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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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Genetic characterization of cucumber genetic resources in the NARO Genebank indicates their multiple dispersal trajectories to the East

The cucumber (Cucumis sativus) is an economically important vegetable crop cultivated and consumed worldwide. Despite its popularity, the manner in which cucumbers were dispersed from their origin in South Asia to the rest of the world, particularly to the east, remains a mystery due to the lack of written records. In this study, we performed genotyping-by-sequencing (GBS) on 723 worldwide cucumber accessions, mainly deposited in the Japanese National Agriculture and Food Research Organization (NARO) Genebank, to characterize their genetic diversity, relationships, and population structure. Analyses based on over 60,000 genome-wide single-nucleotide polymorphisms identified by GBS revealed clear genetic differentiation between Southeast and East Asian populations, suggesting that they reached their respective region independently, not progressively. A deeper investigation of the East Asian population identified two subpopulations with different fruit characteristics, supporting the traditional classification of East Asian cucumbers into two types thought to have been introduced by independent routes. Finally, we developed a core collection of 100 accessions representing at least 93.2% of the genetic diversity present in the entire collection. The genetic relationships and population structure, their associations with geographic distribution and phenotypic traits, and the core collection presented in this study are valuable resources for elucidating the dispersal history and promoting the efficient use and management of genetic resources for research and breeding in cucumber. Key messageGenotyping-by-sequencing of 723 worldwide cucumber genetic resources revealed that cucumbers were dispersed eastward via at least three distinct routes, one to Southeast Asia and two from different directions to East Asia.

plant biology↗

A mix-and-match reverse genetics system for evaluating genetic determinants of orthobunyavirus neurological disease

The encephalitic orthobunyaviruses have tri-segmented, negative sense RNA genomes and can cause severe neurological disease in humans, including La Crosse virus (LACV), which is the leading cause of pediatric arboviral encephalitis in the United States. However, little is known about the genetic factors that drive neuropathogenesis. Reverse genetics (RG) systems are valuable tools for studying viral genetics and pathogenesis. Plasmid-based cDNA RG systems are available for LACV, however the plasmid backbones are medium-copy number and have a propensity for recombination. We therefore generated a plasmid-based cDNA RG system for LACV utilizing a more stable and high-copy number plasmid backbone. Additionally, we created the first full RG systems for two closely related orthobunyaviruses, Jamestown Canyon virus (JCV), and Inkoo virus (INKV), which have differing reported disease incidences in humans and differing neuropathogenic phenotypes in mice compared to LACV. We compared wild type (wt) viruses with RG-derived viruses in human neuronal cells and in mice, and found that RG-derived viruses maintained the replication and neuropathogenic phenotypes of their wt counterpart. Additionally, we demonstrated that reverse genetics plasmids from different parental viruses can be readily mix-and-matched to generate reassortant viruses. This system provides a valuable genetic tool utilizing viruses with differing neuropathogenic phenotypes to investigate the genetic determinants of orthobunyavirus neuropathogenesis.

microbiology↗

Genetic Fingerprinting of Herbarium Hop Specimens Reveals Genetic Diversity and Relationships with Modern Finnish Hops

We sampled 351 hop herbarium specimens for genetic analyses of their identities through definition of unique set of samples by extraction of duplicates and comparative analyses with modern hop samples from Finland and worldwide. We also analyzed genetic diversity and assessed genetic clustering and structure within and between herbarium hops specimens and modern hop germplasm. A set of 26 previously published hop microsatellites (SSRs) proven in diversity analyses have been used for genetic evaluations of herbarium hop DNA extracted from pressed and dried specimens of which the oldest was dated back to the year of 1841. A genetic fingerprint was generated for all samples and unique ones has been generated in pairwise comparisons of pairs of samples and eliminations of duplicates. For unique set of samples, a genetic distance matrix was created for clustering analyses as well allele frequencies matrix for model-based clustering analyses. Herbarium hop samples representing historical DNA showed no clear differentiation (clustering or sub-clustering) when analyzed with presently grown modern hops. Weak tendency of hops to cluster according to the geographical origin has been noticed. We detected 39 groups of hop herbarium duplicates representing 94 specimens, where redundancy showed to be low when compared to modern Finnish hops (redundancy >70%). Analyzing herbarium hops through DNA extraction will add another link in investigating the origin and spread of Finnish hops from ancient times. Finnish hops has been described as a millennia old and native to Finland.

evolutionary biology↗

Genetic risk for coronary heart disease alters the influence of Alzheimer’s genetic risk on mild cognitive impairment

BACKGROUNDAlzheimers disease (AD) is under considerable genetic influence. However, known susceptibility loci only explain a modest proportion of variance in disease outcomes. This small proportion could occur if the etiology of AD is heterogeneous. We previously found that an AD polygenic risk score (PRS) was significantly associated with mild cognitive impairment (MCI), an early stage of AD. Poor cardiovascular health is also associated with increased risk for AD and has been found to interact with AD pathology. Conditions such as coronary artery disease (CAD) are also heritable, and may contribute to heterogeneity if there are interactions of genetic risk for these conditions as there is phenotypically. However, case-control designs based on prevalent cases of a disease with relatively high case-fatality rate such as CAD may be biased toward individuals who have long post-event survival times and may therefore also identify loci with protective effects.\n\nMETHODSWe compared interactions between an AD-PRS and two CAD-PRSs, one based on a GWAS of incident cases and one on prevalent cases, on MCI status in 1,209 individuals.\n\nRESULTSAs expected, the incidence-based CAD-PRS interacts with the AD-PRS to further increase MCI risk. Conversely, higher prevalence-based CAD-PRSs reduced the effect of AD genetic risk on MCI status.\n\nCONCLUSIONSThese results demonstrate: i) the utility of including multiple PRSs and their interaction effects; ii) how genetic risk for one disease may modify the impact of genetic risk for another; and iii) the importance of considering ascertainment procedures of GWAS being used for genetic risk prediction.

genomics↗

On Using Local Ancestry to Characterize the Genetic Architecture of Human Phenotypes: Genetic Regulation of Gene Expression in Multiethnic or Admixed Populations as a Model

BackgroundUnderstanding the nature of the genetic regulation of gene expression promises to advance our understanding of the genetic basis of disease. However, the methodological impact of use of local ancestry on high-dimensional omics analyses, including most prominently expression quantitative trait loci (eQTL) mapping and trait heritability estimation, in admixed populations remains critically underexplored.\n\nResultsHere we develop a statistical framework that characterizes the relationships among the determinants of the genetic architecture of an important class of molecular traits. We estimate the trait variance explained by ancestry using local admixture relatedness between individuals. Using National Institute of General Medical Sciences (NIGMS) and Genotype-Tissue Expression (GTEx) datasets, we show that use of local ancestry can substantially improve eQTL mapping and heritability estimation and characterize the sparse versus polygenic component of gene expression in admixed and multiethnic populations respectively. Using simulations of diverse genetic architectures to estimate trait heritability and the level of confounding, we show improved accuracy given individual-level data and evaluate a summary statistics based approach. Furthermore, we provide a computationally efficient approach to local ancestry analysis in eQTL mapping while increasing control of type I and type II error over traditional approaches.\n\nConclusionOur study has important methodological implications on genetic analysis of omics traits across a range of genomic contexts, from a single variant to a prioritized region to the entire genome. Our findings highlight the importance of using local ancestry to better characterize the heritability of complex traits and to more accurately map genetic associations.

bioinformatics↗

Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores

Summary statistics from a genome-wide association study (GWAS) can be used to generate a polygenic score (PGS). For complex, behavioral traits, the correlation between an individuals PGS and their phenotype may contain bias alongside the causal effect of the individuals genes (due to geographic, ancestral, and/or socioeconomic confounding). We formalize the recent introduction of a different source of bias in regression models using PGSs: the effects of parental genes on offspring outcomes, also known as genetic nurture. GWAS do not discriminate between the various pathways through which genes influence outcomes, meaning existing PGSs capture both direct genetic effects and genetic nurture effects. We construct a theoretical model for genetic effects and show that, unlike other sources of bias in PGSs, the presence of genetic nurture biases PGS coefficients from both naive OLS (between-family) and family fixed effects (within-family) regressions. This bias is in opposite directions; while naive OLS estimates are biased upwards, family fixed effects estimates are biased downwards. We quantify this bias for a given trait using two novel parameters that we identify and discuss: (1) the genetic correlation between the direct and nurture effects and (2) the ratio of the SNP heritabilities for the direct and nurture effects.

genomics↗

Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain at different anatomic sites

Chronic musculoskeletal pain has a negative impact on all aspects of human life. Genetic studies of pain are complicated by the high complexity and heterogeneity of pain phenotypes. In this research, we aimed to reduce phenotype heterogeneity and reveal genes and pathways shared by chronic musculoskeletal pain at four locations: back, neck/shoulder, hip, and knee. Our study was based on the results of genome-wide association studies performed using UK Biobank data with a total sample size of 456,000 individuals. We applied principal component analysis based on the matrix of genetic covariances between the studied pain traits and constructed four genetically independent phenotypes (GIPs). The leading GIP (GIP1) explains the largest proportion of the genetic variance of and covariance between the analyzed phenotypes (78.4%), and the later GIPs (GIP2-4) explain progressively less. We identified and replicated five loci associated with GIP1 and one locus associated with GIP2. The genes decisively prioritized for the GIP1-associated loci were SLC39A8, ECM1, and FOXP2. For the remaining two GIP1-associated loci, we proposed several candidates (AMIGO3, BSN, RBM6, FAM212A, RNF123, UBA7 and MIR7114, NSMF, NOXA1, GRIN1), but were unable to prioritize any of them convincingly. The most likely causal gene in the locus associated with GIP2 was GDF5. For GIP1, gene set/tissue/cell type enrichment analyses identified multiple terms related to the nervous system. Genetic correlations analysis revealed a genetic overlap between GIP1 and osteoarthritis as well as a set of anthropometric (such as overweight and waist circumference), sociodemographic (such as age of first birth and college completion) and psychiatric/personality (such as depressive symptoms and neuroticism) traits. We suggest that GIP1 represents a biopsychological component of chronic musculoskeletal pain, related to physiological and psychological aspects and likely reflecting pain perception and processing.

genomics↗

LEAPING A CONSERVATION GENETICS GAP: COMBINING POPULATION GENETICS AND SOCIAL NETWORK ANALYSIS FOR LUPINUS PERENNIS RESTORATION

Genomic data can assist conservation planning, but implementation of genetic-based recommendations is rare. Closing this "conservation genetics gap" is crucial for restoration and translocation decisions, particularly for highly fragmented ecosystems like pine barrens. We first analyze the conservation genetics gap in pine barren management organizations using a survey. We then analyze whole-genome data to characterize population structure and diversity in the pine barren keystone plant Lupinus perennis. We find little genetic difference among L. perennis populations in the Northeast United States. While populations show signs of isolation by distance (rho = 0.785, p = 0.001), we find no correlation between population size and heterozygosity (Estimate = 0.003, p = 0.357) or inbreeding (Estimate = 0.028, p = 0.416). We also find no effect of seed source population on forecasted effective population size in restoration simulations. These findings and our recommendation that managers consider non-local seed provenancing for L. perennis restorations in the Northeast have been integrated into SWAP policy in two states. We generally recommend practitioners record seed provenance, save genetic material for future testing, and incorporate fitness metrics into restoration monitoring. To effectively close the conservation genetics gap, researchers providing conservation recommendations must consult with practitioners before designing experiments.

genomics↗

Genome-wide association study and genetic differentiation analysis reveal the genetic basis of Vibrio harveyi resistance in blackspotted croaker (Protonibea diacanthus)

Vibrio harveyi is a primary causative agent of vibriosis, leading to catastrophic economic losses in the blackspotted croaker (Protonibea diacanthus) aquaculture. However, the genetic architecture underlying its resistance remains poorly understood. In this study, we conducted the first integrated genome-wide association study (GWAS) and genetic differentiation analysis (F_ST) to investigate the genetic basis of V. harveyi resistance. A total of 450 juveniles were challenged, and 300 individuals (comprising 150 resistant and 150 susceptible) were selected for whole-genome resequencing. Genomic heritability (h^2) was estimated at 0.374+/-0.29 for survival time (ST) and 0.237+/-0.185 for survival status (SS), indicating moderate genetic control. Notably, an exceptionally high genetic correlation (r_g = 0.999) was observed between ST and SS, while resistance traits were genetically independent of growth performance (r_g < 0.03). Through the convergence of GWAS and selection sweep signals, a major-effect QTL was identified on chromosome 4. Candidate gene prioritization identified high-confidence targets involved in post-transcriptional regulation and mRNA stability, specifically elavl4 (harboring a top-tier exon variant), rorb, cbpc6, and epn4. Functional enrichment analysis further revealed that resistance is significantly associated with "rRNA processing", "mRNA surveillance pathway", and "nucleocytoplasmic transport", suggesting that efficient RNA metabolic control is a critical determinant of host survival. These findings provide novel insights into the non-canonical immune mechanisms of P. diacanthus and offer robust molecular markers for marker-assisted selection and genomic selection, facilitating the development of disease-resistant strains in the sciaenid industry.

genomics↗

Characterisation of Genetically-Derived Patient Clusters Highlights Genetic Heterogeneity of Inflammatory Bowel Disease

Background and aims. Inflammatory Bowel Disease (IBD) is a complex immune-mediated condition with a strong genetic contribution. The genetics of IBD are highly complex, with inflammation, autoimmunity, and mucosal immunity pathways involved in its pathogenicity. GenePy is a gene-level disease burden metric. The integration of clinical and genetic data and the application of machine learning methods can aid patient stratification for personalised care. Methods. Lists of consensus IBD pathway genes were curated. GenePy scores were computed from whole exome sequencing data. A K-Means algorithm was optimised using clustering quality and stability metrics on the GenePy scores of genes in each IBD pathway, and the results replicated in three independent IBD cohorts (SPARC IBD, MSCCR IBD, and Southampton IBD). Chi-square tests assessed the association between cluster assignment and phenotypic features, and were multiple test corrected via Benjamini-Hochberg FDR. Results. A strong association was replicated for NOD signalling genes driving IBD subtype, Crohns disease behaviour, and IBD surgery across all cohorts, as well as granuloma in Southampton IBD. This was mainly driven by NOD2. Similar genetic clustering patterns were observed across all cohorts, with additional phenotypic enrichment in clusters driven by NLRP1 (surgery in MSCCR IBD), and nominally significant enrichment for disease behaviour linked to BIRC2 (B2 in Southampton IBD and B2B3 in SPARC IBD). Conclusions. This analysis identified a common genetic architecture across NOD signalling genes across IBD cohorts, replicated a signal for NOD2 as a monogenic driver of disease with a strong phenotypic enrichment, and identified other putative genetic drivers of IBD, such as the NLRP1 gene.

bioinformatics↗

Genome-wide LD scores enable robust heritability and genetic correlation estimation from summary statistics across genetic ancestries

Our knowledge of human complex trait architecture across diverse populations remains limited. Estimating SNP heritability and genetic correlation from GWAS summary statistics - successful in revealing genetic architecture in homogeneous cohorts - is challenging in structured and admixed populations due, in part, to the difficulty of representing long-range LD. We present SUMMIT, a statistical framework that combines genome-wide LD scores, efficiently estimated using random projections, with GWAS summary statistics to estimate genome-wide and annotation-specific heritability and genetic correlation. In simulations that explore diverse aspects of genetic architecture across European (EUR), South Asian (SAS), and admixed African-European cohorts (AFR) in the UK Biobank (UKB), SUMMIT had increased accuracy and reduced bias compared to prior methods, with the largest gains in non-European ancestries reflecting improved modeling of long-range LD. Across 40 UKB traits, SUMMIT produced estimates of genome-wide common-SNP heritability (h_g^2) and heritability enrichments in genomic annotations that were broadly concordant across ancestries with the SUMMIT h_g^2 estimates more closely matching recent whole-genome sequencing based estimates. SUMMIT substantially improved genetic correlation analysis recovering more significant findings across ancestries (23 SAS and 3 AFR at FDR < 0.05 compared with none and two for cov-LDSC) with the non-European discoveries showing concordant effects in Europeans suggesting that, like heritability, global patterns of pleiotropy are largely shared across ancestries. By combining accurate genome-wide LD and efficient moment estimation, SUMMIT enables investigation into how heritability and genetic correlation vary across populations and genomic annotations, including in structured and admixed cohorts, at the genome-wide, annotation-specific, and cross-trait levels.

genomics↗

Host-pathogen genetic interactions underlie tuberculosis susceptibility in genetically diverse mice

The outcome of an encounter with Mycobacterium tuberculosis depends on the pathogens ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to associate bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb mutant fitness across the CC panel revealed that many virulence pathways are only in specific host microenvironments, identifying the large fraction of the pathogens genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits were associated with genetic variants distributed across the mouse genome, identifying the specific host-pathogen genetic interactions that influence pathogenesis.

genetics↗

Genetic epidemiology of blood type, disease and trait variants, and genome-wide genetic diversity in over 11,000 domestic cats

In the largest DNA-based study of domestic cat to date, 11,036 individuals (10,419 pedigreed cats from 91 breeds and breed types and 617 non-pedigreed cats) were genotyped via commercial panel testing, elucidating the distribution and frequency of known genetic variants associated with blood type, disease and physical traits across cat breeds. Blood group determining variants, which are relevant clinically and in cat breeding, were genotyped to assess the across breed distribution of blood types A, B and AB. Extensive panel testing identified 13 disease-associated variants in 48 breeds or breed types for which the variant had not previously been observed, strengthening the argument for panel testing across populations. The study also indicates that multiple breed clubs have effectively used DNA testing to reduce disease-associated genetic variants within certain pedigreed cat populations. Appearance-associated genetic variation in all cats is also discussed. Additionally, we combined genotypic data with phenotype information and clinical documentation, actively conducted owner and veterinarian interviews, and recruited cats for clinical examination to investigate the causality of a number of tested variants across different breed backgrounds. Lastly, genome-wide informative SNP heterozygosity levels were calculated to obtain a comparable measure of the genetic diversity in different cat breeds. This study represents the first comprehensive exploration of informative Mendelian variants in felines by screening over 10,000 domestic cats. The results qualitatively contribute to the understanding of feline variant heritage and genetic diversity and demonstrate the clinical utility and importance of such information in supporting breeding programs and the research community. The work also highlights the crucial commitment of pedigreed cat breeders and registries in supporting the establishment of large genomic databases that when combined with phenotype information can advance scientific understanding and provide insights that can be applied to improve the health and welfare of cats.

genetics↗

Initial approach to the Conservation Genetics of the Guatemalan Beaded Lizard (Heloderma charlesbogerti): A route to genetic rescue

In this study, samples from 33 Guatemalan Beaded Lizard (Heloderma charlesbogerti) were analyzed for genetic diversity. Twenty-three samples were obtained from wild individuals from two separate population areas, and 10 samples were obtained from captive individuals. Because the seasonally dry tropical forest habitat sampled for this study, is degraded and fragmented, it was hypothesized that beaded lizard populations were small and isolated and would be subject to genetic erosion and an elevated extinction risk. To test this hypothesis, eight microsatellite markers were employed to analyze 22 individual samples from the population of Cabanas, Zacapa, a single individual from the eastern-most population and 10 captive individuals of unknown origin. An average of three alleles per maker was reported for the Cabanas population, evidencing a low genetic diversity. In addition, a recent bottleneck event was detected and an effective population size of 19.6 was estimated. Demographic reconstruction using a Bayesian approach was inconclusive possibly due to a small dataset and shallow coalescence trees obtained with the generated data. No clear structuring pattern was detected for the Cabanas population and most samples from individuals in captivity were found to have similar alleles to the ones from Cabanas. Population designation is challenging without the genotyping of every wild population, but unique alleles were found in captive individuals of unknown origin that could suggest that different genotypes might exist within other, less studied, wild populations. Low genetic diversity, and a small effective population size represent a risk for the Cabanas population facing the threats of isolation, habitat loss and climate change. These findings suggest that genetic management of the Cabanas population might be utilized to avoid high rates of inbreeding and subsequent inbreeding depression.

genetics↗

Genetics of Latin American Diversity (GLAD) Project: insights into population genetics and association studies in recently admixed groups in the Americas

Latin America is underrepresented in genetic studies, which can exacerbate disparities in personalized genomic medicine. However, genetic data of thousands of Latin Americans are already publicly available, but require a bureaucratic maze to navigate all the data access and consenting issues. We present the Genetics of Latin American Diversity (GLAD) Project, a platform that compiles genome-wide information of 54,077 Latin Americans from 39 studies representing 45 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene-flow across the Americas. Also, we developed a simulated-annealing-based algorithm to match the genetic background of external samples to our database and share summary statistics without transferring individual-level data. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic softwares in the presence of admixture. By making this resource available, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.

genetics↗

Systemizing is genetically correlated with autism and is genetically distinct from social autistic traits

The core diagnostic criteria for autism comprise two symptom domains - social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, yet, this hypothesis has not been tested using molecular genetics. We test this using a GWAS of a non-social autistic trait, systemizing (N = 51,564), defined as the drive to analyse and build systems. We demonstrate that systemizing is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemizing. Supporting this, polygenic scores for systemizing are significantly positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism.

genetics↗

The current obesity “epidemic”: segregation of familial genetic risk in NHANES cohort supports a major role for large genetic effects

The continuing increase in many countries in adult body mass index (BMI kg/m2) and its dispersion is contributed to by interaction between genetic susceptibilities and an increasingly obesogenic environment (OE). The determinants of OE-susceptibility are unresolved, due to uncertainty around relevant genetic and environmental architecture. We aimed to test the multi-modal distributional predictions of a Mendelian genetic architecture based on collectively common, but individually rare, large-effect variants and their ability to account for current trends in a large population-based sample. We studied publicly available adult BMI data (n = 9102) from 3 cycles of NHANES (1999, 2005, 2013). A first degree family history of diabetes served as a binary marker (FH0/FH1) of genetic obesity susceptibility. We tested for multi-modal BMI distributions non-parametrically using kernel-smoothing and conditional quantile regression (CQR), obtained parametric fits to a Mendelian model in FH1, and estimated FH x OE interactions in CQR models and ANCOVA models incorporating secular time. Non-parametric distributional analyses were consistent with multi-modality and fits to a Mendelian model in FH1 reliably identified 3 modes. Mode separation accounted for ~40% of BMI variance in FH1 providing a lower bound for the contribution of large effects. CQR identified strong FH x OE interactions and FH1 accounted for ~60% of the secular trends in BMI and its SD in ANCOVA models. Multimodality in the FH effect is inconsistent with a predominantly polygenic, small effect architecture and we conclude that large genetic effects interacting with OE provide a better quantitative explanation for current trends in BMI.

genetics↗

Genetic structure in patchy populations of a candidate foundation plant: a case study of Leymus chinensis (Poaceae) using genetic and clonal diversity

PREMISEThe distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species since they create and define ecological communities, contributing disproportionately to ecosystem function. METHODSWe examined the distribution of genetic diversity and clones, which we defined first as unique multi-locus genotypes (MLG), and then by grouping similar MLGs into multi-locus lineages (MLL). We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass Leymus chinensis. We examined the relationship between genetic and clonal diversities, their variation with patch-size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species. RESULTSEvery ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single MLL. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three. CONCLUSIONSWe found strong genetic structure among patches of L. chinensis. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.

ecology↗