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Reversing cancer cachexia remains a challenge. Genetic biomarkers for the early detection of the disease have been explored in order to enable the implementation of preventive measures. We therefore genotyped candidate genes based on cachexia phenotype and quantified adiponectin and GDF-15 levels in cachectic patients with gastrointestinal cancer. Patients with a diagnosis of gastrointestinal cancer were divided into a cachectic and a non-cachectic group after the start of chemotherapy. A control group (no cancer) was also included. We genotyped the following single nucleotide polymorphisms (SNPs) by quantitative PCR: FOXO3 (rs1935949), FOXO3 (rs4946935), ACVR2B (rs2268757), and SELP (rs6136). In addition, we quantified adiponectin and GDF-15 levels by ELISA. The rs2268757 SNP in the ACVR2B gene was associated with the weight loss phenotype in cachectic patients with gastrointestinal cancer (non-cachectic, P = 0.004). Plasma adiponectin levels were higher in cachectic patients compared to controls (P = 0.01) and non-cachectic patients (P = 0.004). GDF-15 was also elevated in cachectic patients compared to controls (P < 0.0001) and non-cachectic patients (P = 0.001). Analysis by sex showed elevated adiponectin levels in men (control, P = 0.01) and cachectic women (control, P = 0.04; non-cachectic, P = 0.01), as well as elevated GDF-15 levels in men (control, P = 0.002) and cachectic women (control, P = 0.002; non-cachectic, P = 0.007). However, there was no significant difference in the levels of these cytokines between cachectic men and women. The results suggest the rs2268757 SNP in the ACVR2B gene, adiponectin, and GDF-15 as potential biomarkers of cachexia in gastrointestinal cancer. [ABSTRACT FROM AUTHOR]

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public health problem, resulting in > 1 million deaths each year. Drug resistance (DR), including the multi-drug form (MDR-TB), is challenging control of the disease. Whilst many DR mutations in the Mtb genome are known, analysis of large datasets generated using whole genome sequencing (WGS) platforms can reveal new variants through the assessment of genotype-phenotype associations. Here, we apply tree-based ensemble methods to a dataset comprised of 35,777 Mtb WGS and phenotypic drug-susceptibility test data across first- and second-line drugs. We compare model performance across models trained using mutations in drug-specific regions and genome-wide variants, and find high predictive ability for both first-line (area under ROC curve (AUC); range 88.3–96.5) and second-line (AUC range 84.1–95.4) drugs. To aggregate information from low-frequency variants, we pool mutations by functional impact and observe large improvements in predictive accuracy (e.g., sensitivity: pyrazinamide + 25%; ethionamide + 10%). We further characterise loss-of-function mutations observed in resistant phenotypes, uncovering putative markers of resistance (e.g., ndh 293dupG, Rv3861 78delC). Finally, we profile the distribution of known DR-associated single nucleotide polymorphisms across discretised minimum inhibitory concentration (MIC) data generated from phenotypic testing (n = 12,066), and identify mutations associated with highly resistant phenotypes (e.g., inhA − 779G > T and 62T > C). Overall, our work demonstrates that applying machine learning to large-scale WGS data is useful for providing insights into predicting Mtb binary drug resistance and MIC phenotypes, thereby potentially assisting diagnosis and treatment decision-making for infection control. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CVDs) are complex, multifactorial conditions that require personalized assessment and treatment. Advancements in multi-omics technologies, namely RNA sequencing and whole-genome sequencing, have provided translational researchers with a comprehensive view of the human genome. The efficient synthesis and analysis of this data through integrated approach that characterizes genetic variants alongside expression patterns linked to emerging phenotypes, can reveal novel biomarkers and enable the segmentation of patient populations based on personalized risk factors. In this study, we present a cutting-edge methodology rooted in the integration of traditional bioinformatics, classical statistics, and multimodal machine learning techniques. Our approach has the potential to uncover the intricate mechanisms underlying CVD, enabling patient-specific risk and response profiling. We sourced transcriptomic expression data and single nucleotide polymorphisms (SNPs) from both CVD patients and healthy controls. By integrating these multi-omics datasets with clinical demographic information, we generated patient-specific profiles. Utilizing a robust feature selection approach, we identified a signature of 27 transcriptomic features and SNPs that are effective predictors of CVD. Differential expression analysis, combined with minimum redundancy maximum relevance feature selection, highlighted biomarkers that explain the disease phenotype. This approach prioritizes both biological relevance and efficiency in machine learning. We employed Combination Annotation Dependent Depletion scores and allele frequencies to identify variants with pathogenic characteristics in CVD patients. Classification models trained on this signature demonstrated high-accuracy predictions for CVD. The best performing of these models was an XGBoost classifier optimized via Bayesian hyperparameter tuning, which was able to correctly classify all patients in our test dataset. Using SHapley Additive exPlanations, we created risk assessments for patients, offering further contextualization of these predictions in a clinical setting. Across the cohort, RPL36AP37 and HBA1 were scored as the most important biomarkers for predicting CVDs. A comprehensive literature review revealed that a substantial portion of the diagnostic biomarkers identified have previously been associated with CVD. The framework we propose in this study is unbiased and generalizable to other diseases and disorders. [ABSTRACT FROM AUTHOR]

In military populations, gene-environment interactions can influence performance and health outcomes. Brain-derived neurotrophic factor (BDNF) is a central nervous system protein that is important for neuronal function and synaptic plasticity. A BDNF single nucleotide polymorphism, rs6265, leads to an amino acid substitution of valine (Val) with methionine (Met) at codon 66 (Val66Met), which may influence an individual's response to occupational stress, and predispose military members to psychological disorders. Telomere length (TL), a novel measure of biological aging, can be used as a biomarker of stress. Accordingly, telomere shortening may be a surrogate indicator of physiological weathering due to chronic disease and stressful life events. To increase our understanding about the potential effect of the Val66Met mutation on the human stress response, we evaluated the relationships between Val66Met, TL, and mental health symptoms in a military population. In this pilot study (N = 164), we observed an association between Val66Met and reduced TL (p = 0.048). There was no relationship between Val66Met and mental health symptoms. These results support the investigation of gene-environment interactions, and their potential influence on TL due to occupational stress such as military service. [ABSTRACT FROM AUTHOR]

Acne is a prevalent inflammatory disease in dermatology, and its pathogenesis may be associated with inflammation, immunity, and other mechanisms. It commonly manifests in young individuals and frequently imposes a heavy economic, physical, and psychological burden on patients. Gut microbes and blood metabolites, as significant immune and inflammatory regulators in the body, have been hypothesized to form the "neurocutaneous axis." Nonetheless, the precise causal relationships among the gut microbes, circulating blood metabolites, and acne development have yet to be elucidated. This study employed bidirectional two-sample Mendelian randomization (MR) to probe the causal impacts of 412 distinct gut microbes and 249 blood metabolites on acne. Single nucleotide polymorphisms (SNPs), which are closely associated with gut microbes and blood metabolites, were utilized as instrumental variables. This approach was taken to discern whether these elements serve as pathogenic or protective factors in relation to acne. Furthermore, a mediation analysis encompassing gut microbes, blood metabolites, and acne was conducted to explore potential correlations between gut microbes and blood metabolites, as well as their cumulative effects on acne. This was done to substantiate the notion of causality. Bidirectional two-sample MR analysis revealed 8 gut bacteria, 6 bacterial metabolic abundance pathways determined by birdshot, and 8 blood metabolites significantly associated with acne. The mediation MR analysis revealed 2 potential causal relationships, namely, Bifidobacterium-DHA-Acne and Bifidobacterium-Degree of Unsaturation-Acne. This study identified gut microbes and blood metabolites that are causally associated with acne. A potential causal relationship between gut microbes and blood metabolites was obtained via mediation analysis. These insights pave the way for the identification of new targets and the formulation of innovative approaches for the prevention and treatment of acne. [ABSTRACT FROM AUTHOR]

Failure to consider population structure when managing harvested fishes increases the risk of stock depletion, yet empirical estimates of population structure are often lacking for important fishery species. In this study, we characterise genetic variation in single nucleotide polymorphisms (SNPs) to assess population structure for three harvested species of tropical snappers across the broad (up to 300 km wide) and extensive (~ 4000 km) continental shelf of north-western Australia. Comparisons across ~ 300 individuals per species, showed remarkably similar patterns of genetic structure among Lutjanus sebae (red emperor), L. malabaricus (saddletail snapper) and Pristipomoides multidens (goldband snapper) despite subtle differences in biological and ecological traits. Low levels of genetic subdivision were reflected in an isolation by distance relationship where genetic connectivity increased with geographic proximity. This indicates extensive but not unlimited dispersal across the north-western Australian shelf. Our findings provide evidence of connectivity between current management areas, violating the assumption of multiple independent stocks. Spatial stock assessment models may be more suitable for the management of these species however demographic connectivity rates cannot be accurately estimated from the conventional population genetic approaches applied in this study. We recommend that managers aim to maintain adequate spawning biomass across current management areas, and assess stocks at finer scales, where practical. [ABSTRACT FROM AUTHOR]

Chloroquine is still used as a first-line treatment for uncomplicated Plasmodium vivax malaria in India and resistance to this therapy can act as a major hurdle for malaria elimination. It is difficult to monitor drug-efficacy and drug resistance through in vivo and in vitro studies in case of Plasmodium vivax so analysis of molecular markers serves as an important tool to track resistance. Molecular methods that are currently in use for detecting single nucleotide polymorphisms in resistant genes including Polymerase chain reaction (PCR), Realtime-Polymerase chain reaction require highly sophisticated labs and are time consuming. So, with this background the study has been designed to optimize Loop Mediated Isothermal Amplification Assay to detect single nucleotide polymorphisms in chloroquine resistance gene of Plasmodium vivax in field settings. Eighty-eight Plasmodium vivax positive samples were collected. Pvmdr1 gene was amplified for all the samples and sequenced. Obtained sequences were analyzed for the presence of single nucleotide polymorphisms in the target gene. Further Loop Mediated Isothermal Amplification Assay primer sets were designed for the target mutants and the assay was optimized. Clinical as well as analytical sensitivity and specificity for the assay was calculated. Double mutants with variations at T958M and F1076L were detected in 100% of the Plasmodium vivax clinical isolates with haplotype M958 Y976 Y1028 L1076. Designed primers for Loop Mediated Isothermal Amplification Assay successfully detected both the mutants (T958M and F1076L) in 100% of the isolates and do not show cross-reactivity with other strains. So, the assay was 100% sensitive and specific for detecting single nucleotide polymorphisms in the target Pvmdr1 gene. Limit of detection was found to be 0.9 copies/µl and lowest DNA template concentration detected by designed assay was 1.5 ng/µL. Observed prevalence of single nucleotide polymorphisms in Pvmdr 1 gene is indicating a beginning of trend towards chloroquine resistance in Plasmodium vivax. The present study optimized LAMP for detecting single nucleotide polymorphisms in Plasmodium vivax cases in field settings, thus would help in finding significant hubs of emerging chloroquine drug resistance and ultimately helping in the management of suitable antimalarial drug policy. [ABSTRACT FROM AUTHOR]

Oral cancer (ORCA) is the most prevalent histological subtype of oral malignancies in which immune modulation is relevant. The goal of this work was to employ Mendelian randomization (MR) to investigate the causal connection between the immune-related proteins MICB, CTSA, MMP9, and ORCA. The Open GWAS database of the Integrative Epidemiology Unit (IEU) was accessed to collect GWAS data for ORCA (ieu-b-4961), MICB (prot-a-1898), CTSA (prot-a-717) and MMP9 (prot-a-1921). From 372,373 samples, the ORCA dataset comprises 7,723,107 single nucleotide polymorphisms (SNPs). MICB, CTSA, and MMP9 all have 10,534,735 SNPs and 3,301 sample sizes. Then, the primary SVMR implementation approaches were weighted mode, simple mode, inverse variance weighted (IVW), weighted median, and MR-Egger. IVW was the most effective technique. A sensitivity study was also carried out to assess the correctness of SVMR data, with special focus devoted to heterogeneity, horizontal pleiotropy, and Leave-One-Out (LOO). MVMR was eventually implemented as well. A Mendelian randomization analysis of the three exposure factors in the dataset (ieu-b-94, ebi-a-GCST012237) was also performed to validate the study results. According to the SVMR results, there was a noteworthy causal interaction between ORCA and MICB (P = 0.0014), MMP9 (P = 0.0343), and CTSA (P = 0.0003). Furthermore, odds ratios (ORs) values revealed that MMP9 (OR = 1.0005) was an ORCA risk factor, whereas MICB (OR = 0.9994) and CTSA (OR = 0.9993) were security factors. The robustness of the SVMR findings was confirmed by the p-values of the heterogeneity and horizontal pleiotropy, both of which were greater than 0.05. The MVMR result did not affect any of the safety or hazard features of these three exposure factors. However, the P value for MMP9 was greater than 0.05, implying that MICB and CTSA may have a greater influence on ORCA than MMP9. The validation outcomes in both datasets harmonized with the findings from previous research, thereby solidifying the reliability of results. Our investigation provided a crucial resource for further research on the subject by demonstrating a causal relationship between ORCA and MICB, CTSA, and MMP9. [ABSTRACT FROM AUTHOR]

This cross-sectional study explores the impact of FTO gene single nucleotide polymorphisms (SNPs) rs9939609 and rs1421085 on dietary habits contributing to obesity risk in Thai adults. The study enrolled 384 participants from Bangkok, categorized as non-obese (BMI < 25 kg/m2) or obese (BMI ≥ 25 kg/m2) based on WHO Asia Pacific Guidelines. Genotyping for FTO variants was performed using DNA from blood samples. While both SNPs adhered to Hardy–Weinberg equilibrium, the association between risk alleles and anthropometric measurements was not statistically significant. However, risk allele carriers showed significantly higher intakes of sugar and saturated fat compared to homozygous dominant individuals. In the obese group, the odds ratio for high-sugar intake was 2.22 (95% CI 1.13–4.37, p = 0.021) for rs9939609 risk allele carriers. For high-saturated fat intake, the odds ratio was 1.86 (95% CI 1.02–3.40, p = 0.041). Similar associations were observed for rs1421085. Risk allele carriers also exhibited significantly higher leptin levels (p < 0.043) and a positive correlation with myeloperoxidase levels (p < 0.038). These findings highlight the complex relationship between FTO risk alleles, increased consumption of sugar and saturated fat, and obesity-related parameters. The insights emphasize the importance of considering both genetic and dietary factors in obesity prevention strategies. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDAC) has high mortality and rising incidence rates. Recent data indicate that the gut microbiome and associated metabolites may play a role in the development of PDAC. To complement and inform observational studies, we investigated associations of genetically predicted abundances of individual gut bacteria and genetically predicted circulating concentrations of microbiome-associated metabolites with PDAC using Mendelian randomisation (MR). Gut microbiome-associated metabolites were identified through a comprehensive search of Pubmed, Exposome Explorer and Human Metabolome Database. Single Nucleotide Polymorphisms (SNPs) associated by Genome-Wide Association Studies (GWAS) with circulating levels of 109 of these metabolites were collated from Pubmed and the GWAS catalogue. SNPs for 119 taxonomically defined gut genera were selected from a meta-analysis performed by the MiBioGen consortium. Two-sample MR was conducted using GWAS summary statistics from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including a total of 8,769 cases and 7,055 controls. Inverse variance-weighted MR analyses were performed along with sensitivity analyses to assess potential violations of MR assumptions. Nominally significant associations were noted for genetically predicted circulating concentrations of mannitol (odds ratio per standard deviation [ORSD] = 0.97; 95% confidence interval [CI]: 0.95–0.99, p = 0.006), methionine (ORSD= 0.97; 95%CI: 0.94-1.00, p = 0.031), stearic acid (ORSD= 0.93; 95%CI: 0.87–0.99, p = 0.027), carnitine = (ORSD=1.01; 95% CI: 1.00-1.03, p = 0.027), hippuric acid (ORSD= 1.02; 95%CI: 1.00-1.04, p = 0.038) and 3-methylhistidine (ORSD= 1.05; 95%CI: 1.01–1.10, p = 0.02). Two gut microbiome genera were associated with reduced PDAC risk; Clostridium sensu stricto 1 (OR: 0.88; 95%CI: 0.78–0.99, p = 0.027) and Romboutsia (OR: 0.87; 95%CI: 0.80–0.96, p = 0.004). These results, though based only on genetically predicted gut microbiome characteristics and circulating bacteria-related metabolite concentrations, provide evidence for causal associations with pancreatic carcinogenesis. [ABSTRACT FROM AUTHOR]

This study was performed on Micropterus salmoides to determine growth-linked gene and single nucleotide polymorphism (SNP) markers under carbohydrate diet and varying temperature through RNA-seq and whole-genome re-sequencing. The results showed that growth-related genes were primarily enriched in the fat digestion and absorption signaling pathway, playing a role in lipid transport and metabolism. Fatty acid binding protein 6, bile salt-activated lipase-like, lysophosphatidylcholine acyltransferase 2, phospholipase A2, minor isoenzyme-like, and phospholipase A2, group IB (pancreas) were identified as the crucial genes. The differentially expressed genes between high and low temperatures were enriched in the pentose phosphate pathway, with carbohydrate transport and metabolism were most affected by temperature. Major facilitator superfamily domain containing 10, phosphogluconate dehydrogenase, fructose-1,6-bisphosphatase 1a, and spinster homolog 3 transcript variant X1(spns3) were the shared genes affected by temperature. From all the common genes, 10 growth-associated SNP markers were identified. The TT genotype at rs7781 was associated with lower body weight, while AA genotype at rs31434173 and CC genotype at rs31435313 showed positive correlation with body weight. Analogously, the GG genotype at rs31436887 and AA genotype at rs31438769 also found to characterize better growth performance. At low temperature, individuals with the AA genotype at rs11506587 and rs31435313 exhibited the slowest growth. For the genotypes labeled with rs11510589, the GG individual grew faster than the AA individual, whereas the opposite phenomenon occurred in these genotypes when labeled with rs11511314. The genotypes at rs32970704 and rs32967921 showed no growth correlation. The AA genotype at rs31435313 in spns3 had the slowest growth under a carbohydrate-rich diet regardless of the temperature. Our study presents candidate genes and SNP markers associated with growth influenced by carbohydrate and temperature, providing basis for the development of M. salmoides strain that better accepts carbohydrate diets at varying temperature. [ABSTRACT FROM AUTHOR]

Shiga toxin-producing Escherichia coli (STEC) can cause mild diarrhea even severe hemolytic uremic syndrome (HUS). Shiga toxin (Stx) is the primary virulence factor. Two Stx types and several subtypes have been identified. STEC strains encoding stx2f (Stx2f-STECs) are frequently identified from pigeons. Stx2f was initially considered to be associated with mild symptoms, more recently Stx2f-STECs have been isolated from HUS cases, indicating their pathogenic potential. Here, we investigated the prevalence of Stx2f-STECs among domestic pigeons in two regions in China, characterized the strains using whole-genome sequencing (WGS), and assessed the Stx2f transcriptions. Thirty-two Stx2f-STECs (4.36%) were culture-positive out of 734 fecal samples (one strain per sample). No other stx subtype-containing strain was isolated. Four serotypes and two sequence types were determined, and a novel sequence type ST15057 was identified. All strains harbored the E. coli attaching and effacing gene eae. Two types of Stx2f prophages were assigned. Stx2f-STECs showed variable Stx transcription levels induced by mitomycin C. Whole genome single-nucleotide polymorphism (wgSNP) analysis revealed different genetic backgrounds between pigeon-derived strains and those from diarrheal or HUS patients. In contrast, pigeon-derived Stx2f-STECs from diverse regions exhibited genetic similarity. Our study reports the prevalence and characteristics of Stx2f-STECs from pigeons in China. The pigeon-derived strains might pose low public health risk. [ABSTRACT FROM AUTHOR]

The calmodulin-binding transcription activator (CAMTA) family contributes to stress responses in many plant species. The Oryza sativa ssp. japonica genome harbors seven CAMTA genes; however, intraspecific variation and functional roles of this gene family have not been determined. Here, we comprehensively evaluated the structure and characteristics of the CAMTA genes in japonica rice using bioinformatics approaches and RT-qPCR. Within the CAMTA gene and promoter sequences, 527 single nucleotide polymorphisms were retrieved from 3,024 rice accessions. The CAMTA genes could be subdivided into 5–14 haplotypes. Association analyses between haplotypes and phenotypic traits, such as grain weight and salt stress parameters, identified phenotypic differences between rice subpopulations harboring different CAMTA haplotypes. Co-expression analyses and the identification of CAMTA-specific binding motifs revealed candidate genes regulated by CAMTA. A Gene Ontology functional enrichment analysis of 690 co-expressed genes revealed that CAMTA genes have key roles in defense responses. An interaction analysis identified 30 putative CAMTA interactors. Three genes were identified in co-expression and interaction network analyses, suggesting that they are potentially regulated by CAMTAs. Based on all information obtained together with the phenotypes of the CRISPR-Cas9 knockout mutant lines of three OskCAMTA genes generated, CAMTA1 likely plays important roles in the response to salt stress in rice. Overall, our findings suggest that the CAMTA gene family is involved in development and the salt stress response and reveal candidate target genes, providing a basis for further functional characterization. [ABSTRACT FROM AUTHOR]

Psoriasis is a chronic inflammatory skin disorder with multiple causes, including genetic and environmental factors. Despite advances in treatment, there remains a need to identify novel therapeutic targets. A Mendelian randomization (MR) analysis was conducted to identify therapeutic targets for psoriasis. Data on cis-expression quantitative trait loci were obtained from the eQTLGen Consortium (n = 31,684). Summary statistics for psoriasis (outcome) were sourced from the GWAS Catalog with a sample size of 484,598, including 5,427 cases and 479,171 controls. Colocalization analysis was used to assess whether psoriasis risk and gene expression were driven by shared single nucleotide polymorphisms. Drug prediction and molecular docking were utilized to validate the pharmacological value of the drug targets. The MR analysis found that 81 drug targets were significantly associated, and two (TYK2 and PRSS36) were supported by colocalization analysis (PP.H4 > 0.80). Phenome-wide association studies did not show any associations with other traits at the gene level. Biologically, these genes were closely related to immune function. Molecular docking revealed strong binding with drugs and proteins, as supported by available structural data. This study validated TYK2 as a drug target for psoriasis, in line with its existing clinical use, including the development of decucravacitinib. PRSS36 is a potential novel target requiring further investigation. [ABSTRACT FROM AUTHOR]

To identify genetic influences on subfoveal choroidal thickness of older adults using a genome-wide association study (GWAS). We recruited 300 participants from the population-based Korean Longitudinal Study on Health and Aging (KLoSHA) and Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD) cohort studies and 500 participants from the Bundang age-related macular degeneration (AMD) cohort study dataset. We conducted a GWAS on older adult populations in the KLoSHA and KLOSCAD cohorts. Single nucleotide polymorphisms (SNPs) associated with choroidal thickness were identified with P values < 1.0 × 10−4 in both the right and left eyes, followed by validation using the Bundang AMD cohort dataset. This association was further confirmed by a functional in vitro study using human umbilical vein endothelial cells (HUVECs). The ages of the cohort participants in the discovery and validation datasets were 73.5 ± 3.3 and 71.3 ± 7.9 years, respectively. In the discovery dataset, three SNPs (rs1916762, rs7587019, and rs13320098) were significantly associated with choroidal thickness in both eyes. This association was confirmed for rs1916762 (genotypes GG, GA, and AA) and rs7587019 (genotypes GG, GA, and AA), but not for rs13320098. The mean choroidal thickness decreased by 56.7 μm (AA, 73.8%) and 31.1 μm (GA, 85.6%) compared with that of the GG genotype of rs1916762, and by 55.4 μm (AA, 74.2%) and 28.2 μm (GA, 86.7%) compared with that of the GG genotype of rs7587019. The SNPs rs1916762 and rs7587019 were located close to the FAM124B gene near its cis-regulatory region. Moreover, FAM124B was highly expressed in vascular endothelial cells. In vitro HUVEC experiments showed that the inhibition of FAM124B was associated with decreased vascular endothelial proliferation, suggesting a potential mechanism of choroidal thinning. FAM124B was identified as a susceptibility gene affecting subfoveal choroidal thickness in older adults. This gene may be involved in mechanisms underlying retinal diseases associated with altered choroidal thickness, such as age-related macular degeneration. [ABSTRACT FROM AUTHOR]

Cassava (Manihot esculenta Crantz) is a vital carbohydrate source for over 800 million people globally, yet its production in East Africa is severely affected by cassava brown streak disease (CBSD). Genebanks, through ex-situ conservation, play a pivotal role in preserving crop diversity, providing crucial resources for breeding resilient and disease-resistant crops. This study genotyped 234 South American cassava accessions conserved at the CIAT genebank, previously phenotyped for CBSD resistance by an independent group, to perform a genome-wide association analysis (GWAS) to identify genetic variants associated with CBSD resistance. Our GWAS identified 35 single nucleotide polymorphism (SNP) markers distributed across various chromosomes, associated with disease severity or the presence/absence of viral infection. Markers were annotated within or near genes previously identified with functions related to pathogen recognition and immune response activation. Using the SNP candidates, we screened the world's largest cassava collection for accessions with a higher frequency of favorable genotypes, proposing 35 accessions with potential resistance to CBSD. Our results provide insights into the genetics of CBSD resistance and highlight the importance of genetic resources to equip breeders with the raw materials needed to develop new crop varieties resistant to pests and diseases. [ABSTRACT FROM AUTHOR]

Aedes aegypti and Aedes albopictus mosquitoes spread major vector-borne viral diseases in tropical and sub-tropical regions of the globe. In this study, we sequenced the genome of Indian Ae. aegypti and Ae. albopictus and mapped to their reference genomes. Comparative genomics were performed between our strain and the reference strains. A total of 14,416,484 single nucleotide polymorphisms (SNPs) and 156,487 insertions and deletions (InDels) were found in Ae. aegypti, and 28,940,433 SNPs and 188,987 InDels in Ae. albopictus. Particular emphasis was given to gene families involved in mosquito digestion, development, and innate immunity, which could be putative candidates for vector control. Serine protease cascades and their inhibitors called serpins, play a central role in these processes. We extracted high-impact variants in genes associated with serine proteases and serpins. This study reports for the first time a high coverage genome sequence data of an Indian Ae. albopictus mosquito. The results from this study will provide insights into Indian Aedes specific polymorphisms and the evolution of immune related genes in mosquitoes, which can serve as a resource for future comparative genomics and those pursuing the development of targeted biopesticides for effective mosquito control strategies. [ABSTRACT FROM AUTHOR]

Oral potentially malignant disorders (OPMDs) with genomic alterations have a heightened risk of evolving into oral squamous cell carcinoma (OSCC). Currently, genomic data are typically obtained through invasive tissue biopsy. However, brush biopsy is a non-invasive method that has been utilized for identifying dysplastic cells in OPMD but its effectiveness in reflecting the genomic landscape of OPMDs remains uncertain. This pilot study investigates the potential of brush biopsy samples in accurately reconstructing the genomic profile and tumor evolution in a patient with both OPMD and OSCC. We analyzed single nucleotide variants (SNVs), copy number aberrations (CNAs), and subclonal architectures in paired tissue and brush biopsy samples. The results showed that brush biopsy effectively captured 90% of SNVs and had similar CNA profiles as those seen in its paired tissue biopsies in all lesions. It was specific, as normal buccal mucosa did not share these genomic alterations. Interestingly, brush biopsy revealed shared SNVs and CNAs between the distinct OPMD and OSCC lesions from the same patient, indicating a common ancestral origin. Subclonal reconstruction confirmed this shared ancestry, followed by divergent evolution of the lesions. These findings highlight the potential of brush biopsies in accurately representing the genomic profile of OPL and OSCC, proving insight into reconstructing tumor evolution. [ABSTRACT FROM AUTHOR]

The sea urchin Diadema africanum is a macro-herbivore found in the rocky reef systems of the West African region and Macaronesian archipelagos. Over several decades, high densities of this species have generated marine barrens in certain areas at the Canary Islands. In contrast, more recently, during the last few years, the species has suffered mass mortality events that continue to the present day. In this study, we used 9,109 Single Nucleotide Polymorphisms (SNPs) and a fragment of a mitochondrial gene to evaluate the species' population structure, effects of mass mortalities on its diversity, and potential local adaptation across the Canary Islands and Cabo Verde. Our research provides compelling evidence of low genomic diversity and homogeneity across the studied area for neutral markers, along with recent demographic fluctuations. The high connectivity among distant areas likely allows a rapid recovering of the populations from local mortality events. Interestingly, we also observed genomic sub-structure from 405 SNPs identified as candidate loci under selection for seawater temperature. The lack of divergence among distant sites and the low diversity found can be attributed to the species' divergence from a small ancestral genomic pool, followed by a contemporary demographic expansion, and ongoinggene flow. [ABSTRACT FROM AUTHOR]

While previous research has shown the potential links between taste perception pathways and brain-related conditions, the area involving Alzheimer's disease remains incompletely understood. Taste perception involves neurotransmitter signaling, including serotonin, glutamate, and dopamine. Disruptions in these pathways are implicated in neurodegenerative diseases. The integration of olfactory and taste signals in flavor perception may impact brain health, evident in olfactory dysfunction as an early symptom in neurodegenerative conditions. Shared immune response and inflammatory pathways may contribute to the association between altered taste perception and conditions like neurodegeneration, present in Alzheimer's disease. This study consists of an exploration of expression-quantitative trait loci (eQTL), utilizing whole-blood transcriptome profiles, of 28 taste perception genes, from a combined cohort of 475 African American subjects. This comprehensive dataset was subsequently intersected with single-nucleotide polymorphisms (SNPs) identified in Genome-Wide Association Studies (GWAS) of Alzheimer's Disease (AD). Finally, the investigation delved into assessing the association between eQTLs reported in GWAS of AD and the profiles of 741 proteins from the Olink Neurological Panel. The eQTL analysis unveiled 3,547 statistically significant SNP-Gene associations, involving 412 distinct SNPs that spanned all 28 taste genes. In 17 GWAS studies encompassing various traits, a total of 14 SNPs associated with 12 genes were identified, with three SNPs consistently linked to Alzheimer's disease across four GWAS studies. All three SNPs demonstrated significant associations with the down-regulation of TAS2R41, and two of them were additionally associated with the down-regulation of TAS2R60. In the subsequent pQTL analysis, two of the SNPs linked to TAS2R41 and TAS2R60 genes (rs117771145 and rs10228407) were correlated with the upregulation of two proteins, namely EPHB6 and ADGRB3. Our investigation introduces a new perspective to the understanding of Alzheimer's disease, emphasizing the significance of bitter taste receptor genes in its pathogenesis. These discoveries set the stage for subsequent research to delve into these receptors as promising avenues for both intervention and diagnosis. Nevertheless, the translation of these genetic insights into clinical practice requires a more profound understanding of the implicated pathways and their pertinence to the disease's progression across diverse populations. [ABSTRACT FROM AUTHOR]

The muskox (Ovibos moschatus), an integral component and iconic symbol of arctic biocultural diversity, is under threat by rapid environmental disruptions from climate change. We report a chromosomal-level haploid genome assembly of a muskox from Banks Island in the Canadian Arctic Archipelago. The assembly has a contig N50 of 44.7 Mbp, a scaffold N50 of 112.3 Mbp, a complete representation (100%) of the BUSCO v5.2.2 set of 9225 mammalian marker genes and is anchored to the 24 chromosomes of the muskox. Tabulation of heterozygous single nucleotide variants in our specimen revealed a very low level of genetic diversity, which is consistent with recent reports of the muskox having the lowest genome-wide heterozygosity among the ungulates. While muskox populations are currently showing no overt signs of inbreeding depression, environmental disruptions are expected to strain the genomic resilience of the species. One notable impact of rapid climate change in the Arctic is the spread of emerging infectious and parasitic diseases in the muskox, as exemplified by the range expansion of muskox lungworms, and the recent fatal outbreaks of Erysipelothrix rhusiopathiae, a pathogen normally associated with domestic swine and poultry. As a genomics resource for conservation management of the muskox against existing and emerging disease modalities, we annotated the genes of the major histocompatibility complex on chromosome 2 and performed an initial assessment of the genetic diversity of this complex. This resource is further supported by the annotation of the principal genes of the innate immunity system, genes that are rapidly evolving and under positive selection in the muskox, genes associated with environmental adaptations, and the genes associated with socioeconomic benefits for Arctic communities such as wool (qiviut) attributes. These annotations will benefit muskox management and conservation. [ABSTRACT FROM AUTHOR]

To investigate the association between single nucleotide polymorphism (SNP) at the rs3918188, rs1799983 and rs1007311 loci of the endothelial nitric oxide synthase (eNOS) gene and genetic susceptibility to systemic lupus erythematosus (SLE) in northeastern China. The base distribution of eNOS gene rs3918188, rs1799983 and rs1007311 in 1712 human peripheral blood samples from Northeast China was detected by SNaPshot sequencing technology. The correlation between genotype, allele and gene model of these loci of the eNOS gene and the genetic susceptibility to SLE was investigated by logistic regression analysis. The results of the differences in the frequency distribution of their gene models were visualised using R 4.3.2 software. Finally, HaploView 4.2 software was used to analyse the relationship between the haplotypes of the three loci mentioned above and the genetic susceptibility to SLE. A multifactor dimensionality reduction (MDR) analysis was used to determine the best SNP-SNP interaction model. The CC genotype and C allele at the rs3918188 locus may be a risk factor for SLE (CC vs AA: OR = 1.827, P < 0.05; C vs A: OR = 1.558, P < 0.001), and this locus increased the risk of SLE in the dominant model and the recessive model (AC + CC vs AA: OR = 1.542, P < 0.05; CC vs AA + AC: OR = 1.707, P < 0.001), while the risk of SLE was reduced in the overdominant model (AC vs AA + CC: OR = 0.628, P < 0.001). The GT genotype and T allele at locus rs1799983 may be a protective factor for SLE (GT vs GG: OR = 0.328, P < 0.001; T vs G: OR = 0.438, P < 0.001) and this locus reduced the risk of SLE in the overdominant model (GT vs GG + TT: OR = 0.385, P < 0.001). There is a strong linkage disequilibrium between the rs1007311 and rs1799983 loci of the eNOS gene. Among them, the formed haplotype AG increased the risk of SLE compared to GG. AT and GT decreased the risk of SLE compared to GG. In this study, the eNOS gene rs3918188 and rs1799983 loci were found to be associated with susceptibility to SLE. This helps to deeply explore the mechanism of eNOS gene and genetic susceptibility to SLE. It provides a certain research basis for the subsequent exploration of the molecular mechanism of these loci and SLE, as well as the early diagnosis, treatment and prognosis of SLE. [ABSTRACT FROM AUTHOR]

High-density genomic data analyzed by accurate statistical methods are of potential to enlighten past breeding practices such as selection by unraveling fixed regions. In this study, four native Turkish sheep breeds (80 samples) were genotyped via 296.097 single nucleotide polymorphisms (SNPs) detected by double-digest restriction site-associated DNA (ddRADseq) library preparation combined with the Illumina HiSeq X Ten instrument in order to identify genes under selection pressure. A total of 32, 136, 133, and 119 protein-coding genes were detected under selection pressure by runs of homozygosity (ROH), integrated haplotype score (iHS), the ratio of extended haplotype homozygosity (Rsb), and fixation index (FST) approaches, respectively. Of these, a total of 129 genes were identified by at least two statistical models which overlapped with a total of 52 quantitative trait loci (QTL)-associated SNPs, known to be related to fiber diameter, milk content, body weight, carcass traits, some blood parameters, and entropion. A total of six genes under selection pressure were validated by three statistical approaches five of which are of potential to be integrated into animal breeding since they were associated with wool fiber diameter (ZNF208B), behaviors related to neurocognitive development (CBX1 and NFE2L1), adaptation to high-altitude (SDK1), and anxiety causing internal stress (GSG1L). The sixth gene (COPZ1) turned out to play an important role in coping with different types of cancer in mammals. In particular, ROH analysis uncovered significant findings that the Güney Karaman (GKR) had experienced different selection practices than the Akkaraman (AKR) breed. Moreover, some genes specifically under selection in the GKR breed turned out to be associated with olfaction (OR6K6, OR6N1, OR6N2, and OR4C16), survival during the gestation period (PRR15L), and heat stress (CDK5RAP9). The results of this study imply that GKR may become genetically different from the AKR breed at the genome level due to most probably experiencing different adaptation processes occurring in raised climatic conditions. These differences should be conserved to face future challenges, while other native Turkish sheep breeds could be monitored via genome-wide high-density SNP data to obtain deeper knowledge about the effects of natural selection. [ABSTRACT FROM AUTHOR]

Although prostate cancer is a common occurrence among males, the relationship between existing risk prediction models remains unclear. The objective of this hospital-based retrospective study is to investigate the impact of polygenic risk scores (PRSs) on the incidence and prognosis of prostate cancer in the Han Chinese population. A total of 24,778 male participants including 903 patients with prostate cancer at Taichung Veterans General Hospital were enrolled in the study. PRS was calculated using 269 single nucleotide polymorphisms and their corresponding effect sizes from the polygenic score catalog. The association between PRS and the risk prostate cancer was evaluated using Cox proportional hazards regression model. Among the 24,778 participants, 903 were diagnosed with prostate cancer. The risk of prostate cancer was significantly higher in the highest quartile of PRS distribution compared to the lowest (hazard ratio = 4.770, 95% CI = 3.999–5.689, p < 0.0001), with statistical significance across all age groups. Patients in the highest quartile were diagnosed with prostate cancer at a younger age (66.8 ± 8.3 vs. 69.5 ± 8.8, p = 0.002). Subgroup analysis of patients with localized or stage 4 prostate cancer showed no significant differences in biochemical failure or overall survival. This hospital-based cohort study observed that a higher PRS was associated with increased susceptibility to prostate cancer and younger age of diagnosis. However, PRS was not found to be a significant predictor of disease stage and prognosis. These findings suggest that PRS could serve as a useful tool in prostate cancer risk assessment. [ABSTRACT FROM AUTHOR]

Liver cancer, classified as a malignant hepatic tumor, can be divided into two categories: primary, originating within the liver, and secondary, resulting from metastasis to the liver from other organs. Hepatocellular carcinoma (HCC) is the main form of primary liver cancer and the third leading cause of cancer-related deaths. The diagnosis and prognosis of HCC using current methods still face numerous challenges. This study aims to develop novel diagnostic and prognostic models while identifying new biomarkers for improved HCC treatment. Diagnostic and prognostic models for HCC were constructed using traditional binary classification methods and machine learning algorithms based on the TCGA database (Downloaded in August 2023). The mechanisms by which APLN (Apelin) affects HCC were investigated using single-cell sequencing data sourced from the GEO database (GSE149614). The diagnostic models yielded by various algorithms could effectively distinguished HCC samples from normal ones. The prognostic model, composed of four genes, was constructed using LASSO and Cox regression algorithms, demonstrating good performance in predicting the three-year survival rate of HCC patients. The HCC biomarker Apelin (APLN) was identified in this study. APLN in liver cancer tissues mainly comes from endothelial cells and is associated with the carcinogenesis of these cells. APLN expression is significantly upregulated in liver cancer tissues, marking it as a viable indicator of endothelial cell malignancy in HCC. Furthermore, APLN expression was determined to be an independent predictor of tumor endothelial cell carcinogenesis, unaffected by its modifications such as single nucleotide variation, copy number variation, and methylation. Additionally, liver cancers characterized by high APLN expression are likely to progress rapidly after T2 stage. Our study presents diagnostic and prognostic models for HCC with appreciably improved accuracy and reliability compared to previous reports. APLN is a reliable HCC biomarker and contributes to the establishment of our models. [ABSTRACT FROM AUTHOR]

Identifying mechanisms that drive population divergence under varying geographic and ecological scenarios can inform our understanding of evolution and speciation. In particular, analysis of genetic data from island populations with known colonisation timelines allows us to identify potential source populations of diverging island subspecies and current relationships among populations. Silvereyes (Zosterops lateralis) are a small passerine that have served as a valuable study system to investigate evolutionary patterns on both large and small geographic scales. We examined genetic relatedness and diversity of two silvereye subspecies, the mainland Z. l. cornwalli and island Z. l. chlorocephalus, and used 18 077 single nucleotide polymorphisms (SNPs), to compare locations across southeast Queensland, Australia. Although silvereyes are prolific island colonisers our findings revealed population divergence over relatively small spatial scales was strongly influenced by geographic isolation mediated by water barriers. Strong genetic connectivity was displayed between mainland sites, but minimal inter-island connectivity was shown despite comparable sampling distances. Genetic diversity analysis showed little difference in heterozygosity between island and mainland populations, but lower inbreeding scores among the island populations. Our study confirmed the range of the Z. l. chlorocephalus subspecies throughout the southern Great Barrier Reef. Our results show that water barriers and not geographic distance per se are important in driving incipient divergence in island populations. This helps to explain the relatively high number of phenotypically differentiated, but often geographically proximate, island silvereye subspecies compared to a lower number of phenotypically less well-defined Australian continental subspecies. [ABSTRACT FROM AUTHOR]

The epidemic and outbreaks of influenza B Victoria lineage (Bv) during 2019–2022 led to an analysis of genetic, epitopes, charged amino acids and Bv outbreaks. Based on the National Influenza Surveillance Network (NISN), the Bv 72 strains isolated during 2019–2022 were selected by spatio-temporal sampling, then were sequenced. Using the Compare Means, Correlate and Cluster, the outbreak data were analyzed, including the single nucleotide variant (SNV), amino acid (AA), epitope, evolutionary rate (ER), Shannon entropy value (SV), charged amino acid and outbreak. With the emergence of COVID-19, the non-pharmaceutical interventions (NPIs) made Less distant transmission and only Bv outbreak. The 2021–2022 strains in the HA genes were located in the same subset, but were distinct from the 2019–2020 strains (P < 0.001). The codon G → A transition in nucleotide was in the highest ratio but the transversion of C → A and T → A made the most significant contribution to the outbreaks, while the increase in amino acid mutations characterized by polar, acidic and basic signatures played a key role in the Bv epidemic in 2021–2022. Both ER and SV were positively correlated in HA genes (R = 0.690) and NA genes (R = 0.711), respectively, however, the number of mutations in the HA genes was 1.59 times higher than that of the NA gene (2.15/1.36) from the beginning of 2020 to 2022. The positively selective sites 174, 199, 214 and 563 in HA genes and the sites 73 and 384 in NA genes were evolutionarily selected in the 2021–2022 influenza outbreaks. Overall, the prevalent factors related to 2021–2022 influenza outbreaks included epidemic timing, Tv, Ts, Tv/Ts, P137 (B → P), P148 (B → P), P199 (P → A), P212 (P → A), P214 (H → P) and P563 (B → P). The preference of amino acid mutations for charge/pH could influence the epidemic/outbreak trends of infectious diseases. Here was a good model of the evolution of infectious disease pathogens. This study, on account of further exploration of virology, genetics, bioinformatics and outbreak information, might facilitate further understanding of their deep interaction mechanisms in the spread of infectious diseases. [ABSTRACT FROM AUTHOR]

Abstract This cross-sectional study explores the impact of FTO gene single nucleotide polymorphisms (SNPs) rs9939609 and rs1421085 on dietary habits contributing to obesity risk in Thai adults. The study enrolled 384 participants from Bangkok, categorized as non-obese (BMI

Abstract Phedimus latiovalifolius (Y.N.Lee) D.C.Son & H.J.Kim is exclusively distributed in the high mountains in the Korean Peninsula, mainly along the Baekdudaegan mountain range. Despite its morphological and distributional distinction from other Phedimus Raf. species, its taxonomic identity and phylogenetic relationship with congeneric species remain unclear. This study employs genotyping-by-sequencing-derived genome-wide single nucleotide polymorphisms to establish the monophyly of P. latiovalifolius and its relationship with closely related species. Genetic diversity and population differentiation of P. latiovalifolius are also assessed to provide baseline genetic information for future conservation and management strategies. Our phylogenetic analyses robustly demonstrate the monophyletic nature of P. latiovalifolius, with P. aizoon (L.) ‘t Hart identified as its closest sister lineage. There is no genetic evidence supporting a hybrid origin of P. latiovalifolius from P. aizoon involving either P. ellacombeanus (Praeger) ‘t Hart or P. kamtschaticus (Fisch.) ‘t Hart. Population genetic analyses reveal two major groups within P. latiovalifolius. A higher genetic variation is observed in P. ellacombeanus than in the congeneric species. Notably, most of the genetic variation exists within P. latiovalifolius populations. Given its distribution and the potential role of Baekdudaegan as an East Asian Pleistocene refugia, P. latiovalifolius could be considered rare and endemic, persisting in the refugium across glacial/interglacial cycles.

Abstract Pepper agronomic traits serve as pivotal indicators for characterizing germplasm attributes and correlations. It is important to study differential genotypic variation through phenotypic differences of target traits. Whole genome resequencing was used to sequence the whole genome among different individuals of species with known reference genomes and annotations, and based on this, differential analyses of individuals or populations were carried out to identify SNPs for agronomic traits related to pepper. This study conducted a genome-wide association study encompassing 26 key agronomic traits in 182 upward-growing fruits of C. frutescens and C. annuum. The population structure (phylogenetics, population structure, population principal component analysis, genetic relationship) and linkage disequilibrium analysis were realized to ensure the accuracy and reliability of GWAS results, and the optimal statistical model was determined. A total of 929 SNPs significantly associated with 26 agronomic traits, were identified, alongside the detection of 519 candidate genes within 100 kb region adjacent to these SNPs. Additionally, through gene annotation and expression pattern scrutiny, genes such as GAUT1, COP10, and DDB1 correlated with fruit traits in Capsicum frutescens and Capsicum annuum were validated via qRT-PCR. In the CH20 (Capsicum annuum) and YB-4 (Capsicum frutescens) cultivars, GAUT1 and COP10 were cloned with cDNA lengths of 1065 bp and 561 bp, respectively, exhibiting only a small number of single nucleotide variations and nucleotide deletions. This validation provides a robust reference for molecular marker-assisted breeding of pepper agronomic traits, offering both genetic resources and theoretical foundations for future endeavors in molecular marker-assisted breeding for pepper.

Single nucleotide polymorphisms (SNPs) could increase the susceptibility of individuals to develop obesity and type 2 diabetes (T2DM). Obesity and T2DM are closely related pathophysiologically, thus similar SNPs could mediate both these diseases, but this is rarely reported. Furthermore, limited studies have been performed to summarize SNP data in the Asian population compared to the Western population. In this study, we aimed to summarize SNPs that are associated with the development of obesity and T2DM among Asian populations. We searched six literature databases and Review Manager (RevMan) was used for meta-analysis. The pooled odds ratios (ORs) and 95% CIs were calculated with a random effects model for the heterogeneity among studies. The pooled analysis showed that rs9939609 (FTO gene) and rs17782313 and rs571312 (MC4R gene) are associated with obesity with an odd ratio (OR) of 1.37, 1.36 and 1.29 respectively. For T2DM, five SNPs, rs7903146 and rs12255372 (TCF7L2 gene), rs13266634 and rs11558471 (SLC30A8 gene) and rs2283228 (KCNQ1 gene) have also shown strong associations with T2DM at OR of 1.64, 1.61, 1.22, 1.29 and 1.60 respectively. This data could be used to develop a gene screening panel for assessing obesity and T2DM susceptibility. [ABSTRACT FROM AUTHOR]

The causal relationship between lipid levels and bladder cancer is still inconclusive currently. We aimed to reveal the causal relationship between triglycerides, HDL, and LDL and the risk of bladder cancer by univariable and multivariable Mendelian randomization (MR) analysis. The single nucleotide polymorphisms (SNPs) of exposure (triglycerides: 441,016 samples; HDL: 403,943 samples; LDL: 440,546 samples) were obtained from UK Biobank. The Genetic variation related to bladder cancer included 1554 cases and 359,640 controls. Univariable and multivariable MR methods were conducted with subsequent analysis, and smoking was regarded as a confounder. The inverse-variance weighted (IVW), MR-Egger, weighted-median method, Cochran's Q test, and MR-PRESSO were considered the main MR analysis and sensitivity analysis methods. Univariable MR analysis results suggested the triglycerides level (P = 0.011, OR = 1.001, 95% CI = 1.000–1.002) was causally associated with increased risk of bladder cancer. Multivariable MR results indicated that higher triglyceride levels could still increase the risk of bladder cancer after adjusting the effects of HDL, LDL, and smoking (P = 0.042, OR = 1.001, 95% CI = 1.000–1.002). Our findings supported that triglyceride level is causally associated with an increased risk of bladder cancer independent of LDL and HDL at the genetic level. Timely attention to changes in blood lipid levels might reduce the risk of bladder cancer. [ABSTRACT FROM AUTHOR]

Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP–SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP–SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP–SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a hub SNP with a significant main effect and a large minor allele frequency (MAF) tended to have a higher false-positive rate. In addition, peripheral null SNPs in a cluster with a small MAF tended to enhance false positivity. We also demonstrated that using the modified significance criterion based on the 3 p-value rules and the bootstrap approach (3pRule + bootstrap) can reduce false positivity and maintain high true positivity. In addition, our results also showed that a pair without a significant main effect tends to have weak or no interaction. This study identified the cluster effect and suggested using the 3pRule + bootstrap approach to enhance SNP–SNP interaction detection accuracy. [ABSTRACT FROM AUTHOR]

Conversion of sputum from positive to negative is one of the indicators to evaluate the efficacy of anti-tuberculosis treatment (ATT). We investigate the factors associated with delayed sputum conversion after 2 or 5 months of ATT from the perspectives of bacteriology and genomics. A retrospective study of sputum conversion in sputum positive 1782 pulmonary tuberculosis (PTB) was conducted from 2021 to 2022 in Beijing, China. We also designed a case-matched study including 24 pairs of delayed-sputum-conversion patients (DSCPs) and timely-sputum-conversion patients (TSCPs), and collect clinical isolates from DSCPs before and after ATT and initial isolates of TSCPs who successfully achieved sputum conversion to negative after 2 months of ATT. A total of 75 strains were conducted drug sensitivity testing (DST) of 13 anti-TB drugs and whole-genome sequencing (WGS) to analyze the risk factors of delayed conversion and the dynamics changes of drug resistance and genomics of Mycobacterium tuberculosis (MTB) during ATT. We found TSCPs have better treatment outcomes and whose initial isolates show lower levels of drug resistance. Clinical isolates of DSCPs showed dynamically changing of resistance phenotypes and intra-host heterogeneity. Single nucleotide polymorphism (SNP) profiles showed large differences between groups. The study provided insight into the bacteriological and genomic variation of delayed sputum conversion. It would be helpful for early indication of sputum conversion and guidance on ATT. [ABSTRACT FROM AUTHOR]

The bidirectional effect of hyperuricemia on chronic kidney disease (CKD) underscores the importance of hyperuricemia as a risk factor for CKD. We evaluated the effect of hyperuricemia on the presence and development of CKD after considering genetic background by calculating polygenic risk scores (PRSs). We employed genome-wide association study summary statistics—excluding the United Kingdom Biobank (UKB) datasets among published CKD Gen Consortium papers—to calculate the PRSs for CKD in white background subjects. To validate PRS performance, we divided the UKB into two datasets to validate and test the data. We used logistic regression analysis to evaluate the association between hyperuricemia and CKD, and performed Kaplan–Meier survival analysis exclusively for subjects with available follow-up data. In total, 438,253 clinical data and 4,307,940 single nucleotide polymorphisms from 459,155 samples were included. We observed a significant positive association between PRS and CKD and the presence and development of CKD. Hyperuricemia significantly increased CKD risk (adjusted odds ratio 1.55, 95% confidence interval 1.48–1.61). The impact of hyperuricemia on CKD was maintained irrespective of PRS range. In addition, negative interaction between hyperuricemia and PRS for CKD was found. Survival analysis indicates that the presence of hyperuricemia significantly increased the risk of CKD development. The PRS for CKD thoroughly reflects the risk of CKD development. Hyperuricemia is a significant indicator of CKD risk, even after incorporating the genetic risk score for CKD. Irrespective of genetic risk, patients with a prospective risk of developing CKD require uric acid monitoring and management. [ABSTRACT FROM AUTHOR]

Developing high-yielding rice varieties that possess favorable agronomic characteristics and enhanced grain Zn content is crucial in ensuring food security and addressing nutritional needs. This research employed ICIM, IM, and multi-parent population QTL mapping methods to identify important genetic regions associated with traits such as DF, PH, NT, NP, PL, YLD, TGW, GL, GW, Zn, and Fe. Two populations of recombinant inbred lines consisting of 373 lines were phenotyped for agronomic, yield and grain micronutrient traits for three seasons at IRRI, and genotyped by sequencing. Most of the traits demonstrated moderate to high broad-sense heritability. There was a positive relationship between Zn and Fe contents. The principal components and correlation results revealed a significant negative association between YLD and Zn/Fe. ICIM identified 81 QTLs, while IM detected 36 QTLs across populations. The multi-parent population analysis detected 27 QTLs with six of them consistently detected across seasons. We shortlisted eight candidate genes associated with yield QTLs, 19 genes with QTLs for agronomic traits, and 26 genes with Zn and Fe QTLs. Notable candidate genes included CL4 and d35 for YLD, dh1 for DF, OsIRX10, HDT702, sd1 for PH, OsD27 for NP, whereas WFP and OsIPI1 were associated with PL, OsRSR1 and OsMTP1 were associated to TGW. The OsNAS1, OsRZFP34, OsHMP5, OsMTP7, OsC3H33, and OsHMA1 were associated with Fe and Zn QTLs. We identified promising RILs with acceptable yield potential and high grain Zn content from each population. The major effect QTLs, genes and high Zn RILs identified in our study are useful for efficient Zn biofortification of rice. [ABSTRACT FROM AUTHOR]

The recent surge in the plant-based protein market has resulted in high demands for soybean genotypes with improved grain yield, seed protein and oil content, and essential amino acids (EAAs). Given the quantitative nature of these traits, complex interactions among seed components, as well as between seed components and environmental factors and management practices, add complexity to the development of desired genotypes. In this study, the across-environment seed protein stability of 449 genetically diverse plant introductions was assessed, revealing that genotypes may display varying sensitivities to such environmental stimuli. The EAAs valine, phenylalanine, and threonine showed the highest variable importance toward the variation in stability, while both seed protein and oil contents were among the explanatory variables with the lowest importance. In addition, 56 single nucleotide polymorphism (SNP) markers were significantly associated with various seed components. Despite the strong phenotypic Pearson's correlation observed among most seed components, many independent genomic regions associated with one or few seed components were identified. These findings provide insights for improving the seed concentration of specific EAAs and reducing the negative correlation between seed protein and oil contents. [ABSTRACT FROM AUTHOR]

Phedimus latiovalifolius (Y.N.Lee) D.C.Son & H.J.Kim is exclusively distributed in the high mountains in the Korean Peninsula, mainly along the Baekdudaegan mountain range. Despite its morphological and distributional distinction from other Phedimus Raf. species, its taxonomic identity and phylogenetic relationship with congeneric species remain unclear. This study employs genotyping-by-sequencing-derived genome-wide single nucleotide polymorphisms to establish the monophyly of P. latiovalifolius and its relationship with closely related species. Genetic diversity and population differentiation of P. latiovalifolius are also assessed to provide baseline genetic information for future conservation and management strategies. Our phylogenetic analyses robustly demonstrate the monophyletic nature of P. latiovalifolius, with P. aizoon (L.) ‘t Hart identified as its closest sister lineage. There is no genetic evidence supporting a hybrid origin of P. latiovalifolius from P. aizoon involving either P. ellacombeanus (Praeger) ‘t Hart or P. kamtschaticus (Fisch.) ‘t Hart. Population genetic analyses reveal two major groups within P. latiovalifolius. A higher genetic variation is observed in P. ellacombeanus than in the congeneric species. Notably, most of the genetic variation exists within P. latiovalifolius populations. Given its distribution and the potential role of Baekdudaegan as an East Asian Pleistocene refugia, P. latiovalifolius could be considered rare and endemic, persisting in the refugium across glacial/interglacial cycles. [ABSTRACT FROM AUTHOR]

Leaf scald, caused by Xanthomonas albilineans, is a severe disease affecting sugarcane worldwide. One of the most practical ways to control it is by developing resistant sugarcane cultivars. It is essential to identify genes associated with the response to leaf scald. A panel of 170 sugarcane genotypes was evaluated for resistance to leaf scald in field conditions for 2 years, followed by a 1-year greenhouse experiment. The phenotypic evaluation data showed a wide continuous distribution, with heritability values ranging from 0.58 to 0.84. Thirteen single nucleotide polymorphisms (SNPs) were identified, significantly associated with leaf scald resistance. Among these, eight were stable across multiple environments and association models. The candidate genes identified and validated based on RNA-seq and qRT-PCR included two genes that encode NB-ARC leucine-rich repeat (LRR)-containing domain disease-resistance protein. These findings provide a basis for developing marker-assisted selection strategies in sugarcane breeding programs. [ABSTRACT FROM AUTHOR]

The incidence of Pseudomonas aeruginosa infections in healthcare environments, particularly in low-and middle-income countries, is on the rise. The purpose of this study was to provide comprehensive genomic insights into thirteen P. aeruginosa isolates obtained from Egyptian healthcare settings. Phenotypic analysis of the antimicrobial resistance profile and biofilm formation were performed using minimum inhibitory concentration and microtiter plate assay, respectively. Whole genome sequencing was employed to identify sequence typing, resistome, virulome, and mobile genetic elements. Our findings indicate that 92.3% of the isolates were classified as extensively drug-resistant, with 53.85% of these demonstrating strong biofilm production capabilities. The predominant clone observed in the study was ST773, followed by ST235, both of which were associated with the O11 serotype. Core genome multi-locus sequence typing comparison of these clones with global isolates suggested their potential global expansion and adaptation. A significant portion of the isolates harbored Col plasmids and various MGEs, all of which were linked to antimicrobial resistance genes. Single nucleotide polymorphisms in different genes were associated with the development of antimicrobial resistance in these isolates. In conclusion, this pilot study underscores the prevalence of extensively drug-resistant P. aeruginosa isolates and emphasizes the role of horizontal gene transfer facilitated by a diverse array of mobile genetic elements within various clones. Furthermore, specific insertion sequences and mutations were found to be associated with antibiotic resistance. [ABSTRACT FROM AUTHOR]

The duration-of-fertility (DF), which was defined as the number of days when breeding hens lay fertile eggs following copulation or artificial insemination (AI), is an important economic trait in chick production when it has strong effects on fertile egg output and production costs. Little is known about the underlying genes and molecular markers related to DF trait to date. Here, we measured the DF of 701 Chinese Jinghong hens and 408 Jingfen hens. The DF showed high individual variability and potential for genetic improvement. Then, 192 Jinghong breeding hens were provided for a genome-wide association study, 27 SNPs respectively located in three genomic linkage regions (GGA1:41Kb; GGA3:39Kb and GGA8:39Kb) were suggested to be significantly associated with DF. Particularly, 6 of these 27 SNPs were further verified to be associated with DF in the 701 Jinghong and 408 Jingfen hens using PCR-RFLP genotyping method. These 27 SNPs were also mapped to 7 genes according to their genomic position. Furtherly, 5 of these 7 genes were tested using qPCR. Results show that the CYP2D6, WBP2NL, ESR1 and TGFBR3 mRNA expression levels of hens with long DF were significantly higher than the hens with short DF (P < 0.05). Overall, findings in our research provide new insight into the genetic basis of duration-of-fertility in breeding hens while providing new clues for further functional validation on the DF-related genetic regulation mechanism and improvement of DF through chicken breeding. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the genetic polymorphisms of related gene loci (CYP2C9*3, VKORC1-1639G > A) based on demographic and clinical factors, and use the maximum a posterior Bayesian method to construct a warfarin individualized dose prediction model in line with the Chinese Han population. Finally, the built model is compared and analyzed with the widely used models at home and abroad. In this study, a total of 5467 INR measurements are collected from 646 eligible subjects in our hospital, and the maximum a posterior Bayesian method is used to construct a warfarin dose prediction that conforms to the Chinese Han population on the basis of the Hamberg model. The model is verified and compared with foreign models. This study finds that body weight and concomitant use of amiodarone have a significant effect on the anticoagulant effect of warfarin. The model can provide an effective basis for individualized and rational dosing of warfarin in Han population more accurately. In the performance of comparison with different warfarin dose prediction models, the new model has the highest prediction accuracy, and the prediction percentage is as high as 72.56%. The dose predicted by the Huang model is the closest to the actual dose of warfarin. The population pharmacokinetics and pharmacodynamics model established in this study can better reflect the distribution characteristics of INR values after warfarin administration in the Han population, and performs better than the models reported in the literature. [ABSTRACT FROM AUTHOR]

Idiopathic normal pressure hydrocephalus (iNPH) affects mainly aged populations. The gradual shortening of telomere length (TL) is one of the hallmarks of aging. Whereas the genetic contribution of TL to the iNPH is incompletely understood. We aimed to investigate the causal relationship between TL and iNPH through the Mendelian randomization (MR) analysis. We respectively obtained 186 qualified single nucleotide polymorphisms (SNPs) of TL and 20 eligible SNPs of iNPH for MR analysis. The result of MR analysis showed that genetically predicted longer TL was significantly associated with a reduced odd of iNPH (odds ratio [OR] = 0.634 95% Confidence interval [CI] 0.447–0.899, p = 0.011). The causal association remained consistent in multivariable MR (OR = 0.530 95% CI 0.327–0.860, p = 0.010). However, there was no evidence that the iNPH was causally associated with the TL (OR = 1.000 95% CI 0.996–1.004, p = 0.955). Our study reveals a potential genetic contribution of TL to the etiology of iNPH, that is a genetically predicted increased TL might be associated with a reduced risk of iNPH. [ABSTRACT FROM AUTHOR]

The microbial communities of the oral cavity are important elements of oral and systemic health. With emerging evidence highlighting the heritability of oral bacterial microbiota, this study aimed to identify host genome variants that influence oral microbial traits. Using data from 16S rRNA gene amplicon sequencing, we performed genome-wide association studies with univariate and multivariate traits of the salivary microbiota from 610 unrelated adults from the Danish ADDITION-PRO cohort. We identified six single nucleotide polymorphisms (SNPs) in human genomes that showed associations with abundance of bacterial taxa at different taxonomical tiers (P < 5 × 10–8). Notably, SNP rs17793860 surpassed our study-wide significance threshold (P < 1.19 × 10–9). Additionally, rs4530093 was linked to bacterial beta diversity (P < 5 × 10–8). Out of these seven SNPs identified, six exerted effects on metabolic traits, including glycated hemoglobin A1c, triglyceride and high-density lipoprotein cholesterol levels, the risk of type 2 diabetes and stroke. Our findings highlight the impact of specific host SNPs on the composition and diversity of the oral bacterial community. Importantly, our results indicate an intricate interplay between host genetics, the oral microbiota, and metabolic health. We emphasize the need for integrative approaches considering genetic, microbial, and metabolic factors. [ABSTRACT FROM AUTHOR]

Although there is an association between abdominal aortic aneurysm (AAA) and circulating immune cell phenotypes, the exact causal relationship remains unclear. This study aimed to explore the causal relationships between immune cell phenotypes and AAA risk using a bidirectional two-sample Mendelian randomization approach. Data from genome-wide association studies pertaining to 731 immune cell traits and AAA were systematically analyzed. Using strict selection criteria, we identified 339 immune traits that are associated with at least 3 single nucleotide polymorphisms. A comprehensive MR analysis was conducted using several methods including Inverse Variance Weighted, Weighted Median Estimator, MR-Egger regression, Weighted Mode, and Simple Median methods. CD24 on switched memory cells (OR = 0.922, 95% CI 0.914–0.929, P = 2.62e−79) at the median fluorescence intensities level, and SSC-A on HLA-DR + natural killer cells (OR = 0.873, 95% CI 0.861–0.885, P = 8.96e−81) at the morphological parameter level, exhibited the strongest causal associations with AAA. In the reverse analysis, no significant causal effects of AAA on immune traits were found. The study elucidates the causal involvement of multiple circulating immune cell phenotypes in AAA development, signifying their potential as diagnostic markers or therapeutic targets. These identified immune traits may be crucial in modulating AAA-related inflammatory pathways. [ABSTRACT FROM AUTHOR]

Genome interpretation (GI) encompasses the computational attempts to model the relationship between genotype and phenotype with the goal of understanding how the first leads to the second. While traditional approaches have focused on sub-problems such as predicting the effect of single nucleotide variants or finding genetic associations, recent advances in neural networks (NNs) have made it possible to develop end-to-end GI models that take genomic data as input and predict phenotypes as output. However, technical and modeling issues still need to be fixed for these models to be effective, including the widespread underdetermination of genomic datasets, making them unsuitable for training large, overfitting-prone, NNs. Here we propose novel GI models to address this issue, exploring the use of two types of transfer learning approaches and proposing a novel Biologically Meaningful Sparse NN layer specifically designed for end-to-end GI. Our models predict the leaf and seed ionome in A.thaliana, obtaining comparable results to our previous over-parameterized model while reducing the number of parameters by 8.8 folds. We also investigate how the effect of population stratification influences the evaluation of the performances, highlighting how it leads to (1) an instance of the Simpson's Paradox, and (2) model generalization limitations. [ABSTRACT FROM AUTHOR]

Speech-in-noise (SIN) perception is a primary complaint of individuals with audiometric hearing loss. SIN performance varies drastically, even among individuals with normal hearing. The present genome-wide association study (GWAS) investigated the genetic basis of SIN deficits in individuals with self-reported normal hearing in quiet situations. GWAS was performed on 279,911 individuals from the UB Biobank cohort, with 58,847 reporting SIN deficits despite reporting normal hearing in quiet. GWAS identified 996 single nucleotide polymorphisms (SNPs), achieving significance (p < 5*10−8) across four genomic loci. 720 SNPs across 21 loci achieved suggestive significance (p < 10−6). GWAS signals were enriched in brain tissues, such as the anterior cingulate cortex, dorsolateral prefrontal cortex, entorhinal cortex, frontal cortex, hippocampus, and inferior temporal cortex. Cochlear cell types revealed no significant association with SIN deficits. SIN deficits were associated with various health traits, including neuropsychiatric, sensory, cognitive, metabolic, cardiovascular, and inflammatory conditions. A replication analysis was conducted on 242 healthy young adults. Self-reported speech perception, hearing thresholds (0.25–16 kHz), and distortion product otoacoustic emissions (1–16 kHz) were utilized for the replication analysis. 73 SNPs were replicated with a self-reported speech perception measure. 211 SNPs were replicated with at least one and 66 with at least two audiological measures. 12 SNPs near or within MAPT, GRM3, and HLA-DQA1 were replicated for all audiological measures. The present study highlighted a polygenic architecture underlying SIN deficits in individuals with self-reported normal hearing. [ABSTRACT FROM AUTHOR]

The prevalence of thyroid dysfunction diseases (TDFDs) and osteoporosis (OP) is high. Previous studies have indicated a potential association between TDFDs and OP, yet the causal direction remains unclear. This study aimed to investigate the potential causal relationship between TDFDs and the risk of developing OP and related fractures. We obtained pooled data from genome-wide association studies (GWASs) conducted on TDFDs and OP in European populations and identified single-nucleotide polymorphisms (SNPs) with genome-wide significance levels associated with exposure to TDFDs as instrumental variables. Inverse variance weighted (IVW) was employed as the primary method for Mendelian randomization (MR) analysis, supplemented by MR‒Egger, weighted median, simple mode and weighted mode methods. Sensitivity analyses were conducted to evaluate the robustness of the findings. The IVW method demonstrated an increased risk of OP in patients with TDFDs, including hyperthyroidism and hypothyroidism (TDFDs: OR = 1.11; 95% CI 1.09, 1.13; hypothyroidism: OR = 1.14; 95% CI 1.10, 1.17; hyperthyroidism: OR = 1.09; 95% CI 1.06, 1.12). These findings were supported by supplementary analysis, which revealed a positive correlation between TDFDs and the risk of OP. Multiple sensitivity analyses confirmed the absence of horizontal pleiotropy in the study, thus indicating the robustness of our results. The causal relationship between TDFDs and increased risk of OP implies the need for early bone mineral density (BMD) screening and proactive prevention and treatment strategies for individuals with TDFDs. [ABSTRACT FROM AUTHOR]

Abstract Single nucleotide polymorphisms (SNPs) are one of the most common determinants and potential biomarkers of human disease pathogenesis. SNPs could alter amino acid residues, leading to the loss of structural and functional integrity of the encoded protein. In humans, members of the minichromosome maintenance (MCM) family play a vital role in cell proliferation and have a significant impact on tumorigenesis. Among the MCM members, the molecular mechanism of how missense SNPs of minichromosome maintenance complex component 6 (MCM6) contribute to DNA replication and tumor pathogenesis is underexplored and needs to be elucidated. Hence, a series of sequence and structure-based computational tools were utilized to determine how mutations affect the corresponding MCM6 protein. From the dbSNP database, among 15,009 SNPs in the MCM6 gene, 642 missense SNPs (4.28%), 291 synonymous SNPs (1.94%), and 12,500 intron SNPs (83.28%) were observed. Out of the 642 missense SNPs, 33 were found to be deleterious during the SIFT analysis. Among these, 11 missense SNPs (I123S, R207C, R222C, L449F, V456M, D463G, H556Y, R602H, R633W, R658C, and P815T) were found as deleterious, probably damaging, affective and disease-associated. Then, I123S, R207C, R222C, V456M, D463G, R602H, R633W, and R658C missense SNPs were found to be highly harmful. Six missense SNPs (I123S, R207C, V456M, D463G, R602H, and R633W) had the potential to destabilize the corresponding protein as predicted by DynaMut2. Interestingly, five high-risk mutations (I123S, V456M, D463G, R602H, and R633W) were distributed in two domains (PF00493 and PF14551). During molecular dynamics simulations analysis, consistent fluctuation in RMSD and RMSF values, high Rg and hydrogen bonds in mutant proteins compared to wild-type revealed that these mutations might alter the protein structure and stability of the corresponding protein. Hence, the results from the analyses guide the exploration of the mechanism by which these missense SNPs of the MCM6 gene alter the structural integrity and functional properties of the protein, which could guide the identification of ways to minimize the harmful effects of these mutations in humans.

Abstract The associations of vitamin D receptor (VDR)- single nucleotide polymorphisms (SNPs) with the symptoms of COVID-19 may vary between patients with different severities of COVID-19. Therefore, in the present study, we aim to compare VDR polymorphisms in severe and mild COVID-19 patients. In this study, a total number of 85 hospitalized patients and 91 mild/moderate patients with COVID-19 were recruited. SNPs in VDR genes were determined using ARMS and then confirmed by sanger sequencing. The mean (SD) age of participants in hospitalized and non-hospitalized group was 59.0 (12.4) and 47.8 (14.8) years, respectively. Almost 46% of participants in hospitalized and 48% of participant in non-hospitalized group were male. The frequency of TT genotype of SNP rs11568820 was significantly lower in hospitalized than non-hospitalized group (3.5% vs. 17.6%; P = 0.018). However, there was no significant differences between genotypes of SNPs rs7970314 and rs4334089 and also alleles frequencies in all SNPs of two groups. The genotype of rs11568820 SNP had an inverse association with hospitalization of patients with COVID-19 after adjustment for comorbidities [OR 0.18, 95% CI 0.04, 0.88; P = 0.034]. While, there was no relationship between genotypes of SNPs rs7970314 and rs4334089 and hospitalization. The TT genotype of rs11568820 plays protective role in sever COVID-19 and hospitalization. Further studies with a large sample size which consider various confounding factors are warranted to confirm our results.