10. Gene regulatory networks Flashcards
What are gene regulatory networks?
Gene regulatory networks (GRNs) - systems of interacting genes that work together to control gene expression in a cell or organism
From all possible gene interactions in a cell how are some interaction possibilities constrained?
Many genes in cell - potentially could all interact - but don’t because GRNs organised in motifs - which constrain the number of possible interactions between genes
Don’t need proof for all mechanisms to be able to work them out - GRN motifs are reused in different GRNs
Why are GRNs driven to operate?
GRNs are driven to operate to take cells to more stable states - some gene expression states are more stable than others - directed towards a basin of attraction - a stable transcriptional state of a cell - usally a differentiated state
Middle cell states in the process of differentiation - progenitors - in meta-stable states - are responsive to extrinsic inputs to drive GRNs to get to a more stable expression state
What is a GRN motif?
A GRN motif is a small functional system of gene interaction - several motifs come together to form GRNs
A GRN motif can be:
- feedforward loop
- feedback loop
- single input module
Explain an example of a GRN motif acting to drive cell differentiation from a meta-stable state into a stable state
Gata1-Pu.1 cross-antagonism GRN motif - bipotential progenitors in a meta-stable state -Gata1-Pu.1 interact by repressing each other - once one is slightly more expressed-> adopts the fate of either an erythroid cell (Gata1) or a myeloid cell (Pu.1) - stable differentiated cell states
This system is not reliant on extrinsic signalling - self-regulated decision - mechanism important in blood cells because are not spatially constricted - a dynamic cell environemnt - no chance for spatial signal
Describe development as a GRN
Development - one big GRN landscape - initial GRNs high in E -> subsequent GRNs lower and lower in E - drives cells into more stable differentiated cell states
What is a double negative gate subcircuit GRN motif?
Double negative gate subcircuit - repressing a repressor system -> coordinated activation of target genes
More safe when 2 factors guard expression - less ‘leaky’ system
What is a double negative gate GRN motif?
Double negative gate - need 2 signals for activation:
- a broad signal, not specific for the GRN, just present as a representative the the cell localisation
- a specific signal needed for the GRN activation
Common mechanism for conferring spatially restricted patterns of gene expression - prevents genes from being expressed ectopically - multilayered gene regulation
What is a positive feedback lockdown circuit GRN motif?
Positive feedback lockdown circuit - initial signal activates but the activation upkeeping maintained by the activated genes - independent of the inital activator
A motif for cellular memory - remember which genes turned on
Explain what is cellular memory
Cellular memory - cell state is independent of input - of initiator
Lecture summary
Paper discussed in the lecture Balaskas et al. 2011; what was the main idea challenged in this study?
Balaskas et al. 2011 challenged the French flag model or morphogen gradient - suggests that cell fate corresponds to local concentration of the morphogen => morphogen patterning = cell fate patterning
Used neural tube development signalling + patterning - Shh acts as a morphogen to induce different cell fates in th eneural tube - HOWEVER proved that morphogen (Shh) patterning is not equal to cell fate patterning - dependent on GRN
Cell fate decisions nto explained by morphogen positional identity - also depends on GRN input
What results were obatined when Shh activity was measured across D-V of the neural tube over time in Balaskas et al. 2011?
Higher Shh activity (Gli activation) in ventral side but gradient declines over time
Shows that there is a morphogen gradient but it is dynamic - not static - changes over time throughout the neural tube - French Flag challenged because it proposes a static morphogen gradient across tissue - but here a dynamic gradient with changing Shh levels and still functions as a morphogen to induce different cell fates
What was the boundry between different morphogen gradient thresholds investigated within neural tube in Balaskas et al. 2011?
The boundries between different Shh induction cell fates investigated - expression of Nkx.2.2, Olig2, Pax6 - the three fate markers - looked at their positional expression over time - over time gradient changes
What was noticed once morphogen Shh was removed in Balaskas et al. 2011?
When Shh was removed - Nkx2.2 marker still apeeared independently of Shh - but others didn’t - GRN behind is strong behinf Shh
What is the GRN behind neural tube patterning in Balaskas et al. 2011?
What was observed when specific cell fate markers where KO in Balaskas et al. 2011?
When KO - other specific cell fate markersw were displaced from their normal spatial patterns - they interact in GRN
How was mathematicla modelling used to investigate neural tube patterning GRN expression in Balaskas et al. 2011?
Computer simulation - mathematical modelling of cell fate marker expression levels - neural tube fate GRN - trying to predict patterning from knowing the GRN interactions
How was the cncept of hysteresis investigated in in Balaskas et al. 2011?
Investigtaed if hysteresis acted in Shh level induced outcome stabilization - observed that yes - certain level of Shh needed to induce - keeps constant no matter the increase above - also needs a certain level not to turn on Nkx2.2 below which didn’t respond
Explain what is hysteresis in GRNs
