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: 9360639
• 负责人: SERGEI A KAZAKOV
• 金额: $ 80.38万
• 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 2019-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9360639
• 关键词: Address; Adoption; Affect; Applications Grants; Biological; Biological Markers; Biology; Cancer Patient; Data; Detection; Development; Dimerization; Disease; Drug Targeting; Early Diagnosis; Gel; Goals; 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; Reagent; Reporting; Reproducibility; Reverse Transcription; Role; Sampling; Small RNA; Source; Technology; Testing; Time; Transcript; Work; cancer biomarkers; cost; design; dimer; experimental study; human tissue; microRNA biomarkers; next generation sequencing; novel; novel strategies; prevent; prototype; 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.

抽象的 该提案解决了小RNA的下一代测序（NGS）中序列偏差的问题 例如microRNA（miRNA）以及较大的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的准确表达分析 序列对于理解miRNA生物学和开发新生物标志物和发展很重要 治疗靶标。 NGS目前是发现和表达分析的最全面的方法 小的RNA序列。但是，NGS表达分析数据低估了大多数的丰度 样品中的miRNA，有些是多达10,000倍。了解样本中真正的丰富性，而不是 只是样本之间的相对变化，对于将miRNA作为生物标志物或 毒品目标候选人。无偏见的其他优势包括发现新型RNA和 检测当前NGS方法无法检测到的低丰度RNA，尤其是在具有A的样品中 低浓度RNA。当前可用的准备RNA测序方法中的偏差来源 NGS的库效率低下，并且两个测序适配器与样品的序列依赖性连接 RNA。导致这种连接偏见的主要因素是miRNA的分子内折叠和 miRNA和适配器之间的分子间折叠，这会影响连接酶访问和结合的能力 mirna结束。因此，需要新的，更准确的方法，并且大多数先前的小RNA分析 应该重新评估实验。为了解决这些问题，我们正在开发一种新方法，mir- ACS（miRNA适应器循环和测序），用于制备无偏的测序文库 适用于miRNA和其他小RNA以及一般RNA-使用的大型RNA的小片段 seq。 miR-AC的关键特征包括（i）仅使用一个组合适配器（CAD）连接miRNA 结合用于Illumina测序的标准3'-和5'-适配器的序列，产生miRNA-CAD 连接产品； （ii）miRNA-CAD产物的圆形化； （iii）阻止不属于的自由CAD物种 连接到mirnas； （iv）圆形miRNA-CAD产物的RT-PCR扩增以产生标准 测序放大器包含一个单个RNA特异性序列插入，两侧是5'-和3'-apapter 序列。在第一阶段，我们证明了miR-ACS方法的可行性（概念证明） 与最佳当前库准备方法相比，大大减少了miRNA测序偏差。在阶段 ii我们将彻底优化miR-ACS，以最大程度地减少偏差并允许对更大种类进行测序 RNA（尺寸最高150 nt）的RNA输入非常低。此外，我们将简化协议以促进 用户的采用和商业可行性。