Mitochondria are indispensable organelles of eukaryotic cells, takes part in the
efficient generation of energy required for the cellular activities. They also converge
to accomplish various functions such as intrinsic apoptotic pathway, fatty acid beta
oxidation, cellular balance of reactive oxygen species (ROS), iron sulphur cluster
biogenesis and so-forth which are necessary for the viability of the cell.
Ominous diseases may arise of incompetent mitochondrial function activity, for
example, cardiomyopathy, optic atrophy and diabetes mellitus. Mitochondrial
disorders may emerge as a result of mutations not only in the mitochondria DNA
(mtDNA) but also in the nuclear DNA (nDNA) encoding proteins, which forms part
of the mitochondrial proteome.
The advent of next generation sequencing (NGS) data has hugely accelerated the
generation of millions of DNA sequences and opened up avenues to study diseases
at a rapid pace. NGS enables transcriptome sequencing of both the normal and the
disease samples realised by the RNA sequencing (RNA-seq) technology. This
facilitate the measure of the gene expression in the diseases compared to their
normal samples, in addition to the capture of disease specific mutations. In this
thesis, workflows to extract mutation and expression data from the RNAseq samples
using well developed bioinformatics tools have been achieved.
Mitochondria encompassing crucial cellular functions are fulfilled by protein coding
genes encoded by both mtDNA and nDNA. In this thesis, an overall model termed as
mitochondrial model (MitoModel) is developed, which at present includes 17
mitochondria specific processes with 659 genes further grouped into functional
clusters. The MitoModel forms a network model with genes connected not only
within a single function but also across functions. It is an interactive model with an option to map mutation and expression data and further the MitoModel provide
users several information including enrichment analysis of most affected
mitochondrial function and a downloadable variants file.
The usage of MitoModel has proved the efficiency of the approach to understand the
behaviour of the mitochondria from the RNA-seq data in HCT116 5/4, RPE1 5/3
12/3 and RPE1H2B 21/3 aneuploidy cell lines generated by collaborators. It also
throws light on the differences in the mitochondrial metabolism and physiology in
the extreme stress reactivity mice from the expression data. Finally, MitoModel was
successfully used to emphasize on the representative mitochondrial genes that were
consistently affected in the RNA-seq data of 16 samples of primary colorectal cancer
and corresponding liver metastases samples