Data from: Purging deleterious mutations in conservation programmes: combining optimal contributions with inbred matings

Conservation programmes aim at minimising the loss of genetic diversity, which allows populations to adapt to potential environmental changes. This can be achieved by calculating how many offspring every individual should contribute to the next generation to minimise global coancestry. However, an undesired consequence of this strategy is that it maintains deleterious mutations, compromising the viability of the population. In order to avoid this, optimal contributions could be combined with inbred matings, to expose and eliminate recessive deleterious mutations by natural selection in a process known as purging. Although some populations that have undergone purging experienced reduced inbreeding depression, this effect is not consistent across species. Whether purging by inbred matings is efficient in conservation programmes depends on the balance between the loss of diversity, the initial decrease in fitness and the reduction in mutational load. Here we perform computer simulations to determine whether managing a population by combining optimal contributions with inbred matings improves its long-term viability while keeping reasonable levels of diversity. We compare the management based on genealogical information with management based on molecular data to calculate coancestries. In the scenarios analysed, inbred matings never led to higher fitness and usually maintained lower diversity than random or minimum coancestry matings. Replacing genealogical with molecular coancestry can maintain a larger genetic diversity but can also lead to a lower fitness. Our results are strongly dependent on the mutational model assumed for the trait under selection, the population size during management and the reproductive rate.

保育计划（conservation programmes）旨在最大限度减少遗传多样性（genetic diversity）的丧失，而遗传多样性是种群适应潜在环境变化的核心基础。该目标可通过计算每个个体应向下一代贡献的后代数量，以最小化全局共祖率（global coancestry）来实现。然而，该策略存在一项不良后果：会保留有害突变（deleterious mutations），进而损害种群的生存活力。为规避该问题，可将最优贡献策略与近交交配（inbred matings）相结合，通过被称为遗传清除（purging）的过程借助自然选择（natural selection）暴露并淘汰隐性有害突变。尽管部分经历遗传清除的种群出现了近交衰退（inbreeding depression）程度的降低，但该效应在不同物种间并不一致。近交交配介导的遗传清除能否在保育计划中发挥有效作用，取决于多样性丧失、适合度初始下降与突变负荷（mutational load）降低三者间的动态平衡。本研究通过计算机模拟（computer simulations），探究将最优贡献策略与近交交配相结合的种群管理模式，能否在维持合理遗传多样性水平的同时提升种群的长期生存活力。我们对比了基于谱系信息（genealogical information）与基于分子数据（molecular data）计算共祖率的两种管理方案。在所分析的场景中，近交交配从未带来更高的适合度，且通常较随机交配或最小共祖交配维持更低的遗传多样性。将谱系共祖率替换为分子共祖率，虽可维持更高水平的遗传多样性，但也可能导致适合度下降。本研究结果强烈依赖于所假设的受选性状突变模型、管理期间的种群规模以及繁殖速率。