Markov Random Fields in Cancer Mutation Dependencies

Even though a large amount of evidence would suggest that PP2A serine/threonine protein phosphatase acts as a tumour suppressor the genomics data to support this claim is limited. We fit a sparse binary Markov random field with individual sample's total mutational frequency as an additional covariate to model the dependencies between the mutations occurring in the PP2A encoding genes. We utilize the data from recent large scale cancer genomics studies, where the whole genome from a human tumour biopsy has been analysed. Our results show a complex network of interactions between the occurrence of mutations in our twenty examined genes. According to our analysis the mutations occurring in the genes PPP2R1A, PPP2R3A, and PPP2R2B are identified as the key mutations. These genes form the core of the network of conditional dependency between the mutations in the investigated twenty genes. Additionally, we note that the mutations occurring in PPP2R4 seem to be more influential in samples with higher number of total mutations. The mutations occurring in the set of genes suggested by our results has been shown to contribute to the transformation of human cells. We conclude that our evidence further supports the claim that PP2A acts as a tumour suppressor and restoring PP2A activity is an appealing therapeutic strategy.

Annotation of Gyrodactylus salaris transcriptome

Relationship between organisms within an ecosystem is one of the main focuses in the study of ecology and evolution. For instance, host-parasite interactions have long been under close interest of ecology, evolutionary biology and conservation science, due to great variety of strategies and interaction outcomes. The monogenean ecto-parasites consist of a significant portion of flatworms. Gyrodactylus salaris is a monogenean freshwater ecto-parasite of Atlantic salmon (Salmo salar) whose damage can make fish to be prone to further bacterial and fungal infections. G. salaris is the only one parasite whose genome has been studied so far. The RNA-seq data analyzed in this thesis has already been annotated by using LAST. The RNA-seq data was obtained from Illumina sequencing i.e. yielded reads were assembled into 15777 transcripts. Last resulted in annotation of 46% transcripts and remaining were left unknown. This thesis work was started with whole data and annotation process was continued by the use of PANNZER, CDD and InterProScan. This annotation resulted in 56% successfully annotated sequences having parasite specific proteins identified. This thesis represents the first of Monogenean transcriptomic information which gives an important source for further research on this specie. Additionally, comparison of annotation methods interestingly revealed that description and domain based methods perform better than simple similarity search methods. Therefore it is more likely to suggest the use of these tools and databases for functional annotation. These results also emphasize the need for use of multiple methods and databases. It also highlights the need of more genomic information related to G. salaris.