Data from: An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment

Quantitative genetics approaches, and particularly animal models, are widely used to assess the genetic (co)variance of key fitness related traits and infer adaptive potential of wild populations. Despite the importance of precision and accuracy of genetic variance estimates and their potential sensitivity to various ecological and population specific factors, their reliability is rarely tested explicitly. Here, we used simulations and empirical data collected from an 11-year study on tree swallow (Tachycineta bicolor), a species showing a high rate of extra-pair paternity and a low recruitment rate, to assess the importance of identity errors, structure and size of the pedigree on quantitative genetic estimates in our dataset. Our simulations revealed an important lack of precision in heritability and genetic-correlation estimates for most traits, a low power to detect significant effects and important identifiability problems. We also observed a large bias in heritability estimates when using the social pedigree instead of the genetic one (deflated heritabilities) or when not accounting for an important cause of resemblance among individuals (for example, permanent environment or brood effect) in model parameterizations for some traits (inflated heritabilities). We discuss the causes underlying the low reliability observed here and why they are also likely to occur in other study systems. Altogether, our results re-emphasize the difficulties of generalizing quantitative genetic estimates reliably from one study system to another and the importance of reporting simulation analyses to evaluate these important issues.

数量遗传学（quantitative genetics）方法，尤其是动物模型（animal models），被广泛用于评估与核心适合度相关性状的遗传（共）方差，并推断野生种群的适应潜力。尽管遗传方差估计的精准性与准确性至关重要，且这些估计值可能对各类生态因素与种群特异性因素存在敏感性，但它们的可靠性却极少得到明确检验。在此，我们利用模拟实验与针对双色树燕（Tachycineta bicolor）的11年野外研究收集的实证数据开展分析——该物种具有较高的婚外父权（extra-pair paternity）发生率与较低的种群补充率（recruitment rate），以此评估系谱（pedigree）的个体识别误差、结构与规模对本数据集内数量遗传学估计结果的影响。我们的模拟实验结果显示，多数性状的遗传力（heritability）与遗传相关（genetic-correlation）估计值存在显著的精准性不足问题，检测显著效应的统计效力较低，且存在严重的可识别性（identifiability）难题。此外，我们还观察到两类显著的遗传力估计偏差：若使用社会系谱（social pedigree）替代遗传系谱（genetic pedigree），会得到低估的遗传力值；若在部分性状的模型参数化（model parameterizations）过程中未考虑个体间相似性的重要诱因（例如永久环境效应（permanent environment）或窝巢效应（brood effect）），则会得到高估的遗传力值。我们探讨了本研究中观察到的低可靠性背后的成因，以及为何这类问题在其他研究系统中同样可能出现。综上，本研究结果再次强调了两项核心要点：其一，难以将单个研究系统得到的数量遗传学估计结果可靠地推广至其他系统；其二，需通过模拟分析来评估这类关键问题的重要性。