Gene Regulation Networks and Systems-Level Control
From Single Genes to Regulatory Circuits
Network view
Gene regulation is best understood as a layered network of DNA elements, transcription factors, cofactors, chromatin state, signaling pathways, and feedback loops. System behavior can be nonlinear, switch-like, noisy, or oscillatory.
Important network motifs
Regulatory logic
AND-like control
- Requires multiple inputs
- Improves specificity
OR-like control
- Any input can drive output
- Supports redundancy
Noise matters
Stochastic gene expression is not just experimental nuisance; it can be functionally exploited during differentiation, adaptation, and bet-hedging.
Which motif is most associated with generating bistable cell states?
Positive feedback can stabilize alternative states and create memory-like behavior.
Correct answer: Positive feedback
Why are gene regulatory networks often nonlinear?
These features make output disproportionate to input across different regimes.
Correct answer: Because regulatory interactions include cooperativity, saturation, feedback, and thresholds
Typical systems-biology data types
| Data type | What it captures |
|---|---|
| Time-course RNA-seq | Dynamic expression changes |
| Perturb-seq | Transcriptomic response to perturbation |
| Single-cell multiome | Co-accessibility and expression in individual cells |
| Phosphoproteomics | Signal transduction state |
| CRISPR screen | Functional gene dependencies |
What is the most likely function of a feedforward loop in regulation?
Feedforward loops often tune the dynamics of gene expression.
Correct answer: To shape response timing or filter transient inputs
What is one advantage of single-cell analysis over bulk profiling?
Single-cell methods reveal rare states, trajectories, and lineage branching.
Correct answer: It resolves heterogeneity among individual cells that bulk measurements average out