Missense Single Nucleotide Polymorphisms Research Articles

Insights into genetic diversity and functional significance of the bHLH genes in cotton fiber development

This study investigated the identification and distribution of single nucleotide polymorphisms (SNPs) within basic Helix-Loop-Helix (bHLH) transcription factors (TFs) across diverse cotton (Gossypium hirsutum) accessions, including wild, landrace, and improved varieties. Comprehensive genomic analyses revealed substantial SNP diversity in wild cotton, distinct from that observed in landraces and improved accessions. Comparative analysis showed notable variations in SNP abundance and impact levels across different accessions, with missense SNPs being prevalent. Nucleotide substitution patterns highlighted the dominance of G>A and A>G substitutions. Population genetic analyses unveiled significant genetic diversity within wild accessions and distinct clustering between wild and improved accessions. Temporal expression profiling of bHLH genes during cotton fiber development demonstrated dynamic expression patterns, emphasizing their roles in fiber initiation, elongation, and cellulose biosynthesis. Moreover, association analysis identified SNPs significantly associated within bHLH genes, particularly GhbHLH149, with fiber quality traits, indicating their potential functional significance. Population genetic analyses further revealed evidence of positive selection on GhbHLH149 during cotton improvement. This study provides a comprehensive understanding of SNP diversity, gene expression dynamics, and genetic selection in bHLH genes, offering valuable insights for future cotton breeding efforts aimed at improving fiber quality traits in cotton.

In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene

Single nucleotide polymorphisms (SNPs) are one of the most common determinants and potential biomarkers of human disease pathogenesis. SNPs could alter amino acid residues, leading to the loss of structural and functional integrity of the encoded protein. In humans, members of the minichromosome maintenance (MCM) family play a vital role in cell proliferation and have a significant impact on tumorigenesis. Among the MCM members, the molecular mechanism of how missense SNPs of minichromosome maintenance complex component 6 (MCM6) contribute to DNA replication and tumor pathogenesis is underexplored and needs to be elucidated. Hence, a series of sequence and structure-based computational tools were utilized to determine how mutations affect the corresponding MCM6 protein. From the dbSNP database, among 15,009 SNPs in the MCM6 gene, 642 missense SNPs (4.28%), 291 synonymous SNPs (1.94%), and 12,500 intron SNPs (83.28%) were observed. Out of the 642 missense SNPs, 33 were found to be deleterious during the SIFT analysis. Among these, 11 missense SNPs (I123S, R207C, R222C, L449F, V456M, D463G, H556Y, R602H, R633W, R658C, and P815T) were found as deleterious, probably damaging, affective and disease-associated. Then, I123S, R207C, R222C, V456M, D463G, R602H, R633W, and R658C missense SNPs were found to be highly harmful. Six missense SNPs (I123S, R207C, V456M, D463G, R602H, and R633W) had the potential to destabilize the corresponding protein as predicted by DynaMut2. Interestingly, five high-risk mutations (I123S, V456M, D463G, R602H, and R633W) were distributed in two domains (PF00493 and PF14551). During molecular dynamics simulations analysis, consistent fluctuation in RMSD and RMSF values, high Rg and hydrogen bonds in mutant proteins compared to wild-type revealed that these mutations might alter the protein structure and stability of the corresponding protein. Hence, the results from the analyses guide the exploration of the mechanism by which these missense SNPs of the MCM6 gene alter the structural integrity and functional properties of the protein, which could guide the identification of ways to minimize the harmful effects of these mutations in humans.

Association of HNMT gene polymorphisms with carnosine content in red-brown Korean native chickens.

Carnosine and anserine affect the meat flavor. The contents of carnosine and anserine in meat are affected by genetic and environmental factors. This study aimed to discover the single-nucleotide polymorphisms (SNPs) in the HNMT and HNMT-like genes and to associate them with the content of carnosine and anserine in Korean native chicken-red brown line (KNC-R ). This study used a total of 384 birds (males, n=192; females, n=192) aged 10 weeks old, for genotyping HNMT and HNMT-like genes. One synonymous SNP (rs29009298C/T) of the HNMT gene was genotyped by PCR-RFLP methods whereas four missense SNPs (rs734406537G/A; rs736514667A/G; rs15881680G/A and rs316765035T/C) of the HNMT gene, and one missense SNP rs737657949A/C of the HNMT-like gene were genotyped by PACE genotyping technology. Two-way ANOVA of the R program was used to associate HNMT genotypes with the contents of carnosine and anserine in KNC- R chickens. There were significant associations (p<0.05) between the genotypes of the synonymous SNP:rs29009298C/T, missense SNP rs736514667A/G of the HNMT gene and the content of carnosine in KNC-Rs. This study also reported the sex effect on the carnosine content, where females had more content of carnosine compared to that of male KNC-R. Two SNPs (synonymous: rs735769522C/T) and missense: rs736514667A/G) in the HNMT gene might be used as genetic markers in the selection and breeding of chickens with better taste and high-flavored meat.

The role of genetic polymorphisms in the sulfation of pregnenolone by human cytosolic sulfotransferase SULT2B1a

Pregnenolone is a key intermediate in the biosynthesis of many steroid hormones and neuroprotective steroids. Sulfotransferase family cytosolic 2B member 1 (SULT2B1a) has been reported to be highly selective to sulfate pregnenolone. This study aimed to clarify the effect of missense single nucleotide polymorphisms (SNPs) of the human SULT2B1 gene on the sulfating activity of coded SULT2B1a allozymes toward Pregnenolone. To investigate the effects of single nucleotide polymorphisms of the SULT2B1 gene on the sulfation of pregnenolone by SULT2B1a allozymes, 13 recombinant SULT2B1a allozymes were generated, expressed, and purified using established procedures. Human SULT2B1a SNPs were identified by a comprehensive database search. 13 SULT2B1a nonsynonymous missense coding SNPs (cSNPs) were selected, and site-directed mutagenesis was used to generate the corresponding cDNAs, packaged in pGEX-2TK expression vector, encoding these 13 SULT2B1a allozymes, which were bacterially expressed in BL21 E. coli cells and purified by glutathione-Sepharose affinity chromatography. Purified SULT2B1a allozymes were analyzed for sulfating activities towards pregnenolone. In comparison with the wild-type SULT2B1a, of the 13 allozymes, 11 showed reduced activity toward pregnenolone at 0.1 µM. Specifically, P134L and R259Q allozymes, reported to be involved in autosomal-recessive congenital ichthyosis, displayed low activity (1–10%) toward pregnenolone. The findings of this study may demonstrate the impact of genetic polymorphism on the sulfation of pregnenolone in individuals with different SULT2B1 genotypes.

Evaluation of SNP in the CDH8 and CDH10 Genes Associated with Autism Using In-Silico Tools

Autism spectrum disorder (ASD) is defined as a pervasive and multifactorial neurodevelopmental disorder (ND). It is characterized by repetitive behavioral patterns as well as symptoms of social interaction and communication disorder. The cadherin (CDH) superfamily is a large group of synaptic cell adhesion molecules and has been widely related with ND, including autism. The aim of this study is to evaluate the potentially deleterious missense single nucleotide polymorphisms (SNPs) in CDH8 and CDH10 genes, which are related with ASD and cause amino acid changes, using internet-based software tools. To identify potentially harmful missense SNPs; all SNPs were screened using SIFT, PolyPhen-2, PROVEAN, SNPs&amp;GO, Meta-SNP, and SNAP2 software tools, and common deleterious ones were filtered out. Its effect on protein stabilization was investigated with I-Mutant 3.0 and MUpro tools. Three-dimensional models of these common damaging amino acid changes were evaluated with the HOPE software. As a result of in silico analysis of 577 missense SNPs in the CDH8 gene; The rs145143780 (Y572C) polymorphism common damaging ‎SNP has been detected by all software tools.‎ According to the results of the in silico analysis of 526 missense SNPs found in the CDH10 gene; The rs13174039 (V459G), rs147882578 (N485K), rs201423740 (Y306C), rs201956238 (F317L) and rs373340564 (R128C) common damaging SNPs have been identified in all polymorphisms by all software tools. As a result of this study, it is thought that the data obtained will make important contributions to future relevant experimental studies.

Insights into the structure–function relationship of missense mutations in the human TOP2A protein in ovarian cancer

Topoisomerase 2-alpha (TOP2A) is a nuclear protein that is responsible for the maintenance of the topological state of DNA. TOP2A is highly upregulated in ovarian cancer, and its copy number is an important prognosis factor. A large number of single-nucleotide polymorphism (SNP), insertion, and deletion mutations have been reported in TOP2A. Thus, a structural and functional study of missense SNPs was carried out to screen potentially damaging mutations. The 193 non-synonymous SNPs in the coding region of TOP2A in the dbSNP database were selected for in silico analysis. The deleterious SNPs were screened using sorting intolerant from tolerant (SIFT), PolyPhen-2, SNAP2, and SNPs&amp;amp;Go, and we obtained four possibly damaging SNPs at the end (Y481C, N7741, E922K, and R1514W). Mutants Y481C and E922K were predicted to be highly deleterious and showed decreased protein stability compared with native proteins, as predicted by I-Mutant 3. We used the SWISS-MODEL to model the structure of these two mutants, and the structural attributes of modeled mutants were studied using Hope Project, solvent accessibility-based protein–protein interface identification and recognition (SPPIDER), SRide, and HBAT, which predicted small variations from the native protein. Molecular dynamics simulation demonstrated a decrease in root mean square deviation (RMSD) and the radius of gyration of two mutants, which is relative to the native protein. The molecular docking of TOP2A with etoposide suggests that mutations may lead to resistance to TOP2A-targeted chemotherapy. In addition, the relative expression analysis performed by qRT-PCR also reveals that there is a three-fold increase in the expression levels of the TOP2A protein in ovarian adenoma cancer cell lines. Our analysis reveals that Y481C and E922K are highly damaging variants of TOP2A, which alter the protein dynamics and may be implicated in causing ovarian cancer.

BRCA2 Polymorphisms and Breast Cancer Susceptibility: a Multi-Tools Bioinformatics Approach.

The main focus of this investigation is to identify deleterious single nucleotide polymorphisms (SNPs) located in the BRCA2 gene through in silico approach, thereby,providing an understanding of potential consequences regarding the susceptibility to breast cancer. The GenomAD database was used to identify SNPs. To determine the potential adverse consequences, our study employed various prediction tools, including SIFT, PolyPhen, PredictSNP, SNAP2, PhD-SNP, and ClinVar. The pathogenicity associated with the deleterious snSNPs was evaluated bu MutPred and Fathmm. Additionally, I-Mutant and MuPro were used to assess the stability, followed by conservation and protein-protein interaction analysis using robust computational tools. The 3D structure of BRCA2 protein was generated by SwissModel, followed by validation using PROCHECK and Errat. The GenomAD database was used to identify a total of 7, 921 SNPs, including 1940 missense SNPs. A set of 69 SNPs predicted by consensus to be damaging across all platforms was identified. Mutpred and Fathmm identified 48 and 38 SNPs, respectively to be associated with cancer. While I- Mutant and MuPro assays suggested 22 SNPs to decrease protein stability. Additionally, these 22 SNPs reside within highly conserved regions of the BRCA2 protein. Domain analysis, utilizing InterPro, pinpointed 18 deleterious mutations within crucial DNA binding domains and one in the BRC repeat region. This study establishes a foundation for future experimental validations and the creation of breast cancer-targeted treatment approaches.

Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease

Chronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.

MISSENSE MUTATIONS IN THE IRAK1 GENE ARE ASSOCIATED WITH AN INCREASED RISK OF SYSTEMIC LUPUS ERYTHEMATOSUS

Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation in humans. Missense SNPs can change protein structure and function. This study aimed to determine missense SNPs of the IRAK1 gene that can affect the amino acid sequence and lead to changes in protein structure and function, as well as their relationship as a risk factor for SLE. In this in silico method, several bioinformatics tools have been used to identify missense SNPs, including their properties and impacts, as well as their interaction networks with proteins. The tools used were PolyPhenv2, SIFT, PhD-SNP, PROVEAN, SNAP, Panthers, I-Mutant 3.0, and GeneMania. Four missense SNPs, rs11465830, rs1059702, rs1059703, and 10127175, were obtained from the NCBI SNP database. The SIFT test results showed that all the SNPs were tolerant. In the test results obtained using PolyPhen, the four SNPs were benign. The results of the probe test indicated that the four SNPs were neutral. When tested with SNAP, one SNP was neutral, and three others had an impact. In the PhD-SNP test, all SNPs were neutral. In the panther test, all SNPs were benign. The I-mutant assay showed that the four SNPs could decrease protein stability. Tests with GeneMania have reported that most interactions between genes were between IRAK1 and MYD88, and physical interactions were the most dominant form of interaction. Conclusion. rs10127175, rs11465830, rs1059702, and rs1059703 are missense SNPs in IRAK1, which can disrupt protein stability and be a risk factor for SLE. Keywords: IRAK1, SNP, Missense, Systemic Lupus Erythematosus

Identification of Coding Variants in 10q22.1 Associated with Vitiligo in the Chinese Han Population.

Objective: This study aims to identify causal variants associated with vitiligo in an expanded region of 10q22.1. Materials and Methods: We conducted a fine-scale deep analysis of the expanded 10q22.1 region using in a large genome-wide association studies dataset consisting of 1117 cases and 1701 controls through imputation. We selected five nominal coding single nucleotide polymorphisms (SNPs) located in SLC29A3 and CDH23 and genotyped them in an independent cohort of 2479 cases and 2451 controls in a Chinese Han population cohort using the Sequenom MassArray iPLEX1 system. Results: A missense SNP in SLC29A3, rs2252996, showed strong evidence of association with vitiligo (p = 1.34 × 10-8, odds ratio [OR] = 0.82). Three synonymous SNPs (rs1084004 in SLC29A3; rs12218559 and rs10999978 in CDH23) provided suggestive evidence of association for vitiligo (p = 1.69 × 10-6, OR = 0.84; p = 9.47 × 10-5, OR = 1.18; p = 6.90 × 10-4, OR = 1.16, respectively). Stepwise conditional analyses identified two significant independent disease-associated signals from the four SNPs (both p < 0.05; both D' = 0.03; and r2 = 0.00). Conclusion: The study identifies four genetic coding variants in SLC29A3 and CDH23 on 10q22.1 that may contribute to vitiligo susceptibility with one missense variant affecting disease subphenotypes. The presence of multiple genetic variants underscores their significant role in the genetic pathogenesis of the disease.

A missense SNP in the tumor suppressor SETD2 reduces H3K36me3 and mitotic spindle integrity in Drosophila.

Mutations in SETD2 are among the most prevalent drivers of renal cell carcinoma (RCC). We identified a novel single nucleotide polymorphism (SNP) in SETD2, E902Q, within a subset of RCC patients, which manifests as both an inherited or tumor-associated somatic mutation. To determine if the SNP is biologically functional, we used CRISPR-based genome editing to generate the orthologous mutation within the Drosophila melanogaster Set2 gene. In Drosophila, the homologous amino acid substitution, E741Q, reduces H3K36me3 levels comparable to Set2 knockdown, and this loss is rescued by reintroduction of a wild-type Set2 transgene. We similarly uncovered significant defects in spindle morphogenesis, consistent with the established role of SETD2 in methylating α-Tubulin during mitosis to regulate microtubule dynamics and maintain genome stability. These data indicate the Set2 E741Q SNP affects both histone methylation and spindle integrity. Moreover, this work further suggests the SETD2 E902Q SNP may hold clinical relevance.

Computational Exploration of Single-Nucleotide Polymorphisms in the Human hRAS Gene: Implications and Insights.

Background A group of genes called oncogenes includes the Harvey rat sarcoma virus (hRAS) gene. Along with hRAS, Kirsten rat sarcoma viral oncogene homolog (kRAS) and neuroblastoma RAS viral oncogene homolog(nRAS) genes belong to the Rat sarcoma (Ras) family of oncogenes. These three genes result in Rho guanosine triphosphate hydrolases (GTPases) as their protein product. Instructions for producing the protein hRAS, which is mainly involved in controlling cell division, are provided by the hRAS gene. The hRAS protein transfers signals from outside through a process called signal transduction.Because the hRAS protein is a GTPase, it changes the chemical guanosine-5'-triphosphate (GTP) into guanosine diphosphate (GDP). GTP and GDP molecules operate as switches to turn on and off the hRAS. This study aimed to anticipate the structure and stability of the protein resulting from missense single-nucleotide polymorphisms (SNPs) in the human hRAS genes. Methodology To investigate the possible negative effects associated with these SNPs, bioinformatic analysis is typically essential. The following tools were employed for forecasting harmful SNPs: Scale-Invariant Feature Transform (SIFT), Protein Analysis Through Evolutionary Relationships (PANTHER), non-synonymous SNP by Protein Variation Effect Analyzer (PROVEAN), and non-synonymous SNP by Single Nucleotide Polymorphism Annotation Platform (SNAP). Results The present study identified a total of 11 SNPs using the SIFT approach, which were shown to have functional significance. Only two of these 11 SNPs were determined to be tolerable, whereas nine were shown to be detrimental. Among the 11 SNPs analyzed, seven (Q61H, Q99H, K117R, A121D, A146V, R169W, R169Q) were classified as possibly damaging,and four (G13V, Q22K, Q61K, Q13V) were categorized as probably benign according to the predictions made by PANTHER tools. Therefore, the seven SNPs were identified as high-risk SNPs. Conclusions Given that SNPs have the potential to be candidates for cellular alterations brought on by mutations that are associated with cancer, this study provides vital information about how SNPs might be utilized as a diagnostic marker for cancer.

Unraveling the function and structure impact of deleterious missense SNPs in the human OX1R receptor by computational analysis

The orexin/hypocretin receptor type 1 (OX1R) plays a crucial role in regulating various physiological functions, especially feeding behavior, addiction, and reward. Genetic variations in the OX1R have been associated with several neurological disorders. In this study, we utilized a combination of sequence and structure-based computational tools to identify the most deleterious missense single nucleotide polymorphisms (SNPs) in the OX1R gene. Our findings revealed four highly conserved and structurally destabilizing missense SNPs, namely R144C, I148N, S172W, and A297D, located in the GTP-binding domain. Molecular dynamics simulations analysis demonstrated that all four most detrimental mutant proteins altered the overall structural flexibility and dynamics of OX1R protein, resulting in significant changes in the structural organization and motion of the protein. These findings provide valuable insights into the impact of missense SNPs on OX1R function loss and their potential contribution to the development of neurological disorders, thereby guiding future research in this field.

Delving into the significance of the His289Tyr single-nucleotide polymorphism in the glutamate ionotropic receptor kainate-1 (Grik1) gene of a genetically audiogenic seizure model.

Genetic abnormalities affecting glutamate receptors are central to excitatory overload-driven neuronal mechanisms that culminate in seizures, making them pivotal targets in epilepsy research. Increasingly used to advance this field, the genetically audiogenic seizure hamster from Salamanca (GASH/Sal) exhibits generalized seizures triggered by high-intensity acoustic stimulation and harbors significant genetic variants recently identified through whole-exome sequencing. Here, we addressed the influence of the missense single-nucleotide polymorphism (C9586732T, p.His289Tyr) in the glutamate receptor ionotropic kainate-1 (Grik1) gene and its implications for the GASH/Sal seizure susceptibility. Using a protein 3D structure prediction, we showed a potential effect of this sequence variation, located in the amino-terminal domain, on the stability and/or conformation of the kainate receptor subunit-1 protein (GluK1). We further employed a multi-technique approach, encompassing gene expression analysis (RT-qPCR), Western blotting, and immunohistochemistry in bright-field and confocal fluorescence microscopy, to investigate critical seizure-associated brain regions in GASH/Sal animals under seizure-free conditions compared to matched wild-type controls. We detected disruptions in the transcriptional profile of the Grik1 gene within the audiogenic seizure-associated neuronal network. Alterations in GluK1 protein levels were also observed in various brain structures, accompanied by an unexpected lower molecular weight band in the inferior and superior colliculi. This correlated with substantial disparities in GluK1-immunolabeling distribution across multiple brain regions, including the cerebellum, hippocampus, subdivisions of the inferior and superior colliculi, and the prefrontal cortex. Notably, the diffuse immunolabeling accumulated within perikarya, axonal fibers and terminals, exhibiting a prominent concentration in proximity to the cell nucleus. This suggests potential disturbances in the GluK1-trafficking mechanism, which could subsequently affect glutamate synaptic transmission. Overall, our study sheds light on the genetic underpinnings of seizures and underscores the importance of investigating the molecular mechanisms behind synaptic dysfunction in epileptic neural networks, laying a crucial foundation for future research and therapeutic strategies targeting GluK1-containing kainate receptors.

Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, ‎we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.

Computational analysis of Alzheimer's disease-associated missense SNPs to understand underlying molecular mechanisms and identify diagnostic biomarkers

BackgroundAlzheimer's disease (AD) is the most common and progressive type of brain disorder that affects parts of the brain responsible for memory, speaking, thinking, and many other important functions. Apart from its common risk factors such as aging, environment, and lifestyle elements, the risk of developing AD largely depends on gene variants, which present a promising opportunity for identifying novel diagnostic and therapeutic biomarkers. ObjectivesEarly studies have revealed numerous SNPs simultaneously associated with AD and other diseases such as Parkinson's disease, stroke, multiple sclerosis, and more. Therefore, it is important to conduct research on identifying single nucleotide missense mutations in certain genes specifically linked to AD to understand the prognosis and diagnosis of the disease. MethodsIn this research, we utilized multiple sequence-based computational tools and database servers to analyze specific missense single nucleotide polymorphisms and their potential effects on protein structure and stability. ResultsOur in-silico analysis revealed SNPs of 3 genes, specifically, ATP8B4, UBXN11, and TREM2, to be deleterious. The associating mutations were found to be destabilizing the protein structure and function of deleterious genes. ConclusionThree genes, including ATP8B4, UBXN11, and TREM2 and their associated SNPs, were found to be deleterious and are potentially linked to AD. Amino acid changes associated with these genes were found to affect their interactions, which are connected to specific biological processes and pathways that may trigger AD.

Impact of missense TSBP1 variants on the susceptibility to coronary heart disease

BackgroundA genome-wide association study has recognized C6orf10-BTNL2 polymorphism in coronary artery disease. The goal of this study was to explore the potential correlation of nine missense TSBP1 variants with coronary heart disease (CHD) risk in the Chinese Han population. MethodsNine TSBP1 missense single nucleotide polymorphisms (SNPs) were selected for genotyping by the Agena MassARRAY platform. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to analyze the contribution of TSBP1 SNPs to CHD predisposition by logistic regression models adjusted by age, sex, drinking, and smoking. The correlation of TSBP1 variants with clinical data in CHD patients was examined by Kruskal-Wallis test. Resultsrs9268368-C (p = 0.039, OR = 1.18, 95 % CI: 1.01–1.38) was related to an increased risk of CHD, while rs3749966-C (p = 0.032, OR = 0.49, 95 % CI: 0.25–0.96) and rs3129941-A (p = 0.011, OR = 0.74, 95 % CI: 0.59–0.93) might be protective factors against CHD occurrence in the Chinese Han population. We also observed the effects of demographic characteristics (age, sex, alcohol consumption, and smoking) and complications (hypertension and diabetes) on the interactive association of TSBP1 polymorphisms with CHD susceptibility. rs139993810 was related to the levels of high-density lipoprotein cholesterol (HDL-C, p = 0.030). ConclusionsOur findings determined the association of TSBP1 rs9268368, rs3749966, and rs3129941 with CHD occurrence in the Chinese Han population, and highlighted the influence of demographic characteristics and complications on the interactive association of TSBP1 polymorphisms with CHD risk.

In silico analysis of missense SNPs in GABRA1, GABRB1, and GABRB3 genes associated with some diseases in neurodevelopmental disorders

BackgroundNeurodevelopmental disorders are disorders that are generally seen in the early developmental period of an individual's life and involve more than one disease that causes disruptions in the central nervous system. These disorders can be given as examples of diseases such as autism, mental retardation, some epileptic disorders, communication disorders, and mental retardation. The aim of this study is to determine the possible harmful effects of missense single nucleotide polymorphisms (SNPs) in the GABRA1, GABRB1, and GABRB3 genes, which are associated with neurodevelopmental disorders, on the structure and stabilization of the protein, using in silico methods. Software tools SIFT, PolyPhen-2 HumVar, PolyPhen-2 HumDiv, PROVEAN, SNAP2, PHD-SNP, SNP&GO, PANTHER, and Meta-SNP were used to predict harmful SNPs. I-Mutant and MUpro software tools were used to predict the effects of predicted harmful SNPs on protein stabilization. The STRING software tool was used for protein–protein interactions, the GeneMANIA software tool for gene–gene interactions, and the Project HOPE software tool for three-dimensional modeling examples.ResultsAs a result of the bioinformatics analysis, rs121434579, rs139163545, and rs267600530 in the GABRA1 gene; rs74608570, rs75612351, rs78815529 in the GABRB1 gene, and rs7819600779, rs1719850690, rs7819600779, rs171985060690, rs7819600779, rs1719850600779, rs149963014 in the GABRB3 gene were predicted as harmful SNPs.ConclusionsIn this study, protein structure, function, and stabilization of SNPs known to cause amino acid substitutions in GABRA1, GABRB1, and GABRB3 genes associated with some diseases in neurodevelopmental disorders were investigated using bioinformatics tools. As a result of the results obtained in our study, it is thought that it will benefit experimental studies and bioinformatics studies.

Bioinformatic analysis of the effect of SNPs in the pig TERT gene on the structural and functional characteristics of the enzyme to develop new genetic markers of productivity traits

BackgroundTelomerase reverse transcriptase (TERT) plays a crucial role in synthesizing telomeric repeats that safeguard chromosomes from damage and fusion, thereby maintaining genome stability. Mutations in the TERT gene can lead to a deviation in gene expression, impaired enzyme activity, and, as a result, abnormal telomere shortening. Genetic markers of productivity traits in livestock can be developed based on the TERT gene polymorphism for use in marker-associated selection (MAS). In this study, a bioinformatic-based approach is proposed to evaluate the effect of missense single-nucleotide polymorphisms (SNPs) in the pig TERT gene on enzyme function and structure, with the prospect of developing genetic markers.ResultsA comparative analysis of the coding and amino acid sequences of the pig TERT was performed with corresponding sequences of other species. The distribution of polymorphisms in the pig TERT gene, with respect to the enzyme’s structural-functional domains, was established. A three-dimensional model of the pig TERT structure was obtained through homological modeling. The potential impact of each of the 23 missense SNPs in the pig TERT gene on telomerase function and stability was assessed using predictive bioinformatic tools utilizing data on the amino acid sequence and structure of pig TERT.ConclusionsAccording to bioinformatic analysis of 23 missense SNPs of the pig TERT gene, a predictive effect of rs789641834 (TEN domain), rs706045634 (TEN domain), rs325294961 (TRBD domain) and rs705602819 (RTD domain) on the structural and functional parameters of the enzyme was established. These SNPs hold the potential to serve as genetic markers of productivity traits. Therefore, the possibility of their application in MAS should be further evaluated in associative analysis studies.

In Silico Prediction and Molecular Docking of SNPs in NRP1 Gene Associated with SARS-COV-2.

Neuropilin-1 (NRP1) which is a main transmembrane cell surface receptor acts as a host cell mediator resulting in increasing the SARS-Cov-2 infectivity and also plays a role in neuronal development, angiogenesis and axonal outgrowth. The goal of this study is to estimate the impact of single nucleotide polymorphisms (SNPs) in the NRP1 gene on the function, structure and stabilization of protein as well as on the miRNA-mRNA binding regions using bioinformatical tools. It is also aimed to investigate the changes caused by SNPs in NRP1 on interactions with drug molecule and spike protein. The missense type of SNPs was analyzed using SIFT, PolyPhen-2, SNAP2, PROVEAN, Mutation Assessor, SNPs&GO, PhD-SNP, I-Mutant 3.0, MUpro, STRING, Project HOPE, ConSurf, and PolymiRTS. Docking analyses were conducted by AutoDock Vina program. As a result, a total of 733 missense SNPs were determined within the NRP1 gene and nine SNPs were specified as damaging to the protein. The modelling results showed that wild and mutant type amino acids had some different properties such as size, charge, and hydrophobicity. Additionally, their three-dimensional structures of protein were utilized for confirmation of these differences. After evaluating the results, nine polymorphisms rs141633354, rs142121081, rs145954532, rs200028992, rs200660300, rs369312020, rs370117610, rs370551432, rs370641686 were determined to be damaging on the structure and function of NRP1 protein and located in conserved regions. The results of molecular docking showed that the binding affinity values are nearly the same for wild-type and mutant structures support that the mutations carried out are not in the focus of the binding site, therefore the ligand does not affect the binding energy. It is expected that the results will be useful for future studies.