Genetic Heterogeneity in Autism Spectrum Disorders in a Population Isolate

Positional cloning has enabled hypothesis-free, genome-wide scans for genetic factors contributing to disorders or traits. Traditionally linkage analysis has been used to identify regions of interest, followed by meticulous fine mapping and candidate gene screening using association methods and finally sequencing of regions of interest. More recently, genome-wide association analysis has enabled a more direct approach to identify specific genetic variants explaining a part of the variance of the phenotype of interest. Autism spectrum disorders (ASDs) are a group of childhood onset neuropsychiatric disorders with shared core symptoms but varying severity. Although a strong genetic component has been established in ASDs, genetic susceptibility factors have largely eluded characterization. Here, we have utilized modern molecular genetic methods combined with the advantages provided by the special population structure in Finland to identify genetic risk factors for ASDs. The results of this study show that numerous genetic risk factors exist for ASDs even within a population isolate. Stratification based on clinical phenotype resulted in encouraging results, as previously identified linkage to 3p14-p24 was replicated in an independent family set of families with Asperger syndrome, but no other ASDs. Fine-mapping of the previously identified linkage peak for ASDs at 3q25-q27 revealed association between autism and a subunit of the 5-hydroxytryptamine receptor 3C (HTR3C). We also used dense, genome-wide single nucleotide polymorphism (SNP) data to characterize the population structure of Finns. We observed significant population substructure which correlates with the known history of multiple consecutive bottle-necks experienced by the Finnish population. We used this information to ascertain a genetically homogenous subset of autism families to identify possible rare, enriched risk variants using genome-wide SNP data. No rare enriched genetic risk factors were identified in this dataset, although a subset of families could be genealogically linked to form two extended pedigrees. The lack of founder mutations in this isolated population suggests that the majority of genetic risk factors are rare, de novo mutations unique to individual nuclear families. The results of this study are consistent with others in the field. The underlying genetic architecture for this group of disorders appears highly heterogeneous, with common variants accounting for only a subset of genetic risk. The majority of identified risk factors have turned out to be exceedingly rare, and only explain a subset of the genetic risk in the general population in spite of their high penetrance within individual families. The results of this study, together with other results obtained in this field, indicate that family specific linkage, homozygosity mapping and resequencing efforts are needed to identify these rare genetic risk factors.

Optimization of sample preparation for next-generation sequencing with Illumina Genome Analyzer II

The growing interest for sequencing with higher throughput in the last decade has led to the development of new sequencing applications. This thesis concentrates on optimizing DNA library preparation for Illumina Genome Analyzer II sequencer. The library preparation steps that were optimized include fragmentation, PCR purification and quantification. DNA fragmentation was performed with focused sonication in different concentrations and durations. Two column based PCR purification method, gel matrix method and magnetic bead based method were compared. Quantitative PCR and gel electrophoresis in a chip were compared for DNA quantification. The magnetic bead purification was found to be the most efficient and flexible purification method. The fragmentation protocol was changed to produce longer fragments to be compatible with longer sequencing reads. Quantitative PCR correlates better with the cluster number and should thus be considered to be the default quantification method for sequencing. As a result of this study more data have been acquired from sequencing with lower costs and troubleshooting has become easier as qualification steps have been added to the protocol. New sequencing instruments and applications will create a demand for further optimizations in future.