Overview
Epigenomics is the genome-wide study of epigenetic modifications, chemical changes to DNA and chromatin that regulate gene expression without altering the underlying DNA sequence. These modifications include DNA methylation at CpG dinucleotides, post-translational histone modifications (such as acetylation, methylation, and phosphorylation), and chromatin accessibility patterns. Epigenomic maps vary across cell types, developmental stages, and disease states, providing a dynamic layer of information that complements the static genome. Large-scale projects such as the ENCODE and Roadmap Epigenomics consortia have produced comprehensive epigenomic atlases for hundreds of human cell types.
Methods
Epigenomic profiling relies on techniques adapted for high-throughput sequencing. Whole-genome bisulfite sequencing (WGBS) converts unmethylated cytosines to uracil, allowing single-base resolution methylation maps. ChIP-seq uses antibodies to immunoprecipitate specific histone modifications or transcription factor-bound regions, followed by sequencing. ATAC-seq and DNase-seq map open chromatin regions to identify active regulatory elements. Hi-C and related methods capture three-dimensional chromatin conformation. Bioinformatics pipelines process raw reads through alignment, peak calling (using MACS2 or PeakDene), and differential enrichment analysis. Integrative analysis combining multiple epigenomic tracks reveals chromatin states, such as active promoters, enhancers, and repressed regions, using tools like ChromHMM.
Applications
Epigenomics has transformed our understanding of development, aging, and disease. Aberrant DNA methylation patterns are hallmarks of cancer, with tumor suppressor gene silencing by promoter hypermethylation now a therapeutic target. Epigenomic profiling guides the discovery of enhancers and other regulatory elements studied in gene regulation and epigenetics. The technique is closely related to chromatin immunoprecipitation (ChIP) but scaled to the entire genome. Epigenomics also illuminates how DNA replication timing correlates with chromatin state, and how environmental exposures leave lasting epigenetic marks that influence health outcomes across the lifespan.
Practical Protocol
For whole-genome bisulfite sequencing (WGBS), start with 100–500 ng of genomic DNA spiked with 0.5% unmethylated lambda phage DNA as a conversion control. Fragment DNA by sonication to 200–400 bp, then perform end repair, A-tailing, and adapter ligation. Treat with sodium bisulfite using the EZ DNA Methylation-Gold Kit, which converts unmethylated cytosines to uracil while leaving methylated cytosines intact. PCR amplify (12 cycles) with uracil-tolerant polymerase (e.g., PfuTurbo Cx) and sequence paired-end 150 bp. Align reads with Bismark: bismark --genome genome_dir -1 R1.fastq -2 R2.fastq -o bismark_output. Remove duplicate reads with deduplicate_bismark. Extract methylation calls: bismark_methylation_extractor --gzip --bedGraph --counts --buffer_size 10G bismark_output.bam. The output includes per-CpG methylation percentages in a bedGraph or CX report file. For differential methylation analysis, use methylKit in R: methRead to import coverage files, calculateDiffMeth to identify differentially methylated cytosines or regions with q-value < 0.05 and methylation difference > 25%. For ENCODE ChIP-seq histone modification analysis, process raw reads through the ENCODE pipeline: align with Bowtie2, filter duplicates, call peaks with MACS2 using --broad mode for H3K27me3 or H3K36me3, and generate signal tracks with bedClip and bedGraphToBigWig. Chromatin state segmentation with ChromHMM combines multiple histone marks (H3K4me3, H3K27ac, H3K4me1, H3K36me3, H3K27me3) into a combinatorial model: java -jar ChromHMM.jar LearnModel -b 200 binarized_beds output_dir 15 hg38. The 15-state model segments the genome into active promoters, enhancers, transcribed regions, repressed Polycomb domains, and heterochromatin.
