Abstract
BackgroundLow pass sequencing has been proposed as a cost-effective alternative to genotyping arrays to identify genetic variants that influence multifactorial traits in humans. For common diseases this typically has required both large sample sizes and comprehensive variant discovery. Genotyping arrays are also routinely used to perform pharmacogenetic (PGx) experiments where sample sizes are likely to be significantly smaller, but clinically relevant effect sizes likely to be larger.ResultsTo assess how low pass sequencing would compare to array based genotyping for PGx we compared a low-pass assay (in which 1x coverage or less of a target genome is sequenced) along with software for genotype imputation to standard approaches. We sequenced 79 individuals to 1x genome coverage and genotyped the same samples on the Affymetrix Axiom Biobank Precision Medicine Research Array (PMRA). We then down-sampled the sequencing data to 0.8x, 0.6x, and 0.4x coverage, and performed imputation. Both the genotype data and the sequencing data were further used to impute human leukocyte antigen (HLA) genotypes for all samples. We compared the sequencing data and the genotyping array data in terms of four metrics: overall concordance, concordance at single nucleotide polymorphisms in pharmacogenetics-related genes, concordance in imputed HLA genotypes, and imputation r2. Overall concordance between the two assays ranged from 98.2% (for 0.4x coverage sequencing) to 99.2% (for 1x coverage sequencing), with qualitatively similar numbers for the subsets of variants most important in pharmacogenetics. At common single nucleotide polymorphisms (SNPs), the mean imputation r2 from the genotyping array was 0.90, which was comparable to the imputation r2 from 0.4x coverage sequencing, while the mean imputation r2 from 1x sequencing data was 0.96.ConclusionsThese results indicate that low-pass sequencing to a depth above 0.4x coverage attains higher power for association studies when compared to the PMRA and should be considered as a competitive alternative to genotyping arrays for trait mapping in pharmacogenetics.
Highlights
Low pass sequencing has been proposed as a cost-effective alternative to genotyping arrays to identify genetic variants that influence multifactorial traits in humans
For our purposes we considered the genotypes from the Precision Medicine Research Array (PMRA) as “truth”; in this case the positive percent agreement” (PPA) ranged from 98.2% for 0.4x coverage sequencing to 99.2% for 1x coverage sequencing, while the Negative percent agreement (NPA) ranged from 99.8% for 0.4x coverage to 99.9% for 1x coverage (Table 1)
We selected 79 individuals to be both genotyped and sequenced. These individuals derive from a pool of Genotype concordance at ADME genes We compared the concordance between the genotypes at variants in ADME genes as defined by PPA (%) NPA (%) No Calls (Average)
Summary
Low pass sequencing has been proposed as a cost-effective alternative to genotyping arrays to identify genetic variants that influence multifactorial traits in humans. For common diseases this typically has required both large sample sizes and comprehensive variant discovery. By far the most commonly-used approach is the genotyping array, in which a set of known polymorphisms (usually around 500,000-2,000,000) is measured This technology is inexpensive (currently on the order of tens to hundreds of dollars), but the set of genetic variants profiled is a small number of all known variants, and the technology does not allow for the detection of new (for example rare or population-specific) genetic variants. As an intuition for why this approach is useful, note that a human sample sequenced at 0.4x coverage is expected to have a single sequencing read covering each of around 28 million of the 84.7 million genetic variants identified in the 1000 Genomes Project [1], while a genotyping array obtains measurements (albeit somewhat less noisy measurements) at two orders of magnitude fewer sites
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