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Structural Calibration of the Rates of Amino Acid Evolution in a Search for Darwin in Drifting Biological Systems
Author(s) -
Christina Toft,
Mario A. Fares
Publication year - 2010
Publication title -
molecular biology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.637
H-Index - 218
eISSN - 1537-1719
pISSN - 0737-4038
DOI - 10.1093/molbev/msq123
Subject(s) - evolvability , biology , amino acid , selection (genetic algorithm) , neutral mutation , evolutionary biology , neutral theory of molecular evolution , molecular evolution , genetic drift , mutation rate , genetics , computational biology , genetic code , phylogenetics , genetic variation , gene , machine learning , computer science
In the last two decades, many reports of proteins under positive selection have brought the neutral theory into question. However, the methods used to detect selection have ignored the evolvability of amino acids within proteins, which is fundamental to distinguishing positive selection from the relaxed constraints caused by genetic drift. Disentangling these two counterbalancing forces is essential to test the neutral theory. Here, we calibrate rates of amino acid divergence by using structural information from the full set of crystallized proteins in bacteria. In agreement with previous reports, we show that rates of amino acid evolution correlate negatively with the number of per-amino acid atomic interactions. Calibration of the rates of evolution allows identifying signatures of selection in biological systems that evolve under strong genetic drift, such as endosymbiotic bacteria. Application of this method identifies different rates and dynamics of evolution for highly connected amino acids in the structure compared with sparsely connected ones. We also unearth patterns of Darwinian selection in fundamental cellular proteins in endosymbiotic bacteria including the cochaperonin GroES, ribosomal proteins, proteins involved in cell cycle control, DNA-binding proteins, and proteins involved in DNA replication and repair. This is, to our knowledge, the first attempt to distinguish adaptive evolution from relaxed constraints in biological systems under genetic drift.

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