Search Results (322)

This study systematically explored immune targets in gastric adenocarcinoma (GAC) suitable for mRNA vaccine development. Based on multi-omics data from public databases, we first screened a set of potential tumor-associated antigen genes. Subsequently, using ten machine learning algorithms, we constructed 101 prognostic models and, through optimization and comparison, selected the Random Survival Forest (RSF) method to establish a clinical prognostic model for GAC consisting of seven genes (TYMP, IFGN, ITGAX, GBP5, GBP4, STAT1, CD84). At both the genetic and protein levels, these genes were closely associated with the antigen presentation process, suggesting the potential functional role of this model in antigen presentation. Further analysis of the immune infiltration characteristics in GAC preliminarily revealed its possible immune evasion mechanisms. Building on this, we designed candidate mRNA vaccine templates for GAC using the mRNAdesigner platform. Additionally, this study investigated the potential roles of the above seven genes in GAC progression and screened small-molecule compounds targeting these genes. Molecular dynamics simulations (MD) were performed to verify the binding stability between these compounds and their corresponding proteins. This study comprehensively simulated the tumor microenvironment (TME) and antigen presentation process in GAC, evaluated the clinical translation potential of the neoantigen prognostic model and its predictive value for immunotherapy, and provided a preliminary design scheme for an mRNA vaccine against GAC. The findings offer new evidence for identifying immune therapy targets in GAC and are expected to advance the development of immunotherapy strategies for GAC. Full article

Silver–Russell syndrome (SRS) is most commonly caused by epigenetic alterations at 11p15.5 or maternal uniparental disomy of chromosome 7 [upd(7)mat], though other molecular mechanisms remain unclear. While microdeletions encompassing MEST have been associated with SRS-like phenotypes, no pathogenic intragenic MEST variants have been reported to date. We describe a 6-month-old male infant with clinical features suggestive of a SRS-like phenotype, including intrauterine and postnatal growth restriction, triangular facies, prominent forehead, and small extremities. Methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) revealed neither methylation abnormalities at 11p15.5, 7p13, or 7q32 nor copy number variations (CNVs) in these regions. Trio whole-exome sequencing (trio-WES) identified a paternally inherited splice-site variant (c.890 + 1G > A) in MEST. Given the paternal-specific expression of MEST, this variant resides on the functionally active allele. Based on in silico predictions and clinical correlation, this case identifies MEST as a plausible candidate gene for SRS and provides a rationale for further functional studies. Phenotypic variation exists across molecular subtypes, yet definitive genotype–phenotype correlations await larger, systematically ascertained cohorts. Full article

Soft tissue sarcomas (STSs) are a heterogeneous group of rare mesenchymal malignancies with overlapping morphological and immunohistochemical features, often making definitive diagnosis challenging. Recent advances in next-generation sequencing (NGS) have enabled the identification of recurrent molecular alterations that contribute to tumor classification, prognostic stratification, and precision oncology approaches. This retrospective study aimed to evaluate the diagnostic and clinical impact of molecular profiling in pediatric soft tissue sarcomas using the Oncomine Childhood Cancer Research Assay (OCCRA) panel. Fifty-five frozen tumor samples representing 24 distinct soft tissue sarcoma subtypes were obtained from the Pediatric Oncology Institute -IOP/GRAACC/UNIFESP Biobank (B-053). Molecular analysis was performed using NGS to identify gene fusions, single nucleotide variants (SNVs), copy number variations (CNVs), and insertions/deletions (InDels). Clinically relevant molecular alterations were identified in 70% (37/55) of cases, including 18 fusion transcripts, 13 SNVs, 8 CNVs, and 6 InDels. Recurrent and diagnostically relevant alterations included BCOR::CCNB3, ASPSCR1::TFE3, NFR1::BRAF, FUS::DDIT3, EML4::NTRK3, ETV6::NTRK3, CIC::DUX4, NAB2::STAT6 and SS18::SSX1/2 fusions, as well as amplifications involving PDGFRA, FGFR1, GLI1, CDK4, ERBB3, and KIT. Pathogenic variants affecting genes involved in tumor suppression and chromatin remodeling, including TP53, NF1, DICER1, SMARCA4, PTEN, and PIK3CA, were also detected. Importantly, molecular profiling had significant diagnostic impact in several histologically ambiguous tumors, enabling molecular reclassification and refinement of previously inconclusive or inaccurate pathological diagnoses. In multiple cases, NGS transformed descriptive histopathological interpretations into genetically defined sarcoma entities, including NTRK-rearranged spindle cell neoplasms, CIC-rearranged sarcomas, synovial sarcoma, low-grade fibromyxoid sarcoma, and clear cell sarcoma. Furthermore, the identification of actionable alterations highlighted potential opportunities for targeted therapies and precision medicine approaches. Our findings demonstrate that comprehensive molecular profiling significantly enhances diagnostic accuracy in pediatric soft tissue sarcomas, particularly in morphologically challenging cases. The integration of NGS into routine sarcoma diagnostics enables biologically informed tumor classification and supports personalized therapeutic strategies. Full article

Copy number variation (CNV) is a major class of genomic structural variation that can shape economically important traits by altering gene dosage and gene expression. MAX (MYC-associated factor X), a core component of the MYC-MAX-MXD1 transcriptional regulatory network, is critically involved in cell proliferation, differentiation, and development. However, the relationship between MAX CNVs and morphometric traits in cattle remains largely unknown. Here, we genotyped MAX CNVs by quantitative real-time PCR (qPCR) in 572 Chinese cattle from five breeds, including Qinchuan (QC), Ji’an (JA), Jinnan (JN), Nanyang (NY), and Xianan (XN) cattle, and evaluated the association of MAX CNVs with morphometric traits. MAX CNVs exhibited distinct breed-specific distribution patterns: the gain type predominated in QC, the loss type predominated in JN, NY, and XN, whereas JA showed a relatively balanced distribution across the three CNV types. Based on raw p values, MAX CNVs showed a nominal association with chest girth in JN cattle and nominal associations with chest girth and hucklebone width in NY cattle (p < 0.05). Individuals with the medium type showed higher least-squares means for the nominally associated traits than those with the loss or gain types. MAX CNVs explained 5.9% of the phenotypic variance in chest girth in JN cattle and 13.6% and 12.2% of the phenotypic variance in chest girth and hucklebone width in NY cattle, respectively. These results suggest that MAX CNVs may represent a breed-specific candidate locus related to morphometric traits in Chinese cattle. However, because no formal multiple-testing correction was applied and this study did not include independent population validation or functional validation, further studies are needed before considering any potential application in marker-assisted selection. Full article

Background: Human papillomavirus (HPV) infection defines a distinct subtype of head and neck squamous cell carcinoma (HNSCC). Although HPV-positive (HPV+) HNSCC generally shows better overall survival than HPV-negative (HPV−) disease, it is frequently associated with cervical lymph node metastasis. However, the epithelial cell states and viral gene-associated mechanisms underlying HPV−related metastatic progression remain incompletely understood. This study aimed to identify metastasis-associated epithelial subpopulations in HPV+ HNSCC and explore the potential role of HPV16 E7 in regulating metastatic programs. Methods: Public single-cell RNA-sequencing datasets from paired primary and metastatic HNSCC samples were integrated and analyzed to characterize malignant epithelial subpopulations. Copy number variation (CNV) inference, clustering, pathway enrichment, stemness scoring, and trajectory analysis were performed to define metastasis-associated epithelial states. TCGA transcriptomic data and tissue-based validation were used to support candidate gene screening. In vitro functional assays were performed using SERPINB3-knockdown and HPV16 early gene-overexpressing CAL27 cell models. Results: Single-cell analysis identified stem-like metastatic epithelial subpopulations in HPV+ and HPV− HNSCC. In HPV+ metastatic lesions, an ALDH2+/LAMB3+ epithelial subpopulation showed elevated epithelial–mesenchymal transition activity and stem-like features. SERPINB3 displayed a dynamic expression pattern during HPV+ metastatic progression. Functional assays showed that SERPINB3 knockdown enhanced CAL27 cell migration and invasion and was associated with activation of MYC- and epithelial–mesenchymal transition-related transcriptional programs. Among HPV16 early genes, E5, E6, E6*, and E7 showed different degrees of SERPINB3 suppression, while E7-expressing cells exhibited distinct transcriptional alterations associated with epithelial plasticity and metastatic-related programs. Conclusions: This study identifies a stem-like metastatic epithelial state in HPV-associated HNSCC and suggests a potential HPV16 early gene-SERPINB3-MYC-related regulatory mechanism involved in metastatic epithelial plasticity. Full article

The neurexin1 gene (NRXN1) encodes a presynaptic adhesion molecule that plays a critical role in synapse formation, maintenance, and function. Copy-number variants (CNVs) affecting the NRXN1 locus, including submicroscopic deletions, represent rare variant acting as a predisposition for neurodevelopmental disorders, such as Pitt–Hopkins-like syndrome type 2 (MIM #614325) and susceptibility to schizophrenia (MIM #621407). Variations in NRXN1 gene are associated with marked clinical heterogeneity. We present a familial case involving two male siblings (aged 6 and 5 years) and their 28-year-old mother, all exhibiting variable neurodevelopmental phenotypes. Both children demonstrated disharmonic developmental profiles characterized by impaired communication, speech largely intelligible only to their parents, and behaviors consistent with autism spectrum disorder, including reduced eye contact. Mother represents a carrier with only subtle, nonspecific behavioral traits, further supporting the concept of incomplete penetrance and variable expressivity associated with this genetic alteration. Genetic analysis identified a 317 kb NRXN1 deletion shared by all affected family members, accompanied by significant intrafamilial phenotypic variability, suggesting the contribution of additional genetic and/or modifying factors. These findings support the concept that NRXN1 deletions alone do not determine clinical outcome but rather act within a broader genetic and biological context. The marked intrafamilial phenotypic variability and incomplete penetrance observed in this family is compatible with a multiple-hit model, whereby NRXN1 deletions act as susceptibility factors whose phenotypic consequences are shaped by additional genetic and modifying influences. However, the genetic mechanisms underlying the observed phenotypic variability warrant further investigation. Full article

Soybean (Glycine max) is an important model crop for studying plant functional genes, such as the NAC transcription factor (TF) gene family. The NAC transcription factor (TF) family is one of the largest plant-specific TF families and plays critical roles in plant growth, development, and stress responses. In this study, we performed a pan-genome-wide analysis of NAC genes using 29 soybean genomes. A total of 5051 NAC genes were identified and clustered into 245 orthologous gene groups (OGGs), including 58 core, 88 soft-core, 32 shell, and 67 cloud groups. Based on phylogenetic relationships, the representative NAC OGGs were assigned to 18 subfamilies, 17 of which contained soybean NAC genes. Gene duplication analysis indicated that whole-genome duplication (WGD)/segmental duplication was the predominant driver of NAC family expansion, accounting for 90.88% of duplication events. Approximately 39.30% of NAC genes carried at least one intact transposable element (TE) within 2 kb upstream or downstream regions. NAC genes with copy number variation (CNV) harbored more nearby TEs than non-CNV genes (1.54 vs. 1.31 TEs per gene), and dispensable NAC genes contained more nearby TEs than core NAC genes (1.59 vs. 1.33 TEs per gene). These results indicate a significant association between local TE abundance and NAC gene CNV or dispensability. Selection pressure analysis showed that dispensable NAC genes had higher Ka, Ks, and Ka/Ks values than core genes, suggesting relatively relaxed evolutionary constraints. Expression profiling across six tissues revealed distinct transcriptional patterns among NAC subfamilies. Structurally conserved subfamilies generally showed broader expression, whereas structurally divergent subfamilies displayed greater expression variability. Regulatory network and Gene Ontology (GO) enrichment analyses suggested that conserved subfamilies were mainly associated with stress responses, while divergent subfamilies were related to cell wall regulation, signal transduction, and ion homeostasis. Further analysis of Wm82 drought RNA-seq data prioritized several putative drought-responsive NAC candidates, including Glyma.16G043200, Glyma.06G248900, Glyma.07G050600, Glyma.12G206900, and Glyma.18G261300. Overall, these findings elucidate the mechanisms of expansion and the functional divergence of the NAC gene family at the soybean pan-genome level, providing a theoretical basis for understanding NAC gene evolution and facilitating future crop improvement. Full article

Background: Comprehensive genomic profiling (CGP) via next-generation sequencing (NGS) is pivotal for precision oncology, yet many laboratories face challenges with incomplete genomic coverage, complex bioinformatics workflows, and limited integration of key biomarkers. Methods: We evaluated the analytical performance and clinical utility of a CGP assay using 119 tumor samples representing 18 types of cancer, previously analyzed with an orthogonal NGS panel. Concordance was assessed across 81 genes, covering 176 single-nucleotide variants (SNVs), eight copy number variations (CNVs), four deletions, one duplication, and four gene fusions. Limit of detection (LOD) studies employed AcroMetrix Mutant Hotspot Control and SeraSeq Lung and Brain CNV Mix. Microsatellite instability (MSI) and tumor mutational burden (TMB) were quantified. Inter- and intra-run reproducibility were evaluated to assess precision. Results: The CGP assay demonstrated high analytical performance, with >99% sensitivity, 100% specificity, and complete accuracy for variant detection. LOD studies revealed robust detection of SNVs at ≤5% variant allele frequencies (VAF) and CNVs at three copies. MSI and TMB results were consistent with clinical expectations, showing minimal bias compared to the orthogonal panel. Inter- and intra-run testing confirmed 100% reproducibility, indicating strong assay precision. Post-sequencing variant reporting was streamlined using the iCare platform, enabling direct FASTQ-to-report generation without intermediate bioinformatic steps. Conclusions: These findings support the present assay’s clinical utility in personalized oncology assessment. Full article

Host genetic susceptibility to urogenital Chlamydia trachomatis (Ct) reinfection remains poorly understood. Coding variants identified in prior genome-wide association studies (GWAS) explained only a small fraction of the risk of reinfection. Our goal in this study was to characterize whether more risk would be captured by sequence variation that traditional GWAS insufficiently captures. Specifically, we evaluated the risk attributable to SNPs present in regulatory, non-coding regions; post-transcriptional regulation by microRNAs (miRNAs) that may depend on sequence variation in either the miRNA or the target mRNA; and copy number variants (CNVs). We analyzed GWAS data from African American women with or without documented urogenital Ct reinfection. Fine mapping and independent association analyses identified 30 unique index single-nucleotide polymorphisms (iSNPs), which were expanded to variants in linkage disequilibrium. Regulatory annotation was performed using HaploReg, RegulomeDB, FORGEdb, rSNPBase, and GTEx. We examined whether genes identified in the Ct reinfection GWAS are targeted by known Ct infection–associated microRNAs using curated databases. Genome-wide CNV calling was conducted using SNP intensity data, followed by stringent quality control and gene-level association testing. Functional annotation prioritized 7 SNPs with strong regulatory evidence, with stringent criteria for regulatory relevance, using HaploReg, RegulomeDB, FORGEdb, and rSNPBase. The strongest signals were observed at the CHIT1 locus, where multiple intronic variants (including rs2486963 and rs2244385) overlapped regulatory chromatin, altered transcription factor binding motifs, and acted as cis-expression quantitative trait loci for CHIT1 in whole blood. Additional regulatory variants were identified near TDRP, ERICH1, and DLGAP1, showing tissue-specific regulatory effects. MicroRNA analysis revealed extensive post-transcriptional targeting of SOCS6 and SULF1, while CHIT1 showed no curated Ct-associated miRNA interactions. CNV analysis identified 5775 high-confidence events, with nominal gene-level associations observed for ATAD3A, CARD14, TMEM240, and ZNF140. These results indicate that a greater fraction of the susceptibility to urogenital Ct reinfection may be driven by genetic variation affecting immune and epithelial pathways rather than protein-coding changes. Full article

Congenital heart defects (CHDs) are the most common congenital anomalies, with identifiable genetic etiologies in approximately 5–30% of affected infants, depending on the clinical presentation and comorbidities. This study included 216 children with CHD, predominantly syndromic, to explore the role of genetic variants in their morphological phenotypes. Chromosomal microarray (CMA) and whole-exome sequencing (WES) were performed, revealing clinically significant copy number variations (csCNVs) in 59 (27.3%) patients. The most frequent were 22q11.21 (8/59; 13.6%) and 7q11.23 (5/59; 8.5%) deletions. WES was conducted in 28.0% of cases, achieving a detection rate of 29.5%, primarily identifying variants related to Noonan syndrome. Genetic diagnoses were confirmed in 33.3% of patients, with clinically significant CNVs and SNV/INDELs found exclusively in those with syndromic CHD, leading to a 36.5% diagnosis rate in those patients. The identified variants most frequently affected genes encoding transcription factors (40.4%), followed by genes involved in the RAS signaling pathway and structural proteins (17.0%), and chromatin remodeling proteins (12.8%). Full article

Background: Copy number variation (CNV) is an important class of structural variations (SVs) that contribute to phenotypic diversity and environmental adaptation in animals. However, large-scale population-level analyses of CNVs in goats remain limited. This study aimed to comprehensively characterize CNVs and explore their potential roles in economically important traits in Chinese goat populations. Methods: Whole-genome resequencing data from 151 individuals representing 17 Chinese goat breeds were analyzed. CNV regions (CNVRs) were identified across the genome, followed by gene annotation, functional enrichment analysis, and population differentiation analysis based on V_ST. Results: A total of 5636 CNVRs were identified from 151 individuals of 17 goat breeds, including 1365 duplication CNVRs, 4241 deletion CNVRs, and 30 both CNVRs. These CNVRs collectively spanned 2.38% of the goat genome. A total of 912 protein-coding genes overlapped with these CNVRs. After Bonferroni correction, GO enrichment analysis showed that these genes were significantly enriched in terms related to transmembrane transport, cell projection, ion binding, and ATP binding. Population differentiation analysis identified several CNVR-associated candidate genes with potential relevance to production or adaptive traits, including ABCC4, APOL3, EXOC3L4, ERG, B4GALT1, and FTH. Conclusions: This study provides a comprehensive CNVR map of Chinese goat populations and offers insights into the genetic basis of economically important traits, contributing to future genetic improvement and breeding strategies in goats. Full article

The reproductive traits of sheep are very important characteristics influencing productivity. Among these, gestation length (GL) is an important trait with positive or negative influences on birth weight, lamb survival, lambing intervals, ease of lambing, and the dam’s health. This review evaluates the existing knowledge of genetic and environmental factors influencing reproductive traits, with a focus on GL in sheep, and the potential of this knowledge to inform effective molecular breeding programs. The mean GL for sheep is 147 days, generally ranging from 142 to 152 days. Both extremely long and extremely short GL may have either positive or negative effects on sheep rearing. Variations among breeds and within populations arise from complex interactions between nature and nurture. GL has a moderate level of heritability, indicating that genetic factors contribute to phenotypic variation in this trait. The GL is a result of gene-regulatory pathway interactions, hormonal signaling, placental, and fetal–maternal communication. Three stages of gestation are characterized by distinct patterns of gene expression, hormonal regulation, and physiological functions. Advances in genomic technologies, including whole-genome sequencing (WGS) and genome-wide association studies (GWAS), have enhanced the ability to identify the genetic determinants of GL and facilitate their incorporation into molecular breeding strategies. In addition, the invention of molecular biology in the discovery of single-nucleotide polymorphisms (SNPs), insertion/deletion (InDels), and copy number of variants (CNVs) has created new opportunities to uncover the molecular basis of GL. In general, this review offers a comprehensive framework that identifies genetic and environmental determinants of GL and describes their practical implications for sustainable sheep breeding. Full article

Copy number variations (CNVs) are a major source of structural genomic diversity that influences adaptation, reproduction, and production traits in livestock. The Black Bengal goat, an economically important Indian breed known for its high fecundity, superior skin quality, and resilience to humid tropical climates, was studied to uncover its structural genomic landscape. We performed whole-genome CNV analysis using high-depth (10×) sequencing data from eight individuals. A total of 31,816 copy number variants (CNVs) were identified, predominantly duplications, with an average length of approximately 45 kb. These CNVs were combined into 8910 copy number variation regions (CNVRs) covering approximately 0.15 Gb (about 5.3% of the autosomal genome). CNVR hotspots were mainly located on chromosome 1. Gene annotation showed that regions overlapping with CNVs and CNVRs contained more than 1987 protein-coding genes involved in pathways related to immunity, reproduction, metabolism, and extracellular matrix (ECM) organization. The presence of CNVs involving genes such as GDF9 and BMPR1B on chromosomes 7 & 6, respectively, is important because it indicates that the breed has a high reproductive capacity due to dosage-sensitive duplications. Changes in the extracellular matrix and increased dermal strength have been linked to duplications of genes such as COL6A1, LAMC2, LAMB3, FMN1, and CLDN1. This helps explain the superior hide quality of the breed. This research offers a comprehensive map of CNVs and CNVRs within the genome of the Black Bengal goat. It demonstrates how these duplications lead to structural changes that enhance both reproductive performance and skin resilience. These findings provide a valuable genomic resource for future marker-assisted selection, comparative genomics, and conservation breeding programs aimed at preserving indigenous goat populations. Full article

Background: Familial hemiplegic migraine (FHM) is a rare and severe form of migraine disorder featuring aura symptoms that include hemiplegia during attacks. While pathogenic missense variants in CACNA1A, ATP1A2, and SCN1A can cause FHM or its sporadic form, they explain less than 20% of suspected hemiplegic migraine cases, suggesting the involvement of other genes or genetic variations, potentially including copy number variations (CNVs). PPRT2 gene variants including CNVs have also been implicated in hemiplegic migraine. Methods: Multiplex ligation-dependent probe amplification (MLPA) assays were used to investigate the presence of CNVs in the CACNA1A, SCN1A, ATP1A2, and PRRT2 genes in a cohort of 170 unrelated probands suspected to have FHM who had tested negative for pathogenic missense or small indel variants within these genes. Potential CNVs were subsequently confirmed using quantitative PCR. Results: In 15 patients referred for FHM genetic testing, various CNVs in the target genes were detected by MLPA and subsequently validated by quantitative PCR. CACNA1A exon duplications were identified in six patients and deletions found in two. Two patients had ATP1A2 exon deletions, while one had a duplication. For SCN1A, exon deletions were found in three patients and a duplication in one. PRRT2 exon deletions were detected in five patients, with a single nucleotide polymorphism (SNP) array confirming a deletion spanning PRRT2 and neighbouring loci including 26 genes in one of those. Three patients had CNVs in more than one FHM gene. Conclusions: Our study demonstrates the presence of CNVs in FHM genes in a subset of hemiplegic migraine cases (~9%), suggesting a likely role in the disorder and highlighting the need to explore structural variation in addition to the commonly interrogated genetic mutation points. These findings contribute to further understanding of genetic mechanisms that underlie hemiplegic migraine and may inform improved diagnostic and therapeutic strategies. Full article

Background: Accurate identification of cancer driver genes is essential for understanding tumorigenesis and developing targeted therapies. Although graph neural networks (GNNs) have advanced multi-omics integration, existing methods often simply concatenate omics features and underutilize the topological information of biological networks. Methods: We propose M-GNN, a multi-modal GNN framework for cancer driver gene prediction. It employs separate Graph Convolutional Network (GCN) encoders to process four types of omics data (mutation, expression, methylation, copy number variation (CNV)), each represented as a 16-dimensional vector. We incorporate knowledge distillation by using soft labels from a pre-trained teacher model to enhance feature representation. An attention mechanism adaptively fuses the encoded omics features, and a dual-path classifier combining a GCN and a Multilayer Perceptron (MLP) preserves both intrinsic gene properties and network topology. Results: Experiments on three public protein–protein interaction (PPI) networks show that M-GNN consistently achieves the highest or second-highest AUPRC compared to five state-of-the-art methods. Ablation studies confirm the contribution of each module, and biological interpretability analysis—including analysis of GO enrichment and drug sensitivity—validates the reliability of the predicted genes. Conclusions: M-GNN provides a robust and interpretable computational tool for systematic cancer driver gene identification, effectively integrating multi-omics and network data. Full article