PolymiRTS Database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological pathways

Genomic instability in ovarian cancer: Through the lens of single nucleotide polymorphisms

Ovarian cancer (OC) is the deadliest gynecological malignancy among all female reproductive cancers. It is characterized by high mortality rate and poor prognosis. Genomic instability caused by mutations, single nucleotide polymorphisms (SNPs), copy number variations (CNVs), microsatellite instability (MSI), and chromosomal instability (CIN) are associated with OC predisposition. SNPs, which are highly prevalent in the general population, show a greater relative risk contribution, particularly in sporadic cancers. Understanding OC etiology in terms of genetic basis can increase the use of molecular diagnostics and provide promising approaches for designing novel treatment modalities. This will help deliver personalized medicine to OC patients, which may soon be within reach. Given the pivotal impact of SNPs in cancers, the primary emphasis of this review is to shed light on their prevalence in key caretaker genes that closely monitor genomic integrity, viz., DNA damage response, repair, cell cycle checkpoints, telomerase maintenance, and apoptosis and their clinical implications in OC. We highlight the current challenges faced in different SNP-based studies. Various computational methods and bioinformatic tools employed to predict the functional impact of SNPs have also been comprehensively reviewed concerning OC research. Overall, this review identifies that variants in the DDR and HRR pathways are the most studied, implying their critical role in the disease. Conversely, variants in other pathways, such as NHEJ, MMR, cell cycle, apoptosis, telomere maintenance, and PARP genes, have been explored the least.

Mitigating off-target effects of small RNAs: conventional approaches, network theory and artificial intelligence

Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages over small-molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases. In preclinical research, synthetic small RNAs play an essential role in the investigation of physiological and pathological pathways as silencers of specific genes, facilitating discovery and validation of drug targets in different conditions. Off-target effects of small RNAs, however, could make it difficult to interpret experimental results in the preclinical phase and may contribute to adverse events of small RNA therapeutics. Out of the two major types of off-target effects we focused on the hybridization-dependent, especially on the miRNA-like off-target effects. Our main aim was to discuss several approaches, including sequence design, chemical modifications and target prediction, to reduce hybridization-dependent off-target effects that should be considered even at the early development phase of small RNA therapy. Because there is no standard way of predicting hybridization-dependent off-target effects, this review provides an overview of all major state-of-the-art computational methods and proposes new approaches, such as the possible inclusion of network theory and artificial intelligence (AI) in the prediction workflows. Case studies and a concise survey of experimental methods for validating in silico predictions are also presented. These methods could contribute to interpret experimental results, to minimize off-target effects and hopefully to avoid off-target-related adverse events of small RNA therapeutics.

A comprehensive in silico investigation into the pathogenic SNPs in the RTEL1 gene and their biological consequences

The Regulator of Telomere Helicase 1 (RTEL1) gene encodes a critical DNA helicase intricately involved in the maintenance of telomeric structures and the preservation of genomic stability. Germline mutations in the RTEL1 gene have been clinically associated with Hoyeraal-Hreidarsson syndrome, a more severe version of Dyskeratosis Congenita. Although various research has sought to link RTEL1 mutations to specific disorders, no comprehensive investigation has yet been conducted on missense mutations. In this study, we attempted to investigate the functionally and structurally deleterious coding and non-coding SNPs of the RTEL1 gene using an in silico approach. Initially, out of 1392 nsSNPs, 43 nsSNPs were filtered out through ten web-based bioinformatics tools. With subsequent analysis using nine in silico tools, these 43 nsSNPs were further shortened to 11 most deleterious nsSNPs. Furthermore, analyses of mutated protein structures, evolutionary conservancy, surface accessibility, domains & PTM sites, cancer susceptibility, and interatomic interaction revealed the detrimental effect of these 11 nsSNPs on RTEL1 protein. An in-depth investigation through molecular docking with the DNA binding sequence demonstrated a striking change in the interaction pattern for F15L, M25V, and G706R mutant proteins, suggesting the more severe consequences of these mutations on protein structure and functionality. Among the non-coding variants, two had the highest likelihood of being regulatory variants, whereas one variant was predicted to affect the target region of a miRNA. Thus, this study lays the groundwork for extensive analysis of RTEL1 gene variants in the future, along with the advancement of precision medicine and other treatment modalities.

Polymorphism in the Hsa-miR-4274 seed region influences the expression of PEX5 and enhances radiotherapy resistance in colorectal cancer

Identifying biomarkers for predicting radiotherapy efficacy is crucial for optimizing personalized treatments. We previously reported that rs1553867776 in the miR-4274 seed region can predict survival in patients with rectal cancer receiving postoperative chemoradiation therapy. Hence, to investigate the molecular mechanism of the genetic variation and its impact on the radiosensitivity of colorectal cancer (CRC), in this study, bioinformatics analysis is combined with functional experiments to confirm peroxisomal biogenesis factor 5 (PEX5) as a direct target of miR-4274. The miR-4274 rs1553867776 variant influences the binding of miR-4274 and PEX5 mRNA, which subsequently regulates PEX5 protein expression. The interaction between PEX5 and Ku70 was verified by co-immunoprecipitation and immunofluorescence. A xenograft tumor model was established to validate the effects of miR-4274 and PEX5 on CRC progression and radiosensitivity in vivo. The overexpression of PEX5 enhances radiosensitivity by preventing Ku70 from entering the nucleus and reducing the repair of ionizing radiation (IR)-induced DNA damage by the Ku70/Ku80 complex in the nucleus. In addition, the enhanced expression of PEX5 is associated with increased IR-induced ferroptosis. Thus, targeting this mechanism might effectively increase the radiosensitivity of CRC. These findings offer novel insights into the mechanism of cancer radioresistance and have important implications for clinical radiotherapy.

An ontology-based knowledge graph for representing interactions involving RNA molecules

The "RNA world" represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient's biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public repositories, they are scattered across different databases and a centralized, uniform, and semantically consistent representation of the "RNA world" is still lacking. We propose RNA-KG, a knowledge graph (KG) encompassing biological knowledge about RNAs gathered from more than 60 public databases, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. To develop RNA-KG, we first identified, pre-processed, and characterized each data source; next, we built a meta-graph that provides an ontological description of the KG by representing all the bio-molecular entities and medical concepts of interest in this domain, as well as the types of interactions connecting them. Finally, we leveraged an instance-based semantically abstracted knowledge model to specify the ontological alignment according to which RNA-KG was generated. RNA-KG can be downloaded in different formats and also queried by a SPARQL endpoint. A thorough topological analysis of the resulting heterogeneous graph provides further insights into the characteristics of the "RNA world". RNA-KG can be both directly explored and visualized, and/or analyzed by applying computational methods to infer bio-medical knowledge from its heterogeneous nodes and edges. The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.

Exploring non-coding genetic variability in ACE2: Functional annotation and in vitro validation of regulatory variants

The surge in human whole-genome sequencing data has facilitated the study of non-coding region variations, yet understanding their biological significance remains a challenge. We used a computational workflow to assess the regulatory potential of non-coding variants, with a particular focus on the Angiotensin Converting Enzyme 2 (ACE2) gene. This gene is crucial in physiological processes and serves as the entry point for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 19 (COVID-19). In our analysis, using data from the gnomAD population database and functional annotation, we identified 17 significant Single Nucleotide Variants (SNVs) in ACE2, particularly in its enhancers, promoters, and 3' untranslated regions (UTRs). We found preliminary evidence supporting the regulatory impact of some of these variants on ACE2 expression. Our detailed examination of two SNVs, rs147718775 and rs140394675, in the ACE2 promoter revealed that these co-occurring SNVs, when mutated, significantly enhance promoter activity, suggesting a possible increase in specific ACE2 isoform expression. This method proves effective in identifying and interpreting impactful non-coding variants, aiding in further studies and enhancing understanding of molecular bases of monogenic and complex traits.

In Silico Identification of Dysregulated miRNAs Targeting KRAS Gene in Pancreatic Cancer

Pancreatic cancer (PC) is highly lethal, with KRAS mutations in up to 95% of cases. miRNAs inversely correlate with KRAS expression, indicating potential as biomarkers. This study identified miRNAs targeting KRAS and their impact on PC characteristics using in silico methods. dbDEMC identified dysregulated miRNAs in PC; TargetScan, miRDB, and PolymiRTS 3.0 identified miRNAs specific for the KRAS gene; and OncomiR evaluated the association of miRNAs with clinical characteristics and survival in PC. The correlation between miRNAs and KRAS was analysed using ENCORI/starBase. A total of 210 deregulated miRNAs were identified in PC (116 overexpressed and 94 underexpressed). In total, 16 of them were involved in the regulation of KRAS expression and 9 of these (hsa-miR-222-3p, hsa-miR-30a-5p, hsa-miR-30b-5p, hsa-miR-30e-5p, hsa-miR-377-3p, hsa-miR-495-3p, hsa-miR-654-3p, hsa-miR-877-5p and hsa-miR-885-5p) were associated with the clinical characteristics of the PC. Specifically, the overexpression of hsa-miR-30a-5p was associated with PC mortality, and hsa-miR-30b-5p, hsa-miR-377-3p, hsa-miR-495-3p, and hsa-miR-885-5p were associated with survival. Correlation analysis revealed that the expression of 10 miRNAs is correlated with KRAS expression. The dysregulated miRNAs identified in PC may regulate KRAS and some are associated with clinically relevant features, highlighting their potential as biomarkers and therapeutic targets in PC treatment. However, experimental validation is required for confirmation.

Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration

Non-coding RNAs are pivotal regulators of gene and protein expression, exerting crucial influences on diverse biological processes. Their dysregulation is frequently implicated in the onset and progression of diseases, notably cancer. A profound comprehension of the intricate mechanisms governing ncRNAs is imperative for devising innovative therapeutic interventions against these debilitating conditions. Significantly, nearly 80% of our genome comprises ncRNAs, underscoring their centrality in cellular processes. The elucidation of ncRNA functions is pivotal for grasping the complexities of gene regulation and its implications for human health. Modern genome sequencing techniques yield vast datasets, stored in specialized databases. To harness this wealth of information and to understand the crosstalk of non-coding RNAs, knowledge of available databases is required, and many new sophisticated computational tools have emerged. These tools play a pivotal role in the identification, prediction, and annotation of ncRNAs, thereby facilitating their experimental validation. This Review succinctly outlines the current understanding of ncRNAs, emphasizing their involvement in disease development. It also highlights the databases and tools instrumental in classifying, annotating, and evaluating ncRNAs. By extracting meaningful biological insights from seemingly "junk" data, these tools empower scientists to unravel the intricate roles of ncRNAs in shaping human health.

Computational exploration of SLC14A1 genetic variants through structure modeling, protein-ligand docking, and molecular dynamics simulation

The urea transporter UT-B1, encoded by the SLC14A1 gene, has been hypothesized to be a significant protein whose deficiency and dysfunction contribute to the pathogenesis of bladder cancer and many other diseases. Several studies reported the association of genetic alterations in the SLC14A1 (UT-B1) gene with bladder carcinogenesis, suggesting a need for thorough characterization of the UT-B1 protein's coding and non-coding variants. This study used various computational techniques to investigate the commonly occurring germ-line missense and non-coding SNPs (ncSNPs) of the SLC14A1 gene (UT-B1) for their structural, functional, and molecular implications for disease susceptibility and dysfunctionality. SLC14A1 missense variants, primarily identified from the ENSEMBL genome browser, were screened through twelve functionality prediction tools leading to two variants D280Y (predicted detrimental by maximum tools) and D280N (high global MAF) for rs1058396. Subsequently, the ConSurf and NetSurf tools revealed the D280 residue to be in a variable site and exposed on the protein surface. According to I-Mutant2.0 and MUpro, both variants are predicted to cause a significant effect on protein stability. Analysis of molecular docking anticipated these two variants to decrease the binding affinity of UT-B1 protein for the examined ligands to a significant extent. Molecular dynamics also disclosed the possible destabilization of the UT-B1 protein due to single nucleotide polymorphism compared to wild-type protein which may result in impaired protein function. Furthermore, several non-coding SNPs were estimated to affect transcription factor binding and regulation of SLC14A1 gene expression. Additionally, two ncSNPs were found to affect miRNA-based post-transcriptional regulation by creating new seed regions for miRNA binding. This comprehensive in-silico study of SLC14A1 gene variants may serve as a springboard for future large-scale investigations examining SLC14A1 polymorphisms.

The Search for and Functional Analysis of Genetic Variants in microRNA-Binding Sites using Massively Parallel Reporter Assay

A large-scale search for the genetic variants with a bias in the representation of alleles in transcriptome data (AE SNPs) and the binding sites in microRNA 3'-UTRs was performed and their functional significance was assessed using massively parallel reporter assay (MPRA). Of the 629,559 associated "SNP-gene" pairs (eQTLs) discovered in the human liver tissue according to the GTEx Analysis V8 data, 4394 polymorphic positions in the 3'-UTRs of the genes, which represent the eQTLs for these genes were selected. The TargetScanHuman 7.0 algorithm and PolymiRTS database were searched for the potential microRNA-binding sites. Of the predicted microRNA sites affected by eQTL-SNPs, we selected 51 sites with the best evidence of functionality according to Ago2-CLIP-seq, CLEAR-CLIP, and eCLIP-seq for RNA-binding proteins. For MPRA, a library of the plasmids carrying the main and alternative alleles for each AE SNP (in total, 102 constructs) was created. Allele-specific expression for 6 SNPs was detected by transfection of the HepG2 cell line with the constructed plasmid library and sequencing of target DNA and RNA sequences using the Illumina (MiSeq) platform.

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.

Comprehensive characterization of coding and non-coding single nucleotide polymorphisms of the Myoneurin (MYNN) gene using molecular dynamics simulation and docking approaches

Genome-wide association studies (GWAS) identified a coding single nucleotide polymorphism, MYNN rs10936599, at chromosome 3q. MYNN gene encodes myoneurin protein, which has been associated with several cancer pathogenesis and disease development processes. However, there needed to be a more detailed characterization of this polymorphism's (and other coding and non-coding polymorphisms) structural, functional, and molecular impact. The current study addressed this gap and analyzed different properties of rs10936599 and non-coding SNPs of MYNN via a thorough computational method. The variant, rs10936599, was predicted functionally deleterious by nine functionality prediction approaches, like SIFT, PolyPhen-2, and REVEL, etc. Following that, structural modifications were estimated through the HOPE server and Mutation3D. Moreover, the mutation was found in a conserved and active residue, according to ConSurf and CPORT. Further, the secondary structures were predicted, followed by tertiary structures, and there was a significant deviation between the native and variant models. Similarly, molecular simulation also showed considerable differences in the dynamic pattern of the wildtype and mutant structures. Molecular docking revealed that the variant binds with better docking scores with ligand NOTCH2. In addition to that, non-coding SNPs located at the MYNN locus were retrieved from the ENSEMBL database. These were found to disrupt the transcription factor binding regulatory regions; nonetheless, only two affect miRNA target sites. Again, eight non-coding variants were detected in the testes with normalized expression, whereas HaploReg v4.1 unveiled annotations for non-coding variants. In summary, in silico comprehensive characterization of coding and non-coding single nucleotide polymorphisms of MYNN gene will assist researchers to work on MYNN gene and establish their association with certain types of cancers.

Genetic variations in IKZF3, LET7-a2, and CDKN2B-AS1: Exploring associations with metabolic syndrome susceptibility and clinical manifestations

BACKGROUND AND AIM

Metabolic syndrome (MetS) increases the risk of atherosclerosis and diabetes, but there are no approved predictive markers. This study assessed the role of specific genetic variations in MetS susceptibility and their impact on clinical manifestations.

METHOD

In this study, a genotype-phenotype assessment was performed for IKZF3 (rs907091), microRNA-let-7a-2 (rs1143770), and lncRNA-CDKN2B-AS1 (rs1333045).

RESULTS

Analyses indicate that while rs907091 and rs1143770 may have potential associations with MetS susceptibility and an increased risk of atherosclerosis and diabetes, there is an observed trend suggesting that the rs1333045 CC genotype may be associated with a decreased risk of MetS. The genotypes and allele frequencies of rs1333045 were significantly different between studied groups (OR = 0.56, 95% CI 0.38-0.81, p = 0.002, and OR = 0.71, 95% CI 0.55-0.92, p = 0.008), with the CC genotype displaying increased levels of HDL. Furthermore, the rs907091 TT genotype was associated with increased triglyceride, cholesterol, and HOMA index in MetS patients. Subjects with the CC genotype for rs1143770 had higher HbA1c and BMI. In silico analyses illustrated that rs907091 C remarkably influences the secondary structure and the target site of a broad spectrum of microRNAs, especially hsa-miR-4497. Moreover, rs1333045 creates a binding site for seven different microRNAs.

CONCLUSION

Further studies on other populations may help confirm these SNPs as useful predictive markers in assessing the MetS risk.

Comparative Analysis of Published Database Predicting MicroRNA Binding in 3'UTR of mRNA in Diverse Species

BACKGROUND

Micro-RNAs are endogenous non-coding RNA moieties of 22-27 nucleotides that play a crucial role in the regulation of various biological processes and make them useful prognostic and diagnostic biomarkers. Discovery and experimental validation of miRNA is a laborious and time-consuming process. For early prediction, multiple bioinformatics databases are available for miRNA target prediction; however, their utility can confuse amateur researchers in selecting the most appropriate tools for their study.

OBJECTIVE

This descriptive review aimed to analyse the usability of the existing database based on the following criteria: accessibility, efficiency, interpretability, updatability, and flexibility for miRNA target prediction of 3'UTR of mRNA in diverse species so that the researchers can utilize the database most appropriate to their research.

METHODS

A systematic literature search was performed in PubMed, Google Scholar and Scopus databases up to November 2022. ≥10,000 articles found online, including ⁓130 miRNA tools, which contain various information on miRNA. Out of them, 31 databases that provide information on validated 3'UTR miRNAs target databases were included and analysed in this review.

RESULTS

These miRNA database tools are being used in varied areas of biological research to select the most suitable miRNA for their experimental validation. These databases, updated until the year 2021, consist of miRNA-related data from humans, animals, mice, plants, viruses etc. They contain 525-29806351 data entries, and information from most databases is freely available on the online platform.

CONCLUSION

Reviewed databases provide significant information, but not all information is accurate or up-to-date. Therefore, Diana-TarBase and miRWalk are the most comprehensive and up-to-date databases.

LDLR and PCSK9 3´UTR variants and their putative effects on microRNA molecular interactions in familial hypercholesterolemia: a computational approach

BACKGROUND

Familial hypercholesterolemia (FH) is caused by pathogenic variants in low-density lipoprotein (LDL) receptor (LDLR) or its associated genes, including apolipoprotein B (APOB), proprotein convertase subtilisin/kexin type 9 (PCSK9), and LDLR adaptor protein 1 (LDLRAP1). However, approximately 40% of the FH patients clinically diagnosed (based on FH phenotypes) may not carry a causal variant in a FH-related gene. Variants located at 3' untranslated region (UTR) of FH-related genes could elucidate mechanisms involved in FH pathogenesis. This study used a computational approach to assess the effects of 3'UTR variants in FH-related genes on miRNAs molecular interactions and to explore the association of these variants with molecular diagnosis of FH.

METHODS AND RESULTS

Exons and regulatory regions of FH-related genes were sequenced in 83 FH patients using an exon-target gene sequencing strategy. In silico prediction tools were used to study the effects of 3´UTR variants on interactions between miRNAs and target mRNAs. Pathogenic variants in FH-related genes (molecular diagnosis) were detected in 44.6% FH patients. Among 59 3'UTR variants identified, LDLR rs5742911 and PCSK9 rs17111557 were associated with molecular diagnosis of FH, whereas LDLR rs7258146 and rs7254521 and LDLRAP1 rs397860393 had an opposite effect (p < 0.05). 3´UTR variants in LDLR (rs5742911, rs7258146, rs7254521) and PCSK9 (rs17111557) disrupt interactions with several miRNAs, and more stable bindings were found with LDLR (miR-4435, miR-509-3 and miR-502) and PCSK9 (miR-4796).

CONCLUSION

LDLR and PCSK9 3´UTR variants disturb miRNA:mRNA interactions that could affect gene expression and are potentially associated with molecular diagnosis of FH.

Implication of myddosome complex genetic variants in outcome severity of COVID-19 patients

BACKGROUND/PURPOSE(S)

During a viral infection, the immune response is mediated by the toll-like receptors and myeloid differentiation Factor 88 (MyD88) that play an important role sensing infections such as SARS-CoV-2 which has claimed the lives of more than 6.8 million people around the world.

METHODS

We carried out a cross-sectional with a population of 618 SARS-CoV-2-positive unvaccinated subjects and further classified based on severity: 22% were mild, 34% were severe, 26% were critical, and 18% were deceased. Toll Like Receptor 7 (TLR7) single-nucleotide polymorphisms (rs3853839, rs179008, rs179009, and rs2302267) and MyD88 (rs7744) were genotyped using TaqMan OpenArray. The association of polymorphisms with disease outcomes was performed by logistic regression analysis adjusted by covariates.

RESULTS

A significant association of rs3853839 and rs7744 of the TLR7 and MyD88 genes, respectively, was found with COVID-19 severity. The G/G genotype of the rs3853839 TLR7 was associated with the critical outcome showing an Odd Ratio = 1.98 (95% IC = 1.04-3.77). The results highlighted an association of the G allele of MyD88 gene with severe, critical and deceased outcomes. Furthermore, in the dominant model (AG + GG vs. AA), we observed an Odd Ratio = 1.70 (95% CI = 1.02-2.86) with severe, Odd Ratio = 1.82 (95% CI = 1.04-3.21) with critical, and Odd Ratio = 2.44 (95% CI = 1.21-4.9) with deceased outcomes.

CONCLUSION

To our knowledge this work represents an innovative report that highlights the significant association of TLR7 and MyD88 gene polymorphisms with COVID-19 outcomes and the possible implication of the MyD88 variant with D-dimer and IFN-α concentrations.

Investigating Neuron Degeneration in Huntington's Disease Using RNA-Seq Based Transcriptome Study

Huntington's disease (HD) is a progressive neurodegenerative disorder caused due to a CAG repeat expansion in the huntingtin (HTT) gene. The primary symptoms of HD include motor dysfunction such as chorea, dystonia, and involuntary movements. The primary motor cortex (BA4) is the key brain region responsible for executing motor/movement activities. Investigating patient and control samples from the BA4 region will provide a deeper understanding of the genes responsible for neuron degeneration and help to identify potential markers. Previous studies have focused on overall differential gene expression and associated biological functions. In this study, we illustrate the relationship between variants and differentially expressed genes/transcripts. We identified variants and their associated genes along with the quantification of genes and transcripts. We also predicted the effect of variants on various regulatory activities and found that many variants are regulating gene expression. Variants affecting miRNA and its targets are also highlighted in our study. Co-expression network studies revealed the role of novel genes. Function interaction network analysis unveiled the importance of genes involved in vesicle-mediated transport. From this unified approach, we propose that genes expressed in immune cells are crucial for reducing neuron death in HD.

Comprehensive analysis predicting effects of deleterious SNPs of human progesterone receptor gene on its structure and functions: a computational approach

Progesterone receptor plays a crucial role in the development of the mammary gland and breast cancer. Single nucleotide polymorphisms (SNPs) within its gene, PGR, are associated with the risk of miscarriages and preterm birth as well as many cancers across different populations. The main aim of this work is to investigate the most deleterious SNPs in the PGR gene to identify potential biomarkers for various disease susceptibility and treatments. Both sequence and structure-based computational approaches were adopted and in total 11 nsSNPs have been filtered out of 674 nsSNPs along with seven non-coding SNPs. R740Q, I744T and D746E belonged to a mutation cluster. R740Q, D746E along with S865L altered H-bond interactions within the receptor. The same mutations have been found to be associated with several cancers including uterine and breast cancer among others. It is, therefore, possible that the high-risk SNPs associated with cancers may exert their effect by causing changes in the protein structure, particularly in its bonding patterns, and thus affecting its function. In addition, seven non-coding SNPs that were located in the UTR region created a new miRNA site while three SNPs disrupted a conserved miRNA site. These high-risk SNPs can play an instrumental role in generating a dataset of the PGR gene's SNPs. Thus, the present study may pave the way to design and develop novel therapeutics for overcoming the challenges associated with certain cancers and pregnancy that result from a change in the protein structure and function due to the SNP mutations in the PGR gene.Communicated by Ramaswamy H. Sarma.

Discovering Deleterious Single Nucleotide Polymorphisms of Human AKT1 Oncogene: An In Silico Study

BACKGROUND

AKT1 is a serine/threonine kinase necessary for the mediation of apoptosis, angiogenesis, metabolism, and cell proliferation in both normal and cancerous cells. The mutations in the AKT1 gene have been associated with different types of cancer. Further, the AKT1 gene mutations are also reported to be associated with other diseases such as Proteus syndrome and Cowden syndromes. Hence, this study aims to identify the deleterious AKT1 missense SNPs and predict their effect on the function and structure of the AKT1 protein using various computational tools.

METHODS

Extensive in silico approaches were applied to identify deleterious SNPs of the human AKT1 gene and assessment of their impact on the function and structure of the AKT1 protein. The association of these highly deleterious missense SNPs with different forms of cancers was also analyzed. The in silico approach can help in reducing the cost and time required to identify SNPs associated with diseases.

RESULTS

In this study, 12 highly deleterious SNPs were identified which could affect the structure and function of the AKT1 protein. Out of the 12, four SNPs-namely, G157R, G159V, G336D, and H265Y-were predicted to be located at highly conserved residues. G157R could affect the ligand binding to the AKT1 protein. Another highly deleterious SNP, R273Q, was predicted to be associated with liver cancer.

CONCLUSIONS

This study can be useful for pharmacogenomics, molecular diagnosis of diseases, and developing inhibitors of the AKT1 oncogene.

Comprehensive In Silico Characterization of the Coding and Non-Coding SNPs in Human Dectin-1 Gene with the Potential of High-Risk Pathogenicity Associated with Fungal Infections

The human C-type lectin domain family 7 member A (CLEC7A) gene encodes a Dectin-1 protein that recognizes beta-1,3-linked and beta-1,6-linked glucans, which form the cell walls of pathogenic bacteria and fungi. It plays a role in immunity against fungal infections through pathogen recognition and immune signaling. This study aimed to explore the impact of nsSNPs in the human CLEC7A gene through computational tools (MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT, SNAP, and PredictSNP) to identify the most deleterious and damaging nsSNPs. Further, their effect on protein stability was checked along with conservation and solvent accessibility analysis by I-Mutant 2.0, ConSurf, and Project HOPE and post-translational modification analysis using MusiteDEEP. Out of the 28 nsSNPs that were found to be deleterious, 25 nsSNPs affected protein stability. Some SNPs were finalized for structural analysis with Missense 3D. Seven nsSNPs affected protein stability. Results from this study predicted that C54R, L64P, C120G, C120S, S135C, W141R, W141S, C148G, L155P, L155V, I158M, I158T, D159G, D159R, I167T, W180R, L183F, W192R, G197E, G197V, C220S, C233Y, I240T, E242G, and Y3D were the most structurally and functionally significant nsSNPs in the human CLEC7A gene. No nsSNPs were found in the predicted sites for post-translational modifications. In the 5' untranslated region, two SNPs, rs536465890 and rs527258220, showed possible miRNA target sites and DNA binding sites. The present study identified structurally and functionally significant nsSNPs in the CLEC7A gene. These nsSNPs may potentially be used for further evaluation as diagnostic and prognostic biomarkers.

In silico prioritisation of microRNA-associated common variants in multiple sclerosis

BACKGROUND

Genome-wide association studies (GWAS) have highlighted over 200 autosomal variants associated with multiple sclerosis (MS). However, variants in non-coding regions such as those encoding microRNAs have not been explored thoroughly, despite strong evidence of microRNA dysregulation in MS patients and model organisms. This study explores the effect of microRNA-associated variants in MS, through the largest publicly available GWAS, which involved 47,429 MS cases and 68,374 controls.

METHODS

We identified SNPs within the coordinates of microRNAs, ± 5-kb microRNA flanking regions and predicted 3'UTR target-binding sites using miRBase v22, TargetScan 7.0 RNA22 v2.0 and dbSNP v151. We established the subset of microRNA-associated SNPs which were tested in the summary statistics of the largest MS GWAS by intersecting these datasets. Next, we prioritised those microRNA-associated SNPs which are among known MS susceptibility SNPs, are in strong linkage disequilibrium with the former or meet a microRNA-specific Bonferroni-corrected threshold. Finally, we predicted the effects of those prioritised SNPs on their microRNAs and 3'UTR target-binding sites using TargetScan v7.0, miRVaS and ADmiRE.

RESULTS

We have identified 30 candidate microRNA-associated variants which meet at least one of our prioritisation criteria. Among these, we highlighted one microRNA variant rs1414273 (MIR548AC) and four 3'UTR microRNA-binding site variants within SLC2A4RG (rs6742), CD27 (rs1059501), MMEL1 (rs881640) and BCL2L13 (rs2587100). We determined changes to the predicted microRNA stability and binding site recognition of these microRNA and target sites.

CONCLUSIONS

We have systematically examined the functional, structural and regulatory effects of candidate MS variants among microRNAs and 3'UTR targets. This analysis allowed us to identify candidate microRNA-associated MS SNPs and highlights the value of prioritising non-coding RNA variation in GWAS. These candidate SNPs could influence microRNA regulation in MS patients. Our study is the first thorough investigation of both microRNA and 3'UTR target-binding site variation in multiple sclerosis using GWAS summary statistics.

Insights into Online microRNA Bioinformatics Tools

MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs.

Investigation of UTR Variants by Computational Approaches Reveal Their Functional Significance in PRKCI Gene Regulation

Single nucleotide polymorphisms (SNPs) are associated with many diseases including neurological disorders, heart diseases, diabetes, and different types of cancers. In the context of cancer, the variations within non-coding regions, including UTRs, have gained utmost importance. In gene expression, translational regulation is as important as transcriptional regulation for the normal functioning of cells; modification in normal functions can be associated with the pathophysiology of many diseases. UTR-localized SNPs in the PRKCI gene were evaluated using the PolymiRTS, miRNASNP, and MicroSNIper for association with miRNAs. Furthermore, the SNPs were subjected to analysis using GTEx, RNAfold, and PROMO. The genetic intolerance to functional variation was checked through GeneCards. Out of 713 SNPs, a total of thirty-one UTR SNPs (three in 3' UTR region and twenty-nine in 5' UTR region) were marked as ≤2b by RegulomeDB. The associations of 23 SNPs with miRNAs were found. Two SNPs, rs140672226 and rs2650220, were significantly linked with expression in the stomach and esophagus mucosa. The 3' UTR SNPs rs1447651774 and rs115170199 and the 5' UTR region variants rs778557075, rs968409340, and 750297755 were predicted to destabilize the mRNA structure with substantial change in free energy (∆G). Seventeen variants were predicted to have linkage disequilibrium with various diseases. The SNP rs542458816 in 5' UTR was predicted to put maximum influence on transcription factor binding sites. Gene damage index(GDI) and loss of function (o:e) ratio values for PRKCI suggested that the gene is not tolerant to loss of function variants. Our results highlight the effects of 3' and 5' UTR SNP on miRNA, transcription and translation of PRKCI. These analyses suggest that these SNPs can have substantial functional importance in the PRKCI gene. Future experimental validation could provide further basis for the diagnosis and therapeutics of various diseases.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

HBV genotype-dependent association of HLA variants with the serodecline of HBsAg in chronic hepatitis B patients

Seroclearance of hepatitis B surface antigen (HBsAg) is regarded as the functional cure for chronic hepatitis B (CHB). The relationship between human leukocyte antigen (HLA) variants, hepatitis B virus genotype, and longitudinal HBsAg serodecline remains to be explored. A total of 1735 HBeAg-seronegative CHB patients with genotype B or C infection of the community-based REVEAL-HBV cohort were genotyped for rs1710 (HLA-G) and rs2770 (HLA-B) using TaqMan assay. Cox proportional hazard regression and generalized linear mixed models were used to analyze the association of HLA genetic variants with the rate of HBsAg seroclearance and longitudinal HBsAg serodecline. Rs1710 G allele was differentially associated with the HBsAg seroclearance in genotype B [aRR (95% CI) = 0.74 (0.56-0.98)] and genotype C [aRR (95%CI) = 1.43 (1.08-1.88)] infection. Rs2770 G allele was associated with HBsAg seroclearance only in genotype B infection [aRR (95% CI) = 0.69 (0.52-0.91)]. The alleles associated with HBsAg seroclearance were significant predictors for the serodecline of HBsAg levels in an HBV genotype-dependent manner (genotype B infection: rs1710, P = 0.013; rs2770, P = 0.0081; genotype C infection: rs1710, P = 0.0452). Our results suggest both spontaneous HBsAg seroclearance and serodecline are modified by the interaction between HLA variants and HBV genotype.

Landscape of MicroRNA Regulatory Network Architecture and Functional Rerouting in Cancer

Somatic mutations are a major source of cancer development, and many driver mutations have been identified in protein coding regions. However, the function of mutations located in miRNA and their target binding sites throughout the human genome remains largely unknown. Here, we built detailed cancer-specific miRNA regulatory networks across 30 cancer types to systematically analyze the effect of mutations in miRNAs and their target sites in 3' untranslated region (3' UTR), coding sequence (CDS), and 5' UTR regions. A total of 3,518,261 mutations from 9,819 samples were mapped to miRNA-gene interactions (mGI). Mutations in miRNAs showed a mutually exclusive pattern with mutations in their target genes in almost all cancer types. A linear regression method identified 148 candidate driver mutations that can significantly perturb miRNA regulatory networks. Driver mutations in 3'UTRs played their roles by altering RNA binding energy and the expression of target genes. Finally, mutated driver gene targets in 3' UTRs were significantly downregulated in cancer and functioned as tumor suppressors during cancer progression, suggesting potential miRNA candidates with significant clinical implications. A user-friendly, open-access web portal (mGI-map) was developed to facilitate further use of this data resource. Together, these results will facilitate novel noncoding biomarker identification and therapeutic drug design targeting the miRNA regulatory networks.

SIGNIFICANCE

A detailed miRNA-gene interaction map reveals extensive miRNA-mediated gene regulatory networks with mutation-induced perturbations across multiple cancers, serving as a resource for noncoding biomarker discovery and drug development.

MicroRNA Regulatory Network Analysis Using miRNet 2.0

MicroRNAs exert their effects in the context of gene regulatory networks. The recent development of high-throughput experimental approaches and the growing availability of gene expression data have permitted comprehensive functional studies of miRNAs. However, the data interpretation is often challenging due to the fact that miRNAs not only act cooperatively with other miRNAs but also participate in complex networks by interacting with other functional elements, including non-coding RNAs or transcription factors that often have extensive effects on cell biology. This chapter provides detailed practical procedures on how to use miRNet 2.0 ( https://www.mirnet.ca ) to perform miRNA regulatory network analytics to gain functional insights.

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.

Integrative Meta-Analysis of Huntington's Disease Transcriptome Landscape

Huntington's disease (HD) is a neurodegenerative disorder with autosomal dominant inheritance caused by glutamine expansion in the Huntingtin gene (HTT). Striatal projection neurons (SPNs) in HD are more vulnerable to cell death. The executive striatal population is directly connected with the Brodmann Area (BA9), which is mainly involved in motor functions. Analyzing the disease samples from BA9 from the SRA database provides insights related to neuron degeneration, which helps to identify a promising therapeutic strategy. Most gene expression studies examine the changes in expression and associated biological functions. In this study, we elucidate the relationship between variants and their effect on gene/downstream transcript expression. We computed gene and transcript abundance and identified variants from RNA-seq data using various pipelines. We predicted the effect of genome-wide association studies (GWAS)/novel variants on regulatory functions. We found that many variants affect the histone acetylation pattern in HD, thereby perturbing the transcription factor networks. Interestingly, some variants affect miRNA binding as well as their downstream gene expression. Tissue-specific network analysis showed that mitochondrial, neuroinflammation, vasculature, and angiogenesis-related genes are disrupted in HD. From this integrative omics analysis, we propose that abnormal neuroinflammation acts as a two-edged sword that indirectly affects the vasculature and associated energy metabolism. Rehabilitation of blood-brain barrier functionality and energy metabolism may secure the neuron from cell death.

The impact of modifier genes on cone-rod dystrophy heterogeneity: An explorative familial pilot study and a hypothesis on neurotransmission impairment

Cone-rod dystrophies (CORDs) are a heterogeneous group of inherited retinopathies (IRDs) with more than 30 already known disease-causing genes. Uncertain phenotypes and extended range of intra- and interfamilial heterogenicity make still difficult to determine a precise genotype-phenotype correlation. Here, we used a next-generation sequencing approach to study a Sicilian family with a suspected form of CORD. Affected family members underwent ophthalmological examinations and a proband, blind from 50 years, underwent whole genome and exome sequencing. Variant analysis was enriched by pathway analysis and relevant variants were, then, investigated in other family members and in 100 healthy controls from Messina. CORD diagnosis with an intricate pattern of symptoms was confirmed by ophthalmological examinations. A total of about 50,000 variants were identified in both proband's genome and exome. All affected family members presented specific genotypes mainly determined by mutated GUCY2D gene, and different phenotypical traits, mainly related to focus and color perception. Thus, we looked for possible modifier genes. According to relationship with GUCY2D, predicted functional effects, eye localization, and ocular disease affinity, only 9 variants, carried by 6 genes (CACNG8, PAX2, RXRG, CCDC175, PDE4DIP and LTF), survived the filtering. These genes encode key proteins involved in cone development and survival, and retina neurotransmission. Among analyzed variants, CACNG8c.*6819A>T and the new CCDC175 c.76C>T showed extremely low frequency in the control group, suggesting a key role on disease phenotypes. Such discovery could enforce the role of modifier genes into CORD onset/progression, contributing to improve diagnostic test towards a better personalized medicine.

Exonuclease 1 genetic variant is associated with clinical outcomes of pemetrexed chemotherapy in lung adenocarcinoma

Pemetrexed is an anti-folate agent which is one of the most frequently used chemotherapy agents for non-squamous non-small cell lung cancer (NSCLC) patients. However, clinical response to pemetrexed chemotherapy and survival outcome of patients varies significantly. We evaluated whether the genetic variants in miRNA target sites may affect the treatment outcome of pemetrexed chemotherapy in lung adenocarcinoma patients. One hundred SNPs in miRNA binding regions in cancer-related genes were obtained from the crosslinking, ligation, and sequencing of hybrids (CLASH) and CancerGenes database, and the associations with the response to pemetrexed chemotherapy and survival outcomes were investigated in 314 lung adenocarcinoma patients. Two polymorphisms, EXO1 rs1047840G>A and CAMKK2 rs1653586G>T, were significantly associated with worse chemotherapy response (adjusted odds ratio [aOR] = 0.41, 95% CI = 0.24-0.68, P = 0.001, under dominant model; and aOR = 0.33, 95% CI = 0.16-0.67, P = 0.002, under dominant model, respectively) and worse OS (adjusted hazard ratio [aHR] = 1.34, 95% CI = 1.01-1.77, P = 0.04, under dominant model; and aHR = 1.50, 95% CI = 1.06-2.13, P = 0.02, under dominant model, respectively) in multivariate analyses. Significantly increased luciferase activity was noted in EXO1 rs1047840 A allele compared to G allele. In conclusion, two SNPs in miRNA binding sites, especially EXO1 rs1047840G>A, were associated with the chemotherapy response and survival outcome in lung adenocarcinoma patients treated with pemetrexed.

Genetic variant in miR-17-92 cluster binding sites is associated with esophageal squamous cell carcinoma risk in Chinese population

BACKGROUND

Single nucleotide polymorphisms (SNPs) located in microRNA (miRNA) binding sites can affect the interactions between miRNAs and target genes, which is related to cancer susceptibility and tumorigenesis. However, the association between SNPs located in miR-17-92 cluster binding sites and ESCC risk remains unclear. Therefore, we aimed to explore the relationship between polymorphisms in miR-17-92 cluster binding sites and ESCC susceptibility.

METHODS

Six SNPs in the binding sites of miR-17-92 cluster were selected using bioinformatics databases, and their association with ESCC risk was investigated in a case-control study (including 488 cases and 512 controls) based on the population from high incidence areas of ESCC in China. We evaluated the SNP-SNP and SNP-smoking interactions using generalized multifactor dimensionality reduction (GMDR). Moreover, the expression of the miR-17-92 cluster and its target genes was determined in ESCC and adjacent normal tissues by quantitative real-time polymerase chain reaction (qRT-PCR). The dual-luciferase reporter assay was conducted to verify the effect of SNPs on the binding affinity between miRNAs and target genes.

RESULTS

We found that the SNP rs1804506 C > T had a significant association with the decreased ESCC risk. The SNP rs1804506 T allele was associated with a significantly decreased risk of ESCC in the additive model (OR = 0.817, 95% CI = 0.681-0.981, P = 0.030). The rs1804506 T allele had more striking effects on reducing ESCC risk in older individuals, female or non-smoker subgroups. We also found a significant interaction effect between rs1366600 and smoking by GMDR methods (P = 0.011). Additionally, the expression levels of miR-19a-3p and TGFBR3 were significantly downregulated in ESCC tissues compared with normal tissues, and the carriers of rs1804506 TT genotype had lower expression level of TGFBR3 than those of rs1804506 CC/CT genotype. Following dual-luciferase reporter assay showed that the rs1804506 T allele reduced the binding of miR-19a-3p and TGFBR3 3'-UTR.

CONCLUSIONS

Our findings suggest that the rs1804506 polymorphism in miR-17-92 cluster binding sites contributes to the susceptibility of ESCC, which might provide new clues and scientific evidence for the etiology and biomarkers for the prevention and treatment of ESCC.

SNPs in 3'UTR miRNA Target Sequences Associated with Individual Drug Susceptibility

The complementary interaction of microRNAs (miRNAs) with their binding sites in the 3'untranslated regions (3'UTRs) of target gene mRNAs represses translation, playing a leading role in gene expression control. MiRNA recognition elements (MREs) in the 3'UTRs of genes often contain single nucleotide polymorphisms (SNPs), which can change the binding affinity for target miRNAs leading to dysregulated gene expression. Accumulated data suggest that these SNPs can be associated with various human pathologies (cancer, diabetes, neuropsychiatric disorders, and cardiovascular diseases) by disturbing the interaction of miRNAs with their MREs located in mRNA 3'UTRs. Numerous data show the role of SNPs in 3'UTR MREs in individual drug susceptibility and drug resistance mechanisms. In this review, we brief the data on such SNPs focusing on the most rigorously proven cases. Some SNPs belong to conventional genes from the drug-metabolizing system (in particular, the genes coding for cytochromes P450 (CYP 450), phase II enzymes (SULT1A1 and UGT1A), and ABCB3 transporter and their expression regulators (PXR and GATA4)). Other examples of SNPs are related to the genes involved in DNA repair, RNA editing, and specific drug metabolisms. We discuss the gene-by-gene studies and genome-wide approaches utilized or potentially utilizable to detect the MRE SNPs associated with individual response to drugs.

Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer

The Harvey rat sarcoma (HRAS) proto-oncogene belongs to the RAS family and is one of the pathogenic genes that cause cancer. Deleterious nsSNPs might have adverse consequences at the protein level. This study aimed to investigate deleterious nsSNPs in the HRAS gene in predicting structural alterations associated with mutants that disrupt normal protein–protein interactions. Functional and structural analysis was employed in analyzing the HRAS nsSNPs. Putative post-translational modification sites and the changes in protein–protein interactions, which included a variety of signal cascades, were also investigated. Five different bioinformatics tools predicted 33 nsSNPs as “pathogenic” or “harmful”. Stability analysis predicted rs1554885139, rs770492627, rs1589792804, rs730880460, rs104894227, rs104894227, and rs121917759 as unstable. Protein–protein interaction analysis revealed that HRAS has a hub connecting three clusters consisting of 11 proteins, and changes in HRAS might cause signal cascades to dissociate. Furthermore, Kaplan–Meier bioinformatics analyses indicated that the HRAS gene deregulation affected the overall survival rate of patients with breast cancer, leading to prognostic significance. Thus, based on these analyses, our study suggests that the reported nsSNPs of HRAS may serve as potential targets for different proteomic studies, diagnoses, and therapeutic interventions focusing on cancer.

Pharmacogenomics deliberations of 2-deoxy-d-glucose in the treatment of COVID-19 disease: an in silico approach

The outbreak of COVID-19 caused by the coronavirus (SARS-CoV-2) prompted number of computational and laboratory efforts to discover molecules against the virus entry or replication. Simultaneously, due to the availability of clinical information, drug-repurposing efforts led to the discovery of 2-deoxy-d-glucose (2-DG) for treating COVID-19 infection. 2-DG critically accumulates in the infected cells to prevent energy production and viral replication. As there is no clarity on the impact of genetic variations on the efficacy and adverse effects of 2-DG in treating COVID-19 using in silico approaches, we attempted to extract the genes associated with the 2-DG pathway using the Comparative Toxicogenomics Database. The interaction between selected genes was assessed using ClueGO, to identify the susceptible gene loci for SARS-CoV infections. Further, SNPs that were residing in the distinct genomic regions were retrieved from the Ensembl genome browser and characterized. A total of 80 SNPs were retrieved using diverse bioinformatics resources after assessing their (a) detrimental influence on the protein stability using Swiss-model, (b) miRNA regulation employing miRNASNP3, PolymiRTS, MirSNP databases, (c) binding of transcription factors by SNP2TFBS, SNPInspector, and (d) enhancers regulation using EnhancerDB and HaploReg reported A2M rs201769751, PARP1 rs193238922 destabilizes protein, six polymorphisms of XIAP effecting microRNA binding sites, EGFR rs712829 generates 15 TFBS, BECN1 rs60221525, CASP9 rs4645980, SLC2A2 rs5393 impairs 14 TFBS, STK11 rs3795063 altered 19 regulatory motifs. These data may provide the relationship between genetic variations and drug effects of 2-DG which may further assist in assigning the right individuals to benefit from the treatment.

A novel genetic variant potentially altering the expression of MANBA in the cerebellum associated with attention deficit hyperactivity disorder in Han Chinese children

OBJECTIVES

To obtain additional insight into the genetic factors of attention deficit hyperactivity disorder (ADHD).

METHODS

First, we performed a transcriptome-wide association study (TWAS) integrating human cerebellum-specific variant-expression/splicing correlations to identify ADHD susceptibility genes. Then, the associations between expression/splicing quantitative trait loci (eQTLs/sQTLs) of the transcriptome-wide significant genes and ADHD were observed in a case-control study of Han Chinese children. Furthermore, dual luciferase reporter gene assays were performed to validate the regulatory function of ADHD risk variants. Additionally, the transcription level of target genes in blood was detected by real-time quantitative polymerase chain reaction (RT-qPCR) assay.

RESULTS

TWAS identified that the genetically regulated expression of MANBA in the cerebellum was significantly associated with ADHD risk. Furthermore, we observed a higher risk of ADHD and more severe clinical symptoms in subjects harbouring heterozygous (TC) or mutant homozygous (TT) genotypes of MANBA rs1054037 than CC carriers. The dual luciferase reporter gene assay revealed that the mutation of rs1054037(C > T) potentially upregulated MANBA expression by eliminating the binding site for hsa-miR-5591-3P. Finally, RT-qPCR showed that MANBA expression in blood samples of patients was significantly higher than that of controls.

CONCLUSIONS

Taken together, these results suggest a role of MANBA in the development of ADHD.

miRNA therapeutics in precision oncology: a natural premium to nurture

The dynamic spectrum of microRNA (miRNA) has grown significantly over the years with its identification and exploration in cancer therapeutics and is currently identified as an important resource for innovative strategies due to its functional behavior for gene regulation and modulation of complex biological networks. The progression of cancer is the consequence of uncontrolled, nonsynchronous procedural faults in the biological system. Diversified and variable cellular response of cancerous cells has always raised challenges in effective cancer therapy. miRNAs, a class of non-coding RNAs (ncRNAs), are the natural genetic gift, responsible to preserve the homeostasis of cell to nurture. The unprecedented significance of endogenous miRNAs has exhibited promising therapeutic potential in cancer therapeutics. Currently, miRNA mimic miR-34, and an antimiR aimed against miR-122 has entered the clinical trials for cancer treatments. This review, highlights the recent breakthroughs, challenges, clinical trials, and advanced delivery vehicles in the administration of miRNA therapies for precision oncology.

mintRULS: Prediction of miRNA–mRNA Target Site Interactions Using Regularized Least Square Method

Identification of miRNA–mRNA interactions is critical to understand the new paradigms in gene regulation. Existing methods show suboptimal performance owing to inappropriate feature selection and limited integration of intuitive biological features of both miRNAs and mRNAs. The present regularized least square-based method, mintRULS, employs features of miRNAs and their target sites using pairwise similarity metrics based on free energy, sequence and repeat identities, and target site accessibility to predict miRNA-target site interactions. We hypothesized that miRNAs sharing similar structural and functional features are more likely to target the same mRNA, and conversely, mRNAs with similar features can be targeted by the same miRNA. Our prediction model achieved an impressive AUC of 0.93 and 0.92 in LOOCV and LmiTOCV settings, respectively. In comparison, other popular tools such as miRDB, TargetScan, MBSTAR, RPmirDIP, and STarMir scored AUCs at 0.73, 0.77, 0.55, 0.84, and 0.67, respectively, in LOOCV setting. Similarly, mintRULS outperformed other methods using metrics such as accuracy, sensitivity, specificity, and MCC. Our method also demonstrated high accuracy when validated against experimentally derived data from condition- and cell-specific studies and expression studies of miRNAs and target genes, both in human and mouse.

In silico comprehensive analysis of coding and non-coding SNPs in human mTOR protein

The mammalian/mechanistic target of rapamycin (mTOR) protein is an important growth regulator and has been linked with multiple diseases including cancer and diabetes. Non-synonymous mutations of this gene have already been found in patients with renal clear cell carcinoma, melanoma, and acute lymphoid leukemia among many others. Such mutations can potentially affect a protein’s structure and hence its functions. In this study, therefore, the most deleterious SNPs of mTOR protein have been determined to identify potential biomarkers for various disease treatments. The aim is to generate a structured dataset of the mTOR gene’s SNPs that may prove to be an asset for the identification and treatment of multiple diseases associated with the target gene. Both sequence and structure-based approaches were adopted and a wide variety of bioinformatics tools were applied to analyze the SNPs of mTOR protein. In total 11 nsSNPs have been filtered out of 2178 nsSNPs along with two non-coding variations. All of the nsSNPs were found to destabilize the protein structure and disrupt its function. While R619C, A1513D, and T1977R mutations were shown to alter C alpha distances and bond angles of the mTOR protein, L509Q, R619C and N2043S were predicted to disrupt the mTOR protein’s interaction with NBS1 protein and FKBP1A/rapamycin complex. In addition, one of the non-coding SNPs was shown to alter miRNA binding sites. Characterizing nsSNPs and non-coding SNPs and their harmful effects on a protein’s structure and functions will enable researchers to understand the critical impact of mutations on the molecular mechanisms of various diseases. This will ultimately lead to the identification of potential targets for disease diagnosis and therapeutic interventions.

MiRLog and dbmiR: prioritization and functional annotation tools to study human microRNA sequence variants

The recent identification of noncoding variants with pathogenic effects suggests that these variations could underlie a significant number of undiagnosed cases. Several computational methods have been developed to predict the functional impact of noncoding variants, but they exhibit only partial concordance and are not integrated with functional annotation resources, making the interpretation of these variants still challenging. MicroRNAs (miRNAs) are small noncoding RNA molecules that act as fine regulators of gene expression and play crucial functions in several biological processes, such as cell proliferation and differentiation. An increasing number of studies demonstrate a significant impact of miRNA single nucleotide variants (SNVs) both in Mendelian diseases and complex traits. To predict the functional effect of miRNA SNVs, we implemented a new meta‐predictor, MiRLog, and we integrated it into a comprehensive database, dbmiR, which includes a precompiled list of all possible miRNA allelic SNVs, providing their biological annotations at nucleotide and miRNA levels. MiRLog and dbmiR were used to explore the genetic variability of miRNAs in 15,708 human genomes included in the gnomAD project, finding several ultra‐rare SNVs with a potentially deleterious effect on miRNA biogenesis and function representing putative contributors to human phenotypes.

In silico screening and analysis of single-nucleotide polymorphic variants of the ABCC2 gene affecting Dubin-Johnson syndrome

BACKGROUND AND STUDY AIMS

Dubin-Johnson syndrome (DJS) is a benevolent genetic disorder of the liver with autosomal inheritance. It is a rare disorder characterized by an increase in conjugated bilirubin and anomaly in coproporphyrin clearance. DJS is caused by deleterious mutations in the ABCC2 gene. A polymorphism in the ABCC2 gene causes malfunctions in its ability to regulate the efflux of different organic anions, such as bilirubin, from hepatocytes to the canaliculi. Multidrug resistance protein 2 (MRP2) encoded by the ABCC2 gene is one of the main regulators of the export of bilirubin to respective sites. ABCC2 gene mutations have widely drawn attention in the pathology of DJS in various populations.

PATIENTS AND METHODS

The ABCC2 gene was subjected to the National Center for Biotechnology Information (NCBI) database in 2020, and non-synonymous single-nucleotide polymorphisms (nsSNPs) and variants in untranslated regions were studied using different computational servers. SIFT, Protein variation effect analyzer, and PolyPhen-2 were used to retrieve the damaging Single-nucleotide polymorphisms (SNPs); PhD-SNP, SNPs&GO, and Protein Analysis Through Evolutionary Relationships were used to predict the association of nsSNPs with DJS; Mutation3D illustrated the location of variants in the protein; SNAP2, MutPred2, ELASPIC, and HOPE were used to predict the structural and functional effects of these mutations on MRP2; and I-mutant 3.0 and MuPro were used to determine the effects of polymorphism on the function of MRP2.

RESULTS

In this study, 18,947 SNPs were screened from the NCBI database, followed by a series of refinement of variants using online available servers. We concluded that 41 ABCC2 gene variants are vital etiological candidates for DJS in humans. These 41 variants had highly damaging effects on the MRP2 protein, which may lead to deficient transportation capacity, thereby affecting the efflux of bilirubin across the canalicular membrane.

CONCLUSION

In silico tools are an alternative approach for predicting the target SNPs. Hence, previously unreported variants can be considered strong etiological candidates for diseases related to MRP2.

Investigating the interference of single nucleotide polymorphisms with miRNA mediated gene regulation in pancreatic ductal adenocarcinoma: An in silico approach

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a strong genetic component and single nucleotide polymorphisms (SNPs) in key genes have been found to modulate the susceptibility of the individuals to the disease. SNPs in 3'-UTR of the target genes or in miRNA seed region has gained much importance as this may lead to impairment of miRNA-mRNA interaction. Not much information about this phenomenon is available with respect to PDAC and we wanted to predict such SNPs which could affect miRNA function in the disease using bioinformatics tools.

METHODS

After identifying the deregulated miRNAs and genes in PDAC, we determined how many of those altered genes are among experimentally validated targets of those miRNAs. Subsequently, SNPs which could alter these miRNA-mRNA interactions were detected using multiple webtools following high stringent conditions. Disease relevance of the SNPs were also evaluated.

RESULTS

We identified a total of 2492 experimentally validated target genes for 303 miRNAs deregulated in PDAC. Our meta-analysis from 363 PDAC patients and 162 control individuals resulted in a set of differentially expressed genes in pancreatic cancer, which was further compared with the miRNA target genes to get targets differentially expressed in pancreatic cancer. We further detected SNPs either in 'seed' region of miRNAs or 'seed-match' sequence of mRNAs either having disruption or creation of miRNA binding site, correlated the expression for each miRNA-SNP-mRNA interaction. Selected SNPs were found to be in LD with important GWAS identified SNPs.

CONCLUSION

Our study, hereby, explores the probable effects of SNPs on miRNA-target mRNA interactions. Through stringent analytical methods, we have identified 3 common variants and 13other rare variants possibly interfering with miRNA mediated gene regulation in PDAC.

Association of a miRNA-binding site polymorphism in IL-16 gene with disease risk and clinical characteristics of rheumatoid arthritis and systemic lupus erythematosus

INTRODUCTION

/objectives. Single nucleotide polymorphisms (SNPs) located at the 3'-UTR region of the target genes of microRNAs (miRNAs) can dysregulate their expression via disrupting the binding site of miRNAs. Interleukin-16 (IL-16) is involved in the pathogenesis of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). In the current study, we assessed the possible association between rs1131445 polymorphism in IL-16 gene with risk and clinical characteristics of RA and SLE in the Iranian population.

METHODS

In this case-control study, 120 patients with RA, 120 patients with SLE, and 120 unrelated healthy subjects were collected to estimate rs1131445 (T > C) polymorphism in IL-16 gene using real-time PCR high-resolution melting (HRM) method.

RESULTS

Our results demonstrated considerable associations between TC genotype and C allele of rs1131445 with enhanced risk of RA (OR_{for TC genotype} = 3.01; 95%CI [1.667-5.526], P < 0.001; OR_{for C allele} = 1.96; 95%CI [1.314-2.941], P < 0.001). Besides, there was a marginal association between CC genotype and increased risk of RA (P: 0.031). However, there was an insignificant correlation between genotypes and allele frequencies of rs1131445 with incidence risk of SLE (P > 0.05). Moreover, stratification analysis indicated that the C allele in rs1131445 was linked with disease activity-associated laboratory parameters such as CRP and ESR in both RA and SLE patients, as well as the higher incidence of neurological symptoms in SLE subjects (P < 0.05).

CONCLUSION

These results proposed a significant association between IL-16 polymorphism and augmented risk of RA and clinical characteristics of RA and SLE.

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.

Classical and noncanonical functions of miRNAs in cancers

Alterations in microRNAs (miRNAs) expression are causative in the initiation and progression of human cancers. The molecular events responsible for the widespread differential expression of miRNAs in malignancy are exemplified by their location in cancer-associated genomic regions, epigenetic mechanisms, transcriptional dysregulation, chemical modifications and editing, and alterations in miRNA biogenesis proteins. The classical miRNA function is synonymous with post-transcriptional repression of target protein genes. However, several studies have reported miRNAs functioning outside this paradigm and some of these novel modes of regulation of gene expression have been implicated in cancers. Here, we summarize key aspects of miRNA involvement in cancer, with a special focus on these lesser-studied mechanisms of action.

Molecular insights into the role of genetic determinants of congenital hypothyroidism

In our previous studies, we have demonstrated the association of certain variants of the thyroid-stimulating hormone receptor (TSHR), thyroid peroxidase (TPO), and thyroglobulin (TG) genes with congenital hypothyroidism. Herein, we explored the mechanistic basis for this association using different in silico tools. The mRNA 3'-untranslated region (3'-UTR) plays key roles in gene expression at the post-transcriptional level. In TSHR variants (rs2268477, rs7144481, and rs17630128), the binding affinity of microRNAs (miRs) (hsa-miR-154-5p, hsa-miR-376a-2-5p, hsa-miR-3935, hsa-miR-4280, and hsa-miR-6858-3p) to the 3'-UTR is disrupted, affecting post-transcriptional gene regulation. TPO and TG are the two key proteins necessary for the biosynthesis of thyroid hormones in the presence of iodide and H₂O₂. Reduced stability of these proteins leads to aberrant biosynthesis of thyroid hormones. Compared to the wild-type TPO protein, the p.S398T variant was found to exhibit less stability and significant rearrangements of intra-atomic bonds affecting the stoichiometry and substrate binding (binding energies, ΔG of wild-type vs. mutant: ‒15 vs. ‒13.8 kcal/mol; and dissociation constant, K_d of wild-type vs. mutant: 7.2E^-12 vs. 7.0E^-11 M). The missense mutations p.G653D and p.R1999W on the TG protein showed altered ΔG (0.24 kcal/mol and 0.79 kcal/mol, respectively). In conclusion, an in silico analysis of TSHR genetic variants in the 3'-UTR showed that they alter the binding affinities of different miRs. The TPO protein structure and mutant protein complex (p.S398T) are less stable, with potentially deleterious effects. A structural and energy analysis showed that TG mutations (p.G653D and p.R1999W) reduce the stability of the TG protein and affect its structure-functional relationship.

Nuclear Pore Glycoprotein 62 Genetic Variant rs9523 is Associated with Clinical Outcomes of Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Lung Adenocarcinoma Patients

Introduction

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have represented the prototype of targeted therapy in NSCLC. Patients with EGFR-mutant lung adenocarcinoma extract an extraordinary clinical benefit from EGFR-TKIs. However, the extent and duration of these responses are heterogeneous, suggesting the existence of genetic modifiers affecting an individual’s response to TKIs. We investigated whether genetic variants in miRNA binding sites are associated with the clinical outcome of EGFR-TKIs in lung adenocarcinoma patients.

Methods

One hundred SNPs at miRNA binding sites in cancer-related genes were selected for the analysis using the crosslinking, ligation and sequencing of hybrids (CLASH) and CancerGenes database. qRT-PCR and luciferase assays were conducted to evaluate the functional relevance of the SNPs.

Results

NUP62 rs9523A>G were significantly associated with worse response to EGFR-TKIs, overall survival (OS), and progression-free survival (PFS). The other three SNPs (DVL2 rs2074216G>A, ARF1 rs11541557G>T, and UHRF1 rs2261988C>A) were significantly associated with worse OS and PFS. The rs9523A>G was significantly associated with decreased NUP62 expression in tumor tissues. In addition, a significantly decreased luciferase activity was noted in NUP62 rs9523 G allele compared to A allele.

Conclusion

Genetic variants in miRNA binding sites, especially NUP62 rs9523A>G, may be useful in predicting the clinical outcomes of EGFR-mutant lung adenocarcinoma patients treated with EGFR-TKIs.