Name: identification of circular rnas using rna sequencing
Uploaded: 2019-11-14T11:00:00
Description: Watch this Scientific Journal Video about Identification of Circular RNAs using RNA Sequencing at JoVE.com

我们感谢亚利桑那州太阳城的旗帜太阳健康研究所脑和身体捐赠计划（BBDP）提供人脑组织。BBDP得到了国家神经疾病和中风研究所（U24 NS072026帕金森病及相关疾病国家脑和组织资源）、国家老龄问题研究所（P30AG19610亚利桑那州阿尔茨海默病核心中心）、亚利桑那州卫生服务部（合同211002， 亚利桑那阿尔茨海默氏症研究中心），亚利桑那生物医学研究委员会（合同4001，0011，05-901和1001到亚利桑那州帕金森病联合会）和迈克尔J。福克斯帕金森研究基金会27日。这项研究也得到了国土安全部和亚利桑那州（ADHS补助金+ADHS14-052688）的支持。我们还感谢安德里亚·施密特（班纳研究）和辛西娅·莱丘加（TGen）提供的行政支持。

这项研究是按照所有机构、国家和国际人类福利准则进行的。脑组织从位于亚利桑那州太阳城的横幅太阳健康研究所脑和身体捐献项目获得。大脑和身体捐赠计划的运作由西方机构审查委员会（WIRB协议#20120821批准）。所有主体或其法律代表在知情同意书上签了字。商业（非脑）生物标本是从蛋白酶中购买的。
1. RNase R 治疗
注：在以下步骤中，...

<ol>
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在这项研究中，测试了两个市售的库制备试剂盒、预处理选项和输入RNA量，以优化circRNA扩充协议，用于构建circRNA测序库。根据本研究的评估，在创建 circRNA 测序库方面，一些关键方面和关键步骤是显而易见的。我们的评估证实了RNase R预处理的效用，这反映在检测到的环RNA数量的增加上。总体而言，在使用具有RNase R预处理和4μg输入RNA的Illumina TruSeq库试剂盒时，环RNA的倍增性更高。这些结果与先?...

循环RNA（CircRNA）是内源性的、非编码的RNA，由于它们在真核转录组1、2、3中的普遍表达而备受关注。它们形成于外向的回拼接时，因此最初被认为是拼接伪像4，5。然而，最近的研究表明，circRNA表现出细胞类型，组织和发育阶段的具体表达3，6和进化保存2，3。此外，它们还参与调节蛋白质-蛋白质相互作用7、微RNA（miRNA）结合3、8、9、10和调节亲基因转录11。
在经典RNA测序（RNA-seq）中，由于多A选择mRNA，在库构建过程中，循环RNA可能完全丢失，或者由于丰度低，可能难以分离。然而，最近的circRNA表征研究已经纳入了使用RNase R的预处理步骤，以丰富circRNA2，12，13。RNase R 是一种驱外酶，可消化线性RNA，留下圆形RNA结构。CircRNA扩充方案通过生成和比较来自两个市售的全转录组构建试剂盒的数据进行优化，无论是否采用RNase R预处理步骤，并使用不同量的总RNA输入（1至4μg）。接下来，优化的协议用于评估五个不同大脑区域（小脑 [BC]、下垂叶 [IP]、中端脑环叶 [MG]、下垂皮层 [OC] 和上等前额陀螺 [SF]） 和四个其他组织类型（肝脏 [LV]、肺 [LU]、淋巴结 [LN] 和胰腺] 的环状RNA的丰度。RNA-seq库对端测序，并使用六种不同的circRNA预测算法对数据进行分析：find_circ3，CIRI14，Mapsplice15，KNIFE16，DCC17和CIRCexplorer18。根据我们的分析，当使用带有RNase R预处理和4μg总输入RNA的搁浅总RNA库制备试剂盒时，检测到的唯一循环RNA数量最多。此处介绍了优化的协议。正如先前报道的19，20，与其他组织类型相比，大脑中观察到的环RNA的富集性最高。

<table>
	<tbody>
		<tr>
			<td>1000 &#181;L pipette tips</td>
			<td>Rainin</td>
			<td>GP-L1000F</td>
			<td></td>
		</tr>
		<tr>
			<td>20 &#181;L pipette tips</td>
			<td>Rainin</td>
			<td>SR L 10F</td>
			<td></td>
		</tr>
		<tr>
			<td>200 &#181;L pipette tips</td>
			<td>Rainin</td>
			<td>SR L 200F</td>
			<td></td>
		</tr>
		<tr>
			<td>2200 TapeStation Accessories (foil covers)</td>
			<td>Agilent Technologies</td>
			<td>5067-5154</td>
			<td></td>
		</tr>
		<tr>
			<td>2200 TapeStation Accessories (tips)</td>
			<td>Agilent Technologies</td>
			<td>5067-5153</td>
			<td></td>
		</tr>
		<tr>
			<td>Adhesive Film for Microplates</td>
			<td>VWR</td>
			<td>60941-064</td>
			<td></td>
		</tr>
		<tr>
			<td>AMPure XP Beads 450 mL</td>
			<td>Beckman Coulter</td>
			<td>A63882</td>
			<td>PCR purification</td>
		</tr>
		<tr>
			<td>Eppendorf twin.tec 96-Well PCR Plates</td>
			<td>VWR</td>
			<td>951020401</td>
			<td></td>
		</tr>
		<tr>
			<td>High Sensitivity D1000 reagents</td>
			<td>Agilent Technologies</td>
			<td>5067-5585</td>
			<td></td>
		</tr>
		<tr>
			<td>High Sensitivity D1000 ScreenTape</td>
			<td>Agilent Technologies</td>
			<td>5067-5584</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 2500 Sequencing System</td>
			<td>Illumina</td>
			<td>SY-401-2501</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 3000/4000 PE Cluster Kit</td>
			<td>Illumina</td>
			<td>PE-410-1001</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 3000/4000 SBS Kit (150 cycles)</td>
			<td>Illumina</td>
			<td>FC-410-1002</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 4000 Sequencing System</td>
			<td>Illumina</td>
			<td>SY-401-4001</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq PE PE Rapid Cluster Kit v2</td>
			<td>Illumina</td>
			<td>PE-402-4002</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq Rapid SBS Kit v2 (50 cycle)</td>
			<td>Illumina</td>
			<td>FC-402-4022</td>
			<td></td>
		</tr>
		<tr>
			<td>Kapa Total RNA Kit</td>
			<td>Roche</td>
			<td>KK8400</td>
			<td></td>
		</tr>
		<tr>
			<td>Molecular biology grade ethanol</td>
			<td>Fisher Scientific</td>
			<td>BP28184</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit Assay Tubes</td>
			<td>Supply Center by Thermo Fischer</td>
			<td>Q32856</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit dsDNA High Sense Assay Kit</td>
			<td>Supply Center by Thermo Fischer</td>
			<td>Q32854</td>
			<td></td>
		</tr>
		<tr>
			<td>RNA cleanup and concentrator - 5</td>
			<td>Zymo</td>
			<td>RCC-100</td>
			<td>Contains purification columns, collection tubes</td>
		</tr>
		<tr>
			<td>RNAClean XP beads</td>
			<td>Beckman Coulter Genomics</td>
			<td></td>
			<td>RNA Cleanup beads</td>
		</tr>
		<tr>
			<td>Rnase R</td>
			<td>Lucigen</td>
			<td>RNR07250</td>
			<td></td>
		</tr>
		<tr>
			<td>SuperScript II Reverse Transcriptase 10,000 units</td>
			<td>ThermoFisher (LifeTech)</td>
			<td>18064014</td>
			<td></td>
		</tr>
		<tr>
			<td>TapeStation 2200</td>
			<td>Agilent Technologies</td>
			<td></td>
			<td>Nucleic Acid analyzer</td>
		</tr>
		<tr>
			<td>TElowE</td>
			<td>VWR</td>
			<td>10128-588</td>
			<td></td>
		</tr>
		<tr>
			<td>TruSeq Stranded Total RNA Library Prep Kit</td>
			<td>Illumina</td>
			<td>20020596</td>
			<td>Kit used in section 3</td>
		</tr>
		<tr>
			<td>Two-Compartment Divided Tray</td>
			<td>VWR</td>
			<td>3054-1004</td>
			<td></td>
		</tr>
		<tr>
			<td>UltraPure Water</td>
			<td>Supply Center by Thermo Fischer</td>
			<td>10977-015</td>
			<td></td>
		</tr>
		<tr>
			<td>Universal control RNA</td>
			<td>Agilent</td>
			<td>740000</td>
			<td></td>
		</tr>
	</tbody>
</table>

identification of circular rnas using rna sequencing

循环RNA（循环RNA）是一类非编码RNA，涉及微RNA（miRNA）调节、蛋白质-蛋白质相互作用的中介和父母基因转录的调节等功能。在传统的下一代RNA测序（RNA-seq）中，在mRNA库的构建过程中，由于多A选择，循环RNA通常被忽视，或者发现丰度非常低，因此难以分离和检测。在这里，通过比较库制备试剂盒、预处理选项和各种RNA输入总量，优化了circRNA库构建协议。测试了两个市售全转录组库制备试剂盒，带和无RNase R预处理，并使用可变量的总RNA输入（1至4μg）。测试。最后，多种组织类型;包括肝、肺、淋巴结和胰腺;以及多个大脑区域;包括小脑、下垂叶、中时陀螺、腹皮层和上额前陀螺;比较以评估组织类型的环RNA丰度。使用六种不同的环RNA检测工具（find_circ、CIRI、Mapsplice、KNIFE、DCC和CIRCexplorer）对生成的RNA-seq数据进行分析后发现，具有RNase R预处理和4μgRNA输入的搁浅总RNA库制备试剂盒是最佳选择用于识别最高相对数量的环RNA 的方法。与以前的发现一致，与其他组织类型相比，在脑组织中观察到的环RNA的富集性最高。

使用市售的通用控制RNA（UC）和使用两个库制备试剂盒生成的数据，这两个试剂盒在其协议中都包括核糖核酸消耗步骤。使用分析工作流（数据分析工作流，第 4 节），总体而言，TruSeq 数据集中检测到的环RNA 数量高于 Kapa 数据集（图 1）。尽管两个试剂盒的数据集中的核糖体RNA （rRNA） 百分比低于 5%，输入量较低（1，2 微克），但 Kapa 数据集的 rRNA 含量较高，为 4、5 和 10 ug...

Watch this Scientific Journal Video about Identification of Circular RNAs using RNA Sequencing at JoVE.com

Identification of Circular RNAs using RNA Sequencing

循环RNA（循环RNA）是非编码RNA，在转录调节和蛋白质之间的中介相互作用中可能发挥作用。在对构建环RNA测序库的不同参数进行评估后，利用RNase R预处理的搁浅总RNA库制备编制了一个协议，并在此提出。

使用RNA测序识别循环RNA

Circular RNAs (circRNAs) are a class of non-coding RNAs involved in functions including micro-RNA (miRNA) regulation, mediation of protein-protein ...

该协议是评估圆RNA库制备的关键方面的结果，如试剂盒类型、RNase R治疗、输入量及其对圆环RNA检测的影响。它可实现最佳的圆环RNA检测，并根据用户的需求提供有关可调参数的数据。识别不同样本类型的圆环RNA将有助于我们更好地了解其表达的分布，并设置这些分子的功能作用。此方法可应用于任何总RNA样本。在开始协议之前，将RNA样本放在冰上是重要的。在准备前评估安捷伦生物分析器或磁带站上的 RIN 和 DV200 值，并在使用 RNA 时遵循适当的步骤。首先在39微升无RNase水中将总RNA稀释至4微克，然后上下移液混合。在单独的管中，使用 1x RNase R 缓冲液将 RNase R 稀释到每微升两个单位的工作浓度。将总RNA的39微升和5个微升的10xRNase R反应缓冲液放入1.5微升反应管中，并混合。加入稀释的 RNase R.的六微升，然后将移液器调整为全反应量，然后通过上下移液 10 次混合溶液。将管子放在37摄氏度的水浴中10分钟，确保将全部反应量浸入水浴中。然后，将管子放在冰上，并立即进行RNA清理和浓缩。在开始之前，准备RNA洗涤缓冲液，将浓缩液与48毫升100%乙醇混合，并放入收集管中。准备就绪后，将两卷RNA结合缓冲液添加到RNase R处理样品中，并很好地混合。在混合物中加入150微升100%乙醇，共300微升，将整个体积转移到柱子上，并离心机30秒。去除流，并将400微升RNA准备缓冲液直接添加到柱子中。离心30秒，然后丢弃流经。然后，将700微升RNA洗涤缓冲液加入柱，离心机30秒，然后丢弃流经。再添加 400 微升的洗涤缓冲器，离心机两分钟，并将柱转移到新的无 RNase 1.5 毫升管中。将移液器尖端在柱过滤器正上方，小心地将 11 微升无 RNase 水直接添加到柱中。让样品在室温下坐一分钟，然后离心一分钟。确保 1.5 毫升管中有流量，然后丢弃柱。纯化的RNA样品可以储存在零下80摄氏度，或立即用于库准备。将纯化总RNA的10微升转移到96井PCR板中的清洁井中。加入五微升的 rRNA 结合缓冲液，然后加入五升 rRNA 去除混合微升，然后轻轻上下移液器混合试剂。密封板，并在68摄氏度的高温下在预编程和预热热循环器块上孵育5分钟。孵育后，让板在室温下坐一分钟。从板上取下密封件，并将 35 微升涡旋室温 rRNA 去除珠添加到样品中。将移液器调整为 45 微升，上下移液器 10 至 20 次以彻底混合。让板在室温下坐一分钟。将板转移到磁性支架上，在那里孵育一分钟或直到溶液清除。将上一液转移到板上的新井。然后将板从磁性支架转移到板支架上。涡流RNA清理珠子，直到它们被很好地分散，并添加99微升珠到样品。上下移液混合，在室温下孵育板10分钟。将板转移到磁性支架上，并在那里保留五分钟，或直到溶液清除，然后从井中清除并丢弃所有上清液。当板还在磁支架上时，在井中加入200微升新鲜准备好的80%乙醇，而不会打乱珠子。将乙醇留在井中30秒，然后取出并丢弃。向井中加入 11 微升的洗脱缓冲液，然后上下移液混合。在室温下孵育板两分钟，然后将其转移回磁性支架，并一直放在该板，直到溶液清除。将 8.5 微升的上一液转移到同一板上的新井中，并将 8.5 微升的 Elute、Primer、碎片高混合添加到每个包含样品的井中。上下移液10次，以彻底混合，密封板，并在热循环器预热至94摄氏度中孵育8分钟。将样品冷却至4摄氏度，从热循环器中取出板，并短暂离心。为该协议评估了两个图书馆准备工具包，TruSeq和KAKA。总体而言，使用TruSeq试剂盒时检测到的圆形RNA数量和核糖核糖核RNA百分比较低，因此选择TruSeq进行进一步实验。通过比较预处理和非预处理库生成的数据，评估了 RNase R 预处理的重要性。正如预期的那样，与未预处理的库相比，在预处理库中始终识别着数量较高的循环RNA。输入RNA的量经过优化，可检测循环RNA的更高多样性。库使用1、2和4微克输入RNA，使用4微克总RNA时观察到循环RNA物种的最高多样性。优化方案用于比较来自四个健康捐赠者的五个大脑区域的循环RNA丰度，以及来自六个健康捐赠者的其他组织类型。总的来说，与其他组织类型相比，大脑中观察到的圆形RNase的丰度更高。在开始协议之前，在使用 RNA 时，必须记住遵循适当的程序，包括戴手套、用 RNase 湿巾彻底清洁长凳和移液器或喷雾器，以及事先将 RNA 放在冰上。按照这个程序，可以执行正交验证，如桑格测序识别的圆RNA结。新的环RNA的发现和它们存在的进一步证据开辟了探索其生物功能的新研究领域。

identification-of-circular-rnas-using-rna-sequencing

Research

JoVE Journal

Genetics

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

Knowing how RNAs interact with themselves and with others is key to understanding RNA based gene regulation in the cell. While examples of RNA-RNA interactions such as microRNA-mRNA interactions have been shown to regulate gene expression, the full extent to which RNA interactions occur in the cell is still unknown. Previous methods to study RNA interactions have primarily focused on subsets of RNAs that are interacting with a particular protein or RNA species. Here, we detail a method named Sequencing of Psoralen crosslinked, Ligated, and Selected Hybrids (SPLASH) that allows genome-wide capture of RNA interactions in vivo in an unbiased manner. SPLASH utilizes in vivo crosslinking, proximity ligation, and high throughput sequencing to identify intramolecular and intermolecular RNA base-pairing partners globally. SPLASH can be applied to different organisms including bacteria, yeast and human cells, as well as diverse cellular conditions to facilitate the understanding of the dynamics of RNA organization under diverse cellular contexts. The entire experimental SPLASH protocol takes about 5 days to complete and the computational workflow takes about 7 days to complete.

Here, we detail the method of Sequencing of Psoralen crosslinked, Ligated, and Selected Hybrids (SPLASH), which enables genome-wide mapping of intramolecular and intermolecular RNA-RNA interactions in vivo. SPLASH can be applied to study RNA interactomes of organisms including yeast, bacteria and humans.

使用生物素化补骨脂素全球定位RNA-RNA相互作用

Knowing how RNAs interact with themselves and with others is key to understanding RNA based gene regulation in the cell. While examples of RNA-RNA ...

科研

遗传学

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for protein synthesis by translating codons in mRNA into amino acid sequences. tRNAs were long considered as house-keeping molecules that lacked regulatory functions. However, a growing body of evidence indicates that cellular tRNA levels fluctuate in correspondence to varying conditions such as cell type, environment, and stress. The fluctuation of tRNA expression directly influences gene translation, favoring or repressing the expression of particular proteins. Ultimately comprehending the dynamic of protein synthesis requires the development of methods able to deliver high-quality tRNA profiles. The method that we present here is named SPOt, which stands for Streamlined Platform for Observing tRNA. SPOt consists of three steps starting with metabolic labeling of cell cultures with radioactive orthophosphate, followed by guanidinium thiocyanate-phenol-chloroform extraction of radioactive total RNAs and finally hybridization on in-house printed macroarrays. tRNA levels are estimated by quantifying the radioactivity intensities at each probe spot. In the protocol presented here we profile tRNAs in Mycobacterium smegmatis mc2155, a nonpathogenic bacterium often used as a model organism to study tuberculosis.

We describe an original transfer RNA analysis platform named SPOt (Streamlined Platform for Observing tRNA). SPOt simultaneously measures cellular levels of all tRNAs in biological samples, in only three steps, and in less than 24 hours.

使用 Macroarrays 的转移 rna 的代谢标记和剖面分析

Transfer RNAs (tRNA) are abundant short non-coding RNA species that are typically 76 to 90 nucleotides in length. tRNAs are directly responsible for ...

Retrospective MicroRNA Sequencing: Complementary DNA Library Preparation Protocol Using Formalin-fixed Paraffin-embedded RNA Specimens

&#8211;Archived, clinically classified formalin-fixed paraffin-embedded (FFPE) tissues can provide nucleic acids for retrospective molecular studies of cancer development. By using non-invasive or pre-malignant lesions from patients who later develop invasive disease, gene expression analyses may help identify early molecular alterations that predispose to cancer risk. It has been well described that nucleic acids recovered from FFPE tissues have undergone severe physical damage and chemical modifications, which make their analysis difficult and generally requires adapted assays. MicroRNAs (miRNAs), however, which represent a small class of RNA molecules spanning only up to ~18&#8211;24 nucleotides, have been shown to withstand long-term storage and have been successfully analyzed in FFPE samples. Here we present a 3&#39; barcoded complementary DNA (cDNA) library preparation protocol specifically optimized for the analysis of small RNAs extracted from archived tissues, which was recently demonstrated to be robust and highly reproducible when using archived clinical specimens stored for up to 35 years. This library preparation is well adapted to the multiplex analysis of compromised/degraded material where RNA samples (up to 18) are ligated with individual 3&#39; barcoded adapters and then pooled together for subsequent enzymatic and biochemical preparations prior to analysis. All purifications are performed by polyacrylamide gel electrophoresis (PAGE), which allows size-specific selections and enrichments of barcoded small RNA species. This cDNA library preparation is well adapted to minute RNA inputs, as a pilot polymerase chain reaction (PCR) allows determination of a specific amplification cycle to produce optimal amounts of material for next-generation sequencing (NGS). This approach was optimized for the use of degraded FFPE RNA from specimens archived for up to 35 years and provides highly reproducible NGS data.

Formalin-fixed paraffin-embedded specimens represent a valuable source of molecular biomarkers of human diseases. Here we present a laboratory-based cDNA library preparation protocol, initially designed with fresh frozen RNA, and optimized for the analysis of archived microRNAs from tissues stored up to 35 years.

回顾性 MicroRNA 排序: 用福尔马林固定石蜡嵌入 RNA 标本补充 DNA 文库制备协议

&#8211;Archived, clinically classified formalin-fixed paraffin-embedded (FFPE) tissues can provide nucleic acids for retrospective molecular studies of ...

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been used to analyze the spectrum of clonal mutations in malignancy. Though far more efficient than traditional Sanger methods, NGS struggles with identifying rare clonal and subclonal mutations due to its high error rate of ~0.5&#8211;2.0%. Thus, standard NGS has a limit of detection for mutations that are &#62;0.02 variant allele fraction (VAF). While the clinical significance for mutations this rare in patients without known disease remains unclear, patients treated for leukemia have significantly improved outcomes when residual disease is &#60;0.0001 by flow cytometry. In order to mitigate this artefactual background of NGS, numerous methods have been developed. Here we describe a method for Error-corrected DNA and RNA Sequencing (ECS), which involves tagging individual molecules with both a 16 bp random index for error-correction and an 8 bp patient-specific index for multiplexing. Our method can detect and track clonal mutations at variant allele fractions (VAFs) two orders of magnitude lower than the detection limit of NGS and as rare as 0.0001 VAF.

Next-generation sequencing (NGS) is a powerful tool for genomic characterization that is limited by the high error rate of the platform (~0.5&#8211;2.0%). We describe our methods of error-corrected sequencing that allow us to obviate the NGS error rate and detect mutations at variant allele fractions as rare as 0.0001.

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 ...

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

The identification of physical interactions between genes and regulatory elements is challenging but has been facilitated by chromosome conformation capture methods. This modification to the 4C-seq protocol mitigates PCR bias by minimizing over-amplification of PCR templates and maximizes the mappability of reads by incorporating an addition restriction enzyme digest step.

利用下一代序列染色体构象捕获 (4 c 序列) 的高通量识别基因调控数列

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and ...

Overexpressing Long Noncoding RNAs Using Gene-activating CRISPR

Long noncoding RNA (lncRNA) biology is a new and exciting field of research, with the number of publications from this field growing exponentially since 2007. These studies have confirmed that lncRNAs are altered in almost all diseases. However, studying the functional roles for lncRNAs in the context of disease remains difficult due to the lack of protein products, tissue-specific expression, low expression levels, complexities in splice forms, and lack of conservation among species. Given the species-specific expression, lncRNA studies are often restricted to human research contexts when studying disease processes. Since lncRNAs function at the molecular level, one way to dissect lncRNA biology is to either remove the lncRNA or overexpress the lncRNA and measure cellular effects. In this article, a written and visualized protocol to overexpress lncRNAs in vitro is presented. As a representative experiment, an lncRNA associated with inflammatory bowel disease, Interferon Gamma Antisense 1 (IFNG-AS1), is shown to be overexpressed in a Jurkat T-cell model. To accomplish this, the activating clustered regularly interspaced short palindromic repeats (CRISPR) technique is used to enable overexpression at the endogenous genomic loci. The activating CRISPR technique targets a set of transcription factors to the transcriptional start site of a gene, enabling a robust overexpression of multiple lncRNA splice forms. This procedure will be broken down into three steps, namely (i) guide RNA (gRNA) design and vector construction, (ii) virus generation and transduction, and (iii) colony screening for overexpression. For this representative experiment, a greater than 20-fold enhancement in IFNG-AS1 in Jurkat T cells was observed.

Traditional cDNA-based overexpression techniques have a limited applicability for the overexpression of long noncoding RNAs due to their multiple splice forms with potential functionality. This review reports a protocol using CRISPR technology to overexpress multiple splice variants of a long noncoding RNA.

使用基因激活 crispr 过度表达长非编码 rna

Long noncoding RNA (lncRNA) biology is a new and exciting field of research, with the number of publications from this field growing exponentially since ...

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, and was deployed to West Africa during the recent Ebola virus epidemic, highlighting this possibility. In addition to its practical advantages (low cost, ease of equipment transport and use), this technology also provides fundamental advantages over second-generation sequencing approaches, particularly the very long read length, ability to directly sequence RNA, and real-time availability of data. Raw read accuracy is lower than with other sequencing platforms, which represents the main limitation of this technology; however, this can be partially mitigated by the high read depth generated. Here, we present a field-compatible protocol for sequencing of the mRNAs encoding for Niemann-Pick C1, which is the cellular receptor for ebolaviruses. This protocol encompasses extraction of RNA from animal blood samples, followed by RT-PCR for target enrichment, barcoding, library preparation, and the sequencing run itself, and can be easily adapted for use with other DNA or RNA targets.

Nanopore sequencing is a novel technology that allows cost-effective sequencing in remote locations and resource-poor settings. Here, we present a protocol for sequencing of mRNAs from whole blood that is compatible with such conditions.

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, ...

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to normal and pathological conditions. The goal of this protocol is to generate high-quality, large-scale transcriptome data of each endocrine cell type with the use of a droplet-based microfluidic single-cell RNA sequencing technology. Such data can be utilized to build the gene expression profile of each endocrine cell type in normal or specific conditions. The process requires careful handling, accurate measurement, and rigorous quality control. In this protocol, we describe detailed steps for human pancreatic islets dissociation, sequencing, and data analysis. The representative results of about 20,000 human single islet cells demonstrate the successful application of the protocol.

Here, we present a protocol to generate high-quality, large-scale transcriptome data of single cells from isolated human pancreatic islets using a droplet-based microfluidic single-cell RNA sequencing technology.

人类胰腺胰岛的单细胞RNA测序与分析

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to ...

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing (RIPiT-Seq)

RNA immunoprecipitation in tandem (RIPiT) is a method for enriching RNA footprints of a pair of proteins within an RNA:protein (RNP) complex. RIPiT employs two purification steps. First, immunoprecipitation of a tagged RNP subunit is followed by mild RNase digestion and subsequent non-denaturing affinity elution. A second immunoprecipitation of another RNP subunit allows for enrichment of a defined complex. Following a denaturing elution of RNAs and proteins, the RNA footprints are converted into high-throughput DNA sequencing libraries. Unlike the more popular ultraviolet (UV) crosslinking followed by immunoprecipitation (CLIP) approach to enrich RBP binding sites, RIPiT is UV-crosslinking independent. Hence RIPiT can be applied to numerous proteins present in the RNA interactome and beyond that are essential to RNA regulation but do not directly contact the RNA or UV-crosslink poorly to RNA. The two purification steps in RIPiT provide an additional advantage of identifying binding sites where a protein of interest acts in partnership with another cofactor. The double purification strategy also serves to enhance signal by limiting background. Here, we provide a step-wise procedure to perform RIPiT and to generate high-throughput sequencing libraries from isolated RNA footprints. We also outline RIPiT&#39;s advantages and applications and discuss some of its limitations.

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing RIPiT-Seq

Here, we present a protocol to enrich endogenous RNA binding sites or &#34;footprints&#34;&#160;of RNA:protein (RNP) complexes from mammalian cells. This approach involves two immunoprecipitations of RNP subunits and is therefore dubbed RNA immunoprecipitation in tandem (RIPiT).

RNA足迹的识别:通过RNA免疫沉淀在串联中的蛋白质复合物,然后测序(RIPiT-Seq)

RNA immunoprecipitation in tandem (RIPiT) is a method for enriching RNA footprints of a pair of proteins within an RNA:protein (RNP) complex. RIPiT ...

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

The study of small RNAs (sRNAs) by next-generation sequencing (NGS) is challenged by bias issues during library preparation. Several types of sRNA such as plant microRNAs (miRNAs) carry a 2&#39;-O-methyl (2&#39;-OMe) modification at their 3&#39;&#160;terminal nucleotide. This modification adds another difficulty as it inhibits 3&#39;&#160;adapter ligation. We previously demonstrated that modified versions of the &#39;TruSeq (TS)&#39;&#160;protocol have less bias and an improved detection of 2&#39;-OMe RNAs. Here we describe in detail protocol &#39;TS5&#39;, which showed the best overall performance. TS5 can be followed either using homemade reagents or reagents from the TS kit, with equal performance.

Improving Small RNA-seq: Less Bias and Better Detection of 2&#039;-O-Methyl RNAs

We present a detailed small RNA library reparation protocol with less bias than standard methods and an increased sensitivity for 2&#39;-O-methyl RNAs. This protocol can be followed using homemade reagents to save cost or using kits for convenience.

改进小RNA-seq：减少偏差，更好地检测2'-O-甲基RNA

The study of small RNAs (sRNAs) by next-generation sequencing (NGS) is challenged by bias issues during library preparation. Several types of sRNA such as ...