A statistical method to detect chromosomal regions with DNA copy number alterations using SNP-array-based CGH data

Single nucleotide polymorphism (SNP) arrays were used to detect chromosomal regions with DNA copy number alterations. Current statistical methods for microarray-based comparative genomic hybridization (array-CGH) analysis generally assume certain relationships among adjacent markers on the same chromosome, and these assumptions may be questionable. For an SNP-array-based CGH study, multiple normal reference SNP arrays were collected. In order to utilize these normal reference SNP arrays, we derived an empirical distribution of signal ratios for each SNP marker. With an assumed threshold value for the overall error rate control and the defined signal ratio ranges for chromosomal amplification and deletion, we proposed a procedure to identify chromosomal alteration regions based on several bootstrapped one-sample t-tests and the false discovery rate control. When we have multiple arrays for different individuals with the same disease, our method can also be used to detect SNP markers for chromosomal alteration regions that are common among these individuals. We applied our method to a published SNP array data set for breast carcinoma cell lines. For an individual with breast cancer, numerous chromosomal alteration regions were identified. Compared to results of previous studies, our method identified more chromosomal alteration regions, with some being implicated in the literature to harbor genes associated with breast cancer. For multiple cancer arrays, our results suggested the existence of common chromosomal alteration regions. However, a high proportion of false positives also indicated that genetic variations among different individuals with breast cancer can be present.     

Applications of homemade kit in mutation detection of genes

With the accomplishment of Human Genome Project (HGP), single nucleotide polymorphism (SNP) and mutation detection in human genome are becom-ing a new researching focus. These researches can help us to understand the phenotype diversity of indi-vidual, disease susceptibility and drug resistance of different colonies. Traditional method used for muta-tion detection is slab gel electrophoresis, which re-mains labor-intensive and time-consuming because of the requirement of radioactivity or te…     

A multiplex single nucleotide polymorphism genotyping method using ligase‐based mismatch discrimination and CE‐SSCP

Accuracy, simplicity, and cost‐effectiveness are the most important criteria for a genotyping method for SNPs compatible with clinical use. One method developed for SNP genotyping, ligase‐based discrimination, is considered the simplest for clinical diagnosis. However, multiplex assays using this method are limited by the detection method. Although CE has been introduced as an alternative to error prone microarray‐based detection, the design process and multiplex assay procedure are complicated because of the DNA size‐dependent separation principle. In this study, we developed a simple and accurate multiplex genotyping method using reaction condition‐optimized ligation and high‐resolution CE‐based SSCP. With this high‐resolution CE‐SSCP system, we are able to use similar‐sized probes, thereby eliminating the complex probe design step and simplifying the optimization process. We found that this method could accurately discriminate single‐base mismatches in SNPs of the tp53 gene, used as targets for multiplex detection.     

A method of identifying the blood contributor in mixture stains through detecting blood-specific mRNA polymorphism

In the past decades, messenger RNA (mRNA) biomarkers have been employed to identify the origin of body fluids in forensic medicine. We hypothesized that the polymorphism of mRNA could be applied to identify individuals in mixture samples composed of two body fluids. In this study, we selected five blood-specific mRNA biomarkers of venous blood (SPTB, CD3G, AMICA1, ANK1, and GYPA) that encompass 16 SNPs to identify the mixture contributor(s). Five specific gene markers for menstrual blood, semen, skin, saliva, and vaginal secretions were amplified and typed as body-fluid positive controls. We established the system of multiplex PCR and single base extension (SBE) reaction followed by CE. The amplicon size was between 90bp and 294bp. The peripheral blood specificity was examined against other human body fluids, including saliva, semen, skin, menstrual blood, and vaginal secretion. The 16 SNPs were peripheral blood specific and could be successfully typed in homemade mixtures which are composed of different body fluids with 1 ng peripheral blood mRNA added. This system showed a supersensitivity (1:100) in detecting the trace amount of peripheral blood mixed in other body fluids and a combined discrimination power (CDP) of 0.99929 in Chinese population. It was the first time to establish a method for identifying the blood donors and deconvoluting mixtures through detecting mRNA polymorphism with SNaPshot assay. This peripheral blood specific SNP typing system showed high sensitivity to the typing of blood source specific markers regardless of other body fluids in the mixture.     

Beyond labels: A review of the application of quantum dots as integrated components of assays, bioprobes, and biosensors utilizing optical transduction

A comprehensive review of the development of assays, bioprobes, and biosensors using quantum dots (QDs) as integrated components is presented. In contrast to a QD that is selectively introduced as a label, an integrated QD is one that is present in a system throughout a bioanalysis, and simultaneously has a role in transduction and as a scaffold for biorecognition. Through a diverse array of coatings and bioconjugation strategies, it is possible to use QDs as a scaffold for biorecognition events. The modulation of QD luminescence provides the opportunity for the transduction of these events via fluorescence resonance energy transfer (FRET), bioluminescence resonance energy transfer (BRET), charge transfer quenching, and electrochemiluminescence (ECL). An overview of the basic concepts and principles underlying the use of QDs with each of these transduction methods is provided, along with many examples of their application in biological sensing. The latter include: the detection of small molecules using enzyme-linked methods, or using aptamers as affinity probes; the detection of proteins via immunoassays or aptamers; nucleic acid hybridization assays; and assays for protease or nuclease activity. Strategies for multiplexed detection are highlighted among these examples. Although the majority of developments to date have been in vitro, QD-based methods for ex vivo biological sensing are emerging. Some special attention is given to the development of solid-phase assays, which offer certain advantages over their solution-phase counterparts.     

一种基于磁性纳米粒子PCR的高通量SNP分型方法

利用磁性纳米粒子PCR扩增(MNPs-PCR)和等位基因特异性双色荧光探针(Cy3, Cy5)杂交, 建立了一种单核苷酸多态性(SNP)分型的新方法. 应用该方法对9个样本MTHFR基因的C677T多态进行检测, 野生和突变型样本正错配信号比大于9.0, 杂合型正错配信号比接近1.0, 分型结果经测序验证. 此方法无须产物纯化、浓缩, 扫描分型结果快速、直观, 是一种操作简单、快速、高通量、高灵敏度的分型方法.     

Highly multiplex and sensitive SNP genotyping method using a three‐color fluorescence‐labeled ligase detection reaction coupled with conformation‐sensitive CE

For the development of clinically useful genotyping methods for SNPs, accuracy, simplicity, sensitivity, and cost‐effectiveness are the most important criteria. Among the methods currently being developed for SNP genotyping technology, the ligation‐dependent method is considered the simplest for clinical diagnosis. However, sensitivity is not guaranteed by the ligation reaction alone, and analysis of multiple targets is limited by the detection method. Although CE is an attractive alternative to error‐prone hybridization‐based detection, the multiplex assay process is complicated because of the size‐based DNA separation principle. In this study, we employed the ligase detection reaction coupled with high‐resolution CE‐SSCP to develop an accurate, sensitive, and simple multiplex genotyping method. Ligase detection reaction could amplify ligated products through recurrence of denaturation and ligation reaction, and SSCP could separate these products according to each different structure conformation without size variation. Thus, simple and sensitive SNP analysis can be performed using this method involving the use of similar‐sized probes, without complex probe design steps. We found that this method could not only accurately discriminate base mismatches but also quantitatively detect 37 SNPs of the tp53 gene, which are used as targets in multiplex analysis, using three‐color fluorescence‐labeled probes.     

Logic Regression

Logic regression is an adaptive regression methodology that attempts to construct predictors as Boolean combinations of binary covariates. In many regression problems a model is developed that relates the main effects (the predictors or transformations thereof) to the response, while interactions are usually kept simple (two- to three-way interactions at most). Often, especially when all predictors are binary, the interaction between many predictors may be what causes the differences in response. This issue arises, for example, in the analysis of SNP microarray data or in some data mining problems. In the proposed methodology, given a set of binary predictors we create new predictors such as “X₁, X₂, X³, and X⁴ are true,” or “X⁵ or X⁶ but not X⁷ are true.” In more specific terms: we try to fit regression models of the form g(E[Y]) = b₀ + b₁ L₁ + · · · + b_n L_n , where L_j is any Boolean expression of the predictors. The L_j and b_j are estimated simultaneously using a simulated annealing algorithm. This article discusses how to fit logic regression models, how to carry out model selection for these models, and gives some examples.     

Stochastic method to control Mycobacterium tuberculosis epidemic

We study the origin of TB (tuberculosis) epidemic and complex distributions of various populations of TB infection within the stochastic framework. The stochastic nature of this disease infection could be linked to the stochastic behaviour at genome level which is exhibited in SNP (single nucleotide polymorphism) distributions of experimentally identified hotspot driver genes. Our results show the emergence of random clusters, and well-defined discrete domains of the respective species populations in the model driven by demographic stochasticity and intrinsic complex species interaction. The multifractal analysis of the time series of the species populations indicate that TB epidemic could be mainly caused by contact communication and is directional. We propose that any TB epidemic may have high chance of approximately periodic recurrence and can be controlled by optimizing some of the parameters involved in the system modelling.     

The haplotype assembly model with genotype information and iterative local-exhaustive search algorithm

The minimum error correction (MEC) model for haplotype reconstruction is efficient only when the error rate in SNP fragments is low. In order to improve reconstruction rate, additional genotype information is added into MEC model as an extension to MEC model. In this paper, we first establish a new mathematical model for haplotype assembly problem with genotype information. Several properties of the mathematical model are proved. Then an iterative local-exhaustive search algorithm is proposed based on the model and its properties. The main idea is to find the optimal pair among 2(l-1) (l denotes the number of heterozygous sites of a genotype) haplotype pairs by performing local exhaustive search for the promising haplotype pair step by step. By experiments and comparison, extensive numerical results on real data and simulated data indicate that our algorithm outperforms the other algorithms in terms of efficiency and robustness.