Summary
The nature of an organism is determined largely by the dynamic interplay between its gene
repertoire and the regulatory apparatus, which consists of transcription factors. The assembly of
regulatory interactions linking transcription factors (TF) to their target genes (TG) forms a
transcriptional regulatory network. This thesis focuses on the following fundamental aspects of
evolution of transcriptional networks: (i) evolution of TFs, (ii) evolutionary mechanisms of
network growth, (iii) types of changes during evolution, and (iv) dynamic response of network
structure to different growth conditions within an organism.
(i) A computational procedure that identified 271 putative TFs in the E. coli genome was
developed. Evolutionary analysis of domain organisation of TFs revealed that the DNA binding
domains (DBD) belong to one of the 11 SCOP superfamilies. We showed that ~75% of TFs
evolved by gene duplication. It was also shown that proteins that contain DBDs from the same
superfamily could have different regulatory functions. It is rather the position of TF binding site
within DNA that determines its function as an activator or a repressor.
(ii) Mechanisms for the evolution of regulatory networks were developed. Analysis of domain
organisation of TFs and TGs in the known E. coli and yeast regulatory networks revealed that
close to 90% of all regulatory interactions have evolved through duplication of the pre-existing
genes. Regulatory interactions were either inherited or modified subsequent to gene duplication.
We also showed that global and local structure of regulatory networks cannot be attributed to
duplication alone, indicating the action of other evolutionary forces.
(iii) A computational procedure that allowed reconstruction of transcriptional regulatory networks
for 175 prokaryotic genomes was developed. Analysis of the reconstructed networks led to
characterization of patterns of evolutionary change in both global and local network structure.
We showed that regulatory hubs have been lost or replaced in the absence of apparent
selective pressure to maintain them. Levels of conservation of regulatory motifs found within
transcriptional networks were also assessed. An intriguing finding was that the same gene could
be a part of different motifs in different genomes. This study provides the first overview of
transcriptional control in poorly characterised genomes.
(iv) For the yeast genome, gene expression data across different growth conditions was
integrated with the known transcriptional network in order to identify condition specific
sub-networks. We found that the structure of these sub-networks differed significantly. The set
of regulatory hubs was different for various conditions, suggesting that differential expression of
key hubs could induce particular cellular conditions. We discovered that different types of
network motifs are being preferentially used in different conditions and provide insight into the
dynamic usage of regulatory interactions within an organism.
This thesis illuminates principles in the evolution of transcription factors, networks within &
across organisms and the dynamic usage within an organism. It also provides predictions that
could be useful in engineering regulatory networks in different organisms.