Despite the advancement in sequencing technologies, around 98% of the genome is usually disregarded due to the lack of interpretation methods. Here, I compare different sequence-based deep-learning approaches for predicting the functionality of the non-coding genome. Using the largest non-coding variant database, I tested the change in prediction as pathogenic vs. benign variants were introduced. Then, I benchmarked their performance on different genomic regions and phenotypes and built a logistic regression model for cell- and phenotype-specific track selection. The models outperformed state-of-the-art evolutionary- and variantbased methods. Finally, I compared different target-gene annotation databases using ontology-based Resnik’s semantic similarity. I combined the previous steps in a variant-to-phenotype or phenotype-to-variant workflow and applied it to rare variants.

Syftet med detta projekt var att konstruera en mindre variant av pQlacZ-1 för att senare kunna använda den som reportervektor i Ideonella dechloratans. pQlacZ-1 är en plasmid som är 17,1 kbp stor, som skulle kunna användas som reportervektor i  Ideonella dechloratans för att kunna undersöka olika promotorsekvenser. Detta är möjligt eftersom pQlacZ-1 är en broad host range plasmid och saknar promotorsekvensen för lacZ genen. Ett problem med pQlacZ-1 är dess storlek vilket gör den svår att transformera, och då speciellt i Ideonella dechloratans som är svår att transformera överhuvudtaget. En stor del av projektet har lagts på att ta reda på hur pQlacZ-1 ser ut i detalj, då detta inte finns väl beskrivet. Även efter denna studie saknas information om ett fragment för att få en helt klar bild över hur plasmiden är uppbyggd. Efter att ha ställt upp en hypotes om hur plasmiden ser ut så identifierades ett område som kunde klyvas bort och det var fragmentet med lacA och lacY. Detta gjordes  genom en dubbelklyvning med SalI och BstBI. Den nya mindre varianten av plasmiden har jag valt att kalla pQlacZ-1cc och den ska teoretiskt sett vara ca 13427 bp stor, vilket bör göra den lättare att jobba med. Ytterligare arbete behövs för att verifiera konstruktionen i pQlacZ-1cc. / The aim with this project was to design a smaller version of pQlacZ-1 in order to later use it as a reporter vector in Ideonella dechloratans.  pQlacZ-1 is a plasmid that is 17,1 kbp big, which might be used as a reporter vector in Ideonella dechloratans to investigate different promoter sequences. This is possible because pQlacZ-1 is a broad host range plasmid and lacks the promoter sequence of the lacZ gene. A problem with pQlacZ-1 is its size which makes it difficult to transform, and especially in Ideonella dechloratans which is difficult to transform at all. A large part of the project has been about finding out how pQlacZ-1 looks like in detail, as this is not well described. Even after this study information about one fragment is missing to get a completely clear picture of how the plasmid is constructed. After formulation of a hypothesis about how the plasmid is constructed, a section that could be removed was identified. The part of pQlacZ-1 that was removed was the lacA and lacY. This was done by a double digestion with SalI and BstBI. The new smaller version of the plasmid, is called pQlacZ-1cc. Theoretically it should be about 13427 bp, which should make it easier to work with. Additional work is required to verify the design of pQlacZ-1cc.

The process of antigenic variation in African trypanosomes allows the survival of the parasite by constantly switching the variant surface glycoprotein (VSG) expressed in their surface. There are believed to be several hundred copies of these silent VSG genes in the parasite's genome and they are expressed differentially. The majority of these genes are not capable of being transcribed in situ and must therefore be expressed from specialised transcriptional units known as bloodstream expression sites (BESs). Only one such site is active at any one time, ensuring that a single VSG is expressed in the trypanosome's surface coat. Switching the expressed VSG involves replacing the VSG in the active BES, or activating a new BES in conjunction with silencing the previously active. Differential expression of variant surface glycoprotein (VSG) genes, has a strong association with telomeres. All BESs are telomeric and differential activation involves recombination into the telomeric environment or silencing/activation of subtelomeric promoters. A number of pathogen contingency gene systems associated with immune evasion involve telomeric loci, which has prompted speculation that chromosome ends provide conditions conducive for the operation of rapid gene switching mechanisms. Ku is a protein associated with yeast telomeres that is directly involved in DNA recombination and gene silencing. The main aim of this thesis was to test the hypothesis that Ku in trypanosomes is centrally involved in differential VSG expression. In order to compare trypanosome Ku homologues with those from other organisms, it was necessary to compile homology alignments with other Ku homologues using Clustal W analysis. Subsequent experiments looked at the fate of exogenously introduced restriction enzyme target sites after transient transformation with cassettes encoding the restriction enzyme. A final analysis looked for the presence of NHEJ in homologous recombination- deficient trypanosomes. Disrupting this element of DNA repair would hopefully lead to other forms of repair becoming detectable, and even up-regulated. Rad51, in yeast a member of the Rad52 epistasis group (integral in yeast homologous recombination), had previously been demonstrated to be involved in DNA repair in trypanosomes (McCulloch & Barry, 1999). rad51 mutants were electroporated with cassettes containing noncompatible ends that would prevent their integration into the endogenous genome via conventional homologous recombination. This cassette also contained promoter DNA sequence to allow selection in the event of integration into non-transcribed regions of the genome. Study of the junctions encompassing the integration sites of the cassette allowed investigation into how the cassettes were integrated, and revealed to us the extent of the sequence homology required to catalyse integration. The method of repair detection observed indicated that classical homologous recombination is not the only pathway utilised by African trypanosomes to metabolise DNA double-strand breaks.

Motivation: Next-generation sequencing technology is increasingly being used for clinical diagnostic tests. Unlike research cell lines, clinical samples are often genomically heterogeneous due to low sample purity or the presence of genetic subpopulations. Therefore, a variant calling algorithm for calling low-frequency polymorphisms in heterogeneous samples is needed. Result: We present a novel variant calling algorithm that uses a hierarchical Bayesian model to estimate allele frequency and call variants in heterogeneous samples. We show that our algorithm improves upon current classifiers and has higher sensitivity and specificity over a wide range of median read depth and minor allele frequency. We apply our model and identify twelve mutations in the PAXP1 gene in a matched clinical breast ductal carcinoma tumor sample; two of which are loss-of-heterozygosity events.

Students come to college for a change and for most this is their first time away from home. Some students come looking for acceptance and a chance to freely be themselves. Individuals that identify as transgender or gender-variant have a difficult time finding a way to be themselves in this setting when they do not have a safe place to live. This research examines students who live in campus housing at a large, Midwestern institution. Past research on transgender issues is presented in its limited availability along with the results of an electronic survey of student opinions of gender-neutral housing and restrooms. The possibility of instituting such changes at this specific institution is examined.

Recent advances in Next Generation Sequencing (NGS) technologies have facilitated the generation of massive amounts of genomic data which in turn is bringing the promise that personalized medicine will soon become widely available. As a result, there is an increasing pressure to develop computational tools to analyze and interpret genomic data. In this dissertation, we present a systematic approach for interrogating patients’ genomes to identify candidate causal genomic variants of Mendelian and oligogenic diseases. To achieve that, we leverage the use of biomedical data available from extensive biological experiments along with machine learning techniques to build predictive models that rival the currently adopted approaches in the field. We integrate a collection of features representing molecular information about the genomic variants and information derived from biological networks. Furthermore, we incorporate genotype-phenotype relations by exploiting semantic technologies and automated reasoning inferred throughout a cross-species phenotypic ontology network obtained from human, mouse, and zebra fish studies. In our first developed method, named PhenomeNet Variant Predictor (PVP), we perform an extensive evaluation of a large set of synthetic exomes and genomes of diverse Mendelian diseases and phenotypes. Moreover, we evaluate PVP on a set of real patients’ exomes suffering from congenital hypothyroidism. We show that PVP successfully outperforms state-of-the-art methods, and provides a promising tool for accurate variant prioritization for Mendelian diseases. Next, we update the PVP method using a deep neural network architecture as a backbone for learning and illustrate the enhanced performance of the new method, DeepPVP on synthetic exomes and genomes. Furthermore, we propose OligoPVP, an extension of DeepPVP that prioritizes candidate oligogenic combinations in personal exomes and genomes by integrating knowledge from protein-protein interaction networks and we evaluate the performance of OligoPVP on synthetic genomes created by known disease-causing digenic combinations. Finally, we discuss some limitations and future steps for extending the applicability of our proposed methods to identify the genetic underpinning for Mendelian and oligogenic diseases.

An exome sequencing analysis pipeline was constructed to analyze NET germline and somatic samples. SNPs and INDELs were called and annotated from germline and somatic tissue. CNVs were also called for the tumor samples. This was accomplished using open source bioinformatics software that has been developed by the research community. Broad Institute "best practices" were followed. Some of the tools that were used include BWA, SAMtools, GATK, Varscan, VT, VEP, and GEMINI. Computational resources were provided by The University of Iowa NEON computer cluster. 57 germline samples and 15 tumor samples across 23 families with a history of NETs produced 4,452 germline variants, 1,695 somatic variants, 5,853 LOH events, and 627 CNV calls. False positive and driver candidacy filtering was applied. One family with Currarino syndrome has an inherited germline missense variant in MNX1. This variant has a phred-scaled Combined Annotation Dependant Depletion score of 35, putting it in the top 0.031% of deleterious variants. CNV analysis demonstrates that 8 of the 15 tumor samples have large-scale deletions of chromosome 18, three of which have nearly the entire chromosome deleted. An affected tumor suppressor gene in this region includes DCC, which is present in all three variant discovery techniques. Variant prioritization techniques are effective, but need further development to increase candidate variant/gene discovery rate.

Although complete understanding of the mechanisms of rare genetic variants in disease continues to elude us, Next Generation Sequencing (NGS) has facilitated significant gene discoveries across the disease spectrum. However, the cost of NGS hinders its use for identifying rare variants in common diseases that require large samples. To circumvent the need for larger samples, designing efficient sampling studies is crucial in order to detect potential associations. This research therefore evaluates sampling designs for rare variant - quantitative trait association studies and assesses the effect on power that freely available public cohort data can have in the design. Performing simulations and evaluating common and unconventional sampling schemes results in several noteworthy findings. Specifically, the extreme-trait design is the most powerful design for analyzing quantitative traits. This research also shows that sampling more individuals from the extreme of clinical interest does not increase power. Variant filtering has served as a "proof-of-concept" approach for the discovery of disease-causing genes in Mendelian traits and formal statistical methods have been lacking in this area. However, combining variant filtering schemes with existing rare variant association tests is a practical alternative. Thus, this thesis also compares the robustness of six burden-based rare variant association tests for Mendelian traits after a variant filtering step in the presence of genetic heterogeneity and genotyping errors. This research shows that with low locus heterogeneity, these tests are powerful for testing association. With the exception of the weighted sum statistic (WSS), the remaining tests were very conservative in preserving the type I error when the number of affected and unaffected individuals was unequal. The WSS, on the other hand, had inflated type I error as the number of unaffected individuals increased. The framework presented can serve as a catalyst to improve sampling design and to develop robust statistical methods for association testing.

No description available.

As my thesis project, I developed and implemented the SAGA Youth and Family Program through the Wingspan LGBT Community Center and the Southern Arizona Gender Alliance. The first chapter analyzes the use of rights discourse by advocates of transgender youth as a means to gain needed protection and concessions. The second chapter introduces the SAGA Youth and Family Program created to build supportive communities for gender-variant and transgender youth and their families and to end unnecessary isolation, discrimination and harassment affecting transgender and gender-variant youth, their families, and their communities. The SAGA Youth and Family website comprises the final chapter and is one of the three components of the SAGA Youth and Family Program.