Development of a Computational Framework for Integrating transcriptome and metagenome sequencing, annotation and pathway prediction to identify key stress and disease association networks in plants

Two most important and established techniques which utilises the Next Generation Sequencing Based methods for biological data generation are transcriptome and Metagenome sequencing. While the former provides insights into the exact transcriptome dynamics of a particular organism in a particular timeframe, the latter is used for the analyses of the microbial communities in a particular region in an either time or experimental condition specific manner. The basic steps following the sequencing run is more or less similar involving assembly, annotation, prediction of repetitive sequences and pathway analyses. However, the target reference databases and genomes differ and in case of transcriptome analyses, for organisms who do not have their complete genome sequenced as yet, de novo transcriptome analyses is performed for proper elucidation of the RNAome. However, if we consider the soil plant continuum concept, then an integration of these two techniques might enable us to properly understand the genetic responses of plants in context of the rhizospheric microorganisms, soil profiles and abiotic stress parameters such as salinity or heavy metal enrichment.

Prediction and Design of Antisense Oligonucleotides against tRNA derived fragments (tRFs) and small RNAs implicated in various diseases and development of a Antisense Oligonucleotide repository- ASObase

The relevance of the non-coding genome to human disease has mainly been studied in the context of the widespread disruption of microRNA (miRNA) expression and function that is seen in human cancer. However, we are only beginning to understand the nature and extent of the involvement of non-coding RNAs (ncRNAs) in disease. Other ncRNAs, such as PIWI-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), tRNA derived microRNAs and long non coding RNAs are emerging as key elements of cellular homeostasis. Along with microRNAs, dysregulation of these ncRNAs is being found to have relevance not only to tumorigenesis, but also to neurological, cardiovascular, developmental and other diseases. tRNAs are characterized by their evolutionarily conserved secondary and tertiary structures, extensive post-transcriptional processing and modifications (up to 100 nucleoside modifications have been described), extreme stability and resistance to nucleases. Moreover, the human genome contains more than 500 genes encoding over 40 different tRNAs. Identification of novel ncRNAs derived from tRNAs, known as tRNA-derived RNA fragments, has recently gained significant attention. Some of these fragments are derived from precursor tRNA molecules, others from mature cytoplasmic tRNAs. The list of possible functions of tRNA-derived fragments is growing. The recent discovery that the abundance of 5'-tRNA halves found in sperm and oocytes rapidly decreases upon fertilization suggests that this class of molecules can be physiologically regulated. Similarly, 5'-tRNA halves and 5'-tRFs are found in exosomes within semen. tRNAs and tRNA fragments has been reported as novel sources of piRNAs (PIWI-interacting RNAs) in both mouse gametes and zygotes as well as in human somatic cells. The functions of these tRNA-derived piRNAs are not known but may be connected to epigenetic inheritance, silencing of retrotransposons and other genetic elements or post-transcriptional regulation of mRNAs. Finally, tRNA fragments are also induced by viral infections such as by Respiratory Syncytial Virus (RSV).

Thus as we attempt to quantify the functions of these small molecules in diseases, it is imperative to devise plan of actions to regulate, control and suppress their activities, such that the onset of diseases can be prevented. This project aims to explore the efficacy of antisense oligonucleotides as a mechanism for controlling the function of these non coding small molecules. Both wet lab and computational techniques would be explored for mining, predicting and validating the interactions of the designed antisense oligonucleotides to their respective targets as well as identify the efficacy of these interactions through RNA sequencing.