Continuous-time modeling of cell fate determination in Arabidopsis flowers

Abstract

BackgroundThe genetic control of floral organ specification is currently being investigated by various approaches, both experimentally and through modeling. Models and simulations have mostly involved boolean or related methods, and so far a quantitative, continuous-time approach has not been explored.ResultsWe propose an ordinary differential equation (ODE) model that describes the gene expression dynamics of a gene regulatory network that controls floral organ formation in the model plant Arabidopsis thaliana. In this model, the dimerization of MADS-box transcription factors is incorporated explicitly. The unknown parameters are estimated from (known) experimental expression data. The model is validated by simulation studies of known mutant plants.ConclusionsThe proposed model gives realistic predictions with respect to independent mutation data. A simulation study is carried out to predict the effects of a new type of mutation that has so far not been made in Arabidopsis, but that could be used as a severe test of the validity of the model. According to our predictions, the role of dimers is surprisingly important. Moreover, the functional loss of any dimer leads to one or more phenotypic alterations.

Developmental and evolutionary diversity of plant MADS-domain factors: insights from recent studies

“…Advanced proteomics and in vivo imaging approaches can be used to systematically study the regulation of MADS-box transcription factor activities in planta. In addition, the modeling of MADS-box regulatory networks can provide novel insights (Espinosa-Soto et al, 2004;van Mourik et al, 2010), but will require more quantitative in vivo data in the future.Finally, a number of studies have shown that many MADS-box genes have roles in more than one organ or developmental stage. How can the same factor have different functions in different developmental contexts?…”

Integrating two patterning processes in the flower

“…2 The interacting MADS genes form a gene regulatory network that has been studied previously with the help of mathematical modeling. [3][4][5] Recently, Urbanus et The resulting computational model will help explore hypothetical interactions between the MADS and auxin regulation networks in floral organ patterning. For example, it is still unknown whether MADS proteins function mainly in dimers, 8 or in tetramers, or even higher order complexes.…”

Modeling Regulatory Networks to Understand Plant Development: Small Is Beautiful

“…For instance, the auxin signaling model by Vernoux et al (2011) reduces the binding of TIR1 receptors with auxin and Aux/IAA to a simple MichaelisMenten term in the equations (Figure 2A) by assuming this processes is fast when compared with changes in gene expression. This type of reduction is also often used to eliminate the variables describing dimers from a system, assuming proteinprotein binding is much faster than the processes such as transcription or translation (for example, see Savage et al, 2008;van Mourik et al, 2010;Band et al, 2012c). However, it is worth stressing that the quasi-steady state assumption can lead to the wrong dynamics if this assumption is not valid (i.e., if there is not a clear separation of timescales).…”

“…Organisms such as Arabidopsis typically have large gene families in their genome (such as the 29 Aux/IAAs and 23 ARFs; Chapman and Estelle, 2009), and it is common for modelers to try and reduce this complexity by lumping whole gene families together so that they are represented by a single variable (for example, see Middleton et al, 2010;van Mourik et al, 2010). This is a reasonable first step and is most likely a valid one provided the individual family members all have similar behavior.…”

“…Since a Boolean approach was used, a relatively high number of genes (around 15) could be studied. However, more recently, an ODE-based model (van Mourik et al, 2010) of floral specification has been developed. The model reproduced known mutant behaviors for several mutations but also predicted new phenotypic effects of mutations yet to be tested.…”