Choquet Marvin
Faculty of Biosciences and Aquaculture, Nord University, Bodø, Norway.
Mol Ecol Resour. 2021 Feb;21(2):351-354. doi: 10.1111/1755-0998.13218. Epub 2020 Jul 13.
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.
全基因组测序仍然常常是一项困难、昂贵且耗时的任务。各种简化基因组代表性测序(RRS)方案的出现,如限制性位点关联DNA测序(RADseq),使得无需进行全基因组测序就能获取全基因组信息。然而,要充分发挥RRS方案的潜力,需要针对所研究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拟方案行为的程度是有限的。在本期《分子生态学资源》中,里维拉 - 科隆等人(2020年)介绍了RADinitio,这是一款用于模拟RADseq数据的新软件,旨在以最高的代表性水平进行模拟。通过考虑文库制备和测序参数对所得序列的影响,RADinitio能够在设计RADseq实验时精确识别失败的根源。这款新软件在RADseq数据模拟方面取得了相当大的进展,很可能会提高RADseq实验的成功率。