Literature DB >> 18780742

F(ST) and Q(ST) under neutrality.

Judith R Miller1, Bryan P Wood, Matthew B Hamilton.   

Abstract

A commonly used test for natural selection has been to compare population differentiation for neutral molecular loci estimated by F(ST) and for the additive genetic component of quantitative traits estimated by Q(ST). Past analytical and empirical studies have led to the conclusion that when averaged over replicate evolutionary histories, Q(ST) = F(ST) under neutrality. We used analytical and simulation techniques to study the impact of stochastic fluctuation among replicate outcomes of an evolutionary process, or the evolutionary variance, of Q(ST) and F(ST) for a neutral quantitative trait determined by n unlinked diallelic loci with additive gene action. We studied analytical models of two scenarios. In one, a pair of demes has recently been formed through subdivision of a panmictic population; in the other, a pair of demes has been evolving in allopatry for a long time. A rigorous analysis of these two models showed that in general, it is not necessarily true that mean Q(ST) = F(ST) (across evolutionary replicates) for a neutral, additive quantitative trait. In addition, we used finite-island model simulations to show there is a strong positive correlation between Q(ST) and the difference Q(ST) - F(ST) because the evolutionary variance of Q(ST) is much larger than that of F(ST). If traits with relatively large Q(ST) values are preferentially sampled for study, the difference between Q(ST) and F(ST) will also be large and positive because of this correlation. Many recent studies have used tests of the null hypothesis Q(ST) = F(ST) to identify diversifying or uniform selection among subpopulations for quantitative traits. Our findings suggest that the distributions of Q(ST) and F(ST) under the null hypothesis of neutrality will depend on species-specific biology such as the number of subpopulations and the history of subpopulation divergence. In addition, the manner in which researchers select quantitative traits for study may introduce bias into the tests. As a result, researchers must be cautious before concluding that selection is occurring when Q(ST) not equal F(ST).

Mesh:

Year:  2008        PMID: 18780742      PMCID: PMC2567353          DOI: 10.1534/genetics.108.092031

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  23 in total

1.  Genetic variability at neutral markers, quantitative trait land trait in a subdivided population under selection.

Authors:  Valérie Le Corre; Antoine Kremer
Journal:  Genetics       Date:  2003-07       Impact factor: 4.562

2.  Experimental demonstration of a causal relationship between heterogeneity of selection and genetic differentiation in quantitative traits.

Authors:  Emmanuelle Porcher; Tatiana Giraud; Isabelle Goldringer; Claire Lavigne
Journal:  Evolution       Date:  2004-07       Impact factor: 3.694

3.  The genetical structure of populations.

Authors:  S WRIGHT
Journal:  Ann Eugen       Date:  1951-03

4.  Molecular and quantitative genetic divergence among populations of house mice with known evolutionary histories.

Authors:  T J Morgan; M A Evans; T Garland; J G Swallow; P A Carter
Journal:  Heredity (Edinb)       Date:  2005-05       Impact factor: 3.821

5.  Genetic differentiation of neutral markers and quantitative traits in predominantly selfing metapopulations: confronting theory and experiments with Arabidopsis thaliana.

Authors:  Emmanuelle Porcher; Tatiana Giraud; Claire Lavigne
Journal:  Genet Res       Date:  2006-02       Impact factor: 1.588

6.  Estimation, variance and optimal sampling of gene diversity II. Diploid locus.

Authors:  O Pons; K Chaouche
Journal:  Theor Appl Genet       Date:  1995-07       Impact factor: 5.699

Review 7.  Evolutionary inference from QST.

Authors:  Michael C Whitlock
Journal:  Mol Ecol       Date:  2008-03-17       Impact factor: 6.185

8.  Does natural selection promote population divergence? A comparative analysis of population structure using amplified fragment length polymorphism markers and quantitative traits.

Authors:  T Steinger; P Haldimann; K A Leiss; H Müller-Schärer
Journal:  Mol Ecol       Date:  2002-12       Impact factor: 6.185

9.  Does habitat fragmentation reduce fitness and adaptability? A case study of the common frog (Rana temporaria).

Authors:  Markus Johansson; Craig R Primmer; Juha Merilä
Journal:  Mol Ecol       Date:  2007-07       Impact factor: 6.185

10.  Contemporary fisherian life-history evolution in small salmonid populations.

Authors:  Mikko T Koskinen; Thrond O Haugen; Craig R Primmer
Journal:  Nature       Date:  2002-10-24       Impact factor: 49.962

View more
  10 in total

1.  Decanalization of wing development accompanied the evolution of large wings in high-altitude Drosophila.

Authors:  Justin B Lack; Matthew J Monette; Evan J Johanning; Quentin D Sprengelmeyer; John E Pool
Journal:  Proc Natl Acad Sci U S A       Date:  2016-01-11       Impact factor: 11.205

2.  Adaptation to local ultraviolet radiation conditions among neighbouring Daphnia populations.

Authors:  Brooks E Miner; Benjamin Kerr
Journal:  Proc Biol Sci       Date:  2010-10-13       Impact factor: 5.349

3.  Influence of mutation rate on estimators of genetic differentiation--lessons from Arabidopsis thaliana.

Authors:  Ilkka Kronholm; Olivier Loudet; Juliette de Meaux
Journal:  BMC Genet       Date:  2010-05-01       Impact factor: 2.797

4.  Molecular and quantitative trait variation within and among small fragmented populations of the endangered plant species Psilopeganum sinense.

Authors:  Qigang Ye; Feiyan Tang; Na Wei; Xiaohong Yao
Journal:  Ann Bot       Date:  2013-11-20       Impact factor: 4.357

5.  Geometric morphometric analysis of Colombian Anopheles albimanus (Diptera: Culicidae) reveals significant effect of environmental factors on wing traits and presence of a metapopulation.

Authors:  Giovan F Gómez; Edna J Márquez; Lina A Gutiérrez; Jan E Conn; Margarita M Correa
Journal:  Acta Trop       Date:  2014-04-02       Impact factor: 3.112

6.  Spatially varying selection shapes life history clines among populations of Drosophila melanogaster from sub-Saharan Africa.

Authors:  D K Fabian; J B Lack; V Mathur; C Schlötterer; P S Schmidt; J E Pool; T Flatt
Journal:  J Evol Biol       Date:  2015-03-13       Impact factor: 2.411

7.  Evidence of local adaptation despite strong drift in a Neotropical patchily distributed bromeliad.

Authors:  Myriam Heuertz; Clarisse Palma-Silva; Bárbara Simões Santos Leal; Cleber Juliano Neves Chaves; Vanessa Araujo Graciano; Christophe Boury; Luis Alberto Pillaca Huacre
Journal:  Heredity (Edinb)       Date:  2021-05-05       Impact factor: 3.832

8.  So far away, yet so close: strong genetic structure in Homonota uruguayensis (Squamata, Phyllodactylidae), a species with restricted geographic distribution in the Brazilian and Uruguayan Pampas.

Authors:  Jéssica F Felappi; Renata C Vieira; Nelson J R Fagundes; Laura V Verrastro
Journal:  PLoS One       Date:  2015-02-18       Impact factor: 3.240

9.  Ethanol resistance in Drosophila melanogaster has increased in parallel cold-adapted populations and shows a variable genetic architecture within and between populations.

Authors:  Quentin D Sprengelmeyer; John E Pool
Journal:  Ecol Evol       Date:  2021-10-20       Impact factor: 2.912

10.  Genetic differentiation revealed by selective loci of drought-responding EST-SSRs between upland and lowland rice in China.

Authors:  Hui Xia; Xiaoguo Zheng; Liang Chen; Huan Gao; Hua Yang; Ping Long; Jun Rong; Baorong Lu; Jiajia Li; Lijun Luo
Journal:  PLoS One       Date:  2014-10-06       Impact factor: 3.240

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.