Next-generation sequencing and genome analysis in dimorphic fungi and human: using genomic variation to recognize and understand disease

The work of this thesis has a common focus on bioinformatics, comparative genomics of fungal genomes and clinical genomics of human chronic disease. We primarily focused on using genomic data of dimorphic fungal pathogens in order to obtain a better perspective and understanding of how commonly used assembly, annotation and genomic comparison bioinformatics programs dealt with genomic data. Our group re-sequenced the reference strains that had been used for the existing assemblies and annotations of Paracoccidioides spp., and used the new, higher quality reads to substantially improve the reference assemblies and annotations of these pathogenic fungi. We also sequenced de novo the species Emmonsia crescens and E. parva, which are closely related to the causal agent of blastomycosis, Blastomyces dermatitidis, but non-pathogenic or with low virulence. We performed comparative analyses of gene content and structure between various strains of B. dermatitidis, E. crescens and E. parva. Using available sequences, we then designed and analytically validated two primer pairs from regions that are unique to Histoplasma capsulatum but present across diverse strains of this species, and can therefore be utilized to detect the presence of H. capsulatum. Using the same approach, we also designed and analytically validated three primer pairs of high confidence for the amplification of sequence fragments that are unique to the genus Paracoccidioides. We designed and implemented an algorithm that takes any given sequence(s) and splits the sequence into fragments in order to query the unique percentage of the fragment against a group of sequences that are closely related to the query as well as outgroups that may be relevant in clinical settings, including human. we genotyped 67 selected SNPs within the 9p21.3 locus of the human genome, motivated by its proven association with cardiovascular disease, for a Colombian cohort of 357 healthy individuals with data collected for detailed hemodynamic and other phenotypic traits. We also sequenced the exome of a patient with familiar hypercholesterolemia.

• Fecha de publicación: 2017
• Institución: Universidad del Rosario
• Repositorio: Repositorio EdocUR - U. Rosario
• Idioma: spa
• OAI Identifier: oai:repository.urosario.edu.co:10336/13803
• Acceso en línea: https://doi.org/10.48713/10336_13803; http://repository.urosario.edu.co/handle/10336/13803
• Palabra clave: Genomics; Bioinformatics; Enfermedades; Biología Computacional; Genoma fúngico; Genoma viral; Enfermedad crónica; Genomics; Bioinformatics
• License: Abierto (Texto Completo)