Identification of phenotypes in Caenorabhditis elegans on the basis of sequence similarity.

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dc.contributor.advisorBaker, Erich J.
dc.contributor.advisorLee, Myeongwoo.
dc.contributor.authorBatra, Sushil.
dc.contributor.departmentBiomedical Studies.en
dc.contributor.otherBaylor University. Institute of Biomedical Studies.en
dc.date.accessioned2009-06-02T17:59:06Z
dc.date.available2009-06-02T17:59:06Z
dc.date.copyright2009-05
dc.date.issued2009-06-02T17:59:06Z
dc.descriptionIncludes bibliographical references (p. 99-110).en
dc.description.abstractIn biomedical research, Caenorabhditis elegans is an ideal choice as experimental organism due to striking similarity with human genome and its distinct features such as short life span, small reproductive cycle, simple body plan, easily observable mutant phenotypes and ease of cultivation in laboratory. The 97 megabase genomic sequence of C. elegans comprises approximately 19,920 genes, of which about 2807 genes (14% of total genome) are uniquely associated with one or more RNAi phenotypes. The challenge to assign phenotypes to remaining 86% genes has incited development of new rapid techniques and computational tools. Objective of this project was to identify phenotypes in C. elegans on the basis of sequence similarity using bioinformatics techniques. To find similarity in genes, we used BLAST as computational tool and predicted the phenotypes. Bi-directional pair wise BLAST was performed on 2,807 unique genes (associated with known phenotypes) against 19,920 genes. As a result, 141 new genes (with unknown phenotype) were obtained which share high sequence similarity with known RNAi phenotype genes of 16 categories. In the present work, putative genes associated with two phenotypes, Ste (37 genes) and Unc (29 genes), were studied by RNA interference (RNAi) in laboratory. The outcome of these experiments assigned sterility phenotype to 8 new genes and uncoordinated phenotype to 12 new genes which were not linked with any phenotype in previous studies. These observations were further verified by silencing the response using reverse transcriptase polymerase chain reaction (RT-PCR) for Ste genes. Thus, bioinformatics techniques were successfully utilized in identification of phenotypes on the basis of sequence similarity with a relatively high success rate of 22% and 41% for sterility and uncoordinated phenotypes respectively. High success rate of this bioinformatics technique will allow researchers to focus their efforts on identifying particular phenotypes of interest and understanding various biological processes and elucidating the pathogenesis of diseases.en
dc.description.degreePh.D.en
dc.description.statementofresponsibilityby Sushil Batra.en
dc.format.extentxiii, 110 p. : ill.en
dc.format.extent170881 bytes
dc.format.extent758123 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2104/5325
dc.language.isoen_USen
dc.rightsBaylor University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact librarywebmaster@baylor.edu for inquiries about permission.en
dc.rights.accessrightsWorldwide accessen
dc.subjectCaenorabhditis elegans.en
dc.subjectPhenotype.en
dc.subjectSmall interfering RNA.en
dc.subjectGenomes.en
dc.subjectBLAST (Electonic resource)en
dc.subjectSequential analysis.en
dc.subjectBioinformatics.en
dc.titleIdentification of phenotypes in Caenorabhditis elegans on the basis of sequence similarity.en
dc.typeThesisen

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