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The statistical geometry of transcriptome divergence in cell-type evolution and cancer

Author

Listed:
  • Cong Liang

    (Systems Biology Institute, Yale University
    Yale University
    Present address: 300 Heffernan Drive, B31 Room 267, West Haven, Connecticut 06516, USA)

  • Alistair R.R. Forrest

    (RIKEN Center for Life Science Technologies (CLST)
    Present address: 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan)

  • Günter P. Wagner

    (Systems Biology Institute, Yale University
    Yale University
    Present address: 300 Heffernan Drive, B31 Room 271, West Haven, Connecticut 06516, USA)

Abstract

In evolution, body plan complexity increases due to an increase in the number of individualized cell types. Yet, there is very little understanding of the mechanisms that produce this form of organismal complexity. One model for the origin of novel cell types is the sister cell-type model. According to this model, each cell type arises together with a sister cell type through specialization from an ancestral cell type. A key prediction of the sister cell-type model is that gene expression profiles of cell types exhibit tree structure. Here we present a statistical model for detecting tree structure in transcriptomic data and apply it to transcriptomes from ENCODE and FANTOM5. We show that transcriptomes of normal cells harbour substantial amounts of hierarchical structure. In contrast, cancer cell lines have less tree structure, suggesting that the emergence of cancer cells follows different principles from that of evolutionary cell-type origination.

Suggested Citation

  • Cong Liang & Alistair R.R. Forrest & Günter P. Wagner, 2015. "The statistical geometry of transcriptome divergence in cell-type evolution and cancer," Nature Communications, Nature, vol. 6(1), pages 1-6, May.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms7066
    DOI: 10.1038/ncomms7066
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