Detection of single nucleotide polymorphisms using electrospray ionization mass spectrometry: validation of a one-well assay and quantitative pooling studies

Single nucleotide polymorphisms (SNPs) are currently being mapped and databased at a remarkable pace, providing a viable means for understanding disease susceptibility, differential drug response and human evolution. Consequently, there is an increasing demand for SNP genotyping technologies that are simple, rapid, cost effective and readily amenable to automation for high-throughput analyses. In this study, we improved the Survivor Assay, a SNP detection method based on electrospray ionization mass spectrometry (ESI-MS), with several developments. One improvement is the development of a one-well assay, requiring no off-line purification of the polymerase chain reaction product, achieved by simple addition of reagent solution into a single well. Another is the on-line separation of magnesium and dideoxynucleotides using an in-house made monolithic metal chelating column, eliminating any off-line sample preparation prior to mass spectrometric analysis. Here the Survivor Assay is extended from a proof-of-principle concept to a validated method by genotyping six SNPs from five different regions of human genomic DNA in 55 individual samples with 100% accuracy. This improved Survivor Assay eliminates the tedious and time-consuming steps of sample preparation, minimizes sample handing and offers a high-throughput analysis of SNPs by ESI-MS. The current combined preparation and analysis time is 2 min per sample. The simplicity of this method has potential for full automation and parallel chromatography and, thus, reduced analysis time. In addition, we have adapted the Survivor Assay for quantitative SNP analysis in pooled DNA samples. The capabilities and sensitivity of this approach were evaluated. We demonstrate that an allele occurring at a frequency of 2% can consistently be quantitated.     

Computational analysis for the determination of deleterious nsSNPs in human MTHFD1 gene

Single nucleotide polymorphisms (SNPs) are the most common genetic polymorphisms and play a major role in many inherited diseases. Methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) is one of the enzymes involved in folate metabolism. In the present study, the functional and structural consequences of nsSNPs of human MTHFD1 gene was analyzed using various computational tools like SIFT, PolyPhen2, PANTHER, PROVEAN, SNAP2, nsSNPAnalyzer, PhD-SNP, SNPs&GO, I-Mutant, MuPro, ConSurf, InterPro, NCBI Conserved Domain Search tool, ModPred, SPARKS-X, RAMPAGE, FT Site and PyMol. Out of 327 nsSNPs form human MTHFD1 gene, total 45 SNPs were predicted as functionally most significant SNPs, among which 17 were highly conserved and functional, 17 were highly conserved and structural residues. Among 45 most significant SNPs, 15 were predicted to be involved in post translational modifications. The p.Gly165Arg may interfere in homodimer interface formation. The p.Asn439Lys and p.Asp445Asn may interfere in binding interactions of MTHFD1 protein with cesium cation and potassium. The two SNPs (p.Asp562Gly and p.Gly637Cys) might interfere in interactions of MTHFD1 with ligand.     

Miniaturized platforms for the detection of single-nucleotide polymorphisms

Conventional methods for detecting single-nucleotide polymorphisms (SNPs), the most common form of genetic variation in human beings, are mostly limited by their analysis time and throughputs. In contrast, advances in microfabrication technology have led to the development of miniaturized platforms that can potentially provide rapid high-throughput analysis at small sample volumes. This review highlights some of the recent developments in the miniaturization of SNP detection platforms, including microarray-based, bead-based microfluidic and microelectrophoresis-based platforms. Particular attention is paid to their ease of fabrication, analysis time, and level of throughput.     

Single nucleotide polymorphism detection in the hMSH2 gene using conformation-sensitive CE

CE allows for highly reproducible analysis of DNA fragments which can be used to detect DNA mutations including SNPs. We have utilized a simple and direct CE analysis method for SNP analysis called conformation-sensitive CE (CSCE), based on the principle of single nucleotide different to produce conformational changes in the mildly denaturing solvent system. This method was applied to analysis of a mutation in the promoter region of the hMSH2 gene. This gene belongs to the human DNA mismatch repair system, which is responsible for recognizing and repairing mispaired nucleotides, and mutations in the hMSH2 gene are known to cause hereditary nonpolyposis colorectal cancer (HNPCC). PCR fragments generated from the promoter region of the hMSH2 gene, displaying either a C/C homozygote, C/T heterozygote, or T/T homozygote genotype, did not require further pretreatment before electrokinetic injection. The CE separation, using a 1xTris-borate-EDTA (TBE) buffer containing 3% w/v hydroxylethyl cellulose (HEC) and 6 M urea, was performed under reverse polarity with a separation temperature of 15 degrees C. The genotypes of 204 healthy volunteers and 13 colorectal cancer patients were determined using CSCE, and the results confirmed by DNA sequencing. While the CSCE separations were shown to be highly reproducible and sensitive for screening large populations, no correlation was observed between cancer patients and this hMSH2 gene polymorphism.     

Rapid discrimination of single-nucleotide mismatches using a microfluidic device with monolayered beads

A microfluidic device incorporating monolayered beads is developed for the discrimination of single-nucleotide mismatches, based on the differential dissociation kinetics between perfect match (PM) and mismatched (MM) duplexes. The monolayered beads are used as solid support for the immobilization of oligonucleotide probes containing a single-base variation. Target oligonucleotides hybridize to the probes, forming either PM duplexes or MM duplexes containing a single mismatch. Optimization studies show that PM and MM duplexes are easily discriminated based on their dissociation but not hybridization kinetics under an optimized buffer composition of 100 mM NaCl and 50% formamide. Detection of single-nucleotide polymorphism (SNP) using the device is demonstrated within 8 min using four probes containing all the possible single-base variants. The device can easily be modified to integrate multiplexed detection, making high-throughput SNP detection possible.     

A dynamical characterization of evolutionarily stable states

Evolutionary stability, the central solution concept in evolutionary game theory, is closely related to local asymptotic stability in a certain nonlinear dynamical system operating on the state space, the so-called "replicator dynamics". However, a purely dynamical characterization of evolutionary stability is not available in an elementary manner. This characterization can be achieved by investigating so-called "derived games" which consist of mixed strategies corresponding to successful states in the original game. Using well-known facts, several characterization results are obtained within this context. These also may shed light on the extremality properties of evolutionary stability.     

错配杂交化学发光法检测细胞色素P4501A1基因多态性

建立一种检测细胞色素P4501A1基因多态性的新方法。针对每个多态位点设计两根寡核苷酸探针，两根探针的区别仅在于突变位点处一个碱基。每个样品分别与两根探针进行杂交，采用化学发光法检测杂交体，通过两根探针的杂交信号强度之比确定基因型。与参考方法比较，该法具有快速、简便、费用低廉等优点。     

HC-HDSD: A method of hypergraph construction and high-density subgraph detection for inferring high-order epistatic interactions

Detecting epistatic interactions, or nonlinear interactive effects of Single Nucleotide Polymorphisms (SNPs), has gained increasing attention in explaining the “missing heritability” of complex diseases. Though much work has been done in mapping SNPs underlying diseases, most of them constrain to 2-order epistatic interactions. In this paper, a method of hypergraph construction and high-density subgraph detection, named HC-HDSD, is proposed for detecting high-order epistatic interactions. The hypergraph is constructed by low-order epistatic interactions that identified using the normalized co-information measure and the exhaustive search. The hypergraph consists of two types of vertices: real ones representing main effects of SNPs and virtual ones denoting interactive effects of epistatic interactions. Then, both maximal clique centrality algorithm and near-clique mining algorithm are employed to detect high-density subgraphs from the constructed hypergraph. These high-density subgraphs are inferred as high-order epistatic interactions in the HC-HDSD. Experiments are performed on several simulation data sets, results of which show that HC-HDSD is promising in inferring high-order epistatic interactions while substantially reducing the computation cost. In addition, the application of HC-HDSD on a real Age-related Macular Degeneration (AMD) data set provides several new clues for the exploration of causative factors of AMD.