Oral Presentation 29th Lorne Cancer Conference 2017

Single-Cell Genome-Wide Analysis of DNA Methylation (#24)

Heather J Lee 1 2 , Christof Angermueller 3 , Stephen J Clark 1 , Iain C Macaulay 2 , Mabel J Teng 2 , Tim Xiaoming Hu 2 3 4 , Felix Krueger 5 , Sebastien A Smallwood 1 6 , Chris P Ponting 2 4 , Thierry Voet 2 7 , Gavin Kelsey 1 , Oliver Stegle 3 , Wolf Reik 1 2 8 9
  1. Epigenetics Programme, Babraham Institute, Cambridge, UK
  2. Sanger Institute, Cambridge, UK
  3. European Bioinformatics Institute, European Molecular Biology Laboratory, Cambridge, UK
  4. Functional Genomics Unit, University of Oxford, Oxford, UK
  5. Bioinformatics Group, Babraham Institute, Cambridge, UK
  6. Fredrich Miescher Institute for Biomedical Research, Basel, Switzerland
  7. Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium
  8. Department of Physiology, University of Cambridge, Cambridge, UK
  9. Centre for Trophoblast Research, University of Cambridge, Cambridge, UK

Single-cell sequencing technologies are revolutionising our understanding of heterogeneous cell populations in development and disease. Incorporation of epigenetic information with single-cell transcriptomic and genomic analyses will provide valuable insights into the molecular mechanisms of gene regulation1. DNA methylation occurs on cytosine residues of CpG dinucleotides in mammalian cells. This epigenetic modification is dynamically regulated during development and is globally dysregulated in many cancer types. We developed single-cell bisulphite sequencing (scBS-seq)2, which provides quantitative, single-nucleotide information on DNA methylation for up to 50% of cytosines across the genome. Extending on this work, we recently reported parallel single-cell methylome and transcriptome sequencing (scM&T-seq)3, which allows both DNA methylation and gene expression to be assayed from the same single cell. The development of these methods will be described, and a comparison to other single-cell epigenomic methods will be provided. To illustrate the power of integrated single-cell multi-omics, biological insights gained from scM&T-seq analysis of mouse embryonic stem cells will be presented.

  1. Clark, Lee, Smallwood et al. (2016) Genome Biol 17:72.
  2. Smallwood, Lee, et al. (2014) Nat Methods 11:817-20.
  3. Angermueller, Clark, Lee, Macaulay, et al. (2016) Nat Methods 13:229-32.