这项工作是从莫格里奇研究所的研究和威斯康星大学基金会的资金支持。我们感谢克里斯塔伊士曼社论援助。

1。提取总RNA <ol><li>加入1ml Trizol试剂细胞/组织，和同质化18-22如果有必要的纱布针。 </li><li>添加200μL氯仿，并在30分钟14000转的自旋在4 ° C </li><li>取出顶部的水层，添加0.5μL线性丙烯酰胺，再加入500μL异丙醇。让我们在室温下坐了20分钟。 </li><li>转速14000 RPM在4℃，洗涤沉淀，用70％乙醇，真空干燥。 </li><li>悬浮在1μL的核酸游离水和转移200μLPCR管。 </li></ol> 2。准备双链的cDNA <ol><li>以上1μLRNA 1μL100微米寡DT - T7反转录引物（5&#39; - GGCCAGTGAATTGTAATACGACTCACTATAGGGAGGCGGTTTTTTTTTTTTTTTTTTTTTTTT -3“），热在70 ° C为5分，和单元冰酷（加热块）。 </li><li>加入1μL的5倍财政司司长缓冲区，0.5μL的DTT，0.5μLdNTP混合液0.5μLRnaseOUT（上标第二包）。 </li><li>加热至42° C的PCR仪1分钟，再加入0.5μL标II逆转录酶。孵育1小时，在42 ° C。 </li><li>热火在70 ° C为10分钟，冷却至4 ° C。 </li><li>在冰上，上述反应中添加以下： </li></ol><ul><li>核酸自由水 - 22.75μL </li><li> 5X第二链缓冲 - 7.5μL </li><li> dNTP混合液 - 0.75μL </li><li>大肠杆菌DNA连接酶 - 0.25μL </li><li>大肠杆菌DNA聚合酶 - 1μL </li><li> RnaseH - 0.25μL </li></ul>孵育2小时，在16 ° C，然后加入1μLT4 DNA聚合酶，和额外的10分钟孵育16 ° C。 <ol start="6"><li>转移到1.5 mL Eppendorf管，并加入80μl水。 </li><li>加入0.5μL线性丙烯酰胺。 </li><li>加入72μL3米NH4OAc和480μL100％冷乙醇。沉淀为1小时在-20 ° C </li><li>在14000转的自旋在4 ° C 30分钟，用1 ml 70％乙醇，在14000转离心2分钟，真空干燥约10分钟。 </li></ol> 3。 通过体外转录扩增聚一个基因<ol><li>上述基因重悬在3.5μL的核酸游离水。 </li><li>以上，加1μL的dNTPs（共4μL），1 10X反应缓冲液和1μL的T7聚合酶，并从Megascript套件RnaseOUT 0.5μL。 </li><li>在37 ° C过夜PCR仪。 </li><li>下一步准备就绪。可存放于-80 ° C。 </li></ol> 4。一个基因扩增聚碎裂<ol><li>上述反应和4μL10X碎片试剂加入26μL水。 </li><li>热火在PCR仪在70 ° C整整7分钟。 </li><li>添加5μL碎片停止缓冲区，把冰样本。 </li></ol> 5。 RNA的清洁<ol><li>上述反应中，加入60μl水和缓冲区的RNeasy MinElute试剂盒的RLT 350μL，由吹打混合。 </li><li>添加到离心柱250μL乙醇，吹打的组合，和吸管。 </li><li>在8000 RCF为20秒旋转。 </li><li>洗一次与视网膜色素上皮，旋转20秒，用80％的乙醇，自旋为2分钟，5分钟旋转的干栏的第二时间。 </li><li>洗脱RNA在10μL的核酸游离水。 </li></ol> 6。 cDNA合成第一链合成为单读库： <ol><li>在PCR管中，添加以下内容： </li></ol><ul><li>零碎聚一个基因 - 10μL </li><li> NotI nonamer随机引物 - 1μL </li></ul>在70 ° C孵育5分钟，在热循环，并在冰上快速寒意。 NotI Nonamer引物（5&#39; - TGAATTCGCGGCCGCTCAAGCAGAAGACGGCATACGAGCTCTTCCGATCT NNNNNNNNN -3“）。 5&#39;近端序列NotI酶切位点，而直到随机地区的下一个序列是从芯片序列套件Illumina的适配器B序列的反向补充。 <ol开始=“2”&gt; <li>上述措施外，新增的冰以下（标III套件）： </li></ol><ul><li> 5X第一链缓冲-4μL </li><li>数码地面电视 - 2μL </li><li> dNTP的混合物* - 1.5μL </li></ul>放在热循环42℃2分钟，加标III逆转录酶1μL，42℃孵育1小时。 *而不是dCTP，5 - 甲基dCTP在dNTP的混合物。 第一链合成配对结束库： <ol><li>在PCR管中，添加以下内容： </li></ol><ul><li>零碎聚一个基因 - 10μL </li><li>随机六聚体引物 - 1μL </li></ul>在65 ° C孵育5分钟，在热循环，并在冰上快速寒意。 <ol start="2"><li>上述情况，添加以下上冰（上标firststrand III套件）： </li></ol><ul><li> 5X第一链缓冲 - 4μL </li><li>数码地面电视 - 2μL </li><li> dNTPs（从试剂盒） - 1.5μL </li></ul>放在热循环1分钟，在45 ° C，加入标III逆转录酶1μL，在45 ° C孵育1小时。 第二链的合成（两个库）： <ol start="3"><li>上述情况，添加冰以下（标第二包）： </li></ol><ul><li>水（核糖核酸免费） - 91μL </li><li> 5X第二链缓冲 - 30μL </li><li> dNTPs（套件） - 3μL </li><li>大肠杆菌DNA连接酶 - 1μL </li><li>大肠杆菌DNA聚合酶 - 4μL </li><li>大肠杆菌核糖核酸酶H - 1μL </li></ul>颠倒混合管，短的自旋和孵化在16 ° C，2小时。 7。净化的cDNA <ol><li> Zymo列，单一的读取和配对结束库30μL水，水在40μL洗脱纯化cDNA样本。 </li></ol> 8。结束维修对于一个读库： <ol><li>上述40μL的cDNA，地址： </li></ol><ul><li>用10mm ATP T4 DNA连接酶缓冲液 - 5μL </li><li> dNTP混合液 - 2μL </li><li> T4 DNA聚合酶 - 1μL </li><li> Klenow酶（用水稀释1:5 1U /μL） - 1μL </li><li> T4 PNK - 1μL </li></ul>在30分钟的热循环仪孵育20 ° C。 对于配对年底库： （使用Illumina的配对结束样品制备试剂盒） <ol><li>上述30μL的cDNA，地址： </li></ol><ul><li>核糖核酸酶DNA酶自由水 - 45μL </li><li>用10mm ATP T4 DNA连接酶缓冲液 - 10μL </li><li> 10MM的dNTP混合 - 4μL </li><li> T4 DNA聚合酶 - 5μL </li><li> Klenow酶 - 1μL </li><li> T4 PNK - 5μL </li></ul>在30分钟的热循环仪孵育20 ° C。 9。 cDNA的清洁起来<ol><li>彗星<html>瘦最多的cDNA使用Zymo列。在34μL的EB单一的读取和配对结束库32μLEB洗脱。 </li></ol> 10。新增“A”基地的3&#39;的DNA片段结束对于一个读库： <ol><li>准备以下的反应组合： </li></ol><ul><li> DNA样本 - 34μL </li><li>的Klenow缓冲 - 5μL </li><li> dATP的 - 10μL </li><li>出的Klenow - 1μL </li></ul> 30分钟在37 ° C。 对于配对年底库： <ol><li>准备以下的反应组合： </li></ol><ul><li> DNA样本 - 32μL </li><li>的Klenow缓冲 - 5μL </li><li> dATP的 - 10μL </li><li>出的Klenow - 3μL </li></ul> 30分钟在37 ° C。 11。 cDNA的清洁起来<ol><li>清理的cDNA使用zymo列。在10μL的EB洗脱。 </li></ol> 12。适配器结扎jove_step“&gt;单个读库： （使用Illumina的芯片序列样品制备试剂盒） <ol><li>准备以下的反应组合： </li></ol><ul><li> DNA样本 - 10μL </li><li>适配器寡糖组合 - 1μL </li><li> 2X DNA连接酶缓冲液-15μL </li><li> DNA连接酶 - 4μL </li></ul>在室温15分钟孵育。适配器应解冻的冰和稀释1:20。 对于配对年底库： （使用Illumina的配对结束样品制备试剂盒） <ol><li>准备以下的反应组合： </li></ol><ul><li> DNA样本 - 10μL </li><li> PE适配器寡糖混合 - 10μL </li><li> 2X DNA连接酶缓冲液 - 25μL </li><li> DNA连接酶 - 5μL </li></ul>孵育15分钟，在20 ° C。适配器应解冻的冰和稀释1:20。 13。连接反应清理<ol><li>使用ZY清理连接反应莫列。在44μL水洗脱单个读库和5μL的EB的另一个配对结束库洗脱6μLEB。 </li></ol>执行NotI消化，只对单一的读库<ul><li>基因 - 44μL </li><li> NEB缓冲3 - 5μL </li><li>牛血清白蛋白 - 0.5μL </li><li> NotI - 1μL </li></ul> 2小时至过夜孵育37 ° C，并净化反应zymo列。 6缓冲区的EB液流出，其次是与5μLEB的第二洗脱。 14。尺寸选择/凝胶净化执行以下使用2％SYBR安全电子凝胶自Invitrogen。 <ol><li>运行程序的0 - PreRun 2分钟。 </li><li>负载自Invitrogen稀释1:4 1KB再加上阶梯，并载入10μL。 </li><li>加载所有的DNA样本，并填写10μL水空车道。 </li><li>运行程序的1 EGel 2％，运行28分钟。 </li><li>大小选择200-300 bp的凝胶SLICE与一个新的刀片。 </li></ol> 15。洗脱DNA的凝胶片<ol><li>称取凝胶片，并添加3卷缓冲区QG 1凝胶的体积（使用凝胶提取试剂盒自Qiagen） </li><li>孵育50 ° C为10分钟或直到凝胶片溶解。 </li><li>添加ispropanol 1卷，倒置或移液混合。 </li><li>添加到列，最高速度为1分钟的旋转，并丢弃流过。 </li><li>加入500μlQG到列的缓冲区，为1分钟，以最大的速度旋转，并丢弃流过。 </li><li>加入750μl的Buffer PE的列，最高速度为1分钟旋转，并丢弃流过。 </li><li>离心机最高速度为1分钟。 </li><li>在36μL的EB单一的读取和配对结束库23μLEB洗脱。 </li></ol> 16。 PCR扩增对于一个读库： （使用Illumina的芯片序列样品制备试剂盒） <ol><li>准备的followin克PCR反应的组合： </li></ol><ul><li>的DNA - 36μL </li><li> 5X Phusion缓冲区 - 10μL </li><li> dNTP混合液 - 1.5μL </li><li> PCR引物1.1 - 1μL </li><li> PCR引物2.1 - 1μL </li><li> Phusion聚合酶 - 0.5μL </li></ul>使用下面的PCR协议： <ul class="lalpha"><li> 30秒98 ° C </li><li> 10个循环： <ul><li> 10秒98 ° C </li><li> 30秒65 ° C </li><li> 30秒72 ° C </li></ul></li><li> 5分钟72 ° C </li><li>保持在4 ° C </li></ul> *套件是用于第一次，与EB缓冲液稀释的PCR引物1:2。 对于配对年底库： （使用Illumina的配对结束样品制备试剂盒） <ol><li>准备以下的PCR反应： </li></ol><ul><li>的DNA - 23μL </li><li> Phusion DNA聚合酶 - 25μL </li><li> PCR引物PE 1.1 - 1μL </li><li> PCR引物PE 2.1 -1μL </li></ul>放大使用下列PCR协议： <ol><li> 30秒98 ° C </li><li> 10个循环： <ul><li> 10秒98 ° C </li><li> 30秒65 ° C </li><li> 30秒72 ° C </li></ul></li><li> 5分钟72 ° C </li><li>保持在4 ° C </li></ol> *套件是用于第一次，与EB缓冲液稀释的PCR引物1:2。 17。图书馆清洁<ol><li>清理库使用zymo列。洗脱12μLEB </li></ol> 18。定量库<ol><li>定量库使用量子比特。这是准备进行测序。测序引物从Illumina的单一读取集群生成工具包V4或更高的单读库和Illumina的配对结束集群代包V4或更高配对结束库使用。 </li></ol> 19。数据分析领结6是用来米AP读取的RefSeq基因组（NCBI的构建36.1）。单端读取（30个核苷酸）和对端读取（42个核苷酸）映射允许多达10场比赛的基因组，并允许每读取两个不匹配。每百万（TPM）值的转录来衡量使用RSEM 7（RNA - seq的期望最大化）的基因表达。 20。代表性的成果：我们T7LA库读取和配对的单端从1微克，100微克，10微克，1微克和100 PG总RNA（图1）开始运行。评价我们的协议，我们没有T7 RNA 10μg总RNA被称为“MinAmp”这些控制库，开始放大的单读取和配对月底库，具有最小的放大。他们所接受的唯一的扩增PCR的协议结束近10个周期，以结扎Illumina的测序适配器，一步步共同所有的图书馆。所有RNA用于分离从H14人类胚胎干细胞8。 我们首先计算由各种库（表1和补充表1）发现的基因数目。对于读取和配对的单端库，为10 ng T7LA库确定为10微克MinAmp库几乎相同数量的基因，与10个或更多的TPM。 10吴T7LA库在单个读库的情况下，确定由10微克非放大库中确定的8500基因的100％。 10吴T7LA库配对结束库，发现86％的非放大10微克库（7961）的9267个基因中发现的基因。低于10 ng库没有能够找出许多基因。例如，在单个读协议，1毫微克库只认〜50％，由10微克MinAmp库确定出的基因，促使我们T7LA协议为10 ng总RNA的最低金额限制。此外，一个看家基因的映射，<html> GAPDH的（图2）显示所有T7LA至少开始的RNA 10ng库确定所有外显子，包括极端的5&#39;外显子。 10吴T7LA单读和配对与MinAmp库年底库的比较，显示了高度的相似性（Spearman相关，R = 0.90和0.95，图3a和b）。我们还比较了两个单读取和配对的结束，从10 ng总RNA库，他们有很高的相关系数（R = 0.92），表明这两种类型的图书馆使用T7LA协议产生了一个非常类似的基因表达签名（图3c）。因此，T7LA方法是能够产生可靠和全面MinAmp库的测序库的，但是从1000倍的起点较低的材料。 <img alt="图1" src="/files/ftp_upload/3340/3340fig1.jpg" /> 图1中的模式和单个读库准备协议配对结束。 jove_content“&gt; <img alt="图2" src="/files/ftp_upload/3340/3340fig2.jpg" /> 图2的所有读取和配对的单端库，一个看家基因GAPDH的基因组浏览器的图片。单个读库左侧的比例尺显示350共读。配对结束库中心的比例尺表示5000共读。横轴代表的GAPDH的基因组序列。 <img alt="图3" src="/files/ftp_upload/3340/3340fig3.jpg" /> 图3基因表达的相关性之间的各种库（斯皮尔曼）：在单读吴T7LA 10和10微克MinAmp库显示，这两个库有一个非常相似的基因表达模式（R = 0.90）B.配对结束C.基因表达的相关性吴T7LA 10和10微克MinAmp库演示了他们的基因表达图谱的相似性（ R = 0.95）。10吴配对月底和10毫微克的单个读库之间的pressions显示T7LA方法编写这些库（R = 0.92）之间的相似程度高。 <img alt="图4" src="/files/ftp_upload/3340/3340fig4.jpg" /> 图4的人类胚胎干细胞所有读取和配对的单端库的具体genes5鉴定。 <table border="1"><tbody><tr><td> 图书馆 </td><td> 类型° </td><td> 原材料集群 </td><td> 集群通过 ​​过滤器（ ％） </td><td> 对齐到基因组％ </td><td> ％的误差率 </td><td> 基因鉴定 </td></tr><tr><td> MinAmp 10ug </td><td>单读</td><td> 225602 + / - 4952 </td><td> 65.48 + / - 2.58 </td><td> 47.61 + / - 0.53 </td><td> 0.62 + / - 0.06 </td><td> 8500 </td></tr><tr><td> 1ug T7LA </td><td>单读</td><td> 144818 + / - 6513 </td><td> 82.21 + / - 6.45 </td><td> 48.09 + / - 0.27 </td><td> 0.42 + / - 0.03 </td><td> 8757 </td></tr><tr><td> 100ng T7LA </td><td>单读</td><td> 27385 + / - 1818 </td><td> 81.33 + / - 11.75 </td><td> 44.46 + / - 4.53 </td><td> 0.49 + / - 0.10 </td><td> 8709 </td></tr><tr><td> 10ng T7LA </td><td>单读</td><td> 11184 + / - 985 </td><td> 60.70 + / - 3.70 </td><td> 14.96 + / - 1.15 </td><td> 0.99 + / - 0.30 </td><td> 8589 </td></tr><tr><td> 1ng T7LA </td><td>单读</td><td> 12695 + / - 1365 </td><td> 53.27 + / - 16.76 </td><td> 4.08 + / - 0.79 </td><td> 2.25 + / - 1.56 </td><td> 4720 </td></tr><tr><td> 100pg T7LA </td><td>单读</td><td> 10390 + / - 1398 </td><td> 72.99 + / - 2.90 </td><td> 1.48 + / - 0.20 </td><td> 1.51 + / - 0.39 </td><td> 1121 </td></tr><tr><td colspan="7"></td></tr><tr><td> MinAmp 10ug </td><td>配对完R1 </td><td> 95786 + / - 12937 </td><td> 90.77 + / - 2.79 </td><td> 58.50 + / - 0.95 </td><td> 0.94 + / - 0.38 </td><td> 9267 </td></tr><tr><td></td><td>配对完R2的</td><td> 95786 + / - 12937 </td><td> 90.77 + / - 2.79 </td><td> 58.13 + / - 1.13 </td><td> 0.99 + / - 0.37 </td><td></td></tr><tr><td> 1ug T7LA </td><td>配对完R1 </td><td> 297669 + / - 10196 </td><td> 91.35 + / - 0.36 </td><td> 46.​​89 + / - 0.14 </td><td> 0.47 + / - 0.01 </td><td> 7334 </td></tr><tr><td></td><td>配对完R2的</td><td> 297669 + / - 10196 </td><td> 91.35 + / - 0.36 </td><td> 45.52 + / - 0.12 </td><td> 0.51 + / - 0.01 </td><td></td></tr><tr><td> 100ng T7LA </td><td>配对完R1 </td><td> 205602 + / - 9932 </td><td> 90.53 + / - 0.76 </td><td> 63.44 + / - 1.00 </td><td> 0.48 + / - 0.02 </td><td> 8011 </td></tr><tr><td></td><td>配对完R2的</td><td> 205602 + / - 9932 </td><td> 90.53 + / - 0.76 </td><td> 61.80 + / - 8.09 </td><td> 0.60+ / - 0.36 </td><td></td></tr><tr><td> 10ng T7LA </td><td>配对完R1 </td><td> 214622 + / - 11155 </td><td> 89.98 + / - 1.13 </td><td> 56.32 + / - 1.94 </td><td> 0.80 + / - 0.26 </td><td> 7961 </td></tr><tr><td></td><td>配对完R2的</td><td> 214622 + / - 11155 </td><td> 89.98 + / - 1.13 </td><td> 46.​​41 + / - 18.39 </td><td> 2.48 + / - 2.68 </td><td> ; </td></tr><tr><td> 1ng T7LA </td><td>配对完R1 </td><td> 144951 + / - 19841 </td><td> 90.54 + / - 1.19 </td><td> 3.91 + / - 0.16 </td><td> 8.71 + / - 0.86 </td><td> 8124 </td></tr><tr><td></td><td>配对完R2的</td><td> 144951 + / - 19841 </td><td> 90.54 + / - 1.19 </td><td> 3.27 + / - 1.21 </td><td> 9.11 + / - 3.52 </td><td></td></tr><tr><td> 100pg T7LA </td><td>配对完R1 </td><td> 1876​​00 + / - 11759 </td><td> 89.52 + / - 1.11 </td><td> 1.78 + / - 0.05 </td><td> 13.42 + / - 0.50 </td><td> 6623 </td></tr><tr><td></TD&gt; <td>配对完R2的</td><td> 1876​​00 + / - 11759 </td><td> 89.52 + / - 1.11 </td><td> 1.99 + / - 0.23 </td><td> 15.29 + / - 0.96 </td><td></td></tr></tbody></table> · R1和R2是正向和反向序列标记 *≥10的TPM 表1：集群数字，基因识别，错误率，％读取和配对的单端库的对齐方式。 补充表1。所有基因的名单和所有样品的TPM值，单个读取和配对结束。

<ol>
	<li>Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B. B., Siddiqui, A., Lao, K., Surani, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=mRNA-Seq+whole-transcriptome+analysis+of+a+single+cell.">mRNA-Seq whole-transcriptome analysis of a single cell.</a> Nature Methods. 6, 377-382 (2009).</li><li>Armour, C. D., Castle, J. C., Chen, R., Babak, T., Loerch, P., Jackson, S., Shah, J. K., Dey, J., Rohl, C. A., Johnson, J. M., Raymond, C. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+transcriptome+profiling+using+selective+hexamer+priming+for+cDNA+synthesis.">Digital transcriptome profiling using selective hexamer priming for cDNA synthesis.</a> Nature Methods. 6, 647-649 (2009).</li><li>Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., Wold, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mapping+and+quantifying+mammalian+transcriptomes+by+RNA-Seq.">Mapping and quantifying mammalian transcriptomes by RNA-Seq.</a> Nature Methods. 5, 621-628 (2008).</li><li>Mamanova, L., Andrews, R. M., James, K. D., Sheridan, E. M., Ellis, P. D., Langford, C. F., Ost, T. W., Collins, J. E., Turner, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FRT-seq+amplification-free,+strand-specific+transcriptome+sequencing.">FRT-seq amplification-free, strand-specific transcriptome sequencing.</a> Nature Methods. 5, 130-132 (2010).</li><li>Sengupta, S., Ruotti, V., Bolin, J., Elwell, A., Hernandez, A., Thomson, J., Stewart, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Highly+consistent,+fully+representative+mRNA-Seq+libraries+from+ten+nanograms+of+total+RNA.">Highly consistent, fully representative mRNA-Seq libraries from ten nanograms of total RNA.</a> Biotechniques. 49, 898-904 (2010).</li><li>Langmead, B., Trapnell, C., Pop, M., Salzberg, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+and+memory-efficient+alignment+of+short+DNA+sequences+to+the+human+genome.">Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.</a> Genome. Biology. 10, R25-R25 (2009).</li><li>Li, B., Ruotti, V., Stewart, R. M., Thomson, J. A., Dewey, C. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-Seq+gene+expression+estimation+with+read+mapping+uncertainty.">RNA-Seq gene expression estimation with read mapping uncertainty.</a> Biotechniques. 26, 493-500 (2010).</li><li>Thomson, J. A., Itskovitz-Eldor, J., Shapiro, S. S., Waknitz, M. A., Swiergiel, J. J., Marshall, V. S., Jones, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Embryonic+stem+cell+lines+derived+from+human+blastocysts.">Embryonic stem cell lines derived from human blastocysts.</a> Science. 282, 1145-1147 (1998).</li></ol>

作者透露，翟细胞动力学国际（CDI）的创始人，stockowner，顾问和董事会成员。他还担任科学顾问，并在战术II干细胞的风险投资公司的财务利益。

1微克至2.5微克10日起的总RNA量之间的配对结束库当前的协议要求。在这里，我们目前我们对直线的T7扩增（T7LA）的方法来准备，此方法允许读取和配对的单端Illumina的测序库，并显示生成低至10纳克的总RNA库，生产数据是可比的，微创（MinAmp）放大1000倍以上的起始原料（10μg总RNA）的库。为10 ng图书馆不仅找出类似的基因总数，但也产生类似（图3a和b）的基因表达签名。此外，读取和T7LA方法产生配对的单端库是对方（图3c），这使研究人员能够比较无论从协议中作出的库产生的数据非常相似。由于这些库准备从人类胚胎干细胞的RNA，我们搜索为30个干细胞库中的特定基因，并发现，几乎所有这些基因（93-100％）发现至少10启动总RNA（图4）吴库，从而验证了我们的协议。我们相信，我们的协议将是非常有用的，为研究人员，特别是在诸如流量排序细胞或激光微解剖组织起始原料限制的情况下，。在这种情况下，我们的协议将允许从开始量大得多，因为我们的协议产生的表达谱，在至少3订单开始RNA的幅度相媲美的库生成的基因表达数据相媲美。

<table border="1"><tbody><tr><td>公司</td><td>包/试剂</td><td>目录＃ </td><td>特殊注释</td></tr><tr><td> Ambion公司</td><td>碎片试剂</td><td> AM8740 </td><td></td></tr><tr><td> Ambion公司</td><td>班轮丙烯酰胺</td><td> AM9520 </td><td></td></tr><tr><td> Ambion公司</td><td> MEGAscript的T7套装</td><td> AM1334 </td><td></td></tr><tr><td> Ambion公司</td><td>非DEPC处理核酸免费水</td><td> AM9932 </td><td></td></tr><tr><td> Fermentas公司</td><td> dNTP的设置</td><td> R0181 </td><td></td></tr><tr><td> Fermentas公司</td><td>甲基化的dNTPs </td><td> R0431 </td><td>仅适用于单个读样品制备</td></tr><tr><td> Illumina公司</td><td> TruSeq SR集群生成工具包V5 </td><td> GD - 203 - 5001 </td><td>仅适用于单个读样品制备</td></tr><tr><td> Illumina公司</td><td> TruSeq SEQ工具包V5 36个循环</td><td> FC - 104 - 5001 </td><td></td></tr><tr><td> Illumina公司</td><td>芯片序列样品制备试剂盒</td><td> IP - 102 - 1001 </td&gt; <td>对于只有一个读样品制备。可更换，NEB DNA样品制备预混设置1 CAT＃E6040S </td></tr><tr><td> Illumina公司</td><td> TruSeq PE集群生成套件V5 </td><td> PE - 203 - 5001 </td><td>仅适用于配对结束样品制备</td></tr><tr><td> Illumina公司</td><td>配对完样品制备工具包</td><td> PE - 102 - 1001 </td><td>仅适用于配对结束样品制备</td></tr><tr><td> Invitrogen公司</td><td>次加梯</td><td> 10787-018 </td><td></td></tr><tr><td> Invitrogen公司</td><td>大肠杆菌核糖核酸酶H </td><td> 18021-014 </td><td></td></tr><tr><td> Invitrogen公司</td><td>核糖核酸酶输出</td><td> 10777-019 </td><td></td></tr><tr><td> Invitrogen公司</td><td>第二链缓冲5倍</td><td> 10812-014 </td><td></td></tr><tr><td> Invitrogen公司</td><td>大肠杆菌DNA聚合酶</td><td> 18010-017 </td><td></td></tr><tr><td> Invitrogen公司</td><td> E -凝胶的SYBR安全2％ </td><td> G521802 </td><td></td></tr><tr><td> Invitrogen公司</td><td>标iII（5X FS缓冲区和0.1M的数码地面电视） </td><td> 18080-085 </td><td></td></tr><tr><td> Invitrogen公司</td><td> Trizol法</td><td> 12183555 </td><td></td></tr><tr><td> Invitrogen公司</td><td> RNA的quibit检测试剂盒</td><td> Q32852 </td><td></td></tr><tr><td> Invitrogen公司</td><td>双链协量子比特检测试剂盒</td><td> Q32851 </td><td></td></tr><tr><td> Invitrogen公司</td><td>大肠杆菌DNA连接酶</td><td> 18052-019 </td><td></td></tr><tr><td> Invitrogen公司</td><td> T4 DNA聚合酶</td><td> 18005-025 </td><td></td></tr><tr><td> Invitrogen公司</td><td>超纯DNA酶核糖核酸酶水</td><td> 10977-015 </td><td></td></tr><tr><td> Invitrogen公司</td><td>标二双链cDNA合成试剂盒</td><td> 11917-020 </td><td></td></tr><tr><td> Invitrogen公司</td><td>随机引物（Invitrogen公司） </td><td> 48190-011 </td><td>仅适用于配对结束样品制备</td></tr><tr><td>内幕交易审裁处</td><td> Not1Nonamer乙底漆</td><td> N / A </td><td>对于单读SAM仅PLE准备</td></tr><tr><td>内幕交易审裁处</td><td>寡糖DT的T7 </td><td> N / A </td><td></td></tr><tr><td> NEB </td><td> Not1消化试剂盒</td><td> R0189S </td><td>仅适用于单个读样品制备</td></tr><tr><td> Qiagen公司</td><td>的RNeasy Minelute套件</td><td> 74204 </td><td></td></tr><tr><td> Qiagen公司</td><td>的RNeasy试剂​​盒（50） </td><td> 74104 </td><td></td></tr><tr><td> Qiagen公司</td><td>凝胶纯化试剂盒</td><td> 28604 </td><td></td></tr><tr><td> Qiagen公司</td><td> DNA酶设置</td><td> 79254 </td><td></td></tr><tr><td> Qiagen公司</td><td>的RNeasy MinElute套件</td><td> 74204 </td><td></td></tr><tr><td> Zymo研究</td><td> DNA的清洁和选矿厂（250X） </td><td> D4014 </td><td></td></tr></tbody></table>

single read and paired end mrna-seq illumina libraries from 10 nanograms total rna

全转录组测序的mRNA - Seq的是现在被广泛用于执行全球基因表达，突变，等位基因特异性表达，其他的全基因组分析。甚至打开的mRNA - Seq的非基因组测序的基因表达分析的大门。的mRNA - Seq的提供高灵敏度，大动态范围，并允许测量样品中的转录拷贝数。 Illumina公司的基因组分析仪进行测序一个大数目相对较短的序列（&gt; 10 7）读取（&lt;150 bp的）。“配对结束”的方法，其中一个单一的长读是在两个其两端测序，允许跟踪交替剪接路口插入和缺失，是有用的De Novo转录大会。 研究人员面临的主要挑战之一是数量有限的起始原料。例如，开始在激光微解剖，可收获细胞实验总RNA米AY在毫微克的措施。从这些样品中的mRNA - Seq的库的制备已被描述 1，2，但涉及显著PCR扩增，可能会引入偏差。其他RNA - seq的图书馆建设以最小的PCR扩增程序已经出版3，4，但需要启动总RNA微克金额。 在这里，我们描述的Illumina的Genome Analyzer的II平台库的准备，避免显著的PCR扩增和只需要10微克的总RNA测序的mRNA - Seq的协议。尽管这个协议已经前面描述的单端测序，它表明的情况下引进显著放大偏置定向库验证，在这里我们验证它进一步用于配对的最终协议。我们选择性地放大聚腺苷酸化的信使RNA，从开始使用总RNA，T7基于Eberwine线性扩增法，创造了“T7洛杉矶“（T7线性扩增）。扩增聚一个mRNA的是零散的，反转录和适配器结扎，以产生最后的测序库。对于读取和配对的单端运行，序列映射到人类转录组 6和规范化，使从多次运行数据可以比较，我们的报告基因表达的转录每百万为单位测量（TPM），这是一个出众的措施RPKM 比较样本7时。

Watch this Scientific Journal Video about Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA at JoVE.com

Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA

在这里，我们描述了读取和配对的单端Illumina公司的mRNA - Seq的测序基础上的T7线性RNA扩增的基因表达分析库的制备方法。该协议只需要10微克启动总RNA，并产生了高度一致库代表整个笔录。

单次读取和配对的最终从10微克总RNA的mRNA - Seq的Illumina的图书馆

Whole transcriptome sequencing by mRNA-Seq is now used extensively to perform global gene expression, mutation, allele-specific expression and other ...

single-read-paired-end-mrna-seq-illumina-libraries-from-10-nanograms

Research

JoVE Journal

Biology

39.1K 次观看.  Morgridge Institute for Research. 在这里，我们描述了读取和配对的单端Illumina公司的mRNA - Seq的测序基础上的T7线性RNA扩增的基因表达分析库的制备方法。该协议只需要10微克启动总RNA，并产生了高度一致库代表整个笔录。

视频: Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA

Large-Scale Screens of Metagenomic Libraries

Metagenomic libraries archive large fragments of contiguous genomic sequences from microorganisms without requiring prior cultivation. Generating a streamlined procedure for creating and screening metagenomic libraries is therefore useful for efficient high-throughput investigations into the genetic and metabolic properties of uncultured microbial assemblages. Here, key protocols are presented on video, which we propose is the most useful format for accurately describing a long process that alternately depends on robotic instrumentation and (human) manual interventions. First, we employed robotics to spot library clones onto high-density macroarray membranes, each of which can contain duplicate colonies from twenty-four 384-well library plates. Automation is essential for this procedure not only for accuracy and speed, but also due to the miniaturization of scale required to fit the large number of library clones into highly dense spatial arrangements. Once generated, we next demonstrated how the macroarray membranes can be screened for genes of interest using modified versions of standard protocols for probe labeling, membrane hybridization, and signal detection. We complemented the visual demonstration of these procedures with detailed written descriptions of the steps involved and the materials required, all of which are available online alongside the video.

宏基因组库的大型屏幕

Metagenomic libraries archive large fragments of contiguous genomic sequences from microorganisms without requiring prior cultivation.  Generating a ...

科研

生物学

RNA Extraction from Neuroprecursor Cells Using the Bio-Rad Total RNA Kit

使用Bio - Rad公司的总RNA试剂盒从Neuroprecursor细胞的RNA提取

Obtaining High Quality RNA from Single Cell Populations in Human Postmortem Brain Tissue

We proposed to investigate the gray matter reduction in the superior temporal gyrus seen in schizophrenia patients, by interrogating gene expression profiles of pyramidal neurons in layer III. It is well known that the cerebral cortex is an exceptionally heterogeneous structure comprising diverse regions, layers and cell types, each of which is characterized by distinct cellular and molecular compositions and therefore differential gene expression profiles. To circumvent the confounding effects of tissue heterogeneity, we used laser-capture microdissection (LCM) in order to isolate our specific cell-type i.e pyramidal neurons.
Approximately 500 pyramidal neurons stained with the Histogene staining solution were captured using the Arcturus XT LCM system. RNA was then isolated from captured cells and underwent two rounds of T7-based linear amplification using Arcturus/Molecular Devices kits. The Experion LabChip (Bio-Rad) gel and electropherogram indicated good quality a(m)RNA, with a transcript length extending past 600nt required for microarrays. The amount of mRNA obtained averaged 51&mu;g, with acceptable mean sample purity as indicated by the A260/280 ratio, of 2.5. Gene expression was profiled using the Human X3P GeneChip probe array from Affymetrix.

We describe a process using laser-capture microdissection to isolate and extract RNA from a homogeneous cell population, pyramidal neurons, in layer III of the superior temporal gyrus in postmortem human brains. We subsequently linearly amplify (T7-based) mRNA, and hybridize the sample to the Affymetrix human X3P microarray.

人死后脑组织中的单细胞群获得高品质的RNA

We proposed to investigate the gray matter reduction in the superior temporal gyrus seen in schizophrenia patients, by interrogating gene expression ...

A High Throughput Screen for Biomining Cellulase Activity from Metagenomic Libraries

Cellulose, the most abundant source of organic carbon on the planet, has wide-ranging industrial applications with increasing emphasis on biofuel production 1. Chemical methods to modify or degrade cellulose typically require strong acids and high temperatures. As such, enzymatic methods have become prominent in the bioconversion process. While the identification of active cellulases from bacterial and fungal isolates has been somewhat effective, the vast majority of microbes in nature resist laboratory cultivation. Environmental genomic, also known as metagenomic, screening approaches have great promise in bridging the cultivation gap in the search for novel bioconversion enzymes. Metagenomic screening approaches have successfully recovered novel cellulases from environments as varied as soils 2, buffalo rumen 3 and the termite hind-gut 4 using carboxymethylcellulose (CMC) agar plates stained with congo red dye (based on the method of Teather and Wood 5). However, the CMC method is limited in throughput, is not quantitative and manifests a low signal to noise ratio 6. Other methods have been reported 7,8 but each use an agar plate-based assay, which is undesirable for high-throughput screening of large insert genomic libraries. Here we present a solution-based screen for cellulase activity using a chromogenic dinitrophenol (DNP)-cellobioside substrate 9. Our library was cloned into the pCC1 copy control fosmid to increase assay sensitivity through copy number induction 10. The method uses one-pot chemistry in 384-well microplates with the final readout provided as an absorbance measurement. This readout is quantitative, sensitive and automated with a throughput of up to 100X 384-well plates per day using a liquid handler and plate reader with attached stacking system.

This protocol describes a high throughput screen for cellulolytic activity from a metagenomic library expressed in Escherichia coli. The screen is solution based and highly automated, and uses one-pot chemistry in 384 well microplates with the final readout as an absorbance measurement.

一个Biomining从宏基因组库的纤维素酶的活性高通量筛选

Cellulose, the most abundant source of organic carbon on the planet, has wide-ranging industrial applications with increasing emphasis on biofuel ...

In vitro Transcription and Capping of Gaussia Luciferase mRNA Followed by HeLa Cell Transfection

In vitro transcription is the synthesis of RNA transcripts by RNA polymerase from a linear DNA template containing the corresponding promoter sequence (T7, T3, SP6) and the gene to be transcribed (Figure 1A). A typical transcription reaction consists of the template DNA, RNA polymerase, ribonucleotide triphosphates, RNase inhibitor and buffer containing Mg2+ ions.
Large amounts of high quality RNA are often required for a variety of applications. Use of in vitro transcription has been reported for RNA structure and function studies such as splicing1, RNAi experiments in mammalian cells2, antisense RNA amplification by the "Eberwine method"3, microarray analysis4 and for RNA vaccine studies5. The technique can also be used for producing radiolabeled and dye labeled probes6. Warren, et al. recently reported reprogramming of human cells by transfection with in vitro transcribed capped RNA7. The T7 High Yield RNA Synthesis Kit from New England Biolabs has been designed to synthesize up to 180 &mu;g RNA per 20 &mu;l reaction. RNA of length up to 10kb has been successfully transcribed using this kit. Linearized plasmid DNA, PCR products and synthetic DNA oligonucleotides can be used as templates for transcription as long as they have the T7 promoter sequence upstream of the gene to be transcribed.
Addition of a 5' end cap structure to the RNA is an important process in eukaryotes. It is essential for RNA stability8, efficient translation9, nuclear transport10 and splicing11. The process involves addition of a 7-methylguanosine cap at the 5' triphosphate end of the RNA. RNA capping can be carried out post-transcriptionally using capping enzymes or co-transcriptionally using cap analogs. In the enzymatic method, the mRNA is capped using the Vaccinia virus capping enzyme12,13. The enzyme adds on a 7-methylguanosine cap at the 5' end of the RNA using GTP and S-adenosyl methionine as donors (cap 0 structure). Both methods yield functionally active capped RNA suitable for transfection or other applications14 such as generating viral genomic RNA for reverse-genetic systems15 and crystallographic studies of cap binding proteins such as eIF4E16.
In the method described below, the T7 High Yield RNA Synthesis Kit from NEB is used to synthesize capped and uncapped RNA transcripts of Gaussia luciferase (GLuc) and Cypridina luciferase (CLuc). A portion of the uncapped GLuc RNA is capped using the Vaccinia Capping System (NEB). A linearized plasmid containing the GLuc or CLuc gene and T7 promoter is used as the template DNA. The transcribed RNA is transfected into HeLa cells and cell culture supernatants are assayed for luciferase activity. Capped CLuc RNA is used as the internal control to normalize GLuc expression.

In vitro Transcription and Capping of Gaussia Luciferase mRNA Followed by HeLa Cell Transfection

This method describes high yield in vitro synthesis of both capped and uncapped mRNA from a linearized plasmid containing the Gaussia luciferase (GLuc) gene. The RNA is purified and a fraction of the uncapped RNA is enzymatically capped using the Vaccinia virus capping enzyme. In the final step, the mRNA is transfected into HeLa cells and cell culture supernatants are assayed for luciferase activity.

在体外转录和Gaussia荧光素酶基因的上限由HeLa细胞转染

In vitro transcription is the synthesis of RNA transcripts by RNA polymerase from a linear DNA template containing the corresponding promoter sequence ...

Chromatin Interaction Analysis with Paired-End Tag Sequencing (ChIA-PET) for Mapping Chromatin Interactions and Understanding Transcription Regulation

Genomes are organized into three-dimensional structures, adopting higher-order conformations inside the micron-sized nuclear spaces 7, 2, 12. Such architectures are not random and involve interactions between gene promoters and regulatory elements 13. The binding of transcription factors to specific regulatory sequences brings about a network of transcription regulation and coordination 1, 14. 
Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) was developed to identify these higher-order chromatin structures 5,6. Cells are fixed and interacting loci are captured by covalent DNA-protein cross-links. To minimize non-specific noise and reduce complexity, as well as to increase the specificity of the chromatin interaction analysis, chromatin immunoprecipitation (ChIP) is used against specific protein factors to enrich chromatin fragments of interest before proximity ligation. Ligation involving half-linkers subsequently forms covalent links between pairs of DNA fragments tethered together within individual chromatin complexes. The flanking MmeI restriction enzyme sites in the half-linkers allow extraction of paired end tag-linker-tag constructs (PETs) upon MmeI digestion. As the half-linkers are biotinylated, these PET constructs are purified using streptavidin-magnetic beads. The purified PETs are ligated with next-generation sequencing adaptors and a catalog of interacting fragments is generated via next-generation sequencers such as the Illumina Genome Analyzer. Mapping and bioinformatics analysis is then performed to identify ChIP-enriched binding sites and ChIP-enriched chromatin interactions 8. 
We have produced a video to demonstrate critical aspects of the ChIA-PET protocol, especially the preparation of ChIP as the quality of ChIP plays a major role in the outcome of a ChIA-PET library. As the protocols are very long, only the critical steps are shown in the video.

Chromatin Interaction Analysis with Paired-End Tag Sequencing ChIA-PET for Mapping Chromatin Interactions and Understanding Transcription Regulation

Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) is a method for de novo detection of chromatin interactions, for better understanding of transcriptional control.

配对末端标签测序（嘉PET）测绘染色质相互作用和了解转录调控染色质相互作用分析

Genomes are organized into three-dimensional structures, adopting higher-order conformations inside the micron-sized nuclear spaces 7, 2, 12. Such ...

TChIP-Seq: Cell-Type-Specific Epigenome Profiling

Epigenetic regulation plays central roles in gene expression. Since histone modification was discovered in the 1960s, its physiological and pathological functions have been extensively studied. Indeed, the advent of next-generation deep sequencing and chromatin immunoprecipitation (ChIP) via specific histone modification antibodies has revolutionized our view of epigenetic regulation across the genome. Conversely, tissues typically consist of diverse cell types, and their complex mixture poses analytic challenges to investigating the epigenome in a particular cell type. To address the cell type-specific chromatin state in a genome-wide manner, we recently developed tandem chromatin immunoprecipitation sequencing (tChIP-Seq), which is based on the selective purification of chromatin by tagged core histone proteins from cell types of interest, followed by ChIP-Seq. The goal of this protocol is the introduction of best practices of tChIP-Seq. This technique provides a versatile tool for tissue-specific epigenome investigation in diverse histone modifications and model organisms.

We describe a step-by-step protocol for tandem chromatin immunoprecipitation sequencing (tChIP-Seq) that enables the analysis of cell-type-specific genome-wide histone modification.

tchip-seq: 细胞专用表观体分析

Epigenetic regulation plays central roles in gene expression. Since histone modification was discovered in the 1960s, its physiological and pathological ...

Nuclei Isolation from Adult Mouse Kidney for Single-Nucleus RNA-Sequencing

The kidneys regulate diverse biological processes such as water, electrolyte, and acid-base homeostasis. Physiological functions of the kidney are executed by multiple cell types arranged in a complex architecture across the corticomedullary axis of the organ. Recent advances in single-cell transcriptomics have accelerated the understanding of cell type-specific gene expression in renal physiology and disease. However, enzyme-based tissue dissociation protocols, which are frequently utilized for single-cell RNA-sequencing (scRNA-seq), require mostly fresh (non-archived) tissue, introduce transcriptional stress responses, and favor the selection of abundant cell types of the kidney cortex resulting in an underrepresentation of cells of the medulla.
Here, we present a protocol that avoids these problems. The protocol is based on nuclei isolation at 4 &#176;C from frozen kidney tissue. Nuclei are isolated from a central piece of the mouse kidney comprised of the cortex, outer medulla, and inner medulla. This reduces the overrepresentation of cortical cells typical for whole-kidney samples for the benefit of medullary cells such that data will represent the entire corticomedullary axis at sufficient abundance. The protocol is simple, rapid, and adaptable and provides a step towards the standardization of single-nuclei transcriptomics in kidney research.

Here, we present a protocol to isolate high-quality nuclei from frozen mouse kidneys that improve the representation of medullary kidney cell types and avoids the gene expression artifacts from enzymatic tissue dissociation.

从成年小鼠肾脏中分离细胞核以进行单核RNA测序

The kidneys regulate diverse biological processes such as water, electrolyte, and acid-base homeostasis. Physiological functions of the kidney are ...

从冷冻哺乳动物组织中分离和分析单个细胞核

A Simple, Quick, and Partially Automated Protocol for the Isolation of Single Nuclei from Frozen Mammalian Tissues for Single Nucleus Sequencing

Single-cell and single-nucleus RNA sequencing have become common laboratory applications due to the wealth of transcriptomic information that they provide. Single nucleus RNA sequencing, particularly, is useful for investigating gene expression in difficult-to-dissociate tissues. Furthermore, this approach is also compatible with frozen (archival) material. Here, we describe a protocol to isolate high-quality single nuclei from frozen mammalian tissues for downstream single nucleus RNA sequencing in a partially-automated manner using commercially available instruments and reagents. Specifically, a robotic dissociator is used to automate and standardize tissue homogenization, followed by an optimized chemical gradient to filter the nuclei. Lastly, we accurately and automatically count the nuclei using an automated fluorescent cell counter. The performance of this protocol is demonstrated on mouse brain, rat kidney, and cynomolgus liver and spleen tissue. This protocol is straightforward, rapid, and readily adaptable to various mammalian tissues without requiring extensive optimization and provides good quality nuclei for downstream single nuclei RNA sequencing.

作者聚焦：增强药物发现 - 开发从冷冻组织中提取细胞核的自动化标准化方案 

The study describes a simple, quick, and partially automated protocol to isolate high-quality nuclei from frozen mammalian tissues for downstream single nuclei RNA sequencing.