Data from: EpiRADseq: scalable analysis of genome-wide patterns of methylation using next-generation sequencing
Cite this dataset
Schield, Drew R. et al. (2016). Data from: EpiRADseq: scalable analysis of genome-wide patterns of methylation using next-generation sequencing [Dataset]. Dryad. https://doi.org/10.5061/dryad.hs200
1. Research addressing the role of epigenetics in a diversity of experimental and natural systems is rapidly accumulating. Diverse methods have been developed to study epigenetic states, including bisulfite sequencing and AFLP-based approaches. However, existing methods are sometimes difficult to apply to non-traditional model organisms that lack genomic resources (bisulfite sequencing), and can fail to be economical and readily scalable to diverse research questions because of reliance on traditional Sanger sequencing (AFLP approaches). 2. Here we develop a reduced-representation library-based approach that is scalable and economical to quantitatively compare patterns of genome-wide methylation. This approach shares substantial similarity to the now widely used double digest restriction-site associated DNA sequencing-based method (ddRADseq), except that it utilizes a methylation-sensitive restriction enzyme. This method therefore identifies changes in the genomic methylation state of cytosine (to 5-methyl-cytosine; 5mC) by sampling loci (via next-generation sequencing) that are not methylated within a sample. We test this method to identify shifts in the epigenome of clonal water fleas (Daphnia ambigua) in response to exposure to fish predator cues, which are known to induce transgenerational changes in life history traits. 3. We found evidence for differential transgenerational responses (inferred via significant shifts in the methylation state of sampled loci) to predator cues among our treatment groups, and remarkably consistent responses within treatment groups. Our results demonstrate that this method is capable of producing highly repeatable results even without the use of a reference genome. 4. Applications of this general method are broad and diverse, and include the analysis of epigenetic shifts in both experimental and natural study systems.