<p>In this work, I present four studies across the range of 'omics data types - a Genome- Wide Association Study for gene-by-sex interaction of obesity traits, computational models for transcription start site classification, an assessment of reference-based mapping methods for RNA-Seq data from non-model organisms, and a statistical model for open-platform proteomics data alignment.</p><p>Obesity is an increasingly prevalent and severe health concern with a substantial heritable component, and marked sex differences. We sought to determine if the effect of genetic variants also differed by sex by performing a genome-wide association study modeling the effect of genotype-by-sex interaction on obesity phenotypes. Genotype data from individuals in the Framingham Heart Study Offspring cohort were analyzed across five exams. Although no variants showed genome-wide significant gene-by-sex interaction in any individual exam, four polymorphisms displayed a consistent BMI association (P-values .00186 to .00010) across all five exams. These variants were clustered downstream of LYPLAL1, which encodes a lipase/esterase expressed in adipose tissue, a locus previously identified as having sex-specific effects on central obesity. Primary effects in males were in the opposite direction as females and were replicated in Framingham Generation 3. Our data support a sex-influenced association between genetic variation at the LYPLAL1 locus and obesity-related traits.</p><p>The application of deep sequencing to map 5' capped transcripts has confirmed the existence of at least two distinct promoter classes in metazoans: focused promot- ers with transcription start sites (TSSs) that occur in a narrowly defined genomic span and dispersed promoters with TSSs that are spread over a larger window. Pre- vious studies have explored the presence of genomic features, such as CpG islands and sequence motifs, in these promoter classes, and our collaborators recently inves- tigated the relationship with chromatin features. It was found that promoter classes are significantly differentiated by nucleosome organization and chromatin structure. Here, we present computational models supporting the stronger contribution of chro- matin features to the definition of dispersed promoters compared to focused start sites. Specifically, dispersed promoters display enrichment for well-positioned nucleosomes downstream of the TSS and a more clearly defined nucleosome free region upstream, while focused promoters have a less organized nucleosome structure, yet higher presence of RNA polymerase II. These differences extend to histone vari- ants (H2A.Z) and marks (H3K4 methylation), as well as insulator binding (such as CTCF), independent of the expression levels of affected genes.</p><p>The application of next-generation sequencing technology to gene expression quantification analysis, namely, RNA-Sequencing, has transformed the way in which gene expression studies are conducted and analyzed. These advances are of partic- ular interest to researchers studying non-model organisms, as the need for knowl- edge of sequence information is overcome. De novo assembly methods have gained widespread acceptance in the RNA-Seq community for non-model organisms with no true reference genome or transcriptome. While such methods have tremendous utility, computational complexity is still a significant challenge for organisms with large and complex genomes. Here we present a comparison of four reference-based mapping methods for non-human primate data. We explore mapping efficacy, correlation between computed expression values, and utility for differential expression analyses. We show that reference-based mapping methods indeed have utility in RNA-Seq analysis of mammalian data with no true reference, and that the details of mapping methods should be carefully considered when doing so. We find that shorter seed sequences, allowance of mismatches, and allowance of gapped alignments, in addition to splice junction gaps result in more sensitive alignments of non-human primate RNA-Seq data.</p><p>Open-platform proteomics experiments seek to quantify and identify the proteins present in biological samples. Much like differential gene expression analyses, it is often of interest to determine how protein abundance differs in various physiological conditions. Label free LC-MS/MS enables the rapid measurement of thousands of proteins, providing a wealth of peptide intensity information for differential analysis. However, the processing of raw proteomics data poses significant challenges that must be overcome prior to analysis. We specifically address the matching of peptide measurements across samples - an essential pre-processing step in every proteomics experiment. Presented here is a novel method for open-platform proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion data. Our results suggest that the inclusion of additional data results in higher numbers of more confident matches, without increasing the number of mismatches. We also show that the incorporation of product ion data can improve results dramatically. Based on these results, we argue that the incorporation of ion mobility drift times and product ion information are worthy pursuits. In addition, alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods. The addition of drift times and/or high energy to alignment methods and accurate mass and time (AMT) tag databases can greatly improve experimenters ability to identify measured peptides, reducing analysis costs and potentially the need to run additional experiments.</p> / Dissertation

Volvo Group’s cab plant in Umeå produces cab bodies and consists of three operating areas; the Stamping and parts production, the Body in White and the Paint shop. Today the plant produces around XXX cabs/week, but the goal is to reach the invested capacity of XXX cabs/week. In order to increase the production capacity, the efficiency of both the manual and the automated processes need to be improved. Unlike the manual processes in where the capacity can be increased by enlarged workforce, the automated processes need to be optimized. Today the cabs are produced in the same order as the orders are received. The cab plant wants to investigate if the capacity of the automated segment in the Body in White unit can be increased by changing the order in the production sequence. This culminates in the following problem definition:  Is there untapped potential of the Body in White that can be achieved by an optimization of the production sequence? If so, how can Volvo Group’s cab plant in Umeå utilize this knowledge in the production planning process? The objective of the project was achieved by combining discrete event simulation with a heuristic optimization approach. The results shows that long batches in the production sequence limit the throughput of the system. By spreading the unfavorable subsequences of batches evenly over the production sequence, the total throughput of the Body in White can be increased by 52 cabs/week. / Volvokoncernens hyttfabrik i Umeå producerar förarhytter och är uppdelad i tre driftsområden; pressning och detaljtillverkning, hyttsammansättning och ytbehandling. Idag producerar fabriken ca XXX hytter/vecka, men möjlighet finns att nå upp till den investerade kapaciteten på XXX hytter/vecka. För att kunna öka produktionskapaciteten behöver både de manuella och de automatiserade processerna effektiviseras. Till skillnad från de manuella processerna, där kapaciteten kan ökas genom att öka antalet operatörer, behöver de automatiserade processerna optimeras. Idag produceras hytterna i samma ordning som beställningarna kommer in. Hyttfabriken vill undersöka om det finns en möjlighet att öka kapaciteten för den automatiserade processen i Body in White genom att optimera produktionssekvensen. Detta leder fram till följande problemformulering: Finns det outnyttjad potential i Body in White som kan uppnås genom att optimera produktionssekvensen? Hur kan Volvokoncernens hyttfabrik i Umeå utnyttja denna kunskap vid planering av produktionen? Målet med projektet har uppnåtts genom att kombinera diskret händelsesimulering med optimering genom heuristiker. Resultatet visar att stora batcher av samma variant i produktionen begränsar genomströmningen i processen. Genom att bland annat sprida ut de ogynnsamma delsekvenserna jämnt över produktionssekvensen kan den totala genomströmningen i Body in White ökas med 52 hytter/vecka.

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Primary hyperparathyroidism (pHPT) is a pathology associated with one or multiple hyperfunctioning parathyroid glands.  The disease prevalence occurs in roughly 1-2% of the population primarily post-menopausal women.  The molecular pathology of the disease is poorly understood.  Elevated serum calcium levels in the setting of an inappropriately elevated parathyroid hormone level are indicative of the disease process.  The ultimate treatment of the disease is to remove the hyperfunctioning gland. The aim of this thesis was to examine potential genetic and epigenetic aberrations that are potentially disease causing. The methylation signature of normal and pathological parathyroid tissue has yet to be investigated.  DNA was bisulphite modified and analyzed using the Infinium HumanMethylation27 BeadChip. Distinct hierarchical clustering of genes with altered DNA methylation profiles in normal and pathologic parathyroid tissue was evident.  DNA hypermethylation of CDKN2B, CDKN2A, WT1, SFRP1, SFRP2, and SFRP4 known to be important in the development of parathyroid tumors were associated with reduced gene expression in both benign and malignant parathyroid tumors. Familial primary hyperparathyroidism (FPHPT) may occur due to an underlying germ-line mutation in the MEN1, CASR, or HRPT2/CDC73 genes.  Eighty-six young (≤45 years of age) patients with clinically non-syndromic PHPT underwent genetic analysis.  Eight of 86 (9.3%) young patients with clinically non-familial PHPT displayed deleterious germ-line mutations in the susceptibility genes (4 MEN1, 3 CASR, and 1 HRPT2/ CDC73). Accumulation of non-phosphorylated active β -catenin has been reported to commonly occur in parathyroid adenomas from patients with primary hyperparathyroidism (pHPT).  We assessed possible β-catenin stabilizing mutations in a large series of parathyroid adenomas. A total of one hundred and eighty sporadic parathyroid adenomas were examined for mutations in exon 3 of the CTNNB1gene. The mutation S33C (TCT &gt;TGT) was detected by direct-DNA sequencing of PCR fragments in 1 out of 180 sporadic parathyroid adenomas (0.68 %). Eight matched tumor-constitutional DNA pairs from patients with sporadic parathyroid adenomas underwent whole-exome capture and high-throughput sequencing.  Four of eight tumors displayed a frame shift deletion or nonsense mutations within the MEN1 gene, which was accompanied by loss of heterozygosity of the remaining wild-type allele.  One tumor harbored a Y641N mutation of the histone methyltransferase EZH2 gene, previously linked to myeloid and lymphoid malignancy formation. Targeted sequencing in the additional 185 parathyroid adenomas revealed a high rate of MEN1 mutations (35%).

Brassica napus (L.) contributes over $19 billion dollars each year to the Canadian economy. However, yields are constantly threatened by Sclerotinia sclerotiorum (Lib) de Bary, the fungus responsible for Sclerotinia stem rot. To date, there are no global RNA profiling data or gene regulatory analyses of plant tissues directly at the main site of foliar infection in the B. napus-S. sclerotiorum pathosystem. Using RNA sequencing and a gene regulatory analysis, I discovered putative transcriptional regulators of biological processes associated with the tolerant phenotype of B. napus cv. Zhougyou821 including subcellular localization of proteins, pathogen detection, and redox homeostasis. Functional characterization of Arabidopsis mutants identified a number of genes that contribute directly to plant defense to S. sclerotiorum. Together this research amounts to the expansion of our understanding of the B. napus-S. sclerotiorum pathosystem and a valuable resource to help protect B. napus crops from virulent pathogens such as S. sclerotiorum. / October 2016

Bioinformatics is a unique field in that it incorporates many different disciplines, including biology, computer science, and statistics, to study biological data. There is a vast array of techniques that utilize bioinformatics, including pangenomics, RNASeq, whole genome metagenomics, and 16S sequencing. To study bacterial interactions, we used a model system of species interactions, Myxococcus xanthus. M. xanthus is a soil bacterium that is a known predator of other bacteria. It has one of the largest repertoires of two component systems (TCS) to respond to external stresses. TCS are a pair of proteins, one that senses environmental stress (histidine kinase, HK) and another that usually acts as a transcriptional regulator (response regulators, RR). We studied a class of RRs, NtrC-like, reliant on an alternative sigma factor, sigma54. The oligomerization of NtrC-like RRs is regulated to modulate activation of the protein, which would change the bacterium’s ability to respond to its environment. We studied HsfA, a NtrC-like RR that regulates specialized metabolites. Specialized metabolites are used in bacterial interactions. In predation interactions they are used to kill prey. Our goal was to find genes that might be involved in specialized metabolite production that would aid in predation. We used prediction tools to find putative binding sites of HsfA to find potentially new metabolites. We used two motifs to attempt to predict if the oligomerization of these response regulators is positively or negatively regulated. We found that the presence of a motif in the receiver domain to be associated with negative regulation of oligomerization, but further studies are needed to experimentally confirm this finding. One environment in which bacterial interactions occur is in the gut. The gut microbiome is the consortium of organisms and their genomic content in the gastrointestinal tract. The gut microbiome is sensitive to aspects of a person’s lifestyle, such as diet and medication. Here we studied the effect of two different diets and two drugs on the gut microbiome. Risperidone, an antipsychotic used to treat schizophrenia and bipolar disorder, has been shown to cause obesity and diabetes. We studied the effect of diet and risperidone usage on weight gain and the microbiome using a C57Bl/6J female mouse model. Our results show that diet has a strong impact on the microbial composition of the gut in response to risperidone. As many mental health patients stop and restart their medication, we examined the effect of stopping and restarting risperidone on the microbiome. When risperidone is stopped the microbiome reverts to a state similar to the control group but diverges into a different microbial composition upon restarting treatment. Interestingly, mice did not gain significantly more weight than their control group upon the second risperidone treatment. Further studies are needed to examine the functional changes occurring with the stop and restart of risperidone to determine the mechanism of mice resisting weight gain during the second round of treatment. Captopril is used to treat hypertension, a very common disease in the United States. Here we studied the effect of captopril on weight gain, metabolic phenotypes, and the gut microbiome. Our results showed that captopril caused an increase in resting metabolic rate (RMR) in mice. This occurred through an increase in energy expenditure. This increase in RMR had the effect of captopril-treated mice being resistant to weight gain. Our group has previously shown that the gut microbiome can directly affect RMR. Therefore, we studied the gut microbiome of captopril-treated mice. We observed a shift in their gut microbiome to organisms Akkermansia muciniphila and Lactobacillus, associated with lean body mass. Captopril therefore has the potential to be a better medication to treat patients with both hypertension and obesity. Further studies are needed to determine the effect of captopril on the microbiome in a hypertension mouse model.