hRFT2基因单核苷酸多态性的生物信息学分析

旨在筛选可能与人类疾病有关的hRFT2基因单核苷酸多态性(single nucleotide polymorphisms,nsSNPs)和突变位点,从SNP数据库中检索并筛选出395个有效的hRFT2基因SNPs,其中包括30个同义SNPs(synonymous SNPs,sSNPs)和31个非同义SNPs(non-synonymous single nucleotide polymorphisms,nsSNPs)。分别采用SIFT、SNPs3D和PolyPhen-2方法分析nsSNPs引起的氨基酸替换是否可能影响hRFT2的功能。结果表明,5个nsSNPs(rs11477762、rs146302587、rs146492942、rs76947760和rs145431028)可能严重影响hRFT2蛋白的功能,其中rs76947760和rs145431028的影响已得到临床证明,另外3个nsSNPs(rs148387972、rs140391358和rs3746802)也可能对hRFT2有较大的影响。     

Accurate prediction of deleterious protein kinase polymorphisms

MOTIVATION: Contemporary, high-throughput sequencing efforts have identified a rich source of naturally occurring single nucleotide polymorphisms (SNPs), a subset of which occur in the coding region of genes and result in a change in the encoded amino acid sequence (non-synonymous coding SNPs or 'nsSNPs'). It is hypothesized that a subset of these nsSNPs may underlie common human disease. Testing all these polymorphisms for disease association would be time consuming and expensive. Thus, computational methods have been developed to both prioritize candidate nsSNPs and make sense of their likely molecular physiologic impact. RESULTS: We have developed a method to prioritize nsSNPs and have applied it to the human protein kinase gene family. The results of our analyses provide high quality predictions and outperform available whole genome prediction methods (74% versus 83% prediction accuracy). Our analyses and methods consider both DNA sequence conservation, which most traditional methods are based on, as well unique structural and functional features of kinases. We provide a ranked list of common kinase nsSNPs that have a higher probability of impacting human disease based on our analyses.     

Where in the genome are significant single nucleotide polymorphisms from genome-wide association studies located?

Recent technological progress has permitted the efficient performance of genome-wide association studies (GWAS) to map genetic variants associated with common diseases. Here, we analyzed 2,893 single nucleotide polymorphisms (SNPs) that have been identified in 593 published GWAS as associated with a disease phenotype with respect to their genomic location. In absolute numbers, most significant SNPs are located in intergenic regions and introns. When compared to their representation on the chips, there is essentially overrepresentation of nonsynonymous coding SNPs (nsSNPs), synonymous coding SNPs, and SNPs in untranscribed regions upstream of genes among the disease associated SNPs. A Gene Ontology term analysis showed that genes putatively causing a phenotype often code for membrane associated proteins or signal transduction genes.     

The ApoE gene of Alzheimer's disease (AD)

The ApoE gene responsible for the Alzheimer's disease has been examined to identify functional consequences of single-nucleotide polymorphisms (SNPs). Eighty-eight SNPs have been identified in the ApoE gene in which 31 are found to be nonsynonymous, 8 of them are coding synonymous, 33 are found to be in intron, and 3 are in untranslated region. The SNPs found in the untranslated region consisted of two SNPs from 5′ and one SNP from the 3′. Twenty-nine percent of the identified nsSNPs have been reported as damaging. In the analysis of SNPs in the UTR regions, it has been recognized that rs72654467 from 5′ and rs71673244 from 5′ and 3′ are responsible for the alteration in levels of expression. Both native and mutant protein structures were analyzed along with the stabilization residues. It has been concluded that among all SNPs of ApoE, the mutation in rs11542041 (R132S) has the most significant effect on functional variation.     

LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources

MOTIVATION: The NCBI dbSNP database lists over 9 million single nucleotide polymorphisms (SNPs) in the human genome, but currently contains limited annotation information. SNPs that result in amino acid residue changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity. RESULTS: We have developed LS-SNP, a genomic scale software pipeline to annotate nsSNPs. LS-SNP comprehensively maps nsSNPs onto protein sequences, functional pathways and comparative protein structure models, and predicts positions where nsSNPs destabilize proteins, interfere with the formation of domain-domain interfaces, have an effect on protein-ligand binding or severely impact human health. It currently annotates 28,043 validated SNPs that produce amino acid residue substitutions in human proteins from the SwissProt/TrEMBL database. Annotations can be viewed via a web interface either in the context of a genomic region or by selecting sets of SNPs, genes, proteins or pathways. These results are useful for identifying candidate functional SNPs within a gene, haplotype or pathway and in probing molecular mechanisms responsible for functional impacts of nsSNPs. AVAILABILITY: http://www.salilab.org/LS-SNP CONTACT: rachelk@salilab.org SUPPLEMENTARY INFORMATION: http://salilab.org/LS-SNP/supp-info.pdf.     

Phenotype prediction of nonsynonymous single nucleotide polymorphisms in human phase II drug/xenobiotic metabolizing enzymes: perspectives on molecular evolution

Nonsynonymous single nucleotide polymorphisms (nsSNPs) in coding regions can lead to amino acid changes that might alter the protein’s function and account for susceptibility to disease and altered drug/xenobiotic response. Many nsSNPs have been found in genes encoding human phase II metabolizing enzymes; however, there is little known about the relationship between the genotype and phenotype of nsSNPs in these enzymes. We have identified 923 validated nsSNPs in 104 human phase II enzyme genes from the Ensembl genome database and the NCBI SNP database. Using PolyPhen, Panther, and SNAP algorithms, 44%–59% of nsSNPs in phase II enzyme genes were predicted to have functional impacts on protein function. Predictions largely agree with the available experimental annotations. 68% of deleterious nsSNPs were correctly predicted as damaging. This study also identified many amino acids that are likely to be functionally critical, but have not yet been studied experimentally. There was significant concordance between the predicted results of Panther and PolyPhen, and between SNAP non-neutral predictions and PolyPhen scores. Evolutionarily non-neutral (destabilizing) amino acid substitutions are thought to be the pathogenetic basis for the alteration of phase II enzyme activity and to be associated with disease susceptibility and drug/xenobiotic toxicity. Furthermore, the molecular evolutionary patterns of phase II enzymes were characterized with regards to the predicted deleterious nsSNPs.     

In silico analysis of structural and functional consequences in p16INK4A by deleterious nsSNPs associated CDKN2A gene in malignant melanoma

In this study, we identified the most deleterious nsSNP in CDKN2A gene through structural and functional properties of its protein (p16INK4A) and investigated its binding affinity with cdk6. Out of 118 SNPs, 14 are nsSNPs in the coding region and 17 SNPs were found in the untranslated region (UTR). FastSNP suggested that 7 SNPs in the 5' UTR might change the protein expression levels. Sixty-four percent of nsSNPs are found to be damaged in PolyPhen server among the 14 nsSNPs investigated. With this effort, we modeled the mutant p16INK4A proteins based on these deleterious nsSNPs, out of which three nsSNPs associated p16INK4A had RMSD values of greater than 3.00 A with native protein. From a comparison of total energy of these three mutant proteins, we identified that the major mutation is from Aspartic acid to Tyrosine at the residue position of 84 of p16INK4A. Further, we compared the binding efficiency of both native and mutant p16INK4A with cdk6. We found that mutant p16INK4A has less binding affinity with cdk6 compared to native type. This is due to ten hydrogen bonds and eight salt bridges which exist between the native type and cdk6, whereas the mutant type makes only nine hydrogen bonds and five salt bridges with cdk6. Based on our investigation, we propose that the SNP with the ID rs11552822 could be the most deleterious nsSNP in CDKN2A gene, causing malignant melanoma, as it was well correlated with experimental studies carried out elsewhere.     

Using functional annotation for the empirical determination of Bayes Factors for genome-wide association study analysis

A genome wide association study (GWAS) typically results in a few highly significant 'hits' and a much larger set of suggestive signals ('near-hits'). The latter group are expected to be a mixture of true and false associations. One promising strategy to help separate these is to use functional annotations for prioritisation of variants for follow-up. A key task is to determine which annotations might prove most valuable. We address this question by examining the functional annotations of previously published GWAS hits. We explore three annotation categories: non-synonymous SNPs (nsSNPs), promoter SNPs and cis expression quantitative trait loci (eQTLs) in open chromatin regions. We demonstrate that GWAS hit SNPs are enriched for these three functional categories, and that it would be appropriate to provide a higher weighting for such SNPs when performing Bayesian association analyses. For GWAS studies, our analyses suggest the use of a Bayes Factor of about 4 for cis eQTL SNPs within regions of open chromatin, 3 for nsSNPs and 2 for promoter SNPs.     

Structure analysis of deleterious nsSNPs in human PALB2 protein for functional inference

Partner and Localizer of BRCA2 or PALB2 is a typical tumor suppressor protein, that responds to DNA double stranded breaks through homologous recombination repair. Heterozygous mutations in PALB2 are known to contribute to the susceptibility of breast and ovarian cancer. However, there is no comprehensive study characterizing the structural and functional impacts of SNPs located in the PALB2 gene. Therefore, it is of interest to document a comprehensive analysis of coding and non-coding SNPs located at the PALB2 loci using in silico tools. The data for 1455 non-synonymous SNPs (nsSNPs) located in the PALB2 loci were retrieved from the dbSNP database. Comprehensive characterization of the SNPs using a combination of in silico tools such as SIFT, PROVEAN, PolyPhen, PANTHER, PhD-SNP, Pmut, MutPred 2.0 and SNAP-2, identified 28 functionally important SNPs. Among these, 16 nsSNPs were further selected for structural analysis using conservation profile and protein stability. The most deleterious nsSNPs were documented within the WD40 domain of PALB2. A general outline of the structural consequences of each variant was developed using the HOPE project data. These 16 mutant structures were further modelled using SWISS Model and three most damaging mutant models (rs78179744, rs180177123 and rs45525135) were identified. The non-coding SNPs in the 3'' UTR region of the PALB2 gene were analyzed for altered miRNA target sites. The comprehensive characterization of the coding and non-coding SNPs in the PALB2 locus has provided a list of damaging SNPs with potential disease association. Further validation through genetic association study will reveal their clinical significance.     

Exploration of deleterious single nucleotide polymorphisms in late-onset Alzheimer disease susceptibility genes

Non-synonymous single nucleotide polymorphisms (nsSNPs) are considered as biomarkers to disease susceptibility. In the present study, nsSNPs in CLU, PICALM and BIN1 genes were screened for their functional impact on concerned proteins and their plausible role in Alzheimer disease (AD) susceptibility. Initially, SNPs were retrieved from dbSNP database, followed by identification of potentially deleterious nsSNPs and prediction of their effect on proteins by PolyPhen and SIFT. Protein stability and the probability of mutation occurrence were predicted using I-Mutant and PANTHER respectively. SNPs3D and FASTSNP were used for the functional analysis of nsSNPs. The functional impact on the 3D structure of proteins was evaluated by SWISSPDB viewer and NOMAD-Ref server. On analysis, 3 nsSNPs with IDs rs12800974 (T158P) of PICALM and rs11554585 (R397C) and rs11554585 (N106D) of BIN1 were predicted to be functionally significant with higher scores of I-Mutant, SIFT, PolyPhen, PANTHER, FASTSNP and SNPs3D. The mutant models of these nsSNPs also showed very high energies and RMSD values compared to their native structures. Current study proposes that the three nsSNPs identified in this study constitute a unique resource of potential genetic factors for AD susceptibility.     

Targeted genome-wide investigation identifies novel SNPs associated with diabetic nephropathy

Loci contributing to complex disease have been identified by focusing on genome-wide scans utilising non-synonymous single nucleotide polymorphisms (nsSNPs). We employed Illumina's HNS12 BeadChip (13,917 high-value SNPs) which was specifically designed to capture nsSNPs and ideally complements more dense genome-wide association studies that fail to consider many of these putatively functional variants. The HNS12 panel also includes 870 tag SNPs covering the major histocompatibility region. All individuals genotyped in this study were Caucasians with (cases) and without (controls) diabetic nephropathy. About 449 individuals with type 2 diabetes (203 cases, 246 controls) were genotyped in the initial study. 1,467 individuals with type 1 diabetes (718 cases, 749 controls) were genotyped in the follow up study. 11,152 SNPs were successfully analysed and ranked for association with diabetic nephropathy based on significance (P) values. The top ranked 32 SNPs were subsequently genotyped using MassARRAY iPLEX(?) and TaqMan technologies to investigate association of these polymorphisms with nephropathy in individuals with type 1 diabetes. The top ranked nsSNP, rs1543547 (P?=?10(-5)), is located in RAET1L, a major histocompatibility class I-related gene at 6q25.1. Of particular interest, multiple nsSNPs within the top ranked (0.2%) SNPs are within several plausible candidate genes for nephropathy on 3q21.3 and 6p21.3.     

A double-screening method to identify reliable candidate non-synonymous SNPs from chicken EST data

Discovery of non-synonymous single nucleotide polymorphisms (nsSNP), which cause amino acid substitutions, is important because they are more likely to alter protein function than synonymous SNPs (sSNP) or those SNPs that do not result in amino acid changes. By changing the coding sequences, nsSNP may play a role in heritable differences between individual organisms. In the chicken and many other vertebrates, the main obstacle for identifying nsSNP is that there is insufficient protein and mRNA sequence information for self-species referencing and thus, determination of the correct reading frame for expressed sequence tags (ESTs) is difficult. Therefore, in order to estimate the correct reading frame at nsSNP in chicken ESTs, a double-screening approach was designed using self- or cross-species protein referencing, in addition to the ESTScan coding region estimation programme. Starting with 23 427 chicken ESTs, 1210 potential SNPs were discovered using a phred/phrap/polyphred/consed pipeline process and among these, 108 candidate nsSNP were identified with the double screening method. A searchable SNP database (chicksnps) for the candidate chicken SNPs, including both nsSNPs and sSNPs is available at http://chicksnps.afs.udel.edu. The chicken SNP data described in this paper have been submitted to the data base SNP under National Center for Biotechnology Information assay ID ss4387050-ss4388259.     

Genome-wide association analysis of canine atopic dermatitis and identification of disease related SNPs

In humans, genome-wide association studies (GWAS) have been shown to be an effective and thorough approach for identifying polymorphisms associated with disease phenotypes. Here, we describe the first study to perform a genome-wide association study in canine atopic dermatitis (cAD) using the Illumina Canine SNP20 array, containing 22,362 single-nucleotide polymorphisms (SNPs). The aim of the study was to identify SNPs associated with cAD using affected and unaffected Golden Retrievers. Further validation studies were performed for potentially associated SNPs using Sequenom genotyping of larger numbers of cases and controls across eight breeds (Boxer, German Shepherd Dog, Labrador, Golden Retriever, Shiba Inu, Shih Tzu, Pit Bull, and West Highland White Terriers). Using meta-analysis, two SNPs were associated with cAD in all breeds tested. RS22114085 was identified as a susceptibility locus (p?=?0.00014, odds ratio?=?2) and RS23472497 as a protective locus (p?=?0.0015, odds ratio?=?0.6). Both of these SNPs were located in intergenic regions, and their effects have been demonstrated to be independent of each other, highlighting that further fine mapping and resequencing is required of these areas. Further, 12 SNPs were validated by Sequenom genotyping as associated with cAD, but these were not associated with all breeds. This study suggests that GWAS will be a useful approach for identifying genetic risk factors for cAD. Given the clinical heterogeneity within this condition and the likelihood that the relative genetic effect sizes are small, greater sample sizes and further studies will be required.     

Screening and structural evaluation of deleterious Non-Synonymous SNPs of ePHA2 gene involved in susceptibility to cataract formation

Age-related cataract is clinically and genetically heterogeneous disorder affecting the ocular lens, and the leading cause of vision loss and blindness worldwide. Here we screened nonsynonymous single nucleotide polymorphisms (nsSNPs) of a novel gene, EPHA2 responsible for age related cataracts. The SNPs were retrieved from dbSNP. Using I-Mutant, protein stability change was calculated. The potentially functional nsSNPs and their effect on protein was predicted by PolyPhen and SIFT respectively. FASTSNP was used for functional analysis and estimation of risk score. The functional impact on the EPHA2 protein was evaluated by using SWISSPDB viewer and NOMAD-Ref server. Our analysis revealed 16 SNPs as nonsynonymous out of which 6 nsSNPs, namely rs11543934, rs2291806, rs1058371, rs1058370, rs79100278 and rs113882203 were found to be least stable by I-Mutant 2.0 with DDG value of > -1.0. nsSNPs, namely rs35903225, rs2291806, rs1058372, rs1058370, rs79100278 and rs113882203 showed a highly deleterious tolerance index score of 0.00 by SIFT server. Four nsSNPs namely rs11543934, rs2291806, rs1058370 and rs113882203 were found to be probably damaging with PSIC score of ≥ 2. 0 by Polyp hen server. Three nsSNPs namely, rs11543934, rs2291806 and rs1058370 were found to be highly polymorphic with a risk score of 3-4 with a possible effect of Non-conservative change and splicing regulation by FASTSNP. The total energy and RMSD value was higher for the mutant-type structure compared to the native type structure. We concluded that the nsSNP namely rs2291806 as the potential functional polymorphic that is likely to have functional impact on the EPHA2 gene.     

Applications of computational algorithm tools to identify functional SNPs in cytokine genes

Understanding the functions of single nucleotide polymorphisms (SNPs) can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. However, how to identify functional SNPs from a pool containing both functional and neutral SNPs is challenging. In this study, we analyzed the genetic variations that can alter the expression and function of a group of cytokine proteins using computational tools. As a result, we extracted 4552 SNPs from 45 cytokine proteins from SNPper database. Of particular interest, 828 SNPs were in the 5'UTR region, 961 SNPs were in the 3' UTR region, and 85 SNPs were non-synonymous SNPs (nsSNPs), which cause amino acid change. Evolutionary conservation analysis using the SIFT tool suggested that 8 nsSNPs may disrupt the protein function. Protein structure analysis using the PolyPhen tool suggested that 5 nsSNPs might alter protein structure. Binding motif analysis using the UTResource tool suggested that 27 SNPs in 5' or 3'UTR might change protein expression levels. Our study demonstrates the presence of naturally occurring genetic variations in the cytokine proteins that may affect their expressions and functions with possible roles in complex human disease, such as immune diseases.     

Sequence diversity in 36 candidate genes for cardiovascular disorders.

Two strategies involving whole-genome association studies have been proposed for the identification of genes involved in complex diseases. The first one seeks to characterize all common variants of human genes and to test their association with disease. The second one seeks to develop dense maps of single-nucleotide polymorphisms (SNPs) and to detect susceptibility genes through linkage disequilibrium. We performed a molecular screening of the coding and/or flanking regions of 36 candidate genes for cardiovascular diseases. All polymorphisms identified by this screening were further genotyped in 750 subjects of European descent. In the whole set of genes, the lengths explored spanned 53.8 kb in the 5' regions, 68.4 kb in exonic regions, and 13 kb in the 3' regions. The strength of linkage disequilibrium within candidate regions suggests that genomewide maps of SNPs might be efficient ways to identify new disease-susceptibility genes, provided that the maps are sufficiently dense. However, the relatively large number of polymorphisms within coding and regulatory regions of candidate genes raises the possibility that several of them might be functional and that the pattern of genotype-phenotype association might be more complex than initially envisaged, as actually has been observed in some well-characterized genes. These results argue in favor of both genomewide association studies and detailed studies of the overall sequence variation of candidate genes, as complementary approaches.     

Geographical distribution of selected and putatively neutral SNPs in Southeast Asian malaria parasites

Loci targeted by directional selection are expected to show elevated geographical population structure relative to neutral loci, and a flurry of recent papers have used this rationale to search for genome regions involved in adaptation. Studies of functional mutations that are known to be under selection are particularly useful for assessing the utility of this approach. Antimalarial drug treatment regimes vary considerably between countries in Southeast Asia selecting for local adaptation at parasite loci underlying resistance. We compared the population structure revealed by 10 nonsynonymous mutations (nonsynonymous single-nucleotide polymorphisms [nsSNPs]) in four loci that are known to be involved in antimalarial drug resistance, with patterns revealed by 10 synonymous mutations (synonymous single-nucleotide polymorphisms [sSNPs]) in housekeeping genes or genes of unknown function in 755 Plasmodium falciparum infections collected from 13 populations in six Southeast Asian countries. Allele frequencies at known nsSNPs underlying resistance varied markedly between locations (F(ST) = 0.18-0.66), with the highest frequencies on the Thailand-Burma border and the lowest frequencies in neighboring Lao PDR. In contrast, we found weak but significant geographic structure (F(ST) = 0-0.14) for 8 of 10 sSNPs. Importantly, all 10 nsSNPs showed significantly higher F(ST) (P < 8 x 10(-5)) than simulated neutral expectations based on observed F(ST) values in the putatively neutral sSNPs. This result was unaffected by the methods used to estimate allele frequencies or the number of populations used in the simulations. Given that dense single-nucleotide polymorphism (SNP) maps and rapid SNP assay methods are now available for P. falciparum, comparing genetic differentiation across the genome may provide a valuable aid to identifying parasite loci underlying local adaptation to drug treatment regimes or other selective forces. However, the high proportion of polymorphic sites that appear to be under balancing selection (or linked to selected sites) in the P. falciparum genome violates the central assumption that selected sites are rare, which complicates identification of outlier loci, and suggests that caution is needed when using this approach.     

Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach

The AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is a member of most frequently activated proliferation and survival signaling pathway in cancer. Recently, hyperactivation of AKT1, due to functional point mutation in the pleckstrin homology (PH) domain of AKT1 gene, has been found to be associated with human colorectal, breast and ovarian cancer. Thus, considering its crucial role in cellular signaling pathway, a functional analysis of missense mutations of AKT1 gene was undertaken in this study. Twenty nine nsSNPs (non-synonymous single nucleotide polymorphism) within coding region of AKT1 gene were selected for our investigation and six SNPs were found to be deleterious by combinatorial predictions of various computational tools. RMSD values were calculated for the mutant models which predicted four substitutions (E17K, E319G, D32E and A255T) to be highly deleterious. The insight of the structural attribute was gained through analysis of, secondary structures, solvent accessibility and intermolecular hydrogen bond analysis which confirmed one missense mutation (E17K) to be highly deleterious nsSNPs. In conclusion, the investigated gene AKT1 has twenty nine SNPs in the coding region and through progressive analysis using different bioinformatics tools one highly deleterious SNP with rs121434592 was profiled. Thus, results of this study can pave a new platform to sort nsSNPs for several important regulatory genes that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case control studies.     

Next‐generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan)

To map resistance genes for Fusarium wilt (FW) and sterility mosaic disease (SMD) in pigeonpea, sequencing‐based bulked segregant analysis (Seq‐BSA) was used. Resistant (R) and susceptible (S) bulks from the extreme recombinant inbred lines of ICPL 20096 × ICPL 332 were sequenced. Subsequently, SNP index was calculated between R‐ and S‐bulks with the help of draft genome sequence and reference‐guided assembly of ICPL 20096 (resistant parent). Seq‐BSA has provided seven candidate SNPs for FW and SMD resistance in pigeonpea. In parallel, four additional genotypes were re‐sequenced and their combined analysis with R‐ and S‐bulks has provided a total of 8362 nonsynonymous (ns) SNPs. Of 8362 nsSNPs, 60 were found within the 2‐Mb flanking regions of seven candidate SNPs identified through Seq‐BSA. Haplotype analysis narrowed down to eight nsSNPs in seven genes. These eight nsSNPs were further validated by re‐sequencing 11 genotypes that are resistant and susceptible to FW and SMD. This analysis revealed association of four candidate nsSNPs in four genes with FW resistance and four candidate nsSNPs in three genes with SMD resistance. Further, In silico protein analysis and expression profiling identified two most promising candidate genes namely C.cajan_01839 for SMD resistance and C.cajan_03203 for FW resistance. Identified candidate genomic regions/SNPs will be useful for genomics‐assisted breeding in pigeonpea.