Search Results (469)

Tartary buckwheat is an important medicinal and edible crop known for its significant health benefits to humans. While numerous Tartary buckwheat germplasm resources have been collected in China, the genetic diversity and core germplasm resources remain largely unclear. The aim of this work was to analyze the genetic variability and construct a core germplasm collection of Tartary buckwheat. Fifteen highly polymorphic SSR markers were used to investigate 659 Tartary buckwheat accessions. A total of 142 alleles were marked, with an average of 9.47 alleles per locus. Genetic variability analysis revealed that these collected accessions exhibit high genetic diversity and can be classified into seven subgroups. Among wild, landrace, and improved accessions, the wild accession showed the highest genetic diversity, while no significant genetic variation was observed between the landrace and improved accessions. Based on genetic diversity and population structure analyses, a core germplasm collection containing 165 accessions (47 wild, 92 landrace, and 26 improved) was constructed, ensuring high genetic diversity and good representation. This study not only highlighted the genetic differences among Tartary buckwheat accessions, but also provided insights into the population structure and the development of a core germplasm collection. It provided important references for the conservation of genetic diversity and the genetic improvement of Tartary buckwheat. Full article

Background: The Signal Transducer and Activator of Transcription 1 (STAT1) gene is an essential component of the JAK-STAT signaling pathway. This pathway plays a pivotal role in the regulation of different cellular processes, including immune responses, cell growth, and apoptosis. Mutations in the STAT1 gene contribute to a variety of immune system dysfunctions. Objectives: We aim to identify disease-susceptible single-nucleotide polymorphisms (SNPs) in STAT1 gene and predict structural changes associated with the mutations that disrupt normal protein–protein interactions using different computational algorithms. Methods: Several in silico tools, such as SIFT, Polyphen v2, PROVEAN, SNAP2, PhD-SNP, SNPs&GO, Pmut, and PANTHER, were used to determine the deleterious nsSNPs of the STAT1. Further, we evaluated the potentially deleterious SNPs for their effect on protein stability using I-Mutant, MUpro, and DDMUT. Additionally, we predicted the functional and structural effects of the nsSNPs using MutPred. We used Alpha-Missense to predict missense variant pathogenicity. Moreover, we predicted the 3D structure of STAT1 using an artificial intelligence system, alphafold, and the visualization of the 3D structures of the wild-type amino acids and the mutant residues was performed using ChimeraX 1.9 software. Furthermore, we analyzed the structural and conformational variations that have resulted from SNPs using Project Hope, while changes in the biological interactions between wild type, mutant amino acids, and neighborhood residues was studied using DDMUT. Conservational analysis and surface accessibility prediction of STAT1 was performed using ConSurf. We predicted the protein–protein interaction using STRING database. Results: In the current study, we identified six deleterious nsSNPs (R602W, I648T, V642D, L600P, I578N, and W504C) and their effect on protein structure, function, and stability. Conclusions: These findings highlight the potential of approaches to pinpoint pathogenic SNPs, providing a time- and cost-effective alternative to experimental approaches. To the best of our knowledge, this is the first comprehensive study in which we analyze STAT1 gene variants using both bioinformatics and artificial-intelligence-based model tools. Full article

Background/Objectives: The increasing pressure from pathogens and parasites on Apis mellifera populations is resulting in significant colony losses. It is desirable to identify resistance-associated single-nucleotide polymorphisms (SNPs) and their variability for the purpose of breeding resilient honeybee lines. This study examined the genetic diversity of 13 SNPs previously studied for associations with various resistance-providing traits, including six linked to Varroa-specific hygiene, five linked to suppressed mite reproduction, one linked to immune response, and one linked to chalkbrood resistance. Methods: Genotyping was performed using a novel SNaPshot genotyping panel designed for this study. The sample pool consisted of 308 honeybee samples in total, covering all 77 administrative districts of the Czech Republic. Results: All examined loci were polymorphic. The frequency of positive alleles in our population is medium to low, depending on the specific SNP. An analysis of genotype frequencies revealed that most loci exhibited the Hardy–Weinberg equilibrium. A comparison of the allele and genotype frequencies of the same locus between samples from hives and samples from flowers revealed no significant differences. The genetic diversity, as indicated by the heterozygosity values, ranged from 0.05 to 0.50. The fixation index (F) was, on average, close to zero, indicating minimal influence of inbreeding or non-random mating on the genetic structure of the analyzed samples. Conclusions: The obtained results provide further insights into the genetic variation of SNPs associated with the immune response and resistance to pathogens in honeybee populations in the Czech Republic. This research provides a valuable foundation for future studies of honeybee diversity and breeding. Full article

Convolvulus persicus L. is an endangered narrow-range taxon, characteristic of the habitats along the coastal regions of the Caspian and the Black Seas. The aims of our research were to update the actual distribution area and the genetic evaluation of three representative populations from the western coastline of the Black Sea located in Sulina, Agigea, and Durankulak. ISSR amplifications were used to assess the genetic intrapopulation diversity and the genetic differentiation among populations. The average genetic polymorphism was 57.8 ± 16.03%. The intrapopulation genetic diversity parameters indicated that the Agigea population exhibits a higher genetic diversity, with this small population being part of the Agigea Marine Dunes Reserve. Although the interpopulation genetic distance was reduced (0.176–0.223) and the distribution of the total variation (AMOVA) was 57% within the population and 43% among the populations, the interpopulation genetic differentiation (PhiPT) was high (0.428, p < 0.001), probably due to the large geographical distances between the remaining populations. The populations’ genetic structures showed a lower genetic distance between the Agigea and Sulina samples. The clonability test supported the vegetative multiplication on the Durankulak and Sulina beaches. Our results showed that the genetic diversity and the distance among the populations in C. persicus were influenced by habitat conditions, destruction, and fragmentation, but also by conservation measures. Full article

Many important plants’ agronomic traits, such as crop yield, stress tolerance, and other traits, are controlled by multiple genes and exhibit complex inheritance patterns. Traditional breeding methods often encounter difficulties in dealing with these traits due to their complexity. However, genomic selection (GS), which utilizes high-density molecular markers across the entire genome to facilitate selection in breeding programs, excels in capturing the genetic variation associated with these traits. This enables more accurate and efficient selection in breeding. The traditional crop genome selection model, based on statistical methods or machine learning models, often treats samples as independent entities while neglecting the abundance latent relational information among them. Consequently, this limitation hampers their predictive performance. In this study, we proposed a novel crop genome selection model based on hypergraph attention networks for genomic prediction (HGATGS). This model incorporates dynamic hyperedges that are designed based on sample similarity to validate the efficacy of high-order relationships between samples for phenotypic prediction. By introducing an attention mechanism, it assigns weights to different hyperedges and nodes, thereby enhancing the ability to capture kinship relationships among samples. Additionally, residual connections are incorporated between hypergraph convolutional layers to further improve model stability and performance. The model was validated on datasets for multiple crops, including wheat, corn, and rice. The results showed that HGATGS significantly outperformed traditional statistical methods and machine learning models on the Wheat 599, Rice 299, and G2F 2017 datasets. On Wheat 599, HGATGS achieved a correlation coefficient of 0.54, a 14.9% improvement over methods like R-BLUP and BayesA (0.47). On Rice 299, HGATGS reached 0.45, a 66.7% increase compared to other models like R-BLUP and SVR (0.27). On G2F 2017, HGATGS attained 0.88, slightly surpassing other models like R-BLUP and BayesA (0.87). We conducted ablation experiments to compare the model’s performance across three datasets, and found that the model integrating hypergraph attention and residual connections performed optimally. Subsequent comparisons of the model’s prediction performance with dynamically selected different k values revealed optimal performance when K = (3,4). The model’s prediction performance was also compared across different single nucleotide polymorphisms (SNPs) and sample sizes in various datasets, with HGATGS consistently outperforming the comparison models. Finally, visualizations of the constructed hypergraph structures showed that certain nodes have high connection densities with hyperedges. These nodes often represent varieties or genotypes with significant impacts on traits. During feature aggregation, these high-connectivity nodes contribute significantly to the prediction results and demonstrate better prediction performance across multiple traits in multiple crops. This demonstrates that the method of constructing hypergraphs through correlation relationships for prediction is highly effective. Full article

Switchgrass (Panicum virgatum L.) is an important cellulosic biofuel grass native to North America. Rust, caused by Puccinia spp. is the most predominant disease of switchgrass and has the potential to impact biomass conversion. In this study, virulence patterns were determined on a set of 38 switchgrass genotypes for 14 single-spore rust isolates from 14 field samples collected in seven states. Single nucleotide polymorphism (SNP) variation was also assessed in 720 sequenced cloned amplicons representing 654 base pairs of the elongation factor 1-α gene from the field samples. Five major haplotypes were identified differing by 11 out of the 39 SNP positions identified. STRUCTURE, Principal Coordinate Analysis, and phylogenetic analyses divided the rust population into two genetic clusters. Virginia and Georgia had the highest and lowest rust genetic diversity, respectively. Only nine accessions showed a differential disease response between the 14 isolates, allowing the identification of eight races, differing by 1–3 virulence factors. Overall, the results suggested clonal reproduction of the pathogen and a North–South differentiation via local adaptation. However, similar haplotypes and races were also recovered from several states, suggesting migration events, and highlighting the need to further investigate the switchgrass rust population structure and evolution in the USA. Full article

Background: Bipolar disorder (BD) is a chronic condition associated with treatment resistance, cognitive decline, structural brain changes, and an approximately 13-year reduction in life expectancy compared to the general population. Depression in BD substantially impairs quality of life, while neuroinflammation and excitotoxicity are thought to contribute to the recurrence of mood episodes and disease progression. Brain-derived neurotrophic factor (BDNF) plays a key role in neuronal growth and function, with its dysregulation being linked to various psychiatric disorders. This study is an extension of a previously published clinical trial and was conducted to assess the effects of three BDNF and BDNF-AS gene polymorphisms (rs1519480, rs6265, and rs10835210) on treatment outcomes and serum BDNF levels in patients with treatment-resistant bipolar disorder depression (TRBDD) over an eight-week period. Methods: This study included 41 participants from a previously conducted randomized clinical trial, all of whom had available BDNF serum samples and genotype data. The participants, aged 21 to 65, were diagnosed with bipolar disorder, and treatment-resistant depression was assessed using the Maudsley Staging Method. Participants were randomly assigned to receive either escitalopram plus a placebo (ESC+PBO) or escitalopram plus celecoxib (ESC+CBX) over an 8-week period. Statistical analyses included a mixed ANOVA and chi-square tests to compare the minor allele carrier status of three SNPs with treatment response and remission rates. Results: Non-carriers of the rs6265 A allele (p = 0.005) and carriers of the rs10835210 A allele (p = 0.007) showed a significantly higher response to treatment with adjunctive celecoxib compared to escitalopram alone. Additionally, remission rates after adjunctive celecoxib were significantly higher in both carriers and non-carriers across all three SNPs compared to escitalopram alone. However, remission rates were notably higher in non-carriers of the rs1519480 G allele and rs10835210 A allele, as well as in carriers of the rs6265 A allele. Conclusions: This study suggests that genetic variations in BDNF and BDNF-AS genes significantly influence treatment response to and remission with escitalopram and celecoxib in bipolar disorder. Full article

Saffron (Crocus sativus L.) is one of the most expensive spices in the world. Saffron, prized for its vibrant color, aroma, and taste, is essential in the food industry and traditional medicine. Its culinary uses, therapeutic benefits, and potential antioxidant, anti-inflammatory, and anticancer properties highlight its significant importance. Its genetic diversity has significant implications for cultivation and quality. In this study, genetic diversity among 76 saffron accessions, collected from 13 localities of Taliouin region of Morocco, were evaluated using sequence-related amplified polymorphism (SRAP) markers. A total of 63 polymorphic fragments were produced with an average of total number and polymorphic bands per primer were of 10.5 and 10.16, respectively. Most of the variations among the localities, revealed by the Analysis of Molecular Variance, originated from the within accessions differentiation (81%; p < 0.010). Cluster Analysis, Principal Coordinate Analysis (PCoA), and population structure confirmed the main groups and corroborated genetic homogeneity across accessions. In fact, close relationships were revealed between accessions from different locations, showing that there was no relationship between genetic divergence and geographical locality. This investigation represents a pivotal advance towards fostering sustainable development and bolstering the economic empowerment of the saffron farming communities in Morocco. Full article

Maize is a critical crop for food, feed, and bioenergy worldwide. This study characterized the genetic diversity and population structure of 212 important inbred lines collected from the Southeast China breeding program using the Maize6H-60K single nucleotide polymorphism (SNP) array. To investigate the genetic architecture of plant height (PH) and ear height (EH), genome-wide association analysis (GWAS) was performed on this population in 2021 and 2022. Cluster analysis and population genetic structure analysis grouped the 212 maize inbred lines into 10 distinct categories. GWAS identified significant associations for PH, EH, and the EH/PH ratio. A total of 40 significant SNP (p < 8.55359 × 10⁻⁷) were detected, including nine associated with PH, with phenotypic variation explained (PVE) ranging from 3.42% to 25.92%. Additionally, 16 SNP were linked to EH, with PVE ranging from 2.49% to 38.49%, and 15 SNP were associated with the EH/PH ratio, showing PVE between 3.43% and 16.83%. Five stable SNP, identified across two or more environments, were further analyzed. Three of these SNP loci are reported for the first time in this study: two loci associated with the PH, AX-108020973, and AX-108022922, as well as one new locus, AX-108096437, which was significantly associated with the EH/PH ratio. Additionally, two other significant SNP (AX-247241325 and AX-108097244) were located within a 2 Mb range of previously identified QTL and/or related SNP. Within the 200 kb confidence intervals of these five stable SNP loci, 76 functionally annotated genes were identified. Further functional analysis indicated that 14 of these genes may play a role in regulating plant morphology, which is primarily involved in hormone synthesis, microtubule development, root growth, and cell division regulation. For instance, the homologous genes GRMZM2G375249 and GRMZM2G076029 in maize correspond to OsPEX1 in rice, a protein similar to extension proteins that are implicated in lignin biosynthesis, plant growth promotion, and the negative regulation of root growth through gibberellin-mediated pathways. The candidate gene corresponding to AX-108097244 is GRMZM2G464754; previous studies have reported its involvement in regulating EH in maize. These findings enhance the understanding of QTL associated with maize plant-type traits and provide a foundation for cloning PH, EH-related genes. Therefore, the results also support the development of functional markers for target genes and the breeding of improved maize varieties. Full article

Tea oil is an important high-quality edible oil derived from woody plants. Camellia oleifera is the largest and most widely planted oil-producing plant in the Camellia genus in China, and its seeds are the most important source for obtaining tea oil. In current research, improving the yield and quality of tea oil is the main goal of oil tea genetic breeding. The aim of this study was to investigate the degree of genetic variation in an early crossing population of C. oleifera and identify single nucleotide polymorphisms (SNPs) and genes significantly associated with fruit traits, which can provide a basis for marker-assisted selection and gene editing for achieving trait improvement in the future. In this study, we selected a crossing population of approximately 40-year-old C. oleifera with a total of 330 samples. Then, ddRAD sequencing was used for SNP calling and population genetic analysis, and association analysis was performed on fruit traits measured repeatedly for two consecutive years. The research results indicate that over 8 million high-quality SNPs have been identified, but the vast majority of SNPs occur in intergenic regions. The nucleotide polymorphism of this population is at a low level, and Tajima’s D values are mostly greater than 0, indicating that the change in this population was not suitable for the model of central evolution. The population structure analysis shows that the population has seven theoretical sources of genetic material and can be divided into seven groups, and the clustering analysis results support the population structure analysis results. Association analysis identified significant SNPs associated with genes related to the seed number of a single fruit and seed kernel oil content. Our findings provide a basis for molecular breeding and future genetic improvement of cultivated oil tea. Full article

Salinity stress significantly affects rice yield, especially when it occurs during the germination stage. Direct seeding is an emerging method to conserve water in rice cultivation. However, to date, there have been limited efforts to screen rice germplasm for salt tolerance under this approach. In this study, 40 rice genotypes were evaluated for salt tolerance using a combination of germination and growth parameters. A total of 59 microsatellite markers were used to assess genetic diversity, revealing significant variation in both germination and growth traits. Based on germination parameters, IR36, Sri Malaysia 2, and MR185 performed well under saline conditions, while Hashemi Tarom and BAS2000 exhibited weak tolerance. MR219, MR211, and MR263 were identified as superior salt-tolerant genotypes against all growth parameters. BAS2000 and MCHKAB were identified as salt-sensitive, showing reduced growth in key traits, including root and shoot development. Marker-based genotyping identified a total of 287 alleles. The number of alleles per locus ranged from two to nine with an average of 4.86. The polymorphic information content (PIC) ranged from four to eight. The markers RM21, RM481 RM566, RM488, RM9, RM217, RM333, RM242, RM209, RM38, RM539, RM475, RM267, RM279, and RM430 were found highly polymorphic with PIC value > 0.7 and contain the highest number of alleles (≥6). Model- and distance-based population structures both inferred the presence of three clusters in the studied rice germplasm. Based on cluster analysis, Shiroodi, Hashemi Tarom, and BAS2000 were found as weak salt-tolerant varieties, whereas MR211 and MR219 are two Malaysian varieties found to be highly tolerant and have a high potential for direct seeding methods. An AMOVA test suggested that 95% genetic diversity was within the population, which implies that significant genetic variation was present in rice germplasm to be used to select parents for future breeding programs. Full article

Actinobacillus pleuropneumoniae is a major swine pathogen, classified into 19 serotypes based on capsular polysaccharide (CPS) loci. This study aimed to improve the diagnostic method to differentiate between serotypes 9 and 11, which are challenging to distinguish using conventional serological and molecular methods. A novel qPCR assay based on locked nucleic acid (LNA) probes was developed and validated using a collection of reference strains representing all known 19 serotypes. The assay demonstrated specificity in detecting the nucleotide variation characteristic of the serotype 9 reference strain. However, the analysis of a clinical isolate collection identified discrepancies between LNA-qPCR and serological results, prompting further investigation of the cps and O-Ag loci. Subsequent nanopore sequencing and whole-genome sequencing of a collection of 31 European clinical isolates, previously identified as serotype 9, 11, or undifferentiated 9/11, revealed significant genetic variations in the cps and O-Ag loci. Ten isolates had a cpsF sequence identical to that of the serotype 11 reference strain, while six isolates had single-nucleotide polymorphisms that were unlikely to cause significant coding changes. In contrast, 15 isolates had interruptions in the cpsF gene, distinct from that found in the serotype 9 reference strain, potentially leading to a serotype 9 CPS structure. In the O-Ag loci, differences between serotypes 9 and 11 were minimal, although some isolates had mutations potentially affecting O-Ag expression. Overall, these findings suggest that multiple genetic events can lead to the formation of a serotype 9 CPS structure, hindering the development of a single qPCR assay capable of detecting all cpsF gene mutations. Our results suggest that, currently, a comprehensive analysis of the cpsF gene is necessary to accurately determine whether the capsule of an isolate corresponds to serotype 9 or 11. Although such analyses are feasible with the advent of third-generation sequencing technologies, their accessibility, cost, and time to result limit their use in routine diagnostic applications. Under these circumstances, the designation of the hybrid serovar 9/11 remains a valid approach. Full article

This study investigated the genetic diversity and genomic variation in wild Cordyceps chanhua populations from four regions in China—Dazhou, Sichuan (ICD); Lu’an, Anhui (ICL); Taizhou, Zhejiang (ICT); and Yixing, Jiangsu (ICY)—to elucidate genetic differentiation patterns and provide a scientific foundation for resource conservation and sustainable utilization. Whole-genome resequencing was performed, yielding high-quality sequencing data (Q20 > 98%, Q30 > 94%, coverage: 93.62–95.79%) and enabling the detection of 82,428 single-nucleotide polymorphisms (SNPs) and 12,517 insertion–deletion markers (InDels). Genomic variations were unevenly distributed across chromosomes, with chromosome chrU05 exhibiting the highest SNP density (5187.86), suggesting a potential hotspot of genetic diversity. Phylogenetic analysis confirmed that all samples belonged to the C. chanhua lineage but revealed significant genetic differentiation among regions. Population structure analysis, supported by structure analysis and PCA, identified two distinct subgroups (G1 and G2) closely associated with geographic origins, reflecting the influence of both environmental and geographic factors on genetic differentiation. These findings underscore the substantial interregional genetic diversity in C. chanhua populations, highlighting the importance of tailored conservation strategies and region-specific germplasm utilization. The study provides critical genomic insights to support marker-assisted breeding, regional cultivation optimization, and the sustainable development of C. chanhua resources. Full article

Italian ryegrass (Lolium multiflorum, IRG) and perennial ryegrass (Lolium perenne L., PRG) are widely cultivated as forage grasses in Korea using heterogeneous and polycross techniques, which promote genetic diversity within varieties. However, their genetic diversity patterns in Korea remain underexplored. This study evaluated the genetic diversity of IRG (eight varieties, including one exotic) and PRG (two exotic varieties) using 66 simple sequence repeat (SSR) markers. Across 87 samples (nine IRG and two PRG varieties), 655 alleles were identified, averaging 9.9 per locus. Key genetic parameters included heterozygosity (0.399), observed heterozygosity (0.675), fixation index (0.4344), and polymorphic informative content (0.6428). The lowest within-variety genetic distance was observed in ‘Hwasan 104ho’ (0.469), while ‘IR901’ had the highest (0.571). Between varieties, the closest genetic distance was between ‘Greencall’ and ‘Greencall 2ho’ (0.542), and the furthest was between ‘Kowinmaster’ and ‘Aspire’ (0.692). Molecular variance analysis showed 90% variation within varieties and 10% among varieties. Five clusters (I–V) were identified, with cluster I primarily including diploid IRG varieties and the tetraploid ‘Hwasan 104ho.’ Structural analysis differentiated diploid from tetraploid varieties (K = 2) and further separated tetraploid IRG and PRG (K = 3). Principal component analysis confirmed these groupings, with ‘Greencall’ and ‘Greencall 2ho’ exhibiting the closest genetic distance (0.227) and ‘Greencall’ and ‘Aspire’ the furthest (0.384). These findings provide a foundational resource for marker-assisted breeding to improve agronomic traits and enhance the efficiency of ryegrass breeding programs. Full article

Prion diseases are fatal neurodegenerative diseases that can be transmitted by infectious protein particles, PrP^Scs, encoded by the endogenous prion protein gene (PRNP). The origin of prion seeds is unclear, especially in non-human hosts, and this identification is pivotal to preventing the spread of prion diseases from host animals. Recently, an abnormally high amyloid propensity in prion proteins (PrPs) was found in a frog, of which the genetic variations in the PRNP gene have not been investigated. In this study, genetic polymorphisms in the PRNP gene were investigated in 194 Dybowski’s frogs using polymerase chain reaction (PCR) and amplicon sequencing. We carried out in silico analyses to predict functional alterations according to non-synonymous single nucleotide polymorphisms (SNPs) using PolyPhen-2, PANTHER, SIFT, and MutPred2. We used ClustalW2 and MEGA X to compare frog PRNP and PrP sequences with those of prion-related animals. To evaluate the impact of the SNPs on protein aggregation propensity and 3D structure, we utilized AMYCO and ColabFold. We identified 34 novel genetic polymorphisms including 6 non-synonymous SNPs in the frog PRNP gene. The hydrogen bond length varied at codons 143 and 207 according to non-synonymous SNPs, even if the electrostatic potential was not changed. In silico analysis predicted S143N to increase the aggregation propensity, and W6L, C8Y, R211W, and L241F had damaging effects on frog PrPs. The PRNP and PrP sequences of frogs showed low homology with those of prion-related mammals. To the best of our knowledge, this study was the first to discover genetic polymorphisms in the PRNP gene in amphibians. Full article