Identification of the Barley Circadian Clock from Genome Wide Time-Series Gene Expression Data

Most organisms have developed the capability of synchronizing their life cycle to the environment. As regards plants, the circadian clock regulatory network controls diverse biological processes, such as photosynthesis and flowering. The self-sustaining central oscillator consists in a complex network of interlocking genes activations, inhibitions and feedback loops that incorporates the environmental inputs.
Most biological experiments are costly and time consuming. Hence, the typical sampling rate of time-series gene expression data varies between 1 sample every 2 to 4 hours. Consequently, the identification of the functional properties of the individual components in gene regulatory networks is challenging.
Our approach uses Linear Time-Invariant (LTI) models to describe the causality between pairs of time-series genes expression data to retrieve information about the topology of the barley circadian clock. One significant advantage of this approach is that the identified models contain dynamical information on the nature of the regulation.