Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (leaves 118-126).

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

published_or_final_version / Microbiology / Master / Master of Medical Sciences

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

A new generation of non-Sanger-based sequencing technologies, so called “next-generation” sequencing (NGS), has been changing the landscape of genetics at unprecedented speed. In particular, our capacity in deciphering the genotypes underlying phenotypes, such as diseases, has never been greater. However, before fully applying NGS in medical genetics, researchers have to bridge the widening gap between the generation of massively parallel sequencing output and the capacity to analyze the resulting data. In addition, even a list of candidate genes with potential causal variants can be obtained from an effective NGS analysis, to pinpoint disease genes from the long list remains a challenge. The issue becomes especially difficult when the molecular basis of the disease is not fully elucidated. New NGS users are always bewildered by a plethora of options in mapping, assembly, variant calling and filtering programs and may have no idea about how to compare these tools and choose the “right” ones. To get an overview of various bioinformatics attempts in mapping and assembly, a series of performance evaluation work was conducted by using both real and simulated NGS short reads. For NGS variant detection, the performances of two most widely used toolkits were assessed, namely, SAM tools and GATK. Based on the results of systematic evaluation, a NGS data processing and analysis pipeline was constructed. And this pipeline was proved a success with the identification of a mutation (a frameshift deletion on Hnrnpa1, p.Leu181Valfs*6) related to congenital heart defect (CHD) in procollagen type IIA deficient mice. In order to prioritize risk genes for diseases, especially those with limited prior knowledge, a network-based gene prioritization model was constructed. It consists of two parts: network analysis on known disease genes (seed-based network strategy)and network analysis on differential expression (DE-based network strategy). Case studies of various complex diseases/traits demonstrated that the DE-based network strategy can greatly outperform traditional gene expression analysis in predicting disease-causing genes. A series of simulation work indicated that the DE-based strategy is especially meaningful to diseases with limited prior knowledge, and the model’s performance can be further advanced by integrating with seed-based network strategy. Moreover, a successful application of the network-based gene prioritization model in influenza host genetic study further demonstrated the capacity of the model in identifying promising candidates and mining of new risk genes and pathways not biased toward our current knowledge. In conclusion, an efficient NGS analysis framework from the steps of quality control and variant detection, to those of result analysis and gene prioritization has been constructed for medical genetics. The novelty in this framework is an encouraging attempt to prioritize risk genes for not well-characterized diseases by network analysis on known disease genes and differential expression data. The successful applications in detecting genetic factors associated with CHD and influenza host resistance demonstrated the efficacy of this framework. And this may further stimulate more applications of high throughput genomic data in dissecting the genetic components of human disorders in the near future. / published_or_final_version / Biochemistry / Doctoral / Doctor of Philosophy

Thermonuclear (Type Ia) supernovae are excellent distance indicators, due to their uniform peak brightness. They are also important contributors to the chemical evolution of galaxies since their explosions supply large amounts of iron peak elements to the interstellar medium. However, there is no consensus on the progenitor systems of these supernovae. As a result, different delay times from the formation of the binary system to the supernova have been proposed. Whether the observed rate of supernova Type Ia in early-type galaxies supports a progenitor channel with one or two degenerate objects has been disputed. While the predominant old population found in early-type galaxies supports longer delay times, the presence of recent star formation might indicate the opposite. In this work, we employ a double-burst model to account for the relative contribution of both populations. We show that for a DTD ∝ t^−1, convolved with star formation histories that are relevant for early-type galaxies, the supernova rate is independent of a host galaxy’s colour. Our results indicate that a DTD with no cutoff is preferred, thus favoring the double-degenerate scenario. / Graduate

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

No description available.

Despite the known benefits of performing aerobic and resistance exercise independently, the metabolic effects of performing aerobic and resistance exercise in succession, remain unclear. Several studies suggest that the alteration of exercise sequence may influence carbohydrate and lipid oxidation and energy expenditure during exercise and in recovery. High intensity resistance exercise performed prior to a bout of aerobic exercise has been shown to augment fat oxidation during the subsequent bout of aerobic exercise. Changes in hormone and metabolite concentrations from prior resistance exercise could potentially influence substrate selection and energy expenditure in a subsequent bout of aerobic exercise. However, an exercise session whereby aerobic exercise is followed by a bout of resistance exercise has yet to be evaluated to determine the metabolic effects (specifically, the differences in substrate selection for energy provision) when exercise sequence is altered. It was hypothesized that when resistance exercise was performed prior to a bout of aerobic exercise, sympathetic nervous system activity would be elevated, leading to an increase in non-esterified fatty acid (NEFA) and glycerol concentrations and resultant increase in lipid oxidation during the aerobic portion of the exercise compared to the opposite sequence. It was also hypothesized that during recovery there would be an increased reliance on fat oxidation for energy provision with a resistance-aerobic exercise sequence compared to an aerobic-resistance exercise sequence. Additionally, the differences in metabolite concentrations and respiratory parameters between two identical bouts of aerobic exercise performed on separate days (~1 week apart) were measured and it was hypothesized that day-to-day variability would be non-significant (p>0.05). Plasma glucose, lactate, NEFA, glycerol, insulin, C-peptide, glucagon, epinephrine and norepinephrine concentrations in addition to oxygen consumption (VO2) and respiratory exchange ratio (RER) were measured in nine healthy, recreationally active males that participated in 3 different, randomized exercise trials (Trial A: aerobic exercise; Trial AR: aerobic exercise followed by a bout of resistance exercise; Trial RA: resistance exercise followed by an aerobic exercise bout). The aerobic exercise bout was performed at 60% VO2 max for 30 min while the resistance exercise bout consisted of 5 exercises (overhead squat, chest press, triceps extension, shoulder press, and dead-lift) performed for 3 sets of 8 repetitions at 70% 1-RM. Contrary to the primary hypothesis, NEFA concentrations and lipid oxidation rates were similar for the aerobic exercise bout of both the AR and RA trials. During recovery, lipid oxidation was elevated immediately post-exercise in the RA trial compared to the AR trial, however there were no differences between trials by 15 min post-exercise. Furthermore, only epinephrine, and not norepinephrine, concentrations were significantly higher after aerobic exercise in the RA trial compared to the AR trial. VO2 and energy expenditure values were similar for the duration of the 30 min recovery. These results suggest that while exercise sequence may influence carbohydrate and lipid oxidation immediately post exercise, substrate selection and utilization are similar during aerobic exercise bouts irrespective of the sequence in which aerobic and resistance exercise are performed. Thus, when resistance exercise is performed prior to aerobic exercise, compared to the opposite sequence, overall energy provision is not altered at the volume and intensity of exercise performed in this study.