As we head into fall in the northern hemi, the air gets a bit lighter, the leaves change, and improved ways to approach Reduced Representation Bisulfite Sequencing (RRBS), histone modification characterization, and bisulfite sequencing mapping emerge. Check out these three new techniques featured by our friends over at BMC in the latest issue of Genome Biology that may just take your own epigenetics project to the next level.
Gel-free Multiplexed Reduced Representation Bisulfite Sequencing (mRRBS)
There are quite a few ways to accomplish genome-scale mapping of DNA methylation, but throughput has often been a limiting factor. Scientists at the Broad Institute developed a protocol to aid in the mapping of DNA methylation, which they call gel-free multiplexed reduced representation bisulfite sequencing (mRRBS). Their technique requires less work to handle and enables processing of 96 or more samples in a week. The team also found that mRRBS achieves similar CpG coverage to original RRBS protocols, while delivering higher throughput and lower costs; traits that are well suited to large-scale DNA methylation mapping studies, like those using cancer samples.
Get all the details on mRRBS at Genome Biology, Boyle et al. October 2012.
Enhanced Characterization of Histone Post-translational Modifications
A group at Pacific Northwest National Laboratory has created a new way to help crack the histone code. They devised a “novel online two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS) platform for high-throughput and sensitive characterization of histone post-translational modifications (PTMs) at the intact protein level.” The platform provides spot-on identification of 708 histone isoforms from one analysis of 7.5 µg purified core histones, plus, throughput and sensitivity are vastly improved compared to previous methods.
Find out more at Genome Biology, Tian et al. October 2012.
BatMeth: Improved Bisulfite Sequencing Mapping
Bisulfite treatment and next-gen sequencing lets you study 5-methylcytosine in the genome, but it also creates mismatches between sequencing reads and the reference genome, making mapping reads slow and inaccurate. To tackle that issue National University of Singapore and Genome Institute of Singapore researchers designed BatMeth, which is “an algorithm that integrates novel Mismatch Counting, List Filtering, Mismatch Stage Filtering and Fast Mapping onto Two Indexes components.” The Singapore scientists found in experiments that BatMeth is faster and more accurate than other tools available today. BatMeth can be found for free at http://code.google.com/p/batmeth/
Read all about BatMeth at Genome Biology, Lim et al. October 2012.