Component Discriminant Analysis Research Articles

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.

Genetic variability of maize (Zea mays) germplasm from Iran: genotyping with a maize 600K SNP array and genome-wide scanning for selection signatures

Context Maize (Zea mays L.) is one of the most economically important plants of the cereal family; it has value as human food, livestock feed, and as a component of industrial products. Aims This study focused on genetic diversity and existence of genetic divergence among promising maize inbred lines in Iran. Methods A commercial maize 600K SNP (single-nucleotide polymorphism) array was used to inspect genetic variability among 93 maize inbred lines. Key results The rate of transition mutation was twice as high as transversion mutation, and the density of detected SNPs was greater close to telomere regions of maize chromosomes. Considering the fluctuation of observed, expected and total heterozygosity and fixation index values across maize chromosomes, as well as polymorphism information content values, there is a high level of genetic variability among the studied maize panel. In addition, discriminant analysis of the principal components revealed four subpopulations in which the subpopulation ‘Line’ was distinct from other subpopulations and had no genomic overlap with them. Selection signature analysis revealed 177 regions harbouring 75 genes that differentiate among subgroups. Detected genes had a role in the mitogen-activated protein kinase signalling pathway, spliceosome, protein processing in endoplasmic reticulum, and hormone signal transduction. Conclusions We conclude that remarkable genetic diversity and differentiation exists among the studied maize subpopulations. The most differentiated SNPs among the subpopulations were associated with important biological processing genes and pathways. Implications The findings provide valuable insights for future maize breeding programs through exploitation of heterosis, as well as marker-assisted selection.

Transmission of ceftazidime-avibactam-resistant Escherichia coli among pets, veterinarians and animal hospital environment

Ceftazidime-avibactam (CZA) is a recently approved combination synthetic β-lactamase inhibitor used in human clinical medicine. Cases of CZA resistance in humans have already been reported, but limited research has investigated CZA resistance in pets. This study explored the prevalence and transmission of CZA-resistant Escherichia coli (CZAREC) among pets, their owners, veterinarians, and the environment in animal hospitals. A total of 5,419 clinical samples were collected from dogs and cats, along with samples from the environment (n = 5,843), veterinarians (n = 557), and pet owners (n = 368) in animal hospitals. From these samples, 760 E. coli isolates were obtained, out of which 60 were identified as CZAREC. These included 34 isolates from the environment (9.14 %, n = 372), three from veterinarians (8.11 %, n = 37), and 23 from animals (6.82 %, n = 337). No CZAREC isolates were found in pet owners. The predominant sequence types of CZARECs were ST156 (n = 20), ST410 (n = 19) and ST101 (n = 7). Bayesian analysis revealed six clusters comprising 47 isolates from the hospital environment, pets, and veterinaries, displaying genetic relatedness of less than 100 core genome single nucleotide polymorphisms (cgSNPs) between any two isolates in each cluster. Some CZAREC isolates with high genetic similarity persisted in the same animal hospital for four to six months. Moreover, discriminant analysis of principal components indicated that most isolates from different hosts shared a genetic source in the human/dog/cat merged cluster. Overall, evidence of CZARECs transmission was found among pets, the environment, and veterinarians in animal hospitals. The findings emphasize the importance of monitoring CZARECs in the veterinary clinical setting to ensure the health of both pets and humans.

Validation of sorghum quality control (QC) markers across African breeding lines.

Sorghum [Sorghum bicolor (L.) Moench] is a cereal crop of critical importance in the semi-arid tropics, particularly in Africa where it is second only to maize (Zea mays L.) by area of cultivation. The International Crops Research Institute for the Semi-Arid Tropics sorghum breeding program for Eastern and Southern Africa is the largest in the region and develops improved varieties for target agro-ecologies. Varietal purity and correct confirmation of new crosses are essential for the integrity and efficiency of a breeding program. We used 49 quality control (QC) kompetitive allele-specific PCR single nucleotide polymorphism (SNP) markers to genotype 716 breeding lines. Note that 46 SNPs were polymorphic with the top 10 most informative revealing polymorphism information content (PIC), minor allele frequency (MAF), and observed heterozygosity (Ho ) of 0.37, 0.43, and 0.02, respectively, and explaining 45% of genetic variance within the first two principal components (PC). Thirty-nine markers were highly informative across 16 Burkina Faso breeding lines, out of which the top 10 revealed average PIC, MAF, and Ho of 0.36, 0.39, and 0.05, respectively. Discriminant analysis of principal components done using top 30 markers separated the breeding lines into five major clusters, three of which were distinct. Six of the top 10 most informative markers successfully confirmed hybridization of crosses between genotypes IESV240, KARIMTAMA1, F6YQ212, and FRAMIDA. A set of 10, 20, and 30 most informative markers are recommended for routine QC applications. Future effort should focus on the deployment of these markers in breeding programs for enhanced genetic gain.

The effect of missing data on evolutionary analysis of sequence capture bycatch, with application to an agricultural pest

Sequence capture is a genomic technique that selectively enriches target sequences before high throughput next-generation sequencing, to generate specific sequences of interest. Off-target or ‘bycatch’ data are often discarded from capture experiments, but can be leveraged to address evolutionary questions under some circumstances. Here, we investigated the effects of missing data on a variety of evolutionary analyses using bycatch from an exon capture experiment on the global pest moth, Helicoverpa armigera. We added > 200 new samples from across Australia in the form of mitogenomes obtained as bycatch from targeted sequence capture, and combined these into an additional larger dataset to total > 1000 mitochondrial cytochrome c oxidase subunit I (COI) sequences across the species’ global distribution. Using discriminant analysis of principal components and Bayesian coalescent analyses, we showed that mitogenomes assembled from bycatch with up to 75% missing data were able to return evolutionary inferences consistent with higher coverage datasets and the broader literature surrounding H. armigera. For example, low-coverage sequences broadly supported the delineation of two H. armigera subspecies and also provided new insights into the potential for geographic turnover among these subspecies. However, we also identified key effects of dataset coverage and composition on our results. Thus, low-coverage bycatch data can offer valuable information for population genetic and phylodynamic analyses, but caution is required to ensure the reduced information does not introduce confounding factors, such as sampling biases, that drive inference. We encourage more researchers to consider maximizing the potential of the targeted sequence approach by examining evolutionary questions with their off-target bycatch where possible—especially in cases where no previous mitochondrial data exists—but recommend stratifying data at different genome coverage thresholds to separate sampling effects from genuine genomic signals, and to understand their implications for evolutionary research.

Cryptic sexual reproduction in an emerging Eucalyptus shoot and foliar pathogen

AbstractEucalyptus scab and shoot malformation is an emerging disease and a serious threat to the global plantation forestry industry. The disease appeared in North Sumatra (Indonesia) in the early 2010s and the causal agent was recently described as a novel species, Elsinoe necatrix. Nothing is known regarding its possible origin or why it emerged rapidly to cause a serious local epidemic. To investigate its population biology, we developed 15 polymorphic microsatellite markers as well as mating‐type markers using genome sequences for two E. necatrix isolates. Isolates of the pathogen were collected from different host varieties at four locations in the Lake Toba region of North Sumatra and characterized using these markers. A high level of genotypic diversity was observed for all populations with little to no genetic differentiation between sampling areas. Discriminant analysis of principal components, genotype networks and analysis of molecular variance all showed a lack of population structure and a high level of gene flow among sampling regions. Mating‐type ratios and linkage disequilibrium analyses suggest that sexual recombination is likely to be occurring, although a sexual state has not been found for the pathogen. The results of this study highlight the fact that new genotypes of E. necatrix, probably arising from cryptic sexual recombination, will challenge efforts to manage the disease, and that breeding and selection for tolerance will require substantial host genetic diversity.

Genetic differentiation and bottleneck effects in the malaria vectors Anopheles farauti and Anopheles punctulatus after an LLIN-based vector control program in Papua New Guinea.

Implementation of long-lasting insecticide-treated net (LLIN) programs to control human malaria transmission leads to substantial reductions in the abundance of Anopheles mosquitoes, but the impact on the population genetic structure of the malaria vectors is poorly known, nor has it been investigated in Papua New Guinea, where malaria is highly endemic and where several species of Anopheles have vector roles. Here, we applied Wright's F-statistic, analysis of molecular variance, Bayesian structure analysis, and discriminant analysis of principle components to microsatellite genotype data to analyze the population genetic structure of Anopheles farauti between and within the northern and southern lowland plains and of Anopheles punctulatus within the northern plain of Papua New Guinea after such a program. Bottleneck effects in the two malaria vectors were analyzed using Luikart and Cornuet's tests of heterozygosity. A large, panmictic population of An. punctulatus pre-LLIN program diverged into two subregional populations corresponding to Madang and East Sepik provinces post-LLIN distribution and experienced a genetic bottleneck during this process. By contrast, the An. farauti population existed as two regional populations isolated by mountain ranges pre-LLIN, a genetic structure that persisted after the distribution of LLINs with no further geographic differentiation nor evidence of a genetic bottleneck. These findings show the differential response of populations of different vector species to interventions, which has implications for program sustainability and gene flow.

Assessment of the Genetic Diversity and Structure of the Korean Endemic Freshwater Fish Microphysogobio longidorsalis (Gobioninae) Using Microsatellite Markers: A First Glance from Population Genetics.

Microphysogobio longidorsalis is endemic to South Korea and inhabits small areas of the Namhangang, Bukhangang, and Imjingang Rivers in the Hangang River water system. Endemic species usually are more vulnerable than species with a wide distribution. Notably, there is a lack of basic conservation data for M. longidorsalis. We analyzed 19 microsatellite loci in six populations of M. longidorsalis in South Korea to characterize their population structure and genetic diversity. The genetic diversity of the microsatellites was 0.741-0.779, which is lower than that of other freshwater fishes. The pairwise genetic differentiation of microsatellite (FST) values ranged from 0.007 to 0.041, suggesting low genetic differentiation between the populations. The Jojongicheon stream population (CP) had an effective population size of <100. Therefore, conservation efforts are required to prevent inbreeding depression in M. longidorsalis. Discriminant analysis of principal components showed that the Hangang River water system would be a single management unit (MU). Our findings provide fundamental genetic insights for the formulation of conservation strategies for M. longidorsalis.

Population Genetic Structure of the Rubber Tree Powdery Mildew Pathogen (Erysiphe quercicola) from China.

In order to manage agricultural pathogens, it is crucial to understand the population structure underlying epidemics. Rubber tree powdery mildew, caused by Erysiphe quercicola, is a serious threat to rubber plantations worldwide, especially in subtropical environments including all rubber tree-growing regions in China. However, the population structure of the pathogen is uncertain. In this study, 16 polymorphic microsatellite markers were used to genotype powdery mildew samples from the main rubber tree-growing regions including Yunnan (YN), Hainan (HN), western Guangdong (WG), and eastern Guangdong (EG). YN had higher genotypic diversity (Simpson's indices), genotypic evenness, Nei's gene diversity, allelic richness, and private allelic richness than the other regions. Cluster analysis, discriminant analysis of principal components, pairwise divergence, and shared multilocus genotype analyses all showed that YN differed significantly from the other regions. The genetic differentiation was small among the other three regions (HN, WG, and EG). Analysis of molecular variance indicated that the variability among regions accounted for 22.37% of the total variability. Genetic differentiation was significantly positively correlated (Rxy = 0.772, P = 0.001) with geographic distance. Linkage equilibrium analysis suggested possible occurrence of sexual recombination although asexual reproduction predominates in E. quercicola. The results suggested that although significant genetic differentiation of E. quercicola occurred between YN and the other regions, pathogen populations from the other three regions lacked genetic differentiation.

Performance of the Action Observation-Based Brain-Computer Interface in Stroke Patients and Gaze Metrics Analysis.

Brain-computer interfaces (BCIs) are anticipated to improve the efficacy of rehabilitation for people with motor disabilities. However, applying BCI in clinical practice is still a challenge due to the great diversity of patients. In the current study, a novel action observation (AO) based BCI was proposed and tested on stroke patients. Ten non-hemineglect patients and ten hemineglect patients were recruited. Four AO stimuli were designed, each presenting a decomposed action to complete the reach-and-grasp task. EEG data and eye movement data were collected. Eye movement data was utilized to analyze the reasons for individual differences in BCI performance. Task discriminative component analysis was utilized to perform online target detection. The results showed that the designed AO-based BCI could simultaneously induce steady state motion visual evoked potential (SSMVEP) from the occipital region and sensory motor rhythm from the sensorimotor region in stroke patients. The average online detection accuracy among the four AO stimuli reached 67% within 3 s in the non-hemineglect group, while the accuracy only reached 35% in the hemineglect group. Gaze metrics showed that the average total duration of fixations during the stimulus phase in the hemineglect group was only 1.31 s ± 0.532 s which was significantly lower than that in the non-hemineglect group. The results indicated that hemineglect patients have difficulty gazing at the AO stimulus, resulting in poor detection performance and weak desynchronization in the sensorimotor region. Furthermore, the degree of neglect is inversely proportional to the target detection accuracy in hemineglect stroke patients. In addition, the gaze metrics associated with cognitive load were significantly correlated with the accuracy in non-hemineglect patients. It indicated the cognitive load may affect the AO-based BCI. The current study will expedite the clinical application of AO-based BCI.

Genomic and phenotypic characterization of finger millet indicates a complex diversification history.

Advances in sequencing technologies mean that insights into crop diversification can now be explored in crops beyond major staples. We use a genome assembly of finger millet, an allotetraploid orphan crop, to analyze DArTseq single nucleotide polymorphisms (SNPs) at the whole and sub-genome level. A set of 8778 SNPs and 13 agronomic traits was used to characterize a diverse panel of 423 landraces from Africa and Asia. Through principal component analysis (PCA) and discriminant analysis of principal components, four distinct groups of accessions were identified that coincided with the primary geographic regions of finger millet cultivation. Notably, East Africa, presumed to be the crop's origin, exhibited the lowest genetic diversity. The PCA of phenotypic data also revealed geographic differentiation, albeit with differing relationships among geographic areas than indicated with genomic data. Further exploration of the sub-genomes A and B using neighbor-joining trees revealed distinct features that provide supporting evidence for the complex evolutionary history of finger millet. Although genome-wide association study found only a limited number of significant marker-trait associations, a clustering approach based on the distribution of marker effects obtained from a ridge regression genomic model was employed to investigate trait complexity. This analysis uncovered two distinct clusters. Overall, the findings suggest that finger millet has undergone complex and context-specific diversification, indicative of a lengthy domestication history. These analyses provide insights for the future development of finger millet.

Genetic diversity and breed-informative SNPs identification in domestic pig populations using coding SNPs.

Background: The use of breed-informative genetic markers, specifically coding Single Nucleotide Polymorphisms (SNPs), is crucial for breed traceability, authentication of meat and dairy products, and the preservation and improvement of pig breeds. By identifying breed informative markers, we aimed to gain insights into the genetic mechanisms that influence production traits, enabling informed decisions in animal management and promoting sustainable pig production to meet the growing demand for animal products. Methods: Our dataset consists of 300 coding SNPs genotyped from three Italian commercial pig populations: Landrace, Yorkshire, and Duroc. Firstly, we analyzed the genetic diversity among the populations. Then, we applied a discriminant analysis of principal components to identify the most informative SNPs for discriminating between these populations. Lastly, we conducted a functional enrichment analysis to identify the most enriched pathways related to the genetic variation observed in the pig populations. Results: The alpha diversity indexes revealed a high genetic diversity within the three breeds. The higher proportion of observed heterozygosity than expected revealed an excess of heterozygotes in the populations that was supported by negative values of the fixation index (FIS) and deviations from the Hardy-Weinberg equilibrium. The Euclidean distance, the pairwise FST, and the pairwise Nei's GST genetic distances revealed that Yorkshire and Landrace breeds are genetically the closest, with distance values of 2.242, 0.029, and 0.033, respectively. Conversely, Landrace and Duroc breeds showed the highest genetic divergence, with distance values of 2.815, 0.048, and 0.052, respectively. We identified 28 significant SNPs that are related to phenotypic traits and these SNPs were able to differentiate between the pig breeds with high accuracy. The Functional Enrichment Analysis of the informative SNPs highlighted biological functions related to DNA packaging, chromatin integrity, and the preparation of DNA into higher-order structures. Conclusion: Our study sheds light on the genetic underpinnings of phenotypic variation among three Italian pig breeds, offering potential insights into the mechanisms driving breed differentiation. By prioritizing breed-specific coding SNPs, our approach enables a more focused analysis of specific genomic regions relevant to the research question compared to analyzing the entire genome.

Population genetics of queen conch, Aliger gigas (Linnaeus, 1758) (Gastropoda: Strombidae) at the Cuban island platform

Abstract The queen conch, Aliger gigas is a large marine gastropod mollusc that inhabits shallow seagrass meadows and sandplain habitats throughout the Caribbean. Owing to overfishing and degradation of the environment, it has become an endangered species in most of its habitat. Research on Cuban populations of A. gigas is scarce and mostly focused on conch exploitation. The present study assesses, for the first time, the genetic diversity and population structure of A. gigas from six locations on the Cuban platform, using five microsatellite loci. At most of the sampled locations, the observed heterozygosity was lower than expected and the FIS value was significantly positive, both of which suggest inbreeding. Also, we found evidence of bottlenecks for two of the locations with a deficit of heterozygotes. Although statistically significant, only 1.66% of the total variance was explained by genetic differentiation among populations, and discriminant analysis of principal components showed different degrees of overlapping between all locations. Accordingly, the results showed that there is an extensive and symmetrical exchange of genetic information. Sparse non-negative matrix factorization analysis determined the existence of three ancestral populations admixed across the sampled locations. Thus, our results suggest that A. gigas from the Cuban island platform could be a unique population, which is relevant for management and conservation strategies.