Name: optimization for sequencing and analysis of degraded ffpe-rna samples
Uploaded: 2020-06-08T15:00:00
Description: Watch this Scientific Journal Video about Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples at JoVE.com

我们感谢Danielle Carrick博士（国家癌症研究所癌症控制和人口科学司）的持续帮助，特别是为发起这项研究、向我们提供样本以及数据分析过程中的有益建议。我们衷心感谢弗雷德里克国家癌症研究实验室CCR测序基金的所有成员在样品制备和测序方面给予的帮助，特别是布伦达·霍在样品QC、奥克萨纳德语图书馆QC、塔蒂亚娜·斯米尔诺娃（Tatyana Smirnova）操作测序器方面给予的帮助。我们还要感谢测序设施生物信息学集团的沈蔡伟和阿什利·沃尔顿帮助数据分析和RNA-seq管道实施。我们还感谢 CCBR 和 NCBR 在 RNaseq 分析管道和最佳实践开发方面提供的援助。

1. RNA数量和质量评估
<ol><li>根据预定义的标准选择FFPE样品，并使用适当的方法（例如，FFPE-核酸萃取试剂盒、材料表）提取RNA。 注：有几种不同的方法可用于FFPE-RNA提取，包括较新的微解剖方法，可以工作很少的组织，并提取高质量的RNA12，13，14。12,13,14</li>
	<li>应尽最大努力在所有阶段保持RNA的完整性。这包?...

<ol>
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此处描述的方法概述了从 FFPE-RNA 样品获取良好序列数据所需的主要步骤。使用这种方法需要考虑的要点是：（1） 通过最小化样品处理和冷冻和解冻周期，确保提取后尽可能保存RNA。单独的 QC 等号是非常有帮助的。（2） 使用最适合给定样本集的质量控制指标。RIN 值和 DV200通常对降级样本没有用处，DV100可能是评估给定样本集中质量的首选指标。（3） 对于更退化的样品，最好使?...

使用下一代测序方法使我们能够从各种类型的样品中收集大量信息。但是，对于常用的生成序列数据的方法，旧样本和保存不良的样本仍然不起作用，并且通常需要对成熟的协议进行修改。FFPE组织代表这种样本类型，已广泛用于临床标本11，2，3。2,3虽然FFPE保存维持组织形态，但FFPE组织中的核酸通常表现出广泛的损伤和降解，使得很难检索基因组信息，这些信息可能导致对各种疾病背后的分子机制有重要的见解。
RNA测序产生的基因表达数据通常有助于研究疾病和抗药性机制，并补充DNA突变分析。然而，RNA更容易降解，使得从FFPE组织生成准确的基因表达数据更具挑战性。此外，由于测序的广泛可用性和可负担性是较新的，较老的标本往往没有储存在保持RNA完整性所需的条件下。FFPE样品的一些问题包括：由于嵌入石蜡而导致RNA降解，RNA的化学改性导致测序所需的酶过程的分裂或折射性，以及多A尾部的丢失，限制了寡聚-dT作为反向转录酶的引物的适用性。另一个挑战是在次优条件下处理/储存FFPE样品，这可能导致组织5中的RNA等实验室分子进一步降解。这尤其与在预计对样本进行RNA测序的基因表达分析时可能收集的较老样本特别相关。所有这些都导致提取的RNA的质量和数量下降，可用于生成有用的序列数据。成功概率低，加上测序成本高，使许多研究人员无法尝试从可能有用的FFPE样本中生成和分析基因表达数据。近年来的一些研究表明，FFPE组织在基因表达分析22、6、7、8、96,7,方面的可用性，尽管样本较少和/或较新。8,9
作为可行性研究，我们使用从从监测、流行病学和最终结果（SEER）癌症登记册中提取的FFPE肿瘤组织标本中提取的RNA，用于RNA测序和基因表达分析10。从临床病理实验室采购，来自高级卵巢血清腺癌的FFPE组织在RNA提取前的不同条件下储存7-32年。因为在大多数情况下，这些块储存在不同的地点多年，没有期望将来有任何敏感的基因分析，没有采取任何谨慎保存核酸。因此，大多数样品的RNA质量较差，大部分样品被细菌污染。然而，我们能够执行基因定量，测量基因覆盖的均匀性和连续性，并在生物复制中执行Pearson相关分析，以测量可重复性。基于一组关键特征基因面板，我们将研究中的样本与癌症基因组图谱（TCGA）数据进行了比较，确认约60%的样本具有可比的基因表达特征11。根据各种QC结果和样本元数据之间的相关性，我们确定了关键QC指标，这些指标具有良好的预测价值，可用于识别更有可能生成可用序列数据11的样本。
在这里，我们描述了用于FFPE-RNA质量评估的方法，从提取的RNA样本开始的测序库的生成，以及测序数据的生物信息分析。

<table>
	<tbody>
		<tr>
			<td>2100 Bioanalyzer</td>
			<td>Agilent</td>
			<td>G2939BA</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent DNA 7500 Kit</td>
			<td>Agilent</td>
			<td>5067-1506</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent High Sensitivity DNA Kit</td>
			<td>Agilent</td>
			<td>5067-4626</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent RNA 6000 Nano Kit</td>
			<td>Agilent</td>
			<td>5067-1511</td>
			<td></td>
		</tr>
		<tr>
			<td>AllPrep DNA/RNA FFPE Kit</td>
			<td>Qiagen</td>
			<td>80234</td>
			<td></td>
		</tr>
		<tr>
			<td>CFX96 Touch System</td>
			<td>Bio-Rad</td>
			<td>1855195</td>
			<td></td>
		</tr>
		<tr>
			<td>Library Quantification kit v2-Illumina</td>
			<td>KapaBiosystems</td>
			<td>KK4824</td>
			<td></td>
		</tr>
		<tr>
			<td>NEBNext Ultra II Directional RNA Library Prep Kit for Illumina</td>
			<td>New England Biolabs</td>
			<td>E7765S</td>
			<td>https://www.neb.com/protocols/2017/02/07/protocol-for-use-with-ffpe-rna-nebnext-rrna-depletion-kit</td>
		</tr>
		<tr>
			<td>NEBNext rRNA Depletion Kit (Human/Mouse/Rat)</td>
			<td>New England Biolabs</td>
			<td>E6310L</td>
			<td></td>
		</tr>
		<tr>
			<td>NextSeq 500 Sequencing System</td>
			<td>Illumina</td>
			<td>SY-415-1001</td>
			<td>NextSeq 500 System guide: https://support.illumina.com/content/dam/illumina-support/documents/documentation/system_documentation/nextseq/nextseq-500-system-guide-15046563-06.pdf</td>
		</tr>
		<tr>
			<td>NextSeq PhiX Control Kit</td>
			<td>Illumina</td>
			<td>FC-110-3002</td>
			<td></td>
		</tr>
		<tr>
			<td>NSQ 500/550 Hi Output KT v2.5 (150 CYS)</td>
			<td>Illumina</td>
			<td>20024907</td>
			<td></td>
		</tr>
		<tr>
			<td>10X Genomics Magnetic Separator</td>
			<td>10X Genomics</td>
			<td>120250</td>
			<td></td>
		</tr>
		<tr>
			<td>Rotator Multimixer</td>
			<td>VWR</td>
			<td>13916-822</td>
			<td></td>
		</tr>
		<tr>
			<td>C1000 Touch Thermal Cycler</td>
			<td>Bio-Rad</td>
			<td>1851197</td>
			<td></td>
		</tr>
		<tr>
			<td>Sequencing reagent kit</td>
			<td>Illumina</td>
			<td>20024907</td>
			<td></td>
		</tr>
		<tr>
			<td>Flow cell package</td>
			<td>Illumina</td>
			<td>20024907</td>
			<td></td>
		</tr>
		<tr>
			<td>Buffer cartridge and the reagent cartridge</td>
			<td>Illumina</td>
			<td>20024907</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium hydroxide solution (0.2N)</td>
			<td>Millipore Sigma</td>
			<td>SX0607D-6</td>
			<td></td>
		</tr>
		<tr>
			<td>TRIS-HCL Buffer 1.0M, pH 7.0</td>
			<td>Fisher Scientific</td>
			<td>50-151-871</td>
			<td></td>
		</tr>
	</tbody>
</table>

optimization for sequencing and analysis of degraded ffpe-rna samples

RNA测序（RNA-seq）的基因表达分析能够对临床样本进行独特的洞察，从而潜在地了解各种疾病的基础以及抗药性和/或易感性机制。然而，FFPE组织是临床标本中保存组织形态的最常见方法，它不是基因表达分析的最佳来源。从这些样本中获得的RNA通常退化、碎片和化学修饰，从而导致测序库不理想。反过来，这些生成质量较差的序列数据，对于基因表达分析和突变发现可能不可靠。为了充分利用FFPE样品，并从低质量样品中获取最佳数据，在规划实验设计、准备测序库和数据分析过程中采取某些预防措施非常重要。这包括使用适当的指标进行精确的样品质量控制 （QC），确定测序库生成期间各种步骤的最佳方法，以及仔细的库 QC。此外，应用正确的软件工具和参数进行序列数据分析对于识别RNA-seq数据中的伪影、过滤污染和低质量读取、评估基因覆盖率的均匀性以及测量生物复制中基因表达特征的可重复性至关重要。这些步骤可确保对非常异构RNA样品进行分析的高精度和可重复性。在这里，我们描述了样品QC，库制备和质量控制，测序和数据分析的各种步骤，可以帮助增加从低质量RNA获得的有用数据的数量，例如从FFPE-RNA组织获得的数据。

上述方法适用于67个FFPE样品，这些样品在各种不同条件下储存了7~32年（样本储存中值为17.5年）。此处介绍的数据集和分析结果此前在赵等11年进行了描述和发布。在检查样品质量时，如前面所述（即图2中的示例痕迹），DV100被认为比 DV200更有用处，因为准确测量高降解 RNA 样品较小片段大小的比例更为敏感。
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Watch this Scientific Journal Video about Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples at JoVE.com

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

该方法描述了提高从正式固定石蜡嵌入（FFPE）RNA样品中获得的序列数据的质量和数量的步骤。我们描述了更准确地评估FFPE-RNA样品质量、准备测序库和分析FFPE-RNA样品数据的方法。

降解FFPE-RNA样品测序与分析优化

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding ...

我们的协议可用于提高从FFPE衍生的RNA样本生成的基因表达数据的质量和数量，特别是在质量欠佳的样品中。该技术评估FFPE组织样品中的RNA质量，并优化其下游处理，以提高样品测序数据的数量和质量。此方法允许在生物和临床样本中全面鉴定成绩单，并可能提供对基因组在发育和疾病中的功能元素的洞察。FFPE-RNA降解和样品质量控制方法的选择、库制备和数据分析都十分棘手。在选择正确的方法和适当的控制措施时要一丝不苟。视觉演示允许观看者观察在规划、评估和测序过程中所需的细微修改和预防措施，尤其是对于保存不善的 FFPE 样品。要检查RNA样品的质量，请根据制造商的说明在RNA QC系统上运行样品，并使用适当的生物分析软件分析样品中RNA片段的分布，并计算超过100个和200个核苷酸的片段比例。根据质量控制指标，识别片段少于 40% 的样本，其片段时间超过 100 个核苷酸，以便排除这些样品的加工。对于测序，根据室温水浴中的运行参数解冻相应的测序试剂盒，并在解冻后将试剂盘放在四摄氏度。将流量电池包装在室温下放置 30 分钟。当包正在变暖时，打开 Illumina 实验管理器应用程序并选择"创建示例表"。选择要使用的音序器，然后单击"下一步"。输入试剂盒条形码和其他适当的工作流程参数。然后上传根据 Illumina 序列条件创建的示例表。要准备样本库和控制库 PhiX，请将数据库进行变性和稀释到适当的浓度，并混合样品和 PhiX 控制库以获得 5% PhiX 控制容积比。当流动细胞准备就绪时，取出包装，用无绒醇擦拭清洁玻璃表面，然后用低绒实验室组织擦干玻璃。从四摄氏度的存储中取出试剂盒，并反转墨盒五次以混合试剂。轻轻敲击工作台上的墨盒，以减少气泡，将变性和稀释的样品装入指定储液罐中的试剂盒中。将流动电池、缓冲盒和试剂盒加载到系统中。然后执行自动检查并检查输出，以确保运行参数通过系统检查。自动检查完成后，选择开始排序运行。要可视化预处理 QC 和对齐后 QC 结果，请运行多 QC 以 HTML 格式生成聚合报告。若要确定批处理效果并评估给定数据集的质量映射，请使用 R 脚本运行主组件分析。然后，可以使用不同样本之间的 Pearson 相关性进行样本相关性分析。估计超过100个核苷酸的片段比例比估计超过200个核苷酸的片段更有用，因为它对于准确测量高降解RNA样本较小片段比例更敏感。鉴于样品组的高降解程度，建议采用总RNA库制备方法。例如，此处显示了从四个不同的样本编写的排序库。此处显示了原始 FastQ 文件排序质量和示例适配器内容的概述。FastQC 筛查有助于检测样品中的细菌或小鼠污染等污染。STAR 对齐可用于确定映射到参考基因组的读取比例、唯一映射到参考基因组的读取百分比以及未映射或映射到多个位置的读取比例。卡和 RSeQC 统计信息可用于确定映射读取中信使 RNA、电子基和互生基的百分比。对于这些具有代表性的分析，一些降级的库存在三个主要偏差，其中，与五个主要端更靠近三个黄金末尾的读取映射更多。此外，还可以执行主要成分分析，以确定每个样品的生物复制的主要成分捕获的总变异百分比。注意避免样品降解，为每个样品准备复制和多个涂层，使用适当的指标来评估样品质量，并使用正确的库准备方法。使用这种方法，可以使用以前无法使用的 FFPE 样本进行更大的 NGS 研究，这些样本具有不同的存储时间和条件，从而深入了解各种不同的疾病状态。该技术为研究人员研究现有的具有丰富临床信息的大型FFPE样本档案铺平了道路，可以大大加强基于人群的癌症研究。

Research

JoVE Journal

Genetics

Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma

经典霍奇金淋巴瘤的芦苇细胞的流分选和外显子测序

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically ...

科研

遗传学

Detection of Copy Number Alterations Using Single Cell Sequencing

单细胞测序拷贝数改变的检测

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and ...

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

适用于下一代测序的植物细菌DNA富集方法的优化与比较分析

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic ...

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

核密度分析的天然染色质沉淀测序文库的生成

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution ...

Chromatin Immunoprecipitation (ChIP) Protocol for Low-abundance Embryonic Samples

Chromatin Immunoprecipitation ChIP Protocol for Low-abundance Embryonic Samples

低丰度胚胎标本的染色质沉淀 (芯片) 协议

Chromatin immunoprecipitation (ChIP) is a widely-used technique for mapping the localization of post-translationally modified histones, histone variants, ...

Robust DNA Isolation and High-throughput Sequencing Library Construction for Herbarium Specimens

植物标本标本的鲁棒 DNA 分离与高通量测序库建设

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

基于纠错 DNA 和 RNA 测序的稀有事件检测方法

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been ...

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

用于下一代测序的近全长 HIV-1 Proviruses 的扩增

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near ...

Semiconductor Sequencing for Preimplantation Genetic Testing for Aneuploidy

用于抗倍体植入前基因测试的半导体测序

Chromosomal aneuploidy, one of the main causes leading to embryonic development arrest, implantation failure, or pregnancy loss, has been well documented ...

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

纳米测序全血 mRNA 测序

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, ...