Abstract
Contamination from present-day DNA is a fundamental issue when studying ancient DNA from historical or archaeological material, and quantifying the amount of contamination is essential for downstream analyses. We present AuthentiCT, a command-line tool to estimate the proportion of present-day DNA contamination in ancient DNA datasets generated from single-stranded DNA libraries. The prediction is based solely on the patterns of post-mortem damage observed on ancient DNA sequences. The method has the power to quantify contamination from as few as 10,000 mapped sequences, making it particularly useful for analysing specimens that are poorly preserved or for which little data is available.
Highlights
After the death of an organism, its DNA decays and is progressively lost through time [1, 2]
Ancient DNA deamination patterns used in this study Deamination patterns in ancient DNA (aDNA) sequences depend on the DNA library preparation method used [45]
Excluding the first and last five bases to mask potential overhangs, we found that C-to-Ts are common in adjacent positions in many samples, with a significant deviation from the geometric distribution expected from independent events (p < 10−15, chi-square goodness-of-fit test; see Additional file 1: Supplementary Note 1 for more details or for results excluding the first and last ten bases), and from a control using sheared present-day human DNA that was treated like aDNA [9]
Summary
After the death of an organism, its DNA decays and is progressively lost through time [1, 2]. Whereas microbial sequences rarely align to the reference genome used for identifying endogenous sequences if appropriate length cut-offs are used [7,8,9], contamination with DNA from closely related organisms represents a recurrent problem [10,11,12]. This is true for the genomic analyses of ancient humans, as the individuals handling the specimens during excavation and at later times often leave their DNA behind [13, 14]. An estimate of the level of present-day DNA contamination is desirable for making decisions when screening samples to identify those that can be further sequenced with reasonable effort and expenses
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