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Doctoral thesis, 2014

Bioinformatic methods for metagenomics and comparative genetics in veterinary medicine

Norling, Martin

Abstract

Good science includes innovation, investigation, and rigor. This thesis’ first study is related to rigor. This study was performed at the International Livestock Research Institute (ILRI) in Nairobi, as part of the Arbovirus Incidence and Diversity (AVID) project. A field sample recording system was developed, which saves time and location metadata from the global positioning system (GPS), as well as a connected system monitoring the biobank, freezer, incubators and servers. This monitoring system more than once prevented loss of resources due to freezer failure by alerting responsible personnel, and was later published in 'Biopreservation and Biobanking'. The sampling system was re-used in the second study, a Ugandan project aimed to identify African swine fever (ASF) in pigs. In this study Ndumu virus, a relatively unstudied virus previously only found in culicine mosquitoes, was discovered in domestic pigs. For the third study, collaboration with ILRI continued with a study analyzing the 'Muguga Cocktail', the live vaccine currently used to control Theileria parva, a protozoan parasite causing East Coast Fever (ECF) in cattle. Live vaccines have many problems, such as high costs, difficult manufacturing, and the risk that misused vaccine will spread the disease. An in-depth study of the three parasite stocks included in the vaccine was performed, where genomic differences were identified with the goal of explaining the success of the vaccine, as well as identify a potential set of antigens which may in the future replace the live vaccine with a subunit vaccine. Finally, for the fourth study, the metagenomic theme continued with the development of the MetLab, a tool for experimental design and analysis for viral metagenomics projects. The tool consists of three parts: (i) tools to estimate the sequencing needs of a metagenomic project, (ii) simulation tools, allowing users to simulate metagenomics sequencing data, and (iii) the system runs metagenomic analysis pipelines.

Keywords

bioinformatics; metagenomics; virology; infection biology; next generation sequencing

Published in

Acta Universitatis Agriculturae Sueciae
2014, number: 2014:73
ISBN: 978-91-576-8094-5, eISBN: 978-91-576-8095-2
Publisher: Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences

Authors' information

Norling, Martin
Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics

UKÄ Subject classification

Bioinformatics and Systems Biology

URI (permanent link to this page)

https://res.slu.se/id/publ/61079