Component Discriminant Analysis Research Articles

Elucidating genetic variability between randomly bred domestic cats and Persian domestic cats from different geographical locations using microsatellite markers.

The domestic cat (Felis catus) is a newly evolved species in the family Felidae that has developed some great features among mammals. It is critical to conserve these species and prevent inbreeding from reducing their genetic diversity by understanding their genetic relationships and applying the information to breeding management. The diverse population was an excellent choice for studying genetic diversity and inbreeding phenomena. To conduct this research, 128 individuals from 8 populations, including Azerbaijan, Persian, Ahar, Uermia, Tehran, Karaj, Turkish and Shop cat (both genders), were randomly selected from different geographical regions. We selected eight STR markers with different chromosomal locations based on polymorphism and observed allele numbers in the next step. DNA extraction was performed using tail hair root, PCR and electrophoresis, and gel staining was performed according to routine laboratory protocol. For statistical analysis, CONVERT versions POPGENE, ARLEQUIN GenAlEx and R script analysis. Remarkably, our results showed that 23 alleles were identified in 128 samples. The highest number of alleles belonged to the FCa096 locus (eight alleles) in the Persian population, followed by FCa045 (seven alleles) in the Persian and Ahar populations. Another new finding is that the lowest number of alleles belonged to the 35 and FCa77 locus (two alleles). In addition, pairwise differentiation between and within populations was examined using the genetic distance index. Overall, the results showed that the degree of differentiation within the population is high in the Turkish population compared to other population groups and lower in the Azerbaijan population. In addition, principal component discriminant analysis-based analysis based on the ADAGENET package shows the distribution of samples by geographical location. The results show that genetic mixing between populations is high. On this basis, we conclude that randomly bred domestic cats have a higher level of diversity than Persian domestic cats. This is an interesting topic for future work.

Variability of amylose content and its correlation with the paste properties of cassava starch.

The amylose content can significantly impact the diverse industrial applications of cassava starch. This study aimed to assess the variability of cassava germplasm concerning amylose content and other attributes pertinent to root quality, alongside its correlation with paste properties. Starch extracted from 281 genotypes, obtained in germplasm evaluation trials, was evaluated for amylose content, with additional analysis of parameters such as pasting temperature, time to peak viscosity (TPV), viscosity breakdown (BrD), retrogradation tendency, and maximum, minimum, and final viscosities. The genotypes exhibited considerable variation in dry matter content (ranging from 27.06% to 41.02%), starch content (from 14.61% to 25.67%), cyanogenic compounds (1.77 to 7.81), and amylose content (0.05% to 33.23%). High phenotypic variability in paste properties was observed, alongside a low residual effect for most traits, resulting in high broad-sense heritabilities (>0.95). Strong correlations of significant magnitude (>0.80) were found between parameters such as peak viscosity × viscosity breakdown, minimum viscosity × final viscosity, and final viscosity × retrogradation tendency. Moderate correlations were also identified, such as between dry matter content × starch content (0.56). While positive, correlations between amylose content and paste properties were of low magnitude (ranging from 0.13 to 0.35), except for TPV and BrD. Principal component discriminant analysis clustered the germplasm into six distinct groups based on root quality and paste properties, with most improved genotypes falling into two clusters characterized by high starch and dry matter contents. This study underscores the necessity of simultaneous evaluation of amylose content and paste properties in the breeding pipeline. Additionally, clustering cassava genotypes proves beneficial in identifying those that fulfill specific requirements in industrial and breeding applications.

The Range‐Wide Genetic Structure of a High‐Elevation Conifer Species, Subalpine Larch

ABSTRACTAimSubalpine larch is a long‐lived conifer with a restricted distribution at treeline in the mountains of western North America. Climate change is reducing the availability of this habitat and subalpine larch is unlikely to adapt to its changing environment due to its long generation time, relatively low levels of standing genetic variation and the high degree of habitat fragmentation across the species' range. This study seeks to elucidate the genetic structure of subalpine larch to inform future conservation and management efforts.LocationWestern North America.TaxonSubalpine larch (Larix lyallii Parl.).MethodsTissue was collected from high‐elevation populations across the entire species range. Restriction site associated DNA sequencing was used to generate single nucleotide polymorphism (SNP) data. Population genetic analyses identified genetic differentiation.ResultsClustering analyses performed using 751 neutral SNPs identified three genetically differentiated regions: the Cascade Range, the southern Rocky Mountains and the northern Rocky Mountains. AMOVA confirmed significant genetic differentiation among regions. A discriminant analysis of principal components and a dendrogram of Provesti's genetic distance both supported the hypothesis that genetically distinct lineages arose after dispersal from a single Pleistocene refugium. Significant isolation by distance (IBD) supported the key role of dispersal in shaping modern patterns of genetic variation in subalpine larch.Main ConclusionsPost‐Pleistocene dispersal resulted in genetic differentiation among groups of subalpine larch in the Cascade Range, the southern Rocky Mountains and the northern Rocky Mountains. These three regions should be prioritised for future management.

Genetic diversity and population structure of wild Salvia miltiorrhiza in China revealed by microsatellite markers and implication for conservation

AbstractSalvia miltiorrhiza is an outcrossing and perennial herb native to China. Although well-known for its medicinal value, there is a lack of knowledge regarding its natural population genetics. Here, we used 12 microsatellite markers to investigated population genetic diversity and structure of 215 samples from populations naturally distributed in central eastern China. A moderate level of genetic diversity was detected probably due to the over-mining of its roots. The allelic richness (AR) ranged from 3.034 to 4.889 with an average of 3.891. Moreover, pairwise estimates of FST among the populations of S. miltiorrhiza varied from 0.036 to 0.312 and two clusters were obtained by STRUCTURE and discriminant analysis of principal components. It is likely that the genetic differentiation of these two clusters was formed during glacial periods. Our result provides insights into the conservation of this valuable medicinal plant.

Aperiodic Component Analysis in Quantification of Steady-State Visually Evoked Potentials.

In this study, we aimed to investigate whether and how the aperiodic component in electroencephalograms affects different quantitative processes of steady-state visually evoked potentials and the performance of corresponding brain-computer interfaces. We applied the Fitting Oscillations & One-Over-F method to parameterize power spectra as a combination of periodic oscillations and an aperiodic component. Electroencephalographic responses and system performance were measured and compared using four prevailing methods: power spectral density analysis, canonical correlation analysis, filter bank canonical correlation analysis and the state-of-the-art method, task discriminant component analysis. We found that controlling for the aperiodic component prominently downgraded the performance of brain-computer interfaces measured by canonical correlation analysis (94.9% to 82.8%), filter bank canonical correlation analysis (94.1% to 87.6%), and task discriminant component analysis (96.5% to 70.3%). However, it had almost no effect on that measured by power spectral density analysis (80.4% to 78.7%). This was accompanied by a differential aperiodic impact between power spectral density analysis and the other three methods on the differentiation of the target and non-target stimuli. The aperiodic component distinctly impacts the quantification of steady-state visually evoked potentials and the performance of corresponding brain-computer interfaces. Our work underscores the significance of taking into account the dynamic nature of aperiodic activities in research related to the quantification of steady-state visually evoked potentials. The source code for our approach is available at https://github.com/didi226/scut_ssvep_aperiod.

HBeeID: a molecular tool that identifies honey bee subspecies from different geographic populations

BackgroundHoney bees are the principal commercial pollinators. Along with other arthropods, they are increasingly under threat from anthropogenic factors such as the incursion of invasive honey bee subspecies, pathogens and parasites. Better tools are needed to identify bee subspecies. Genomic data for economic and ecologically important organisms is increasing, but in its basic form its practical application to address ecological problems is limited.ResultsWe introduce HBeeID a means to identify honey bees. The tool utilizes a knowledge-based network and diagnostic SNPs identified by discriminant analysis of principle components and hierarchical agglomerative clustering. Tests of HBeeID showed that it identifies African, Americas-Africanized, Asian, and European honey bees with a high degree of certainty even when samples lack the full 272 SNPs of HBeeID. Its prediction capacity decreases with highly admixed samples.ConclusionHBeeID is a high-resolution genomic, SNP based tool, that can be used to identify honey bees and screen species that are invasive. Its flexible design allows for future improvements via sample data additions from other localities.

Rapid Classification and Differentiation of Sepsis-Related Pathogens Using FT-IR Spectroscopy.

Sepsis is a life-threatening condition arising from a dysregulated host immune response to infection, leading to a substantial global health burden. The accurate identification of bacterial pathogens in sepsis is essential for guiding effective antimicrobial therapy and optimising patient outcomes. Traditional culture-based bacterial typing methods present inherent limitations, necessitating the exploration of alternative diagnostic approaches. This study reports the successful application of Fourier-transform infrared (FT-IR) spectroscopy in combination with chemometrics as a potent tool for the classification and discrimination of microbial species and strains, primarily sourced from individuals with invasive infections. These samples were obtained from various children with suspected sepsis infections with bacteria and fungi originating at different sites. We conducted a comprehensive analysis utilising 212 isolates from 14 distinct genera, comprising 202 bacterial and 10 fungal isolates. With the spectral analysis taking several weeks, we present the incorporation of quality control samples to mitigate potential variations that may arise between different sample plates, especially when dealing with a large sample size. The results demonstrated a remarkable consistency in clustering patterns among 14 genera when subjected to principal component analysis (PCA). Particularly, Candida, a fungal genus, was distinctly recovered away from bacterial samples. Principal component discriminant function analysis (PC-DFA) allowed for distinct discrimination between different bacterial groups, particularly Gram-negative and Gram-positive bacteria. Clear differentiation was also observed between coagulase-negative staphylococci (CNS) and Staphylococcus aureus isolates, while methicillin-resistant S. aureus (MRSA) was also separated from methicillin-susceptible S. aureus (MSSA) isolates. Furthermore, highly accurate discrimination was achieved between Enterococcus and vancomycin-resistant enterococci isolates with 98.4% accuracy using partial least squares-discriminant analysis. The study also demonstrates the specificity of FT-IR, as it effectively discriminates between individual isolates of Streptococcus and Candida at their respective species levels. The findings of this study establish a strong groundwork for the broader implementation of FT-IR and chemometrics in clinical and microbiological applications. The potential of these techniques for enhanced microbial classification holds significant promise in the diagnosis and management of invasive bacterial infections, thereby contributing to improved patient outcomes.

Low genetic differentiation despite high habitat fragmentation in an endemic and endangered species of Iridaceae from South America: implications for conservation

Abstract To conserve threatened species effectively, it is crucial to map the genetic variation of the remaining populations. Thus, using 15 microsatellites markers, from which 10 were specially developed for this study, we investigated genetic structure and gene flow patterns of Herbertia zebrina Deble, a critically endangered species endemic from grasslands of southern Brazil. We also investigated the degree of habitat fragmentation and the impacts on levels of genetic diversity, mating system and pollinators of the species. STRUCTURE and discriminant analysis of principal components identified the existence of three genetic clusters. Populations were not isolated by distance, and genetic differentiation among populations was low (7.0%). Migration rates were also low, but no evidence of genetic bottlenecks was found. However, effective population-scaled mutation rates (Θ) were < 1, suggesting that populations could be experiencing genetic drift, but the reason remains unknown. The results indicate that measurements of habitat fragmentation were not significantly correlated with genetic diversity estimates, which tend to increase with fragment size. H. zebrina was identified as an outcrossing species and specialized pollinators, such as Chalepogenus goeldianus and Lanthanomelissa betinae were rarely observed. Our findings suggest that genetic differentiation across multiple populations within the entire geographic distribution of H. zebrina is very low and populations may struggle to adapt to the current environmental and pollination changes. However, habitat fragmentation is still too recent to detect significant impacts on the levels of genetic variation. Thus, conservation plans are necessary to avoid further declines of this species.

Congruent patterns of cryptic cladogenesis revealed using RADseq and Sanger sequencing in a velvet worm species complex (Onychophora: Peripatopsidae: Peripatopsis sedgwicki)

In the present study, first generation DNA sequencing (mitochondrial cytochrome c oxidase subunit one, COI) and reduced-representative genomic RADseq data were used to understand the patterns and processes of diversification of the velvet worm, Peripatopsis sedgwicki species complex across its distribution range in South Africa. For the RADseq data, three datasets (two primary and one supplementary) were generated corresponding to 1,259–11,468 SNPs, in order to assess the diversity and phylogeography of the species complex. Tree topologies for the two primary datasets were inferred using maximum likelihood and Bayesian inferences methods. Phylogenetic analyses using the COI datasets retrieved four distinct, well-supported clades within the species complex. Five species delimitation methods applied to the COI data (ASAP, bPTP, bGMYC, STACEY and iBPP) all showed support for the distinction of the Fort Fordyce Nature Reserve specimens. In the main P. sedgwicki species complex, the species delimitation methods revealed a variable number of operational taxonomic units and overestimated the number of putative taxa. Divergence time estimates coupled with the geographic exclusivity of species and phylogeographic results suggest recent cladogenesis during the Plio/Pleistocene. The RADseq data were subjected to a principal components analysis and a discriminant analysis of principal components, under a maximum-likelihood framework. The latter results corroborate the four main clades observed using the COI data, however, applying additional filtering revealed additional diversity. The high overall congruence observed between the RADseq data and COI data suggest that first generation sequence data remain a cheap and effective method for evolutionary studies, although RADseq does provide a far greater resolution of contemporary temporo-spatial patterns.

Spatial genetic patterns of a long-lived tree species: the case of Pinus leiophylla in a human-altered landscape of central Mexico

In long-lived species, deforestation can modify the genetic diversity patterns of recent populations. The spatial-structure genetics of Pinus leiophylla Schiede ex Schltdl. & Cham. was investigated in adults and seedlings of remnant populations from central Mexico. Two chloroplast intergenic regions were sequenced of two cohorts (adults and seedlings) of 121 individuals of P. leiophylla from three localities. Higher genetic differentiation was found in adults ( ФST = 0.09) than in seedlings ( ФST = 0.03). The discriminant analysis of principal components detected four genetic clusters and the Mantel test found a weak but significant isolation by distance pattern ( r2 = 0.05, p = 0.002). Sixteen percent of genetic variation was explained by the spatial component according to the genetic neighborhood analysis. And the effect of three landscape features, i.e., elevation, aspect (sine and cosine), and land use, explored with ResistanceGA, detected that land use significantly restricts gene flow between populations, mostly in the farming category. This study emphasizes the critical role of preserving forest cover to maintain connectivity among remnants of P. leiophylla. Insights of this study will contribute to the conservation of conifers in Mexican temperate forests, especially within landscapes heavily altered by human activities.

Being Stung Once or Twice by Bees (Apis mellifera L.) Slightly Disturbed the Serum Metabolome of SD Rats to a Similar Extent.

In most cases, the number of honeybee stings received by the body is generally small, but honeybee stings can still cause serious allergic reactions. This study fully simulated bee stings under natural conditions and used 1H Nuclear Magnetic Resonance (1H NMR) to analyze the changes in the serum metabolome of Sprague-Dawley (SD) rats stung once or twice by honeybees to verify the impact of this mild sting on the body and its underlying mechanism. The differentially abundant metabolites between the blank control rats and the rats stung by honeybees included four amino acids (aspartate, glutamate, glutamine, and valine) and four organic acids (ascorbic acid, lactate, malate, and pyruvate). There was no separation between the sting groups, indicating that the impact of stinging once or twice on the serum metabolome was similar. Using the Principal Component Discriminant Analysis ( PCA-DA) and Variable Importance in Projection (VIP) methods, glucose, lactate, and pyruvate were identified to help distinguish between sting groups and non-sting groups. Metabolic pathway analysis revealed that four metabolic pathways, namely, the tricarboxylic acid cycle, pyruvate metabolism, glutamate metabolism, and alanine, aspartate, and glutamate metabolism, were significantly affected by bee stings. The above results can provide a theoretical basis for future epidemiological studies of bee stings and medical treatment of patients stung by honeybees.

Disentangling genetic diversity of Myotis septentrionalis: population structure, demographic history, and effective population size

Abstract Myotis septentrionalis (Northern Long-eared Bat) has recently suffered a >90% decline in population size in North America due to white-nose syndrome (WNS). We assessed genetic diversity, population structure, current effective population size, and demographic history of M. septentrionalis distributed across the United States to determine baseline levels pre-WNS. We analyzed RADseq data from 81 individuals from Kentucky, Louisiana, Michigan, Minnesota, North Carolina, Oklahoma, and Wisconsin. Additionally, we examined population genetic structure using discriminant analysis of principal components, fastStructure, and STRUCTURE. We then estimated effective population size and demographic history using fastsimcoal2. Similar levels of genetic diversity were found across all samples. We found no population genetic structure in the varied analyses from these contemporary samples. The best model for demographic history estimated a rapid population expansion followed by a slower expansion approximately 340,000 years ago. The vagility of M. septentrionalis, along with male dispersal and random mating, may provide a buffer against serious bottleneck effects stemming from rapid population declines due to WNS. This research provides a baseline for tracking and monitoring the influence of WNS on genetic diversity such as potential reduced diversity or increased population structuring in the future.

Genetic Diversity, Linkage Disequilibrium, and Population Structure in a Common Bean Reference Collection

An in-depth understanding of the extent and pattern of genetic diversity and population structure in crop populations is of paramount importance for any crop improvement program to efficiently promote the translation of genetic diversity into genetic gain. A reference collection of 150 common bean genotypes selected from the International Center for Tropical Agriculture’s global core collection was evaluated using single-nucleotide polymorphism (SNP) markers to quantify the amount of genetic diversity, linkage disequilibrium, and population structure. The cultivars and landraces of the collection were diverse and originated from 14 countries, and wild accessions were used as controls for each gene pool. The collection was genotyped using an SNP array, generating a total of 5398 locus calls distributed across the entire bean genome. The SNP data quality was checked, and two datasets were generated. The first dataset (Dataset_1) comprised a set of 5108 SNPs and 150 genotypes after filtering for 10% missing alleles and an MAF < 0.05. The second dataset (Dataset_2) comprised a set of 2300 SNPs that remained after removing any null-allele SNPs and LD pruning for a criterion of r2 < 0.2. Dataset_1 was used for a principal coordinate analysis (PCoA), phylogenetic relationship determination, an analysis of molecular variance (AMOVA), and a discriminant analysis of principal components. Dataset_2 was used for a population structure analysis using STRUCTURE software and is proposed for a genome-wide association study (GWAS). The population structure analysis split the reference collection into two subpopulations according to an Andean or Mesoamerican gene pool. The Mesoamerican populations displayed higher genetic differentiation and tended to split into more groups that were somewhat aligned with common bean races. Andean beans were characterized by a larger average LD but lower LD percentage, a small average genetic distance between members of the population, and a higher major allele frequency, which suggested narrower genetic diversity compared to the Mesoamerican gene pool. In conclusion, the results indicated the presence of high genetic diversity, which is useful for a GWAS. However, the presence of significant linkage disequilibrium requires that genetic distance be considered as a co-factor for any further genetic studies. Overall, the molecular variation observed in the genotypes shows that this reference collection is valuable as a genebank-derived diversity panel which is useful for marker trait association studies.

Development and validation of the Axiom-MaruPri SNP chip for genetic analyses of domesticated old world camelids

Camels play a crucial socio-economic role in sustaining the livelihoods of millions in arid and semi-arid regions. They possess remarkable physiological attributes which enable them to thrive in extreme environments, and provide a source of meat, milk and transportation. With their unique traits, camels embody an irreplaceable source of untapped genomic knowledge. This study introduces Axiom-MaruPri, a medium-density SNP chip meticulously designed and validated for both Camelus bactrianus and Camelus dromedarius. Comprising of 182,122 SNP markers, derived from the re-sequenced data of nine Indian dromedary breeds and the double-humped Bactrian camel, this SNP chip offers 34,894 markers that display polymorphism in both species. It achieves an estimated inter-marker distance of 14 Kb, significantly enhancing the coverage of the camel genome. The medium-density chip has been successfully genotyped using 480 camel samples, achieving an impressive 99 % call rate, with 96 % of the 182,122 SNPs being highly reliable for genotyping. Phylogenetic analysis and Discriminant Analysis of Principal Components yield clear distinctions between Bactrian camels and dromedaries. Moreover, the discriminant functions substantially enhance the classification of dromedary camels into different breeds. The clustering of various camel breeds reveals an apparent correlation between geographical and genetic distances. The results affirm the efficacy of this SNP array, demonstrating high genotyping precision and clear differentiation between Bactrian and dromedary camels. With an enhanced genome coverage, accuracy and economic efficiency the Axiom_MaruPri SNP chip is poised to advance genomic breeding research in camels. It holds the potential to serve as an invaluable genetic resource for investigating population structure, genome-wide association studies and implementing genomic selection in domesticated camelid species.

Genetic Diversity and Population Structure of the Invasive Oriental Fruit Fly, Bactrocera dorsalis (Diptera: Tephritidae) in Burkina Faso.

Bactrocera dorsalis Hendel is a highly invasive horticultural pest that is of major economic importance worldwide. In Burkina Faso, it is one of the main insect pests that affects the production and exportation of mangos. Understanding the biology and the genetic dynamics of this insect pest provides crucial information for the development of effective control measures. The aim of this study was to understand the distribution, diversity, and genetic structure of B. dorsalis in Burkina Faso. Male flies were collected transversally in Burkina Faso and analyzed by PCR using 10 microsatellite markers. The results showed an abundance of B. dorsalis varying from 87 to 2986 flies per trap per day at the different sampling sites. The genetic diversity was high at all sites, with an average Shannon's Information Index (I) of 0.72 per site. The gene flow was high between study populations and ranged from 10.62 to 27.53 migrants. Bayesian admixture analysis showed no evidence of structure, while Discriminant Analysis of Principal Components identified three weakly separated clusters in the population of B. dorsalis in Burkina Faso. The results of this study could be used to optimize the effectiveness of current control interventions and to guide the implementation of new, innovative, and sustainable strategies.

Azole resistance mechanisms and population structure of the human pathogen Aspergillus fumigatus on retail plant products.

Aspergillus fumigatus is a ubiquitous saprotroph and human-pathogenic fungus that is life-threatening to the immunocompromised. Triazole-resistant A. fumigatus was found in patients without prior treatment with azoles, leading researchers to conclude that resistance had developed in agricultural environments where azoles are used against plant pathogens. Previous studies have documented azole-resistant A. fumigatus across agricultural environments, but few have looked at retail plant products. Our objectives were to determine if azole-resistant A. fumigatus is prevalent in retail plant products produced in the United States (U.S.), as well as to identify the resistance mechanism(s) and population genetic structure of these isolates. Five hundred twenty-five isolates were collected from retail plant products and screened for azole resistance. Twenty-four isolates collected from compost, soil, flower bulbs, and raw peanuts were pan-azole resistant. These isolates had the TR34/L98H, TR46/Y121F/T289A, G448S, and H147Y cyp51A alleles, all known to underly pan-azole resistance, as well as WT alleles, suggesting that non-cyp51A mechanisms contribute to pan-azole resistance in these isolates. Minimum spanning networks showed two lineages containing isolates with TR alleles or the F46Y/M172V/E427K allele, and discriminant analysis of principle components identified three primary clusters. This is consistent with previous studies detecting three clades of A. fumigatus and identifying pan-azole-resistant isolates with TR alleles in a single clade. We found pan-azole resistance in U.S. retail plant products, particularly compost and flower bulbs, which indicates a risk of exposure to these products for susceptible populations and that highly resistant isolates are likely distributed worldwide on these products.IMPORTANCEAspergillus fumigatus has recently been designated as a critical fungal pathogen by the World Health Organization. It is most deadly to people with compromised immune systems, and with the emergence of antifungal resistance to multiple azole drugs, this disease carries a nearly 100% fatality rate without treatment or if isolates are resistant to the drugs used to treat the disease. It is important to determine the relatedness and origins of resistant A. fumigatus isolates in the environment, including plant-based retail products, so that factors promoting the development and propagation of resistant isolates can be identified.

Association of circulating biomarkers with illness severity measures differentiates myalgic encephalomyelitis/chronic fatigue syndrome and post-COVID-19 condition: a prospective pilot cohort study.

Accumulating evidence suggests that autonomic dysfunction and persistent systemic inflammation are common clinical features in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID. However, there is limited knowledge regarding their potential association with circulating biomarkers and illness severity in these conditions. This single-site, prospective, cross-sectional, pilot cohort study aimed to distinguish between the two patient populations by using self-reported outcome measures and circulating biomarkers of endothelial function and systemic inflammation status. Thirty-one individuals with ME/CFS, 23 individuals with long COVID, and 31 matched sedentary healthy controls were included. All study participants underwent non-invasive cardiovascular hemodynamic challenge testing (10min NASA lean test) for assessment of orthostatic intolerance. Regression analysis was used to examine associations between outcome measures and circulating biomarkers in the study participants. Classification across groups was based on principal component and discriminant analyses. Four ME/CFS patients (13%), 1 with long COVID (4%), and 1 healthy control (3%) presented postural orthostatic tachycardia syndrome (POTS) using the 10-min NASA lean test. Compared with matched healthy controls, ME/CFS and long COVID subjects showed higher levels of ET-1 (p < 0.05) and VCAM-1 (p < 0.001), and lower levels of nitrites (NOx assessed as NO2- + NO3-) (p < 0.01). ME/CFS patients also showed higher levels of serpin E1 (PAI-1) and E-selectin than did both long COVID and matched control subjects (p < 0.01 in all cases). Long COVID patients had lower TSP-1 levels than did ME/CFS patients and matched sedentary healthy controls (p < 0.001). As for inflammation biomarkers, both long COVID and ME/CFS subjects had higher levels of TNF-α than did matched healthy controls (p < 0.01 in both comparisons). Compared with controls, ME/CFS patients had higher levels of IL-1β (p < 0.001), IL-4 (p < 0.001), IL-6 (p < 0.01), IL-10 (p < 0.001), IP-10 (p < 0.05), and leptin (p < 0.001). Principal component analysis supported differentiation between groups based on self-reported outcome measures and biomarkers of endothelial function and inflammatory status in the study population. Our findings revealed that combining biomarkers of endothelial dysfunction and inflammation with outcome measures differentiate ME/CFS and Long COVID using robust discriminant analysis of principal components. Further research is needed to provide a more comprehensive characterization of these underlying pathomechanisms, which could be promising targets for therapeutic and preventive strategies in these conditions.

SSR Marker–Based Genetic Diversity and Relationship Analyses of Stephania tetrandra S. Moore

AbstractStephania tetrandra S. Moore (family: Menispermaceae), a dioecious herbaceous vine and the only species in the subgenus Botryodiscia of the genus Stephania of the family Menispermaceae, is mainly distributed in hilly areas south of the Huaihe River in China and found in many provinces of China, showing a high genetic diversity. This paper aimed to study genetic diversity of and genetic relationship among individuals of S. tetrandra within China to provide a basis for evaluation, exploitation, and utilization of S. tetrandra by using simple sequence repeat (SSR) molecular markers. Our results show that effective products were amplified from the 26 screened SSR gene loci, a total of 183 alleles amplified (2–16 alleles amplified by each pair of primers). Among the 26 loci, 16 had a PIC value higher than 0.5, indicating a high level of polymorphism. For most of the loci, the number of effective alleles was lower than that of the observed alleles, and the observed heterozygosity was lower than the expected heterozygosity. The genetic differentiation coefficient (0.021–0.547) was lower than 0.05 (low level of genetic differentiation) for 7 loci and higher than 0.25 (very high level of genetic differentiation) for 2 loci, and had a value representing a medium level of genetic differentiation for the remaining 17 loci. The intra-population inbreeding coefficient had a positive value for 21 loci, suggesting the presence of inbreeding and homozygous excess. The gene flow value was bigger than 1, indicating that genetic drift and natural selection played an unimportant role in population genetic differentiation of S. tetrandra. Based on discriminant analysis of principal components and Bayesian Information Criterion, K-means clustering was performed on 620 samples. These samples were divided into 9 genetic clusters, whose similarity coefficients and genetic distances were 0.755–0.918 and 0.067–0.280, respectively, indicating that these clusters were highly similar and short-distanced. The Bayesian clustering analysis was implemented in the STRUCTURE software to analyze the genetic structure of S. tetrandra and it was found that the 620 samples could be clustered into 5 ancestor groups; the 9 clusters and 40 natural populations inherited genes from the 5 groups to varying degrees, but the proportion of genes inherited from the 5 groups by each cluster and natural population differed. S. tetrandra was characterized by the presence of population structure and pronounced genetic subdivision, which, together with the presence of gene flow, may indicate a relatively stable recent state of these populations.

Genetic Diversity Analysis of Anisogramma anomala in the Pacific Northwest and New Jersey.

Anisogramma anomala, a biotrophic ascomycete, causes eastern filbert blight (EFB) of hazelnuts (Corylus spp.). EFB is endemic in eastern North America, preventing the commercial production of European hazelnut (C. avellana L.). In contrast, the historic absence of A. anomala in the Pacific Northwest (PNW) supported the development of a robust hazelnut industry. Circa 1960, A. anomala was inadvertently introduced into southwestern Washington, causing orchard devastation. Distribution of the pathogen in the PNW has been hypothesized to be the result of a single-point introduction. This study aimed to investigate the single-point introduction hypothesis of A. anomala by comparing the genetic diversity of A. anomala samples from the PNW and New Jersey (NJ). Specimens from the main PNW production region (n = 60) and an area within the pathogen's native range, NJ (n = 151), were genotyped using 15 simple sequence repeat (SSR) markers. The following were used to assess genetic diversity and population structure: allelic summary statistics, discriminant analysis of principal components, network median-joining tree, analysis of multilocus genotypes, and allelic population diversity analysis. Analyses separated the samples into one cluster containing all the PNW isolates, and five clusters of NJ isolates. The PNW samples were nearly genetically uniform, and the NJ isolates were diverse. These findings support the hypothesis that A. anomala in the PNW was derived from a single-point introduction and corroborate previous studies that have shown A. anomala is very diverse in NJ. This indicates that maintaining restrictions on the movement of Corylus into the PNW is important to prevent the introduction of new populations of A. anomala, thus protecting the PNW hazelnut industry.

Diversity and Clonality in Populations of Phytophthora citrophthora and P. syringae Causing Brown Rot of Citrus in California.

Phytophthora citrophthora and P. syringae are currently the primary causal organisms of brown rot of citrus fruits in California. To possibly find an explanation for the prevalence of the previously minor species P. syringae, we determined the population structures of both pathogens in California using next-generation sequencing and population genomics analyses. Whole-genome sequencing and aligning with newly assembled reference genomes identified 972,266 variants in 132 isolates of P. citrophthora and 422,208 variants in 154 isolates (including 24 from noncitrus tree crops) of P. syringae originating from three major growing regions. The resulting data sets were visualized using principal component analysis, discriminant analysis of principal components, unweighted pair-group method with arithmetic mean dendrograms, fastStructure, and minimum spanning networks, and we obtained the index of association, diversity summary statistics, and genetic distance statistics values GST, G''ST, and Jost's D. Subpopulations of both species were mostly defined by their geographic origin indicating restricted dispersal of inoculum. Except for five isolates, the population structure of P. citrophthora (that is heterothallic and unlikely to reproduce sexually) was clonal to semi-clonal, with very little genetic diversity within and among subgroups. In contrast, the population structure of P. syringae was also clonal to semi-clonal, but isolates were placed into four main clusters of much higher diversity. Clonality in both species can be explained by a high level of asexual reproduction. The higher diversity in the homothallic P. syringae is likely due to commonly occurring sexual reproduction. One distinct cluster of P. syringae consisted solely of isolates from noncitrus hosts; therefore, the origin of P. syringae in citrus could not be resolved.