Whole‐genome sequencing is still often a difficult, costly and time‐consuming task. The emergence of various genome reduced‐representation sequencing (RRS) protocols such as restriction site‐associated DNA sequencing (RADseq) has facilitated the access to genome‐wide information, without the need for whole‐genome sequencing. Reaching the full potential of RRS protocols though requires adjustments and tailoring to the species under investigation. To that end, simulation software has been developed to guide researchers in the customization of their RADseq experiment, but the extent to which these tools mimic the behaviour of a protocol in generating sequencing data is limited. In this current issue of Molecular Ecology Resources, Rivera‐Colón et al. (2020) introduce RADinitio, a new software for simulating RADseq data designed to perform simulations at the highest level of representativeness. By taking into account the effects of library preparation and sequencing parameters on the resulting sequences, RADinitio allows the precise identification of the sources of failure when designing a RADseq experiment. This new software represents a considerable advance in RADseq data simulation and will likely lead to increased success in RADseq experiments.

中文翻译：

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使用新的模拟软件 RADinitio 自定义并充分利用您的缩减表示测序实验。

全基因组测序通常仍然是一项困难、昂贵且耗时的任务。各种基因组减少表达测序 (RRS) 协议的出现，例如限制性位点相关 DNA 测序 (RADseq)，促进了对全基因组信息的访问，而无需进行全基因组测序。虽然要充分发挥 RRS 协议的潜力，但需要根据调查的物种进行调整和定制。为此，已经开发了模拟软件来指导研究人员定制他们的 RADseq 实验，但这些工具在生成测序数据时模仿协议行为的程度是有限的。在本期分子生态资源中，Rivera-Colón 等人。(2020) 介绍RADinitio，一种用于模拟 RADseq 数据的新软件，旨在以最高水平的代表性进行模拟。通过考虑文库制备和测序参数对结果序列的影响，RADinitio允许在设计 RADseq 实验时精确识别失败的来源。这个新软件代表了 RADseq 数据模拟的相当大的进步，并且可能会增加 RADseq 实验的成功率。