Abstract
Whole-genome bisulfite sequencing (WGBS) is a popular method for characterizing cytosine methylation because it is fully quantitative and has base-pair resolution. While WGBS is prohibitively expensive for experiments involving many samples, low-coverage WGBS can accurately determine global methylation and erasure at similar cost to high-performance liquid chromatography (HPLC) or enzyme-linked immunosorbent assays (ELISA). Moreover, low-coverage WGBS has the capacity to distinguish between methylation in different cytosine contexts (e.g., CG, CHH, and CHG), can tolerate low-input material (<100cells), and can detect the presence of overrepresented DNA originating from mitochondria or amplified ribosomal DNA. In addition to describing a WGBS library construction and quantitation approach, here we detail computational methods to predict the accuracy of low-coverage WGBS using empirical bootstrap samplers and theoretical estimators similar to those used in election polling. Using examples, we further demonstrate how non-independent sampling of cytosines can alter the precision of error calculation and provide methods to improve this.
Highlights
Cytosine methylation is a well-described epigenetic modification that is essential for vertebrate development [1, 2], and when in the CG dinucleotide context, can transmit molecular memory postreplication
This unique ability is due to the symmetry of CG dinucleotides; methylation signals on the template strand are recognized by maintenance methylation enzymes and copied to
Considerable methylation does exist on cytosines outside of the CG context in mammals, and the CG/CHG context in plants; this methylation is unable to maintain epigenetic memory post-replication and has as yet unknown function in mammals [4]
Summary
Cytosine methylation is a well-described epigenetic modification that is essential for vertebrate development [1, 2], and when in the CG dinucleotide context, can transmit molecular memory postreplication. A simple method to assay DNA methylation at low cost, but retain sequence context information, is to perform WGBS at low coverage [11–15] In this way, global DNA methylation is effectively surveyed as if one was undertaking polling to predict the outcome of political election from a large population of voters. This protocol outlines two methods (one theoretical, one empirical) to calculate the margin of error (ε) associated with estimating global methylation level In doing so, this informs the experimentalist the number of cytosine calls, and how much sequencing is required in order to accurately predict global DNA methylation levels within a given confidence interval. For the sake of completeness, we have included a post-bisulfite adapter tagging (PBAT) protocol outlining WGBS library construction; any WGBS protocol can be used to predict global methylation using our theoretical and empirical sampling estimation methods
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