Scythians were nomadic and semi-nomadic people that ruled the Eurasian steppe during much of the first millennium BCE. While having been extensively studied by archaeology, very little is known about their genetic identity. To fill this gap, we analyzed ancient mitochondrial DNA (mtDNA) from Scythians of the North Pontic Region (NPR) and successfully retrieved 19 whole mtDNA genomes. We have identified three potential mtDNA lineage ancestries of the NPR Scythians tracing back to hunter-gatherer and nomadic populations of east and west Eurasia as well as the Neolithic farming expansion into Europe. One third of all mt lineages in our dataset belonged to subdivisions of mt haplogroup U5. A comparison of NPR Scythian mtDNA linages with other contemporaneous Scythian groups, the Saka and the Pazyryks, reveals a common mtDNA package comprised of haplogroups H/H5, U5a, A, D/D4, and F1/F2. Of these, west Eurasian lineages show a downward cline in the west-east direction while east Eurasian haplogroups display the opposite trajectory. An overall similarity in mtDNA lineages of the NPR Scythians was found with the late Bronze Age Srubnaya population of the Northern Black Sea region which supports the archaeological hypothesis suggesting Srubnaya people as ancestors of the NPR Scythians. The Eurasian Steppe is a vast grassland region that stretches from the Carpathian foothills to Outer Mongolia. For millennia, the steppe was home to human populations that had a significant and long-lasting impact on the cultural history of the Eurasian continent. One such group that emerged at the beginning of the Iron Age had developed into an ethno-cultural agglomerate commonly referred to as the Scythians. The Scythians are best known from ancient Persian, Greek and Assyrian literary sources mainly for their nomadic warrior lifestyle, but they are also known to have actively practiced farming, pastoralism and may have been among the earliest peoples to master the art of horseback ridingth–3rd century BCE)6th–3rd century BCE) from the Sayano-Altai region of Siberia2th–3rd century BCE, may have been formed on the foundation of pre-existing groups belonging to such cultures as Srubnaya (Timber Grave) and Thracian Hallstattth–7th century BCEThe territory occupied by contemporaneous nomadic and semi-nomadic Scythian groups with shared elements of material culture extended between the lower stretches of the Danube River in the west and the Yenisei River in the east24The relationships between the groups of the Scythian horizon are not fully understood. Some researchers regard the NPR Scythians and Scytho-Siberians as one society on account of similar animal motifs on the products of their material culture, while others consider them to be different populations each having a distinct origin and geographic specificity yet sharing cultural traditionsMost of the current knowledge about the genetic relations among the populations belonging to the Scythian cultural horizon is based on studies of non-coding mitochondrial DNA (mtDNA) fragments from Scythian remains from the lower Don and southern Ural regions in Russia714151617n = 21) and Ukraine (n = 8). Moldavian samples were obtained from the Archaeological Laboratory collection at the Taras Shevchenko University in Tiraspol. Ukrainian Scythians came from the Archeology Archives of the Institute of Archaeology, National Academy of Sciences of Ukraine in Kyiv and Odessa, and the Department of Culture and Tourism of the Cherkasy Regional State Administration. Detailed information about the ancient individuals can be found in We extracted ancient DNA (aDNA) from 29 Iron Age Scythian individuals excavated in present-day Moldova  in Poland. Ukrainian samples consisted of both bone fragments (n = 5) and teeth (n = 3), which were analyzed at the Archaeological Research Laboratory (AFL), Department of Archaeology and Classical Studies, Stockholm University (SU) in Sweden and the Archeogenetics Laboratory at Grand Valley State University (GVSU) in Allendale, Michigan, USA.All procedures leading to Next Generation Sequencing (NGS) were performed in the ancient DNA laboratories located at AMU and the AFL. Mitochondrial hypervariable region I (HVRI) and haplogroup-diagnostic coding regions of mtDNA of the Ukrainian samples were analyzed at GVSU using the methods described in the Illumina sequencing was performed at the National Genomics Infrastructure (NGI) in Stockholm, Sweden. Sequence data were merged and mapped to human genome as previously published®) for human mtDNA provided by MYcroarray®  for mtDNA enrichment by hybridization capture on the Illumina sequencing libraries. The procedure was undertaken on 25 libraries, which did not yield sufficient mtDNA genome coverage (less than 5x), after initial Illumina screening . More details about mitochondrial genome capture can be found in We used commercially biotinylated probes . Long (−M 110), short (−m 35), and low-quality sequences (−q 20) were removed using Cutadapt v.1.8.1We processed sequence data from PGM Ion Torrent using a pipeline adjusted specifically to the Ion Torrent reads. Sequences were demultiplexed by barcodes using the FASTX-Toolkit  was calculated to determine molecular sex of individuals sequenced on the Illumina platformy ratio ≤ 0.016 were identified as females, while those with RY ≥ 0.077 were determined as males  and median network is shown in Comparative ancient samples used in the statistical analyses were retrieved from the web depositories  and literature. Detailed information about comparative samples used in principal component analysis (PCA), pairwise genetic distances  and their frequencies to cover suggested Asian influences into Scythian populations . PCA wasWe have performed top-down clustering analysis in the form of k-means algorithm to explore the unbiased population relations in the PCA based on haplogropup frequencies sample-set. K-means analysis was performed in RapidMiner Studio 7 .FST) were applied only to samples with complete ancient mt genomes  with the most common mutations weighted reversely to their frequency.The median network was calculated and computed for the haplogroup U5 using the Networks 4.614 software , H , J , as well as haplogroups N1b1a, W3a and T2b . East Eurasian mt lineages were represented by haplogroups A, D4j2, F1b, M10a1a1a, and H8c , in total, comprising 26.3% of our sample set.The results of the low-resolution mtDNA screening at GVSU were consistent with whole mt capture results from AMU see . PolymorTo trace genetic affinities between Scythians from present day Moldova and Ukraine (SCU) and other European and Asian ancient populations, their mt haplogroup frequencies were visualized in the space of principle components. The PCA plot of the first two components accounted for 43.4% of the total variance . The SCUFST values calculated on complete mt genomes and visualized using MDS  and Yamnaya (YAM)  populations  and Corded Ware Culture (CWC) . The European Neolithic Linear Ware culture (LBK)  and Near Eastern Neolithic populations (NEN)  appeared most distant to the individuals in our dataset. Correspondingly, in the resulted FST based MDS plot , our Scythian group positioned proximately to Srubnaya (SRU), Yamnaya (YAM) and Unetice (UNC) populations and distantly to Near Eastern and European Neolithic  and Near Eastern hunter-gatherer (HGNE) populations  summarized and tested the distribution of genetic variability within and between subpopulations. We tested several other combinations of grouping Scythians with two or more populations. The results suggested the combination with the highest intragroup and lowest intergroup genetic variability to be the Scythians-Srubnaya sample-set . Second best result was observed in combination of Scythians with Unetice sample-set . The AMOVA results are summarized in Considering the high number of Scythian individuals identified as belonging to haplogroup U5 (31.6%), we conducted median network analysis of published ancient haplotypes belonging to U5a and U5b subdivisions and ranging from the Mesolithic  to the Iron Age . HaplotyOn the basis of published data concerning the phylogeography of mt lineages distribution in ancient populations of Europe and Asia, the 19 complete mt genomes of the NPR Iron Age Scythians produced in this study fall into three main groups of different ancestry. The first group of mt lineages is represented by U5 haplotypes that are considered to be a European Hunter-Gatherer genetic component444446484950Representatives of the U5 haplogroup account for one third of the mt haplotypes identified in analyzed Scythians. These ultimately relate to West Eurasian hunter-gatherers, whose descendants extended throughout the European subcontinent and into East Eurasia from the Mesolithic to the Bronze Age. We have combined the known diversity of the prehistoric U5 lineage from different sources1945464752535455FST = 0.06, FST = 0.04, respectively, p > 0.05), particular lineages such as J1c2, T2b, H/H5, H, W and N1b1a ultimately go back to the earliest European farmers. Lineages of J1c, H5 and T2b belong to the Neolithic farming package of mtDNA haplogroups which have been found in most Neolithic and Bronze Age European populations1944475519The second group of identified mt genomes in the NPR Scythians is comprised of lineages that suggest associations of the NPR Scythians with the Neolithic European farming groups. Although the mt lineage composition of analyzed Scythians significantly differs from that seen in NEN and LBK groups 4747ulations . AMOVA fulations . Our resth -1st century BCE) and Xiongnurd century BCE). Furthermore, haplogroup M have been identified in Pleistocene individuals from western Europe but it is thought that these lineages disappeared due to bottleneck effect in the Last Glacial MaximumThe third group of lineages identified in the NPR Scythians is derived from East Eurasian ancestry. Since, to our knowledge, there is no evidence of agricultural subsistence in East Eurasian Scythians, these lineages should be considered to be genetic components associated with nomadic populations. Mitochondrial haplogroups such as A, D and F have already been found in samples from the Mesolithic, Neolithic, Bronze and Iron Age southern Siberia and the Altai71415161855646566th -2nd century BCE)714161771Previous analyses of mtDNA HVRI sequence data from Scythians inhabiting Rostov-on-Don region in eastern NPR also resulted in the identification of East Eurasian lineages, such as DScythians from Rostov-on-Don as well as Pazyryks from Altai and Inner Mongolia were carriers of mixed east and west Eurasian lineages, with the dominant presence of the latter at 62.5% and 53.3%, respectively71314151617Sequence data from whole mt genomes indicate three potential mtDNA lineage ancestries of the NPR Scythians. The first component traces back to west Eurasian hunter-gatherers and is represented by the lineages belonging to subdivisions of haplogroup U5. The second component is composed of mt lineages connected with Neolithic farming expansion into Europe . The last ancestral mt lineage component is comprised of east Eurasian haplotypes belonging to D, A, F1, H8 and M10 which point to association of the NPR Scythians with east Eurasian populations, in particular from the Altai region. A comparison of NPR Scythian mtDNA lineages with other ancient groups suggests close genetic affinities with representatives of the Bronze Age Srubnaya population, which is in agreement with the archaeological hypothesis suggesting Srubnaya people as the ancestors of the NPR Scythians. However, to provide additional genetic support for this hypothesis data from nuclear genomes are needed.How to cite this article: Juras, A. et al. Diverse origin of mitochondrial lineages in Iron Age Black Sea Scythians. Sci. Rep.7, 43950; doi: 10.1038/srep43950 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


This study assessed the spatial genetic structure of a rare plant (Grevillea) situated along creeks and on floodplains in the Southwest Australian Floristic Region. The landscape features of this unique region and the life-history traits of this species have had profound impacts on its structure. Our results highlight that for conservation of riparian species, avoiding an impact to hydrodynamic processes is critical, as they play a vital role in species gene flow, and consequently, genetic diversity. Understanding this is important for managing threatened species, especially one in an international biodiversity hotspot such as the SAFR in Western Australia. Grevillea sp. Cooljarloo (Proteaceae), which is restricted to a 20 km2 region impacted by mining in the northern sandplains of the Southwest Australian Floristic Region, an international biodiversity hotspot. Within creek lines and floodplains, the distribution is largely continuous. Models of dispersal within riparian systems were assessed by spatial genetic analyses including population level partitioning of genetic variation and individual Bayesian clustering. High levels of genetic variation and weak isolation by distance within creek line and floodplain populations suggest large effective population sizes and strong connectivity, with little evidence for unidirectional gene flow as might be expected from hydrochory. Regional clustering of creek line populations and strong divergence among creek line populations suggest substantially lower levels of gene flow among creek lines than within creek lines. There was however a surprising amount of genetic admixture in floodplain populations, which could be explained by irregular flooding and/or movements by highly mobile nectar-feeding bird pollinators. Our results highlight that for conservation of rare riparian species, avoiding an impact to hydrodynamic processes, such as water tables and flooding dynamics, may be just as critical as avoiding direct impacts on the number of plants.Landscape features and life-history traits affect gene flow, migration and drift to impact on spatial genetic structure of species. Understanding this is important for managing genetic diversity of threatened species. This study assessed the spatial genetic structure of the rare riparian  Gene flow is a key evolutionary force affecting spatial genetic structure within species . Gene flLandscape features impacting gene flow may be striking, for example mountain ranges . This taxon (subsequently referred to as G. ‘Cooljarloo’) is listed as Priority 1 (rare and threatened) by the Western Australian Department of Parks and Wildlife , Western Australia  and bees (including the introduced honeybee Apis mellifera) are likely to play a role in pollination  using ArcGIS 10.1  and visualized as contour lines to illustrate elevation changes within the study region . Creek lBanksia-dominated woodland. The west creek line opens up into a floodplain before continuing west into Nambung National Park , observed and expected heterozygosity (HO and HE) and inbreeding coefficient (FIS), were estimated for each population using GenAlEx 6.5 (AR) and private allelic richness (pR) were estimated for each population at every locus with HP-rare ] ]  in GenAlq) to an assumed genetic cluster, using a Markov Chain Monte Carlo algorithm. Given the restricted range of populations, an admixture ancestry model with correlated allele frequencies was used. The number of potential genetic clusters (K) in the data set was tested from 1 to 10, replicated 10 times for 1 million generations and a burn-in of 100000. Optimum K was identified using the ∆K function of K, and was calculated using STRUCTURE HARVESTER  values for each K, the most likely number of clusters (K) was determined from where the DIC values plateau (K (qi) was obtained to illustrate these values. Similarity among different runs was assessed using the similarity coefficient (H) in CLUMPP 1.1.2 , which represents the strength of spatial autocorrelation, ranging from 0 to 1. In this analysis, the spatial parameter was set ψ = 0.6, as recommended by the authors (PP 1.1.2  for bothG. ‘Cooljarloo’ populations were mapped and sampled had an average elevation of 51 ± 0.5 m (37–79 m), which was significantly lower than the average elevation of 91 ± 2.3 (52–91 m) (P < 0.001) in habitats where G. ‘Cooljarloo’ was not found. Elevational differences affected the habitat types , which reflect the presence or absence of G. ‘Cooljarloo’.Elevation within the study site ranged from 30 to 205 m. Areas where FIS deviated significantly from zero within five populations (P < 0.001). Mean private allelic richness was significantly greater  for floodplain populations (pR = 0.2) than creek line populations (pR = 0.1)  of genetic parameters across nine loci were: number of alleles 5.2 (range = 3.6–6.2), allelic richness 5.1 (3.9–5.9), observed heterozygosity 0.64 (0.58–0.77) and expected heterozygosity 0.69 (0.63–0.76). ulations , with feR = 0.1) . All othFST across all populations was 0.087 (0.028–0.178), mean pairwise DEST was 0.215 (0.072–0.422) (FST = 0.112 (inter), 0.064 (intra), P = 0.024; mean DEST = 0.273 (inter), 0.137 (intra), P = 0.014). The highest pairwise FST value was 0.178 (NPC2/SPC3) and the lowest was 0.027 (WPC2/WPC3), which reflected geographic distance . The highest DEST value was 0.422 (NPC1/SPC2) and the lowest was 0.072 (NPC1/NPC2) again reflecting geographic distance . Pairwise FST for intra-creek population pairs for each individual creek was 0.065 (NPC), 0.060 (SPC) and 0.054 (WPC), and DEST was 0.145 (NPC), 0.097 (SPC) and 0.170 (WPC). In addition, pairwise FST for inter-creek comparisons when we compare one creek to another was 0.105 (NPC vs. SPC), 0.088 (NPC vs. WPC) and 0.138 (SPC vs. NPC), and DEST comparisons are 0.233 (NPC vs. SPC), 0.245 (NPC vs. WPC) and 0.339 (SPC vs. NPC).Mean (and range) pairwise 2–0.422) , and bot2–0.422) . GeneticP = 0.02; Analysis of molecular variance partitioned a small, but significant, amount of the total genetic variation among the three geographic clusters (4.5 %), among populations within geographic clusters (4.6 %) and among individuals within populations (4.1 %), with the remainder (86.8 %) partitioned within individuals . When apD distance ) against logarithmic geographic distance was significant when calculated across all sampled populations .Near identical ordinations were generated from each of the three distance matrices. The first two principal axes in the PCoA of Nei’s distance  explaineK against K[see] values from STRUCTURE indicated two genetic clusters were optimal  suggesting that the admixture model had a better fit , followed by NPC (qi = 0.97) and WPC (qi = 0.78). Two CFP populations, CFP(10) and CFP(34), showed high levels of admixture. CFP (10) showed highest identity with SPC (qi = 0.42) and WPC populations (qi = 0.48), whereas CFP (34) had highest identity with NPC (qi = 0.61) and SPC (qi =0.26) populations. CFP (15) was clustered with SCP populations (qi = 0.99).The distribution of genetic clusters across the creek lines and floodplains as assigned by TESS is illustrated in see. When usGrevillea ‘Cooljarloo’ is restricted to creek lines and floodplains with an average elevation of 51 m a.s.l., and is absent from intervening habitats that average 91 m in elevation. These landscape features strongly influence the distribution and spatial structure of genetic variation for this species. Spatial genetic analyses supported a conclusion of three genetic clusters that largely corresponded to the disjunct regional distribution of G. ‘Cooljarloo’ in northern, southern and western creek lines and floodplains. A significant isolation by distance relationship was associated with comparisons among creek lines, but not within creek lines. Similar levels of genetic differentiation across similarly small spatial scales have been found in many other riparian plant species .The relatively even distribution of alleles, allelic richness, moderately high heterozygosity and weak genetic differentiation within creek lines does not support a largely unidirectional, source–sink relationship between upstream (source) and downstream (sink) populations . This conclusion is consistent with some previous tests of unidirectional dispersal in other riparian systems, where the absence of downstream accumulation of genetic diversity is proposed to be due to upstream seed dispersal through zoochory and higher seed recruitment opportunities in upstream habitats due to density dependence of recruitment (FST = 0.060) was significantly lower than that for pairs of populations among creeks (FST = 0.110), which indicates that landscape features among creek lines inhibit gene flow relative to within creek lines. However, the very wide range of pairwise population genetic distance values between creek lines (FST = 0.032–0.178), despite an overall similarity in geographic distance within creek line populations (FST = 0.030–0.054), much higher than those among creek lines (mean FST = 0.110), despite similar geographic distances. These results suggest that floodplains may be a landscape feature facilitating gene flow independently of distance, and that the non-floodplain landscape between creek lines acts as barriers to gene flow. These results suggest that floodplain flooding events, although less frequent than creek line flow events, provide for more effective and extensive dispersal of seeds. It may also suggest that pollinators are more mobile across floodplains than across creek lines (discussed further below).The mean genetic differentiation among populations within creeks  floodplain populations suggests a directional pattern of dispersal to these habitats. This pattern suggests a source–sink relationship from multiple creek line populations into these floodplain populations. Given that multiple sources are involved, the classic source–sink model predicting lower genetic diversity in sink populations coming from a single succession of source populations  delta K in STRUCTURE, K = 2 and (B) deviance information criterion (DIC) in TESS, K = 3.Supporting Information Figure S1T.H.H. was supported by an Australian Postgraduate Award (APA) and the University Postgraduate Award (UPA) from the University of Western Australia. This work was supported in part by a contract to M.L.M. from Tronox Limited.All authors have made a substantial contribution to the paper.None declared.


Oryza rufipogon Griff. species complex from a wide range of ecological niches. We made strategic expeditions around diversity hot spots in 64 districts of nine different agro-climatic zones of the country and collected 418 wild rice accessions. Significant variation was observed among the accessions for 46 morphological descriptors, allowing classification into O. nivara, O. rufipogon, and O. sativa f. spontanea morpho-taxonomic groups. Genome-specific pSINE1 markers confirmed all the accessions having AA genome, which were further classified using ecotype-specific pSINE1 markers into annual, perennial, intermediate, and an unknown type. Principal component analysis revealed continuous variation for the morphological traits in each ecotype group. Genetic diversity analysis based on multi-allelic SSR markers clustered these accessions into three major groups and analysis of molecular variance for nine agro-climatic zones showed that 68% of the genetic variation was inherent amongst individuals while only 11% of the variation separated the zones, though there was significant correlation between genetic and spatial distances of the accessions. Model based population structure analysis using genome wide bi-allelic SNP markers revealed three sub-populations designated ‘Pro-Indica,’ ‘Pro-Aus,’ and ‘Mid-Gangetic,’ which showed poor correspondence with the morpho-taxonomic classification or pSINE1 ecotypes. There was Pan-India distribution of the ‘Pro-Indica’ and ‘Pro-Aus’ sub-populations across agro-climatic zones, indicating a more fundamental grouping based on the ancestry closely related to ‘Indica’ and ‘Aus’ groups of rice cultivars. The Pro-Indica population has substantial presence in the Eastern Himalayan Region and Lower Gangetic Plains, whereas ‘Pro-Aus’ sub-population was predominant in the Upper Gangetic Plains, Western Himalayan Region, Gujarat Plains and Hills, and Western Coastal Plains. In contrast ‘Mid-Gangetic’ population was largely concentrated in the Mid Gangetic Plains. The information presented here will be useful in the utilization of wild rice resources for varietal improvement.Wild relatives of crops possess adaptive mutations for agronomically important traits, which could play significant role in crop improvement for sustainable agriculture. However, global climate change and human activities pose serious threats to the natural habitats leading to erosion of genetic diversity of wild rice populations. The purpose of this study was to explore and characterize India’s huge untapped wild rice diversity in  O. rufipogon Griff. and O. nivara Sharma et Shastry are of common occurrence in India  (Xa-21 (Pi-9 (Pi-40(t)  . There hx (ORSC) , bacteri)  , BPH resPi-40(t)  and L-myolerance . The croolerance . Howeveructivity .2 (as accessed on 02 February 2016). Indian Genebank at the National Bureau of Plant Genetic Resources (NBPGR) listed 354 accessions of O. rufipogon and 723 accessions of O. nivara3 (as accessed on 02 February 2016).The changing global climate, increasing human population, developmental pressure, and other human activities pose serious threat to natural habitats and consequently to the genetic diversity of the wild rice populations . TherefopSINE1 (Oryza species. Short interspersed nuclear elements (SINE) are found in almost all eukaryotes and are excellent candidates for evolutionary analysis due to their specific characters. Plant SINE1 (pSINE1) retrotransposons were first identified in O. sativa and O. glaberrima by pSINE1 elements, each having large numbers of pSINE1 markers were identified among O. sativa and O. officinalis complexes . Minimum sampling distance between accessions was kept 20 km. Earlier In order to conserve and utilize the fast-depleting Indian wild rice resource, different agro-climatic zones categorized by the Planning Commission of India  were expKharif season of each year from 2011 to 2014 at Indian Agricultural Research Institute, New Delhi, India. Each accession was planted in a single row with 10 plants per row and grid spacing of 50 cm by 50 cm. Each accession was evaluated once in a single year and observations were recorded on three random plants for 46 morphological descriptors (Supplementary Table S2). Traits were evaluated visually and a standard method was followed for transforming each trait value into numeric form using descriptors for wild and cultivated rice  at 65°C for 45 min in a water bath, mixed with equal volume of phenol:chloroform:isoamyl alcohol (25:24:1) and centrifuged at 10,000 rpm for 15 min. The aqueous phase was transferred to a fresh tube and DNA was precipitated overnight with equal volume of chilled isopropanol, dissolved in 100 μl of TE and quantified by agarose gel electrophoresis along with known amounts of bacteriophage λ DNA and also by NanoDrop 8000 spectrophotometer (Thermo Scientific). For species and ecotype identification we used nine different pSINE1 markers according to 2, 0.15 μl of 2.5 mM dNTP mixture, 0.12 μl (0.6 unit) of Taq DNA polymerase (Vivantis), and 5.73 μl of H2O. The temperature profile of the PCR amplification was initial denaturation at 95°C for 5 min, followed by 35 cycles of denaturation at 95°C for 45 s, annealing at 50–56°C for 40 s, extension at 72°C for 1 min, and a final extension at 72°C for 10 min. PCR products were separated by electrophoresis in 2.5% Metaphor agarose gel for pSINE1 markers and 4% Metaphor agarose gel for SSR markers.For molecular characterization, DNA was extracted from the leaves of a single representative plant grown from the original seeds collected during the field expedition using the method of Supplementary Figure S1). To design the new assay a 36-plex Sequenom MassARRAY SNP assay described earlier  of Illumina. After evaluation, the ADT-generated output SNP score file was sent for Oligo Pool Assay (OPA) synthesis. To customize the array, VeraCode technology was employed. The final output score and design ability rank signifies the quality of SNPs and success of OPA. The output score value was kept in the range of 0.600–1.1 and the design ability rank was 1.0 (Supplementary Table S3). SNP genotyping was performed according to the protocol provided by Illumina for VeraCode GoldenGate Genotyping Assay . Data analysis was performed with Genome Studio v2011.1 software with an initial Gentrain threshold of 0.25. Plink software was used to extract the data from genome studio for population structure analysis using STRUCTURE v2.3.4 software  with both burn-in and replication values set at 50,000. The optimal K-value indicates the number of genetically distinct sub-populations while change in the log probability of the data between successive K-values signifies the ΔK . In order to evaluate correspondence between er v3.25  using CSer v3.25  and dender v3.25  and ‘Phaer v3.25 . The anaer v3.25 . The ManO. nivara/O. rufipogon and intermediate wild rice accessions belonging to the ORSC complex from 64 districts of 12 states representing nine agro-climatic zones of India (Supplementary Table S1). Keeping in view the typical wild rice habitats, collections were made from different ecological niches, including uncultivated land near rice fields, rice fields with poor weed control, along roadsides and canals, fresh water ponds, shallow and marshy lands, upland rice fields and nearby fallow lands, costal saline and other stress prone areas . This covered a wide range of ecological niches for both annual (O. nivara) and perennial (O. rufipogon) ORSC wild rice populations. To minimize duplication and capture of representative diversity, wild rice seed samples were collected from sites minimum 20 km apart in remote villages, roadsides and undisturbed areas. To obtain full passport data, farmers, knowledgeable local persons and state university rice breeders were interviewed. The new accessions were collected from wide eco-geographical regions ranging from 14°N to 32°N latitude and 70°E to 93°E longitude and assigned accession numbers NKSWR001–NKSWR396 (Supplementary Table S1). Further, to find new sources of resistance to different biotic and abiotic stresses efforts were made to collect seeds of healthy looking plants growing in the stress-prone ‘hot spot’ areas. Accessions collected during 5 years of exploration were evaluated for different biotic and abiotic stresses, which further helped us revisit some of the areas with useful sources of diversity.Multiple expeditions were made for the collection of Figures 2A,B). Further, in these areas wild rice was plentiful on the roadsides in the protected buffer zone between the road and the farmers’ field. In the upland habitats of Chhattisgarh, Goa, Himachal Pradesh, and Uttarakhand, wild rice was often found growing in the middle of the paddy fields with poor weed management . In general ORSC wild rice was found in the same habitats that have abundant rice cultivation and rarely in the areas devoid of rice farming. Large habitat with more than a hectare of pure stand of wild rice was rare throughout the Indian countryside. The shrinking habitat of wild rice is primarily due to clean cultivation with good weed management and developmental pressure from growing rural and small town population, loss of common uncultivated village land, rampant urbanization and industrialization. Quite often, wild rice was seen growing in the middle of the town within protected boundary walls on land waiting for building construction, which will surely disappear as the construction work is completed, e.g., Khalilabad in Uttar Pradesh and Raipur in Chhattisgarh .From the 64 districts explored, we found that Sibsagar in Assam; Gaya and Patna in Bihar; Daboi in Gujarat; and Azamgarh, Ballia, Basti, Chandauli, and Siddharthnagar in Uttar Pradesh have plentiful pure stands of wild rice in large ponds and shallow lowland habitats (Supplementary Table S2). The analysis of variance for quantitative morphological traits revealed that mean sums of square values were highly significant and hence used for further analysis (Supplementary Table S2). A wide range of variability was observed for the qualitative morphological traits . Similarly, tremendous variability was measured for plant height, culm number, days to 50% flowering, grain length, grain width, panicle exertions, awning, awn color, awn length and anther length. Leaf blade color was green in 176 accessions, dark green in 163, purple margins in 49, purple tips in 17, light green in 11, and purple in one accession. Basal leaf sheath color was purple in 183 accessions, green in 152, light purple in 60, and purple lines in 21 accessions. Leaf angle was erect type in 244 accessions, droopy type in 130 accessions and horizontal type in 21 accessions. As for the growth habit, 115 accessions have spreading habit, 14 accessions have prostrate habit with small rhizomes and 89 have erect type with culm angle of lower than 60°. Panicles were close type in 64 accessions, open type in 119 and intermediate type in 234 accessions. High variability was also recorded for awning and awn color. Six classes of awning was recorded, namely no awns in 19 accessions, short and partly awned in 36, short and fully awned in 78, long and partly awned in four, and long and fully awned in 280 accessions. Six different awn colors were recorded, namely red in 152 accessions, straw in 127, purple in 32, black in 9, golden in 8 and white in the remaining 90 accessions. Panicle exertion also showed six classes, namely enclosed in three accessions, just exerted in 136, well exerted in 127, partly enclosed in 108, moderately well exerted in 21 and partly exerted in 22 accessions. Anther length varied from 1.6 mm in NKSWR009, NKSWR038, and NKSWR107 to 6.0 mm in NKSWR393. Panicle length ranged from 9.3 cm in NKSWR130 to 34.0 cm in NKSWR243. Plant height ranged from 37 cm in NKSWR096 to 226 cm in NKSWR391. Days to 50% flowering ranged from 77 days in NKSWR008 to 158 days in O. nivara 336698, 330630, and 330650. Based on the diagnostic morphological descriptors described in the methods section, 307 accessions were classified as O. nivara type, 66 accessions as O. rufipogon type and 45 accessions as intermediate (O. sativa f. spontanea) type (Supplementary Table S2).The wild rice samples collected from remote villages were planted in the experimental fields at New Delhi and data were recorded for 46 phenotypic traits (descriptors) on all the 418 accessions  are diagnostic markers for the classification of AA genome wild rice species (O. rufipogon) accessions and differentiates them from the other AA genome species. Here, O. nivara Sharma et Shastry is not considered a separate species but taken as an annual form of O. rufipogon Griff. Presence of marker r601 is specific to O. barthii whereas presence of both r601 and r801 is specific to O. glumaepatula. The remaining two AA genome species, viz. O. meridionalis and O. longistaminata, are confirmed by the presence of markers r904 and r705, respectively. We found that all the 418 accessions were positive for the pSINE1-r1 marker allele of 740 bp, indicating that each belonged to the AA genome. Furthermore, the ORSC-specific pSINE1-r502 marker allele of 380 bp was also present in all the 418 accessions, indicating that all belonged to the ORSC complex, namely O. nivara, O. rufipogon or their intermediate type. Marker pSINE1-r2 has been described to differentiate O. rufipogon from O. nivara , 132 as perennial (O. rufipogon), and 102 as intermediate type. Interestingly, the remaining 67 accessions were classified as unknown type because they showed a novel PCR amplicon size not described by pSINE1 ecotypes showed first two principal components accounting for 23.77% of the total variation. PC1 explained 13.62% of the total variance and it separated annual wild rice accessions from perennial and intermediate accessions, whereas PC2 explained 10.14% of the phenotypic variance but there was no clear grouping of the accessions .For an objective classification of the ORSC wild rice accessions in our collection, we analyzed nine different  species . Presenc. nivara . Here, wecotypes . Thus, aSupplementary Table S5). The 24 SSR markers showed total 96 alleles, ranging from two alleles for HvSSR03-23 to six alleles for HvSSR01-22 locus. Major allele frequency (A) ranged from 0.33 (HvSSR05-37) to 0.90 (HvSSR06-34), gene diversity (G) from 0.17 (HvSSR06-34) to 0.75 (HvSSR07-33), heterozygosity (Ho) from 0.0 (HvSSR05-07) to 0.74 (HvSSR07-33), and polymorphic information content (PIC) from 0.16 (HvSSR06-34) to 0.72 (HvSSR07-33). Robustness and competency of SSR markers for studying overall molecular genetic diversity in rice germplasm has been reported earlier . Cluster analysis and distance metrics illustrated that no two accessions were identical, and the collection was genetically quite diverse. In general accessions collected from the same agro-climatic zone grouped together showing close genetic relationship as seen in the color-coded dendrogram . Among the cluster-specific agro-climatic populations, accessions of the EHR zone from Assam (dark green) were confined to cluster II, and those from LGP (light green) and ECP (red) zones were confined to cluster I. On the other hand MGP (black) and WCP (blue) accessions were present in all the three clusters, whereas EPH (orange), WHR (medium green), UGP (magenta), and GPH (cyan) accessions were present in two clusters each. This shows that at least six agro-climatic zones have ORSC populations belonging to more than one genetic lineage, with MGP and WCP wild rice populations being the most diverse.To identify genetic diversity and interrelationship of individuals in our wild rice collection a set of 24 hyper variable SSR (HvSSR) markers, one from each arm of the 12 rice chromosomes was analyzed  and expected (He) heterozygosity ranged from 0.102  to 0.169 (intermediate) and from 0.585 (intermediate) to 0.637 , respectively. The number of alleles (Na), effective alleles (Ne), and fixation index (F) were quite similar for all the four ecotypes (Table 1). Genetic characteristics of wild rice populations collected from nine agro-climatic zones of India showed wide range of observed (Ho) and expected (He) heterozygosity ranging from 0.065 for LGP to 0.247 for EHR and from 0.461 for ECP to 0.619 for MGP, respectively (Table 2). There was significant variation in Na values, ranging from 2.833 for ECP to 4.542 for MGP populations and F-values ranging from 0.549 for EHR to 0.888 for LGP population. Analysis of molecular variance (AMOVA) generated from the genetic distance matrix showed significant variations between populations of different ecotypes and different agro-climatic zones, among individuals and within individuals. Within individual variation is accessed by the GenAlEx software due to varying levels of heterozygosity of marker loci from different segments of the genome. This statistics is not available for pure homozygous individuals. AMOVA for pSINE1 marker-based ecotypes showed the largest proportion of genetic variation (73.6%) was among individuals, followed by 21.4% within individuals and only a small proportion (5%) was due to differences among ecotypes (Supplementary Table S6). To partition the molecular variation on the basis of geographical origin, the nine populations from different agro-climatic zones were analyzed, which revealed a comparatively higher variation of 11% among populations, but the largest proportion of variation (68%) was still among individuals followed by 21% within individuals (Table 3). The Mantel test showed low but significant correlation  between the genetic distance and geographic distance (UTM) matrix of populations from different agro-climatic zones. To measure the level of gene flow between wild rice populations from different agro-climatic zones, a matrix was generated for the number of migrants per generation (Nm) and Fst between each pair of all agro-climatic zones. Overall average Fst was 0.108 at P < 0.001 and average Nm was 1.786 for all the agro-climatic zones. Pairwise Nm analysis based on Fst data matrix showed a high level of gene flow with higher Nm values between geographically adjacent populations as compared to distant populations (Table 4). For example the highest Nm value of 5.234 was between UGP and WHR followed by 4.473 between WCP and GPH regions, whereas the lowest Nm value was 0.571 between EHR and LGP followed by 0.700 between GPH and ECP regions.Genetic characterization of four Supplementary Table S7). The Bayesian model based analysis of population structure of 395 accessions using 48-plex SNP with no missing data showed optimum population structure at K = 3, suggesting three major sub-populations in these accessions. Sub-population I  comprising 12.66% of the accessions and sub-population II  accounting for 49.88% of the accessions both have predominance of pSINE1 annual and perennial ecotypes, while population III (colored blue) accounting for 37.46% of the accessions has predominance of pSINE1 intermediate and perennial ecotypes. The mean Fst values for population I, II, and III were 0.6412, 0.7393, and 0.9345, respectively (Supplementary Table S8), suggesting significant proportion of admixture types in the Indian ORSC sub-populations I and II. Based on our earlier study with a subset of these wild rice accessions along with Indica and Aus rice cultivars and co-clustering of known Indica and Aus rice cultivars in the present study, the sub-populations I, and II are designated ‘Pro-Indica,’ ‘Pro-Aus’ populations, respectively . Interestingly, the Fst values of the 10 Indica and Aus rice cultivars used in this study show substantial admixture of Mid-Gangetic blood in all of them except Nagina 22. Pro-Indica and Pro-Aus sub-populations were distributed widely throughout India but sub-population III was concentrated mainly in the Mid Gangetic Plains and Eastern Coastal Plains, and was designated Mid-Gangetic population . Average distance between individuals in the same cluster (expected heterogeneity) estimated by the STRUCTURE software were significantly different for the sub-populations I, II, and III, with values of 0.1498, 0.1353, and 0.0262, respectively. Admixture types with Fst values of less than 0.9 were observed in each sub-population with the maximum of 54.23% admixture types in sub-population-I, followed by 23.8% in sub-population-II and 22.0% in sub-population-III. This indicates substantial level of natural intercrossing among the three sub-populations of Indian ORSC, particularly with the Pro-Indica sub-population.For determining population structure 418 Indian ORSC wild rice accessions and five each of the Aus and Indica rice cultivars were genotyped using genome wide 48-plex SNP array . Apart from its predominance in the MGP region, the Mid-Gangetic sub-population has significant presence in the Eastern Coastal Plains and Eastern Plains and Hills zones. In contrast to Pro-Aus and Mid-Gangetic sub-populations Pro-Indica sub-population did not dominate any specific agro-climatic zone. In order to examine the specific geographical distribution of pure representatives of the three sub-populations, accessions with Fst values of greater than 0.9 were selected and plotted in the map but there was no significant change in the pattern of geographic distribution of the three sub-populations across India .It was interesting to note that Upper Gangetic Plains, Western Himalayan Region and Western Coastal Plains and Gujarat Hills and Plains zones have the predominance of Pro-Aus sub-population, with minor presence of Pro-Indica type in the WHR, WCP, and GHP zones. The Upper Gangetic Plains and northern parts of the Mid-Gangetic Plains have exclusive presence of Pro-Aus sub-population . Clusters II and III were of mixed type where cluster II has individuals from Pro-Indica and Mid-Gangetic sub-populations while cluster III has individuals from Pro-Indica and Pro-Aus, sub-populations. Cluster-IV, although well separated from the major Pro-Aus cluster VI, also has accessions belonging to Pro-Aus sub-population only. Five Aus rice cultivars were nested in the major Pro-Aus cluster VI, but five Indica rice cultivars were grouped with the mixed type cluster II. Though cluster II was further split into three sub-clusters and Indica rice cultivars were nested with Pro-Indica wild rice sub-clusters IIa and IIc . Interestingly, accessions belonging to the minor Pro-Aus clusters III and IV came from six diverse Agro-climatic zones of India. However, mixed cluster II came from EPH, ECP, LGP, and MGP zones all in the eastern part of India showing that diversity analysis does group the genotypes into additional clusters according to their geographical origin while population structure analysis reveals their inherent genetic structure based on the ancestral lineage (Supplementary Table S9).Diversity analysis based on the 48-plex SNP array data grouped 395 wild rice accessions and 10 rice cultivars into six clusters. Color-coding of the accessions according to their population structure showed that clusters I and V represent Pro-Indica and Mid-Gangetic sub-populations, respectively, whereas clusters IV and VI represent Pro-Aus sub-population . The analysis revealed that at K-values of greater than five large numbers of accessions showed admixture types and there was no clear correspondence between population structure and agro-climatic zones. Up to K4 the Pro-Indica and Pro-Aus sub-populations did not split, but the Mid-Gangetic population was split into two subgroups (1 and 3), whereas at K5 the Pro-Aus sub-population also split into two subgroups (2 and 3) and Mid-Gangetic population remained split into two subgroups (4 and 5) but with no obvious correlation of the subgroups with agro-climatic zones . Interestingly, at K6 the two subgroups of Mid-Gangetic population once again merged into a single group but other two sub-populations showed further splitting and admixtures. Hence, for further analysis we used the optimum population structure of K3.Although the optimum number of sub-populations determined by Structure Harvester based on the ΔpSINE1 ecotypes and the three population structures obtained with the SNP and SSR markers in different agro-climatic zones showed a broad but not exact agreement among the different classifications . According to the morpho-taxonomic classification O. nivara was the predominant species in all agro-climatic zones except the EHR zone where O. rufipogon was predominant species. O. rufipogon was also present though in minor proportion in all the agro-climatic zones except LGP which was occupied entirely by O. nivara. The intermediate type O. sativa f. spontanea was also present in all the zones except EHR and LGP, and was the second most dominant category in the WHR and GPH zones. The pSINE1 ecotypes showed a similar distribution pattern to the morpho-taxonomic species groups in different zones, except that the proportion of perennial (O. rufipogon) and intermediate ecotypes was almost doubled and that of annual ecotype (O. nivara) was halved. The new category of unknown ecotype was also distributed in seven out of the nine zones, and represented fifty percent of the accessions from LGP zone .A comparative analysis of the distribution of morpho-taxonomic species groups, Figure 7 and Supplementary Table S9). However, we have preferred SNP-based population structure because of highly reproducible bi-allelic markers with no missing or ambiguous genotyping scores, and also high number of marker loci in the SNP assay (48 loci) as compared to the HvSSR assay (24 loci). According to SNP assay the Pro-Indica sub-population was present in all the agro-climatic zones except UGP, and it was a predominant group in ECP, EHR, EPH, and LGP zones in the eastern part of India. The Pro-Aus sub-population was present in all the agro-climatic zones without exceptions, and was highly predominant group in UGP, WHR, GPH, and WCP zones in the north-western region of India and the largest group even in the EHR, EPH, and LGP zones in the eastern India. The Mid-Gangetic population was most predominant in the MGP followed by ECP zone, and substantial presence in the geographically adjacent LGP and EPH zones .The agro-climatic zonal distribution of SNP-based population structure showed a broad agreement with SSR-based structure, but with some significant differences. Firstly, the overall proportion of Pro-Aus type accessions was reduced and that of Pro-Indica type was enhanced in the EHR, EPH, GPH, and WCP zones. Also, with SSR-based structure the ECP and LGP zones were fully occupied by the Mid-Gangetic population, whereas with SNP classification these zones showed substantial presence of all the three sub-populations. The interchange of population structure between SNP and SSR markers based classification was largely along the agro-climatic zones  and perennial (O. rufipogon) and also between cultivated O. sativa and wild rice is present among the wild rice populations  have open floral structure and hence they frequently outcross with each other and with cultivated rice . Based on the Fst values, Pro-Indica sub-population showed the highest proportion of admixture types, followed by Pro-Aus population, while Mid-Gangetic population has the least proportion of admixture types. Pro-Indica and Pro-Aus sub-populations, both showed pan India distribution but Pro-Aus sub-population was predominant in the UGP, WHR, GPH, and WCP zones of north-western India. Similarly, the Pro-Indica sub-population was present throughout India but was predominant in the EHR and LGP zones of eastern India. Similar overlapping geographical distribution of wild rice sub-populations with closeness to different domesticated cultivar groups have been reported recently by O. sativa f. spontanea), which can cross frequently with both cultivated and wild rice and produce admixture types  and least proportion of variation was between ecotypes or populations from different agro-climatic zones. Model based population structure analysis using genome wide SNP markers classified the accessions into three sub-populations which show close correspondence with Indica and Aus rice cultivar groups and pure wild rice populations, designated Pro-Indica, Pro-Aus and Mid-Gangetic sub-populations, respectively. There was wide eco-geographical distribution of the Pro-Indica and Pro-Aus sub-populations, while Mid-Gangetic population was limited to the Gangetic plains whereas north-western region of India was occupied predominantly by the Pro-Aus sub-population and the eastern region by the Pro-Indica sub-population. This information will be useful for understanding the process of rice domestication and utilization of wild rice resources for varietal improvement.A fresh collection of 418 ORSC wild rice accessions was made from diverse agro-climatic zones of India and classified on the basis of morphological features in to p-SINE1 markers, data analysis and manuscript writing; NS: designing of SNP genotyping panel; SM: morphological trait measurements, SNP genotyping and data analysis; BPS: collection of wild rice, SSR genotyping; KT: design and maintenance of database; VR: manuscript editing; AS: guiding field experiments; NKS: wild rice collection, planning and supervision of the experiments, manuscript editing and finalization.BS: collection and maintenance of wild rice, phenotyping, genotyping using SSR, SNP and The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


AbstractAcheilognathustypus from present-day range-wide localities to re-evaluate an in-progress restoration program around Lake Izunuma-Uchinuma, Miyagi, Japan. Acheilognathustypus showed low sequence diversity with only eight haplotypes and π and ĥ values of 0.59129 and 0.00118 respectively. Genetic data suggests Acheilognathustypus is adapted to pulsed environments and prone to population flush and crash. Genotyping of populations in introduced localities revealed that their source is not from nearby localities.Genotyping of endangered species is helpful for establishing and evaluating conservation strategies. Mitochondrial sequence data was analyzed from 541 individuals of a critically endangered fish,  Genotyping of endangered species offers opportunities for establishing conservation strategies, particularly for evaluating conservation unit . This isAcheilognathustypus Bleeker, 1863 is a medium-sized bitterling endemic to eastern Honshu Island, Japan. It was a common freshwater fish in shallow lakes, ponds, lowland rivers, and streams several decades ago, but desperately declined after the World War II . A small population near the lake was found in 2001, and restoration project of the bitterling to the lake started in 2003 including transplantation activities Acheilognd War II  with thetivities .Acheilognathustypus from the present range-wide localities for re-evaluation of the restoration program. The dataset of this research is also helpful for conservation programs of this critically endangered fish.In this report mitochondrial sequence data was analyzed from 541 individuals of Acheilognathustypus indicated that introduction took place from #6-1 into #8. Next, individuals were taken from #8 and released to #6-6, and then from #6-6 to #6-5. Introduction into #7 took place from Katsurazawa Pond in Kashimadai before the source population declined.The samples included fin-clips of 541 individuals from 18 localities collected from 2001 through 2011 , 1.2 µL of 10× ExTaq buffer, 0.06 µL (0.3 U) of ExTaq , 1 µL of primers (5 pmol each), 7.28 µL of Milli-Q grade water. PCR reaction started with 3 min at 94°C followed by 35 cycles of 30 sec at 94°C, 30 sec at 55°C, 120 sec at 72°C with final extension at 72°C for 5 min. Both L and H-strand primers worked for double-stranded sequencing with BigDye terminator v.3.1 kit run on an ABI3730 sequencer . Sequences used in this research cover nucleotide position 15640 to 16142 of the mitochondrial genome of Acheilognathustypus (AB239602) . PCR primers were L16019 on the L-strand (GCTACCAAAGCCAGAATTCTAA)  and CrpHB239602) . DDBJ/Gexy-(πx+πy)/2 where πxy is average number of nucleotide difference between populations x and y, and πx and πy stand for this value between individuals within populations x and y. We inferred population expansion and contraction states calculating PageBreakized sample size was set at 30 for each locality  and rounded up and down for minor and major haplotypes respectively to make them integer for calculation conveniences and approximation  based on pairwise net nucleotide divergence indicated that introduced stocks  are close to each other, distant from others and somewhere in between localities in Fukushima  and others Fig. . Except PageBreakconservative but still gave similar results. Paucity in number (1-3) of haplotypes in individual localities with positive D values is due to further subsequent bottleneck after the overall geological bottleneck and expansion  of 20 years ago, Lake Kasumigaura (172 km2) of more than 30 years ago, and Teganuma Lake (4 km2) of 45 years ago were such good habitats for Acheilognathustypus    Fig. , Table 3Acheilognathustypus into the ponds #6-6 from #8 and then from #6-6 to #6-5 took place when population at #6-1 declined temporarily. At that time it was not possible to introduce Acheilognathustypus from #6-1 which was the only known locality near Lake Isunuma-Uchinuma. Pond #8 was then selected for the source of pond #6-6 based on the unverified information that it was introduced from #6-1, but it was misleading.Introduction of PageBreakalso found after intensive survey . We conducted this genetic research after the finding of these populations, and identified the introduced populations near the lake  were not representatives of the past Lake Izunuma-Uchinuma population.A lesson from above is importance of intensive survey of habitats, both known and unknown, before introduction. Population at #6-1 recovered in 2011 (Table


Cylindrus obtusus is one of the most prominent endemic snail species of the Eastern Alps. It is restricted to alpine meadows and calcareous rocky habitats above 1500 m. Peculiar intraspecific differences have been observed in its genital tract in the eastern populations the two mucus glands associated with the love dart sac are highly variable, while almost no variation was observed in the western populations. This raises the question whether the mode and success of reproduction of the respective populations are different. To find out whether these anatomical differences reflect genetic differentiation, which might be an indication for distinct glacial refugia, we investigated a 650 bp fragment of the mitochondrial cytochrome oxidase subunit 1 gene (COI)  and 9 microsatellite loci from samples  covering the whole distribution range of the species.COI sequences show a geographic differentiation between eastern, central and western populations. The westernmost localities, which were covered under ice sheets during glacial periods, are characterized by extreme low variability. Overall genetic distances among all individuals are small (max. 1.7% p-distance). The microsatellite analysis reveals a high differentiation between populations, implying restriction of gene flow. The highest genetic variability was found in the central populations. Remarkably, nearly all individuals from the eastern populations, which are more variable in their genital morphology, are homozygous in all microsatellite loci, although different alleles were found within populations.The C. obtusus as indicated by the microsatellite data in the easternmost populations. This finding is supported by the deformation of the mucus glands in the same populations. Since mucus glands play an important role in sexual reproduction, it seems plausible that in selfing organisms these structures are reduced. The phylogeographic structure revealed by COI sequences implies that the species has survived the ice ages within the Calcareous Alps. The small genetic distances among all individuals (max. 1.7%) suggest that C. obtusus has experienced severe bottlenecks in the past.The most peculiar outcome of the study is the strong evidence for selfing in The online version of this article (doi:10.1186/s12862-017-0977-0) contains supplementary material, which is available to authorized users. Cylindrus obtusus  ),ensities . The seqC. obtusus represents a single species and that there are no cryptic species hidden in this taxon. However, the altered mode of reproduction in the eastern populations can be considered as a factor that could foster isolation and thus future speciation.Cryptic species are a known phenomenon especially in gastropods, which might lead to underestimation of animal diversity . The oveCOI sequences revealed a geographic differentiation between eastern, central and western populations of C. obtusus, suggesting survival in several refugia during the last glacial periods which were probably accompanied by severe bottlenecks.The phylogeographic results based on In the current study we discovered an exceptional example of different reproduction modes in geographically separated populations. On the basis of microsatellite data we conclude that the easternmost populations of this hermaphroditic land snail species reproduce predominately by selfing. This finding is supported by the deformation of the mucus glands in the same populations. Mucus of these glands covers the love dart in the course of normal sexual reproduction in hermaphroditic pulmonate land snails and is the reason for increased probability of paternity for the dart shooting partner. The more western populations have homogenously developed mucus glands and the population genetic parameters show no signs for selfing. Our phylogeographic data indicate that these eastern populations survived the last glacial maximum in a separate refugium. Thus, we assume that, probably due to drift effects during glacial bottlenecks and postglacial expansion in the eastern habitats, an altered reproduction mode might have become predominant. It remains to be investigated whether interbreeding between the two forms still may occur.C. obtusus investigated in the present study were collected in the years 1997 to 2010 and cover the whole distribution range. Additional file The samples of COI was amplified with the primers CO1alb_fw (5′-CCA CTA ACC ACA AAG ATA TTG GGA C-’) and CO1Cyobt1_rv (5′-ATT AGA ATA TAC ACT TCC GGA TGG Cc-3′). The resulting sequence (without primers) was 662 bp in length. PCRs were performed on a Master Gradient thermocycler (Eppendorf) in 25 μl with 1–3 μl template DNA, 0.5 unit Taq DNA polymerase (Roche), 0.5 μM of each primer and 0.2 mM of each dNTP (Roche). Each PCR comprised 35 reaction cycles with an annealing temperature of 50 °C. Control reactions were carried out for both DNA extractions and PCR amplifications. PCR products were purified using the QIAquick PCR Purification kit (Qiagen) and analyzed by direct sequencing (both directions). Sequencing was performed at LGC Genomics  using the original PCR primers.DNA was extracted with the First-DNA all-tissue Kit (GEN-IAL), following the manufacturer’s protocol and a final elution volume of 100 μl. A section of the mt Microsatellites used in the present study were isolated and tested by Arthofer et al. . The folPCR amplifications were performed in a volume of 12.5 μl using 1 μl DNA. For multiplexed loci, a QIAGEN Multiplex PCR Kit  was used with 0.2 μM of each primer and the PCR conditions described in Arthofer et al. : 15 min The sequences determined in this study are deposited in GenBank under the accession numbers: MF153098 - MF153377. Microsatellite data are stored in the Dryad Digital Repository under doi:10.5061/dryad.4gr1h.p-distances were calculated using MEGA version 4 [www.fluxus-engineering.com), putting equal weight on each site and using the postprocessing option ‘mp calculation’. The numbers of haplotypes, haplotype and nucleotide diversities were determined with ARLEQUIN 3.11 [Sequences were edited in BioEdit version 7.0.5.3 . There wersion 4 , which wersion 4  and to persion 4  were conUIN 3.11 . For cluUIN 3.11  and the UIN 3.11 , 54.The software package ARLEQUIN 3.11  was usedWe used the Bayesian methodology of STRUCTURE  to estimAdditional file 1: Figure S1.COI sequences. Each individual is defined by an individual Id, the origin of geographic region, and the Id of the sampling sites. For relevant nodes, bootstrap values are indicated. (PDF 1433 kb)Neighbour joining tree of the Additional file 2: Figure S2.Principle component analyses (PCA) of microsatellite and sequence data. (PDF 1565 kb)Additional file 3: Table S1.Nucleotide and haplotype diversity (standard deviation in parentheses) calculated for geographic regions. Ni = number of individuals, Nl = number of localities, H = number of haplotypes, h = haplotype diversity, pi = nucleotide diversity. (PDF 324 kb)Additional file 4: Figure S3.Summarising in a rarefaction approach the Allelic Richness of sample size g = 10, g = 20, and g = 30 and the mean number of private alleles multiplied by 10 of g = 12. The groupings of the mt haplotypes  and populations with low or no selfing versus high selfing are indicated. (PDF 1431 kb)Additional file 5: Figure S4.Isolation By Distance (IBD) as calculated for the whole microsatellite data set; the western together with the central populations; and for the eastern population separately. (PDF 1463 kb)Additional file 6: Table S2.COI: individuals for which the COI was sequenced; IndId ms: individuals which were analyzed with microsatellites; geographic information (PDF 438 kb)Sampling site information. spId: sampling Id; IndId Additional file 7: Table S3.All voucher specimens were deposited in the Mollusca collection of the 3rd Zoological Department of the Natural History Museum Vienna . The numbers behind the last slash correspond to those in Additional file


Cephus cinctus Norton (Hymenoptera: Cephidae), is a key pest of wheat in the northern Great Plains of North America, and damage resulting from this species has recently expanded southward. Current pest management practices are inadequate and uncertainty regarding geographic origin, as well as limited data on population structure and dynamics across North America impede progress towards more informed management. We examined the genetic divergence between samples collected in North America and northeastern Asia, the assumed native range of C. cinctus using two mitochondrial regions (COI and 16S). Subsequently, we characterized the structure of genetic diversity in the main wheat producing areas in North America using a combination of mtDNA marker and microsatellites in samples collected both in wheat fields and in grasses in wildlands. The strong genetic divergence observed between North American samples and Asian congeners, in particular the synonimized C. hyalinatus, did not support the hypothesis of a recent American colonization by C. cinctus. Furthermore, the relatively high genetic diversity both with mtDNA and microsatellite markers offered additional evidence in favor of the native American origin of this pest. The genetic diversity of North American populations is structured into three genetic clusters and these are highly correlated with geography. Regarding the recent southern outbreaks in North America, the results tend to exclude the hypothesis of recent movement of damaging wheat stem sawfly populations from the northern area. The shift in host plant use by local populations appears to be the most likely scenario. Finally, the significance of these findings is discussed in the context of pest management.The wheat stem sawfly,  Cephus cinctus Norton, (Hymenoptera: Cephidae) is one of the most serious pest for wheat production in North America with annual losses exceeding US$350 million [i.e. Montana, North Dakota, South Dakota) [C. cinctus was first observed in Colorado nearly 150 years [The wheat stem sawfly,  million . The mai Dakota) , 2. Rece50 years . Tiller C. cinctus infestations afterwards followed the westward movement of wheat production across the Canadian prairies and the northern US parts of the Great Plains [Cephus cinctus has been considered for a long time as a North American species, originally attacking native grasses and gradually adapting to wheat (i.e. to spring wheat and more recently to winter wheat) after the introduction of the crop by European settlers in western North America. However, an alternative hypothesis, based on morphological observations from individuals of Cephus hyalinatus Konow collected in northeastern Asia emerged in the 1990's [C. hyalinatus under C. cinctus. They further suggested that several other Asian species, including C. camtschatcalis Enslin and C. zahaikevitschi Ermolenko, may also be conspecific with C. cinctus. Moreover, only four other species in the grass-mining tribe Cephini are present in North America. The European wheat stem sawfly, Cephus pygmaeus (L.) and the black grain stem sawfly, Trachelus tabidus (F.) are known to have been introduced from Europe [Calameuta clavata (Norton) and Calameuta middlekauffi Smith and Schiff which are poorly known species found in the western United States [C. cinctus and the synonimized C. hyalinatus collected in Asia, using two mitochondrial regions (COI and 16S). These findings should provide new insights into the origin of North American wheat stem sawfly populations.Although the wheat stem sawfly is a key pest of wheat in North America, its origin remains obscure. This species was first reported and described from samples collected from wild grasses in Colorado in 1872 , 6. It wm Europe , 11 and d States , 13. TheC. cinctus populations relies on negligible use of insecticides, host plant resistance programs and the optimization of conservation biological control and various tillage operations [i.e. population size changes, range expansions or contractions) [C. cinctus on wildland grasses, and understanding gene flow among those populations would provide valuable information. In the second part of the study, we characterize the structure of genetic diversity in the populations of the wheat stem sawfly in the main wheat producing areas of western North America using a combination of mtDNA marker and five microsatellites on samples collected both from wheat and from grasses in wildlands. Finally, the significance of these findings is discussed in the context of pest management.Current management of erations , 2. Howeerations . The paterations –16, the erations  and alsoerations , 19 and actions) . Little actions) . The autCephus cinctus and, more broadly members of the genus Cephus, are widely regarded as important insect pests of wheat. Research on these species is welcomed by farmers because understanding their biology and behavior may be useful to protect crops from losses due to these pests. Thus, for sampling carried out on private lands, we had permission from the owners. Collection of these species on public lands was conducted in compliance with existing regulations for insects defined as non-commercial, as determined by local offices. Additionally, these field studies did not involve endangered or protected species.C. cinctus were collected between 2001 and 2014 across two Canadian provinces and six US states  and native Bromus marginatus Nees ex Steud.  (C. cinctus [Samples of S states . SamplinPoaceae) . Because cinctus , in whicC. hyalinatus were kindly provided by the National Museum of Natural History, Smithsonian Institution  and comprised dried, pinned museum samples collected between 1960 and 1970 in Siberia, except for one specimen that was collected in Inner Mongolia (China) in 2002 and was preserved in alcohol . Specimens of C. fumipennis were identified by Dr. Aiping Liu  and subsequently confirmed by D. Smith.Specimens of For fresh samples, extraction of total genomic DNA was performed using Qiagen DNeasy Blood & Tissue kit following manufacturer’s protocol (July 2006) after several washes to remove ethanol. For museum samples, a non-destructive DNA extraction was performed using the DNeasy extraction protocol (Qiagen Inc) as modified by C.D. Zhu & J.S. Noyes (unpublished).C. cinctus, collected in Canada, Montana and Colorado, these samples corresponding to the most common haplotypes of the two lineages found across North America (see section on Phylogeography of North American Wheat Stem Sawflies).For this phylogenetic study, we focused on seven specimens of COI) and a 442 bp of the ribosomal 16S RNA (16S). Additional details on primers and PCR conditions can be found in www.codoncode.com) and multiple alignments were performed using CLUSTAL W [16S and COI sequence datasets were merged with the homologous regions obtained from the complete mitochondrion sequencing of four Cephidae species that were obtained from NCBI .Polymerase chain reaction (PCR) amplifications were conducted for two mitochondrial gene fragments: a 264-bp region of the cytochrome c oxidase subunit I  with 200,000 MCMC generations, a thinning value of 100 and a burn-in of 25%. As recommended by the developers, the convergence of the MCMC chain was confirmed visually [The Poisson tree processes (PTP) model for species delimitation  was usedvisually .COI mitochondrial region was partially amplified (762 bp) with C1-J-2183 and TL2-N-3014 pair of primers as described by Simon et al [The Intraspecific phylogenetic relationships were analyzed in two different ways. First, we reconstructed by Bayesian analysis using MrBayes 3.1.2. The methodology was the same as previously described. An haplotype network was then constructed in PopART  using TCHd) and nucleotide diversity (π) for each of the sampling locality was conducted with Arlequin 3.5 [D [Fs [For further analysis, sampling locations containing one or two individuals were pooled with the nearest sampling site or excluded when the sites were too much isolated (> 30km). The estimation of gene diversity (quin 3.5 . Demogran 3.5 [D  and Fu’s5 [D [Fs . These tK = 2 to K = 10) using 10,000 permutations from 100 random initial conditions. Each group defined by SAMOVA was analyzed separately for its gene diversity (Hd) and nucleotide diversity (π). Allelic richness r was computed using the rarefaction method proposed by Petit et al [http://www.pierroton.inra.fr/genetics/labo/Software/Contrib).A spatial analysis of molecular variance (SAMOVA) was used to investigate geographical structure with SAMOVA 1.0 . This apit et al  with ConFinally, a hierarchic analysis of molecular variance (AMOVA) was applied between collections from wildland grasses and wheat fields to test for host plant effect on the genetic structure of populations. This analysis was conducted with the software Arlequin 3.5.Five microsatellite markers, described by Hartel et al  were useAR) with the rarefaction method, observed and expected heterozygosity (Ho and He) and inbreeding coefficients (Fis) were estimated using FSTAT 2.9.3.2 [Deviation from Hardy-Weinberg equilibrium and linkage disequilibrium between pairs of loci were tested with Genepop 4.2.1 . Allelic 2.9.3.2 .K ranging from 1 to 8. We assessed the uppermost level of population structure by using the ΔK method [To explore the population structure within the whole dataset, we used the Bayesian clustering approach implemented in Structure 2.3.4 . An admiK method  implemenK method . The graK method .Traditional methods may be useful for describing population structure and complementary to Bayesian methods , we alsoFST. Estimation of FST values and their statistical significance was conducted using Arlequin 3.5. Isolation by distance (IBD) was examined within the whole dataset and separately for the groups detected with Structure. IBD was investigated by testing the correlation between pairwise FST and geographical distances using the Mantel test as implemented in Genepop.The level of genetic differentiation among populations was quantified by the estimation of the pairwise 16S and COI) were successfully amplified from all specimens. All haplotypes discovered in this study were deposited in GenBank under the accession numbers reported in COI sequences were aligned with a 264 bp portion and the 16S sequences were aligned with a 442 bp portion.The two loci  in the COI dataset and null in the 16S dataset  and 2.3% (±0.7) for COI and 16S respectively) were lower than the pairwise divergences observed at the congeneric level (COI (0.5% ± 0.2) and ten times higher for 16S (0.2% ± 0.1). The level of COI pairwise divergence between C. cinctus and C. hyalinatus was 8.0% (± 1.7) and 9.5% (± 1.6) for Lineage 1 and Lineage 2 of C. cinctus, respectively. The 16S pairwise divergence was 5.3% (± 1.0) between C. cinctus and C. hyalinatus and 5.0% (± 1.0) for the Lineage 1 and Lineage 2 of C. cinctus . The Bayesian phylogenetic tree was well supported as major nodes were supported by posterior probabilities ≥ 0.75  while nucleotide diversity was 0.012 (± 0.006). Reduced haplotype diversity and nucleotide diversity were observed in several populations distributed across the sampling area, mainly in Saskatchewan, Canada and Colorado, USA . When coD tests  and Fu’s FS tests (for one site in Colorado) showed significant negative values  and within populations (40.75%: P < 0.001). Only a small and non-significant fraction of differentiation was attributed to host plants (6.65%: P = 0.060).AMOVA showed that the genetic variation was quite evenly distributed among populations within groups , with highest values observed in the southern populations and the lowest in western Montana. Expected heterozygosity ranged from 0.512 to 0.770 , and theThe NJ tree constructed from Cavalli-Sforza and Edward’s chord distances showed a split between three groups matching the clusters identified with Structure: (i) the populations from western Montana, (ii) the populations from the North  and (iii) all southern populations  and the population from North Dakota .K = 2 in all runs, largely corresponding to western Montana vs. all other populations  being Q = 53.4% for the Southern cluster and Q = 45.6% for the Northern cluster  than the differentiation observed between populations of the Northern and Southern clusters (mean FST = 0.060).The level of genetic differentiation among populations was low to moderate with pairwise clusters . The paiversus genetic distances was statistically significant (p < 0.001) indicating a weak IBD, with a Mantel correlation coefficient (Mantel r) of 0.09, however, Mantel tests for IBD within each cluster were non-significant.Across all populations, the Mantel test of geographic Cephus cinctus with morphological observations combined with historical data [C. cinctus. The genetic divergence for COI between C. cinctus and C. hyalinatus collected from the presumed native range of C. cinctus (i.e. Asia) and more specifically Siberia , obtained from C. fumipennis was considered as a good candidate [C. cinctus, indicating that it is not a suitable host for the parasitoid [C. hyalinatus in northeastern Asia, combined with the genetic methods applied here, would allow to confirm or infirm the present results and definitively would help in elucidating the origin of this pest.To date, only one study has examined the assumption of Asian native status of cal data . The pre cinctus ) was wit cinctus . This suequences  and the equences , this meequences , 54–57 aequences . Furtherequences , 60. Likandidate . Howeverrasitoid . In the Cephus genus. The only previous phylogeny of the Cephinae, based on another COI region, did not include either C. cinctus or C. hyalinatus or other potential Asian conspecifics [Cephus species, but coloration varies, hence it may cloud the systematics for those species [The present data confirm that a revision of the genus is clearly needed to understand species delineation. To our knowledge, there is no complete phylogeny of the pecifics . Color d species . An inte species , 64.C. hyalinatus is high both for the COI and the 16S sequences, suggesting that Lineage 1 corresponds neither to C. hyalinatus nor to any of the species considered. The evidence of two divergent lineages was unexpected as only two Cephus species are known from the USA [Among the 63 mitochondrial haplotypes, we observed two divergent lineages, Lineage 1 and 2. Lineage 1 corresponds to only two individuals collected in the Rocky Mountains in western Montana. Moreover, the divergence observed between the Lineage 1 and  the USA , 23. ThiK method suggested that the uppermost level of population structure was K = 2, however the ΔK method may underestimate the number of population clusters [K = 3, the resulting clustering corresponds largely to those observed with the mtDNA analysis. Moreover, the NJ tree provided similar qualitative outcomes and the PCoA was largely congruent with the definition of three clusters. Consequently, both mitochondrial and microsatellite data identified three genetic clusters in our sampling set  showed the same divergent pattern of the wheat stem sawfly development between western and eastern Montana [versus southern populations were documented , which both include exotic species, are considered. Regarding the genetic pattern observed across the Rocky Mountains, this area corresponds to a less disturbed environment where the wheat cover is less abundant than in the others sampled localities. Rand et al [C. cinctus in response to increasing amounts of landscape-level wheat cover although no correlation was found between this variable and C. cinctus infestation, as might be expected. The Mountain cluster could be best explained by the topology of this area. The Rocky Mountains correspond to an area of rugged topology with isolated arable valleys that might act as physical barriers limiting the gene flow between populations and might explain the highest level of differentiation observed. Isolated populations with limited gene flow with others increase the chance of inbreeding as supported by relatively high positive FIS values observed in several populations from the Mountain cluster.In phytophagous insects, host plant, habitat fragmentation, reproductive system, dispersal capacity and geographical or reproductive barrier are reported as the main drivers of genetic structure , 17, 69.nd et al  found coHigh genetic diversity within populations is highly advantageous for colonizing species as it enables responses to selection pressure. Some wheat production practices such as the increase of no-till agriculture, provide a favorable environment for this insect. This practice may enhance the sawfly overwintering survival, increasing the population size and its potential range expansion , 23, 70.C. cinctus. These findings are important for management, particularly when the use of biological control agents is considered [Bracon cephi and Bracon lissogaster [Our results support the North American origin of nsidered , 61, 66.nsidered . The ressogaster , 66, forBromus spp. were highly abundant. Species composition at these sites could consist of an exotic subspecies of Bromus inermis (Bromus inermis ssp. inermis), or smooth brome, introduced into North America in the late 1880’s and is commonly found in wheat fields or in close proximity [Bromus inermis (Bromus inermis ssp. pumpellianus), or Pumpelly’s brome, and/or the native mountain brome, Bromus marginatus. Smooth brome, Pumpelly’s brome and mountain brome are found in all areas where C. cinctus samples were collected. Nevertheless, 16 haplotypes were found at sites where these congeneric populations were, therefore some members of this genus could act as a reservoir for the wheat stem sawfly. However, smooth brome would not be a good host in terms of suitability, despite its apparent attractiveness to foraging and ovipositing adults [We observed a parallel pattern of the wheat stem sawfly genetic diversity for individuals collected in wheat and grasses. The three haplogroups have been detected both for wheat and grasses and only a low (and non-significant) fraction of the structure was attributed to host plants. However, the absence of an “host effect” remains tentative as the sampling on grasses was restricted to Montana (mainly distributed in western Montana) and, most of individuals were swept in sites where one genus of grass, actually three members of roximity , 74, andg adults . By 1928g adults . This asThe present study shows that there are three different genetic clusters distributed across the North American wheat production area. These distinct evolutionary units, with potentially different biological characteristics , 65, 66,C. cinctus for long distances is unlikely, but not impossible [C.cinctus habitat that is now dominated by wheat. Farms have become larger and often wheat fields for a single farming operation can be separated by more than 20 miles. Thus, necessary flights across fallow land can be a greater distance than in the past. Little is known about the dispersal ability of sawflies in general, however it is considered that they weakly disperse by active flights [Another interesting point highlighted by the results is the discrepancy between the assumed low mobility of the wheat stem sawfly  and the possible . However flights . For the flights . TypicalC. cinctus. Western wheatgrass, Pascopyrum smithii (Rydb.) A. Love, widely used in private and commercial settings, is one example of widespread planting of C. cinctus host plants in locations where they have been displaced for many years. It is not possible to determine if changes in wheat cultivation or increasing restoration of native hosts of C. cinctus are important in the rapid spread of new populations in the southern part of its range in winter wheat. However, movement of C. cinctus populations may be less impaired with patchy localized restoration of hosts across urban and suburban landscapes and increased planting of favored hosts in transportation corridors.Other practices that have changed in recent years relate to cultivation and landscape practices. Revegetation efforts in modern prairie landscaping and disturbed areas, including highways , 79, witDiabrotica virgifera virgifera [A further implication of this finding is an overall high risk of spread of resistance alleles, due to the apparent gene flow, at least within clusters. One strategy used to control wheat stem sawfly populations is the development of new resistant cultivars, primarily solid-stemmed wheat varieties , 80, 81.irgifera , could pS1 Appendix(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S1 FigFCT for K = 2–10 groups.Values of fixation index, (DOCX)Click here for additional data file.