When it comes time to tackle the big data of the epigenome, tools and databases are your best friend. However, in today’s modern world, there’s more than one way to crack the epigenome and now two new tools serve up some interesting perspectives on the use of reference sequence.
Going Deep into Databases
Felipe Albrecht and team from the Max Planck Institute for Informatics in Germany have developed DeepBlue. For the past 3 years, the team has been working away at this epigenomic data server with a sleek and modern web interface that serves up one healthy dose of international big data.
DeepBlue imports from:
And is capable of analysis like:
- Filtering epigenomic data by metadata and region attributes.
- Finding overlapping regions sets.
- Grouping regions.
- Retrieving DNA sequences.
- Pattern matching operations.
While the manuscript is imminent, DeepBlue is already awaiting you.
Go Reference Genome Free during RRBS with epiGbs
Reduced representation bisulfite sequencing (RRBS) has proved to be a useful tool for exploring the epigenome; however, its tricks at reducing representation also produce some novel difficulties. Now a talented team from the Netherlands take a new perspective on RRBS and bring forth epiGbs.
epiGbs takes on a genotyping by sequencing approach combined with bisulfite conversion to provide some integrative methylomic and genomic data. The epiGbs methodology utilizes methylation sensitive restriction enzymes to digest genomic DNA, which is then ligated to barcoded adapters with 5mC that are compatible with Illumina sequencing technology. After ligation to barcoded adaptors, the samples are pooled, size selected, bisulfite treated, and PCR amplified to create the sequencing library.
The use of 5mC on the barcoded adaptors ensures they remain as C after bisulfite conversion, while the flanking C will always have been converted due to the use of methylation sensitive restriction enzymes. Thus, the 5mC barcode design proves useful for trimming the adapter sequence during bioinformatic analysis. Additionally, in order to tackle the reduced complexity of the genome, the epiGbs informatics pipeline cleverly takes advantage of paired end sequencing and uses both strands to discriminate between CpG-SNP and non-methylated CpG by checking for the presence of a G on the other strand.
Here’s what epiGbs offers up:
- A simpler and more cost-effective protocol.
- The ability to call both DNA methylation levels and SNPs.
- The resulting output can then be put directly into a genome browser for visualization and into RnBeads for analysis of differential methylation.
Ultimately, epiGbs enables explorative and comparative analysis of DNA methylation and genetic variation in hundreds of samples without the need for a reference genome, which makes it uniquely non-model organism friendly.