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Positively selected amino acid replacements within the RuBisCO enzyme of oak trees are associated with ecological adaptations

Lookup NU author(s): Dr Maxim KapralovORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2017 Hermida-Carrera et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Phylogenetic analysis by maximum likelihood (PAML) has become the standard approach to study positive selection at the molecular level, but other methods may provide complementary ways to identify amino acid replacements associated with particular conditions. Here, we compare results of the decision tree (DT) model method with ones of PAML using the key photosynthetic enzyme RuBisCO as a model system to study molecular adaptation to particular ecological conditions in oaks (Quercus). We sequenced the chloroplast rbcL gene encoding RuBisCO large subunit in 158 Quercus species, covering about a third of the global genus diversity. It has been hypothesized that RuBisCO has evolved differentially depending on the environmental conditions and leaf traits governing internal gas diffusion patterns. Here, we show, using PAML, that amino acid replacements at the residue positions 95, 145, 251, 262 and 328 of the RuBisCO large subunit have been the subject of positive selection along particular Quercus lineages associated with the leaf traits and climate characteristics. In parallel, the DT model identified amino acid replacements at sites 95, 219, 262 and 328 being associated with the leaf traits and climate characteristics, exhibiting partial overlap with the results obtained using PAML.


Publication metadata

Author(s): Hermida-Carrera C, Fares MA, Fernández A, Gil-Pelegrin E, Kapralov MV, Mir A, Molins A, Peguero-Pina JJ, Rocha J, Sancho-Knapik D, Galmes J

Publication type: Article

Publication status: Published

Journal: PLoS ONE

Year: 2017

Volume: 12

Issue: 8

Online publication date: 31/08/2017

Acceptance date: 15/08/2017

Date deposited: 24/10/2017

ISSN (print): 1932-6203

Publisher: Public Library of Science

URL: https://doi.org/10.1371/journal.pone.0183970

DOI: 10.1371/journal.pone.0183970


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