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PubMed2026

Polysomal Profiling Coupled to Allele-Specific Proteomics Reveals an EIF4H TranSNP Allele Possessing Higher mRNA Translation Potential.

To search for genetic sources of allele-specific mRNA translation, we leveraged heterozygous polymorphisms and variants present in the exome of HCT116 colorectal adenocarcinoma-derived cells, computing allelic fractions from both total and polysome-associated RNA from RNA-Seq data. Allelic imbalance in polysomal RNA led us to nominate 52 coding variants associated with allele-specific mRNA translation, of which 16 are nonsynonymous. To validate instances of allele-specific translation, a proteomics workflow was developed that combines label-free shotgun analysis, high-pH reversed-phase peptide fractionation, and targeted parallel reaction monitoring using isotope-labeled peptide standards. Using this approach, we provide proof-of-concept validation of the heterozygous G>A, R183H missense single-nucleotide variant rs1554710467 in the eukaryotic initiation factor 4H (EIF4H) gene. The variant is present in two EIF4H alternatively spliced variants, which showed equivalent translation efficiency in HCT116 cells but differ in abundance. The alternative peptide containing H183 was significantly more abundant than the corresponding reference peptide containing R183, consistent with the over-representation of the alternative allele in polysomal RNA in HCT116 cells. A dual-fluorescence ribosome-stalling assay confirmed the enhanced translation potential of the variant allele. The two EIF4H allelic proteins exhibited similar stability and subpolysomal localization. This study demonstrates the feasibility of using allele-specific proteomics at the endogenous protein levels by exploiting heterozygous coding variants. Overall, our approach extends the toolbox available to investigate allele-specific differences in mRNA translation potential, a relatively underexplored layer of gene expression regulation that could reveal interindividual differences in disease-relevant phenotypes.

Humans↗

PubMed2026

Long-read based detection of large copy number variants with potential functional significance using the ContextSV structural variant caller.

Long-read sequencing enables improved detection of structural variants (SVs) in the human genome due to its substantially increased read lengths. However, currently widely used long-read SV callers primarily rely on alignment-based evidence, limiting their ability to detect large and complex SVs and potentially missing disease-relevant events. To address these limitations, we developed ContextSV, a framework that integrates alignment evidence with copy number predictions derived from sequencing coverage and single-nucleotide variant allele frequencies to improve SV detection, particularly for large copy number variants (CNVs). We additionally developed ContextScore, a machine learning-based classification model to assign SV confidence scores based on genomic context features and integrated it within ContextSV. Through benchmarking analyses on both simulated and real datasets, we demonstrate that ContextSV improves detection of large CNVs and inversions that may be missed by existing long-read SV callers. We further illustrate its utility by identifying and experimentally validating multiple large SVs in the KOLF2.1J reference stem cell line that were not detected by other methods. Collectively, our results demonstrate that ContextSV serves as a valuable complement to existing long-read SV detection approaches by improving sensitivity for large and clinically relevant SVs.

Humans↗

PubMed2025

Structural variation detection and association analysis of whole-genome-sequence data from 16,543 Alzheimer's disease sequencing project subjects.

INTRODUCTION: The role of structural variations (SVs) in Alzheimer's disease (AD) remains understudied. METHODS: We analyzed whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (N = 16,543) and identified 400,234 (168,223 high-quality) SVs. Laboratory validation yielded a sensitivity of 82% (85% for high-quality). RESULTS: We found a burden of singletons (odds ratio [OR] = 1.07, p = 0.0017) and homozygous deletions (OR = 1.14, p < 0.0001) in cases. On AD genes, we observed the ultra-rare SVs associated with the disease, including protein-altering SVs in ABCA7, APP, PLCG2, and SORL1. Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, exemplified by a 5k deletion in LD (R2 = 0.99) with rs143080277 in NCK2. We identified a rare deletion near RNA5SP293 associated with AD (OR = 1.99, p = 1.3 × 10-5), which was replicated using an independent dataset. DISCUSSION: This study highlights the pivotal role of SVs in AD genetics. HIGHLIGHTS: Observed a significant burden of singletons and homozygous deletions in Alzheimer's disease (AD) patients. Identified rare protein-altering structural variations (SVs) in ABCA7, APP, PLCG2, and SORL1. Established linkages between SVs and AD risk-associated single nucleotide variants (SNVs). Discovered a novel deletion near RNA5SP293 linked to AD, replicated independently. Uncovered over-representation of SVs in neuronal function pathways.

Humans↗

PubMed2026

Determinants of functional burden pleiotropy and gene dosage responses across human traits.

Pleiotropic and monotonic effects of gene dosage are central to understanding comorbidities in developmental pediatric and psychiatric disorders, yet the underlying biological processes are not well characterized. Here we develop a functional burden analysis to investigate the association of all protein-coding copy-number variants, genome-wide, with 43 complex traits in approximately 500,000 UK Biobank participants. We test variant associations disrupting 172 tissue or cell-type gene sets, finding associations for all traits, which we replicate in the All of Us cohort. Functional burden pleiotropy, defined as the number of traits significantly associated with a gene set, correlates with genetic constraint and is higher for brain than non-brain functions, even after normalizing for genetic constraint. Levels of pleiotropy, measured by burden correlation, are similar in deletions and loss-of-function single-nucleotide variants, and higher than in common variants and duplications. Most gene dosage responses are non-monotonic, with deletions and duplications showing same-direction effects, and monotonic responses decrease with genetic constraint. We observe associations between functional gene sets and traits for either deletions or duplications, but rarely both, with negatively correlated effect sizes. Together, these results link genetic constraint and brain-specific mechanisms to the whole-body multimorbidity of neurodevelopmental and psychiatric conditions.

Humans↗

PubMed2025

Genetic predisposition and mediating pathways in ischemic stroke-induced cardiac arrhythmias: a genome-wide analysis.

INTRODUCTION: The clinical presentation of stroke-heart syndrome (SHS) underscores the interplay between the central nervous system and the cardiovascular system. While cardiac arrhythmia is the prevalent form of cardiac injury in SHS patients, the causal link between ischemic stroke and cardiac arrhythmia is still unclear. METHODS: Mendelian randomization analyses and genome-wide association studies data were used to investigate the causal role of ischemic stroke on cardiac complications. Mediation and colocalization analyses were used to identify potential pathways and shared genetic variants. Single nucleotide polymorphisms (SNPs) associated with arrhythmias and ischemic stroke were used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Gene expression omnibus (GEO) database from atrial fibrillation patients were used for validation. RESULTS: Mendelian randomization analyses showed a strong correlation between arrhythmias, including ventricular tachyarrhythmias and atrial fibrillation, with ischemic stroke. Diabetic microvascular (nephropathy, retinopathy) and macrovascular (cardiomyopathy, peripheral arterial disease) complications significantly mediated the effect of ischemic stroke on cardiac arrhythmias and atrial fibrillation, explaining 28.69 % and 20.48 % of the indirect effect, respectively. Colocalization analyses identified a shared causal variant in the Phosphodiesterase 3A (PDE3A) gene (rs11045239), providing genetic evidence for a shared pathogenic pathway between ischemic stroke and cardiac arrhythmias. Moreover, KEGG pathway enrichment analyses identified a role of the cyclic adenosine monophosphate (cAMP) signaling pathway in both ischemic stroke and arrhythmias. Validation using the GEO database confirmed a significant upregulation of the PDE3A gene expression in atrial fibrillation patients. CONCLUSION: This study demonstrated a causal link between ischemic stroke and cardiac arrhythmias, with diabetic complications as one mediating factor. The identification of a shared causal variant in the PDE3A gene and the role of the cAMP signaling pathway have the potential to improve prediction and management of SHS patients.

Humans↗

PubMed2025

Gene dosage architecture across complex traits.

UNLABELLED: Copy number variants (CNVs) have large effects on complex traits, but they are rare and remain challenging to study. As a result, our understanding of biological functions linking gene dosage to complex traits remains limited, and whether these functions sensitive to gene dosage are similar to those underlying the effects of rare single nucleotide variants (SNVs) and common variants remains unknown. METHODS: We developed FunBurd, a functional burden analysis, to test the association of CNVs aggregated within functional gene sets. We applied this approach in 500,000 individuals from the UK Biobank to associate 43 complex traits with CNVs disrupting 172 gene sets across tissues and cell types. We compared CNV findings with those from common variants and LoF (Loss of Function) SNVs in the same cohort using the same functional gene sets. RESULTS: All 43 traits showed FDR significant associations with CNVs. Brain tissue and neuronal cell-types showed the highest levels of pleiotropy. Most of the functional gene set associations could, in part, be explained by genetic constraint, except for brain related processes. Shared genetic contributions between pairs of traits were concordant across types of variants, but on average 2-fold higher, for rare CNVs and SNVs compared to common variants.Functional enrichment across traits found limited overlap between CNVs and common variants. Moreover, the effects of deletions and duplications were negatively correlated for most traits.In conclusion, we present new methods to separate the contributions of genetic constraint and gene function to the associations of CNVs with complex traits. Overall, the functional convergence between different types of variants -even between deletions and duplications-remains limited.

Journal Article↗

PubMed2025

Long-read sequencing of single cell-derived melanoma subclones reveals divergent and parallel genomic and epigenomic evolutionary trajectories.

Tumor evolution is driven by various mutational processes, ranging from single-nucleotide variants (SNVs) to large structural variants (SVs) to dynamic shifts in DNA methylation. Current short-read sequencing methods struggle to accurately capture the full spectrum of these genomic and epigenomic alterations due to inherent technical limitations. To overcome that, here we introduce an approach for long-read sequencing of single-cell derived subclones, and use it to profile 23 subclones of a mouse melanoma cell line, characterized with distinct growth phenotypes and treatment responses. We develop a computational framework for harmonization and joint analysis of different variant types in the evolutionary context. Uniquely, our framework enables detection of recurrent amplifications of putative driver genes, generated by independent SVs across different lineages, suggesting parallel evolution. In addition, our approach revealed gradual and lineage-specific methylation changes associated with aggressive clonal phenotypes. We also show our set of phylogeny-constrained variant calls along with openly released sequencing data can be a valuable resource for the development of new computational methods.

Journal Article↗

PubMed2025

TSC angiofibroma and ungual fibroma have different mutation signatures, with recurrent mutations in KMT2C.

PURPOSE: Tuberous sclerosis complex (TSC) is an autosomal dominant tumor suppressor syndrome characterized by tumors affecting multiple tissues, including skin, due to inactivating TSC1/TSC2 variants. Genome-wide profiling of somatic mutations in a unique collection of angiofibroma (FAF) and ungual fibroma (UF) TSC skin tumors was performed. METHODS: Genome sequencing was performed on 9 samples, comprising 4 FAF and 5 UF, along with 6 matched normal samples from 6 individuals with TSC. RESULTS: TSC-FAF and TSC-UF skin tumors have different mutation signatures, with a predominance of UV-related single-nucleotide variant (SNV; SBS7a and SBS7b) and dinucleotide variant (DNV; DBS1) signatures in FAF, and aging-related SNV (SBS1 and SBS5) signatures in UF. We also identified a novel DNV signature for TSC-UF, with frequent TG>CA and TT>GG substitutions. Furthermore, 3 inactivating somatic mutations in KMT2C were observed in 2 of 4 TSC-FAF and 5 mutations in other cancer genes. CONCLUSION: The distinct SNV mutation signatures seen in TSC-FAF and UF indicate that they develop through distinct pathogenic mechanisms, UV-induced mutagenesis in FAF, and aging-related mutagenesis in UF. The mechanism of the novel DNV signature in UFs merits further investigation. Our observation on the occurrence of KMT2C mutations suggests that KMT2C inactivation contributes to the pathogenesis of TSC-FAF.

Humans↗

PubMed2026

SeqQC-former: A sequence-quality fusion framework for QC-aware review prioritization of candidate somatic SNVs in cancer genomics.

The accurate prioritization of candidate somatic single-nucleotide variants (SNVs) remains a challenge due to the substantial variability in sequencing quality across genomic loci. SeqQC-Former is a sequence-quality fusion framework that integrates the local nucleotide context with read-level quality-control (QC) covariates derived from matched tumor-normal sequencing data. This integration generates QC-aware prioritization scores for the downstream review of candidate variants. Unlike conventional variant callers, SeqQC-Former is designed not to infer biological truth but to support post-calling review and prioritization under heterogeneous sequencing conditions. The framework was trained and evaluated on a SEQC2-derived dataset comprising 89,447 candidate loci, including 1378 positive and 88,069 negative loci. In chromosome-held-out validation, which aims to reduce potential genomic-position leakage, SeqQC-Former demonstrated strong discrimination (AUROC = 0.9479; AUPRC = 0.9448), indicating good generalization to previously unseen chromosomes. Given that the SEQC2-derived labels contain QC-associated information; these results should be interpreted as an evaluation of QC-aware prioritization capability rather than an independent validation of biological variant correctness. Ablation analyses revealed that structured QC covariates provided the dominant predictive signal under the current SEQC2-derived labeling regime. SeqQC-Former achieved a significantly higher AUROC than classical machine-learning baselines, as determined by DeLong's test (p < 0.01). Application to 53,164 glioblastoma variants demonstrated that external predictions were sensitive to QC scaling and threshold selection, underscoring that model outputs should be interpreted as QC-dependent prioritization scores rather than calibrated probabilities or definitive biological classifications. Overall, SeqQC-Former offers a reproducible post-calling QC-aware prioritization framework for large-scale somatic SNV review and underscores the importance of explicitly modeling sequencing-quality information when interpreting structured cancer genomics datasets.

Humans↗

PubMed2025

The human IG heavy chain constant gene locus is enriched for large structural variants and coding polymorphisms that vary among human populations.

The human immunoglobulin heavy chain constant (IGHC) domain of antibodies (Ab) is responsible for effector functions critical to immunity. This domain is encoded by genes in the IGHC locus, where descriptions of genomic diversity remain incomplete. We utilized long-read sequencing to build an IGHC haplotype/variant catalog from 105 individuals of diverse ancestry. We discovered uncharacterized single nucleotide variants (SNV) and large structural variants (SVs, n=7), representing new genes and alleles enriched for non-synonymous substitutions, highlighting potential functional effects. Of the 221 identified IGHC alleles, 192 were novel. SNV, SV, and gene allele/genotype frequencies revealed population differentiation, including (i) hundreds of SNVs in African and East Asian populations exceeding a fixation index (FST) of 0.3, and (ii) an IGHG4 haplotype carrying coding variants uniquely enriched in Asian populations. Our results illuminate missing signatures of IGHC diversity and establish a new foundation for investigating IGHC germline variation in Ab function and disease.

Journal Article↗

PubMed2026

Protocol for haplotype-resolved structural variant detection via long-read sequencing using cuteHap.

Long-read sequencing technologies have revolutionized human genome exploration at an unparalleled resolution, particularly facilitating the analysis of structural variation (SV) at haplotype resolution. Here, we present a protocol for using cuteHap, a robust framework for haplotype-aware SV detection through phased alignment reads generated by diverse long-read sequencing platforms. We describe procedures for single-nucleotide variant (SNV) calling, read phasing, SV calling, and genotyping. We also establish a benchmarking pipeline to evaluate the detected SV callsets. For complete details on the use and execution of this protocol, please refer to Cao et al.1.

Bioinformatics↗

PubMed2006

Specific changes in the proteomic pattern produced by the BRCA1-Ser1841Asn missense mutation.

BRCA1 is a nuclear phosphoprotein that plays a key role in many cell functions, including DNA repair, control of transcription, recombination and cell cycle homeostasis. Inherited missense mutations in the BRCA1 gene may predispose to breast and ovarian cancer, but the molecular mechanisms underlying BRCA1-induced tumorigenesis are still to be elucidated. Functional studies performed so far have contributed to the characterization of several single-nucleotide variants, mostly located at the BRCT domain, but very little is known about modifications in the protein pattern occurring in cells carrying these mutations. To shed more light in the molecular events triggered by missense mutations affecting breast cancer susceptibility genes, we have analyzed the whole cell proteome of stably transfected HeLa cell lines bearing three distinct single aminoacid changes in the BRCA1 protein (Ser1841Asn, Met1775Arg and Trp1837Arg) by means of liquid chromatography coupled to tandem-mass spectrometry. The results show that the Met1775Arg and the Trp1837Arg do not produce significant changes in the proteomic pattern compared to cells transfected with the wild-type BRCA1 cDNA. On the other hand, a different profile is detected in the BRCA1 Ser1841Asn-bearing cell line. In this particular subset, our attention has been focused on two proteins--the tumor protein D52 (TD52) and the folate receptor alpha (FOL1)--whose expression has been already reported to be upregulated in breast cancer, as well as in other tumors. Our findings indicate that Ser1841Asn BRCA1 mutation is able to activate specific protein pathways that are not triggered by other single aminoacid changes and pinpoint to the role TD52 and FOL1 as potential markers in breast cancer patients carrying this particular BRCA1 gene alteration.

Amino Acid Substitution↗

PubMed2019

Discovering human transcription factor physical interactions with genetic variants, novel DNA motifs, and repetitive elements using enhanced yeast one-hybrid assays.

Identifying transcription factor (TF) binding to noncoding variants, uncharacterized DNA motifs, and repetitive genomic elements has been technically and computationally challenging. Current experimental methods, such as chromatin immunoprecipitation, generally test one TF at a time, and computational motif algorithms often lead to false-positive and -negative predictions. To address these limitations, we developed an experimental approach based on enhanced yeast one-hybrid assays. The first variation of this approach interrogates the binding of >1000 human TFs to repetitive DNA elements, while the second evaluates TF binding to single nucleotide variants, short insertions and deletions (indels), and novel DNA motifs. Using this approach, we detected the binding of 75 TFs, including several nuclear hormone receptors and ETS factors, to the highly repetitive Alu elements. Further, we identified cancer-associated changes in TF binding, including gain of interactions involving ETS TFs and loss of interactions involving KLF TFs to different mutations in the TERT promoter, and gain of a MYB interaction with an 18-bp indel in the TAL1 superenhancer. Additionally, we identified TFs that bind to three uncharacterized DNA motifs identified in DNase footprinting assays. We anticipate that these enhanced yeast one-hybrid approaches will expand our capabilities to study genetic variation and undercharacterized genomic regions.

Algorithms↗

PubMed2025

G4SNVHunter: An R/Bioconductor Package for Evaluating SNV-Induced Disruption of G-Quadruplex Structures Leveraging the G4Hunter Algorithm.

G-quadruplexes (G4s) are nucleic acid secondary structures with important regulatory functions. Single-nucleotide variants (SNVs), one of the most common forms of genetic variation, can potentially impact the formation of G4 structures if they occur within G4 regions. However, there is currently a lack of software tools specifically designed to assess such effects. Here, we present an R/Bioconductor package named G4SNVHunter, which enables rapid detection of variants that may disrupt G4 structures. This tool, based on the core principles of the G4Hunter algorithm, can provide precise quantitative assessment of the propensity for G4 formation within genomic sequences. Specialized experimental methods can then be designed based on the results provided by G4SNVHunter to further verify the specific functions of the affected G4 structures, facilitating deeper insights into the biological impacts of genetic variants from the perspective of G4 structures. To showcase the functionality of the G4SNVHunter package, we analyzed the Neandertal and Denisovan archaic introgressed variants detected by the Sprime software, and identified approximately 5,800 variants located within G4 regions, among which around 230 may impair G4 structure formation propensity. The source code for the G4SNVHunter package has been publicly released under the MIT license at https://github.com/rongxinzh/G4SNVHunter and https://bioconductor.org/packages/devel/bioc/html/G4SNVHunter.html.

G-Quadruplexes↗

PubMed2006

Single-nucleotide polymorphisms of mismatch repair genes in healthy Chinese individuals and sporadic colorectal cancer patients.

Mismatch repair (MMR) genes are among of the most important genes associated with colorectal cancer (CRC). Single-nucleotide polymorphisms (SNPs) are generally thought to provide important information across a wide spectrum of life sciences; however, no study of association between SNPs of MMR genes and Chinese sporadic colorectal cancer (SCRC) is available. We chose 29 reported single-nucleotide variants that have rarely been verified in a population-based study. We identified SNPs and the genotype-phenotype association in Chinese populations of 150 healthy individuals and 160 SCRC patients. We extracted the genomic DNA from the blood of these individuals and used sequencing to determine these SNPs. Three SNPs (MLH1 394G-->C, 655A-->G, 1151T-->A) occurred with a frequency of 8.8-11.2% in the Chinese population. These SNPs formed a series with combined effects. The haplotype of concurrent MLH1 655 and 1151 SNPs and the haplotype combinations of MLH1 1151, MLH1 394 occurred exclusively in SCRC. None of the other 26 variants were detected in the Chinese population.

Adaptor Proteins, Signal Transducing↗

PubMed2026

SARS-CoV-2 intra-host variation shows evidence of transmission and convergent evolution in a university surveillance cohort.

Monitoring and understanding the transmission and evolution of SARS-CoV-2 remains a significant public health priority. Within-host genetic variation provides insight into viral evolution during infection and may help infer transmission events. In this study, we analysed intra-host variation in SARS-CoV-2 genome sequences from Boston University's testing mandate. Focusing on intra-host single nucleotide variants (iSNVs), we inferred transmission events and assessed the selective forces shaping within-host viral evolution. To minimize false-positive iSNVs resulting from systematic biases, we implemented stringent data filtering and developed a heuristic to exclude contamination-derived artefacts arising from batched sequencing. We find that intra-host variation is limited and infrequently transmitted during acute infections, suggesting that shared iSNVs serve as highly specific but insensitive markers of transmission. We also observed incomplete purifying selection shaping within-host diversity, with the loci most affected changing among variants of concern. Finally, we identified a highly recurrent iSNV (G11083T) which may represent a site of positive selection. Our results highlight that within-host variation provides insight into within-host pathogen evolution, in spite of its limited use in genomic epidemiology.

SARS-CoV-2↗

PubMed2003

An investigation of the 5-HT2C receptor gene as a migraine candidate gene.

Migraine is a common complex disorder, currently classified into two main subtypes, migraine with aura (MA) and migraine without aura (MO). The strong preponderance of females to males suggests an X-linked genetic component. Recent studies have identified an X chromosomal susceptibility region (Xq24-q28) in two typical migraine pedigrees. This region harbours a potential candidate gene for the disorder, the serotonin receptor 2C (5-HT(2C)) gene. This study involved a linkage and association approach to investigate two single nucleotide variants in the 5-HT(2C) gene. In addition, exonic coding regions of the 5-HT(2C) gene were also sequenced for mutations in X-linked migraine pedigrees. Results of this study did not detect any linkage or association, and no disease causing mutations were identified. Hence, results for this study do not support a significant role of the 5-HT(2C) gene in migraine predisposition.

Case-Control Studies↗

PubMed2025

Exome-wide association study of bleeding events in patients receiving direct oral anticoagulants.

BackgroundDirect oral anticoagulants (DOACs) are first-line medications for stroke prevention in non-valvular atrial fibrillation (AF). However, variability in drug response poses risks of hemorrhagic or thromboembolic events.ObjectivesAlthough genetic influences on DOACs safety are increasingly recognized, robust evidence directly linking specific polymorphisms to bleeding risk remains limited.DesignMulti-center observational case-control study including exome-wide association analysis of 196 non-valvular AF patients treated with rivaroxaban or apixaban, comprising 97 with bleeding complications and 99 without.MethodsDOAC plasma concentrations, urinary 6-β-hydroxycortisol and cortisol levels were measured for CYP3A4 phenotyping. Sequencing was performed on the DNBSEQ G-400 platform. Single-nucleotide variant (SNV) associations with bleeding risk were assessed using logistic regression with additive, dominant, and recessive genetic models. Polygenic risk scores (PRSs) were calculated to evaluate cumulative genetic effects.ResultsNo SNVs reached Bonferroni-corrected significance under any model. PRSs showed weak predictive ability for bleeding with apixaban. For rivaroxaban, regression indicated that ln Css min/D + 1 index increased with PRS, age, and 6-β-hydroxycortisol/cortisol ratio, but decreased with higher 6-β-hydroxycortisol and coronary heart disease presence. No statistically significant differences were found for the PharmGKB Level 3 variants rs1045642 (rivaroxaban) and rs2231142 (apixaban). Trends toward statistical significance were observed for the rs2472304-G variant in rivaroxaban users, rs6977165-C in apixaban users, and for the CYP3A4*1/*36 diplotype.ConclusionResidual equilibrium concentration of DOACs, including dose-adjusted, did not independently predict bleeding risk in non-valvular AF patients. Variants rs2472304 and rs6977165 may warrant further investigation as potential contributors to bleeding risk.

Humans↗