced throughout the world has led to a broad spectrum of phenotypic diversity with more than one thousand different sheep breeds [Understanding the genetic diversity of these key sheep breeds in Australia is important to design and interpret studies that investigate genome-wide association and genomic prediction. For example, the amount of diversity in a population is a key indicator of the amount of phenotypic data (reference data) that is required to obtain accurate genomic predictions. This is also important when interpreting genome-wide association studies (GWAS) data since high levels of diversity reduce the likelihood that highly significant markers are at a large distance from the quantitative trait locus (QTL) that underlies variation in phenotype and allows for easier identification of possible functional regions.Genetic diversity can be estimated from pedigree data or from molecular marker data. Estimates of genetic diversity are more robust when marker data is used and particularly so when pedigree records are poor or shallow. However, this advantage is small or absent when low-density markers such as microsatellites are used –4. The hF statistic (FST) [Ne) [There are a number of methods that can be used to estimate genetic diversity using marker data. These include observed and expected heterozygosity , 6, runsic (FST) , linkageST) [Ne) .Ne. Wright’s F statistics  are widely used to estimate genetic diversity within and between populations [Heterozygosity measures the genetic variation within a population and is one of the most widely used genetic diversity parameters . A high ulations , 11. RunNe [Ne size and other genetic events such as selection, migration, mutation and recombination events influence the extent of LD within a population [LD between any two markers reflects the extent of non-random association between them. LD underpins selection decisions in a wide range of livestock species that have adopted genetic technologies for selection purposes. Marker-assisted selection (MAS), genomic selection and GWAS all largely depend on the extent of LD within a population. It is the extent of LD that determines the minimum number of markers required for a successful genome-wide study; with LD remaining high over longer chromosomal segments, fewer markers are needed. Conversely, denser panels are required if LD decays rapidly. The pattern of LD decay also provides information on the evolutionary history of a population and can be used to estimate, e.g., the ancestral Ne , 13. Ne pulation . Comparipulation –17, pig pulation , horse [pulation , chickenpulation  and sheepulation –23.Our objective was to describe and compare LD patterns, and the level and structure of genetic diversity in the five commercial Australian sheep populations mentioned above. The results are expected to provide valuable information for the design and analysis of genetic association studies and genomic selection, as well as for the management of genetic resources in the most economically important Australian sheep populations.Samples for genotyping were collected under approval number 344 AEC12-049 of the University of New England Animal Ethics Committee.n = 253), Merino , Poll Dorset , and two crossbred populations i.e., Merino and Border Leicester F1 crosses , and crosses of Merino × Border Leicester with Poll Dorset . MER is a wool breed, while BL and PD are primarily meat breeds; each breed was separately selected for its own specific purposes. MxB and MxBxP are straight F1 crosses from the pure breeds rather than terminal composite breeds and are not subjected to artificial selection. These crosses are often used for both wool and meat production. All animals were genotyped using the Illumina OvineSNP50 BeadChip , which includes 54,241 SNPs.The study consisted of 1273 sheep chosen from the Australian Sheep CRC Information Nucleus flock from five different populations: three pure breeds i.e., Border Leicester  and had no assigned genomic location. Markers on sex chromosomes were also excluded from the analysis. Quality control was performed using snpQC [A number of quality control measures were applied to all SNPs as follows: SNPs were removed if they had a call rate <95 %, a GC score <0.6, a minor allele frequency (MAF) <0.01 and if deviation in SNP heterozygosity was greater than three standard deviations from the mean. Data was also removed if SNP genotypes deviated from the Hardy-Weinberg equilibrium . Forty-one markers were excluded from the analysis because they had no assigned genomic location in Oar_v3.1.Chromosomal coordinates for each SNP were obtained by aligning the region that covered approximately 120 bp around each SNP, to the latest release of the ovine genome sequence assembly, Oar_v3.1, by BLAST (HE) was calculated as a measure of genetic diversity. HE for each SNP was calculated separately and then averaged to find the average genetic diversity for each breed. Population relatedness was evaluated using pair-wise estimates of FST. First, expected heterozygosities for subpopulations (HS) and for the total population (HT) were calculated for each locus for each pair of populations, then HS and HT were averaged across all loci. H values (expected heterozygosities for populations and combined populations) were calculated as 1 minus the sum of the squared allele frequencies at a locus. To calculate HT, allele frequencies between two populations were averaged before the calculation. To calculate HS, H values were averaged after the calculation. In both cases, the averages were weighted by the relative sizes of the two populations. FST was then calculated for each pair of populations as (HT − HS)/HT. A principal component analysis (PCA) was used to examine the genetic structure of the five populations. The PCA was performed using a genomic relationship matrix [Gene diversity or expected heterozygosity (p matrix  to definl) was calculated by a method similar to that proposed by [ns was the number of genotyped SNPs per individual, ni was the number of individuals, α was the percentage of false positive ROH (set to 0.05 in the present study) and het was the mean SNP heterozygosity across all SNPs. Since very short and common ROH are often due to LD, ROH that were <500 kb long were removed. Finally, the maximum gap between consecutive homozygous SNPs was set to 250 kb.Runs of homozygosity were defined for individuals in each of the five populations using PLINK v1.07  with sliposed by :1\documeRuns of homozygosity were estimated for each individual and then categorized based on ROH length . The mean sum of ROH within each ROH category was calculated by adding up the length of all ROH for each individual in each ROH category and then the results were averaged per breed population. The percentage of occurrences of a SNP in a ROH was calculated for each SNP by counting the number of times the SNP was detected in a ROH across the dataset of the whole population.D′ and r2, for an easy comparison of our results with those of other reports. Haploview v4.2 [D′ and r2) were estimated. SNP pairs were grouped according to their pairwise distance into 14 categories: <10 kb, 10–20 kb, 20–40 kb, 40–60 kb, 60–100 kb, 100–200 kb, 200–500 kb, 500 kb–1 Mb, 1–2 Mb, 2–5 Mb, 5–10 Mb, 10–20 Mb, 20–50 Mb, and >50 Mb. Average LD within each group was calculated for each breed. Average LD with neighbouring pairs of SNPs and average LD across the chromosome were also estimated for each chromosome. For non-syntenic SNPs, a subset of SNPs from the whole genome was used to estimate LD. For each autosome, a random representative sample of SNPs was selected to obtain an estimate of LD (5 % of the SNPs for each autosome). Haploview v4.2 was also used to identify the haplotype blocks present in each chromosome. Haplotype blocks were defined using the method described in [D′ was higher than 0.98 and if the lower bound was higher than 0.7.As a measurement of LD, we used the two most commonly used statistics, iew v4.2  was usedribed in . Two SNPNe) was calculated for each breed using the default parameters and the random mating model in the software NEESTIMATOR v2 [Ne.Effective population size  was <0.95, and 337 because they deviated from the HWE. Forty-one SNPs could not be mapped to the ovine Genome Assembly v3.1 and were removed from the analysis. No individual was removed due to low call rates (CRIND). A total of 48,599 SNPs across the five populations met the filtering criteria and were included in the final analysis. The distributions of the SNPs after filtering and the average distances between adjacent SNPs on each chromosome are in Additional file Ovis aries chromosome) to 61.62 kb on OAR24. Autosomes varied in size, with OAR24 being the shortest (42.03 Mb) and OAR1 the longest chromosome (275.61 Mb). After filtering, the number of SNPs on each chromosome ranged from 683 on OAR24 to 5484 on OAR1. The distribution of MAF differed between populations  non-autosomal SNPs and 314 SNPs that had no chromosome assignment were removed. Another 3837 SNPs were excluded: 1662 because minor allele frequency (MAF) was <0.01, 1838 because SNP call rate , which were the most closely related pair. These estimates reflected expectations since MER and BL contributed to both crosses. Higher average FST values were observed for every pair-wise comparison of populations involving MER. Figure Analysis of genetic diversity using the average observed heterozygosity and average expected heterozygosity Table  showed tST Table . The twoFST = 0.03, which The number of ROH differed significantly between populations. BL had the largest total number of ROH 12,561) followed by PD (9875) and MER (2008). There were 49.65, 37.89 and 7.57 ROH per animal for the BL, PD and MER breeds, respectively. As expected, we found that the pure breeds had more ROH across the whole genome than the crosses. In fact, MxB and MxBxP had, in total, only 80 and 331 ROH. Figure ,561 follAmong the 1273 animals, 1015 (80 %) had at least one ROH longer than 1 Mb and 751 (59 %) had at least one ROH longer than 5 Mb. If we consider only the pure breeds, then all animals had at least one ROH longer than 1 Mb and 688 of the 782 animals (88 %) had at least one ROH longer than 5 Mb. There are clear differences between breeds in the frequencies of the ROH of various lengths  with on average 11.89 % of the chromosome consisting of ROH. Generally, the number of ROH per chromosome tended to decrease with chromosome length , 0.27 (MER), 0.33 (PD), 0.29 (MxB), and 0.3 (MxBxP). Average LD between adjacent SNPs per chromosome was also estimated and some variation in the extent of LD on different chromosomes was observed for the five populations. In each population, the maximum average LD between adjacent SNPs was observed on OAR10 and was equal to 0.25 (BL), 0.15 (MER), 0.21 (PD), 0.17 (MxB), and 0.16 (MxBxP). However, the minimum average LD between adjacent SNPs was found for different chromosomes in the five populations  were calculated based on the SNP genotypes for all five populations  of 0.38 and 99.86 % polymorphic SNPs. This fits well with the known history of the breed. The foundation of the Australian Merino population involves contributions from different European, Asian and African breeds [Ne sizes [In this study, we identified clear but modest genetic differences between three pure sheep breeds MER, BL and PD. Analysis of genetic diversity within these three populations Table  showed tn breeds  and, then breeds . The hign breeds . PD sheeNe sizes .Ne size of BL (Ne = 140) and PD (Ne = 152) in comparison to MER (Ne = 348). The Ne sizes of BL and PD are similar to those reported for Spanish Churra sheep (Ne = 128) [Ne = 119 and 122) [Ne reported in our study are significantly smaller than those reported by the SheepHapMap project [Ne [Ne agree, with the largest and smallest Ne for MER and BL, respectively.The extent and pattern of genome-wide LD are important for QTL mapping of production traits in association studies, i.e., it is the strength of LD between markers and QTL that provide the statistical power to detect associations in GWAS. In our analysis, BL and PD had a significantly higher average LD compared to MER with the latter also showing a higher rate of LD decay. Figure e = 128)  and for and 122) . Howeverr2 and D′ values revealed that at the same genomic distance, the average D′ value was larger than the average r2 value, which is in agreement with previous reports [D′ but not r2 [r2 is the preferred measure of LD in the context of QTL mapping, whereas D′ is the measure of choice to assess recombination patterns. Taken together, both D’ and r2 showed that beyond 20 Mb the average LD values for all populations are very similar to the average value of non-syntenic SNPs  gene, which is associated with the absence of horns in sheep [Higher levels of homozygosity and LD are expected in genomic regions that have undergone intensive selection for a particular trait . Itin sheep  and for in sheep . A QTL ain sheep , 52. We HERC2-like gene i.e. LOC101102534 (between 112.4 and 112.7 Mb) is located near this region and has been reported to affect hair colour and skin pigmentation in humans [OAR2 had the largest number of ROH and a large proportion of genome within haplotype blocks. This chromosome contains SNP OAR2_119604666.1 which had the largest number of occurrences in ROH  animals had at least one ROH that spanned this region. Among these 109 animals, 103 contained SNP s07957.1 (at 50 218 062) in their ROH segments. In this region, PD had a long haplotype block (399.99 kb) of 5 SNPs and BL has two long haplotype blocks of 280.63 and 413.29 kb of six SNPs each. In contrast, MER had two small haplotype blocks of 16.35 and 9.5 kb of two SNPs each. We explored a 1 Mb region (49.2 to 51.2 Mb) in each direction from the SNP s07957.1 on OAR15 and found that this region contains 39 protein coding genes, which represents about 3.6 % of the total number of genes present on OAR15 (1098 genes). The list of the genes with their description and summary functions of their human homologs is in Additional file Genetic diversity and therefore genome-wide LD information is important for genomic selection studies. Genomic selection (GS) uses genetic markers that cover the whole genome to predict genomic estimated breeding values (GEBV). In genomic selection, the accuracy of GEBV depends largely on the heritability of the trait, its genetic architecture and the effective size of the targeted populations. The low levels of LD and high levels of diversity observed in these populations suggest that accuracies of prediction in sheep could be lower than in other populations that have higher LD under similar trait/population scenarios. As proposed by Kijas et al. , denser He) and fixation index (FST), in five Australian sheep populations i.e. the three most economically important pure breeds and two crosses of these pure breeds. LD decayed rapidly in all populations but the rate of decay varied significantly between them. While genetic distances between breeds were relatively modest in comparison to other livestock species, the genetic diversity within Merino was high. The results of this study improve our understanding of the genetic diversity in the three main Australian sheep breeds and will be useful to perform effective GWAS studies. Our results also provide insights into the influence of selection within these breeds and provide useful knowledge that will contribute to design appropriate and successful genomic selection programs.We estimated and compared linkage disequilibrium (LD) and several other genetic diversity parameters, including gene diversity (