This PhD thesis work is fruit of a collaboration between the Department of Physics “Enrico Fermi” of the University of Pisa and the gsk Vaccines Center in Siena - GSK Vaccines, Siena. It falls within the context of bacterial population genomics, with a particular interest in applications to species able to cause severe diseases such as meningitis. In this context is inserted my PhD thesis work: in the necessity of evaluate and quantify variations among bacterial genomes belonging to the same species in order to analyse and reconstruct the population structure of that species. During my PhD I developed a pipeline that can measure polymorphisms mutation rates, on a whole genome level, for big datasets of genomes (up to 4000 genomes). On the basis of these rates it is possible to reconstruct phylogenetic trees of the species, to observe recombination event among strains and to perform studies of association between genomic features and phenotypical or epidemiological classifications.

Measuring genomic variations associated with bacterial population structure

BARUCCO, MARA
2017

Abstract

This PhD thesis work is fruit of a collaboration between the Department of Physics “Enrico Fermi” of the University of Pisa and the gsk Vaccines Center in Siena - GSK Vaccines, Siena. It falls within the context of bacterial population genomics, with a particular interest in applications to species able to cause severe diseases such as meningitis. In this context is inserted my PhD thesis work: in the necessity of evaluate and quantify variations among bacterial genomes belonging to the same species in order to analyse and reconstruct the population structure of that species. During my PhD I developed a pipeline that can measure polymorphisms mutation rates, on a whole genome level, for big datasets of genomes (up to 4000 genomes). On the basis of these rates it is possible to reconstruct phylogenetic trees of the species, to observe recombination event among strains and to perform studies of association between genomic features and phenotypical or epidemiological classifications.
4-mag-2017
Italiano
bacterial population
clustering methods
GBS
GWAS
meningo
NTHi
whole genome sequencing
Leporini, Dino
Muzzi, Alessandro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/150593
Il codice NBN di questa tesi è URN:NBN:IT:UNIPI-150593