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Covariation of Branch Lengths in Phylogenies of Functionally Related Genes

Overview of attention for article published in PLOS ONE, December 2009
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Title
Covariation of Branch Lengths in Phylogenies of Functionally Related Genes
Published in
PLOS ONE, December 2009
DOI 10.1371/journal.pone.0008487
Pubmed ID
Authors

Wai Lok Sibon Li, Allen G. Rodrigo

Abstract

Recent studies have shown evidence for the coevolution of functionally-related genes. This coevolution is a result of constraints to maintain functional relationships between interacting proteins. The studies have focused on the correlation in gene tree branch lengths of proteins that are directly interacting with each other. We here hypothesize that the correlation in branch lengths is not limited only to proteins that directly interact, but also to proteins that operate within the same pathway. Using generalized linear models as a basis of identifying correlation, we attempted to predict the gene ontology (GO) terms of a gene based on its gene tree branch lengths. We applied our method to a dataset consisting of proteins from ten prokaryotic species. We found that the degree of accuracy to which we could predict the function of the proteins from their gene tree varied substantially with different GO terms. In particular, our model could accurately predict genes involved in translation and certain ribosomal activities with the area of the receiver-operator curve of up to 92%. Further analysis showed that the similarity between the trees of genes labeled with similar GO terms was not limited to genes that physically interacted, but also extended to genes functioning within the same pathway. We discuss the relevance of our findings as it relates to the use of phylogenetic methods in comparative genomics.

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Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 350%
Brazil 4 200%
Canada 3 150%
Australia 1 50%
Portugal 1 50%
United Kingdom 1 50%
Spain 1 50%
Argentina 1 50%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 750%
Student > Ph. D. Student 11 550%
Professor > Associate Professor 7 350%
Student > Master 6 300%
Student > Bachelor 5 250%
Other 13 650%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 1950%
Biochemistry, Genetics and Molecular Biology 6 300%
Computer Science 2 100%
Earth and Planetary Sciences 2 100%
Mathematics 1 50%
Other 4 200%