这项工作得到了 R01DK102001 (N.A.Z.)、P30DK072488 (N.A.Z.) 和 T32DK098107 (T.L.H. 和 J.E.N.) 的支持。

下面概述的所有动物协议均符合并经马里兰大学动物保育和使用委员会 (IACUC) 批准. 
 1. 胚准备 <ol> <li> 通过自然交配生成胚胎 <ol> <li> 培养胚胎到3月龄, 生殖成熟度 5 , 8.</li>
		<li> 在胚胎采集前, 将成年雄性和雌性鱼从所需的菌株分离到分离的交配槽中, 并在每个容器中添加2雄性和3雌性. 
		注: 使用转基因的 insulin2a:mCherry 荧光报告株可以分析胰腺和 #946;-细胞. </li>
		<li> 将鱼转移到配有新鲜系统水的交配罐中, 并在第二天早上灯亮后立即移除分隔条. </li>
		<li> 允许鱼自然交配, 直到底部罐中的胚胎被观察到。以30分钟的间隔收集胚胎, 直到收集到所需的数量。将每个收集的时间点存储在28.5 和 #176 的胚胎培养基中的不同培养皿中; C. </li>
		<li> 在实验培养基中进行遗传物质或放置的显微注射 6 , 如果需要, 并培养新鲜的汉克和 #39 的胚胎培养基 8 在10厘米的 Petri 皿中28.5 和 #176; 注: 对于吗 (MO) 注入或突变动物的基因表达分析, 请注意, 每个操作都可能对基因表达产生附带影响。突变体可以在转录水平表现出基因补偿, 而 MO-based 基因的目标是 9 . </li>
	</ol> </li> <li> 阶段胚胎 <ol> <li> 在 50 和 #8211 的组中培养胚胎; 每10厘米培育皿中有75胚 以促进所有胚胎的一致发育时间. </li>
		<li> 在卵、外包和节阶段使用解剖显微镜监测发育形态学, 以确保发育进程 10 . 
		注: 去除任何垂死或畸形的胚胎, 以防止在盘中发育迟缓. </li>
		<li> 根据发育年龄分离胚胎。测量胚胎年龄使用节数字在分割以后 (post-gastrulation, 10.33 h 岗位受精 (hpf)) 直到大约 24 hpf。在 24 hpf 后, 用总体长来分期胚胎和幼虫. 
		注意: 节是在胚胎的背侧出现的 v 字形的胚层组织. </li>
		<li> 将已排序的胚胎放入28.5 和 #176; C 孵化器, 使发展达到预期的年龄. </li>
	</ol> </li> </ol> 2。单细胞离解: 整个胚胎和排序的细胞数量 <ol> <li> 整个胚胎分离 <ol> <li> 在预期的阶段安乐斑马鱼胚胎, 将培养皿放在冰上5-15 分钟, 直到没有观察到运动.</li>
		<li> 将20胚胎池转移到标记为1.5 毫升的离心管上。从离心管中取出多余的胚胎介质. </li>
		<li> 添加200和 #181; L 溶解试剂 (参见 材料表 ) 到含有胚胎的试管中。用杵质机械裂解试剂中的胚。添加800和 #181; L 溶解试剂, 使总体积为1毫升。存储在-80 和 #176; C 直到 RNA 提取. </li>
	</ol> </li> <li> 流排序的单元隔离 11 <ol> <li> 将胚胎从培养皿转移到1.5 毫升的离心管中, 并尽可能移除胚胎培养基. 
		注意: 根据胚胎年龄, 在这一步也可能需要机械离解。与胚胎和 #62; 48 hpf, 我们建议使用杵来破坏胚胎的完整性, 然后再继续. </li>
		<li> 孵育1毫升的离解缓冲 1 (见 材料表 ) 在1.5 毫升离心管的胚胎。室温孵育15-30 分钟。研制的解决方案, 轻轻地移向上和向下使用 P1000 提示混合每3-4 分钟在孵化步骤。不要涡流. </li>
		<li> 用离心法收集胚胎3分钟, 在 300 x 克和清除上清液。在1毫升离解缓冲2中重新暂停胚胎 (请参见 材料表 )。在室温下孵育15-30 分钟, 定期吸管研磨. </li>
		<li> 在显微镜下, 通过稀释1-2 和 #181 对荧光活化的细胞分类器中的悬浮液进行消化. 
		注意: 当被检查的分显示单细胞的细胞簇和胚胎组织的片断时, 完全消化已经发生. </li>
		<li> 以 300 x g 的离心法收集细胞, 5 分钟去除上清液。将细胞重新悬浮到1毫升的缓冲区, 重力过滤器通过40和 #181; m 细胞滤网从样品中去除未消化的组织. </li>
		<li> 使用例计算单元格, 并将其与资产管制的缓冲区稀释到大约 1x 10 6 在一个资产管制管中的单元/mL. 
		注: 对于每个胚胎 (少于5% 的总) 的细胞类型, 如胰腺和 #946;-细胞, 使用至少1000阶段匹配的胚胎. </li>
		<li> 为资产管制系统分类设备提供含有1毫升悬浮液样品的资产管制系统, 以及只含有裂解试剂或外地资产管制系统缓冲的资产管制系统管。门的流量分拣机只收集单一的细胞, 表达的荧光记者. </li>
		<li> 在收集到所需的单元格编号之前执行资产管制流程排序. 
		注意: 要执行 RNASeq, 有一个最小的总 RNA 需要。我们发现 3,000-5 000 细胞足以分离高质量高浓度的 RNA. </li>
		<li> 将收集的细胞储存在冰上, 并立即进行 RNA 制备. </li>
	</ol> </li> </ol> 3。rna 准备 <ol> <li> 提取 rna <ol> <li> 在室温下孵育所收集的样品 (从步骤 2) 和裂解试剂5分钟. </li>
		<li> 为每1.0 毫升的裂解试剂添加0.2 毫升氯仿, 并在十五年代用手倒置试管. 室温下孵育2-3 分钟。离心样品在 1.2万 x g 为15分钟在4和 #176; C. </li>
		<li> 将分离的, 水相转移到一个新鲜的管, 并添加0.5 毫升的异丙醇为每1.0 毫升的裂解试剂使用。室温孵育10分钟。离心样品在 1.2万 x g 为10分钟在4和 #176; C. </li>
		<li> 用75% 乙醇洗涤, 并将样品在 7500 x g 上离心5分钟, 在4和 #176; c. 完全去除上清, 使空气在室温下干燥。在15-30 和 #181 中重新悬浮 RNA; 焦二乙基 (DEPC)-处理过的水. </li>
	</ol> </li> <li> 纯化高质量的 rna <ol> <li> 将 RNA 悬浮与1/10 卷3M 醋酸钠 (pH 5.5) 和1的异丙醇量结合起来。在室温下孵育20分钟, 将样品在 12500 x g 离心10分钟, 在4和 #176; C. </li>
		<li> 在 DEPC 处理过的水中用 ice-cold 70% 乙醇清洗颗粒, 并将样品在 1万 x g 上离心5分钟, 在4和 #176; 重复一次洗涤步骤. </li>
		<li> 清除上清, 允许在室温下干燥。重新悬浮在 DEPC 处理的水中. </li>
		<li> 使用吸收光谱仪测定提取的 RNA 浓度 (ng/和 #181; L) 和纯度 (260/230 比)。在继续 RNASeq 之前, 请确保260/230 值为 ~ 2.0。存储在-80 和 #176; C 直到我们e (最多6月). </li>
		<li> 将 RNA 样本发送给供应商或核心以进行 RNASeq 和基因表达变化分析, 这是基于顺序读取的量化。从供应商返回的结果通常提供的基因列表显示, 在样本之间的成绩单读取明显的折叠变化. 
		注: 如果上述方法产生质量较差的 RNA, 则可以使用列。rna 样本的数量、浓度和 rna 完整性数字应与供应商或核心确认。供应商或核心也通常会评估. </li>
	</ol> </li> </ol> 4。路径和 GO 术语分析 注意: 在核心或供应商提供的 RNASeq 后, 请参阅 图 1 , 以了解基因表达分析的代表性输出. 
<ol> <li> 对差异表达的基因排序 <ol> <li> 在电子表格管理软件中比较单个实验条件与控制 <ol> <li> 打开数据 (结果) (请参见 材料表).</li>
			<li> 选择 #39 旁边的下拉箭头; 排序和 #39; 按钮并选择和 #34; 自定义排序和 #34; 在包含实验与控制条件中的差异表达基因的电子表格中. </li>
			<li> 选择 #39 下的框; 列和 #39; 在弹出的窗口中, 选择按和 #39 排序; 利物浦和 #39; 专栏。确保和 #39; 价值和 #39; 在和 #39 中选择; 排序 #39; 列。选择以排序从和 #39; 最大到最小和 #39; 在和 #39; 命令和 #39; 列并单击和 #34; 确定和 #34;. 
			注: 这将排序差异表达的基因, 使那些增加表达 (正面利物浦) 将出现在列表的顶部, 而那些减少表达 (负利物浦) 将出现在列表的底部. </li>
		</ol> </li> <li> 将多个实验条件与单个控件进行比较, 如下所示。
		<ol> <li> 在实验1与控制电子表格中选择空列中的第一个单元格, 以确定在两个实验条件中发现的差异表达基因。在单元格中键入以下公式: <img alt="Equation" src="/files/ftp_upload/56187/56187eq1.jpg"/> 注意: 此公式是 IF、ISERROR 和匹配函数的组合。(i) 比赛功能, 比赛 (Experimental2_vs_Control!A:A,0), 将查找 A1 (ENSEMBL ID) 中的值, 该列 (a:) 的电子表格名为 Experimental2_vs_Control (Experimental2_vs_Control!)。#34; 0 和 #34; 指示查找精确匹配, 如果找到精确匹配, 则函数将返回值 #34; 1 和 #34; 如果未找到匹配项, 则函数将返回错误和 #34; N/a 和 #34;。(ii) 比赛功能的结果, 然后输入到 ISERROR 函数, ISERROR (匹配 (A1, Experimental2_vs_Control!A:A,0)), 如果输入是和 #34; 1 和 #34; 表明匹配被发现, 它将返回和 #34; 假和 #34; 如果输入是和 #34; N/a 和 #34; 表示未找到匹配, 则返回和 #34; 真和 #34;。(三) #34; 真实与 #34; 或 #34; 虚假和 #34; 结果然后输入 if 函数, 如果 (ISERROR (Experimental2_vs_Control!A:A,0), #34; #34 #34;D 重复 #34;) 在哪里, 如果输入是和 #34; 真实和 #34; 表示未找到匹配项, 则将返回第一组引号 (和 #34; #34;) 为空, 因此单元格将为空。如果输入 #34; FALSE 和 #34; 表示匹配, 则将返回第二组引号 (和 #34;D 重复和 #34;) 之间的值, 并且单元格会说和 #34;D 重复 #34;. </li>
			<li> 按 #34; 输入和 #34; 或 #34; 返回和 #34; 运行等式。选择包含公式的单元格, 然后单击单元格右下角的框。保持鼠标单击并将所选区域一直拖到列中, 直到最后一个 #39; 功能 ID 和 #39;, 将公式复制到列中的每个单元格中. </li>
			<li> 选择和 #34; 自定义排序和 #34; 再次, 通过单击 #34; + #34; 左下角的图标, 添加第二级排序。在第一级, #34; 排序依据和 #34;, 在列选择和 #34;D 重复和 #34;, 根据选择和 #39 排序; 值和 #39;, 根据顺序选择和 #39; Z 到 A 和 #39;。在第二级, #34; 然后通过和 #34;, 在列选择和 #39; 利物浦和 #39; 根据选择和 #39; 价值和 #39; 根据顺序选择和 #39; 最大到最小和 #39; 选择和 #34; 好 #34;. 
			注意: 这将根据表达变化的方向性将基因列表分类为4组。重要的是要检查在两个实验条件中发现的基因, 以确保表达的变化是在同一方向的两个或相反的方向. </li>
			<li> 在继续之前从基因符号列中删除任何括号, 否则在数据库中将找不到结果。选择包含基因符号的整列。选择和 #34; 编辑和 #34; 然后, #34; 替换和 #34; 在下拉 #39; 文件和 #39; 菜单。类型和 #34;(*) 和 #34; 在和 #34; 查找: 和 #34; "替换" 窗口的栏, 然后离开和 #34; 替换为: 和 #34; 栏为空。选择和 #39; 替换所有 #39; 删除括号中的所有实例. 
			注: * 表示任意数量的字符, 通过在两个圆括号之间放置此字符, 程序将提示您在突出显示的单元格中查找任何实例, 并且任何括号实例都将被替换为无, 从而删除它们. </li>
		</ol> </li> </ol> </li> <li> 确定富集路径 <ol> <li> 复制要确定剪贴板的丰富路径的集合的基因符号。转到 ConsensusPathDB 12 。选择和 #34; 基因组分析和 #34; 在网页的左栏, 其次是和 #34; 过度表征分析和 #34;. </li>
		<li> 将 #34 中的基因列表粘贴;P 浪费基因/蛋白质标识符和 #34 的列表; 框。在 #34 中选择基因符号; 基因/蛋白质标识符类型和 #34; 框和单击 #34;P roceed 和 #34;。根据路径数据库和 #34 的定义, 选择;P athways 旁边的框和 #34; 在 "Pathway-based 集" 部分下. 
		注意: 将显示许多用于分析的选项, 包括要搜索的可用数据库的列表。我们建议取消所有数据库, 除了 Kegg 和 Reactome 数据库, 因为它们是最建立和全面的。还可以根据需要调整与输入列表和 p 值截止设置的最小重叠。我们建议将这些设置保留在默认的2基因最小重叠和 0.01 p 值截止处. </li>
		<li> 选择和 #34; 查找丰富集和 #34; 获取输入列表中包含基因的路径列表. 
		注: 输出将以表格的形式, 包括每个通路的名称, 其次是和 #34; 设置大小和 #34; (指明通路中总基因的数量); #34; 候选人包含和 #34; (表明输入列表中的基因数量在该通路中), 以及 p 值和 q 值 (罗斯福), 和数据库的路径被确定. </li>
	如上所述, </ol> </li> <li> 生成路径网络 <ol> <li> 确定丰富的路径. </li>
		<li> 选择所有富集路径以在通路网络中可视化, 通过选择要可视化的路径名称旁边的每个框, 或单击和 #34; 全部和 #34; 下 #34; 选择和 #34; 在选择框上方的列标题中, 选择和 #34;可视化所选集和 #34;. 
		注意: 我们建议, 如果有少于30的所有路径的可视化;如果有大于30的路径, 我们建议选择前30最丰富的路径 (那些含有最大数量的基因从输入列表). </li>
		<li> 调整和 #34; 相对重叠和 #34; 和 #34; 共享候选和 #34; 筛选器, 通过选择页面顶部中心的任一框并输入渴求百分比相对重叠或共享候选的数量, 要更加严格, 以便使路径网络中的更贴切的重叠更清晰, 并选择和 #34; 应用和 #34;. 
		注意: 我们建议最小的相对重叠 0.2, 表明20% 基因重叠之间的2通路, 以连接他们, 至少2共享候选人。通过单击页面左上角的图形图例可以看到图形图例. </li>
	</ol> </li> <li> 确定丰富的 GO 术语 <ol> <li> 复制该组的基因符号, 其中一个希望将丰富的基因本体确定为剪贴板。转到 #39; go 富集分析工具和 #39; 在基因本体论联合体中 13 。将基因符号列表粘贴在页面左侧的框中, #34; 您的基因 id 在这里和 #8230; #34; </li> <li> 选择要使用的 GO 术语集, 在 "基因 id" 框下面列出: 生物过程、分子功能或细胞成分。选择 (推荐) 和 #39; 生物过程和 #39;选择和 #39; 斑马鱼和 #39; 在 GO 术语框下方, 单击并 #34; 提交和 #34; 
		注意: 我们建议使用默认的 p 值截断 0.05. </li>
	</ol> </li> </ol> 5。qRT pcr 验证方法 注: 在复制实验中, 应通过靶向 qRT pcr 验证 RNASeq 基因表达变化的个体基因. 
<ol> <li> cDNA 合成 <ol> <li> 使用3.1 节中描述的方法从胚胎中提取 RNA。RNA 提取. </li>
		<li> 转换1和 #181; 使用 cdna 转换试剂盒将 RNA 转化为 cdna (请参阅 材料表 )。结合 RNA、dNTPs 和逆转录酶。根据制造商和 #39 的规格执行 thermocycler 反应. </li>
		<li> 在 DEPC 处理的水中稀释1:3 的 cDNA。存储在4和 #176; C 最多1-2 月. </li>
	</ol> </li> <li> qRT-pcr 验证 <ol> <li> 选择由 RNA 测序结果 qRT pcr 验证的基因。在表达中发现具有高折叠变化的基因。确定这些基因中哪一个也含有高的读数, 因为这表明了丰富的表达. </li>
		<li> 选择10-12 目标从高折叠变化, 高读取计数列表的基因。设计引物, 以放大跨越至少1内含子外显子边界的目标基因. </li>
		<li> 将基因或目标区域输入 qPCR 入门设计站点 14 。选择 #34;d 设计 2 qPCR 底漆和 #34; 并提示网站创建入门集. 
		注意: 一定要包括内部控制底漆, 例如 和 #946;-肌动蛋白 , 以规范样本之间的比较。#946;-肌动蛋白底漆为 F: 5 和 #39; TCGAGCTGTCTTCCCATCCA-3 和 #39; R: 5 和 #39;-TCACCAACGTAGCTGTCTTTCTG-3 和 #39;. </li>
		<li> 将 cDNA、前引物、反转底漆和聚合酶结合。进行 qRT PCR 扩增, 以确定基因的相对表达 15 . </li>
		<li> 通过相对量化测定来分析感兴趣基因的相对 mRNA 表达 15 . </li>
		<li> 将 qRT PCR 与 RNASeq 结果进行比较, 以确保差异表达式的方向性一致. </li>
	</ol>
	</li>
</ol>

<ol>
	<li>Nusslein-Volhard, C., Dahm, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Zebrafish. , (2002).</li><li>Detrich, H. W., Zon, L., Westerfield, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Zebrafish: Disease Models and Chemical Screens. , (2017).</li><li>Detrich, H. W., Zon, L. I., Westerfield, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Zebrafish: Genetics, Genomics, and Transcriptomics. , (2016).</li><li>Detrich, H. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Zebrafish: Genetics, Genomics and Informatics. , (2011).</li><li>Avdesh, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regular+care+and+maintenance+of+a+zebrafish+(Danio+rerio)+laboratory:+an+introduction.">Regular care and maintenance of a zebrafish (Danio rerio) laboratory: an introduction.</a> J Vis Exp. (69), e4196 (2012).</li><li>Rosen, J. N., Sweeney, M. F., Mably, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microinjection+of+zebrafish+embryos+to+analyze+gene+function.">Microinjection of zebrafish embryos to analyze gene function.</a> J Vis Exp. (25), (2009).</li><li>Hwang, W. Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficient+genome+editing+in+zebrafish+using+a+CRISPR-Cas+system.">Efficient genome editing in zebrafish using a CRISPR-Cas system.</a> Nat Biotechnol. 31 (3), 227-229 (2013).</li><li>Westerfield, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The zebrafish book. A guide for the laboratory use of zebrafish (Danio rerio). , (2000).</li><li>Rossi, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genetic+compensation+induced+by+deleterious+mutations+but+not+gene+knockdowns.">Genetic compensation induced by deleterious mutations but not gene knockdowns.</a> Nature. 524 (7564), 230-233 (2015).</li><li>Kimmel, C. B., Ballard, W. W., Kimmel, S. R., Ullmann, B., Schilling, T. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stages+of+embryonic+development+of+the+zebrafish.">Stages of embryonic development of the zebrafish.</a> Dev Dyn. 203 (3), 253-310 (1995).</li><li>Samsa, L. A., Fleming, N., Magness, S., Qian, L., Liu, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolation+and+Characterization+of+Single+Cells+from+Zebrafish+Embryos.">Isolation and Characterization of Single Cells from Zebrafish Embryos.</a> J Vis Exp. (109), (2016).</li><li>. IDT Primerquest Tool Available from: <a target="_blank" href="https://www.idtdna.com/Primerquest/Home/Index">https://www.idtdna.com/Primerquest/Home/Index</a> (2017)</li><li>Heid, C. A., Stevens, J., Livak, K. J., Williams, P. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real+time+quantitative+PCR.">Real time quantitative PCR.</a> Genome Res. 6 (10), 986-994 (1996).</li><li>Leitch, C. C., Lodh, S., Prieto-Echague, V., Badano, J. L., Zaghloul, N. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Basal+body+proteins+regulate+Notch+signaling+through+endosomal+trafficking.">Basal body proteins regulate Notch signaling through endosomal trafficking.</a> J Cell Sci. 127 (Pt 11), 2407-2419 (2014).</li><li>Lodh, S., Hostelley, T. L., Leitch, C. C., O'Hare, E. A., Zaghloul, N. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+effects+on+beta-cell+mass+by+disruption+of+Bardet-Biedl+syndrome+or+Alstrom+syndrome+genes.">Differential effects on beta-cell mass by disruption of Bardet-Biedl syndrome or Alstrom syndrome genes.</a> Hum Mol Genet. 25 (1), 57-68 (2016).</li><li>Hostelley, T. L., Lodh, S., Zaghloul, N. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole+organism+transcriptome+analysis+of+zebrafish+models+of+Bardet-Biedl+Syndrome+and+Alstrom+Syndrome+provides+mechanistic+insight+into+shared+and+divergent+phenotypes.">Whole organism transcriptome analysis of zebrafish models of Bardet-Biedl Syndrome and Alstrom Syndrome provides mechanistic insight into shared and divergent phenotypes.</a> BMC Genomics. 17, 318 (2016).</li></ol>

作者没有什么可透露的。

本协议中描述的方法提供了一个相对快速和 cost-effective 的策略, 用于对整个动物或特定排序的细胞群进行转录分析。斑马鱼为这种类型的研究提供了一个有利的模式, 因为在产生大量的起始物质, 易于实施遗传或环境实验条件, 以及大量的可用性光谱的转基因记者线允许隔离细胞类型的特定和组织特定的群体。
虽然这里没有详细说明, 但这种方法可以很容易地容纳从幼鱼或成年...

全球基因表达的比较分析是鉴别新基因的重要工具。这种分析通常依赖于对实验和对照样本的成绩单丰度进行定量评估。靶向方法, 如 qRT PCR 是相对快速和准确的调查单基因表达变化。RNA 测序 (RNASeq) 提供了一种宽泛的、无假设的方法来识别样本间基因表达的显著变化, 使之成为跨实验系统进行此类调查的标准。
斑马鱼已成为一个突出的模式, 在许多疾病地区。最初为他们的用途开发生物学研究, 由于他们的高繁殖力和相对地低维护费用, 试验性使用斑马鱼已经演变包括各种各样的表型从胚胎到成人阶段并且分子分析的宽数组1,2,3。事实上, 这些优势使分子机械研究迅速和 cost-effective, 因为容易获得大量的材料结合在一起, 在生活的所有阶段的遗传和环境操作的容易。此外, 斑马鱼的胚胎和幼虫的透明性质使它非常适合于生成细胞和组织特异的转基因报告线, 允许在体内离散细胞群的可视化4。利用此类线, 根据报告基因表达, 对特定孤立细胞类型进行全球基因表达分析。
在这里, 我们提出了一个全面的协议, 全球基因表达分析使用 RNASeq 后, 养殖斑马鱼胚胎。基因实验操作, 包括基于吗 (MO) 的瞬态基因击倒或 CRISPR 介导的基因组编辑, 已在别处出现5,6,7。因此, 我们专注于一个详细的协议, 分离 RNA 从整个胚胎或排序的转基因记者表达细胞后, 简单的计算分析 RNASeq 结果使用路径工具和基因本体 (GO) 术语。最后, 我们还包括了一种通过定量逆转录酶 pcr (qRT pcr) 验证基因表达变化的策略。这些协议适用于斑马鱼的胚胎在广泛的实验条件, 包括比较遗传突变体或环境条件。

<table>
	<tbody>
		<tr>
			<td>Commercial Reagents</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>TriZol</td>
			<td>Thermo Scientific</td>
			<td>15596026</td>
			<td>lysis reagent</td>
		</tr>
		<tr>
			<td>TrypLE</td>
			<td>Gibco</td>
			<td>12604013</td>
			<td>dissociation buffer 1</td>
		</tr>
		<tr>
			<td>FACSMax</td>
			<td>Genlantis</td>
			<td>T200100</td>
			<td>dissociation buffer 2</td>
		</tr>
		<tr>
			<td>DEPC-treated water</td>
			<td>Sigma</td>
			<td>95284</td>
			<td></td>
		</tr>
		<tr>
			<td>FirstStrand cDNA conversion</td>
			<td>Thermo Scientific</td>
			<td>K1621</td>
			<td>cDNA conversion kit</td>
		</tr>
		<tr>
			<td>2X SYBR Green Master Mix</td>
			<td>Roche</td>
			<td>4707516001</td>
			<td>qRT-PCR Master Mix</td>
		</tr>
		<tr>
			<td>FACS buffer</td>
			<td>Fisher Scientific</td>
			<td>50-105-9042</td>
			<td></td>
		</tr>
		<tr>
			<td>chloroform</td>
			<td>Sigma Aldrich</td>
			<td>288306</td>
			<td></td>
		</tr>
		<tr>
			<td>sodium acetate</td>
			<td>Sigma Aldrich</td>
			<td>S2889</td>
			<td></td>
		</tr>
		<tr>
			<td>Name</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>Zebrafish Strains</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Tuebingen</td>
			<td>ZIRC</td>
			<td>ZL57</td>
			<td></td>
		</tr>
		<tr>
			<td>ins2a:mCherry</td>
			<td>ZIRC</td>
			<td>ZL1483</td>
			<td></td>
		</tr>
		<tr>
			<td>Name</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>Equipment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>40 micron cell strainer</td>
			<td>Sigma</td>
			<td>CLS431750</td>
			<td></td>
		</tr>
		<tr>
			<td>FACS tube</td>
			<td>BD Falcon</td>
			<td>352063</td>
			<td></td>
		</tr>
		<tr>
			<td>hemocytometer</td>
			<td>Sigma</td>
			<td>Z359629</td>
			<td></td>
		</tr>
		<tr>
			<td>Dissecting Microscope</td>
			<td>Zeiss</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Inverted Microscope</td>
			<td>Zeiss</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Nanodrop</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Illumina HiSeq</td>
			<td>Illumina</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>LightCycler 480</td>
			<td>Roche</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Mating tanks 1.0L Crossing Tank Set</td>
			<td>Aquaneering</td>
			<td>ZHCT100</td>
			<td></td>
		</tr>
		<tr>
			<td>FACS tube 5 mL polypropylene tube</td>
			<td>BD Falcon</td>
			<td>352063</td>
			<td></td>
		</tr>
		<tr>
			<td>Name</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>Software</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Excel</td>
			<td>Microsoft</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Consensus Path DB</td>
			<td>http://cpdb.molgen.mpg.de/</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>GO Enrichment Analysis</td>
			<td colspan="2">http://geneontology.org/page/go-enrichment-analysis</td>
			<td></td>
		</tr>
	</tbody>
</table>

sample preparation and analysis of rnaseq-based gene expression data from zebrafish

分析全球基因表达变化是一个有价值的工具, 以确定新的途径的基础观察表型。斑马鱼是一个很好的模型, 快速评估整个转录从整个动物或单个细胞的数量, 由于 RNA 的容易分离, 从大量的动物。本文介绍了利用 RNA 测序 (RNASeq) 对斑马鱼胚胎进行全球基因表达分析的协议。我们描述的是从整个胚胎或细胞群中获得的 RNA 的制备方法。我们还描述了一种分析 RNASeq 数据的方法, 用以识别全球基因表达数据集的富集通路和基因本体 (GO) 术语。最后, 我们提供了一个协议, 以验证基因表达变化使用定量逆转录酶 pcr (qRT pcr)。这些协议可用于比较分析的控制和实验组斑马鱼, 以确定新的基因表达变化, 并提供分子洞察的表型的兴趣。

差异表达基因的分类:
为了鉴别斑马鱼 Alström 综合征和 Bardet-Biedl 综合征 (BBS) 模型幼虫期的差异表达基因, 我们以alms1或bbs1的记录为目标, 将先前经过验证的拼接阻断 MOs 注入野生型斑马鱼胚胎16,17。在5天后受精 (dpf), 两个 RNA 复制从每个条件提取, 以及胚胎注射控制钼, 如?...

Watch this Scientific Journal Video about Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish at JoVE.com

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

斑马鱼 RNASeq-based 基因表达数据的样品制备与分析

该协议提出了一种从斑马鱼胚胎, 幼虫, 或排序细胞的整体转录分析的方法。我们包括 RNA 的分离, RNASeq 数据的通路分析, 和 qRT pcr 验证基因表达的变化。

The analysis of global gene expression changes is a valuable tool for identifying novel pathways underlying observed phenotypes. The zebrafish is an ...

sample-preparation-analysis-rnaseq-based-gene-expression-data-from

Research

JoVE Journal

Genetics

10.7K 次观看.  University of Maryland School of Medicine. 该协议提出了一种从斑马鱼胚胎, 幼虫, 或排序细胞的整体转录分析的方法。我们包括 RNA 的分离, RNASeq 数据的通路分析, 和 qRT pcr 验证基因表达的变化。

视频: Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures

Circadian clocks are functional in all light-sensitive organisms, allowing for an adaptation to the external world by anticipating daily environmental changes. Considerable progress in our understanding of the tight connection between the circadian clock and most aspects of physiology has been made in the field over the last decade. However, unraveling the molecular basis that underlies the function of the circadian oscillator in humans stays of highest technical challenge. Here, we provide a detailed description of an experimental approach for long-term (2-5 days) bioluminescence recording and outflow medium collection in cultured human primary cells. For this purpose, we have transduced primary cells with a lentiviral luciferase reporter that is under control of a core clock gene promoter, which allows for the parallel assessment of hormone secretion and circadian bioluminescence. Furthermore, we describe the conditions for disrupting the circadian clock in primary human cells by transfecting siRNA targeting CLOCK. Our results on the circadian regulation of insulin secretion by human pancreatic islets, and myokine secretion by human skeletal muscle cells, are presented here to illustrate the application of this methodology. These settings can be used to study the molecular makeup of human peripheral clocks and to analyze their functional impact on primary cells under physiological or pathophysiological conditions.

Here, we describe settings to monitor in parallel circadian bioluminescence and the secretory activity of human islet cells and primary myotubes. For this, we employed lentiviral gene delivery of a luciferase core clock reporter, followed by in vitro synchronization and collection of outflow medium by continuous cell perifusion.

在人原代细胞培养生物钟基因表达及荷尔蒙分泌的并行测量

Circadian clocks are functional in all light-sensitive organisms, allowing for an adaptation to the external world by anticipating daily environmental ...

科研

遗传学

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

Gene expression measurements from bulk populations of cells can obscure the considerable transcriptomic variation of individual cells within those populations. Single-cell gene expression measurements can help assess the role of noise in gene expression, identify correlations in the expression of pairs of genes, and reveal subpopulations of cells that respond differently to a stimulus. Here, we describe a procedure to measure the expression of up to 96 genes in single mammalian cells isolated from a population growing in tissue culture. Cells are sorted into lysis buffer by fluorescence-activated cell sorting (FACS), and the mRNA species of interest are reverse-transcribed and amplified. Gene expression is then measured using a microfluidic real-time PCR machine, which performs up to 96 qPCR assays on up to 96 samples at a time. We also describe the generation and use of PCR amplicon standards to enable the estimation of the absolute number of each transcript. Compared with other methods of measuring gene expression in single cells, this approach allows for the quantification of more distinct transcripts than RNA FISH at a lower cost than RNA-Seq.

We describe a method to sort single mammalian cells and to quantify the expression of up to 96 target genes of interest in each cell. This method includes the use of internal qPCR standards to enable the estimation of absolute transcript counts.

单细胞基因表达谱使用流式细胞仪和qPCR内部标准

Gene expression measurements from bulk populations of cells can obscure the considerable transcriptomic variation of individual cells within those ...

Studying Cell Cycle-regulated Gene Expression by Two Complementary Cell Synchronization Protocols

The gene expression program of the cell cycle represents a critical step for understanding cell cycle-dependent processes and their role in diseases such as cancer. Cell cycle-regulated gene expression analysis depends on cell synchronization into specific phases. Here we describe a method utilizing two complementary synchronization protocols that is commonly used for studying periodic variation of gene expression during the cell cycle. Both procedures are based on transiently blocking the cell cycle in one defined point. The synchronization protocol by hydroxyurea (HU) treatment leads to cellular arrest in late G1/early S phase, and release from HU-mediated arrest provides a cellular population uniformly progressing through S and G2/M. The synchronization protocol by thymidine and nocodazole (Thy-Noc) treatment blocks cells in early mitosis, and release from Thy-Noc mediated arrest provides a synchronized cellular population suitable for G1 phase and S phase-entry studies. Application of both procedures requires monitoring of the cell cycle distribution profiles, which is typically performed after propidium iodide (PI) staining of the cells and flow cytometry-mediated analysis of DNA content. We show that the combined use of two synchronization protocols is a robust approach to clearly determine the transcriptional profiles of genes that are differentially regulated in the cell cycle (i.e. E2F1 and E2F7), and consequently to have a better understanding of their role in cell cycle processes. Furthermore, we show that this approach is useful for the study of mechanisms underlying drug-based therapies (i.e. mitomycin C, an anticancer agent), because it allows to discriminate genes that are responsive to the genotoxic agent from those solely affected by cell cycle perturbations imposed by the agent.

We report two cell synchronization protocols that provide a context for studying events related to specific phases of the cell cycle. We show that this approach is useful for analyzing the regulation of specific genes in an unperturbed cell cycle or upon exposure to agents affecting the cell cycle.

通过两个互补细胞同步方案研究细胞周期调控的基因表达

The gene expression program of the cell cycle represents a critical step for understanding cell cycle-dependent processes and their role in diseases such ...

Bidirectional Retroviral Integration Site PCR Methodology and Quantitative Data Analysis Workflow

Integration Site (IS) assays are a critical component of the study of retroviral integration sites and their biological significance. In recent retroviral gene therapy studies, IS assays, in combination with next-generation sequencing, have been used as a cell-tracking tool to characterize clonal stem cell populations sharing the same IS. For the accurate comparison of repopulating stem cell clones within and across different samples, the detection sensitivity, data reproducibility, and high-throughput capacity of the assay are among the most important assay qualities. This work provides a detailed protocol and data analysis workflow for bidirectional IS analysis. The bidirectional assay can simultaneously sequence both upstream and downstream vector-host junctions. Compared to conventional unidirectional IS sequencing approaches, the bidirectional approach significantly improves IS detection rates and the characterization of integration events at both ends of the target DNA. The data analysis pipeline described here accurately identifies and enumerates identical IS sequences through multiple steps of comparison that map IS sequences onto the reference genome and determine sequencing errors. Using an optimized assay procedure, we have recently published the detailed repopulation patterns of thousands of Hematopoietic Stem Cell (HSC) clones following transplant in rhesus macaques, demonstrating for the first time the precise time point of HSC repopulation and the functional heterogeneity of HSCs in the primate system. The following protocol describes the step-by-step experimental procedure and data analysis workflow that accurately identifies and quantifies identical IS sequences.

This manuscript describes the experimental procedure and software analysis for a bidirectional integration site assay that can simultaneously analyze upstream and downstream vector-host junction DNA. Bidirectional PCR products can be used for any downstream sequencing platform. The resulting data are useful for a high-throughput, quantitative comparison of integrated DNA targets.

双向逆转录病毒整合位点PCR方法和定量数据分析工作流程

Integration Site (IS) assays are a critical component of the study of retroviral integration sites and their biological significance. In recent retroviral ...

Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput

The aleurone layer of barley grains is an important model system for hormone-regulated gene expression in plants. In aleurone cells, genes required for germination or early seedling development are activated by gibberellin (GA), while genes associated with stress responses are activated by abscisic acid (ABA). The mechanisms of GA and ABA signaling can be interrogated by introducing reporter gene constructs into aleurone cells via particle bombardment, with the resulting transient expression measured using enzyme assays. An improved protocol is reported that partially automates and streamlines the grain homogenization step and the enzyme assays, allowing significantly more throughput than existing methods. Homogenization of the grain samples is carried out using an automated tissue homogenizer, and GUS (&#946;-glucuronidase) assays are carried out using a 96-well plate system. Representative results using the protocol suggest that phospholipase D activity may play an important role in the activation of HVA1 gene expression by ABA, through the transcription factor TaABF1.

An improved protocol is presented for the measurement of transient gene expression from reporter constructs in barley aleurone cells after particle bombardment. The combination of automated grain grinding with 96-well plate enzyme assays provides high throughput for the procedure.

提高吞吐量的轰击大麦糊粉层层中基因表达的测定

The aleurone layer of barley grains is an important model system for hormone-regulated gene expression in plants. In aleurone cells, genes required for ...

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling pathway is one of such essential molecular machinery for cell-to-cell communications, which plays key roles in normal development of embryos. This pathway involves a cell-to-cell transfer of oscillatory information with ultradian rhythms, but despite the progress in molecular biology techniques, it has been challenging to elucidate the impact of multicellular interactions on oscillatory gene dynamics. Here, we present a protocol that permits optogenetic control and live monitoring of gene expression patterns in a precise temporal manner. This method successfully revealed that intracellular and intercellular periodic inputs of Notch signaling entrain intrinsic oscillations by frequency tuning and phase shifting at the single-cell resolution. This approach is applicable to the analysis of the dynamic features of various signaling pathways, providing a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

Here, we present a protocol to analyze cell-to-cell transfer of oscillatory information by optogenetic control and live monitoring of gene expression. This approach provides a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

细胞间相互作用中基因表达模式的控制与分析的 Optogenetic 方法

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling ...

An Ecdysone Receptor-based Singular Gene Switch for Deliberate Expression of Transgene with Robustness, Reversibility, and Negligible Leakiness

Precise control of transgene expression is desirable in biological and clinical studies. However, because the binary feature of currently employed gene switches requires the transfer of two therapeutic expression units concurrently into a single cell, the practical application of the system for gene therapy is limited. To simplify the transgene expression system, we generated a gene switch designated as pEUI(+) encompassing a complete set of transgene expression modules in a single vector. Comprising of the GAL4 DNA-binding domain and modified EcR (GvEcR), a minimal VP16 activation domain fused with a GAL4 DNA-binding domain, as well as a modified Drosophila ecdysone receptor (EcR), the newly developed singular gene switch is highly responsive to the administration of a chemical inducer in a time- and dosage-dependent manner. The pEUI(+) vector is a potentially powerful tool for improving the control of transgene expression in both biological research and pre-clinical studies. Here, we present a detailed protocol for modulation of a transient and stable transgene expression using pEUI(+) vector by the treatment of tebufenozide (Teb). Additionally, we share important guidelines for the use of Teb as a chemical inducer.

Here, we present a protocol for the modulation of transgene expression using pEUI(+) singular gene switch by tebufenozide treatment.

一种基于昆虫蜕皮激素受体的奇异基因开关, 用于对转基因进行有鲁棒性、可逆性和可忽略的泄漏的刻意表达

Precise control of transgene expression is desirable in biological and clinical studies. However, because the binary feature of currently employed gene ...

Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to abiotic stresses and diseases. As the plant microbiome can be highly complex, low-cost, high-throughput methods such as amplicon-based sequencing of the 16S rRNA gene are often preferred for characterizing its microbial composition and diversity. However, the selection of appropriate methodology when conducting such experiments is critical for reducing biases that can make analysis and comparisons between samples and studies difficult. This protocol describes in detail a standardized methodology for the collection and extraction of DNA from soil, rhizosphere, and root samples. Additionally, we highlight a well-established 16S rRNA amplicon sequencing pipeline that allows for the exploration of the composition of bacterial communities in these samples, and can easily be adapted for other marker genes. This pipeline has been validated for a variety of plant species, including sorghum, maize, wheat, strawberry, and agave, and can help overcome issues associated with the contamination from plant organelles.

Here, we describe a protocol to obtain amplicon sequence data of soil, rhizosphere, and root endosphere microbiomes. This information can be used to investigate the composition and diversity of plant-associated microbial communities, and is suitable for the use with a wide range of plant species.

从土壤、根际和根 Endosphere 提取细菌群落数据的根菌群探析

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to ...

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

We have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing high-throughput short-read DNA sequencing. The resulting sequence datasets can not only track what genes in a population that are enriched during selection for positive yeast 2-hybrid interactions, but also give detailed information about the relevant subdomains of proteins sufficient for interaction. Here, we describe a full suite of stand-alone software programs that allow non-experts to perform all the bioinformatics and statistical steps to process and analyze DNA sequence fastq files from a batch yeast 2-hybrid assay. The processing steps covered by these software include: 1) mapping and counting sequence reads corresponding to each candidate protein encoded within a yeast 2-hybrid prey library; 2) a statistical analysis program that evaluates the enrichment profiles; and 3) tools to examine the translational frame and position within the coding region of each enriched plasmid that encodes the interacting proteins of interest.

Deep sequencing of yeast populations selected for positive yeast 2-hybrid interactions potentially yields a wealth of information about interacting partner proteins. Here, we describe the operation of specific bioinformatics tools and customized updated software to analyze sequence data from such screens.

间歇酵母 2-混合筛序列数据的信息化分析

We have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing ...

Preparation and Gene Modification of Nonhuman Primate Hematopoietic Stem and Progenitor Cells

Hematopoietic stem and progenitor cell (HSPC) transplantation has been a cornerstone therapy for leukemia and other cancers for nearly half a century, underlies the only known cure of human immunodeficiency virus (HIV-1) infection, and shows immense promise in the treatment of genetic diseases such as beta thalassemia. Our group has developed a protocol to model HSPC gene therapy in nonhuman primates (NHPs), allowing scientists to optimize many of the same reagents and techniques that are applied in the clinic. Here, we describe methods for purifying CD34+ HSPCs and long-term persisting hematopoietic stem cell (HSC) subsets from primed bone marrow (BM). Identical techniques can be employed for the purification of other HSPC sources (e.g., mobilized peripheral blood stem cells [PBSCs]). Outlined is a 2 day protocol in which cells are purified, cultured, modified with lentivirus (LV), and prepared for infusion back into the autologous host. Key readouts of success include the purity of the CD34+ HSPC population, the ability of purified HSPCs to form morphologically distinct colonies in semisolid media, and, most importantly, gene modification efficiency. The key advantage to HSPC gene therapy is the ability to provide a source of long-lived cells that give rise to all hematopoietic cell types. As such, these methods have been used to model therapies for cancer, genetic diseases, and infectious diseases. In each case, therapeutic efficacy is established by enhancing the function of distinct HSPC progeny, including red blood cells, T cells, B cells, and/or myeloid subsets. The methods to isolate, modify, and prepare HSPC products are directly applicable and translatable to multiple diseases in human patients.

The goal of this protocol is to isolate nonhuman primate CD34+ cells from primed bone marrow, to gene-modify these cells with lentiviral vectors, and to prepare a product for infusion into the autologous host. The total protocol length is approximately 48 h.

非人类灵长类动物造血干细胞和祖细胞的制备及基因修饰

Hematopoietic stem and progenitor cell (HSPC) transplantation has been a cornerstone therapy for leukemia and other cancers for nearly half a century, ...