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A computational screen for site selective A-to-I editing detects novel sites in neuron specific Hu proteins
Department of Molecular Biology and Functional Genomics, Stockholm University.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
Department of Molecular Biology and Functional Genomics, Stockholm University.
Department of Computer Science, Duke University, Durham, United States.
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2010 (English)In: BMC Bioinformatics, ISSN 1471-2105, Vol. 11Article in journal (Refereed) Published
Abstract [en]

Background: Several bioinformatic approaches have previously been used to find novel sites of ADAR mediated A-to-I RNA editing in human. These studies have discovered thousands of genes that are hyper-edited in their non-coding intronic regions, especially in alu retrotransposable elements, but very few substrates that are site-selectively edited in coding regions. Known RNA edited substrates suggest, however, that site selective A-to-I editing is particularly important for normal brain development in mammals. Results: We have compiled a screen that enables the identification of new sites of site-selective editing, primarily in coding sequences. To avoid hyper-edited repeat regions, we applied our screen to the alu-free mouse genome. Focusing on the mouse also facilitated better experimental verification. To identify candidate sites of RNA editing, we first performed an explorative screen based on RNA structure and genomic sequence conservation. We further evaluated the results of the explorative screen by determining which transcripts were enriched for A-G mismatches between the genomic template and the expressed sequence since the editing product, inosine (I), is read as guanosine (G) by the translational machinery. For expressed sequences, we only considered coding regions to focus entirely on re-coding events. Lastly, we refined the results from the explorative screen using a novel scoring scheme based on characteristics for known A-to-I edited sites. The extent of editing in the final candidate genes was verified using total RNA from mouse brain and 454 sequencing. Conclusions: Using this method, we identified and confirmed efficient editing at one site in the Gabra3 gene. Editing was also verified at several other novel sites within candidates predicted to be edited. Five of these sites are situated in genes coding for the neuron-specific RNA binding proteins HuB and HuD.

Place, publisher, year, edition, pages
2010. Vol. 11
Keyword [en]
double-stranded-rna, pre-messenger-rna, adenosine deamination, snp, database, identification, adar1, gene, sequences, mouse, information
National Category
Bioinformatics and Systems Biology
URN: urn:nbn:se:kth:diva-19281DOI: 10.1186/1471-2105-11-6ISI: 000275198500001ScopusID: 2-s2.0-77649109065OAI: diva2:337328
Swedish Research Council
QC 20100525Available from: 2010-08-05 Created: 2010-08-05 Last updated: 2011-01-21Bibliographically approved
In thesis
1. Taking advantage of phylogenetic trees in comparative genomics
Open this publication in new window or tab >>Taking advantage of phylogenetic trees in comparative genomics
2008 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

Phylogenomics can be regarded as evolution and genomics in co-operation. Various kinds of evolutionary studies, gene family analysis among them, demand access to genome-scale datasets. But it is also clear that many genomics studies, such as assignment of gene function, are much improved by evolutionary analysis. The work leading to this thesis is a contribution to the phylogenomics field. We have used phylogenetic relationships between species in genome-scale searches for two intriguing genomic features, namely and A-to-I RNA editing. In the first case we used pairwise species comparisons, specifically human-mouse and human-chimpanzee, to infer existence of functional mammalian pseudogenes. In the second case we profited upon later years' rapid growth of the number of sequenced genomes, and used 17-species multiple sequence alignments. In both these studies we have used non-genomic data, gene expression data and synteny relations among these, to verify predictions. In the A-to-I editing project we used 454 sequencing for experimental verification.

We have further contributed a maximum a posteriori (MAP) method for fast and accurate dating analysis of speciations and other evolutionary events. This work follows recent years' trend of leaving the strict molecular clock when performing phylogenetic inference. We discretised the time interval from the leaves to the root in the tree, and used a dynamic programming (DP) algorithm to optimally factorise branch lengths into substitution rates and divergence times. We analysed two biological datasets and compared our results with recent MCMC-based methodologies. The dating point estimates that our method delivers were found to be of high quality while the gain in speed was dramatic.

Finally we applied the DP strategy in a new setting. This time we used a grid laid out on a species tree instead of on an interval. The discretisation gives together with speciation times a common timeframe for a gene tree and the corresponding species tree. This is the key to integration of the sequence evolution process and the gene evolution process. Out of several potential application areas we chose gene tree reconstruction. We performed genome-wide analysis of yeast gene families and found that our methodology performs very well.

Place, publisher, year, edition, pages
Stockholm: KTH, 2008. 53 p.
Trita-CSC-A, ISSN 1653-5723 ; 2008:09
Computer Science
National Category
Bioinformatics (Computational Biology)
urn:nbn:se:kth:diva-4757 (URN)978-91-7178-987-7 (ISBN)
Public defence
2008-06-04, FD05, Albanova, Roslagstullsbacken 21, Stockholm, 09:30
QC 20100923Available from: 2008-05-16 Created: 2008-05-16 Last updated: 2010-09-23Bibliographically approved

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