Genome-wide DNA methylation and SNP genotyping of ǂKhomani San
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE99091 | GEO | 2017/05/20
SECONDARY ACCESSION(S): PRJNA387266
REPOSITORIES: GEO
Similar Datasets
Project description:Genome-wide DNA methylation and SNP genotyping of ǂKhomani San
| PRJNA387266 | ENA
Project description:Genome-wide DNA methylation profiling was conducted in two batches for 56 ǂKhomani San living in the South African Kalahari using the Illumina 450k array on saliva-derived DNA
2017-05-18 | GSE99029 | GEO
Project description:48 ǂKhomani San living in the South African Kalahari were genotyped using the Illumina OmniExpress, OmniExpress Plus, and HumanHap550 arrays
2017-05-20 | GSE99090 | GEO
Project description:With the increasing demand for higher throughput single nucleotide polymorphism (SNP) genotyping, the quantity of genomic DNA often falls short of the number of assays required. We investigated the use of degenerate oligonucleotide primed polymerase chain reaction (DOP-PCR) to generate a template for our SNP genotyping methodology of fluorescence polarization template-directed dye-terminator incorporation detection. DOP-PCR employs a degenerate primer (5'-CCGACTCGAGNNNNNNATGTGG-3') to produce non-specific uniform amplification of DNA. This approach has been successfully applied to microsatellite genotyping. We compared genotyping of DOP-PCR-amplified genomic DNA to genomic DNA as a template. Results were analyzed with respect to feasibility, allele loss of alleles, genotyping accuracy and storage conditions in a high-throughput genotyping environment. DOP-PCR yielded overall satisfactory results, with a certain loss in accuracy and quality of the genotype assignments. Accuracy and quality of genotypes generated from the DOP-PCR template also depended on storage conditions. Adding carrier DNA to a final concentration of 10 ng/microl improved results. In conclusion, we have successfully used DOP-PCR to amplify our genomic DNA collection for subsequent SNP genotyping as a standard process.
| S-EPMC137182 | biostudies-literature
Project description:BACKGROUND: Genome-wide association studies (GWAS) using array-based genotyping technology are widely used to identify genetic loci associated with complex diseases or other phenotypes. The costs of GWAS projects based on individual genotyping are still comparatively high and increase with the size of study populations. Genotyping using pooled DNA samples, as also being referred as to allelotyping approach, offers an alternative at affordable costs. In the present study, data from 100 DNA samples individually genotyped with the Affymetrix Genome-Wide Human SNP Array 6.0 were used to estimate the error of the pooling approach by comparing the results with those obtained using the same array type but DNA pools each composed of 50 of the same samples. Newly developed and established methods for signal intensity correction were applied. Furthermore, the relative allele intensity signals (RAS) obtained by allelotyping were compared to the corresponding values derived from individual genotyping. Similarly, differences in RAS values between pools were determined and compared. RESULTS: Regardless of the intensity correction method applied, the pooling-specific error of the pool intensity values was larger for single pools than for the comparison of the intensity values of two pools, which reflects the scenario of a case-control study. Using 50 pooled samples and analyzing 10,000 SNPs with a minor allele frequency of >1% and applying the best correction method for the corresponding type of comparison, the 90% quantile (median) of the pooling-specific absolute error of the RAS values for single sub-pools and the SNP-specific difference in allele frequency comparing two pools was 0.064 (0.026) and 0.056 (0.021), respectively. CONCLUSIONS: Correction of the RAS values reduced the error of the RAS values when analyzing single pool intensities. We developed a new correction method with high accuracy but low computational costs. Correction of RAS, however, only marginally reduced the error of true differences between two sample groups and those obtained by allelotyping. Exclusion of SNPs with a minor allele frequency of ? 1% notably reduced the pooling-specific error. Our findings allow for improving the estimation of the pooling-specific error and may help in designing allelotyping studies using the Affymetrix Genome-Wide Human SNP Array 6.0.
| S-EPMC3727995 | biostudies-literature
Project description:Methylation of CpG dinucleotides is a fundamental mechanism of epigenetic regulation in eukaryotic genomes. Development of methods for rapid genome wide methylation profiling will greatly facilitate both hypothesis and discovery driven research in the field of epigenetics. In this regard, a single molecule approach to methylation profiling offers several unique advantages that include elimination of chemical DNA modification steps and PCR amplification.A single molecule approach is presented for the discernment of methylation profiles, based on optical mapping. We report results from a series of pilot studies demonstrating the capabilities of optical mapping as a platform for methylation profiling of whole genomes. Optical mapping was used to discern the methylation profile from both an engineered and wild type Escherichia coli. Furthermore, the methylation status of selected loci within the genome of human embryonic stem cells was profiled using optical mapping.The optical mapping platform effectively detects DNA methylation patterns. Due to single molecule detection, optical mapping offers significant advantages over other technologies. This advantage stems from obviation of DNA modification steps, such as bisulfite treatment, and the ability of the platform to assay repeat dense regions within mammalian genomes inaccessible to techniques using array-hybridization technologies.
| S-EPMC2516518 | biostudies-other
Project description:This SuperSeries is composed of the SubSeries listed below.
2014-08-12 | GSE46401 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2013-12-28 | GSE52578 | GEO
Project description:SNP genotyping has emerged as a technology to incorporate copy number variants (CNVs) into genetic analyses of human traits. However, the extent to which SNP platforms accurately capture CNVs remains unclear. Using independent, sequence-based CNV maps, we find that commonly used SNP platforms have limited or no probe coverage for a large fraction of CNVs. Despite this, in 9 samples we inferred 368 CNVs using Illumina SNP genotyping data and experimentally validated over two-thirds of these. We also developed a method (SNP-Conditional Mixture Modeling, SCIMM) to robustly genotype deletions using as few as two SNP probes. We find that HapMap SNPs are strongly correlated with 82% of common deletions, but the newest SNP platforms effectively tag about 50%. We conclude that currently available genome-wide SNP assays can capture CNVs accurately, but improvements in array designs, particularly in duplicated sequences, are necessary to facilitate more comprehensive analyses of genomic variation.
| S-EPMC2759751 | biostudies-literature
Project description:During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors. High reliability of genotyping technology is needed to have confidence in using SNP data and interpreting GWAS results. Therefore, reproducibility of two widely genotyping technology platforms from Affymetrix and Illumina was assessed by analyzing four technical replicates from each of the six individuals in five laboratories. Genotype concordance of 99.40% to 99.87% within a laboratory for the sample platform, 98.59% to 99.86% across laboratories for the same platform, and 98.80% across genotyping platforms was observed. Moreover, arrays with low quality data were detected when comparing genotyping data from technical replicates, but they could not be detected according to venders' quality control (QC) suggestions. Our results demonstrated the technical reliability of currently available genotyping platforms but also indicated the importance of incorporating some technical replicates for genotyping QC in order to improve the reliability of GWAS results. The impact of discordant genotypes on association analysis results was simulated and could explain, at least in part, the irreproducibility of some GWAS findings when the effect size (i.e. the odds ratio) and the minor allele frequencies are low.
| S-EPMC3436888 | biostudies-literature