The eastern subterranean termite, Reticulitermes flavipes, is the most widely dispersed termite in North America. The genus Reticulitermes spp. is responsible for 80% of total termite damage caused to urban structures each year. Little is known about the genetic structure of termites, particularly at the colony level. Evidence for what genetically defines a termite colony is a hotly debated topic in current literature due to the implications such findings would have regarding current lawsuits against pest control operations. Information on termite genetic structure is sparse. In this study, the genetic variation and gene flow among Texas populations of R. flavipes at the statewide level and city level was examined. A 324-337 base pairs segment of the mtDNA, AT-rich region was a polymerase chain reaction amplified from 104 different termite specimens from 12 Texas cities. The DNA extracts were then subjected to PCR amplification using specific primers and it was then sequenced. Using the sequence data and appropriate statistical measures it was found that, at the statewide level, nucleotide and haplotypic diversity is low. Gene flow was found to be low on a statewide basis. At the city level nucleotide and haplotypic diversity was high. The findings of this study provide insights into termite genetic structure.

Thesis (Ph. D.) -- Lincoln University, 2009. / Also available via the World Wide Web.

With the completion of human genome sequencing project and the rapid development of sequencing technologies, our capacity in tackling with genetic and genomic changes that underlie human diseases has never been greater. The recent successes in identifying disease causal single nucleotide variations (SNVs) for Mendelian disorders using whole exome sequencing may bring us one step further to understand the pathogenesis of Mendelian diseases. However, many hurdles need to be overcome before the promises can become widespread reality. In this study, we investigated various strategies and designed a toolkit named PriSNV for SNV identification and prioritization, respectively. The SNV identification pipeline including read alignment, PCR duplication removal, indel realignment, base quality score recalibration, SNV and genotype calling was examined by simulation and real sequencing data. By incorporating sequencing errors and small indels, most of the read alignment software can achieve satisfied results. Nonetheless, the reads with medium size and large indels are prone to be wrongly mapped to the reference genome due to the limitation of gap opening strategies of available read alignment software. In addition, although mapping quality can only reflect certain information of the mapping error rate, it is still important to be adopted to filter out obvious read alignment errors. The PCR duplication removal, indel realignment and base quality score recalibration have proven to be necessary and can substantially reduce the false positive SNV calls. Based on the same quality criterion, Varscan performs as the most sensitive software for SNV calling, unfortunately at mean time the false positive calls are enriched in its result. In order to prioritize the small subset of functionally important variants from tens of thousands of variants in whole human exome, we developed a toolkit called PriSNV, a systematic prioritization pipeline that makes use of information on variant quality, gene candidacy based on the number of novel nonsynonymous mutations in a gene, gene functional annotation, known involvement in the disease or relevant pathways, and location in linkage regions. Prediction of functional impact of the coding variants is also used to aid the search for causal mutations in Mendelian disorders. For the patient affected by Chron's disease, the candidate genes can be substantially reduced from 9615 to 3 by the gene selection strategies implemented in PriSNV. In general, our results for SNV identification can help the biologists to realize the limitation of available software and shed light on the development of new strategies for accurately identifying SNV calls in the future. PriSNV, the software we developed for SNV prioritization, can provide significant help to biologists in prioritizing SNV calls in a systematic way and reducing search space for further analysis and experimental verification. / published_or_final_version / Paediatrics and Adolescent Medicine / Master / Master of Philosophy

Recent founder mutations may play important roles in complex diseases and Mendelian disorders. Detecting shared haplotypes of identity by descent (IBD) could facilitate discovery of these mutations. Several programs address this such as threshold-based methods on genetic distance and probabilistic model-based methods, but they are usually limited to only detecting pair-wise shared haplotypes and not providing a comparison between cases and controls. In this study, a novel algorithm and a applied software package (HaploShare)is developed to detect extended haplotypes that are shared by multiple individuals, which also allows comparisons between cases and controls. A catalog of haplotypes is firstly generated from healthy controls from the same population and used for phasing genotypes in cases. By accounting for all possible haplotype pairs that could explain the genotypes for each individual in a given haplotype block and possible transitions between blocks, the effect of phase uncertainty on detection power is minimized. In cases, haplotypes shared by pairs are identified and used to detect sharing of these haplotypes by different pairs. A likelihood ratio of a shared haplotype due to IBD or chance is estimated for each extended haplotype. Controls are used similarly through many rounds of simulations to obtain an empirical null distribution of the largest likelihood ratios of shared haplotypes, to give statistical estimates of shared haplotypes detected in cases that may be associated with an underlying disease. Series of tests were performed to investigate the performance of HaploShare. Simulations of shared haplotypes demonstrated that HaploShare has better power not only on the detection of pair-wise shared haplotypes but multiple shared haplotypes in most of the simulation scenarios, comparing with other four commonly used programs. False positive rate (FPR) and the false discovery rate (FDR) were also evaluated by statistical calculation. According to the result, both of the two values were extremely low (FPR = 6.28x10-6 , FDR = 0.006), indicating that very few randomly shared haplotypes can be wrongly reported as IBD by HaploShare. HaploShare was also tested on real cases on population data and family linkage analysis. 14 out of 173 Hirschsprung's disease cases were reported by HaploShare of carrying a common haplotype of 250 kb in length, which was consistent with previous findings by direct genotyping and candidate approach. Another testing case is an affected family with 8 cases and 9 unaffected individuals. Disease linked region can be correctly identified by traditional methods if all the data and the entire pedigree were provided. HaploShare showed the ability to locate the shared region even when very limited cases are available, which is clearly beyond the detection power of traditional methods. The results from empirical simulations and real case applications indicate that HaploShare could effectively make use of population genotype information to improve the power of detection of shared haplotypes. The method may extend the findings in human genetics of both complex and single gene diseases. / published_or_final_version / Psychiatry / Doctoral / Doctor of Philosophy

No description available.

No description available.

Thesis (PhD)--University of South Australia, 1995

Thesis (doctoral)--Universität, Jena, 2006. / Includes bibliographical references (p. 287-295).

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Diss. (sammanfattning) Stockholm : Karol. inst. / Härtill 7 uppssatser.