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Examining the Impact of Imputation Errors on Fine-Mapping Using DNA Methylation QTL as a Model Trait.
- Source :
-
Genetics [Genetics] 2019 Jul; Vol. 212 (3), pp. 577-586. Date of Electronic Publication: 2019 Apr 30. - Publication Year :
- 2019
-
Abstract
- Genetic variants disrupting DNA methylation at CpG dinucleotides (CpG-SNP) provide a set of known causal variants to serve as models to test fine-mapping methodology. We use 1716 CpG-SNPs to test three fine-mapping approaches (Bayesian imputation-based association mapping, Bayesian sparse linear mixed model, and the J-test), assessing the impact of imputation errors and the choice of reference panel by using both whole-genome sequence (WGS), and genotype array data on the same individuals ( n = 1166). The choice of imputation reference panel had a strong effect on imputation accuracy, with the 1000 Genomes Project Phase 3 (1000G) reference panel ( n = 2504 from 26 populations) giving a mean nonreference discordance rate between imputed and sequenced genotypes of 3.2% compared to 1.6% when using the Haplotype Reference Consortium (HRC) reference panel ( n = 32,470 Europeans). These imputation errors had an impact on whether the CpG-SNP was included in the 95% credible set, with a difference of ∼23% and ∼7% between the WGS and the 1000G and HRC imputed datasets, respectively. All of the fine-mapping methods failed to reach the expected 95% coverage of the CpG-SNP. This is attributed to secondary cis genetic effects that are unable to be statistically separated from the CpG-SNP, and through a masking mechanism where the effect of the methylation disrupting allele at the CpG-SNP is hidden by the effect of a nearby SNP that has strong linkage disequilibrium with the CpG-SNP. The reduced accuracy in fine-mapping a known causal variant in a low-level biological trait with imputed genetic data has implications for the study of higher-order complex traits and disease.<br /> (Copyright © 2019 Chundru et al.)
- Subjects :
- CpG Islands
Genome-Wide Association Study standards
Humans
Polymorphism, Single Nucleotide
Quantitative Trait, Heritable
Reference Standards
Reproducibility of Results
Whole Genome Sequencing standards
DNA Methylation
Genome-Wide Association Study methods
Quantitative Trait Loci
Whole Genome Sequencing methods
Subjects
Details
- Language :
- English
- ISSN :
- 1943-2631
- Volume :
- 212
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Genetics
- Publication Type :
- Academic Journal
- Accession number :
- 31040117
- Full Text :
- https://doi.org/10.1534/genetics.118.301861