Lycaon pictus) and lions (Panthera leo), and to test correlations between genetic distance, geographic distance and landscape resistance due to human activity. We found weaker connectivity, a stronger correlation between genetic distance and geographic distance, and a stronger correlation between genetic distance and landscape resistance for lions than for wild dogs, and propose a new hypothesis that adaptations to interspecific competition may help to explain differences in vulnerability to isolation by humans.Current extinction rates are comparable to five prior mass extinctions in the earth’s history, and are strongly affected by human activities that have modified more than half of the earth’s terrestrial surface. Increasing human activity restricts animal movements and isolates formerly connected populations, a particular concern for the conservation of large carnivores, but no prior research has used high throughput sequencing in a standardized manner to examine genetic connectivity for multiple species of large carnivores and multiple ecosystems. Here, we used RAD SNP genotypes to test for differences in connectivity between multiple ecosystems for African wild dogs ( Large mammals are among the most affected taxa2, and large carnivores have experienced particularly large declines in numbers and geographic distribution4. While many African protected areas have retained all of their large carnivores, the lion (Panthera leo), cheetah (Acinonyx jubatus) and African wild dog (Lycaon pictus) are all considered vulnerable or endangered7, and understanding the processes that allow demographic and genetic connections between small and increasingly isolated populations of such species is critical for their long-term conservation8.Current extinction rates are unprecedented in human history, and are comparable to five prior mass extinctions in the earth’s history10, which is increasingly determined by human activity12. More than half of the earth’s terrestrial surface has been modified by humans13, and extensive data from GPS tracking show that animal movements decrease as the human footprint increases14. Because of the concerns described above, large carnivores are well-represented in research on the ways that the human activities affect animal movement15 and connectivity between carnivore populations has been a focal point for many large-scale conservation efforts 17. Despite these efforts, we are aware of no prior research that has applied standardized methods to test the relationship between landscape resistance and genetic connectivity for multiple large carnivores and multiple ecosystems. Connectivity between a given pair of ecosystems is affected not only by the landscape, but also by species’ traits8, and within the African large carnivore guild, well-documented responses to interspecific competition are likely to affect connectivity through opposing effects on individual movement and population density. In direct interactions between species, lions and spotted hyenas (Crocuta crocuta) are behaviorally dominant, while cheetahs and African wild dogs are subordinate, and populations of the dominant competitors invariably outnumber those of the subordinates20. Wild dogs and cheetahs reduce competition through diet partitioning, temporal segregation and spatial segregation24, and there is consistent evidence that they often persist within an ecosystem by avoiding unfavorable locations where competition is strong26.Connections between ecosystems depend on their area and isolationsubordinate competitors, and (ii) correlations between anthropogenic landscape resistance and genetic differentiation will be weaker for subordinate competitors. Broadly, the Competition-Movement-Connection hypothesis focuses on the effect of species’ traits on connectivity27. More narrowly, it identifies interspecific competition as a strong limiting effect for subordinate competitors in this guild, and suggests that the adaptations that allow subordinates to avoid unfavorable locations within ecosystems28 will also facilitate connectivity between ecosystems, if the adaptations are sufficiently general . In contrast, the Competition-Density-Connection hypothesis notes that dominant competitors within this guild attain higher population densities, and  predicts that (i) landscape-scale genetic differentiation will be weaker for dominant competitors, and (ii) correlations between anthropogenic landscape resistance and genetic differentiation will be weaker for dominant competitors 37. We quantified anthropogenic landscape resistance between ecosystems by fitting a circuit model to the Human Footprint Index (HFI), which provides ground-truthed one km2 resolution mapping of built environments, crop lands, pasture lands, human population density, night lights, railways, roadways, and navigable waterways11. The HFI combines these effects in a single measure of human alteration of the landscape that has been shown to detect effects on animal movement14 and allows repeatable analysis for other species and ecosystems. Prior validation of the HFI confirms that it has low root-mean-squared-error for the biomes in this study38. Finally, we tested correlations between genetic distance, geographic distance and landscape resistance using Mantel tests39.We tested these predictions using SNP genotypes for African wild dogs  and lions  in Zambia  and southern Tanzania (Selous). Briefly (see full methods below), we collected tissue samples and recorded locations  but strong for lions . The correlation between genetic distance and anthropogenic landscape resistance  but strong for lions .African wild dogs showed considerably stronger connectivity between ecosystems than lions, suggesting that a strong capacity for individual movement overrides the effects of low population density. Ordination of SNP genotypes with t-distributed stochastic neighbor embedding revealed extensive genetic overlap between ecosystems for wild dogs and little genetic overlap for lions Fig. . Spatial43 and has long been recognized as an important force structuring large carnivore guilds46. Our results suggest that the adaptations of subordinate competitors may increase connectivity between ecosystems by promoting their ability to move through areas with unfavorable conditions47, even though competition holds them at low population densities25.Interspecific competition affects virtually all species48, translocations complicate the task of identifying the sources of traffic). Fencing can also be used as a conservation tool for small populations50, with obvious consequences for connectivity. In this study, we examined only populations that have not been affected by fencing or translocation.Our analyses compared three ecosystems for each species and measured geographic distance and anthropogenic resistance between each pair of ecosystems, but only two ecosystems (Luangwa and Kafue) were sampled for both species. We did not examine lions in Liuwa because this population is mainly derived from lions translocated from Kafue. Southern Tanzania’s Selous Game Reserve provided an alternative lion population with similar isolation by distance and anthropogenic resistance, and all of the patterns hold if one restricts attention only to Kafue and Luangwa Figs  and 3. T55. Because variation in the distribution and intensity of human hunting is not captured by changes in the physical landscape, its potential effects on connectivity were not included in this analysis. Further study is warranted to test whether its effects within ecosystems propagate into connectivity between ecosystems.Legal and illegal human hunting can drive local source-sink dynamics in lions and other carnivores, both by drawing individuals out of protected areas to vacant territories where hunting has occurred (promoting movement), by increasing mortality rates just outside protected areas (impeding movement), or by decreasing population density RAD SNP genotypes at thousands of loci contain enough information to detect recent restrictions in gene flow  and the hypothesis that subordinate competitors are better connected than dominant competitors  warrants testing with other species and locations. More broadly, it is well established that species’ traits affect connectivity, but there is considerable scope for better understanding of the traits and processes that most affect connectivity. Finally, our analysis shows that the human footprint affects not only short-term movementsAs part of long-term field studies conducted with methods approved by the Zambia Department of National Parks and Wildlife and the Tanzania Commission for Science and Technology and Department of Wildlife, we collected tissue biopsies in the field when individuals were anaesthetized for radiocollaring or snare removal. Other individuals were sampled with little disturbance using biopsy darts (PneuDart) fired from a stationary vehicle with a Dan-Inject JM Standard air rifle. Within Zambia, samples were collected only by licensed wildlife veterinarians and within Tanzania samples were collected only by trained personnel with extensive experience using biopsy darts, following guidelines of the Department of National Parks and Wildlife (Zambia), and the Commission for Science and Technology (Tanzania) approved by the Montana State University Animal Care and Use Committee (protocol 2010-39). Samples were immediately transferred to ethanol for storage. We extracted DNA at our Luangwa field site using the QIAsymphony DNA kit (Qiagen) according to manufacturer’s instructions. Extract quantity and purity were assessed at our lab in Sweden initially using a spectrophotometer . DNA quality for sequencing was further screened by gel electrophoresis using the Kodak Electrophoresis Documentation and Analysis System 120 (Eastman Kodak), and finally screened using a Qubit prior to library preparation and sequencing at the National Genomics Institute, Stockholm.DNA extracts from lions and wild dogs were sequenced using DNA associated with the restriction site for EcoR1, optimizing the trade-off between breadth of coverage (≈1% of the genome) and read depth (minimum of 30 × /nucleotide). Specifically, we used EcoR1 to digest 0.5 μg of each DNA extract according to manufacturer’s instructions. We removed the activated enzyme using the MinElute Reaction Cleanup kit (Qiagen) in two elutions, and visualized the second elution by gel electrophoresis to assess the quality of the digestion. Satisfactory samples (91%) were sent to the National Genomics Institute (Stockholm) for library construction and preparation. Fragments 400 to 700 bp were excised and blunt end repaired. Paired-end, multiplexed adapters were ligated to the fragments by sample, and equimolar concentrations were sequenced on an Illumina HiSeq. 2500 or NovaSeq, resulting in 2 × 150 bp paired-end reads. We demultiplexed sequenced Illumina reads using the barcode_splitter option of the FASTX Toolkit (v 0.0.13) and removed adapters with cutadapt . Reads were trimmed and quality filtered using the FASTX Toolkit trimmer and quality_filter options respectively using the settings: q 10, p 70. Sequence quality was assessed using FastQC . Sequences were used as input for SNP detection using Stacks (v. 2.0), with settings m 5–10, M 4, n 3. These procedures yielded genotypes for 3,528 SNP loci from 205 lions in 3 ecosystems, and for 2,584 loci from 96 wild dogs in 3 ecosystems.http://corearray.sourceforge.net/tutorials/SNPRelate/. We examined spatial variation in genotypes using ordination by t-distributed stochastic neighbor embedding. We confirmed that patterns of similarity and difference between ecosystems from t-SNE were stable across iterations and were the same as those produced by the PCA procedures of the SNPRelate package. We also used spatial PCA to describe spatial variation in genotypes. We identified the sPCA components to retain for each species following procedures described by Jombart at https://github.com/thibautjombart/adegenet/wiki/Tutorials, retaining one global component in the sPCA for lions  or Zambia and Tanzania (lions), and using CircuitScape to obtain current maps linking each pair of ecosystems (with zero resistance within ecosystems). Pairwise resistance values from CircuitScape were used as entries in the landscape resistance matrix.We calculated genetic distance across all loci as the Euclidean distance from the first three t-SNE components, and compared these to matrices of geographic distance and anthropogenic landscape resistance using Mantel tests. We obtained anthropogenic landscape resistance values by downloading the global Human Footprint Index dataset from Dataset 1Dataset 2Dataset 3Dataset 4Dataset 5Dataset 6Supplementary Tables and Figures


Galeus melastomus, Scyliorhinus canicula) and two rajid skates . Sampling and experimental analyses were designed to primarily test if the Sicilian Channel can be considered as effective eco-physiological barrier for Mediterranean demersal sympatric elasmobranchs.The unique and complex paleoclimatic and paleogeographic events which affected the Mediterranean Sea since late Miocene deeply influenced the distribution and evolution of marine organisms and shaped their genetic structure. Following the Messinian salinity crisis and the sea-level fluctuations during the Pleistocene, several Mediterranean marine species developed deep genetic differentiation, and some underwent rapid radiation. Here, we consider two of the most prioritized groups for conservation in the light of their evolutionary history: sharks and rays (elasmobranchs). This paper deals with a comparative multispecies analysis of phylogeographic structure and historical demography in two pairs of sympatric, phylogenetically- and ecologically-related elasmobranchs, two scyliorhinid catsharks  obtained from a total of 248 individuals sampled in the Western and Eastern Mediterranean Sea as well as in the adjacent northeastern Atlantic Ocean. Phylogeographic analysis was performed by haplotype networking and testing spatial genetic differentiation of samples . Demographic history of Mediterranean populations was reconstructed using mismatch distribution and Bayesian Skyline Plot analyses.R. miraletus more structured than R. clavata. However, such structuring of skate lineages was not consistent with the separation between Western and Eastern Mediterranean. Sudden demographic expansions occurred synchronously during the upper Pleistocene  in both skates and G. melastomus, likely related to optimal environmental conditions. In contrast, S. canicula experienced a slow and constant increase in population size over the last 350,000 years.No spatial genetic differentiation was identified in either catshark species, while phylogeographic structure of lineages was identified in both skates, with The comparative analysis of phylogeographic and historical demographic patterns for the Mediterranean populations of these elasmobranchs reveals that historical phylogeographic breaks have not had a large impact on their microevolution. We hypothesize that interactions between environmental and ecological/physiological traits may have been the driving force in the microevolution of these demersal elasmobranch species in the Mediterranean rather than oceanographic barriers. The Mediterranean Sea has been universally recognised as a cradle of biodiversity . This chScyliorhinus canicula  and R. miraletus L. (brown skate), and the scyliorhinid catsharks Galeus melastomus  and Scyliorhinus canicula L. , was analysed at three mitochondrial gene fragments which have been proven polymorphic at the population level , which may potentially have driven their microevolution. Nucleotide variation in the target species, namely the rajid skates on level . SamplinR. miraletus) due to catchability and/or selectivity characteristics of associated fishing methods . Individuals were specifically assigned using the available identification guidelines and keys  and associated biological data were collected during international research cruises  Agreement area and amending Council Regulation (EC) No 1967/2006 concerning management measures for the sustainable exploitation of fishery resources in the Mediterranean Sea, adopted by the Council on 20th October 2011 (2011/C 345 E/01).Okamejei kenojei . The thermal profile consisted of an initial denaturation step at 94 °C for 5 min, 35 cycles of denaturation at 94 °C for 30 s, annealing at Ta  was extracted using the CTAB protocol . Three m; MEGA 7 . A conse; MEGA 7  accordinFor each species, COI, NADH2 and CR partial sequences were aligned with ClustalW algorithm implemented in MEGA and concatenated to generate a combined dataset for subsequent analyses.The software DnaSP v.6  was usedSpecies-specific haplotype networks were created using the TCS method as implemented in PopART v.1.7 .a priori hierarchical geographical structure on three levels: between sub-basins; between geographical areas, within sub-basin; within geographical areas. The statistical significance of the resulting Φ values was estimated by comparing the observed distribution with a null distribution generated by 10,000 permutations, in which individuals were redistributed randomly into samples.The Analysis of Molecular Variance (AMOVA) was performed with Arlequin v.3.5  groupingThe population structure was also assessed by a Principal Component Analysis (PCA) performed with the software Past v.2.03  on a paiD, Fu’s FS and Ramos-Onsis & Rozas’s R2 neutrality tests  were used as test statistics with 1,000 bootstrap replicates. Lastly, we reconstructed the historical demography using the coalescent-based Bayesian Skyline Plot approach  were high in all samples, with the exception of the skate samples from Balearic, Ligurian and Tyrrhenian Seas (h and nucleotide diversity (π) were significantly higher in the EMED than in the WMED samples in all species, except for S. canicula  (The thornback ray  (NEATL) . SlightlR. miraletus, exhibited a stronger phylogeographic structure across the Mediterranean samples than R. clavata, indicated by the presence of three Mediterranean and one northeastern Atlantic/Western Mediterranean haplotype clusters . Conversely, high molecular variation was detected between geographical areas within sub-basins in R. clavata, R. miraletus and S. canicula, revealing a genetic structure independent from their grouping in Western and Eastern Mediterranean sub-basins.The AMOVA  did not D, Fu’s FS and Ramos-Onsins & Rozas’s R2 indexes were largely consistent within each species  revealed that the observed distributions were not statistically different from those expected under a sudden expansion model in all species, even if the SSD and rg values of R. miraletus were higher than those estimated for the other species  did not always differentiate populations of marine phylogenetically- and ecologically-related taxa with similar differentiation patterns for instance, the discordant differentiation genetic patterns of the Atlantic-Mediterranean seabream species canicula .G. melastomus, a species widely distributed in the outer continental shelves and upper slopes , and the small-spotted catshark S. canicula, which inhabits the shallow waters of continental shelves  and the uppermost slopes (200–400 m depth). For the blackmouth catshark, our findings are consistent with the results of a recent small-scale study, which showed an absence of population structure and high connectivity in the Western Mediterranean Sea  did not display well-identified geographical haplotype clusters. Both species showed any specific mtDNA lineage in the Adriatic Sea and this appears different with respect to the R. polystigma, that exhibited a weakly divergent but fixed COI haplotype . Thus, further analyses based on high-resolution markers, should be conducted in order to explore these scenarios.Although mtDNA variance was not significantly different between Western and Eastern Mediterranean populations in any of the elasmobranch species considered, we detected significant differences in the levels of genetic diversity in three out of four taxa. In R. miraletus  that has been estimated solely from rajid lineages and with different mtDNA gene fragments  Click here for additional data file.10.7717/peerj.5560/supp-2Table S2GM= G. melastomus; SC, S. canicula; RC, R. clavata; RM, R. miraletus.PCR and sequencing primers. Primer pairs and annealing temperatures (Ta) used to amplify and sequencing the three mitochondrial DNA fragments in the four elasmobranch species. The annealing temperatures for the PCR reactions are also reported. Click here for additional data file.10.7717/peerj.5560/supp-3Supplemental Information 1Click here for additional data file.10.7717/peerj.5560/supp-4Supplemental Information 2Click here for additional data file.10.7717/peerj.5560/supp-5Supplemental Information 3Click here for additional data file.10.7717/peerj.5560/supp-6Supplemental Information 4Click here for additional data file.


Capsicum genotypes from different geographical areas of Ethiopia with the aim of capturing genetic diversity. Morphological traits and high-resolution melting analysis distinguished one Capsicum baccatum, nine Capsicum frutescens and 132 Capsicum annuum accessions in the collection. Measurement of plant growth parameters revealed variation between germplasms in parameters including plant height, stem thickness, internode length, number of side branches, fruit width, and fruit length. Broad-sense heritability was maximum for fruit weight, followed by length and width of leaves. We used genotyping by sequencing (GBS) to identify single-nucleotide polymorphisms (SNPs) in the panel of 142 Capsicum germplasms and found 2,831,791 genome-wide SNP markers. Among these, we selected 53,284 high-quality SNPs and used them to estimate the level of genetic diversity, population structure, and phylogenetic relationships. From model-based ancestry analysis, the phylogenetic tree and principal-coordinate analysis (PCoA), we identified two distinct genetic populations: one comprising 132 C. annuum accessions and the other comprising the nine C. frutescens accessions. GWAS analysis detected 509 SNP markers that were significantly associated with fruit-, stem- and leaf-related traits. This is the first comprehensive report of the analysis of genetic variation in Ethiopian Capsicum species involving a large number of accessions. The results will help breeders utilize the germplasm collection to improve existing commercial cultivars.We established a collection of 142  Capsicum in the Solanaceae family, commonly known as chilli peppers, are major crop plants and are almost cosmopolitan in distribution [Capsicum, namely C. annuum L., C. chinense Jacq., C. frutescens L., C. baccatum L. and C. pubescens Ruiz et Pav., represent the most economically important vegetables worldwide [Members of the genus ribution . Chilli ribution  and are ribution , 4. The ribution . The fivorldwide .Capsicum from its primary center of cultivation, Bolivia and Peru [Capsicum growing areas [Capsicum species growing in different regions has been reported [Capsicum [The independent diffusion and subsequent domestication of the five cultivated species of and Peru , to Eurong areas . Charactreported . It has Capsicum .th century and subsequently from all over the world; they have since been cultivated for centuries and adapted to varied pocket agro-ecological zones. Such situations contributed to the evolution of local Ethiopian genotypes with different fruit types, pungency levels and disease resistance [C. annuum inbred line, H3, was reported to be the most important and persistent source of powdery mildew (Leveillula taurica) and have been used to breed resistant varieties [Capsicum species indicated the existence of considerable genetic variability.According to Bozokalfa and Eşiyok , capsicusistance . Adaptatarieties . Differearieties . Owing tarieties , Shumbularieties , Marame arieties  and GeleCapsicum genotypes, including multivariate analyses of large numbers of phenotypic descriptors [Capsicum spp. [Capsicum [Germplasm diversity is crucial to successful breeding programs. Such diversity is important for broadening the genetic base, as it increases the probability of finding more unique genes for which two parents have different alleles . Numerous methods have been used to estimate genetic diversity among criptors , 7, 15 acriptors  and molecriptors . Since mcum spp. . Next-gecum spp. . NGS hascum spp. . The usecum spp. . Genotypcum spp. . The usecum spp. , 20. It cum spp. . It is hcum spp. . In the Capsicum –28.Capsicum germplasms collected from different localities of the six regions of Ethiopia using morphological and molecular markers to explore the genetic diversity available in a wide collection of germplasm. The data presented herein may be useful to understand the diversity of Capsicum in Ethiopia and use the information for the breeding purpose. Similarly, our finding may give additional insight into the quantitative trait loci controlling fruit weight.The present study was undertaken to characterize Capsicum by the EBI based on the descriptor: four as C. frutescens and 38 as C. annuum. According to the germplasm descriptors, the EBI collected peppers in Ethiopia during 16 different years since the first germplasm record from the Limu wereda of the Oromia region in 1978. The majority of Capsicum germplasm collection (59%) was done between 1984 and 1990, during which most geographical areas with significant pepper cultivation were covered. In this experiment, three plants of each of the 142 germplasms were grown under greenhouse conditions at Biotong Seed Co. Ltd., Anseong, Republic of Korea, in 2017. Seeds were disinfected using 2% sodium chlorate and 10% trisodium phosphate.The germplasm collection of 142 genotypes used in this study was obtained from the Ethiopian Biodiversity Institute (EBI). These germplasms were collected from different pepper-growing areas of the country: 47 from eight zones of Amhara ; five from the Metekel zone of Benishangul Gumuz ; 38 from eight zones of Oromia ; 40 from five zones of the Southern Nations, Nationalities and Peoples (SNNPs) region ; one from the Jigjiga area of Somali ; and two from different weredas (districts) of Tigray  . Ten gerFor each germplasm, 12 growth traits and nine flower-, 17 fruit- and two seed-related traits were evaluated according to the descriptions used by the Rural Development Administration (RDA) gene bank, South Korea, with some modifications . MorpholTomato analyzer version 3.0 was used to measure fruit perimeter (FP), fruit area (FA), fruit width mid height (FWMH), maximum fruit width (MFW), fruit height mid-width (FHMW) and fruit curved height (FCH) as previously described . A SpearThe phenotypic (PCV) and genotypic (GCV) coefficients of variation were estimated as percentages of the corresponding phenotypic and genotypic standard deviations from the trait grand means as used by Khan et al. . EstimatCapsicum germplasms, high-resolution melting (HRM) was performed as described previously [C. annuum, C. chinense, C. frutescens, C. chacoense and C. baccatum, were used.To the identify the species of 142 eviously , 33. A Reviously . Five reTwo or three young leaves from each germplasm were used as sources of DNA. Total DNA was extracted using the modified cetyl trimethylammonium bromide (CTAB) method as described previously . The conPstI (rare cutter) and MseI (frequent cutter). Each GBS library was a 96-plex library consisting of 60 and 82 samples from the Capsicum diversity panel . Data analysis and SNP identification were performed as described previously . Raw rea2 values and imputed ratio of minor and major alleles were used to select suitable imputed quality. A final filtering was performed based on minor allele frequency of more than 0.05, SNP coverage >0.6 and inbreeding coefficient >0.8. The P values of SNPs from GWAS were subjected to a false-discovery rate (FDR) analysis, and Bonferroni correction was done to reduce false-negative results from the GWAS analysis. A significance threshold level at a P value of 0.05 was set after Bonferroni multiple-test correction.The 53,284 filtered SNPs were used for genome-wide association (GWAS) mapping. The default settings of Genomic Association and Prediction Integrated Tool of the R package were used to estimate GWAS based on the compressed mixed linear model . SNPs wiCapsicum genotypes as well as the geographically based subpopulations were also identified by PowerMaker version 3.25. To investigate the population structure, assess genetic diversity and remove near-duplicates , both parametric and non-parametric approaches were used. Pairwise geographic distances between accessions, pairwise FST between accessions in the different groups and analysis of molecular variances (AMOVAs) were calculated using GenAlEx 6.503, with 999 permutations for testing variance components [For each SNP, polymorphic information content (PIC), heterozygosity (H2), gene diversity, genotype number, allele number and allele frequency were calculated using Power Marker software , and themponents .http://pritch.bsd.uchicago.edu/structure.html) [K from K = 1 to K = 5. The best number of K was chosen with the DeltaK method [Population structure was estimated from 13,998 selected SNPs from the 53,284 polymorphic SNPs used in GWAS analysis that can easily be handled by the software used for population structure analysis. Population structure was determined using STRUCTURE software (re.html) , which wK method  by runniK method .Phylogenetic trees were produced using genotyping data with 53,284 SNP markers using both the unweighted neighbor-joining method and the hierarchical cladding method based on the dissimilarity matrix calculated with Manhattan index, as implemented in the DARwin software (version 6.0.9) , and wasC. annuum, C. frutescens and C. baccatum. The four markers C2_At5g19560, C2_At5g50020, Waxy and PepTrn showed a polymorphism that was highly specific for the three species , C2_At5g50020 (13), Waxy (eight) and PepTrn (32). Confirmation of C. baccatum status was made on the basis of the specific melting curve shape using PepTrn and C2_At5g50020 markers. C. frutescens accessions were likewise identified on the basis of melting curve shape using the markers Waxy and PepTrn. C2_At5g50020 also identified two C. frutescens accessions (SNU-142 and SNU-143).In addition to the preexisting identification of some of the germplasms by EBI, and the assessment of morphological features  and SNP  species . Eighty-Capsicum types from Amhara, Oromia, SNNPs and Tigray. The only fasciculate Capsicum type was obtained from the Bibugn wereda of Amhara at an altitude of 1850 m.a.s.l.  gene bank of South Korea. Plant habits were spreading (12.9%), half-spreading (59.7%), erect (26.6%) and fasciculate 0.7%). Spreading types were collected from Amhara, Oromia and SNNPs at altitudes ranging between 1000 and 2570 meters above sea level (m.a.s.l.), while the altitude range for half-spreading plant types was 1150–2780 m.a.s.l. distributed in different locations of Amhara, Benishangul Gumuz, Oromia, SNNPs, Somalia and Tigray. A relatively narrower altitude range (1200–2060 m.a.s.l.) was observed for the erect m.a.s.l. .Capsicum growing regions, with a wider altitude range (1000–2570 m.a.s.l.). Wider variation in stem thickness was observed in C. annuum (6.32–33 mm) than in C. frutescens (7.2–15.7 mm). Mean stem thickness for C. baccatum was 23.3 mm. The maximum mean internode length (11.4 cm) was measured for C. frutescens, while the minimum (9.23 cm) average internode length was observed for C. annuum. Similarly, the maximum average number of side branches below first node  was counted in C. frutescens, followed by C. annuum  , stem thickness (6–33 mm), internode length (4–18.5 cm) and number of side branches (4–30) all evidenced variation. The seven tallest germplasms (140–175 cm in height) were collected from SNNPs at a mean altitude of 1300 m.a.s.l. Short to medium-height germplasms were collected from all of 4–30) .C. annuum and SNU17-34 from C. frutescens), had two. The maximum measured fruit length was 14.4 cm and the minimum was 1.8 cm, each found for one accession. Respectively, 24%, 22%, 21%, 19%, 18% and 12% of germplasms had fruit lengths measuring 8, 5, 4, 7, 6 and 9 cm. The minimum fruit length score was 3 cm (seen for seven germplasms). Fruit width ranged between 0.3 and 3.2 cm. The majority of germplasms (39%) had fruit widths measuring 2 cm, with 35% measuring 1.5 and 22% measuring 2.5 cm. The fruit shape index, which is the ratio of fruit length to width, ranged between 1.5 and 13. Whereas the fruits of 73.5% of germplasms have two locules, 24.3% had three locules. Only three germplasms  displayed four locules. Weights of fruits varied between 1 and 22 g. Seed number per fruit ranged from zero for one germplasm  to over 175 for two other germplasms of C. annuum (SNU17-102 and SNU17-116).Other morphological traits similarly showed variation . Most geEstimates of phenotypic (PCVs) and genotypic coefficients of variation (GCVs), broad-sense heritability and genetic advance are shown in We identified 2,831,791 genome-wide SNPs in our germplasm panel. We filtered these by removing rare alleles , alleles with high missing ratios (absent from more than 30% of the germplasms) and alleles with high heterozygosity (more than 80%). To explore the genetic diversity of the panel, we analyzed all the germplasms using 53,284 high-quality SNPs. The chromosomal distribution and proportion of polymorphic markers used for the competition is shown in C. annuum and 0.701 in six C. frutescens germplasms. Categorically, the average C. annuum PIC value for the major growing region (SNNPs) was 0.693 per marker, with a range running from 0.692 in six germplasms collected from Gurage and Kembata zones to 0.693 in 24 germplasms collected from Gurage, Kembata, Bench Maji, Keficho and Semen Omo zones. A similar trend was observed in the PIC values of C. annuum for the Amhara and Oromia regions, representing respectively 39 and 24 germplasms. For the C. frutescens germplasms of SNNPs, the average PIC value was 0.701 per marker, and for Oromia it was 0.964. The overall gene diversity and mean heterozygosity were 0.74 and 0.02, respectively.The amount and organization of genetic diversity among the model-based populations is presented in To quantify the genetic diversity within and among subpopulations, we partitioned the total molecular variance into two clades according to the STRUCTURE simulation result. Averaged across the 130 germplasms, 92% of the total genetic diversity was partitioned between germplasms within the subpopulations, and only 8% was attributed to differences at the individual level .Capsicum germplasms using the program STRUCTURE 2.3.4 [K from 1 to 5 with 10 iterations using 130 germplasms. The estimated likelihood (lnP(D)) was greatest for K = 2 (Capsicum germplasm panel [Fst) statistic for genetic differentiation. We observed a low average distance (HE) between individuals in the same clade in subpopulation C1 (0.05) and a higher HE in subpopulation C2 (0.07). The FST values for subpopulations C1 and C2 were 0.713 and 0.850, respectively.We inferred the population structure of the 130 Ethiopian RE 2.3.4 . We carror K = 2 , suggestsm panel . The claC. frutescens germplasms were grouped separately from C. annuum , Amhara (47 germplasms), Oromia (37 germplasms), Benishangul (5 germplasms), Somali (1 germplasm) and Tigray (2 germplasms), which accounted for 24%, 33%, 26%, 3.5%, 0.7% and 1.4% of germplasms, respectively. The growing altitude range of C. frutescens (1200–1310 m.a.s.l.) was narrow compared with that of C. annuum , the number of markers linked to various traits varied from a maximum of 187 for fruit length to a minimum of one for fruit shape index, leaf color, petal length, petal width and stem color  is especially highly valued for its high pungency for flavoring and coloring. Work by Berhanu et al. [C. annuum. We also recognized the presence of some C. frutescens collections, known locally as "mitmita", growing on some part of the country. They are known locally for being highly pungent. Yayeh (1998) had previously described the existence of C. frutescens in Ethiopia [Capsicum species across Africa was described by Eshbaugh (1983), who summarized the evolutionary history of peppers and described how the genus was introduced to East Africa [C. annuum and C. frutescens in West African countries [The greater the genetic diversity of germplasm, the greater is the chance of success in breeding desirable strains. Knowledge of population structure and genetic diversity is essential for association mapping studies, genomic selection and the classification of individual genotypes into different groups. In the present study, we classified Ethiopian u et al. , Shimeliu et al.  and Abrhu et al.  had demoEthiopia . In addit Africa . Similarountries .Although morphological traits are important in the study of genetic diversity, because of their mostly polygenic nature and their dependence on various environmental factors, they may not always reflect real genetic variation . Owing tCapsicum species. Two enzymes, PstI and MseI, were used to reduce genome complexity, consistent with previous studies by Han et al. [We performed GBS for genotyping 142 germplasms of n et al. . Using tHeritability values are helpful in predicting the expected progress to be achieved through the process of selection; high heritability coupled with high genetic advance (GA) is an indicator of a high proportion of additivity in the genetic variance, and consequently suggests that a high genetic gain can be expected from selection . The herOur panel of germplasms exhibited a wide range of genetic diversity for different agro-morphological traits. Plant habits as a measure of plant architecture; growth parameters including plant height, stem thickness, internode length, number of side branches; and morphological traits such as number of flowers per axil, length and thickness of fruits, fruit weight and number of locules all showed variation among germplasms.Capsicum germplasms investigated in this study. The PCoA showed tight clustering within the first clade, composed of C. annuum, and the second clade, in which all C. frutescens are grouped. A previous diversity study of 39 cultivated Ethiopian C. annuum strains using AFLP distance estimation, however, showed four major clusters [C. frutescens has been shown to have close affinity to C. annuum, they were grouped separately in this study [Ho (observed heterozygosity) as compared to He (expected heterozygosity) in the subpopulations indicated the presence of inbreeding in the majority of Ethiopian Capsicum germplasms. The average distance (HE) between individuals in same clade value was lower in subpopulation C1 (0.05) than in subpopulation C2 (0.07), indicating that C1 contained less variation. Genetic differentiation (FST) value for subpopulations C1 and C2 were 0.713 and 0.85, respectively, predicting that the germplasms in the two clades have several genotype patterns. There was a significant correlation between some of the morphological traits, such as plant height and fruit width, as indicated by SNP-marker-based matrices   and Han GWAS identified 31 SNP markers for fruit weight in this study. On chromosome 3, the SNP markers were co-localized at two different locations with the QTL reports of Han et al. (2016), Chaim et al. (2001) and Nimmakayala et al. (2016) , 51, 54,Capsicum germplasms, representing the six administrative regions covering all Capsicum-growing agro-ecologies in the country. Our morphological and molecular characterization provides insight into the genetic variability of Capsicum in Ethiopia.This study is the first detailed characterization of a large sample of the Ethiopian Capsicum germplasms showed high variation that can be exploited for the further breeding. Two distinct subpopulations were identified from the 130 accessions used in this study based on SNP information from our GBS library. Model-based population structure, phylogenic study and PCoA revealed similar results. Probably because of the existence of a dominant informal seed-distribution system in the country, the majority of germplasms collected from different geographical areas were grouped into the same or different clades, without clear association with growing region. However, clade 1, which contained the majority of germplasms, consisted mainly of C. annuum and C. baccatum. Clade 2 was composed mainly of C. frutescens accessions collected from different growing regions of the SNNPs region. GWAS analysis helped us to further identify significant markers associated with important morphological traits, some of which were co-localized with reported QTLs. Besides providing additional information to identify candidate genes for the traits considered, this study reconfirms the validity of using GBS and downstream analysis for marker-assisted selection in Capsicum.The phenotypic and molecular characterization of Ethiopian S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.S8 Table(XLSX)Click here for additional data file.S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S4 Fig(DOCX)Click here for additional data file.


Vombatus ursinus) in south‐east Australia that are presently—but were not historically—isolated by marine barriers. Using genome‐wide single nucleotide polymorphisms, we identified three genetically distinct groups  corresponding to the recognized subspecies. However, isolation by distance was observed in the Tasmanian population, indicating additional constraints on gene flow can contribute to divergence in the absence of marine barriers, and may also explain genetic structuring among fragmented mainland populations. We additionally confirm origins and quantify the genetic divergence of an island population 46 years after the introduction of 21 individuals from the Vulnerable Bass Strait subspecies. In the light of our findings, we make recommendations for the maintenance of genetic variation and fitness across the species range.Island populations can represent genetically distinct and evolutionarily important lineages relative to mainland conspecifics. However, phenotypic divergence of island populations does not necessarily reflect genetic divergence, particularly for lineages inhabiting islands periodically connected during Pleistocene low sea stands. Marine barriers may also not be solely responsible for any divergence that is observed. Here, we investigated genetic divergence among and within the three phenotypically distinct subspecies of bare‐nosed wombats ( This event isolated Tasmania and an array of islands from continental Australia during the flooding of Bass Strait, protecting some populations from causes of extinction that are present on the mainland  is a large (up to 50 kg), fossorial marsupial endemic and historically widespread in south‐east Australia , Bass Strait islands  and Tasmanian  , and (c) assess the genetic provenance of the Maria Island population with respect to conservation genetic resources of V. u. ursinus. Discovery of genetically distinct populations across the wombat range will assist in determining spatial units that warrant independent management and support ongoing conservation planning for this Australian marsupial.Here, we utilize genome‐wide single nucleotide polymorphisms (SNPs) to (a) quantify the population structure of bare‐nosed wombats across their current range in the context of the presently recognized subspecies and their potentially dynamic history of connectivity, (b) document within region genetic variation to assess gene flow within a continuously distributed and sampled subspecies , Bass Strait islands , Tasmania  and Maria Island , representative of the bare‐nosed wombat distribution, were sent to Diversity Arrays Technology Pty Ltd (DArT), Canberra, Australia, for DArTseq analysis. DArTseq utilizes complexity reduction  and next‐generation sequencing methodologies to produce genome‐wide SNPs , missing data per locus (>20%), missing data per individual (>10%), secondaries , minor allele frequencies (≤0.05), mean read depth per sample (<8) and heterozygosity (>0.5). Outlier SNPs identified according to both pcadapt . This approach was taken to reduce the risk of mis‐identifying SNPs as out of HWE that are truly reflective of genetic structure . Filtering resulted in a total of 9,064 SNPs for 162 individuals  were performed for the mainland region given the discrete spatial sample distribution and potential for false inference of genetic breaks if isolation by distance operates  following the methodology of Meirmans . The RDA33.1Ho = 0.19‒0.21), followed by Tasmania , and Maria and Flinders islands . The western mainland  had the lowest genetic diversity .Diversity estimates are described in Table 3.2p ≤ 0.01) after correction for false discovery rates. The mainland was less differentiated from Flinders and Maria islands (FST = 0.24) than it was from Tasmania (FST = 0.32), and Tasmania was most differentiated from the Flinders and Maria islands (FST = 0.33). Within the mainland, central Victoria (cVIC), eastern Victoria (eVIC) and New South Wales (NSW) had lower population differentiation (FST = 0.07–0.11), but experienced higher differentiation from South Australia . Differentiation was also assessed at the population level within mainland groupings (Supporting information Data FST = 0.05), and their differentiation from other populations was similar  ranged from 0.24 to 0.33  all Tasmanian individuals, (b) Maria Island and Flinders Island individuals, and (c) all mainland individuals. The fastSTRUCTURE analysis produced results consistent with the PCA when 3 Figure , with ass Figure . PCAs ans Figure , but no K range from 1 to 3 for Tasmania . One of the eight individuals in the separate cluster was spatially discordant (from the east). sPCA revealed significant global structure in Tasmania (p < 0.01), but no local structure (p = 0.95). Individuals were genetically similar to those sampled adjacently, with the exception of east–west comparisons across north‐central Tasmania .fastSTRUCTURE suggested a 44.1V. ursinus subspecies originated in the mid‐1800s and early 1900s when differences in body and skull size were observed in the geographically separated groups. The mainland subspecies was described as the largest, and Flinders Island V. ursinus were the smallest . However, the genetic divergence of these populations does not immediately align with our current understanding of historical marine isolation. Specifically, the reconstruction of the southern coastline of Australia suggests that the flooding of the Bassian Plain separated the mainland from both Tasmania and Flinders Island first, while a land bridge still connected Tasmania and Flinders Island for an additional ~5–7 kyr Coller, . However4.2Within Tasmania, where sampling was more continuous, there was evidence for isolation by distance. While bare‐nosed wombats are capable of dispersal across varied landscapes (as their distribution suggests), they exhibit relatively small home ranges , it is worth noting that eight individuals were assigned (>99% ancestry) to a separate population cluster. Seven of these individuals were from the Tamar Valley region , specifically Narawntapu National Park and Greens Beach area. These locations are geographically close (<20 km) and well sampled in consecutive years due to research conducted in the area . This longitudinal pattern of genetic differentiation is consistent with previous studies of V. u. hirsutus, using microsatellite loci . However, we reveal a second population of V. u. ursinuslocated on Maria Island. Following the translocation event of 1971, wombats on Maria Island were considered rare  it represents security for the future of V. u. ursinus and (b) indicates the potential ease at which V. u. ursinus could be re‐introduced to Bass Strait islands.Bare‐nosed wombats have been subjected to considerable human interference across the Bass Strait islands, becoming extinct on King, Cape Barren, Flinders, Deal and Clarke islands. Given this history, V. ursinus subspecies in the Maria Island population, suggesting either (a) V. u. tasmaniensis was present at the time of translocation but no genetic signature has been retained to present, or (b) this lineage was not present at the time of translocation. If wombats were already present at the time of the Flinders translocation event, their low abundance may have reflected inbreeding depression , the Department of Primary Industries, Parks, Water and Environment , Monash University (BSci2000/09), Melbourne University Veterinary Science Animal Experimentation Ethics Sub‐Committee (#98108) and Australian National University (A2016/08).https://doi.org/10.5061/dryad.5t37q5f.Reference sequences and SNP genotypes are available at the Dryad Digital Repository:  Click here for additional data file.


Pityogenes chalcographus, a common and widespread insect in Eurasia. Using Restriction Associated DNA Sequencing, we studied the population structure of this beetle across a wide part of its western Palaearctic range with the goal of elucidating the role of Pleistocene glacial-interglacial cycling and its close relationship to its main host plant Norway spruce. Genetic distance among geographic sites was generally low, but clustering analysis revealed three genetically distinct groups, that is, southern, central/south-eastern, and north-eastern locations. Thus, three key P. chalcographus glacial refugia were identified: in the Italian-Dinaric region, the Carpathians, and the Russian plain, shared with its main host. The current phylogeographic signal was affected by genetic divergence among geographically isolated refugia during glacial periods and postglacial re-establishment of genetic exchange through secondary contact, reflected by admixture among genetic groups. Additionally, certain life history traits, like the beetle’s dispersal and reproductive behaviour, considerably influenced its demographic history. Our results will help to understand the biogeography of other scolytine beetles, especially species with similar life history traits.Historical climatic oscillations and co-evolutionary dependencies were key evolutionary drivers shaping the current population structure of numerous organisms. Here, we present a genome-wide study on the biogeography of the bark beetle  During glacial periods major parts of the northern hemisphere were covered by a thick ice shield. In Europe, glaciation of northern regions and high elevation areas as well as permafrost made these habitats largely inhospitable for life. Glaciation contracted the ranges of many species, geographically restricting populations to glacial refugia3. Numerous European species endured glaciation events in the Mediterranean region, though Extra-Mediterranean refugia like the Carpathian Mountains have also been described4. In many cases, contraction of a species’ range to multiple, isolated refugia limited gene flow and caused genetic divergence among refugia2. Following the end of a glacial period, organisms expanded from refugia, recolonizing formerly inhospitable areas and re-establishing genetic exchange. Current population structure thus may reflect past divergence events followed by gene flow during secondary contact5.Historical events and processes have shaped the distribution and genetic structure of numerous organisms. Past climatic oscillations, like glacial and interglacial cycling during the Pleistocene, were major evolutionary drivers in many speciesPityogenes chalcographus (L.)  that provides clear evidence for past genetic divergence in multiple glacial refugia. Pityogenes chalcographus has a wide geographic range that now covers major parts of Eurasia, from central Italy to northern Scandinavia and from western Europe to East Asia6. The distribution of western Palaearctic P. chalcographus is embedded in the range of its main host tree Norway spruce, Picea abies6, and the range patterns of these two species are likely impacted by climate-driven historical processes10.Here, we present a genome-wide study on the biogeography of the bark beetle P. chalcographus is structured in three geographically distinct mitochondrial clades8. One clade mainly occurs in northern European regions, another in central Europe, and southern Europe harbours higher haplotype diversity8. The demography of P. chalcographus was likely affected by range changes during the Pleistocene, as these mitochondrial clades diverged at the beginning of the last ice ages about 100,000 years ago8. Pityogenes chalcographus might have survived the last ice ages in multiple, geographically separated refugia, concordant with those of Norway spruce9. These refugia were proposed to be located in the Apennines in Italy, in the Carpathians or the Bulgarian Mountains, and in the Russian plain8. Moreover, an additional refugium in the Dinaric Alps was suggested7.Previous work using single molecular markers describes that European P. chalcographus have been proposed, but with little supporting evidence. For example, heritable bacterial endosymbionts, like Wolbachia or Cardinium, can alter the reproduction of numerous arthropods, consequently affecting the population structure of their hosts12. Despite low-titre and low-prevalence endosymbiont infections, the reproductive outcome of P. chalcographus is unlikely affected by these bacteria14.Other evolutionary drivers resulting in population structure in Pityogenes chalcographus is an oligophagous bark beetle, feeding in tree species of a few genera within the plant family Pinaceae6, and host specialization has also been proposed to drive population differentiation. Specialization to different host plants results in phenotypic and genetic differentiation among populations of many herbivorous insects15. Pityogenes chalcographus successfully uses various conifers as hosts in addition to Norway spruce6, but does not exhibit host-plant related lineage diversification16. Nevertheless, host preference and developmental performance in Norway spruce is highest17.P. chalcographus8. Nonetheless, due to the limited resolution of previously applied markers8 and the complex life history of this species, detailed knowledge on its demographic history, especially during glacial cycling, is scarce. In particular, in-depth information on the number and locality of Pleistocene refugia and impact of postglacial processes on the present genetic structure is lacking. The goal of this study was to make robust inferences about P. chalcographus phylogeography using a comprehensive set of genome-wide molecular markers. Studying large panels of single nucleotide polymorphisms (SNPs) provides a powerful approach to inferring phylogeographic history19. By examining SNP variation among 16 geographic sites spanning a wide part of the P. chalcographus range, we provide new insights into glacial-interglacial processes that have shaped the current population structure across geography. We identify key Pleistocene glacial refugia and infer postglacial secondary contact in the context of host plant availability and P. chalcographus life history traits. In addition, we discuss species-specific features of P. chalcographus and other bark beetles that may influence the inferred phylogeographic patterns. Finally, our study will help to understand demographic processes in other species of the weevil subfamily Scolytinae, especially species with similar life histories.Instead, all available evidence suggests that Pleistocene ice ages were major drivers shaping the biogeography of Pityogenes chalcographus is a Palaearctic species whose distribution tracks that of suitable host plants. It is oligophagous on various conifers with Norway spruce as the main host in Europe6. Pityogenes chalcographus preferentially breeds in thin-barked parts of trees, including branches or upper stem sections20 and can be a forest pest during environmentally favourable conditions21. Male beetles initiate host attacks and attract conspecifics using aggregation pheromones22. The species is polygynous; two to seven female beetles mate with one single male, and each female lays on average ten to 26 eggs23. After subcortical larval and pupal development, and maturation feeding of young beetles on phloem tissue, a new generation of adults disperses to attack fresh hosts. Pityogenes chalcographus can produce up to three generations per year20.Pityogenes chalcographus was collected from 16 geographic sites between 2004 and 2009  following the manufacturer’s instructions. DNA concentrations were estimated using a ‘NanoDrop 2000C’ and all samples were either concentrated or diluted the same concentration ±10% for downstream library preparation.P. chalcographus on a multi-locus, genome-wide scale, we applied double digest Restriction Associated DNA Sequencing (ddRADSeq)24 using EcoRI and MseI restriction enzymes, as modified from25 (details on library preparation and sequencing see SI 2).To study 26 (for details see SI 3). Due to the lack of a P. chalcographus reference genome only forward reads were used in this study. A de-novo ‘pseudo-reference’ genome was created using the ustacks algorithm in STACKS (v1.35)28 (parameters see SI 3). De-multiplexed and filtered reads were mapped to the ‘pseudo-reference’ genome using BWA-MEM (v0.7.12)29. SNP calling was performed using the Unified Genotyper in GATK (v3.3.0)30. We filtered out SNPs when i) the average base quality-phred score was <20, ii) the total depth per locus across all individuals was <10, iii) sites appeared to be over-assembled , and iv) the minor allele frequency across all individuals was <0.05. Moreover, only individuals with >10,000 retained SNPs were kept for downstream analyses. Location information of SNPs passing these filters was extracted and further analyses were performed in ANGSD (v0.913), using the GATK model31 (parameters used in ANGSD see SI 3). Individuals with more than 30% missing data were removed and loci that were present in less than 80% of samples were discarded.Raw reads were de-multiplexed and filtered as ingenind object in R via the package adegent (v2.0.1)33. Pairwise Nei’s FST values were calculated in the R package hierfstat34 and the G”ST value, as an additional, unbiased estimator36, in the R package mmod37. Additional population genetic statistics are reported in SI 4.Descriptive statistics and population genetic metrics were inferred from called genotypes calculated in ANGSD, using a final data set with 5,470 loci (requirements for passing filters see above and SI 3). SNPs were converted to a P. chalcographus follows an isolation-by-distance (IBD) pattern a Mantel test38, as implemented in the R package adegenet33, was performed. To estimate genetic distances among populations we calculated FST/(1 − FST)39 using pairwise Nei’s FST values as determined above. Geographical distances were inferred from the shortest distance between locations using the R package geosphere (v1.5-7)40 and were subsequently ln-transformed.To assess whether the genetic structure of P. chalcographus geographic sites we used called genotypes as above, converted in a genpop object, that is, allele counts per population, in the R package adegenet33. Relationships were calculated applying a NJ-approach with 1,000 bootstrap replicates based on Nei’s distances in the R package poppr42. Results were visualized in FigTree (v1.4.3)43.To assess the relationship among 44 was run using genotype likelihoods, thus considering uncertainty of genotype calls45. Genotype likelihoods were calculated in ANGSD and loci were retained when the base quality phred-score was >20, the mapping quality phred-score >20, and the missing data rate was below 30%. Again, only loci present in at least 80% of individuals were retained. This resulted in a total number of 13,105 loci. The optimal number of groups  for clustering individuals was tested for K = 1 to K = 15, using changes in log-likelihood values between Ks46, running ten independent replicates with 10,000 iterations each. In addition to the optimal K-value, biologically meaningful Ks, i.e., K = 3 and K = 4, were tested . Calculation of optimal K-values and visualization of admixture plots were done in R47.To study the admixture and population structure of individuals from different locations a structure analysis was performed. NGSadmix48. DAPC was calculated in R using the package adegenet48 using called genotypes  as described above. To achieve an optimal discrimination and avoid over-fitting of data, the optimum-α-score to estimate the optimal number of principal components was assessed.Population structure was further studied by performing a Discriminant Analysis of Principal Components (DAPC), a multivariate statistical method identifying clusters based on linear combinations of genotypes produced by principal component analysis (PCA)P. chalcographus demography, we performed an approximate Bayesian computation (ABC) analysis implemented in DIYABC (v2.1.0)49. We tested four evolutionary scenarios on a reduced data set . The highest FST value was calculated between the Italian site ITTO and the eastern Carpathian site ROSA (=0.071). Further, an overall G”ST value of 0.021 was determined. For additional population statistics see SI 4, Table Based on called genotypes, the average Nei’s pairwise FP. chalcographus does not follow a strong IBD-pattern. The Mantel test did not reveal a significant positive correlation between genetic and geographic distances among locations , the Greek site GRDA is the south-eastern-most and closest to the two Carpathian sites . The Austrian location, for example, is close to the northern Italian sites , and to the two central sites in France . The Apennine sites ITAB and ITPA are the southernmost and therefore on the edge of the Italian-Dinaric (blue) group. Within the north-eastern group (red), the Polish location POCH is closest to the central/south-eastern group Fig. .P. chalcographus was scenario 4  during the last ice ages caused divergence of mitochondrial cladesP. chalcographus from Russian, Swedish, Polish, and Lithuanian sites (north-eastern group) indicates that these individuals survived periods of increased glaciation in the Russian plain. Grouping of beetles from the French, Romanian, and Greek sites  suggests a refugium in the Carpathians (or Bulgarian Mountains)10. Italian-Dinaric P. chalcographus, including beetles from the Austrian site, might have survived glaciation events in southern Europe, where major Norway spruce refugia in the Apennines and the Dinaric Alps were found55. These two mountain ranges are geographically relatively close and several small refugia between them have been reported57. Because P. chalcographus is a long-range disperser58, we propose one Italian-Dinaric P. chalcographus refugium.Clustering of P. chalcographus might have survived Pleistocene ice ages also in the more eastern part of its range. Due to its oligophagous feeding behaviour, it can utilize Asian conifers, like Picea obovata, Picea jezoensis, or Pinus koraiensis, as hosts6. Several refugia of these tree species have been described in Asia, for example in Siberia (P. obovata)59 or in the Far East . Thus, P. chalcographus might have endured unfavourable conditions during the Pleistocene even in these regions, shared with a respective host. However, detailed knowledge on the genetic population structure of P. chalcographus from the eastern Palaearctic and its influence on European populations are not available and future research should focus on extensive sampling of this region to get a more complete picture of the beetle’s biogeography.In addition to these refugia, P. chalcographus expanded its range to previously inhospitable habitats. As for glacial periods, we assume that recolonization of the beetle and its main host also occurred parallel. For example, present Norway spruce in Fennoscandia was recolonized from a single refugium in the Russian plain63. Clustering of P. chalcographus from north-eastern locations suggests that these beetles also originated predominately from this Russian refugium, consistent with a tight insect-host relationship. Assuming three P. chalcographus refugia, NGSadmix results suggest secondary contact, for example, in Poland where north-eastern and central/south-eastern European beetles admixed  having lower amounts of admixture. Moreover, NGSadmix results suggest that P. chalcographus from this central European refugium also contributed to the genetic architecture of north-eastern European and northern Italian locations, reflecting additional secondary contact, for example, in the Southern Alps and Austria.After the end of the last ice ages about 10,000 years ago, xed Fig. . We cannP. chalcographus from the Italian-Dinaric refugium may also have contributed to the genetic structure of central/south-eastern sites and only limited to north-eastern sites.Recolonization from the Italian-Dinaric refugium mainly accounted for the genetic structure of southern sites. The southernmost populations in this area  show low amounts of admixture compared to the northern Italian sites and the Austrian location. Furthermore, NGSadmix results suggest that 64. Furthermore, various European lepidopteran species show demographic patterns affected by climatic fluctuations during the Pleistocene similar to P. chalcographus: range contractions to geographically isolated refugia in Mediterranean and Extra-Mediterranean regions resulted in divergence among these refugia, followed by postglacial secondary contact and re-establishment of genetic exchange67. In addition, diversification of the butterfly family Nymphalidae was found as a result of angiosperm radiation during the Cretaceous era68, a comparable co-evolutionary history as reported for weevils50. Taking this knowledge together underlines our hypothesis that glacial-interglacial cycling and the association to its main host plant were major evolutionary drivers in P. chalcographus.Similar biogeographic patterns, that is, climate-driven range contractions and expansions and a tight host plant association, have also been reported from other insect species. For example, numerous butterflies (Lepidoptera) are characterized by their close relationship to plants, resulting in mutual adaptations to each other and overlapping distribution areas of insect and hostP. chalcographus. One important trait that affects the genetic structure of bark beetles is their dispersal behaviour18. IBD describes an increase of genetic differentiation among sites with increasing geographic distance69, presumably because of limited dispersal70. Pityogenes chalcographus can spread over long distances, more than 80 km aided by wind58, facilitating exchange of genetic material among sites. This feature might explain the absence of an IBD pattern in P. chalcographus, as long-range dispersing insects are generally characterized by a weak relationship between genetic and geographic distance71. In addition to the beetle’s intrinsic, species-specific traits, anthropogenic influence might also explain the lack of IBD. Various insects, like the bark beetle Tomicus piniperda72, the fire ant Solenopsis invicta73, or the leafhopper Scaphoideus titanus74 exhibit an absence of this pattern, for example, due to human trade. As humans have been trading across Eurasia for more than 2000 years76, we therefore cannot rule out a human influence on the genetic structure of P. chalcographus.In addition to the influence of past climatic oscillations, specific life history traits likely contributed to the current genetic structure of P. chalcographus, Norway spruce, has a wide, current range10 and was also very common before the last ice ages78. The absence of insuperable physical barriers in the ranges of P. chalcographus and its main host9 probably results the low level of population differentiation and high amounts of admixture found in this study. This is corroborated by the relatively close relationship of P. chalcographus from Italian-Dinaric and the Austrian sites, suggesting that the Alps were not a strong barrier for dispersal of these two species. In contrast, physical barriers were found to affect the genetic architecture of other bark beetles, for example the mountain pine beetle Dendroctonus ponderosae in North America, where deserts and mountain ranges hampered gene flow among populations53.Further, the main host of P. chalcographus is its reproductive behaviour. It releases aggregation pheromones, a complex system of semiochemicals22, to attract male and female conspecifics. It is polygynous where one male can mate with several females, has a high fecundity, and can produce up to three generations per year23. Pityogenes chalcographus might have established thousands of generations of different origin since the end of the last glaciation events, likely reflected in high levels of admixture and low levels of differentiation.Another factor that might have influenced the genetic architecture of P. chalcographus was shaped by past climatic oscillations during the Pleistocene and co-evolutionary processes with its main host plant. Limited exchange of genetic material among different refugia during glaciation events is still reflected in the phylogeographic signal observed today; however, extensive postglacial admixture as a result of certain intrinsic traits has resulted in low levels of differentiation.In conclusion, the phylogeography of Supplementary Information


Qualea grandiflora, a tree species widely distributed in the biome. Totally, 40 populations distributed in the Cerrado core and Amazon savannas were analyzed using chloroplast and nuclear DNA sequences. We used phylogeographic, coalescent and ecological niche modeling approaches. Genetic data revealed a phylogeographic structure shaped by Pleistocene climatic oscillations. An eastern-western split in the Cerrado core was observed. The central portion of the Cerrado core harbored most of the sampled diversity for cpDNA. Ecological niche models predicted the presence of a large historical refuge in this region and multiple small refuges in peripheral areas. Relaxed Random Walk (RRW) models indicated the ancestral population in the north-western border of the central portion of the Cerrado core and cyclical dynamics of colonization related to Pleistocene climatic oscillations. Central and western ancient connections between Cerrado core and Amazonian savannas were observed. No evidence of connections among the Amazonian savannas was detected. Our study highlights the importance of Pleistocene climatic oscillations for structuring the genetic diversity of Q. grandiflora and complex evolutionary history of ecotonal areas in the Cerrado. Our results do not support the recent replacement of a large area in the Amazon forest by savanna vegetation. The Amazonian savannas appear to be fragmented and isolated from each other, evolving independently a long ago.The evolutionary processes underlying the high diversity and endemism in the Cerrado, the most extensive Neotropical savanna, remain unclear, including the factors promoting the presence and evolution of savanna enclaves in the Amazon forest. In this study, we investigated the effects of past climate changes on genetic diversity, dynamics of species range and the historical connections between the savanna enclaves and Cerrado core for  We investigated the effects of past climatic changes on the genetic diversity, dynamics of species range and historical connections between the Amazonian savannas and Cerrado core. We tested the hypothesis that during the Pleistocene, there was variation in range toward the north and south of a climatically stable area in the Cerrado core during cooling and warming periods, respectively. Additionally, we tested the existence of corridors connecting the Cerrado core and Amazonian savannas. Specifically, we aimed at answering the following questions: (1) When and from where did the lineages of Q. grandiflora disperse? (2) What is the historical evolutionary relationship between the Cerrado core and disjoint Central and western Amazonian savannas? (3) By what mechanism would these regions have been connected and when would these connections have been established?In this study, we conducted extensive sampling of Q. grandiflora, belongs to the family Vochysiaceae, occurring exclusively in tropical regions   and Hamilton (trnS-trnG)  regions was conducted using 30 primer pairs for previously described cpDNA regions  with ARLEQUIN 3.5 ].The location of potential barriers to gene flow was inferred using Monmonier's maximum difference algorithm  for cpDNA and nDNA were estimated for each cluster, each population and all populations together for both regions (cpDNA and nDNA) using ARLEQUIN 3.5  and a general substitution rate for the AGT1 region , based on parsimony criteria , Last Glacial Maximum  and Last Interglacial  time periods based on climatic simulations  of r > 0.9)  were obtained for all geographical coordinates, at a spatial resolution of 1 km, from the WorldClim database  and test or validation set (25% of occurrences). We constructed models 10 times and averaged the output to produce data used in the downstream analyses. Next, we defined a threshold value above grid cells, considered to have environmental characteristics suitable for maintaining viable populations of the species Pearson, . We usedQ. grandiflora points, we used 202 occurrences of Eugenia uruguayensis obtained from NeoTropTree  as threshold-dependent accuracy measures and Area Under Curve (AUC) as a threshold-independent measure  and 693 bp (trnS-trnG). In the concatenated form, the entire sequence  showed 29 polymorphic sites, specifically 14 insertions/deletions , one inversion (with 30 bp) and 14 substitutions, generating 32 haplotypes. The nuclear gene sequence (nDNA: AGT1) was 1,182 bp long and highly variable and showed 64 variable sites, all substitutions, generating 59 haplotypes.The alignment of cpDNA regions produced fragments of 664 bp  than in the Cerrado core populations . The total haplotype diversity was 0.888 and 0.973 and total nucleotide diversity was 0.0027 and 0.0071 for cpDNA and nDNA, respectively. The populations showed high genetic differentiation for cpDNA (FST = 0.790); however, for nDNA, this differentiation was lower (FST = 0.231). Genetic distance correlated significantly with geographical distance for cpDNA , while for nDNA, these distances did not correlate .The molecular diversity indices and haplotype distribution in each population for both datasets are summarized in Table Q. grandiflora as seven and six, respectively , supporting the hypothesis of recent demographic and spatial expansions in all phylogeographic clusters for cpDNA and for all populations together  periods, with the suitability areas extending from the southernmost part to the northern portion of the Cerrado. Moreover, in the LIG, there was a putative connection between the Amazonian savanna (population aSAN) and Cerrado core  from the remaining ones, evidenced by the MJ network, BI analysis and, Monmonier's maximum difference algorithm. In the same way GENELAND analyses performed with cpDNA and nDNA data together reinforce this structure of the CE region. This separation between eastern and western Cerrado core was similarly observed for two other congeneric species, Q. multiflora and Q. parviflora . These mountain ranges are present from the northern until the southern portion of the putative barrier b estimated by the BARRIER analysis . Moreover, small refuges in southern and western Cerrado were predicted highlighting that the diversity observed in this biome could have resulted from a complex scenario where cyclical isolation and recolonization processes from multiple refuges occurred. Besides, the high genetic diversity and genetic structure observed in Q. grandiflora can be a result from fast range contractions events with absence of gene flow between isolated areas  exhibited high cpDNA diversity Table . This diQ. grandiflora was probably located at the north-western border of the CC cluster. During the Early Pleistocene (ca 1.49 Ma), the species began its colonization from this area toward the CC cluster and Amazonian savanna . Since this period, lineage colonization, mainly from the CC cluster, underwent a cyclical process with colonization toward the north occurring most in cooling periods. Contrastingly, in warming periods, lineages dispersed toward the eastern and southern portions of the Cerrado core, reaching latitudes beyond 20°S.The putative ancestral population of Q. grandiflora at latitudes beyond 20°S in LGM.Southern Cerrado (SC cluster) showed low genetic diversity for cpDNA Table , which wQ. grandiflora highlights the evolutionary complexity of ecotonal areas in the Cerrado, influenced by climatic changes in the Pleistocene.Population cQGA, located within the Pantanal vegetation complex, showed only one exclusive haplotype (C27), phylogenetically close to the exclusive haplotype observed in a savanna enclave in south-western Amazonia (aHTA population). The RRW analysis showed that lineage colonization toward populations aHTA and cQGA from the central western began at approximately 1.17 Ma from the same region, corroborating the disjunction in clustering revealed by GENELAND. Population cPRI, located in a peripheral area in the transition between north-eastern Cerrado and Caatinga (a xeric vegetation type), did not show variation, displaying only a single haplotype (C04) shared with core populations. This agreed with the probable recent colonization of this area (0.45 Ma), demonstrated by the RRW analysis. In conclusion, our data for Q. grandiflora did not support the replacement of a large continuous area of the Amazon forest by savanna vegetation, yet they did not fully refute Haffer's  constituted an isolated cluster, wherein only one endemic and divergent  haplotype was observed, evidencing an ancient isolation of the population aSAN from the Cerrado core. Furthermore, the RRW model showed that lineages probably dispersed to aSAN only by a central corridor at the end of a cold period in the Early Pleistocene (ca 1.49 Ma). Later, this region was isolated by a vicariant process, probably by Amazon forest expansion. The nDNA evidenced similar findings, with most of the haplotypes exclusive to the population aSAN. However, for this genetic nuclear marker, two haplotypes were shared with populations located in the central portion of the Cerrado core and one of them was shared with cPRI as well. These data suggested the existence of a central connection between the core and aSAN  yet did not exclude a putative connection between aSAN and cPRI through Coastal corridor. However, cPRI and aSAN could also have independently received the same nDNA haplotype from the core. The ENM studies on Q. grandiflora predicted the suitability area at the same place where the Central corridor could have occurred during LIG. Furthermore, a recent study based on uranium/thorium dating and oxygen isotopic records obtained for stalagmites in a cave located near the population aSAN , from this area, colonized cQGA and a small putative refuge near aVHA and aHTA, as predicted by the ENM analysis. Later, in the Middle Pleistocene, this refuge appeared to be the source of lineages constituting populations aVHA and aHTA, which could explain the relative genetic proximity between cQGA and aHTA. Populations aHTA and aVHA were clustered together in GENELAND analysis, probably due they common ancestry. In the same way, cQGA population showed high probability of belonging both to the same cluster as aHTA and aVHA or cSER. These results together corroborate the species colonization routes inferred by RRW analysis and also could explain the pattern obtained in the GENELAND non-spatialized model . The 18O records indicate that western portion Amazon forest remained wetter than the eastern side, reinforcing the non-connection between populations aHTA and aSAN.The genetic divergence between south-western and central Amazonian savannas observed for cpDNA was similarly observed for nDNA. The haplotypes obtained in aHTA were exclusive and genetically distant from the nDNA haplotypes of aSAN  and aVHA (located at western Cerrado border at the Cerrado/Amazon forest transition). The different connections observed between the Cerrado core and central and south-western Amazonian savannas in different cooling periods could be related to a dichotomous pattern of response to climatic changes between the western (aHTA side) and eastern (aSAN side) Amazonian portions described by Cheng et al. . AccordiThis is the first time a genetic study on plant species in the Cerrado evidenced a central connection between the Cerrado core and Amazonian savannas. According to our results, these connections occurred during a remote period, before LIG or LGM. The Amazonian savannas appear to be fragmented and isolated from each other, evolving independently a long ago. Our study brings insights into the historical relationships between the Cerrado core and Amazonian savannas. However, due to intrinsic stochasticity of the coalescent processes and influence of other features such as life histories traits, more studies with increased marker numbers, more Amazonian savanna samples and analysis of other species are necessary to improve our knowledge about the evolutionary history of the Amazonian savannas.Our findings reinforce that the central part of Cerrado core is an important area for the conservation of the biome genetic diversity. Additionally, other small stable areas during Pleistocene climatic oscillations with exclusive haplotypes and/or high diversity are important to ensure the evolutionary potential of the species under predicted future climatic changes. Thus, these multiple potential refuges should be included in conservation programs. Special attention should be paid to poorly known Amazonian savannas, which show exclusive haplotypes and independent evolution of Cerrado core.RB, JL-F, ML planned and designed the research. RB performed laboratory work. RB, ML, and JL-F collected the population samples. ML and JL-F provide financial resources to work. RB, TP, MB and RM carry out the data analyzes. All authors contributed to the manuscript writing, mainly RB and ML.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.


Allium cepa L. Aggregatum-Group), commonly known as shallot or potato onion, has a long tradition of cultivation in Fennoscandian home gardens. During the last decades, more than 80 accessions, maintained as vegetatively propagated clones, have been gathered from home gardens in all Fennoscandian countries. A genetic analysis showed regional patterns of accessions belonging to the same genetic group. However, accessions belonging to the same genetic group could originate in any of the countries. These results suggested both short- and long-distance exchange of set onions, which was confirmed by several survey responses. Some of the most common genetic groups also resembled different modern varieties. The morphological characterization illustrated that most characters were strongly influenced by environment and set onion properties. The only reliably scorable trait was bulb skin color. Neither our morphological nor genetic results support a division between potato onions and shallots. Instead, naming seems to follow linguistic traditions. An ethnobotanical survey tells of the Fennoscandian multiplying onions as being a crop with reliable harvest, excellent storage ability, and good taste. An increased cultivation of this material on both household and commercial scale should be possible.Multiplying onion (The online version of this article (10.1007/s12231-018-9426-2) contains supplementary material, which is available to authorized users. Allium species commercially cultivated are bulb onion (Allium cepa L. Common onion-Group) and leek (Allium ampeloprasum L.), both propagated from seed of hybrid varieties. In contrast, home gardeners often use indigenous multiplying (aggregating) onion, known as shallot or potato onion (Allium cepa L. Aggregatum-Group). These onions are clonally propagated, and they rarely flower and set seed under Fennoscandian climatic conditions. The name potato onion probably stems from the similarity to potato propagation. Cloves of the onions are planted in the spring, and in early autumn, a cluster of, normally around ten, onions can be harvested. The onions grow fast and are hardy even in northern Scandinavia and are known for having excellent storage capacity  are mentioned already in the earliest written sources concerning Scandinavia. For example, there are reports of Vikings bringing onions on their ships during long-distance sea travel during the 10th century , as well as gardening NGOs and national crop biodiversity programs in the Nordic countries, has been gathering locally cultivated vegetables during the last decades  How diverse are accessions of Fennoscandian multiplying onion?, (2) What are the geographical patterns of seed (set onion) exchange?, (3) What is the relationship to commercial clones?, and (4) Can genetic or morphological differences between potato onion and shallot be identified?Allium spp. , or from the Swedish National Program for Diversity of Cultivated Plants (accessions with prefix SWE). As a contrasting material for the genetic analysis, six local accessions from Georgia and eight modern varieties were included. These accessions were obtained from The Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany (accessions with prefix ALL), or purchased commercially. Materials are summarized in Table Allium cepa Common onion-Group) (Fischer and Bachmann Green shoots or the innermost layers of onion bulbs (< 100 mg fresh weight) were used for DNA extraction. The extractions were performed using either the E.Z.N.A Plant DNA kit from Omega Biotek  or the DNeasy plant mini kit from Qiagen  in accordance with the manufacturers’ instructions. Genotyping was performed using 12 microsatellite markers originally designed for bulb onion  as well as local name of the accession, cultivation practices, phenology, history, and use . This analysis again showed the clear differentiation of the homogenous group of accessions from Georgia from the Fennoscandian material. The modern varieties were well separated from each other and in many cases located away from the Fennoscandian onions, however with notable exceptions Fig. a. LookinTo geographically visualize distribution of genetic variability, we performed discriminant analysis of principal components (DAPC). In the model, we used ten different genetic groups as BIC values formed a plateau around this number (data not shown). The proportion of assignment to each group for each accession was plotted on a map at the location of the origin of the accession Fig. . The mosSince multiplying onions are mainly vegetatively propagated, a high degree of clonality among accessions was expected. We identified eight genotypes that were shared by two or more accessions. The most common genotype was found in 13 accessions, mainly from Denmark. The two second most common genotypes were each found in five accessions. The first of these two genotypes was represented by accessions from Denmark, Norway, and Sweden, and the second genotype by accessions from Denmark and Sweden and the modern variety ‘Success.’ All the three most common genotypes (comprising 23 accessions) were closely related to each other, differing only in single locus. They belong completely or mainly to the light green genetic group in Fig. A total number of 24 survey responses were received (48%). The majority of responses were from Denmark and Sweden. The replies are summarized in Table Regarding cultivation and phenology, most respondents used small- or medium-sized bulbs for cultivation Table . CultivaThe keeping ability varied from over the winter until more than 2 years Table . Dry andFor many of the respondents, the histories of the plants were highlighted, in some cases with a long story dating back at least 50 years. Often, the onions were given from one generation to the next within a family. When details were present, a mother to daughter line could often be detected (in Scandinavian “mormor”). Only in one case was a male mentioned (respondent NGB16555). The onions were used in a lot of different dishes and no clear pattern or country differences were detected.Although no common cultivation experiment with all accessions included has been performed, the comparison of data clearly showed the difficulty in performing characterization of accessions based on morphological characters. The only character that showed a consistent scoring among experiments was red skin color, co-occurring with violet flesh color. Accessions with these traits were, however, not apparently genetically related Fig. c. Other A number of potential clones, i.e., accessions with identical genotypes, were identified. It must be noted that the number of genetic markers is small and that more markers could putatively reveal genetic differences between accessions here considered as potential clones. Conversely, there is also a small risk of genotyping errors due to stuttering in the microsatellite analysis that, for example, make differentiation between homozygous and heterozygous loci difficult , no identical clones were found when comparing accessions from different Swedish locations  collected from Nordic gardens, low clonality was found ESM 2.Ethnobotanical survey sent out to donors from Denmark, Norway, and Sweden. (DOCX 19 kb)