Nicholas Geard, Janet Wiles and John Mattick

1
Modelling the Role of Small RNAs in Gene
Regulation
Nicholas Geard, Janet Wiles and John Mattick
Statistics averaged over 100 networks with the
following parameters
Results Structure
genome length 100,000 genes 350 protein
length 6 sRNA length 7
The Model
Input Distribution
Output Distribution

• An Artificial Genome is generated and parsed to
  extract genes (indicated by 1010 promoter
  sequences).
• Genes are divided into messenger RNA (mRNA),
  which is translated into a protein, and
  non-coding, small RNA (sRNA), which remains
  untranslated.
• The upstream regulatory region of each gene is
  searched for binding sites matching the protein
  and sRNA sequences.
• These regulatory interactions are combined to
  create a gene regulatory network.

Background

• As the number of functional components in genetic
  systems increases, the level of regulation to
  control dynamic behaviour increases.
• In contrast to prokaryotic organisms, eukaryotes
  seem to have overcome this regulatory constraint.
• It has been suggested that small, non-coding RNAs
  may act as regulatory elements, allowing the
  complexity of the system to increase without the
  need for additional regulatory genes.
• Our model has been developed to generate
  artificial regulatory networks both with and
  without small RNA regulation.
• Comparisons of structure and dynamics indicate
  that small RNA regulation allows increased
  control of complex networks.

Results Dynamics
(Expression Patterns for Synchronous Model)
Protein sRNA
Protein Only
Genes
Genes
Contact nic_at_itee.uq.edu.au
Time
Time
Complex and Intelligent Systems Group and
Institute for Molecular Bioscience