Genetics and molecular biology have contributed to the development of rationalized plant breeding programs. Recent developments in both high-throughput experimental analyses of biological systems and in silico data processing offer the possibility to address the whole gene regulatory network (GRN) controlling a given trait. GRN models can be applied to identify topological features helping to shortlist potential candidate genes for breeding purposes. Time-series data sets can be used to support dynamic modelling of the network. This will enable a deeper comprehension of network behaviour and the identification of the few elements to be genetically rewired to push the system towards a modified phenotype of interest. This paves the way to design more efficient, systems biology-based breeding strategies.
Keywords: dynamic network analysis; gene discovery; gene regulatory networks; network engineering; plant breeding.
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