Optimizing Single-Cell Long-Read Sequencing for Enhanced Isoform Detection in Pancreatic Islets

选择性拼接 生物 RNA剪接 计算生物学 转录组 核糖核酸 基因亚型 胰岛 深度测序 小岛 鉴定(生物学) 基因 RNA序列 信使核糖核酸 单细胞测序 DNA测序 电池类型 细胞生物学 功能(生物学) 剪接 基因表达 生物信息学 机制(生物学) 细胞 基因表达谱 遗传学 分子生物学
作者
Annanya Sethiya,Christopher J Hill,Lori Sussel,Kristen L. Wells
出处
期刊:Diabetes [American Diabetes Association]
标识
DOI:10.2337/db25-0424
摘要

Alternative splicing is an essential mechanism for generating protein diversity by producing distinct isoforms from a single gene. Dysregulation of splicing that affects pancreatic function and immune tolerance has been linked to both types 1 and 2 diabetes. Next-generation sequencing technologies, with their short read lengths, are limited in their ability to accurately detect splice variants. Long-read sequencing technologies offer the potential to overcome these limitations by providing full-length transcript information; however, their application in single-cell RNA sequencing has been hindered by technical challenges, including insufficient read lengths and higher error rates. Furthermore, cell types that produce high levels of a single transcript, such as islet endocrine cells, can obscure identification of lower-abundance transcripts. In this study, we optimized a protocol for single-cell long-read sequencing in pancreatic islets to improve read length and transcript detection. Our findings demonstrate that 5′ library preparation protocols outperform 3′ protocols, resulting in better transcript identification. Furthermore, we show that targeted depletion of insulin transcripts enhances the detection of informative reads, highlighting the utility of transcript-depletion strategies. This optimized protocol enables isoform-specific gene expression analysis and reveals differential transcript usage across the various cell types in pancreatic islets. By leveraging this approach, we gain deeper insights into the transcriptomic complexity and cellular heterogeneity within pancreatic islets. Article Highlights This study addresses the limitations of current single-cell long-read RNA sequencing technologies in detecting full-length transcripts and isoform diversity, particularly in pancreatic islets. We demonstrate that optimizing single-cell library preparation protocols reproducibly enhances read length and transcript identification in pancreatic islets. Combined with targeted insulin depletion and extended reverse transcription, 5′ capture methods significantly improved read length and isoform detection compared with standard protocols, while maximizing the number of informative reads. These improvements yield longer reads in single-cell experiments, substantially enhancing transcript identification and enabling more accurate analysis of isoform diversity.

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