Machine learning reveals the transcriptional regulatory network and circadian dynamics of PCC 7942.

Journal: Proceedings of the National Academy of Sciences of the United States of America
PMID: 39269777

Abstract

is an important cyanobacterium that serves as a versatile and robust model for studying circadian biology and photosynthetic metabolism. Its transcriptional regulatory network (TRN) is of fundamental interest, as it orchestrates the cell's adaptation to the environment, including its response to sunlight. Despite the previous characterization of constituent parts of the TRN, a comprehensive layout of its topology remains to be established. Here, we decomposed a compendium of 300 high-quality RNA sequencing datasets of the model strain PCC 7942 using independent component analysis. We obtained 57 independently modulated gene sets, or iModulons, that explain 67% of the variance in the transcriptional response and 1) accurately reflect the activity of known transcriptional regulations, 2) capture functional components of photosynthesis, 3) provide hypotheses for regulon structures and functional annotations of poorly characterized genes, and 4) describe the transcriptional shifts under dynamic light conditions. This transcriptome-wide analysis of provides a quantitative reconstruction of the TRN and presents a knowledge base that can guide future investigations. Our systems-level analysis also provides a global TRN structure for PCC 7942.

Authors

  • Yuan Yuan
    Department of Geriatrics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
  • Tahani Al Bulushi
    Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA 92093.
  • Anand V Sastry
    Department of Bioengineering, University of California San Diego, La Jolla, CA, 92093, USA.
  • Cigdem Sancar
    Center for Circadian Biology, University of California, San Diego, La Jolla, CA 92093.
  • Richard Szubin
    Department of Bioengineering, University of California-San Diego, La Jolla, California, USA.
  • Susan S Golden
    Center for Circadian Biology, University of California, San Diego, La Jolla, CA 92093.
  • Bernhard O Palsson
    Department of Bioengineering, University of California, San Diego, CA, USA.

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