Abstract
BackgroundRecent computational advances in ancient DNA research have opened access to the detection of ancient DNA methylation footprints at the genome-wide scale. The most commonly used approach infers the methylation state of a given genomic region on the basis of the amount of nucleotide mis-incorporations observed at CpG dinucleotide sites. However, this approach overlooks a number of confounding factors, including the presence of sequencing errors and true variants. The scale and distribution of the inferred methylation measurements are also variable across samples, precluding direct comparisons.FindingsHere, we present DamMet, an open-source software program retrieving maximum likelihood estimates of regional CpG methylation levels from ancient DNA sequencing data. It builds on a novel statistical model of post-mortem DNA damage for dinucleotides, accounting for sequencing errors, genotypes, and differential post-mortem cytosine deamination rates at both methylated and unmethylated sites. To validate DamMet, we extended gargammel, a sequence simulator for ancient DNA data, by introducing methylation-dependent features of post-mortem DNA decay. This new simulator provides direct validation of DamMet predictions. Additionally, the methylation levels inferred by DamMet were found to be correlated to those inferred by epiPALEOMIX and both on par and directly comparable to those measured from whole-genome bisulphite sequencing experiments of fresh tissues.ConclusionsDamMet provides genuine estimates for local DNA methylation levels in ancient individual genomes. The returned estimates are directly cross-sample comparable, and the software is available as an open-source C++ program hosted at https://gitlab.com/KHanghoj/DamMet along with a manual and tutorial.
Highlights
Recent studies in ancient DNA research have demonstrated that osseous methylomes can be mapped from the high-throughput DNA sequencing (HTS) data underlying ancient genomes [1,2,3]
To obtain the maximum likelihood estimate (MLE) of methylation position-specific post-mortem DNA deamination (PMD) rates, the likelihood function makes use of chromosome-wide read observations covering a cytosine located in a CpG context in the reference genome and an equal number of observations of cytosines located outside a CpG context
We find that the MLEs of position-specific PMD rates at both methylated and unmethylated cytosines (D) are highly accurate, at least down to 5-fold coverage, regardless of the PMD profile and library protocol considered (Fig. 1 and Supplementary Results Section 2.1.3)
Summary
Recent studies in ancient DNA (aDNA) research have demonstrated that osseous methylomes can be mapped from the high-throughput DNA sequencing (HTS) data underlying ancient genomes [1,2,3]. Findings: Here, we present DamMet, an open-source software program retrieving maximum likelihood estimates of regional CpG methylation levels from ancient DNA sequencing data. It builds on a novel statistical model of post-mortem DNA damage for dinucleotides, accounting for sequencing errors, genotypes, and differential post-mortem cytosine deamination rates at both methylated and unmethylated sites. The returned estimates are directly cross-sample comparable, and the software is available as an open-source C++ program hosted at https://gitlab.com/KHanghoj/DamMet along with a manual and tutorial
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