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

Liang, C
•
Alam, I
•
Albanese, D
altro
Zucchelli, Silvia
2015
  • journal article

Periodico
NATURE COMMUNICATIONS
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.
DOI
10.1038/ncomms7066
WOS
WOS:000348830600001
Archivio
http://hdl.handle.net/20.500.11767/12604
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84923072107
https://www.ncbi.nlm.nih.gov/pubmed/?term=10.1038%2Fncomms7066
Diritti
closed access
Soggetti
  • rna-seq data

  • phylogenetic networks...

  • Settore BIO/13 - Biol...

Scopus© citazioni
28
Data di acquisizione
Jun 2, 2022
Vedi dettagli
Web of Science© citazioni
35
Data di acquisizione
Mar 17, 2024
Visualizzazioni
1
Data di acquisizione
Apr 19, 2024
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