Single nucleotide polymorphism hunting in cyberspace

From basic mechanisms to therapeutic perspectives in cluster headache

PURPOSE OF REVIEW

The pathophysiological understanding of cluster headache has evolved significantly over the past years. Although it is now well known that the trigeminovascular system, the parasympathetic system and the hypothalamus play important roles in its pathomechanism, we increasingly understand the functional role several neurotransmitters and hormones play in the communication between these structures.

RECENT FINDINGS

This work will give an overview of the current understanding of the role of calcitonin gene-related peptide, vasoactive intestinal peptide, pituitary adenylate cyclase-activating peptide, melatonin and orexins in cluster headache. On the basis of recent evidence, this study will also review the relevance of the monoclonal calcitonin gene-related peptide antibody galcanezumab as well as the sleep-regulating hormone melatonin in the treatment of cluster headache.

SUMMARY

Herein, we aim to review the basic mechanisms implicated in the pathophysiology of cluster headache and how the increased mechanistic understanding may lead to the discovery of novel therapeutic targets.

Mining of EST-SSR markers of Musa and their transferability studies among the members of order the Zingiberales

Expressed sequence tags (ESTs) databases of 11 Musa complementary DNA libraries were retrieved from National Center of Biotechnology Information and used for mining simple sequence repeats (SSRs). Out of 21,056 unique ESTs, SSR regions were found only in 5,158 ESTs. Among these SSR containing ESTs, the occurrence of trinucleotide repeats are the most abundant followed by mono-, di-, tetra-, hexa-, and pentanucleotides. Moreover, this study showed that the rate of class II SSRs (<20 nucleotides) was higher than the class I SSRs (<20 nucleotides), and proportion of class I and II SSRs as abundant for tri-repeats. As a representative sample, primers were synthesized for 24 ESTs, carrying >12 nucleotides of SSR region, and tested among the various genomic group of Musa accessions. The result showed that 88 % of primers were functional primers, and 43 % are showing polymorphism among the Musa accessions. Transferability studies of Musa EST-SSRs among the genera of the order Zingiberales exhibited 100 and 58 % transferability in Musaceae and Zingiberaceae, respectively. The sequence comparison of SSR regions among the different Musa accessions confirmed that polymorphism is mainly due to the variation in repeat length. High percentage of cross-species, cross-genera, and cross-family transferability also suggested that these Musa EST-SSR markers will be a valuable resource for the comparative mapping by developing COS markers, in evolutionary studies and in improvement of the members of Zingiberaceae and Musaceae.

Bioinformatic processing to identify single nucleotide polymorphism that potentially affect Ape1 function

Inactivation of DNA damage response mechanisms is associated with several disease syndromes, including cancer, aging and neurodegeneration. A major corrective pathway for alkylation or oxidative DNA damage is base excision repair (BER). As part of an effort to identify variation in DNA repair genes, we used the expressed sequence tag (EST) database to identify amino acid variation in Ape1, an essential gene in the BER repair pathway. Nucleotide substitutions were considered valid only if the amino acid changes were observed in at least two independent EST sequencing runs (i.e. two independent EST reports). In total eighty amino acid variants were identified for the Ape1 gene. Using software tools SIFT and PolyPhen, which predict impacts of amino acid substitutions on protein structure and function, twenty-six variants were predicted by both algorithms to be deleterious to protein function. Majority of these intolerant mutations such as V206C and F240S, lie within the core of the protein and may affect the stability and folding of Ape1, or in the case of N212H, N212K, and Y171N, are close to the enzyme's active site and could drastically affect its function. A few of the intolerant mutations, i.e., G178V and E217R, are surface residues and are far from the active site, and as such, the predicted effect on Ape1 stability or function is not evident. These variants are reagents for further protein function studies and molecular epidemiology studies of cancer susceptibility.

High-throughput single-base mismatch detection for genotyping of UDP-glucuronosyltransferase (UGT1A1) with probe capture assay coupled with modified allele-specific primer extension reaction (MASPER)

We have developed a new method based on specific primer extension reactions coupled with plate hybridization for high-throughput genotyping of single-base mutations. To improve the switching characteristics of the primer extension reaction, we introduced an artificial mismatch two bases upstream of the 3'-terminal base in the detection primers. A set of primers that correspond to wild-type and mutant DNA segments can be used to accurately analyze single-base mutations. The termini of these primers are at the mutation positions. The primer extension products produced by polymerase chain reaction (PCR) were captured by an oligonucleotide probe immobilized on the surface of microtiter wells and were detected by a colorimetric assay using the streptavidin-conjugated horseradish peroxidase. We used the new method to genotype 96 individuals for 211G>A (G71R) and 119 for 1456T>G (Y486D) in the UDP-glucuronosyltransferase1A1 gene; the results were completely concordant with those found by direct sequencing. The proposed method includes ordinary PCR and a microplate assay format, and may be used in routine laboratory tests.

Functional annotation of expressed sequence tags as a tool to understand the molecular mechanism controlling flower bud development in tree peony

Tree peony (Paeonia suffruticosaAndrews) is an important medicinal and ornamental plant. In China, its root bark is an important ingredient for traditional Chinese medicine. It is valued as an ornamental plant because its flower shows a wide variation in shape and color. We used flower buds at different developmental stages to construct the first cDNA library for this organism. A total of 2241 raw expressed sequence tags (ESTs) were obtained after unidirectional sequencing. After processing and assembly, they resulted in a total of 1300 unigenes [363 contigs with an average size of 3.5 ESTs (ranging from 2 up to 36) and 937 singletons]. Gene Ontology categories were assigned and further summarized into 13 broad families with biological roles according to similar functional characteristics or cellular roles. A total of 185 single nucleotide polymorphisms were detected for all contigs. We were able to detect open reading frames in the consensus sequences of 1268 unigenes. 97.5% of the ESTs showed significant similarity to sequences present in public databases. One hundred and sixty-seven short sequence repeats were obtained in the whole data set. All the analysis and information will be valuable resources for a better understanding of this important plant and also can be used for functional study in Paeoniaceae.

Mining for single nucleotide polymorphisms in pig genome sequence data

Background

Single nucleotide polymorphisms (SNPs) are ideal genetic markers due to their high abundance and the highly automated way in which SNPs are detected and SNP assays are performed. The number of SNPs identified in the pig thus far is still limited.

Results

A total of 4.8 million whole genome shotgun sequences obtained from the NCBI trace-repository with center name "SDJVP", and project name "Sino-Danish Pig Genome Project" were analysed for the presence of SNPs. Available BAC and BAC-end sequences and their naming and mapping information, all obtained from SangerInstitute FTP site, served as a rough assembly of a reference genome. In 1.2 Gb of pig genome sequence, we identified 98,151 SNPs in which one of the sequences in the alignment represented the polymorphism and 6,374 SNPs in which two sequences represent an identical polymorphism. To benchmark the SNP identification method, 163 SNPs, in which the polymorphism was represented twice in the sequence alignment, were selected and tested on a panel of three purebred boar lines and wild boar. Of these 163 in silico identified SNPs, 134 were shown to be polymorphic in our animal panel.

Conclusion

This SNP identification method, which mines for SNPs in publicly available porcine shotgun sequences repositories, provides thousands of high quality SNPs. Benchmarking in an animal panel showed that more than 80% of the predicted SNPs represented true genetic variation.

Mining for SNPs and SSRs using SNPServer, dbSNP and SSR taxonomy tree

Molecular genetic markers represent one of the most powerful tools for the analysis of genomes and the association of heritable traits with underlying genetic variation. The development of high-throughput methods for the detection of single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) has led to a revolution in their use as molecular markers. The availability of large sequence data sets permits mining for these molecular markers, which may then be used for applications such as genetic trait mapping, diversity analysis and marker assisted selection in agriculture. Here we describe web-based automated methods for the discovery of SSRs using SSR taxonomy tree, the discovery of SNPs from sequence data using SNPServer and the identification of validated SNPs from within the dbSNP database. SSR taxonomy tree identifies pre-determined SSR amplification primers for virtually all species represented within the GenBank database. SNPServer uses a redundancy based approach to identify SNPs within DNA sequences. Following submission of a sequence of interest, SNPServer uses BLAST to identify similar sequences, CAP3 to cluster and assemble these sequences and then the SNP discovery software autoSNP to detect SNPs and insertion/deletion (indel) polymorphisms. The NCBI dbSNP database is a catalogue of molecular variation, hosting validated SNPs for several species within a public-domain archive.

Using mtDNA sequences to estimate SNP parameters in ESTs

Discovery of single nucleotide polymorphisms (SNPs) requires analysis of redundant sequences such as those available in large public databases. The ability to detect SNPs, especially those of low frequency, is dependent on the depth and scale of the discovery effort. Large numbers of SNPs have been identified by mining large-scale EST surveys and whole genome sequencing projects. These surveys however are subject to ascertainment bias and the inherent errors in large-scale single pass sequencing efforts. For example, the number of steps involved in the construction and sequencing of cDNA libraries make ESTs highly error prone, resulting in an increased frequency of nonvalid SNPs obtained in these surveys. Sequences of mtDNA genes are often incorporated into cDNA libraries as an artifact of the library construction process and are typically either subtracted from cDNA libraries or are considered superfluous when evaluating the information content of EST datasets. Sequences of mtDNA genes provide a unique resource for the analysis of SNP parameters in EST projects. This study uses sequences from four turkey muscle cDNA libraries to demonstrate how mtDNA sequences gleaned from collections of ESTs can be used to estimate SNP parameters and thus help predict the validity of SNPs.

Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species

Simple sequence repeat (SSR) markers are widely used in many plant and animal genomes due to their abundance, hypervariability, and suitability for high-throughput analysis. Development of SSR markers using molecular methods is time consuming, laborious, and expensive. Use of computational approaches to mine ever-increasing sequences such as expressed sequence tags (ESTs) in public databases permits rapid and economical discovery of SSRs. Most of such efforts to date focused on mining SSRs from monocotyledonous ESTs. In this study, we have computationally mined and examined the abundance of SSRs in more than 1.54 million ESTs belonging to 55 dicotyledonous species. The frequency of ESTs containing SSRs among species ranged from 2.65% to 16.82%. Dinucleotide repeats were found to be the most abundant followed by tri- or mono-nucleotide repeats. The motifs A/T, AG/GA/CT/TC, and AAG/AGA/GAA/CTT/TTC/TCT were the predominant mono-, di-, and tri-nucleotide SSRs, respectively. Most of the mononucleotide SSRs contained 15-25 repeats, whereas the majority of the di- and tri-nucleotide SSRs contained 5-10 repeats. The comprehensive SSR survey data presented here demonstrates the potential of in silico mining of ESTs for rapid development of SSR markers for genetic analysis and applications in dicotyledonous crops.

Quantify single nucleotide polymorphism (SNP) ratio in pooled DNA based on normalized fluorescence real-time PCR

Background

Conventional real-time PCR to quantify the allele ratio in pooled DNA mainly depends on PCR amplification efficiency determination and Ct value, which is defined as the PCR cycle number at which the fluorescence emission exceeds the fixed threshold. Because of the nature of exponential calculation, slight errors are multiplied and the variations of the results seem too large. We have developed a new PCR data point analysis strategy for allele ratio quantification based on normalized fluorescence ratio.

Results

In our method, initial reaction background fluorescence was determined based upon fitting of raw fluorescence data to four-parametric sigmoid function. After that, each fluorescence data point was first subtracted by respective background fluorescence and then each subtracted fluorescence data point was divided by the specific background fluorescence to get normalized fluorescence. By relating the normalized fluorescence ratio to the premixed known allele ratio of two alleles in standard samples, standard linear regression equation was generated, from which unknown specimens allele ratios were extrapolated using the measured normalized fluorescence ratio. In this article, we have compared the results of the proposed method with those of baseline subtracted fluorescence ratio method and conventional Ct method.

Conclusion

Results demonstrated that the proposed method could improve the reliability, precision, and repeatability for quantifying allele ratios. At the same time, it has the potential of fully automatic allelic ratio quantification.

Confirming single nucleotide polymorphisms from expressed sequence tag datasets derived from three cattle cDNA libraries

Using the Phred/Phrap/Polyphred/Consed pipeline established in the National Livestock Research Institute of Korea, we predicted candidate coding single nucleotide polymorphisms (cSNPs) from 7,600 expressed sequence tags (ESTs) derived from three cDNA libraries (liver, M. longissimus dorsi, and intermuscular fat) of Hanwoo (Korean native cattle) steers. From the 7,600 ESTs, 829 contigs comprising more than two EST reads were assembled using the Phrap assembler. Based on the contig analysis, 201 candidate cSNPs were identified in 129 contigs, in which transitions (69%) outnumbered transversions (31%). To verify whether the predicted cSNPs are real, 17 SNPs involved in lipid and energy metabolism were selected from the ESTs. Twelve of these were confirmed to be real while five were identified as artifacts, possibly due to expressed sequence tag sequence error. Further analysis of the 12 verified cSNPs was performed using the program BLASTX. Five were identified as nonsynonymous cSNPs, five were synonymous cSNPs, and two SNPs were located in 3'-UTRs. Our data indicated that a relatively high SNP prediction rate (71%) from a large EST database could produce abundant cSNPs rapidly, which can be used as valuable genetic markers in cattle.

Single-nucleotide polymorphism phylotyping of Escherichia coli

We describe a rapid and easily automated phylogenetic grouping technique based on analysis of bacterial genome single-nucleotide polymorphisms (SNPs). We selected 13 SNPs derived from a complete sequence analysis of 11 essential genes previously used for multilocus sequence typing (MLST) of 30 Escherichia coli strains representing the genetic diversity of the species. The 13 SNPs were localized in five genes, trpA, trpB, putP, icdA, and polB, and were selected to allow recovery of the main phylogenetic groups (groups A, B1, E, D, and B2) and subgroups of the species. In the first step, we validated the SNP approach in silico by extracting SNP data from the complete sequences of the five genes for a panel of 65 pathogenic strains belonging to different E. coli pathovars, which were previously analyzed by MLST. In the second step, we determined these SNPs by dideoxy single-base extension of unlabeled oligonucleotide primers for a collection of 183 commensal and extraintestinal clinical E. coli isolates and compared the SNP phylotyping method to previous well-established typing methods. This SNP phylotyping method proved to be consistent with the other methods for assigning phylogenetic groups to the different E. coli strains. In contrast to the other typing methods, such as multilocus enzyme electrophoresis, ribotyping, or PCR phylotyping using the presence/absence of three genomic DNA fragments, the SNP typing method described here is derived from a solid phylogenetic analysis, and the results obtained by this method are more meaningful. Our results indicate that similar approaches may be used for a wide variety of bacterial species.

An interactive bovine in silico SNP database (IBISS)

An interactive bovine in silico SNP (IBISS) database has been created through the clustering and aligning of bovine EST and mRNA sequences. Approximately 324,000 EST and mRNA sequences were clustered to produce 29,965 clusters (producing 48,679 consensus sequences) and 48,565 singletons. A SNP screening regime was placed on variations detected in the multiple sequence alignment files to determine which SNPs are more likely to be real rather than sequencing errors. A small subset of predicted SNPs was validated on a diverse set of bovine DNA samples using PCR amplification and sequencing. Fifty percent of the predicted SNPs in the "putative >1" category were polymorphic in the population sampled. The IBISS database represents more than just a SNP database; it is also a genomic database containing uniformly annotated predicted gene mRNA and protein sequences, gene structure, and genomic organization information.

Expression-Based Discovery of Variation in the Human Glutathione S-Transferase M3 Promoter and Functional Analysis in a Glioma Cell Line Using Allele-Specific Chromatin Immunoprecipitation

Discovery and functional evaluation of biologically significant regulatory single nucleotide polymorphisms (SNP) in carcinogen metabolism genes is a difficult challenge because the phenotypic consequences may be both transient and subtle. We have used a gene expression screening approach to identify a functional regulatory SNP in glutathione S-transferase M3 (GSTM3). Anttila et al. proposed that variation in GSTM3 expression was affected by exposure to cigarette smoke and inheritance of the GSTM1-null genotype. To investigate the mechanism of GSTM3 expression was affected by exposure to cigarette smoke and inheritance of the GSTM1-null genotype. To investigate the mechanism of GSTM3 expression variation, we measured GSTM3 expression in lymphoblast cells from a human Centre d'Etude du Polymorphisme Humain family and observed a low expression phenotype. Promoter sequencing revealed two novel GSTM3 promoter SNPs: A/C and A/G SNPs, 63 and 783 bp upstream of the codon 1 start site, respectively. In this pedigree, the two children homozygous for the −63C/C genotype had 8-fold lower GSTM3 expression relative to the two children with the −63A/A genotype, with no association between A−783G SNP and GSTM3 expression. Further evaluation using genotyped glioma cell lines and with luciferase reporter constructs showed that the −63C allele was associated with lower GSTM3 expression (P &lt; 0.0001 and P &lt; 0.003). RNA pol II chromatin immunoprecipitation was combined with quantitative probed-based allelic discrimination genotyping to provide direct evidence of a 9-fold reduced RNA pol II binding capacity for the −63C allele. These results show that the GSTM3 −63C allele strongly affects gene expression in human cell lines and suggests that individuals who carry the low expression allele may be deficient in glutathione transferase catalyzed biological functions.

Comparison of four flow cytometric SNP detection assays and their use in plant improvement

Single nucleotide polymorphisms (SNPs) are attractive DNA markers due to their abundance and potential for use in automated high-throughput genotyping. Numerous SNP genotyping assays have been developed, but it is unclear which assays are best suited and most efficient for various types of plant improvement research. The objective of this study was to compare the accuracy, efficiency, and cost of four SNP genotyping assays: single-base extension (SBE), allele-specific primer extension (ASPE), oligonucleotide ligation (OL), and direct hybridization (DH). All four assay methods used the same Luminex 100 flow cytometer platform. Fifty-eight F(2)-derived soybean [Glycine max (L.) Merr.] lines from a cross between inbred lines G99-G725 and N00-3350 were genotyped at four SNPs. SBE and ASPE clearly differentiated between the two homozygotes and the heterozygote at each SNP. Results were in agreement with those identified using the SNaPshot minisequencing assay as a control. In contrast, the OL and DH assays were unable to differentiate between genotypes at some of the SNPs. However, when the cost per data point for the four different assays was compared, the cost of OL and DH was only about 70% of that for SBE, with DH requiring the least time of the four assays. On the basis of cost and labor, ASPE is more cost-effective and simpler than SBE, and would therefore be a good method for genetic mapping and diversity studies which require a large number of markers and a high level of multiplexing. DH appears to be the most economical assay for marker-assisted selection, though optimization for DH would be required for some SNP markers.

Neurogenomics: at the intersection of neurobiology and genome sciences

Neurogenomics is the study of how the genome as a whole contributes to the evolution, development, structure and function of the nervous system. It includes investigations of how genome products (transcriptomes and proteomes) vary in time and space. Neurogenomics differs markedly from the application of genome sciences to other systems, particularly in the spatial category, because anatomy and connectivity are paramount to our understanding of function in the nervous system. We focus here on some of the influences of genomics and its associated technologies on neuroscience. We discuss comparative genomics, gene expression atlases of the brain, network genetics and applications to behavioral phenotypes, and consider the culture, organization and funding of genome-scale projects.

Identifying Functional Genetic Variants in DNA Repair Pathway Using Protein Conservation Analysis

The role of DNA repair in initiation, promotion, and progression of malignancy suggests that variations in DNA repair genes confer altered cancer risk. Accordingly, DNA repair gene variants have been studied extensively in the context of cancer predisposition. Single nucleotide polymorphisms (SNPs) are the most common genetic variations in the human genome. A fraction of SNPs are located within the genes, which are likely to alter the gene expression and function. SNPs that change the encoded amino acid sequence of the proteins (non-synonymous; nsSNPs) are potentially genetic disease determinant variations. However, as not all amino acid substitutions are supposed to lead to a change in protein function, it will be necessary to have a priori prediction and determination of the functional consequences of amino acid substitutions per se, and then together with other genetic and environmental factors to study their possible association with a trait. Here we report the analysis of nsSNPs in 88 DNA repair genes and their functional evaluation based on the conservation of amino acids among the protein family members. Our analysis demonstrated that &gt;30% of variants of DNA repair proteins are highly likely to affect the function of the proteins drastically. In this study, we have shown that three nsSNPs, which were predicted to have functional consequences (XRCC1-R399Q, XRCC3-T241M, XRCC1-R280H), were already found to be associated with cancer risk. The strategy developed and applied in this study has the potential to identify functional protein variants of DNA repair pathway that may be associated with cancer predisposition.

Mining for single nucleotide polymorphisms and insertions/deletions in maize expressed sequence tag data

We have developed a computer based method to identify candidate single nucleotide polymorphisms (SNPs) and small insertions/deletions from expressed sequence tag data. Using a redundancy-based approach, valid SNPs are distinguished from erroneous sequence by their representation multiple times in an alignment of sequence reads. A second measure of validity was also calculated based on the cosegregation of the SNP pattern between multiple SNP loci in an alignment. The utility of this method was demonstrated by applying it to 102,551 maize (Zea mays) expressed sequence tag sequences. A total of 14,832 candidate polymorphisms were identified with an SNP redundancy score of two or greater. Segregation of these SNPs with haplotype indicates that candidate SNPs with high redundancy and cosegregation confidence scores are likely to represent true SNPs. This was confirmed by validation of 264 candidate SNPs from 27 loci, with a range of redundancy and cosegregation scores, in four inbred maize lines. The SNP transition/transversion ratio and insertion/deletion size frequencies correspond to those observed by direct sequencing methods of SNP discovery and suggest that the majority of predicted SNPs and insertion/deletions identified using this approach represent true genetic variation in maize.

Direct micro-haplotyping by multiple double PCR amplifications of specific alleles (MD-PASA)

Analysis of haplotypes is an important tool in population genetics, familial heredity and gene mapping. Determination of haplotypes of multiple single nucleotide polymorphisms (SNPs) or other simple mutations is time consuming and expensive when analyzing large populations, and often requires the help of computational and statistical procedures. Based on double PCR amplification of specific alleles, described previously, we have developed a simple, rapid and low-cost method for direct haplotyping of multiple SNPs and simple mutations found within relatively short specific regions or genes (micro-haplotypes). Using this method, it is possible to directly determine the physical linkage of multiple heterozygous alleles, by conducting a series of double allele-specific PCR amplification sets with simple analysis by gel electrophoresis. Application of the method requires prior information as to the sequence of the segment to be haplotyped, including the polymorphic sites. We applied the method to haplotyping of nine sites in the chicken HSP108 gene. One of the haplotypes in the population apparently arose by recombination between two existing haplotypes, and we were able to locate the point of recombination within a segment of 19 bp. We anticipate rapidly growing needs for SNP haplotyping in human (medical and pharmacogenetics), animal and plant genetics; in this context, the multiple double PCR amplifications of specific alleles (MD-PASA) method offers a useful haplotyping tool.

Characterization of DNA polymorphisms in the E-cadherin gene (CDH1) promoter region

E-cadherin is a tumor suppressor involved in epithelial cell-cell interactions. Some of the nucleotide variation in the 5'-promoter region of the gene influences transcriptional efficiency. We investigated single nucleotide polymorphisms (SNPs) in the promoter-exon 1 region of the E-cadherin gene (CDH1) using fluorescence-based PCR-single-strand conformation polymorphism (PCR-SSCP) analysis. We detected four kinds of polymorphisms between nucleotides -516 and +12, numbering from the translation initiation site. SNPs were localized at -472G-->GA, -288T-->deltaT, -285C-->A, and -54G-->C. Variants -472GA and -285A were frequently found in controls, but the -288deltaT and -54C are rare variants. We examined the effects of these variants on transcription. The activity of promoters containing the variants -288deltaT, -285A, or -54C was lower than the activity of promoters with the major variants, as assayed by a luciferase reporter gene. Variants -472G and -472GA displayed the same promoter activity. The decreased transcriptional activity from variant promoters affects the expression of E-cadherin.

In silico approaches to mechanistic and predictive toxicology: an introduction to bioinformatics for toxicologists

Bioinformatics, or in silico biology, is a rapidly growing field that encompasses the theory and application of computational approaches to model, predict, and explain biological function at the molecular level. This information rich field requires new skills and new understanding of genome-scale studies in order to take advantage of the rapidly increasing amount of sequence, expression, and structure information in public and private databases. Toxicologists are poised to take advantage of the large public databases in an effort to decipher the molecular basis of toxicity. With the advent of high-throughput sequencing and computational methodologies, expressed sequences can be rapidly detected and quantitated in target tissues by database searching. Novel genes can also be isolated in silico, while their function can be predicted and characterized by virtue of sequence homology to other known proteins. Genomic DNA sequence data can be exploited to predict target genes and their modes of regulation, as well as identify susceptible genotypes based on single nucleotide polymorphism data. In addition, highly parallel gene expression profiling technologies will allow toxicologists to mine large databases of gene expression data to discover molecular biomarkers and other diagnostic and prognostic genes or expression profiles. This review serves to introduce to toxicologists the concepts of in silico biology most relevant to mechanistic and predictive toxicology, while highlighting the applicability of in silico methods using select examples.

Sequence variation in genes and genomic DNA: methods for large-scale analysis

The large-scale typing of sequence variation in genes and genomic DNA presents new challenges for which it is not clear that current technologies are sufficiently sensitive, robust, or scalable. This review surveys the current platform technologies: separation-based approaches, which include mass spectrometry; homogeneous assays; and solid-phase/array-based assays. We assess techniques for discovering and typing variation on a large scale, especially that of single-nucleotide polymorphisms. The in-depth focus is the DNA chip/array platform, and some of the published large-scale studies are closely examined. The problem of large-scale amplification is addressed, and emerging technologies for present and future needs are indicated.

A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms

We describe a map of 1.42 million single nucleotide polymorphisms (SNPs) distributed throughout the human genome, providing an average density on available sequence of one SNP every 1.9 kilobases. These SNPs were primarily discovered by two projects: The SNP Consortium and the analysis of clone overlaps by the International Human Genome Sequencing Consortium. The map integrates all publicly available SNPs with described genes and other genomic features. We estimate that 60,000 SNPs fall within exon (coding and untranslated regions), and 85% of exons are within 5 kb of the nearest SNP. Nucleotide diversity varies greatly across the genome, in a manner broadly consistent with a standard population genetic model of human history. This high-density SNP map provides a public resource for defining haplotype variation across the genome, and should help to identify biomedically important genes for diagnosis and therapy.

Data mining: Efficiency of using sequence databases for polymorphism discovery

An open question in research on Single Nucleotide Polymorphisms (SNPs) is, what is the percentage of true SNPs found by in silico pre-screening? To this end, we selected 13 genes, and determined the complete collection of "true" polymorphisms, or polymorphisms experimentally detected, existing in these genes in our laboratory using Denaturing High Performance Liquid Chromatography (DHPLC) and fluorescent sequencing, or in other laboratories using comparable methods. The genes studied by our group were PTGS2, IGFBP1, IGFBP3, and CYP19. GenBank sequence information was then aligned using two methods, and sequence differences termed "candidate" polymorphisms. We then compared the series of SNPs obtained experimentally and in silico and we have found that in silico methods are relatively specific (up to 55% of candidate SNPs found by SNPFinder have been discovered by experimental procedure) but have low sensitivity (not more than 27% of true SNPs are found by in silico methods).

SNPing in the human genome

More than a million genetic markers in the form of single nucleotide polymorphisms are now available for use in genotype-phenotype studies in humans. The application of new strategies for representational cloning and sequencing from genomes combined with the mining of high-quality sequence variations in clone overlaps of genomic and/or cDNA sequences has played an important role in generating this new resource. The focus of variation analysis is now shifting from the identification of new markers to their typing in populations, and novel typing strategies are rapidly emerging. Assay readouts on oligonucleotide arrays, in microtiter plates, gels, flow cytometers and mass spectrometers have all been developed, but decreasing cost and increasing throughput of DNA typing remain key if high-density genetic maps are to be applied on a large scale.

High-throughput SNP genotyping by allele-specific PCR with universal energy-transfer-labeled primers

We have developed a new method for high-throughput genotyping of single nucleotide polymorphisms (SNPs). The technique involves PCR amplification of genomic DNA with two tailed allele-specific primers that introduce priming sites for universal energy-transfer-labeled primers. The output of red and green light is conveniently scored using a fluorescence plate reader. The new method, which was validated on nine model SNPs, is well suited for high-throughput, automated genotyping because it requires only one reaction per SNP, it is performed in a single tube with no post-PCR handling, the same energy-transfer-labeled primers are used for all analyses, and the instrumentation is inexpensive. Possible applications include multiple-candidate gene analysis, genomewide scans, and medical diagnostics.

An SNP map of the human genome generated by reduced representation shotgun sequencing

Most genomic variation is attributable to single nucleotide polymorphisms (SNPs), which therefore offer the highest resolution for tracking disease genes and population history. It has been proposed that a dense map of 30,000-500,000 SNPs can be used to scan the human genome for haplotypes associated with common diseases. Here we describe a simple but powerful method, called reduced representation shotgun (RRS) sequencing, for creating SNP maps. RRS re-samples specific subsets of the genome from several individuals, and compares the resulting sequences using a highly accurate SNP detection algorithm. The method can be extended by alignment to available genome sequence, increasing the yield of SNPs and providing map positions. These methods are being used by The SNP Consortium, an international collaboration of academic centres, pharmaceutical companies and a private foundation, to discover and release at least 300,000 human SNPs. We have discovered 47,172 human SNPs by RRS, and in total the Consortium has identified 148,459 SNPs. More broadly, RRS facilitates the rapid, inexpensive construction of SNP maps in biomedically and agriculturally important species. SNPs discovered by RRS also offer unique advantages for large-scale genotyping.

Using bioinformatics in gene and drug discovery

Bioinformatics has, out of necessity, become a key aspect of drug discovery in the genomic revolution, contributing to both target discovery and target validation. The author describes the role that bioinformatics has played and will continue to play in response to the waves of genome-wide data sources that have become available to the industry, including expressed sequence tags, microbial genome sequences, model organism sequences, polymorphisms, gene expression data and proteomics. However, these knowledge sources must be intelligently integrated.

Obesity--a genetic disease of adipose tissue?

Although the rapid increase in the prevalence of obesity in many countries suggests that environmental factors (mainly overeating and physical inactivity) play the most important role in the development of overweight, it is very likely that genetic factors also contribute. It appears that one major gene in combination with one or several minor genes constitute the genetic components behind excess accumulation of body fat in most obese individuals. However, monogenic obesity has been described in a few families due to changes in leptin, leptin receptor, prohormone convertase, pro-opiomelanocortin or melanocortin-4 receptor. None of the monogenic variants is of great importance for common human obesity; the latter genes are unknown so far. Results from genomic scans suggest that major obesity genes are located on chromosomes 2, 10, 11 and 20. Studies of candidate genes indicate that the minor obesity genes control important functions of adipose tissue, and that structural variance in these genes may alter adipose tissue function in a way that promotes obesity. Such genes are beta 2- and beta 3-adrenoceptors, hormone-sensitive lipase, tumour necrosis factor alpha, uncoupling protein-1, low-density lipoprotein receptor, and peroxisome proliferator activator receptor gamma-2. Some of these genes may promote obesity by gene-gene interactions (for example beta 3-adrenoceptors and uncoupling protein-1) or gene-environment interactions (for example beta 2-adrenoceptors and physical activity). Some are important for obesity only among women (for example beta 2- and beta 3-adrenoceptors, low-density lipoprotein receptor and tumour necrosis factor alpha). Few 'non-adipose' genes have so far shown a firm association to common human obesity, which could suggest that the important genes for the development of excess body fat also control adipose tissue function.

The use of single nucleotide polymorphisms in the isolation of common disease genes

The numerous successes using positional cloning to identify genes mutated in monogenic disorders has galvanised geneticists to start using similar techniques to tackle common complex diseases such as asthma, osteoarthritis, depression and early onset heart disease. The technology is currently at an intermediate stage in which linkage in family studies is being supplemented with locus-specific association studies in populations, enabling accurate localisation of the disease causing or susceptibility gene. These studies are often labour and time intensive unless focus is placed on biological candidate genes. In general, most candidate gene studies for common diseases have been unrewarding. However, single nucleotide polymorphisin (SNP) mapping has accelerated complex disease gene localisation, providing a tool to narrow the linkage region by the detection of multiple SNPs associated with the disease in a relatively small linkage disequilibriuln (LD) region. Identification of susceptibility genes will enable a better understanding of the mechanisms of the disease processes and will facilitate the discovery of new and more efficacious medicines. Whole genome SNP maps will also allow abbreviated SNP profiles to be developed for pharmacogenetic applications, enabling physicians to tailor therapeutic regimens (i.e., identify patients likely to receive therapeutic benefit and not suffer adverse reactions).

Single nucleotide polymorphism libraries: why and how are we building them?

A great deal of time and money is currently being invested in the production of large libraries of single nucleotide polymorphisms (SNPs) - variations of one nucleotide between the DNA sequence of individuals. This review compares and contrasts the available sources of SNP data, and describes the rationale behind the SNP mapping efforts, from the study of common diseases to unraveling an individual's response to medication.

Identification of 167 polymorphisms in 88 genes from candidate neurodegeneration pathways

Catalogs of intra-gene polymorphisms are needed to facilitate wide-ranging candidate gene-based association studies in common complex diseases. With this in mind, we have scanned multiple alignments of expressed sequence tags and of genomic DNA sequences (PCR products from four to eight unrelated individuals) to find polymorphisms in 195 genes putatively involved in neurodegenerative illness (including components of oxidative stress, excitotoxicity, inflammation, apoptosis and aging). This led to the discovery of 167 polymorphisms in 88 genes. These comprised 163 single nucleotide polymorphisms, one insertion/deletion, and three other variations involving more than one base pair. The polymorphisms were distributed in the exons (87), introns (70), and gene flanking regions (10). Of the exonic polymorphisms, 17 would give rise to non-synonymous amino acid substitutions. These findings now provide a valuable resource for association studies in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease.

The essence of SNPs

Single nucleotide polymorphisms (SNPs) are an abundant form of genome variation, distinguished from rare variations by a requirement for the least abundant allele to have a frequency of 1% or more. A wide range of genetics disciplines stand to benefit greatly from the study and use of SNPs. The recent surge of interest in SNPs stems from, and continues to depend upon, the merging and coincident maturation of several research areas, i.e. (i) large-scale genome analysis and related technologies, (ii) bio-informatics and computing, (iii) genetic analysis of simple and complex disease states, and (iv) global human population genetics. These fields will now be propelled forward, often into uncharted territories, by ongoing discovery efforts that promise to yield hundreds of thousands of human SNPs in the next few years. Major questions are now being asked, experimentally, theoretically and ethically, about the most effective ways to unlock the full potential of the upcoming SNP revolution.