In silico analysis of single nucleotide polymorphism (SNPs) in human β-globin gene

Computational Analysis of Single Nucleotide Polymorphisms in Human HIC1 Gene

Background A putative tumor suppressor gene called HIC1 (hypermethylated in cancer) is situated at 17p13.3, a locus where the allelic loss occurs often in human malignancies, including breast cancer. Hypermethylated in cancer 1 protein is a protein that in humans is encoded by the HIC1 gene and it's a Homo sapiens (Human). This gene functions as a growth regulatory and tumor repressor gene. The molecular function of HIC1 gene includes DNA-binding transcription factor activity, sequence-specific DNA binding, DNA binding, histone deacetylase binding, protein binding, metal ion binding, nucleic acid binding, DNA-binding transcription repressor activity, RNA polymerase II-specific, DNA-binding transcription factor activity, RNA polymerase II-specific. The biological process of HIC1 gene includes multicellular organism development, negative regulation of Wnt signaling pathway, positive regulation of DNA damage response, signal transduction by p53 class mediator regulation of transcription, DNA-templated, negative regulation of transcription by RNA polymerase II, Wnt signaling pathway, transcription, DNA-templated, intrinsic apoptotic signaling pathway in response to DNA damage, cellular response to DNA damage stimulus. The study aimed to predict the stability and structure of the protein that will arise from single nucleotide polymorphisms (SNPs) in the human HIC1 gene. Methodology To investigate the possible negative effects associated with these SNPs, bioinformatic analysis is typically essential. The following tools were employed for forecasting harmful SNPs: scale-invariant feature transform (SIFT), Protein Analysis Through Evolutionary Relationships (PANTHER), nonsynonymous SNP by Protein Variation Effect Analyzer (PROVEAN), and nonsynonymous SNP by Single Nucleotide Polymorphism Annotation Platform (SNAP). Results The present study identified a total of 36 SNPs using the SIFT approach, which were shown to have functional significance. Twenty-six were determined to be tolerable, whereas 10 were shown to be detrimental. Out of 20 SNPs, seven (P370A, P646S, R654P, A476T, S400S, D666N, D7V) SNPs were predicted as "Possibly damaging" and seven (L9F, G468R, G490R, L482R, S12W, G489D, S12P) were identified as "probably benign", and six (R725G, G620S, A56V, E463D, D394N, L338V) were identified as "probably damaging" according to the predictions made by PANTHER tools. The majority of the pixels on the strip were red, indicating that the gene changes may have dangerous consequences. These results highlight the need for more research to fully comprehend how these mutations affect the hic1 protein's function, which is essential for the emergence of different types of cancer. Conclusion The current research has provided us with essential information about how SNPs might be used as a diagnostic marker for cancer, given that SNPs may be candidates for cellular changes caused by mutations linked to cancer.

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

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

Investigation of pathogenic germline variants in gastric cancer and development of "GasCanBase" database

BACKGROUND

Gastric cancer, which is also known as stomach cancer, can be influenced by both germline and somatic mutations. Non-synonymous Single Nucleotide Polymorphisms (nsSNPs) in germline have long been reported to play a pivotal role in cancer progression.

AIM

The aim of this study is to examine the nsSNP in GC-associated genes. The study also aims to develop a database with extensive information regarding the nsSNPs in the GC-associated genes and their impacts.

METHODS AND RESULTS

A total of 34,588 nsSNPs from 1,493,460 SNPs of the 40 genes were extracted from the available SNP database. Drug binding and energy minimization were examined by molecular docking and YASARA. To validate the existence of the germline CDH1 gene mutation (rs34466743) in the isolated blood DNA of gastric cancer (GC) patients, polymerase chain reaction (PCR) and DNA sequencing were performed. According to the results of the gene network analysis, 17 genes may interact with other types of cancer. A total of 11,363 nsSNPs were detected within the 40 GC genes. Among these, 474 nsSNPs were predicted to be damaging and 40 to be the most damaging. The SNPs in domain regions were thought to be strong candidates that alter protein functions. Our findings proposed that most of the selected nsSNPs were within the domains or motif regions. Free Energy Deviation calculation of protein structure pointed toward noteworthy changes in the structure of each protein that can demolish its natural function. Subsequently, drug binding confirmed the structural variation and the ineffectiveness of the drug against the mutant model in individuals with these germline variants. Furthermore, in vitro analysis of the rs34466743 germline variant from the CDH1 gene confirmed the strength and robustness of the pipeline that could expand the somatic alteration for causing cancer. In addition, a comprehensive gastric cancer polymorphism database named "GasCanBase" was developed to make data available to researchers.

CONCLUSION

The findings of this study and the "GasCanBase" database may greatly contribute to our understanding of molecular epidemiology and the development of precise therapeutics for gastric cancer. GasCanBase is available at: https://www.gascanbase.com/.

Identification of a Novel Heterozygous Mutation in the EIF2B4 Gene Associated With Vanishing White Matter Disease

Vanishing white matter disease (VWM) is one of the most common childhood inherited leukoencephalopathies with autosomal recessive inheritance. Mutations in five genes, EIF2B1-5, have been identified as the major cause of VWM. In this study, a targeted gene capture sequencing panel comprising 160 known pathogenic genes associated with leukoencephalopathies was performed in a large Han Chinese family affected by adult-onset VWM, and a novel heterozygous missense mutation (c.1337G > A [p. R446H]) in EIF2B4 (NM_001034116.2) was detected. Further functional studies in HEK 293 cells showed dramatically reduced EIF2Bδ protein levels in the mutated group compared with the wild-type group. This study revealed that a heterozygous missense mutation (c.1337G > A [p. R446H]) in EIF2B4 was potentially associated with the adult-onset mild phenotype of VWM. In contrast to previous reports, autosomal dominant inheritance was also observed in adult-onset VWM.

Structural and Dynamic Investigation of non-synonymous variations in Renin-AGT complex revealed altered binding via hydrogen bonding network reprogramming to accelerate the hypertension pathway

Hypertension is one of the major issues worldwide and one of the main factors involved in heart and kidney failure. Angiotensinogen and renin are key components of the renin-angiotensin-aldosterone system (RAAS), which plays an indispensable role in hypertension. The aimed of this study to find out the non-synonymous mutations and structure-based mutation-function correlation in the Renin-AGT complex and reveal the most deleterious mutations to accelerated hypertension. In the current study, we employed computational modelling and molecular simulation approaches to demonstrate the impact of specific mutations in the REN-AGT interface in hypertension. Computational algorithms i.e. PhD-SNP, PolyPhen-1, MAPP, SIFT, SNAP, PredictSNP, PolyPhen-2, and PANTHER predicted 20 mutations as deleterious in AGT while only five mutations were conformed as deleterious in the Renin protein. Investigation of the bonding analysis revealed that two mutations S107L and V193F in Renin altered the hydrogen-bonding paradigm at the interface site. Furthermore, exploration of structural-dynamic behaviors demonstrated by that these mutations also increases the structural stability to regulate the expression of disease pathway. The flexibility index of each residues and structural compactness analysis further validated the findings by portraying the difference in the dynamic behavior in contrast to the wild type. Binding energy calculations based on molecular mechanics/generalized Born surface area (MM/GBSA) methods were used which further established the binding differences between the wild type, S107L, and V193F mutant variants. The total binding energy for wild type, S107L, and V193F were reported to be -27.79 kcal/mol, -47.72 kcal/mol, and -38.25 kcal/mol respectively. In conclusion, these two mutations increase the binding free energy alongside the docking score to enhance the binding between Renin and AGT to overexpress this pathway in a hypertension disease condition. Patients with these mutations may be screened for potential therapeutic intervention.

Computational and drug target analysis of functional single nucleotide polymorphisms associated with Haemoglobin Subunit Beta (HBB) gene

There is overwhelming evidence implicating Haemoglobin Subunit Beta (HBB) protein in the onset of beta thalassaemia. In this study for the first time, we used a combined SNP informatics and computer algorithms such as Neural network, Bayesian network, and Support Vector Machine to identify deleterious non-synonymous Single Nucleotide Polymorphisms (nsSNPs) present in the HBB gene. Our findings highlight three major mutation points (R31G, W38S, and Q128P) within the HBB gene sequence that have significant statistical and computational associations with the onset of beta thalassaemia. The dynamic simulation study revealed that R31G, W38S, and Q128P elicited high structural perturbation and instability, however, the wild type protein was considerably stable. Ten compounds with therapeutic potential against HBB were also predicted by structure-based virtual screening. Interestingly, the instability caused by the mutations was reversed upon binding to a ligand. This study has been able to predict potential deleterious mutants that can be further explored in the understanding of the pathological basis of beta thalassaemia and the design of tailored inhibitors.

The Spectrum of β-Thalassemia Mutations in Siirt Province, Southeastern Turkey

β-Thalassemia (β-thal) is the most common hereditary genetic blood disorder. The aims of this study were: (i) to determine the mutation types and the frequency of these mutations in β-thal patients to obtain the ethnic origins of the population in Siirt Province; (ii) to evaluate the pathogenicity of these mutations by performing in silico analysis; (iii) to reveal the genotype-phenotype correlation by comparing the clinical manifestation of our patients to the specific mutations in this population. This study included 34 patients (18 males and 16 females) with a mean age of 9.1 ± 3.6 years (range 3-16 years). All mutations were determined using sequence analysis methods, and the mutations were analyzed using bioinformatics tools. Thirteen different mutations were detected in the patients: IVI-I-110 (G>A) (HBB: c.93-21G>A) (38.9%); IVS-II-1 (G>A) (HBB: c.315_1G>A) (11.1%); -30 (T>A) (HBB: c.-80T>A) (9.25%) and IVS-I-1 (G>A) (HBB: c.92 + 1G>A) (9.25%), were the most common, and these mutations constituted 68.5% of the cases. Missense codon 6 (A>T) (HBB: c.20A>T) was not pathogenic; however, all the intronic mutations (IVS-I-1, IVS-I-110, IVS-II-1) and frameshift mutations [codon 44 (-C) (HBB: c.135delC) and codons 36/37 (-T) (HBB: c.112delT)] resulted in disease. These mutations can be used to determine the ethnic origin of the Siirt population and, in affected pregnant women, to develop prenatal strategies. A fatal phenotype can be identified by in silico analysis; however, mutations that are unknown prior to marriage, pregnancy, and childbirth or new mutations can be less accurately identified.

Computational analysis of high-risk SNPs in human CHK2 gene responsible for hereditary breast cancer: A functional and structural impact

Nowadays CHK2 mutation is studied frequently in hereditary breast and ovarian cancer patients in addition to BRCA1/BRCA2. CHK2 is a tumor suppressor gene that encodes a serine/threonine kinase, also involved in pathways such as DNA repair, cell cycle regulation and apoptosis in response to DNA damage. CHK2 is a well-studied moderate penetrance gene that correlates with third high risk susceptibility gene with an increased risk for breast cancer. Hence before planning large population study, it is better to scrutinize putative functional SNPs of CHK2 using different computational tools. In this study, we have used various computational approaches to identify nsSNPs which are deleterious to the structure and/or function of CHK2 protein that might be causing this disease. Computational analysis was performed by different in silico tools including SIFT, Align GVGD, SNAP-2, PROVEAN, Poly-Phen-2, PANTHER, PhD-SNP, MUpro, iPTREE-STAB, Consurf, InterPro, NCBI Conserved Domain Search tool, ModPred, SPARKS-X, RAMPAGE, Verify-3D, FT Site, COACH and PyMol. Out of 78 nsSNP of human CHK2 gene, seven nsSNPs were predicted functionally most significant SNPs. Among these seven nsSNP, p.Arg160Gly, p.Gly210Arg and p.Ser415Phe are highly conserved residues with conservation score of 9 and three nsSNP were predicted to be involved in post translational modification. The p.Arg160Gly and p.Gly210Arg may interfere in phosphopeptide binding site on FHA conserved domain. The p.Ser415Phe may interfere in formation of activation loop of protein-kinase domain and might interfere in interactions of CHK2 with ligand. The study concludes that mutation of serine to phenylalanine at position 415 is a major mutation in native CHK2 protein which might contribute to its malfunction, ultimately causing disease. This is the first comprehensive study, where CHK2 gene variants are analyzed using in silico tools hence it will be of great help while considering large scale studies and also in developing precision medicines related to these polymorphisms in the era of personalized medicine.

Structural prediction, whole exome sequencing and molecular dynamics simulation confirms p.G118D somatic mutation of PIK3CA as functionally important in breast cancer patients

To understand the structural and functional importance of PIK3CA somatic mutations, whole exome sequencing, molecular dynamics simulation techniques in combination with in silico prediction algorithms such as SIFT, PolyPhen, Provean and CADD were employed. Twenty out of eighty missense somatic mutations in PIK3CA gene were found to be pathogenic by all the four algorithms. Most recurrent mutations found were known hotspot PIK3CA mutations with known clinical significance like p.E545 K, p.E545A, p.E545 G and p.C420R. A missense mutation p.G118D was found to be recurrently mutated in 5 cases. Interestingly, this mutation was observed in one of the patients who underwent whole exome sequencing and was completely absent from the controls. To see the effect of this mutation on the structure of PIK3CA protein, molecular dynamics simulation was performed. By molecular dynamics approach, we have shown that p.G118D mutation deviated from the native structure which was supported by the decrease in the number of hydrogen bonds, difference in hydrogen bond distance and angle, difference in root mean square deviation between the native and the mutant structures.

Identification of deleterious SNPs and their effects on BCL11A, the master regulator of fetal hemoglobin expression

The B-cell lymphoma/leukemia 11A protein (encoded by BCL11A gene) is a key regulator of fetal-to-adult hemoglobin switching as seen in post-natal life. Although genetic polymorphisms like SNPs in BCL11A gene are expected to affect fetal hemoglobin (HbF) expression levels, yet their implications are poorly studied. This study utilizes a computational approach to identify the deleterious SNPs which may affect the structure and function of BCL11A protein. The study also generated a 3D structure of native and mutants. The analysis identified two SNPs in BCL11A as highly deleterious: N391K and C414S which are expected to affect structure and stability of the protein. According to conservation analysis, both residues N391 and C414 were identified as highly conserved. Additionally, post-translational modification sites were predicted at both sites. Ligand binding sites were also predicted in N391 and C414. Therefore, N391K and C414S in BCL11A can considered as important candidates to mediate HbF variation.

Homology modeling and in silico prediction of Ulcerative colitis associated polymorphisms of NOD1

Cytosolic pattern recognition receptors play key roles in innate immune response. Nucleotide binding and oligomerisation domain containing protein 1 (NOD1) belonging to the Nod-like receptor C (NLRC) sub-family of Nod-like receptors (NLRs) is important for detection and clearance of intra-cellular Gram negative bacteria. NOD1 is involved in activation of pro-inflammatory pathways. Limited structural data is available for NOD1. Using different templates for each domain of NOD1, we determined the full-length homology model of NOD1. ADP binding amino acids within the nucleotide binding domain (NBD) of NOD1 were also predicted. Key residues in inter-domain interaction were identified by sequence comparison with Oryctolagus cuniculus NOD2, a related protein. Interactions between NBD and winged helix domain (WHD) were found to be conserved in NOD1. Functional and structural effect of single nucleotide polymorphisms within the NOD1 NBD domain associated with susceptibility risk to Ulcerative colitis (UC), an inflammatory disorder of the colon was evaluated by in silico studies. Mutations W219R and L349P were predicted to be damaging and disease associated by prediction programs SIFT, PolyPhen2, PANTHER, SNP&GO, PhD SNP and SNAP2. We further validated the effect of W219R and L349P mutation on NOD1 function in vitro. Elevated mRNA expression of pro-inflammatory cytokines IL8 and IL-1β was seen as compared to the wild type NOD1 in intestinal epithelial cell line HT29 when stimulated with NOD1 ligand. Thus, these mutations may indeed have a bearing on pathogenesis of inflammation during UC.

In silico approach to identify non-synonymous SNPs in human obesity related gene, MC3R (melanocortin-3-receptor)

The melanocortin-3-receptor (MC3R) is a novel gene candidate for human obesity, which involved in controlling the energy homeostasis and food intake behavior. The main aim behind this work is to investigate the potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in obesity related gene MC3R by using six computational tools viz., PolyPhen, I-Mutant, PROVEAN, SIFT, PANTHER and PhD-SNP. In our study, we predicted eight nsSNPs i.e., rs74315393 (Ile146Asn), rs368205448 (Asp121Tyr), rs143321797 (Phe45Ser), rs17847261 (Cys274Ser), rs144166442 (Pro257His), rs370533946 (Leu224Pro), rs371354428 (Pro72Leu) and rs373708098 (Gly249Ser) found to be potentially deleterious. The functional impact of three nsSNPs i.e., rs74315393, rs368205448 and rs143321797 have already been validated experimentally in the context of human obesity. Moreover, Homology modeling and structural analysis were carried out for already experimentally validated nsSNPs i.e., rs74315393, rs368205448 and rs143321797 to check the stability of predicted models. The mutant models showed higher energy and RMSD (Root mean square deviation) values. In addition, FTSite server predicted one nsSNP i.e., rs368205448 (Asp121Tyr) out of eight identified nsSNPs found in the MC3R protein binding site. Thus, the present computational study may suggest that predicted nsSNPs possibly be a better drug target and contribute to the treatment and better understanding of human obesity.

Bioinformatics Approach for Prediction of Functional Coding/Noncoding Simple Polymorphisms (SNPs/Indels) in Human BRAF Gene

This study was carried out for Homo sapiens single variation (SNPs/Indels) in BRAF gene through coding/non-coding regions. Variants data was obtained from database of SNP even last update of November, 2015. Many bioinformatics tools were used to identify functional SNPs and indels in proteins functions, structures and expressions. Results shown, for coding polymorphisms, 111 SNPs predicted as highly damaging and six other were less. For UTRs, showed five SNPs and one indel were altered in micro RNAs binding sites (3' UTR), furthermore nil SNP or indel have functional altered in transcription factor binding sites (5' UTR). In addition for 5'/3' splice sites, analysis showed that one SNP within 5' splice site and one Indel in 3' splice site showed potential alteration of splicing. In conclude these previous functional identified SNPs and indels could lead to gene alteration, which may be directly or indirectly contribute to the occurrence of many diseases.

Identification of Deleterious Mutations in Myostatin Gene of Rohu Carp (Labeo rohita) Using Modeling and Molecular Dynamic Simulation Approaches

The myostatin (MSTN) is a known negative growth regulator of skeletal muscle. The mutated myostatin showed a double-muscular phenotype having a positive significance for the farmed animals. Consequently, adequate information is not available in the teleosts, including farmed rohu carp, Labeo rohita. In the absence of experimental evidence, computational algorithms were utilized in predicting the impact of point mutation of rohu myostatin, especially its structural and functional relationships. The four mutations were generated at different positions (p.D76A, p.Q204P, p.C312Y, and p.D313A) of MSTN protein of rohu. The impacts of each mutant were analyzed using SIFT, I-Mutant 2.0, PANTHER, and PROVEAN, wherein two substitutions (p.D76A and p.Q204P) were predicted as deleterious. The comparative structural analysis of each mutant protein with the native was explored using 3D modeling as well as molecular-dynamic simulation techniques. The simulation showed altered dynamic behaviors concerning RMSD and RMSF, for either p.D76A or p.Q204P substitution, when compared with the native counterpart. Interestingly, incorporated two mutations imposed a significant negative impact on protein structure and stability. The present study provided the first-hand information in identifying possible amino acids, where mutations could be incorporated into MSTN gene of rohu carp including other carps for undertaking further in vivo studies.

Molecular Dynamics: New Frontier in Personalized Medicine

The field of drug discovery has witnessed infinite development over the last decade with the demand for discovery of novel efficient lead compounds. Although the development of novel compounds in this field has seen large failure, a breakthrough in this area might be the establishment of personalized medicine. The trend of personalized medicine has shown stupendous growth being a hot topic after the successful completion of Human Genome Project and 1000 genomes pilot project. Genomic variant such as SNPs play a vital role with respect to inter individual's disease susceptibility and drug response. Hence, identification of such genetic variants has to be performed before administration of a drug. This process requires high-end techniques to understand the complexity of the molecules which might bring an insight to understand the compounds at their molecular level. To sustenance this, field of bioinformatics plays a crucial role in revealing the molecular mechanism of the mutation and thereby designing a drug for an individual in fast and affordable manner. High-end computational methods, such as molecular dynamics (MD) simulation has proved to be a constitutive approach to detecting the minor changes associated with an SNP for better understanding of the structural and functional relationship. The parameters used in molecular dynamic simulation elucidate different properties of a macromolecule, such as protein stability and flexibility. MD along with docking analysis can reveal the synergetic effect of an SNP in protein-ligand interaction and provides a foundation for designing a particular drug molecule for an individual. This compelling application of computational power and the advent of other technologies have paved a promising way toward personalized medicine. In this in-depth review, we tried to highlight the different wings of MD toward personalized medicine.

Functional and Structural Consequences of Damaging Single Nucleotide Polymorphisms in Human Prostate Cancer Predisposition Gene RNASEL

A commonly diagnosed cancer, prostate cancer (PrCa), is being regulated by the gene RNASEL previously known as PRCA1 codes for ribonuclease L which is an integral part of interferon regulated system that mediates antiviral and antiproliferative role of the interferons. Both somatic and germline mutations have been implicated to cause prostate cancer. With an array of available Single Nucleotide Polymorphism data on dbSNP this study is designed to sort out functional SNPs in RNASEL by implementing different authentic computational tools such as SIFT, PolyPhen, SNPs&GO, Fathmm, ConSurf, UTRScan, PDBsum, Tm-Align, I-Mutant, and Project HOPE for functional and structural assessment, solvent accessibility, molecular dynamics, and energy minimization study. Among 794 RNASEL SNP entries 124 SNPs were found nonsynonymous from which SIFT predicted 13 nsSNPs as nontolerable whereas PolyPhen-2 predicted 28. SNPs found on the 3' and 5' UTR were also assessed. By analyzing six tools having different perspectives an aggregate result was produced where nine nsSNPs were found to be most likely to exert deleterious effect. 3D models of mutated proteins were generated to determine the functional and structural effect of the mutations on ribonuclease L. The initial findings were reinforced by the results from I-Mutant and Project HOPE as these tools predicted significant structural and functional instability of the mutated proteins. Expasy-ProSit tool defined the mutations to be situated in the functional domains of the protein. Considering previous analysis this study revealed a conclusive result deducing the available SNP data on the database by identifying the most damaging three nsSNP rs151296858 (G59S), rs145415894 (A276V), and rs35896902 (R592H). As such studies involving polymorphisms of RNASEL were none to be found, the results of the current study would certainly be helpful in future prospects concerning prostate cancer in males.

In silico analysis of consequences of non-synonymous SNPs of Slc11a2 gene in Indian bovines

The aim of our study was to analyze the consequences of non-synonymous SNPs in Slc11a2 gene using bioinformatic tools. There is a current need of efficient bioinformatic tools for in-depth analysis of data generated by the next generation sequencing technologies. SNPs are known to play an imperative role in understanding the genetic basis of many genetic diseases. Slc11a2 is one of the major metal transporter families in mammals and plays a critical role in host defenses. In this study, we performed a comprehensive analysis of the impact of all non-synonymous SNPs in this gene using multiple tools like SIFT, PROVEAN, I-Mutant and PANTHER. Among the total 124 SNPs obtained from amplicon sequencing of Slc11a2 gene by Ion Torrent PGM involving 10 individuals of Gir cattle and Murrah buffalo each, we found 22 non-synonymous. Comparing the prediction of these 4 methods, 5 nsSNPs (G369R, Y374C, A377V, Q385H and N492S) were identified as deleterious. In addition, while tested out for polar interactions with other amino acids in the protein, from above 5, Y374C, Q385H and N492S showed a change in interaction pattern and further confirmed by an increase in total energy after energy minimizations in case of mutant protein compared to the native.

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22 nsSNPs were predicted to decrease the stability of protein based on I-Mutant.

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From these SNPs, 5 was identified as deleterious by SIFT, PROVEAN, and PANTHER.

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Y374C, Q385H and N492S were found to be damaging.

Analysis of consequences of non-synonymous SNP in feed conversion ratio associated TGF-β receptor type 3 gene in chicken

The recent advances in high throughput sequencing technology accelerate possible ways for the study of genome wide variation in several organisms and associated consequences. In the present study, mutations in TGFBR3 showing significant association with FCR trait in chicken during exome sequencing were further analyzed. Out of four SNPs, one nsSNP p.Val451Leu was found in the coding region of TGFBR3. In silico tools such as SnpSift and PANTHER predicted it as deleterious (0.04) and to be tolerated, respectively, while I-Mutant revealed that protein stability decreased. The TGFBR3 I-TASSER model has a C-score of 0.85, which was validated using PROCHECK. Based on MD simulation, mutant protein structure deviated from native with RMSD 0.08 Å due to change in the H-bonding distances of mutant residue. The docking of TGFBR3 with interacting TGFBR2 inferred that mutant required more global energy. Therefore, the present study will provide useful information about functional SNPs that have an impact on FCR traits.

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Investigated functional nsSNP p.Val451Leu (rs312979494) in feed conversion ratio (FCR) associated TGFBR3 of chicken

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Computational tools (SIFT and I-Mutant 2.0) predicted that this nsSNP was deleterious.

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Mutant structure of TGFBR3 showed high energies and RMS deviations compared to native using MD simulation.

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Molecular docking of TGFBR3 with interacting protein TGFBR2 showed an increase in global energy of mutant compared to native.

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We have predicted that functional SNP has an impact on TGFBR3 of chicken and thus can be treated as candidate SNP in screening.

First comprehensive in silico analysis of the functional and structural consequences of SNPs in human GalNAc-T1 gene

GalNAc-T1, a key candidate of GalNac-transferases genes family that is involved in mucin-type O-linked glycosylation pathway, is expressed in most biological tissues and cell types. Despite the reported association of GalNAc-T1 gene mutations with human disease susceptibility, the comprehensive computational analysis of coding, noncoding and regulatory SNPs, and their functional impacts on protein level, still remains unknown. Therefore, sequence- and structure-based computational tools were employed to screen the entire listed coding SNPs of GalNAc-T1 gene in order to identify and characterize them. Our concordant in silico analysis by SIFT, PolyPhen-2, PANTHER-cSNP, and SNPeffect tools, identified the potential nsSNPs (S143P, G258V, and Y414D variants) from 18 nsSNPs of GalNAc-T1. Additionally, 2 regulatory SNPs (rs72964406 and #x26; rs34304568) were also identified in GalNAc-T1 by using FastSNP tool. Using multiple computational approaches, we have systematically classified the functional mutations in regulatory and coding regions that can modify expression and function of GalNAc-T1 enzyme. These genetic variants can further assist in better understanding the wide range of disease susceptibility associated with the mucin-based cell signalling and pathogenic binding, and may help to develop novel therapeutic elements for associated diseases.

Clinically significant missense variants in human GALNT3, GALNT8, GALNT12, and GALNT13 genes: intriguing in silico findings

Aberrant glycosylation by N-acetylgalactosaminyl transferases (GALNTs) is a well-described pathological alteration that is widespread in hereditary diseases, prominently including human cancers, familial tumoral calcinosis and hyperostosis-hyperphosphatemia. In this study, we integrated different computational tools to perform the in silico analysis of clinically significant mutations (nsSNPs/single amino acid change) at both functional and structural levels, found in human GALNT3, GALNT8, GALNT12, and GALNT13 genes. From function and structure based insights, mutations encoding R162Q, T359K, C574G, G359D, R297W, D303N, Y396C, and D313N substitutions were concordantly predicted highly deleterious for relevant GALNTs proteins. From intriguing findings, T359K-GALNT3 was simulated with high contribution for disease susceptibility (tumor calcinosis) as compared to its partner variant T272K (Ichikawa et al. [2006] J. Clin. Endocrinol. Metab. 91:4472-4475). Similarly, the prediction of high damaging behavior, evolutionary conservation and structural destabilization for C574G were proposed as major contributing factors to regulate metabolic disorder underlying tumor calcinosis and hyperostosis-hyperphosphatemia syndrome. In case of R297W-GALNT12, prediction of highly deleterious effect and disruption in ionic interactions were anticipated with reduction in enzymatic activity, associated with bilateral breast cancer and primary colorectal cancers. The second GALNT12 mutation (D303N)-known splice variant-was predicted with disease severity as a result of decrease in charge density and buried behavior neighboring the catalytic B domain. In the lack of adequate in silico data about systematic characterization of clinically significant mutations in GALNTs genes, current study can be used as a significant tool to interpret the role of GALNTs reaction chemistry in disease-association risks in body.

SITDEM: a simulation tool for disease/endpoint models of association studies based on single nucleotide polymorphism genotypes

The association analysis between single nucleotide polymorphisms (SNPs) and disease or endpoint in genome-wide association studies (GWAS) has been considered as a powerful strategy for investigating genetic susceptibility and for identifying significant biomarkers. The statistical analysis approaches with simulated data have been widely used to review experimental designs and performance measurements. In recent years, a number of authors have proposed methods for the simulation of biological data in the genomic field. However, these methods use large-scale genomic data as a reference to simulate experiments, which may limit the use of the methods in the case where the data in specific studies are not available. Few methods use experimental results or observed parameters for simulation. The goal of this study is to develop a Web application called SITDEM to simulate disease/endpoint models in three different approaches based on only parameters observed in GWAS. In our simulation, a key task is to compute the probability of genotypes. Based on that, we randomly sample simulation data. Simulation results are shown as a function of p-value against odds ratio or relative risk of a SNP in dominant and recessive models. Our simulation results show the potential of SITDEM for simulating genotype data. SITDEM could be particularly useful for investigating the relationship among observed parameters for target SNPs and for estimating the number of variables (SNPs) required to result in significant p-values in multiple comparisons. The proposed simulation tool is freely available at http://www.snpmodel.com.

Polymorphism of the multiple hemoglobins in blood clam Tegillarca granosa and its association with disease resistance to Vibrio parahaemolyticus

Hemoglobin (Hb) is the major protein component of erythrocytes in animals with red blood, but it can serve additional functions beyond the transport of oxygen. In this study, we identified polymorphism in the blood clam Tegillarca granosa Hb (Tg-Hb) genes and investigated the association of this polymorphism with resistance/susceptibility to Vibrio parahaemolyticus. Analysis of the 540 sequences revealed 28 SNPs in the coding region of three Tg-Hbs, corresponding to about one SNP per 48 bp. Three SNPS: HbIIA-E2-146, HbIIB-E2-23, HbIIB-E2-121 showed a significant association with resistance/susceptibility to V. parahaemolyticus (P < 0.05). To further demonstrate that three significant SNPs of Tg-Hbs is associated with resistance of clams to V. parahaemolyticus, SNPs were genotyped in V. parahaemolyticus resistant strain clams and the wild base population from which this strain was derived. The results indicated that the nonsynonymous mutation T allele at HbIIA-E2-146 and A allele at HbIIB-E2-23 are associated with V. parahaemolyticus resistance in the blood clam, and its association with disease resistance may be due to its cause changes in amino acid sequences to a functional polymorphism. Together with previous bacterial challenge study, these results provides direct evidence that variation at HbIIA-E2-146 and HbIIB-E2-23 are associated with disease resistance in the blood clam, and these two polymorphic loci could be potential gene markers for the future molecular selection of strains that are resistant to diseases caused by V. parahaemolyticus.

Systematic investigation of predicted effect of nonsynonymous SNPs in human prion protein gene: a molecular modeling and molecular dynamics study

Nonsynonymous mutations in the human prion protein (HuPrP) gene contribute to the conversion of HuPrP(C) to HuPrP(Sc) and amyloid formation which in turn leads to prion diseases such as familial Creutzfeldt-Jakob disease and Gerstmann-Straussler-Scheinker disease. In order to better understand and predict the role of HuPrP mutations, we developed the following procedure: first, we consulted the Human Genome Variation database and dbSNP databases, and we reviewed literature for the retrieval of aggregation-related nsSNPs of the HuPrP gene. Next, we used three different methods - Polymorphism Phenotyping (PolyPhen), PANTHER, and Auto-Mute - to predict the effect of nsSNPs on the phenotype. We compared the predictions against experimentally reported effects of these nsSNPs to evaluate the accuracy of the three methods: PolyPhen predicted 17 out of 22 nsSNPs as "probably damaging" or "possibly damaging"; PANTHER predicted 8 out of 22 nsSNPs as "Deleterious"; and Auto-Mute predicted 9 out of 20 nsSNPs as "Disease". Finally, structural analyses of the native protein against mutated models were investigated using molecular modeling and molecular dynamics (MD) simulation methods. In addition to comparing predictor methods, our results show the applicability of our procedure for the prediction of damaging nsSNPs. Our study also elucidates the obvious relationship between predicted values of aggregation-related nsSNPs in HuPrP gene and molecular modeling and MD simulations results. In conclusion, this procedure would enable researchers to select outstanding candidates for extensive MD simulations in order to decipher more details of HuPrP aggregation. An animated interactive 3D complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:34.

Self-catalytic DNA depurination underlies human β-globin gene mutations at codon 6 that cause anemias and thalassemias

The human β-globin gene contains an 18-nucleotide coding strand sequence centered at codon 6 and capable of forming a stem-loop structure that can self-catalyze depurination of the 5'G residue of that codon. The resultant apurinic lesion is subject to error-prone repair, consistent with the occurrence about this codon of mutations responsible for 6 anemias and β-thalassemias and additional substitutions without clinical consequences. The 4-residue loop of this stem-loop-forming sequence shows the highest incidence of mutation across the gene. The loop and first stem base pair-forming residues appeared early in the mammalian clade. The other stem-forming segments evolved more recently among primates, thereby conferring self-depurination capacity at codon 6. These observations indicate a conserved molecular mechanism leading to β-globin variants underlying phenotypic diversity and disease.