Variants In Region Research Articles

Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology.

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are risk factors for human disease. We measured chromatin accessibility in 1932 aliquots of sorted neurons and non-neurons from 616 human postmortem brains and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTLs). Only 10.4% of caQTLs are shared between neurons and non-neurons, which supports cell type-specific genetic regulation of the brain regulome. Incorporating allele-specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms that underlie disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs and identified the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides insights into disease etiology.

Disentangling the heterogeneity of multiple sclerosis through identification of independent neuropathological dimensions

Multiple sclerosis (MS) is a heterogeneous neurological disorder with regards to clinical presentation and pathophysiology. Here, we investigated the heterogeneity of MS by performing an exploratory factor analysis on quantitative and qualitative neuropathology data collected for 226 MS donors in the Netherlands Brain Bank autopsy cohort. Three promising dimensions were identified and subsequently validated with clinical, neuropathological, and genetic data. Dimension 1 ranged from a predominance of remyelinated and inactive lesions to extensive pathological changes, higher proportions of active and mixed lesions, and foamy microglia morphology. This pattern was positively correlated with more severe disease, the presence of B and T cells, and neuroaxonal damage. Scoring high on dimension 2 was associated with active lesions, reactive sites, and the presence of nodules. These donors had less severe disease, a specific pattern of cortical lesions, and MS risk variants in the human leukocyte antigen region, the latter indicating a connection between disease onset and this neuropathological dimension. Donors scoring high on dimension 3 showed increased lesional pathology with relatively more mixed and inactive lesions and ramified microglia morphology. This pattern was associated with longer disease duration, subpial cortical lesions, less involvement of the adaptive immune system, and less axonal damage. Taken together, the three dimensions may represent (1) demyelination and immune cell activity associated with pathological and clinical progression, (2) microglia (re)activity and possibly lesion initiation, and (3) loss of lesion activity and scar formation. Our findings highlight that a thorough understanding of the interplay between multiple pathological characteristics is crucial to understand the heterogeneity of MS pathology, as well as its association with genetic predictors and disease outcomes. The scores of donors on the dimensions can serve as an important starting point for further disentanglement of MS heterogeneity and translation into observations and interventions in living cohorts with MS.

Determinants of gastric cancer immune escape identified from non-coding immune-landscape quantitative trait loci

The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3′ untranslated region (3′-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3′-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3′-UTR eQTLs in immune-related genes. Our approach identifies numerous 3′-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer.

Critical reasoning on the co-expression module QTL in the dorsolateral prefrontal cortex

Expression quantitative trait locus (eQTL) analysis is a popular method of gaining insight into the function of regulatory variation. While cis-eQTL resources have been instrumental in linking genome-wide association study variants to gene function, complex trait heritability may be additionally mediated by other forms of gene regulation. Toward this end, novel eQTL methods leverage gene co-expression (module-QTL) to investigate joint regulation of gene modules by single genetic variants. Here we broadly define a "module-QTL" as the association of a genetic variant with a summary measure of gene co-expression. This approach aims to reduce the multiple testing burden of a trans-eQTL search through the consolidation of gene-based testing and provide biological context to eQTLs shared between genes. In this article we provide an in-depth examination of the co-expression module eQTL (module-QTL) through literature review, theoretical investigation, and real-data application of the module-QTL to three large prefrontal cortex genotype-RNA sequencing datasets. We find module-QTLs in our study that are disease associated and reproducible are not additionally informative beyond cis- or trans-eQTLs for module genes. Through comparison to prior studies, we highlight promises and limitations of the module-QTL across study designs and provide recommendations for further investigation of the module-QTL framework.

Interaction Studies of Hexameric and Pentameric IgMs with Serum-Derived C1q and Recombinant C1q Mimetics.

The interaction between IgM and C1q represents the first step of the classical pathway of the complement system in higher vertebrates. To identify the significance of particular IgM/C1q interactions, recombinant IgMs were used in both hexameric and pentameric configurations and with two different specificities, along with C1q derived from human serum (sC1q) and two recombinant single-chain variants of the trimeric globular region of C1q. Interaction and complement activation assays were performed using the ELISA format, and bio-layer interferometry measurements to study kinetic behavior. The differences between hexameric and pentameric IgM conformations were only slightly visible in the interaction assay, but significant in the complement activation assay. Hexameric IgM requires a lower concentration of sC1q to activate the complement compared to pentameric IgM, leading to an increased release of C4 compared to pentameric IgM. The recombinant C1q mimetics competed with sC1q in interaction assays and were able to inhibit complement activation. The bio-layer interferometry measurements revealed KD values in the nanomolar range for the IgM/C1q interaction, while the C1q mimetics exhibited rapid on and off binding rates with the IgMs. Our results make C1q mimetics valuable tools for developing recombinant C1q, specifically its variants, for further scientific studies and clinical applications.

Diverse Gene Regulatory Mechanisms Alter Rattlesnake Venom Gene Expression at Fine Evolutionary Scales.

Understanding and predicting the relationships between genotype and phenotype is often challenging, largely due to the complex nature of eukaryotic gene regulation. A step towards this goal is to map how phenotypic diversity evolves through genomic changes that modify gene regulatory interactions. Using the Prairie Rattlesnake (Crotalus viridis) and related species, we integrate mRNA-seq, proteomic, ATAC-seq and whole-genome resequencing data to understand how specific evolutionary modifications to gene regulatory network components produce differences in venom gene expression. Through comparisons within and between species, we find a remarkably high degree of gene expression and regulatory network variation across even a shallow level of evolutionary divergence. We use these data to test hypotheses about the roles of specific trans-factors and cis-regulatory elements, how these roles may vary across venom genes and gene families, and how variation in regulatory systems drive diversity in venom phenotypes. Our results illustrate that differences in chromatin and genotype at regulatory elements play major roles in modulating expression. However, we also find that enhancer deletions, differences in transcription factor expression, and variation in activity of the insulator protein CTCF also likely impact venom phenotypes. Our findings provide insight into the diversity and gene-specificity of gene regulatory features and highlight the value of comparative studies to link gene regulatory network variation to phenotypic variation.

Peripheral Blood Gene Expression Profiling Reveals Molecular Pathways Associated with Cervical Artery Dissection.

Cervical artery dissection (CeAD) is the primary cause of ischemic stroke in young adults. Monogenic heritable connective tissue diseases account for fewer than 5% of cases of CeAD. The remaining sporadic cases have known risk factors. The clinical, radiological, and histological characteristics of systemic vasculopathy and undifferentiated connective tissue dysplasia are present in up to 70% of individuals with sporadic CeAD. Genome-wide association studies identified CeAD-associated genetic variants in the non-coding genomic regions that may impact the gene transcription and RNA processing. However, global gene expression profile analysis has not yet been carried out for CeAD patients. We conducted bulk RNA sequencing and differential gene expression analysis to investigate the expression profile of protein-coding genes in the peripheral blood of 19 CeAD patients and 18 healthy volunteers. This was followed by functional annotation, heatmap clustering, reports on gene-disease associations and protein-protein interactions, as well as gene set enrichment analysis. We found potential correlations between CeAD and the dysregulation of genes linked to nucleolar stress, senescence-associated secretory phenotype, mitochondrial malfunction, and epithelial-mesenchymal plasticity.

Mapping and functional characterization of structural variation in 1060 pig genomes

BackgroundStructural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence.ResultsWe present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV’s impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies.ConclusionsThis SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.

Identification and characterization of whole blood gene expression and splicing quantitative trait loci during early to mid-lactation of dairy cattle

BackgroundCharacterization of regulatory variants (e.g., gene expression quantitative trait loci, eQTL; gene splicing QTL, sQTL) is crucial for biologically interpreting molecular mechanisms underlying loci associated with complex traits. However, regulatory variants in dairy cattle, particularly in specific biological contexts (e.g., distinct lactation stages), remain largely unknown. In this study, we explored regulatory variants in whole blood samples collected during early to mid-lactation (22–150 days after calving) of 101 Holstein cows and analyzed them to decipher the regulatory mechanisms underlying complex traits in dairy cattle.ResultsWe identified 14,303 genes and 227,705 intron clusters expressed in the white blood cells of 101 cattle. The average heritability of gene expression and intron excision ratio explained by cis-SNPs is 0.28 ± 0.13 and 0.25 ± 0.13, respectively. We identified 23,485 SNP-gene expression pairs and 18,166 SNP-intron cluster pairs in dairy cattle during early to mid-lactation. Compared with the 2,380,457 cis-eQTLs reported to be present in blood in the Cattle Genotype-Tissue Expression atlas (CattleGTEx), only 6,114 cis-eQTLs (P < 0.05) were detected in the present study. By conducting colocalization analysis between cis-e/sQTL and the results of genome-wide association studies (GWAS) from four traits, we identified a cis-e/sQTL (rs109421300) of the DGAT1 gene that might be a key marker in early to mid-lactation for milk yield, fat yield, protein yield, and somatic cell score (PP4 > 0.6). Finally, transcriptome-wide association studies (TWAS) revealed certain genes (e.g., FAM83H and TBC1D17) whose expression in white blood cells was significantly (P < 0.05) associated with complex traits.ConclusionsThis study investigated the genetic regulation of gene expression and alternative splicing in dairy cows during early to mid-lactation and provided new insights into the regulatory mechanisms underlying complex traits of economic importance.

Abstract PO4-14-11: Findings of clinically significant variants (Tier IA) with OmniSeq INSIGHT ® in a breast cancer cohort of 987 patients

Abstract Background: There were an estimated 2.3 million new breast cancer cases worldwide in 2020, with breast cancer now the most diagnosed type of cancer representing 25% of cancer cases and 17% of cancer deaths (1). The GLOBOCAN Cancer Tomorrow prediction tool estimates that incidence will increase by &amp;gt; 45% by 2040 (2). Optimal treatment for breast cancer is increasingly dependent upon knowing a patient’s somatic and germline genomic alteration status. To highlight the importance of these genomic alterations, we provide an overview of the genomic findings in 987 consecutive breast cancer patients tested in the course of routine clinical care. Methods: Comprehensive Genomic and Immune Profiling (CGIP) was performed on 987 qualified breast cancer samples at a CAP/CLIA and NYS CLEP certified reference laboratory with the OmniSeq INSIGHT ® test (3). OmniSeq INSIGHT ® is a next generation sequencing-based laboratory developed test for the detection of genomic variants, signatures, HLA Class I genotypes, and immune gene expression in formalin-fixed paraffin-embedded (FFPE) tumor tissue. DNA is sequenced to detect small variants in the full exonic coding region of 523 genes, copy number alterations in 59 genes (gains and losses), as well as analysis of microsatellite instability (MSI) and tumor mutational burden (TMB). RNA is sequenced to detect fusions and splice variants in 55 genes, in addition to mRNA expression in 64 immune genes. The resultant information, along with PD-L1 protein expression by immunohistochemistry (IHC), is intended for use by qualified health care professionals in accordance with professional guidelines in oncology for management of patients with solid neoplasms. Tier IA variants include variants with strong clinical significance as per AMP–ASCO–CAP recommendations (4). Results: There were 384 Tier IA variants detected in 370 of 987 breast cancer patients (~37.5%) with 251 in PIK3CA (65.3%), 60 in ERBB2 (15.6%), 46 in BRCA2 (11.9%), 19 in BRCA1 (4.9%), 4 in NTRK3 (1.0%), 1 in NTRK1 (0.26%) and 1 in PALB2 (0.26%) including copy number variations (CNV), gene fusion and single nucleotide variants (SNV). At the individual gene level for Tier IA variants, PIK3CA had 251 SNVs detected, ERBB2 had 55 CNVs, 1 gene fusion and 4 SNVs detected, BRCA2 had 39 SNVs and 8 CNVs detected, BRCA1 had 19 SNVs, NTRK3 had 4 gene fusions, NTRK1 had 1 gene fusion and PALB2 had 1 SNV detected. At the variant class level, there were 63 CNVs, 6 gene fusions and 315 SNVs observed. Conclusions: CGIP for breast cancer patients identified one or more clinically significant Tier IA genomic alterations that directs targeted therapy in ~ 37.5% of patients in a cohort of real world patients tested during the standard course of clinical care. This highlights the need for comprehensive genomic testing in breast cancer patients to drive therapeutic decision making.

Novel putative causal mutations associated with fat traits in Nellore cattle uncovered by eQTLs located in open chromatin regions

Intramuscular fat (IMF) and backfat thickness (BFT) are critical economic traits impacting meat quality. However, the genetic variants controlling these traits need to be better understood. To advance knowledge in this area, we integrated RNA-seq and single nucleotide polymorphisms (SNPs) identified in genomic and transcriptomic data to generate a linkage disequilibrium filtered panel of 553,581 variants. Expression quantitative trait loci (eQTL) analysis revealed 36,916 cis-eQTLs and 14,408 trans-eQTLs. Association analysis resulted in three eQTLs associated with BFT and 24 with IMF. Functional enrichment analysis of genes regulated by these 27 eQTLs revealed noteworthy pathways that can play a fundamental role in lipid metabolism and fat deposition, such as immune response, cytoskeleton remodeling, iron transport, and phospholipid metabolism. We next used ATAC-Seq assay to identify and overlap eQTL and open chromatin regions. Six eQTLs were in regulatory regions, four in predicted insulators and possible CCCTC-binding factor DNA binding sites, one in an active enhancer region, and the last in a low signal region. Our results provided novel insights into the transcriptional regulation of IMF and BFT, unraveling putative regulatory variants.

Exploring the role of HLA variants in neuroblastoma susceptibility through whole exome sequencing.

Although a number of susceptibility loci for neuroblastoma (NB) have been identified by genome-wide association studies, it is still unclear whether variants in the HLA region contribute to NB susceptibility. In this study, we conducted a comprehensive genetic analysis of variants in the HLA region among 724 NB patients and 2863 matched controls from different cohorts. We exploited whole-exome sequencing data to accurately type HLA alleles with an ensemble approach on the results from three different typing tools, and carried out rigorous sample quality control to ensure a fine-scale ancestry matching. The frequencies of common HLA alleles were compared between cases and controls by logistic regression under additive and non-additive models. Population stratification was taken into account adjusting for ancestry-informative principal components. We detected significant HLA associations with NB. In particular, HLA-DQB1*05:02 (OR = 1.61; padj = 5.4 × 10-3) and HLA-DRB1*16:01 (OR = 1.60; padj = 2.3 × 10-2) alleles were associated to higher risk of developing NB. Conditional analysis highlighted the HLA-DQB1*05:02 allele and its residue Ser57 as key to this association. DQB1*05:02 allele was not associated to clinical features worse outcomes in the NB cohort. Nevertheless, a risk score derived from the allelic combinations of five HLA variants showed a substantial predictive value for patient survival (HR = 1.53; p = 0.032) that was independent from established NB prognostic factors. Our study leveraged powerful computational methods to explore WES data and HLA variants and to reveal complex genetic associations. Further studies are needed to validate the mechanisms of these interactions that contribute to the multifaceted pattern of factors underlying the disease initiation and progression.

TSVM: Transfer Support Vector Machine for Predicting MPRA Validated Regulatory Variants.

Genome-wide association studies have shown that common genetic variants associated with complex diseases are mostly located in non-coding regions, which may not be causal. In addition, the limited number of validated non-coding functional variants makes it difficult to develop an effective supervised learning model. Therefore, improving the accuracy of predicting non-coding causal variants has become critical. This study aims to build a transfer learning-based machine learning method for predicting regulatory variants to overcome the problem of limited sample size. This paper presents a supervised learning method transfer support vector machine (TSVM) for massively parallel reporter assays (MPRA) validated regulatory variants prediction. First, uses a convolutional neural network to extract features with transfer learning. Second, the extracted features are selected by random forest method. Third, the selected features are used to train support vector machine for classification. We performed scale sensitivity experiments on the MPRA dataset and validated the effectiveness of transfer learning. The model achieves the Mcc of 0.326 and the AUC of 0.720, which are higher than the state-of-the-art method.

The First Case of Autosomal Recessive CADINS-like Disease Caused by Novel Compound Heterozygous Hypomorphic Variants in CARD11.

Abstract CARD11 is a lymphocyte-specific scaffold protein connecting antigen receptor ligation to signaling governing lymphocyte proliferation and differentiation. We and others have shown that heterozygous, dominant negative (DN) CARD11 mutations disrupting T cell receptor (TCR)-induced NF-κB signaling cause severe atopy in humans, often with recurrent infections and humoral immune deficits. Here we describe a patient with a history of recurrent upper respiratory infections, recalcitrant atopic dermatitis and common variable immunodeficiency, carrying novel compound heterozygous CARD11 variants (G689E, R920L) in regions of the protein (PDZ and L4, respectively) not normally associated with deleterious mutations. By transfecting variant expression plasmids into CARD11-deficient Jurkat T cells harboring an NF-κB-driven GFP reporter, we found that G689E was mildly hypomorphic, whereas R920L was a complete loss-of-function mutation with negligible DN activity against wild-type CARD11. However, TCR-induced NF-κB activity was markedly reduced upon variant co-expression, strongly suggesting this patient represents the first autosomal recessive case of CARD11-associated Atopy with Dominant Interference of NF-κB Signaling (CADINS) disease. Additional experiments examining different amino acid substitutions at these residues highlight key biochemical interactions between the PDZ and L4 domains, with important implications for future CARD11 structure-function and clinical diagnostic studies.

Investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment.

Defining genetic factors impacting chemotherapy failure can help to better predict response and identify drug resistance mechanisms. However, there is limited understanding of the contribution of inherited noncoding genetic variation on inter-individual differences in chemotherapy response in childhood acute lymphoblastic leukemia (ALL). Here we map inherited noncoding variants associated with treatment outcome and/or chemotherapeutic drug resistance to ALL cis-regulatory elements and investigate their gene regulatory potential and target gene connectivity using massively parallel reporter assays and three-dimensional chromatin looping assays, respectively. We identify 54 variants with transcriptional effects and high-confidence gene connectivity. Additionally, functional interrogation of the top variant, rs1247117, reveals changes in chromatin accessibility, PU.1 binding affinity and gene expression, and deletion of the genomic interval containing rs1247117 sensitizes cells to vincristine. Together, these data demonstrate that noncoding regulatory variants associated with diverse pharmacological traits harbor significant effects on allele-specific transcriptional activity and impact sensitivity to antileukemic agents.

Abstract 137: Identification Of A Noncoding Genetic Variant In The Tissue Factor Locus That Reverses Lethal Thrombosis In Mice

Background: Thrombosis is initiated by tissue factor (TF, gene name F3 ) binding to coagulationFVII, with tissue factor pathway inhibitor (TFPI) inhibiting this complex. Alterations in TF orTFPI expression significantly affect thrombosis. Reducing TFPI expression by 50% ( Tfpi +/-) inmice results in a perinatal lethal phenotype on the Factor V Leiden homozygous( F5 L/L )prothrombotic background. We used the F5 L/L Tfpi +/- lethal phenotype to conduct a dominantsensitized whole genome ENU mutagenesis screen to suppress the F5 L/L Tfpi +/- lethality. Weidentified a Modifier of Factor 5 Leiden 6 (MF5L6) line with 72% penetrance and 85 F5 L/L Tfpi +/- offspring. A significant linkage peak (LOD=4.35),explaining half the suppressing effect andcontaining F3 (Chromosome 3) was identified. Goals/Hypothesis: To identify the genomic variant controlling F3 expression in the MF5L6 line. Methods: To quantify F3 expression in the surviving mice from MF5L6, quantitative PCR onliver, lung, and heart tissues from MF5L6 was performed. We used Sanger DNA and highthroughput sequencing to identify candidate TF regulatory variants in the F3 locus. Theprothrombin time assay was used to test the effects of reduced TF expression on in vitro bloodcoagulation. Results: Two distinct expression profiles in the lung and liver of the MF5L6 mice wereobserved, those that had a 50% reduction in F3 mRNA and those that did not. Heart tissuesexhibited one expression profile, suggesting that the variant regulates F3 expressiontissue-specifically. Sanger sequencing of the F3 coding region revealed no coding mutations inMF5L6 mice. Whole genome sequencing identified two novel candidate variants (in unknownF3 regulatory elements) in the 200 kilobase upstream region of F3 . The 50% reduction in F3 resulted in significant changes in coagulation by the prothrombin assay (n=18,p&lt;0.0009). Conclusion: We identified novel candidate variants for regulating F3 gene expression and aredetermining their mechanism of action. Investigation of these variants will provide new insightsinto the regulation of F3 and enable us to identify the variant(s) responsible for the remainder ofthe thrombosis suppressing effect in MF5L6. Our findings provide new insights into the geneticregulation of thrombosis.

Regional-specific calibration enables application of computational evidence for clinical classification of 5′ cis-regulatory variants in Mendelian disease

To date, clinical genetic testing for Mendelian disease variants has focused heavily on exonic coding and intronic gene regions. This multi-step study was undertaken to provide an evidence base for selecting and applying computational approaches for use in clinical classification of 5' cis-regulatory region variants. Curated datasets of clinically reported disease-causing 5' cis-regulatory region variants and variants from matched genomic regions in population controls were used to calibrate six bioinformatic tools as predictors of variant pathogenicity. Likelihood ratio estimates were aligned to code weights following ClinGen recommendations for application of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) classification scheme. Considering code assignment across all reference dataset variants, performance was best for CADD (81.2%) and REMM (81.5%). Optimized thresholds provided moderate evidence toward pathogenicity (CADD, REMM) and moderate (CADD) or supporting (REMM) evidence against pathogenicity. Both sensitivity and specificity of prediction were improved when further categorizing variants based on location in an EPDnew-defined promoter region. Combining predictions (CADD, REMM, and location in a promoter region) increased specificity at the expense of sensitivity. Importantly, the optimal CADD thresholds for assigning ACMG/AMP codes PP3 (≥10) and BP4 (≤8) were vastly different from recommendations for protein-coding variants (PP3≥25.3; BP4≤22.7); CADD <22.7 would incorrectly assign BP4 for >90% of reported disease-causing cis-regulatory region variants. Our results demonstrate the need to consider a tiered approach and tailored score thresholds to optimize bioinformatic impact prediction for clinical classification of 5' cis-regulatory region variants.

Mutations in the TP53, VEGFA, and CTH Genes as Key Molecular Markers for the Diagnosis of Glioblastoma.

Background Brain cancer, particularly glioblastoma (GBM), is a global health problem. Despite therapy advances, GBM patients have a poor prognosis. The progression and etiology of GBM may be linked to gene polymorphisms in the VEGFA, TP53, and CTHgenes, among others. However, the genetic variations and their interaction in GBM are not fully understood. This study examines the effects of mutations in the VEGFA, TP53, and CTH genes on GBM. Methodology Tissue and blood samples were obtained for hematological, biochemical, and genetic analysis from 18 patients diagnosed with GBM as well as 28 healthy individuals. Standard methods were adopted to perform hematological and biochemical analyses, whereas mutational landscape and expression profiles were obtained from publicly accessible databases. Tissue samples were processed for genomic DNA extraction, and genotype determination was carried out through conventional polymerase chain reaction (PCR) and Sanger sequencing. Results The study involved 18 patients with grade IV GBM beforetreatment and 28 healthy individuals. The patients consisted of11 men (61%) and seven females (39%), while healthy individuals included 14 (50%) males and 14 (50%) females. Sixty-seven percentof patients were under 50, 17% between 51 and 60, and 17% over 61, compared to healthy individualswho were 61% under 50, 7%between 51 and 60, and 32% over 60. GBM patients showed higher neutrophil and monocyte counts (median 81% (63.9, 83.5) and 4.2% (3.8-7.3)), respectively, and lower lymphocyte counts (median 13.4% (8.8, 28.40)) compared to controls. The median values of aspartate transaminase (AST), alanine transaminase (ALT), and alkaline phosphatase (ALP) showed no significant differences between the control and GBM groups. GBM patients had significantly higher median CRP levels of 2.55 (1.6, 98) than controls. Analysis of databases revealed a high prevalence of mutations in TP53, with splice region variants, missense variants, and intron variants being the most common. VEGFA and CTH also displayed mutations, primarily missense and intron variants. Gene expression analysis showed significantly higher levels of TP53 and VEGFA in GBM patients compared to controls. CTH expression also exhibited a slight increase in GBM patients. Sanger sequencing identified three mutations in the TP53 gene, including a novel mutation (11915C>A) not previously reported in external databases. Additionally, novel mutations were found in the VEGFA (841G>GA, 919T>TG) and CTH (28398A>AC, 28399A>AT) genes. Conclusions This study highlights the immune dysregulation, inflammation, and genetic variations in GBM.The findings emphasize the potential importance of the TP53, VEGFA, and CTH genes as targets for therapies and diagnostic biomarkers of GBM. Further study is necessary to comprehend these genetic variations' functional implications and their use in personalized GBM treatment.

Bayesian colocalization of GWAS and eQTL signals reveals cell type-specific genes and regulatory variants for susceptibility to subtypes of ischemic stroke

A colocalization analysis of genome-wide association study (GWAS) signals and expression quantitative trait loci (eQTL) was conducted to pinpoint target genes and their regulatory nucleotide variants for subtypes of ischemic stroke. We utilized GWAS data from prominent meta-analysis consortia (MEGASTROKE and GIGASTROKE) and single-cell eQTL data in brain and blood tissues to enhance accuracy and minimize noise inherent in bulk RNA-seq. Employing Bayesian colocalization methods, we identified ten shared loci between GWAS and eQTL signals, targeting five eGenes. Specifically, RAPH1 and ICA1L were discovered for small vessel stroke (SVS), whereas SCYL3, CAV1, and CAV2 were for cardioembolic stroke (CS). However, no findings have been made for large artery stroke. The exploration and subsequent functional analysis of causal variants within the colocalized regions revealed their regulatory roles, particularly as enhancer variants (e.g., rs144505847 and rs72932755 targeting ICA1L; rs629234 targeting SCYL3; rs3807989 targeting CAV1 and CAV2). Notably, our study unveiled that all eQTL for CS were identified in oligodendrocytes, while those for SVS were across excitatory neurons, astrocytes, and oligodendrocyte precursor cells. This underscores the heterogeneous tissue-specific genetic factors by subtypes of ischemic stroke. The study emphasizes the need for intensive research efforts to discover causative genes and variants, unravelling the cell type-specific genetic architecture of ischemic stroke subtypes. This knowledge is crucial for advancing our understanding of the underlying pathophysiology and paving the way for precision neurology applications.

The genetics of niche-specific behavioral tendencies in an adaptive radiation of cichlid fishes.

Behavior is critical for animal survival and reproduction, and possibly for diversification and evolutionary radiation. However, the genetics behind adaptive variation in behavior are poorly understood. In this work, we examined a fundamental and widespread behavioral trait, exploratory behavior, in one of the largest adaptive radiations on Earth, the cichlid fishes of Lake Tanganyika. By integrating quantitative behavioral data from 57 cichlid species (702 wild-caught individuals) with high-resolution ecomorphological and genomic information, we show that exploratory behavior is linked to macrohabitat niche adaptations in Tanganyikan cichlids. Furthermore, we uncovered a correlation between the genotypes at a single-nucleotide polymorphism upstream of the AMPA glutamate-receptor regulatory gene cacng5b and variation in exploratory tendency. We validated this association using behavioral predictions with a neural network approach and CRISPR-Cas9 genome editing.