Characterization of single-nucleotide polymorphisms in coding regions of human genes

Genetic susceptibility of Saudi Population to Hepatitis B Virus (HBV) infection and the predicted functional consequences.. [DOI: 10.1101/2025.03.16.25323998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Chronic Hepatitis B virus (HBV) infection poses a global public health challenge, for which an effective cure remains elusive. A substantial amount of data has shown that single nucleotide polymorphisms (SNPs) within host genes can affect the regulation and expression of proteins, thereby influencing the susceptibility to HBV infection as well as disease progression and response to treatment. HBV-related SNPs have been identified in the population of Saudi Arabia, however, there is a lack of in-depth characterization of the translational and functional impact of these SNPs. This article aims to analyze the SNPs significantly associated with HBV-associated complications in the Saudi population, predict their functional impact using bioinformatic tools and propose future projections for HBV research in Saudi Arabia. The findings of these genetic studies are likely to pave the way for developing more effective preventive and therapeutic interventions by personalizing the management of HBV infection.

Computational Insight in the Identification of Non-Synonymous Single-Nucleotide Polymorphism Affecting the Structure and Function of Interleukin-4

BACKGROUND

IL4 is a versatile cytokine essentially known for differentiation, proliferation and cell death in cells. Its dysregulation has been found to be associated with the development of inflammatory disorders.

OBJECTIVE

The goal of the current investigation is to identify and select non-synonymous single-nucleotide polymorphisms (nsSNPs) in the IL-4 gene by employing computational methods which may have a potential functional impact on the occurrence of disease.

METHOD AND RESULT

Six different nsSNPs were predicted to be deleterious based on the consensus of different algorithms: SIFT, Polyphen2 (Humdiv and HumVar), PredictSNP and SNP&GO. I-mutant and MuPro assessment revealed a decrease in the stability of these mutants except K150M. Modelling was then carried out to build the wild type along with its mutants, followed by superimposition of the wild type with mutants to evaluate the RMSD value, which lies between 0.26 and 0.34. Simulation results of mutant models, along with wild type, showed that four of the mutants (N113Y, A118G, R109W and K150M) deviated most and were unstable. A118G showed a significant deviation from the wild type, while V53A and C123R were stable.

CONCLUSION

The finding establishes the evidence that the identified six nsSNPs of IL-4 can be the new entrant presenting their candidature for genetic testing.

TP53 mutations and MDM2 polymorphisms in breast and ovarian cancers: amelioration by drugs and natural compounds

Globally, breast and ovarian cancers are major health concerns in women and account for significantly high cancer-related mortality rates. Dysregulations and mutations in genes like TP53, BRCA1/2, KRAS and PTEN increase susceptibility towards cancer. Here, we discuss the impact of mutations in the key regulatory gene, TP53 and polymorphisms in its negative regulator MDM2 which are reported to accelerate cancer progression. Missense mutations, null mutations, transversions, transitions, and point mutations occurring in the TP53 gene can cause an increase in metastatic activity. This review discusses mutations occurring in exon regions of TP53, polymorphisms in MDM2 and their interaction with large ribosomal subunit protein (RPL) leading to cancer development. We also highlight the potential of small molecules e.g. p53 activators like XI-011, Tenovin-1, and Nutlin-3a for the treatment of breast and ovarian cancers. The therapeutic efficacy of natural compounds in amelioration of these two types of cancers is also discussed.

TGF-β1 promoter functional gene polymorphism -509 C/T in the maternal susceptibility to recurrent pregnancy loss in South Indian women

Transforming growth factor beta 1 (TGF-β1) is an anti-inflammatory pleiotropic cytokine that regulates implantation and adhesion of trophoblasts to the extracellular matrix. It regulates the balance of Th1/Th2 cytokines and the generation of anti-inflammatory peripheral regulatory T cells (FOXP3 + Tregs), which is necessary for a healthy pregnancy. Single nucleotide polymorphisms (SNP) affecting TGF-β1 production/function may predispose to pregnancy loss. The aim of this study is to evaluate the association between the TGF-β1 -509C/T polymorphism, its serum concentrations, and recurrent pregnancy loss. The study comprised 150 RPL cases and 150 healthy controls for genotyping TGF-β1 -509C/T polymorphism using the Amplification Refractory Mutation System-Polymerase Chain Reaction (ARMS-PCR). Serum concentrations of TGF-β1 protein were estimated by enzyme-linked immunosorbent assay. From our study, women with CT genotype exhibited a protective role against RPL [OR (95 % CI) = 0.48(0.30-0.76), p = 0.002], while women with TT genotype had a significantly higher risk among RPL patients and exhibited twofold increased risk [OR (95 % CI) = 2.34(1.37-4.01), p = 0.002]. Observation of patient's follow-up data revealed a significant relation with CT genotype of unfavorable pregnancy outcome (CT vs. CC + TT, OR 2.46, 95 % C.I: 1.11-5.43, p = 0.039). Further, variant allele T was significantly elevated in women with unfavorable pregnancy compared with favorable pregnancy outcome, indicating considerable association of T allele in unfavorable pregnancy outcome (T vs. C, OR: 2.68, 95 % C.I: 1.52-4.74, p = <0.001). Serum concentrations of TGF-β1 have shown significant variation between patients and controls, as well as among RPL patients with favorable and unfavorable pregnancy outcome in correspondence to each genotype CC, CT, and TT (p < 0.05). Furthermore, genotype-dependent variation was observed within both the patient and control groups; however, this variation was not observed among RPL women with favorable and unfavorable pregnancy outcome. Our investigation revealed a significant influence of TGF-β1C-509 T polymorphism on RPL risk in South Indian women.

Pathogenic single nucleotide polymorphisms in RhoA gene: Insights into structural and functional impacts on RhoA-PLD1 interaction through molecular dynamics simulation

Molecular switches serve as key regulators of biological systems by acting as one of the crucial driving forces in the initiation of signal transduction pathway cascades. The Ras homolog gene family member A (RhoA) is one of the molecular switches that binds with GTP in order to cycle between an active GTP-bound state and an inactive GDP-bound state. Any aberrance in control over this circuit, particularly due to any perturbation in switching, leads to the development of different pathogenicity. Consequently, the single nucleotide polymorphisms (SNPs) within the RhoA gene, especially deleterious genetic variations, are crucial to study to forecast structural alteration and their functional impacts in light of disease onset. In this comprehensive study, we employed a range of computational tools to screen the deleterious SNPs of RhoA from 207 nonsynonymous SNPs (nsSNPs). By utilizing 7 distinct tools for further analysis, 8 common deleterious SNPs were sorted, among them 5 nsSNPs (V9G, G17E, E40K, A61T, F171L) were found to be in the highly conserved regions, with E40K and A61T at G2 and G3 motif of the GTP-binding domain respectively, indicating potential perturbation in GTP/GDP binding ability of the protein. RhoA-GDP complex interacts with the enzyme phospholipase, specifically PLD1, to regulate different cellular activities. PLD1 is also a crucial regulator of thrombosis and cancer. In that line of focus, our initial structural analysis of Y66H, A61T, G17E, I86N, and I151T mutations of RhoA revealed remarkable decreased hydrophobicity from which we further filtered out G17E and I86N which may have potential impact on the RhoA-GDP-PLD1 complex. Intriguingly, the comparative 250 ns (ns) molecular dynamics (MD) simulation of these two mutated complexes revealed overall structural instability and altered interaction patterns. Therefore, further investigation into these deleterious mutations with in vitro and in vivo studies could lead to the identification of potential biomarkers in terms of different pathogenesis and could also be utilized in personalized therapeutic targets in the long run.

Unlocking the Door for Precision Medicine in Rare Conditions: Structural and Functional Consequences of Missense ACVR1 Variants

Rare diseases and conditions have thus far received relatively less attention in the field of precision/personalized medicine than common chronic diseases. There is a dire need for orphan drug discovery and therapeutics in ways that are informed by the precision/personalized medicine scholarship. Moreover, people with rare conditions, when considered collectively across diseases worldwide, impact many communities. In this overarching context, Activin A Receptor Type 1 (ACVR1) is a transmembrane kinase from the transforming growth factor-β superfamily and plays a critical role in modulating the bone morphogenetic protein signaling. Missense variants of the ACVR1 gene result in modifications in structure and function and, by extension, abnormalities and have been predominantly linked with two rare conditions: fibrodysplasia ossificans progressiva and diffuse intrinsic pontine glioma. We report here an extensive bioinformatic analyses assessing the pool of 50,951 variants and forecast seven highly destabilizing mutations (R206H, G356D, R258S, G328W, G328E, R375P, and R202I) that can significantly alter the structure and function of the native protein. Protein-protein interaction and ConSurf analyses revealed the crucial interactions and localization of highly deleterious mutations in highly conserved domains that may impact the binding and functioning of the protein. cBioPortal, CanSAR Black, and existing literature affirmed the association of these destabilizing mutations with posterior fossa ependymoma, uterine corpus carcinoma, and pediatric brain cancer. The current findings suggest these deleterious nonsynonymous single nucleotide polymorphisms as potential candidates for future functional annotations and validations associated with rare conditions, further aiding the development of precision medicine in rare diseases.

Quantifying allele-specific CRISPR editing activity with CRISPECTOR2.0

Off-target effects present a significant impediment to the safe and efficient use of CRISPR-Cas genome editing. Since off-target activity is influenced by the genomic sequence, the presence of sequence variants leads to varying on- and off-target profiles among different alleles or individuals. However, a reliable tool that quantifies genome editing activity in an allelic context is not available. Here, we introduce CRISPECTOR2.0, an extended version of our previously published software tool CRISPECTOR, with an allele-specific editing activity quantification option. CRISPECTOR2.0 enables reference-free, allele-aware, precise quantification of on- and off-target activity, by using de novo sample-specific single nucleotide variant (SNV) detection and statistical-based allele-calling algorithms. We demonstrate CRISPECTOR2.0 efficacy in analyzing samples containing multiple alleles and quantifying allele-specific editing activity, using data from diverse cell types, including primary human cells, plants, and an original extensive human cell line database. We identified instances where an SNV induced changes in the protospacer adjacent motif sequence, resulting in allele-specific editing. Intriguingly, differential allelic editing was also observed in regions carrying distal SNVs, hinting at the involvement of additional epigenetic factors. Our findings highlight the importance of allele-specific editing measurement as a milestone in the adaptation of efficient, accurate, and safe personalized genome editing.

Prediction of Deleterious Single Amino Acid Polymorphisms with a Consensus Holdout Sampler

Background

Single Amino Acid Polymorphisms (SAPs) or nonsynonymous Single Nucleotide Variants (nsSNVs) are the most common genetic variations. They result from missense mutations where a single base pair substitution changes the genetic code in such a way that the triplet of bases (codon) at a given position is coding a different amino acid. Since genetic mutations sometimes cause genetic diseases, it is important to comprehend and foresee which variations are harmful and which ones are neutral (not causing changes in the phenotype). This can be posed as a classification problem.

Methods

Computational methods using machine intelligence are gradually replacing repetitive and exceedingly overpriced mutagenic tests. By and large, uneven quality, deficiencies, and irregularities of nsSNVs datasets debase the convenience of artificial intelligence-based methods. Subsequently, strong and more exact approaches are needed to address these problems. In the present work paper, we show a consensus classifier built on the holdout sampler, which appears strong and precise and outflanks all other popular methods.

Results

We produced 100 holdouts to test the structures and diverse classification variables of diverse classifiers during the training phase. The finest performing holdouts were chosen to develop a consensus classifier and tested using a k-fold (1 ≤ k ≤5) cross-validation method. We also examined which protein properties have the biggest impact on the precise prediction of the effects of nsSNVs.

Conclusion

Our Consensus Holdout Sampler outflanks other popular algorithms, and gives excellent results, highly accurate with low standard deviation. The advantage of our method emerges from using a tree of holdouts, where diverse LM/AI-based programs are sampled in diverse ways.

Screening and analysis of single nucleotide polymorphism in the 3'-UTR microRNA target regions and its implications for lung tumorigenesis

Aim: The study aims to identify high-impact single nucleotide polymorphisms (SNPs) in miRNA target sites of genes associated with lung cancer.Materials & methods: Lung cancer genes were obtained from Uniprot KB. miRNA target site SNPs were mined from MirSNP, miRdSNP and TargetScan. SNPs were shortlisted based on binding impact, minor allele frequency and conservation. Gene expression was analyzed in genes with high-impact SNPs in healthy versus lung cancer tissue. Additionally, enrichment, pathway and network analyzes were performed.Results: 19 high-impact SNPs were identified in miRNA target sites of lung cancer-associated genes. These SNPs affect miRNA binding and gene expression. The genes are involved in key cancer related pathways.Conclusion: The identified high-impact miRNA target site SNPs and associated genes provide a starting point for case-control studies in lung cancer patients in different populations.

Recent advances in enzyme-free and enzyme-mediated single-nucleotide variation assay in vitro

Single-nucleotide variants (SNVs) are the most common type variation of sequence alterations at a specific location in the genome, thus involving significant clinical and biological information. The assay of SNVs has engaged great awareness, because many genome-wide association studies demonstrated that SNVs are highly associated with serious human diseases. Moreover, the investigation of SNV expression levels in single cells are capable of visualizing genetic information and revealing the complexity and heterogeneity of single-nucleotide mutation-related diseases. Thus, developing SNV assay approaches in vitro, particularly in single cells, is becoming increasingly in demand. In this review, we summarized recent progress in the enzyme-free and enzyme-mediated strategies enabling SNV assay transition from sensing interface to the test tube and single cells, which will potentially delve deeper into the knowledge of SNV functions and disease associations, as well as discovering new pathways to diagnose and treat diseases based on individual genetic profiles. The leap of SNV assay achievements will motivate observation and measurement genetic variations in single cells, even within living organisms, delve into the knowledge of SNV functions and disease associations, as well as open up entirely new avenues in the diagnosis and treatment of diseases based on individual genetic profiles.

Polymorphisms of CYP7A1 and HADHB Genes and Their Effects on Milk Production Traits in Chinese Holstein Cows

Our preliminary research proposed the cytochrome P450 family 7 subfamily A member 1 (CYP7A1) and hydroxyacyl-coenzyme A dehydrogenase trifunctional multienzyme complex beta subunit (HADHB) genes as candidates for association with milk-production traits in dairy cattle because of their differential expression across different lactation stages in the liver tissues of Chinese Holstein cows and their potential roles in lipid metabolism. Hence, we identified single-nucleotide polymorphisms (SNPs) of the CYP7A1 and HADHB genes and validated their genetic effects on milk-production traits in a Chinese Holstein population with the goal of providing valuable genetic markers for genomic selection (GS) in dairy cattle, This study identified five SNPs, 14:g.24676921A>G, 14:g.24676224G>A, 14:g.24675708G>T, 14:g.24665961C>T, and 14:g.24664026A>G, in the CYP7A1 gene and three SNPs, 11:g.73256269T>C, 11:g.73256227A>C, and 11:g.73242290C>T, in HADHB. The single-SNP association analysis revealed significant associations (p value ≤ 0.0461) between the eight SNPs of CYP7A1 and HADHB genes and 305-day milk, fat and protein yields. Additionally, using Haploview 4.2, we found that the five SNPs of CYP7A1 formed two haplotype blocks and that the two SNPs of HADHB formed one haplotype block; notably, all three haplotype blocks were also significantly associated with milk, fat and protein yields (p value ≤ 0.0315). Further prediction of transcription factor binding sites (TFBSs) based on Jaspar software (version 2023) showed that the 14:g.24676921A>G, 14:g.24675708G>T, 11:g.73256269T>C, and 11:g.73256227A>C SNPs could alter the 5' terminal TFBS of the CYP7A1 and HADHB genes. The 14:g.24665961C>T SNP caused changes in the structural stability of the mRNA for the CYP7A1 gene. These alterations have the potential to influence gene expression and, consequently, the phenotype associated with milk-production traits. In summary, we have confirmed the genetic effects of CYP7A1 and HADHB genes on milk-production traits in dairy cattle and identified potential functional mutations that we suggest could be used for GS of dairy cattle and in-depth mechanistic studies of animals.

Potential new cancer biomarkers revealed by quantum chemistry associated with bioinformatics in the study of selectin polymorphisms

Understanding the complex mechanisms involved in diseases caused by or related to important genetic variants has led to the development of clinically useful biomarkers. However, the increasing number of described variants makes it difficult to identify variants worthy of investigation, and poses challenges to their validation. We combined publicly available datasets and open source robust bioinformatics tools with molecular quantum chemistry methods to investigate the involvement of selectins, important molecules in the cell adhesion process that play a fundamental role in the cancer metastasis process. We applied this strategy to investigate single nucleotide variants (SNPs) in the intronic and UTR regions and missense SNPs with amino acid changes in the SELL, SELP, SELE, and SELPLG genes. We then focused on thyroid cancer, seeking these SNPs potential to identify biomarkers for susceptibility, diagnosis, prognosis, and therapeutic targets. We demonstrated that SELL gene polymorphisms rs2229569, rs1131498, rs4987360, rs4987301 and rs2205849; SELE gene polymorphisms rs1534904 and rs5368; rs3917777, rs2205894 and rs2205893 of SELP gene; and rs7138370, rs7300972 and rs2228315 variants of SELPLG gene may produce important alterations in the DNA structure and consequent changes in the morphology and function of the corresponding proteins. In conclusion, we developed a strategy that may save valuable time and resources in future investigations, as we were able to provide a solid foundation for the selection of selectin gene variants that may become important biomarkers and deserve further investigation in cancer patients. Large-scale clinical studies in different ethnic populations and laboratory experiments are needed to validate our results.

Detection of Transversions and Transitions in HBG2 Cis-Elements Associated with Sickle Cell Allele in Ghanaians

Short tandem repeats located 5' prime to the β-globin gene, have been observed to be in linkage disequilibrium with the HbS allele, and thought to affect the severity of sickle cell disease. Here, we report on new mutants within the HBG2 region that may impact sickle cell disease. To determine the cis-acting elements microsatellites, indels and single nucleotide polymorphisms (SNPs), within the HBG2 region by sequencing, in subjects with sickle cell disease. The case-control study was located at the Center for Clinical Genetics, Sickle cell unit, Korle-Bu Teaching Hospital. A questionnaire was used for demographic data and clinical information. Hematological profile (red blood cell, white blood cell, platelet, hemoglobin and mean corpuscular volume) were assessed in 83 subjects. A set of 45 samples comprising amplified DNA on the HBG2 gene from HbSS (22), HbSC (17) and 6 controls (HbAA) were sequenced. Differences in the microsatellite region between sickle cell disease (SCD) (HbSS and HbSC) genotypes and control subjects were identified by counting and assessed by Chi-square analysis. Red blood cells, hematocrit, platelets, white blood cells and hemoglobin indices differed in genotypic groups. HbSS subjects were affirmed to have severer hemolytic anemia than HbSC subjects. Two indels (T1824 and C905) were seen in both SS and SC genotypes. Two peculiar SNPs: G:T1860 (transition) and A:G1872 transversions were found within the HBG2 gene that were significantly associated with the HbSS genotype (Fisher's exact test, p = 0.006) and HbS allele respectively (Fisher's exact test, p = 0.006). Cis-acting elements in HbSS and HbSC were different and may contribute to the phenotype seen in the disease state.

The Emerging Role of Toll-Like Receptor-Mediated Neuroinflammatory Signals in Psychiatric Disorders and Acquired Epilepsy

The new and evolving paradigms of psychiatric disorders pathogenesis are deeply inclined toward chronic inflammation that leads to disturbances in the neuronal networks of patients. A strong association has been established between the inflammation and neurobiology of depression which is mediated by different toll-like receptors (TLRs). TLRs and associated signalling pathways are identified as key immune regulators to stress and infections in neurobiology. They are a special class of transmembrane proteins, which are one of the broadly studied members of the Pattern Recognition Patterns family. This review focuses on summarizing the important findings on the role of TLRs associated with psychotic disorders and acquired epilepsy. This review also shows the promising potential of TLRs in immune response mediated through antidepressant therapies and TLRs polymorphism associated with various psychotic disorders. Moreover, this also sheds light on future directions to further target TLRs as a therapeutic approach for psychiatric disorders.

Computational identification and analysis of deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene: a structural and functional impact

Cytochrome P450 oxidoreductase (POR) protein is essential for steroidogenesis, and POR gene mutations are frequently associated with P450 Oxidoreductase Deficiency (PORD), a disorder of hormone production. To our knowledge, no previous attempt has been made to identify and analyze the deleterious/pathogenic non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene through an extensive computational approach. Computational algorithms and tools were employed to identify, characterize, and validate the pathogenic SNPs associated with certain diseases. To begin with, all the high-confidence SNPs were collected, and their structural and functional impacts on the protein structures were explored. The results of various in silico analyses affirm that the A287P and R457H variants of POR could destabilize the interactions between the amino acids and the hydrogen bond networks, resulting in functional deviations of POR. The literature study further confirms that the pathogenic mutations (A287P and R457H) are associated with the onset of PORD. Molecular dynamics simulations (MDS) and essential dynamics (ED) studies characterized the structural consequences of prioritized deleterious mutations, representing the structural destabilization that might disrupt POR biological function. The identified deleterious mutations at the cofactor's binding domains might interfere with the essential interactions between the protein and cofactors, thus inhibiting POR catalytic activity. The consolidated insights from the computational analyses can be used to predict potential deleterious mutants and understand the disease's pathological basis and the molecular mechanism of drug metabolism for the application of personalized medication. HIGHLIGHTSNADPH cytochrome P450 oxidoreductase (POR) mutations are associated with a broad spectrum of human diseasesIdentified and analyzed the most deleterious nsSNPs of POR through the sequence and structure-based prediction toolsInvestigated the structural and functional impacts of the most significant mutations (A287P and R457H) associated with PORDMolecular dynamics and PCA-based FEL analysis were utilized to probe the mutation-induced structural alterations in PORCommunicated by Ramaswamy H. Sarma.

Unveiling clinically significant PPARγ mutations for thiazolidinedione treatment responsiveness through atomistic simulations

In Type 2 diabetes, increased insulin sensitivity is induced by thiazolidinedione activation of the peroxisome proliferator-activated receptor gamma (PPARγ). Recent data indicate a relationship between SNPs in PPARγ and poor drug response. Therefore, understanding the pathogenic consequences of mutations in PPARγ-mediated protein-drug interactions will be prima-facie for establishing personalized medicine. The PPARG gene has 197 missense SNPs, 22 of which were determined to be both deleterious and destabilizing, employing in silico approaches. Molecular docking analysis suggested that the mutation influenced the binding energy of at least seven of the variants. The mutant R316H was identified as the most damaging and deleterious from the observed results. For a better understanding of the dynamic variation upon mutation at the atomic level, molecular dynamics simulations of the wild-type and R316H mutant PPARγ structure were performed. The analysis indicates that the mutation increased protein structural compactness while decreasing flexibility. The reduced dynamics in the mutant structure was further validated by principal component analysis. This mechanistic evaluation of the PPARγ protein variants provides insight into the relationship between genetic variation and interindividual variability of drug responsiveness and will facilitate the future studies for the development of tailored treatment regime for precision medicine.

In Silico Evaluation of Coding and Non-Coding nsSNPs in the Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure, and Function

The thrombopoietin receptor (MPL) gene is a critical regulator of hematopoiesis, and any alterations in its structure or function can result in a range of hematological disorders. Non-synonymous single nucleotide polymorphisms (nsSNPs) in MPL have the potential to disrupt normal protein function, prompting our investigation into the most deleterious MPL SNPs and the associated structural changes affecting protein-protein interactions. We employed a comprehensive suite of bioinformatics tools, including PredictSNP, InterPro, ConSurf, I-Mutant2.0, MUpro, Musitedeep, Project HOPE, STRING, RegulomeDB, Mutpred2, CScape, and CScape Somatic, to analyze 635 nsSNPs within the MPL gene. Among the analyzed nsSNPs, PredictSNP identified 28 as significantly pathogenic, revealing three critical functional domains within MPL. Ten of these nsSNPs exhibited high conservation scores, indicating potential effects on protein structure and function, while 14 were found to compromise MPL protein stability. Although the most harmful nsSNPs did not directly impact post-translational modification sites, 13 had the capacity to substantially alter the protein's physicochemical properties. Some mutations posed a risk to vital protein-protein interactions crucial for hematological functions, and three non-coding region nsSNPs displayed significant regulatory potential with potential implications for hematopoiesis. Furthermore, 13 out of 21 nsSNPs evaluated were classified as high-risk pathogenic variants by Mutpred2. Notably, amino acid alterations such as C291S, T293N, D295G, and W435C, while impactful on protein stability and function, were deemed non-oncogenic "passenger" mutations. Our study underscores the substantial impact of missense nsSNPs on MPL protein structure and function. Given MPL's central role in hematopoiesis, these mutations can significantly disrupt hematological processes, potentially leading to a variety of disorders. The identified high-risk pathogenic nsSNPs may hold promise as potential biomarkers or therapeutic targets for hematological diseases. This research lays the foundation for future investigations into the MPL gene's role in the realm of hematological health and diseases.

A Neanderthal/Denisovan GLI3 variant contributes to anatomical variations in mice

Changes in genomic structures underlie phenotypic diversification in organisms. Amino acid-changing mutations affect pleiotropic functions of proteins, although little is known about how mutated proteins are adapted in existing developmental programs. Here we investigate the biological effects of a variant of the GLI3 transcription factor (GLI3R1537C) carried in Neanderthals and Denisovans, which are extinct hominins close to modern humans. R1537C does not compromise protein stability or GLI3 activator-dependent transcriptional activities. In contrast, R1537C affects the regulation of downstream target genes associated with developmental processes. Furthermore, genome-edited mice carrying the Neanderthal/Denisovan GLI3 mutation exhibited various alterations in skeletal morphology. Our data suggest that an extinct hominin-type GLI3 contributes to species-specific anatomical variations, which were tolerated by relaxed constraint in developmental programs during human evolution.

Enzymatic synthesis and nanopore sequencing of 12-letter supernumerary DNA

The 4-letter DNA alphabet (A, T, G, C) as found in Nature is an elegant, yet non-exhaustive solution to the problem of storage, transfer, and evolution of biological information. Here, we report on strategies for both writing and reading DNA with expanded alphabets composed of up to 12 letters (A, T, G, C, B, S, P, Z, X, K, J, V). For writing, we devise an enzymatic strategy for inserting a singular, orthogonal xenonucleic acid (XNA) base pair into standard DNA sequences using 2'-deoxy-xenonucleoside triphosphates as substrates. Integrating this strategy with combinatorial oligos generated on a chip, we construct libraries containing single XNA bases for parameterizing kmer basecalling models for commercially available nanopore sequencing. These elementary steps are combined to synthesize and sequence DNA containing 12 letters - the upper limit of what is accessible within the electroneutral, canonical base pairing framework. By introducing low-barrier synthesis and sequencing strategies, this work overcomes previous obstacles paving the way for making expanded alphabets widely accessible.

Impact of highly deleterious non-synonymous polymorphisms on GRIN2A protein's structure and function

GRIN2A is a gene that encodes NMDA receptors found in the central nervous system and plays a pivotal role in excitatory synaptic transmission, plasticity and excitotoxicity in the mammalian central nervous system. Changes in this gene have been associated with a spectrum of neurodevelopmental disorders such as epilepsy. Previous studies on GRIN2A suggest that non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein's structure and function. To gain a better understanding of the impact of potentially deleterious variants of GRIN2A, a range of bioinformatics tools were employed in this study. Out of 1320 nsSNPs retrieved from the NCBI database, initially 16 were predicted as deleterious by 9 tools. Further assessment of their domain association, conservation profile, homology models, interatomic interaction, and Molecular Dynamic Simulation revealed that the variant I463S is likely to be the most deleterious for the structure and function of the protein. Despite the limitations of computational algorithms, our analyses have provided insights that can be a valuable resource for further in vitro and in vivo research on GRIN2A-associated diseases.

Functional characterization of human genomic variation linked to polygenic diseases

The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.

Evaluation of SNPs from human IGFBP6 associated with gene expression: an in-silico study

In the bloodstream and in local tissues, most IGF molecules are associated with the one of the members of the IGF-binding protein (IGFBP) family, which are divided into six distinct types. IGF-binding proteins have been demonstrated to either decrease or increase the growth-promoting effects of IGFs on cell culture, by extending their half-life. They alter how IGFs interact with the receptors on their cell surfaces. IGFBP6 gene is associated with disease in-situ carcinoma. Upregulation or downregulation of IGFBP6 gene has been implicated in different types of cancer in humans. Nonsynonymous SNPs changes have the potential to affect the protein's structure and function. Potential functional SNPs can be assessed before undertaking studies in larger populations because validation of these functional SNPs can be a crucial problem. So, in this in-silico investigation, we used a variety of sequence- and structure-based bioinformatics methods to separate the potential nsSNPs of the IGFBP6 gene from the neutral ones. In total of 216 nsSNPs, 5 were found to have potential effects using 5 prediction tools. From which, 2 nsSNPs (R128G and R164H) were selected as potentially damaging due to their presence in highly conserved region and ability to decrease protein stability. Among these 2 nsSNPs, only R164H was found to be associated with Uterine corpus endometrial carcinoma. It was also found that both, upregulation or downregulation of IGFBP6 gene can lead to the different types of cancers. The findings of the present study will certainly be valuable in the future large population-based investigations as well as drug discovery, especially developing personalized medicine.Communicated by Ramaswamy H. Sarma.

Polymorphisms in VDR, CYP27B1, CYP2R1, GC and CYP24A1 Genes as Biomarkers of Survival in Non-Small Cell Lung Cancer: A Systematic Review

The objective of this systematic review was to provide a compilation of all the literature available on the association between single-nucleotide polymorphisms (SNPs) in the genes involved in the metabolic pathway of vitamin D and overall survival (OS) and progression-free survival (PFS) in patients with non-small cell lung cancer (NSCLC). This systematic review was conducted in accordance with the PRISMA guidelines. It included all the literature published up to 1 November 2022 and was carried out in four databases (Medline [PubMed], Scopus, Web of Science, and Embase), using the PICO strategy, with relevant keywords related to the objective. The quality of the studies included was evaluated with an assessment tool derived from the Strengthening the Reporting of Genetic Association Studies (STREGA) statement. Six studies were included in this systematic review. Our findings showed that the BsmI (rs1544410), Cdx-2 (rs11568820), FokI (rs2228570), ApaI (rs7975232), TaqI (rs731236), rs4646536, rs6068816, rs7041, and rs10741657 SNPs in the genes that play a part in vitamin D synthesis (CYP2R1, CYP27B1), transport (GC), and metabolism (CYP24A1), as well as in the vitamin D receptor (VDR), are associated with OS and/or PFS in patients with NSCLC. The SNPs in VDR have been the most extensively analyzed. This systematic review summed up the available evidence concerning the association between 13 SNPs in the main genes involved in the vitamin D metabolic pathway and prognosis in NSCLC. It revealed that SNPs in the VDR, CYP27B1, CYP24A1, GC, and CYP2R1 genes could have an impact on survival in this disease. These findings suggest the identification of prognostic biomarkers in NSCLC patients. However, evidence remains sparse for each of the polymorphisms examined, so these findings should be treated with caution.

High risk genetic variants of human insulin receptor substrate 1(IRS1) infer structural instability and functional interference

Insulin receptor substrate 1(IRS1) is a signaling adapter protein encoded by the IRS1 gene. This protein delivers signals from insulin and insulin-like growth factor-1(IGF-1) receptors to the phosphatidylinositol 3-kinases (P13K)/protein kinase B (Akt) and Extracellular signal-regulated kinases (Erk) - Mitogen-activated protein (MAP) kinase pathways, which regulate particular cellular processes. Mutations in this gene have been linked to type 2 diabetes mellitus, a heightened risk of insulin resistance, and an increased likelihood of developing a number of different malignancies. The structure and function of IRS1 could be severely compromised as a result of single nucleotide polymorphism (SNP) type genetic variants. In this study, we focused on identification of the most harmful non-synonymous SNPs (nsSNPs) of the IRS1 gene as well as prediction of their structural and functional consequences. Six different algorithms made the initial prediction that 59 of the 1142 IRS1 nsSNPs would have a negative impact on the protein structure. In-depth evaluations detected 26 nsSNPs located inside the functional domains of IRS1. Following that, 16 nsSNPs were identified as more harmful based on conservation profile, hydrophobic interaction, surface accessibility, homology modelling, and inter-atomic interactions. Following an in-depth analysis of protein stability, M249T (rs373826433), I223T (rs1939785175) and V204G (rs1574667052) were identified as three most deleterious SNPs and were subjected to molecular dynamics simulation for further insights. These findings will help us understand the implications for disease susceptibility, cancer progression, and the efficacy of therapeutic development against IRS1 gene mutants.Communicated by Ramaswamy H. Sarma.

A protein enzyme-free strategy for fluorescence detection of single nucleotide polymorphisms using asymmetric MNAzymes

To establish protein enzyme-free and simple approach for sensitive detection of single nucleotide polymorphisms (SNPs), the nucleic acid amplification reactions were developed to reduce the dependence on protein enzymes (polymerase, endonuclease, ligase). These methods, while enabling highly amplified analysis for the short sequences, cannot be generalized to long genomic sequences. Herein, we develop a protein enzyme-free and general SNPs assay based on asymmetric MNAzyme probes. The multi-arm probe (MNAzyme-9_M-13) with two asymmetric recognition arms, containing a short (9 nt) and a long (13 nt) arm, is designed to detect EGFR T790 M mutation (MT). Owing to the excellent selectivity of short recognition arm, MNAzyme-9_M-13 probe can efficiently avoid interferences from wild-type target (WT) and various single-base mutations. Through a one-pot mixing, MNAzyme-9_M-13 probe enables the sensitive detection of MT, without protein enzyme or multi-step operation. The calculated detection limit for MT is 0.59 nM and 0.83%. Moreover, this asymmetric MNAzyme strategy can be applied for SNPs detection in long genomic sequences as well as short microRNAs (miRNAs) only by changing the low-cost unlabeled recognition arms. Therefore, along with simple operation, low-cost, protein enzyme-free and strong versatility, our asymmetric MNAzyme strategy provides a novel solution for SNPs detection and genes analysis.

Molecular dynamics simulations and bioinformatics' analysis of deleterious missense single nucleotide polymorphisms in Glyoxalase-1 gene

Glyoxalase-1 (Glo-1) is a key member of the Glyoxalase system, the primary line of defense against dicarbonyl stress which, in tandem, with reduced levels of expression or activity of Glyoxalase-1 enzyme, has been implicated in various human diseases like type 2 diabetes mellitus (T2DM) and its vascular complications. The association of Glo-1 single nucleotide polymorphisms with genetic susceptibility to T2DM and its vascular complications is yet to be explored. Therefore, in this study, we have employed a computational approach to identify the most damaging missense or nonsynonymous SNPs (nsSNPs) in Glo-1 gene. Initially, we characterized missense SNPs that are damaging to the structural and functional integrity of Glo-1 using various bioinformatic tools. These tools included SIFT, PolyPhen-2, SNAP, PANTHER, PROVEAN, PhD-SNP, SNPs&GO, I-Mutant, MUpro and MutPred2. One of these missense SNPs (rs1038747749; corresponding to amino acid change Arginine to Glutamine at position 38) was found to be highly conserved in evolution and is an important part of the enzyme's active site, glutathione binding site, as well as the dimeric interface based on the results obtained from ConSurf and NCBI Conserved Domain Search tools. Project HOPE reported that this mutation replaces a positively charged polar amino acid (Arginine) with a small, neutrally charged amino acid (Glutamine). Comparative modelling of wildtype and mutant (R38Q) Glo-1 proteins was performed in the run up to molecular dynamics simulation analysis which showed that rs1038747749 adversely impacts Glo-1 protein's stability, rigidity, compactness, hydrogen bonds/interactions as demonstrated by the results of various parameters computed during the analysis.Communicated by Ramaswamy H. Sarma.

Soybean (Glycine max) isoflavone conjugate hydrolysing β-glucosidase (GmICHG): a promising candidate for soy isoflavone bioavailability enhancement

Isoflavones are a sub-class of phenylpropanoids having health benefits and a role in plant defence and plant-rhizobium interaction. Isoflavone conjugate hydrolysis is crucial in determining the bioactivity and bioavailability of these isoflavones inside the human body. This study examined the different characteristics of soy isoflavone conjugate hydrolysing β-glucosidase (GmICHG) to explore its potential for isoflavone bioavailability enhancement. We cloned the full-length GmICHG cDNA from the soybean seedling roots from the DS2706 variety of 1545 bp. The bioinformatics analysis revealed secretion and glycosylation of this protein. The evolutionary relatedness of this gene to the other glucosidases interestingly had related sequences outside the Papilionaceae family. The protein had a pI above neutral of 7.62 and optimum pH of 6.0, indicating its activity in the extracellular acidic environment. The GmICHG gene expression at three stages of seedling roots gradually rose to 1.84 ± 0.54 fold and a concomitant increase in the β-glucosidase activity. The enzyme kinetics of GmICHG showed a K m of 6.38 mM and V max of 2.82 U/ml and an optimum temperature of 40 °C. These hint that soy ICHG can be a potent candidate for the isoflavone bioavailability enhancement by hydrolysing their β-glycosidic bonds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03427-5.

Single nucleotide polymorphisms rs7799039 and rs2167270 in leptin gene and elevated serum levels of adiponectin predispose Iranians to Behçet's disease

BACKGROUND

Behçet's Disease (BD) is a chronic autoimmune disease with unknown etiology. Adipokines due to their roles in the regulation of immune responses might be important in the induction and progression of BD.

SUBJECTS AND METHODS

This case-control study included 340 patients with BD and 310 healthy controls. Single nucleotide polymorphisms (SNPs) in adiponectin (rs266729 and rs1501299) and leptin (rs7799039 and rs2167270) genes were determined using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and serum levels of adipokines were measured using enzyme-linked immunosorbent assay (ELISA).

RESULTS

A higher frequency of leptin rs7799039 GG, AG, and AG +GG genotypes and G allele was revealed in patients. Besides, patients had more leptin rs2167270 AG and AG +AA genotypes and A allele. Furthermore, rs2167270 AA genotype and A allele were more frequently seen in total and female patients who had genital aphthous. Patients had significantly more serum levels of adiponectin while those with genital aphthous had significantly more leptin levels. No significant association was observed between genotypes and alleles of adiponectin SNPs and BD.

CONCLUSION

Our findings indicated that leptin gene polymorphisms might predispose Iranian individuals to BD. Besides, elevated serum levels of adiponectin might facilitate BD pathogenesis.

BDNF-related mutations in major depressive disorder: a systematic review

OBJECTIVE

A better understanding of the genetic, molecular and cellular mechanisms of brain-derived neurotrophic factor (BDNF) and its association with neuroplasticity could play a pivotal role in finding future therapeutic targets for novel drugs in major depressive disorder (MDD). Because there are conflicting results regarding the exact role of BDNF polymorphisms in MDD still, we set out to systematically review the current evidence regarding BDNF-related mutations in MDD.

METHODS

We conducted a keyword-guided search of the PubMed and Embase databases, using 'BDNF' or 'brain-derived neurotrophic factor' and 'major depressive disorder' and 'single-nucleotide polymorphism'. We included all publications in line with our exclusion and inclusion criteria that focused on BDNF-related mutations in the context of MDD.

RESULTS

Our search yielded 427 records in total. After screening and application of our eligibility criteria, 71 studies were included in final analysis. According to present overall scientific data, there is a possibly major pathophysiological role for BDNF neurotrophic systems to play in MDD. However, on the one hand, the synthesis of evidence makes clear that likely no overall association of BDNF-related mutations with MDD exists. On the other hand, it can be appreciated that solidifying evidence emerged on specific significant sub-conditions and stratifications based on various demographic, clinico-phenotypical and neuromorphological variables.

CONCLUSIONS

Further research should elucidate specific BDNF-MDD associations based on demographic, clinico-phenotypical and neuromorphological variables. Furthermore, biomarker approaches, specifically combinatory ones, involving BDNF should be further investigated.

Effects of the pathological E200K mutation on human prion protein: A computational screening and molecular dynamics approach

The human prion protein gene (PRNP) is mapped to the short arm of chromosome 20 (20pter-12). Prion disease is associated with mutations in the prion protein-encoding gene sequence. Earlier studies found that the mutation G127V in the PRNP increases protein stability. In contrast, the mutation E200K, which has the highest mutation rate in the prion protein, causes Creutzfeldt-Jakob disease (CJD) in humans and induces protein aggregation. We aimed to identify the structural mechanisms of E200k and G127V mutations causing CJD. We used a variety of bioinformatic algorithms, including SIFT, PolyPhen, I-Mutant, PhD-SNP, and SNP& GO, to predict the association of the E200K mutation with prion disease. MD simulation is performed, and graphs for root mean square deviation, root mean square fluctuation, radius of gyration, DSSP, principal component analysis, porcupine, and free energy landscape are generated to confirm and prove the stability of the wild-type and mutant protein structures. The protein is analyzed for aggregation, and the results indicate more fluctuations in the protein structure during the simulation owing to the E200K mutation; however, the G127V mutation makes the protein structure stable against aggregation during the simulation.

Association of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) Gene Polymorphisms with Type 2 Diabetes among Malay Ethnics

Background  Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder, and the underlying causes remain unknown and have not been fully elucidated. Several candidate genes have been associated with T2DM in various populations with conflicting results. The variations found in glucokinase ( GCK ), glucokinase regulatory protein ( GCKR ), and glucose-6-phosphatase 2 ( G6PC2 ) genes were not well studied, particularly among Asians. Aims  The main objective of this study was to determine the candidate genetic polymorphisms of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) genes in T2DM among Malay ethnics. Methods  In this candidate gene association study, a total of 180 T2DM subjects and 180 control subjects were recruited to determine the genotypes using polymerase chain reaction-restriction fragment length polymorphism and Taqman probe assay methods. Genotype and allele frequencies in case and control samples were compared using the chi-squared test to determine a significant difference. Results  The body mass index, fasting blood glucose, hemoglobin A1c, systolic and diastolic blood pressure, and total cholesterol were significantly different ( p  < 0.05) between T2DM and control subjects. The genotypic and allelic frequencies of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) gene polymorphisms were significantly different between T2DM and controls ( p  < 0.05). Conclusion  Hence, rs1799884 of GCK gene and rs780094 of GCKR gene and rs560887 of the G6PC2 gene are possible genetic biomarkers in T2DM development among Malay ethnics in Malaysia.

Pathogenicity of PKCγ Genetic Variants-Possible Function as a Non-Invasive Diagnostic Biomarker in Ovarian Cancer

Ovarian cancer has the highest mortality rate among gynecologic malignancies, owing to its misdiagnosis or late diagnosis. Identification of its genetic determinants could improve disease outcomes. Conventional Protein Kinase C-γ (PKCγ) dysregulation is reported in several cancers. Similarly, its variant rs1331262028 is also reported to have an association with hepatocellular carcinoma. Therefore, the aim of the present study was to analyze the variant rs1331262028 association with ovarian cancer and to determine its impact on PKCγ's protein interactions. Association of variation was determined through genotyping PCR (cohort size:100). Protein-protein docking and molecular dynamic simulation were carried out to study the variant impact of PKCγ interactions. The study outcome indicated the positive association of variant rs1331262028 with ovarian cancer and its clinicopathological features. Molecular dynamics simulation depicted the potential influence of variation on PKCγ molecular signaling. Hence, this study provided the foundations for assessing variant rs1331262028 as a potential prognostic marker for ovarian cancer. Through further validation, it can be applied at the clinical level.

Genetic Val66Met BDNF Variant Increases Hyperphagia on Fat-rich Diets in Mice

High prevalence of obesity is attributable in part to consumption of highly palatable, fat-rich foods. However, the mechanism controlling dietary fat intake is largely unknown. In this study we investigated the role of brain-derived neurotrophic factor (BDNF) in the control of dietary fat intake in a mouse model that mimics the common human Val-to-Met (Val66Met) polymorphism that impairs BDNF release via the regulated secretory pathway. BdnfMet/Met mice gained weight much faster than wild-type (WT) mice and developed severe obesity due to marked hyperphagia when they were fed HFD. Hyperphagia in these mice worsened when the fat content in their diet was increased. Conversely, mice lacking leptin exhibited similar hyperphagia on chow and HFD. When 2 diets were provided simultaneously, WT and BdnfMet/Met mice showed a comparable preference for the more palatable diet rich in either fat or sucrose, indicating that increased hyperphagia on fat-rich diets in BdnfMet/Met mice is not due to enhanced hedonic drive. In support of this interpretation, WT and BdnfMet/Met mice increased calorie intake to a similar extent during the first day after chow was switched to HFD; however, WT mice decreased HFD intake faster than BdnfMet/Met mice in subsequent days. Furthermore, we found that refeeding after fasting or nocturnal feeding with HFD activated TrkB more strongly than with chow in the hypothalamus of WT mice, whereas TrkB activation under these 2 conditions was greatly attenuated in BdnfMet/Met mice. These results indicate that satiety factors generated during HFD feeding induce BDNF release to suppress excess dietary fat intake.

Deleterious single nucleotide polymorphisms (SNPs) of human IFNAR2 gene facilitate COVID-19 severity in patients: a comprehensive in silico approach

In humans, the dimeric receptor complex IFNAR2-IFNAR1 accelerates cellular response triggered by type I interferon (IFN) family proteins in response to viral infection including Coronavirus infection. Studies have revealed the association of the IFNAR2 gene with severe illness in Coronavirus infection and indicated the association of genomic variants, i.e. single nucleotide polymorphisms (SNPs). However, comprehensive analysis of SNPs of the IFNAR2 gene has not been performed in both coding and non-coding region to find the causes of loss of function of IFNAR2 in COVID-19 patients. In this study, we have characterized coding SNPs (nsSNPs) of IFNAR2 gene using different bioinformatics tools and identified deleterious SNPs. We found 9 nsSNPs as pathogenic and disease-causing along with a decrease in protein stability. We employed molecular docking analysis that showed 5 nsSNPs to decrease binding affinity to IFN. Later, MD simulations showed that P136R mutant may destabilize crucial binding with the IFN molecule in response to COVID-19. Thus, P136R is likely to have a high impact on disrupting the structure of the IFNAR2 protein. GTEx portal analysis predicted 14 sQTLs and 5 eQTLs SNPs in lung tissues hampering the post-transcriptional modification (splicing) and altering the expression of the IFNAR2 gene. sQTLs and eQTLs SNPs potentially explain the reduced IFNAR2 production leading to severe diseases. These mutants in the coding and non-coding region of the IFNAR2 gene can help to recognize severe illness due to COVID 19 and consequently assist to develop an effective drug against the infection.Communicated by Ramaswamy H. Sarma.

Capturing nucleic acid variants with precision using CRISPR diagnostics

CRISPR/Cas systems have the ability to precisely target nucleotide sequences and enable their rapid identification and modification. While nucleotide modification has enabled the therapeutic correction of diseases, the process of identifying the target DNA or RNA has greatly expanded the field of molecular diagnostics in recent times. CRISPR-based DNA/RNA detection through programmable nucleic acid binding or cleavage has been demonstrated for a large number of pathogenic and non-pathogenic targets. Combining CRISPR detection with nucleic acid amplification and a terminal signal readout step allowed the development of numerous rapid and robust nucleic acid platforms. Wherever the Cas effector can faithfully distinguish nucleobase variants in the target, the platform can also be extended for sequencing-free rapid variant detection. Some initial PAM disruption-based SNV detection reports were limited to finding or integrating mutated/mismatched nucleotides within the PAM sequences. In this review, we try to summarize the developments made in CRISPR diagnostics (CRISPRDx) to date emphasizing CRISPR-based SNV detection. We also discuss the applications where such diagnostic modalities can be put to use, covering various fields of clinical research, SNV screens, disease genotyping, primary surveillance during microbial infections, agriculture, food safety, and industrial biotechnology. The ease of rapid design and implementation of such multiplexable assays can potentially expand the applications of CRISPRDx in the domain of affinity-based target sequencing, with immense possibilities for low-cost, quick, and widespread usage. In the end, in combination with proximity assays and a suicidal gene approach, CRISPR-based in vivo SNV detection and cancer cell targeting can be formulated as personalized gene therapy.

The effects of missense OPN3 mutations in melanocytic lesions on protein structure and light-sensitive function

Opsin 3 (OPN3), a member of the light-sensitive, retinal-dependent opsin family, is widely expressed in a variety of human tissues and plays a multitude of light-dependent and light-independent roles. We recently identified five missense variants of OPN3, including p. I51T, p. V134A, p. V183I, p. M256I and p. C331Y, in human melanocytic tumours. However, it remains unclear how these OPN3 variants affect OPN3 protein structure and function. Herein, we conducted structural and functional studies of these variant proteins in OPN3 by molecular docking and molecular dynamics simulations. Moreover, we performed in vitro fluorescence calcium imaging to assess the functional properties of five single-nucleotide variant (SNV) proteins using a site-directed mutagenesis method. Notably, the p. I51T variant was not able to effectively dock with 11-cis-retinal. Additionally, in vitro, the p. I51T SNVs failed to induce any detectable changes in intracellular Ca²⁺ concentration at room temperature. Taken together, these results reveal that five SNVs in the OPN3 gene have deleterious effects on protein structure and function, suggesting that these mutations, especially the p. I51T variant, significantly disrupt the canonical function of the OPN3 protein. Our findings provide new insight into the role of OPN3 variants in the loss of protein function.

Visualizing Single-Nucleotide Variations in a Nuclear Genome Using Colocalization of Dual-Engineered CRISPR Probes

Direct visualization of single-nucleotide variation (SNV) in single cells is of great importance for understanding the spatial organization of genomes and their relationship with cell phenotypes. Herein, we developed a new strategy for visualizing SNVs in a nuclear genome using colocalization of dual-engineered CRISPR probes (CoDEC). By engineering the structure of sgRNA, we incorporated a hairpin in the spacer domain for improving SNV recognition specificity and a loop in the nonfunctional domain for localized signal amplification. Using guide probe-based colocalization strategy, we can successfully distinguish on-target true positive signals from the off-target false positives with high accuracy. Comparing with a proximity ligation-based assay (CasPLA), the probe colocalization strategy extended applicable target gene sites (the distance between two designed probes can be extended to around 200nt) and improved detection efficiency. This newly developed method provides a facile way for studying in situ information on SNVs in individual cells for basic research and clinical applications with single-molecule and single-nucleotide resolutions.

A new test suggests hundreds of amino acid polymorphisms in humans are subject to balancing selection

The role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here, we introduce a new test, based on the McDonald–Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and provide some evidence that hundreds of nonsynonymous polymorphisms are subject to balancing selection.

Genomic medicine on the frontier of precision medicine

Genomic medicine has created a great deal of hope since the completion of the Human Genome Project (HGP). Genomic medicine promises disease prevention and early diagnosis in the context of precision medicine. Precision medicine as a scientific discipline has introduced as an evolution in medicine. The rapid growth of high-development technologies permits the assessment of biological systems. Study of the integrated profiles of omics, such as genome, transcriptome, proteome and other omics information lead to significant advances in personalized and precision medicine. In the context of precision medicine, pharmacogenomics can play an important role in order to discriminate responders and non-responders to medications and avoiding toxicity and achieving the optimum dose. So precision medicine in accordance with genomic medicine will transform medicine from conventional evidence-based medicine in the diagnosis and treatment towards precision based-medicine. In this review, we have summarized the related issues for genomic medicine and precision medicine.

Association between miR-146a rs2910164, miR-196a2 rs11614913, and miR-499 rs3746444 polymorphisms and the risk of esophageal carcinoma: A case-control study

MicroRNAs (miRNAs) are a group of small, non‐coding, and endogenous RNAs that regulate gene expression and over 50% of them are located at cancer‐related genomic regions or fragile sites. According to previous studies there is significant association of miRNA single nucleotide polymorphisms (SNPs) with tumorigenesis (e.g., esophageal cancer, hepatocellular cancer, gastric cancer, bladder cancer, breast cancer, lung cancer, and colon cancer), however, the conclusions have been inconsistent. To investigate the relationship between miR‐146a rs2910164 C > G, miR‐196a2 rs11614913 T > C, and miR‐499 rs3746444 A > G polymorphisms and the susceptibility to esophageal squamous cell cancer (ESCC) in the Chinese Han nationality, we recruited 829 cases and 1522 controls in our study. In this case–control study, our results suggest that the rs3746444 GG genotype increased ESCC risk [homozygote model: adjusted odds ratio (OR), 2.26; 95% CI, 1.33–3.83; p = 0.003, recessive model: adjusted OR, 2.34; 95% CI, 1.38–3.96; p = 0.002], which remained consistent after Bonferroni correction. There was no association of rs11614913 and rs2910164 polymorphisms with ESCC. After adjusting by age, sex, smoking, and drinking status and body mass index (BMI), the multiple logistic analysis suggested that rs11614913 T → C variation reduced ESCC susceptibility in females and in the ≥63 years old subgroups, while rs2910164 C → G variation increased ESCC risk in both two BMI subgroups.

Brain-derived neurotrophic factor in Alzheimer's disease and its pharmaceutical potential

Synaptic abnormalities are a cardinal feature of Alzheimer's disease (AD) that are known to arise as the disease progresses. A growing body of evidence suggests that pathological alterations to neuronal circuits and synapses may provide a mechanistic link between amyloid β (Aβ) and tau pathology and thus may serve as an obligatory relay of the cognitive impairment in AD. Brain-derived neurotrophic factors (BDNFs) play an important role in maintaining synaptic plasticity in learning and memory. Considering AD as a synaptic disorder, BDNF has attracted increasing attention as a potential diagnostic biomarker and a therapeutical molecule for AD. Although depletion of BDNF has been linked with Aβ accumulation, tau phosphorylation, neuroinflammation and neuronal apoptosis, the exact mechanisms underlying the effect of impaired BDNF signaling on AD are still unknown. Here, we present an overview of how BDNF genomic structure is connected to factors that regulate BDNF signaling. We then discuss the role of BDNF in AD and the potential of BDNF-targeting therapeutics for AD.

In-silico analysis unravels the structural and functional consequences of non-synonymous SNPs in the human IL-10 gene

Background

Interleukin-10 (IL-10) is an anti-inflammatory cytokine that affects different immune cells. It is also associated with the stimulation of the T and B cells for the production of antibodies. Several genetic polymorphisms in the IL-10 gene have been reported to cause or aggravate certain diseases like inflammatory bowel disease, rheumatoid arthritis, systemic sclerosis, asthma, etc. However, the disease susceptibility and abnormal function of the mutated IL-10 variants remain obscure.

Results

In this study, we used seven bioinformatics tools (SIFT, PROVEAN, PMut, PANTHER, PolyPhen-2, PHD-SNP, and SNPs&GO) to predict the disease susceptible non-synonymous SNPs (nsSNPs) of IL-10. Nine nsSNPs of IL-10 were predicted to be potentially deleterious: R42G, R45Q, F48L, E72G, M95T, A98D, R125S, Y155C, and I168T. Except two, all of the putative deleterious mutations are found in the highly conserved region of IL-10 protein structure, thus affecting the protein's stability. The 3-D structure of mutant proteins was modeled by project HOPE, and the protein–protein interactions were assessed with STRING. The predicted nsSNPs: R42Q, R45Q, F48L, E72G, and I168T are situated in the binding site region of the IL-10R1 receptor. Disruption of binding affinity with its receptor leads to deregulation of the JAK-STAT pathway and results in enhanced inflammation that imbalance in cellular signaling. Finally, Kaplan–Meier Plotter analysis displayed that deregulation of IL-10 expression affects gastric and ovarian cancer patients' survival rate. Thus, IL-10 could be useful as a potential prognostic marker gene for some cancers.

Conclusion

This study has determined the deleterious nsSNPs of IL-10 that might contribute to the malfunction of IL-10 protein and ultimately lead to the IL-10 associated diseases.

Fitness Effects of Mutations: An Assessment of PROVEAN Predictions Using Mutation Accumulation Data

Predicting fitness in natural populations is a major challenge in biology. It may be possible to leverage fast-accumulating genomic data sets to infer the fitness effects of mutant alleles, allowing evolutionary questions to be addressed in any organism. In this paper, we investigate the utility of one such tool, called PROVEAN. This program compares a query sequence with existing data to provide an alignment-based score for any protein variant, with scores categorized as neutral or deleterious based on a pre-set threshold. PROVEAN has been used widely in evolutionary studies, for example, to estimate mutation load in natural populations, but has not been formally tested as a predictor of aggregate mutational effects on fitness. Using three large published data sets on the genome sequences of laboratory mutation accumulation lines, we assessed how well PROVEAN predicted the actual fitness patterns observed, relative to other metrics. In most cases, we find that a simple count of the total number of mutant proteins is a better predictor of fitness than the number of proteins with variants scored as deleterious by PROVEAN. We also find that the sum of all mutant protein scores explains variation in fitness better than the number of mutant proteins in one of the data sets. We discuss the implications of these results for studies of populations in the wild.

In-Silico and In-Vitro Analysis of Human SOS1 Protein Causing Noonan Syndrome - A Novel Approach to Explore the Molecular Pathways

Aims

Perform in-silico analysis of human SOS1 mutations to elucidate their pathogenic role in Noonan syndrome (NS).

Background

NS is an autosomal dominant genetic disorder caused by single nucleotide mutation in PTPN11, SOS1, RAF1, and KRAS genes. NS is thought to affect approximately 1 in 1000. NS patients suffer different pathogenic effects depending on the mutations they carry. Analysis of the mutations would be a promising predictor in identifying the pathogenic effect of NS.

Methods

We performed computational analysis of the SOS1 gene to identify the pathogenic nonsynonymous single nucleotide polymorphisms (nsSNPs) th a t cause NS. SOS1 variants were retrieved from the SNP database (dbSNP) and analyzed by in-silico tools I-Mutant, iPTREESTAB, and MutPred to elucidate their structural and functional characteristics.

Results

We found that 11 nsSNPs of SOS1 that were linked to NS. 3D modeling of the wild-type and the 11 nsSNPs of SOS1 showed that SOS1 interacts with cardiac proteins GATA4, TNNT2, and ACTN2. We also found that GRB2 and HRAS act as intermediate molecules between SOS1 and cardiac proteins. Our in-silico analysis findings were further validated using induced cardiomyocytes (iCMCs) derived from NS patients carrying SOS1 gene variant c.1654A>G (NSiCMCs) and compared to control human skin fibroblast-derived iCMCs (C-iCMCs). Our in vitro data confirmed that the SOS1, GRB2 and HRAS gene expressions as well as the activated ERK protein, were significantly decreased in NS-iCMCs when compared to C-iCMCs.

Conclusion

This is the first in-silico and in vitro study demonstrating that 11 nsSNPs of SOS1 play deleterious pathogenic roles in causing NS.

A comprehensive in silico investigation into the nsSNPs of Drd2 gene predicts significant functional consequences in dopamine signaling and pharmacotherapy

DRD2 is a neuronal cell surface protein involved in brain development and function. Variations in the Drd2 gene have clinical significance since DRD2 is a pharmacotherapeutic target for treating psychiatric disorders like ADHD and schizophrenia. Despite numerous studies on the disease association of single nucleotide polymorphisms (SNPs) in the intronic regions, investigation into the coding regions is surprisingly limited. In this study, we aimed at identifying potential functionally and pharmaco-therapeutically deleterious non-synonymous SNPs of Drd2. A wide array of bioinformatics tools was used to evaluate the impact of nsSNPs on protein structure and functionality. Out of 260 nsSNPs retrieved from the dbSNP database, initially 9 were predicted as deleterious by 15 tools. Upon further assessment of their domain association, conservation profile, homology models and inter-atomic interaction, the mutant F389V was considered as the most impactful. In-depth analysis of F389V through Molecular Docking and Dynamics Simulation revealed a decline in affinity for its native agonist dopamine and an increase in affinity for the antipsychotic drug risperidone. Remarkable alterations in binding interactions and stability of the protein-ligand complex in simulated physiological conditions were also noted. These findings will improve our understanding of the consequence of nsSNPs in disease-susceptibility and therapeutic efficacy.

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools

Single nucleotide polymorphisms (SNPs) help to understand the phenotypic variations in humans. Genome-wide association studies (GWAS) have identified SNPs located in the tumor protein 63 (TP63) locus to be associated with the genetic susceptibility of cancers. However, there is a lack of in-depth characterization of the structural and functional impacts of the SNPs located at the TP63 gene. The current study was designed for the comprehensive characterization of the coding and non-coding SNPs in the human TP63 gene for their functional and structural significance. The functional and structural effects of the SNPs were investigated using a wide variety of computational tools and approaches, including molecular dynamics (MD) simulation. The deleterious impact of eight nonsynonymous SNPs (nsSNPs) affecting protein stability, structure, and functions was measured by using 13 bioinformatics tools. These eight nsSNPs are in highly conserved positions in protein and were predicted to decrease protein stability and have a deleterious impact on the TP63 protein function. Molecular docking analysis showed five nsSNPs to reduce the binding affinity of TP63 protein to DNA with significant results for three SNPs (R319H, G349E, and C347F). Further, MD simulations revealed the possible disruption of TP63 and DNA binding, hampering the essential protein function. PolymiRTS study found five non-coding SNPs in miRNA binding sites, and the GTEx portal recognized five eQTLs SNPs in single tissue of the lung, heart (LV), and cerebral hemisphere (brain). Characterized nsSNPs and non-coding SNPs will help researchers to focus on TP63 gene loci and ascertain their association with certain diseases.

A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene

PLCG1 gene is responsible for many T-cell lymphoma subtypes, including peripheral T-cell lymphoma (PTCL), angioimmunoblastic T-cell lymphoma (AITL), cutaneous T-cell lymphoma (CTCL), adult T-cell leukemia/lymphoma along with other diseases. Missense mutations of this gene have already been found in patients of CTCL and AITL. The non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein structure as well as its functions. In this study, probable deleterious and disease-related nsSNPs in PLCG1 were identified using SIFT, PROVEAN, PolyPhen-2, PhD-SNP, Pmut, and SNPS&GO tools. Further, their effect on protein stability was checked along with conservation and solvent accessibility analysis by I-mutant 2.0, MUpro, Consurf, and Netsurf 2.0 server. Some SNPs were finalized for structural analysis with PyMol and BIOVIA discovery studio visualizer. Out of the 16 nsSNPs which were found to be deleterious, ten nsSNPs had an effect on protein stability, and six mutations (L411P, R355C, G493D, R1158H, A401V and L455F) were predicted to be highly conserved. Among the six highly conserved mutations, four nsSNPs (R355C, A401V, L411P and L455F) were part of the catalytic domain. L411P, L455F and G493D made significant structural change in the protein structure. Two mutations-Y210C and R1158H had post-translational modification. In the 5' and 3' untranslated region, three SNPs, rs139043247, rs543804707, and rs62621919 showed possible miRNA target sites and DNA binding sites. This in silico analysis has provided a structured dataset of PLCG1 gene for further in vivo researches. With the limitation of computational study, it can still prove to be an asset for the identification and treatment of multiple diseases associated with the target gene.

Missense mutations involvement in COX-2 structure, and protein-substrate binding affinity: in-silico study

Cyclooxygenase-2 (COX-2) is an inducible inflammatory enzyme, which produces prostanoids from arachidonic acid. COX-2 overexpression and over-activity can cause inflammation, tumorigenesis, and angiogenesis. Prostanoids are the main reason for the inflammation, and increase of mitogenesis by COX-2. So, any change such as mutations that can lead to COX-2 over-activity could ignite the tumor situations with increase of prostanoids production is one of its ways. The aim of this study was to check the effect of 166 missense mutations of COX-2 on protein features that can affect the COX-2 activity such as protein stability, fluctuation, 2D structure, and its binding affinity with the substrate by in silico methods, network modeling, and docking calculations, by which 44 of them shown to be deleterious. Among them, the S124I and S474F mutations can increase the stability of the protein. 11.36% of deleterious nsSNPs were part of the substrate-binding region among which the M508T, H337R, and V511G have the potential to affect the protein by 2D structure alteration. V511G can improve binding affinity and H337R showed a small decrease in the deformation overall energy that can represent a decrease in the stability of COX-2. Also, L517S showed a significant decrease in the binding power of COX-2/substrate but based on the anisotropic network modeling this mutation has a dual effect on COX-2 stability. These nsSNPs/mutations have the potential causing an increase or decrease of tumorigenesis because increasing of COX-2 stability and its binding affinity can lead to altering its activity.

Evolutionary and functional lessons from human-specific amino acid substitution matrices

Human genetic variation in coding regions is fundamental to the study of protein structure and function. Most methods for interpreting missense variants consider substitution measures derived from homologous proteins across different species. In this study, we introduce human-specific amino acid (AA) substitution matrices that are based on genetic variations in the modern human population. We analyzed the frequencies of >4.8M single nucleotide variants (SNVs) at codon and AA resolution and compiled human-centric substitution matrices that are fundamentally different from classic cross-species matrices (e.g. BLOSUM, PAM). Our matrices are asymmetric, with some AA replacements showing significant directional preference. Moreover, these AA matrices are only partly predicted by nucleotide substitution rates. We further test the utility of our matrices in exposing functional signals of experimentally-validated protein annotations. A significant reduction in AA transition frequencies was observed across nine post-translational modification (PTM) types and four ion-binding sites. Our results propose a purifying selection signal in the human proteome across a diverse set of functional protein annotations and provide an empirical baseline for interpreting human genetic variation in coding regions.