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New computational methods reveal tRNA identity element divergence between Proteobacteria and Cyanobacteria
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
2007 (English)In: Biochimie, ISSN 0300-9084, E-ISSN 1638-6183, Vol. 89, no 10, 1276-1288 p.Article in journal (Refereed) Published
Abstract [en]

There are at least 21 subfunctional classes of tRNAs in most cells that, despite a very highly conserved and compact common structure, must interact specifically with different cliques of proteins or cause grave organismal consequences. Protein recognition of specific tRNA substrates is achieved in part through class-restricted tRNA features called tRNA identity determinants. In earlier work we used TFAM, a statistical classifier of tRNA function, to show evidence of unexpectedly large diversity among bacteria in tRNA identity determinants. We also created a data reduction technique called function logos to visualize identity determinants for a given taxon. Here we show evidence that determinants for lysylated isoleucine tRNAs are not the same in Proteobacteria as in other bacterial groups including the Cyanobacteria. Consistent with this, the lysylating biosynthetic enzyme TilS lacks a C-terminal domain in Cyanobacteria that is present in Proteobacteria. We present here, using function logos, a map estimating all potential identity determinants generally operational in Cyanobacteria and Proteobacteria. To further isolate the differences in potential tRNA identity determinants between Proteobacteria and Cyanobacteria, we created two new data reduction visualizations to contrast sequence and function logos between two taxa. One, called Information Difference logos (ID logos), shows the evolutionary gain or retention of functional information associated to features in one lineage. The other, Kullback–Leibler divergence Difference logos (KLD logos), shows recruitments or shifts in the functional associations of features, especially those informative in both lineages. We used these new logos to specifically isolate and visualize the differences in potential tRNA identity determinants between Proteobacteria and Cyanobacteria. Our graphical results point to numerous differences in potential tRNA identity determinants between these groups. Although more differences in general are explained by shifts in functional association rather than gains or losses, the apparent identity differences in lysylated isoleucine tRNAs appear to have evolved through both mechanisms.

Place, publisher, year, edition, pages
2007. Vol. 89, no 10, 1276-1288 p.
Keyword [en]
tRNA identity, Function logos, tRNA identity determinants, Lysylated isoleucine tRNA, TilS, Aminoacyl-tRNA synthetase, Proteobacteria, Cyanobacteria, Kullback–Leibler Divergence
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:uu:diva-96429DOI: 10.1016/j.biochi.2007.07.013ISI: 000250613600015PubMedID: 17889982OAI: oai:DiVA.org:uu-96429DiVA: diva2:170998
Available from: 2007-11-13 Created: 2007-11-13 Last updated: 2017-12-14Bibliographically approved
In thesis
1. A Study in RNA Bioinformatics: Identification, Prediction and Analysis
Open this publication in new window or tab >>A Study in RNA Bioinformatics: Identification, Prediction and Analysis
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Research in the last few decades has revealed the great capacity of the RNA molecule. RNA, which previously was assumed to play a main role only as an intermediate in the translation of genes to proteins, is today known to play many important roles in the cell in addition to that as a messenger RNA and transfer RNA, including the ability to catalyze reactions and gene regulations at various levels.

This thesis investigates several computational aspects of RNA. We will discuss identification of novel RNAs and RNAs that are known to exist in related species, RNA secondary structure prediction, as well as more general tools for analyzing, visualizing and classifying RNA sequences.

We present two benchmark studies concerning RNA identification, both de novo identification/characterization of single RNA sequences and homology search methods.

We develope a novel algorithm for analysis of the RNA folding landscape that is based on the nearest neighbor energy model adopted in many secondary structure prediction programs. We implement this algorithm, which computes structural neighbors of a given RNA secondary structure, in the program RNAbor, which is accessible on a web server.

Furthermore, we combine a mutual information based structure prediction algorithm with a sequence logo visualization to create a novel visualization tool for analyzing an RNA alignment and identifying covarying sites.

Finally, we present extensions to sequence logos for the purpose of tRNA identity analysis. We introduce function logos, which display features that distinguish functional subclasses within a large set of structurally related sequences, as well as the inverse logos, which display underrepresented features. For the purpose of comparing tRNA identity elements between different taxa we introduce two contrasting logos, the information difference and the Kullback-Leibler divergence difference logos.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2007. 75 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 364
Keyword
RNA, bioinformatics, secondary structure, structure prediction, dynamic programming, energy landscape, homology search, sequence logo, tRNA
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:uu:diva-8305 (URN)978-91-554-7019-7 (ISBN)
Public defence
2007-12-07, B42, BMC, Husargatan 3, Uppsala, 13:00
Opponent
Supervisors
Available from: 2007-11-13 Created: 2007-11-13Bibliographically approved

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Freyhult, EvaNilsson, Olle

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