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Towards the automation of feature recognition in DNA sequence

University of British Columbia

Computational molecular biology encompasses the analysis of nucleic acid sequences for patterns or information that correlate with gene structure and function. It is a goal of such sequence analysis to be able to “read” a sequence and interpret its meaning automatically, as in the translation of a language. This DNA language is composed of many overlapping codes, some of which are reasonably well-understood, while others remain to be discovered. The challenge is to extract as much information as possible from the sequence data available, although there are limitations to our knowledge of how the cell and its biological processes interpret the language. This dissertation examines progress made in the past five years in automatically identifying features ofDNA sequence, in particular the recognition of protein-coding regions and of common repetitive elements in human genomic DNA. In the course of this examination, two computer programs have been developed, SORF1ND for the automated recognition of coding exons, and REPFIND for recognition of common repeat elements. These programs are described in detail, and they are tested on defined datasets of human genes. An examination of a particular Alu repeat insert in two patients with Huntington disease has also lead to the discovery of a new Alu subfamily, the Sb2 Alu subfamily. The dissertation explores the relationship of this subfamily with others, and provides evidence for a model ofAlu element propagation involving multiple active source Alu genes. Experiments are described that support the existence of the new Alu subfamily in several primates, and an attempt is made to search for Alu element dimorphisms involving this subfamily.

Thesis/Dissertation

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2009-06-04

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http://hdl.handle.net/2429/8786

Genetics

University of British Columbia

UBCV

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