Genome Assembly and Computational Analysis Pipelines for Bacterial Pathogens

  • Farania Rangkuti

Student thesis: Master's Thesis

Abstract

Pathogens lie behind the deadliest pandemics in history. To date, AIDS pandemic has resulted in more than 25 million fatal cases, while tuberculosis and malaria annually claim more than 2 million lives. Comparative genomic analyses are needed to gain insights into the molecular mechanisms of pathogens, but the abundance of biological data dictates that such studies cannot be performed without the assistance of computational approaches. This explains the significant need for computational pipelines for genome assembly and analyses. The aim of this research is to develop such pipelines. This work utilizes various bioinformatics approaches to analyze the high-­throughput genomic sequence data that has been obtained from several strains of bacterial pathogens. A pipeline has been compiled for quality control for sequencing and assembly, and several protocols have been developed to detect contaminations. Visualization has been generated of genomic data in various formats, in addition to alignment, homology detection and sequence variant detection. We have also implemented a metaheuristic algorithm that significantly improves bacterial genome assemblies compared to other known methods. Experiments on Mycobacterium tuberculosis H37Rv data showed that our method resulted in improvement of N50 value of up to 9697% while consistently maintaining high accuracy, covering around 98% of the published reference genome. Other improvement efforts were also implemented, consisting of iterative local assemblies and iterative correction of contiguated bases. Our result expedites the genomic analysis of virulent genes up to single base pair resolution. It is also applicable to virtually every pathogenic microorganism, propelling further research in the control of and protection from pathogen-­associated diseases.
Date of AwardJun 2011
Original languageEnglish
Awarding Institution
  • Computer, Electrical and Mathematical Science and Engineering
SupervisorArnab Pain (Supervisor)

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