Inference of the genetic network regulating lateral root initiation in Arabidopsis thaliana.

TitleInference of the genetic network regulating lateral root initiation in Arabidopsis thaliana.
Publication TypeJournal Article
Year of Publication2013
AuthorsMuraro D, Voβ U, Wilson M, Bennett M, Byrne H, De Smet I, Hodgman C, King J
JournalIEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM
Volume10
Issue1
Pagination50-60
Date Published2013 Jan-Feb
Abstract

Regulation of gene expression is crucial for organism growth, and it is one of the challenges in systems biology to reconstruct the underlying regulatory biological networks from transcriptomic data. The formation of lateral roots in Arabidopsis thaliana is stimulated by a cascade of regulators of which only the interactions of its initial elements have been identified. Using simulated gene expression data with known network topology, we compare the performance of inference algorithms, based on different approaches, for which ready-to-use software is available. We show that their performance improves with the network size and the inclusion of mutants. We then analyze two sets of genes, whose activity is likely to be relevant to lateral root initiation in Arabidopsis, and assess causality of their regulatory interactions by integrating sequence analysis with the intersection of the results of the best performing methods on time series and mutants. The methods applied capture known interactions between genes that are candidate regulators at early stages of development. The network inferred from genes significantly expressed during lateral root formation exhibits distinct scale free, small world and hierarchical properties and the nodes with a high out-degree may warrant further investigation.

DOI10.3109/08820139.2013.801986
Alternate JournalIEEE/ACM Trans Comput Biol Bioinform