Genotypic Diversity Research Articles

Characterization, Antibiotic Susceptibility, and Clonal Analysis of Carbapenem-Resistant Klebsiella pneumoniae From Different Clinical Cases.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is recognized for its great ability to resist prescription drugs and its association with severe infections in humans. This study was designed to evaluate the characteristic resistance spectrum, to characterize the implicated carbapenem-resistant genes (CRGs), and to determine the extent of genetic diversity among Klebsiella pneumoniae isolates from human clinical cases in Duhok province. Methodology: The VITEK-2 system was used to investigate the phenotypic antibiotic susceptibility of 23 K. pneumoniae isolated from distinct human clinical situations, multiplex PCR was used to assign the key common carbapenem-resistant genes (IMP, OXA48-like, bla-NDM, and KPC) in phenotypically carbapenem-resistant isolates, and the Enterobacterial Repetitive Intergenic Consensus Polymerase Chain Reaction (ERIC-PCR) assay was utilized to ascertain the clonal associations among those isolates. Phenotypic resistance analysis revealed high resistance rates to various antibiotics, with all isolates exhibiting multidrug resistance (MDR). Coronavirus disease 2019 (COVID-19) patient isolates demonstrated significantly higher resistance compared to other sources. In addition, all isolates showed complete phenotypic resistance to carbapenems, PCR screening for CRGs identified blaOXA-48 as the predominant gene, present in all isolates. Genetic fingerprinting revealed diverse genotypes, with COVID-19 patient isolates exhibiting high similarity, contrasting with maximum diversity in non-COVID-19 clinical isolates.

Persistence Over Millennia Through Extreme Clonal Longevity: Phylogenomic Insight Into History of One of the World's Rarest Plant Species

ABSTRACTAimThe evolutionary history of European alpine plant species with medium to large geographical ranges is relatively well explored. Here, we investigate the genetic structure and diversity of an extremely narrow endemic and one of the world's rarest plants.LocationEastern Carpathians, Romania.TaxonAndryala laevitomentosa (Asteraceae), an evolutionarily isolated herb species with a worldwide range limited to five micropopulations distributed along a 1.8 km long mountain ridge.MethodsWe used three plastid loci, nuclear ribosomal ITS and genome‐wide, mostly nuclear 26,272 Single‐Nucleotide Polymorphism (SNPs) obtained from RAD‐seq data. We assessed haplotype and genotype diversity, dated the resulting phylogeographic structure, quantified seed production and inferred vegetative propagation.ResultsMaternally inherited plastid markers and nuclear genomic data revealed a concordant pattern: (i) limited genetic diversity, with seven cpDNA haplotypes and 11 RAD‐seq multilocus genotypes; (ii) a strong geographic structure corresponding to spatially isolated genets (clones). The species is likely of early Pleistocene origin (c. 2 Mya), and the estimated age of individual clones varied from c. 24 to 64 Kya. The average seed set assessed over 3 years was only 0.4%. However, the species reproduces vegetatively by axillary and adventitious rosettes formed on rhizomes and roots, respectively.Main ConclusionsThe strong trade‐off between sexual and vegetative reproduction explains not only a deep and ancient phylogeographic structure but also the rarity of the species. Its survival depends almost entirely on vegetative reproduction. The genets of A. laevitomentosa are amongst the oldest clones ever documented in angiosperms. The persistence of these clones in situ for tens of thousands of years suggests an exceptional ability of this species to adapt to major climatic oscillations throughout the Pleistocene and Holocene and challenge our perception of the extent of resilience in plants.

A new dimension of leaf economic spectrum: temporal instability of relationships among genotypes.

Leaf economic spectrum (LES) relationships have been studied across many different plant lineages and at different organizational scales. However, the temporal stability of the LES relationships is largely unknown. We used the wild blueberry system with high genotypic diversity to test whether trait-trait relationships across genotypes demonstrate the same LES relationships found in the global database (GLOPNET) and whether they are stable across years. We studied leaf structure, photosynthesis, and leaf nutrients for 16 genotypes of two wild blueberry species semi-naturally grown in a common farm in Maine, USA, across 4 yr. We found substantial variation in leaf structure, physiology, and nutrient traits within and among genotypes, as well as across years in wild blueberries. The LES trait-trait relationships (covariance structure) across genotypes were not always found in all years. The trait syndrome of wild blueberries was shifted by changing environmental conditions over the years. Additionally, traits in 1 yr cannot be used to predict those of another year. Our findings show that LES generally holds among genotypes but is temporally unstable, stressing the significant influence of trait plasticity in response to fluctuating environmental conditions across years, and the importance of temporal dimensions in shaping functional traits and species coexistence.

Natural variation in the chickpea metabolome under drought stress.

Chickpea is the world's fourth largest grown legume crop, which significantly contributes to food security by providing calories and dietary protein globally. However, the increased frequency of drought stress has significantly reduced chickpea production in recent years. Here, we have performed a field experiment with 36 diverse chickpea genotypes to evaluate grain yield, photosynthetic activities and molecular traits related to drought stress. For metabolomics analysis, leaf tissue was collected at three time points representing different pod-filling stages. We identified L-threonic acid, fructose and sugar alcohols involved in chickpea adaptive drought response within the mid-pod-filling stage. A stress susceptibility index for each genotype was calculated to identify tolerance capacity under drought, distributing the 36 genotypes into four categories from best to worst performance. To understand how biochemical mechanisms control different traits for genetic improvement, we performed a differential Jacobian analysis, which unveiled the interplay between various metabolic pathways across three time points, including higher flux towards inositol interconversions, glycolysis for high-performing genotypes, fumarate to malate conversion, and carbon and nitrogen metabolism perturbations. Metabolic GWAS (mGWAS) analysis uncovered gene candidates involved in glycolysis and MEP pathway corroborating with the differential biochemical Jacobian results. Accordingly, this proposed data analysis strategy bridges the gap from pure statistical association to causal biochemical relations by exploiting natural variation. Our study offers new perspectives on the genetic and metabolic understanding of drought tolerance-associated diversity in the chickpea metabolome and led to the identification of metabolic control points that can be also tested in other legume crops.

What in Earth? Analyses of Canadian soil populations of Aspergillus fumigatus.

Aspergillus fumigatus is a globally distributed mold and a major cause of opportunistic infections in humans. Because most infections are from environmental exposure, it is critical to understand environmental populations of A. fumigatus. Soil is a major ecological niche for A. fumigatus. Here, we analyzed 748 soil isolates from 21 locations in six provinces and one territory in Canada. All isolates were genotyped using nine microsatellite markers. Due to small sample size and/or close proximities for some local samples, these isolates were grouped into 16 local geographic and ecological populations. Our results indicated high allelic and genotypic diversities within most local and provincial populations. Interestingly, low but statistically significant genetic differentiations were found among geographic populations within Canada, with relatively similar proportions of strains and genotypes belonging to two large genetic clusters. In Hamilton, Ontario, and Vancouver, BC, where two and three ecological populations were analyzed, respectively, we found limited genetic difference among them. Most local and provincial populations showed evidence of both clonality and recombination, with no population showing random recombination. Of the 748 soil isolates analyzed here, two were resistant to triazole antifungals. We discuss the implications of our results to the evolution and epidemiology of A. fumigatus.

Genetic diversity study of bacterial wilt-tolerant bell pepper (Capsicum annuum) genotypes using cluster and principal component analysis

The present study was carried out during summer and rainy (kharif) seasons of 2019 and 2020 at the research farm of Himachal Pradesh Krishi Vishvavidyalaya, Palampur, Himachal Pradesh to study the genetic diversity among 43 bacterial wilt tolerant genotypes of bell pepper (Capsicum annuum L. var. grossum Sendt), focusing on 12 quantitative and 3 qualitative traits along with disease resistance. The experiment was laid out in a randomized complete block design (RCBD) with 3 replications. Following hierarchical cluster analysis, the 43 unique genotypes were categorized into 5 separate clusters. Cluster I consisted of maximum number of genotypes (39), followed by clusters II, III, IV and V, each having only one genotype. The greatest inter-cluster distance was observed between cluster II and V (3090.70), while the smallest distance was noted between cluster II and III (1299.21). Cluster I displayed the greatest intra-cluster distance (803.75), while clusters II, III, IV and V showed the lowest distances (0.00). The primary contributors to genetic divergence were found to be capsanthin content (23.4%), followed by ascorbic acid (21.4%), fruit length (12.5%), plant survival (11.1%) and marketable fruit yield/plant (10.9%). Principal component analysis indicated that the initial six principal components, each possessing an eigen value surpassing one, jointly accounted for 70.62% of the total observed variability. PCA biplot revealed that, the traits namely, marketable fruits/plant, average fruit weight, harvest duration and plant height were the major yield contributing traits. The results underscored the importance of genetic characterization and the selection of diverse genotypes for hybridization, facilitating the development of improved bell pepper cultivars with enhanced productivity and quality.

Host genetics shapes Pinus radiata phenotypic plasticity under drought and is linked with root-associated soil microbiome shifts

Under current and future climate scenarios, identifying drought-resistant tree species, tree genotypes, and beneficial interactions between trees and their root-associated soil microbiomes is becoming more imperative for maintaining tree health and sustaining increasingly vulnerable forests. We designed a genotype x soil x watering x time glasshouse experiment using Pinus radiata as a model tree to assess the magnitude of the effect of host genotype and root-associated soil microbiome on the phenotype response (functional traits, metabolome, nutrients) under drought. We identified the shikimate pathway as a critical metabolic pathway for Pinus radiata drought resistance, with the shikimic acid intermediate being one of the strongest drought signals, besides downstream metabolites such as flavonoids and phenylpropanoids. Overall, we found that the host genotype diversity was a key actor in the observed phenotype response of P. radiata to drought. In contrast, the microbiome was attributed a minor supporting role. Contrary to our hypothesis, dry soils could not support drought-sensitive genotypes under drought stress. Instead, the drought-resistant genotype was able to leverage locally adaptive bacteria to match local selective drought pressures at the expense of tree growth. This highlights the significance of finding specific combinations of tree genotype and mutualistic microbial communities that would thrive under future environmental pressures.

Megaselia scalaris and Senotainia tricuspis Infesting Apis mellifera: Detection by Quantitative PCR, Genotyping, and Involvement in the Transmission of Microbial Pathogens.

The Megaselia scalaris and Senotainia tricuspis parasitoid flies of the honeybee Apis mellifera were found to infest apiaries of different European and Mediterranean countries but their prevalence and impact on apiary health are little known. Therefore, in this study, quantitative PCR (qPCR)-based methods were developed for their rapid detection directly in hive matrices. The newly developed qPCR assays were targeted at the mitochondrial cytochrome oxidase subunit I (COI) gene for the M. scalaris and the cytochrome B (cytB) gene for the S. tricuspis. The tests were preliminarily applied to 64 samples of adult honeybees and hive debris collected in the Abruzzo and Molise regions, Central Italy, and the Republic of Kosovo showing that both flies occur in the two countries and more frequently in Italy. The positive apiaries in Italy were re-sampled by capturing viable forager bees and isolating emerging flies to carry out the genotyping and analyses aimed at defining if these flies can transmit honeybee pathogens. Genotyping based on the COI and cytB gene sequencing for M. scalaris and S. tricuspis, respectively, identified one S. tricuspis genotype and diverse genotypes of M. scalaris highly similar to those from distant countries. Some fly isolates harbored the DNA or RNA of honeybee microbial pathogens Paenibacillus larvae, deformed wing viruses A and B (DWVA and B), black queen cell virus (BQCV), chronic paralysis virus (CBPV), and Nosema ceranae. The results indicated that these parasites should be efficiently controlled in apiaries by using rapid detection methods to facilitate the large screening studies and early detection.

Extensive Genomic Rearrangement of Catalase-Less Cyanobloom-Forming Microcystis aeruginosa in Freshwater Ecosystems.

Many of the world's freshwater ecosystems suffer from cyanobacteria-mediated blooms and their toxins. However, a mechanistic understanding of why and how Microcystis aeruginosa dominates over other freshwater cyanobacteria during warmer summers is lacking. This paper utilizes comparative genomics with other cyanobacteria and literature reviews to predict the gene functions and genomic architectures of M. aeruginosa based on complete genomes. The primary aim is to understand this species' survival and competitive strategies in warmer freshwater environments. M. aeruginosa strains exhibiting a high proportion of insertion sequences (~ 11%) possess genomic structures with low synteny across different strains. This indicates the occurrence of extensive genomic rearrangements and the presence of many possible diverse genotypes that result in greater population heterogeneities than those in other cyanobacteria in order to increase survivability during rapidly changing and threatening environmental challenges. Catalase-less M. aeruginosa strains are even vulnerable to low light intensity in freshwater environments with strong ultraviolet radiation. However, they can continuously grow with the help of various defense genes (e.g., egtBD, cruA, and mysABCD) and associated bacteria. The strong defense strategies against biological threats (e.g., antagonistic bacteria, protozoa, and cyanophages) are attributed to dense exopolysaccharide (EPS)-mediated aggregate formation with efficient buoyancy and the secondary metabolites of M. aeruginosa cells. Our review with extensive genome analysis suggests that the ecological vulnerability of M. aeruginosa cells can be overcome by diverse genotypes, secondary defense metabolites, reinforced EPS, and associated bacteria.

Exploring genetic variability in fodder quality of forage sorghum in the North – Eastern regions of India

This study investigated genetic variability, character association, and genetic diversity in ninety-five forage sorghum genotypes, evaluated using a randomized block design for seven fodder quality traits. Analysis of variance revealed significant differences among genotypes for all traits. Genotypes such as G90 (424B), G23 (334B), G87 (CSV21F), G76 (330B), and G45 (373B) exhibit desirable fodder quality traits. Notably, G90 (424B) and G47 (NSS5B) stand out for their superior green forage yield per plant and fodder quality, making them prime candidates for varietal development programs. Crude protein emerged as a crucial selection factor for fodder quality. Green forage yield per plant showed minimal association with the other quality traits. A strong positive correlation was observed among in vitro organic matter digestibility, metabolic energy, crude protein, and ash content. D2 analysis identified five clusters, with genotypes from clusters V and IV recommended for crossing to produce superior transgressive segregants for fodder quality. Acid detergent fibre, crude protein, and ash content significantly contributed to genetic divergence. Considering these selected traits and genotypes, they could be invaluable in future sorghum forage breeding programs aimed at enhancing fodder quality traits. Keywords: Correlation, genetic diversity, Path analysis, Sorghum Fodder quality

Multivariate analysis in chickpea genotypes under timely sown condition

Abstract Yield, a multifaceted trait influenced by genetic and environmental factors, requires a comprehensive assessment beyond emphasizing only on yield alone. Thus, understanding the intricate relationship between yield and its associated traits across diverse chickpea genotypes is essential. The current investigation was undertaken at the Breeder seed production unit, JNKVV, Jabalpur, Madhya Pradesh, during the 2021-22 cropping season. Significant variations were found by analysis of variance (ANOVA) among the 40 genotypes under study, indicating substantial variability. Post hoc DMRT analysis further confirmed notable genetic diversity across all traits. Regression and Principal component analysis highlighted the significance of optimizing biological yield per plant, effective pods, total number of pods, and secondary branches to enhance grain yield. Strategic selection prioritizing these traits can facilitate the development of high-yielding chickpea varieties with enhanced agronomic characteristics. This analysis identified five principal components explaining 80.74% of genotypic variability. Ultimately, the genotypes ICCV 211210, RVG-204, and ICCV 211206 emerged as promising based on PC scores. Keywords: Chickpea, DMRT, Regression, PCA, Yield

Intraspecific diversity of Erwinia amylovora strains from northern Algeria

BackgroundFire blight, caused by Erwinia amylovora, is the most destructive bacterial disease affecting plants in the Rosaceae family, leading to significant economic losses. In Algeria, this disease has been reported since 2010. This study aimed to investigate the origin of fire blight in Algeria, in order to increase knowledge of the epidemiology of this serious disease and contribute to its management. A comprehensive characterization of 18 E. amylovora isolates recovered from northern Algeria between 2016 and 2021 to evaluate their phenotypical and genotypical diversity was conducted.ResultsPhenotypic differences, particularly in growth kinetics, virulence, and fatty acid profiles, allowed differentiation of strains into five groups, possibly indicating distinct introduction events. Genetic characterization revealed that only one strain lacked the ubiquitous plasmid pEA29, which is correlated with reduced virulence, while none harbored the pEI70 plasmid. Phylogenetic analysis using concatenated sequences of the recA, groEL, rpoS, ams, and hrpN genes grouped Algerian strains with those from a broadly prevalent clade. CRISPR genotyping identified a novel CR1 pattern and three genotypes, two of them previously unreported.ConclusionsThis study represents the first phenotypic, genetic, and phylogenetic investigation of E. amylovora strains in the region, and provides valuable information on the possible pathways of the introduction of this fire blight pathogen in northern Africa. The findings suggest one or more introduction events from a common ancestor, likely originating in northern Italy, followed by dispersal in various regions of Algeria.

Principal Component Analysis in rice (Oryza sativa L.) varieties for three seasons in Annamalai Nagar, an east coast region of Tamil Nadu

Principal component analysis (PCA) was used to assess genetic variability and identify key yield-contributing traits among 50 rice genotypes evaluated over three seasons under saline conditions. The study aimed to select promising donor lines for developing salt-tolerant, high-yielding cultivars suitable for coastal regions. PCA identified three principal components (PCs) that explained 73.19%, 70.34%, and 64.81% of the total genetic variation in seasons 1, 2 and 3, respectively. Key plant attributes, such as grain yield per plant, panicle grain density, total tiller number, and productive tiller count, showed significant positive associations with PC1 across various growth stages, underscoring their crucial role in explaining the genetic diversity among the genotypes. Plant height, panicle length, and hundred-grain weight also emerged as major contributors to variation. The PCA biplots consistently demonstrated positive correlations between grain yield and traits like panicle length, hundred-grain weight, and tillering ability. In contrast, days to 50% flowering exhibited a negative association with yield. Genotypes G10, G49, G36, G41, G9, G4, G22, and G21 displayed favourable combinations of grain yield per plant, identifying them as potential donor lines for breeding programs aimed at improving rice yield and associated agronomic traits. This comprehensive PCA analysis highlights the effectiveness of the approach in capturing genotypic diversity and guiding the selection of promising germplasm for targeted trait improvement in rice.

Ecological distribution and phylogenetic diversity of measles virus genotypes in West Africa, 2001 to 2020

IntroductionMeasles remains a significant threat to public health in developing countries, particularly among children under the age of 5. A pivotal aspect of the measles eradication initiative involves the genetic characterization of wild-type viruses to better understand transmission patterns and inform vaccination strategies. ObjectiveThis study aims to investigate the ecology and genotype diversity of the measles virus in West Africa from 2001 to 2020, utilizing available sequence data from the GenBank. MethodologyWe conducted a comprehensive analysis using maximum-likelihood phylogenetics, focusing on the N450 fragment from measles virus isolates found in West Africa between 2001 and 2020. Additionally, pairwise sequence comparison analysis was carried out to determine the evolutionary divergence of various genotypes in West Africa and their genetic distance from vaccine strains. ResultsOur findings indicate that over the past 2 decades, B3, D3, and D8 isolates have been circulating in various West African countries. Notably, B3 isolates have been identified as the primary contributors to endemic transmission, as evidenced by the concurrent presence of the same isolate in different countries within the subregion. Furthermore, our analysis reveals a significant shift in the circulation of D3 and D8 isolates, which were originally reported exclusively in New Guinea over 15 years ago but are now dominated by the B3 genotype. ConclusionOver the past 2 decades, B3, D3, and D8 measles virus genotypes have circulated in 10 West African countries. Particularly, B3.1 isolates currently dominate, especially in Nigeria, indicating endemic transmission. However, despite the informative value of N450, complete genome sequencing data is highly needed to accurately understand the evolutionary dynamics of the measles virus in West Africa.

Study of Genetic Diversity of Aromatic Rice Genotypes Using Random Amplified Polymorphic DNA Markers

The study of genetic variation in aromatic rice is necessary for enhancing and preserving its genetic makeup. In this study, we amplified four Random Amplified Polymorphic DNA (RAPD) markers from the genomes of 11 different aromatic rice genotypes in order to evaluate the genetic variation and relatedness in aromatic rice. The genotypes were collected from different sources- five of which were obtained from the Bangladesh Rice Research Institute, one from the Bangladesh Institute of Nuclear Agriculture, and the remaining five were local genotypes. In RAPD profiling, twenty-seven of the thirty-six bands that were generated by the four primers were polymorphic, resulting in an estimated average polymorphism of 47.22 percent. The average value of the polymorphic information content was 0.309 with a range from 0.165 to 0.456, indicating that the primers were effective to detect genetic diversity between the genotypes. The genetic diversity and Shannon information index across all of the genotypes and primers were 0.176 and 0.260, respectively, which indicated that there was a certain amount of genetic variation in the studied aromatic rice genotypes. Kalizira and Binadhan-9 genotypes had the smallest genetic distance (0.057), while it was the highest (0.406) between the BRRI dhan 34 and BRRI dhan 50. The genotype pairs BRRI dhan 38 vs BRRI dhan 34, BRRI dhan 38 and Kalizira, and Zirakatari and Kalizira had also a higher level (0.365) of genetic distances. The genotypes were grouped into two main clusters in the UPGMA dendrogram. Cluster I included five genotypes: BRRI dhan 34, Basmoti, Atashail, Kalizira, and Binadhan-9. Cluster II included remaining six genotypes: BR5, BRRI dhan 38, BRRI dhan 50, Uknimodhu, BRRI dhan 37, and Zirakatari. Documentation of the genetic variation and relatedness among the aromatic rice genotypes under this investigation could be useful for future research into the development of aromatic rice and related fields. J Bangladesh Agril Univ 22(3): 277-284, 2024

A deep-learning model for characterizing tumor heterogeneity using patient-derived organoids

Genotypic and phenotypic diversity, which generates heterogeneity during disease evolution, is common in cancer. The identification of features specific to each patient and tumor is central to the development of precision medicine and preclinical studies for cancer treatment. However, the complexity of the disease due to inter- and intratumor heterogeneity increases the difficulty of effective analysis. Here, we introduce a sequential deep learning model, preprocessing to organize the complexity due to heterogeneity, which contrasts with general approaches that apply a single model directly. We characterized morphological heterogeneity using microscopy images of patient-derived organoids (PDOs) and identified gene subsets relevant to distinguishing differences among original tumors. PDOs, which reflect the features of their origins, can be reproduced in large quantities and varieties, contributing to increasing the variation by enhancing their common characteristics, in contrast to those from different origins. This resulted in increased efficiency in the extraction of organoid morphological features sharing the same origin. Linking these tumor-specific morphological features to PDO gene expression data enables the extraction of genes strongly correlated with intertumor differences. The relevance of the selected genes was assessed, and the results suggest potential applications in preclinical studies and personalized clinical care.

Effectiveness and Genetic Control of Trichoderma spp. as a Biological Control of Wheat Powdery Mildew Disease.

Wheat powdery mildew (WPM) is one of the most devasting diseases that affects wheat yield worldwide. Few efforts have been made to control such a serious disease. An effective way to control WPM is urgently needed. Biological control is an effective way to control plant diseases worldwide. In this study, the efficiency of three different Trichoderma spp. in controlling WPM at the seedling growth stage was tested using 35 highly diverse wheat genotypes. Highly significant differences were found in WPM resistance among the four treatments, confirming the efficiency of Trichoderma in controlling WPM. Of the three species, T. asperellum T34 (T34) was the most effective species in controlling WPM, as it reduced the symptoms by 50.56%. A set of 196 wheat genotypes was used to identify the genetic control of the WPM resistance induced by T34. A total of 39, 27, and 18 gene models were identified to contain the significant markers under Pm, T34, and the improvement in powdery mildew resistance due to T34 (T34_improvement) conditions. Furthermore, no gene model was common between T34 and Pm, suggesting the presence of completely different genetic systems controlling the resistance under T34 and Pm. The functional annotation and biological process pathways of the detected gene models confirm their association with the normal and induced resistance. This study, for the first time, confirms the efficiency of T34 in controlling WPM and provides a deep understanding of the genetic control of induced and normal resistance to WPM.

Rare occurrence of Blastocystis in sea turtles and insects (cockroaches, houseflies, and crickets) from several states in Peninsular Malaysia.

Blastocystis a single-celled eukaryotic protist, is known to inhabit the intestines of various hosts, including humans, and has been implicated in a wide spectrum of symptoms, ranging from gastrointestinal issues to skin disorders, thereby establishing its status as an emerging infectious agent. In this study, the prevalence of Blastocystis infection was investigated in insects, including cockroaches, houseflies, and crickets, as well as sea turtles. Additionally, the genotypic characteristics of the isolated Blastocystis strains were examined, and the evolutionary relationships between Blastocystis species found in sea turtles, and animals/humans were determined. Microscopic techniques and molecular methods were utilized in this study. The results showed that four out of 90 insects (4.44%) and one out of 13 sea turtles (7.7%) were infected by Blastocystis. Furthermore, detailed observations revealed the presence of characteristic morphological features, such as vacuolar forms in the cockroach, cricket and sea turtle samples and binary fission from cockroach samples, indicative of Blastocystis' mode of reproduction. While the ST8 of Blastocystis in sea turtles were successfully identified, no subtyping was achieved for the infected insects. This study not only establishes the occurrence of Blastocystis infection in sea turtles but also uncovers its ability to infect insects, suggesting a potential reservoir role for these organisms. Overall, this research emphasizes the significance of comprehending the prevalence, genotypic diversity, and evolutionary relationships of Blastocystis across various hosts. Such insights are instrumental in developing effective control measures and public health interventions to mitigate the associated symptoms and prevent future outbreaks.

Heat stress tolerance in wheat seedling: Clustering genotypes and identifying key traits using multivariate analysis

Elevated atmospheric heat is considered as one of the bottlenecks for global wheat production. Screening potential wheat genotypes against heat stress and selecting some suitable indicators to assist in understanding thermotolerance could be crucial for sustaining wheat cultivation. Accordingly, 80 diverse bread wheat genotypes were evaluated in controlled lab condition by imposing a week-long heat stress (35/25 °C D/N) at the seedling stage. The response of heat stress was evaluated using multivariate analysis techniques on 20 morpho-physiological traits. Results showed significant variations in the studied traits due to the imposition of heat stress. Eleven seedling traits that contributed significantly to the genotypic variability were identified using principal component analysis (PCA). A substantial correlation between most of the selected seedling attributes was observed. Hierarchical cluster analysis identified three distinct clusters among the tested wheat genotypes. Cluster 1, consisting of 33 genotypes, exhibited the highest tolerance to heat stress, followed by Cluster 2 (18 genotypes) with moderate tolerance and Cluster 3 (29 genotypes) showing susceptibility. Linear discriminant analysis (LDA) approved that nearly 93 % of the wheat genotypes were appropriately ascribed to each cluster. The squared distance analysis confirmed the distinct nature of the clusters. Using multi-trait genotype-ideotype distance index (MGIDI), all 12 identified tolerant genotypes (BG-30, BD-468, BG-24, BD-9908, BG-32, BD-476, BD-594, BD-553, BD-488, BG-33, BD-495, and AS-10627) originated from Cluster 1. Selection gain in MGIDI analysis, broad-sense heritability, and multiple linear regression analysis together identified shoot and root dry and fresh weights, chlorophyll contents (a and total), shoot tissue water content, root-shoot dry weight ratio, and efficiency of photosystem II (PS II) as the most vital discriminatory factors explaining heat stress tolerance of 80 wheat genotypes. The identified genotypes with superior thermotolerance would offer resourceful genetic tools for breeders to improve wheat yield in warmer regions. The traits found to have greater contribution in explaining heat stress tolerance will be equally important in prioritizing future research endeavors.

Assessing genotypic diversity by multivariate analysis and predicting useful selection ranges using decision tree in soybean (Glycine max L.)

The existence of sufficient genetic variability and knowing the suitable selection criterion ranges are indispensable requirements of breeding studies. This study aimed to explore genetic diversity in ten F2 populations (heterozygous–heterogeneous), five parents, and three commercial check cultivars by multivariate methods and to predict useful selection ranges using a decision tree model for further breeding studies. Hybridizations were made in 2019, F1 populations were grown, and F2 seeds were obtained in 2020. Genotypes were grown according to an Augmented Randomized Complete-Block Design in 2021 at Aydın Adnan Menderes University Faculty of Agriculture. Results revealed considerable genetic diversity and transgressive segregation in key characteristics across the F2 populations. Seed yields of F2 plants are higher than those of the parents. The seed protein and oil content of the F2 plants were not different from the parents and commercial checks. Higher phenotypic than genotypic variance indicated a high influence of environment on the inheritance of all studied characteristics. The highest broad heritability was observed in the number of shattered pods per plant (94.81 %) and the lowest in infertile pods per plant (2.16 %). Seed yield showed a significant and positive genotypic correlation with the number of fertile pods per plant (0.61**) and a significant negative association with the number of fertile branches per plant (−0.53**). Principal component analysis (PCA) of 14 quantitative characteristics showed that soybean genotypes separated by the first four components contributed 71.12 % of total genetic variation, with important yield-attributing characteristics present in PC1 and PC3, while important seed quality characteristics were noted in PC2. The decision tree model indicated that genotypes with high yield and optimum quality could be obtained by selecting the number of fertile pods 87–119 per plant and a hundred-seed weight greater than 14.55 g.