酿酒酵母新生与成熟转录本的RNA结构比较分析
2026年2月27日
RNA二级结构主要通过结构探测方法观察到成熟RNA。共转录结构跟踪测序（CoSTseq）将核运行过程与结构探测结合起来，该方法已被用于研究新生RNA上的聚合酶位置。CoSTseq因此能够观察RNA在活性转录下的RNA二级结构。
我们研究了共转录RNA加工，包括新生RNA从合成RNA聚合酶中出现时的折叠方式。在此之前，我们无法监测RNA在合成过程中的折叠，这也阻碍了我们的研究。所以这种新方法克服了这些空白。
CoSTseq旨在研究酵母中新生的RNA折叠。它在分析高丰度RNA方面尤其有效。首先，将酿酒酵母菌株BY4741接种于50毫升YPAD培养基中，并在30摄氏度下以每分钟200转的速度振动培养，直到培养达到中期的日志阶段。
收集约三毫升酵母培养物，相当于1.8个光学密度单位，使用预冷离心机在2,500 x g离心机温度下四摄氏度，离心三分钟。将上清液丢弃到废物容器中。将颗粒重新悬浮在10毫升冷PBS中，并以2,500克离心机离心，温度为4摄氏度，持续三分钟。
去除上清液，将酵母颗粒冰封保存。小心地将酵母颗粒重新注入10毫升冷的0.5%萨科基中，避免产生气泡。将再悬浮酵母在冰上孵育20分钟以促进渗透，然后以400 x g在4摄氏度下沉淀5分钟，再用P-1000移液器将可渗透酵母细胞重新悬浮在100微升无核酸酶水中。
制备2.5倍转录缓冲液，配合新加入的5毫莫拉二硫糖醇，预热2.5倍结构探针缓冲液至30摄氏度。在干净的两毫升管中，加入所有必要的反应组分并充分混合。接着，将100微升准备好的酵母细胞加入反应管，并在设定为30摄氏度的热搅拌机中培养，以每分钟500转的速度摇晃两分钟。
然后迅速加入200微升预热的2.5倍结构探测缓冲液，同时加入25微升二甲基硫酸盐试剂。轻轻地将管子分两下脉冲旋转，然后将其放回设定为30摄氏度、每分钟500转的孵化器中。继续在热搅拌机上孵育四分钟，样品间隔30秒。
提前准备好止水和洗涤缓冲剂，并放在冰上等使用。通过在反应管中加入一毫升止液缓冲液，阻止二甲基硫酸盐甲基化。现在将标记为二甲基硫酸盐的样品在3,500 x g的温度下，在预冷却离心机中离心五分钟。
旋转后，将上清液丢弃到合适的废物容器中。向沉淀中加入一毫升冷却洗涤缓冲液，然后重新挂起。在3,500 x g下重复离心五分钟。
立即进行RNA提取，不要冷冻酵母颗粒。将标记为二甲基硫酸盐的酵母沉淀重新悬浮在600微升RNA溶解缓冲液中，然后将悬浮液转移到装有40微升20%十二烷基硫酸钠的管子中。将样品在65摄氏度下孵育30秒，摇晃速度为每分钟950转。
接着，按照标准程序进行RNA的酚氯仿萃取。对链氨亲和素磁珠进行漩涡，并将44微升的珠子转移到新的管子中，每样本共80微克RNA。将磁珠放在磁性架上，直到珠子稳定。
取出储存缓冲液后，将微珠重新悬浮在一毫升预洗缓冲液A中。现在将悬浮液在室温下孵育两分钟，然后磁化并去除上清液。清洗后，将珠子重新悬浮在88微升的2倍结合缓冲液中。将80微升悬浮液转移到一个无菌的1.5毫升管中，该管内含80微克生物素化RNA样本，容量为80微升。
将珠状样品混合物在室温下旋转20分钟。然后将管子放置在磁机架上，收集含有成熟RNA的流动，并保存用于沉淀，以便通过DMS-MaPseq流程进行成熟RNA的多重A选择。接着，用500微升高盐缓冲液冲洗两次珠状RNA复合体。
然后用500微升1X结合缓冲液冲洗一次，最后用500微升低盐缓冲液冲洗一次。现在向小珠=新生RNA复合物中加入300微升RNA试剂，彻底重新悬浮，并在60摄氏度热搅拌机上培养五分钟。接着加入60微升氯仿，涡旋，在室温下孵育三分钟。
将样品在14,000 x g的温度下离心，在预冷却离心机中离心五分钟。最后，将约180微升的上层水相转移到新的收集管中。丢弃剩余的有机相，留下珠子和残留的水溶液。
纯化新生RNA后，进行模板切换逆转录，连接5'接合器，并选择文库进行测序。在1%琼脂糖凝胶上的测试PCR产物可视化显示，引物二聚体形成极少，且在共转录结构测序或CoSTseq和DMS-MaPseq文库中，约有300个碱基对的特征性涂抹。CoSTseq样本的电泳图确认了文库大小分布，峰值约为285碱基对。
ASC1 mRNA的读段比对显示CoSTseq文库涵盖了内含子的覆盖，证实该RNA处于初期阶段。而DMS-MaPseq文库缺乏内含子覆盖，表明RNA已成熟。18S在rRNA前的cott转录折叠基质显示，当RNA聚合酶从rDNA位点第790位向811位推进时，DMS反应性发生了突兀变化。
对ADH1 mRNA的DMS反应性分析显示，新生型与成熟型态之间存在相似的轮廓，显示结构稳定性区域。相比之下，SSA2 mRNA在新生型和成熟型态之间表现出不同的DMS反应性区域，表明成熟过程中存在结构变化。通过CoSTseq，研究人员可以确定体内新生RNA二级结构以及RNA聚合酶在RNA转录本上的位置。
CoSTseq步骤时间紧迫，使用有毒化学品。最好一次处理不超过两个样本。从CoSTseq产生的总RNA中，非生物素化RNA可用于传统的DMS-MaPseq进行成熟结构探测。
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Overview
This article presents Co-transcriptional Structure Tracking sequencing (CoSTseq), a method for probing the secondary structure of nascent RNA as it emerges from RNA polymerase in Saccharomyces cerevisiae. CoSTseq enables simultaneous mapping of RNA polymerase position and RNA base pairing status, overcoming previous limitations in studying transient, low-abundance nascent transcripts. The protocol also allows parallel analysis of mature RNA structures using DMS-MaPseq.
Key Study Components
Area of Science
- RNA biology
- Structural genomics
- Molecular genetics
Background
- RNA secondary structures formed during transcription influence gene expression, RNA processing, translation, and stability.
- Traditional methods primarily analyze mature RNA, leaving nascent RNA folding poorly understood.
- Nascent RNAs are rare and transient, making their isolation and structural characterization challenging.
- Understanding cotranscriptional folding is critical for elucidating RNA function and regulation.
Purpose of Study
- To develop and demonstrate a protocol for capturing the structure of nascent RNA in vivo.
- To simultaneously determine RNA polymerase position and RNA base pairing status during transcription.
- To compare nascent and mature RNA structures within the same experimental framework.
Methods Used
- Growth and preparation of S. cerevisiae cultures.
- Transcriptional run-on with biotin-NTP incorporation to stall RNA polymerase at active sites.
- DMS (dimethyl sulfate) treatment to methylate unpaired A, C, and U nucleotides in RNA.
- Biotin-based enrichment of nascent RNA using streptavidin magnetic beads.
- RNA extraction, reverse transcription with template switching, and library preparation for sequencing.
- Parallel DMS-MaPseq workflow for mature RNA structure analysis.
Main Results
- CoSTseq libraries showed coverage across introns, confirming capture of nascent RNA, while DMS-MaPseq libraries lacked intron coverage, indicating mature RNA.
- DMS reactivity profiles revealed abrupt structural changes in 18S pre-rRNA as RNA polymerase progressed along the gene.
- ADH1 mRNA displayed similar DMS reactivity in nascent and mature forms, suggesting structural stability.
- SSA2 mRNA exhibited differences in DMS reactivity between nascent and mature forms, indicating structural remodeling during maturation.
Conclusions
- CoSTseq enables in vivo mapping of nascent RNA secondary structures and RNA polymerase positions.
- The method provides insights into cotranscriptional RNA folding and structural transitions during RNA maturation.
- CoSTseq can be performed alongside DMS-MaPseq for comprehensive analysis of RNA structure dynamics.
Frequently Asked Questions
Executive Industry Relevance
Co-transcriptional Structure Tracking sequencing (CoSTseq) enables direct analysis of nascent RNA folding and polymerase position in vivo, addressing a critical gap in understanding RNA structure dynamics during transcription. This capability enhances predictive confidence in gene regulation studies and supports mechanistic de-risking at the target validation stage. Integrating nascent and mature RNA structure analysis informs early discovery decisions and portfolio triage in RNA-targeted drug development.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables interrogation of RNA folding states as transcripts emerge from RNA polymerase.
- Supports functional target validation by mapping structural transitions relevant to gene regulation.
- Improves predictive confidence in RNA-targeted therapeutic hypotheses.
- Facilitates portfolio triage by distinguishing stable versus dynamic RNA regions.
Screening & Assay Development
- Prepares validated RNA structure datasets for downstream screening workflows.
- Enables assay standardization by providing quantitative DMS reactivity profiles.
- Supports reproducibility through parallel analysis of nascent and mature transcripts.
- Facilitates reliable evaluation of compound effects on RNA structure.
Translational & Preclinical Research
- Aligns RNA structure analysis with disease-relevant gene expression systems.
- Provides continuity from discovery through preclinical validation of RNA-targeted mechanisms.
- Enables risk-adjusted advancement by revealing structural remodeling during RNA maturation.
- Supports mechanistic de-risking for RNA-based therapeutic strategies.
Pipeline & Workflow Integration
CoSTseq integrates into the discovery continuum from early hypothesis testing through lead identification and preclinical research, enabling comprehensive RNA structure analysis at multiple pipeline stages.
- Discovery Biology: Supports hypothesis testing and pathway clarification by mapping nascent RNA folding in vivo.
- Screening: Provides quantitative, reproducible DMS reactivity outputs for assay readiness.
- Analytics: Delivers paired-end sequencing data to compare structural states across transcript maturation.
- Translational Research: Connects RNA structure dynamics to disease-relevant gene expression and biomarker alignment.
- Enterprise Reuse: Establishes a reusable platform for RNA structure analysis across diverse targets and conditions.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in RNA-targeted discovery.
- Operational Value: Standardizes RNA structure probing with scalable, parallelizable workflows.
- Strategic Value: Enables better go/no-go decisions and capital efficiency by clarifying RNA structural transitions.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of RNA-targeted programs.
Implementation Considerations
- Requires expertise in RNA biology, sequencing, and chemical probing techniques.
- Needs access to paired-end sequencing platforms and analytical infrastructure for DMS reactivity analysis.
- Demands cross-team standardization for sample handling and data interpretation.
- Adaptation may be needed for different yeast strains or RNA abundance levels.
- Throughput is limited by time-sensitive steps and handling of toxic chemicals.
