PromoLign: a database for upstream region analysis and SNPs

Bioinformatics tools for discovery and functional analysis of single nucleotide polymorphisms

With the high speed DNA sequencing of genome, databases of genome data continue to grow, and the understanding of genetic variation between individuals grows as well. Single nucleotide polymorphisms (SNPs), a main type of genetic variation, are increasingly important resource for understanding the structure and function of the human genome and become a valuable resource for investigating the genetic basis of disease. During the past years, in addition to experimental approaches to characterize specific variants, intense bioinformatics techniques were applied to understand effects of these genetic changes. In the genetics studies, one intends to understand the molecular basis of disease, and computational methods are becoming increasingly important for SNPs selection, prediction and understanding the downstream effects of genetic variation. The review provides systematic information on the available resources and methods for SNPs discovery and analysis. We also report some new results on DNA sequence-based prediction of SNPs in human cytochrome P450, which serves as an example of computational methods to predict and discovery SNPs. Additionally, annotation and prediction of functional SNPs, as well as a comprehensive list of existing tools and online recourses, are reviewed and described.

SNP association mapping across the extended major histocompatibility complex and risk of B-cell precursor acute lymphoblastic leukemia in children

The extended major histocompatibility complex (xMHC) is the most gene-dense region of the genome and harbors a disproportionately large number of genes involved in immune function. The postulated role of infection in the causation of childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL) suggests that the xMHC may make an important contribution to the risk of this disease. We conducted association mapping across an approximately 4 megabase region of the xMHC using a validated panel of single nucleotide polymorphisms (SNPs) in childhood BCP-ALL cases (n=567) enrolled in the Northern California Childhood Leukemia Study (NCCLS) compared with population controls (n=892). Logistic regression analyses of 1,145 SNPs, adjusted for age, sex, and Hispanic ethnicity indicated potential associations between several SNPs and childhood BCP-ALL. After accounting for multiple comparisons, one of these included a statistically significant increased risk associated with rs9296068 (OR=1.40, 95% CI=1.19-1.66, corrected p=0.036), located in proximity to HLA-DOA. Sliding window haplotype analysis identified an additional locus located in the extended class I region in proximity to TRIM27 tagged by a haplotype comprising rs1237485, rs3118361, and rs2032502 (corrected global p=0.046). Our findings suggest that susceptibility to childhood BCP-ALL is influenced by genetic variation within the xMHC and indicate at least two important regions for future evaluation.

Chapter 15: disease gene prioritization

Disease-causing aberrations in the normal function of a gene define that gene as a disease gene. Proving a causal link between a gene and a disease experimentally is expensive and time-consuming. Comprehensive prioritization of candidate genes prior to experimental testing drastically reduces the associated costs. Computational gene prioritization is based on various pieces of correlative evidence that associate each gene with the given disease and suggest possible causal links. A fair amount of this evidence comes from high-throughput experimentation. Thus, well-developed methods are necessary to reliably deal with the quantity of information at hand. Existing gene prioritization techniques already significantly improve the outcomes of targeted experimental studies. Faster and more reliable techniques that account for novel data types are necessary for the development of new diagnostics, treatments, and cure for many diseases.

A functional XPNPEP2 promoter haplotype leads to reduced plasma aminopeptidase P and increased risk of ACE inhibitor-induced angioedema

Angiotensin I-converting enzyme inhibitors (ACEi) are widely used antihypertensive agents that are associated with a potentially life-threatening reaction, ACEi-angioedema. Impaired metabolism of bradykinin and des-Arg(9) -bradykinin by aminopeptidase P (APP) is a key contributor to ACEi-angioedema. This study aimed to characterize the genetic regulation of the XPNPEP2 gene and identify the genetic factors contributing to variance in plasma APP activity and ACEi-angioedema. Additive genetic factors accounted for 47.3% of variance in plasma APP activity in healthy individuals. Nested deletion analysis identified the minimal promoter (-338 bp to -147 bp) and an enhancer region (-2,502 bp to -2,238 bp). Three polymorphisms (c.-2399C>A, c.-1612G>T, and c.-393G>A) were significantly associated with plasma APP activity. Haplotype ATG was significantly associated with reduced reporter gene activity and with reduced plasma APP activity. The c.-2399C>A polymorphism was located in an enhancer region and was predicted to differentially bind hepatic nuclear factor 4 (HNF4). Over expression of HNF4 increased the activation of haplotype ATG compared with haplotype CGG. In a case control study of subjects with a history of ACEi-angioedema, haplotype ATG was significantly associated with ACEi-angioedema (OR 4.87 [1.78-13.35] P = 0.002). The ATG haplotype is functional and contributes to ACEi-angioedema through a reduction in APP.

A PPARα promoter variant impairs ERR-dependent transactivation and decreases mortality after acute coronary ischemia in patients with diabetes

Activation of peroxisome proliferator-activated receptor alpha (PPARα) occurs in animal models of diabetes (DM) and is implicated in pathological responses to myocardial ischemia. Using bioinformatics, we identified a single nucleotide polymorphism (SNP) in the PPARα gene promoter (PPARA -54,642 G>A; rs135561) that altered the consensus sequence for a nuclear receptor binding site. Electrophoretic mobility shift assays showed that the domain bound two known PPARA transcriptional activators, estrogen-related receptor (ERR)-α and -γ and that PPARA G bound with greater affinity than PPARA A (>2-fold; P<0.05). Likewise, promoter-reporter analyses showed enhanced transcriptional activity for PPARA G vs. PPARA A for both ERR-α and -γ (3.1 vs.1.9-fold; P<0.05). Since PPARα activation impairs post-ischemic cardiac function in experimental models of DM, we tested whether decreased PPARA transcription in PPARA A carriers favorably impacted outcome after acute coronary ischemia in 705 patients hospitalized with acute coronary syndromes (ACS; 552 Caucasian, 106 African American). PPARA A allele frequencies were similar to non-diseased subjects. However, PPARA genotype correlated with 5-year mortality in diabetic (22.2% AA vs. 18.8% AG vs. 39.5% GG; P = 0.008), but not non-diabetic (P = 0.96) subjects (genotype by diabetes interaction P = 0.008). In the diabetic ACS subjects, PPARA A carriers had strikingly reduced all-cause mortality compared to PPARA G homozygotes, (unadjusted HR 0.44, 95% CI 0.26-0.75; P = 0.003; adjusted HR 0.48, 95% CI 0.27-0.83; P = 0.009). Consistent with previous descriptions of PPARα in experimental models and human disease, we describe a novel PPARA promoter SNP that decreases transcriptional activation of PPARA and protects against mortality in diabetic patients after ACS.

Candidate gene analysis of femoral neck trabecular and cortical volumetric bone mineral density in older men

In contrast to conventional dual-energy X-ray absorptiometry, quantitative computed tomography separately measures trabecular and cortical volumetric bone mineral density (vBMD). Little is known about the genetic variants associated with trabecular and cortical vBMD in humans, although both may be important for determining bone strength and osteoporotic risk. In the current analysis, we tested the hypothesis that there are genetic variants associated with trabecular and cortical vBMD at the femoral neck by genotyping 4608 tagging and potentially functional single-nucleotide polymorphisms (SNPs) in 383 bone metabolism candidate genes in 822 Caucasian men aged 65 years or older from the Osteoporotic Fractures in Men Study (MrOS). Promising SNP associations then were tested for replication in an additional 1155 men from the same study. We identified SNPs in five genes (IFNAR2, NFATC1, SMAD1, HOXA, and KLF10) that were robustly associated with cortical vBMD and SNPs in nine genes (APC, ATF2, BMP3, BMP7, FGF18, FLT1, TGFB3, THRB, and RUNX1) that were robustly associated with trabecular vBMD. There was no overlap between genes associated with cortical vBMD and trabecular vBMD. These findings identify novel genetic variants for cortical and trabecular vBMD and raise the possibility that some genetic loci may be unique for each bone compartment.

Annotating the regulatory genome

Determining the timing and molecular repertoire responsible for gene expression is fundamental to understanding a gene's function. Heritable differences in this character are increasingly regarded as explanatory for complex and common traits. For many known trait-predisposing genes, studies have sought to elucidate the associated logic behind gene regulation. However, there exist many challenges in deciphering these mechanisms. Among them, it is recognized that we have limited understanding of regulatory complexity, the current models of gene regulation have low specificity and any gene's regulatory logic is dependent on biological context. Addressing these limitations and defining the regulatory genome is an ongoing challenge for molecular biology. We discuss current efforts to define and annotate the regulatory genome by focusing on curation and text-mining activities. We further highlight the type of information and curation process for describing regulatory elements within the ORegAnno database ( www.oreganno.org ) and how the general standards for such information are changing.

High-density association study of 383 candidate genes for volumetric BMD at the femoral neck and lumbar spine among older men

Genetics is a well-established but poorly understood determinant of BMD. Whereas some genetic variants may influence BMD throughout the body, others may be skeletal site specific. We initially screened for associations between 4608 tagging and potentially functional single nucleotide polymorphisms (SNPs) in 383 candidate genes and femoral neck and lumbar spine volumetric BMD (vBMD) measured from QCT scans among 862 community-dwelling white men >or=65 yr of age in the Osteoporotic Fractures in Men Study (MrOS). The most promising SNP associations (p < 0.01) were validated by genotyping an additional 1156 white men from MrOS. This analysis identified 8 SNPs in 6 genes (APC, DMP1, FGFR2, FLT1, HOXA, and PTN) that were associated with femoral neck vBMD and 13 SNPs in 7 genes (APC, BMPR1B, FOXC2, HOXA, IGFBP2, NFATC1, and SOST) that were associated with lumbar spine vBMD in both genotyping samples (p < 0.05). Although most associations were specific to one skeletal site, SNPs in the APC and HOXA gene regions were associated with both femoral neck and lumbar spine BMD. This analysis identifies several novel and robust genetic associations for volumetric BMD, and these findings in combination with other data suggest the presence of genetic loci for volumetric BMD that are at least to some extent skeletal-site specific.

Evaluating the accuracy of a functional SNP annotation system

Many common and chronic diseases are influenced at some level by genetic variation. Research done in population genetics, specifically in the area of single nucleotide polymorphisms (SNPs) is critical to understanding human genetic variation. A key element in assessing role of a given SNP is determining if the variation is likely to result in change in function. The SNP Integration Tool (SNPit) is a comprehensive tool that integrates diverse, existing predictors of SNP functionality, providing the user with information for improved association study analysis. To evaluate the SNPit system, we developed an alternative gold standard to measure accuracy using sensitivity and specificity. The results of our evaluation demonstrated that our alternative gold standard produced encouraging results.

Genetic associations with thalidomide mediated venous thrombotic events in myeloma identified using targeted genotyping

A venous thromboembolism (VTE) with the subsequent risk of pulmonary embolism is a major concern in the treatment of patients with multiple myeloma with thalidomide. The susceptibility to developing a VTE in response to thalidomide therapy is likely to be influenced by both genetic and environmental factors. To test genetic variation associated with treatment related VTE in patient peripheral blood DNA, we used a custom-built molecular inversion probe (MIP)-based single nucleotide polymorphism (SNP) chip containing 3404 SNPs. SNPs on the chip were selected in "functional regions" within 964 genes spanning 67 molecular pathways thought to be involved in the pathogenesis, treatment response, and side effects associated with myeloma therapy. Patients and controls were taken from 3 large clinical trials: Medical Research Council (MRC) Myeloma IX, Hovon-50, and Eastern Cooperative Oncology Group (ECOG) EA100, which compared conventional treatments with thalidomide in patients with myeloma. Our analysis showed that the set of SNPs associated with thalidomide-related VTE were enriched in genes and pathways important in drug transport/metabolism, DNA repair, and cytokine balance. The effects of the SNPs associated with thalidomide-related VTE may be functional at the level of the tumor cell, the tumor-related microenvironment, and the endothelium. The clinical trials described in this paper have been registered as follows: MRC Myeloma IX: ISRCTN68454111; Hovon-50: NCT00028886; and ECOG EA100: NCT00033332.

Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival

BACKGROUND

We have engaged in an international program designated the Bank On A Cure, which has established DNA banks from multiple cooperative and institutional clinical trials, and a platform for examining the association of genetic variations with disease risk and outcomes in multiple myeloma. We describe the development and content of a novel custom SNP panel that contains 3404 SNPs in 983 genes, representing cellular functions and pathways that may influence disease severity at diagnosis, toxicity, progression or other treatment outcomes. A systematic search of national databases was used to identify non-synonymous coding SNPs and SNPs within transcriptional regulatory regions. To explore SNP associations with PFS we compared SNP profiles of short term (less than 1 year, n = 70) versus long term progression-free survivors (greater than 3 years, n = 73) in two phase III clinical trials.

RESULTS

Quality controls were established, demonstrating an accurate and robust screening panel for genetic variations, and some initial racial comparisons of allelic variation were done. A variety of analytical approaches, including machine learning tools for data mining and recursive partitioning analyses, demonstrated predictive value of the SNP panel in survival. While the entire SNP panel showed genotype predictive association with PFS, some SNP subsets were identified within drug response, cellular signaling and cell cycle genes.

CONCLUSION

A targeted gene approach was undertaken to develop an SNP panel that can test for associations with clinical outcomes in myeloma. The initial analysis provided some predictive power, demonstrating that genetic variations in the myeloma patient population may influence PFS.

Genetic variants in major histocompatibility complex-linked genes associate with pediatric liver transplant rejection

BACKGROUND & AIMS

Limited access to large samples precludes genome-wide association studies of rare but complex traits. To localize candidate genes with family-based genome-wide association, a novel exploratory analysis was first tested on 1774 major histocompatibility complex single nucleotide polymorphisms (SNPs) in 240 DNA samples from 80 children with primary liver transplantation and their biologic parents.

METHODS

Initially, 57 SNPs with large differences (P < .05) in minor allele frequencies were selected when parents of children with early rejection (rejectors) were compared with parents of nonrejectors.

RESULTS

In hypothesis testing of selected SNPs, the gamete competition statistic identified the minor allele G of the SNP rs9296068, near HLA-DOA, as being significantly different (P = .018) between outcome groups in parent-to-child transmission. Subsequent simple association testing confirmed over- and undertransmission of rs9296068 based on the most significant differences between outcome groups, of 1774 SNPs tested (P = .002), and allele (G) frequencies that were greater among rejectors (51.4% vs 36.8%, respectively, P = .015) and lower among nonrejectors (26.8% vs 36.8%, respectively, P = .074) compared with 400 normal control Caucasian children. In early functional validation, rejectors demonstrated significant repression of the first HLA-DOA exon closest to rs9296068. Also, intragraft B lymphocytes, whose antigen-presenting function is selectively inhibited by HLA-DOA were 3-fold more numerous during rejection among rejectors with the risk allele, than those without.

CONCLUSIONS

The minor allele of the SNP rs9296068 is significantly associated with liver transplantation rejection and with enhanced B-lymphocyte participation in rejection, likely because of a dysfunctional HLA-DOA gene product.

From SNPs to functional studies in cardiovascular pharmacogenomics

Functional studies can be utilized to give importance/relevance to clinical associations. Once a clinical genetic or pharmacogenetic association is found, molecular studies can be utilized to explore the mechanism for the association. By employing cells in culture or transgenic mice modified with specific variant genes or sequence polymorphisms of interest, pathophysiological processes and response to pharmacological agents may be tested under conditions that are not approachable in human patients. These mechanistic studies may be particularly important when it comes to pharmacogenetic associations by providing significant, clinically relevant insights into the variable responses patients show to drug therapy.

In silico detection of sequence variations modifying transcriptional regulation

Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation.

DNA sequence variations (polymorphisms) that affect the expression levels of genes play important roles in the pathogenesis of many complex diseases. Compared with genetic variations that alter the amino acid sequences of encoded proteins, which are relatively easy to identify, sequence variants that affect the regulation of genes are difficult to pinpoint among the large amount of nonfunctional polymorphisms located in the vicinity of genes. Computational methods to distinguish functional from neutral variations could therefore prove useful to direct limited laboratory resources to sites most likely to exhibit a phenotypic effect. In this paper we present a Web-based tool for the identification of genetic variation in potential transcription factor binding sites. This tool can be used by any scientist interested in the characterization of regulatory polymorphisms. Using experimentally verified regulatory polymorphisms and background data collected from the literature, we evaluate the method's capacity to identify regulatory genetic variation, and we discuss the limitations of its application.

A novel method combining linkage disequilibrium information and imputed functional knowledge for tagSNP selection

Analyses of high-density SNPs in genetic studies have the potential problems of prohibitive genotyping costs and inflated false discovery rates. Current methods select subsets of representative SNPs (tagSNPs) using information either on potential biologic functionality of the SNPs or on the underlying linkage disequilibrium (LD) structure, but not both. Combining the two types of information may lead to more effective tagSNP selection. The proposed method combines both functional and LD information using a weighted factor analysis (WFA) model. The WFA was applied to the dense SNP collection from 129 genes sequenced by the SeattleSNPs Program for Genomic Application. TagSNPs selected by WFA were compared with those selected by an LD-based method. WFA allowed prioritization of SNPs that would otherwise share equivalent ranking due to underlying LD structure alone. Furthermore, WFA consistently included SNPs not selected by function or by LD alone. A literature review of a subset of genes revealed that SNPs selected by WFA were more likely represented in published reports.

Identification of NR1I2 genetic variation using resequencing

OBJECTIVE

The nuclear receptor NR1I2 (also called PXR or SXR) is primarily expressed in mouse and human liver and intestines. Direct activation of NR1I2 occurs in response to a range of xenobiotics, which causes the formation of a heterodimer with the RXR receptor. This heterodimer binds to the nuclear receptor response elements of downstream genes such as ABCB1, CYP2C, and CYP3A. This study determined the extent of NR1I2 variation in three world populations.

METHODS

Variation in NR1I2 was identified by pooled resequencing in African, Asian, and European populations. Validation was performed in European and African populations using PCR and Pyrosequencing technology. RNA expression of NR1I2, ABCB1 and CYP3A4 was assessed using real-time PCR.

RESULTS

Of 36 single nucleotide polymorphisms (SNPs) identified, 24 were in the untranslated region, 8 were intronic, and 4 exonic. Thirty-six percent were unique to the African population. In comparison with previously published data, we identified 13 novel polymorphisms. The NR1I2 -566A > C polymorphism was significantly associated with ABCB1 and CYP3A4 RNA expression in colon tumor (P = 0.04 in both cases), however, this polymorphism was not associated with NR1I2 expression.

CONCLUSION

With NR1I2 playing such a large role in the regulation of genes involved in drug metabolism and transport, genetic variation contributing to altered NR1I2 function may have an important clinical impact.

Survey of polymorphic sequence variation in the immediate 5' region of human DNA repair genes

Systematic screens have revealed extensive DNA sequence variation existing in the human population. Studies of the role of polymorphic genetic variants in explaining the association of family history with risk of common disease have generally focused on variants predicted to disrupt protein structure and activity. Recent studies have identified genetic variation in the level of expression of many genes, variation that is potentially biologically relevant in explaining individual variation in disease risk. In a survey of data available for 108 DNA repair genes that have been systematically screened for sequence variation, an average of 3.3 SNPs per gene were found to exist at a variant allele frequency of at least 0.02 in the region 2kb upstream from the 5'-untranslated region. One-third of the genes harbored a SNP with an allele frequency of at least 0.02 within a predicted promotor element. These variants are distributed among promoter elements that average 20 elements per gene. The frequency of polymorphic SNPs in CpG islands was 0.8 per gene, while the frequency of SNPs in the 5'-UTR was 0.7 per gene. The recognition of extensive genetic variation with potential to impact levels of gene expression, and thereby exacerbate the impact of amino acid substitution variants on the activity of proteins, increases the complexity of analyses required to explain the molecular genetic basis for the familial contribution to the sporadic incidence of common disease.

Cis-regulatory variations: a study of SNPs around genes showing cis-linkage in segregating mouse populations

Background

Changes in gene expression are known to be responsible for phenotypic variation and susceptibility to diseases. Identification and annotation of the genomic sequence variants that cause gene expression changes is therefore likely to lead to a better understanding of the cause of disease at the molecular level. In this study we investigate the pattern of single nucleotide polymorphisms (SNPs) in genes for which the mRNA levels show cis-genetic linkage (gene expression quantitative trait loci mapping in cis, or cis-eQTLs) in segregating mouse populations. Such genes are expected to have polymorphisms near their physical location (cis-variations) that affect their mRNA levels by altering one or more of the cis-regulatory elements. This led us to characterize the SNPs in promoter (5 Kb upstream) and non-coding gene regions (introns and 5 Kb downstream) (cis-SNPs) and the effects they may have on putative transcription factor binding sites.

Results

We demonstrate that the cis-eQTL genes (CEGs) have a significantly higher frequency of cis-SNPs compared to non-CEGs (when both sets are taken from the non-IBD regions, i.e. regions not identical by descent). Most CEGs having cis-SNPs do not contain these SNPs in the phylogenetically conserved regions. In those CEGs that contain cis-SNPs in the phylogenetically conserved regions, enrichment of cis-SNPs occurs both within and outside of the conserved sequences. A higher fraction of CEGs are also seen to harbor cis-SNP that affect predicted transcription factor binding sites, a likely consequence of the higher cis-SNPs density in these genes.

Conclusion

This present study provides the first genome-wide investigation of the putative cis-regulatory variations in a large set of genes whose levels of expression give rise to cis-linkage in segregating mammalian populations. Our results provide insights into the challenges that exist in identifying polymorphisms regulating gene expression using bioinformatic sequence analysis approaches. The data provided herein should benefit future investigations in this area.

Genetic interaction between expanded murine Hdh alleles and p53 reveal deleterious effects of p53 on Huntington's disease pathogenesis

Huntingtin, the protein product of the Huntington's disease (HD) gene, is known to interact with the tumor suppressor p53. It has recently been shown that activation of p53 upregulates the level of huntingtin, both in vitro and in vivo, whereas p53 deficiency in HD-transgenic flies and mice has been found to be beneficial. To explore further the involvement of p53 in HD pathogenesis, we generated mice homozygous for a mutant allele of Hdh (HdhQ140) and with zero, one, or two functional alleles of p53. p53 deficiency resulted in a reduction of mutant huntingtin expression in brain and testis, an increase in proenkephalin mRNA expression and a significant increase in nuclear aggregate formation in the striatum. Because aggregation of mutant huntingtin is suggested to be a protective mechanism, both the increase in aggregate load and the restoration of proenkephalin expression suggest a functional rescue of at least several aspects of the HD phenotype by a deficiency in p53.

ORegAnno: an open access database and curation system for literature-derived promoters, transcription factor binding sites and regulatory variation

MOTIVATION

Our understanding of gene regulation is currently limited by our ability to collectively synthesize and catalogue transcriptional regulatory elements stored in scientific literature. Over the past decade, this task has become increasingly challenging as the accrual of biologically validated regulatory sequences has accelerated. To meet this challenge, novel community-based approaches to regulatory element annotation are required.

SUMMARY

Here, we present the Open Regulatory Annotation (ORegAnno) database as a dynamic collection of literature-curated regulatory regions, transcription factor binding sites and regulatory mutations (polymorphisms and haplotypes). ORegAnno has been designed to manage the submission, indexing and validation of new annotations from users worldwide. Submissions to ORegAnno are immediately cross-referenced to EnsEMBL, dbSNP, Entrez Gene, the NCBI Taxonomy database and PubMed, where appropriate.

AVAILABILITY

ORegAnno is available directly through MySQL, Web services, and online at http://www.oreganno.org. All software is licensed under the Lesser GNU Public License (LGPL).

The patterns of natural variation in human genes

Currently, more than 10 million DNA sequence variations have been uncovered in the human genome. The most detailed variation discovery efforts have focused on candidate genes involved in cardiovascular disease or in susceptibilities associated with exposure to environmental agents. Here we provide an overview of natural genetic variation from the literature and in 510 human candidate genes resequenced for variation discovery. The average human gene contains 126 biallelic polymorphisms, 46 of which are common (> or =5% minor allele frequency) and 5 of which are found in coding regions. Using this complete picture of genetic diversity, we explore conservation, signatures of selection, and historical recombination to mine information useful for candidate gene association studies. In general, we find that the patterns of human gene variation suggest that no one approach will be appropriate for genetic association studies across all genes. Therefore, many different approaches may be required to identify the elusive genotypes associated with common human phenotypes.

SNPselector: a web tool for selecting SNPs for genetic association studies

SUMMARY

Single nucleotide polymorphisms (SNPs) are commonly used for association studies to find genes responsible for complex genetic diseases. With the recent advance of SNP technology, researchers are able to assay thousands of SNPs in a single experiment. But the process of manually choosing thousands of genotyping SNPs for tens or hundreds of genes is time consuming. We have developed a web-based program, SNPselector, to automate the process. SNPselector takes a list of gene names or a list of genomic regions as input and searches the Ensembl genes or genomic regions for available SNPs. It prioritizes these SNPs on their tagging for linkage disequilibrium, SNP allele frequencies and source, function, regulatory potential and repeat status. SNPselector outputs result in compressed Excel spreadsheet files for review by the user.

AVAILABILITY

SNPselector is freely available at http://primer.duhs.duke.edu/

Interethnic variability of ERCC2 polymorphisms

Excision Repair Cross-Complementing Rodent Repair Group 2 (ERCC2) plays an important role in DNA repair by eliminating bulky DNA adducts produced by platinum agents during the nucleotide excision repair pathway. Several studies have associated polymorphisms in ERCC2 with response to platinum therapy, lung cancer risk, and DNA repair capacity. This study examined ERCC2 polymorphisms and haplotype structure across 18.9 kb in 95 European, 95 African, and 95 Asian individuals. Single-nucleotide polymorphisms (SNPs) (ERCC2 -9164 A>T, -1989 A>G, -516 G>A, 468 C>A [Arg156Arg], 1737 C>T [Val579Val], 2133 C>T [Asp711Asp], and 2251 T>G [Lys751Gln]) were mined and mapped using Golden Path, PolyMAPr, and Promolign. Genotyping was performed using PCR and pyrosequencing. Allele frequencies ranged from 0 to 0.47 (Europeans), 0.05 to 0.72 (Africans), and 0 to 0.47 (Asians). The synonymous cSNP at codon 579 could not be confirmed in our populations. There were significant differences in haplotype structure and frequency between populations. This information on ERCC2 genomic structure will allow the construction of definitive studies to clarify the clinical role of this important gene.