Herrera Carlos M
Estación Biológica de Doñana, Consejo Superior de Investigaciones Científicas (CSIC), Isla de La Cartuja, Sevilla, Spain.
Methods Mol Biol. 2012;888:315-29. doi: 10.1007/978-1-61779-870-2_18.
Methods for estimating quantitative trait heritability in wild populations have been developed in recent years which take advantage of the increased availability of genetic markers to reconstruct pedigrees or estimate relatedness between individuals, but their application to real-world data is not exempt from difficulties. This chapter describes a recent marker-based technique which, by adopting a genomic scan approach and focusing on the relationship between phenotypes and genotypes at the individual level, avoids the problems inherent to marker-based estimators of relatedness. This method allows the quantification of the genetic component of phenotypic variance ("degree of genetic determination" or "heritability in the broad sense") in wild populations and is applicable whenever phenotypic trait values and multilocus data for a large number of genetic markers (e.g., amplified fragment length polymorphisms, AFLPs) are simultaneously available for a sample of individuals from the same population. The method proceeds by first identifying those markers whose variation across individuals is significantly correlated with individual phenotypic differences ("adaptive loci"). The proportion of phenotypic variance in the sample that is statistically accounted for by individual differences in adaptive loci is then estimated by fitting a linear model to the data, with trait value as the dependent variable and scores of adaptive loci as independent ones. The method can be easily extended to accommodate quantitative or qualitative information on biologically relevant features of the environment experienced by each sampled individual, in which case estimates of the environmental and genotype × environment components of phenotypic variance can also be obtained.
近年来已开发出一些用于估计野生种群数量性状遗传力的方法，这些方法利用了越来越多的遗传标记来重建谱系或估计个体间的亲缘关系，但将它们应用于实际数据并非毫无困难。本章介绍了一种基于标记的最新技术，该技术通过采用基因组扫描方法并关注个体水平上的表型与基因型之间的关系，避免了基于标记的亲缘关系估计方法所固有的问题。这种方法能够对野生种群中表型变异的遗传成分（“遗传决定程度”或“广义遗传力”）进行量化，并且只要同一群体中大量个体样本同时具备表型性状值和大量遗传标记（例如，扩增片段长度多态性，AFLP）的多位点数据，就可以应用该方法。该方法首先识别那些个体间变异与个体表型差异显著相关的标记（“适应性位点”）。然后，通过将线性模型拟合到数据中，以性状值作为因变量，适应性位点得分作为自变量，估计样本中由适应性位点个体差异在统计学上解释的表型变异比例。该方法可以很容易地扩展，以纳入每个采样个体所经历的环境的生物学相关特征的定量或定性信息，在这种情况下，还可以获得表型变异的环境成分和基因型×环境成分的估计值。
