我们非常感谢我们的同事斯蒂芬·休斯和亨利·莱文的意见，这是建立逆转录病毒整合位点的测序NGS协议在恩格尔曼实验的关键。这项工作是由美国国立卫生研究院授予AI039394和​​AI052014（以ANE）和AI060354（哈佛大学艾滋病研究中心）的支持。

The authors have nothing to disclose.

一种用于逆转录病毒整合位点的分析协议，从通过基因组分布模式映射的初始病毒感染步骤，进行说明。这个协议是适用于任何反转录病毒和任何可感染的细胞类型。此外，该测定管道是相当敏感，以回收的从基因组DNA等效的系列稀释独特的整合位点令人满意编号以与6.4×10 -5的MOI启动的感染的可能性。当从可能含有低病毒载量，其中只有细胞的一小部分会窝藏集成原病​​毒感染的患者施加到样本这种敏感性使得协议特别有用。在这一领域36,38,41-43之前方法论的论文一致，在这个协议的生物信息学部分的多个步骤将定制的脚本开发受益顺序处理大量数据文件。虽然BLAT 58是马pping在本协议中所述程序，用户可能会发现蝴蝶结67（http://bowtie-bio.sourceforge.net/index.shtml）是一个合适的选择。 一个替代的生物信息学流水线最近报道的测定莫洛尼鼠白血病病毒（的MoMLV）整合位点19。在它被开发成独立的软件，是可公开获得的，并且是相当强大的，因为它最初是用于映射成千上万的独特的MoMLV整合位点即管道是有用的。然而，现有的软件最初被设计为专门重新分析报告的MoMLV数据集，所以重新编程将是必要定制管道交替的实验设计（该工具的功能是最近扩展到包括腺相关病毒和TOL2和AC / Ds转载体68）。此外，该协议描述的初步整合位点的产生.bed文件，但并没有制定出必要的地图网站的具体步骤，相关的基因组注释。读者可能会发现"向整合位点分析"服务器69，这是当前稿件的审查过程中释放，分析使用此处描述的协议所产生的NGS序列非常有用。 某些点应该使用任何协议时，分析逆转录病毒整合位点的数据集被强调。当在串联制备多个库，一个显著潜在存在样品的交叉污染。即使样品的串扰非常小的水平可以掩盖的结果以呈现NGS运行不可用的水平。因此，所有的湿钳工工作应在消毒，专用层流罩或PCR工作站来完成。一组吸液管和试剂诸如无核酸酶的水，应专门致力于整合位点扩增。每个库制备过程中使用独特的连接体可以限制潜在的跨放大，并且还允许交叉鉴定原始FASTA文件中的每个库中读取。 考虑使用超声与酶切片段化的基因组DNA的优劣是很重要的。一方面，超声处理提供剪切点的相对随机分布，但随后所需DNA修复和A尾步骤持续降低的接头连接产物的产率相比，用限制酶产生的粘性末端进行结扎。另一方面，限制性酶消化提供剪切点，这将不可避免地引入已恢复的数据中的一些偏倚的-支付较少的人口。利用限制性内切酶以丢弃上游LTR序列将在两种情况下（ 图1）导致在位于基因组中的该位点的上游整合位点的一小部分的损失。任何数据偏差，可能会导致可广告通过文库制备过程中忽略从协议的酶消化，过滤掉导致从测序数据上游LTR序列的众多打扮。 虽然当前协议是相当敏感的，能够产生数百万的独特整合位点21,40，所有可用的集成的仅约三分之一的可预期在即使有最好的库制剂（参考的给定实验被放大。70和未发表意见）。分析从暗藏的病毒载量低的低MOI感染或患者的样品时，这可能引起并发症。这种限制可以部分通过重复测序同样文库制备和/或测序并行同一DNA样本得出多个库来克服。在检测灵敏度提高未来也会相应是逆转录病毒整合位点的测序深化翻译应用非常有利。

病毒DNA（VDNA）到宿主细胞基因组中的整合是在逆转录病毒的生命周期的一个重要步骤。积分是由病毒酶整合酶（IN），其执行，导致建立稳定地插入原病毒1的两个不同的催化过程来完成的。在亚基接合是通过逆转录生成的线性VDNA的端部，形成具有VDNA高阶intasome端通过一个IN多聚体2-4保持在一起。在切割中称作3&#39;-处理的处理顺序的3&#39;从不变5&#39;-CA-3下游VDNA的端部"，留下凹入3&#39;在每个VDNA末端5-8活性羟基结束。该intasome随后导入细胞核作为大型组件的主机的一部分，并称为preintegration复合物（PIC），9-11的病毒蛋白。遇到细胞靶DNA（T-DNA）后，使用VDNA 3&#39;-羟基GRO起坐裂解TDNA顶部和底部股线以交错的方式，同时通过链转移12,13的过程中加入VDNA到TDNA 5&#39;磷酸基团。 在本地和全球尺度上表现出逆转录病毒整合位点的偏好。在当地，共识的整合位点包括了从VDNA插入位点14,15大约五到十个基点的上游和下游跨越弱保守的回文T-DNA序列。全球范围内，逆转录病毒针对具体的染色质注释16。有七种不同的逆转录病毒属 - 通过ε，伦蒂和spuma阿尔法。慢病毒，包括HIV-1，有利于积极转录基因17机构内部整合，而gammaretroviruses优先整合到转录起始位点（起始位置跟）和有源增强地区18-20。与之形成鲜明对比，泡沫病毒强烈向heterochrom偏见ATIC区域，如基因贫乏椎板相关领域21。当地TDNA基地偏好由IN和T-DNA 13,22,23之间核蛋白的接触特定网络决定的很大一部分。对于慢病毒和gammaretroviruses，相对于基因组注释集成是通过中和同源细胞因子24-27之间的相互作用支配很大一部分。改变IN-T-DNA相互作用网络13,22,23,28的细节，扰乱或重新工程宿主因子交互25-27,29-32是行之有效的战略分别重新定位在本地和全球层面的整合。 用来编目逆转录病毒整合位点的DNA测序方法的功率在过去几十年的极大增加。整合位点用费力净化和手工克隆技术产生只是根据研究33,34独特的网站屈指可数回收创举。LTR宿主DNA结的LM-PCR扩增与映射单个整合位点，以转化领域人类和小鼠草案基因组，与来自外源组织培养细胞的感染中回收网的增加至几百到上千17数量的能力的结合18。 LM-PCR检测方法NGS的更近的组合已派出图书馆深度跃然而出。具体而言，焦磷酸测序，得到的独特的集成网站30,35-38数以万计的量级，而库测序通过使用DNA聚类可以产生数以百万计的独特序列19-21,39的。在这里，我们描述了扩增和测序使用DNA集群NGS逆转录病毒整合位点的优化LM-PCR方法。该方法结合了所需的适配器序列引入PCR引物，因此直接进入扩增的DNA分子，从而排除了要求用于向sequen之前一个额外的适配器连接步骤庆安40。在生物信息学分析管道中，从LTR宿主DNA结到的独特的整合位点的映射到相关的基因组特征的原始测序数据的解析，也一般地描述。按照这一领域36,38,41-43从以前的方法确定的协议的优先级，自定义脚本可以开发，以帮助在生物信息学管道的具体步骤的完成。该实用程序和协议的灵敏度通过扩增，测序和映射从在感染的1.0（MOI），以及一个滴定系列该DNA的近似多重感染的组织培养细胞中的HIV-1的整合位点与代表性数据示出通过未感染的细胞的DNA中稀释5倍的步骤为1的最大稀释度:15625，得到的6.4×10 -5的近似等效惯性矩。

<table border="0" cellpadding="0" cellspacing="0" width="1326">
	<tbody>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">DMEM</td>
			<td style="width:199px;">Gibco</td>
			<td style="width:111px;">11965-084</td>
			<td style="width:780px;">Standard cell culture medium, compatible with HEK293T cells</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Fetal Bovine Serum</td>
			<td style="width:199px;">Thermo Scientific</td>
			<td style="width:111px;">SH 30088.03</td>
			<td>Different lots of serum may need to be pre-screened for optimal viral production</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Penicillin/Streptomycin</td>
			<td style="width:199px;">Corning</td>
			<td style="width:111px;">30-002-Cl</td>
			<td>Antibiotics to be added to DMEM</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Phosphate-buffered saline</td>
			<td style="width:199px;">Mediatech</td>
			<td style="width:111px;">21-040-CV</td>
			<td>Used to wash cells</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Trypsin EDTA</td>
			<td style="width:199px;">Corning</td>
			<td style="width:111px;">25-053-CI</td>
			<td>Used to detach adherent cells from tissue culture plates</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">PolyJet</td>
			<td style="width:199px;">SignaGen Laboratories</td>
			<td style="width:111px;">SL100688</td>
			<td>DNA transfection reagent</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:237px;">0.45 &#181;m Filters</td>
			<td style="width:199px;">Thermo Scientific</td>
			<td>09-740-35B</td>
			<td>Used to filter virus particle-containing cell culture media</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Turbo DNase</td>
			<td style="width:199px;">Ambion</td>
			<td style="width:111px;">AM2239</td>
			<td>Used to degrade carryover plasmid DNA from virus stocks</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">HIV-1 p24 Antigen Capture Assay</td>
			<td style="width:199px;">ABL Inc.</td>
			<td style="width:111px;">5447</td>
			<td>Used to quantify yield of virus production</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">DNeasy Blood &#38; Tissue Kit</td>
			<td style="width:199px;">Qiagen</td>
			<td style="width:111px;">69506</td>
			<td>Used to purify genomic DNA from cells</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Sonicator</td>
			<td style="width:199px;">Covaris</td>
			<td style="width:111px;">S2</td>
			<td>With this model of sonicator perform two rounds of duty cycle, 5%; intensity, 3; cycles per burst, 200; time, 80 sec</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Nuclease-Free Water</td>
			<td style="width:199px;">GeneMate</td>
			<td style="width:111px;">G-3250-125</td>
			<td>Commercially-available water is recommended to reduce the possibility of sample cross-contamination</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">QIAQuick PCR Purification Kit</td>
			<td style="width:199px;">Qiagen</td>
			<td style="width:111px;">28106</td>
			<td>Used to purify DNA during library construction</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">End-It DNA End-Repair Kit</td>
			<td style="width:199px;">Epicentre</td>
			<td style="width:111px;">ER81050</td>
			<td>Used to repair DNA ends of sonicated DNA samples</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Klenow Fragment (3&#39;-5&#39; exo&#8211;)</td>
			<td style="width:199px;">New England Biolabs (NEB)</td>
			<td style="width:111px;">M0212S</td>
			<td>Used with dATP to A-tail repaired DNA fragments</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">dATP</td>
			<td style="width:199px;">Thermo Scientific</td>
			<td style="width:111px;">R0141</td>
			<td>Deoxyadenosine triphosphate</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">MseI</td>
			<td style="width:199px;">NEB</td>
			<td>R0525L</td>
			<td>Restriction endonuclease for genomic DNA cleavage</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">BglII</td>
			<td style="width:199px;">NEB</td>
			<td style="width:111px;">R0144L</td>
			<td>Restriction endonuclease to suppress amplification of upstream HIV-1 U5 sequence</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">T4 DNA Ligase</td>
			<td style="width:199px;">NEB</td>
			<td style="width:111px;">M0202L/6218</td>
			<td>Enzyme for covalent joining of compatible DNA ends</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">DNA Oligonucleotides</td>
			<td>Integrated DNA Technologies</td>
			<td>custom</td>
			<td>Have the company purify the oligos. HPLC purification suffices for DNAs &#60;30 nucleotides; PAGE purify longer DNAs&#160;</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Advantage 2 Polymerase Mix</td>
			<td style="width:199px;">Clontech</td>
			<td style="width:111px;">639202</td>
			<td>Commercial mix containing DNA polymerase for PCR</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">dNTPs (100 mM solutions)</td>
			<td style="width:199px;">Thermo Scientific</td>
			<td style="width:111px;">R0181</td>
			<td>Dilute the four chemicals on ice with sterile water to reach the intermediate worrking concentrations of 2.5 mM each dNTP</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">NanoDrop</td>
			<td style="width:199px;">Thermo Scientific</td>
			<td style="width:111px;">NanoDrop 2000</td>
			<td>Spectrophotometer for determination of DNA concentration</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">Qubit Fluorimeter</td>
			<td style="width:199px;">Life Technologies</td>
			<td style="width:111px;">Qubit&#174; 3.0</td>
			<td>Fluorometer used to confirm integration site library DNA concentration</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">2200 TapeStation System</td>
			<td style="width:199px;">Agilent</td>
			<td style="width:111px;">G2964AA</td>
			<td>Tape-based assay to confirm integration site library DNA size distribution</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:237px;">MiSeq</td>
			<td style="width:199px;">Illumina</td>
			<td style="width:111px;">SY-410-1003</td>
			<td>Used for NGS</td>
		</tr>
	</tbody>
</table>

amplification, next-generation sequencing, and genomic dna mapping of retroviral integration sites

在本地和全球尺度上表现出逆转录病毒整合签名的偏好。这里，我们提出了（1）的生成用连接介导的PCR（LM-PCR）扩增和新一代测序（NGS）逆转录病毒整合位点的不同的库的详细的协议;（2）绘制的每个病毒 - 的基因组位置使用BEDTools交界处，和（3）分析统计相关数据主机。从感染的细胞中提取的基因组DNA是通过消化用限制性酶或通过超声处理分段。合适的DNA末端修复后，双链连接子连接到DNA末端，和半巢式PCR是使用这两个病毒的长末端重复（LTR）端部和连接接头DNA互补的引物进行的。 PCR引物携带NGS期间用于DNA聚类所需的序列，否定为单独的适配器连接的要求。质量控制（QC）下进行，以评估DNA片段大小分布和适应呃之前NGS DNA结合。序列输出文件过滤含有LTR-读取，并确定LTR和连接器的序列裁剪掉。修剪宿主细胞序列被映射到使用BLAT参照基因组和被过滤为最小97％的同一性的参照基因组中的独特点。独特的整合位点是审查相邻核苷酸（nt）的顺序和分配相对于不同的基因特性。使用该协议，高复杂度的整合位点文库可从基因组DNA在三天构成。该包括易感组织培养细胞至整合位点分析的外源病毒感染的整个协议可以因此在大约一到两周进行。这项技术的应用近期涉及到艾滋病毒感染患者的整合位点的纵向分析。

表4列出一个代表性实验的结果，以示出用于从感染细胞的培养物中回收整合位点的NGS的灵敏度。未感染的细胞的DNA被用于串联从其中在平均每个细胞包含一个积分40的感染稀释的基因组DNA。 15625:在五个步骤的1的最大稀释制备稀释液。在滴定系列的基因组DNA，然后通过超声处理片段化或通过用限制性内切核酸酶消化MseI和BglⅡ，随后的LM-PCR的独特整合位点的数目，以及网站地图近端到选定的基因组注释的数目，是根据上述方案计算。数据分析显示，数十个独特的集成网站（量的1-2％，从整齐的基因组DNA恢复）从哪里理论上只有15625人被感染的细胞制备库恢复。 </p&gt; 当分析整合位数据集，这是至关重要的数据进行比较，以匹配组随机基因组位点，这被称为匹配的随机控制或MRC。作为代表性的结果通过限制性内切酶消化或超声剪切基因组DNA，两个不同的数据集MRC构建。 MRC 恩茨包含从hg19随机选择地点邻近MseI和BglⅡ酶切的部位产生50000独特的基因组位点，而MRC 随机窝藏10000个网站不归从设置基因组标记物的距离产生。仅可映射回一个独特基因组位置的位点应该在MRC的数据集一起使用。作为超声剪基因组DNA从序列偏压基本上不含，MRC 随机可能被视为较适用于由通过超声处理的DNA片段化所产生的数据集。管控一体化的另类风格站点数据集可以在体外通过重组蛋白质反应而产生，intasome核蛋白复合21，或从急性感染的细胞17与脱蛋白的基因组DNA提取的PIC，然后按照对LM-PCR和NGS协议21。 为整合位点的通过超声处理对限制性消化（比较纯样品之间），以及用于比较的MRC ENZ和MRC 随机的 ，显示在图2中 。整合位点的分布回收回收的分布比较的P值以下超声处理是类似于由限制回收酶消化用于检查的所有注释，以在对CpG岛接近而言明显的最大方差。正如预期的那样18,65两个数据集显著从缅甸红十字会在集成方面的RefSeq基因和基因Ð内不同密度周围的平均整合位点，而两个数据集是相对于CpG岛和起始位置跟分配方面类似缅甸红十字会。由于相对较少的HIV-1的整合位点映射内的CpG岛或TSS的2.5 kb的，增加网的总数回收降低的倾向，可以集（ 表4和图2）之间产生的可变性。序列标识来确认整合位数据的真实性示于图3。共识的HIV-1整合位点14,22（-3）TDG （G / V）的TWA（C / B）CHA（+7）（使用的生物化学基本代码国际联盟写入;反斜杠表示VDNA的位置正链连接和下划线表示5-bp的序列重复以下的HIV-1整合和DNA修复）可以由两个分片技术制备的库明显看出，虽然确定性程度与感染细胞的稀释增大而减小脱氧核糖核酸。从对比数据MRC对准的随机位置未能产生基地偏好可观的水平。 <img alt="图1" src="/files/ftp_upload/53840/53840fig1.jpg" /> 图1:集成网站库制剂流程图说明 （ 一 ）通过转染HEK293T细胞，收获和过滤上清液48小时后，通过超速离心浓缩和感染靶细胞的病毒适当浓度生成病毒股票。感染后至少五天，提取基因组DNA。请参阅第1及额外的实验细节正文2。 （B和C）片段纯化的基因组DNA消化用限制性酶或通过超声处理。限制性内切酶鸡尾酒应该包括酶（ 如 BglII位）下游从上游病毒LTR裂解反击-选择LM-P内部VDNA序列的CR放大。绿色星号和（C）中支箭头表示该BglⅡ位应该接头结扎之后施加。红色亮点病毒序列，而黑色的亮点宿主细胞的序列。隐含DNA断裂点（不按比例）由"X"标记的HIV-1包含许多MseI和Ⅱ部位;只有那些相关的协议被示出。地图上方的括号表示由LM-PCR优先扩增所述U5-细胞DNA的区域。 （D）净化零散的DNA（然后最终修复超声的情况和A-尾），并以结扎（E）兼容的非对称连接分子（蓝色）。在（D）的品红圆圈表示将要放大的整合位点。在连接器的短链的3&#39;末端的星号表示氨基保护修饰。 （ 六 ）开展第一轮的半巢式PCR用首轮LTR底漆（红色）和连接器的引物（蓝色）。在T他的PCR回合中，接头引物编码的DNA聚类和NGS引物结合序列（分组为绿色附属物蓝色接头引物），而LTR的引物缺乏这样的序列。 （G）净化第一轮PCR产物，并进行第二轮半巢式PCR。在这一轮的PCR，使用相同的接头引物与在第一轮（蓝+绿附属物），与第二轮LTR引物（红色）携带的DNA的聚类和NGS引物结合序列以及用于复用条形码（一起分组为一个绿色的附属物红色LTR底漆）。 （H）净化第二轮PCR产物作为最终的整合位点库（品红色盒装，由品红圆圈标记整合位点）。提交等分，为质量控制和NGS测序服务。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53840/53840fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <i毫克ALT ="图2"SRC ="/文件/ ftp_upload / 53840 / 53840fig2.jpg"/&gt; 图 2:P 值对在DNA碎片用超声或经酶切与所属缅甸红十字会整合位点扩增比较 RefSeq的基因和附近的CpG岛和的TSS内的整合位点，以及区域的基因密度分布的数字，中列出。≥0.05以粗体和斜体突出表4中 的P值由Wilcoxon秩和检验计算Fisher精确测试b 的P值计算 的P值çMRC 恩茨 :。匹配随机控制;一套50000独特的整合位点是随机选择汞构建在接近MseI /BglⅡ限制位点位置产生19ðMRC 随机 :匹配包含10,000独特的整合位点随机控制通过随机selecti生产在没有正常化酶切位点接近hg19纳克的立场。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53840/53840fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图3" src="/files/ftp_upload/53840/53840fig3.jpg" /> 图3:序列标志描绘的HIV-1相应设定从代表实验库由（A）的用限制酶消化或（B）的声处理制备使用WebLogo软件进行比对库整合位点。在滴定系列的每个稀释描绘，从整齐的DNA在该图中，以第1的最大稀释的顶部:15625在底部。 （C）顺序徽标50,000独特的基因组位点的MRC。误差棒基本上代表在任何特定位置在碱掺入的标准偏差。更具体地，将n每个误差条的otal高度等同于小样品校正两次66，其用于熵存在于相对较小的数据集的低估控制。 x轴表示相对于集成在零点网站宿主细胞基因组DNA中核苷酸的立场。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53840/53840fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="表格1" src="/files/ftp_upload/53840/53840table1.jpg" /> 表1:连接器专用和第二寡核苷酸序列的链接建设和PCR扩增轮LTR引物编码DNA集群接头序列，这是颜色编码为:黑色，基地互补的链接或将HIV-1 LTR;红色，唯一索引或条码;绿色，测序引物结合位点;对于DNA集群蓝色，接头序列。单端（SE）测序REActions将利用测序引物退火到第二轮LTR引READ1（绿色）序列，而配对末端（PE）的反应将同时使用（READ1和READ2）测序引物。 一个链接的短链包含3&#39;氨基保护修改。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53840/53840table1large.jpg" target="_blank">请点击此处查看该表的放大版本。</a> <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> 试剂 </td><td> 要添加每反应 </td></tr><tr><td>第一轮LTR引物（15μM）: </td><td> 2.5微升</td></tr><tr><td>接头特异性引物（15μM）: </td><td> 0.5微升</td></tr><tr><td> 10X PCR缓冲液: </td><td> 2.5微升</td></tr><tr><td>的dNTP（2.5每个MM） </td><td> 0.5微升</td></tr><tr><td> DNA聚合酶组合: </td><td> 0.5微升</td></tr><tr><td>连接反应: </td><td> 100纳克</td></tr><tr><td>无核酸酶水: </td><td>多达25微升</td></tr></tbody></table> 表2:配方为第一轮的PCR要添加到每个单独的PCR管被指示每个指定试剂的量。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> 试剂 </td><td> 要添加每反应 </td></tr><tr><td>第二轮LTR引物（15μM）: </td><td> 2.5微升</td></tr><tr><td>接头特异性引物（15μM）: </td><td> 0.5微升</td></tr><tr><td> 10X PCR缓冲液: </td><td> 2.5微升</td></tr><tr><td>的dNTP（2.5每个MM） </td><td> 0.5微升</td></tr><tr><td> DNA聚合酶组合: </td><td> 0.5微升</td></tr><tr><td>第一轮PCR: </TD&gt; <td> 100纳克</td></tr><tr><td>无核酸酶水: </td><td>多达25微升</td></tr></tbody></table> 表3:第二轮PCR配方要添加到每个PCR管各试剂的量表示。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> 图书馆 </td><td> #Unique网站 </td><td> ％ 一 RefSeq的 </td><td> ％的CpG +/- 2.5 kb的b </td><td> TSS％+/- 2.5 kb的Ç </td><td> 平均。基因密度+/- 500 KBð </td></tr><tr><td>超声，整齐</td><td> 3,169 </td><td> 71.2 </td><td> 5.1 </td><td> 3.7 </td><td> 15.8 </td></tr><tr><td>超声处理，1:5 </td><td> 366 </td><td> 75.1 </td><td> 2.7 </td><td> 3 </td><td> 16.3 </td></tr><tr><tD&gt;超声，1:25 </td><td> 254 </td><td> 74 </td><td> 7.1 </td><td> 5.1 </td><td> 16.7 </td></tr><tr><td>超声处理，1:125 </td><td> 430 </td><td> 69.8 </td><td> 6.9 </td><td> 6 </td><td> 14.6 </td></tr><tr><td>超声处理，1:625 </td><td> 314 </td><td> 65.6 </td><td> 5.6 </td><td> 6.7 </td><td> 13.5 </td></tr><tr><td>超声处理，1:3,125 </td><td> 116 </td><td> 73.6 </td><td> 3.5 </td><td> 2.5 </td><td> 13.1 </td></tr><tr><td>超声处理，1:15625 </td><td> 72 </td><td> 62.5 </td><td> 0 </td><td> 1.4 </td><td> 14.7 </td></tr><tr><td>文摘，整齐</td><td> 7428 </td><td> 69.8 </td><td> 3.6 </td><td> 2.9 </td><td> 15.2 </td></tr><tr><td>消化，1:5 </td><td> 1460 </td><td> 71.4 </td><td> 4.4 </td><td> 3.4 </td><td> 14.9 </td></tr><tr><td>文摘1:25 </td><td> 394 </td><td> 68.8 </td><td> 4.3 </td><td> 3.3 </td><td> 15.8 </td></tr><tr> &lt;TD&gt;文摘，1:125 </td><td> 172 </td><td> 71 </td><td> 0 </td><td> 3 </td><td> 14 </td></tr><tr><td>消化，1:625 </td><td> 134 </td><td> 73.9 </td><td> 3.7 </td><td> 3.7 </td><td> 14.1 </td></tr><tr><td>消化，1:3,125 </td><td> 100 </td><td> 83.1 </td><td> 6.4 </td><td> 5.2 </td><td> 19.1 </td></tr><tr><td>消化，1:15625 </td><td> 73 </td><td> 74 </td><td> 4.1 </td><td> 1.4 </td><td> 9.7 </td></tr><tr><td> MRC 恩茨 ê </td><td> 50000 </td><td> 44.7 </td><td> 4.2 </td><td> 4 </td><td> 8.7 </td></tr><tr><td> MRC 随机 ˚F </td><td>万</td><td> 41.3 </td><td> 5.3 </td><td> 4.2 </td><td> 8.6 </td></tr></tbody></table> 表4: 代表滴定系列整合位点基因组总经销站点，整合日的百分比。在范围内的TSS的2.5 kb的秋天的RefSeq基因中，B CpG岛的2.5 kb的范围内，并且C D周围的平均整合位点有1 Mb内的基因密度E×MRC 恩茨 :。匹配随机控制;一套50000独特的整合位点被随机选择邻近的hg19 MseI /BglⅡ限制位点位置产生˚FMRC 随机 :包含通过随机选择在hg19位置，而正常化固定位置产生10,000个唯一的整 ​​合位点相匹配的随机控制。

Watch this Scientific Journal Video about Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites at JoVE.com

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

We describe a protocol for amplifying retroviral integration sites from the genomic DNA of infected cells, sequencing the amplified virus-host junctions, and then mapping these sequences to a reference genome. We also describe techniques to quantify the distribution of integration sites relative to various genomic annotations using BEDTools.

逆转录病毒整合位点的扩增，新一代测序和基因组DNA制图

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of ...

amplification-next-generation-sequencing-genomic-dna-mapping

Nanyang Technological University

Research

JoVE Journal

Biology

17.5K 次观看.  Dana-Farber Cancer Institute. We describe a protocol for amplifying retroviral integration sites from the genomic DNA of infected cells, sequencing the amplified virus-host junctions, and then mapping these sequences to a reference genome. We also describe techniques to quantify the distribution of integration sites relative to various genomic annotations using BEDTools.

视频: Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Isolation of Genomic DNA from Mouse Tails

从鼠尾基因组DNA提取

科研

生物学

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in their nucleotide composition and consist of a complex mosaic of sequence patterns. These patterns include so-called Mid-Range Inhomogeneity (MRI) regions -- sequences 30-10000 nucleotides in length that are enriched by a particular base or combination of bases (e.g. (G+T)-rich, purine-rich, etc.). MRI regions are associated with unusual (non-B-form) DNA structures that are often involved in regulation of gene expression, recombination, and other genetic processes (Fedorova &amp; Fedorov 2010). The existence of a strong fixation bias within MRI regions against mutations that tend to reduce their sequence inhomogeneity additionally supports the functionality and importance of these genomic sequences (Prakash et al. 2009).
Here we demonstrate a freely available Internet resource -- the Genomic MRI program package -- designed for computational analysis of genomic sequences in order to find and characterize various MRI patterns within them (Bechtel et al. 2008). This package also allows generation of randomized sequences with various properties and level of correspondence to the natural input DNA sequences. The main goal of this resource is to facilitate examination of vast regions of non-coding DNA that are still scarcely investigated and await thorough exploration and recognition.

We present a public computational web site for the analysis of genomic sequences. It detects DNA sequence patterns with various non-random nucleotide compositions. This resource also generates randomized sequences with diverse levels of complexity.

磁共振成像基因 - 公共资源为研究基因组DNA序列内模式

Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in ...

Competitive Genomic Screens of Barcoded Yeast Libraries

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily. The tempo of these advances is accelerating, promising greater depth and breadth. In light of these extraordinary advances, the need for fast, parallel methods to define gene function becomes ever more important. Collections of genome-wide deletion mutants in yeasts and E. coli have served as workhorses for functional characterization of gene function, but this approach is not scalable, current gene-deletion approaches require each of the thousands of genes that comprise a genome to be deleted and verified. Only after this work is complete can we pursue high-throughput phenotyping. Over the past decade, our laboratory has refined a portfolio of competitive, miniaturized, high-throughput genome-wide assays that can be performed in parallel. This parallelization is possible because of the inclusion of DNA 'tags', or 'barcodes,' into each mutant, with the barcode serving as a proxy for the mutation and one can measure the barcode abundance to assess mutant fitness. In this study, we seek to fill the gap between DNA sequence and barcoded mutant collections. To accomplish this we introduce a combined transposon disruption-barcoding approach that opens up parallel barcode assays to newly sequenced, but poorly characterized microbes. To illustrate this approach we present a new Candida albicans barcoded disruption collection and describe how both microarray-based and next generation sequencing-based platforms can be used to collect 10,000 - 1,000,000 gene-gene and drug-gene interactions in a single experiment.

We have developed comprehensive, unbiased genome-wide screens to understand gene-drug and gene-environment interactions. Methods for screening these mutant collections are presented.

条形码酵母图书馆竞争力的基因屏幕

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily.  The tempo of these advances is ...

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the subcellular distribution of a specific tagged fluorescent marker in the secretory pathway. Arabidopsis is a powerful biological model for genetic studies because of its genome size, generation time, and conservation of molecular mechanisms among kingdoms. The array genotyping as an approach to map the mutation in alternative to the traditional method based on molecular markers is advantageous because it is relatively faster and may allow the mapping of several mutants in a really short time frame. This method allows the identification of proteins that can influence the integrity of any organelle in plants. Here, as an example, we propose a screen to map genes important for the integrity of the endoplasmic reticulum (ER). Our approach, however, can be easily extended to other plant cell organelles (for example see1,2), and thus represents an important step toward understanding the molecular basis governing other subcellular structures.

A fundamental quest in cell biology is to define the mechanisms that underlie the identity of the organelles that make eukaryotic cells. Here we propose a method to identify the genes responsible for the morphological and functional integrity of plant organelles using fluorescence microscopy and next-generation sequencing tools.

荧光显微镜筛选和新一代测序:参与细胞器完整性的基因鉴定的有用工具

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the ...

Selective Capture of 5-hydroxymethylcytosine from Genomic DNA

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene expression, maintenance of genome integrity, parental imprinting, X-chromosome inactivation, regulation of development, aging, and cancer1. Recently, the presence of an oxidized 5-mC, 5-hydroxymethylcytosine (5-hmC), was discovered in mammalian cells, in particular in embryonic stem (ES) cells and neuronal cells2-4. 5-hmC is generated by oxidation of 5-mC catalyzed by TET family iron (II)/&alpha;-ketoglutarate-dependent dioxygenases2, 3. 5-hmC is proposed to be involved in the maintenance of embryonic stem (mES) cell, normal hematopoiesis and malignancies, and zygote development2, 5-10. To better understand the function of 5-hmC, a reliable and straightforward sequencing system is essential. Traditional bisulfite sequencing cannot distinguish 5-hmC from 5-mC11. To unravel the biology of 5-hmC, we have developed a highly efficient and selective chemical approach to label and capture 5-hmC, taking advantage of a bacteriophage enzyme that adds a glucose moiety to 5-hmC specifically12.
Here we describe a straightforward two-step procedure for selective chemical labeling of 5-hmC. In the first labeling step, 5-hmC in genomic DNA is labeled with a 6-azide-glucose catalyzed by &beta;-GT, a glucosyltransferase from T4 bacteriophage, in a way that transfers the 6-azide-glucose to 5-hmC from the modified cofactor, UDP-6-N3-Glc (6-N3UDPG). In the second step, biotinylation, a disulfide biotin linker is attached to the azide group by click chemistry. Both steps are highly specific and efficient, leading to complete labeling regardless of the abundance of 5-hmC in genomic regions and giving extremely low background. Following biotinylation of 5-hmC, the 5-hmC-containing DNA fragments are then selectively captured using streptavidin beads in a density-independent manner. The resulting 5-hmC-enriched DNA fragments could be used for downstream analyses, including next-generation sequencing.
Our selective labeling and capture protocol confers high sensitivity, applicable to any source of genomic DNA with variable/diverse 5-hmC abundances. Although the main purpose of this protocol is its downstream application (i.e., next-generation sequencing to map out the 5-hmC distribution in genome), it is compatible with single-molecule, real-time SMRT (DNA) sequencing, which is capable of delivering single-base resolution sequencing of 5-hmC.

Described is a two-step labeling process using &beta;-glucosyltransferase (&beta;-GT) to transfer an azide-glucose to 5-hmC, followed by click chemistry to transfer a biotin linker for easy and density-independent enrichment. This efficient and specific labeling method enables enrichment of 5-hmC with extremely low background and high-throughput epigenomic mapping via next-generation sequencing.

从基因组DNA选择性捕获的5  - 羟甲基

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene ...

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

One of the major questions in microbial ecology is &#8220;who is there?&#8221; This question can be answered using various tools, but one of the long-lasting gold standards is to sequence 16S ribosomal RNA (rRNA) gene amplicons generated by domain-level PCR reactions amplifying from genomic DNA. Traditionally, this was performed by cloning and Sanger (capillary electrophoresis) sequencing of PCR amplicons. The advent of next-generation sequencing has tremendously simplified and increased the sequencing depth for 16S rRNA gene sequencing. The introduction of benchtop sequencers now allows small labs to perform their 16S rRNA sequencing in-house in a matter of days. Here, an approach for 16S rRNA gene amplicon sequencing using a benchtop next-generation sequencer is detailed. The environmental DNA is first amplified by PCR using primers that contain sequencing adapters and barcodes. They are then coupled to spherical particles via emulsion PCR. The particles are loaded on a disposable chip and the chip is inserted in the sequencing machine after which the sequencing is performed. The sequences are retrieved in fastq format, filtered and the barcodes are used to establish the sample membership of the reads. The filtered and binned reads are then further analyzed using publically available tools. An example analysis where the reads were classified with a taxonomy-finding algorithm within the software package Mothur is given. The method outlined here is simple, inexpensive and straightforward and should help smaller labs to take advantage from the ongoing genomic revolution.

Characterizing microbial community has been a longstanding goal in environmental microbiology. Next-generation sequencing methods now allow for the characterization of microbial communities at an unprecedented depth with minimal cost and labor. We detail here our approach to sequence bacterial 16S ribosomal RNA genes using a benchtop sequencer.

的16S核糖体RNA基因的扩增子的新一代测序

One of the major questions in microbial ecology is &#8220;who is there?&#8221; This question can be answered using various tools, but one of the ...

Targeted DNA Methylation Analysis by Next-generation Sequencing

The role of epigenetic processes in the control of gene expression has been known for a number of years. DNA methylation at cytosine residues is of particular interest for epigenetic studies as it has been demonstrated to be both a long lasting and a dynamic regulator of gene expression. Efforts to examine epigenetic changes in health and disease have been hindered by the lack of high-throughput, quantitatively accurate methods. With the advent and popularization of next-generation sequencing (NGS) technologies, these tools are now being applied to epigenomics in addition to existing genomic and transcriptomic methodologies. For epigenetic investigations of cytosine methylation where regions of interest, such as specific gene promoters or CpG islands, have been identified and there is a need to examine significant numbers of samples with high quantitative accuracy, we have developed a method called Bisulfite Amplicon Sequencing (BSAS). This method combines bisulfite conversion with targeted amplification of regions of interest, transposome-mediated library construction and benchtop NGS. BSAS offers a rapid and efficient method for analysis of up to 10 kb of targeted regions in up to 96 samples at a time that can be performed by most research groups with basic molecular biology skills. The results provide absolute quantitation of cytosine methylation with base specificity. BSAS can be applied to any genomic region from any DNA source. This method is useful for hypothesis testing studies of target regions of interest as well as confirmation of regions identified in genome-wide methylation analyses such as whole genome bisulfite sequencing, reduced representation bisulfite sequencing, and methylated DNA immunoprecipitation sequencing.

Bisulfite amplicon sequencing (BSAS) is a method for quantifying cytosine methylation in targeted genomic regions of interest. This method uses bisulfite conversion paired with PCR amplification of target regions prior to next-generation sequencing to produce absolute quantitation of DNA methylation at a base-specific level.

有针对性的DNA甲基化分析通过新一代测序

The role of epigenetic processes in the control of gene expression has been known for a number of years. DNA methylation at cytosine residues is of ...

DamID-seq: Genome-wide Mapping of Protein-DNA Interactions by High Throughput Sequencing of Adenine-methylated DNA Fragments

The DNA adenine methyltransferase identification (DamID) assay is a powerful method to detect protein-DNA interactions both locally and genome-wide. It is an alternative approach to chromatin immunoprecipitation (ChIP). An expressed fusion protein consisting of the protein of interest and the E. coli DNA adenine methyltransferase can methylate the adenine base in GATC motifs near the sites of protein-DNA interactions. Adenine-methylated DNA fragments can then be specifically amplified and detected. The original DamID assay detects the genomic locations of methylated DNA fragments by hybridization to DNA microarrays, which is limited by the availability of microarrays and the density of predetermined probes. In this paper, we report the detailed protocol of integrating high throughput DNA sequencing into DamID (DamID-seq). The large number of short reads generated from DamID-seq enables detecting and localizing protein-DNA interactions genome-wide with high precision and sensitivity. We have used the DamID-seq assay to study genome-nuclear lamina (NL) interactions in mammalian cells, and have noticed that DamID-seq provides a high resolution and a wide dynamic range in detecting genome-NL interactions. The DamID-seq approach enables probing NL associations within gene structures and allows comparing genome-NL interaction maps with other functional genomic data, such as ChIP-seq and RNA-seq.

We describe herein an assay by coupling DNA adenine methyltransferase identification (DamID) to high throughput sequencing (DamID-seq). This improved method provides a higher resolution and a wider dynamic range, and allows analyzing DamID-seq data in conjunction with other high throughput sequencing data such as ChIP-seq, RNA-seq, etc.

DamID-SEQ:蛋白质-DNA相互作用的全基因组映射腺嘌呤甲基化的DNA片段通过高通量测序

The DNA adenine methyltransferase identification (DamID) assay is a powerful method to detect protein-DNA interactions both locally and genome-wide. It is ...

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding RNAs. Standard RNAseq requires 30 - 100 million sequencing reads and can include multiple RNA products such as mRNA and noncoding RNAs. We demonstrate how targeted RNAseq (capture) permits a focused study on selected RNA products using a desktop sequencer. RNAseq capture can characterize unannotated, low, or transiently expressed transcripts that may otherwise be missed using traditional RNAseq methods. Here we describe the extraction of RNA from cell lines, ribosomal RNA depletion, cDNA synthesis, preparation of barcoded libraries, hybridization and capture of targeted transcripts and multiplex sequencing on a desktop sequencer. We also outline the computational analysis pipeline, which includes quality control assessment, alignment, fusion detection, gene expression quantification and identification of single nucleotide variants. This assay allows for targeted transcript sequencing to characterize gene expression, gene fusions, and mutations.

We describe a targeted RNA sequencing-based method that includes preparation of indexed cDNA libraries, hybridization and capture with custom probes and data analysis to interrogate selected transcripts for gene expression, mutations, and gene fusions. Targeted RNAseq permits cost-effective, rapid evaluation of selected transcripts on a desktop sequencer.

有针对性的RNA测序分析表征基因表达和基因组改变

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding ...

Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing

Folding reporters are proteins with easily identifiable phenotypes, such as antibiotic resistance, whose folding and function is compromised when fused to poorly folding proteins or random open reading frames. We have developed a strategy where, by using TEM-1 &#946;-lactamase (the enzyme conferring ampicillin resistance) on a genomic scale, we can select collections of correctly folded protein domains from the coding portion of the DNA of any intronless genome. The protein fragments obtained by this approach, the so called &#34;domainome&#34;, will be well expressed and soluble, making them suitable for structural/functional studies.
By cloning and displaying the &#34;domainome&#34; directly in a phage display system, we have showed that it is possible to select specific protein domains with the desired binding properties (e.g., to other proteins or to antibodies), thus providing essential experimental information for gene annotation or antigen identification.
The identification of the most enriched clones in a selected polyclonal population can be achieved by using novel next-generation sequencing technologies (NGS). For these reasons, we introduce deep sequencing analysis of the library itself and the selection outputs to provide complete information on diversity, abundance and precise mapping of each of the selected fragment. The protocols presented here show the key steps for library construction, characterization, and validation.

The protocols described allow the construction, characterization and selection (against the target of choice) of a &#34;domainome&#34; library made from any DNA source. This is achieved by a research pipeline that combines different technologies: phage display, a folding reporter and next generation sequencing with a web tool for data analysis.

Interactome: Domainome 图书馆建设、噬菌体展示和下一代测序的验证与选择协议

Folding reporters are proteins with easily identifiable phenotypes, such as antibiotic resistance, whose folding and function is compromised when fused to ...