Search PubMed⌕ Search

Biomedical subjects

Mark J Rieder

Publications and source records attributed to Mark J Rieder.

10 recordsLinked to original sources

Comprehensive identification and characterization of diallelic insertion-deletion polymorphisms in 330 human candidate genes.

Despite being the second most frequent type of polymorphism in the genome, diallelic insertion-deletion polymorphisms (indels) have received far less attention in the study of sequence variation. In this report, we describe an approach that can detect indels in the heterozygous state and can comprehensively identify indels in the target sequence. Using this approach, we identified 2393 indels in a set of 330 candidate genes, i.e. an average of seven indels per gene with about two indels per gene being common (minor allele frequency >or=0.1). We compared the population genetic characteristics of indels with substitutions in this data. Our data supported the findings that deletions occur more frequently in the human genome. 5'-UTR and coding regions of the genes showed a significantly lower diversity for indels compared with other regions, suggesting differences in effects of selection on indels and substitutions. Sequence diversity and pairwise linkage disequilibrium (LD) findings of the different populations were similar to earlier results and included a greater skew towards low-frequency variants and a faster rate of LD decay in the African-descent population compared with the non-African populations. Within populations, the allele frequency spectra and LD-decay profiles for indels were similar to substitutions. Overall, the findings suggest that, although the mechanisms giving rise to indels may be different from those causing substitutions, the evolutionary histories of indels and substitutions are similar, and that indels can play a valuable role in association studies and marker selection strategies.

5' Untranslated Regions↗

Pattern of sequence variation across 213 environmental response genes.

To promote the clinical and epidemiological studies that improve our understanding of human genetic susceptibility to environmental exposure, the Environmental Genome Project (EGP) has scanned 213 environmental response genes involved in DNA repair, cell cycle regulation, apoptosis, and metabolism for single nucleotide polymorphisms (SNPs). Many of these genes have been implicated by loss-of-function mutations associated with severe diseases attributable to decreased protection of genomic integrity. Therefore, the hypothesis for these studies is that individuals with functionally significant polymorphisms within these genes may be particularly susceptible to genotoxic environmental agents. On average, 20.4 kb of baseline genomic sequence or 86% of each gene, including a substantial amount of introns, all exons, and 1.3 kb upstream and downstream, were scanned for variations in the 90 samples of the Polymorphism Discovery Resource panel. The average nucleotide diversity across the 4.2 MB of these 213 genes is 6.7 x 10(-4), or one SNP every 1500 bp, when two random chromosomes are compared. The average candidate environmental response gene contains 26 PHASE inferred haplotypes, 34 common SNPs, 6.2 coding SNPs (cSNPs), and 2.5 nonsynonymous cSNPs. SIFT and Polyphen analysis of 541 nonsynonymous cSNPs identified 57 potentially deleterious SNPs. An additional eight polymorphisms predict altered protein translation. Because these genes represent 1% of all known human genes, extrapolation from these data predicts the total genomic set of cSNPs, nonsynonymous cSNPs, and potentially deleterious nonsynonymous cSNPs. The implications for the use of these data in direct and indirect association studies of environmentally induced diseases are discussed.

Apoptosis↗

Population history and natural selection shape patterns of genetic variation in 132 genes.

Identifying regions of the human genome that have been targets of natural selection will provide important insights into human evolutionary history and may facilitate the identification of complex disease genes. Although the signature that natural selection imparts on DNA sequence variation is difficult to disentangle from the effects of neutral processes such as population demographic history, selective and demographic forces can be distinguished by analyzing multiple loci dispersed throughout the genome. We studied the molecular evolution of 132 genes by comprehensively resequencing them in 24 African-Americans and 23 European-Americans. We developed a rigorous computational approach for taking into account multiple hypothesis tests and demographic history and found that while many apparent selective events can instead be explained by demography, there is also strong evidence for positive or balancing selection at eight genes in the European-American population, but none in the African-American population. Our results suggest that the migration of modern humans out of Africa into new environments was accompanied by genetic adaptations to emergent selective forces. In addition, a region containing four contiguous genes on Chromosome 7 showed striking evidence of a recent selective sweep in European-Americans. More generally, our results have important implications for mapping genes underlying complex human diseases.

Black People↗

Sequence-based linkage analysis.

The rapid decrease in the cost of DNA sequencing will enable its use for novel applications. Here, we investigate the use of DNA sequencing for simultaneous discovery and genotyping of polymorphisms in family linkage studies. In the proposed approach, short contiguous segments of genomic DNA, regularly spaced across the genome, are resequenced in each pedigree member, and all sequence polymorphisms discovered within a pedigree are used as genetic markers. We use computer simulations consistent with observed human sequence diversity to show that segments of 500-1,000 base pairs, spaced at intervals of 1-2 Mb across the genome, provide linkage information that equals or exceeds that of traditional marker-based approaches. We validate these results experimentally by implementing the sequence-based linkage approach for chromosome 19 in CEPH pedigrees.

Chromosome Mapping↗

Evidence for substantial fine-scale variation in recombination rates across the human genome.

Characterizing fine-scale variation in human recombination rates is important, both to deepen understanding of the recombination process and to aid the design of disease association studies. Current genetic maps show that rates vary on a megabase scale, but studying finer-scale variation using pedigrees is difficult. Sperm-typing experiments have characterized regions where crossovers cluster into 1-2-kb hot spots, but technical difficulties limit the number of studies. An alternative is to use population variation to infer fine-scale characteristics of the recombination process. Several surveys reported 'block-like' patterns of diversity, which may reflect fine-scale recombination rate variation, but limitations of available methods made this impossible to assess. Here, we applied a new statistical method, which overcomes these limitations, to infer patterns of fine-scale recombination rate variation in 74 genes. We found extensive rate variation both within and among genes. In particular, recombination hot spots are a common feature of the human genome: 47% (35 of 74) of genes showed substantive evidence for a hot spot, and many more showed evidence for some rate variation. No primary sequence characteristics are consistently associated with precise hot-spot location, although G+C content and nucleotide diversity are correlated with local recombination rate.

Genome, Human↗

Haplotype diversity across 100 candidate genes for inflammation, lipid metabolism, and blood pressure regulation in two populations.

Recent studies have suggested that a significant fraction of the human genome is contained in blocks of strong linkage disequilibrium, ranging from ~5 to >100 kb in length, and that within these blocks a few common haplotypes may account for >90% of the observed haplotypes. Furthermore, previous studies have suggested that common haplotypes in candidate genes are generally shared across populations and represent the majority of chromosomes in each population. The conclusions drawn from these preliminary studies, however, are based on an incomplete knowledge of the variation in the regions examined. To bridge this gap in knowledge, we have completely resequenced 100 candidate genes in a population of African descent and one of European descent. Although these genes have been well studied because of their medical importance, we demonstrate that a large amount of sequence variation has not yet been described. We also report that the average number of inferred haplotypes per gene, when complete data is used, is higher than in previous reports and that the number and proportion of all haplotypes represented by common haplotypes per gene is variable. Furthermore, we demonstrate that haplotypes shared between the two populations constitute only a fraction of the total number of haplotypes observed and that these shared haplotypes represent fewer of the African-descent chromosomes than was expected from previous studies. Finally, we show that restricting variation discovery to coding regions does not adequately describe all common haplotypes or the true haplotype block structure observed when all common variation is used to infer haplotypes. These data, derived from complete knowledge of genetic variation in these genes, suggest that the haplotype architecture of candidate genes across the human genome is more complex than previously suggested, with important implications for candidate gene and genomewide association studies.

Africa↗

Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium.

Common genetic polymorphisms may explain a portion of the heritable risk for common diseases. Within candidate genes, the number of common polymorphisms is finite, but direct assay of all existing common polymorphism is inefficient, because genotypes at many of these sites are strongly correlated. Thus, it is not necessary to assay all common variants if the patterns of allelic association between common variants can be described. We have developed an algorithm to select the maximally informative set of common single-nucleotide polymorphisms (tagSNPs) to assay in candidate-gene association studies, such that all known common polymorphisms either are directly assayed or exceed a threshold level of association with a tagSNP. The algorithm is based on the r(2) linkage disequilibrium (LD) statistic, because r(2) is directly related to statistical power to detect disease associations with unassayed sites. We show that, at a relatively stringent r(2) threshold (r2>0.8), the LD-selected tagSNPs resolve >80% of all haplotypes across a set of 100 candidate genes, regardless of recombination, and tag specific haplotypes and clades of related haplotypes in nonrecombinant regions. Thus, if the patterns of common variation are described for a candidate gene, analysis of the tagSNP set can comprehensively interrogate for main effects from common functional variation. We demonstrate that, although common variation tends to be shared between populations, tagSNPs should be selected separately for populations with different ancestries.

Algorithms↗

Additional SNPs and linkage-disequilibrium analyses are necessary for whole-genome association studies in humans.

More than 5 million single-nucleotide polymorphisms (SNPs) with minor-allele frequency greater than 10% are expected to exist in the human genome. Some of these SNPs may be associated with risk of developing common diseases. To assess the power of currently available SNPs to detect such associations, we resequenced 50 genes in two ethnic samples and measured patterns of linkage disequilibrium between the subset of SNPs reported in dbSNP and the complete set of common SNPs. Our results suggest that using all 2.7 million SNPs currently in the database would detect nearly 80% of all common SNPs in European populations but only 50% of those common in the African American population and that efficient selection of a minimal subset of SNPs for use in association studies requires measurement of allele frequency and linkage disequilibrium relationships for all SNPs in dbSNP.

Alleles↗

Novel paraoxonase (PON1) nonsense and missense mutations predicted by functional genomic assay of PON1 status.

Paraoxonase (PON1) has been termed an environmental response enzyme for its function in the detoxification of organophosphate pesticides, nerve agents and pharmaceuticals such as glucocorticoids and statins, as well as its cardioprotective role in breaking down oxidized LDL. PON1(192) genotype can be predicted with high accuracy from an examination of the two-dimensional plot of paraoxon and diazoxon hydrolysis rates [ 1]. Individuals for whom this functional genomic assay failed to predict PON1(192) genotype, or who had a low PON activity relative to others with the same genotype, were predicted to have genetic alterations that explained the inconsistency. Sequencing of the PON1 region of 23 Caucasian individuals detected a nonsense mutation changing amino acid 194 from a Trp to a stop codon (PON1(Trp194stop)). It was predicted that subjects who genotyped as PON1(192QR) but phenotyped as PON1(192QQ) or PON1(192RR) might carry the protein truncation mutation for which the defective product failed to be detected by the phenotyping assay. Screening of the five discordant subjects resulted in the detection of a single Caucasian carrying the stop codon, and determined its phasing on the PON1(192R) allele. Sequencing confirmed the change and revealed an additional subject with a likely deletion of the 5' end of the PON1 gene. Additional sequencing of 25 subjects with low PON1 activities identified two additional previously undescribed PON1 mutations, which may affect PON1 function: PON1(Pro90Leu) associated with the PON1(192Q) allele and PON1(Asp124missplice) associated with the PON1(192R) allele.

Aryldialkylphosphatase↗

Mitochondrial genetic variants and Alzheimer disease: a case-control study of the T4336C and G5460A variants.

The T4336C mitochondrial genetic variant was associated with Alzheimer disease in several previous studies. Recent investigations, however, failed to confirm this association. We tested this association in newly diagnosed Alzheimer disease cases and controls of similar age and gender recruited from an established HMO serving Seattle, Washington and surrounding areas. In this, the largest case-control study reported to date, the T4336C variant was not associated with Alzheimer disease overall (present in 6 of 236 cases and 7 of 328 controls; odds ratio = 1.20, 95% CI 0.33 to 4.22). There was evidence of effect modification by Apolipoprotein E (APOE) status--among subjects with an APOE epsilon 4 allele, the T4336C variant was associated with disease (present in 5 of 139 cases and none of 82 controls; odds ratio = infinity, 95% CI 0.73 to infinity). APOE may be an important modifier of the T4336C effect, potentially explaining variable findings across previous studies. Alternatively, the positive findings reported to date may simply reflect the problem of "type I" error inherent in genetic association studies. Substantially larger samples than are currently available would be required to resolve this question. G5460(A/T) variants were also investigated and found not to be associated with Alzheimer disease.

Aged↗