Poster Presentation 45th Lorne Genome Conference 2024

Multi-epigenomic analysis conducted using sequential techniques on a single sample (#112)

Alex Woodworth 1 , Brandon Signal 1 , Shannon Huskins 1 , Adele Woodhouse 2 , Phillippa Taberlay 1
  1. School of Medicine, University of Tasmania, Hobart, TAS
  2. Wicking Dementia Research and Education Centre, Hobart, Tasmania, Australia

The epigenome comprises a range of regulatory mechanisms which operate dynamically and cooperatively to maintain the correct structure and function of the genome. There are a variety of well-established assays which elucidate elements of this regulatory network, such as Chromatin Immunoprecipitation (ChIP) for locating transcription factors and histone modifications, Chromatin Conformation Capture (3C) and its derivatives for determining three-dimensional structure, and Nucleosome Occupancy and Methylome sequencing (NOMe-Seq). While these techniques are effective, obtaining combinatorial epigenetic data usually involves dividing a sample and conducting these assays in parallel, then collating the results to provide an overview of the epigenetic landscape for each sample. This method operates only on the average state of the sample for each assay and therefore cannot resolve correlations in epigenetic state at an individual molecular level.

 

To overcome this limitation, and to allow multiple epigenetic assays to be conducted usefully on limited samples, this project is attempting to conduct the previously mentioned techniques in sequence in a single assay. This assay will be able to identify nucleosome positioning, methylation, histone modifications, and interacting DNA regions simultaneously on the same strand of DNA, allowing for a more nuanced examination of interacting epigenetic systems. Initially, we have incorporated HiC methodology into the NOMe-Seq assay. This combined method detects chromatin interactions, in addition to DNA methylation and nucleosome positioning at the points of interaction. We have also developed a combined NOMe and ChIP-Seq workflow, which we have used to identify distinct subpopulations with differing locus-specific DNA accessibility associated with changes in histone modifications.