Davies Sarah W, Scarpino Samuel V, Pongwarin Thanapat, Scott James, Matz Mikhail V
Department of Integrative Biology, The University of Texas at Austin, Texas 78712
Santa Fe Institute, Santa Fe, New Mexico 87501
G3 (Bethesda). 2015 Oct 4;5(12):2639-45. doi: 10.1534/g3.115.020701.
Increasingly, researchers are interested in estimating the heritability of traits for nonmodel organisms. However, estimating the heritability of these traits presents both experimental and statistical challenges, which typically arise from logistical difficulties associated with rearing large numbers of families independently in the field, a lack of known pedigree, the need to account for group or batch effects, etc. Here we develop both an empirical and computational methodology for estimating the narrow-sense heritability of traits for highly fecund species. Our experimental approach controls for undesirable culturing effects while minimizing culture numbers, increasing feasibility in the field. Our statistical approach accounts for known issues with model-selection by using a permutation test to calculate significance values and includes both fitting and power calculation methods. We further demonstrate that even with moderately high sample-sizes, the p-values derived from asymptotic properties of the likelihood ratio test are overly conservative, thus reducing statistical power. We illustrate our methodology by estimating the narrow-sense heritability for larval settlement, a key life-history trait, in the reef-building coral Orbicella faveolata. The experimental, statistical, and computational methods, along with all of the data from this study, are available in the R package multiDimBio.
越来越多的研究人员对估计非模式生物性状的遗传力感兴趣。然而,估计这些性状的遗传力存在实验和统计方面的挑战,这些挑战通常源于在野外独立饲养大量家系所带来的后勤困难、缺乏已知的谱系、需要考虑群体或批次效应等。在这里,我们开发了一种经验和计算方法,用于估计高繁殖力物种性状的狭义遗传力。我们的实验方法在控制不良培养效应的同时,尽量减少培养数量,提高了在野外的可行性。我们的统计方法通过使用置换检验来计算显著性值,解决了模型选择中的已知问题,并且包括拟合和功效计算方法。我们进一步证明,即使样本量适中,从似然比检验的渐近性质得出的p值也过于保守,从而降低了统计功效。我们通过估计造礁珊瑚蜂巢珊瑚幼虫附着这一关键生活史性状的狭义遗传力来说明我们的方法。实验、统计和计算方法,以及本研究的所有数据,都可以在R包multiDimBio中获得。