Uncovering the transcriptional circuitry in skeletal muscle regeneration

Skeletal muscle has a remarkable ability to regenerate after repeated and complete destruction of the tissue. The healing phases for an injured muscle undergo an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network is confronted by significant challenges and requires the integration of multiple experimental data types. In this work we present a system approach to describe the transcriptional circuitry during skeletal muscle regeneration using time-course expression data and motif scanning information. Time-lagged correlation analysis was utilized to evaluate the transcription factor (TF) → target associations. Our analysis identified six TFs that potentially play a central role throughout the regeneration process. Four of them have previously been described to be important for muscle regeneration and differentiation. The remaining two TFs are identified as novel regulators that may have a role in the regeneration process. We hope that our work may provide useful clues to help accelerate the recovery process in injured skeletal muscle.