A time-resolved multi-omic atlas of the developing mouse liver

  1. Yi Wang1,2
  1. 1State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences, Institute of Lifeomics, Beijing 102206, China;
  2. 2Alkek Center for Molecular Discovery, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA;
  3. 3Department of Life Sciences, East China Normal University, Shanghai 200241, China;
  4. 4State Key Laboratory of Genetic Engineering, Human Phenome Institute, Institutes of Biomedical Sciences, and School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai 200433, China
  1. 5 These authors contributed equally to this work.

  • Corresponding author: yiw{at}bcm.edu
  • Abstract

    Liver organogenesis and development are composed of a series of complex, well-orchestrated events. Identifying key factors and pathways governing liver development will help elucidate the physiological and pathological processes including those of cancer. We conducted multidimensional omics measurements including protein, mRNA, and transcription factor (TF) DNA-binding activity for mouse liver tissues collected from embryonic day 12.5 (E12.5) to postnatal week 8 (W8), encompassing major developmental stages. These data sets reveal dynamic changes of core liver functions and canonical signaling pathways governing development at both mRNA and protein levels. The TF DNA-binding activity data set highlights the importance of TF activity in early embryonic development. A comparison between mouse liver development and human hepatocellular carcinoma (HCC) proteomic profiles reveal that more aggressive tumors are characterized with the activation of early embryonic development pathways, whereas less aggressive ones maintain liver function–related pathways that are elevated in the mature liver. This work offers a panoramic view of mouse liver development and provides a rich resource to explore in-depth functional characterization.

    Footnotes

    • Received June 5, 2019.
    • Accepted January 17, 2020.

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