Drivers of Mating Type Composition in Tetrahymena thermophila.


Journal

Genome biology and evolution
ISSN: 1759-6653
Titre abrégé: Genome Biol Evol
Pays: England
ID NLM: 101509707

Informations de publication

Date de publication:
06 12 2020
Historique:
accepted: 15 09 2020
pubmed: 19 9 2020
medline: 6 10 2021
entrez: 18 9 2020
Statut: ppublish

Résumé

Sex offers advantages even in primarily asexual species. Some ciliates appear to utilize such reproductive strategy with many mating types. However, the factors determining the composition of mating types in the unicellular ciliate Tetrahymena thermophila are poorly understood, and this is further complicated by non-Mendelian determination of mating type in the offspring. We therefore developed a novel population genetics model to predict how various factors influence the dynamics of mating type composition, including natural selection. The model predicted either the coexistence of all seven mating types or fixation of a single mating type in a population, depending on parameter combinations, irrespective of natural selection. To understand what factor(s) may be more influential and to test the validity of theoretical prediction, five replicate populations were maintained in laboratory such that several factors could be controlled or measured. Whole-genome sequencing was used to identify newly arising mutations and determine mating type composition. Strikingly, all populations were found to be driven by strong selection on newly arising beneficial mutations to fixation of their carrying mating types, and the trajectories of speed to fixation agreed well with our theoretical predictions. This study illustrates the evolutionary strategies that T. thermophila can utilize to optimize population fitness.

Identifiants

pubmed: 32946549
pii: 5908519
doi: 10.1093/gbe/evaa197
pmc: PMC7846192
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

2328-2343

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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Auteurs

Guangying Wang (G)

Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei, China.
University of Chinese Academy of Sciences, Beijing, China.

Kai Chen (K)

Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei, China.
University of Chinese Academy of Sciences, Beijing, China.

Jing Zhang (J)

Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei, China.
University of Chinese Academy of Sciences, Beijing, China.

Shanjun Deng (S)

State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China.

Jie Xiong (J)

Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei, China.

Xionglei He (X)

State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China.

Yunxin Fu (Y)

Laboratory for Conservation and Utilization of Bioresources, Yunnan University, Kunming, China.
Department of Biostatistics and Data Science and Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston.

Wei Miao (W)

Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei, China.
University of Chinese Academy of Sciences, Beijing, China.
CAS Center for Excellence in Animal Evolution and Genetics, Kunming, China.

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