Disease Gene Identification Using High-Throughput Genomic Technologies
|dc.contributor.author||Tiffin, Heather Rachel|
|dc.identifier.citation||Tiffin, H. R. (2012). Disease Gene Identification Using High-Throughput Genomic Technologies (Thesis, Master of Science). University of Otago. Retrieved from http://hdl.handle.net/10523/2300||en|
|dc.description.abstract||Identification of the underlying genetic and molecular components that contribute to human disease can provide significant insight into the biological processes that underlie the development and regulation of affected tissues. This project successfully employed two alternative strategies for Mendelian disease gene identification. The first strategy utilised a combined genetic mapping and candidate gene approach for the identification of sequence variants contributing to a Noonan syndrome-like (NS-like) condition affecting males in a small New Zealand family. Affected family members exhibit short stature, characteristic facial dysmorphia, hypertrophic cardiomyopathy, pulmonary stenosis, thoracic scoliosis and pectus deformities consistent with NS, a disorder that is caused by aberrant RAS-MAPK pathway signalling. Affected individuals exhibit additional cardiac and musculoskeletal abnormalities that are inconsistent with the NS phenotype. The use of a candidate gene approach was based on the premise that a specific biochemical pathway is disrupted in the pathogenesis of NS and NS-related disorders, and the assumption that this is an X-linked disorder. This led to the identification of a novel complex indel mutation within the four and a half LIM domains 1 gene (FHL1) that results in a complete loss of exon 6, and differentially affects its three splice isoforms FHL1A, FHL1B and FHL1C. The muscular phenotype observed in this family can be accounted for by the loss of FHL1A and the production of a truncated FHL1B transcript. Preliminary experiments designed to assess activation of the RAS-MAPK pathway also indicate that this FHL1 alteration leads to an increase in MAPK signalling, potentially providing a link between the molecular lesion and the NS-like phenotype. The second strategy utilised a combined homozygosity mapping and exome sequencing approach for the identification of sequence variants contributing to a familial form of primary endocardial fibroelastosis (EFE). Affected family members exhibited symptoms characteristic of primary EFE, later confirmed by autopsy. Homozygosity mapping was used based on the assumption that there is unrecognised parental consanguinity and presumed ancestral inheritance of the same recessive allele contributing to the disease in this family. This defined a genomic candidate region within which the disease-causing variant could be sought. Whole exome sequencing was carried out for identification of the potentially pathogenic variant present within the pre-defined candidate interval. Application of a robust filtering strategy led to the identification of a single promising candidate gene, myosin light kinase 3 (MYLK3), for causation of familial primary EFE observed in this small New Zealand family. The variant identified in this gene fits the proposed single-gene autosomal recessive inheritance model and is predicted to hinder protein function. MYLK3 is expressed in the appropriate tissues at the appropriate developmental time period, and down regulation of its protein product, caMLCK, has been shown to cause a cardiac phenotype with similarities to the phenotype observed in individuals with primary EFE. This work extends the spectrum of FHL1-related disorders and potentially implicates FHL1 in the development of a NS-like phenotype, previously thought to be restricted to mutations in key components of the RAS-MAPK signalling pathway. This work also identifies the first promising candidate gene for causation of familial Primary EFE.|
|dc.publisher||University of Otago|
|dc.rights||All items in OUR Archive are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.|
|dc.title||Disease Gene Identification Using High-Throughput Genomic Technologies|
|thesis.degree.discipline||Women's and Children's Health|
|thesis.degree.name||Master of Science|
|thesis.degree.grantor||University of Otago|
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