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Simultaneous Bayesian gene tree reconstruction and reconciliation analysis
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-5896-473X
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
2009 (English)In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 106, 5714-5719 p.Article in journal (Refereed) Published
Abstract [en]

We present GSR, a probabilistic model integrating gene duplication, sequence evolution, and a relaxed molecular clock for substitution rates, that enables genomewide analysis of gene families. The gene duplication and loss process is a major cause for incongruence between gene and species tree, and deterministic methods have been developed to explain such differences through tree reconciliations. Although probabilistic methods for phylogenetic inference have been around for decades, probabilistic reconciliation methods are far less established. Based on our model, we have implemented a Bayesian analysis tool, PrIME-GSR, for gene tree inference that takes a known species tree into account. Our implementation is sound and we demonstrate its utility for genomewide gene-family analysis by applying it to recently presented yeast data. We validate PrIME-GSR by comparing with previous analyses of these data that take advantage of gene order information. In a case study we apply our method to the ADH gene family and are able to draw biologically relevant conclusions concerning gene duplications creating key yeast phenotypes. On a higher level this shows the biological relevance of our method. The obtained results demonstrate the value of a relaxed molecular clock. Our good performance will extend to species where gene order conservation is insufficient.

Place, publisher, year, edition, pages
2009. Vol. 106, 5714-5719 p.
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-8465DOI: 10.1073/pnas.0806251106ISI: 000264967500048Scopus ID: 2-s2.0-65249107239OAI: oai:DiVA.org:kth-8465DiVA: diva2:13795
Note
Original title: Gene tree analysis reaching maturity QC 20100923Available from: 2008-05-16 Created: 2008-05-16 Last updated: 2011-09-13Bibliographically 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.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2008:09
Keyword
Computer Science
National Category
Bioinformatics (Computational Biology)
Identifiers
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
Opponent
Supervisors
Note
QC 20100923Available from: 2008-05-16 Created: 2008-05-16 Last updated: 2010-09-23Bibliographically approved

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