Front Genet [JOURNAL]
Sun
200 papers
LAIOR: a hyperbolic neural ODE variational framework for interpretable single-cell manifold learning and trajectory inference.
Fu Z, Fu J, Zhang K … +2 more , Ran T, Chen C
Front Genet · 2026 · PMID 42333095 · Full text
Single-cell omics data are high-dimensional, sparse, and noisy, and learning embeddings that simultaneously preserve local cell-state structure, global hierarchy, and smooth developmental trajectories remains an open pro...
Single-cell omics data are high-dimensional, sparse, and noisy, and learning embeddings that simultaneously preserve local cell-state structure, global hierarchy, and smooth developmental trajectories remains an open problem. Existing approaches typically achieve only one of these goals: classical methods emphasize either local neighborhoods or global variance; deep generative models cluster cell types well but often fracture trajectory continuity; and hyperbolic embeddings capture hierarchy but are numerically fragile in practice. We present LAIOR (Lorentz attentive interpretable ordinary differential equation (ODE)-regularized variational autoencoder (VAE)), a unified variational framework that combines three complementary inductive biases in a single forward pass: (i) encourages tree-like latent hierarchy while remaining numerically stable tangent-space clamping and exponential-map gating; (ii) a captures coordinated biological programs rather than forcing latent independence; and (iii) stabilizes latent trajectories through explicit learned dynamics. Across 118 single-cell datasets (53 scRNA-seq and 65 scATAC-seq) benchmarked against 23 baseline methods on 22 complementary metrics, LAIOR improves manifold continuity, trajectory coherence, and embedding fidelity while retaining competitive clustering performance. Ablation and sensitivity analyses show that ODE regularization stabilizes geometric learning and dampens hyperparameter sensitivity. Architecture interpretation experiments on two well-characterized reference systems (human bone marrow and mouse pancreatic endocrinogenesis) demonstrate that LAIOR's encoder and decoder pathways decompose cellular variation into mutually exclusive, biologically coherent latent modules, and biological validation experiments on two previously unseen hematopoietic perturbation cohorts ( knockout and chemotherapy-induced bone marrow failure) show that the same interpretability contract transfers to perturbed biology. LAIOR generalizes across RNA and chromatin accessibility modalities without architectural changes. Head-to-head comparisons against both dynamical baselines (scTour) and foundation models (scGPT, scFoundation) confirm that explicit geometric and dynamical inductive biases recover trajectory structure that large-scale pretraining alone does not. Together, these results establish LAIOR as a practical, interpretable framework for single-cell manifold and trajectory analysis.
Pan-cancer screening, bioinformatics analysis, and experimental validation identify TEX10 as a key biomarker driving OSCC progression.
Sun R, Zhao J, Guo J … +4 more , Jin L, Liu J, Xu H, Bai Y
Front Genet · 2026 · PMID 42333094 · Full text
BACKGROUND: TEX10 is a nuclear protein involved in chromatin remodeling. Its pan-cancer diagnostic, prognostic, and immunotherapeutic value has not been systematically evaluated, and its role in oral squamous cell carcin...
BACKGROUND: TEX10 is a nuclear protein involved in chromatin remodeling. Its pan-cancer diagnostic, prognostic, and immunotherapeutic value has not been systematically evaluated, and its role in oral squamous cell carcinoma (OSCC) remains unclear. METHODS: We employed TCGA and GTEx data for pan-cancer analysis of TEX10's prognostic and immune associations, along with OSCC-specific clinical, diagnostic and survival correlations. Protein-protein interaction (PPI) network, GO/KEGG enrichment analysis and assays assessed its biological roles and effects on viability, migration, invasion, apoptosis and cell cycle. RESULTS: TEX10 was upregulated in 15 cancer types and served as a prognostic biomarker for multiple cancers. It was associated with dysregulation of the tumor immune microenvironment and significantly enriched in pathways including cell cycle and DNA replication. In oral squamous cell carcinoma, high TEX10 expression positively correlated with advanced clinical stage, TNM stage, and smoking history, demonstrating high diagnostic accuracy and prognostic value. experiments confirmed that TEX10 knockdown suppressed cell viability, migration, and invasion, promoted apoptosis. Similarly, TEX10 knockdown induced G0/G1 phase cell cycle arrest by downregulating Cyclin D1, CDK4, and upregulating p21. CONCLUSION: TEX10 plays an important role in cell cycle progression in OSCC, showing promise as a diagnostic and prognostic biomarker and therapeutic target.
Multi-omics profiling reveals an auxin-salicylic acid signaling hub driving flavonoid depletion and accelerated vigor loss in tetraploid Chinese cabbage seeds.
Meng C, Liu X, Wu F … +4 more , Ma X, Chen X, Ma L, Wang M
Front Genet · 2026 · PMID 42333093 · Full text
BACKGROUND: Seed vigor, encompassing rapid uniform germination and robust seedling establishment, is critical for crop yield. While induced tetraploidy confers desirable agronomic traits in Chinese cabbage ( ssp. ), tetr...
BACKGROUND: Seed vigor, encompassing rapid uniform germination and robust seedling establishment, is critical for crop yield. While induced tetraploidy confers desirable agronomic traits in Chinese cabbage ( ssp. ), tetraploid seeds exhibit accelerated viability loss during storage compared to diploid counterparts, imposing substantial economic constraints. The metabolic and regulatory mechanisms underlying this ploidy-associated vigor penalty remain elusive. RESULTS: TTC assay revealed that seed viability exhibited the most pronounced decline in the 17-year time gradient. Consequently, we prioritized omics analyses on the 19-year and 23-year seeds. Tetraploid seeds demonstrated markedly accelerated viability decline under identical storage conditions, with 2023-harvested tetraploid lots exhibiting the most extensive metabolic rewiring. Comparative transcriptomics revealed ploidy- and year-specific segregation of genes involved in hormone signaling and carbohydrate metabolism. Notably, tetraploid seeds activated a unique auxin--salicylic acid (SA) signaling axis characterized by upregulation of , , , and IAA family genes, concomitant with elevated indole-3-acetic acid (IAA) and abscisic acid (ABA) accumulation. Genome-wide transcription factor analysis identified ploidy-specific expression patterns in bHLH, WRKY, and bZIP families, with bHLH genes predominantly enriched in tetraploids and bZIP factors associated with diploid seeds. Metabolomic profiling highlighted energy pathway imbalance, specifically starch/sucrose metabolism and glycerophospholipid dysregulation, as the earliest metabolic predictors of vigor loss in tetraploids. CONCLUSION: Our findings redefine ploidy-associated seed vigor deterioration as a predictable, metabolically driven syndrome orchestrated by hormone signaling crosstalk and secondary metabolite depletion. The identified auxin--SA signaling axis and energy-metabolism markers provide molecular targets for marker-assisted breeding of high-vigor tetraploid cultivars.
From genes to generations: genetic evaluation and counseling for infertility and pregnancy loss.
Skrypnyk C, AlHafnawi HH, AlHarmi R … +2 more , Amin E, Albuarki H
Front Genet · 2026 · PMID 42333092 · Full text
INTRODUCTION: Understanding the genetics of reproductive disorders is key to improving diagnosis, treatment, and overall reproductive health. This study aimed to describe the characteristics, assessment, investigations,...
INTRODUCTION: Understanding the genetics of reproductive disorders is key to improving diagnosis, treatment, and overall reproductive health. This study aimed to describe the characteristics, assessment, investigations, and recommendations in patients seeking genetic counseling for infertility and pregnancy loss. METHODS: This is a retrospective cross-sectional study that included couples who presented to the Genetic Disease Clinic, University Hospital, King Abdullah Medical City, Bahrain, with a chief complaint of infertility or pregnancy loss over 13 years from 2012 to 2024. RESULTS: Out of 912 patients who approached the clinic, 175 records (19.2%) belonged to couples (n = 350) who visited the clinic with infertility or pregnancy loss. Eighty couples (45.7%) were diagnosed with primary infertility, while 95 couples (54.3%) were diagnosed with secondary infertility. The mean marriage duration before visits was 7.7 ± 4.9 years. Meanwhile, 19 couples were identified as having advanced age in both partners (10.9%), 30 couples with advanced maternal age (17.1%), and 11 couples with advanced paternal age (6.3%). Additionally, couples with secondary infertility had an average of 1.6 pregnancies, with a mean of 1.4 early pregnancy losses. A male factor was identified in 30.3% of the couples (n = 53) and a combination of both male and female factors was reported in 52.0% (n = 91). Infertility and pregnancy loss were attributed to chromosomal aberrations solely in 27.4% of the couples (n = 48) and to monogenic carrier status in 14.3% of the couples (n = 25). Exome sequencing and gene panels were recommended and/or conducted in 49 couples (28%). fertilization and preimplantation genetic testing were recommended for couples with proven monogenic or chromosomal-related infertility. CONCLUSION: A couple's genetic profile significantly impacts fertility potential and outcomes. Genetic counseling, screening, and diagnostic testing enable timely and personalized interventions.
Genetic heterogeneity correlated with phenotypic variability in 6 Chinese families with Alport syndrome.
Gao J, Zhou H, Zhang L … +2 more , Su Z, Liu S
Front Genet · 2026 · PMID 42326388 · Full text
BACKGROUND: Alport syndrome (AS) is a common hereditary kidney disease, mainly characterized by hematuria, progressive renal dysfunction, sensorineural hearing loss, and ocular symptoms, which significantly impacts patie...
BACKGROUND: Alport syndrome (AS) is a common hereditary kidney disease, mainly characterized by hematuria, progressive renal dysfunction, sensorineural hearing loss, and ocular symptoms, which significantly impacts patients the quality of life patients' quality of life and lifespan. However, due to its atypical and heterogeneous clinical features, the relationship between genotype and phenotype remains complex, posing AS diagnostic challenges. METHOD: Genetic variants were screened by whole exome sequencing (WES) followed by verification with Sanger sequencing. Genotype-phenotype analysis was also conducted, and a novel variant ( c.3203G>A) was selected for functional studies. RESULTS: We identified seven variants in six families, including autosomal dominant ( c.352G>A, c.71 + 1G>C), autosomal recessive ( c.2736dupA, c.4235G>T), X-linked ( c.512del, c.3053del), and one spontaneous variant ( c.3203G>A). Functional studies on the novel variants ( c.3203G>A) demonstrated a significantly decrease significant decrease in the mRNA expression level in HEK293 T cells and the weakened cell migration ability. CONCLUSION: We identified four novel pathogenic changes causing AS, revealing the genetic heterogeneity of AS and expanding its genotype phenotype spectrum, holding significant implications for prenatal diagnosis.
Diagnostic yield of long-read sequencing for rare diseases: a systematic review.
Ibrahim AA, Fakhro KA, Abdallah AM
Front Genet · 2026 · PMID 42326387 · Full text
BACKGROUND: Nearly half of patients with rare genetic disorders remain undiagnosed, which may in part be due to limitations of current short-read sequencing (SRS) approaches in detecting complex genomic alterations. Long...
BACKGROUND: Nearly half of patients with rare genetic disorders remain undiagnosed, which may in part be due to limitations of current short-read sequencing (SRS) approaches in detecting complex genomic alterations. Long-read whole genome sequencing (lrWGS) technologies can address these limitations through enhanced detection of structural variants (SVs), repetitive regions, and epigenetic changes. METHODS: To evaluate the diagnostic yield of lrWGS in patients with rare genetic diseases receiving inconclusive or negative results from standard testing, we searched the PubMed, Science Direct, Scopus, and ProQuest databases to July 2025 for studies applying lrWGS to unresolved rare disease cases and reporting diagnostic outcomes. Risk of bias was assessed using the QUADAS-2 tool. RESULTS: Nine studies involving 646 previously unresolved cases that underwent lrWGS met the inclusion criteria. Of these, 29 individuals (24 unique diagnoses involving 25 genes) received a definitive diagnosis through lrWGS, a diagnostic yield of 4.5%. SVs accounted for the majority of identified variants (41.67%), followed by combined SV/single-nucleotide variants (20.83%), methylation changes (16.67%), and other variant types (copy number variations, indels, and tandem repeats). Most detected variants were in regions typically inaccessible to short-read whole-exome sequencing (WES). lrWGS also enabled phasing and methylation analysis in a single assay, which was valuable for compound-heterozygosity detection and diagnostic interpretation. CONCLUSION: lrWGS shows clear potential for improving diagnostic rates in previously unresolved rare disease cases, particularly when applied after WES and combined with advanced tools such as phasing and methylation profiling. As technologies evolve and become more accessible, lrWGS may increasingly become a first-tier diagnostic approach, especially in phenotypically complex conditions. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/y5azb/overview, identifier 10.17605/OSF.IO/Y5AZB.
Exploration of candidate genes associated with rare SNVs in pulmonary stenosis using whole-exome sequencing and machine learning.
Liu Y, Chen S, Liang Y … +7 more , Huang S, Zhang B, Liu S, Yang L, Zhao L, Xu R, Wu Y
Front Genet · 2026 · PMID 42326386 · Full text
BACKGROUND: Pulmonary stenosis (PS) is a common form of congenital heart disease (CHD) that impairs cardiopulmonary function and can be life-threatening in severe cases. As a complex polygenic disorder, the genetic basis...
BACKGROUND: Pulmonary stenosis (PS) is a common form of congenital heart disease (CHD) that impairs cardiopulmonary function and can be life-threatening in severe cases. As a complex polygenic disorder, the genetic basis of PS remains incompletely understood. METHODS: Rare pathogenic single nucleotide variants (SNVs) were identified from whole-exome sequencing (WES) data of 185 sporadic PS patients and 100 healthy controls using multiple pathogenicity-filtering strategies. Gene-level burden test was performed, with complementary analysis using sequence kernel association test-optimal (SKAT-O). Three machine learning algorithms-least absolute shrinkage and selection operator (LASSO), random forest (RF), and extreme gradient boosting (XGBoost)-were applied to prioritize candidate genes. The overlap between machine learning-based selections and burden test results was systematically evaluated. Final candidate genes were further prioritized through protein-protein interaction (PPI) network analysis, and their expression in human pulmonary artery endothelial cells (HPAECs) was assessed by reverse transcription quantitative polymerase chain reaction (RT-qPCR). RESULTS: Comparative analyses showed that different machine learning algorithms exhibited distinct feature selection patterns, with RF demonstrating the highest concordance with burden test results. A total of 17 candidate genes were prioritized (). CONCLUSION: These findings indicate that machine learning can complement conventional gene-based analyses of WES data. This study provides a set of candidate genes associated with PS and offers a basis for further investigation of its genetic architecture.
HMMR as a robust prognostic biomarker correlates with immune infiltration and cell cycle pathways in oral squamous cell carcinoma: a multi-cohort bioinformatics analysis based on TCGA and GEO databases.
Liu L, Chen S, Gong H … +2 more , Qi X, Wang M
Front Genet · 2026 · PMID 42326385 · Full text
INTRODUCTION: Oral squamous cell carcinoma (OSCC), a prevalent head and neck malignancy with complex molecular pathogenesis and poor prognosis, remains a critical clinical challenge. This study aimed to elucidate the rol...
INTRODUCTION: Oral squamous cell carcinoma (OSCC), a prevalent head and neck malignancy with complex molecular pathogenesis and poor prognosis, remains a critical clinical challenge. This study aimed to elucidate the role of hyaluronic acid mediated motility receptor (HMMR) in OSCC progression and evaluate its potential as a diagnostic and prognostic biomarker. METHODS: Transcriptomic data was integrated from the TCGA OSCC cohort and two independent GEO cohorts (GSE37991, GSE41613). Differential expression analysis was performed using DESeq2. Common differentially expressed genes (DEGs) were identified via Venn diagram analysis, followed by functional enrichment analysis using the STRING database. Univariate and multivariate Cox regression analyses were conducted with the survival package to identify prognostic markers, and the predictive performance was evaluated by receiver operating characteristic (ROC) analysis. Immune infiltration analysis, pathway enrichment analysis, and protein-protein interaction (PPI) network analysis via GeneMANIA were further applied to explore biological functions. RESULTS: A total of 2,477 upregulated and 2,214 downregulated differentially expressed genes (DEGs) were identified, with 245 common DEGs pinpointed across datasets. Cluster1 genes were significantly associated with OSCC pathogenesis in functional enrichment. CCNA1, HMMR, and RAG1 were identified as potential prognostic markers, with HMMR demonstrating the strongest predictive value (AUC = 0.919 in ROC analysis). HMMR was significantly overexpressed in OSCC tissues compared to normal controls (P < 0.001), and its high expression correlated with advanced T stage, N stage, pathological grade, shorter disease-specific survival, and disease-free survival. Multivariate analysis confirmed HMMR as an independent prognostic factor for overall survival. Immune infiltration analysis revealed that HMMR expression was positively correlated with 11 immune cell subsets, particularly Th2 cells (r = 0.465) and T helper cells (r = 0.356), suggesting a role in modulating the tumor immune microenvironment. Pathway enrichment linked HMMR to tumor proliferation, hypoxia response, DNA damage repair, and G2/M cell cycle checkpoints. The PPI network analysis identified HMMR-associated complexes involving cell cycle regulators (e.g., CDK1, CCNB1, AURKA), implicating roles in cell cycle regulation, DNA repair, and mitotic progression. DISCUSSION: Collectively, this study establishes HMMR as a robust prognostic biomarker for OSCC, tightly associated with malignant progression, immune cell infiltration, and key oncogenic pathways. HMMR and its interacting network represent promising targets for OSCC precision medicine, offering new insights into diagnostic strategies and therapeutic development.
SIGMA: self-supervised inference of gene networks via masked auto-encoding.
Wang Q, Zhang Z, Liao NQ … +2 more , Yang S, He Z
Front Genet · 2026 · PMID 42326384 · Full text
OBJECTIVES: Inferring gene regulatory networks (GRNs) from expression profiles is essential for identifying critical genes within complex disease pathways. However, current machine learning-based GRN inference methods fa...
OBJECTIVES: Inferring gene regulatory networks (GRNs) from expression profiles is essential for identifying critical genes within complex disease pathways. However, current machine learning-based GRN inference methods face two challenges. Unsupervised methods struggle to achieve satisfactory accuracy in inference, while supervised methods are limited by the scarcity of high-quality interaction labels. Further, existing models demonstrate significant shortcomings when it comes to transferring reasoning to other GRN task subtypes. These issues affect GRN inference and hinder the ability to discover new regulatory patterns. FINDINGS: To address these challenges, we have developed SIGMA: a transformer-based framework that uses self-supervised learning to pretrain the encoder on expression profiles. This alleviates the need for high-quality labels. During pretraining, it converts gene expression pairs into non-overlapping patches, and randomly masks some of these patches. This forces the encoder to extract correlation representations from the unmasked patches without label guidance, enabling the decoder to reconstruct the masked patches while preserving their similarity. Experiments have demonstrated that the pretrained encoder can accurately infer GRNs and be used to infer other subtypes, thereby reducing reliance on labels. Benchmark tests on human and mouse datasets have shown that SIGMA outperforms state-of-the-art methods. When applied to breast cancer datasets, SIGMA produced predictions that were consistent with established networks and identified candidate interactions that were not present in the gold-standard networks. Further investigation and experimental validation of these relationships is warranted.
Case report: novel compound heterozygous variants including an exon 30-54 duplication in a child with a highly suggestive primary ciliary dyskinesia phenotype.
Wang S, Zhang Y, Wu M … +6 more , He Y, Chen S, Xu X, Lv M, Ji J, Wang Y
Front Genet · 2026 · PMID 42317261 · Full text
Primary ciliary dyskinesia (PCD) is a rare disorder characterized by dysfunction of motile cilia and chronic progressive respiratory disease, mianly inherited in an autosomal recessive manner. Biallelic variants in dynei...
Primary ciliary dyskinesia (PCD) is a rare disorder characterized by dysfunction of motile cilia and chronic progressive respiratory disease, mianly inherited in an autosomal recessive manner. Biallelic variants in dynein axonemal heavy chain 11 () have been reported in association with PCD and are typically associated with normal ciliary ultrastructure. In addition, exon-level copy number variants (CNVs) in , particularly duplications, remain poorly characterized and are prone to being overlooked by conventional sequencing workflows. We report a 9-year-old Chinese girl with recurrent lower respiratory tract infections, chronic pansinusitis, and bronchiectasis. Pulmonary function testing showed isolated small-airway dysfunction with preserved FEV1, with nasal nitric oxide (nNO) severely reduced (5.4 nL/min). Trio whole-exome sequencing integrated with read-depth CNV analysis detected novel compound heterozygous variants: a paternal inherited missense variant (c.6556A>C, p.Thr2186Pro) and a previously unreported maternally derived intragenic duplication encompassing exons 30-54. The missense variant was confirmed by Sanger sequencing, and the exon-level dosage gain was confirmed by qPCR. This case expands the spectrum of variants and highlights the importance of incorporating CNV detection into exome-based diagnostic process for children with a highly suggestive PCD phenotype.
Identification of QTL associated with pod number in soybean.
Xiong Y, Yu H, Mao A … +8 more , Jadoon S, Liu Z, Liu K, Zhang Z, Chen Y, Gyebi-Nimako B, Qiu L, Wang J
Front Genet · 2026 · PMID 42317260 · Full text
Pod number is an important factor influencing soybean yield. In this study, a recombinant inbred line population derived from the cross between improved cultivar () and wild soybean () was subjected to multi-environment...
Pod number is an important factor influencing soybean yield. In this study, a recombinant inbred line population derived from the cross between improved cultivar () and wild soybean () was subjected to multi-environment phenotypic evaluation for pod number. Quantitative trait locus (QTL) mapping associated with pod number was performed utilizing both linkage analysis (LA) and genome-wide association study (GWAS) by integrating the phenotypic and genotypic data. The results showed that a total of 16 QTLs associated with pod number, notably, overlapping genomic intervals were observed between (by linkage analysis) and (by EMMAX), as well as between (by LA) and (by EMMAX), and these intervals were regarded as major-effect Quantitative trait locus regions. Furthermore, two candidate genes (, and ) encode a basic Helix-Loop-Helix (bHLH transcription factor and an armadillo (-repeat protein respectively, as determined through linkage disequilibrium analysis, SNP variant analysis, haplotype analysis, and gene functional annotation. These two candidates are possibly involved in the regulation of flower number, flowering time, and pod number (siliques number in ). These findings pave the way for gene cloning related to pod number, and provide novel insights into the genetic architecture underlying pod number variation in soybean.
Derivation of prediction error variance for non-genotyped individuals in genomic selection.
Junqueira VS, Yokoo MJ, Cardoso FF
Front Genet · 2026 · PMID 42311761 · Full text
Genomic selection has transformed plant and animal breeding by enabling accurate prediction of genetic merit using DNA markers; however, comprehensive genotyping of all selection candidates remains economically prohibiti...
Genomic selection has transformed plant and animal breeding by enabling accurate prediction of genetic merit using DNA markers; however, comprehensive genotyping of all selection candidates remains economically prohibitive for most breeding programs. While breeding programs must decide which subset of individuals to genotype within budget constraints, current approaches rely primarily on experience-based decisions rather than quantitative frameworks. We present explicit mathematical derivations for prediction error variance (PEV) in non-genotyped individuals under mixed model equations, providing a theoretical foundation for evaluating genotyping strategies prospectively. The approach derives PEV expressions for non-genotyped selection candidates under different relationship matrix structures, including pedigree-based, genomic, and hybrid single-step methodologies that combine both information sources. The derivations accommodate complex breeding program structures with historical training populations containing both genotypes and phenotypes alongside contemporary selection candidates with only pedigree information. Using Schur complement methods applied to partitioned mixed model equations, the framework enables calculation of prediction uncertainty without requiring actual phenotypic data from selection candidates. The expressions simplify under different information scenarios, from cases with complete phenotypic data to situations where only relationship information is available. The method was validated through simulations across six scenarios with populations ranging from 180 to 15,500 individuals, confirming numerical equivalence with direct matrix inversion while demonstrating computational and memory advantages that increase with population size. Although genomic relationship matrix operations dominate the complexity, matrix decomposition techniques, including Cholesky factorization and APY methodology, can improve efficiency. The mathematical framework provides quantitative tools for transitioning from experience-based to mathematically-informed genotyping decisions, with applications extending to any field requiring prospective quantification of prediction uncertainty under resource constraints.
The effect of human-specific genetic variants on neuronal spinogenesis.
Rosas NM, Szombathy A, Szigeti K
Front Genet · 2026 · PMID 42311760 · Full text
Fundamental morphological and functional differences between the brains of animal models and humans are at least partially related to human-specific genes and genetic variants. As one of the structural underpinnings of b...
Fundamental morphological and functional differences between the brains of animal models and humans are at least partially related to human-specific genes and genetic variants. As one of the structural underpinnings of brain function is the dendritic spine, we systematically queried a curated list of human-specific genes and genetic variants. We found that with the current knowledge base, 4.3% are linked to the dendritic spine. Functionally these genes converge on the cytoskeleton, Ca signaling, small GTPases, NMDAR, and WNT signaling and trafficking suggesting human specific modification of canonical pathways. Significant gaps in knowledge are identified and concerted efforts are needed. Understanding human-specific genetic contributions to the unique features of the human brain will address existing translational gaps and facilitate the development of successful treatments for neuropsychiatric disorders, advance environmental neuroscience for early childhood intervention and environmental risk reduction in aging and dementia.
Biobank consent preferences and implications for a mixed consent model: biomedical researchers vs. community stakeholders in a semi-urban Yoruba community, Nigeria.
Ogunrin OA
Front Genet · 2026 · PMID 42311759 · Full text
BACKGROUND: Several consent models have been described in the literature for genomic research, with some focusing specifically on biobanking. Sub-Saharan African scholars reported a preference for broad consent among key...
BACKGROUND: Several consent models have been described in the literature for genomic research, with some focusing specifically on biobanking. Sub-Saharan African scholars reported a preference for broad consent among key stakeholders, identical to narratives from most studies in Europe and the USA. However, there have been reports of a generational shift with divergent views among potential genomic research participants in sub-Saharan Africa due to communitarian ethos and relative solidarity. To avoid ethical conflicts in biobanking research in sub-Saharan Africa, it is imperative to explore the preferences of the various stakeholders. OBJECTIVE: To explore the opinions of research stakeholders, namely: biomedical clinician-researchers, community elders, and community members, on informed consent models in biobanking research. METHODS: This qualitative study employed key-informant semi-structured interviews and focus group discussions to collect data from purposively selected participants. Sample sizes for the stakeholders' categories were determined by theoretical saturation. Thirty clinician-researchers and four community elders were interviewed. Fifteen focus group sessions were held with 50 community members. The methodological design, adapted from grounded theory, used the constant comparative method of data analysis. Data and methodological triangulation, reflexivity, and code-recode reliability index were used to ascertain data quality. RESULTS: Twelve of the biomedical researchers preferred blanket consent, aligning with the preferences of adult community members. Ten of the researchers opted for broad consent. The community elders opined that community members would prefer tiered consent. The youth participants differed from the researchers and community adults, preferring re-consenting. The findings of this study showed discordant views on consent model preferences among the various stakeholders. CONCLUSION: Discordance in consent preferences among the key stakeholders is a potential source of ethical conflict. A hybrid or mixed-consent model that provides participants with the option to choose the consent model they prefer for every research stage, and flexibility to change their choices as the research progresses, is recommended. This will reflect the fundamental principle of autonomy and demonstrate responsive communitarianism and relative solidarity. It will also provide a robust, culturally sensitive, and context-specific model that reflects the preferences of community stakeholders and addresses the fundamental ethical issues encountered in biobanking.
Genetic variation at the IL-18-137C>G is associated with poor sepsis prognosis and enhanced inflammatory responses: a multicenter hospital-based study.
Li Z, Gu W, Liu L … +10 more , Li J, Zhang M, Yang W, Yang M, Zhang J, Zhong H, Liu Y, He J, Yin H, Shao Y
Front Genet · 2026 · PMID 42311758 · Full text
BACKGROUND: Sepsis is a life-threatening condition caused by dysregulated immune responses, leading to inflammation, tissue damage, and organ failure. This study investigates the role of the IL-18 rs187238 (-137C>G) poly...
BACKGROUND: Sepsis is a life-threatening condition caused by dysregulated immune responses, leading to inflammation, tissue damage, and organ failure. This study investigates the role of the IL-18 rs187238 (-137C>G) polymorphism in sepsis susceptibility, progression, and patient prognosis. METHODS: A multicenter case-control study was conducted with 784 sepsis patients and 776 healthy controls. The IL-18 rs187238 polymorphism was genotyped using imLDR™ multiplex SNP genotyping method. ELISA and qRT-PCR were used to detect related inflammatory cytokine expression, while functional analysis was performed using dual-luciferase assays to evaluate the impact of the rs187238 variant on IL-18 promoter activity. RESULTS: We observed a significant association between the rs187238 polymorphism and 28-day ICU mortality in sepsis patients. The CG/GG genotypes (OR = 1.470, 95% CI = 1.029-2.129, = 0.037) were more frequently observed in non-survivors compared to survivors, with a notable difference in the frequency of the G allele (OR = 1.534, 95% CI = 1.111-2.133, = 0.010). Kaplan-Meier survival analysis confirmed that patients with CG/GG genotypes had significantly lower 28-day survival rates compared to those with the CC genotype ( = 0.028). However, no significant differences in genotype and allele frequencies were observed between cases and healthy controls, nor between sepsis and septic shock patients. Sepsis patients with CG/GG genotypes had significantly higher IL-18 levels than those with the CC genotype. Dual-luciferase assays confirmed that the G allele increased IL-18 promoter activity, supporting its genetic influence on IL-18 expression. Additionally, sepsis patients with CG/GG genotypes expressed significantly increased levels of IL-1β, IL-6, and ICAM-1 than those with CC genotype. IL-18 treatment enhanced the expression of IL-1β, IL-6, IL-27, TNF-α, and MCP-1 in THP-1 macrophages upon LPS stimulation. In HUVECs, IL-18 treatment further enhanced LPS-induced IL-6, IL-27, TNF-α, and ICAM-1 expression, while promoting apoptosis and reducing VE-cadherin levels, emphasizing its role in inflammation and endothelial dysfunction in sepsis. CONCLUSION: The IL-18 rs187238 C>G polymorphism is linked to higher IL-18 expression and intensified inflammatory responses, which are associated with poor sepsis prognosis. The sepsis-associated risk rs187238-G allele serves as a potential prognostic biomarker for sepsis-related mortality. Targeting IL-18 or its genetic variations might offer new avenues for sepsis therapy.
Temporal trends in artemisinin partial resistance and other antimalarial drug mutations in from Kagera region, Northwestern Tanzania, 2021-2023.
Simkin A, Mandai SS, Fola AA … +24 more , Young NW, Marglous J, Pereus D, Bakari C, Madebe RA, Seth MD, Mrengela RB, Kisambale AJ, Chacha GA, Mandara CI, Francis F, Mbwambo D, Garimo I, Chacky F, Aaron S, Lusasi A, Molteni F, Njau RJA, Kajange S, Nhiga SL, Mohamed A, Juliano JJ, Ishengoma DS, Bailey JA
Front Genet · 2026 · PMID 42311757 · Full text
Artemisinin-based combination therapies (ACTs) remain the cornerstone of malaria treatment, yet the emergence of artemisinin partial resistance (ART-R) in Africa threatens their efficacy. ART-R is primarily associated wi...
Artemisinin-based combination therapies (ACTs) remain the cornerstone of malaria treatment, yet the emergence of artemisinin partial resistance (ART-R) in Africa threatens their efficacy. ART-R is primarily associated with mutations in kelch13 (K13), notably R561H, which has been linked to delayed parasite clearance in East Africa. We genotyped 2,866 isolates from seven districts in Tanzania's Kagera region (2021-2023) using 121 molecular inversion probes (MIP) targeting key resistance loci to characterize trends in ART-R and other resistance markers. The WHO-validated K13 mutation R561H persisted in border districts of Karagwe and Kyerwa, with prevalence ranging from 14% to 26%, and appeared for the first time in Muleba in 2022 (10.0%) and Bukoba rural district (0.7%) in 2023, indicating eastward spread toward Lake Victoria. Regional prevalence of R561H rose from 5.5% in 2021 to 6.9% in 2023. Additional validated (A675V) and candidate (V568G, P441L) mutations were detected at low frequencies. Markers associated with reduced sensitivity to partner drugs showed minimal change. Early DHFR and DHPS mutations were near fixation and high-level resistance markers (DHFR I164L and DHPS A581G) exhibited marked gradients. These latest mutations are significantly spatially colocalized (weighted spearman R = 0.58, P = 0.045) and co-occur within a number of individual genomes. These results highlight notable variation in mutation prevalence and underscore the importance of high-resolution surveillance to identify emerging hotspots and guide targeted interventions. Sustained molecular monitoring is critical to inform treatment policy, preserve ACT efficacy, and mitigate the risk of widespread resistance across East Africa.
MetaComb: a meta-learning framework for drug combination response prediction from cell lines to patients.
Guo C, Li T, Deng X … +6 more , Ma Y, He F, Diao L, Wang Z, Li D, Liu Z
Front Genet · 2026 · PMID 42306099 · Full text
INTRODUCTION: Combination therapy has emerged as a pivotal strategy in oncology to enhance efficacy and overcome drug resistance. Computational prediction models of drug combinations trained on abundant cell line data pr...
INTRODUCTION: Combination therapy has emerged as a pivotal strategy in oncology to enhance efficacy and overcome drug resistance. Computational prediction models of drug combinations trained on abundant cell line data provide a starting point, but their applicability to patients remains constrained by inherent biological disparities between cultured cell lines and patient-derived tumors. However, due to ethical and cost issues, patient-derived datasets remain scarce, thus, developing patient-level predictive algorithms must explicitly confront the few-shot problem of relevant data. METHOD: To break through the small sample bottleneck, we used the Model-Agnostic Meta-Learning (MAML) to develop a Meta-Learning Drug Combination Response Prediction (MetaComb) method for patient drug combination response prediction, using drug structures and gene expression profiles of cell lines/patients as the model input. In MetaComb, the meta-model was trained on data-rich cell line-specific drug combination response prediction tasks and subsequently fine-tuned to adapt to scenarios with limited samples. RESULTS: MetaComb outperformed conventional transfer learning in predicting drug combination response, improving AUROC by 8.5% for data-poor cell lines and by 7.4% for patient ex vivo samples. And for the patients with data, MetaComb also achieved superior accuracy over existing methods. Given the limited patient cohort, these results demonstrate the feasibility of MetaComb, but further validation with larger patient datasets is needed. DISCUSSION: This study, as a proof-of-concept, provided an initial evidence that the MetaComb meta-learning framework is feasible for patient-derived drug combination response prediction under few-shot conditions, by transferring drug-combination response knowledge from preclinical cell lines. Current patient-level assessment is insufficient to support generalization to other cancer types or patient populations, and in the future, with the accumulation of relevant patient-derived data, further validation with larger patient cohorts is required.
Accuracy of genomic prediction for milk production traits in Mehsana buffalo.
Patel MR, Patel AC, Joshi RS … +5 more , Patel DV, Nayee N, Sudhakar A, Jakhesara SJ, Koringa PG
Front Genet · 2026 · PMID 42306098 · Full text
INTRODUCTION: Genomic information can contribute significantly to the increase in the accuracy of genetic evaluation compared to relying solely on pedigree relationships. Hence, the objective of this study was to compare...
INTRODUCTION: Genomic information can contribute significantly to the increase in the accuracy of genetic evaluation compared to relying solely on pedigree relationships. Hence, the objective of this study was to compare the accuracy of genomic prediction for 305 days milk yield (305DMY), 305 days fat yield (305DFY), 305 days solid-not-fat yield (305DSNFY) and 305 days protein yield (305DPY) traits in Mehsana buffalo using pedigree best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) models. Prediction bias was assessed by estimating the regression coefficient of corrected yield (Yc) on predicted breeding values (BVs). METHODS: The phenotype dataset comprised of test day records of 10,897 Mehsana buffalo for milk yield, 10,896 for fat yield, 10,581 for SNF yield and 10,578 for protein yield were used for present study. A total of 4,107 blood samples of Mehsana buffaloes were collected and genotyped using BUFFCHIP 54K SNP array. After the quality control, final dataset comprised of 3,887 Mehsana buffalo with 53,292 SNPs. RESULTS: The prediction accuracies obtained using PBLUP ranged from 0.078 to 0.088, whereas those from ssGBLUP ranged from 0.088 to 0.100. The average predictive accuracies across traits were 0.083 for PBLUP and 0.093 for ssGBLUP, representing an overall improvement of 11.37% with ssGBLUP. The regression coefficients of predictions ranged from 0.44 to 0.52 for PBLUP and from 0.45 to 0.61 for ssGBLUP across production traits. The average regression coefficients were 0.48 for PBLUP and 0.53 for ssGBLUP, indicating reduced prediction bias under the ssGBLUP model. CONCLUSION: ssGBLUP provides more accurate and less biased breeding value predictions than PBLUP for production traits in Mehsana buffaloes.
Pathogenic mechanisms of mutations in X-linked retinitis pigmentosa: integrating clinical pedigree and single-cell transcriptomics.
Wang X, Bai Y, Zuo X … +3 more , Lei X, Wang X, Zou G
Front Genet · 2026 · PMID 42306097 · Full text
PURPOSE: This study aims to identify pathogenic retinitis pigmentosa G () mutations in a Chinese pedigree with X-linked retinitis pigmentosa (XLRP) and elucidate the cellular and molecular mechanisms underlying -associat...
PURPOSE: This study aims to identify pathogenic retinitis pigmentosa G () mutations in a Chinese pedigree with X-linked retinitis pigmentosa (XLRP) and elucidate the cellular and molecular mechanisms underlying -associated photoreceptor degeneration through the integrated analysis of clinical data and single-cell transcriptomics. METHODS: A three-generation Chinese XLRP pedigree was enrolled for comprehensive ophthalmic examinations, including BCVA, OCT, FAF, and ERG. Whole-exome sequencing was performed on the proband to identify the pathogenic variants, followed by Sanger sequencing for validation in family members. To analyze the downstream molecular mechanisms, we analyzed a public single-cell RNA sequencing dataset (SRP535874) of mutant retinal organoids across four developmental time-points (D40-D200). Bioinformatics analyses included cell clustering, differential expression analysis, GO/KEGG enrichment, protein-protein interaction (PPI) network construction, and pseudotime trajectory analysis. RESULTS: A hemizygous frameshift mutation (c.2476_2477del; p.R826Gfs*8) in the ORF15 region of was identified in the proband and confirmed in his two sons by Sanger sequencing. Clinical examinations revealed severe retinal degeneration in the affected male, intermediate phenotype in female carriers, and early-stage changes in the young affected male. Single-cell transcriptomic analysis of mutant retinal organoids revealed a paradoxical increase in photoreceptor transcriptional activity at late developmental stages (D150 and D200) despite the loss of the outer retinal structure in the patients, which may reflect aberrant differentiation and impaired functional maturation of photoreceptor precursors. Differential expression analysis showed upregulation of the stress-response genes and downregulation of phototransduction and ciliary transport genes. GO and KEGG enrichment analyses implicated disrupted ribosome biogenesis, RNA metabolism, ubiquitin-mediated proteolysis, and neurodegenerative disease pathways. PPI network analysis indicated decoupling of the core "ciliary transport-phototransduction axis" and activation of a coordinated stress-response module. Pseudotime trajectory analysis showed arrested photoreceptor differentiation at an intermediate stage, preventing the progression to functional maturity. CONCLUSION: We identify a previously reported but extremely rare ORF15 frameshift mutation (c.2476_2477del; p.R826Gfs*8) in a Chinese XLRP pedigree. Single-cell transcriptomic analysis indicates that loss-of-function mutation may disrupt the ciliary transport-phototransduction axis, activate stress responses, and block photoreceptor differentiation. These findings expand the mutation spectrum, provide mechanistic insights into XLRP pathogenesis, and have implications for genetic counseling and targeted therapy.
Editorial: Circular RNAs: from anomalies to cellular regulators.
Barbagallo D, Chianese R, Manfrevola F
Front Genet · 2026 · PMID 42306096 · Full text
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