Frontiers in Genetics最新文献

Existing genotype imputation reference panels are mainly derived from European populations, limiting their accuracy in non-European populations. To improve imputation accuracy for Indonesians, the world's fourth most populous country, we combined Whole Genome Sequencing (WGS) data from 227 West Javanese individuals with East Asian data from the 1,000 Genomes Project. This created three reference panels: EAS 1KGP3 (EASp), Indonesian (INDp), and a combined panel (EASp + INDp). We also used ten West-Javanese samples with WGS and SNP-typing data for benchmarking. We identified 1.8 million novel single nucleotide variants (SNVs) in the West Javanese population, which, while similar to the East Asians, are distinct from the Central Indonesian Flores population. Adding INDp to the EASp reference panel improved imputation accuracy (R2) from 0.85 to 0.90, and concordance from 87.88% to 91.13%. These findings underscore the importance of including West-Javanese genetic data in reference panels, advocating for broader WGS of diverse Indonesian populations to enhance genomic studies.

Background: Obesity, a prevalent metabolic disorder, is linked to perturbations in the balance of gene expression regulation. Noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs), play pivotal roles in regulating gene expression. The aim of this study was to identify additional ncRNA candidates that are implicated in obesity, elucidating their potential as key regulators of the pathogenesis of obesity.

Methods: We identified distinct ncRNA expression profiles in omental adipose tissue in obese and healthy subjects through comprehensive whole-transcriptome sequencing. Subsequent analyses included functional annotation with GO and KEGG pathway mapping, validation via real-time quantitative polymerase chain reaction (qRT‒PCR), the exploration of protein‒protein interactions (PPIs), and the identification of key regulatory genes through network analysis.

Results: The results indicated that, compared with those in healthy individuals, various lncRNAs, circRNAs, and miRNAs were significantly differentially expressed in obese subjects. Further verifications of top changed gene expressions proved the most genes' consistence with RNA-sequencing including 11 lncRNAs and 4 circRNAs. Gene network analysis highlighted the most significant features associated with metabolic pathways, specifically ENST00000605862, ENST00000558885, and ENST00000686149. Collectively, our findings suggest potential ncRNA therapeutic targets for obesity, including ENST00000605862, ENST00000558885, and ENST00000686149.

Background: Sepsis, a critical infectious disease, is intricately linked to the dysfunction of the intracellular Golgi apparatus. This study aims to explore the relationship between sepsis and the Golgi apparatus using bioinformatics, offering fresh insights into its diagnosis and treatment.

Methods: To explore the role of Golgi-related genes in sepsis, we analyzed mRNA expression profiles from the NCBI GEO database. We identified differentially expressed genes (DEGs). These DEGs, Golgi-associated genes obtained from the MSigDB database, and key modules identified through WGCNA were intersected to determine Golgi-associated differentially expressed genes (GARGs) linked to sepsis. Subsequently, functional enrichment analyses, including GO, KEGG, and GSEA, were performed to explore the biological significance of the GARGs.A PPI network was constructed to identify core genes, and immune infiltration analysis was performed using the ssGSEA algorithm. To further evaluate immune microenvironmental features, unsupervised clustering was applied to identify immunological subgroups. A diagnostic model was developed using logistic regression, and its performance was validated using ROC curve analysis. Finally, key diagnostic biomarkers were identified and validated across multiple datasets to confirm their diagnostic accuracy.

Results: By intersecting DEGs, WGCNA modules, and Golgi-related gene sets, 53 overlapping GARGs were identified. Functional enrichment analysis indicated that these GARGs were predominantly involved in protein glycosylation and Golgi membrane-related processes. PPI analysis further identified eight hub genes: B3GNT5, FUT11, MFNG, ST3GAL5, MAN1C1, ST6GAL1, C1GALT1C1, and GALNT14. Immune infiltration analysis revealed significant differences in immune cell populations, mainly activated dendritic cells, and effector memory CD8⁺ T cells, between sepsis patients and healthy controls. A diagnostic model constructed using five pivotal genes (B3GNT5, FUT11, MAN1C1, ST6GAL1, and C1GALT1C1) exhibited predictive accuracy, with AUC values exceeding 0.96 for all genes. Validation with an independent dataset confirmed the differential expression patterns of B3GNT5, C1GALT1C1, and GALNT14, reinforcing their potential as robust diagnostic biomarkers for sepsis.

Conclusion: This study elucidates the link between sepsis and the Golgi apparatus, introduces novel biomarkers for sepsis diagnosis, and offers valuable insights for future research on its pathogenesis and treatment strategies.

Introduction: The role of syngameons in adaption to microgeographical environmental heterogeneity is important and could be one of the sources of rich species diversity in tropical forests. In addition, negative frequency- or density-dependent selection is one of the major processes contributing to the maintenance of genetic diversity.

Methods: To assess genetic factors that affect the fitness of seedlings of Rubroshorea curtisii, a dominant canopy tree species in hill dipterocarp forests, the inter- and intra-population genetic structure of individuals from natural populations and individuals at two permanent plots in a hill dipterocarp forest with reproductive stage was studied. Further, a total of 460 seedlings derived from six mother trees in the plot were raised in a nursery, and their pollen donors were identified using genetic marker based paternity assignment. Seed weight, bi-parental genetic relatedness, and bi-parental genetic heterogeneity based on the clustering analysis were used to analyze their effects on seedling fitness.

Results: A Bayesian based clustering analysis revealed that three genetically distinct clusters were observed in almost all populations throughout the distributional range of the species in Malay Peninsula and provided the optimum explanation for the genetic structure of 182 mature individuals in the plots. The two clusters showed larger genetic differentiation from the ancestral admixture population, but the other one was not differentiated. The bi-parental larger genetic heterogeneity was associated with a significantly higher probability of seedling survivorship, and likewise, higher performance of vertical growth of the seedlings; but the seed weight and genetic relatedness did not significantly affect those.

Discussion: This evidence suggests that fitter seedlings derived from mating between parents with different genetic clusters contribute to maintaining genetic diversity through negative frequency-dependent selection and may have an important role in adaptation in the tropical forest plant community.

Objective: Long non-coding RNA (lncRNA) is aberrantly expressed in a variety of tumor diseases. To date, its specific role in acute myeloid leukemia (AML) has not been fully elucidated. This study aims to evaluate the association between aberrant lncRNA expression and poor prognosis in AML patients, and to systematically assess the relationship between aberrant lncRNA expression and AML prognosis.

Methods: We conducted a comprehensive literature search in PubMed, Embase, Cochrane Library, CNKI (China National Knowledge Infrastructure), WanFang (China Wanfang Database), VIP (China VIP Database), and Sinomed (China Biomedical Literature Database) to identify relevant Chinese and English articles. The search period covered from the inception of these databases to 4 August 2024. Articles were screened according to predefined inclusion and exclusion criteria, and meta-analysis was performed using Stata.

Results: A total of 25 articles were included in the analysis. Aberrant lncRNA expression was significantly associated with reduced overall survival (univariate HR = 2.46, 95%CI 2.11-2.88, P < 0.001; multivariate HR = 2.46, 95%CI 2.11-2.88, P < 0.001), event-free survival (HR = 1.51, 95%CI 1.19-1.90, P = 0.001), recurrence-free survival (HR = 2.82, 95%CI 2.03-3.91, P < 0.001), and disease-free survival (HR = 2.390, 95%CI 1.037-5.507, P = 0.041). These findings were statistically significant. The 25 articles collectively identified 22 lncRNAs whose aberrant expression was associated with AML prognosis. Notably, multiple studies highlighted the aberrant expression of lncRNA CRNDE, ZEB2-AS1, and TUG1 as being particularly relevant to AML prognosis. Our meta-analysis revealed that high expression of lncRNA CRNDE and TUG1 was associated with reduced overall survival, while high expression of lncRNA ZEB2-AS1 was linked to decreased disease-free survival, both with statistically significant differences.

Conclusion: The expression levels of lncRNAs are closely associated with the prognosis of AML patients and may serve as important indicators for monitoring prognosis in the future. However, further high-quality studies are needed to validate these findings.

TCP transcription factors are a unique class of transcription factors that play important roles in alleviating abiotic stresses such as drought and salt. In this study, the whole-genome data of three cultivated varieties, namely, "SFS", "Sang" and "OT3098v2", were utilized to identify and analyze the members of the TCP gene family in oats, and their responses to two abiotic stresses, drought and salt, were also investigated. Results showed that there are 83, 65, and 30 non-redundant TCP genes in the three oats, with the highest number of TCP genes specific to the "SFS", reaching 22 genes. The oat TCP genes can be classified into three subfamilies: PCF, CIN, and CYC/TB1. Most AsTCP genes have important motifs, Motif 1 and Motif 2, which are part of the bHLH domain. Additionally, various cis-acting elements related to hormone response, abiotic stress, light response, and growth and development were found in the promoters of AsTCP genes. The main amplification mechanism of the oat TCP gene family is fragment duplication. Two tandem duplications, AsTCP058/AsTCP059 and AsTCP023/AsTCP025, are stably present in the three oats. The highest number of AsTCP collinear relationships exist in the "SFS" with 89 pairs. After drought and salt stress treatments, significant differences in gene expression were observed among different oat cultivars and treatment periods. Genes that showed significant expression changes under both treatments (AsTCP021, AsTCP033, AsTCP044, AsTCP053, and AsTCP058) may play important roles in oat's response to abiotic stresses. Notably, AsTCP053 gene was significantly upregulated at 24 h of stress treatment and showed a more sensitive response to salt stress. This study provides insights into the functional characterization of the oat TCP gene family and its molecular mechanisms underlying stress tolerance.

Background: Dystrophin is a key protein encoded by the DMD gene, serves as a scaffold linking the cytoskeleton to the extracellular matrix that plays a critical role in muscle contraction, relaxation, and structural integrity. Mutations, particularly single-point amino acid substitutions, can lead to dysfunctional Dystrophin, causing muscular dystrophies, with Duchenne muscular dystrophy (DMD) being the most severe form.

Objective: This study aimed to evaluate the effects of 184 single-point amino acid substitutions on the structure and function of Dystrophin using computational approaches.

Methods: Many computational tools were used to predict the impact of amino acid substitutions on protein stability, solubility, and function. Pathogenic potential was assessed using disease phenotype predictors and CADD scores, while allele frequency data from gnomAD contextualized mutation prevalence. Additionally, aggregation propensity, frustration analysis, and post-translational modification sites were analyzed for functional disruptions.

Results: Of the 184 substitutions analyzed, 50 were identified as deleterious, with 41 predicted to be pathogenic. Seventeen mutations were localized in the Calponin-homology (CH) 1 domain, a critical functional region of Dystrophin. Six substitutions (N26H, N26K, G47W, D98G, G109A, and G109R) were predicted to decrease protein solubility and were located in minimally frustrated regions, potentially compromising Dystrophin functionality and contributing to DMD pathogenesis.

Conclusion: This study provides novel insights into the molecular mechanisms of DMD, highlighting specific mutations that disrupt Dystrophin's solubility and function. These findings could inform future therapeutic strategies targeting Dystrophin mutations to address DMD pathogenesis.

Introduction: Endoscopic tissue biopsy combined with histopathology is the gold standard for the diagnosis of colorectal cancer (CRC); however, the invasive nature of this procedure hinders its acceptance by patients. Therefore, there exists a critical need to identify novel markers facilitating early CRC detection and prognosis. Circular RNAs (circRNAs) hold promise as novel clinical diagnostic markers. This study aimed to investigate the impact of circDOCK1 on CRC metastasis and prognosis as well as its underlying molecular mechanisms.

Methods: We explored circRNA expression profiles in four pairs of CRC tissues and adjacent non-carcinoma tissues via microarray analysis. After Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and circRNA-miRNA network analyses, circDOCK1 was chosen for further investigation. We evaluated its clinical relevance in 80 CRC tissue pairs and adjacent controls, correlating circDOCK1 expression with clinical characteristics. Follow-up data from patient telephone interviews were analyzed for survival outcomes. Transfection efficiency was confirmed via qRT-PCR in HCT116 and SW480 colon cells, and the effects of circDOCK1 on cell proliferation, migration, and invasion were assessed.

Results: Microarray data revealed 149 significantly differentially expressed circRNAs, including 71 upregulated and 78 downregulated circRNAs, in CRC tissues. CircDOCK1 exhibited elevated expression in patients with CRC and emerged as an independent prognostic factor. Kaplan-Meier curve analysis suggested that circDOCK1 expression is an unfavorable prognostic factor in patients with CRC. In vivo experiments revealed that circDOCK1 overexpression enhanced the proliferation, migration, and invasion of CRC cells, with consistent results upon circDOCK1 downregulation.

Conclusion: These data indicate that circDOCK1 may play a role in promoting the proliferation, migration, and invasion of CRC cells, suggesting its potential as a CRC biomarker.

Introduction: Polygenic Scores (PGSs) assess cumulative genetic risk variants that contribute to the association with complex diseases like Alzheimer's Disease (AD). The PGS Catalog is a valuable repository of PGSs of various complex diseases, but it lacks standardized annotations and harmonization, making the information difficult to integrate for a specific disease.

Methods: In this study, we curated 44 PGS datasets for AD from the PGS Catalog, categorized them into five methodological groups, and annotated 813,257 variants to nearby genes. We aligned the scores based on the "GWAS significant variants" (GWAS-SV) method with the GWAS Catalog and flagged redundant files and those with a "limited scope" due to insufficient external GWAS support. Using rank aggregation (RA), we prioritized consistently important variants and provided an R package, "PgsRankRnnotatR," to automate this process.

Results: Of the six RA methods evaluated, "Dowdall" method was the most robust. Our refined dataset, enhanced by multiple RA options, is a valuable resource for AD researchers selecting PGSs or exploring AD-related genetic variants.

Discussion: Our approach offers a framework for curating, harmonizing, and prioritizing PGS datasets, improving their usability for AD research. By integrating multiple RA methods and automating the process, we provide a flexible tool that enhances PGS selection and genetic variant exploration. This framework can be extended to other complex diseases or traits, facilitating broader applications in genetic risk assessment.