Fig. 2.

Workflow for high-throughput methyl-DNAshape method. a Sequence pool. DNA fragments were considered for MC simulations to capture a sequence space that includes CpG methylation. Published sequences (left rectangular box) [23] and manually designed sequences (right rectangular box) included DNA fragments comprising a variable core (containing at least one methylated CpG step, called “mg” step) and flanks (4 bp in length). Right flanks were reverse complements of left flanks. For a given length of core sequence (5, 6, or 7 bp), all possible sequences (Additional file 1) were considered for MC simulations. b Seed structures. Canonical B-DNA structures were generated for all selected sequences. The 5-methyl groups (orange circles) were introduced at cytosine positions with letter “m” (on Watson and Crick strand). c All-atom MC trajectories. Simulations were performed on seed structures for 2 million MC cycles, with snapshots recorded every 100 cycles after equilibration. d Mining trajectories. Recorded snapshots were analyzed for DNA shape features (see Additional file 1: Supplementary methods) associated with corresponding DNA sequences. e Pentamer Query Table (PQT). Pentamer sliding-window approach was applied to analyzed DNA fragments. Calculated DNA shape features (HelT, MGW, ProT, and Roll) were recorded at the center of each pentamer. Assigned value for a corresponding shape feature represents the average of all shape feature values in the sequence pool for a given pentamer in the PQT. f Front-end interface. Our easy-to-use methyl-DNAshape web server or DNAshapeR Bioconductor/R package can be used to profile shape features of any genomic region and DNA sequences of any length by using a pentamer sliding-window approach. The methyl-DNAshape web server, available at http://rohslab.usc.edu/methyl-DNAshape/, also outputs the effect of methylation on shape features in terms of Δshape (shown here for MGW)