Scacchetti Alessandro, Shields Emily J, Trigg Natalie A, Wilusz Jeremy E, Conine Colin C, Bonasio Roberto
Epigenetics Institute and Department of Cell and Developmental Biology; University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Department of Urology and Institute of Neuropathology, Medical Center-University of Freiburg, 79106 Freiburg, Germany.
bioRxiv. 2023 Jun 8:2023.06.06.543899. doi: 10.1101/2023.06.06.543899.
Despite the numerous sequencing methods available, the vast diversity in size and chemical modifications of RNA molecules makes the capture of the full spectrum of cellular RNAs a difficult task. By combining quasi-random hexamer priming with a custom template switching strategy, we developed a method to construct sequencing libraries from RNA molecules of any length and with any type of 3' terminal modification, allowing the sequencing and analysis of virtually all RNA species. Ligation-independent detection of all types of RNA (LIDAR) is a simple, effective tool to comprehensively characterize changes in small non-coding RNAs and mRNAs simultaneously, with performance comparable to separate dedicated methods. With LIDAR, we comprehensively characterized the coding and non-coding transcriptome of mouse embryonic stem cells, neural progenitor cells, and sperm. LIDAR detected a much larger variety of tRNA-derived RNAs (tDRs) compared to traditional ligation-dependent sequencing methods, and uncovered the presence of tDRs with blocked 3' ends that had previously escaped detection. Our findings highlight the potential of LIDAR to systematically detect all RNAs in a sample and uncover new RNA species with potential regulatory functions.
尽管有多种可用的测序方法，但RNA分子在大小和化学修饰方面的巨大差异使得捕获细胞RNA的全谱成为一项艰巨任务。通过将准随机六聚体引物与定制的模板切换策略相结合，我们开发了一种方法，可从任何长度且具有任何类型3'末端修饰的RNA分子构建测序文库，从而实现几乎所有RNA种类的测序和分析。全类型RNA连接无关检测法（LIDAR）是一种简单有效的工具，可同时全面表征小非编码RNA和mRNA的变化，其性能与单独的专用方法相当。利用LIDAR，我们全面表征了小鼠胚胎干细胞、神经祖细胞和精子的编码和非编码转录组。与传统的依赖连接的测序方法相比，LIDAR检测到的tRNA衍生RNA（tDR）种类要多得多，并且发现了以前未被检测到的3'末端封闭的tDR的存在。我们的研究结果突出了LIDAR在系统检测样本中所有RNA以及发现具有潜在调控功能的新RNA种类方面的潜力。
