DNA sequence-specific recognition by transcriptional factors

dc.contributor.author Xu, Wu
dc.contributor.department Theses & dissertations (Interdisciplinary)
dc.date 2020-08-05T05:05:16.000
dc.date.accessioned 2021-02-26T08:45:36Z
dc.date.available 2021-02-26T08:45:36Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2003
dc.date.issued 2003-01-01
dc.description.abstract <p>The whole genome sequences from a wide variety of species including 599 viruses, and viroids, 205 naturally occurring plasmids, 185 organelles, 31 eubacteria, seven archaea, one fungus, two animals and one plant are available. 2000-3000 transcription factors out of approximate 30,000-40,000 genes in human genome, which play the central role in controlling cell development, cell growth and differentiation. Abnormal activity of transcriptional factors often leads to diseases. Elucidating the transcriptional regulatory network will be the next challenge of the post-genomic era. Gene regulation initiates from the selective binding of transcription factors to a particular DNA site out of a vast number of potential sites in the genome. It is unclear how transcription factors could specifically recognize the correct sites out of hundreds or thousands potential sites in the genome. We investigated the DNA recognition sites functionally mapped by biochemical and biophysically approaches and also transcription factor-DNA complexes solved by X-ray or NMR from Protein Data Bank. The purpose of this study is to find whether there is a simple code for transcription factor-DNA recognition. Our analyses show that (i) the length for DNA recognition sequences is typically from 4-10 bases; (ii) there is no GC or AT preference for our studied sequences; (iii) positively charged amino acids-Arg and Lys are found to be the majority of contacts with base and phosphate; (iv) some favored interaction pairs, Arg-G, Lys-G and Glu-C, are observed from our studies. However, no simple code for transcription factor-DNA recognition is obtained from our study. A relational database for storing and retrieving collected data is generated as an example to demonstrate the importance of database in computational biology.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/rtd/20093/
dc.identifier.articleid 21092
dc.identifier.contextkey 18791898
dc.identifier.doi https://doi.org/10.31274/rtd-20200803-416
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/20093
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/97460
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/rtd/20093/Xu_ISU_2003_X82.pdf|||Fri Jan 14 22:19:34 UTC 2022
dc.subject.keywords Biochemistry, biophysics, and molecular biology
dc.subject.keywords Bioinformatics and computational biology
dc.title DNA sequence-specific recognition by transcriptional factors
dc.type thesis
dc.type.genre thesis
dspace.entity.type Publication
thesis.degree.discipline Bioinformatics and Computational Biology
thesis.degree.level thesis
thesis.degree.name Master of Science
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