4.1 Article

Regeneration in the Era of Functional Genomics and Gene Network Analysis

Journal

BIOLOGICAL BULLETIN
Volume 221, Issue 1, Pages 18-34

Publisher

UNIV CHICAGO PRESS
DOI: 10.1086/BBLv221n1p18

Keywords

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Funding

  1. Marine Biological Laboratory, The Charles Evans Foundation [A0005138]
  2. G. Harold and Leila Y. Mathers Research Professorship of Geriatrics and Adult Development (JDB)
  3. University of Texas, Austin
  4. Paralyzed Veterans of America Research [2586]
  5. Morton Cure Paralysis Fund
  6. Feinstein Institute for Medical Research
  7. Essel Foundation
  8. Howard Hughes Medical Institute (Williams College)

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What gives an organism the ability to regrow tissues and to recover function where another organism fails is the central problem of regenerative biology. The challenge is to describe the mechanisms of regeneration at the molecular level, delivering detailed insights into the many components that are cross-regulated. In other words, a broad, yet deep dissection of the system-wide network of molecular interactions is needed. Functional genomics has been used to elucidate gene regulatory networks (GRNs) in developing tissues, which, like regeneration, are complex systems. Therefore, we reason that the GRN approach, aided by next generation technologies, can also be applied to study the molecular mechanisms underlying the complex functions of regeneration. We ask what characteristics a model system must have to support a GRN analysis. Our discussion focuses on regeneration in the central nervous system, where loss of function has particularly devastating consequences for an organism. We examine a cohort of cells conserved across all vertebrates, the reticulospinal (RS) neurons, which lend themselves well to experimental manipulations. In the lamprey, a jawless vertebrate, there are giant RS neurons whose large size and ability to regenerate make them particularly suited for a GRN analysis. Adding to their value, a distinct subset of lamprey RS neurons reproducibly fail to regenerate, presenting an opportunity for side-by-side comparison of gene networks that promote or inhibit regeneration. Thus, determining the GRN for regeneration in RS neurons will provide a mechanistic understanding of the fundamental cues that lead to success or failure to regenerate.

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