Thesis (MSc)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Metagenomic studies that make use of next-generation sequencing (NGS) generate large amounts of sequence data, representing the genomes of multiple organisms of which no prior knowledge is necessarily available. In this study, a metagenomic NGS approach was used to detect multiple novel mycoviral sequences in grapevine phloem tissue. Individual sequencing libraries of doublestranded RNA (dsRNA) from two grapevine leafroll diseased (GLD) and three shiraz diseased (SD) vines were sequenced using an Illumina HiScanSQ instrument. Over 3.2 million reads were generated from each of the samples and these reads were trimmed and filtered for quality before being de novo assembled into longer contigs. The assembled contigs were subjected to BLAST (Basic Local Alignment Search Tool) analyses against the NCBI (National Centre for Biotechnology Information) database and classified according to database sequences with which they had the highest identity. Twenty-six putative mycovirus species were identified, belonging to the families Chrysoviridae, Endornaviridae, Narnaviridae, Partitiviridae and Totiviridae. Two of the identified mycoviruses, namely grapevine-associated chrysovirus (GaCV) and grapevine-associated mycovirus 1 (GaMV-1) have previously been identified in grapevine while the rest appeared to be novel mycoviruses not present in the NCBI database. Primers were designed from the de novo assembled mycoviral sequences and used to screen the grapevine dsRNA used for sequencing as well as endophytic fungi isolated from the five sample vines. Only two mycoviruses, related to sclerotinia sclerotiorum partitivirus S and chalara elegans endornavirus 1 (CeEV-1), could be detected in grapevine dsRNA and in fungus isolates. In order to validate the presence of mycoviruses in grapevine phloem tissue, two additional sequencing runs, using an Illumina HiScanSQ and an Applied Biosystems (ABI) SOLiD 5500xl instrument respectively, were performed. These runs generated more and higher quality sequence data than the first sequencing run. Twenty-two of the putative mycoviral sequences initially detected were detected in the subsequent sequence datasets, as well as an additional 29 species not identified in the first HiScanSQ sequence datasets. The samples harboured diverse mycovirus populations, with as many as 19 putative species identified in a single vine. This indicates that the complete virome of diseased grapevines will include a high number of mycoviruses. Additionally, the complete genome of a novel endornavirus, for which we propose the name grapevine endophyte endornavirus (GEEV), was assembled from one of the second HiScanSQ sequence datasets. This is the first complete genome of a mycovirus detected in grapevine. Grapevine endophyte endornavirus has the highest sequence similarity to CeEV-1 and is the same virus that was previously detected in fungus isolates using the mycovirus primers. The virus was detected in two fungus isolates, namely Stemphylium sp. and Aureobasidium pullulans, which is of interest since mycoviruses are not known to be naturally associated with two distinctly different fungus genera. Mycoviral sequence data generated in this study can be used to further investigate the diversity and the effect of mycoviruses in grapevine. / AFRIKAANSE OPSOMMING: Metagenomiese studies, wat gebruik maak van volgende-generasie volgordebepalingstegnologie, het die vermoë om die genetiese samestelling van veelvoudige onbekende organismes te bepaal deurdat dit groot hoeveelhede data genereer. Die bogenoemde tegniek was in hierdie studie aangewend om aantal nuwe mikovirusse in die floëem weefsel van wingerd te identifiseer. Dubbelstring-RNS was gesuiwer vanuit twee druiwestokke met rolbladsiekte en drie met shirazsiekte en Illumina HiScanSQ instrument is gebruik om meer as 3.2 miljoen volgorde fragmente te genereer van elk van die monsters. Lae-kwaliteit volgordes was verwyder en die oorblywende kort volgorde fragmente was saamgestel om langer konstrukte te vorm wat met behulp van BLAST soektogte teen die NCBI databasis geïdentifiseer kon word. Ses-en-twintig mikovirus spesies, wat aan die families Chrysoviridae, Endornaviridae, Narnaviridae, Partitiviridae en Totiviridae behoort, was geïdentifiseer. Twee van die geïdentifiseerde mikovirusse, naamlik grapevine-associated chrysovirus (GaCV) en grapevine-associated mycovirus 1 (GaMV-1), was voorheen al in wingerd gekry terwyl die res nuwe mikovirusse is wat tans nie in die NCBI databasis voorkom nie. Inleiers was ontwerp vanaf die saamgestelde mikovirus basisvolgordes en gebruik om wingerd dubbelstring-RNS sowel as swamme wat vanuit die wingerd geïsoleer is te toets vir die teenwoordigheid van hierdie mikovirusse. Slegs twee mikovirusse, wat onderskeidelik verwant is aan sclerotinia sclerotiorum partitivirus S en chalara elegans endornavirus 1 (CeEV-1), kon deur middel van die inleiers in wingerd en swam isolate geïdentifiseer word. Twee addisionele volgordebepalingsreaksies, wat gebruik gemaak het van die Illumina HiScanSQ en ABI SOLiD 5500xl volgordebepalingsplatforms, was gebruik om die teenwoordigheid van mikovirusse in wingerd te bevestig. Groter hoeveelheid volgorde fragmente was geprodusser wat ook van hoër gehalte was as dié van die eerste volgordebepalingsreaksie. Twee-en-twintig mikovirus spesies kon weer geïdentifiseer word, sowel as 29 spesies wat nie in die eerste HiScanSQ basisvolgorde datastelle gevind was nie. Die wingerdstokke wat in hierdie studie ondersoek was, het hoë diversiteit van mikovirusse bevat aangesien daar tot 19 mikovirus spesies in enkele wingerdstok geïdentifiseer was. Dit is aanduiding dat volledige virus profiele van siek wingerdstokke aantal mikovirusse sal insluit. Die vollengte genoomvolgorde van voorheen onbekende endornavirus was saamgestel vanuit een van die tweede HiScanSQ volgorde datastelle. Dit is die eerste mikovirus wat in wingerd gevind word waarvan die volledige genoomvolgorde bepaal is en ons stel die naam grapevine endophyte endornavirus (GEEV) voor vir hierdie virus. Grapevine endophyte endornavirus is die naaste verwant aan CeEV-1 en is dieselfde virus wat voorheen in wingerd dubbelstring-RNS en swam isolate gevind was deur middel van die mikovirus inleiers. Swam isolate waarin GEEV gevind is, was geïdentifiseer as Stemphylium sp. en Aureobasidium pullulans. Dit is van belang dat GEEV in twee swam isolate gevind is wat aan verskillende genusse behoort aangesien hierdie verskynsel nog nie voorheen in die natuur gevind is nie. Mikovirus nukleiensuurvolgordes wat in hierdie studie bepaal was kan gebruik word in toekomstige studies om die verskeidenheid en impak van mikovirusse in wingerd verder te ondersoek. / National Research Foundation (NRF) / Stellenbosch University

Ribonucleic acid (RNA) is an essential molecule, which carries out a wide variety of functions within the cell, from its crucial involvement in protein synthesis to catalysing biochemical reactions and regulating gene expression. Such diverse functional repertoire is indebted to complex structures that RNA can adopt and its flexibility as an interacting molecule. It has become possible to experimentally measure these two crucial aspects of RNA regulatory role with such technological advancements as next-generation sequencing (NGS). NGS methods can rapidly obtain the nucleotide sequence of many molecules in parallel. Designing experiments, where only the desired parts of the molecule (or specific parts of the transcriptome) are sequenced, allows to study various aspects of RNA biology. Analysis of NGS data is insurmountable without computational methods. One such experimental method is RNA structure probing, which aims to infer RNA structure from sequencing chemically altered transcripts. RNA structure probing data is inherently noisy, affected both by technological biases and the stochasticity of the underlying process. Most existing methods do not adequately address the issue of noise, resorting to heuristics and limiting the informativeness of their output. In this thesis, a statistical pipeline was developed for modelling RNA structure probing data, which explicitly captures biological variability, provides automated bias-correcting strategies, and generates a probabilistic output based on experimental measurements. The output of our method agrees with known RNA structures, can be used to constrain structure prediction algorithms, and remains robust to reduced sequence coverage, thereby increasing sensitivity of the technology. Another recent experimental innovation maps RNA-protein interactions at very high temporal resolution, making it possible to study rapid binding events happening on a minute time scale. In this thesis, a non-parametric algorithm was developed for identifying significant changes in RNA-protein binding time-series between different conditions. The method was applied to novel yeast RNA-protein binding time-course data to study the role of RNA degradation in stress response. It revealed pervasive changes in the binding to the transcriptome of the yeast transcription termination factor Nab3 and the cytoplasmic exoribonuclease Xrn1 under nutrient stress. This challenged the common assumption of viewing transcriptional changes as the major driver of changes in RNA expression during stress and highlighted the importance of degradation. These findings inspired a dynamical model for RNA expression, where transcription and degradation rates are modelled using RNA-protein binding time-series data.

Over the last decades the crustacean aquaculture sector has been steadily growing, in order to meet global demands for its products. A major hurdle for further growth of the industry is the prevalence of viral disease epidemics that are facilitated by the intense culture conditions. A devastating virus impacting on the sector is the White Spot Syndrome Virus (WSSV), responsible for over US $10 billion in losses in shrimp production and trade. The Pathogenicity of WSSV is high, reaching 100 % mortality within 3-10 days in penaeid shrimps. In contrast, the European shore crab Carcinus maenas has been shown to be relatively resistant to WSSV. Uncovering the basis of this resistance could help inform on the development of strategies to mitigate the WSSV threat. C. maenas has been used widely in studies on ecotoxicology and host-pathogen interactions. However, like most aquatic crustaceans, the genomic resources available for this species are limited, impairing experimentation. Therefore, to facilitate interpretations of the exposure studies, we first produced a C. maenas transcriptome and genome scaffold assembly. We also produced a transcriptome for the European lobster (Homarus gammarus), an ecologically and commercially important crustacean species in United Kingdom waters, for use in comparing WSSV responses in this, a susceptible species, and C. maenas. For the C. maenas transcriptome assembly we isolated and pooled RNA from twelve different tissues and sequenced RNA on an Illumina HiSeq 2500 platform. After de novo assembly a transcriptome encompassing 212,427 transcripts was produced. Similar, the H. gammarus transcriptome was based on RNA from nine tissues and contained 106,498 transcripts. The transcripts were filtered and annotated using a variety of tools (including BLAST, MEGAN and RSEM) and databases (including GenBank, Gene Ontology and KEGG). The annotation rate for transcripts in both transcriptomes was around 20-25 % which appears to be common for aquatic crustacean species, as a result of the lack of well annotated gene sequences for this clade. Since it is likely that the host immune system would play an important role in WSSV infection we characterized the IMD, JAK/STAT, Toll-like receptor and other innate immune system pathways. We found a strong overlap between the immune system pathways in C. maenas and H. gammarus. In addition we investigated the sequence diversity of known WSSV interacting proteins amongst susceptible penaeid shrimp/lobster and the more resistant C. maenas. There were differences in viral receptor sequences, like Rab7, that correlate with a less efficient infection by WSSV. To produce the genome scaffold assembly for C. maenas we isolated DNA from muscle tissue and produced both paired-end and mate pair libraries for processing on the Illumina HiSeq 2500 platform. A de novo draft genome assembly consisting of 338,980 scaffolds and covering 362 Mb (36 % of estimated genome size) was produced, using SOAP-denovo2 coupled with the BESST scaffolding system. The generated assembly was highly fragmented due to the presence of repetitive areas in the C. maenas genome. Using a combination of ab initio predictors, RNA-sequencing data from the transcriptome datasets and curated C. maenas sequences we produced a model encompassing 10,355 genes. The gene model for C. maenas Dscam, a gene potentially involved in (pan)crustacean immune memory, was investigated in greater detail as manual curation can improve on the results of ab initio predictors. The scaffold containing C. maenas Dscam was fragmented, thus only contained the latter exons of the gene. The assembled draft genome and transcriptomes for C. maenas and H. gammarus are valuable molecular resources for studies involving these and other aquatic crustacean species. To uncover the basis of their resistance to WSSV, we infected C. maenas with WSSV and measured mRNA and miRNA expression for 7 time points spread over a period of 28 days, using RNA-Seq and miRNA-Seq. The resistance of C. maenas to WSSV infection was confirmed by the fact that no mortalities occurred. In these animals replicating WSSV was latent and detected only after 7 days, and this occurred in five of out 28 infected crabs only. Differential expression of transcripts and miRNAs were identified for each time point. In the first 12 hours post exposure we observed decreased expression of important regulators in endocytosis. Since it is established that WSSV enters the host cells through endocytosis and that interactions between the viral protein VP28 and Rab7 are important in successful infection, it is likely that changes in this process could impact WSSV infection success. Additionally we observed an increased expression of transcripts involved in RNA interference pathways across many time points, indicating a longer term response to initial viral exposure. miRNA sequencing showed several miRNAs that were differentially expressed. The most striking finding was a novel C. maenas miRNA that we found to be significantly downregulated in every WSSV infected individual, suggesting that it may play an important role in mediating the response of the host to the virus. In silico target prediction pointed to the involvement of this miRNA in endocytosis regulation. Taken together we hypothesize that C. maenas resistance to WSSV involves obstruction of viral entry by endocytosis, a process probably regulated through miRNAs, resulting in inefficient uptake of virions.

Microsporidia are a unique phylum of ubiquitous fungal pathogens that are able to infect a wide variety of hosts, including economically and ecologically important organisms. Recently, global declines of the Western honeybee (Apis mellifera) have been associated with infections of the microsporidian pathogen Nosema ceranae. This species was originally described in the Asiatic honeybee (A. cerana), and its identification in global A. mellifera hives could result from a recent host transfer. Recent genome studies have found that global populations of this parasite from A. mellifera hives are polyploid and that humans may have fueled their global expansion. In this thesis, I investigate the genetic diversity of N. ceranae populations from within their native range (Thailand) and among different hosts (A. mellifera, A. cerana), putting them in context with other previously sequenced global populations. Using both PCR and genome-based methods, my findings reveal that Thai populations of N. ceranae exhibit interesting genetic differences from other global pathogen populations but also have some similarities. Thai N. ceranae populations share many single nucleotide polymorphisms (SNPs) with other global populations and appear to be clonal. However, in stark contrast with previous studies, these populations carry many SNPs not found in other global populations of this parasite, indicating that these populations have evolved in their current geographic location for some time. This genome analysis also indicates the potential presence of diploidy within Thai populations of N. ceranae and possible host-specific loss of heterozygosity. Overall, my findings begin to reveal interesting patterns of genetic diversity in N. ceranae populations that bring us one step closer to understanding the biology and genetics of this important honeybee pathogen.

Summary: Breast cancer (BC) is the most frequent cancer type in female population of Europe. Approximately 5 - 10 % accounts for its hereditary form which is characterized by high penetrance, early onset, risen recurrence risk and development of other cancers. Mutational analyses of high risk patients identify a predisposing mutation in one of the most studied genes (BRCA1, BRCA2, TP53, ATM, CHEK2, NBS1, PALB2) only in less than one third of tested breast cancer patients. Lately, with the use of new methods of next-generation sequencing, a number of other susceptibility or candidate genes were characterized, but the incidence of their pathogenic alteration is often geographically different. A notable proportion of high risk patients from families with hereditary BC can represent carriers of population-specific, or private mutations. Most of the to date identified BC susceptibility genes codes for proteins involved in DNA repair, especially repair of double strand break DNA repair. Nevertheless the mutation analysis was conducted only on a small fraction of these DNA repair genes. We can expect that in the group of yet nontested genes coding for DNA repair proteins a rare, but clinically important genetic alterations predisposing to BC in affected families can be discovered. This work describes a...

Next-Generation Sequencing (NGS) technologies have been evolving at an unparalleled pace. The ability to generate millions of base pairs of data in a short time and at lower cost than previously has led to a dramatic expansion of technologies within the field. This dissertation discusses the development and validation of new methods for assessing genomic variation, dynamic changes in gene expression, high-accuracy sequencing, and analysis of recombination events. By reducing the cost of analyzing many samples for genetic divergence by genotyping the same region of the genome in multiple samples, researchers can pursue investigations on a larger scale. Next-RAD (Nextera fragmentation with Restriction-Associated Digestion) allows analysis of a uniform subset of loci between organisms for comparison of populations by genetic differences with reduced burdens of cost and data analysis. This method was applied to the Anopheles darlingi mosquito to identify three distinct species that were thought to be a uniform population. The lowering cost of large-scale sequencing investigations allows for massively parallel analysis of genomic function in a single assay. Regulation of gene expression in response to stress is a complex process which can only be understood by analyzing many pathways in tandem. A novel method is described which quantifies on a genome-wide scale the expression of millions of randomer tags driven by associated transcriptional enhancers. This method provides novel data in the form of high-resolution analysis of gene regulation. Aside from generating novel data types, another force behind development of new technologies is to improve data quality. One limitation of NGS is the inherent error rate. PELE-Seq (Paired End Low Error Sequencing) was developed to address this problem, by employing completely overlapping paired-end reads as well as a dual barcoding strategy to eliminate incorrect sequences resulting from final library amplification. This new tool improves data quality dramatically. Finally, the rapid expansion of tools necessitates the identification of new applications for these technologies. To this end, 10x Genomics Linked-Read sequencing was employed to identify recombination events in multiple species. The haplotype-resolved nature of the data generated from such assays has many promising applications.

Breast cancer is a clinically and molecularly heterogeneous disease displaying distinct therapeutic responses. Although recent studies have explored the genomic and transcriptomic landscapes of breast cancer, the epigenetic architecture has received less attention. To address this, an optimised Reduced Representation Bisulfite Sequencing protocol was performed on 1482 primary breast tumours (and 237 matched adjacent normal tissues). This constitutes the largest breast cancer methylome yet, and this thesis describes the bioinformatics and statistical analysis of this study. Noticeable epigenetic drift (both gain and loss of homogeneous DNA methylation patterns) was observed in breast tumours when compared to normal tissues, with markedly higher differences in late replicating genomic regions. The extent of epigenetic drift was also found to be highly heterogeneous between the breast tumours and was sharply correlated with the tumour’s mitotic index, indicating that epigenetic drift is largely a consequence of the accumulation of passive cell division related errors. A novel algorithm called DMARC (Directed Methylation Altered Regions in Cancer) was developed that utilised the tumour-specific drift rates to discriminate between methylation alterations attained as a consequence of stochastic cell division errors (background) and those reflecting a more instructive biological process (directed). Directed methylation alterations were significantly enriched for gene expression changes in breast cancer, compared to background alterations. Characterising these methylation aberrations with gene expression led to the identification of breast cancer subtype-specific epigenetic genes with consequences on transcription and prognosis. Cancer genes may be deregulated by multiple mechanisms. By integrating with existing copy number and gene expression profiles for these tumours, DNA methylation alterations were revealed as the predominant mechanism correlated with differentially expressed genes in breast cancer. The crucial role of DNA methylation as a mechanism to target the silencing of specific genes within copy number amplifications is also explored which led to the identification of a putative tumour suppressor gene, THSZ2. Finally, the first genome-wide assessment of epigenomic evolution in breast cancer is conducted. Both, the level of intratumoural heterogeneity, and the extent of epiallelic burden were found to be prognostic, and revealed an extraordinary distinction in the role of epiclonal dynamics in different breast cancer subtypes. Collectively, the results presented in this thesis have shed light on the somatic DNA methylation basis of inter-patient as well as intra-tumour heterogeneity in breast cancer. This complements our genetic knowledge of the disease, and will help move us towards tailoring treatments to the patient's molecular profile.

Sepsis is one of the leading causes for fatalities in the intensive care unit, and also one of the biggest health problems worldwide. It is a disease caused primarily by bacterial infections but can also be caused by viral or fungal infections. Since it is such a big health problem being associated with increased risk of sepsis, coupled with longer stays in the intensive care unit, the need for fast diagnosis and treatment is very important. Currently, culture is the leading diagnostic method for identification of bacteria, although other methods are currently being tested to improve identification time and decrease cost and workload. Next generation sequencing (NGS) has the capacity to output several million reads in a single experiment, making it very fast and relatively cheap compared to other older sequencing methods such as Sanger sequencing. The ability to analyze genes and even whole genomes, opens the possibilities to identify factors such as bacterial species, virulence genes and antibiotic resistance genes. The aim of this study was to find any possible correlations between 16 species of streptococci and clinical data in patients with suspected sepsis. Initial species identification was performed using MALDI-TOF before the samples were sequenced using NGS. Sequence files were then quality controlled and trimmed before being assembled. Following assembly, coverage was controlled for all assembled genomes before the downstream analysis started. Different tools such as 16S RNA species identification, multi locus sequence typing and antibiotic resistance finder were used, among other tools. The results were extremely mixed, with the overall quality of the data being of good quality, but the assembly and downstream analysis being worse. The most consistent species was S. pyogenes. No correlation between sepsis patients and relevant clinical data was found. The mixed quality of results from assembly and downstream analysis were most likely contributed to difficulties in culturing and sequencing of the streptococci. Finding ways to circumvent these problems would most likely aid in general sequencing of streptococcal species, and hopefully in clinical applications as well.

abstract: Rapid advancements in genomic technologies have increased our understanding of rare human disease. Generation of multiple types of biological data including genetic variation from genome or exome, expression from transcriptome, methylation patterns from epigenome, protein complexity from proteome and metabolite information from metabolome is feasible. "Omics" tools provide comprehensive view into biological mechanisms that impact disease trait and risk. In spite of available data types and ability to collect them simultaneously from patients, researchers still rely on their independent analysis. Combining information from multiple biological data can reduce missing information, increase confidence in single data findings, and provide a more complete view of genotype-phenotype correlations. Although rare disease genetics has been greatly improved by exome sequencing, a substantial portion of clinical patients remain undiagnosed. Multiple frameworks for integrative analysis of genomic and transcriptomic data are presented with focus on identifying functional genetic variations in patients with undiagnosed, rare childhood conditions. Direct quantitation of X inactivation ratio was developed from genomic and transcriptomic data using allele specific expression and segregation analysis to determine magnitude and inheritance mode of X inactivation. This approach was applied in two families revealing non-random X inactivation in female patients. Expression based analysis of X inactivation showed high correlation with standard clinical assay. These findings improved understanding of molecular mechanisms underlying X-linked disorders. In addition multivariate outlier analysis of gene and exon level data from RNA-seq using Mahalanobis distance, and its integration of distance scores with genomic data found genotype-phenotype correlations in variant prioritization process in 25 families. Mahalanobis distance scores revealed variants with large transcriptional impact in patients. In this dataset, frameshift variants were more likely result in outlier expression signatures than other types of functional variants. Integration of outlier estimates with genetic variants corroborated previously identified, presumed causal variants and highlighted new candidate in previously un-diagnosed case. Integrative genomic approaches in easily attainable tissue will facilitate the search for biomarkers that impact disease trait, uncover pharmacogenomics targets, provide novel insight into molecular underpinnings of un-characterized conditions, and help improve analytical approaches that use large datasets. / Dissertation/Thesis / Doctoral Dissertation Molecular and Cellular Biology 2015

abstract: Obesity and its underlying insulin resistance are caused by environmental and genetic factors. DNA methylation provides a mechanism by which environmental factors can regulate transcriptional activity. The overall goal of the work herein was to (1) identify alterations in DNA methylation in human skeletal muscle with obesity and its underlying insulin resistance, (2) to determine if these changes in methylation can be altered through weight-loss induced by bariatric surgery, and (3) to identify DNA methylation biomarkers in whole blood that can be used as a surrogate for skeletal muscle. Assessment of DNA methylation was performed on human skeletal muscle and blood using reduced representation bisulfite sequencing (RRBS) for high-throughput identification and pyrosequencing for site-specific confirmation. Sorbin and SH3 homology domain 3 (SORBS3) was identified in skeletal muscle to be increased in methylation (+5.0 to +24.4 %) in the promoter and 5’untranslated region (UTR) in the obese participants (n= 10) compared to lean (n=12), and this finding corresponded with a decrease in gene expression (fold change: -1.9, P=0.0001). Furthermore, SORBS3 was demonstrated in a separate cohort of morbidly obese participants (n=7) undergoing weight-loss induced by surgery, to decrease in methylation (-5.6 to -24.2%) and increase in gene expression (fold change: +1.7; P=0.05) post-surgery. Moreover, SORBS3 promoter methylation was demonstrated in vitro to inhibit transcriptional activity (P=0.000003). The methylation and transcriptional changes for SORBS3 were significantly (P≤0.05) correlated with obesity measures and fasting insulin levels. SORBS3 was not identified in the blood methylation analysis of lean (n=10) and obese (n=10) participants suggesting that it is a muscle specific marker. However, solute carrier family 19 member 1 (SLC19A1) was identified in blood and skeletal muscle to have decreased 5’UTR methylation in obese participants, and this was significantly (P≤0.05) predicted by insulin sensitivity. These findings suggest SLC19A1 as a potential blood-based biomarker for obese, insulin resistant states. The collective findings of SORBS3 DNA methylation and gene expression present an exciting novel target in skeletal muscle for further understanding obesity and its underlying insulin resistance. Moreover, the dynamic changes to SORBS3 in response to metabolic improvements and weight-loss induced by surgery. / Dissertation/Thesis / Appendix A / Appendix B / Appendix C / Appendix D / Appendix G / Doctoral Dissertation Biology 2017