Literature DB >> 24784136

Novel population genetics in ciliates due to life cycle and nuclear dimorphism.

David W Morgens1, Timothy C Stutz1, Andre R O Cavalcanti2.   

Abstract

Our understanding of population genetics comes primarily from studies of organisms with canonical life cycles and nuclear organization, either haploid or diploid, sexual, or asexual. Although this template yields satisfactory results for the study of animals and plants, the wide variety of genomic organizations and life cycles of unicellular eukaryotes can make these organisms behave differently in response to mutation, selection, and drift than predicted by traditional population genetic models. In this study, we show how each of these unique features of ciliates affects their evolutionary parameters in mutation-selection, selection-drift, and mutation-selection-drift situations. In general, ciliates are less efficient in eliminating deleterious mutations-these mutations linger longer and at higher frequencies in ciliate populations than in sexual populations--and more efficient in selecting beneficial mutations. Approaching this problem via analytical techniques and simulation allows us to make specific predictions about the nature of ciliate evolution, and we discuss the implications of these results with respect to the high levels of polymorphism and high rate of protein evolution reported for ciliates.
© The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Keywords:  mutation–selection balance; mutation–selection–drift; segregation times; selection–drift

Mesh:

Year:  2014        PMID: 24784136     DOI: 10.1093/molbev/msu150

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  1 in total

1.  Hidden genetic variation in the germline genome of Tetrahymena thermophila.

Authors:  K L Dimond; R A Zufall
Journal:  J Evol Biol       Date:  2016-04-18       Impact factor: 2.411

  1 in total

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