A computational model of the effect of gene misexpression on the development of cortical areas

Abstract

Brain function depends on the specialisation of brain areas. In the murine cerebral cortex, the development of these areas depends on the coordinated expression of several genes in precise spatial patterns in the telencephalon during embryogenesis. Manipulating the expression of these genes during development alters the positions and sizes of cortical areas in the adult. Qualitative data also show that these genes regulate each other's expression during development so that they form a regulatory network with many feedback loops. However, it is currently unknown which regulatory interactions are critical to generating the correct expression patterns to lead to normal cortical development. Here, we formalise the relationships inferred from genetic manipulations into computational models. We simulate many different networks potentially consistent with the experimental data and show that a surprising diversity of networks produce similar results. This demonstrates that existing data cannot uniquely specify the network. We conclude by suggesting experiments necessary to constrain the model and help identify and understand the true structure of this regulatory network.

Adaptive Landscape Shaped by Core Endogenous Network Coordinates Complex Early Progenitor Fate Commitments in Embryonic Pancreas

“…Notably, the prediction is independent of the scRNA-seq analysis since no information from the single-cell data is used. The core endogenous network approach for development has practical significance, which is applicable to a wide range of developmental processes, considering there are core regulatory networks governing hematopoiesis 75 , neural development 76,77 , and other developmental processes 78 .…”

Thirty Years’ History since the Discovery of Pax6: From Central Nervous System Development to Neurodevelopmental Disorders

“…In contrast, Fgf8 from the rostral side induces Sp8 [ 55 , 59 ]. A mathematical analysis of gene regulatory networks using Boolean and computational models has revealed an underpinning expression gradient in the mammalian cortex [ 65 , 66 ]. Although upstream secretary molecules that can induce the expression of Pax6 have not been identified yet, it is of interest that Pax6 controls the responsiveness to secreted molecules such as sonic hedgehog and BMP in the cortex [ 67 ].…”

“…TF: transcriptional factor. The graphical diagram has been redrawn from [ 51 , 54 , 55 , 56 , 60 , 61 , 63 , 66 , 68 , 69 , 70 ]. …”

Theoretical Models of Neural Development

“…This model made testable predictions by determining the constraints on the network interactions necessary to reproduce the experimentally observed gradients ( Figure 2 C). Subsequent work transformed the Boolean model into a system of differential equations for continuous-valued expression levels and showed that the existing experimental data was not sufficient to uniquely specify the network ( Giacomantonio and Goodhill, 2014 ). This is one example of a much more general research program using mathematical models to understand the properties of gene networks ( Smolen et al., 2000 , Jaeger et al., 2004 ).…”