研究人员报道了Ladder-seq，一种在测序前根据长度分离转录本的方法，并利用额外的信息来提高转录本的定量和组装。使用模拟数据，研究人员表明，扩展到处理Ladder-seq数据的kallisto算法可对复杂基因的转录本进行量化，其准确性大大高于传统的kallisto。对于基于参考的组装，一个基于StringTie2算法的定制方案重建了一个单一的转录本，其精度比传统的对应方案高30.8%，对复杂基因的敏感性超过30%。
对于从头组装，基于Trinity算法的类似方案比传统Trinity正确组装了78%的转录本，同时提高了78%的精度。在实验数据中，与传统的RNA测序相比，Ladder-seq揭示了多出40%的携带亚型的基因，并揭示了通过Mettl14敲除m6A耗尽后亚型使用的广泛变化。
据悉，由于缺乏长程信息，从短读RNA测序数据中组装转录本方法的准确性受到限制。
附：英文原文
Title: Partitioning RNAs by length improves transcriptome reconstruction from short-read RNA-seq data
Author: Ringeling, Francisca Rojas, Chakraborty, Shounak, Vissers, Caroline, Reiman, Derek, Patel, Akshay M., Lee, Ki-Heon, Hong, Ari, Park, Chan-Woo, Reska, Tim, Gagneur, Julien, Chang, Hyeshik, Spletter, Maria L., Yoon, Ki-Jun, Ming, Guo-li, Song, Hongjun, Canzar, Stefan
Issue&Volume: 2022-01-10
Abstract: The accuracy of methods for assembling transcripts from short-read RNA sequencing data is limited by the lack of long-range information. Here we introduce Ladder-seq, an approach that separates transcripts according to their lengths before sequencing and uses the additional information to improve the quantification and assembly of transcripts. Using simulated data, we show that a kallisto algorithm extended to process Ladder-seq data quantifies transcripts of complex genes with substantially higher accuracy than conventional kallisto. For reference-based assembly, a tailored scheme based on the StringTie2 algorithm reconstructs a single transcript with 30.8% higher precision than its conventional counterpart and is more than 30% more sensitive for complex genes. For de novo assembly, a similar scheme based on the Trinity algorithm correctly assembles 78% more transcripts than conventional Trinity while improving precision by 78%. In experimental data, Ladder-seq reveals 40% more genes harboring isoform switches compared to conventional RNA sequencing and unveils widespread changes in isoform usage upon m6A depletion by Mettl14 knockout. The quality of RNA sequencing transcriptomes is improved when mRNAs are separated by length.
DOI: 10.1038/s41587-021-01136-7
Source: https://www.nature.com/articles/s41587-021-01136-7
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
本期文章：《自然—生物技术》：Online/在线发表
