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Genome Res. 2012 Apr;22(4):755-65. doi: 10.1101/gr.123901.111. Epub 2012 Jan 23.

Unified modeling of gene duplication, loss, and coalescence using a locus tree.

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  • 1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.

Abstract

Gene phylogenies provide a rich source of information about the way evolution shapes genomes, populations, and phenotypes. In addition to substitutions, evolutionary events such as gene duplication and loss (as well as horizontal transfer) play a major role in gene evolution, and many phylogenetic models have been developed in order to reconstruct and study these events. However, these models typically make the simplifying assumption that population-related effects such as incomplete lineage sorting (ILS) are negligible. While this assumption may have been reasonable in some settings, it has become increasingly problematic as increased genome sequencing has led to denser phylogenies, where effects such as ILS are more prominent. To address this challenge, we present a new probabilistic model, DLCoal, that defines gene duplication and loss in a population setting, such that coalescence and ILS can be directly addressed. Interestingly, this model implies that in addition to the usual gene tree and species tree, there exists a third tree, the locus tree, which will likely have many applications. Using this model, we develop the first general reconciliation method that accurately infers gene duplications and losses in the presence of ILS, and we show its improved inference of orthologs, paralogs, duplications, and losses for a variety of clades, including flies, fungi, and primates. Also, our simulations show that gene duplications increase the frequency of ILS, further illustrating the importance of a joint model. Going forward, we believe that this unified model can offer insights to questions in both phylogenetics and population genetics.

PMID:
22271778
[PubMed - indexed for MEDLINE]
PMCID:
PMC3317157
Free PMC Article
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