Global SLAM-Seq for accurate mRNA decay determination and identification of NMD targets

Gene expression analysis requires accurate measurements of global RNA degradation rates, earlier problematic with methods disruptive to cell physiology. Recently, metabolic RNA labeling emerged as an efficient and minimally invasive technique applied in mammalian cells. Here, we have adapted SH-Linked Alkylation for the Metabolic Sequencing of RNA (SLAM-Seq) for a global mRNA stability study in yeast using 4-thiouracil pulse-chase labeling. We assign high-confidence half-life estimates for 67.5 % of expressed ORFs, and measure a median half-life of 9.4 min. For mRNAs where half-life estimates exist in the literature, their ranking order was in good agreement with previous data, indicating that SLAM-Seq efficiently classifies stable and unstable transcripts. We then leveraged our yeast protocol to identify targets of the Nonsense-mediated decay (NMD) pathway by measuring the change in RNA half-lives; instead of steady-state RNA level changes. With SLAM-Seq, we assign 580 transcripts as putative NMD targets, based on their measured half-lives in wild-type and upf3Δ mutants. We find 225 novel targets, and observe a strong agreement with previous reports of NMD targets, 61.2 % of our candidates being identified in previous studies.This indicates that SLAM-Seq is a simpler and more economic method for global quantification of mRNA half-lives. Our adaptation for yeast yielded global quantitative measures of the NMD effect on transcript half-lives, high correlation with RNA half-lives measured previously with more technically challenging protocols, and identification of novel NMD regulated transcripts that escaped prior detection.基因表达分析需精准测定全局RNA降解速率，既往相关方法多会干扰细胞生理状态，存在应用局限。近年来，代谢RNA标记技术应运而生，该方法高效且微创，已应用于哺乳动物细胞研究。本研究将用于RNA代谢测序的硫氢键连接烷基化测序（SH-Linked Alkylation for the Metabolic Sequencing of RNA, SLAM-Seq）进行适配优化，结合4-硫尿嘧啶脉冲追踪标记技术，开展酵母全局mRNA稳定性研究。本研究为67.5%的已表达开放阅读框（Open Reading Frame, ORF）获得了高置信度的半衰期估计值，测得的半衰期中位数为9.4分钟。对于已有文献报道半衰期估计值的mRNA，其半衰期排序与既往数据一致性良好，表明SLAM-Seq可有效区分稳定与不稳定转录本。随后，本研究依托优化的酵母实验方案，通过测定RNA半衰期的变化（而非稳态RNA水平变化）来鉴定无义介导的mRNA降解（Nonsense-mediated decay, NMD）通路靶点。借助SLAM-Seq，我们基于野生型与upf3Δ突变体中测得的RNA半衰期，将580条转录本鉴定为潜在NMD靶点，其中包含225个全新靶点；本研究筛选的候选靶点中有61.2%已被既往研究证实，与此前报道的NMD靶点重合度极高。上述结果表明，SLAM-Seq是一种更简便、更经济的全局mRNA半衰期定量方法。本次针对酵母的适配研究，实现了NMD通路对转录本半衰期影响的全局定量分析，测得的RNA半衰期与此前采用高难度技术手段获得的数据具有高度相关性，同时还鉴定出了既往研究未发现的受NMD调控的新型转录本。