Neophasia menapia) and the Mexican pine white (Neophasia terlooii), restricted to these “islands” at this transition zone. Given their dependence on pines as the larval hosts, we hypothesized that habitat connectivity affects population structure and is at least in part responsible for their allopatry. We sampled DNA from freshly collected butterflies from 17 sites in the sky islands and adjacent high‐elevation habitats and sequenced these samples using ddRADSeq. Up to 15,399 SNPs were discovered and analyzed in population genetic and phylogenetic contexts with Stacks and pyRAD pipelines. Low genetic differentiation in N. menapia suggests that it is panmictic. Conversely, there is strong evidence for population structure within N. terlooii. Each sky island likely contains a population of N. terlooii, and clustering is hierarchical, with populations on proximal mountains being more related to each other. The N. menapia habitat, which is largely contiguous, facilitates panmixia, while the N. terlooii habitat, restricted to the higher elevations on each sky island, creates distinct population structure. Phylogenetic results corroborate those from population genetic analyses. The historical climate‐driven fluxes in forest habitat connectivity have implications for understanding the biodiversity of fragmented habitats.The sky islands of southeastern Arizona (AZ) mark a major transition zone between tropical and temperate biota and are considered a neglected biodiversity hotspot. Dispersal ability and host plant specificity are thought to impact the history and diversity of insect populations across the sky islands. We aimed to investigate the population structure and phylogeography of two pine‐feeding pierid butterflies, the pine white ( The high‐throughput sequencing approach of ddRADSeq was used to investigate the phylogeography and population structure of two closely related butterfly species restricted to mountain habitats. Despite their flight capabilities and the proximity between some mountain ranges (56 km apart), there was distinct population structure among butterflies in the sky islands of southeastern Arizona. Butterflies in the largely connected belt of pine forest from east–central Arizona northwestward to the Kaibab Plateau exhibited panmixia. The Madrean Archipelago (sky islands) is a region of isolated mountain ranges spanning extreme southeastern Arizona, USA (AZ), southwestern New Mexico, USA, and northern Mexico. The lower elevations  make up the Sonoran Desert to the west and the Chihuahuan Desert to the east. The higher elevations  are interspersed in the gap between the Rocky Mountains to the north and the Sierra Madre Occidental to the south Figure . The skyNeophasia butterflies are an excellent system for investigating how the sky islands have shaped species history. These butterflies are coniferous forest specialists and their evolutionary history likely follows that of their forest habitats, which have been hypothesized to fluctuate in area and connectivity in association with climate changes  ranges from southwestern British Columbia to the Mogollon Rim and White Mountains of AZ . Neophasia terlooii  is present in the sky islands of southeastern AZ southward to the Sierra Madre Occidental in central Mexico , a larval host for both Neophasia species, occurs in the more fragmented Madrean evergreen woodlands and is a predominant member of the comparably larger and more contiguous Rocky Mountain coniferous forests  and N. terlooii (n = 69) were collected from 10 and seven field sites, respectively, throughout AZ in the summer and fall of 2013 and 2014  following the manufacturer's protocol, with some adjustments to optimize DNA recovery Appendix . Each DNN. menapia . Filtered sequences were then demultiplexed using FastX_toolkit FASTQ Barcode splitter and either the 14‐, 10‐, 9‐, or 8‐base barcodes. FastQC reports, filtering, and demultiplexing were all performed using the UF instance of Galaxy  were first assessed for quality by generating FastQC reports  between sampling locations within each species. To determine between location fixation indices, we ran pairwise.fst from “heirfstat”  was performed on the 2.6structure 2.3.4 . Two datasets, each including only minimally admixed sampling sites from one of the clusters, were analyzed again with structure using the aforementioned parameters, except that only K = 1–5 were tested.To identify genetic clusters and estimate cluster membership probabilities of each individual, we used 2.7pyrad pipeline to infer phylogenetic relationships. Eaton ; therefore, we kept the minimum number of individuals  to ten. Up to 100 SNPs per locus (default for parameter ## 26.opt) were allowed. Using pyRAD generated data matrices, maximum likelihood trees with 10,000 ultrafast bootstrap replicates  from a Mantel test. Neophasia menapia did not show significant isolation by distance , nor did genetic distance correlate with geographic distance  resulted in unresolved trees with low branch support. Despite the risk of greater missing data, which can negatively affect accuracy in smaller datasets , but sample sizes from individual populations can be small (n = 6) provided there is a large number of genetic markers . In our study, at least 3,000 SNPs were genotyped using stacks, and thus our sample sizes, averaging ten individuals per site, were appropriate for making FST comparisons.Traditionally, population genetic studies required at least tens of individuals per sampling site to make accurate inferences. Willing, Dreyer, and Oosterhout  found thFST indices for N. menapia, 28 were <0.05, suggesting panmixia. The AMOVA indicated that there was little, but significant genetic variation between sites for N. menapia, but additional analyses suggested this variation is not sufficient to generate robust population or phylogenetic inferences. The two N. menapia sites that were most distant geographically from each other (NJ and FR at 436 km) had an FST value of 0.046, but the two closest N. terlooii sites (HC and SW at 7.6 km) had a similar FST of 0.034  would have been connected with the population in the Huachuca Mountains  and this largely agrees with the molecular data, as it is clustered with the latter three in the first structure analysis. The population in the Pinaleño Mountains (GM) would have been connected with the population in the Chiricahua Mountains (CH), and this is evidenced by admixture with the former. The Santa Catalina Mountains (LM) is the only range that would not have been connected, yet the molecular data suggest admixture with CH and membership to a cluster also containing GM.During our surveys, Neophasia terlooii populations show a very clear hierarchical population structure with respect to populations on each sky island. The northwest–southeast oriented topographic grain of the sky islands . From the Kaibab Plateau to the south rim, the Grand Canyon spans roughly 13 km of unsuitable habitat for N. menapia and there not strong evidence to suggest this distance inhibits gene flow. At their closest point, the northern‐most sky island and ponderosa pine habitat in the southern White Mountains are roughly 70 km apart. This distance appears sufficient to maintain allopatry between N. menapia and N. terlooii, but geographic distance may not be the only factor.It is evident that the geographic distance between the sky island mountains is enough to isolate N. terlooii has long been suspected a mimic of the monarch butterfly (Poulton, N. terlooii while N. menapia may be vulnerable to predation if it were to venture into the range of N. terlooii. To date, N. menapia has not been collected or seen in the sky islands and N. terlooii has not been collected or seen north of the sky islands. Crossing the barrier between the sky islands and the White Mountains is likely a rare event, and any transplants are incapable of starting new populations for reasons that are beyond the scope of this paper. Further sampling of the genetic diversity of both species of Neophasia throughout their respective ranges would provide the data necessary to unravel their biogeographic history in western North America and would contribute to our work here and to knowledge of the evolution of biodiversity in the sky islands. Additionally, the timing and direction of dispersal events is key to further exploring their biogeography. This remains for future study and will require more accurate methods of divergence time estimation at the population level.Even if the geographic distance is within the dispersal capabilities of an organism, or if the habitat between populations is suitable, allopatry can persist for biological reasons such as mating incompatibility, competition, or predation (Tennessen & Zamudio, Poulton, , and, asPoulton, , mimicry5Neophasia population structure in AZ. As our ability to analyze genomic data catches up with our ability to generate data, complex biogeographical studies using nonmodel taxa at very shallow phylogenetic levels will be increasingly common and affordable. With improved algorithms and faster processors, total‐evidence approaches are becoming increasingly feasible, especially for projects with minimal or short‐term funding.We extracted genome‐wide data from 151 individuals and used this data to infer population structure and generate phylogenies for a nonmodel taxon in a neglected biodiversity hotspot. Despite differences in the number and type of loci discovered across the genomic pipelines used, we reached congruent biological conclusions regarding None declared.D.A.H. led this project as a part of his dissertation research; D.A.H., A.Y.K., and J.C.D. conceived the ideas; D.A.H. collected the data; D.A.H. and C.G.S. analyzed the data; and D.A.H. led the writing. Click here for additional data file. Click here for additional data file.


Charadrius alexandrinus) and the White-faced Plovers , shorebirds with parapatric breeding ranges along the Chinese coast. We assessed divergence based on molecular markers with different modes of inheritance and quantified phenotypic and ecological divergence in aspects of morphometric, dietary and climatic niches.Speciation with gene flow is an alternative to the nascence of new taxa in strict allopatric separation. Indeed, many taxa have parapatric distributions at present. It is often unclear if these are secondary contacts, e.g. caused by past glaciation cycles or the manifestation of speciation with gene flow, which hampers our understanding of how different forces drive diversification. Here we studied genetic, phenotypic and ecological aspects of divergence in a pair of incipient shorebird species, the Kentish  contains supplementary material, which is available to authorized users. Understanding how strongly evolutionary processes  shape the divergence of closely related species has been a long-standing interest in evolutionary biology –5. AllopTimema walking-stick insects [Poecilia reticulata), which can maintain population diversification and fixed divergence in genomic regions [An increasing number of studies have shown that divergence can arise and be maintained due to selection imposed by heterogeneous environments despite the homogenizing effect of gene flow , 12. Und insects . In such insects . Locally regions  in the f regions . Though  regions , 22, to Confirming whether genetic differentiation between two taxa is due to strict allopatry or speciation-with-gene-flow remains challenging . TowardsCalidris melanotos) [Shorebirds are a group of migratory species with remarkable movement ability. Seasonal migration may increase the probability of individual dispersal between populations , 28 and lanotos) . Range-wlanotos) –36). Thilanotos) , 26.Charadrius alexandrinus) and the White-faced Plover  and the timing of divergence [C. alexandrinus and C. dealbatus. Because it is difficult to directly quantify divergent selection, it is necessary to make inference from the comparison of traits, which are potential targets of selection in order to offer hints on selective mechanisms in maintaining divergence [Here, we provide comprehensive data from multiple sources to explore divergence patterns between these two species of plovers. We carried out extensive sampling of breeding populations covering the potential area of contact along the Chinese coast. We then obtained genetic polymorphism data from multiple markers with various mutation rates, i.e. mitochondrial DNA, exons and autosomal microsatellites. Using these new datasets, it is possible to estimate the intensity and direction of gene flow , 46 as wvergence  between vergence , 48, 49.p < 0.001, Fig. C. dealbatus had a longer bill . Individuals of C. alexandrinus from Taiwan Island were heavier than continental populations of C. alexandrinus and C. dealbatus (both p < 0.001). QST between coastal populations of C. alexandrinus and C. dealbatus was negatively correlated with geographic distance . For each site, the sample size ranged from 11 to 30 individuals. For each individual, we obtained in total 1729 base pairs (bp) of mtDNA sequence, including 846 bp ATPase6/8, 505 bp D-loop and 378 bp ND3. C. alexandrinus showed higher intraspecific genetic diversity than C. dealbatus  and low at microsatellite loci . For nuclear sequence data, genetic differentiation between species was also significant at autosomal loci  and particularly high at the Z-linked loci NFIL3  and S1PR3 . In the AMOVA analysis, we observed the largest difference between groups when the data were partitioned by species , with this grouping explaining 49.7% of the variance in mtDNA and 2.4% in the microsatellites  and coastal populations . C. alexandrinus populations on Taiwan Island also shared haplotypes with other coastal populations , but were significantly differentiated in microsatellites .Overall genetic differentiation was significant and high in mtDNA data  at 13 different loci.For microsatellite loci, 18 out of 22 markers were successfully genotyped. However, four markers  showed a large proportion of missing data, while another four loci  showed an estimated frequency of null alleles over 10%. Moreover one locus  showed H-W disequilibrium  million years ago. Estimated migration rates in both directions were significant (p < 0.001) with slightly higher gene flow from C. alexandrinus into C. dealbatus (2.69 migrants per generation) than vice versa (ca. two migrants per generation). The estimated effective population size of C. alexandrinus (Ne ≈ 1.59–4.44 million) was about 8–10 times higher than for C. dealbatus (Ne ≈ 0.15–0.52 million).Isolation with migration analyses suggested that C. dealbatus to C. alexandrinus was slightly higher  than in the other direction . In C. alexandrinus populations, one likely migrant from C. dealbatus and two hybrid F1 individuals were identified (probability higher than 0.5). With the same threshold value, two migrants and one hybrid F1 individual were identified in C. dealbatus populations.The estimation of recent gene flow between the two species, carried out with BayesAss using microsatellites, also suggested bidirectional gene flow. Gene flow from C. alexandrinus  collected from sites at the northern Chinese coastline, Qinghai Lake and Taiwan Island were assigned to C. alexandrinus and C. dealbatus , Last Glacial Maximum  and current times, respectively, showed range shifts in both species. In particular, these results suggest that the ranges of both species shrank during the LIG in the Chinese coastal area accompanied by an increase in climatic suitability in the inland region for C. alexandrinus. In contrast, suitable habitats expanded for both species during the LGM in the coastal area, the East China Sea and the northern part of the South China Sea (sea between Hainan and Taiwan), probably due to a fall in sea level.Our ecological niche models effectively captured the current distribution of both tus Fig.  with a hp = 0.019; Additional file The ordination approach, using PCA-env, suggested that the overlap of the current climatic niches of the two species is relatively low . Further isotope space overlap analysis showed that C. alexandrinus individuals had a high probability of being found within the isotopic niche space of C. dealbatus (95.3%), while C. dealbatus individuals showed a relatively low probability of being found in the isotopic niche space of C. alexandrinus . The difference in bill length may be driven by the difference in the use of food resources and also foraging strategies [C. alexandrinus in Taiwan had similarly large body mass and bill lengths when compared to C. dealbatus populations , consisrategies . Neverthons Fig. b-d, g, wC. dealbatus is restricted to breeding sites close to the coast, particularly where there is a warmer tropical climate. In contrast, C. alexandrinus has a wider climatic niche, as represented by a broader climatic zone . This indicates that C. dealbatus probably feeds on a higher energy diet than its sister species [The niche-equivalency test in environmental (E)-space rejects the possibility that the two species are distributed in strictly equivalent environmental space  and recent divergence  and higher mutation rate than autosomes, the Z chromosome has been demonstrated to contribute to reproductive isolation by playing a large role in promoting both prezygotic and postzygotic isolation, because some regions in the Z chromosome can be responsible for encoding sex-related or mating preference traits [In addition, elevated levels of genetic divergence are often found at Z-linked markers compared with autosomal markers, especially at the nascent stage of speciation, termed as the faster-Z effect . Indeed e traits . Hence dThe loci analyzed here represent just a small proportion of the genome and further investigations using whole genome data hold great potential for providing insights on of the genetic basis of divergence in the two plovers. Particularly, it would be important to identify specific genomic regions (“genomic islands of speciation”) characterized by a high level of divergence and reduced level of gene flow –5. Data C. alexandrinus and C. dealbatus.The geographical boundary between the two plovers was ambiguously defined in previous studies , 42. Ourdealbatus, warranted species status, based on differentiation in morphology, behavior and distribution from C. alexandrinus [C. alexandrinus and C. dealbatus mix frequently on the coast of the South China sea [C. dealbatus is a distinct lineage from C. alexandrinus, and deserves a full species status under the General Lineage Concept of Species (GLC hereafter) [C. dealbatus to be considered as a target for conservation. Because it has a restricted range and is one of few breeding shorebirds in subtropical China coastline, where habitat loss may cause a risk of population decline [Kennerley et al. 2008  recommenandrinus . Uncertaandrinus . At oddsandrinus  analyzedandrinus . Such unandrinus –43 and nhina sea . We furthina sea ), our rereafter) , 98, nowreafter) . Beyond  decline .C. alexandrinus and C. dealbatus represent a case of incipient species in which divergent selection associated with ecological differences likely works as an efficient mechanism for the maintenance of divergence in the face of gene flow. While the full species status of C. dealbatus may be justified under the General Lineage Concept of Species, it remains untested whether a strong level of reproductive isolation has been established between C. alexandrinus and C. dealbatus. Furthermore, we have shown low genetic divergence between the two plovers, so it would be of particular importance to explore the patterns of divergence at the genome level and determine whether specific regions are related to reproductive isolation and adaptation. In addition, the IM analysis presented here estimated average historical gene flow, but it would be interesting to evaluate more realistic (and complex) demographic models in order to better estimate changes in Ne and the span of isolation and secondary contact. Genome-wide population genetic approaches promise the power to resolve the evolutionary history of the two Charadrius plovers but also open an avenue to characterize the genetic architecture associated with phenotypic trait divergence and local adaptation [Resolving the balance between diverging selection and gene flow is of fundamental importance to understand speciation processes. Here, we show that aptation , 101.C. alexandrinus and C. dealbatus, as described by [We mainly collected samples along the eastern coastal area of China Fig. a, and alribed by . Birds wp < 0.05,) at the beginning and end of the fieldwork in the year 2014–2015.For each adult individual, four basic morphometric measurements were taken: body mass, wing length, tarsus length and bill length. Body mass was measured with an electronic scale (± 0.1 g). Wing length (flattened) was measured with a wing ruler (± 1 mm). Bill length to skull and tarsus lengths were measured using vernier callipers (± 0.1 mm). Measurements were taken by Q.H., P.J.Q. and C.Y.C. following the standard described in . To avoiQST based on PC1 scores from PCA were calculated following the method used by JF Storz [We carried out principal component analysis (PCA) for the four traits to visualize the variation of morphometric data. Analyses of covariance (ANCOVAs) were conducted based on the PCA results to test statistical significance. We carried out t-tests for each measurement to assess the difference between species. Pairwise morphological difference JF Storz  and plotJF Storz .2. We also sequenced 14 autosomal and two Z-linked exonic loci [2 (2.5 μM). The PCR cycling profiles used are listed in Additional file We extracted genomic DNA using Tiangen Blood & Tissue Genome DNA Kits, following the manufacturer’s protocols . DNA quality was measured with a NanoDrop 2000 . Three mtDNA loci, namely partial ATPase subunit 6/8, partial D-Loop of the mitochondrial control region (CR) and NADH dehydrogenase subunit 3 fragment (ND3), were amplified from all samples using primers from . PCR reanic loci  for a su2. Multiplex PCR products and associated genotypes were isolated on an ABI3730XL  by Invitrogen, Shanghai, China and their length was determined using GeneMapper software v.3.7 (Applied Biosystems) against an internal size standard .Additionally, all samples were genotyped for 22 autosomal microsatellite markers (mst), mostly those genotyped by Küpper et al. , but alsh), haplotype diversity (Hd), number of segregating sites (S), nucleotide diversity (π) and Tajima’s D [For DNA sequence data, we aligned each mitochondrial or nuclear locus using the CLUSTAL W algorithm in MEGA v.6.06 , and thejima’s D , of eachjima’s D . Haplotyjima’s D  in PopARjima’s D .Ho) and expected heterozygosity (HE) in GenAlEx 6.5.1 [We used FreeNA  to checkEx 6.5.1 .C. alexandrinus continental populations and Taiwan island populations; C. dealbatus, and coastal populations (including Hainan Island), Qinghai and Taiwan. Second, we also calculated pairwise ΦST and FST between breeding sites for mtDNA and mst, respectively, and we derived significance levels using 10,000 permutations in Arlequin.We estimated population structure between species and among sampling sites within species with several approaches. First, for the concatenated mtDNA sequences and microsatellites, we performed analyses of molecular variance (AMOVAs) in Arlequin to assess the proportion of genetic variance explained by the different partition settings: the two species; K = 1 to K = 8 for 500,000 Markov chain Monte Carlo (MCMC) generations with 100,000 burn-in. Replicate runs were combined using STRUCTURE Harvester 0.6.94 [For microsatellite genotypes only, we carried out assignment analyses with two model-based Bayesian approaches. First, we performed a Bayesian clustering analysis using the admixture model with correlated allele frequencies in STRUCTURE 2.3.4 , 120. Ter 0.6.94  and CLUMr 0.6.94 . The mosr 0.6.94 . Second,r 0.6.94 . One milFurthermore, to determine the probability that an individual was a hybrid or a migrant, we estimated the posterior probability of each individual based on microsatellite genotypes. First, we used HYBRIDLAB 1.0  to simulCharadrius vociferus sequences from GenBank were used as an outgroup. The generation time was set to 2.5 years. The substitution rate of each locus was calculated using the method in Li et al. [cytb) and then multiplied by the substitution rate for cytb (0.0105 ± 0.0005 substitution/site/mya) [To infer the demographic histories of the two plover species, we applied Isolation with Migration model (IM)  analysesi et al. . The ratite/mya) . We usedite/mya)  for recoite/mya) , the parite/mya) . For eacite/mya)  based onC. alexandrinus and 24 for C. dealbatus) were obtained from our sampling expeditions during 2002–2016, China Bird Report (http://www.birdreport.cn), and the Global Biodiversity Information Facility . Furthermore, bioclimatic variables were obtained from the WorldClim database v.1.4 [To infer potential past range shifts induced by climatic changes, we carried out ecological niche modeling (ENM) using Maxent 3.3.3 k . The geose v.1.4 . For higse v.1.4 , we retaTo explore niche similarity between the two species, we performed an ordination null test of PCA-env in environmental (E)-space , 137. We15N implies higher trophic level [15N and δ13C between the two species, we collected the outer pair of rectrices from seven adults per site at eight sites: Qinghai Lake, Tangshan, Lianyungang and Rudong for C. alexandrinus; Fuzhou, Shanwei, Zhanjiang, Dongfang for C. dealbatus within our sample set. Since both species perform a complete post-breeding molt within their breeding grounds . In ordgrounds : the ratio of net genetic distance of each locus across ingroup–outgroup was calculated, compared with net distance of mitochondrial cytochrome b (cytb) and then multiplied by the substitution rate for cytb . Table S2. Estimates of pairwise FST for each microsatellite locus between C. alexandrinus and C. dealbatus, LD test result (same for both species), Na, number of alleles, Ho, observed heterozygosity and He, expected heterozygosity in each species. Table S3. PCR amplification protocols for three mtDNA, 16 nuclear exons and 22 microsatellite loci genotyped for C. alexandrinus and C. dealbatus.Table S4. Genetic differentiation between each pair of sampling localities of C. alexandrinus and C. dealbatus. Estimates were based on 1729 bp mtDNA  and 13 microsatellite loci . Values highlighted in red represent significant value after Bonferroni correction. Table S5 The morphological measurements of C. alexandrinus and C. dealbatus in different breeding sites along the Chinese coast, and Taiwan and Hainan Islands. Site reference number corresponds to numbers in Fig. SD) are given. Only DNA samples from a breeding site in Cangzhou were collected but not the measurement, the corresponding data is missing for this population. Mean and SD of bill length, wing length and body mass for each population. Measurement data of the site 3-Cangzhou was not collected. Table S6. Pearson’s correlation coefficients between pairwise of bioclimatic variables with the ranges of C. alexandrinus and C. dealbatus. Figure S1. Haplotype networks based on 80 individuals of 12 nuclear loci not shown in Fig. C. alexandrinus (blue) and C. dealbatus (yellow). Figure S2. The Bayesian clustering analysis with STRUCTURE clearly suggested two genetic clusters corresponding to C. alexandrinus and C. dealbatus. Shown is the maximum value of the Delta K (Δ K) in posterior likelihood Ln P (X/K) over 10 runs per K of STRUCTURE. Figure S3. Niche of C. alexandrinus and C. dealbatus in climatic space from a principal component analysis (PCA-env). a) and b) show the niche characteristics of C. alexandrinus and C. dealbatus, respectively, along the first two axes of the PCA. Grey shading shows the density of the occurrences of the species by cell. The solid and dashed contour lines illustrate, respectively, 100 and 50% of the available (background) environment. c) The contribution of the variables on the first two axes of the PCA and the percentage of inertia explained by the two axes. d) Observed niche overlap D between the two ranges (bars with a diamond) and simulated niche overlaps (grey bars) on which tests of niche equivalency were calculated with 100 iterations. Figure S4. Differentiation in the stable isotope ratios among breeding sites (top-left: δ13C and bottom-left: δ15N) and between the two plovers (top-right: δ13C and bottom-right: δ15N). In all representation, C. alexandrinus marked in blue and C. dealbatus in yellow. Figure S5. (a) Newhybrid simulations failed to reliably detect simulated hybrid individuals. Real data of individuals with posterior density higher than 95% in STRUCTURE, and data of 5 simulated F1 and F2 individuals, and 10 back-cross individuals on each direction was used to imitate a situation when hybrids were the minority in the population. (b) Newhybrid results from real data are highly consistent with the STRUCTURE results. KP represents C. alexandrinus, WFP represents C. dealbatus, bx represents back-crosses. Appendix S1. Reconstruction of potential range shifts induced by climatic changes and inference of environmental niche overlap between the two-plover species, Charadrius alexandrinus and C. dealbatus. Appendix S2. Inference of interspecific diet overlap using stable-isotope analysis between the two plover species, Charadrius alexandrinus and C. dealbatus. (DOCX 530 kb)i et al. 010: the


Stevia rebaudiana (Asteraceae), native from Paraguay, accumulates steviol glycosides (SGs) into its leaves. These compounds exhibit acaloric intense sweet taste which answers to consumer demands for reducing daily sugar intake. Despite the developpement of S. rebaudiana cultivation all over the world, the development of new cultivars is very recent, in particular due to a colossal lack of (1) germplasm collection and breeding, (2) studies on genetic diversity and its structuring, (3) genomic tools.http://compgenomics.ucdavis.edu/data/). We genotyped 145 S. rebaudiana individuals, issued from thirty-one cultivars and thirty-one landraces of various origins worldwide. Markers polymorphic information content (PIC) ranged between 0.60 and 0.84. An average of 12 alleles per locus and a high observed heterozygoty of 0.69 could be observed. The landraces revealed twice as many private alleles as cultivars. The genotypes could be clustered into 3 genetic populations. The landraces were grouped in the same cluster in which the oldest cultivars “Eirete” and “MoritaIII” type are also found. The other two clusters only include cultivated genotypes. One of them revealed an original genetic variability. SG phenotypes could not discriminate the three genetic clusters but phenotyping showed a wide range of composition in terms of bitter to sweet SGs.In this study, we developped 18 EST-SSR from 150,258 EST from The Compositae Genome Project of UC Davis (Stevia rebaudiana involving 145 genotypes, including known cultivars as well as landrace populations of different origin. This study pointed out the structuration of S. rebaudiana germplasm and the resource of the landrace populations for genetic improvement, even on the trait of SG’s composition.This is the first study of genetic diversity in  Stevia rebaudiana, native from Paraguay, is a perennial species that accumulates steviol glycosides (SGs) into its leaves. These natural compounds exhibit acaloric intense sweet taste. Leaves of S. rebaudiana were firstly used as a general sweetening agent by native people of Paraguay and Brazil [S. rebaudiana production at the crossroad of these needs. Correlated to growing demand, S. rebaudiana’s cultivation is increasing all over the world. The species can be grown in a wide range of climatic areas. Nevertheless, the cultivation of S. rebaudiana as a crop is very recent and is done on a small scale in the countries of origin. In 1964, its first commercial cultivation was reported in Paraguay . Afterwards, great efforts were made by Sumida in 1971 to establish S. rebaudiana cultivation in Japan . Later on, it was introduced as a crop in many countries. In 2016, 80% of world stevia leaves production was coming from China with 50,000–60,000 tons of dry leaves per year [d Brazil . Consumeper year . Recent This recently developed crop suffers from a lack of high-value adapted and traceable cultivars. Ninety cultivars have been recently listed by Angelini et al. in 2016 . But, faHowever numerous other traits such as seed germination rate, flowering date, aerial biomass yield, response to biotic and abiotic stresses are poorly improved. Then, identification of productive genetic resources and breeding is clearly needed.Stevia, until recently, the lack of genomic information has made genotyping a bottleneck. Some molecular markers as RAPD [S. rebaudiana genetic map in 1999 [S. rebaudiana has just been sequenced in 2017 by the private consortium PureCircle/Coca-Cola/Keygene [S. rebaudiana and for genetic populations analysis SSR remain first choice markers [S. rebaudiana. In 2013, the Compositae Genome Project released EST data from 15 reference transcriptome assemblies for Compositae crops or their wild relatives including S. rebaudiana [S. rebaudiana no studies addressed the question of developing molecular markers to classify germplasm and to question population structure. The purpose of this work was 1) to develop and assess the applicability of EST-SSRs developed for S. rebaudiana as markers in thirty-one landraces genotypes and one hundred and fourteen cultivated genotypes issued from thirty-one cultivars; 2) to identify genetic diversity and population structure in S. rebaudiana’s landraces and cultivars and 3) to check the link between genetic variability and its structure and phenotypic SG variability in cultivated and landraces populations.Collecting and studying germplasm is a key pillar to start a breeding program. Diversity in plant genetic resources provides opportunity for plant breeders to develop new and improved cultivars with desirable characteristics and is also fundamental to limit the genetic erosion. No available public collection exists and only private companies own collections that are not available. The phenotypic study of a limited number of genotypes have been conducted in different countries –10. Sinc as RAPD  and ISSR as RAPD  have bee in 1999 . Due to /Keygene . The con markers , 17. The markers , 19 deveOf the 150,258 unigenes, 3401 SSR pattern could be detected, 1745 being unique. These 1745 SSR are divided into 6% of mono-nucleotide, 16% of di-nucleotide, 52% of tri-nucleotide, 11% of tetra-nucleotide and 15% of penta-nucleotide  inferred with STRUCTURE revealed three clusters with a relatively high Δ= 3 Fig. a. We use= 3 Fig. a, the cuWe built a Neighbor-Joining tree of the 126 non-admixed individuals , RebA, sweet SG as the sum of RebM, RebD and RebBF and bitter SG as the sum of RebC, DulA, Rub and SB. Expectedly, the graph of the variables contrasted the sweet-flavored SGs such as RebA and sweet SG with stevioside and bitter SG Fig. . The graS. rebaudiana has a recognized interest in health and the associated industry is now highly developed and world-wide. Nevertheless, the optimized improvement of Stevia is in its very early stages. Breeding programs are relatively new. In particular, they suffer from the critical lack of in-depth information on genetic resources associated with a lack of genomic tools. On the basis of the gathering of 145 genotypes of origin as diverse as possible, our study has for objective (1) to develop robust SSR markers (2) to study the pattern of genetic diversity and genetic structure of 114 cultivated genotypes from 31 cultivars but also 31 landraces coming from different regions of Argentina and Cuba.The gathering and in-depth study of genetic resources is an essential step in setting up a breeding program. S. rebaudiana is longstanding. In 1999, one hundred and eighty-three RAPD markers were developed and used to produce the first partial genetic map from a pseudo test-cross F1 [S. rebaudiana by [SSR markers are useful for studying genetic diversity because they are highly polymorphic, multi-allelic and their development requires a limited genomic information. Therefore, they are the easiest and more informative molecular markers. The development of molecular markers in cross F1 . RAPD ancross F1 , 21 and cross F1 . As undediana by , 19. Fifdiana by , 22. Thediana by , focuseddiana by , in eggpdiana by  or in opdiana by  that genS. rebaudiana [Nevertheless, in both studies and our, average Ho was high, 0.80 and 0.69 respectively, in accordance with the reported outcross mating system of The population structure and dendogram analyses divided the accessions into three clusters/subpopulations, although the analyses are based on different methods. The low number of admixed genotypes (19/145) can be explained by the composition of the collection, 78% (114/145) of which are cultivated varieties and 22% (31/145) of landraces. No wild genotypes could be analyzed. In addition, the varieties grown are often produced by crossing between two identified parents. The use of a limited number of parents may also explain the low number of admixed.Except for the two Chinese cultivars belonging to admix cluster, no regional aggregation could be observed. Cluster 1, in particular, gathers genotypes from Canada, Germany and Israël, indicating large seed and alleles exchanges in Stevia. Cluster 1 and Cluster 3 consisted essentially of cultivated varieties. Cluster 1 seems to reveal original diversity. It contains the genotype “Gawi” selected in Germany , 27 but S. rebaudiana genetic resources, there is no reference study. But, similar results have been observed in other outcrossing perennials such as alfalfa (Medicago sativa) [Tanacetum cinerariifolium) [Panicum virgatum) [AMOVA results showed that the genetic differentiation was overwhelmingly due to within population variation. As our study is the first large study on  sativa) , Dalmatiifolium)  or agronirgatum) . The higPhenotyping of SGs does not allow to structure the different populations. The three genetic populations differed very little based on this trait. Surprisingly, it is the landraces populations that appear to draw towards the quality of sweetness in SG, while cluster 1 and 3, composed only of cultivars cannot be distinguished. They are composed of cultivars producing very varied SGs, from bitter to sweet, which may seem surprising considering that the ratio SG soft/bitter is the first selection criterion in Stevia .S. rebaudiana involving 145 genotypes, including known cultivars as well as landrace populations of different origin. This study generated 18 new highly polymorphic and robust microsatellite markers. These markers are of great potential for genetic diversity evaluation and germplasm managing which is a crucial step of breeding. These markers could also be used for genotypes traceability. The 145 genotypes of S. rebaudiana were successfully genotyped. They revealed three genetic populations with a remarkable variation within population. Landraces revealed their allelic richness and their interest in term of sweet SG phenotype. They harbor valuable genetic variation for further improvement via breeding as shown through their phenotyping in Argentina [Our study is the first analysis of genetic diversity in rgentina .S. rebaudiana was collected from different origins  according to the pipeline described in Additional file http://abajian.net/sputnik/) were used to identify EST containing SSR. For SSR identification, the minimum motif repeats were defined as 20 repeats for a mononucleotide unit, 10 repeats for a dinucleotide unit, 7 repeats for trinucleotide unit, 5 repeats for tetranucleotide unit and 4 repeats for pentanucleotide unit. Primer pairs flanking the SSRs were designed using Primer3Plus [Microsatellite or SSRs were developed from 150,258 EST generated on 454 sequencing and downloaded from The Compositae Genome Project of UC Davis . The amplifications were performed in a Mastercycler Pro (Eppendorf) with the following PCR protocol: 15 min initial denaturation at 95 °C and 35 cycles of 30 s at 94 °C, 45 s at 55 °C, 60 s at 72 °C, followed by a final extension for 10 min at 72 °C.PCR amplifications were performed in 15 μl reaction volume containing 10 ng of template DNA, 1 X PCR buffer , 2.5 mM MgCLPCR amplicons were separated on denaturing polyacrylamide gels consisting of 4.5% polyacrylamide (acrylamide: bis-acrylamide 19: 1) and 7 M urea in 1× TBE buffer. After run, amplified fragments were visualized using silver staining protocol .Fragments were genotyped at each locus, and the allele sizes were scored using 10–330 bp ladder (Invitrogen).Allele frequencies and genetic diversity measures were calculated using PowerMarker 3.25  and GenAhttp://taylor0.biology.ucla.edu/structureHarvester/) according to Evanno et al. (2005) [Representation of the genetic relationships among individuals was explored with a principal component analysis (PCA) performed with GENETIX v4.05 . We also. (2005) .Steviol glycosides extraction and quantification was done as described in Hastoy et al. (2019) . Nine SGAdditional file 1: Figure S1. Summary of the pipeline for the selection of the 18 SSRs used in the current study. Figure S2. Mean number of private alleles per locus and mean number of distinct allele per locus for the cultivated and landraces genotypes computed with ADZE softwareAdditional file 2: Table S1. Type and number of repeat pattern of the 1745 unique SSR among the 150,258 unigenes available for Stevia rebaudiana at http://compgenomics.ucdavis.edu/data/cwassy_2012/iAssSta.fa (The Compositae Genome Project of UC Davis). Table S2. List of the 18 SSR and related primers and characteristics used in this study. Table S3. List of Stevia rebaudiana cultivated and landraces groups studied. Table S4. Distribution of the studied genotypes in the different clusters and admix following the analysis by Structure


Gadus morhua L.) has formed the basis of many economically significant fisheries in the North Atlantic, and is one of the best studied marine fishes, but a legacy of overexploitation has depleted populations and collapsed fisheries in several regions. Previous studies have identified considerable population genetic structure for Atlantic cod. However, within Norway, which is the country with the largest remaining catch in the Atlantic, the population genetic structure of coastal cod (NCC) along the entire coastline has not yet been investigated. We sampled > 4000 cod from 55 spawning sites. All fish were genotyped with 6 microsatellite markers and Pan I (Dataset 1). A sub-set of the samples (1295 fish from 17 locations) were also genotyped with an additional 9 microsatellites (Dataset 2). Otoliths were read in order to exclude North East Arctic Cod (NEAC) from the analyses, as and where appropriate.Atlantic cod . While no clear genetic groups were identified, genetic differentiation increased among geographically-distinct samples. Although the locus Gmo132 was identified as a candidate for positive selection, possibly through linkage with a genomic region under selection, overall trends remained when this locus was excluded from the analyses. The most common allele in loci Gmo132 and Gmo34 showed a marked frequency change in the north-south gradient, increasing towards the frequency observed in NEAC in the north.We found no difference in genetic diversity, measured as number of alleles, allelic richness, heterozygosity nor effective population sizes, in the north-south gradient. In both data sets, weak but significant population genetic structure was revealed  contains supplementary material, which is available to authorized users. Gadus morhua L.) is a demersal fish found in the northern waters across the Atlantic. Due to its large size and historical high abundance, cod has formed the basis of some of the most commercially important fisheries in the Atlantic for centuries. However, a legacy of over-exploitation, potentially exacerbated by climate-driven changes in distribution, has left several cod populations depleted [The Atlantic cod . The Studies have revealed genetic differences between cod sampled on the eastern and western sides of the Atlantic , 30, 38,In addition to spatial genetic structure, genetic differences have been observed among cod “ecotypes” displaying stationary and long-distance migratory behaviours. For example, large genetic differences have been reported between NCC and NEAC, which display stationary and migratory behaviours respectively , 31, 32.Despite the considerable number of population genetic studies on cod, there are still a number of remaining questions. This is the case for Norway, which is the country with the largest remaining commercial catch of cod in the Atlantic. In Norway, coastal cod are currently divided into two management stocks, defined as NCC north of 62°, and coastal cod south of 62° (from hereon we refer to both of these components as NCC for simplicity). While the NEAC stock is currently at a high level , 51, NCCIn 2002, a project was initiated to map the population genetic structure of NCC along the entire Norwegian coast. This included sampling cod from 55 spawning locations spanning the Russian to Swedish borders with Norway Fig. . At the In the period from 2002 to 2007, 4422 cod were collected from 55 locations along the coast of Norway Fig. . Eleven Although genetic analyses have also been used for identification of NEAC and NCC in Norwegian fisheries , 57, in DNA extraction was performed using the Qiagen DNeasyH96 Blood & Tissue Kit; each of which contained two or more negative controls. All 4346 individuals were genotyped at six microsatellite loci: Gmo2, Gmo3, Gmo34, Gmo35, Gmo132 and Tch11 –62, togeO) and unbiased expected (uHe) heterozygosity, inbreeding coefficient (FIS) and deviations from the expected Hardy-Weinberg distribution, were computed with GenAlEx [Statistical analyses were conducted separately for microsatellites and Pan I. The total number of alleles, and allelic richness, were both calculated with MSA , whereas GenAlEx . Possibl GenAlEx  with sig GenAlEx , impleme GenAlEx  implemenST, and with a 0.01 false discovery rate. Genetic differentiation among sampling sites was tested using the Analysis of Molecular Variance (AMOVA) as well by pairwise FST. Both analyses were implemented in ARLEQUIN v.3.5.1.2 [To test if loci deviated from neutrality, outlier analyses were conducted with LOSITAN  under a .3.5.1.2  and signST were tested for trends in the geographic north-south gradient using the non-parametric Kendall measure of rank correlation [Several parameters such as the number of alleles, allelic richness, allele frequency, Ho, uHe and pairwise Frelation , which mrelation , and imprelation .Population genetic structure and connectivity were investigated using two approaches. First, through BARRIER 2.2 software , which aP = 0.00045)  .Dataset 1 included samples from 55 locations , made up of 25–129 individuals each, that were genotyped for six microsatellites and Pan I. Across the six microsatellites, the total number of alleles observed per sample ranged from 59 to 85, and allelic richness ranged from 9.0–11.1 (Table 45) Fig. . In cont74) Fig. . ObserveP = 0.1721; and τ = 0.0543, P = 0.7888, respectively) . Neither Ho (0.632–0.734) nor uHe (0.669–0.769) showed any trend in the north-south gradient   Fig. . Two of ST per locus significantly differed from zero .In the six microsatellites common to both datasets, the total number of alleles observed per locus showed extremely similar values, despite that the number of individuals genotyped displayed a 3-fold difference between the two data sets . Global FST did not change when removing the individuals showing the genotype Pan I BB, which is the dominating genotype in NEAC and observed in very low frequency in NCC. This meant excluding 104 and 39 individuals from Datasets 1 and 2 respectively (data not shown). After excluding the microsatellite identified to be under positive selection (Gmo132), global FST decreased, but it was still statistically significant in both Dataset 1 , and Dataset 2 .Global FST comparisons within the seven geographically-determined regions were significant , in contrast with 50.5% of the pairwise comparisons among regions , in contrast with the 55% found among regions  and Dataset 2   Fig. .Table 4GHierarchical AMOVAs were conducted for datasets 1 and 2 using the aforementioned geographic approach to define regions. In both cases, the three levels of division  showed significant values Table . The difST of 0.034). Locus Gmo34 showed significant FCT and FST (average FST = 0.005) in all analyses. The extra set of nine microsatellites used in Dataset 2 showed one locus also significant at all levels (Gmo45), but also revealing a weak degree of structuring (average FST = 0.006). Interestingly, the most frequent alleles for both Gmo34 and Gmo132 displayed a strong and highly significant trend in the north-south gradient  and allele 115 from locus Gmo132 ranged from 0.681–0.105  in the direction north to south.Hierarchical AMOVAs per locus showed that the locus Gmo132 was the only one significant at all levels of division in both datasets Table . This maP = 0.0068, Fig. ST = 0.107, P < 0.0001) and hierarchical AMOVA was also significant at the three levels of grouping .Looking at the results for the Pan I locus, that was analysed for all samples, the three different genotypes displayed clearly distinct frequencies throughout the NCC samples Fig. . Genotypng Table . LikewisIn order to investigate the potential admixture between both types of cod, NEAC was used as an outlier group for NCC in STRUCTURE. These analyses showed no clear clustering of populations in the full dataset genotyped at 6 microsatellites Fig.  in agreeNorway is the country with the largest remaining commercial catch of Atlantic cod, and this is the first study to investigate population genetic structure of coastal cod (NCC) along the entire Norwegian coastline. Following the analysis of > 4000 cod sampled from 55 locations, we obtained the following main results: 1. Statistically significant population genetic differentiation was revealed among most of the samples, 2. The observed genetic differentiation followed a pattern of isolation by distance along the north-south gradient, without any clear “breaks”, 3. No distinct change in genetic variation  was observed among the samples in the north-south gradient. Based upon these results, we conclude that NCC displays statistically significant population genetic structure along the Norwegian coastline. Consequently, these results demonstrate that the current management regime, dividing coastal cod in Norway into two management groups, one north and one south of 62°, represents an over-simplification of the true level of population genetic structure, and as such, requires re-evaluation.As detailed in the introduction, Atlantic cod is one of the best-studied marine fishes, and a large number of population genetic studies have revealed a species displaying extensive population genetic structure (reviewed by –7). WhilThe primary aim of the present study was to investigate population genetic differentiation among coastal cod sampled from the entire Norwegian coastline, which stretches over 2500 km from the south in Oslofjord, to the north in Porsangerfjord Fig. . In someThe Pan I BB genotype is nearly fixed for NEAC , and is A distinct north-south cline in the frequency of the allele 115 for the microsatellite Gmo132 was observed here Fig. . This paPopulation genetic differentiation was observed among samples of NCC throughout all regions of Norway, including among samples from southern Norway where NEAC was hardly present (as determined either by Pan I genotype or otolith category). In the far southern region, it is unlikely that NEAC has played a direct role in shaping the evolutionary relationships among NCC populations . However, the interaction between migratory North Sea cod and NCC populations in the south of Norway also remains a potential source of influence on NCC structure in this region . ClearlyCurrent evidence suggests that the long-distance migratory “ecotype” of Atlantic cod, including NEAC, was derived from the stationary “ecotype” , and thaApplying the same management strategy to multiple populations or stock components that vary in their abundance and/or resilience to exploitation inevitably results in overfishing and likely collapse of the weaker component , 97. TheAn additional management contribution from the present analyses is the apparent lack of any clear differences in genetic variation, as reported by numbers of alleles, allelic richness, heterozygosity or the effective population size Fig. , in the Norwegian coastal cod displays statistically significant population genetic structure along the Norwegian coastline, which follows a genetic gradient characterised by isolation by distance. Although not fully resolved, we suggest that genetic introgression and admixture between NEAC and NCC, most in the north and least in the south, together with limited gene-flow among NCC populations, may contribute to the observed population genetic structure of NCC. In turn, we conclude that the current management regime in place, dividing coastal cod in Norway into two management groups, north and south of 62°, represents an over-simplification of the true level of population genetic structure, and as such, requires re-evaluation.Additional file 1:Figure S1. Ho and uHe per sampling site for (a) Dataset 1 (66 samples genotyped at 6 microsatellite markers) and (b) Dataset 2 (18 samples genotyped at 15 microsatellite markers). Locations are ordered from north to south along the coastline. In graph a), Ho and uHe experienced significantly increasing N-S trends . Unlikewise, in graph b), neither Ho nor uHe showed any kind of N-S trend . (ZIP 1059 kb)Additional file 2:Table S1. Genetic differentiation at Dataset 1 (66 samples genotyped at 6 microsatellite markers): Pairwise FST are shown in the lower diagonal whereas P-values computed after 10,000 permutations are shown in the lower diagonal. (XLSX 77 kb)Additional file 3:Raw data. Genotypes for Dataset 1 (66 samples genotyped at 6 microsatellites) and Dataset 2 (18 samples genotyped at 15 microsatellites). Pan I genotypes, and otolith information is provided for each individual as well. (XLSX 563 kb)


Oryza sativa L.) is one of the most important crops of the world and a major staple food for half of the World’s human population. The Northeastern (NE) region of India lies in the Indo-Burma biodiversity hotspot and about 45% of the total flora of the country is found in the region. Local rice cultivars from different states of NE India were analyzed for genetic diversity and population structure using microsatellite markers, and their zinc and iron content.Rice  and the polymorphism information content (0.5895). Nali Dhan cultivar of Arunachal Pradesh possessed the highest genetic diversity (0.3545) among studied populations while Moirangphou Khonganbi of Manipur exhibited the lowest genetic diversity (0.0343). The model-based population structure revealed that all the studied 65 rice cultivars were grouped into two clusters. Cluster I was represented by 36 cultivars and cluster II by 29 cultivars. Badalsali cultivar of Assam possessed the highest Zn content (75.8 μg/g) and Kapongla from Manipur possessed the lowest (17.98 μg/g). The highest and the lowest Fe content was found in Fazu (215.62 μg/g) and Idaw (11.42 μg/g) of Mizoram.The result suggested rice cultivars of NE India possessing high genetic diversity , high Zn  and Fe (Fazu) content can be useful as a source of germplasm for future rice improvement programs. Oryza sativa L.) is the staple food for more than 50 % of the world’s population. The rice production and consumption in Asia alone accounts for more than 90 % of the global rice yields [Rice  to Fazu (215.62 μg/g) with an average of 59.29 μg/g (Table 1.42 μg/gE) varied from 0.1157 (RM315) to 0.8466 (RM72) with an average of 0.6311 respectively. Nei’s genetic diversity varied from 0.1155 (RM315) to 0.8453 (RM72) with an average of 0.6301. Fst ranged from 0.5739 (RM223) to 0.9619 (RM443) with an average of 0.7870. Polymorphism information content (PIC) ranged from 0.1012 (RM315) to 0.8274 (RM72) averaging 0.5895. The summary statistics of each marker is shown in Table The agarose gels showing banding patterns of some rice cultivars were presented in Figs. .8466 RM7 with an Japonica varieties. And cluster II could also be subdivided into four groups comprising rice cultivars of Mizoram, Nagaland, Meghalaya and Indica varieties. Analysis of molecular variance (AMOVA) showed that the genetic variation of two clusters of 65 rice cultivars was distributed into 73% among populations and 27% within populations. Average distances (expected heterozygosity) between individuals in the same cluster varied from Cluster I (0.5197) to cluster II (0.5686). Fst values of Cluster I and Cluster II were found to be 0.2635 and 0.2107 respectively with an average of 0.2371. The mean alpha value was found to be 0.0663.The model-based population structure analysis using STRUCTURE showed that the highest value of ΔK was at K = 2 Fig. , groupinE) of Manipur rice cultivars ranged from 0.0343 (Moirangphoukhonganbi) to 0.1475 (Changlei), and that of Nagaland ranged from 0.1263 (Ekemai) to 0.2323 (Jakjatsuk), and Assam, from 0.0697 (Sakua) to 0.2475 (Bogaahoo), Arunachal Pradesh, from 0.1030 (Aamda) to 0.3545 , Mizoram, from 0.1172 (Tai sanghar) to 0.2333 (Fare) and Meghalaya rice cultivars ranged from 0.1010 (Jaiamenil) to 0.1747 (Menilmibabaret). Rice cultivars of Arunachal Pradesh, in overall exhibited highest gene diversity (0.2022), followed by Nagaland (0.1896), Mizoram (0.1746), Assam (0.1492), Meghalaya (0.1378) and then Manipur (0.0788). The average genetic diversity of all indigenous cultivars was found to be 0.1575 which was higher than that of indica (0.1180) and japonica (0.1170) varieties.Population-wise diversity comparison Table  showed tComparative analysis of gene diversity, Zn and Fe content showed that there was no significant correlation among all the three parameters. However, few cultivars with high gene diversity also showed higher Zn and Fe content Table , Fig. 7.indica and 5 japonica test varieties were performed using twenty-two SSR markers comprising 9 random and 13 trait-linked markers, and Zn and Fe content. Assessments of genetic diversity of NE rice using molecular markers has been reported previously [In this study, genetic structure and diversity analysis of 55 indigenous rice cultivars of Northeast India and 5 eviously –25. Thoueviously , 26, 27,eviously . Althougeviously . In the eviously . High Feeviously . The Zn eviously . Averageeviously , 32. In eviously , among seviously . TherefoE and PIC found in the present study showed a high value of heterozygosity index. The mean Fst values for all loci and between the two clusters were found to be 0.7786 and 0.1987 respectively indicating very high genetic differentiation among loci and among the clusters. Based on SSR analysis, there were seventeen highly informative markers (PIC> 0.50), viz., RM1, RM154, RM131, RM135, RM72, RM171, RM287, RM3825, RM246, RM260, RM525, RM219, RM223, RM8094, RM493, RM3412 and RM169; two informative markers (PIC between 0.25 and 0.50), RM153, RM125, and RM302; and two slightly informative markers (PIC< 0.25), RM315 and RM443 [The NE rice cultivars contain considerable genetic diversity and variable traits which might be good sources for various improvement programs . All SSRnd RM443 , 37.indica and japonica. In the current study, the identified two main clusters can also be divided into sub-clusters corresponding to state-wise grouping. A similar result of state-wise grouping was also observed in aromatic rice germplasm from North Eastern India [Population structure analysis using STRUCTURE showed highest ΔK value at K = 2 revealing that the studied 65 rice cultivars were grouped into two clusters. The number of the cluster was in agreement to the previous studies: two clusters among 29 varieties of cultivated rice of NE India  and two rn India . Accordirn India , alpha vChakhao rice of Manipur, resistance against blast, resistance to gall midge, deep water tolerance in Baon of Assam, drought resistance in Hmawrhang of Mizoram, etc. [In some areas of NE India, rice has been cultivated in shifting or jhum lands which only depend on the Monsoon rain. These cultivars survive in long spells of rainless weather and may be good candidates to look for these variable traits. Other important traits include dark color and aroma in am, etc. , 40, 41.am, etc. . The useam, etc. . Among tThe current study provides a better understanding of genetic structure, diversity, and micronutrient (Zn and Fe) richness in the indigenous rice cultivars of NE India. The cultivars possessing high genetic diversity , high Zn  and Fe (Fazu) contents are promising candidates as parental lines for future rice breeding programs. These findings will further facilitate the conservation strategies and utilization of these landraces for developing sustainable rice improvement programs.Indica and japonica check varieties were kind gifts from ICGEB, New Delhi, ABF, Hyderabad and ICAR, Kolasib. For isolation of DNA, individual cultivars were planted on polypots at Department of Botany, Mizoram University, India.Rice landraces were collected from six states of NE India. Details of collection sites are shown in Table 3) was added to it. The mixture was kept on a hot plate till the fuming of nitrogen dioxide ceased. Another 20 ml of HNO3 was added and the samples were kept on the hot plate at a high temperature until the solution turned colourless. Then hydrogen peroxide (H2O2) was added to make the solution colourless. The mixture was heated until the solution was reduced to 3–5 ml. This extract was diluted to 20 ml with de-ionized water and then filtered through Whatman filter paper 1. The extract was then injected into Atomic Absorption Spectrophotometer  and the results were expressed in μg/g.Dehusked rice seeds were crushed into a fine powder using mortar and pestle. The powdered sample (0.1 g) was placed in a 100 ml conical flask and 20 ml of Nitric acid , 50 ng of each primer and 50 ng template DNA. The amplification conditions were set as, initial denaturation at 94 °C for 5 min, 35 cycles of denaturation at 94 °C for 30 s, annealing for 30 s, extension at 72 °C for 1 min followed by a final extension at 72 °C for 7 min. The amplified products were electrophoresed on 2.5% agarose gel and visualized by standard ethidium bromide staining [Twenty-two simple sequence repeats (SSR) primers Table  were usestaining , 44.TabBands were scored using Alpha View software . Total number of alleles, number of effective alleles, number of polymorphic loci, observed and expected heterozygosity, Nei’sgenetic diversity , Fst, anAdditional file 1. The genotype data of indigenous rice cultivars of NE India and improved varieties.Additional file 2. Pairwise Population Matrix of Nei Genetic Identity.Additional file 3. Pairwise Population Fst Values.Additional file 4. Summary of analysis of molecular variance.


Though extracorporeal membrane oxygenation (ECMO) provides life-saving support, this intervention exposes patients to certain risks. Circulating free hemoglobin (fHb) resulting from mechanically induced hemolysis and insufficient haptoglobin/hemopexin may promote thrombosis within the ECMO circuit. Thrombi in the circuit can result in thromboembolic complications in these patients. Prevention of thrombus formation and propagation in the ECMO circuit may improve clinical outcome. fHb released during hemolysis has been shown to have multiple adverse effects, including thrombosis, but the mechanism by which fHb contributes to thrombosis in an ECMO circuit remains elusive. It is well established that (1) high shear stress generated in the circuit may cause hemolysis, and (2) plasma fibrinogen is adsorbed onto the inner tubing of the ECMO circuit over time. Plasma von Willebrand factor (pVWF) mediates platelet deposition at sites of vascular injury under high shear stress by sensing alterations in the hemodynamic environment. This biophysical property of pVWF that enables hemostasis may also contribute to the pathogenesis of ECMO-induced thrombosis. pVWF contains binding sites for both adsorbed fibrin(ogen) and fHb. High concentrations of fHb increase pVWF-mediated platelet adhesion and thrombus formation on a surface-adsorbed fibrin(ogen) under high shear stress. The molecular mechanism(s) by which fHb drives the conformation of pVWF into a prothrombotic state is currently unknown. Reduction of thrombotic risks during ECMO intervention warrants further investigations into the interaction between pVWF and fHb. Extracorporeal membrane oxygenation (ECMO) provides temporary multi-organ support for patients with congenital or acquired heart and/or lung disease or resuscitative support for patients with cardiopulmonary failure. ECMO functionally substitutes the heart and lungs by circulating blood through a gas exchanger similarly to a heart-lung bypass machine but for a longer duration. Patients supported with ECMO can present with both bleeding and thromboembolic risks despite close monitoring of systemic anticoagulation . BleedinIncreasing evidence suggests elevated levels of free hemoglobin (fHb) in blood of patients on ECMO are a major clinical complication , 4. Highvon Willebrand factor (VWF) is a multimeric glycoprotein that plays a critical function in mediating platelet adhesion and aggregation in hemostasis and thrombosis . The matNormally, plasma (p)VWF does not interact with circulating platelets unless it undergoes conformational changes. In hemostasis, when the integrity of the vessel wall has been compromised, pVWF quickly binds to components exposed in the subendothelial matrix  at high shear stress. This interaction provokes structural changes that expose the contact site for the platelet receptor GPIbα in A1 domain of VWF, allowing circulating platelets to rapidly bind to the collagen-bound VWF , 15. On We and others have demonstrated the capacity of fHb to block the cleavage of VWF by ADAMTS-13 , 24. SomOn the other hand, we speculate that fHb causes thrombosis on surfaces with adsorbed fibrinogen (like the inner tubing of an ECMO circuit) by strengthening the interaction between VWF and GPIbα. The concept is based on our identification and characterization of a novel binding activity of fHb for the A1 domain of VWF and how this interaction seems to be associated with high levels of fHb and thrombosis in patients on ECMO . fHb binThe adsorption of plasma fibrinogen to biomaterials is a quick event that transforms the surface to one that promotes platelet adhesion and thrombus formation under high shear stress as seen in ECMO circuits . It is win vitro heparin had a weak inhibitory effect in reducing thrombosis in the presence of high levels of fHb . The more insights we gain from dissecting the molecular mechanisms by which fHb promotes thrombosis via VWF will lay the foundation for the development of potential therapies to prevent fHb-VWF binding and improve clinical outcome.MC, AY, and CV wrote this article. MC and CV designed and performed experiments.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.