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Computational Analysis of the Evolution of Non-Coding Genomic Sequences

Posted on:2014-09-02Degree:M.S.B.SType:Thesis
University:The University of ToledoCandidate:Saha Mandal, ArnabFull Text:PDF
GTID:2450390005487383Subject:Biology
Abstract/Summary:
The precipitous drop in costs and increase in sequencing efficiency; with simultaneous development of annotation technologies have made way for the availability of numerous eukaryote whole genome sequences. The efficient use of such cornucopia of genomic data housed in several databases has also necessitated increased application of bioinformatic tools and amalgamation of several interdisciplinary studies. This thesis, constituted by three chapters, provides examples of such use of genomic data from three different perspectives. Firstly, a study of population genomes from more than a thousand people provided by the 1000 genomes consortium is conducted across genomic loci corresponding to four genes in different chromosomes. Genetic variants across population genomes were also examined in the light of biased gene conversion theory. Secondly, the profound non-randomness replete within the three billion nucleotides of human genome is also quantitatively characterized for arrangements of specific nucleotide patterns, which reflect on unknown signals critical for human genome organization. Thirdly, evolutionary studies on groups of more than 40,000 orthologous plant introns are conducted to reveal conserved sequence elements in non-coding DNA, which are in turn characterized and compared across animals. The functional significance of conserved regions of non-coding DNA is ascertained on a case by case basis. A novel putative tRNA-like sequence is also discovered in this process within five plant introns.
Keywords/Search Tags:Genomic, Non-coding
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