SNPing in the human genome

Cytochrome P450 1A1, 2E1 and GSTM1 gene polymorphisms and susceptibility to colorectal cancer in the Saudi population

BACKGROUND

The Saudi population has experienced a sharp increase in colorectal and gastric cancer incidences within the last few years. The relationship between gene polymorphisms of xenobiotic metabolizing enzymes and colorectal cancer (CRC) incidence has not previously investigated among the Saudi population. The aim of the present study was to investigate contributions of CYP1A1, CYP2E1, and GSTM1 gene polymorphisms.

MATERIALS AND METHODS

Blood samples were collected from CRC patients and healthy controls and genotypes were determined by polymerase chain reaction restriction fragment length polymorphism and sequencing.

RESULTS AND CONCLUSIONS

CYP2E1*6 was not significantly associated with CRC development (odd ratio=1.29; confidence interval 0.68-2.45). A remarkable and statistically significant association was observed among patients with CYP1Awt/*2A (odd ratio=3.65; 95% confidence interval 1.39-9.57). The GSTM1*0/*0 genotype was found in 2% of CRC patients under investigation. The levels of CYP1A1, CYP2E1 and GSTM1 mRNA gene expression were found to be 4, 4.2 and 4.8 fold, respectively, by quantitative real time PCR. The results of the present case-control study show that the studied Saudi population resembles Caucasians with respect to the considered polymorphisms. Investigation of genetic risk factors and susceptibility gene polymorphisms in our Saudi population should be helpful for better understanding of CRC etiology.

Drop drying on surfaces determines chemical reactivity - the specific case of immobilization of oligonucleotides on microarrays

BACKGROUND

Drop drying is a key factor in a wide range of technical applications, including spotted microarrays. The applied nL liquid volume provides specific reaction conditions for the immobilization of probe molecules to a chemically modified surface.

RESULTS

We investigated the influence of nL and μL liquid drop volumes on the process of probe immobilization and compare the results obtained to the situation in liquid solution. In our data, we observe a strong relationship between drop drying effects on immobilization and surface chemistry. In this work, we present results on the immobilization of dye labeled 20mer oligonucleotides with and without an activating 5'-aminoheptyl linker onto a 2D epoxysilane and a 3D NHS activated hydrogel surface.

CONCLUSIONS

Our experiments identified two basic processes determining immobilization. First, the rate of drop drying that depends on the drop volume and the ambient relative humidity. Oligonucleotides in a dried spot react unspecifically with the surface and long reaction times are needed. 3D hydrogel surfaces allow for immobilization in a liquid environment under diffusive conditions. Here, oligonucleotide immobilization is much faster and a specific reaction with the reactive linker group is observed. Second, the effect of increasing probe concentration as a result of drop drying. On a 3D hydrogel, the increasing concentration of probe molecules in nL spotting volumes accelerates immobilization dramatically. In case of μL volumes, immobilization depends on whether the drop is allowed to dry completely. At non-drying conditions, very limited immobilization is observed due to the low oligonucleotide concentration used in microarray spotting solutions. The results of our study provide a general guideline for microarray assay development. They allow for the initial definition and further optimization of reaction conditions for the immobilization of oligonucleotides and other probe molecule classes to different surfaces in dependence of the applied spotting and reaction volume.

Advances in understanding relationship between miRNA single nucleotide polymorphisms and colorectal cancer

The occurrence and development of colorectal cancer (CRC) are a multifactorial, multi-step evolutionary process. Gene polymorphisms are often involved in tumor development and prognosis. Recent studies have found that certain microRNA (miRNA) single nucleotide polymorphisms were associated with genetic susceptibility to and prognosis of CRC. Understanding the relationship between miRNA single nucleotide polymorphisms and CRC can provide new clues to the detection, prevention, and prognostic evaluation of CRC.

Label-free detection of polynucleotide single-base mismatch via pyrene probe excimer emission

The pyrene probe and pyrene-labeled oligonucleotides (ODNs) probe are expected to be candidates as fluorescent probe for DNA assay. In particular, label-free detection is a very hot because of its simpleness, speediness and cheapness. Herein, we have investigated the use of a pyrenylakylammonium salt, a novel fluorescent probe for the detection of one single nucleotide polymorphism (SNP) in double stranded DNA. After S1 nuclease digestion, the pyrene probes bind electrostatically to the perfect complement DNA and emit a strong excimer emission. However, treatment of the non-complementary DNA with S1 nuclease caused nucleotide fragments of less than 5 bases, which could not induce excimer emission. By comparing ratio of excimer to monomer fluorescence between normal and mutant DNA after S1 nuclease digestion, One-base mutation in DNA was detected easily. This new method may be applied to the detection of SNP.

Fluorescent nucleoside analogue displays enhanced emission upon pairing with guanine

A fluorescent nucleobase analogue, 7-aminoquinazoline-2,4-(1H,3H)-dione, is incorporated into a DNA oligonucleotide and senses mismatched pairing by displaying G-specific fluorescence enhancement.

Seq-SNPing: multiple-alignment tool for SNP discovery, SNP ID identification, and RFLP genotyping

Many sequence-alignment tools were developed to discover single nucleotide polymorphisms (SNPs) derived from resequencing in genomic regions. Whether an identified SNP is indeed a novel SNP or is already contained in dbSNP is often difficult to answer. Here, we describe a freely available software, Seq-SNPing, which is a Java-based software for SNP discovery, and ID identification and editing and visualizating of sequence alignments. It is easy to use, fast, and provides an accurate method for searching and organizing SNP IDs from multiple sequence inputs, thereby greatly facilitating genetic studies. Seq-SNPing provides SNP identification by selecting any range of unaligned or aligned sequences in sequences that are similar. SNP IDs in the National Center for Biotechnology Information (NCBI) or user-defined SNPs within a selected sequence can be identified by Seq-SNPing. Information needed for SNP-RFLP (restriction fragment length polymorphism) genotyping is provided, such as SNP-REs (restriction enzymes), the sequence trimmer, sequence finder, BLAST (Basic Local Alignment Search Tool), SNP-BLAST, UCSC BLAT (BLAST-like alignment tool), RE mining, antisequencer (Anti-seq), and T(m) (melting temperature)/GC% of selected sequence. The thresholds for SNP calling are adjustable by selecting the height of the peak for each nucleotide representative curve in the chromatogram. Therefore, Seq-SNPing can discover SNPs and identify SNP IDs in both sequence text and chromatogram files in a fast and reliable way. The software is fully compatible with Microsoft Windows. The program and user manual are available at http://bio.kuas.edu.tw/Seq-SNPing for download.

Genotyping of single nucleotide polymorphisms using base-quenched probe: a method does not invariably depend on the deoxyguanosine nucleotide

Most available methods for detecting single nucleotide polymorphisms (SNPs) are based principally on the system that can produce an increased fluorescence signal during hybridization. In the current study, we demonstrate a method of base-quenched probe for polymerase chain reaction (PCR) genotyping that requires only a pair of primers and one fluorescent probe and does not invariably depend on the deoxyguanosine nucleotide. This method further exploits the phenomenon of fluorescence quenching of fluorescent-labeled probe during hybridization to its complementary target gene's sequence. 6-Carboxyfluorescein (FAM) can be directly conjugated to a base of either adenine (A), thymine (T), cytosine (C), or guanine (G), referred to as A-, T-, C-, or G-quenched probe, respectively, at either the 5' or 3' end. For describing the method in detail, we chose apolipoprotein M (apoM) as a target gene in the current study. DNA sequencing analyses validated that all four types of base-quenched probes could provide unbiased genotyping results (K = 1, P = 0.000), although the maximum speed of fluorescence increase, max(dF/dT), when using the G-quenched probe method, was approximately twofold lower than the others (P < 0.0001). Moreover, we applied this method to detect another seven SNPs in the genomes of phospholipase A2, monocyte chemoattractant protein 1 (MCP1), and l-ficolin, further confirming our method. It is concluded that this method is precise, simple, and economic as well as suitable for large-scale genotyping studies.

A highly fluorescent nucleoside analog based on thieno[3,4-d]pyrimidine senses mismatched pairing

A highly emissive nucleobase analog, based on a thieno[3,4-d]pyrimidine core, is enzymatically incorporated into RNA oilgonucleotides that function as base discriminating fluorescent probes.

Pharmacogenomics

So far no pharmacogenetic/genomic study has been conducted specifically for anxiety disorders. Some of the presented results, however, do pertain to such disorders. For example, pharmacokinetic aspects of antidepressant drug therapy likely also apply to patients with anxiety disorders, and several genetic polymorphisms in the cytochrome P450 (CYP) gene family and drug transporter molecules, such as the multidrug resistance (MDR) gene type 1, have been reported to influence the pharmacokinetics of antidepressant drugs. At this stage of pharmacogenomics research, it is difficult to interpret the relevance of pharmacodynamic-genetic association studies conducted in depressed patients for anxiety disorders. A number of studies have reported an influence of polymorphisms of genes mostly in the serotonergic pathway on the response to antidepressant drugs in patients suffering from depression. In order to know whether they can be extrapolated to patients with anxiety disorders, clinical studies are warranted. Despite all the shortcomings of the currently available pharmacogenetic studies, this field holds great promise for the treatment of anxiety disorders. In the future, psychiatrists may be able to base treatment decisions (i.e., the type and dose of prescribed drug) on more objective parameters than only the diagnostic algorithms used now. This will limit unwanted side effects and adverse drug reactions, and could reduce time to response, resulting in a more individualized pharmacotherapy.

Automating sequence-based detection and genotyping of SNPs from diploid samples

The detection of sequence variation, for which DNA sequencing has emerged as the most sensitive and automated approach, forms the basis of all genetic analysis. Here we describe and illustrate an algorithm that accurately detects and genotypes SNPs from fluorescence-based sequence data. Because the algorithm focuses particularly on detecting SNPs through the identification of heterozygous individuals, it is especially well suited to the detection of SNPs in diploid samples obtained after DNA amplification. It is substantially more accurate than existing approaches and, notably, provides a useful quantitative measure of its confidence in each potential SNP detected and in each genotype called. Calls assigned the highest confidence are sufficiently reliable to remove the need for manual review in several contexts. For example, for sequence data from 47-90 individuals sequenced on both the forward and reverse strands, the highest-confidence calls from our algorithm detected 93% of all SNPs and 100% of high-frequency SNPs, with no false positive SNPs identified and 99.9% genotyping accuracy. This algorithm is implemented in a software package, PolyPhred version 5.0, which is freely available for academic use.

A guide to the genetics of psychiatric disease

The road to scientific discovery begins with an awareness of what is unknown. Research in science can in some ways be like putting together the pieces of a puzzle without having the benefit of the box-top picture of the completed puzzle. The "picture" in science is an understanding of how nature works in a particular instance, and it takes many separate pieces of the "puzzle" to put this understanding together. These pieces are always of different kinds of data, often obtained using different approaches and techniques. The challenge of the researcher is to picture or hypothesize each of the missing pieces before actually having them in hand, so they can be sought and tested in the laboratory. This "picturing" is actually having a clear idea of what you don't know: having a clear image of the "shape" of the missing piece. This is easy when the puzzle surrounding the missing piece is already in hand, but more difficult with less of it constrained by what is already known. In putting paper puzzles together, the shape of the pieces is not the only limitation that needs to be satisfied. There is also the picture to satisfy, that is, the picture usually has to make sense. In science these constraints can be manifold, and usually the quality of the research is judged by the number of ways a piece of data integrates into and brings together the rest of the puzzle. The multidimensionality of scientific questions makes it virtually essential that as many different pieces of the puzzle as possible be obtained. The more that is not known about the puzzle, the more pieces you need. Thus it is with the genetics of psychiatric diseases. In this guide, we will explore as many of the domains of the genetic puzzle as we are aware of. We will learn a bit of the language of each and how they fit into the puzzle with at least one anecdote to serve as an example. Mapping unknown territory is always a process, but we hope this guide will increase the reader's awareness of what is unknown.

New approaches for genotyping paraffin wax embedded breast tissue from patients with cancer: the Iowa women's health study

BACKGROUND

The use of paraffin wax embedded tissue samples as a source of DNA for genotype analysis has been limited because of difficulties in DNA extraction and single nucleotide polymorphism (SNP) analysis.

AIMS

To test the feasibility of applying the combination of a commonly used DNA isolation procedure, PureGene, and a high throughput SNP analysis method, the polymerase chain reaction (PCR)-INVADER assay, to genotype several types of paraffin wax embedded breast tissues.

METHODS

Twenty formalin fixed, paraffin wax blocks were obtained from five participants in the Iowa women's health study. Each participant provided several types of tissue including normal lymph node, normal nipple/areola tissue, inflammatory/fibrotic breast tissue, or normal breast tissue, and tumour tissue.

RESULTS

Good quality DNA (260/280 ratio >1.6) was obtained from all tissues. Normal lymph nodes yielded the largest amount of DNA (97.1 mug). DNA obtained from the samples was tested for a germline C1183T polymorphism in the MnSOD gene by three methods-PCR-RFLP (restriction fragment length polymorphism), INVADER assay, and PCR-INVADER assay. Of the 20 samples, PCR-RFLP genotyped 16, the PCR-INVADER assay 18, and the INVADER assay two. This methodology was then used to analyse five additional genotypes and confirmed the general applicability of the method.

CONCLUSIONS

This study demonstrated the feasibility of (1) using several paraffin wax embedded breast tissues as a source of DNA for germline genetic analysis, with lymph nodes providing the highest yield, and (2) using the combination of a common extraction method with a high throughput SNP analysis method, the PCR-INVADER assay.

Discrimination of single-nucleotide alterations by G-specific fluorescence quenching

A new strategy for the detection of single-base alterations through fluorescence quenching by guanine (G) is described. We have devised a novel base-discriminating fluorescent (BDF) nucleoside, 4'PyT, that contains a pyrenecarboxamide fluorophore at the thymidine sugar's C4'-position. 4'PyT-containing oligodeoxynucleotides only exhibited enhanced fluorescence in response to the presence of a complementary adenine base. In contrast, the fluorescence of mismatched duplexes containing 4'PyT/N base pairs (N = C, G, or T) was considerably weaker. This highly A-selective fluorescence was a product of guanine-specific quenching efficiency; when the complementary base to 4'PyT was a mismatch, the pyrenecarboxamide fluorophore was able to interact intimately with neighboring G bases (the most likely interaction in the case of intercalation), so effective quenching by the G bases occurred in the mismatched duplexes. In contrast, duplexes containing 4'PyT/A base pairs exhibited strong emission, since in this case the fluorophores were positioned in the minor groove and able to escape fluorescence quenching by the G bases.

Definition and clinical importance of haplotypes

Advances in genotyping and sequencing technologies, coupled with the development of sophisticated statistical methods, have afforded investigators novel opportunities to define the role of sequence variation in the development of common human diseases. At the forefront of these investigations is the use of dense maps of single-nucleotide polymorphisms (SNPs) and the haplotypes derived from these polymorphisms. Here we review basic concepts of high-density genetic maps of SNPs and haplotypes and how they are typically generated and used in human genetic research. We also provide useful examples and tools available for researchers interested in incorporating haplotypes into their studies. Finally, we discuss the latest concepts for the analysis of haplotypes related to human disease, including haplotype blocks, the International HapMap Project, and the future directions of these resources.

Genome-wide strategies for detecting multiple loci that influence complex diseases

After nearly 10 years of intense academic and commercial research effort, large genome-wide association studies for common complex diseases are now imminent. Although these conditions involve a complex relationship between genotype and phenotype, including interactions between unlinked loci, the prevailing strategies for analysis of such studies focus on the locus-by-locus paradigm. Here we consider analytical methods that explicitly look for statistical interactions between loci. We show first that they are computationally feasible, even for studies of hundreds of thousands of loci, and second that even with a conservative correction for multiple testing, they can be more powerful than traditional analyses under a range of models for interlocus interactions. We also show that plausible variations across populations in allele frequencies among interacting loci can markedly affect the power to detect their marginal effects, which may account in part for the well-known difficulties in replicating association results. These results suggest that searching for interactions among genetic loci can be fruitfully incorporated into analysis strategies for genome-wide association studies.

SNP detection using peptide nucleic acid probes and conjugated polymers: applications in neurodegenerative disease identification

A strategy employing a combination of peptide nucleic acid (PNA) probes, an optically amplifying conjugated polymer (CP), and S1 nuclease enzyme is capable of detecting SNPs in a simple, rapid, and sensitive manner. The recognition is accomplished by sequence-specific hybridization between the uncharged, fluorescein-labeled PNA probe and the DNA sequence of interest. After subsequent treatment with S1 nuclease, the cationic water soluble CP electrostatically associates with the remaining anionic PNA/DNA complex, leading to sensitized emission of the labeled PNA probe via FRET from the CP. The generation of fluorescent signal is controlled by strand-specific electrostatic interactions and is governed by the complementarity of the probe/target pair. To assess the method, we compared the ability of the sensor system to detect normal, wild-type human DNA sequences, and those sequences containing a single base mutation. Specifically, we examined a PNA probe complementary to a region of the gene encoding the microtubule associated protein tau. The probe sequence covers a known point mutation implicated in a dominant neurodegenerative dementia known as frontotemporal dementia with parkinsonism linked to chromosome 17 (FTDP-17), which has clinical and molecular similarities to Alzheimer's disease. By using an appropriate PNA probe, the conjugated polymer poly[(9,9-bis(6'-N,N,N-trimethylammoniumhexylbromide)fluorene)-co-phenylene] and S1 nuclease, unambiguous FRET signaling is achieved for the wild-type DNA and not the mutant sequence harboring the SNP. Distance relationships in the CP/PNA assay are also discussed to highlight constraints and demonstrate improvements within the system.

Identification of a pharmacogenetic effect by linkage disequilibrium mapping

A practical limitation to the identification of genetic profiles predictive of drug-induced adverse events is the number of patients with the adverse event that can be tolerated before the drug is withdrawn. Whole genome screening for regions of linkage disequilibrium (LD) associated with a particular phenotype may provide the mechanism to rapidly discover specific and sensitive profiles. We have used data from a large phase III clinical trial of tranilast and typed 76 SNPs over a 2.7 megabase region flanking the uridine diphosphate glucuronosyltranserferase 1A1 gene. Three SNPs within one LD block showed strong association with tranilast-induced hyperbilirubinemia (P<10(-13)). Our data illustrated that a genome-wide LD scan of 100,000-200,000 SNPs is sufficient to identify a pharmacogenetic association with a drug-induced adverse event.

Pharmacogenomics

The discovery of the human genome and subsequent expansion of proteomics research combined with emerging technologies such as functional imaging, biosensors and sophisticated computational biology are producing unprecedented changes in today's healthcare. The expanding knowledge of the molecular basis of cancer has shown that significant differences in gene expression patterns can guide therapy not only for neoplastic conditions, but also for a variety of diseases including inflammatory disorders, cardiovascular disease and neurodegenerative processes. As a result, the fields of pharmacogenetics and pharmacogenomics have emerged as potential new testing platforms for the individualized management of patients. An individual's response to a drug is the complex interaction of both genetic and non-genetic factors. Genetic variants in the drug target itself, disease pathway genes, or drug metabolizing enzymes may all be used as predictors of drug efficacy or toxicity. In oncology, the SNP technology has focused on detecting the predisposition for cancer, predicting of toxic responses to drugs and selecting the best individual and combinations of anti-cancer drugs. Pharmacogenomics involves the application of whole genome technologies (e.g., gene and protein expression data) for the prediction of the sensitivity or resistance of an individual's disease to a single or group of drugs. Genomic microarrays and transcriptional profiling have the ability to generate hundreds of thousands of data points requiring sophisticated and complex information systems necessary for accurate and useful data analysis. This technique has generated a wealth of new information in the fields of leukemia/lymphoma, and solid tumor classification and prediction of metastasis, drug and biomarker target discovery and pharmacogenomic drug efficacy testing.

Straightforward detection of SNPs in double-stranded DNA by using exonuclease III/nuclease S1/PNA system

Single-nucleotide polymorphisms (SNPs) in double-stranded DNA (dsDNA) have been straightforwardly genotyped by matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF MS). Peptide nucleic acid (PNA), a DNA analog, was used as a probe molecule. In its presence, genomic dsDNA was first treated with exonuclease III and then with nuclease S1. By these one-pot reactions, single-stranded DNA fragments including the SNP sites were formed in situ. These fragments were directly analyzed by MALDI-TOF MS, and the identity of the DNA base at the SNP site was determined in terms of mass number. By using two or more PNA probes simultaneously, multiplex analysis was also successful. Various genotypes of apolipoprotein E gene (epsilon2/epsilon2, epsilon3/epsilon3, epsilon4/epsilon4, epsilon2/epsilon3 and epsilon3/epsilon4) were identified from dsDNA obtained by PCR from corresponding patients.

Behavioural screening in mutagenised mice—in search for novel animal models of psychiatric disorders

Complementary to the 'gene-driven' analysis of gene function, 'phenotype-driven' approaches can be performed and may be equally important. Despite the current availability of a long list of mouse mutants, there remains an appreciable need for behavioural phenotypes in mouse models permitting to learn more about the aetiology of psychiatric disorders. This lack can be compensated by phenotype-driven ethyl-nitrosourea (ENU)-mutagenesis programs which aim at identifying novel phenotypes without any a priori assumptions, thus, representing a unique possibility to create novel animal models which approximate the underlying genetic aetiology. The power of mouse mutagenesis critically depends on the phenotyping procedures performed. In the case of ENU-mutants, behavioural phenotyping is especially challenging, as behavioural profiles have to be identified in single individuals. For high-throughput screening, approaches have been made to establish standardised screening protocols including a combination of well-validated, easy to perform behavioural tests. Different strategies are being introduced, which are used in ENU-mutagenesis screens to identify behavioural mutants representing possible endophenotypes of psychiatric diseases.

Combined flash- and glow-type chemiluminescent reactions for high-throughput genotyping of biallelic polymorphisms

The difference in light-emission kinetics between the Ca(2+)-triggered bioluminescent reaction of the photoprotein aequorin (AEQ) and the alkaline phosphatase (ALP)-catalyzed chemiluminescent hydrolysis of dioxetane aryl phosphate substrates was exploited for the analysis of both alleles of biallelic polymorphisms in a single microtiter well. The genotyping of the IVS-1-110 locus of the human beta-globin gene was chosen as a model. Genomic DNA, isolated from whole blood, was first subjected to polymerase chain reaction using primers flanking the polymorphic site. A single oligonucleotide-ligation reaction employing two allele-specific probes, labeled with biotin and digoxigenin, and a common probe carrying a characteristic tail was then performed. The ligation products were captured in a microtiter well through hybridization of the tail with an immobilized complementary oligonucleotide. The products were detected by adding a mixture of streptavidin-aequorin complex and antidigoxigenin-alkaline phosphatase conjugate. AEQ was measured first by adding Ca(2+) and integrating the signal for 3s followed by the addition of the substrate for ALP. The ratio of the luminescence signals obtained from ALP and AEQ gives the genotype of each sample. The coefficient of variation of the dual assay ranged from 7 to 11% for each allele. The reproducibility of the ALP/AEQ signal ratio was about 14%. The proposed assay allows for many samples to be screened in parallel in a single microtiter plate, for single-nucleotide polymorphisms.

Evolutionary algorithms for the selection of single nucleotide polymorphisms

BACKGROUND

Large databases of single nucleotide polymorphisms (SNPs) are available for use in genomics studies. Typically, investigators must choose a subset of SNPs from these databases to employ in their studies. The choice of subset is influenced by many factors, including estimated or known reliability of the SNP, biochemical factors, intellectual property, cost, and effectiveness of the subset for mapping genes or identifying disease loci. We present an evolutionary algorithm for multiobjective SNP selection.

RESULTS

We implemented a modified version of the Strength-Pareto Evolutionary Algorithm (SPEA2) in Java. Our implementation, Multiobjective Analyzer for Genetic Marker Acquisition (MAGMA), approximates the set of optimal trade-off solutions for large problems in minutes. This set is very useful for the design of large studies, including those oriented towards disease identification, genetic mapping, population studies, and haplotype-block elucidation.

CONCLUSION

Evolutionary algorithms are particularly suited for optimization problems that involve multiple objectives and a complex search space on which exact methods such as exhaustive enumeration cannot be applied. They provide flexibility with respect to the problem formulation if a problem description evolves or changes. Results are produced as a trade-off front, allowing the user to make informed decisions when prioritizing factors. MAGMA is open source and available at http://snp-magma.sourceforge.net. Evolutionary algorithms are well suited for many other applications in genomics.

Single-nucleotide mutations for plant functional genomics

In the present genomics era, powerful reverse-genetic strategies are needed to elucidate gene and protein function in the context of a whole organism. However, most current techniques lack the generality and high-throughput potential of descriptive genomic approaches, such as those that rely on microarray hybridization. For example, in plant research, effective insertional mutagenesis and transgenic methods are limited to relatively few species or are inefficient. Fortunately, single-nucleotide changes can be induced in any plant by using traditional chemical mutagens, and progress has been made in efficiently detecting changes. Because base substitutions in proteins provide allelic series, and not just knockouts, this strategy can yield refined insights into protein function. Here, we review recent progress that has been made in genome-wide screening for point mutations and natural variation in plants. Its general applicability leads to the expectation that traditional mutagenesis followed by high-throughput detection will become increasingly important for plant functional genomics.

Genetics of the immune response: identifying immune variation within the MHC and throughout the genome

With the advent of modern genomic sequencing technology the ability to obtain new sequence data and to acquire allelic polymorphism data from a broad range of samples has become routine. In this regard, our investigations have started with the most polymorphic of genetic regions fundamental to the immune response in the major histocompatibility complex (MHC). Starting with the completed human MHC genomic sequence, we have developed a resource of methods and information that provide ready access to a large portion of human and nonhuman primate MHCs. This resource consists of a set of primer pairs or amplicons that can be used to isolate about 15% of the 4.0 Mb MHC. Essentially similar studies are now being carried out on a set of immune response loci to broaden the usefulness of the data and tools developed. A panel of 100 genes involved in the immune response have been targeted for single nucleotide polymorphism (SNP) discovery efforts that will analyze 120 Mb of sequence data for the presence of immune-related SNPs. The SNP data provided from the MHC and from the immune response panel has been adapted for use in studies of evolution, MHC disease associations, and clinical transplantation.

Comparison study for genotyping of a single-nucleotide polymorphism in the tumor necrosis factor promoter gene

A variety of methods that address the detection of single-nucleotide polymorphism (SNP) have been used in molecular diagnostics. The allele-specific polymerase chain reaction (ASPCR) has been one of the most extensively studied, including its application in the tumor necrosis factor (TNF)(-308) genotyping. Many studies have demonstrated that the ASPCR sensitivity and specificity depends on various PCR parameters, with mismatches occurring to a degree of 4%. The purpose of our study was to evaluate a comparison of genotyping of the TNF(-308) using an ASPCR and automated sequencing (ASEQ). In a total of 204 DNA samples, their duplicate examination by the ASPCR and ASEQ revealed concordant results in 96.5% and mismatches in 3.5% genotypes. Depending on the target TNF(-308G/G), TNF(-308G/A) , TNF(-308A/A) sequences, this translated into decreased ASPCR sensitivity to a degree of 98.6%, 94.2%, 60.0%, specificity 94.7%, 97.4%, 100.0%, positive predictive values 97.9%, 92.5%, 100.0%, and negative predictive values 96.4%, 98.0%, 99.0%, respectively. Based on these results, we found ASEQ to be more accurate than ASPCR for the TNF(-308) genotyping. By eliminating the need of empirical determination of appropriate PCR conditions for each studied sequence, ASEQ provides a sensitive and reproducible quality-control benchmark for other SNP assays.

Integration of molecular diagnostics with therapeutics: implications for drug discovery and patient care

The Introduction of targeted therapeutics into clinical practice has created major opportunities for further development of the molecular diagnostics industry. Emerging genomic and proteomic technologies and information are now resulting in the molecular subclassification of disease as the basis for diagnosis, prognosis and therapeutic selection. The ultimate goals of personalized medicine are to take advantage of a molecular understanding of disease, both to optimize drug development and direct preventive resources and therapeutic agents at the right population of people while they are still well. Single nucleotide polymorphisms identification and genotyping have uncovered predisposition markers from cancer and heart disease as well in the prediction of both drug efficacy and toxicity. Pharmacogenomic and pharmacodynamic assays are being developed to enhance the speed and decrease the cost of drug development, as well as reduce side effects and increase response rates in a variety of diseases. The traditional trial and error practice of medicine is progressively eroding in favor of more precise marker-assisted diagnosis and safer and more effective molecularly guided treatment of disease. For the diagnostics industry this represents an unprecedented opportunity for integration, increased value and commercial opportunities for molecularly-derived tests.

Multiplexed microsphere-based flow cytometric assays

Flow cytometry has become an indispensable tool for clinical diagnostics and basic research. Although primarily designed for cellular analysis, flow cytometers can detect any particles in the lower micron range, including inert microspheres of different sizes, dyed with various fluorochromes. Over the past 20 years, microspheres have been used as calibrators for flow cytometers and also as a solid support for numerous molecular reactions quantitated by flow cytometry. Proteins, oligonucleotides, polysaccharides, lipids, or small peptides have been adsorbed or chemically coupled to the surface of microspheres to capture analytes that are subsequently measured by a fluorochrome-conjugated detection molecule. More recently, assays for similar analytes have been multiplexed, or analyzed in the same assay volume, by performing each reaction on a set of microspheres that are dyed to different fluorescent intensities and, therefore, are spectrally distinct. Some recent applications with fluorescent microspheres have included cytokine quantitation, single nucleotide polymorphism genotyping, phosphorylated protein detection, and characterization of the molecular interactions of nuclear receptors. The speed, sensitivity, and accuracy of flow cytometric detection of multiple binding events measured in the same small volume have the potential to replace many clinical diagnostic and research methods and deliver data on hundreds of analytes simultaneously.

Single cell expression analysis--pharmacogenomic potential

A fundamental challenge in biology is to correlate physiology with gene expression in specific cell types. This can only be achieved by understanding gene expression at the level of the single cell because, in many systems, each cell has the capacity to express a unique set of genes. Therefore, each cell can be considered to be functionally distinct. A clearer understanding of gene expression differences at such a discrete level provides an opportunity to develop drugs with more targeted pharmacologies or with decreased side effects.

Multiplexed, high-throughput genotyping by single-base extension and end-labeled free-solution electrophoresis

Technologies that allow for high-throughput, economical, and accurate single nucleotide polymorphism (SNP) genotyping are becoming crucial for modern genomic efforts. Here, we present a method for multiplexed single-base extension (SBE) genotyping that takes advantage of the unique separation modalities made possible via end-labeled free-solution electrophoresis (ELFSE). Three unique SBE oligonucleotide primers, which probe for mutations of clinical importance in the human p53 gene, were covalently conjugated to three unique polypeptoid frictional end labels and mixed together. This primer-polypeptoid conjugate cocktail was then used in a multiplexed SBE reaction followed by free-solution separation in a 96-capillary array electrophoresis (CAE) instrument. The study was designed to demonstrate multiplexed SNP genotyping of several loci in a single reaction and a single subsequent analysis. Further, the electrophoretic analysis was conducted without any viscous polymeric separation media, was complete in less than 10 min, and can be implemented in any capillary or microfluidic electrophoretic system with four-color fluorescent detection capabilities. Multiplexed SBE-ELFSE genotyping analysis resulted in the simultaneous and accurate genotyping of three p53 loci on five different DNA templates in a single reaction set and single CAE analysis. With the implementation of this method in 96 or more capillaries in parallel, high-throughput screening of SNPs will be accessible to a large number of laboratories.

Microarrays and genetic epidemiology: a multipurpose tool for a multifaceted field

The advent of molecular technologies that allow the collection and analysis of large amounts of genetic data is rapidly transforming the field of genetic epidemiology. Whether monitoring infectious outbreaks or identifying genotypic variations that underlie disease susceptibility, genetic epidemiology relies heavily on the analysis of multiple, independently derived results. By allowing the simultaneous monitoring of thousands of genetic or expression data points, microarrays are emerging as particularly powerful tools. Several recent reviews have described array manufacturing and the types of scientific questions that can exploit this technology, but few have addressed how the intended use of an array can dictate its design. This review will focus on this latter issue, with particular emphasis on the genetic epidemiology of infectious disease. The design of arrays for genotyping, expression profiling, and fingerprinting are presented, and examples of recent epidemiological studies are used to illustrate the applications' strong points and limitations. In addition to discussing arrays' ability to provide global views of gene identity or function, the review will describe design options for creating arrays that detect multiple genetic variations. It will also examine the reliability of array-generated fingerprints, assay accessibility, and possibilities for sharing and comparing data across studies. Although many challenges lie ahead, microarrays' multiple abilities appear uniquely poised to accelerate the advance of genetic epidemiology's multiple fronts.

Suspension array technology: evolution of the flat-array paradigm

Suspension arrays of microspheres analyzed using flow cytometry offer a new approach to multiplexed assays for large-scale screening applications. By optically encoding micron-sized polymer particles, suspension microarrays can be created to enable highly multiplexed analysis of complex samples. Each element in the array is comprised of a subpopulation of particles with distinct optical properties and each array element bears a different surface receptor. Nucleic acids, proteins, lipids or carbohydrates can serve as receptors to support the analysis of a wide range of biomolecular assemblies, and applications in genomic and proteomic research are being developed. Coupled with recent innovations for rapid serial analysis of samples, molecular analysis with microsphere arrays holds significant potential as a general analysis platform for both research and clinical applications.

Genetic variance and lipolysis regulation: implications for obesity

Catecholamines are the major lipolytic hormones in human fat cells, and lipolytic catecholamine resistance is described in obesity. Studies on twins and in rare genetic disorders suggest a strong heredity component of catecholamine-induced lipolysis. Polymorphisms in catecholamine receptor signalling pathways have been described, several of which associate with obesity. Many polymorphisms in adrenoceptor genes are functional in transfected cell lines. The importance of polymorphisms in catecholamine signalling pathways for lipolysis regulation is discussed. A Trp64Arg polymorphism in the beta3-receptor, which associates with obesity, is accompanied by changes in lipolytic sensitivity of the receptor in human fat cells. Similarly, a Gln16Glu and an Arg164Ile variation in the beta2-adrenoceptor cause marked variations in the lipolytic sensitivity of this receptor in human adipocytes. Furthermore, beta2-adrenoceptor gene polymorphisms associate with obesity. A dinucleotide (CA) intron repeat in hormone-sensitive lipase gene is linked to obesity and markedly decreases the ability of catecholamines to activate the lipase and thereby lipolysis in human fat cells. However, an Arg389Gly polymorphism in the beta1-adrenoceptor, which alters receptor function in transfected cell lines, has no effect on lipolysis in human fat cells and is not associated with obesity. Thus, polymorphism in human genes that are involved in catecholamine signal transduction have effects on fat cell lipolysis and also relate to obesity. The lipolysis effects of these polymorphisms cannot always be predicted from gene transfer experiments on artificial cell lines. It is possible that genetic variance in catecholamine signalling pathways, through alterations in adipocyte lipolysis, may promote obesity.

Population-based gene discovery in the post-genomic era

The complex genetic nature of many common diseases makes the identification of the genes that predispose to these ailments a difficult task. Consequently, many factors have to be considered in choosing the optimal approach to be taken in gene discovery of susceptibility genes. The elements to be considered include the applicability of a family-based linkage paradigm versus a population-based association design and the effects of linkage disequilibrium (LD) and genotypic relative risk (GRR). In this review we discuss these various points and describe the impact on LD and GRR of studying an isolated (also termed 'founder' or 'homogeneous') population, such as Ashkenazi Jews, as compared to an outbred population, such as Caucasians.

Rational drug discovery revisited: interfacing experimental programs with bio- and chemo-informatics

Over the past few years, bio- and chemo-informatics have rapidly evolved as related yet distinct disciplines. In drug discovery, it is increasingly recognized that combining and integrating these approaches is crucial for their successful application. In addition, the use of complementary experimental and informatics techniques increases the chances of success in many stages of the discovery process, from the identification of novel targets and elucidation of their functions to the discovery and development of lead compounds with desired properties. This review highlights recent trends that emphasize the role of integrated bio- and chemo-informatics research in drug discovery and discusses representative concepts and methodologies.