Abstract/Details

The statistical and molecular logic of gene expression patterns in <i>Caenorhabditis elegans</i>


2004 2004

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Abstract (summary)

Gene regulation uses transcriptional control systems with a molecular logic we seek to understand. Genome-scale sequence and expression data increasingly make it possible to use genomic patterns in sequences and gene expression levels to reveal the logic of transcriptional regulation. In this dissertation, two approaches to understanding transcriptional regulation are developed and applied. First, we describe a novel method for identifying phylogenetic conservation in genomic transcriptional patterns. We use this new approach to identify gene expression programs in aging, development, and mRNA degradation that are shared by organisms as diverse as the nematode Caenorhabiditis elegans, the fruit fly Drosophila melanogaster , the yeast Saccharomyces cerevisiae, and the human Homo sapiens. We use this approach to search databases of gene expression patterns to identify relationships among the physiological programs of diverse organisms. Second, we use a statistical approach, probabilistic segmentation, to identify candidate transcriptional control sequences in the promoters of a large gene family, the chemosensory receptor genes in C. elegans . We identify many new candidate transcriptional control sequences and show that one of these is a novel E-box motif that confers expression in the ADL chemosensory neurons.

Indexing (details)


Subject
Molecular biology;
Genetics
Classification
0307: Molecular biology
0369: Genetics
Identifier / keyword
Biological sciences; Aging; Chemosensory neurons; Transcriptional regulation; mRNA
Title
The statistical and molecular logic of gene expression patterns in <i>Caenorhabditis elegans</i>
Author
McCarroll, Steven Andrew
Number of pages
123
Publication year
2004
Degree date
2004
School code
0034
Source
DAI-B 66/01, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
0496937375, 9780496937370
Advisor
Bergmann, Cornelia I.
University/institution
University of California, San Francisco
University location
United States -- California
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3160437
ProQuest document ID
305202312
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/305202312
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