This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Inference of the Genetic Network Regulating Lateral Root Initiation in Arabidopsis thaliana
Jan.-Feb. 2013 (vol. 10 no. 1)
pp. 50-60
D. Muraro, Centre for Plant Integrative Biol., Univ. of Nottingham, Loughborough, UK
U. Voss, Centre for Plant Integrative Biol., Univ. of Nottingham, Loughborough, UK
M. Wilson, Centre for Plant Integrative Biol., Univ. of Nottingham, Loughborough, UK
M. Bennett, Centre for Plant Integrative Biol., Univ. of Nottingham, Loughborough, UK
H. Byrne, Centre for Plant Integrative Biol., Univ. of Nottingham, Loughborough, UK
I. De Smet, Centre for Plant Integrative Biol., Univ. of Nottingham, Loughborough, UK
C. Hodgman, Centre for Plant Integrative Biol., Univ. of Nottingham, Loughborough, UK
J. King, Centre for Plant Integrative Biol., Univ. of Nottingham, Loughborough, UK
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.
Index Terms:
Algorithm design and analysis,Time series analysis,Inference algorithms,Mathematical model,Educational institutions,Bayesian methods,Prediction algorithms,Arabidopsis thaliana,Reverse engineering,gene expression data
Citation:
D. Muraro, U. Voss, M. Wilson, M. Bennett, H. Byrne, I. De Smet, C. Hodgman, J. King, "Inference of the Genetic Network Regulating Lateral Root Initiation in Arabidopsis thaliana," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 1, pp. 50-60, Jan.-Feb. 2013, doi:10.1109/TCBB.2013.3
Usage of this product signifies your acceptance of the Terms of Use.