Nandi Shuvro P, Cheng Yuhe, Al-Azzam Shams, Saeed Safa, Kristin Audrey, Sunico Nadia, Stuewe Isabella R, Jiang Zichen, Culibrk Luka, Zhivagui Maria, Yang Xiaoxu, Wise Rachel M, Jacobs Foster C, Chavanel Bérénice, Korenjak Michael, Petljak Mia, Balbo Silvia, Hudson Laurie G, Liu Ke Jian, Zavadil Jiri, Gleeson Joseph G, Alexandrov Ludmil B
Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, USA.
Department of Bioengineering, UC San Diego, La Jolla, CA, USA.
bioRxiv. 2025 Sep 16:2025.09.14.676103. doi: 10.1101/2025.09.14.676103.
Ultra-accurate detection of rare somatic mutations is critical for understanding mutational processes in human disease, aging, and environmental exposures, yet current methods are limited by error rates, restricted genome coverage, and high DNA input. We present UDSeq, a duplex sequencing protocol combining random fragmentation, efficient UMI ligation, and quantitative input control to achieve near-complete genome/exome representation from as little as 100 pg DNA. Benchmarking in human sperm estimates a UDSeq error rate of ~2.5×10 per base pair. UDSeq captures mutational signatures from heterogeneous populations without clonal expansion, reproduces exposure-specific patterns in cell lines and rodent models, and enables cross-species profiling. Compared with prior duplex methods, UDSeq yields up to fourfold more usable duplex molecules, improves library conversion, and remains cost-effective. We include a step-by-step protocol with quality-control checkpoints for fragment size, ligation yield, library conversion, and duplication rate. UDSeq provides a scalable, low-input platform for accurate profiling of somatic mutagenesis.
超精确检测罕见体细胞突变对于理解人类疾病、衰老和环境暴露中的突变过程至关重要,但目前的方法受到错误率、有限的基因组覆盖范围和高DNA输入量的限制。我们提出了UDSeq,这是一种双链测序方案,结合了随机片段化、高效的UMI连接和定量输入控制,以实现从低至100 pg DNA获得近乎完整的基因组/外显子表征。在人类精子中的基准测试估计UDSeq的错误率约为每碱基对2.5×10 。UDSeq无需克隆扩增即可从异质群体中捕获突变特征,在细胞系和啮齿动物模型中重现暴露特异性模式,并实现跨物种分析。与先前的双链方法相比,UDSeq产生的可用双链分子多四倍,提高了文库转化率,并且仍然具有成本效益。我们包括一个带有质量控制检查点的分步方案,用于片段大小、连接产量、文库转化率和重复率。UDSeq为体细胞突变的精确分析提供了一个可扩展的低输入平台。