{"title":"突变积累实验中突变方差估计的变异原因","authors":"C. Conradsen, M. Blows, K. McGuigan","doi":"10.1093/genetics/iyac060","DOIUrl":null,"url":null,"abstract":"Characteristics of the new phenotypic variation introduced via mutation have broad implications in evolutionary and medical genetics. Standardised estimates of this mutational variance, VM, span two orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogeneity using two approaches. First, meta-analyses of ~150 estimates from 37 mutation accumulation (MA) studies did not support a difference among taxa (which differ in mutation rate) in standardised VM, but provided equivocal support for standardised VM to vary with trait type (life history versus 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 analysed 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 MA lines to affect standardised VM. Approximating the size of an average MA experiment, variability among repeated estimates of (accumulated) mutational variance was comparable to variation among published estimates of standardised VM for morphological traits. 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.","PeriodicalId":12706,"journal":{"name":"Genetics","volume":"221 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Causes of variability in estimates of mutational variance from mutation accumulation experiments\",\"authors\":\"C. Conradsen, M. Blows, K. McGuigan\",\"doi\":\"10.1093/genetics/iyac060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Characteristics of the new phenotypic variation introduced via mutation have broad implications in evolutionary and medical genetics. Standardised estimates of this mutational variance, VM, span two orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogeneity using two approaches. First, meta-analyses of ~150 estimates from 37 mutation accumulation (MA) studies did not support a difference among taxa (which differ in mutation rate) in standardised VM, but provided equivocal support for standardised VM to vary with trait type (life history versus 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 analysed 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 MA lines to affect standardised VM. Approximating the size of an average MA experiment, variability among repeated estimates of (accumulated) mutational variance was comparable to variation among published estimates of standardised VM for morphological traits. 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.\",\"PeriodicalId\":12706,\"journal\":{\"name\":\"Genetics\",\"volume\":\"221 1\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2021-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genetics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/genetics/iyac060\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/genetics/iyac060","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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. Standardised estimates of this mutational variance, VM, span two orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogeneity using two approaches. First, meta-analyses of ~150 estimates from 37 mutation accumulation (MA) studies did not support a difference among taxa (which differ in mutation rate) in standardised VM, but provided equivocal support for standardised VM to vary with trait type (life history versus 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 analysed 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 MA lines to affect standardised VM. Approximating the size of an average MA experiment, variability among repeated estimates of (accumulated) mutational variance was comparable to variation among published estimates of standardised VM for morphological traits. 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.
期刊介绍:
GENETICS is published by the Genetics Society of America, a scholarly society that seeks to deepen our understanding of the living world by advancing our understanding of genetics. Since 1916, GENETICS has published high-quality, original research presenting novel findings bearing on genetics and genomics. The journal publishes empirical studies of organisms ranging from microbes to humans, as well as theoretical work.
While it has an illustrious history, GENETICS has changed along with the communities it serves: it is not your mentor''s journal.
The editors make decisions quickly – in around 30 days – without sacrificing the excellence and scholarship for which the journal has long been known. GENETICS is a peer reviewed, peer-edited journal, with an international reach and increasing visibility and impact. All editorial decisions are made through collaboration of at least two editors who are practicing scientists.
GENETICS is constantly innovating: expanded types of content include Reviews, Commentary (current issues of interest to geneticists), Perspectives (historical), Primers (to introduce primary literature into the classroom), Toolbox Reviews, plus YeastBook, FlyBook, and WormBook (coming spring 2016). For particularly time-sensitive results, we publish Communications. As part of our mission to serve our communities, we''ve published thematic collections, including Genomic Selection, Multiparental Populations, Mouse Collaborative Cross, and the Genetics of Sex.