Rapid and Affordable Genome-Wide Bisulfite DNA Sequencing by XmaI-Reduced Representation Bisulfite Sequencing

Abstract

We have developed an XmaI-RRBS method for rapid and affordable genome-wide DNA methylation analysis, with library preparation taking only 4 days and sequencing possible within 4 h. We have also addressed several challenges in order to further improve the RRBS technology. XmaI-RRBS may be performed on degraded DNA samples and is compatible with the bench-top next-generation sequencing machines.

cuRRBS: simple and robust evaluation of enzyme combinations for reduced representation approaches

“…Previous studies have tested the potential of other restriction enzymes and enzyme combinations to expand the range of CpG sites that can be targeted in a genome ( 8 – 11 , 28 , 30 , 56 , 57 ). However, to our knowledge, there is currently no computational method that systematically explores the capacity of all commercially-available restriction enzymes to generate ‘personalised’ reduced-representations of the genome whilst minimising the experimental cost ( Supplementary Figure S2E ).…”

“…XmaI-RRBS data generated on the Ion Torrent platform ( 30 ) and MspI&Taq α I-RRBS data generated on the Illumina HiSeq platform ( 31 ) were quality-trimmed using Trim Galore ( www.bioinformatics.babraham.ac.uk/projects/trim_galore/ ) and had base pairs removed from the 3′ end to avoid including filled-in nucleotides with artificial methylation states (the filled-in XmaI, MspI and Taq α I cut sites include the nucleotide sequence CCGG, CG and CG respectively). The data was then mapped to the human genome (for XmaI data, parameters: –non_directional) or the mouse genome (for MspI&Taq α I data, parameters: –directional) using Bismark (0.18.0) ( 55 ).…”

“…We assessed the performance of cuRRBS predictions in two independent experimental datasets ( 30 , 31 ) (see ‘Experimental validation of cuRRBS’ in Results and discussion). We ran cuRRBS fixing the theoretical size ranges tested to the ones reported in the publications ( 30 , 31 ) and we used as our sites of interest the CpGs that overlapped with CpG islands (CGI-CpGs) in the human ( 30 ) and the mouse genomes ( 31 ) respectively. From the cuRRBS output files, we recovered the IDs of the sites that should be theoretically sequenced.…”

“…From the cuRRBS output files, we recovered the IDs of the sites that should be theoretically sequenced. Moreover, using the experimental RRBS data ( 30 , 31 ), we could obtain the IDs of the sites that were actually sequenced (filtered by a given depth of coverage threshold). Afterwards, we calculated the following variables for each one of the datasets: True positives ( TP ): number of CGI-CpGs that cuRRBS predicted to be sequenced and were indeed found in the RRBS data.…”

“…Here, we have tested the enrichment ability of cuRRBS in several biological systems, with sites in both CpG and CHG contexts and multiple species, to showcase the generalisability and utility of the software ( 35 – 41 ). In addition, we take advantage of two recently published independent RRBS datasets to demonstrate the accuracy of the software predictions in both single and double enzyme experimental settings ( 30 , 31 ).…”