Journal Article

Comparative Analysis of Chromosome Counts Infers Three Paleopolyploidies in the Mollusca

Nathaniel M. Hallinan and David R. Lindberg

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 3, issue , pages 1150-1163
Published in print January 2011 |
Published online August 2011 | e-ISSN: 1759-6653 | DOI:

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  • Bioinformatics and Computational Biology
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The study of paleopolyploidies requires the comparison of multiple whole genome sequences. If the branches of a phylogeny on which a whole-genome duplication (WGD) occurred could be identified before genome sequencing, taxa could be selected that provided a better assessment of that genome duplication. Here, we describe a likelihood model in which the number of chromosomes in a genome evolves according to a Markov process with one rate of chromosome duplication and loss that is proportional to the number of chromosomes in the genome and another stochastic rate at which every chromosome in the genome could duplicate in a single event. We compare the maximum likelihoods of a model in which the genome duplication rate varies to one in which it is fixed at zero using the Akaike information criterion, to determine if a model with WGDs is a good fit for the data. Once it has been determined that the data does fit the WGD model, we infer the phylogenetic position of paleopolyploidies by calculating the posterior probability that a WGD occurred on each branch of the taxon tree. Here, we apply this model to a molluscan tree represented by 124 taxa and infer three putative WGD events. In the Gastropoda, we identify a single branch within the Hypsogastropoda and one of two branches at the base of the Stylommatophora. We also identify one or two branches near the base of the Cephalopoda.

Keywords: whole genome duplication; Mollusca evolution; birth–death process; karyotype evolution

Journal Article.  8693 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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