Preparation of sequencing libraries for multi-analyte analysis of small RNAs

制备用于小 RNA 多分析物分析的测序文库

基本信息

批准号：
10759916
负责人：
Sergei A Kazakov
金额：
$ 30万
依托单位：
REALSEQ BIOSCIENCES, INC.
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-21 至 2024-06-20
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10759916
关键词：
Address Awareness Bar Codes Benchmarking Biochemical Process Biogenesis Biological Biological Markers Cancer Diagnostics Cancer Patient Cells Circulation Code Complement Data Analyses Detection Development Discrimination Disease Evaluation Genes Human Hydroxyl Radical Length Libraries Malignant Neoplasms Maps Measures Messenger RNA Methods MicroRNAs Modeling Modification Monitor Mutation Nucleotides Patients Periodicity Phase Phosphorylation Plasma Preparation Process Protocols documentation Publishing RNA RNA Degradation RNA Sequences RNA analysis RNA-Binding Proteins RNA-Protein Interaction RNase protection assay Randomized Reaction Reproducibility Resistance Ribonucleases Sampling Screening for cancer Sensitivity and Specificity Small RNA Specificity Survival Rate Symptoms Technology Testing Tissues Transfer RNA United States Untranslated RNA Variant Visualization Work cancer biomarkers cancer therapy design detection method extracellular improved innovation inorganic phosphate leukemia miRNA expression profiling minimally invasive mortality novel novel strategies technology platform transcriptome sequencing tumor

项目摘要

Recent studies show that the mutations and dysregulated biogenesis of coding and non-coding RNA genes are associated with the development and progression as well as therapy resistance for various cancers. Sequencing analysis of the entire extracellular RNA fragmentome including small non-coding RNAs (like miRNA) as well as fragments of larger coding and non-coding RNA (like mRNA, lncRNA and tRNA) could potentially provide higher origin-specificity and sensitivity profiling required for their use as cancer biomarkers. However, there are technical problems limiting a visualization of the full complement of the RNA fragmentome, most of which is represented by small RNAs (sRNA) and sRNA fragments that are less than 50 nucleotides in size and possess 3’-phosphate (3’-p) or 2’,3’-cyclic phosphate (2’,3’-cP) along with 5’-hydroxyl (5’-OH) or 5’-phosphate (5’-p) termini. RNA molecules having such ends cannot be captured by standard sequencing library preparations which were designed to work primarily with sRNAs having 5’-p/3’-OH ends (e.g., miRNAs), and, therefore, are invisible (or hidden) from detection by sequencing. To analyze a broader spectrum of sRNAs in addition to miRNAs, it is essential to develop RNA-seq library preparation protocols that enable detection of all sRNA classes having different phosphorylation states of their ends as well as discrimination between these sRNA types with differing ends. Although some methods for analysis of the RNA fragmentome have been recently described, none of them provided options that would allow detection of either all sRNA types simultaneously or each type separately using the same approach for library preparation. Also, these methods are focused on detecting specific sRNAs with specific ends (e.g., 5’-OH or 3’-cP) and cannot distinguish between variations of phosphorylation status at the opposite sRNA end. Moreover, most of these methods use reaction conditions that require purification of reaction products before next reaction steps that might result in lost materials and reduced reproducibility. Lastly, there are no commercial kits available for sRNA-seq library preparations that would allow comprehensive analysis of RNA fragmentomics. To address these shortcomings, we propose an advanced approach, called RealSeq-RF, that represents further innovative development of our RealSeq® platform technology for making miRNA sequencing libraries (https://www.realseqbiosciences.com/technology). This new approach advances the capability of RealSeq® to allow detection of all sRNA types or one of them specifically. In Phase I we plan to develop the RealSeq-RF approach (initially) using model synthetic sRNAs (ssRNA) and then validate the developed approach by analyzing and comparing the sRNA fragmentome from plasma of healthy donors and leukemia patients. Because many types of leukemia show no obvious symptoms early in the disease, the development of minimally invasive, early-stage detection of leukemia would be a critical for its successful treatment.

最近的研究表明，编码和非编码 RNA 基因的突变和生物发生失调与与各种癌症的发生和进展以及治疗耐药性相关。整个细胞外 RNA 片段组的分析，包括小非编码 RNA（如 miRNA）以及较大的编码和非编码 RNA（如 mRNA、lncRNA 和 tRNA）片段可能提供更高的然而，它们用作癌症生物标志物所需的起源特异性和敏感性分析。技术问题限制了完整 RNA 片段组的可视化，其中大部分是以小RNA（sRNA）和小于50个核苷酸的sRNA片段为代表，并且具有 3'-磷酸盐 (3'-p) 或 2',3'-环状磷酸盐 (2',3'-cP) 以及 5'-羟基 (5'-OH) 或 5'-磷酸盐 (5'-p) ）具有此类末端的RNA分子不能被标准测序文库制剂捕获。被设计主要用于具有 5'-p/3'-OH 末端的 sRNA（例如 miRNA），因此是不可见的（或隐藏）通过测序检测来分析除 miRNA 之外的更广泛的 sRNA。对于开发 RNA-seq 文库制备方案至关重要，该方案能够检测所有具有以下特征的 sRNA：其末端的不同磷酸化状态以及这些 sRNA 类型之间的区别尽管最近描述了一些RNA片段组分析方法，但没有一种方法是这样的。提供了允许同时检测所有 sRNA 类型或单独检测每种类型的选项此外，这些方法专注于检测特定的 sRNA。具有特定末端（例如 5'-OH 或 3'-cP），并且无法区分磷酸化状态的变化此外，大多数这些方法使用需要纯化的反应条件。下一步反应步骤之前的反应产物可能会导致材料损失和重现性降低。没有可用于 sRNA-seq 文库制备的商业试剂盒可以进行全面的分析为了解决这些缺点，我们提出了一种先进的方法，称为 RNA 片段组学分析。 RealSeq-RF，代表了我们 RealSeq® 平台技术的进一步创新发展 miRNA 测序库 (https://www.realseqbiosciences.com/technology)。 RealSeq® 能够检测所有 sRNA 类型或其中一种，我们计划在第一阶段进行检测。使用模型合成 sRNA (ssRNA) 开发 RealSeq-RF 方法（最初），然后验证通过分析和比较健康捐献者血浆中的 sRNA 片段组和由于许多类型的白血病在疾病早期并没有明显的症状。开发白血病的微创早期检测技术将是其成功的关键治疗。