Systems scale characterization of circadian rhythm pathway in Camellia sinensis

Tea (Camellia sinensis) is among the most valuable commercial crops being a non-alcoholic beverage having antioxidant properties. Like in other plants, circadian oscillator in tea modulates several biological processes according to earth's revolution dependent variations in environmental cues like light and temperature. In the present study, we report genome wide identification and characterization of circadian oscillator (CO) proteins in tea. We first mined the genes (24, in total) involved in circadian rhythm pathway in the 56 plant species having available genomic information and then built their hidden Markov models (HMMs). Using these HMMs, 24 proteins were identified in tea and were further assessed for their functional annotation. Expression analysis of all these 24 CO proteins was then performed in 3 abiotic (A) and 3 biotic conditions (B) stress conditions and co-expressed as well as differentially expressed genes in the selected 6 stress conditions were elaborated. A methodology to identify the differentially expressed genes in specific types of stresses (A or B) is proposed and novel markers among CO proteins are presented. By mapping the identified CO proteins against the recently reported genome wide interologous protein-protein interaction network of tea (TeaGPIN), an interaction sub-network of tea CO proteins (TeaCO-PIN) is developed and analysed. Out of 24 CO proteins, structures of 4 proteins could be successfully predicted and validated using consensus of three structure prediction algorithms and their stability was further assessed using molecular dynamic simulations at 100 ns. Phylogenetic analysis of these proteins is performed to examine their molecular evolution.