A method for preparing unbiased miRNA sequencing libraries (miR-ACS)

一种制备无偏miRNA测序文库（miR-ACS）的方法

• 批准号: 9202976
• 负责人: SERGEI A KAZAKOV
• 金额: $ 99.03万
• 依托单位: SOMAGENICS, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-11 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9202976
• 关键词: Address; Adoption; Affect; Applications Grants; Biological; Biological Markers; Biology; Cancer Patient; Data; Detection; Development; Disease; Drug Targeting; Early Diagnosis; Gel; Goals; Health; Individual; Knowledge; Letters; Libraries; Ligase; Ligation; Malignant Neoplasms; Measurement; Messenger RNA; Methods; MicroRNAs; Molecular Profiling; Monitor; New England; Performance; Phase; Phosphorylation; Preparation; Procedures; Progress Reports; Protocols documentation; Publications; RNA; RNA Sequences; Reaction; Reading; Reagent; Reporting; Reproducibility; Reverse Transcription; Role; Sampling; Small RNA; Source; Technology; Testing; Time; Transcript; Work; cancer biomarkers; cost; design; dimer; human tissue; microRNA biomarkers; next generation sequencing; novel; novel strategies; prevent; prototype; research study; therapeutic target; transcriptome sequencing; tumor

ABSTRACT This proposal addresses the problem of sequence bias in next-generation sequencing (NGS) of small RNAs such as microRNAs (miRNAs) as well as fragments of larger RNAs. Because dysregulation of miRNA expression has been implicated in cancer and other diseases, accurate expression profiling of all miRNA sequences is important for understanding miRNA biology and for development of new biomarkers and therapeutic targets. NGS is currently the most comprehensive approach for discovery and expression profiling of small RNA sequences. However, NGS expression profiling data underestimate the abundance of most miRNAs in a sample, some by as much as 10,000-fold. Knowledge of the true abundances in samples, and not just the relative changes between samples, is important for reliable identification of miRNAs as biomarkers or drug-target candidates. Other advantages of unbiased detection include the ability to discover novel RNAs and detect low-abundance RNAs that cannot be detected by current NGS methods, especially in samples with a low concentration of RNA. The source of bias in currently available methods of preparation RNA sequencing libraries for NGS is inefficient and sequence-dependent ligation of the two sequencing adapters to the sample RNAs. The major factors contributing to this ligation bias are intramolecular folding of the miRNAs and intermolecular folding between miRNAs and adapters, which affect the ability of the ligase to access and ligate the miRNA ends. Thus there is a need for new, more accurate methods, and most previous small RNA profiling experiments should be re-evaluated. To address these problems, we are developing a new approach, miR- ACS (miRNA-Adapter Circularization and Sequencing), for preparing unbiased sequencing libraries that is applicable to miRNAs and other small RNAs as well as small fragments of large RNAs used in general RNA- Seq. Key features of miR-ACS include (i) ligation of miRNAs with only a single combo adapter (CAD) that combines sequences of the standard 3'- and 5'-adapters used for Illumina sequencing, producing miRNA-CAD ligation products; (ii) circularization of the miRNA-CAD products; (iii) blocking of free CAD species that are not ligated to miRNAs; and (iv) RT-PCR amplification of the circular miRNA-CAD products to produce standard sequencing amplicons containing a single RNA-specific sequence insert flanked by the 5'- and 3'-adapter sequences. In Phase I, we have demonstrated the feasibility of the miR-ACS approach (proof-of-concept) by greatly reducing the miRNA sequencing bias in comparison to the best current library prep methods. In Phase II we will thoroughly optimize miR-ACS to maximize bias reduction and to allow sequencing of a larger variety of RNAs (up to 150 nt in size) with very low RNA inputs. In addition, we will streamline the protocol to facilitate its adoption by users and for commercial viability.

摘要 该建议解决了小RNA的下一代测序（NGS）中的序列偏差问题 如微小RNA（miRNAs）以及较大RNA的片段。因为miRNA的失调 表达与癌症和其他疾病有关，所有miRNA的准确表达谱 序列对于理解miRNA生物学和开发新的生物标志物是重要的， 治疗目标NGS是目前最全面的发现和表达谱分析方法 小RNA序列。然而，NGS表达谱数据低估了大多数人的丰度。 在一个样本中的miRNA，有些高达10,000倍。了解样品中的真实丰度，而不是 仅仅是样品之间的相对变化，对于可靠地鉴定miRNA作为生物标志物或 药物靶向候选人无偏检测的其他优点包括发现新RNA的能力， 检测目前NGS方法无法检测到的低丰度RNA，特别是在具有 低浓度的RNA。目前可用的RNA测序制备方法中的偏倚来源 用于NGS的文库是低效的，并且两个测序衔接子与样品的序列依赖性连接 RNA。导致这种连接偏好的主要因素是miRNA的分子内折叠， miRNA和衔接子之间的分子间折叠，其影响连接酶进入和连接的能力 miRNA结束。因此，需要新的、更准确的方法，以及大多数先前的小RNA分析。 实验需要重新评估。为了解决这些问题，我们正在开发一种新的方法，miR- ACS（miRNA-衔接子环化和测序），用于制备无偏倚的测序文库， 适用于miRNA和其他小RNA以及一般RNA中使用的大RNA的小片段- Seq. miR-ACS的关键特征包括（i）仅用单个组合衔接子（CAD）连接miRNA， 组合用于Illumina测序的标准3 '-和5'-衔接子的序列，产生miRNA-CAD 连接产物;（ii）环化miRNA-CAD产物;（iii）阻断不被连接的游离CAD种类。 （iv）RT-PCR扩增环状miRNA-CAD产物以产生标准的 测序扩增子，所述扩增子含有侧翼为5 ′-和3 ′-衔接子的单个RNA特异性序列插入物 序列的在第一阶段，我们已经证明了miR-ACS方法的可行性（概念验证）， 与目前最好的文库制备方法相比，大大降低了miRNA测序偏倚。同相 我们将彻底优化miR-ACS，以最大限度地降低偏倚，并允许更大范围的测序。 的RNA（高达150 nt的大小）与非常低的RNA输入。此外，我们将简化协议以促进 它的用户采用和商业可行性。