{"id":{"repo_id":"wustl","oai_identifier":"oai:openscholarship.wustl.edu:etd-1590"},"canonical_url":"https://search.dev.ndltd.org/etd/wustl/oai:openscholarship.wustl.edu:etd-1590","repository":{"repo_id":"wustl","name":"Washington University in St. Louis","base_url":"https://openscholarship.wustl.edu/do/oai/"},"display":{"title":"Discovering Conserved cis-Regulatory Elements That Regulate Expression in Caenorhabditis elegans","abstract":"The aim of this dissertation is two-fold:: 1) To catalog all <italic>cis</italic>-regulatory elements within the intergenic and intronic regions surrounding every gene in <italic>C.elegans</italic>: i.e. the regulome) and: 2) to determine which cis-regulatory elements are associated with expression under specific conditions. We initially use PhyloNet to predict conserved motifs with instances in about half of the protein-coding genes. This initial first step was valuable as it recovered some known elements and cis-regulatory modules. Yet the results had a lot of redundant motifs and sites, and the approach was not efficiently scalable to the entire regulome of <italic>C. elegans</italic> or other higher-order eukaryotes. Magma: Multiple Aligner of Genomic Multiple Alignments) overcomes these shortcomings by using efficient clustering and memory management algorithms. Additionally, it implements a fast greedy set-cover solution to significantly reduce redundant motifs. These differences make Magma ~70 times faster than PhyloNet and Magma-based predictions occur near ~99% of all <italic>C. elegans</italic> protein-coding genes. Furthermore, we show tractable scaling for higher-order eukaryotes with larger regulomes. Finally, we demonstrate that a Magma-predicted motif, which represents the binding specificity for HLH-30, plays a critical role in the host-defense to pathogenic infections. This novel finding shows that <italic>hlh-30(-)<italic> animals are more susceptible to <italic>S. aureus</italic> and <italic>P. aeruginosa</italic> than their wild type counterparts.","abstract_html":"The aim of this dissertation is two-fold:: 1) To catalog all &lt;italic&gt;cis&lt;/italic&gt;-regulatory elements within the intergenic and intronic regions surrounding every gene in &lt;italic&gt;C.elegans&lt;/italic&gt;: i.e. the regulome) and: 2) to determine which cis-regulatory elements are associated with expression under specific conditions. We initially use PhyloNet to predict conserved motifs with instances in about half of the protein-coding genes. This initial first step was valuable as it recovered some known elements and cis-regulatory modules. Yet the results had a lot of redundant motifs and sites, and the approach was not efficiently scalable to the entire regulome of &lt;italic&gt;C. elegans&lt;/italic&gt; or other higher-order eukaryotes. Magma: Multiple Aligner of Genomic Multiple Alignments) overcomes these shortcomings by using efficient clustering and memory management algorithms. Additionally, it implements a fast greedy set-cover solution to significantly reduce redundant motifs. These differences make Magma ~70 times faster than PhyloNet and Magma-based predictions occur near ~99% of all &lt;italic&gt;C. elegans&lt;/italic&gt; protein-coding genes. Furthermore, we show tractable scaling for higher-order eukaryotes with larger regulomes. Finally, we demonstrate that a Magma-predicted motif, which represents the binding specificity for HLH-30, plays a critical role in the host-defense to pathogenic infections. This novel finding shows that &lt;italic&gt;hlh-30(-)&lt;italic&gt; animals are more susceptible to &lt;italic&gt;S. aureus&lt;/italic&gt; and &lt;italic&gt;P. aeruginosa&lt;/italic&gt; than their wild type counterparts.","abstract_has_math":false,"creators":["Ihuegbu, Nnamdi"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Biology and Biomedical Sciences: Computational and Systems Biology","degree_department":null,"school":null,"contributors":["Gary Stormo"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-01-01T08:00:00Z","date_published":"2011-01-01T08:00:00Z","updated_at":"2026-07-24T06:12:48Z","subjects":["Biology","Computer science","Genetics"],"languages":["English (en)"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.7936/K7M906NX"],"render_values":[{"text":"https://doi.org/10.7936/K7M906NX","href":"https://doi.org/10.7936/K7M906NX","code":true}]}]},"links":{"outbound_url":"https://openscholarship.wustl.edu/etd/591","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Gary Stormo"]},{"key":"dc:creator","label":"Author","values":["Ihuegbu, Nnamdi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2012-05-17T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biology and Biomedical Sciences: Computational and Systems Biology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biology","Computer science","Genetics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English (en)"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openscholarship.wustl.edu/etd/591"]},{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.7936/K7M906NX"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The aim of this dissertation is two-fold:: 1) To catalog all <italic>cis</italic>-regulatory elements within the intergenic and intronic regions surrounding every gene in <italic>C.elegans</italic>: i.e. the regulome) and: 2) to determine which cis-regulatory elements are associated with expression under specific conditions. We initially use PhyloNet to predict conserved motifs with instances in about half of the protein-coding genes. This initial first step was valuable as it recovered some known elements and cis-regulatory modules. Yet the results had a lot of redundant motifs and sites, and the approach was not efficiently scalable to the entire regulome of <italic>C. elegans</italic> or other higher-order eukaryotes. Magma: Multiple Aligner of Genomic Multiple Alignments) overcomes these shortcomings by using efficient clustering and memory management algorithms. Additionally, it implements a fast greedy set-cover solution to significantly reduce redundant motifs. These differences make Magma ~70 times faster than PhyloNet and Magma-based predictions occur near ~99% of all <italic>C. elegans</italic> protein-coding genes. Furthermore, we show tractable scaling for higher-order eukaryotes with larger regulomes. Finally, we demonstrate that a Magma-predicted motif, which represents the binding specificity for HLH-30, plays a critical role in the host-defense to pathogenic infections. This novel finding shows that <italic>hlh-30(-)<italic> animals are more susceptible to <italic>S. aureus</italic> and <italic>P. aeruginosa</italic> than their wild type counterparts."]},{"key":"dc:title","label":"Title","values":["Discovering Conserved cis-Regulatory Elements That Regulate Expression in Caenorhabditis elegans"]}]}],"canonical_facts":{"dc:contributor":["Gary Stormo"],"dc:creator":["Ihuegbu, Nnamdi"],"dc:date.available":["2012-05-17T07:00:00Z"],"dc:description.abstract":["The aim of this dissertation is two-fold:: 1) To catalog all <italic>cis</italic>-regulatory elements within the intergenic and intronic regions surrounding every gene in <italic>C.elegans</italic>: i.e. the regulome) and: 2) to determine which cis-regulatory elements are associated with expression under specific conditions. We initially use PhyloNet to predict conserved motifs with instances in about half of the protein-coding genes. This initial first step was valuable as it recovered some known elements and cis-regulatory modules. Yet the results had a lot of redundant motifs and sites, and the approach was not efficiently scalable to the entire regulome of <italic>C. elegans</italic> or other higher-order eukaryotes. Magma: Multiple Aligner of Genomic Multiple Alignments) overcomes these shortcomings by using efficient clustering and memory management algorithms. Additionally, it implements a fast greedy set-cover solution to significantly reduce redundant motifs. These differences make Magma ~70 times faster than PhyloNet and Magma-based predictions occur near ~99% of all <italic>C. elegans</italic> protein-coding genes. Furthermore, we show tractable scaling for higher-order eukaryotes with larger regulomes. Finally, we demonstrate that a Magma-predicted motif, which represents the binding specificity for HLH-30, plays a critical role in the host-defense to pathogenic infections. This novel finding shows that <italic>hlh-30(-)<italic> animals are more susceptible to <italic>S. aureus</italic> and <italic>P. aeruginosa</italic> than their wild type counterparts."],"dc:identifier":["https://openscholarship.wustl.edu/etd/591"],"dc:identifier.doi":["https://doi.org/10.7936/K7M906NX"],"dc:language":["English (en)"],"dc:subject":["Biology","Computer science","Genetics"],"dc:title":["Discovering Conserved cis-Regulatory Elements That Regulate Expression in Caenorhabditis elegans"],"thesis:degree_discipline":["Biology and Biomedical Sciences: Computational and Systems Biology"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T06:12:48Z"}