Identification of functional SNPs in BARD1 gene and in silico analysis of damaging SNPs: based on data procured from dbSNP database

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.

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/.

Genome-wide in silico analysis leads to identification of deleterious L290V mutation in RBBP5 gene in Bos indicus

Genome-wide deleterious mutations were identified in zebu cattle (Bos indicus) using in silico approach. The ddRAD sequence data of Sahiwal cattle were annotated and aligned with the cattle reference genome (ARS-UCD1.2). A total of 279,383 SNPs were identified at Read Depth10, which were further filtered to 692 missense SNPs. These SNPs were further analyzed, for functional consequences, by using Variant Effect Predictor, PolyPhen, PROVEAN, and PANTHER tools. A total of 18 SNPs, were finally identified as deleterious, and among these, 12 SNPs were mapped on nine different genes. ERRAT, ProSA-web, Project HOPE, TM-Align, and YASSARA tools, further confirmed the protein malfunctioning of one missense (L290V) mutation of Retinoblastoma binding protein-5 (RBBP5) gene, transcribing a cell cycle regulatory protein and associated with Retinoblastoma in human. This derived bioinformatics pipeline may be useful for preliminarily identifying the deleterious DNA mutations in livestock, specifically in absence of any genetic disease records.

Unraveling Extremely Damaging IRAK4 Variants and Their Potential Implications for IRAK4 Inhibitor Efficacy

Interleukin-1-receptor-associated kinase 4 (IRAK4) possesses a crucial function in the toll-like receptor (TLR) signaling pathway, and the dysfunction of this molecule could lead to various infectious and immune-related diseases in addition to cancers. IRAK4 genetic variants have been linked to various types of diseases. Therefore, we conducted a comprehensive analysis to recognize the missense variants with the most damaging impacts on IRAK4 with the employment of diverse bioinformatics tools to study single-nucleotide polymorphisms' effects on function, stability, secondary structures, and 3D structure. The residues' location on the protein domain and their conservation status were investigated as well. Moreover, docking tools along with structural biology were engaged in analyzing the SNPs' effects on one of the developed IRAK4 inhibitors. By analyzing IRAK4 gene SNPs, the analysis distinguished ten variants as the most detrimental missense variants. All variants were situated in highly conserved positions on an important protein domain. L318S and L318F mutations were linked to changes in IRAK4 secondary structures. Eight SNPs were revealed to have a decreasing effect on the stability of IRAK4 via both I-Mutant 2.0 and Mu-Pro tools, while Mu-Pro tool identified a decreasing effect for the G198E SNP. In addition, detrimental effects on the 3D structure of IRAK4 were also discovered for the selected variants. Molecular modeling studies highlighted the detrimental impact of these identified SNP mutant residues on the druggability of the IRAK4 ATP-binding site towards the known target inhibitor, HG-12-6, as compared to the native protein. The loss of important ligand residue-wise contacts, altered protein global flexibility, increased steric clashes, and even electronic penalties at the ligand-binding site interfaces were all suggested to be associated with SNP models for hampering the HG-12-6 affinity towards IRAK4 target protein. This given model lays the foundation for the better prediction of various disorders relevant to IRAK4 malfunction and sheds light on the impact of deleterious IRAK4 variants on IRAK4 inhibitor efficacy.

The association between single nucleotide polymorphisms and ovarian cancer risk: A systematic review and network meta-analysis

BACKGROUND

The relationship between single nucleotide polymorphisms (SNPs) and ovarian cancer (OC) risk remains controversial. This systematic review and network meta-analysis was aimed to determine the association between SNPs and OC risk.

METHODS

Several databases (PubMed, EMBASE, China National Knowledge Infrastructure, Wanfang databases, China Science and Technology Journal Database, and China Biology Medicine disc) were searched to summarize the association between SNPs and OC published throughout April 2021. Direct meta-analysis was used to identify SNPs that could predict the incidence of OC. Ranking probability resulting from network meta-analysis and the Thakkinstian's algorithm was used to select the most appropriate gene model. The false positive report probability (FPRP) and Venice criteria were further tested for credible relationships. Subgroup analysis was also carried out to explore whether there are racial differences.

RESULTS

A total of 63 genes and 92 SNPs were included in our study after careful consideration. Fok1 rs2228570 is likely a dominant risk factor for the development of OC compared to other selected genes. The dominant gene model of Fok1 rs2228570 (pooled OR = 1.158, 95% CI: 1.068-1.256) was determined to be the most suitable model with a FPRP <0.2 and moderate credibility.

CONCLUSIONS

Fok1 rs2228570 is closely linked to OC risk, and the dominant gene model is likely the most appropriate model for estimating OC susceptibility.

HBD-2 variants and SARS-CoV-2: New insights into inter-individual susceptibility

Background

A deep understanding of the causes of liability to SARS-CoV-2 is essential to develop new diagnostic tests and therapeutics against this serious virus in order to overcome this pandemic completely. In the light of the discovered role of antimicrobial peptides [such as human b-defensin-2 (hBD-2) and cathelicidin LL-37] in the defense against SARS-CoV-2, it became important to identify the damaging missense mutations in the genes of these molecules and study their role in the pathogenesis of COVID-19.

Methods

We conducted a comprehensive analysis with multiple in silico approaches to identify the damaging missense SNPs for hBD-2 and LL-37; moreover, we applied docking methods and molecular dynamics analysis to study the impact of the filtered mutations.

Results

The comprehensive analysis reveals the presence of three damaging SNPs in hBD-2; these SNPs were predicted to decrease the stability of hBD-2 with a damaging impact on hBD-2 structure as well. G51D and C53G mutations were located in highly conserved positions and were associated with differences in the secondary structures of hBD-2. Docking-coupled molecular dynamics simulation analysis revealed compromised binding affinity for hBD-2 SNPs towards the SARS-CoV-2 spike domain. Different protein-protein binding profiles for hBD-2 SNPs, in relation to their native form, were guided through residue-wise levels and differential adopted conformation/orientation.

Conclusions

The presented model paves the way for identifying patients prone to COVID-19 in a way that would guide the personalization of both the diagnostic and management protocols for this serious disease.

A comprehensive in silico analysis of the deleterious nonsynonymous SNPs of human FOXP2 protein

FOXP2 encodes the forkhead transcription factor that plays a significant role in language development. Single nucleotide polymorphisms in FOXP2 have been linked to speech- language disorder, autism, cancer and schizophrenia. So, scrutinizing the functional SNPs to better understand their association in disease is an uphill task. The purpose of the current study was to identify the missense SNPs which have detrimental structural and functional effects on the FOXP2 protein. Multiple computational tools were employed to investigate the deleterious role of non-synonymous SNPs. Five variants as Y531H, L558P, R536G and R553C were found to be associated with diseases and located at the forkhead domain of the FOXP2 protein. Molecular docking analysis of FOXP2 DNA binding domain with its most common target sequence 5’-CAAATT-3’ predicted that R553C and L558P mutant variants destabilize protein structure by changing protein-DNA interface interactions and disruption of hydrogen bonds that may reduce the specificity and affinity of the binding. Further experimental investigations may need to verify whether this kind of structural and functional variations dysregulate protein activities and induce formation of disease.

Computational Insights into the Structural and Functional Impacts of nsSNPs of Bone Morphogenetic Proteins

BMPs (bone morphogenetic proteins) are multipurpose (transforming growth factor)TGF-superfamily released cytokines. These glycoproteins, acting as disulfide-linked homo- or heterodimers, are highly potent regulators of bone and cartilage production and repair, cell proliferation throughout embryonic development, and bone homeostasis in the adults. Due to the fact that genetic variation might influence structural functions, this study is aimed to determine the pathogenic effect of nonsynonymous single-nucleotide polymorphisms (nsSNPs) in BMP genes. The implications of these variations, investigated using computational analysis and molecular models of the mature TGF-β domain, revealed the impact of modifications on the function of BMP protein. The three-dimensional (3D) structure analysis was performed on the nsSNP Y316S, V386G, E387G, C389G, and C391G nsSNP in the TGF-β domain of chicken BMP2 and H344P, S347P, V357A nsSNP in the TGF-β domain of chicken BMP4 protein that was anticipated to be harmful and of high risk. The ability of the proteins to perform variety of tasks interact with other molecules depends on their tertiary structural composition. The current analysis revealed the four most damaging variants (Y316S, V386G, E387G, C389G, and C391G), highly conserved and functional and are located in the TGF-beta domain of BMP2 and BMP4. The amino acid substitutions E387G, C389G, and C391G are discovered in the binding region. It was observed that the mutations in the TGF-beta domain caused significant changes in its structural organization including the substrate binding sites. Current findings will assist future research focused on the role of these variants in BMP function loss and their role in skeletal disorders, and this will possibly help to develop practical strategies for treating bone-related conditions.

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

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

Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability

Genetic polymorphisms in DNA damage repair and tumor suppressor genes have been associated with increasing the risk of several types of cancer. Analyses of putative functional single nucleotide polymorphisms (SNP) in such genes can greatly improve human health by guiding choice of therapeutics. In this study, we selected nine genes responsible for various cancer types for gene enrichment analysis and found that BRCA1, ATM, and TP53 were more enriched in connectivity. Therefore, we used different computational algorithms to classify the nonsynonymous SNPs which are deleterious to the structure and/or function of these three proteins. The present study showed that the major pathogenic variants (V1687G and V1736G of BRCA1, I2865T and V2906A of ATM, V216G and L194H of TP53) might have a greater impact on the destabilization of the proteins. To stabilize the high-risk SNPs, we performed mutation site-specific molecular docking analysis and validated using molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) studies. Additionally, SNPs of untranslated regions of these genes affecting miRNA binding were characterized. Hence, this study will assist in developing precision medicines for cancer types related to these polymorphisms.

In silico analysis of nonsynonymous single-nucleotide polymorphisms (nsSNPs) of the SMPX gene

Mutations in the SMPX gene can disrupt the regular activity of the SMPX protein, which is involved in the hearing process. Recent reports showing a link between nonsynonymous single-nucleotide polymorphisms (nsSNPs) in SMPX and hearing loss, thus classifying deleterious SNPs in SMPX will be an uphill task before designing a more extensive population study. In this study, damaging nsSNPs of SMPX from the dbSNP database were identified by using 13 bioinformatics tools. Initially, the impact of nsSNPs in the SMPX gene were evaluated through different in silico predictors; and the deleterious convergent changes were analyzed by energy-minimization-guided residual network analysis. In addition, the pathogenic effects of mutations in SMPX-mediated protein-protein interactions were also characterized by structural modeling and binding energy calculations. A total of four mutations (N19D, A29T, K54N, and S71L) were found to be highly deleterious by all the tools, which are located at highly conserved regions. Furthermore, all four mutants showed structural alterations, and the communities of amino acids for mutant proteins were readily changed, compared to the wild-type. Among them, A29T (rs772775896) was revealed as the most damaging nsSNP, which caused significant structural deviation of the SMPX protein, as a result reducing the binding affinity to other functional partners. These findings reflect the computational insights into the deleterious role of nsSNPs in SMPX, which might be helpful for subjecting wet-lab confirmatory analysis.

Screening and insilico analysis of deleterious nsSNPs (missense) in human CSF3 for their effects on protein structure, stability and function

Human granulocyte colony stimulating factor (hG-CSF), known as CSF3, plays an important role in the growth, differentiation, proliferation, survival, and activation of the granulocyte cell lineage such as neutrophils and their precursors. Functional reduction in native CSF3 protein results in reduced proliferation and activation of neutrophils and leads to neutropenia. Single nucleotide polymorphisms (SNPs) in the CSF3 gene may have deleterious effects on the CSF3 protein function. This study was undertaken to find the functional SNPs in the human CSF3 gene. Results suggest that 18.9% of all the SNPs in the dbSNP database for CSF3 gene were present in the coding region. Out of 59 non-synonymous SNPs (nsSNPs), 26 nsSNPs were predicted to be non-tolerable by SIFT whereas 18 and 7 nsSNPs were predicted as probably damaging and possibly damaging, respectively by PolyPhen. Among this 31 nsSNPs, 16 nsSNPs were identified to be potentially deleterious by PANTHER server, and 4 nsSNPs were found to be neutral by PROVEAN. SNPAnalyzer predicted 7 nsSNPs to be neutral phenotype and the remaining 24 nsSNPs to be associated with diseases. Among the predicted nsSNPs, rs144408123, rs144408123, rs145136406, rs145311241, rs373191696, rs762945096, rs763688260, rs767572172, rs775326370, rs777777864, rs777983866, rs781596455, rs139072004, rs757612684, rs772911210, rs139072004, rs746634544, rs749993200, rs763426127, rs772466210 were identified as deleterious and potentially damaging. I-Mutant analysis revealed that th 20 nsSNPs were important for protein stability of CSF3. Therefore, th 20 nsSNPs may be used for the wider population-based genetic studies and also should be taken into account while engineering the recombinant CSF3 protein for clinical use.

Functional Polymorphisms in BARD1 Association with Neuroblastoma in a regional Han Chinese Population

Neuroblastoma (NB) is a sympathetic nervous system cancer for children, occupying approximately 15% of pediatric oncology deaths. BARD1, a tumor suppressor, is essential for genome stability by interaction with BRCA1. Here, we performed a systematic investigation for the association between SNPs in BARD1 and the risk of NB in Chinese population. After SNP screening in BARD1 gene, we performed case-control study of eleven selected SNPs in BARD1 with 339 NB patients and 778 cancer-free controls. The OR and 95% CI of these candidate SNPs were computed by logistic regression. After adjusted gender and age, seven out of eleven SNPs in BARD1 were significant associated with the risk of NB, including one SNP in 5'-UTR (rs17489363 G > A), two SNPs in exon (rs2229571 G > C and rs3738888 C > T), and four SNPs in intron (rs3768716 A > G, rs6435862 T > G, rs3768707 C > T and rs17487792 C > T). When stratified by the INPC, primary tumor site and the INSS, these seven SNPs were significant associated with GNB/NB, stage III/IV and adrenal origin of NB. Dual-luciferase reporter assay showed rs17489363 A allele-containing haplotypes (TAC, CAC, TAG and CAG), composed with rs34732883 T > C, and rs1129804 C > G, dramatically reduced the transcriptional activity of reporter gene. The major of our study showed that seven SNPs of BARD1 associated with increased NB risk in Chinese population, and four haplotypes could reduce transcription activity of BARD1.

KoVariome: Korean National Standard Reference Variome database of whole genomes with comprehensive SNV, indel, CNV, and SV analyses

High-coverage whole-genome sequencing data of a single ethnicity can provide a useful catalogue of population-specific genetic variations, and provides a critical resource that can be used to more accurately identify pathogenic genetic variants. We report a comprehensive analysis of the Korean population, and present the Korean National Standard Reference Variome (KoVariome). As a part of the Korean Personal Genome Project (KPGP), we constructed the KoVariome database using 5.5 terabases of whole genome sequence data from 50 healthy Korean individuals in order to characterize the benign ethnicity-relevant genetic variation present in the Korean population. In total, KoVariome includes 12.7M single-nucleotide variants (SNVs), 1.7M short insertions and deletions (indels), 4K structural variations (SVs), and 3.6K copy number variations (CNVs). Among them, 2.4M (19%) SNVs and 0.4M (24%) indels were identified as novel. We also discovered selective enrichment of 3.8M SNVs and 0.5M indels in Korean individuals, which were used to filter out 1,271 coding-SNVs not originally removed from the 1,000 Genomes Project when prioritizing disease-causing variants. KoVariome health records were used to identify novel disease-causing variants in the Korean population, demonstrating the value of high-quality ethnic variation databases for the accurate interpretation of individual genomes and the precise characterization of genetic variations.

In silico screening, molecular docking, and molecular dynamics studies of SNP-derived human P5CR mutants

Pyrroline-5-carboxylate reductase (P5CR) encoded by PYCR1 gene is a housekeeping enzyme that catalyzes the reduction of P5C to proline using NAD(P)H as the cofactor. In this study, we used in silico approaches to examine the role of nonsynonymous single-nucleotide polymorphisms in the PYCR1 gene and their putative functions in the pathogenesis of Cutis Laxa. Among the 348 identified SNPs, 15 were predicted to be potentially damaging by both SIFT and PolyPhen tools; of them two SNP-derived mutations, R119G and G206W, have been previously reported to correlate with Cutis Laxa. These two mutations were therefore selected to be mapped to the wild-type (WT) P5CR structure for further structural and functional analyses. The results of comparative computational analyses using I-Mutant and Autodock reveal reductions in both stability and cofactor binding affinity of these two mutants. Comparative molecular dynamics (MD) simulations were performed to evaluate the changes in dynamic properties of P5CR upon mutations. The results reveal that the two mutations enhance the rigidity of P5CR structure, especially that of cofactor binding site, which could result in decreased kinetics of cofactor entrance and egress. Comparison between the structural properties of the WT and mutants during MD simulations shows that the enhanced rigidity of mutants results most likely from the increased number of inter-atomic interactions and the decreased number of dynamic hydrogen bonds. Our study provides novel insight into the deleterious effects of the R119G and G206W mutations on P5CR, and sheds light on the mechanisms by which these mutations mediate Cutis Laxa.

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 SNP analysis of the breast cancer antigen NY-BR-1

Background

Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and metastatic disease. The novel breast cancer associated antigen NY-BR-1 was identified by SEREX analysis and is expressed in the majority (>70%) of breast tumors as well as metastases, in normal breast tissue, in testis and occasionally in prostate tissue. The biological function and regulation of NY-BR-1 is up to date unknown.

Methods

We performed an in silico analysis on the genetic variations of the NY-BR-1 gene using data available in public SNP databases and the tools SIFT, Polyphen and Provean to find possible functional SNPs. Additionally, we considered the allele frequency of the found damaging SNPs and also analyzed data from an in-house sequencing project of 55 breast cancer samples for recurring SNPs, recorded in dbSNP.

Results

Over 2800 SNPs are recorded in the dbSNP and NHLBI ESP databases for the NY-BR-1 gene. Of these, 65 (2.07%) are synonymous SNPs, 191 (6.09%) are non-synoymous SNPs, and 2430 (77.48%) are noncoding intronic SNPs. As a result, 69 non-synoymous SNPs were predicted to be damaging by at least two, and 16 SNPs were predicted as damaging by all three of the used tools. The SNPs rs200639888, rs367841401 and rs377750885 were categorized as highly damaging by all three tools. Eight damaging SNPs are located in the ankyrin repeat domain (ANK), a domain known for its frequent involvement in protein-protein interactions. No distinctive features could be observed in the allele frequency of the analyzed SNPs.

Conclusion

Considering these results we expect to gain more insights into the variations of the NY-BR-1 gene and their possible impact on giving rise to splice variants and therefore influence the function of NY-BR-1 in healthy tissue as well as in breast cancer.

Alteration of microRNA expression in cerebrospinal fluid of unconscious patients after traumatic brain injury and a bioinformatic analysis of related single nucleotide polymorphisms

PURPOSE

It is becoming increasingly clear that genetic factors play a role in traumatic brain injury (TBI), whether in modifying clinical outcome after TBI or determining susceptibility to it. MicroRNAs are small RNA molecules involved in various pathophysiological processes by repressing target genes at the post- transcriptional level, and TBI alters microRNA expression levels in the hippocampus and cortex. This study was designed to detect differentially expressed microRNAs in the cerebrospinal fluid (CSF) of TBI patients remaining unconscious two weeks after initial injury and to explore related single nucleotide polymorphisms (SNPs).

METHODS

We used a microarray platform to detect differential microRNA expression levels in CSF samples from patients with post-traumatic coma compared with samples from controls. A bioinformatic scan was performed covering microRNA gene promoter regions to identify potential functional SNPs.

RESULTS

Totally 26 coma patients and 21 controls were included in this study, with similar distribution of age and gender between the two groups. Microarray showed that fourteen microRNAs were differentially expressed, ten at higher and four at lower expression levels in CSF of traumatic coma patients compared with controls (p<0.05). One SNP (rs11851174 allele: C/T) was identified in the motif area of the microRNA hsa-miR-431-3P gene promoter region.

CONCLUSION

The altered microRNA expression levels in CSF after brain injury together with SNP identified within the microRNA gene promoter area provide a new perspective on the mechanism of impaired consciousness after TBI. Further studies are needed to explore the association between the specific microRNAs and their related SNPs with post-traumatic unconsciousness.

Genomic scan for identifying candidate genes for paratuberculosis resistance in sheep

Breeding objectives relating to health, functional traits and welfare need to receive priority in the research programs and selection schemes, but very few reports are available on natural resistant genotypes in livestock, where some important diseases cause severe economic losses and pose serious zoonotic threats. In this study, diagnosis of paratuberculosis was performed on 759 adult sheep, from a single flock, with the serum antibody enzyme-linked immunosorbent assay; 100 sheep were selected among the extreme divergent animals for the S/P ratio obtained from the test, and were genotyped on the Illumina Ovine SNP50K BeadChip. A genome-wide scan was then performed on the individual marker genotypes, in the attempt to identify genomic regions associated with disease resistance in sheep. For each marker, the allelic substitution effect was calculated by regressing the S/P value on the number of copies of the reference allele. The position on the OARv3.1 Genome Assembly was searched for 32 markers, which showed a statistically significant allelic substitution effect (Raw P < 0.0006 and FDR P < 0.09). All markers were located within, or close to, annotated genes. Five of these genes, SEMA3, CD109, PCP4, PRDM2 and ITFG2 are referred in literature to play a role in either disease resistance or cell-mediated immune response.

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.

Association of three common BARD1 variants with cancer susceptibility: a system review and meta-analysis

BARD1 has been shown to play tumor suppressive roles in human cancer. We performed this meta-analysis and firstly evaluated the association between three common BARD1 polymorphisms (Arg378Ser, Val507Met and Pro24Ser) and cancer susceptibility. We performed this meta-analysis following PRISMA guidelines. A comprehensive search of PubMed, EMBASE, Cochrane Library, OVID and Web of Science databases was done from database inception to August 2014. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were combined to measure the association between BARD1 polymorphisms and cancer risk. On the basis of 10 studies about BARD1 polymorphisms and cancer, we found that BARD1 Val507Met (G/A) polymorphism was associated with decreased cancer susceptibility (allelic model: OR = 0.76, 95% CI: 0.66-0.87, P < 0.00001; dominant model: OR = 0.77, 95% CI: 0.65-0.91, P < 0.00001; recessive model: OR = 0.64, 95% CI: 0.55-0.74, P < 0.00001; homozygote comparison: OR = 0.58, 95% CI: 0.49-0.70, P < 0.00001; heterozygote comparison: OR = 0.85, 95% CI: 0.74-0.99 , P = 0.0008). BARD1 Pro24Ser (C/T) polymorphism was also associated decreased cancer risk in allelic model (OR = 0.72, 95% CI: 0.60-0.88, P = 0.0009), dominant model (OR = 0.70, 95% CI: 0.56-0.87, P = 0.004), recessive model (OR = 0.70, 95% CI: 0.56-0.87 , P = 0.004), homozygote comparison (OR = 0.55, 95% CI: 0.39-0.78, P = 0.0007) and heterozygote comparison (OR = 0.75, 95% CI: 0.62-0.91, P = 0.004). And in our sensitivity analysis, when deleting the study performed by Capasso in 2009, we found that BARD1 Arg378Ser polymorphism was associated with decreased cancer risk in allelic model (OR = 0.81, 95% CI: 0.67-0.97, P = 0.02), dominant model (OR = 0.72, 95% CI: 0.56-0.91, P = 0.007) and heterozygote comparison (OR = 0.72, 95% CI: 0.57-0.91, 0 = 0.006). In conclusion, BARD1 Arg378Ser, Val507Met and Pro24Ser may be associated with decreased cancer risk. More studies with larger samples and gene-environment interactions are needed to confirm our findings.

In silico analysis of single nucleotide polymorphism (SNP) in human TNF-α gene

The TNF-α gene mutations are seen in many diseases especially inflammatory diseases. Hence, before planning a larger population study, it is advisable to sort out the possible functional SNPs. To accomplish this goal, data available in the dbSNP database and different computer programs can be used. Therefore, this study was undertaken to find the functional nsSNPs (non-synonymous single nucleotide polymorphisms) in TNF-α.

Out of the total 169 SNPs, 48 were nsSNPs (non-synonymous single nucleotide polymorphisms), 23 occurred in the mRNA 3′ UTR, 10 occurred in 5′ UTR region, 41 occurred in intronic regions and the rest were other types of SNPs. SIFT and PolyPhen predicted 2 out of 48 nsSNPs as damaging. Among the predicted nsSNPs, rs4645843 and rs1800620 were identified as deleterious and damaging by the SIFT (Sorting Intolerant from Tolerant) and PolyPhen programs. Additionally, I-Mutant and nsSNPAnalyzer showed a decrease in stability for these nsSNPs upon mutation. Protein structural analysis with these amino acid variants was performed by using I-Mutant, Swiss PDB viewer, ANOLEA (Atomic Non-Local Environment Assessment), MUSTER (MUlti-Sources ThreadER) and NOMAD-Ref servers to check their molecular dynamics and energy minimization calculations. This study suggested that P84L and A94T variants of TNF-α could directly or indirectly destabilize the amino acid interactions and hydrogen bond networks thus explaining the functional deviations of protein to some extent.

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We analyze total 48 nsSNPs. Among the predicted nsSNPs, rs4645843, rs1800620 were identified as deleterious and damaging.

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The amino acid residue substitutions which had the greatest impact on the stability of the TNF-α protein were mutations P84L (rs4645843) and A94T (rs1800620).

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rs4645843 and rs1800620 should be considered important candidates in causing diseases related to TNF-α gene malfunction.

Characterization of LGALS3 (galectin-3) as a player in DNA damage response

DNA damage repair (DDR) is an orchestrated process encompassing the injury detection to its complete resolution. DNA double-strand break lesions are repaired mainly by two distinct mechanisms: the error-free homologous recombination (HR) and the error-prone non-homologous end-joining. Galectin-3 (GAL3) is the unique member of the chimeric galectins subfamily and is reported to be involved in several cancer development and progression related events. Recently our group described a putative protein interaction between GAL3 and BARD1, the main partner of breast and ovarian cancer susceptibility gene product BRCA1, both involved in HR pathway. In this report we characterized GAL3/BARD1 protein interaction and evaluated the role of GAL3 in DDR pathways using GAL3 silenced human cells exposed to different DNA damage agents. In the absence of GAL3 we observed a delayed DDR response activation, as well as a decrease in the G 2/M cell cycle checkpoint arrest associated with HR pathway. Moreover, using a TAP-MS approach we also determined the protein interaction network of GAL3.

A cross-sectional study of associations between nonsynonymous mutations of the BARD1 gene and breast cancer in Han Chinese women

The PCR-PIRA and PCR-RFLP techniques were used for BARD1 genotyping. Correlations between gene polymorphisms and the susceptibility to breast cancer were analyzed by logistic regression analysis.

RESULTS

showed that compared with the wild type of 378 Arg/Arg of BRAD1, the homozygotic type of 378 Ser/Ser with Arg378Ser site mutation had a protective effect (adjusted odds ratio: 0.628, 95% confidence interval: 0.306-1.145). Compared with individuals carrying the wild type of 24Pro/Pro, the disease risk of individuals with the heterozygous type of 24 Pro/Ser decreased by 30.6% and that with the mutational homozygotic type of 24 Ser/Ser decreased by 43.8%. SNP sites rs2229571 and rs1048108 of BARD1 are associated with a lower risk of breast cancer but not rs2070094.