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theses

Lysosomes are membrane-bound, acidic eukaryotic cellular organelles. As an enzyme container, they play important roles in the degradation of macromolecules. Monogenic mutations resulting in the loss of enzyme activities in the lysosome may lead to severe health problems, such as neurodegeneration and early death. These conditions are categorized as Lysosomal Storage Diseases (LSDs). The diagnosis of LSDs is typically straightforward. However, in some cases the underlying genetic defects remain unknown. Here, we performed whole exome sequencing on 14 suspected LSD cases, with the goal of finding the causal mutations. From the raw sequence data, we first identified DNA variants in each individual using three variant discovery pipelines: the Genome Analysis Toolkit, LifeScopeTM Genomic Analysis Software and CLC Genomics Workbench. For each variant calling dataset, we then used the Variant Annotation Analysis Search Tool (VAAST) to prioritize disease- causing mutations in 848 candidate LSD genes. As a probabilistic disease gene finder, VAAST integrates allele frequency, amino acid substitution severity and conservation information into a composite likelihood framework. Different from hard filtering ii methods, VAAST preserves all the candidates by listing them according to their disease-causing potential. To obtain the detailed information of each mutation and add one more layer of mutational prediction, we performed SIFT analysis for each dataset. Afterward, tier study was conducted to accommodate the discrepancies between different pipelines and further reprioritize the candidate variants. Finally, based on the mutational validation and functional analysis, we identified nine mutations in six genes to be candidate LSDs causal variants in five individuals, including both known and novel mutations. In summary, our project utilized various bioinformatics analyses tools to decode the extensive exome sequencing data and identify candidate variants for downstream functional studies. The study results provide valuable insights into the genetic basis of LSDs.

ETD_5906

M.S.

Includes bibliographical references

by Nan Wang

doi:10.7282/T3765GZK

ETD graduate

The author owns the copyright to this work.