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Book Summary:
Human DNA consists of a large number of repeat sequences. The repeat sequences can be in the form of tandem repeats and interspersed repeats and cover more than 60% of the human genome sequence. Segmental repeats are a result of duplication events that have occurred during the evolution of human genome. This dissertation presents an algorithmic and computational study of the repeat sequences with emphasis on the identification of the location and order of duplication events as well as the identification of the responsible cellular mechanisms. A complementary goal of this work is to study the effect of the repeat sequences to gene regulation. Thus it provides a comprehensive study of the evolution and function of repeat sequences in the human genome. The primary example of tandem repeat sequences in the human genome are the centromeric alpha-satellite DNA that consists of arbitrary monomer pairs of size approximately 171bp. Although it is possible that alpha-satellite sequences developed as a result of subsequent unequal crossovers only, no formal computational framework had been developed to verify this possibility. This thesis includes such a framework and reports on experiments which imply that pericentromeric alpha-satellite segments are evolutionarily distinct from the higher-order repeat segments. Certain repeat sequences are not only interesting for evolutionary studies but also have essential functional properties. Recent studies demonstrate the existence of special antisense RNAs used in post-transcriptional gene regulation through binding with duplicate target sequences in the mRNA. These RNAs are known to be synthesized naturally to control gene expression in C. elegans, Drosophila and other organisms, or regulate plasmid copy numbers in E. coli; they have also been artificially constructed to knock-out genes of interest in humans and other organisms in order to find out their functions as well as for other purposes. Several computational methods can be used to predict the secondary structure of a single RNA molecule, but no such algorithm exists for reliably predicting the joint secondary structure of two interacting RNA molecules, or measuring the stability of such a joint structure. This dissertation presents a combinatorial approach for solving the RNA-RNA interaction prediction problem between an antisense RNA and its target mRNA. Three main models for joint structure prediction are introduced, and the proposed methods are applied to discover targets for any given antisense RNA in whole genomic and plasmid sequences. |
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