Modern domestication efforts have occurred in a wide range of species. These efforts have led to different levels of change from the initial wild populations and market success. In this study, we explore different breeding cycle parameters to understand the rate of change in different potential starting points of neo‐domestication breeding programs. The design of a program that will bring a new crop to market requires consideration of cost efficiency and resource allocation. More crop diversity on the market creates an opportunity to design different types of food systems that can be tailored toward regional and local food security. Stochastic simulation of the rate of gain and variance is applied to different parameter combinations through the breeding cycle—crossing, evaluation, and selection—to identify population level changes along the continuum of wild to semi‐domestic plant species. The simulated breeding schemes differ in phenotypic gain and variance depending on selection strategy and population type, discovering the largest phenotypic gain of oligogenic traits occurring using phenotypic recurrent selection for landrace and orphan populations while choosing genomic selection for wild populations. There were also differences based on selection strategy, with maximum avoidance consistently leading to lower gains but higher additive variance. Overall, when looking to domesticate a new species, our simulations find phenotypic recurrent selection to be the most cost‐effective option and lead to the most gain in early generations of selection, with marker technology being most useful once initial gains have plateaued.

中文翻译：

---

为战略性创建新驯化育种计划模拟探索参数空间和资源分配


现代驯化工作已经发生在广泛的物种中。这些努力导致了与最初的野生种群和市场成功不同程度的变化。在这项研究中，我们探讨了不同的繁殖周期参数，以了解新驯化繁殖计划不同潜在起点的变化率。将新作物推向市场的计划的设计需要考虑成本效益和资源分配。市场上更多的作物多样性为设计不同类型的食品系统创造了机会，这些系统可以根据区域和地方粮食安全进行定制。在整个育种周期（杂交、评估和选择）中，将增益和方差率的随机模拟应用于不同的参数组合，以确定沿野生到半家养植物物种连续体的种群水平变化。模拟的育种方案根据选择策略和种群类型在表型增益和方差上有所不同，发现在为野生种群选择基因组选择的同时，使用地方品种和孤儿种群的表型递归选择发生的寡基因性状表型增益最大。基于选择策略也存在差异，最大避免始终导致较低的增益但较高的加性方差。总体而言，在寻求驯化新物种时，我们的模拟发现表型递归选择是最具成本效益的选择，并且在早期选择中带来最大的收益，一旦初始收益趋于稳定，标记技术就最有用。