A comprehensive in silico analysis of the functional and structural impact of SNPs in the IGF1R gene

De novo structure prediction of meteorin and meteorin-like protein for identification of domains, functional receptor binding regions, and their high-risk missense variants

Meteorin (Metrn) and Meteorin-like (Metrnl) are homologous secreted proteins involved in neural development and metabolic regulation. In this study, we have performed de novo structure prediction and analysis of both Metrn and Metrnl using Alphafold2 (AF2) and RoseTTAfold (RF). Based on the domain and structural homology analysis of the predicted structures, we have identified that these proteins are composed of two functional domains, a CUB domain and an NTR domain, connected by a hinge/loop region. We have identified the receptor binding regions of Metrn and Metrnl using the machine-learning tools ScanNet and Masif. These were further validated by docking Metrnl with its reported KIT receptor, thus establishing the role of each domain in the receptor interaction. Also, we have studied the effect of non-synonymous SNPs on the structure and function of these proteins using an array of bioinformatics tools and selected 16 missense variants in Metrn and 10 in Metrnl that can affect the protein stability. This is the first study to comprehensively characterize the functional domains of Metrn and Metrnl at their structural level and identify the functional domains, and protein binding regions. This study also highlights the interaction mechanism of the KIT receptor and Metrnl. The predicted deleterious SNPs will allow further understanding of the role of these variants in modulating the plasma levels of these proteins in disease conditions such as diabetes.Communicated by Ramaswamy H. Sarma.

In Silico Tools for Analysis of Single-Nucleotide Polymorphisms in the Bovine Transferrin Gene

Dairy cattle with a high milk yield are susceptible to many infectious diseases, such as mastitis. Subclinical mastitis (SCM) is the most prevalent form of mastitis that predominantly affects animal health, and causes adverse effects on the quality and quantity of milk. In dairy animals, subclinical mastitis often remains undetected, as no gross changes in udder characteristics are visible. In the present study, 135 Holstein Friesian dairy animals were selected and screened as healthy (n = 25) and mastitic (n = 110) based on diagnostic tests such as the California mastitis test, pH, electrical conductivity, and somatic cell count. In this study, the somatic cell count was used as a gold-standard test in differentiating subclinical mastitis animals from healthy ones. The present study was carried out to study polymorphisms in the bovine transferrin gene in cows (with subclinical mastitis and healthy). For the early detection of resistant/or susceptible animals, a useful marker could be provided by the detection of single-nucleotide polymorphisms (SNPs) in the transferrin gene, which are often associated with mammary innate immune response. The sequencing results revealed three nucleotide substitutions: two transversions (230 A > C, 231 C > A) and one transition (294 A > G) in susceptible cows as compared to disease-free subjects. The nucleotide variations at position 230 (GAC > GCA) and 231 (GAC > GCA) were nonsynonymous, and corresponded to an amino acid change from aspartic acid to alanine; whereas at position 294 (GAA > GAG), the mutation was synonymous. In the present study, many in silico tools were taken into consideration to determine the effect of SNPs on protein structure and function. The PROVEAN tool found the amino acid substitution to be neutral and deleterious. PolyPhen-2 revealed the amino acid variations at positions 320 and 321 to most likely be damaging; and at the 341 position, the variations were benign. The I-Mutant and MUpro tools found that the protein stability decreased for nonsynonymous variations. The SIFT tool revealed the protein function was likely to be affected in nonsynonymous variations, with no change in the case of synonymous ones. Phylogenetic analysis of the bovine transferrin gene revealed a close relation of the CA allele with the Bos taurus transferrin, while the G allele was closely related to a cross of Bos indicus × Bos taurus serotransferrins, followed by the Bison bison transferrin. The least relation was shown by both alleles to Capra hircus, Ovis aries, and Bubalus bubalis.

+3179G/A Insulin-Like Growth Factor-1 Receptor Polymorphism: A Novel Susceptibility Contributor in Anti-Ro/SSA Positive Patients with Sjögren's Syndrome: Potential Clinical and Pathogenetic Implications

Background: Alterations of the insulin-like growth factor (IGF) pathway along with genetic variations of the IGF1 receptor (IGF1R) gene have been linked to the development of systemic autoimmunity, possibly through apoptosis induction. This study aims to investigate whether genetic variations of the IGF1R contribute to Sjögren’s syndrome (SS) pathogenesis and explores potential functional implications. Methods: DNA extracted from whole peripheral blood derived from 277 primary SS patients, complicated or not by lymphoma, and 337 Healthy controls (HC) was genotyped for the rs2229765 IGF1R polymorphism using the RFLP-PCR assay. Gene expression of IGF1R and IGF1 isoforms, caspases 1, 4, and 5, and inflammasome components NLRP3, ASC, IL1β, IL18, IL33, IGFBP3, and IGFBP6 were quantitated by RT-PCR in total RNA extracted from minor salivary gland biopsies (MSGs) of 50 SS patients and 13 sicca controls (SCs). In addition, IGF1R immunohistochemical (IHC) expression was assessed in formalin-fixed, paraffin-embedded MSG tissue sections derived from 10 SS patients and 5 SCs. Results: The prevalence of the A/A genotype of the rs2229765 IGF1R polymorphism was significantly higher in the anti-Ro/SSA positive SS population compared to healthy controls (24.8% vs. 10.7%, p = 0.001). Moreover, IGF1Rs at both mRNA and protein levels were reduced in SS-derived MSGs compared to SCs and were negatively associated with caspase 1 transcripts. The latter were positively correlated with NLRP3, ASC, and IL1β at the salivary gland tissue level. IGF1R expression in peripheral blood was negatively correlated with ESR and IgG serum levels and positively correlated with urine-specific gravity values. Conclusions: The rs2229765 IGF1R variant confers increased susceptibility for seropositive primary SS. Dampened IGF1R mRNA and protein expression in salivary gland tissues could be related to increased apoptosis and subsequently to the activation of inflammasome pathways.

Genotype-Structure-Phenotype Correlations of Disease-Associated IGF1R Variants and Similarities to Those of INSR Variants

We previously reported genotype-phenotype correlations in 12 missense variants causing severe insulin resistance, located in the second and third fibronectin type III (FnIII) domains of the insulin receptor (INSR), containing the α-β cleavage and part of insulin-binding sites. This study aimed to identify genotype-phenotype correlations in FnIII domain variants of IGF1R, a structurally related homolog of INSR, which may be associated with growth retardation, using the recently reported crystal structures of IGF1R. A structural bioinformatics analysis of five previously reported disease-associated heterozygous missense variants and a likely benign variant in the FnIII domains of IGF1R predicted that the disease-associated variants would severely impair the hydrophobic core formation and stability of the FnIII domains or affect the α-β cleavage site, while the likely benign variant would not affect the folding of the domains. A functional analysis of these variants in CHO cells showed impaired receptor processing and autophosphorylation in cells expressing the disease-associated variants but not in those expressing the wild-type form or the likely benign variant. These results demonstrated genotype-phenotype correlations in the FnIII domain variants of IGF1R, which are presumably consistent with those of INSR and would help in the early diagnosis of patients with disease-associated IGF1R variants.

Deleterious missense variants in the aflatoxin biosynthesis genes explain the low toxicity of Aspergillus flavus from infected rice

Aspergillus flavus is one of the most natural contaminants of the improperly stored rice grains. It produces several secondary metabolites, like aflatoxins, which are well known hepatotoxic, hepatocarcinogenic and mutagenic agents. This study describes the in silico consequences of the missense mutations identified in several genes of aflatoxins biosynthesis in rice-contaminating A. flavus isolates. In the in vitro portion of the study, aflatoxins production profile was measured, and PCR-single strand-conformation polymorphism (SSCP)-sequencing method was used to genotype the studied genetic loci: aflP, aflM, aflR, PEP, and cob. Results showed aflatoxigenic potential in 79 out of 109 A. flavus isolates. Twenty-two missense and fifty-five synonymous mutations were found to be distributed variably on the studied loci. In the in silico portion of this study, several computations were utilized to predict the effect of each observed missense mutation on proteins structure, function, and stability. Seven mutations (O-methyl transferase: p.G256C; ver-1 dehydrogenase: p.K179 N and p.V183L; aspergillopepsin-1: p.P137L, p.S138F, p.G154C, and p.S158C) were found to be highly deleterious among the missense variants with damaging effects on their proteins' structure and function. In contrast to these detected variations in the aflatoxigenic loci, all missense mutations in the control non-aflatoxigenic cob gene were found to be neutral. These findings indicated that the observed mutations may reduce the concomitant biohazard of their biosynthesized aflatoxins. The current findings suggest that the naturally available variants may reduce or eliminates the dangerous consequences of aflatoxins upon ingesting the rice infected with A. flavus. To the best of our knowledge, this study is the first comprehensive report to analyze the missense mutations on the aflatoxin biosynthesis genes using in vitro and the state-of-art bio-computational tools.

Evolutionary Pattern of Interferon Alpha Genes in Bovidae and Genetic Diversity of IFNAA in the Bovine Genome

Interferons are secretory proteins induced in response to specific extracellular stimuli which stimulate intra- and intercellular networks for regulating innate and acquired immunity, resistance to viral infections, and normal and tumor cell survival and death. Type 1 interferons plays a major role in the CD8 T-cell response to viral infection. The genomic analysis carried out here for type I interferons within Bovidae family shows that cattle, bison, water buffalo, goat, and sheep (all Bovidae), have different number of genes of the different subtypes, with a large increase in the numbers, compared to human and mouse genomes. A phylogenetic analysis of the interferon alpha (IFNA) proteins in this group shows that the genes do not follow the evolutionary pattern of the species, but rather a cycle of duplications and deletions in the different species. In this study we also studied the genetic diversity of the bovine interferon alpha A (IFNAA), as an example of the IFNA genes in cattle, sequencing a fragment of the coding sequence in 18 breeds of cattle from Pakistan, Nigeria and USA. Similarity analysis allowed the allocation of sequences into 22 haplotypes. Bhagnari, Brangus, Sokoto Gudali, and White Fulani, had the highest number of haplotypes, while Angus, Hereford and Nari Master had the least. However, when analyzed by the average haplotype count, Angus, Bhagnari, Hereford, Holstein, Muturu showed the highest values, while Cholistani, Lohani, and Nari Master showed the lowest values. Haplotype 4 was found in the highest number of individuals (74), and in 15 breeds. Sequences for yak, bison, and water buffalo, were included within the bovine haplotypes. Medium Joining network showed that the sequences could be divided into 4 groups: one with highly similar haplotypes containing mostly Asian and African breeds, one with almost all of the Bos taurus American breeds, one mid-diverse group with mostly Asian and African sequences, and one group with highly divergent haplotypes with five N'Dama sequences and one from each of White Fulani, Dhanni, Tharparkar, and Bhagnari. The large genetic diversity found in IFNAA could be a very good indication of the genetic variation among the different genes of IFNA and could be an adaptation for these species in response to viral challenges they face.

Ubiquilin Networking in Cancers

Ubiquilins or UBQLNs, members of the ubiquitin-like and ubiquitin-associated domain (UBL-UBA) protein family, serve as adaptors to coordinate the degradation of specific substrates via both proteasome and autophagy pathways. The UBQLN substrates reveal great diversity and impact a wide range of cellular functions. For decades, researchers have been attempting to uncover a puzzle and understand the role of UBQLNs in human cancers, particularly in the modulation of oncogene's stability and nucleotide excision repair. In this review, we summarize the UBQLNs' genetic variants that are associated with the most common cancers and also discuss their reliability as a prognostic marker. Moreover, we provide an overview of the UBQLNs networks that are relevant to cancers in different ways, including cell cycle, apoptosis, epithelial-mesenchymal transition, DNA repairs and miRNAs. Finally, we include a future prospective on novel ubiquilin-based cancer therapies.

CYP2R1 and CYP27A1 genes: An in silico approach to identify the deleterious mutations, impact on structure and their differential expression in disease conditions

Mutations in CYP2R1 and CYP27A1 involved in the conversion of Cholecalciferol into Calcidiol were associated with the impaired 25-hydroxylase activity therefore affecting the Vitamin D metabolism. Hence, this study attempted to understand the influence of genetic variations at the sequence and structural level via computational approach. The non-synonymous mutations retrieved from dbSNP database were assessed for their pathogenicity, stability as well as conservancy using various computational tools. The above analysis predicted 11/260 and 35/489 non-synonymous mutations to be deleterious in CYP2R1 and CYP27A1 genes respectively. Native and mutant forms of the corresponding proteins were modeled. Further, interacting native and mutant proteins with cholecalciferol showed difference in hydrogen bonds, hydrophobic bonds and their binding affinities suggesting the possible influence of these mutations in their function. Also, expression of these genes in various disease conditions was investigated using GEO datasets which predicted that there is a differential expression in cancer and arthritis.

Prediction of Deleterious Non-synonymous SNPs of Human STK11 Gene by Combining Algorithms, Molecular Docking, and Molecular Dynamics Simulation

Serine-threonine kinase11 (STK11) is a tumor suppressor gene which plays a key role in regulating cell growth and apoptosis. It is widely known as a multitasking kinase and engaged in cell polarity, cell cycle arrest, chromatin remodeling, energy metabolism, and Wnt signaling. The substitutions of single amino acids in highly conserved regions of the STK11 protein are associated with Peutz-Jeghers syndrome (PJS), which is an autosomal dominant inherited disorder. The abnormal function of the STK11 protein is still not well understood. In this study, we classified disease susceptible single nucleotide polymorphisms (SNPs) in STK11 by using different computational algorithms. We identified the deleterious nsSNPs, constructed mutant protein structures, and evaluated the impact of mutation by employing molecular docking and molecular dynamics analysis. Our results show that W239R and W308C variants are likely to be highly deleterious mutations found in the catalytic kinase domain, which may destabilize structure and disrupt the activation of the STK11 protein as well as reduce its catalytic efficiency. The W239R mutant is likely to have a greater impact on destabilizing the protein structure compared to the W308C mutant. In conclusion, these mutants can help to further realize the large pool of disease susceptibilities linked with catalytic kinase domain activation of STK11 and assist to develop an effective drug for associated diseases.

In silico analysis of nsSNPs in ABCB1 gene affecting breast cancer associated protein P-glycoprotein (P-gp)

Breast cancer is one of the most common cancers among women and increased expression of some polymorphic genes, which is rare within families, enhances the risk of breast cancer incidence. The correct identification of the functional SNPs of such genes is important for characterizing the functional aspect of these SNPs which can be assessed by evaluating their significant influence on the structure and function of proteins. Since the presence of SNPs in these genes affects the quality of life of a breast cancer patient, thus, the associated diagnostic markers have a reliable potential for assessing the prognosis of breast cancer. ATP-binding cassette (ABC) genes have been shown to obstruct the treatment of breast cancer by providing resistance to malignant cells from anti-cancer drugs. Some allelic variants of ABCG2 and ABCB1 are also associated with occurrence of skin toxicity during the treatment of breast cancer with anti-cancer drugs. The present study has incorporated comprehensive bioinformatics analysis to explore the possible disease-associated mutations of ABCB1 gene, a gene that resulted from gene-environment interaction study, and understand their consequential effect on the structural and functional behavior of P-glycoprotein. Two gene variants (R538S and M701R) of P-glycoprotein were selected as potentially detrimental point mutations, and these variants were modeled. Molecular dynamic simulation (MDS) studies unraveled the atomic interactions and motion trajectories of the native as well as the two mutant (R538S and M701R) structures and were predicted to have a deleterious effect on breast cancer associated P-gp. Thus, the present study may broaden the way to design novel potent drugs for overcoming the problems associated with multidrug resistance (MDR) resulting from a change in protein conformation due to a mutation in ABCB1 gene.

In Silico Analysis of nsSNPs of Carp TLR22 Gene Affecting its Binding Ability with Poly I:C

Immune response mediated by toll-like receptor 22 (TLR22), only found in teleost/amphibians, is triggered by double-stranded RNA binding to its LRR (leucine-rich repeats) ecto-domain. Accumulated evidences suggested that missense mutations in TLR genes affect its function. However, information on mutation linked pathogen recognition for TLR22 was lacking. The present study was commenced for predicting the effect of non-synonymous single-nucleotide polymorphisms (nsSNPs) on the pathogen recognizable LRR domain of TLR22 of farmed carp, Labeo rohita. The sequence-based algorithms (SIFT, PROVEAN and I-Mutant2.0) indicated that three SNPs (out of 27) such as p.L159F (rs76759876) and p.L529P (rs749355507) of LRR, and p.I836M (rs750758397) of intracellular motifs could potentially disrupt protein function. The 3D structure was generated using MODELLER 9.13 and further validated by SAVEs server. The simulated molecular docking of native TLR22 and mutants with poly I:C ligand indicated that mutations positioned at p.L159F and p.L529P of the LRR region affects the binding affinity significantly. This is the first kind of study of predicting nsSNPs of teleost TLR22 with disturbed ligand binding affinity with its extra-cellular LRR domain and thereby likely hindrance in subsequent signal transduction. This study serves as a guide for in vivo evaluation of impact of mutation on immune response mediated by teleost TLR22 gene.

Maternal IGF1 and IGF1R polymorphisms and the risk of spontaneous preterm birth

BACKGROUND

The insulin-like growth factor (IGF) pathway was involved in the occurrence of spontaneous preterm birth (SPTB), but little is known regarding the relationship between genetic variations in IGF pathway and the risk of SPTB. We aimed to investigate the associations of IGF1 rs972936 and IGF1 receptor (IGF1R) rs2229765 polymorphisms with SPTB risk in a Chinese population.

METHOD

A total of 114 cases of SPTB and 250 controls of term delivery were included from Guangzhou Women and Children's Medical Center, China. The odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) were calculated using multivariate logistic regression.

RESULTS

We found that the GA and GA/AA genotypes of IGF1 rs972936 were associated with an increased risk of SPTB, and the adjusted ORs (95% CI) were 1.74 (1.01-3.02) and 1.75 (1.04-2.93) respectively. Women carrying GA and GA/AA genotypes of IGF1R rs2229765 had a reduced risk compared to those with the GG genotype (0.60 [0.37-0.98] and 0.64 [0.40-1.00] respectively). There were significant interactions between IGF1 rs972936 and GDM status (P for interaction=.02), as well as between IGF1R rs2229765 and pre-pregnancy BMI (P for interaction <.001) on the risk of SPTB.

CONCLUSION

Our findings suggest that polymorphisms of IGF1 rs972936 and IGF1R rs2229765 were associated with the risk of SPTB in Chinese pregnant women and these effects depend on the maternal metabolic status.

Insulin-like growth factor-1 signaling in renal cell carcinoma

Renal cell carcinoma (RCC) incidence is highest in highly developed countries and it is the seventh most common neoplasm diagnosed. RCC management include nephrectomy and targeted therapies. Type 1 insulin-like growth factor (IGF-1) pathway plays an important role in cell proliferation and apoptosis resistance. IGF-1 and insulin share overlapping downstream signaling pathways in normal and cancer cells. IGF-1 receptor (IGF1R) stimulation may promote malignant transformation promoting cell proliferation, dedifferentiation and inhibiting apoptosis. Clear cell renal cell carcinoma (ccRCC) patients with IGF1R overexpression have 70 % increased risk of death compared to patients who had tumors without IGF1R expression. IGF1R signaling deregulation may results in p53, WT, BRCA1, VHL loss of function. RCC cells with high expression of IGF1R are more resistant to chemotherapy than cells with low expression. Silencing of IGF1R increase the chemosensitivity of ccRCC cells and the effect is greater in VHL mutated cells. Understanding the role of IGF-1 signaling pathway in RCC may result in development of new targeted therapeutic interventions. First preclinical attempts with anti-IGF-1R monoclonal antibodies or fragment antigen-binding (Fab) fragments alone or in combination with an mTOR inhibitor were shown to inhibit in vitro growth and reduced the number of colonies formed by of RCC cells.

Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes

FGF23, CYP24A1 and VDR altogether play a significant role in genetic susceptibility to chronic kidney disease (CKD). Identification of possible causative mutations may serve as therapeutic targets and diagnostic markers for CKD. Thus, we adopted both sequence and sequence-structure based SNP analysis algorithm in order to overcome the limitations of both methods. We explore the functional significance towards the prediction of risky SNPs associated with CKD. We assessed the performance of four widely used pathogenicity prediction methods. We compared the performances of the programs using Mathews correlation Coefficient ranged from poor (MCC = 0.39) to reasonably good (MCC = 0.42). However, we got the best results for the combined sequence and structure based analysis method (MCC = 0.45). 4 SNPs from FGF23 gene, 8 SNPs from VDR gene and 13 SNPs from CYP24A1 gene were predicted to be the causative agents for human diseases. This study will be helpful in selecting potential SNPs for experimental study from the SNP pool and also will reduce the cost for identification of potential SNPs as a genetic marker.

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.

Mutational analysis of the insulin-like growth factor 1 receptor tyrosine kinase domain in non-small cell lung cancer patients

The insulin-like growth factor 1 receptor (IGF1R) pathway plays an important role in the pathogenesis of non-small cell lung cancer (NSCLC) and also provides a mechanism of resistance to targeted therapies. IGF1R is therefore an ideal therapeutic target and several inhibitors have entered clinical trials. However, thus far the response to these inhibitors has been poor, highlighting the importance of predictive biomarkers to identify patient cohorts who will benefit from these targeted agents. It is well-documented that mutations and/or deletions in the epidermal growth factor receptor (EGFR) tyrosine kinase (TK) domain predict sensitivity of NSCLC patients to EGFR TK inhibitors. Single-nucleotide polymorphisms (SNPs) in the IGF pathway have been associated with disease, including breast and prostate cancer. The aim of the present study was to elucidate whether the IGF1R TK domain harbours SNPs, somatic mutations or deletions in NSCLC patients and correlates the mutation status to patient clinicopathological data and prognosis. Initially 100 NSCLC patients were screened for mutations/deletions in the IGF1R TK domain (exons 16-21) by sequencing analysis. Following the identification of SNP rs2229765, a further 98 NSCLC patients and 866 healthy disease-free control patients were genotyped using an SNP assay. The synonymous SNP (rs2229765) was the only aberrant base change identified in the IGF1R TK domain of 100 NSCLC patients initially analysed. SNP rs2229765 was detected in exon 16 and was found to have no significant association between IGF1R expression and survival. The GA genotype was identified in 53.5 and 49.4% of NSCLC patients and control individuals, respectively. No significant difference was found in the genotype (P=0.5487) or allele (P=0.9082) frequencies between the case and control group. The present findings indicate that in contrast to the EGFR TK domain, the IGF1R TK domain is not frequently mutated in NSCLC patients. The synonymous SNP (rs2229765) had no significant association between IGF1R expression and survival in the cohort of NSCLC patients.

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.

Triallelic digenic mutation in the prokineticin 2 and GNRH receptor genes in two brothers with normosmic congenital hypogonadotropic hypogonadism

Purpose/aim of the study: To date, different genes have been identified as responsible for the presence of normosmic congenital hypogonadotropic hypogonadism (nCHH). Herein, we report the molecular findings regarding the analysis of PROK2, in two brothers with nCHH.

SUBJECTS AND METHODS

Two siblings with nCHH, in whom mutations in GNRHR, PROKR2 and FGFR1 had been investigated previously, as well as their family were studied. DNA was amplified by PCR and sequenced for the PROK2 gene. Controls were analyzed by restriction fragment-length polymorphism. The structure of PROK2 and its mutant protein were compared using a protein molecular model.

RESULTS

Both affected siblings exhibited a heterozygous p.R117W mutation in PROK2, while their mother was a heterozygous carrier and their father, an unaffected brother and their sister were homozygous wild type. Besides, both patients presented a homozygous p.E90K mutation in GNRHR that had been previously reported.

CONCLUSIONS

We found a novel mutation in PROK2 in two siblings in whom a mutation in the GNRHR gene had been previously reported.

Circulating IGF1 and IGF2 and SNP genotypes in men and pregnant and non-pregnant women

Circulating IGFs are important regulators of prenatal and postnatal growth, and of metabolism and pregnancy, and change with sex, age and pregnancy. Single-nucleotide polymorphisms (SNPs) in genes coding for these hormones associate with circulating abundance of IGF1 and IGF2 in non-pregnant adults and children, but whether this occurs in pregnancy is unknown. We therefore investigated associations of plasma IGF1 and IGF2 with age and genotype at candidate SNPs previously associated with circulating IGF1, IGF2 or methylation of the INS-IGF2-H19 locus in men (n=134), non-pregnant women (n=74) and women at 15 weeks of gestation (n=98). Plasma IGF1 concentrations decreased with age (P<0.001) and plasma IGF1 and IGF2 concentrations were lower in pregnant women than in non-pregnant women or men (each P<0.001). SNP genotypes in the INS-IGF2-H19 locus were associated with plasma IGF1 (IGF2 rs680, IGF2 rs1004446 and IGF2 rs3741204) and IGF2 (IGF2 rs1004446, IGF2 rs3741204 and H19 rs217727). In single SNP models, effects of IGF2 rs680 were similar between groups, with higher plasma IGF1 concentrations in individuals with the GG genotype when compared with GA (P=0.016), or combined GA and AA genotypes (P=0.003). SNPs in the IGF2 gene associated with IGF1 or IGF2 were in linkage disequilibrium, hence these associations could reflect other genotype variations within this region or be due to changes in INS-IGF2-H19 methylation previously associated with some of these variants. As IGF1 in early pregnancy promotes placental differentiation and function, lower IGF1 concentrations in pregnant women carrying IGF2 rs680 A alleles may affect placental development and/or risk of pregnancy complications.

Relevance of insulin-like growth factor 1 receptor gene expression as a prognostic factor in non-small-cell lung cancer

PURPOSE

Signalling through the insulin-like growth factor 1 receptor (IGF-1R) is implicated in carcinogenesis, metastasis, and resistance to cytotoxic cancer therapies. The purpose of this study was to investigate the prognostic role of IGF-1R expression in surgically resected non-small-cell lung cancer (NSCLC), and responses to IGF-1R tyrosine kinase inhibitor NVP-ADW742 in a panel of lung cancer cell lines.

METHODS

Insulin-like growth factor 1 receptor (IGF-1R) expression was evaluated by quantitative RT-PCR in 115 NSCLC samples and in a panel of 6 NSCLC cell lines. Cytotoxicity experiments with IGF-1R inhibitor and conventional systemic drugs such as paclitaxel in cell lines were realised.

RESULTS

Insulin-like growth factor 1 receptor (IGF-1R) was differentially expressed across histologic subtypes, with the lowest levels observed in squamous cell tumours. Median survival was longer in patients with squamous tumour histology expressing low IGF-1R levels. In multivariable analysis, ageing and high tumour stage were significant predictors of worse overall survival. The hazard of death was lower in patients with squamous histology and low IGF-1R gene expression. There was no correlation between IGF-1R expression and response to tyrosine kinase inhibitor in cell lines tested. However, combination drug treatment resulted in synergistically enhanced antiproliferative effects on several cell lines.

CONCLUSIONS

These findings suggest that IGF-1R is a potential target for therapy in NSCLC patients. Combination therapies will have an important role in treatment.

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.

Performance of in silico analysis in predicting the effect of non-synonymous variants in inherited steroid metabolic diseases

BACKGROUND

Unclassified genetic variants are commonly encountered in molecular diagnostic service. In silico analyses using web-based predictive programs may provide information on the nature of the genetic variants, and help to prioritize novel variants for in vitro functional characterization. The objective of this study was to compare the performance of three such programs in genes related to steroid metabolism.

METHODS

The effects of non-synonymous benign and pathogenic sequence variants in the CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP19A1, CYP21A2, DHCR7, HSD3B2, HSD11B2, HSD17B3, POR, and SRD5A2 genes listed in the Human Gene Mutation Database and dbSNP were tested by SIFT, PolyPhen-2 and PON-P. Their concordance, sensitivity, specificity, positive and negative predictive values and accuracy were assessed, using the reported phenotype and the in vitro functional data as gold standards.

RESULTS

797 sequence variants were tested. SIFT and PolyPhen-2 had high concordance, with PolyPhen-2 being slightly superior to SIFT in all assessments. PON-P behaved differently, with one-third of the variants unclassified.

CONCLUSIONS

SIFT and PolyPhen-2 behaved similarly while PON-P behaved differently in predicting pathogenicity in genes related to steroid metabolism. Molecular pathologists should verify the performance of these programs before considering them in clinical decision making, and be aware that these programmes cannot replace in vitro function studies. Clinicians and patients should also be informed about the limitations of genetic testing, particularly when a novel variant is encountered.

Performance of an adipokine pathway-based multilocus genetic risk score for prostate cancer risk prediction

Few biomarkers are available to predict prostate cancer risk. Single nucleotide polymorphisms (SNPs) tend to have weak individual effects but, in combination, they have stronger predictive value. Adipokine pathways have been implicated in the pathogenesis. We used a candidate pathway approach to investigate 29 functional SNPs in key genes from relevant adipokine pathways in a sample of 1006 men eligible for prostate biopsy. We used stepwise multivariate logistic regression and bootstrapping to develop a multilocus genetic risk score by weighting each risk SNP empirically based on its association with disease. Seven common functional polymorphisms were associated with overall and high-grade prostate cancer (Gleason≥7), whereas three variants were associated with high metastatic-risk prostate cancer (PSA≥20 ng/mL and/or Gleason≥8). The addition of genetic variants to age and PSA improved the predictive accuracy for overall and high-grade prostate cancer, using either the area under the receiver-operating characteristics curves (P<0.02), the net reclassification improvement (P<0.001) and integrated discrimination improvement (P<0.001) measures. These results suggest that functional polymorphisms in adipokine pathways may act individually and cumulatively to affect risk and severity of prostate cancer, supporting the influence of adipokine pathways in the pathogenesis of prostate cancer. Use of such adipokine multilocus genetic risk score can enhance the predictive value of PSA and age in estimating absolute risk, which supports further evaluation of its clinical significance.

The effect of input DNA copy number on genotype call and characterising SNP markers in the humpback whale genome using a nanofluidic array

Recent advances in nanofluidic technologies have enabled the use of Integrated Fluidic Circuits (IFCs) for high-throughput Single Nucleotide Polymorphism (SNP) genotyping (GT). In this study, we implemented and validated a relatively low cost nanofluidic system for SNP-GT with and without Specific Target Amplification (STA). As proof of principle, we first validated the effect of input DNA copy number on genotype call rate using well characterised, digital PCR (dPCR) quantified human genomic DNA samples and then implemented the validated method to genotype 45 SNPs in the humpback whale, Megaptera novaeangliae, nuclear genome. When STA was not incorporated, for a homozygous human DNA sample, reaction chambers containing, on average 9 to 97 copies, showed 100% call rate and accuracy. Below 9 copies, the call rate decreased, and at one copy it was 40%. For a heterozygous human DNA sample, the call rate decreased from 100% to 21% when predicted copies per reaction chamber decreased from 38 copies to one copy. The tightness of genotype clusters on a scatter plot also decreased. In contrast, when the same samples were subjected to STA prior to genotyping a call rate and a call accuracy of 100% were achieved. Our results demonstrate that low input DNA copy number affects the quality of data generated, in particular for a heterozygous sample. Similar to human genomic DNA, a call rate and a call accuracy of 100% was achieved with whale genomic DNA samples following multiplex STA using either 15 or 45 SNP-GT assays. These calls were 100% concordant with their true genotypes determined by an independent method, suggesting that the nanofluidic system is a reliable platform for executing call rates with high accuracy and concordance in genomic sequences derived from biological tissue.

Growth hormone insensitivity syndrome caused by a heterozygous GHR mutation: phenotypic variability owing to moderation by nonsense-mediated decay

OBJECTIVES

Growth hormone insensitivity syndrome (GHIS) is characterized by extreme short stature and resistance to the actions of growth hormone (GH). The heterogeneity ranges from the most severe form, known as Laron syndrome, to less severe phenotypes like idiopathic short stature and partial GH insensitivity. Here, we aimed to identify and characterize the molecular cause of severe short stature in a patient with resistance to GH treatment.

PATIENT

We describe a male patient born small for gestational age [38 weeks gestation, length 38·5 cm; -7·8 standard deviation score (SDS), weight 1350 g; -4·84 SDS]. At the age of 7 years (109·7 cm; -2·89 SD), he received GH treatment (1 mg/m(2)/day) for 1 year without any increase in height SDS, IGF-I or IGFBP-3 levels. Double-GH-dose treatment for another year did not result in any improvement in growth factor level either. The patient does not have the typical Laron craniofacial and somatic features.

RESULTS

Analysis of GHR showed a heterozygous nonsense mutation (c.703C>T; p.Arg217X). Extensive mutation screening as well as copy number variation analysis of other candidate genes in the GH-IGF-I axis excluded any additional genetic defects. Analysis of the patient's fibroblasts showed that growth hormone receptor (GHR) messenger ribonucleic acid (mRNA) expressed from the mutant allele was degraded by a mechanism called nonsense-mediated mRNA decay (NMD).

CONCLUSIONS

GHIS in this patient is because of a heterozygous nonsense mutation in GHR. Our study is the first to demonstrate that NMD is involved in the phenotypic variability of GHIS caused by GHR mutations.