Uncover epigenetic mechanisms of gene regulation in development and disease.

EPIGENOMICS CHARACTERIZES THE CHROMATIN STATE down to minuscule chemical modifications. Epigenetic changes to the DNA and associated proteins affect gene expression and may lead to altered cellular states, including diseases.

We analyse a wide range of epigenomic sequencing data in order to gain deeper understanding of intra-cellular molecular mechanisms and to identify biomarkers for diseases.

Below we discuss common epigenomic data types and analyses, and present some of our past work involving epigenomic data analysis. To discuss your epigenomic bioinformatics needs, just leave us a message.

HIGH-THROUGHPUT ASSAYS FOR EPIGENOMIC PROFILING

The most common epigenomic assays focus on DNA methylation, DNA-binding proteins, histone modifications, chromatin accessibility or the 3D conformation of the chromatin.

• DNA methylation. DNA methylation assays based on bisuplhite-treated DNA enable identifying methylation events at the highest resolution. Such assays use next-generation sequencing (whole-genome or reduced representation bisulphite-sequencing) or microarrays. An alternative approach, MeDIP-sequencing, relies on immunoprecipitation and suffers from lower resolution.
• Transcription factor binding and histone modifications. Assays to identify DNA-bound proteins such as transcription factors, as well as chemical modifications to the histone proteins, make use of antibodies. ChIP-sequencing is the most common method, but newer alternatives with better resolution have been developed. These include ChIP-exo, Chipmentation, CUT&RUN and CUT&Tag.
• Chromatin accessibility. The gold standard assay for mapping regions of open chromatin is ATAC-sequencing. ATAC-seq has largely replaced previous methods such as DNase-seq and FAIRE-seq.
• Chromatin conformation. The importance of the chromatin’s three-dimensional conformation has gained particular appreciation recently. Chromatin conformation assays are used to study the physical interactions between genes and their distal regulatory elements as well as the proteins that cause such looping of the chromatin. Hi-C is a typical assay for the former, while ChIA-PET can be applied to the latter.

Peak calling and annotation

THE ANALYSIS WORKFLOW for most sequencing-based epigenomic data (particularly ChIP-seq, ATAC-seq and related experiments) involves identifying, annotating and analysing peaks, or genomic regions with signal of interest.

The raw sequencing reads are first quality-controlled and aligned to a reference genome, after which possible control libraries (pre-IP input and IP with non-specific antibody, in the case of ChIP-seq) are used to normalize the read coverage signal.

To enable further analysis, peaks are annotated with relevant information such as read statistics, and near or overlapping features such as genes, regulatory elements and binding motifs.

Differential peak analysis

TO COMPARE DIFFERENT CONDITIONS, the identified peaks can be statistically compared — or, more commonly, differential peaks can be directly called from the respective read coverage signals.

Similar to differential gene expression analysis, differential peak analysis yields estimates on the effect size and statistical significance. These statistics can be visualized as a volcano plot.

As genome-wide epigenomic measurements yield a continuous signal across the genome, such analyses may also focus on specific regions of interest, such as promoters or known binding sites of a protein of interest. Density heatmaps are used to visualize the signal at sites of interest in different conditions.

Integrating RNA-seq and epigenomic data

PERFORMING RNA-SEQ AND EPIGENOMIC SEQUENCING (such as ChIP or ATAC-seq) on the same samples enables integrative analyses to study gene regulatory programs genome-wide.

Regulatory connections can be identified between enhancers and their target genes, as well as transcription factors and their targets, building on evidence from both gene expression and the epigenomic status of regulatory elements.