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PubMed2003

Identification and characterization of polymorphic variations of the ataxia telangiectasia mutated (ATM) gene in childhood Hodgkin disease.

There are conflicting reports about the involvement of single nucleotide polymorphisms (SNPs) of the ataxia telangiectasia mutated (ATM) gene with cancer, and the consequences of these SNPs for ATM function remain unclear. We therefore sought to identify SNPs of the ATM gene in pediatric Hodgkin disease (HD) and to analyze ATM function in cells from patients with these SNPs. We have identified SNPs of the ATM gene in 5 of 14 children (S1455R, n = 1; H1380Y, n = 1; N1650S, n = 2; and I709I, n = 1). One patient had nonsense-associated altered splicing of the ATM gene. Lymphoblastoid cell lines expressing the S1455R and N1650S exhibited defective ATM-mediated p53 phosphorylation and Chk2 activation; cells expressing the H1380Y exhibited defective c-Abl activation after X-irradiation. Expression of the N1650S in ATM-null fibroblasts conferred only partial hyperradiosensitivity. Furthermore, the introduction of N1650S ATM into U2OS cells, which express wild-type ATM, showed reduced p53-Ser15 phosphorylation, suggesting a dominant-negative effect of the N1650S over the wild-type ATM protein. We conclude that the rare polymorphic variants of the ATM gene that we identified in children with HD encode functionally abnormal proteins, and we discuss the possible genetic risk factors for childhood HD.

Alleles↗
PubMed2005

Variation in conserved non-coding sequences on chromosome 5q and susceptibility to asthma and atopy.

BACKGROUND: Evolutionarily conserved sequences likely have biological function. METHODS: To determine whether variation in conserved sequences in non-coding DNA contributes to risk for human disease, we studied six conserved non-coding elements in the Th2 cytokine cluster on human chromosome 5q31 in a large Hutterite pedigree and in samples of outbred European American and African American asthma cases and controls. RESULTS: Among six conserved non-coding elements (> 100 bp, > 70% identity; human-mouse comparison), we identified one single nucleotide polymorphism (SNP) in each of two conserved elements and six SNPs in the flanking regions of three conserved elements. We genotyped our samples for four of these SNPs and an additional three SNPs each in the IL13 and IL4 genes. While there was only modest evidence for association with single SNPs in the Hutterite and European American samples (P < 0.05), there were highly significant associations in European Americans between asthma and haplotypes comprised of SNPs in the IL4 gene (P < 0.001), including a SNP in a conserved non-coding element. Furthermore, variation in the IL13 gene was strongly associated with total IgE (P = 0.00022) and allergic sensitization to mold allergens (P = 0.00076) in the Hutterites, and more modestly associated with sensitization to molds in the European Americans and African Americans (P < 0.01). CONCLUSION: These results indicate that there is overall little variation in the conserved non-coding elements on 5q31, but variation in IL4 and IL13, including possibly one SNP in a conserved element, influence asthma and atopic phenotypes in diverse populations.

Asthma↗
PubMed2005

A method for finding single-nucleotide polymorphisms with allele frequencies in sequences of deep coverage.

BACKGROUND: The allele frequencies of single-nucleotide polymorphisms (SNPs) are needed to select an optimal subset of common SNPs for use in association studies. Sequence-based methods for finding SNPs with allele frequencies may need to handle thousands of sequences from the same genome location (sequences of deep coverage). RESULTS: We describe a computational method for finding common SNPs with allele frequencies in single-pass sequences of deep coverage. The method enhances a widely used program named PolyBayes in several aspects. We present results from our method and PolyBayes on eighteen data sets of human expressed sequence tags (ESTs) with deep coverage. The results indicate that our method used almost all single-pass sequences in computation of the allele frequencies of SNPs. CONCLUSION: The new method is able to handle single-pass sequences of deep coverage efficiently. Our work shows that it is possible to analyze sequences of deep coverage by using pairwise alignments of the sequences with the finished genome sequence, instead of multiple sequence alignments.

Computers, Molecular↗
PubMed2005

SNP-VISTA: an interactive SNP visualization tool.

BACKGROUND: Recent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at http://genome.lbl.gov/vista/snpvista1. RESULTS: We have developed and present two modifications of an interactive visualization tool, SNP-VISTA, to aid in the analyses of the following types of data: A. Large-scale re-sequence data of disease-related genes for discovery of associated and/or causative alleles (GeneSNP-VISTA). B. Massive amounts of ecogenomics data for studying homologous recombination in microbial populations (EcoSNP-VISTA). The main features and capabilities of SNP-VISTA are: 1) mapping of SNPs to gene structure; 2) classification of SNPs, based on their location in the gene, frequency of occurrence in samples and allele composition; 3) clustering, based on user-defined subsets of SNPs, highlighting haplotypes as well as recombinant sequences; 4) integration of protein evolutionary conservation visualization; and 5) display of automatically calculated recombination points that are user-editable. CONCLUSION: The main strength of SNP-VISTA is its graphical interface and use of visual representations, which support interactive exploration and hence better understanding of large-scale SNP data by the user.

Algorithms↗
PubMed2005

Genome-wide linkage analysis of age at onset of alcohol dependence: a comparison between microsatellites and single-nucleotide polymorphisms.

BACKGROUND: Using the dataset provided for Genetic Analysis Workshop 14 by the Collaborative Study on the Genetics of Alcoholism, we performed genome-wide linkage analysis of age at onset of alcoholism to compare the utility of microsatellites and single-nucleotide polymorphisms (SNPs) in genetic linkage study. METHODS: A multipoint nonparametric variance component linkage analysis method was applied to the survival distribution function obtained from semiparametric proportional hazards model of the age at onset phenotype of alcoholism. Three separate linkage analyses were carried out using 315 microsatellites, 2,467 and 9,467 SNPs, spanning the 22 autosomal chromosomes. RESULTS: Heritability of age at onset was estimated to be approximately 12% (p < 0.001). We observed weak correlation, both in trend and strength, of genome-wide linkage signals between microsatellites and SNPs. Results from SNPs revealed more and stronger linkage signals across the genome compared with those from microsatellites. The only suggestive evidence of linkage from microsatellites was on chromosome 1 (LOD of 1.43). Differences in map densities between the two sets of SNPs used in this study did not appear to confer an advantage in terms of strength of linkage signals. CONCLUSION: Our study provided support for better performance of dense SNP maps compared with the sparse microsatellite maps currently available for linkage analysis of quantitative traits. This better performance could be attributable to precise definition and high map resolutions achievable with dense SNP maps, thus resulting in increased power to detect possible loci affecting given trait or disease.

Age of Onset↗
PubMed2005

Linkage and association analyses of microsatellites and single-nucleotide polymorphisms in nuclear families.

Several simulation studies have suggested that a high-density single-nucleotide polymorphisms (SNPs) marker set may be as useful as a traditional microsatellites (MS) marker set in performing whole-genome linkage analysis. However, very few studies have directly tested the SNPs-based genome-wide scan. In the present study, we compared the linkage results from the SNPs-based scan with a map density of 3-cM spacing with those from the MS scan using a 10-cM marker set among 300 nuclear families each from the Aipotu (AI), Danacaa (DA), and Karangar (KA) populations from the simulated Genetic Analysis Workshop 14 Problem 2 data. We found that information contents obtained from the SNPs scan were somewhat lower than those from the MS scan. However, the linkage results obtained from the two scans showed a high degree of similarity. Both scans identified a similar number of chromosomal regions attaining nominal significance (p < 0.05). Specifically, both scans detected confirmed evidence for linkage (NPL >or= 4.07, p = 2 x 10(-5)) to chromosome 1 in the AI families, chromosomes 1 and 3 in the DA families, and chromosomes 3, 5, and 9 in the KA families. An additional confirmed linkage to chromosome 5 in the AI families was detected only by the MS scan. We also observed slightly wider 1-LOD intervals for more of the SNP peaks than for the MS peaks, which is likely due to lower information contents for the SNPs. Subsequent fine-mapping association analysis further identified 2 to 3 markers significantly associated with disease status in each population; B03T3056, B03T3058, and B05T4139 in the AI population, B03T3056 and B03T3058 in the KA population, and B03T3056, B03T3057, and B03T3058 in the DA population. Among the four markers, three were chosen based on results obtained from the two scans, but one was solely from the SNP scan. In summary, our finding suggests that the SNP-based genome scan has the potential to be as powerful as the traditional MS-based scan and offers good identification of peak location for further fine-mapped association analysis.

Alleles↗
PubMed2005

Whole-genome linkage analysis in mapping alcoholism genes using single-nucleotide polymorphisms and microsatellites.

There is currently a great interest in using single-nucleotide polymorphisms (SNPs) in genetic linkage and association studies because of the abundance of SNPs as well as the availability of high-throughput genotyping technologies. In this study, we compared the performance of whole-genome scans using SNPs with microsatellites on 143 pedigrees from the Collaborative Studies on Genetics of Alcoholism provided by Genetic Analysis Workshop 14. A total of 315 microsatellites and 10,081 SNPs from Affymetrix on 22 autosomal chromosomes were used in our analyses. We found that the results from the two scans had good overall concordance. One region on chromosome 2 and two regions on chromosome 7 showed significant linkage signals (i.e., NPL >or= 2) for alcoholism from both the SNP and microsatellite scans. The different results observed between the two scans may be explained by the difference observed in information content between the SNPs and the microsatellites.

Alcoholism↗
PubMed2005

Comparison of the power between microsatellite and single-nucleotide polymorphism markers for linkage and linkage disequilibrium mapping of an electrophysiological phenotype.

We performed linkage and linkage disequilibrium (LD) mapping analyses to compare the power between microsatellite and single nucleotide polymorphism (SNP) markers. Chromosome-wide analyses were performed for a quantitative electrophysiological phenotype, ttth1, on chromosome 7. Multipoint analysis of microsatellite markers using the variance component (VC) method showed the highest LOD score of 4.20 at 162 cM, near D7S509 (163.7 cM). Two-point analysis of SNPs using the VC method yielded the highest LOD score of 3.98 in the Illumina SNP data and 3.45 in the Affymetrix SNP data around 152-153 cM. In family-based single SNP and SNP haplotype LD analysis, we identified seven SNPs associated with ttth1. We searched for any potential candidate genes in the location of the seven SNPs. The SNPs rs1476640 and rs768055 are located in the FLJ40852 gene (a hypothetical protein), and SNP rs1859646 is located in the TAS2R5 gene (a taste receptor). The other four SNPs are not located in any known or annotated genes. We found the high density SNP scan to be superior to microsatellites because it is effective in downstream fine mapping due to a better defined linkage region. Our study proves the utility of high density SNP in genome-wide mapping studies.

Aging↗
PubMed2005

A comparison of five methods for selecting tagging single-nucleotide polymorphisms.

Our goal was to compare methods for tagging single-nucleotide polymorphisms (tagSNPs) with respect to the power to detect disease association under differing haplotype-disease association models. We were also interested in the effect that SNP selection samples, consisting of either cases, controls, or a mixture, would have on power. We investigated five previously described algorithms for choosing tagSNPS: two that picked SNPs based on haplotype structure (Chapman-haplotypic and Stram), two that picked SNPs based on pair-wise allelic association (Chapman-allelic and Cousin), and one control method that chose equally spaced SNPs (Zhai). In two disease-associated regions from the Genetic Analysis Workshop 14 simulated data, we tested the association between tagSNP genotype and disease over the tagSNP sets chosen by each method for each sampling scheme. This was repeated for 100 replicates to estimate power. The two allelic methods chose essentially all SNPs in the region and had nearly optimal power. The two haplotypic methods chose about half as many SNPs. The haplotypic methods had poor performance compared to the allelic methods in both regions. We expected an improvement in power when the selection sample contained cases; however, there was only moderate variation in power between the sampling approaches for each method. Finally, when compared to the haplotypic methods, the reference method performed as well or worse in the region with ancestral disease haplotype structure.

Genetic Techniques↗
PubMed2005

Accuracy of haplotype estimation in a region of low linkage disequilibrium.

We compared the accuracy of haplotype inferences at a 6 Mb region on chromosome 7 where significant linkage between a brain oscillation phenotype and a cholinergic muscarinic receptor gene was previously reported. Individual haplotype assignments and haplotype frequencies were estimated using 5, 10, and 14 consecutive Illumina single-nucleotide polymorphisms (SNPs) within the 1-LOD unit support interval of the chromosome 7 linkage peak. Initially, haplotypes were constructed incorporating phase information provided by relatives using the pedigree analysis package MERLIN. Population-based haplotypes were inferred using the haplotype estimation software HAPLO.STATS and PHASE, using unrelated individuals. The 14 SNPs within this region exhibited markedly low linkage disequilibrium, and the average D' estimate between SNPs was 0.18 (range: 0.01-0.97). In comparison to the family-based haplotypes calculated in MERLIN, the computational inferences of individual haplotype assignments were most accurate when considering 5 consecutive SNPs, but decayed dramatically when considering 10 or 14 SNPs in both PHASE and HAPLO.STATS. When comparing the two haplotype inference methods, both PHASE and HAPLO.STATS performed poorly. These analyses underscore the difficulties of haplotype estimation in the presence of low linkage disequilibrium and stress the importance of careful consideration of confidence measures when using estimated haplotype frequencies and individual assignments in biomedical research.

Family↗
PubMed2004

Lower rate of genomic variation identified in the trans-membrane domain of monoamine sub-class of Human G-Protein Coupled Receptors: the Human GPCR-DB Database.

BACKGROUND: We have surveyed, compiled and annotated nucleotide variations in 338 human 7-transmembrane receptors (G-protein coupled receptors). In a sample of 32 chromosomes from a Nordic population, we attempted to determine the allele frequencies of 80 non-synonymous SNPs, and found 20 novel polymorphic markers. GPCR receptors of physiological and clinical importance were prioritized for statistical analysis. Natural variation and rare mutation information were merged and presented online in the Human GPCR-DB database http://cyrix.cgb.ki.se. RESULTS: The average number of SNPs per 1000 bases of exonic sequence was found to be twice the average number of SNPs per Kilobase of intronic regions (2.2 versus 1.0). Of the 338 genes, 111 were single exon genes, that is, were intronless. The average number of exonic-SNPs per single-exon gene was 3.5 (n = 395) while that for multi-exon genes was 0.8 (n = 1176). The average number of variations within the different protein domain (N-terminus, internal- and external-loops, trans-membrane region, C-terminus) indicates a lower rate of variation in the trans-membrane region of Monoamine GPCRs, as compared to Chemokine- and Peptide-receptor sub-classes of GPCRs. CONCLUSIONS: Single-exon GPCRs on average have approximately three times the number of SNPs as compared to GPCRs with introns. Among various functional classes of GPCRs, Monoamine GPRCs have lower number of natural variations within the trans-membrane domain indicating evolutionary selection against non-synonymous changes within the membrane-localizing domain of this sub-class of GPCRs.

Alleles↗
PubMed2005

Identification of disease causing loci using an array-based genotyping approach on pooled DNA.

BACKGROUND: Pooling genomic DNA samples within clinical classes of disease followed by genotyping on whole-genome SNP microarrays, allows for rapid and inexpensive genome-wide association studies. Key to the success of these studies is the accuracy of the allelic frequency calculations, the ability to identify false-positives arising from assay variability and the ability to better resolve association signals through analysis of neighbouring SNPs. RESULTS: We report the accuracy of allelic frequency measurements on pooled genomic DNA samples by comparing these measurements to the known allelic frequencies as determined by individual genotyping. We describe modifications to the calculation of k-correction factors from relative allele signal (RAS) values that remove biases and result in more accurate allelic frequency predictions. Our results show that the least accurate SNPs, those most likely to give false-positives in an association study, are identifiable by comparing their frequencies to both those from a known database of individual genotypes and those of the pooled replicates. In a disease with a previously identified genetic mutation, we demonstrate that one can identify the disease locus through the comparison of the predicted allelic frequencies in case and control pools. Furthermore, we demonstrate improved resolution of association signals using the mean of individual test-statistics for consecutive SNPs windowed across the genome. A database of k-correction factors for predicting allelic frequencies for each SNP, derived from several thousand individually genotyped samples, is provided. Lastly, a Perl script for calculating RAS values for the Affymetrix platform is provided. CONCLUSION: Our results illustrate that pooling of DNA samples is an effective initial strategy to identify a genetic locus. However, it is important to eliminate inaccurate SNPs prior to analysis by comparing them to a database of individually genotyped samples as well as by comparing them to replicates of the pool. Lastly, detection of association signals can be improved by incorporating data from neighbouring SNPs.

Alleles↗
PubMed2005

SNiPer: improved SNP genotype calling for Affymetrix 10K GeneChip microarray data.

BACKGROUND: High throughput microarray-based single nucleotide polymorphism (SNP) genotyping has revolutionized the way genome-wide linkage scans and association analyses are performed. One of the key features of the array-based GeneChip Mapping 10K Array from Affymetrix is the automated SNP calling algorithm. The Affymetrix algorithm was trained on a database of ethnically diverse DNA samples to create SNP call zones that are used as static models to make genotype calls for experimental data. We describe here the implementation of clustering algorithms on large training datasets resulting in improved SNP call rates on the 10K GeneChip. RESULTS: A database of 948 individuals genotyped on the GeneChip Mapping 10K 2.0 Array was used to identify 822 SNPs that were called consistently less than 75% of the time. These SNPs represent on average 8.25% of the total SNPs on each chromosome with chromosome 19, the most gene-rich chromosome, containing the highest proportion of poor performers (18.7%). To remedy this, we created SNiPer, a new application which uses two clustering algorithms to yield increased call rates and equivalent concordance to Affymetrix called genotypes. We include a training set for these algorithms based on individual genotypes for 705 samples. SNiPer has the capability to be retrained for lab-specific training sets. SNiPer is freely available for download at http://www.tgen.org/neurogenomics/data. CONCLUSION: The correct calling of poor performing SNPs may prove to be key in future linkage studies performed on the 10K GeneChip. It would prove particularly invaluable for those diseases that map to chromosome 19, known to contain a high proportion of poorly performing SNPs. Our results illustrate that SNiPer can be used to increase call rates on the 10K GeneChip without sacrificing accuracy, thereby increasing the amount of valid data generated.

Algorithms↗
PubMed2006

Conserved genes in a path from commensalism to pathogenicity: comparative phylogenetic profiles of Staphylococcus epidermidis RP62A and ATCC12228.

BACKGROUND: Staphylococcus epidermidis, long regarded as an innocuous commensal bacterium of the human skin, is the most frequent cause of nosocomial infections associated with implanted medical devices. This conditional pathogen provides a model of choice to study genome landmarks correlated with the transition between commensalism and pathogenicity. Traditional investigations stress differences in gene content. We focused on conserved genes that have accumulated small mutation differences during the transition. RESULTS: A comparison of strain ATCC12228, a non-biofilm forming, non-infection associated strain and strain RP62A, a methicillin-resistant biofilm clinical isolate, revealed consistent variation, mostly single-nucleotide polymorphisms (SNPs), in orthologous genes in addition to the previously investigated global changes in gene clusters. This polymorphism, scattered throughout the genome, may reveal genes that contribute to adaptation of the bacteria to different environmental stimuli, allowing them to shift from commensalism to pathogenicity. SNPs were detected in 931 pairs of orthologs with identical gene length, accounting for approximately 45% of the total pairs of orthologs. Assuming that non-synonymous mutations would mark recent evolution, and hence be associated to the onset of the pathogenic process, analysis of ratios of non-synonymous SNPs vs synonymous SNPs suggested hypotheses about possible pathogenicity determinants. The N/S ratios for virulence factors and surface proteins differed significantly from that of average SNPs. Of those gene pairs, 40 showed a disproportionate distribution of dN vs dS. Among those, the presence of the gene encoding methionine sulfoxide reductase suggested a possible involvement of reactive oxygen species. This led us to uncover that the infection associated strain was significantly more resistant to hydrogen peroxide and paraquat than the environmental strain. Some 16 genes of the list were of unknown function. We could suggest however that they were likely to belong to surface proteins or considered in priority as important for pathogenicity. CONCLUSION: Our study proposed a novel approach to identify genes involved in pathogenic processes and provided some insight about the molecular mechanisms leading a commensal inhabitant to become an invasive pathogen.

Bacterial Proteins↗
PubMed2006

Multilocus analysis of SNP and metabolic data within a given pathway.

BACKGROUND: Complex traits, which are under the influence of multiple and possibly interacting genes, have become a subject of new statistical methodological research. One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common multifactorial diseases and their association to different quantitative phenotypic traits. RESULTS: Two types of data from the same metabolic pathway were used in the analysis: categorical measurements of 18 SNPs; and quantitative measurements of plasma levels of several steroids and their precursors. Using the combinatorial partitioning method we tested various thresholds for each metabolic trait and each individual SNP locus. One SNP in CYP19, 3UTR, two SNPs in CYP1B1 (R48G and A119S) and one in CYP1A1 (T461N) were significantly differently distributed between the high and low level metabolic groups. The leave one out cross validation method showed that 6 SNPs in concert make 65% correct prediction of phenotype. Further we used pattern recognition, computing the p-value by Monte Carlo simulation to identify sets of SNPs and physiological characteristics such as age and weight that contribute to a given metabolic level. Since the SNPs detected by both methods reside either in the same gene (CYP1B1) or in 3 different genes in immediate vicinity on chromosome 15 (CYP19, CYP11 and CYP1A1) we investigated the possibility that they form intragenic and intergenic haplotypes, which may jointly account for a higher activity in the pathway. We identified such haplotypes associated with metabolic levels. CONCLUSION: The methods reported here may enable to study multiple low-penetrance genetic factors that together determine various quantitative phenotypic traits. Our preliminary data suggest that several genes coding for proteins involved in a common pathway, that happen to be located on common chromosomal areas and may form intragenic haplotypes, together account for a higher activity of the whole pathway.

Aged↗
PubMed2006

Do host genetic traits in the bacterial sensing system play a role in the development of Chlamydia trachomatis-associated tubal pathology in subfertile women?

BACKGROUND: In women, Chlamydia (C.) trachomatis upper genital tract infection can cause distal tubal damage and occlusion, increasing the risk of tubal factor subfertility and ectopic pregnancy. Variations, like single nucleotide polymorphisms (SNPs), in immunologically important host genes are assumed to play a role in the course and outcome of a C. trachomatis infection. We studied whether genetic traits (carrying multiple SNPs in different genes) in the bacterial sensing system are associated with an aberrant immune response and subsequently with tubal pathology following a C. trachomatis infection. The genes studied all encode for pattern recognition receptors (PRRs) involved in sensing bacterial components. METHODS: Of 227 subfertile women, serum was available for C. trachomatis IgG antibody testing and genotyping (common versus rare allele) of the PRR genes TLR9, TLR4, CD14 and CARD15/NOD2. In all women, a laparoscopy was performed to assess the grade of tubal pathology. Tubal pathology was defined as extensive peri-adnexal adhesions and/or distal occlusion of at least one tube. RESULTS: Following a C. trachomatis infection (i.e. C. trachomatis IgG positive), subfertile women carrying two or more SNPs in C. trachomatis PRR genes were at increased risk of tubal pathology compared to women carrying less than two SNPs (73% vs 33% risk). The differences were not statistically significant (P = 0.15), but a trend was observed. CONCLUSION: Carrying multiple SNPs in C. trachomatis PRR genes tends to result in an aberrant immune response and a higher risk of tubal pathology following a C. trachomatis infection. Larger studies are needed to confirm our preliminary findings.

Antibodies, Bacterial↗
PubMed2006

Association of MTHFR gene polymorphisms with breast cancer survival.

BACKGROUND: Two functional single nucleotide polymorphisms (SNPs) in the 5,10-methylenetetrahydrofolate reductase (MTHFR) gene, C677T and A1298C, lead to decreased enzyme activity and affect chemosensitivity of tumor cells. We investigated whether these MTHFR SNPs were associated with breast cancer survival in African-American and Caucasian women. METHODS: African-American (n = 143) and Caucasian (n = 105) women, who had incident breast cancer with surgery, were recruited between 1993 and 2003 from the greater Baltimore area, Maryland, USA. Kaplan-Meier survival and multivariate Cox proportional hazards regression analyses were used to examine the relationship between MTHFR SNPs and disease-specific survival. RESULTS: We observed opposite effects of the MTHFR polymorphisms A1298C and C677T on breast cancer survival. Carriers of the variant allele at codon 1298 (A/C or C/C) had reduced survival when compared to homozygous carriers of the common A allele [Hazard ratio (HR) = 2.05; 95% confidence interval (CI), 1.05-4.00]. In contrast, breast cancer patients with the variant allele at codon 677 (C/T or T/T) had improved survival, albeit not statistically significant, when compared to individuals with the common C/C genotype (HR = 0.65; 95% CI, 0.31-1.35). The effects were stronger in patients with estrogen receptor-negative tumors (HR = 2.70; 95% CI, 1.17-6.23 for A/C or C/C versus A/A at codon 1298; HR = 0.36; 95% CI, 0.12-1.04 for C/T or T/T versus C/C at codon 677). Interactions between the two MTHFR genotypes and race/ethnicity on breast cancer survival were also observed (A1298C, pinteraction = 0.088; C677T, pinteraction = 0.026). CONCLUSION: We found that the MTHFR SNPs, C677T and A1298C, were associated with breast cancer survival. The variant alleles had opposite effects on disease outcome in the study population. Race/ethnicity modified the association between the two SNPs and breast cancer survival.

Adenine↗
PubMed2004

Detecting imbalanced expression of SNP alleles by minisequencing on microarrays.

BACKGROUND: Each of the human genes or transcriptional units is likely to contain single nucleotide polymorphisms that may give rise to sequence variation between individuals and tissues on the level of RNA. Based on recent studies, differential expression of the two alleles of heterozygous coding single nucleotide polymorphisms (SNPs) may be frequent for human genes. Methods with high accuracy to be used in a high throughput setting are needed for systematic surveys of expressed sequence variation. In this study we evaluated two formats of multiplexed, microarray based minisequencing for quantitative detection of imbalanced expression of SNP alleles. We used a panel of ten SNPs located in five genes known to be expressed in two endothelial cell lines as our model system. RESULTS: The accuracy and sensitivity of quantitative detection of allelic imbalance was assessed for each SNP by constructing regression lines using a dilution series of mixed samples from individuals of different genotype. Accurate quantification of SNP alleles by both assay formats was evidenced for by R2 values > 0.95 for the majority of the regression lines. According to a two sample t-test, we were able to distinguish 1-9% of a minority SNP allele from a homozygous genotype, with larger variation between SNPs than between assay formats. Six of the SNPs, heterozygous in either of the two cell lines, were genotyped in RNA extracted from the endothelial cells. The coefficient of variation between the fluorescent signals from five parallel reactions was similar for cDNA and genomic DNA. The fluorescence signal intensity ratios measured in the cDNA samples were compared to those in genomic DNA to determine the relative expression levels of the two alleles of each SNP. Four of the six SNPs tested displayed a higher than 1.4-fold difference in allelic ratios between cDNA and genomic DNA. The results were verified by allele-specific oligonucleotide hybridisation and minisequencing in a microtiter plate format. CONCLUSIONS: We conclude that microarray based minisequencing is an accurate and accessible tool for multiplexed screening for imbalanced allelic expression in multiple samples and tissues in parallel.

Alleles↗