Maximum Likelihood Estimation of Fitness Components in Experimental Evolution.
experimental evolution
fitness
maximum likelihood
natural selection
time series data
Journal
Genetics
ISSN: 1943-2631
Titre abrégé: Genetics
Pays: United States
ID NLM: 0374636
Informations de publication
Date de publication:
03 2019
03 2019
Historique:
received:
20
12
2018
accepted:
15
01
2019
pubmed:
27
1
2019
medline:
29
3
2019
entrez:
26
1
2019
Statut:
ppublish
Résumé
Estimating fitness differences between allelic variants is a central goal of experimental evolution. Current methods for inferring such differences from allele frequency time series typically assume that the effects of selection can be described by a fixed selection coefficient. However, fitness is an aggregate of several components including mating success, fecundity, and viability. Distinguishing between these components could be critical in many scenarios. Here, we develop a flexible maximum likelihood framework that can disentangle different components of fitness from genotype frequency data, and estimate them individually in males and females. As a proof-of-principle, we apply our method to experimentally evolved cage populations of
Identifiants
pubmed: 30679262
pii: genetics.118.301893
doi: 10.1534/genetics.118.301893
pmc: PMC6404243
doi:
Substances chimiques
Drosophila Proteins
0
y protein, Drosophila
0
Banques de données
figshare
['10.25386/genetics.7616171']
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1005-1017Subventions
Organisme : NIAID NIH HHS
ID : F32 AI138476
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM127418
Pays : United States
Organisme : NIAID NIH HHS
ID : R21 AI130635
Pays : United States
Organisme : Austrian Science Fund FWF
ID : W 1225
Pays : Austria
Informations de copyright
Copyright © 2019 by the Genetics Society of America.
Références
Genetics. 1999 Jun;152(2):755-61
pubmed: 10353915
J Neurobiol. 2003 Apr;55(1):53-72
pubmed: 12605459
Genetics. 2006 Feb;172(2):1009-30
pubmed: 16272418
Genetics. 2008 May;179(1):497-502
pubmed: 18493066
Mol Biol Evol. 2012 Apr;29(4):1187-97
pubmed: 22114362
Genetics. 2012 Oct;192(2):599-607
pubmed: 22851647
Genetics. 2013 Mar;193(3):973-84
pubmed: 23307902
Genetics. 2013 Aug;194(4):1029-35
pubmed: 23709638
Genetics. 2014 Feb;196(2):509-22
pubmed: 24318534
J Genet. 2013 Dec;92(3):349-61
pubmed: 24371158
Genetics. 2014 Apr;196(4):961-71
pubmed: 24478335
Mol Ecol Resour. 2015 Jan;15(1):87-98
pubmed: 24834845
Genetics. 2014 Nov;198(3):1237-50
pubmed: 25213172
Ann Appl Stat. 2014 Dec;8(4):2203-2222
pubmed: 25598858
Evolution. 2015 May;69(5):1101-12
pubmed: 25790030
PLoS Genet. 2015 Apr 07;11(4):e1005069
pubmed: 25849855
Mol Ecol. 2016 Jan;25(1):121-34
pubmed: 26184577
Genetics. 2015 Oct;201(2):425-31
pubmed: 26232409
G3 (Bethesda). 2016 Apr 07;6(4):893-904
pubmed: 26869618
Nat Rev Genet. 2016 Mar;17(3):146-59
pubmed: 26875679
Genetics. 2016 May;203(1):493-511
pubmed: 27010022
Genetics. 2016 Jun;203(2):831-46
pubmed: 27038112
Evolution. 1981 Jan;35(1):11-20
pubmed: 28563465
PLoS Genet. 2017 Jul 20;13(7):e1006796
pubmed: 28727785
Proc Natl Acad Sci U S A. 2018 May 22;115(21):5522-5527
pubmed: 29735716
Genetics. 1974 Dec;78(4):1195-208
pubmed: 4218182
Genetics. 1972 Jul;71(3):439-60
pubmed: 4624921
Theor Popul Biol. 1973 Dec;4(4):425-45
pubmed: 4779108
Heredity (Edinb). 1981 Jun;46(3):321-46
pubmed: 6792162
Heredity (Edinb). 1981 Jun;46(3):347-77
pubmed: 6792163
Behav Genet. 1976 Apr;6(2):141-3
pubmed: 817705
Genet Res. 1976 Aug;28(1):75-88
pubmed: 827464