STATISTICAL METHODS FOR RARE AND COMMON VARIANT ASSOCIATION STUDIES

Complex human diseases are a major challenge for biological research. The goal of my research is to develop effective methods for biostatistics in order to create more opportunities for the prevention and cure of human diseases. This dissertation proposes statistical technologies that have the ability of being adapted to sequencing data in family-based designs, and that account for joint effects as well as gene-gene and gene-environment interactions in the GWA studies. The framework includes statistical methods for rare and common variant association studies. Although next-generation DNA sequencing technologies have made rare variant association studies feasible, the development of powerful statistical methods for rare variant association studies is still underway. Chapter 2 demonstrates two adaptive weighting methods for rare variant association studies based on family data for quantitative traits. The results show that both proposed methods are robust to population stratification, robust to the direction and magnitude of the effects of causal variants, and more powerful than the methods using weights suggested by Madsen and Browning [2009]. In Chapter 3, I extended the previously proposed test for Testing the effect of an Optimally Weighted combination of variants (TOW) [Sha et al., 2012] for unrelated individuals to TOW &ndash F, TOW for Family &ndash based design. Simulation results show that TOW &ndash F can control for population stratification in wide range of population structures including spatially structured populations, is robust to the directions of effect of causal variants, and is relatively robust to percentage of neutral variants. In GWA studies, this dissertation consists of a two &ndash locus joint effect analysis and a two-stage approach accounting for gene &ndash gene and gene &ndash environment interaction. Chapter 4 proposes a novel two &ndash stage approach, which is promising to identify joint effects, especially for monotonic models. The proposed approach outperforms a single &ndash marker method and a regular two &ndash stage analysis based on the two &ndash locus genotypic test. In Chapter 5, I proposed a gene &ndash based two &ndash stage approach to identify gene &ndash gene and gene &ndash environment interactions in GWA studies which can include rare variants. The two &ndash stage approach is applied to the GAW 17 dataset to identify the interaction between KDR gene and smoking status.

Wind plant interaction with series-compensated power systems

Wind power based generation has been rapidly growing world-wide during the recent past. In order to transmit large amounts of wind power over long distances, system planners may often add series compensation to existing transmission lines owing to several benefits such as improved steady-state power transfer limit, improved transient stability, and efficient utilization of transmission infrastructure. Application of series capacitors has posed resonant interaction concerns such as through subsynchronous resonance (SSR) with conventional turbine-generators. Wind turbine-generators may also be susceptible to such resonant interactions. However, not much information is available in literature and even engineering standards are yet to address these issues. The motivation problem for this research is based on an actual system switching event that resulted in undamped oscillations in a 345-kV series-compensated, typical ring-bus power system configuration. Based on time-domain ATP (Alternative Transients Program) modeling, simulations and analysis of system event records, the occurrence of subsynchronous interactions within the existing 345-kV series-compensated power system has been investigated. Effects of various small-signal and large-signal power system disturbances with both identical and non-identical wind turbine parameters (such as with a statistical-spread) has been evaluated. Effect of parameter variations on subsynchronous oscillations has been quantified using 3D-DFT plots and the oscillations have been identified as due to electrical self-excitation effects, rather than torsional interaction. Further, the generator no-load reactance and the rotor-side converter inner-loop controller gains have been identified as bearing maximum sensitivity to either damping or exacerbating the self-excited oscillations. A higher-order spectral analysis method based on modified Prony estimation has been successfully applied to the field records identifying dominant 9.79 Hz subsynchronous oscillations. Recommendations have been made for exploring countermeasures.

Isolation of plant growth promoting bacteria from torch lake sediments and their role in phytoremediation of metal contaminated soil

In this study, we isolated eight copper-resistant bacteria from Torch Lake sediment contaminated by copper mine tailings (stamp sand). Sequence analysis of gyrB and rpoD genes revealed that these organisms are closer to various Pseudomonas species. These eight bacterial isolates were also resistant to zinc, cesium, lead, arsenate and mercury. Further characterization showed that all the strains produced plant growth promoting indole-3-acetic acid (IAA), iron chelating siderophore and solubilized mineral phosphate and metals. The effect of bacterial inoculation on plant growth and copper uptake by maize (Zea mays) and sunflower (Helianthus annuus) was investigated using one of the isolates (Pseudomonas sp. TLC 6-6.5-4) with higher IAA production and phosphate and metal soubilization, which resulted in a significant increase in copper accumulation in maize and sunflower, and an increase in the total biomass of maize. Genes involved in copper resistance of Pseudomonas sp. TLC 6-6.5-4 was analyzed by transposon mutational analysis. Two copper sensitive mutants with significant reduction in copper resistance were identified: CSM1, a mutant disrupted in trp A gene (tryptophan synthase alpha subunit); CSM2, a mutant disrupted in clpA gene (ATP-dependent Clp protease). Proteomic and metabolomic analysis were performed to identify biochemical and molecular mechanisms involved in copper resistance using CSM2 due to its lower minimum inhibitory concentration compared with CSM1 and the wild type. The effect of different bacterial inoculation methods on plant growth, copper uptake and soil enzyme activities was investigated. Four different delivery methods were used including soil inoculation (before or after plant emergence), seed coating and root dipping. Soil inoculation before sowing seeds and coating seeds with PGPB led to better growth of maize, higher copper uptake and an increase in soil invertase and dehydrogenase activities. Proteomic and metabolomic analyses were performed to investigate the effect of bacterial inoculation on maize grown in normal soil and stamp sand. Our results revealed that bacterial inoculation led to environment-dependent effects on maize proteome and metabolome.