Suppr超能文献

共享空间效应对数量遗传参数的影响:在野生红鹿中,考虑空间自相关和家域重叠会降低遗传力的估计值。

Shared spatial effects on quantitative genetic parameters: accounting for spatial autocorrelation and home range overlap reduces estimates of heritability in wild red deer.

机构信息

Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom.

出版信息

Evolution. 2012 Aug;66(8):2411-26. doi: 10.1111/j.1558-5646.2012.01620.x. Epub 2012 Apr 9.

Abstract

Social structure, limited dispersal, and spatial heterogeneity in resources are ubiquitous in wild vertebrate populations. As a result, relatives share environments as well as genes, and environmental and genetic sources of similarity between individuals are potentially confounded. Quantitative genetic studies in the wild therefore typically account for easily captured shared environmental effects (e.g., parent, nest, or region). Fine-scale spatial effects are likely to be just as important in wild vertebrates, but have been largely ignored. We used data from wild red deer to build "animal models" to estimate additive genetic variance and heritability in four female traits (spring and rut home range size, offspring birth weight, and lifetime breeding success). We then, separately, incorporated spatial autocorrelation and a matrix of home range overlap into these models to estimate the effect of location or shared habitat on phenotypic variation. These terms explained a substantial amount of variation in all traits and their inclusion resulted in reductions in heritability estimates, up to an order of magnitude up for home range size. Our results highlight the potential of multiple covariance matrices to dissect environmental, social, and genetic contributions to phenotypic variation, and the importance of considering fine-scale spatial processes in quantitative genetic studies.

摘要

在野生动物种群中,社会结构、有限的扩散和资源的空间异质性是普遍存在的。因此,亲属共享环境和基因,个体之间环境和遗传相似性的来源可能存在混淆。因此,野外的定量遗传研究通常会考虑到容易捕捉到的共享环境效应(例如,父母、巢穴或区域)。在野生动物中,精细的空间效应可能同样重要,但在很大程度上被忽视了。我们使用来自野生赤鹿的数据构建了“动物模型”,以估计四个雌性特征(春季和发情期的活动范围大小、后代出生体重和终生繁殖成功率)的加性遗传方差和遗传率。然后,我们分别将空间自相关和活动范围重叠矩阵纳入这些模型,以估计位置或共享栖息地对表型变异的影响。这些术语解释了所有特征的大量变异,并且它们的纳入导致遗传率估计值降低,对于活动范围大小来说,降低了一个数量级。我们的研究结果强调了使用多个协方差矩阵来剖析表型变异的环境、社会和遗传贡献的潜力,以及在定量遗传研究中考虑精细空间过程的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2053/3437482/7502f298e2e2/evo0066-2411-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验