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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/19021

Title: The de novo Prediction of Functionally Significant Sequence Motifs in Arabidopsis thaliana.
Authors: Austin, Ryan
Advisor: Provart, Nicholas
Department: Cell and Systems Biology
Keywords: arabidopsis
transcription
cis elements
regulatory sequences
c-terminus
bioinformatics
genomics
microarray
motif
abiotic stress
tissue-specific
transcription factor binding site
Issue Date: 18-Feb-2010
Abstract: This thesis performs de novo predictions for functionally significant sequence motifs in the Arabidopsis genome under two separate contexts. Each study applies the use of genomic positional information, statistical over-representation and several biologically contextual filters to maximize the visibility of biological signal in prediction results. Numerous literature supported motifs are prevalent in the results of both studies and a number of novel motif patterns possess a strong potential for in planta significance. The first study examines the statistical over-representation of C-terminal tripeptides as a means for identifying eukaryotic conserved protein targetting signatures. Comparative genomics is applied to the analysis of tripeptide frequencies in the C-terminus of 7 eukaryotic proteomes. While biological signal is maximized through the filtering of both simple sequences and homologous sequences present across protein families. The second study introduces a methodology for the effective prediction of transcription factor binding sites in Arabidopsis. A collection of motif prediction algorithms and a novel enumerative strategy are applied to the prediction of cis-acting regulatory elements within the promoters of genes found coexpressed within distinct tissues and under specific abiotic stress treatments. Overall, the analysis identifies 4 known motifs in expected contexts, 5 known motifs in novel contexts and 7 novel motifs with a high potential for biological function.
URI: http://hdl.handle.net/1807/19021
Appears in Collections:Doctoral
Department of Cell and Systems Biology - Doctoral theses

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