Data from: Degenerate adaptor sequences for detecting PCR duplicates in reduced representation sequencing data improve genotype calling accuracy
Tin, Mandy M. Y.; Rheindt, Frank E.; Cros, Emilie; Mikheyev, Alexander S. (2014), Data from: Degenerate adaptor sequences for detecting PCR duplicates in reduced representation sequencing data improve genotype calling accuracy, Dryad, Dataset, https://doi.org/10.5061/dryad.34dt1
RAD-tag is a powerful tool for high-throughput genotyping. It relies on PCR amplification of the starting material, following enzymatic digestion and sequencing adaptor ligation. Amplification introduces duplicate reads into the data, which arise from the same template molecule and are statistically nonindependent, potentially introducing errors into genotype calling. In shotgun sequencing, data duplicates are removed by filtering reads starting at the same position in the alignment. However, restriction enzymes target specific locations within the genome, causing reads to start in the same place, and making it difficult to estimate the extent of PCR duplication. Here, we introduce a slight change to the Illumina sequencing adaptor chemistry, appending a unique four-base tag to the first index read, which allows duplicate discrimination in aligned data. This approach was validated on the Illumina MiSeq platform, using double-digest libraries of ants (Wasmannia auropunctata) and yeast (Saccharomyces cerevisiae) with known genotypes, producing modest though statistically significant gains in the odds of calling a genotype accurately. More importantly, removing duplicates also corrected for strong sample-to-sample variability of genotype calling accuracy seen in the ant samples. For libraries prepared from low-input degraded museum bird samples (Mixornis gularis), which had low complexity, having been generated from relatively few starting molecules, adaptor tags show that virtually all of the genotypes were called with inflated confidence as a result of PCR duplicates. Quantification of library complexity by adaptor tagging does not significantly increase the difficulty of the overall workflow or its cost, but corrects for differences in quality between samples and permits analysis of low-input material.