Causes of variability in estimates of mutational variance from mutation accumulation experiments.
Characteristics of the new phenotypic variation introduced via mutation have broad implications in evolutionary and medical genetics. Standardized estimates of this mutational variance, VM, span 2 orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogene...
| Publicado en: | Genetics Vol. 221; no. 2; pp. 1 - 15 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Jun2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=157283092&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157283092 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00166731 GNT jtl: Genetics issn: 00166731 maglogo: N pubinfo: dt: Jun2022 vid: 221 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 157283092 157283092 157283092 10.1093/genetics/iyac060 157283092 ppf: 1 ppct: 14 formats: tig: atl: Causes of variability in estimates of mutational variance from mutation accumulation experiments. aug: au: Conradsen, Cara Blows, Mark W. McGuigan, Katrina affil: School of Biological Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia sug: subj: Mutation Human Meta Analysis Descriptive Statistics Data Analysis Software Analysis of Variance ab: Characteristics of the new phenotypic variation introduced via mutation have broad implications in evolutionary and medical genetics. Standardized estimates of this mutational variance, VM, span 2 orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogeneity using 2 approaches. First, meta-analyses of ~150 estimates of standardized VM from 37 mutation accumulation studies did not support a difference among taxa (which differ in mutation rate) but provided equivocal support for differences among trait types (life history vs morphology, predicted to differ in mutation rate). Notably, several experimental factors were confounded with taxon and trait, and further empirical data are required to resolve their influences. Second, we analyzed morphological data from an experiment in Drosophila serrata to determine the potential for unintentional heterogeneity among environments in which phenotypes were measured (i.e. among laboratories or time points) or transient segregation of mutations within mutation accumulation lines to affect standardized VM. Approximating the size of an average mutation accumulation experiment, variability among repeated estimates of (accumulated) mutational variance was comparable to variation among published estimates of standardized VM. This heterogeneity was (partially) attributable to unintended environmental variation or within line segregation of mutations only for wing size, not wing shape traits. We conclude that sampling error contributed substantial variation within this experiment, and infer that it will also contribute substantially to differences among published estimates. We suggest a logistically permissive approach to improve the precision of estimates, and consequently our understanding of the dynamics of mutational variance of quantitative traits. pubtype: Academic Journal doctype: equations & formulas meta analysis research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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