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Role of Mycobacterium avium paratuberculosis (MAP) and TNFSF15 SNPs on TL1A in CD
Title
Role of Mycobacterium avium paratuberculosis (MAP) and TNFSF15 SNPs on TL1A in CD.
Creator
Hassouneh, Sayf Al-Deen, Naser, Saleh, Yooseph, Shibu, Parthasarathy, Sampath, University of Central Florida
Abstract / Description
Tumor Necrosis Factor-Like Ligand 1a (TL1A) is a cytokine encoded by Tumor Necrosis Factor Super Family 15 gene (TNFSF15) gene mostly in endothelial cells which binds to T-cells and foments the production of pro-inflammatory cytokines including TNF-?, IL-6, IL-1b, IFN- ? and IL-13. TL1A level is elevated in inflammatory diseases including Crohn's Disease (CD). Although Single Nucleotide Polymorphisms (SNPs) in TNFSF15 have been reported in CD, no studies have investigated the effect of these...
Show moreTumor Necrosis Factor-Like Ligand 1a (TL1A) is a cytokine encoded by Tumor Necrosis Factor Super Family 15 gene (TNFSF15) gene mostly in endothelial cells which binds to T-cells and foments the production of pro-inflammatory cytokines including TNF-?, IL-6, IL-1b, IFN- ? and IL-13. TL1A level is elevated in inflammatory diseases including Crohn's Disease (CD). Although Single Nucleotide Polymorphisms (SNPs) in TNFSF15 have been reported in CD, no studies have investigated the effect of these SNPs on TL1A, inflammation, and susceptibility to Mycobacterium avium subspecies paratuberculosis (MAP) infection. MAP is a strong candidate in CD pathogenesis. This study is designed to elucidate the combined effect of MAP and SNPs in TNFSF15 (rs4263839, rs7848647, rs6478108, or rs6478109) on TL1A secretion and downstream effect on pro-inflammatory cytokines. Peripheral blood from CD and healthy subjects was analyzed for MAP DNA, TNFSF15 genotyping, circulating TL1A level, and IFN- ? and TNF-? gene expression. Our data is first to report that rs4263839, rs7848647, rs6478108, and rs6478109 in TNFSF15 resulted in increase in circulating TL1A level in healthy and CD samples. Specifically, in CD samples with rs7848647, the average TL1A level was 146.9 pg/mL (&)#177; 124.5 compared 62.4 pg/mL (&)#177; 82.8 in normal samples. Similarly, TL1A level in CD samples with rs6478109 was 141.9 pg/mL (&)#177; 127.7 compared to 71.5 pg/mL (&)#177; 88.4 in normal samples (p(<)0.05). All 4 SNPs resulted in significant elevation in TL1A level in healthy samples (p(<)0.05). Moreover, IFN-? expression was significantly higher, by approximately 1.6-fold in CD patients with SNPs relative to CD patients with no SNPs (p(<)0.05). Interestingly, SNPs in TNFS15 had no significant effect on TNF-? expression. MAP was detected in the blood of 63% of CD compared to 6% healthy subjects (p(<).001). The data did not support a correlation between MAP presence and circulating TL1A levels, and no correlation between SNPs in TNSF15 and MAP susceptibility. This study strongly suggests, that SNPs in TNFSF15 increase TL1A levels and may be a contributory factor to the inflammation experienced by CD patients. Over all, the study emphasizes the need for a pharmacogenomic approach in treatment delivery for patients with CD by using TNFSF15 SNPs to identify patients that would benefit from biologics targeting TL1A rather than TNF-? for more efficacious treatment regiments for CD patients.
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Date Issued
2018
Identifier
CFE0007189, ucf:52263
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007189
Analysis of large-scale population genetic data using efficient algorithms and data structures
Title
Analysis of large-scale population genetic data using efficient algorithms and data structures.
Creator
Naseri, Ardalan, Zhang, Shaojie, Hughes, Charles, Yooseph, Shibu, Zhi, Degui, University of Central Florida
Abstract / Description
With the availability of genotyping data of very large samples, there is an increasing need for tools that can efficiently identify genetic relationships among all individuals in the sample. Modern biobanks cover genotypes up to 0.1%-1% of an entire large population. At this scale, genetic relatedness among samples is ubiquitous. However, current methods are not efficient for uncovering genetic relatedness at such a scale. We developed a new method, Random Projection for IBD Detection (RaPID)...
Show moreWith the availability of genotyping data of very large samples, there is an increasing need for tools that can efficiently identify genetic relationships among all individuals in the sample. Modern biobanks cover genotypes up to 0.1%-1% of an entire large population. At this scale, genetic relatedness among samples is ubiquitous. However, current methods are not efficient for uncovering genetic relatedness at such a scale. We developed a new method, Random Projection for IBD Detection (RaPID), for detecting Identical-by-Descent (IBD) segments, a fundamental concept in genetics in large panels. RaPID detects all IBD segments over a certain length in time linear to the sample size. We take advantage of an efficient population genotype index, Positional BWT (PBWT), by Richard Durbin. PBWT achieves linear time query of perfectly identical subsequences among all samples. However, the original PBWT is not tolerant to genotyping errors which often interrupt long IBD segments into short fragments. The key idea of RaPID is that the problem of approximate high-resolution matching over a long range can be mapped to the problem of exact matching of low-resolution subsampled sequences with high probability. PBWT provides an appropriate data structure for bi-allelic data. With the increasing sample sizes, more multi-allelic sites are expected to be observed. Hence, there is a necessity to handle multi-allelic genotype data. We also introduce a multi-allelic version of the original Positional Burrows-Wheeler Transform (mPBWT).The increasingly large cohorts of whole genome genotype data present an opportunity for searching genetically related people within a large cohort to an individual. At the same time, doing so efficiently presents a challenge. The PBWT algorithm offers constant time matching between one haplotype and an arbitrarily large panel at each position, but only for the maximal matches. We used the PBWT data structure to develop a method to search for all matches of a given query in a panel. The matches larger than a given length correspond to the all shared IBD segments of certain lengths between the query and other individuals in the panel. The time complexity of the proposed method is independent from the number of individuals in the panel. In order to achieve a time complexity independent from the number of haplotypes, additional data structures are introduced.Some regions of genome may be shared by multiple individuals rather than only a pair. Clusters of identical haplotypes could reveal information about the history of intermarriage, isolation of a population and also be medically important. We propose an efficient method to find clusters of identical segments among individuals in a large panel, called cPBWT, using PBWT data structure. The time complexity of finding all clusters of identical matches is linear to the sample size. Human genome harbors several runs of homozygous sites (ROHs) where identical haplotypes are inherited from each parent. We applied cPBWT on UK-Biobank and searched for clusters of ROH region that are shared among multiple. We discovered strong associations between ROH regions and some non-cancerous diseases, specifically auto-immune disorders.
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Date Issued
2018
Identifier
CFE0007764, ucf:52393
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007764
Efficient String Graph Construction Algorithm
Title
Efficient String Graph Construction Algorithm.
Creator
Morshed, S.M. Iqbal, Yooseph, Shibu, Zhang, Shaojie, Valliyil Thankachan, Sharma, University of Central Florida
Abstract / Description
In the field of genome assembly research where assemblers are dominated by de Bruijn graph-based approaches, string graph-based assembly approach is getting more attention because of its ability to losslessly retain information from sequence data. Despite the advantages provided by a string graph in repeat detection and in maintaining read coherence, the high computational cost for constructing a string graph hinders its usability for genome assembly. Even though different algorithms have...
Show moreIn the field of genome assembly research where assemblers are dominated by de Bruijn graph-based approaches, string graph-based assembly approach is getting more attention because of its ability to losslessly retain information from sequence data. Despite the advantages provided by a string graph in repeat detection and in maintaining read coherence, the high computational cost for constructing a string graph hinders its usability for genome assembly. Even though different algorithms have been proposed over the last decade for string graph construction, efficiency is still a challenge due to the demand for processing a large amount of sequence data generated by NGS technologies. Therefore, in this thesis, we provide a novel, linear time and alphabet-size-independent algorithm SOF which uses the property of irreducible edges and transitive edges to efficiently construct string graph from an overlap graph. Experimental results show that SOF is at least 2 times faster than the string graph construction algorithm provided in SGA, one of the most popular string graph-based assembler, while maintaining almost the same memory footprint as SGA. Moreover, the availability of SOF as a subprogram in the SGA assembly pipeline will give user facilities to access the preprocessing and postprocessing steps for genome assembly provided in SGA.
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Date Issued
2019
Identifier
CFE0007504, ucf:52635
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007504
Deciphering the Role of Adrenergic Hormones in Embryonic Cardiac Calcium Signaling and Metabolism
Title
Deciphering the Role of Adrenergic Hormones in Embryonic Cardiac Calcium Signaling and Metabolism.
Creator
Peoples, Jessica, Ebert, Steven, Davidson, Victor, Phanstiel, Otto, Yooseph, Shibu, University of Central Florida
Abstract / Description
The adrenergic hormones norepinephrine (NE) and epinephrine (EPI) are critical regulators of mammalian cardiovascular physiology. NE and EPI mediate stress responses to enhance cardiovascular function, however dysregulation of adrenergic signaling leads to heart failure, congenital heart malformations, and sudden cardiac death. Adrenergic hormone-expressing cells were found in the early embryonic heart, and NE has been determined essential for embryonic cardiac development. Despite extensive...
Show moreThe adrenergic hormones norepinephrine (NE) and epinephrine (EPI) are critical regulators of mammalian cardiovascular physiology. NE and EPI mediate stress responses to enhance cardiovascular function, however dysregulation of adrenergic signaling leads to heart failure, congenital heart malformations, and sudden cardiac death. Adrenergic hormone-expressing cells were found in the early embryonic heart, and NE has been determined essential for embryonic cardiac development. Despite extensive work in adults, the regulatory roles and adrenergic targets of these hormones during embryonic cardiac development have not yet been fully determined. Prior transcriptomic studies from our lab showed that expression of signal transduction and metabolic genes in embryos lacking adrenergic hormones were by far the most affected categories of genes. Thus, we hypothesized that adrenergic hormones stimulate early calcium signaling, and are required for sufficient supply of energy substrates for the metabolic shift from anaerobic glycolysis to aerobic respiration during heart development. We utilized the dopamine ?-hydroxylase knock-out (Dbh-/-) mouse model to examine effects of adrenergic-deficiency on calcium signaling and metabolism during heart development. Using calcium-imaging and patch-clamp techniques, we found that calcium transients, voltage-gated calcium channels, and L-type calcium currents in adrenergic-deficient embryonic hearts were not affected relative to controls indicating adrenergic stimulation did not influence early calcium signaling. Metabolomics analyses of adrenergic-deficient hearts revealed disruption in glycolytic and pentose-phosphate pathways as well as reduced activity of respective regulatory enzymes, glyceraldehyde 3-phosphate dehydrogenase and glucose 6-phosphate dehydrogenase indicating compromised glucose metabolism. Addition of pyruvate to embryonic hearts led to significant recovery of ATP concentrations and oxygen consumption rates, thereby supporting the hypothesis that adrenergic-deficient hearts are (")starved(") of metabolic substrates required for transitions from anaerobic glycolysis to aerobic metabolism. Overall, we showed that adrenergic hormones are not necessary for calcium signaling in the embryonic heart, but are essential regulators ensuring sufficient metabolic substrate and boosting enzymatic activities to fuel aerobic metabolism.
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Date Issued
2018
Identifier
CFE0007233, ucf:52223
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007233