突变积累实验中突变方差估计的变异原因

IF 3.3 3区 生物学
Genetics Pub Date : 2021-07-09 DOI:10.1093/genetics/iyac060
C. Conradsen, M. Blows, K. McGuigan
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引用次数: 2

摘要

通过突变引入的新表型变异的特征在进化和医学遗传学中具有广泛的意义。这种变异方差VM的标准化估计跨越了两个数量级,但其原因仍然没有得到很好的解决。我们使用两种方法研究了估计异质性。首先,对37项突变累积(MA)研究中约150个估计值的荟萃分析不支持标准化VM中分类群之间的差异(突变率不同),但对标准化VM随性状类型(生活史与形态学,预测突变率不同的)的变化提供了模棱两可的支持。值得注意的是,几个实验因素与分类单元和性状混淆,需要进一步的经验数据来解决它们的影响。其次,我们分析了来自锯齿状果蝇实验的形态学数据,以确定测量表型的环境之间(即实验室或时间点之间)无意异质性的可能性,或MA系内突变的短暂分离影响标准化VM的可能性。近似于平均MA实验的大小,(累积的)突变方差的重复估计之间的变异性与已发表的形态性状标准化VM估计之间的差异相当。这种异质性(部分)可归因于意外的环境变异或仅针对翅膀大小而非翅膀形状特征的突变的系内分离。我们得出的结论是,抽样误差在这个实验中造成了很大的变化,并推断它也将在很大程度上导致已发表的估计之间的差异。我们提出了一种逻辑上允许的方法来提高估计的精度,从而提高我们对数量性状变异方差动力学的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
Genetics
Genetics 生物-遗传学
CiteScore
6.20
自引率
6.10%
发文量
177
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.
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