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A Hybrid Micro–Macroevolutionary Approach to Gene Tree Reconstruction

A Hybrid Micro–Macroevolutionary Approach to Gene Tree Reconstruction Gene family evolution is determined by microevolutionary processes (e.g., point mutations) and macroevo- lutionary processes (e.g., gene duplication and loss), yet macroevolutionary considerations are rarely incor- porated into gene phylogeny reconstruction methods. We present a dynamic program to find the most parsi- monious gene family tree with respect to a macroevolutionary optimization criterion, the weighted sum of the number of gene duplications and losses. The existence of a polynomial delay algorithm for duplication/loss phylogeny reconstruction stands in contrast to most formulations of phylogeny reconstruction, which are NP-complete. We next extend this result to obtain a two-phase method for gene tree reconstruction that takes both micro- and macroevolution into account. In the first phase, a gene tree is constructed from sequence data, using any of the previously known algorithms for gene phylogeny construction. In the second phase, the tree is refined by rearranging regions of the tree that do not have strong support in the sequence data to minimize the duplication/lost cost. Components of the tree with strong support are left intact. This hybrid approach incorporates both micro- and macroevolutionary considerations, yet its computational requirements are modest in practice because the two phase approach constrains the search space. Our hybrid http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Computational Biology Unpaywall

A Hybrid Micro–Macroevolutionary Approach to Gene Tree Reconstruction

Durand, Dannie; Halldórsson, Bjarni V.; Vernot, Benjamin
Journal of Computational Biology – Mar 1, 2006
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Publisher
Unpaywall
ISSN
1066-5277
DOI
10.1089/cmb.2006.13.320
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Abstract

Gene family evolution is determined by microevolutionary processes (e.g., point mutations) and macroevo- lutionary processes (e.g., gene duplication and loss), yet macroevolutionary considerations are rarely incor- porated into gene phylogeny reconstruction methods. We present a dynamic program to find the most parsi- monious gene family tree with respect to a macroevolutionary optimization criterion, the weighted sum of the number of gene duplications and losses. The existence of a polynomial delay algorithm for duplication/loss phylogeny reconstruction stands in contrast to most formulations of phylogeny reconstruction, which are NP-complete. We next extend this result to obtain a two-phase method for gene tree reconstruction that takes both micro- and macroevolution into account. In the first phase, a gene tree is constructed from sequence data, using any of the previously known algorithms for gene phylogeny construction. In the second phase, the tree is refined by rearranging regions of the tree that do not have strong support in the sequence data to minimize the duplication/lost cost. Components of the tree with strong support are left intact. This hybrid approach incorporates both micro- and macroevolutionary considerations, yet its computational requirements are modest in practice because the two phase approach constrains the search space. Our hybrid

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Journal of Computational Biology – Unpaywall

Published: Mar 1, 2006

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