Joint annotation of coding and non-coding single nucleotide polymorphisms and mutations in the SNPeffect and PupaSuite databases

Single nucleotide polymorphisms (SNPs) are, together with copy number variation, the primary source of variation in the human genome. SNPs are associated with altered response to drug treatment, susceptibility to disease and other phenotypic variation. Furthermore, during genetic screens for disease-associated mutations in groups of patients and control individuals, the distinction between disease causing mutation and polymorphism is often unclear. Annotation of the functional and structural implications of single nucleotide changes thus provides valuable information to interpret and guide experiments. The SNPeffect and PupaSuite databases are now synchronized to deliver annotations for both non-coding and coding SNP, as well as annotations for the SwissProt set of human disease mutations. In addition, SNPeffect now contains predictions of Tango2: an improved aggregation detector, and Waltz: a novel predictor of amyloid-forming sequences, as well as improved predictors for regions that are recognized by the Hsp70 family of chaperones. The new PupaSuite version incorporates predictions for SNPs in silencers and miRNAs including their targets, as well as additional methods for predicting SNPs in TFBSs and splice sites. Also predictions for mouse and rat genomes have been added. In addition, a PupaSuite web service has been developed to enable data access, programmatically. The combined database holds annotations for 4 965 073 regulatory as well as 133 505 coding human SNPs and 14 935 disease mutations, and phenotypic descriptions of 43 797 human proteins and is accessible via http://snpeffect.vib.be and http://pupasuite.bioinfo.cipf.es/

SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants

Single nucleotide variants (SNVs) are, together with copy number variation, the primary source of variation in the human genome and are associated with phenotypic variation such as altered response to drug treatment and susceptibility to disease. Linking structural effects of non-synonymous SNVs to functional outcomes is a major issue in structural bioinformatics. The SNPeffect database (http://snpeffect.switchlab.org) uses sequence- and structure-based bioinformatics tools to predict the effect of protein-coding SNVs on the structural phenotype of proteins. It integrates aggregation prediction (TANGO), amyloid prediction (WALTZ), chaperone-binding prediction (LIMBO) and protein stability analysis (FoldX) for structural phenotyping. Additionally, SNPeffect holds information on affected catalytic sites and a number of post-translational modifications. The database contains all known human protein variants from UniProt, but users can now also submit custom protein variants for a SNPeffect analysis, including automated structure modeling. The new meta-analysis application allows plotting correlations between phenotypic features for a user-selected set of variants

Relationship of sclerostin and secreted frizzled protein polymorphisms with bone mineral density: an association study with replication in postmenopausal women

Objectives.- Secreted frizzled-related protein and sclerostin, encoded by FRZB and SOST genes, respectively, are extracellular Wnt inhibitors that tend to decrease bone formation. The purpose of this study was to explore the association of sets of polymorphisms capturing common variations of these genes with bone mineral density (BMD). Methods.- Twelve polymorphic loci of the FRZB gene and 7 of the SOST gene were genotyped in postmenopausal women from two Spanish regions (Cantabria, n=1043, and Valencia, n=342). The polymorphisms included tagging SNPs and SNPs with possible functional consequences assessed in silico. Results.-The rs4666865 polymorphism of the FRZB gene was associated with spine BMD in the Cantabria cohort in the single-locus (p=0.008) and the haplotypic analysis. However, the results were not replicated in the Valencia cohort. Several polymorphisms at the 5´region of the SOST gene, and particularly rs851056, were associated with BMD in women from both cohorts (p=0.002 in Cantabria and 0.005 in Valencia). When the results of both cohorts were combined, the mean BMD difference across rs851056 genotypes was 47 mg/cm2 or 0.31 standard deviations (p<0.001). No differences in FRZB and SOST expression was detected across genotypes. Conclusions.- Polymorphisms in the 5’ region of SOST gene are associated with BMD in postmenopausal women, and consequently contribute to explain in part the hereditary influence on bone mass

Wnt receptors, bone mass, and fractures: gene-wide association analysis of LRP5 and LRP6 polymorphisms with replication

Objectives. Genes explaining the susceptibility to osteoporosis have not been fully elucidated. Our objective was to explore the association of polymorphisms capturing common variations of the lipoprotein receptor related protein (LRP) 5 and 6 genes, encoding two Wnt receptors, with femoral neck bone mineral density (BMD) and osteoporotic fractures of the spine and the hip. Design. Cross-sectional, case-control and replication genetic association study. Methods. Thirty nine tagging and functional single nucleotide polymorphisms (SNP) were analyzed in a group of 1043 postmenopausal women and 394 women with hip fractures. The results were replicated in a different group of 342 women. Results. Three SNPs of the LRP6 gene were associated with BMD (nominal uncorrected pvalues< 0.05) in the discovery cohort. One showed a significant association after multiple test correction; two of them were also associated in the replication cohort, with a combined standardized mean difference of 0.51 (p=0.009) and 0.65 (p<0.0001) across rs11054704 and rs2302685 genotypes. In the discovery cohort, several LRP5 SNPs were associated with vertebral fractures (odds ratio 0.67; p=0.01), with hip fractures (unadjusted odds ratios between 0.59 and 1.21, p=0.005-0.033, but not significant after multiple test- or age-adjustment), and with height and the projected femoral neck area, but not with BMD. Transcripts of LRP5 and LRP6 were similarly abundant in bone samples. Conclusions. In this study we found common polymorphisms of LRP5 associated with osteoporotic fractures, and polymorphisms of the LRP6 gene associated with BMD, thus suggesting them as likely candidates to contribute explaining the hereditary influence on osteoporosis

Mutation Screening of Multiple Genes in Spanish Patients with Autosomal Recessive Retinitis Pigmentosa by Targeted Resequencing

Retinitis Pigmentosa (RP) is a heterogeneous group of inherited retinal dystrophies characterised ultimately by the loss of photoreceptor cells. RP is the leading cause of visual loss in individuals younger than 60 years, with a prevalence of about 1 in 4000. The molecular genetic diagnosis of autosomal recessive RP (arRP) is challenging due to the large genetic and clinical heterogeneity. Traditional methods for sequencing arRP genes are often laborious and not easily available and a screening technique that enables the rapid detection of the genetic cause would be very helpful in the clinical practice. The goal of this study was to develop and apply microarray-based resequencing technology capable of detecting both known and novel mutations on a single high-throughput platform. Hence, the coding regions and exon/intron boundaries of 16 arRP genes were resequenced using microarrays in 102 Spanish patients with clinical diagnosis of arRP. All the detected variations were confirmed by direct sequencing and potential pathogenicity was assessed by functional predictions and frequency in controls. For validation purposes 4 positive controls for variants consisting of previously identified changes were hybridized on the array. As a result of the screening, we detected 44 variants, of which 15 are very likely pathogenic detected in 14 arRP families (14%). Finally, the design of this array can easily be transformed in an equivalent diagnostic system based on targeted enrichment followed by next generation sequencing

Association between polymorphisms in RMI1, TOP3A, and BLM and risk of cancer, a case-control study

BACKGROUND: Mutations altering BLM function are associated with highly elevated cancer susceptibility (Bloom syndrome). Thus, genetic variants of BLM and proteins that form complexes with BLM, such as TOP3A and RMI1, might affect cancer risk as well. METHODS: In this study we have studied 26 tagged single nucleotide polymorphisms (tagSNPs) in RMI1, TOP3A, and BLM and their associations with cancer risk in acute myeloid leukemia/myelodysplatic syndromes (AML/MDS; N = 152), malignant melanoma (N = 170), and bladder cancer (N = 61). Two population-based control groups were used (N = 119 and N = 156). RESULTS: Based on consistency in effect estimates for the three cancer forms and similar allelic frequencies of the variant alleles in the control groups, two SNPs in TOP3A (rs1563634 and rs12945597) and two SNPs in BLM (rs401549 and rs2532105) were selected for analysis in breast cancer cases (N = 200) and a control group recruited from spouses of cancer patients (N = 131). The rs12945597 in TOP3A and rs2532105 in BLM showed increased risk for breast cancer. We then combined all cases (N = 584) and controls (N = 406) respectively and found significantly increased risk for variant carriers of rs1563634 A/G (AG carriers OR = 1.7 [95%CI 1.1-2.6], AA carriers OR = 1.8 [1.2-2.8]), rs12945597 G/A (GA carriers OR = 1.5 [1.1-1.9], AA carriers OR = 1.6 [1.0-2.5]), and rs2532105 C/T (CT+TT carriers OR = 1.8 [1.4-2.5]). Gene-gene interaction analysis suggested an additive effect of carrying more than one risk allele. For the variants of TOP3A, the risk increment was more pronounced for older carriers. CONCLUSION: These results further support a role of low-penetrance genes involved in BLM-associated homologous recombination for cancer risk

Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations

BACKGROUND: Linking structural effects of mutations to functional outcomes is a major issue in structural bioinformatics, and many tools and studies have shown that specific structural properties such as stability and residue burial can be used to distinguish neutral variations and disease associated mutations. RESULTS: We have investigated 39 structural properties on a set of SNPs and disease mutations from the Uniprot Knowledge Base that could be mapped on high quality crystal structures and show that none of these properties can be used as a sole classification criterion to separate the two data sets. Furthermore, we have reviewed the annotation process from mutation to result and identified the liabilities in each step. CONCLUSION: Although excellent annotation results of various research groups underline the great potential of using structural bioinformatics to investigate the mechanisms underlying disease, the interpretation of such annotations cannot always be extrapolated to proteome wide variation studies. Difficulties for large-scale studies can be found both on the technical level, i.e. the scarcity of data and the incompleteness of the structural tool suites, and on the conceptual level, i.e. the correct interpretation of the results in a cellular context.status: publishe

Tagging single-nucleotide polymorphisms in candidate oncogenes and susceptibility to ovarian cancer

Low–moderate risk alleles that are relatively common in the population may explain a significant proportion of the excess familial risk of ovarian cancer (OC) not attributed to highly penetrant genes. In this study, we evaluated the risks of OC associated with common germline variants in five oncogenes (BRAF, ERBB2, KRAS, NMI and PIK3CA) known to be involved in OC development. Thirty-four tagging SNPs in these genes were genotyped in ∼1800 invasive OC cases and 3000 controls from population-based studies in Denmark, the United Kingdom and the United States. We found no evidence of disease association for SNPs in BRAF, KRAS, ERBB2 and PIK3CA when OC was considered as a single disease phenotype; but after stratification by histological subtype, we found borderline evidence of association for SNPs in KRAS and BRAF with mucinous OC and in ERBB2 and PIK3CA with endometrioid OC. For NMI, we identified a SNP (rs11683487) that was associated with a decreased risk of OC (unadjusted Pdominant=0.004). We then genotyped rs11683487 in another 1097 cases and 1792 controls from an additional three case–control studies from the United States. The combined odds ratio was 0.89 (95% confidence interval (CI): 0.80–0.99) and remained statistically significant (Pdominant=0.032). We also identified two haplotypes in ERBB2 associated with an increased OC risk (Pglobal=0.034) and a haplotype in BRAF that had a protective effect (Pglobal=0.005). In conclusion, these data provide borderline evidence of association for common allelic variation in the NMI with risk of epithelial OC

Investigation on the role of nsSNPs in HNPCC genes – a bioinformatics approach

<p>Abstract</p> <p>Background</p> <p>A central focus of cancer genetics is the study of mutations that are causally implicated in tumorigenesis. The identification of such causal mutations not only provides insight into cancer biology but also presents anticancer therapeutic targets and diagnostic markers. Missense mutations are nucleotide substitutions that change an amino acid in a protein, the deleterious effects of these mutations are commonly attributed to their impact on primary amino acid sequence and protein structure.</p> <p>Methods</p> <p>The method to identify functional SNPs from a pool, containing both functional and neutral SNPs is challenging by experimental protocols. To explore possible relationships between genetic mutation and phenotypic variation, we employed different bioinformatics algorithms like Sorting Intolerant from Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), and PupaSuite to predict the impact of these amino acid substitutions on protein activity of mismatch repair (MMR) genes causing hereditary nonpolyposis colorectal cancer (HNPCC).</p> <p>Results</p> <p>SIFT classified 22 of 125 variants (18%) as 'Intolerant." PolyPhen classified 40 of 125 amino acid substitutions (32%) as "Probably or possibly damaging". The PupaSuite predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Based on the PolyPhen scores and availability of three-dimensional structures, structure analysis was carried out with the major mutations that occurred in the native protein coded by <it>MSH2 and MSH6 </it>genes. The amino acid residues in the native and mutant model protein were further analyzed for solvent accessibility and secondary structure to check the stability of the proteins.</p> <p>Conclusion</p> <p>Based on this approach, we have shown that four nsSNPs, which were predicted to have functional consequences (<it>MSH2</it>-Y43C, <it>MSH6</it>-Y538S, <it>MSH6</it>-S580L, <it>and MSH6</it>-K854M), were already found to be associated with cancer risk. Our study demonstrates the presence of other deleterious mutations and also endorses with <it>in vivo </it>experimental studies.</p

In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B

<p>Abstract</p> <p>Background</p> <p>In this study, instead of current biochemical methods, the effects of deleterious amino acid substitutions in <it>F8 and F9 </it>gene upon protein structure and function were assayed by means of computational methods and information from the databases. Deleterious substitutions of <it>F8 and F9 </it>are responsible for Haemophilia A and Haemophilia B which is the most common genetic disease of coagulation disorders in blood. Yet, distinguishing deleterious variants of <it>F8 and F9 </it>from the massive amount of nonfunctional variants that occur within a single genome is a significant challenge.</p> <p>Methods</p> <p>We performed an <it>in silico </it>analysis of deleterious mutations and their protein structure changes in order to analyze the correlation between mutation and disease. Deleterious nsSNPs were categorized based on empirical based and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for analysis of protein structure stability.</p> <p>Results</p> <p>Out of 510 nsSNPs in <it>F8</it>, 378 nsSNPs (74%) were predicted to be 'intolerant' by SIFT, 371 nsSNPs (73%) were predicted to be 'damaging' by PolyPhen and 445 nsSNPs (87%) as 'less stable' by I-Mutant2.0. In <it>F9</it>, 129 nsSNPs (78%) were predicted to be intolerant by SIFT, 131 nsSNPs (79%) were predicted to be damaging by PolyPhen and 150 nsSNPs (90%) as less stable by I-Mutant2.0. Overall, we found that I-Mutant which emphasizes support vector machine based method outperformed SIFT and PolyPhen in prediction of deleterious nsSNPs in both <it>F8 </it>and <it>F9</it>.</p> <p>Conclusions</p> <p>The models built in this work would be appropriate for predicting the deleterious amino acid substitutions and their functions in gene regulation which would be useful for further genotype-phenotype researches as well as the pharmacogenetics studies. These <it>in silico </it>tools, despite being helpful in providing information about the nature of mutations, may also function as a first-pass filter to determine the substitutions worth pursuing for further experimental research in other coagulation disorder causing genes.</p