1. What is a GRN?
network that describes regulatory and physical interactions between genes and regulators (transcription factors)
2. Why is there interest in formulating GRNs?
to be able to identify developmental processes, virtual embryos, synthetic tissues/organs
—> recapitulation of GRN regulating gene expression/ development in certain tissues allows one to recreate them/ computational modelling on logic-based processes —> recapitulation of entire modules allows prediction of experimental outcomes based on computational models
3. Which organizational levels of GRNs could be distinguished?
basic unit
motif
module
gene regulatory network
4. Give examples for fundamental GRN motifs
autoregulation (positive or negative feedback)
single input
multi input
cascades
feed forward loop
5. What are composite transcriptional regulatory networks?
GRN that consist of multiple space and time modules?
e.g Drosophila dorsoventral GRN: maternal input and early and late zygotic input
6. At which different levels / approaches could you formalize GRNs mathematically?
thermodynamic models
linear models
Bayesian models
logical (boolean) models
7. For the mathematical approaches, please state which models are good for (i) very complex networks, or (ii) precise kinetic analysis
(i) boolean models
(ii) thermodynamic models?
8. What is considered with time and space modules? Give an example from Drosophila segmentation!
cis regulatory regions that enabel control of gene transcription in time and space
e.g. control of gap genes, pair-rule genes, segment polarity genes
—> even skipped 2:
spatial: controlled via activator (bicoid, hunchback) and repressor (giant and krüppel) thresholds
temporal: activator and repressor expression is temporally and spatially controlled via maternal inputs
9. How can one structure the Drosophila GRN for early dorsoventral pattern formation?
maternal input, early and late zygotic input
(?) spatial: mesoderm, ventral neurogenic ectoderm, dorsal ectoderm
10. What are the features of the sea urchin gastrula model that made this model suitable for GRN analysis
cis-regulatory region of endo-16
—> expression and interference experiments enable investigation of GRN
experimental data can be used to construct boolean models: AND gate, OR gate, AND NOT gate
11. Explain the principal organization of the GRNs controlling endo16 expression in sea urchins. What type of models may be used?
???
endoderm, mesendoderm, mesoderm
boolean models: AND gate, OR gate, AND NOT gate
12. What is a virtual sea urchin?
generation of computational logic models based on logic models based on experimental data
computational model that recapitulates GRN that regulates sea urchin mesendoderm development
enables prediction of experimental outcome
13. How do GRNs evolve?
acquiring of new cis-regulatory regions that enable spatial and temporal control
the more modules that regulate spatial and temporal control, the more precise the transcriptional regulation
14. What is a GRN kernel?
GRN that regulates patterning of a specific organ/tissue/body part conserved within an entire phyla
15. Explain why the “heart GRN kernel” may be of biomedical interest!
allows development of virtual heart GRN
identification of impact/pathology of genetic dieseases
validation of animal models
16. How conserved are GRNs and their elements?
usually highly conserved
—> GRN allewed identification of neural crest cells in tunicates
17. How could one use GRN knowledge to decide whether an iPS cell line (or any iPS derived tissue specific stem cell) is a good source for tissue regeneration?
compare of native/endogenous cells to that of iPS cells :
comparison of differentiation markers
comparison of pluripotency markers
comparison of temporal expression patterns
epigenetic landscape
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