Methodological aspects of whole-genome bisulfite sequencing analysis

Abstract

The combination of DNA bisulfite treatment with high-throughput sequencing technologies has enabled investigation of genome-wide DNA methylation beyond CpG sites and CpG islands. These technologies have opened new avenues to understand the interplay between epigenetic events, chromatin plasticity and gene regulation. However, the processing, managing and mining of this huge volume of data require specialized computational tools and statistical methods that are yet to be standardized. Here, we describe a complete bisulfite sequencing analysis workflow, including recently developed programs, highlighting each of the crucial analysis steps required, i.e. sequencing quality control, reads alignment, methylation scoring, methylation heterogeneity assessment, genomic features annotation, data visualization and determination of differentially methylated cytosines. Moreover, we discuss the limitations of these technologies and considerations to perform suitable analyses.

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“…Bisulfite sequencing is considered the 'gold-standard' to characterize DNA-methylation as the only method resolving nucleotide-level polymorphisms (Schrey et al, 2013;Adusumalli et al, 2014). While whole genome bisulfite sequencing is still expensive for large sample sizes, reduced representation techniques, such as RRBS (Gu et al, 2011), bsRADseq (Trucchi et al, 2016), and epiGBS (van Gurp et al, 2016) allow for cost-effective population epigenetic comparisons, partly without the need for a reference genome.…”

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“…Nevertheless, a number of challenges continue to limit the utility of this technique. These include lower fragment complexity due to unmethylated cytosine to thymine conversion, PCR amplification bias for certain methylation states, significant coverage minimums, and difficulties with interpretation of methylation data in the context of other epigenetic changes, such as chromatin states [6, 7], as well as sequencing costs. As a result, multiple approaches have been developed to yield limited whole genome-level information while circumventing some of these limitations.…”

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