Selective breeding in populations with a limited effective population size may result in a loss of genetic diversity, which can cause an increased concentration of specific disease liability genes. The Dutch Shepherd Dog (DSD) in the Netherlands is an example of such a breed with a small effective population.To evaluate the measurement of genetic diversity and multiplex DNA panel screening for implementation in a breeding strategy for the Dutch Shepherd Dog (DSD) and to investigate the clinical relevance of potentially identified mutations in the multiplex DNA panel screening.Genome-wide SNP testing showed genetic isolation and reduced genetic diversity within coat variety subgroups of the DSD. Panel screening identified a Von Willebrand’s Disease type I mutation. Although decreased Von Willebrand’s Factor proteins were significantly lower in DSDs carrying the VWD-I allele compared to the wildtype, clinical follow-up did not show a significant association between the clinical phenotype and VWD-I genotype.Genetic relationship measurement within a breed population may be a useful tool to enable breeding strategies to conserve genetic diversity. Results from a disease panel screening need to be evaluated for clinical relevance before breed selection restrictions can be considered.The online version of this article (10.1186/s40575-018-0068-6) contains supplementary material, which is available to authorized users. Breed-related health issues in dogs are in part due to selective breeding. In effect, if only a small part of the population is allowed to breed, the individuals of that population become more and more alike, even at the level of genes. This is called limited genetic diversity, and it may increase the occurrence of genetic disorders. In contrast, populations that are not allowed to breed with each other become genetically different.In this paper, we show the use of two genetic tools which support a sensible breeding strategy: 1) genetic relationships and diversity, and 2) screening test for genetic disorders. Both tools are provided by MyDogDNA™. As an example, these genetic tools were studied in the Dutch Shepherd Dog, a breed with three coat varieties . Historically, dogs with different coat varieties were not allowed to breed with each other.The genetic relationship and diversity test showed that the three coat varieties of the Dutch Shepherd Dog were genetically isolated from each other, but within each group they were all much alike.The screening test for genetic disorders in the Dutch Shepherd Dog showed the presence of the disease allele for Von Willebrand’s Disease type I, an inherited bleeding disorder. Further research showed that only a small percentage of the Dutch Shepherd Dogs were genetic carriers of this disease, and none showed evincive clinical signs.In this study we found that genetic relationship results can show how far apart (sub) populations are, and what breeding strategies may be used to increase the diversity within subgroups. Furthermore, a screening test for genetic disorders can identify unexpected mutations that may cause clinical disease.We conclude that a sensible breeding programme includes genetic tools, as well as individual and population-based clinical screening for disorders.Dog breeds are known to be subject to human-induced limitations of the gene pool such as a popular sire effect and a breed barrier – a dog can only be registered as a certain breed if both parents are registered as such – resulting in reproductive isolation. Consequently, dogs from the same breed are genetically similar to each other , to suchThe DSD belongs to the shepherd dog type that originated in the Netherlands in the nineteenth century. It is grouped with e.g. the Saarloos wolfdog , and is Genetic heterozygosity testing is currently routinely based on single nucleotide polymorphism (SNP) genotyping. SNP data can be used to test the genetic relationships of individuals and the genetic diversity of a population . HeterozGenome-wide SNP testing offers more accurate genetic diversity estimates than pedigree records or short-tandem repeat molecular markers  and the The aim of this paper is to evaluate the measurement of genetic diversity and multiplex DNA panel screening for implementation in a breeding strategy for the Dutch Shepherd Dog (DSD).The Von Willebrand’s Disease type I (VWD-I) gene mutation c.7437G > A ). All variety crosses of short haired x long haired together had a genetic diversity of 29.4%, which was significantly higher than the 25.4% of the long haired parent population (p < 0.05)  Fig. c.Results of the disease variant panel screening in the 30 DSDs that were tested in the first phase of this study showed one carrier for VWD-I in the long haired DSD variety, in which a c.7437G > A variant was present Fig. . All dogn = 42, 89% of the dogs from the Dutch population used for breeding) showed an allele frequency of < 3% , since two breeding individuals were carriers and no homozygously affected individuals were found . We found a significant difference in the Von Willebrand protein concentration when comparing the wildtype group with the other two groups combined  , heterozygous carrier (2), and homozygous mutant (2)). However, all of these episodes could be related to trauma, no excessive bleeding was reported. VWF protein concentrations ranged between 7 and 95%. No significant difference in VWF values was found when the three groups were compared . The short haired DSDs have a greater level of diversity. So, in relation to purebred dogs as a whole, our observations showed that the DSD is at the lower end of the spectrum. The genetic diversity of all three DSD varieties is less than that of mixed-breed dogs (43.2%) . Being aBreeding for heterozygosity reduces the risk of inbreeding depression, where accumulation of deleterious mutations leads to a lower individual fitness. This may lead to smaller litters, reduced lifespan and increased mortality in offspring . AlthougWe would in this case advise expanding the effective population size for each coat variety; to make full use of the available gene pool whilst selecting animals with the desired characteristics for the breed. To increase the heterozygosity within the three different coat varieties, we advise to continue variety crossbreeding. It is important to note that the DSD remains a distinct dog breed in this way, but the separation between the coat varieties will decrease, decreasing the risk of accumulation of recessive alleles within coat varieties. Even with breeding between the coat varieties, one of the important desired breed characteristics (coat-length) for the DSD was maintained and future selection of dogs for breeding could be supported by using the tests for traits that are present on MyDogDNA™.The results of the VWD-I sequencing show an allele frequency of < 3% in the DSD breeding population in the years 2013–2015 in the Netherlands. This breeding population is assumed to be the parent population of the current national DSD population. In the subset of 19 dogs that were clinically evaluated, no bleeding tendency was found, although we observed a statistically significant lower VWF protein concentration in dogs hetero- or homozygous for the examined VWD-I mutation. The results of this limited sample confirm that, as in other breeds with VWD-I, the presence of a mutated allele leads to a lower VWD protein concentration but shows only limited signs of haemorrhagic diathesis –36. HoweIncreased inbreeding of (sub) populations of a dog breed, carries the risk of inbreeding depression and increase of allele frequency of disease-causing, usually recessive alleles. Increasing heterozygosity, whilst maintaining characteristics important for the breed, and prevention the segregation of disease-causing gene mutations may be important in a sustainable, healthy breeding program.Genetic relationship measurements can be used to match breeding couples to increase the genetic diversity in a breed population or in subpopulations within a breed. The multiplex DNA panel screening can be used to check for genetic disorders in the breed that were previously unknown and could potentially spread unintendedly in the population.A sensible breeding programme should include application of the described genetic tools with appropriate counselling, as well as individual and population-based clinical screening for disorders with and without a known mutation.Members of the Dutch Shepherd Dog Club volunteered the individual DSDs tested in this study. The numbers in each of the consecutive steps were 1) MyDogDNA™ screening first testing group ; 2) Von Willebrand’s Factor (VWF) type I genotype testing in the long haired DSD population through continued MyDogDNA™ testing and Sanger sequencing ; 3) MyDogDNA™ combined results ; and 4) Evaluation of the bleeding history and coagulation .Crossbreeding of coat varieties in this study took place between short haired and long haired DSDs only. Any crossbreeding between the short haired and wire haired variety is not included in this study, and crossbreeding between long haired and wire haired varieties is not allowed. The parent population of short haired and long haired DSDs were matched  to produce first generation variety crosses. Matching first generation variety crosses with a parent population (backcross) resulted in second generation variety crosses, matching second generation variety crosses with a parent population resulted in third generation variety crosses Fig. a.p < 0.05) The multiplex DNA panel screening is a genotyping microarray, which, at the time of the present study, tested for 189 known disease variants and 22 traits, including coat length and colour [MyDogDNA™  testing consists of two main tests: heterozygosity testing, and multiplex DNA panel screening. Heterozygosity is determined using a genome-wide single nucleotide polymorphism (SNP) test – evaluating genetic relationships and genetic diversity, respectively relating to the individual and the population (e.g. ). For thd colour  . We performed PCR to capture the VWD-I mutation (forward primer (5′- AAATCTCCTTCATAAGCATCCC-3′) and reverse primer (5′- CTGCCTTTCACCCAACCT-3′)). The PCR product was treated with Exonuclease I and Shrimp Alkaline Phosphatase. Sequence reactions, performed with Big Dye Terminator Ready Reaction Mix v3.1 (Applied Biosystems), were sequenced on an ABI3500XL and analyzed in Lasergene (version 12.0 DNASTAR).n = 9), carriers (n = 8) or homozygously affected (n = 2). A detailed history, VWF concentration, coagulation profile, and thrombocyte count were collected. Blood samples from the jugular vein  were used to determine the VWF I antigen concentration by enzyme-linked immunosorbent assay , coaguAdditional file 1:Table S1. Multiplex DNA panel screening. Tested disorders within the multiplex DNA panel screening by MyDogDNA™, organised by type of disorder. Figure S1. Cross-section 2013–2015 Dutch breeding population of the long haired Dutch Shepherd Dog. Cross-section of the long haired Dutch Shepherd Dog breeding population for the years 2013–2015 in the Netherlands, combining the results of MyDogDNA™ multiplex DNA panel screening with Sanger sequencing for the causal variant for Von Willebrand’s Disease type I . Litters are shown by birth year, most were not related. Resulting allele frequency in the breeding population is 2%. (DOCX 186 kb)


Viola elatior in two contrasting early and late successional habitats characterized by strong differences in light-availability and declining population size. Using AFLP markers, we found significantly higher aboveground than seed bank genetic diversity in early successional meadow but not in late successional woodland habitats. Moreover, individually, three of eight woodland populations even showed higher seed bank than aboveground diversity. Genetic differentiation among populations was very strong (фST = 0.8), but overall no significant differentiation could be detected between above ground and seed bank cohorts. Small scale spatial genetic structure was generally pronounced but was much stronger in meadow  than in woodland habitats . Our findings indicate that relative seed bank diversity (i.e. compared to aboveground diversity) increases with ongoing succession and despite decreasing population size. As corroborated by markedly lower small-scale genetic structure in late successional habitats, we suggest that the observed changes in relative seed bank diversity are driven by an increase of outcrossing rates. Persistent seed banks in Viola elatior hence will counteract effects of drift and selection, and assure a higher chance for the species’ long term persistence, particularly maintaining genetic variation in declining populations of late successional habitats and thus enhancing success rates of population recovery after disturbance events.Persistent seed banks are predicted to have an important impact on population genetic processes by increasing effective population size and storing past genetic diversity. Accordingly, persistent seed banks may buffer genetic effects of disturbance, fragmentation and/or selection. However, empirical studies surveying the relationship between aboveground and seed bank genetics under changing environments are scarce. Here, we compared genetic variation of aboveground and seed bank cohorts in 15 populations of the partially cleistogamous  Instead of relying solely on the spatial dispersal of their seeds, many plant species have developed the ability to disperse their offspring in time by accumulating long-lived, dormant seeds of several years in the soil or in aerial reservoirs. Such persistent seed banks are a common feature of plants to counteract the consequences of environmental or demographic stochasticity that can be found across a wide range of life history types, habitats and climate zones ,2. PartiTheory predicts that, beyond affecting demography, seed banks could have an important impact on population genetic processes as they may consist of progeny produced by several and variable above-ground generations under varying selection regimes ,6. ConseA number of studies have been carried out to empirically test the ecological and evolutionary impact of long-lived seed reservoirs. Some of these indicated that persistent seed banks might indeed increase effective population size, both in annuals ,11 and pTo shed some more light on this topic, Honnay et al.  conducteOverall, the study of Honnay et al.  thus gavViola elatior in two habitats representing the endpoints of a management-driven successional gradient, open grassland and alluvial forests fringes. The study species is a weak competitor for light )PBr and Pu. Overall, these differences can mainly be attributed to changes in meadow habitats. This is substantiated by the significant interaction between habitat and cohort for Pu, suggesting that the relationship of the two cohorts changes with ongoing succession. Indeed, using the log-response ratio approach to highlight the relative seed bank genetic diversity (compared to the aboveground cohort) corroborated the results of the linear model for Pu. For all diversity measures but PLP, values of meadow populations were significantly higher in aboveground than seed bank cohorts, whereas in woodlands the two cohorts did not differ. Our data thus imply that relative seed bank genetic diversity increases towards the later successional stage.However, we did not find any clear difference of aboveground diversity  between Generally, higher aboveground than seed bank genetic diversity, as found in meadow populations, might be explained by selection against homozygotes or inbred individuals during germination and recruitment as suggested by earlier seed bank genetic studies ,16,19. HV. elatior, several linked processes may have fostered outcrossing in late successional habitats. First, a change in the balance between outcrossed and selfed flowers might have led to higher outcrossing rates in woodland sites. In partially cleistogamous species, the allocation to outcrossing and selfed flowers is controlled by environmental factors [Viola mirabilis increasing outcrossing rates were indeed shown to be correlated with shading [V. elatior capsules from outcrossed flowers mature only in the warmest period of the year, differences in water availability between meadow and woodland habitats are particularly distinct during the development of outcrossed seeds. This is corroborated by a survey in four populations from the Upper Rhine region  indicating for seeds from outcrossing flowers higher abortion rates (30% vs. 6%) as well as lower seed mass (10 mg vs. 18 mg) in meadow than in woodland sites. In contrast, in the same populations differences for seeds from selfed flowers were less pronounced . Additionally, seed longevity might be higher in woodland habitats, as soil parameters like high moisture content and constant temperatures are beneficial for seed survival. Thus, woodland seed banks potentially could be assembled from more seed generations, leading to higher relative genetic diversity. Finally, also anthropogenic effects may have an impact on the relative contribution of seeds from outcrossing flowers. As most of the floodplain meadows are regularly managed through mowing in early June, large amounts of ripening capsules from outcrossing flowers will be destroyed every year, whereas capsules from selfed flowers can freely develop from July to October, likely leading to a lower proportion of outcrossed seeds in meadow compared to woodland seed banks.In  factors  and outc factors , decreas factors  and incr factors , i.e. th shading . Second,In accordance with Eckstein et al. , we founViola elatior was very high, with 80.1% and 83.5% of genetic variation residing among populations for aboveground and seed bank cohorts, respectively. Similar differentiation (up to 82%) has been also reported in earlier studies on this species [V. elatior habitat related change in selection was not as high as expected and differentiation between cohorts is an exception that occurred only in few individual populations.Genetic differentiation in  species ,31,61, r species , which i species ,62, indi species . AccordiViola elatior the relative impact of outcrossing and thus pollen dispersal increases towards late successional stages. High selfing rates in meadow populations are furthermore corroborated by high Sp values that even exceeded mean values reported for other predominantly selfing species . In con = 0.04, ). Thus,  = 0.04, ) does im = 0.04, . Both, a cohorts ,17,64 su cohorts ).Viola elatior likely reflects the proposed differences in outcrossing rates between habitats. However, generally spatial genetic structure appears to break down relatively fast with ongoing succession and is not stored over longer periods of time in seed bank cohorts. Otherwise much stronger spatial autocorrelation would have been present in the seed bank of woodland populations. Instead, the high correlation of aboveground and seed bank cohorts in both habitats suggests that turnover of seeds in soil and of adult plants is similar in V. elatior and that seeds do not persist in the seed bank for more than few adult generations [Taken together, the observed small-scale spatial genetic structure in erations .Viola elatior in two different regions, we could show that the contribution of outcrossing to reproduction seems to increase from early to late successional stages, leading to higher relative seed bank diversity and lower within population small-scale spatial genetic structure. This suggests that under favorable early successional conditions with high plant densities, populations maintain their approved genotypes mainly by selfing. Under less favorable conditions an increase in outcrossing may keep genetic diversity in V. elatior at a constant level and hence seems to compensate the detrimental effects of small population size. Ultimately, in late successional habitats with a higher risk of extinction, the resulting increased relative seed bank genetic diversity also assures a higher chance for population recovery and thus the long-term persistence of the species.To our knowledge, the present study is the first one that has compared aboveground and seed bank genetic diversity between successional stages. Surveying a relative large number of populations of the partially cleistogamous We suggest that the relationship between seed bank and above ground plants potentially can be driven by both, post-germination selection as seen in meadow habitats and genetic buffering through stored seeds that seems to counteract the effects of drift and selection as seen in woodland populations. However, to substantiate these results and to test if this is not a specific situation in partially cleistogamous plants, further studies surveying seed bank genetics along environmental gradients in species with other mating systems are needed.S1 Text(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S1 FigComparison of correlogram homogeneity is shown for (A) Czech and (B) German aboveground populations grouped for habitats, respectively; ω-test indicates overall significance . *p<0.05 and **p<0.01 indicate significant differences for single distance classes. Cz—Czech Republic; Ger–Germany; AG—aboveground.(TIF)Click here for additional data file.


Hypophthalmichthys molitrix (which is indigenous to eastern Asia) escaped from southern U.S. aquaculture to spread throughout the Mississippi River basin, and since has steadily moved northward. This large, prolific filter-feeder reduces food availability for other fishes. It now has reached the threshold of the Laurentian Great Lakes, where it likely will significantly impact food chains and fisheries. Our study evaluates population genetic variability and differentiation of the silver carp using 10 nuclear DNA microsatellite loci, and sequences of two mitochondrial genes–cytochrome b and cytochrome c oxidase subunit 1, along with the nuclear ribosomal protein S7 gene intron 1. We analyze population samples from: two primary Great Lakes’ invasion fronts , the original establishment “core” in the Lower Mississippi River, and expansion areas in the Upper Mississippi and Missouri rivers. We analyze and compare our results with bighead and other invasive carps, and cyprinid relatives. Results reveal that the silver carp invasion possesses moderate levels of genetic diversity, with more mtDNA haplotypes and unique microsatellite alleles in the “core” Lower Mississippi River population, which also diverges the most. The two invasion fronts also significantly genetically differ. About 3% of individuals  contain a unique and very divergent mtDNA haplotype, which likely stems from historic introgression in Asia with female largescale silver carp H. harmandi. The nuclear microsatellites and S7 sequences of the introgressed individuals do not differ from silver carp and are very distant from bighead carp. These sequence variation data are employed to design and evaluate a targeted high-throughput metabarcoding sequence assay that identifies and distinguishes among species of invasive carps , as well as native cyprinids, using cytochrome b. Our assay further differentiates among selected silver carp haplotypes (including between H. molitrix and H. harmandi), for use in population genetics and future analyses of spread pathways. We test and evaluate this assay on environmental (e)DNA water samples from 48 bait shops in the Great Lakes’ region , using positive and negative controls and custom bioinformatic processing. Test results discern silver carp eDNA in four of the shops–three in Lake Erie and one in the Wabash River watershed–and bighead carp from one of the same Lake Erie venues, suggesting that retailers (who often source from established southerly populations) comprise another introduction vector. Our overall findings thus provide key population genetic and phylogenetic data for understanding and tracing introductions, vectors, and spread pathways for silver carp, their variants, and their relatives.In the 1970s, the introduced silver carp  Discerning the population genetic trajectories of nonindigenous species invasions can enhance our overall understanding of the evolutionary adaptations and changing ecological community dynamics governing today’s ecosystems –3. EstabDreissena polymorpha  ),Silver and bighead carps are prolific filter-feeders that significantly alter both the numbers of plankters and their community compositions, reducing food for sport and commercial fishes –65. SilvThe silver carp’s current North American geographic range is depicted in b (cytb) and 549 nts of the cytochrome oxidase subunit I (COI). We compare representative subsets encompassing all mt and μsat variants with nDNA sequence variation from the single copy ribosomal protein S7 gene intron 1. We relate our results to other genetic studies of silver carp, its relatives, and other exotic species.Little is known about the population genetic and genomic patterns of the silver carp in North America e.g., , 76). Th. Th76]).b metabarcode assay to discern and identify silver carp, bighead carp, and their cyprinid relatives, in order to facilitate early detection and tracking of species and possible hybrids at all life stages, using Illumina MiSeq high-throughput sequencing (HTS). The assay is designed to also simultaneously distinguish among silver carp haplotype variants, for use in population comparisons. We test our assay‘s application for discerning and identifying taxa and possible introduction vectors using eDNA-containing water sampled from 48 bait shops in the Lake Erie, Lake St. Clair, and Wabash River watersheds. Overall, our investigation aims to provide and apply population genetic, evolutionary phylogenetic analysis, and systematic biological knowledge of genetic variation in silver carp and its cyprinid relatives to interpret and understand invasion dynamics, pathways, and progression.Based on those baseline genetic variability data, we design a targeted cytTissue samples from silver carp individuals were collected by us, our laboratory members, federal or state agencies, and university collaborators (see Acknowledgments). Collections were made under their state or federal collection permits, using their protocols, and under the University of Toledo’s IACUC protocol #205400, “Genetic studies for fishery management” to CAS. Samples included 11 collection areas , represeHmo1 and Hmo11 from Mia et al. 2005 [Ar201 from Cheng et al. 2007 [HmoB4, B5, D8, D213, D240, D243, and D246 from King et al. 2011 [b genes, along with the S7 gene intron 1 (S7).Genomic DNA was extracted and purified from the EtOH fixed tissues using DNeasy Blood and Tissue Kits , quality checked on 1% agarose mini-gels stained with ethidium bromide, and assessed with a Nanodrop spectrophotometer . Genetic variation was analyzed at 10 μsat loci, including al. 2005 , Ar201 fal. 2007 , and Hmoal. 2011  for 309 2O. PCRs were conducted on C1000™ thermal cyclers  with 2 min initial denaturation at 94°C, followed by 39 cycles of 40 sec at 94°C, 40 sec annealing  [et al. (2007) [et al. (2011) [2O, with 2μL added to 13μL formamide and ABI GeneScan™–500 LIZ size standard solution, loaded into 96-well plates, denatured for 2 min at 95°C, and analyzed on our ABI 3130xl Genetic Analyzer with GeneMapper 4.0 software (ABI). Output profiles were checked manually to confirm allelic size variants.For the μsats, 10μL polymerase chain reactions (PCRs) contained 0.35 units AmpliTaq DNA polymerase , 1X GeneAmp PCR buffer I (ABI), 80μM total dNTPs, 0.4mM spermadine, 0.52μM of each primer, and 2μL of ≥30ng/μl DNA and ddH. (2005) , 58°C fo. (2007) , and 56°. (2011) ), and 1 b gene, using the primers Song-F (5'–GTGACTTGAAAAACCACCGTTG–3') [5'–GAATTYTRGCTTTGG-GAG–3') [5'–TTCTCCACCAACCACAARGA YATYGG–3') and COIFR1D (5'–CACCTCAGGGTGTC CGAARAAYCARAA–3') [b) or 1μM (COI) of each primer, and 2μL of ≥30ng/μL of DNA template, and ddH2O. Conditions were 3 min at 94°C, followed by 34 cycles of 95°C for 30 sec, 40 sec at 50°C, and 72°C for 45 sec, capped by 5 min at 72°C. We also sequenced the S7 intron using S7RPEX1F and S7RPEX2R following Chow and Hazama 1998 [N = 19), which included randomly selected individuals for all mtDNA haplotypes (We amplified and sequenced 992 nts of the mtDNA cytGTTG–3')  and H5 (-GAG–3')  and 549 ARAA–3') . PCRs coama 1998  for a replotypes , along wplotypes . All seqhttp://www.biotech.cornell.edu/brc/genomics-facility) and MCLAB (http://www.mclab.com/DNA-Sequencing-Services.html), which used ABI Automated 3730 DNA Analyzers. Sequences were quality scored, manually checked, and aligned by us with CODON CODE ALIGNER v7.01 . Additional DNA sequences were mined from N.I.H. GenBank  were visualized on 1% agarose mini-gels stained with ethidium bromide and successful reactions purified with QIAquick PCR Purification Kits (Qiagen) and quantified via Nanodrop. Sanger DNA sequencing was outsourced to the Cornell University Life Sciences Core Laboratories Center  expectations, using the Markov Chain Monte Carlo (MCMC) procedure with 10,000 dememorizations, 1,000 batches, and 10,000 iterations per batch in GENEPOP v4.0 . SignifiNA), observed heterozygosity (HO), and allelic richness  were calculated in FSTAT v2.9.3.2 [p<a) adjusted with standard Bonferroni correction. [HO and AR were evaluated using paired two-tailed t-tests in R v3.2.1 [NPA) per locus, i.e., those appearing unique in a population sample, were identified with CONVERT v1.31 [PPA) was the number of private alleles in a given sample divided by its total number of alleles, using rarefaction representation in ADZEv1.0 to adjust for sample size disparity [Genetic diversity measures, including the number of alleles per locus  in GENEPOP, using MCMC chains of 10,000, 1000 batches, and 10,000 iterations. Probabilities for both types of pairwise genetic divergences were assessed with sequential Bonferroni correction [Pairwise genetic divergences were calculated between all population samples, and separately between the two invasion fronts at the Illinois and Wabash Rivers with the alog θST  in FSTATulations –97, and ple size , we addirrection .Microsatellite DNA variation for all individuals that possessed a highly divergent mtDNA haplotype (“H”) was statistically compared against a group that included all of the other haplotypes see , to bettK = 1–6 genetic groups, with burn-ins of 50,000 and 100,000 iterations, whose relative support was evaluated with delta K [et al. 2004 [Population relationships from μsat variation were visualized using three-dimensional factorial correspondence analysis (3D-FCA)  in GENET delta K  in STRUC delta K . Assignm delta K  for all al. 2004 , and 100b and COI regions, both separately and together as concatenated sequences , in reference to four bighead carp haplotypes. ARLEQUIN calculated numbers of haplotypes (NH), haplotypic diversity (h), numbers and proportions of private haplotypes (NPH and PPH) per sample, and pairwise divergences using θST and exact tests [We evaluated mtDNA sequence variation in the cytequences , adding ct tests . All of http://tree.bio.ed.ac.uk/software/figtree/).Relative percentage of mtDNA concantanted mtDNA haplotypes per population was illustrated using a stacked bar graph, drawn with R. Evolutionary relationships among silver carp sequence variants were evaluated with Bayesian phylogenetic trees in MRBAYES v3.2.6 , in compb gene, we developed primers from conserved aligned sequence regions , bighead carp, and other invasive cyprinid species in retail bait shops, as a pilot study for a larger ongoing project. We evaluated water samples and live bait from 48 bait shops located in the Lake Erie, Lake St. Clair, and Wabash River watersheds in 2016 and 2017. Approximately two dozen bait fishes were purchased from each shop, which were immediately sacrificed in the parking lots using our IACUC protocol. The water containing the fishes was drained into a sterile container, placed on ice, and then frozen at -80°C in the laboratory.We briefly thawed the water samples on ice, and centrifuged 250 ml from each at 4500 rpm and 4°C, for 45 min. The supernatant was discarded and the pellet, containing extra and intracellular DNA and debris, was resuspended in 95% EtOH and stored at -20°C. DNA was extracted within 24 hr with Qiagen DNeasy kits following the manufacturer’s protocol, except that two AW 1 and 2 buffer washes were performed. The Zymo OneStep PCR Inhibitor Removal Kit  was used to alleviate PCR inhibition.http://mcic.osu.edu/).Primers contained spacer inserts to increase the diversity of the HTS libraries . 25μl PChttps://www.ncbi.nlm.nih.gov/) from the command line against a custom database containing cytb sequences of all fishes native to the Great Lakes basin [Custom bioinformatic scripts in PERL v5.26.1 trimmed primers and removed any sequences having a different spacer insert (which might result from index hopping if a few sequences with a different index became incorporated into an HTS library ), or weres basin  and non-es basin . All BLA10.5061/dryad.92h1f12). DNA sequences discerned in our study are in GenBank . All HTS data are in the NCBI Sequence Read Archive (BioProject: PRJNA502563. Accessions: SAMN10349832–925). All data generation methods are detailed in protocols.io (dx.doi.org/10.17504/protocols.io.u6zezf6).All μsat allele data, mtDNA haplotypic frequencies, and custom HTS analysis scripts are deposited in the DRYAD public data base (doi:Hmo-B4) that did not conform to Hardy-Weinberg equilibrium expectations was removed from further analyses. There were no differences in genetic diversity and θST values when population samples were pooled regionally  versus separately for individual sampling locations  co-occurred within the same population (19.8±4.85) versus in different populations (41.0±4.07), indicating high dispersal.Results indicated no linkage disequilibrium, null alleles, or selection. A single locus  did not significantly differ in μsat composition from other silver carp , for which distribution plots did not reveal appreciable structure . GENECLASS2 results for the entire data set also discerned overall mixed assignments. However, the GENECLASS2 assignment test between the two invasion front populations, the Illinois versus the Wabash rivers, indicated that 62% and 98% of their individuals respectively self-assigned. Individuals from the Wabash River population thus showed very high self-assignment.The 3-d FCA  explaineb sequences, along with 248 COI, and 226 concatenated (COI and cytb) sequences for silver carp  and another from the Black River in Russia , which were not available for our sequencing.In total, we analyzed 233 mtDNA cytp Tables  and S1. p Tables . We analGenetic relationships among the haplotypes are depicted in The invasion front populations of the Illinois and Wabash Rivers contained just three haplotypes each, with the Illinois River containing “G” (as well as a greater abundance of “B”) and the Wabash River with “H” Figs  and 4. THaplotypic diversity across all of our samples was 0.54 and did not significantly differ among populations , being hThe haplotype networks revealed a distinctly divergent haplotype “H”, which occurred in all populations except for the Illinois River, and was 47 nt substitutions from the closest silver carp haplotype and 76 from the bighead carp . The “H”Individuals with the “H” mtDNA haplotype did not vary from other silver carp in their nDNA S7 intron sequences, and lacked a common nDNA genotype or pattern, as shown on the Bayesian phylogenetic tree . There wThe Bayesian evolutionary trees using mtDNA  and nDNA5’–TGATGAAAYTTYGGMTCYCTHCTAGG–3’ and reverse primer 5’–AARAAGAATGATGC YCCRTTRGC–3’ to amplify a 135 nt region of the cytb gene that begins at nt114 , spottail shiner N. hudsonius , fathead minnow Pimephales promelas Rafinesque, 1820, and golden shiner Notemigonus crysoleucas Rafinesque, 1820. Among invasive cyprinids, goldfish eDNA was detected in seven samples, grass carp in four, and common carp in five. Silver carp eDNA occurred in four shops after re-sequencing the libraries that had positive detections. Bighead carp eDNA was found in a single shop , but whose ASV frequency (0.07% of reads) fell below the cutoff (0.19%). However, its haplotype matched our bighead carp haplotype “L”, which differed from the silver carp “A” and “B” haplotypes, by 14 and 15 nts respectively , of which 7,998,256  were verifiable; i.e., they contained both primers, the correct spacer (indicating it was not an index hop), and were the correct length  characterize silver carp populations tested here across much of their invasive North American range, based on both μsats and DNA sequences. Genetic diversity at the two invasion front populations did not significantly differ from longer-established core populations, refuting the leading edge hypothesis. Moreover, the two invasive front populations significantly genetically diverged, according to μsat results.AR = 6.1±0.07, HO = 0.60±0.14) that appear comparable to those of other North American invasive fish populations  in the Great Lakes had much lower allelic richness (AR = 3.09±0.91) and similar heterozygosity (HO = 0.59±0.03), based on comparable numbers of μsat loci; its lower allelic richness is attributable to a likely single source introduction and founder effect [AR = 9.01±0.92) was higher and its heterozygosity levels were similar (HO = 0.60±0.05) [Our findings indicate that silver carp populations possess genetic diversity levels  sequences) for 94 silver carp individuals from the Illinois and Mississippi rivers, which were undetected in their samples from the native range . Their haplotypic diversity was reported to be lower in the Mississippi River basin (0.74) than in the native range (0.95). Since their sequences are not in GenBank or other publicly accessible data bases, we cannot directly compare our data with theirs. Our haplotypic diversity was 0.61 in the Lower Mississippi River, ranging down to 0.48 in the Missouri River, and averaged 0.54 across all of our samples. Our results and those from other studies suggest little to no founder effect for the introduced silver carp in North America.Li al. 2011  reportedPterois volitans  and P. miles , which are widely invasive and prolific in the western Atlantic Ocean and the Caribbean Sea, respectively had nine mtDNA control region haplotypes and just a single haplotype in their introduced ranges, versus 36 and 38 in their native ranges [Ptychocheilus grandis  populations have been highly successful invaders of coastal Californian rivers despite 49.6% reduction in allelic richness due to founding by just four individuals [et al. 2012 [Some invasive fish populations have been successful in new areas despite reduced genetic diversity levels, in comparison to native ones. For example, the Indo-Pacific lionfishes e ranges . Sacrameividuals . Indepenal. 2012  discerneal. 2012 . Our resUndaria pinnatifida  contained high genetic diversity worldwide, likely stemming from admixture of multiple native strains [Roman and Darling 2007  describe strains . Likewis strains , 18–19.  strains , 123. ThPerca flavescens  populations [Myodes glareolus , which showed reduced single nucleotide polymorphisms (SNPs), no accumulation of deleterious alleles, and possible selection for traits involved in immunity and behavior [Desmodus rotundus  [The leading edge hypothesis predicts that species with rapidly expanding ranges would possess lower genetic diversity in peripheral populations , 124. Thulations . The leabehavior . Lower dy, 1810) .The leading edge hypothesis has not been supported for some invasions, such as the round goby, whose genetic diversity levels did not differ across the Great Lakes, yet whose populations have remained divergent and respectively stable over their 25 year history [Carcinus maenas  spread from the Atlantic to the Pacific coasts of North America [When invasive species spread via jump dispersal, new population areas frequently possess reduced genetic diversity , as was seen with transport of invasive dreissenid mussels from the Great Lakes to smaller lakes to the west (via overland trailered boats) , 16 and  America . This haThe considerable geographic distances separating silver carp full and half siblings in our study support high dispersal, including within a single generation. Tagging studies of silver carp established in the Wabash River showed that some individuals traveled widely (up to 409 km), while others remained close to the tagging location . This mien masse to analyzing eDNA from water or entire plankton samples from net tows  to detect new occurrences and dispersal patterns by managers. A targeted assay designed by our laboratory to be specific for the two species of invasive dreissenid mussels, distinguishing between them and many of their haplotypes, has been successfully deployed to simultaneously analyze tens of thousands of veliger larvae to species and population levels from net tows, as well as eDNA water samples [Our targeted metabarcoding HTS assay could be applied  samples .Oreothlypis virginiae  of the Black Hills in South Dakota showed no differentiation, implicating high gene flow and dispersal [Significant population genetic differentiation sometimes occurs across the range of invasive species, which often is attributed to high diversity and multiple founding sources, including the round goby , whose pispersal .In the present investigation, the silver carp displays modest levels of inter-population divergences across its invasive North American range. Population differences are most pronounced between the “core” area of original introduction versus expansion areas. Overall, the silver carp invasion appears to have progressed steadily, without bottlenecks or marked changes in genetic composition. Most alleles are distributed throughout the populations, with some significant differences between the invasion fronts of the Illinois and Wabash Rivers. The latter shows especially high self-assignment, which merits evaluation of genomic expression.et al. 2007 [et al. 2011 [Interpreting the genetic compositions, diversity levels, and phylogeographic patterns of introduced populations and their sources facilitates understanding how they colonize, expand their ranges  are closest to our rare “F” (Upper Mississippi River) and “G” (Lower Misssissippi River) haplotypes. The singleton haplotypes “C”, “D”, and “E” all occurred in our Lower Mississippi River “core” population. These results suggest that the original population escape of silver carp into the Lower Mississippi River region migrated to found the expansion areas, and that there likely have not been appreciable additional introductions from other overseas sources.Sequences of cytet al. 2017 [et al.’s 2017 [b and COI gene regions that we sequenced, or had incomplete sequences. With our greater sample size, we discerned that the “H” haplotype is found throughout most of the North American range.In comparison to Farrington al. 2017 , who seq.’s 2017  sequenceH. molitrix with the closely related largescale silver carp species, H. harmandi Sauvage, 1884. Our mtDNA sequence for “H” matches a GenBank haplotype (EU315941) from the Yangtze River. The largescale silver carp H. harmandi is morphologically distinguishable in possessing larger scales and a deeper body than does H. molitrix [H. harmandi haplotype “H” is widespread, occurring in the Lower Mississippi, Upper Mississippi, Missouri, and Wabash rivers, as well as in China.“H” occurred in ~3% of the individuals, which may represent a historic introgression of the silver carp molitrix . The larmolitrix . The twomolitrix . Our finH. harmandi interbreeding with male H. molitrix in Asia. Introgressed native silver carp likely were present as a small percentage of founders in the North American introduction.The S7 sequences and μsat allelic frequencies possessed by the “H” haplotype individuals did not show nDNA differentiation. The “H” haplotype thus appears to have resulted from mtDNA introgression, likely of female b sequence. In comparison, silver carp haplotype “Q”, which is closest to “H”, diverges by 37 nts. Moreover, bighead carp also is very divergent in its S7 sequence.There are 73 nt substitutions separating haplotype “H” from the most similar bighead carp cytet al. 2015 [Hypophthalmichthys spp. individuals in the Mississippi River Basin have interbred or backcrossed, suggestive of a hybrid swarm. The flow of maternal DNA was found to be biased from silver carp to bighead carp in both the F1’s and bighead carp backcrosses [et al. 2013 [Studies have reported that wild silver and bighead carp do not widely interbreed in their native range, having developed pre-zygotic reproductive barriers in sympatry , 133. Hoal. 2015  employedkcrosses . Greateral. 2013 . Across en masse, while genomic techniques can be used to evaluate the relative fitness of variants.Given our objective to analyze the population genetic relationships of the silver carp in its invasive range, it is relevant to consider whether and how genetic components from bighead and possibly largescale silver carp may influence them in the future. It is possible that hybridization has acted to enhance invasive success. Our targeted HTS assay can be applied to track these mtDNA genotypes Morone americana with metabarcoding in one bait shop in Michigan, in which only a single individual was observed in the tank. Previously published methods to detect invasive carps have relied on quantitative (q)PCR , cannotWe did not physically find silver carp in any of the bait stores surveyed, based on morphological examination of purchased samples. However, we discovered silver carp eDNA in the tanks of four shops, indicating likely presence at low densities. In addition, eDNA of bighead carp was identified from one of those shops . We also found eDNA of other invasive cyprinids. Our eDNA findings highlight the probability that silver and bighead carps are prevalent in the retail trade in the Great Lakes watershed, where they likely blend in with other “minnows” for sale. Releases of live bait by anglers may comprise an important vector for their introduction, meriting further investigation. Silver carp in the Mississippi River did not display patterns associated with jump dispersal , 16. It b mutations [The eDNA from the store near the Wabash River contained two silver carp haplotypes that were not recovered in our traditional Sanger sequencing and were not referenced in GenBank . Although those haplotypes were at low frequency, their possibility of being erroneous would stem from the highly unlikely situation of an undetected index hop co-occurring with two separate sequencing errors that were greater than the probabilities calculated from positive controls. This is unlikely due to use of our custom pipeline that removed index hops and a de-noising algorithm that corrected for sequencing error see . Both hautations . These hFurther refinement of bioinformatic pipelines and use of PCR replicates would enhance the veracity of rare haplotypes discerned with targeted eDNA HTS assays , 140. InOur assay has potential widespread use for screening bait fishes, as well as with water and plankton samples from the field. The latter will allow inexpensive and accurate identification of eggs and larvae to species and population , which oThe present investigation resolves phylogeographic and genetic diversity patterns across the invasive North American range of silver carp, significantly advancing from prior knowledge using larger sample sizes and a combined population genetic approach. We discern consistent genetic diversity levels across the invasion’s expansion, including at the fronts leading to the Great Lakes, which significantly differ in genetic composition. We discover and describe a widespread and highly differentiated ancient mtDNA haplotype, which likely originated from historic introgression with the largescale silver carp in Asia, predating the North American introduction. The introgressed individuals do not differ from silver carp in nDNA μsats or gene sequences, suggesting that female largescale silver carp reproduced with male silver carp.There is great interest in preventing entry of silver carp into the Great Lakes system using man-made barriers and the use of genetic tools to detect them at likely introduction points, expansions, or via other possible introduction vectors. Our finding of eDNA from silver carp in bait stores in the Lake Erie and Wabash River watersheds points to another likely introduction vector, as these retailers often source from southerly areas where silver carp are well-established.Our targeted HTS assay is designed to discern and detect multiple divergent haplotypes, including the introgressed haplotype “H”, as well as distinguish and identify related cyprinid species. It can be used on water samples or with plankton tows, which will yield abundant population genetic information, including at early life stages. At egg and larval dispersal stages, new invasions and expansions may be detected early, when it is more feasible to eradicate or control them. The ability to track changes in species composition and population genetic variation, rather than just single species presence or absence, should significantly enhance our understanding of the successes of invasive carps in colonizing new areas. If silver carp spread into the Great Lakes via natural dispersal, populations likely will possess similar genetic diversity, yet may subtly vary in composition, allowing tracking. The fact that the two invasive fronts analyzed here differ in genetic composition, as well as from the longer-established core area of the lower Mississippi River, shows the influence of genetic drift and possible adaptation. Elucidating these genetic patterns will significantly increase ecological understanding of the relative successes and adaptations of invasions, and aid the rapid identification of new populations and range areas.S1 Table(DOCX)Click here for additional data file.S2 TableNucleotide (nt) positions and substitutions, based on alignment to GenBank Accession AY325777 S7-“1” reference sequence, with dots indicating congruence with S7-“1”. Dashes denote sequence deletion (indels). Variants are GenBank Accessions MH938813–43.(DOCX)Click here for additional data file.S3 Tableb gene, with those differing from silver carp haplotype “A” shown and dots denoting homology.Alignment shows silver carp (SVC) haplotypes “A–H”, and two “novel” haplotypes “N1” and “N2” recovered with the targeted HTS assay (GenBank Accessions: MK205185–6), bighead carp (BHC), and other invasive cyprinid sequences. Nucleotide positions (above sequence) are based on the complete cytochrome (DOCX)Click here for additional data file.S4 TableRaw sequence reads, trimmed reads (had both primers and were the correct length), the number and percent that DADA2 successfully merged for all samples and those having sequences that matched silver carp . Samples are named with the year and sample number.(DOCX)Click here for additional data file.


Finding a “health risk” via direct-to-consumer (DTC) genetic testing often does not mean that a patient will go on to develop the health problem in questionDTC genetic tests might report false positives (artefacts)“Reassuring” results from DTC genetic tests might be false negativesMake sure you are confident in the provenance and interpretation of a genetic result before you base any clinical decisions on itIf your patient meets criteria for referral to clinical genetics, refer regardless of the results of their DTC genetic testDirect-to-consumer (DTC) genetic tests are sold online and in shops as a way to “find out what your DNA says.”Some DTC genetic tests promise insights into ancestry or disease risks; others claim to provide information on personality, athletic ability, and child talent. However, interpretation of genetic data is complex and context dependent, and DTC genetic tests may produce false positive and false negative results.Anyone concerned about a result from a DTC genetic test might turn to their general practitioner (GP) or other primary healthcare provider for advice. This practice pointer aims to help clinicians in this scenario and explains what sort of health information is provided by these tests, their limitations, and how clinicians can respond to common questions about them.Most DTC genetic tests don’t sequence the whole genome. They typically use a method called SNP-chip genotyping, which checks for the presence or absence of specific variants throughout the genetic code, such as particular single nucleotide polymorphisms (SNPs), or small insertions or deletions. SNP-chip genotyping detects common genetic variants well, but when SNP-chips detect very rare variants these are often false positives .Genome sequencing is another method becoming more widely used in DTC genetic tests. These tests sequence almost the entire genetic code and identify the variants present within it. However, detecting variants is not the same as knowing their clinical effects—clinical interpretation of genetic variants is challenging and depends on context.People might be drawn to DTC genetic testing in the hope that it will provide clear cut information about their future health. This idea may be reinforced by advertising. For example, a recent analysis of advertising of DTC genetic tests noted that some tests were presented as potentially empowering, with the decision to take them portrayed as responsible—a way that people can take an active role in managing their own health.Box 1If you have a specific clinical question  for which NHS genetic testing might be available, you would probably be better off accessing genetic testing via the NHS than via a DTC company. If you do not have a specific question, then discussing the pros and cons of particular tests is outside the scope of standard clinical practice.Does the DTC genetic testing company have real people you can talk to? Are they qualified  to advise in response to your clinical concerns?If you are worried by the results of your test or want further advice, it might be hard to access this via the NHS.What are the limitations of DTC genetic tests?)Sometimes tests have substantial limitations. If you are worried about a genetic condition in your family, is the DTC genetic test you are thinking about thorough enough to properly check this?  and the Association of Genetic Nurses and Counsellors website (https://www.agnc.org.uk/info-education/documents-websites/).More information for people considering buying DTC genetic tests can be found on the Genetic Alliance website .• Uninterpreted “raw” genetic data—some DTC genetic test companies provide access to uninterpreted genetic data. Customers can download their data and seek an interpretation using third party services.• Jake bought a DTC genetic test online while researching his family history. He enjoyed learning about his ancestry so decided to pay for an optional health report. He was very upset to find that: “you have one variant detected in the LRRK2 gene. People with this variant have an increased risk of developing Parkinson’s disease.” Jake had no family history of Parkinson’s disease.If a “disease-causing” or “disease-predisposing” genetic variant is found in a person with no medical or family history of the corresponding disease, it may be that there are currently unmeasurable protective genetic (or other) factors in that person’s family that mean that the variant is less likely to lead to disease in that person. Most people with apparent “positive” results will not go on to develop the related condition.HNF4A gene developed diabetes by age 40.The predictive meaning of a “disease-causing variant” is often much reduced when found outside the context of a family history of the relevant disease.Aoife was given a DTC ancestry test for Christmas. She sent her raw genetic data to an online interpretation service. This reported that she had a disease-causing BRCA1 variant (increasing her risk of breast and ovarian cancer). Aoife did not have a strong family history of breast or ovarian cancer. She asked her GP to refer her to a breast surgeon. She met the surgeon, who booked a date for her surgery. Her GP also referred her to a clinical genetics service, which arranged NHS testing to check that the BRCA1 variant was really present in Aoife’s DNA—it wasn’t. The online interpretation service had reported a false positive result. Aoife’s operation was cancelled but she still felt anxious about her cancer risk.False positive results can arise for a number of reasons. The quality control for DTC genetic tests is variable. Some tests may be more vulnerable than NHS testing to issues like sample “miscalls,” where initial analysis appears to detect a particular genetic variant but subsequent scrutiny shows that it is an artefact. Results found via third party interpretation services need particular care. This is because the “raw data” that such services interpret will contain artefacts,BRCA1 and BRCA2 genes in UK Biobank participants found that 96% of disease-causing very rare variants identified by SNP-chip genotyping were false positives.The SNP-chip genotyping method that most DTC genetic tests use is unreliable at testing for very rare disease-causing genetic variants. A recent study looking at Lily had treatment for breast cancer in her 40s, and her mother died of ovarian cancer in her 50s. Lily was concerned about an inherited cause, but also wanted to help conserve NHS resources, so she bought a DTC test that included a BRCA screen. She was delighted by the result: no variants were found in BRCA1 or BRCA2. Lily’s GP explained that many DTC BRCA screens only screen for a small proportion of the possible variants in these genes, and referred her to clinical genetics in view of her family history. NHS genetic testing found that Lily had a BRCA1 variant that conferred a high lifetime risk of cancer.BRCA1 and BRCA2 currently only checks for three disease-causing variants mainly relevant for people with Ashkenazi Jewish ancestry; this approach would miss in the region of 80% of people with disease-causing BRCA variants in the general population as there are thousands of different disease-causing BRCA variants that the test does not check for.DTC genetic tests tend to prioritise breadth over detail. For example, the 23andMe “genetic health risk” report for BRCA test that checks if you’ve “got the BRCA gene.” This is incorrect: a BRCA test can range from a spot-check for a handful of specified variants, to a thorough examination of the sequence of both BRCA genes looking for a whole range of possible variants. If your patient has a personal or family history such that you would usually refer to clinical genetics, do this even if they have a reassuring result from a DTC genetic test.Widespread use of phrases such as “having the gene for X” means that many people think that there is just one Genetic data are complicated, and can easily be misinterpreted. DTC genetic tests are sold as providing answers, and patients may understandably expect that their results will be clearly predictive of future health. These expectations, driven by marketing and media coverage, leave people at risk of over-interpreting results from DTC genetic testing.. For example, the Secretary of State for Health declared that having a genetic test “may have saved my life,” after his polygenic risk score identified a 15% risk of developing prostate cancer by age 75. Experts disputed the usefulness of this result—and his interpretation of it—given that the average lifetime risk of a man developing prostate cancer is 18%, and more men die with, than from, prostate cancer.One common pitfall is to compare the result to a “zero risk,” rather than population riskDTC genetic tests are often accessed without discussion with a health professional, so there is little opportunity to address potential mismatches between expectation and reality in advance of testing. Often, relevant and important information regarding the limitations of tests is available on DTC genetic testing websites, but it is easy to see how their disclaimers might be perceived as extensive and tedious lists of terms and conditions, which many people might not engage with in detail.Patients might ask you about a wide range of “positive” results—most will not need referral to clinical genetics. Your regional clinical genetics service may have a local policy regarding DTC genetic test results, and guidance from the Royal College of General Practitioners is expected to be published later this year.BRCA1, BRCA2, MLH1), inform the patient that further testing often shows that DTC genetic test results are inaccurate, so they might need a blood test to confirm or refute their result, and they might not be offered a genetics appointment.DTC genetic test results should not be used to inform health decisions without further scrutiny. For patients said to have “disease-causing” or “likely disease-causing” variants in genes associated with conditions for which early detection may be possible and/or treatment is available . If in doubt, contact your regional clinical genetics service to discuss whether referral is appropriate.If a patient who has taken a DTC genetic test presents with symptoms that they are concerned about (or that they think are explained by the DTC genetic result), assess and investigate the symptoms in the same way that you would for any other patient. If the DTC genetic result would change a patient’s clinical management if it were correct, it needs to be confirmed in an accredited laboratory.When a patient presents with a DTC genetic test result, they may find an explanation of some of the issues discussed in this article helpful. Patients might understandably take results at face value, so it may be useful to discuss possible sources of error in DTC genetic tests (fig 2). Shifting the conversation from discussing genetic risk to addressing modifiable lifestyle factors can be an important part of the consultation. We met the Patient and Public Involvement group at University Hospitals Southampton NHS Foundation Trust to discuss how patients might react to receiving concerning DTC test results, their expectations as to how the NHS should respond, and their views regarding what information might be helpful to discuss with patients. These discussions helped inform every section of the article but were especially key for shaping the section “What to say to patients.” We had 38 responses to a survey on social media about what people might expect from DTC genetic tests, and how they might respond to results. This helped inform the sections “What might people expect from DTC genetic tests?” and “Wider questions,” which reflect some of the issues raised by the survey respondents.What might you ask if a patient told you they were considering buying a DTC genetic test?What might you say to a patient who booked an appointment to discuss a DTC genetic test result indicating a high genetic risk of prostate cancer?What would you say to a patient who started smoking again after receiving a reassuring health report from a DTC genetic test?How can we raise public awareness that many genetic results are not clear cut, and may not substantially shift a person’s pre-existing risk of disease?How can we ensure that patients with personal or family histories suggesting a genetic condition are not falsely reassured by DTC genetic test results?How should additional healthcare costs arising from DTC genetic tests be funded? What regulation might be helpful?www.genethicsUK.org), and cases notified to the British Society of Genomic Medicine. Two of the vignettes discuss BRCA results as referrals to clinical genetics about DTC genetic test results currently most commonly relate to BRCA variants.We developed fictitious cases to illustrate some of the issues with DTC genetic tests, based on recent referrals to our regional genetics department, discussions at GenethicsUK (a forum to discuss ethical issues in genomic medicine – Information relating to the results that DTC genetic tests commonly provide, and to the technology commonly used, is based on accessing websites for various popular DTC genetic testing companies. DTC genetic testing is a rapidly expanding market and many different tests are available, which use various analyses and reporting practices, so inevitably the information in this article cannot be comprehensive.RH drafted the article; GC edited clinical cases, referral criteria, and facilitated PPI involvement; LF contributed to clinical cases and


Elymus tangutorum (Nevski) Hand.-Mazz, a cool-season hexaploid perennial, is an important pasture bunchgrass species used for forages and grassland restoration in Qinghai-Tibet Plateau and northwest China. In this study, 27 E. tangutorum accessions from diverse origins of western China were evaluated using AFLP markers in an effort to delve into the genetic relationships among them. The effects of eco-environmental factors and geographical isolation on the genetic diversity and population structure were also elucidated.Understanding genetic diversity of wild plant germplasm and the relationships between ecogeographic and genetic characteristics may provide insights for better utilizing and conserving genetic resources. FST = 0.162) between Qinghai-Tibet Plateau (QTP) and Xinjiang (XJC), and high differentiation (FST = 0.188) among three Bayesian subgroups. A significant correlation (r = 0.312) between genetic and geographical distance was observed by Mantel test in the species level, while the weak correlation was detected between genetic and environmental distance for all accessions and most of geographical groups. In addition, a significant ecological influence of average annual precipitation on genetic distance was revealed in XJC group and the Bayesian subgroup A.On account of 554 polymorphic fragments amplified with 14 primer combinations, the mean values of some marker parameters including polymorphic information content, resolving power and marker index were 0.2504, 14.10 and 23.07, respectively, validating the high efficiency and reliability of the markers selected. Genetic dissimilarity index values among accessions ranged from 0.1024 to 0.7137 with a mean of 0.2773. STRUCTURE, UPGMA clustering and PCoA analyses showed that all accessions could be divided into the three main clusters; however, this results do not exactly coincide with geographic groups. We found medium differentiation  together, play a crucial role in genetic differentiation patterns. These findings underline the importance of local adaptation in shaping patterns of genetic variability and population structure in E. tangutorum germplasm collected in Western China.This study indicates that AFLP technique are a useful tool to measure genetic diversity in The online version of this article (10.1186/s41065-019-0082-z) contains supplementary material, which is available to authorized users. Elymus Linn. is the largest and most widely distributed genus in the tribe Triticeae, with 150 species grown in temperate regions of the world [Elymus species are also used as fodder grasses and ecological protection [Elymus tangutorum (Nevski) Hand.-Mazz, a perennial hexaploid species with the StYH genome (2n = 6x = 42), along with E. duhuricus Turcz. ex Griseb., E. excelsus Turcz. ex Griseb. and E. ivoroschilowii Probat. constitute the E. dahuricus complex [E. tangutorum differs morphologically from E. dahuricus Turcz. in the light of the short upward awns and its distribution in the Qinghai-Tibet Plateau (QTP), Xinjiang province of China and the Alpine regions of Central Asia. In QTP, E. tangutorum is widely used for the degraded grassland restoration, due to high productivity, drought resistance, cold tolerance, and adaptability [E. tangutorum has been widely studied. Most of studies mainly focused on the domestication, cultivation, phylogenesis and genome constitution [he world , 3. Besiome 2n = x = 42, aome 2n = x = 42, aElymus accessions of ecotypes, and/or cultivars [Elymus species, diverse PCR-based markers, employed in diversity and phylogeny studies, such as RAPD [E. tangutorum populations from Tibet province of China by AFLP analyses [Understanding genetic diversity of wild plant germplasm and the relationships between ecogeographic and genetic characteristics may provide insights for better utilizing and conserving genetic resources . Investiultivars , 9. DNA- as RAPD , ISSR [1 as RAPD , SRAP [1 as RAPD , ScoT [9 as RAPD , and AFL as RAPD –16 have analyses , 5, untiGenetic diversity in natural plant populations is held especially by the spatio-temporal environmental heterogeneity, i.e., genetic differentiation is strongly influenced through isolation by distance or local adaptation –19. To eE. tangutorum germplasm accessions indigenous from two contrasting climatic zones of Western China, namely Qinghai-Tibet plateau and Xinjiang province  to verify the potential influence of spatial and environmental factors on the patterns of detected population structure.Here, AFLP markers were used to analyze, on a regional scale, genetic diversity and structure of 27 wild nce Fig. . The goaE. tangutorum were germinated in vermiculite under identical conditions  in a plant growth chamber. Genomic DNA was extracted from bulked young leaves from five plants per accession employing a CTAB procedure [Twenty seeds of each accession of AFLP fingerprinting was carried out following Vos et al. 1995) with minor modifications , 27, but995 with i = 2 fi (1 − fi), where PICi is the PIC of ith marker, fi stand for the frequency of the present fragments and 1 − fi represent the frequency of absent fragments [Rp = ∑Ib, where Ib (fragment informativeness) defined as Ib = 1–2 × |0.5 − p|, where, p is the proportion of accessions in which the fragment is present [The discriminatory power of each AFLP primer combination was evaluated by calculating polymorphic information content (PIC), marker index (MI), and resolving power (RP) with polymorphic bands only. The formula to calculate PIC value of each primer combination is: PICragments . Marker ragments . The res present .http://web.stanford.edu/group/pritchardlab/structure.html). Following the suggestion by Forsberg et al. [http://taylor0.biology.ucla.edu/struct_harvest/) to detect optimum value of K based on ΔK method [To understand the genetic relationship among all 27 accessions, pair-wise genetic distance (GD) were calculated on the basis of the Dice’s coefficient by NTSYS-pc v2.10 software. To obtain a more detailed view of the distribution of genetic variation within and between different geographical groups (XJ vs QTP), mean GD among accessions belonging to the same and/or different groups was also calculated. Based on GD matrix, the principal coordinate analysis (PCoA) and Unweighted Pair Group Method with Arithmetic (UPGMA) clustering analysis were performed. The robustness of the dendrograms was assessed with 1000 bootstrap iterations by Freetree software . The Bayg et al.  for outcg et al. . We set g et al. , we usedK method . The outK method  using thK method  for bettK method , which hK method . GeograpK method .FST) value was using GenAlEx 6.5 was performed. The observed (Na) and effective number (Ne) of alleles, expected heterozygosity (HE), Shannon’s information index (I) [To validate the genetic variation among and within inferred subgroups according to geographic origins or STRUCTURE results, analysis of molecular variance (AMOVA) based on PhiPT  , and Neihttp://swww.diva-gis.org/). The geographic and environmental distance matrix was calculated based on the Euclidean distance between pairs of collection sites using NTSYS-pc v2.10. Correlation between geographical and genetic distances (Nei-Li coefficients) between accessions was measured by Mantel test with 9999 permutations using IBD (Isolation by Distance) software v1.53 [Based on geographical location of each accession, the corresponding environmental data (precipitation and temperature parameters) was obtained by DIVA-GIS  were polymorphic and 70 (12.6%) were unique (Tables E. tangutorum germplasm from western China could be characterized well by above AFLP dataset retaining abundant variation. Polymorphism information content (PIC) of each primer pair being 0.5 for AFLP as the dominant marker, 38% of polymorphic loci (195) possessed PIC values above 0.25, implying high discriminatory power of AFLP markers for E. tangutorum germplasm. In addition, the marker index (MI) and resolving power (RP) values for individual primer pair were recorded. There were positive correlations between PIC, RP and MI . The most discriminatory primer combinations among 14 primers were E-ATG/M-CTC  followed by E-AAC/M-GAC .The AFLP fingerprinting was performed on 27 wild i), all 27 accessions were assembled into three Bayesian subgroups designated as subgroup A , subgroup B  and subgroup C (red fraction ≥0.2). The three subgroups included 10, 8 and 9 accessions, respectively. Geographically, most of accessions from Xingjiang (XJC)  belonged to subgroup A and the rest resided in subgroup B (Et20) and C (Et04 and Et13). Six accessions from Sichuan (SCC) were part of subgroup B and the five remaining accessions were part of subgroup C. For the three accessions from Gansu (GSC), Et18 consisted in subgroups B and the remaining two belonged to subgroup C.The results of population using the STRUCTURE software showed a clear peak of the ΔK values when K was set at 2 Fig. . Samplesmax = 4, indicating that the sampled accessions belonged to four inferred genome fraction  at KBased on the 509 polymorphic fragments, estimates of the genetic distances (Dice’s coefficient) ranged from 0.1024 to 0.7137 with an average of 0.2773, implying a largely genetic divergence in the germplasm collections studied. Accessions Et08 and Et11 were most related due to a minimum genetic distance of 0.1024, while Et01 and Et23 were most divergent with the maximum genetic distance of 0.7137. The rest of accessions have exhibited different middle levels of genetic distances. Compared with 0.2611 of inter-group dissimilarity, the accessions from Xinjiang were more homogenous with lower dissimilarity values (0.2214), whereas the QTP accessions were more variable genetically with higher dissimilarity values (0.2785). These results were also confirmed by STRUCTURE analysis that most of Xinjiang accessions had pure type of genome fraction. The genetic distance matrix was used to build a hierarchical dendogram of genetic relationships based on the UPGMA clustering method  Fig.  illustraP value was found to be highest among accessions from subgroup A (67.69%) followed by subgroup C (65.16%). The markers were least informative for assessment of genetic variability of accessions from subgroup B with PP restricted to 53.25%. Similarly, subgroup A showed the highest intra-group diversity (I = 0.36 and He = 0.24), whereas subgroup B had the lowest intra-group diversity (I = 0.01 and He = 0.0.01).Geographically, the region of Gansu and Sichuan Province are both part of the QTP region. Hence, we merged the GSC and the SCC group into a new group named QTP group. The total gene diversity across different ecogeographical regions was estimated based on 509 polymorphic fragments  was detected  which were tested by GenAlex 6.5. The total FST = 0.162 indicated that the genetic variability is moderate between QTP and XJC groups. The three subgroups inferred from STRUCTURE showed 81 and 19% of total variance within and among the groups. This means that the total FST was 0.188 (P ≤ 0.01) and the derived three subgroups are highly structured by Bayesian inference panel. Significant differences in the FST were observed for all the pairwise comparisons of three subgroups inferred from STRUCTURE analysis (Table FST (0.274) found between subgroup A and subgroup C was confirmed by their great difference of inferred genome fraction . A similar result was found in each group except GSC  and Subgroup A   [E. nutans by ISSR (91.4%) [The practical availability of molecular markers in plant germplasm characterization depends on their power to discriminate the genotypically different accessions analyzed. In the present paper, the efficiency of AFLPs were assessed by recording different marker parameters concerning polymorphism, PIC (Polymorphic Information Content), MI (marker index) and RP (resolving power). In total, 509 AFLP polymorphic fragments with 91.77% of polymorphism were observed in the current work, which was obviously higher than previous works by AFLP in oT (89%)  and E. n (91.4%) . In all, (91.4%) , 43. Mor (91.4%) .Dactylis glomerata [Phalaris aquatica [E. tangutorum germplasm. A very strong and positive correlation observed among PIC, RP and MI value in present work indicates the use of any of three parameters to screen the informative primer combinations [E. tangutorum collections. The Shannon index is an accurate alternative measure of diversity due to no need for estimate of allele frequencies under Hardy-Weinberg equilibrium. The Shannon diversity detected in this study (0.34) was higher than those of E. sibiricus germplasm from western China by SCoT (I = 0.285) and EST-SSR (I = 0.237) markers [E. tangutorum (Table The polymorphic information content (PIC) values of 0.25 in current study demonstrated good marker discriminatory power in view of PIC value starting from 0 to 0.5 for dominant marker like AFLPs , 46. Thilomerata  and Phalaquatica .The Markaquatica , 50, hadinations ; althoug markers , 51, alsElymus tangutorum accessions and biogeographical patterns by different clustering approaches. The UPGMA tree, the PCoA scatter plot, and the STRUCTURE analyses revealed a similar or identical membership among 27 wild E. tangutorum accessions, with a general grouping pattern including three genetically distinct and consistent groups. When these accessions are grouped according to clusters distinguished from Xinjiang,which were grouped with QTP accessions in Clade II and Clade III respectively. Since projects , it is pprojects . Nonetheprojects . These rntiation , 57.E. tangutorum was frequently used to grassland restoration in Qinghai-Tibetan Plateau as mentioned above [Indeed, the genetic diversity and population structure are determined by joint effects of many factors including geographic distribution, life cycle, mating system, selection and adaptation . Consideed above , 60. TheE. nutans and E. sibiricus collections with similar origins [E. tangutorum, supported by clustering and AMOVA, was also probably driven by its mating system, which is one of the important life-history feature that strongly influence genetic diversity and population structure [Elymus dahuricus complex [E. tangutorum is probably a predominantly self-pollinated species with 0.9 of FST value. In their review, Hamrick and Godt [E. tangutorum accession in present investigation could be treated as a population consisting of seeds of neighboring individual plants collected from differently distant locations [E. tangutorum was present rather within than among groups, since the large-scale geographical group contained numerous accessions with distinctly genetic architecture. These results could be confirmed by that the totally average genetic distance (0.277) between all of accessions was higher than that (0.261) between accessions from the two main geographical groups (QTP and Xinjiang).Results of AMOVA analysis showed low genetic variation among regions accounted for only 16.2% of the germplasm collection, whereas within-region variation accounts for 83.8% of the total variability. Similarly, only 19% of variation was detected for Bayesian groups,. These results on variation among accessions within geographical groups were confirmed with previous studies for  origins , 57. Howtructure . As repoand Godt  claimed and Godt  assumed ocations . This siE. tangutorum accessions and most groups was weakly correlated  compared with the XJC group (r = 0.313), which was not significantly different from zero and might be related to the highly heterogeneous topography nature of the QTP collection. The complex topographic features and climate will work together to form varieties niches to influence the genetic variability [r = 0.685; P = 0.01 and r = 0.594; P = 0.05) in the XJC group and Bayesian subgroup A. A possible explanation for this results is that in Xinjiang with arid and/or semi-arid temperate climate, the lower precipitation hinders seed germination and lead to decrease plants’ genetic diversity [E. nutans germplasm from western China, the environmental divergence like elevation is also related to genetic distance  [r = 0.309), the correlation between the genetic diversity and environmental factor was still unraveled due to the small population size.In virtue of the evolutionary forces, the decisive factor to influence the maintenance of genetic variability is the spatial variation of environment and the ecological difference between habitats . Remarkaed Table  and simi species , 57. Witiability . Thus, siability . In the iversity . In the  = 0.01) . On the  = 0.01) . This coE. tangutorum and geographical and environmental factors  together plays a crucial role in genetic differentiation patterns. These findings highlight the importance of local adaptation in shaping patterns of genetic structure inferred in E. tangutorum accessions fromWestern China. Therefore, collecting and assessing E. tangutorum germplasm from major geographic regions and special ecogeographic environment such as Qinghai-Tibet Plateau, will help to expand the genetic base and sample the full extent of available variation.This study indicates that AFLP markers are a powerful tool to measure genetic diversity in Additional file 1:Table S1. Adaptor and primer sequences used for AFLP analysis. (DOCX 17 kb)Additional file 2:Figure S1. Bayesian clustering results for 27 accessions of Elymus tangutorum using the program TESS from K = 2 to K = 5. (TIF 686 kb)Additional file 3:Figure S2. Maps representing the mean membership proportions for K clusters of Elymus tangutorum. (TIF 80 kb)Additional file 4:Table S2. Different genetic diversity estimates for geographical groups and Bayesian subgroups of E. tangutorum based on AFLP results. (DOCX 18 kb)


Ne) jointly determine intraspecific genetic diversity, but the role of mutation rate is often ignored. Here we investigate genetic diversity, spontaneous mutation rate and Ne in the giant duckweed (Spirodela polyrhiza). Despite its large census population size, whole-genome sequencing of 68 globally sampled individuals reveals extremely low intraspecific genetic diversity. Assessed under natural conditions, the genome-wide spontaneous mutation rate is at least seven times lower than estimates made for other multicellular eukaryotes, whereas Ne is large. These results demonstrate that low genetic diversity can be associated with large-Ne species, where selection can reduce mutation rates to very low levels. This study also highlights that accurate estimates of mutation rate can help to explain seemingly unexpected patterns of genome-wide variation.Mutation rate and effective population size ( Ne) in explaining variation in genetic diversity has received much attention, the role of spontaneous mutation rate is largely ignored. Here, Xu et al. show that giant duckweed has a high Ne yet low genetic diversity, likely due to its low mutation rate.While the role of effective population size ( While intraspecific genetic diversity is known to vary widely among species, the underlying causes remain controversial4. According to population genetic theory, the population mutation parameter (θ) is determined by the product of the spontaneous neutral mutation rate (μ) and effective population size (Ne), and in diploid species θ = 4 × Ne × μ5. In practice, the parameter θ is often estimated by the average pairwise nucleotide diversity (π) at putatively neutral sites6. While the role of Ne in explaining variation in genetic diversity among taxa has received much theoretical and empirical attention, the influence of variation in mutation rate remains largely ignored7.Explaining within-species genetic diversity—measured as the level of intraspecific DNA sequence variation—is one of the major goals in evolutionary and conservation biologys ≪ 1/Ne, where s is the selection coefficient against the increase of mutation rate) as genetic drift overrides the effect of natural selection. This ‘drift-barrier’ hypothesis can explain variation in mutation rates and the observed logarithmic-scaled negative relationship between Ne and μ among species8. An important prediction of this model is that a large effective population size could result in the evolution of a low mutation rate. One consequence of this is that populations with very large effective population sizes may have very low genetic diversity, when selection has driven mutation rate to an extremely low level. However, to our knowledge, whether this pattern is present in eukaryotes is unknown, largely due to the paucity of studies quantifying both genome-wide diversity and spontaneous mutation rates.As most spontaneous mutations are deleterious, selection should favor lower mutation rates, but in small populations the efficacy of selection to lower the mutation rate is limited  (“giant duckweed”). This species is one of the fastest growing angiosperms; under suitable growth conditions, it reproduces predominantly by asexual budding with a duplication rate of 2–3 days10. Consequently, S. polyrhiza often achieves extremely high census population sizes in nature as millions of individuals can be found in a single pond. However, previous studies using a limited number of genetic markers found low genetic diversity12, and whole genome resequencing of two genotypes revealed overall low heterozygosity13. Here, by sequencing 68 world-wide distributed genotypes and measuring spontaneous mutation rate under natural conditions, we show that low genetic variation in S. polyrhiza is associated with low mutation rate in the giant duckweed.To better understand the relationship between genetic diversity, mutation rate, and S. polyrhiza, we sequenced the genomes of 68 genotypes representing the global distribution of the species, using Illumina short-read sequencing with 29× average coverage  as well as 214,262 small indels. This represents on average one SNP per 145 bp in the S. polyrhiza genome, which is low compared to an average of one SNP per 23 bp in Arabidopsis thaliana when a comparable number of genotypes are sequenced16. Among all biallelic SNPs, 14,191 nonsynonymous and 8865 synonymous SNPs were found (Supplementary Table S. polyrhiza range-wide pairwise nucleotide diversity at synonymous sites (πS) was 0.00093, which is among the lowest values reported for any multicellular eukaryote for which genome-wide genetic diversity has been estimated  Asia  and 0.00013 (European versus American population). Within populations, π calculated from all sites ranged from 0.00018 (American population) to 0.00056 (SE Asian population)  of 0.33 varied from 8.6 kb in the SE Asian population to 86.8 kb in the European population. The relatively slow decay of LD in S. polyrhiza may be attributed to its predominantly clonal reproduction. Comparing across populations, we observed much faster LD decay in the SE Asian population, suggesting more frequent  sexual reproduction in this region and/or higher Ne. Together, these results establish that genome-wide nucleotide diversity in S. polyrhiza is extremely low and sexual reproduction might be frequent in the SE Asian population.Population structure analysis based on genome-wide polymorphisms revealed four population clusters in sia Fig. . A few son) Fig. . The aveS. polyrhiza can be explained by universally low mutation rate or, alternatively, low effective population size, we estimated the spontaneous mutation rate and used our estimates of mutation rate and genomic diversity to estimate effective population size. Because environmental factors, such as ultraviolet (UV) light, which prevails in the native habitats of S. polyrhiza, can affect mutation rates21, mutation rates measured in the lab may not necessarily reflect mutation rates in nature. In an attempt to get an estimate of mutation rate more similar to what would be observed in nature we estimated the genomic mutation rate in indoor and outdoor mutation accumulation (MA) experiments, and manipulated UV light in the outdoor experiments to further assess the effect of environmental factors . Among the 15 offspring, four de novo mutations were identified and confirmed by Sanger sequencing. These mutations all originated from the outdoor MA experiments, and located in non-coding regions. One mutation . As so few mutations were observed, we were unable to perform robust statistical analysis to test for treatment effects. However, the higher number of mutations found in outdoor samples and in the presence of UV light is consistent with the hypothesis that outdoor environmental factors increase the spontaneous mutation rate.To investigate if the observed low genomic diversity in S. polyrhiza is within the range of mutation rates reported for unicellular eukaryotes and Eubacteria, but is more than seven times lower than the reported rates for multicellular eukaryotes  were close to 0  or by substitutions of beneficial alleles at linked loci (genetic hitchhiking)Ne can be explained by extremely low mutation rate in S. polyrhiza. Linked selection may have further reduced the genome-wide genetic diversity. The role of mutation rate in driving variation in genetic diversity has been largely ignored, because obtaining accurate estimates of genome-wide genetic diversity and spontaneous mutation rate in a range of organisms has been difficult in the past. Our study emphasizes that accurate estimates of mutation rates are important for explaining patterns of genetic diversity within species.In this study, we show that the unexpected pattern of low genetic diversity in a species with large S. polyrhiza for 20 generations. Spirodela polyrhiza plants were propagated under three conditions: (i) indoors in the absence of UV light, (ii) outdoors in the absence of natural UV light, and (iii) outdoors in the presence of natural UV light. Spirodela polyrhiza genotype 7498 was pre-cultivated for three weeks in N-medium—which supports optimal growth 2 × 4 H2O, 8 mM KNO3, 5 µM H3BO3, 13 µM MnCl2 × 4 H2O, 0.4 µM Na2MoO4 × 2 H2O, 1 mM MgSO4 × 7 H2O, 25 µM FeNaEDTA)—in a climate chamber operating under the following conditions: 16 h light, 8 h dark; light supplied by vertically arranged neon tubes  on each side; light intensity at plant height: 186 ± 3 µmol s−1 m−2 outside polystyrene tubes and 142 ± 3 µmol s−1 m−2 inside polystyrene tube; temperature: 28 °C constant; humidity: 41%. The genotype 7498 originating from North Carolina (USA) was selected based on the existence of a clone-specific reference genome14. A single frond (S1) was transferred to a transparent 50 ml polystyrene tube  containing 30 ml N-medium, covered with foam cap and incubated in a climate chamber under the above specified conditions. To obtain 6 MA lineages per treatment, the S1 ancestor was propagated according to the propagation scheme  with 150 bp paired-end reads. For the 68 S. polyrhiza genotypes, all genotypes of S. polyrhiza  with 150 bp paired-end reads. On average, 48.2 million reads per genotype were generated.The plant tissue was ground by vigorously shaking the Eppendorf tubes with three metal beads for 1 min in a paint shaker  at 50 Hz. All DNA samples were isolated using the CTAB method33 with the parameters: –collapse –trimns –trimqualities –minlength 36. All of the trimmed reads were then mapped to the S. polyrhiza reference genome14 using BWA-MEM34 with default parameters. All reads with multiple mapping positions in the genome were removed and only the mapped reads were kept. PCR duplicates were removed using the “rmdup” function from SAMtools35. The aligned reads were then used for variant  calling using GATK v3.515 following the suggestions on best practices37. In brief, the aligned reads around indels were re-aligned using “IndelRealigner”, and variants were called using the UnifiedGenotyper function with the option -stand_call_conf 30 -stand_emit_conf 10. The variants were then filtered with the option MQ0 ≥ 4 && ((MQ0/(1.0 × DP)) > 0.1) & QUAL < 30.0 & QD < 5.0, which removes all variants that either have more than four samples with MappingQualityZero  and 10% of the mapped reads (DP) with low mapping quality, or have low Phred-scaled probability that a polymorphism exists at the site (QUAL), or low qual score normalized by allele depth (QD). The variant clusters were further annotated as more than three variants within 50 bp using the GATK VariantFiltration function. Only biallelic loci were kept for downstream analysis. The synonymous and non-synonymous variants were annotated using snpEFF (version 4.3 m)38. Due to low sequencing coverage, three individuals from the MA experiments were removed from downstream analysis . Variants from mitochondrial and chloroplast regions and clustered variants were removed using vcftools39. The population structure among the sequenced 68 genotypes was analyzed using fastSTRUCTURE v1.040. To this end, the loci that were not in Hardy-Weinberg equilibrium (P < 0.01) and tightly linked loci (r2 > 0.33) were removed using vcftools and bcftools41, respectively. Multiple K values (refers to number of populations) ranging from 1 to 10 were analyzed and the value K = 4 was selected using the chooseK.py function from the fastSTRUCTURE package. The genome-wide intraspecific diversity was analyzed using Popgenome v2.2.042 using a data set with no missing genotypes , and diversity at synonymous and non-synonymous sites was analyzed using SNPGenie43 using all variants. Overall, more than 88.0% of the genome and ~92.8% of the coding region had sufficient coverage for variant calling. The estimated population genomic summary statistics were then corrected based on the callable sites. Plink44 was used to calculate pairwise linkage disequilibrium (LD) from the dataset, for which related individuals were removed and only SNPs with MAF greater than 0.05 were kept. To model the decline of LD with physical distance, pairwise r2 between sites was used as the use of D′ is sensitive to small sample sizes46, and the decline of LD was modeled using Sved’s equation: E(r2) = (1−/(1 + 4 βd)) + 1/n, where β is the decline in LD with distance d47 and 1/n accounts for small sample size48. The extent of useful LD for mapping can be defined as r2 = 0.3349. In this study we use mean r2 for non-overlapping 100-bp bins to fit Sved’s equation.To analyze genetic diversity and population genomics of the 68 genotypes, additional filtering steps were performed using vcffilter 53. (1) To reduce false positives, we only considered the mapped and properly paired reads with insertion size greater than 100 bp and less than 600 bp using bamtools54. (2) We also excluded all genomic regions that were supported by fewer than nine or greater than 75 reads per sample from both variant counting and genome size calculation, as the variants from the regions that have low or high coverage are likely due to mapping errors (such as repetitive or duplicated regions). On average, 79.7% of the genomic region was kept. (3) Because spontaneous mutations should be only found in the offspring samples but not the ancestor, and the likelihood of a mutation occurring at the exact same position in multiple samples is extremely low , any variants that appeared in more than two samples were removed. (4) Only the heterozygous variants that were supported by at least three reads for both alleles were kept. After these filtering steps, 86 variants were found  and three were loss-of-heterozygosity (LOH) mutations . We further validated these SNPs using a Sanger-sequencing approach. Two LOH loci were very close to the gap of the genome assembly and the PCR primers could thus not be designed. We validated the remaining seven loci (six point-mutations and one LOH). In total, four out of the six point-mutations were confirmed, and the loss of heterozygosity mutation turned out to be a false positive. The confirmed point-mutations are listed in Table The relatively stringent parameters in the variant filtering process theoretically could result in a high rate of false negatives. To control this, we further estimated the false negative rate using the sequence data. We first identified all high-quality heterozygous SNP loci  from the ancestor using the same filtering parameters  and compared them with the heterozygous SNPs in the offspring using a custom script. In theory, all these variants should be found in the clonally produced offspring. Thus, the number of SNPs that could not be identified from the offspring was used to estimate the highest boundary of the false negative rate from our sequencing and variant calling/filtering pipeline, as some of these cases could be a true loss of heterozygosity.56. We introduced 1000 non-reference mutations to the callable regions using BAMsurgeon57 , with a frequency of 0.5 (standard deviation = 0.1). Using the same variant calling and filtering pipeline, we identified 94.5% (945 out of 1000) of the synthetic mutations that were successfully introduced to the BAM files, yielding an average false negative rate of 5.5% (95% CI 4.1–7.2%).In addition, we also estimated the false negative rate by simulating synthetic mutations to the sequence alignments, an approach that has been used previouslyBecause the total amount of DNA from a single individual was limited, the variant validation was performed using the descendants of the ancestor and offspring individuals. Specifically, at the end of the MA experiments, one individual of each line was propagated for four more generations under indoor conditions, after which the plants were frozen in liquid nitrogen for subsequent variant validation.To validate the candidate variants, DNA was isolated as described above. PCR primers were designed based on the 500 bp flanking sequences. The PCR reactions were performed with goTaq DNA polymerase (Promega) using 30 PCR cycles with an annealing temperature of 58 °C. The primer information is listed in Supplemental Data Further information on experimental design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Reporting Summary