小柯机器人

英国欧洲生物信息学研究所Nick Goldman团队近期取得重要工作进展，他们最新研究提出了在纳米孔测序过程中使用贝叶斯实验设计进行动态、自适应采样。该项研究成果2023年1月2日在线发表于《自然—生物技术》杂志上。

据介绍，纳米孔测序仪可以选择要测序的DNA分子，在分析一个小的初始部分后剔除一个分子。目前，选择是基于预定感兴趣的区域，在整个实验中保持不变。因此，测序工作不能重新聚焦于可能对实验成功贡献最大的分子上。

研究人员介绍了BOSS-UNS工具，一种能生成动态更新决策策略的算法框架和软件。研究人员从已经观察到的数据实时更新来量化每个基因组位置的不确定性。对于每个DNA片段，研究人员决定其提供的不确定性预期减少是否保证对其进行完全测序，从而优化信息增益。BOSS-RUNS缓解了微生物群落成员之间和内部的覆盖偏差，从而改善了变异识别，例如，1%丰度物种的低覆盖位点减少了87.5%，检测到的单核苷酸多态性增加了12.5%。

总之，像这样数据驱动的分子选择更新适用于许多测序场景，例如富集差异增加或覆盖率低的区域，从而能够减少响应速度。

附：英文原文

Title: Dynamic, adaptive sampling during nanopore sequencing using Bayesian experimental design

Author: Weilguny, Lukas, De Maio, Nicola, Munro, Rory, Manser, Charlotte, Birney, Ewan, Loose, Matthew, Goldman, Nick

Issue&Volume: 2023-01-02

Abstract: Nanopore sequencers can select which DNA molecules to sequence, rejecting a molecule after analysis of a small initial part. Currently, selection is based on predetermined regions of interest that remain constant throughout an experiment. Sequencing efforts, thus, cannot be re-focused on molecules likely contributing most to experimental success. Here we present BOSS-RUNS, an algorithmic framework and software to generate dynamically updated decision strategies. We quantify uncertainty at each genome position with real-time updates from data already observed. For each DNA fragment, we decide whether the expected decrease in uncertainty that it would provide warrants fully sequencing it, thus optimizing information gain. BOSS-RUNS mitigates coverage bias between and within members of a microbial community, leading to improved variant calling; for example, low-coverage sites of a species at 1% abundance were reduced by 87.5%, with 12.5% more single-nucleotide polymorphisms detected. Such data-driven updates to molecule selection are applicable to many sequencing scenarios, such as enriching for regions with increased divergence or low coverage, reducing time-to-answer.

DOI: 10.1038/s41587-022-01580-z

Source: https://www.nature.com/articles/s41587-022-01580-z

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex