这项工作得到了葛兰研究院 GM117446 的支持。

1. 流式细胞仪分选细胞的制备
<ol><li>接种15毫升试管, 每 YEPD 汤8毫升, 这样, 在隔夜生长后, 每毫升的培养量达到 5 x 106到 1.5 x 107细胞的密度 (见讨论说明 1)。</li>
	<li>向下旋转酵母细胞 (1400 x g, 在室温或4°c) 在15毫升螺丝帽离心机管为5分钟, 并用重悬细胞在1.5 毫升70% 乙醇, 并且转移到1.6 毫升离心管, 让这个坐 1 h 在室温或至少 3 h 在冰 (可以无限期地存储在4摄氏度) (参见讨论点 (2))。</li>
	<li>在离心的酵母细胞 (1.4万 x g, 4 °c) 为1分钟, 并用重悬在1毫升50毫米柠檬酸钠, pH 7.2, 旋转下来 (1.4万 x g, 4 °c) 为1分钟, 吸出上清, 并用重悬在1毫升50毫米柠檬酸钠, pH 7。2, 含有0.25 毫克/毫升 RNAse 溶液, 1 小时在50摄氏度或隔夜在37°c 在热块或水浴。</li>
	<li>添加50µL 蛋白酶 K 溶液 (20 毫克/毫升悬浮10毫米三 pH 7.5, 2 毫米 CaCl2, 50% 重到容量甘油) 和孵育 1 h 在50°c。</li>
	<li>自旋下细胞 (1.4万 x g, 4 °c), 并用重悬细胞在1毫升50毫米柠檬酸钠, pH 值 7.2, 旋转下来 (1.4万 x g, 4 °c), 吸出上清与真空, 并用重悬在1毫升1µM 绿色核酸菌株悬浮在50毫米枸橼酸钠, pH 值 7.2, 在黑暗中孵育1小时室温, 油脂实验 2x, 每2秒 (输出功率2瓦)。</li>
</ol>2. 细胞分类
<ol><li>使用细胞分拣器, 根据 DNA 含量将细胞分类为 G1、S、"早期 G2" 和 "晚期 G2", 从每个细胞周期阶段收集至少160万个单倍体细胞, 如图 1 (参见讨论点 (3))。</li>
	<li>将细胞转移到离心管, 在 1.4万 x g 离心4摄氏度时, 将细胞旋转20分钟, 并吸进上清, 真空 (颗粒可无限期贮存在-20 °c 处; 参见讨论点 (4))。</li>
</ol>3. DNA 提取和测序库的编制
注: 以下步骤是基于 "协议 I" 在酵母基因组 DNA 提取套件 (见材料表)。
<ol><li>添加120µL 的 "消化缓冲", 一个专有的缓冲, 允许酵母溶解酶消化细胞壁, 5 µL 酵母裂解酶, 并用重悬涡流, 孵化37°c 40-60 分钟。</li>
	<li>添加120µL 的 "裂解缓冲", 一个专有的缓冲, 其中包含洗涤剂, 和漩涡硬的10二十年代。</li>
	<li>添加250µL 氯仿-混合彻底1分钟。</li>
	<li>在离心中以最大速度旋转2分钟。</li>
	<li>将上清液载入 DNA 结合柱上, 离心机以最大速度在离心1分钟。</li>
	<li>添加300µL "DNA 洗涤缓冲器", 一个专有的缓冲, 其中含有乙醇, 和离心机1分钟的最大速度在一个离心。丢弃流量, 添加300µL 的 DNA 洗涤缓冲液, 重复洗涤过程。</li>
	<li>将旋转柱转移到新鲜的离心管, 添加60µL (不 TE)-等待 1-3 分钟, 然后离心机十年代洗脱的 DNA。</li>
	<li>测量浓度通过添加5µL 的 DNA 到195µL 的 dsDNA 高灵敏度试剂已稀释 1:200 dsDNA 高灵敏度缓冲, 然后测量荧光荧光计, 使用10µL 的提供标准校准;预计10和50的 DNA 总产量。</li>
	<li>油脂实验 (峰值事件功率 450, 值班系数 30%, 周期每突发 200, 治疗时间六十年代, 水位 6), 以打破 DNA 成 250-350 bp 碎片。</li>
	<li>使用 dna 样本准备套件和序列 (至少 1000万 50 bp 单端读取) 在快速模式下的 dna 测序仪上准备一个库 (参见讨论说明 (5))。</li>
</ol>4. 对序列数据的分析和复制配置文件的生成
<ol><li>使用 Gsnap12将序列与酿酒酵母sacCer3 基因组对齐 (请参阅讨论说明 (6))。</li>
	<li>使用 Bedtools "genomeCoverageBed" 软件13确定每基对读取深度。</li>
	<li>删除读深度中的 artefactual 峰值 (如果存在) (请参见讨论说明 (7))。</li>
	<li>用中线在 20 kb 滑动窗口中使用 "runMean" 函数在 R 包 "caTools" 中, 通过染色体平滑读取深度 (参见讨论说明 (8))。</li>
	<li>将 S 阶段、早期 G2 和后期 G2 的读取深度绘制为完全复制的读取深度的百分比 (请参见讨论说明 (9))。</li>
</ol>

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作者没有什么可透露的。

虽然这项技术是稳健和相对直接的, 但应特别注意以下方面:
(1) 我们建议, 在达到对数阶段之前, 培养至少12小时, 因为在接种后达到所需密度仅为4小时时, 细胞周期分布的差异明显。我们的假设是, 一个已经达到相对稳定的平衡的细胞周期分布比分布在一个饱和的文化最近转移到新鲜的媒介, 更好地代表一个 "真正的" 日志阶段分布。
(2) 通过将100% 乙醇直接添加到酵母培养物中, 而不是在固定前将细胞向下旋转, 以使乙醇的最终浓度为70%。细胞可以生长在合成或丰富 (YEPD) 培养基中。
(3) 通过绘制细胞数作为 530 nm 发射面积的函数, 对细胞周期阶段进行可视化排序。我们发现, G1 和 s 和 G2 之间的拐点是描述 s 相位的有力地标, 我们利用 G2 最大值作为边界来分离早、晚 G2。我们使用 "早期 G2" 和 "晚 G2" 这一术语的清晰度和简洁性, 也许以牺牲准确性为代价, 即细胞在技术上处于 S 阶段, 直到 DNA 复制完成为止。虽然 G2-seq 的目标是确定非常晚复制的网站, 预计将揭示在后期 G2 分数, 我们收集 S 阶段和早期 G2 细胞, 以跟踪复制通过所有阶段的细胞周期。
(4) 在分拣后迅速剥离细胞是至关重要的。不要让细胞在旋转之前过夜。我们有问题恢复细胞的离心, 如果他们已经储存在4摄氏度, 表明他们变得脆弱后, 排序和溶解的时间。
(5) 少量500万读是充足的, 但情节变得不流畅以更低的读数。具有更少读取的数据集可以通过与大于 20 kb 的窗口平滑来容纳, 但我们没有尝试这样做。
(6) 任何广泛使用的对齐软件 (例如、领结14、Novalign (http://www.novocraft.com)、BWA15或 Gsnap12) 都将起作用。
(7) 来自酵母的高通量测序数据显示读深度中偶尔出现的峰值, 这通常反映了 Ty 元素。我们通过将2.5x 中值的读深度替换为在已知的区域之外的读深度 (例如, rDNA), 这些范围大于2.5x 中值, 从而消除了这些。rDNA 和染色体的末端被排除, 因为他们知道包含重复的元素。使用 R 语言的此 "despiking" 示例如下:
# 创建一个名为 "读取" 的数据框, 其中包含数据: 人权 <-代表 ("英联邦倡导", 10) pos <-序列 (1, 10) rd <-c (3, 4, 6, 5, 88, 2, 9, 10, 900, 1) 读取 <-数据框 (' 染色体 ' = 人权中心, "位置" = pos, "read_depth" = rd) # "despike" 读取深度: 读 [, ' despiked '] <-ifelse (读 [, 3] > (2.5 * 中间 (读 [, 3])), (2.5 * 中间 (读 [, 3])), 读 [, 3])
"上限" 或 "despiking" 也可以通过排除映射到多个位置的读取来实现, 但这将消除映射到两个位置的读取。当使用"酵母" 时, 映射到多个位置但仍提供有价值信息的读取实例并不少见, 因为它的基因组源于祖先复制16。
(8) 在 r 包 "动物园" (https://cran.r-project.org/web/packages/zoo/index.html) 和 r 包 "caTools" (https://cran.r-project.org/web/packages/caTools/index.html) 中的 "runmean" 函数中, 我们获得了与 "rollmedian" 函数相似的结果。
(9) 我们尝试了许多方法来规范化读深度, 所有这些都给出了类似的结果。我们偏爱的方法是基于这样的假设, 即至少一些基因组区域在我们的 S 相样本中完全复制。我们确定了读取深度, 表示完全复制的中位读取深度在我们的数据集中在对应于12最早的发射高度信心 ("信心" 评分 > = 7) 的网站的起源在公开可用的数据集。(http://cerevisiae.oridb.org/data_output.php？main=sc_ori_studies & table=Raghu2001_ori & ext_format = & 格式 = 制表符)。对于大多数应用程序, 为规范化而采取的方法并不重要, 而且有许多合理的选项, 其中最简单的就是规范化读取计数总计。然而, 值得注意的是, 如果样本之间重复序列的数量存在很大差异, 则规范化到读取计数总计可能会产生误导。例如, 当比较两个 rDNA 阵列不同于几倍的菌株时, 规范化到总读计数可以使应变基因组的某些区域与较大的 rDNA 阵列 artefactually 比应变更晚地复制数组.
总之, G2-seq 表示复制分析的现有技术的逻辑扩展。与其他测序和微阵列技术一样, G2-seq 具有超过2D 凝胶分析的基因组覆盖范围和缺乏对复制起源位置的知识需求。后者在哺乳动物细胞中尤为重要, 与萌芽的酵母不同, 复制的起源并不局限于特定的序列。另一方面, 2D 凝胶提供了一个分辨率的分子中间体的 DNA 复制完全无法达到的 G2-seq. 将 G2-seq 扩展到其他有机体, 其细胞可以根据 DNA 含量排序, 应该是相对直接的,然而, 高真核生物基因组的高度重复性使得短读序列的排列更具挑战性。在这方面, 新出现的测序技术可能会很有用, 特别是因为 G2-seq 应该相对较长的错误率更高, 因为它可以与更大的读取17相关联。在我们的经验中, 最有可能导致问题的技术问题是让细胞在被分类和 DNA 分离之前就可以坐着。这些细胞看起来特别脆弱, 并且随着时间的推移溶解, DNA 应该在最多一两个小时的排序中被隔离。这项技术的未来方向包括将 S 和 G2 相分成越来越多的分数, 以获得更高分辨率的基因组复制的动力学, 从早期开始到晚期完成。

真核基因组复制是在多个离散站点上启动的, 称为复制的起源, 复制分叉在两个方向上进行 (在 Fragkos et、20151中进行了复查)。起源在他们的时间和射击的效率不同, 并且开发了几个技术监测复制起源活动并且阐明这变化的起因。个体起源的活动可以从单链 DNA2的水平推断出来, 它形成在活跃起源附近, 或者通过使用2D 凝胶电泳监测特定的复制中间体3, 两者都可以检测到放射性探针。这两种技术在酵母中比在哺乳动物细胞中更容易应用, 因为起源仅限于前者的特定已知序列。随着微阵列的出现, 可以评估全球发射的起源。这首先是通过标记 DNA 与重同位素, 将细胞从 G1 块释放到含有轻同位素的介质中, 然后在基因组4中监测重光杂交 dna 的形成。高通量测序的引入允许类似的全基因组监测源活动, 而不需要昂贵的同位素标记。根据 dna 含量及其 dna 进行深度测序, 对细胞进行排列。由于序列覆盖率从1x 到2x 在 s 阶段过程中进行, 因此可以通过比较 s 阶段中单元格的读深度与 G1 或 G25、6中的内容来评估相对复制计时。这些技术, 特别是适用于酵母, 导致了更深的理解如何 dna 序列, 染色质结构, 和 dna 复制蛋白调节起源时间和效率。
在细胞增殖过程中, 基因信息的忠实传递不仅需要成功地启动 DNA 复制, 这在起源上发生, 而且复制的成功完成是复制叉相遇的地方。与开始复制一样, 复制完成的时间在整个基因组中都不同, 某些区域甚至在细胞周期的晚期仍未复制。这些区域可能特别远离主动复制的起源, 也可能含有阻碍 DNA 聚合酶的序列或染色质结构。晚期复制区域可以表现为脆弱的站点, 这与染色体断裂和更高的突变率有关, 并且已经牵连到癌症和老化的7,8,9。然而, 尽管正确完成 DNA 复制在维持基因组稳定性方面的重要性, 但我们对其发生地点和方式的理解远远落后于复制启动。虽然研究了晚期复制与疾病有关的个别基因, 例如, qPCR10, 但目前还缺乏旨在阐明晚期复制的地点和根本原因的全球研究。在这里, 我们描述了一种技术, 我们称之为 "G2 序列", 我们结合流式细胞术与高通量测序, 以揭示完成的基因组复制在酵母11。随着小的变化, 这个协议可以适应任何细胞, 可以根据 DNA 的内容流排序。

<table width="722">
	<tbody>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">YeaStar Genomic DNA kit</td>
			<td style="width:135px;">Genesee Scientific</td>
			<td style="width:119px;">11-323</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">1 &#181;M SYTOX Green</td>
			<td style="width:135px;">ThermoFisher</td>
			<td style="width:119px;">57020</td>
			<td>resuspend in 50 mM sodium citrate, pH 7.2</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">50 mM sodium citrate, pH 7.2</td>
			<td style="width:135px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="147">
			<td height="147" style="width:301px;height:147px;">RNase solution (0.25 mg / mL)</td>
			<td style="width:135px;">Sigma</td>
			<td style="width:119px;">R6513</td>
			<td style="width:167px;">0.25 mg / mL RNaseA resuspended in 50 mM sodium citrate, pH 7.2, boil RNase solution for 10 minutes before the first use only, and from then on store at -20&#176;</td>
		</tr>
		<tr height="42">
			<td height="42" style="width:301px;height:42px;">proteinase K solution (20 mg / mL)</td>
			<td style="width:135px;">ThermoFisher / Invitrogen</td>
			<td style="width:119px;">25530-015</td>
			<td>resuspend in 10 mM Tris, pH 7.5, 2 mM CaCl2, 50% glycerol, store at -20&#176;C</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Model 50 Sonic Dismembrator</td>
			<td style="width:135px;">Fisher Scientific</td>
			<td>FB50A220</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">BD Biosciences FACSAria II</td>
			<td style="width:135px;">BD Biosciences</td>
			<td>644832</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Zymo-spin III columns</td>
			<td style="width:135px;">Zymo Research</td>
			<td style="width:119px;">C1005</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Qubit dsDNA HS Assay Kit</td>
			<td style="width:135px;">ThermoFisher</td>
			<td style="width:119px;">Q32851</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Qubit 3.0 Fluorometer</td>
			<td style="width:135px;">ThermoFisher</td>
			<td style="width:119px;">Q33216</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Covaris Model LE220 Focused-Ultrasonicator</td>
			<td style="width:135px;">Covaris</td>
			<td style="width:119px;">500219</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Illumina TruSeq DNA LT Sample Prep Kit</td>
			<td style="width:135px;">Illumina</td>
			<td>15026486</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Illumina HiSeq 2500 instrument</td>
			<td style="width:135px;">Illumina</td>
			<td>SY&#8211;401&#8211;2501&#160;</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="width:301px;height:63px;">gsnap alignment software</td>
			<td style="width:135px;">open source software / Genentech</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">http://research-pub.gene.com/gmap</td>
		</tr>
	</tbody>
</table>

g2-seq: a high throughput sequencing-based technique for identifying late replicating regions of the genome

许多技术已经开发, 以跟踪 DNA 复制的进展, 通过 S 阶段的细胞周期。这些技术大多用于阐明基因组复制的地点和时间, 而不是完成。然而, 至关重要的是, 我们了解基因组中最后一个完成复制的区域, 因为这些区域的染色体断裂和突变水平较高, 并与疾病和衰老有关。在这里, 我们描述了我们如何扩展了一个技术, 已经被用来监测复制启动, 而不是确定这些区域的基因组最后完成复制。这种方法是基于流式细胞术和高通量测序相结合的。虽然本报告着重于酵母的应用, 该方法可以与任何细胞, 可以排序在流式仪根据 DNA 的内容。

我们已经使用上面描述的程序来识别在萌芽的酵母中晚期复制的地点。使用已知的晚期复制区域对人工染色体进行测试, 证明该方法准确可靠。我们的结果还表明, 及时完成复制的生物学重要性表明, 7 号染色体上的一个晚期复制区域在我们的 G2-seq 结果的基础上被识别为晚复制, 大约损失了三倍, 比可比较的控制区域11更频繁。
图 2中显示了带有 G2-seq 的结果的特定示例。我们假设基因组的区域在缺乏蛋白质乙酰称为 Sir2 的细胞中复制得特别晚。图 2A显示了用于野生类型 (蓝色) 和sir2 (red) 的数据分析的进展情况。原始数据 (上一行) 包含较大的峰值, 其中大部分是由于 Ty 元素的存在。这些峰值被取消上限读深度在2.5x 的中间读深度为每个样品 (中间行)。然后用 20 kb 滑动窗口 (下一行) 平滑 despiked 数据。最后, 数据被规范化并绘制为与 G1 中的水平的比值。sir2突变体中出现的典型后期复制区域在图 2C中突出显示。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56286/56286fig1.jpg"> 图 1.流式细胞仪显示细胞周期分数使用;所有门的外部界限标记。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56286/56286fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56286/56286fig2.jpg"> 图 2.(A-B)用于野生类型 (A) 和sir2 (B) 的原始数据 (顶行)、despiked 数据 (中间行) 和平滑数据 (下一行) 的数据处理进度。(C) S 阶段、早期 G2 和晚期 G2-to G1 读深度的比率。在蓝色和sir2中为红色的野生类型。右上角的高亮区域显示特定于sir2突变体的后期复制区域。刻度表示完成 (2N) 复制的分数;一个完全未复制的单元格将出现在 0.5, 一个完全复制的单元格在1。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56286/56286fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome at JoVE.com

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

G2-seq: 一种基于高通量测序技术的基因组晚期复制区域识别方法

我们描述了一种将流式细胞术和高通量测序相结合的技术来识别基因组的晚期复制区域。

Numerous techniques have been developed to follow the progress of DNA replication through the S phase of the cell cycle. Most of these techniques have ...

g2-seq-high-throughput-sequencing-based-technique-for-identifying

Nanyang Technological University

Research

JoVE Journal

Genetics

5.7K 次观看.  Fred Hutchinson Cancer Research Center. 我们描述了一种将流式细胞术和高通量测序相结合的技术来识别基因组的晚期复制区域。

视频: G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

A Robotic Platform for High-throughput Protoplast Isolation and Transformation

Over the last decade there has been a resurgence in the use of plant protoplasts that range from model species to crop species, for analysis of signal transduction pathways, transcriptional regulatory networks, gene expression, genome-editing, and gene-silencing. Furthermore, significant progress has been made in the regeneration of plants from protoplasts, which has generated even more interest in the use of these systems for plant genomics. In this work, a protocol has been developed for automation of protoplast isolation and transformation from a &#39;Bright Yellow&#39; 2 (BY-2) tobacco suspension culture using a robotic platform. The transformation procedures were validated using an orange fluorescent protein (OFP) reporter gene (pporRFP) under the control of the Cauliflower mosaic virus 35S promoter (35S). OFP expression in protoplasts was confirmed by epifluorescence microscopy. Analyses also included protoplast production efficiency methods using propidium iodide. Finally, low-cost food-grade enzymes were used for the protoplast isolation procedure, circumventing the need for lab-grade enzymes that are cost-prohibitive in high-throughput automated protoplast isolation and analysis. Based on the protocol developed in this work, the complete procedure from protoplast isolation to transformation can be conducted in under 4 hr, without any input from the operator. While the protocol developed in this work was validated with the BY-2 cell culture, the procedures and methods should be translatable to any plant suspension culture/protoplast system, which should enable acceleration of crop genomics research.

A high-throughput, automated, tobacco protoplast production and transformation methodology is described. The robotic system enables massively parallel gene expression and discovery in the model BY-2 system that should be translatable to non-model crops.

机器人平台的高通量原生质体分离和转型

Over the last decade there has been a resurgence in the use of plant protoplasts that range from model species to crop species, for analysis of signal ...

科研

遗传学

Mapping RNA-RNA Interactions Globally Using Biotinylated Psoralen

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

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

使用生物素化补骨脂素全球定位RNA-RNA相互作用

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

Retroviral Scanning: Mapping MLV Integration Sites to Define Cell-specific Regulatory Regions

Moloney murine leukemia (MLV) virus-based retroviral vectors integrate predominantly in acetylated enhancers and promoters. For this reason, mLV integration sites can be used as functional markers of active regulatory elements. Here, we present a retroviral scanning tool, which allows the genome-wide identification of cell-specific enhancers and promoters. Briefly, the target cell population is transduced with an mLV-derived vector and genomic DNA is digested with a frequently cutting restriction enzyme. After ligation of genomic fragments with a compatible DNA linker, linker-mediated polymerase chain reaction (LM-PCR) allows the amplification of the virus-host genome junctions. Massive sequencing of the amplicons is used to define the mLV integration profile genome-wide. Finally, clusters of recurrent integrations are defined to identify cell-specific regulatory regions, responsible for the activation of cell-type specific transcriptional programs.
The retroviral scanning tool allows the genome-wide identification of cell-specific promoters and enhancers in prospectively isolated target cell populations. Notably, retroviral scanning represents an instrumental technique for the retrospective identification of rare populations (e.g. somatic stem cells) that lack robust markers for prospective isolation.

Here, we describe a protocol for genome-wide mapping of the integration sites of Moloney murine leukemia virus-based retroviral vectors in human cells.

逆转录病毒扫描:映射MLV集成站点以定义细胞特异性监管区域

Moloney murine leukemia (MLV) virus-based retroviral vectors integrate predominantly in acetylated enhancers and promoters. For this reason, mLV ...

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution based analysis methodology (nucleosome density ChIP-seq; ndChIP-seq) that enables the generation of combined measurements of micrococcal nuclease (MNase) accessibility with histone modification genome-wide. Nucleosome position and local density, and the posttranslational modification of their histone subunits, act in concert to regulate local transcription states. Combinatorial measurements of nucleosome accessibility with histone modification generated by ndChIP-seq allows for the simultaneous interrogation of these features. The ndChIP-seq methodology is applicable to small numbers of primary cells inaccessible to cross-linking based ChIP-seq protocols. Taken together, ndChIP-seq enables the measurement of histone modification in combination with local nucleosome density to obtain new insights into shared mechanisms that regulate RNA transcription within rare primary cell populations.

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) methodology for the generation of sequence datasets suitable for a nucleosome density ChIP-seq analytical framework integrating micrococcal nuclease (MNase) accessibility with histone modification measurements.

核密度分析的天然染色质沉淀测序文库的生成

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

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

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

植物标本标本的鲁棒 DNA 分离与高通量测序库建设

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

Embryo Microinjection and Transplantation Technique for Nasonia vitripennis Genome Manipulation

The jewel wasp Nasonia vitripennis has emerged as an effective model system for the study of processes including sex determination, haplo-diploid sex determination, venom synthesis, and host-symbiont interactions, among others. A major limitation of working with this organism is the lack of effective protocols to perform directed genome modifications. An important part of genome modification is delivery of editing reagents, including CRISPR/Cas9 molecules, into embryos through microinjection. While microinjection is well established in many model organisms, this technique is particularly challenging to perform in N. vitripennis primarily due to its small embryo size, and the fact that embryonic development occurs entirely within a parasitized blowfly pupa. The following procedure overcomes these significant challenges while demonstrating a streamlined, visual procedure for effectively removing wasp embryos from parasitized host pupae, microinjecting them, and carefully transplanting them back into the host for continuation and completion of development. This protocol will strongly enhance the capability of research groups to perform advanced genome modifications in this organism.

Embryo Microinjection and Transplantation Technique for Nasonia vitripennis Genome Manipulation

Microinjection of Nasonia vitripennis embryos is an essential method for generating heritable genome modifications. Described here is a detailed procedure for microinjection and transplantation of Nasonia vitripennis embryos, which will greatly facilitate future genome manipulation in this organism.

金小蜂金小蜂基因组操作的胚胎显微注射和移植技术

The jewel wasp Nasonia vitripennis has emerged as an effective model system for the study of processes including sex determination, haplo-diploid sex ...

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our entire society's ability to treat systemic infections. In the United States alone, antibiotic-resistant infections kill approximately 23,000 people a year and cost around 20 billion USD in additional healthcare. One approach to combat antimicrobial resistance is combination therapy, which is particularly useful in the critical early stage of infection, before the infecting organism and its drug resistance profile have been identified. Many antimicrobial treatments use combination therapies. However, most of these combinations are additive, meaning that the combined efficacy is the same as the sum of the individual antibiotic efficacy. Some combination therapies are synergistic: the combined efficacy is much greater than additive. Synergistic combinations are particularly useful because they can inhibit the growth of antimicrobial drug resistant strains. However, these combinations are rare and difficult to identify. This is due to the sheer number of molecules needed to be tested in a pairwise manner: a library of 1,000 molecules has 1 million potential combinations. Thus, efforts have been made to predict molecules for synergy. This article describes our high-throughput method for predicting synergistic small molecule pairs known as the Overlap2 Method (O2M). O2M uses patterns from chemical-genetic datasets to identify mutants that are hypersensitive to each molecule in a synergistic pair but not to other molecules. The Brown lab exploits this growth difference by performing a high-throughput screen for molecules that inhibit the growth of mutant but not wild-type cells. The lab's work previously identified molecules that synergize with the antibiotic trimethoprim and the antifungal drug fluconazole using this strategy. Here, the authors present a method to screen for novel synergistic combinations, which can be altered for multiple microorganisms.

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Synergistic drug combinations are difficult and time-consuming to identify empirically. Here, we describe a method for identifying and validating synergistic small molecules.

通过重叠2方法高通量识别协同药物组合

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our ...

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.

DNA regulatory elements, such as enhancers, control gene expression by physically contacting target gene promoters, often through long-range chromosomal interactions spanning large genomic distances. Promoter Capture Hi-C (PCHi-C) identifies significant interactions between promoters and distal regions, enabling the assignment of potential regulatory sequences to their target genes.

启动子捕获高分辨率, 全基因组的启动子交互分析

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the ...

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

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

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

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

利用下一代序列染色体构象捕获 (4 c 序列) 的高通量识别基因调控数列

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

CRISPR-mediated Genome Editing of the Human Fungal Pathogen Candida albicans

This method describes the efficient CRISPR mediated genome editing of the diploid human fungal pathogen Candida albicans. CRISPR-mediated genome editing in C. albicans requires Cas9, guide RNA, and repair template. A plasmid expressing a yeast codon optimized Cas9 (CaCas9) has been generated. Guide sequences directly upstream from a PAM site (NGG) are cloned into the Cas9 expression vector. A repair template is then made by primer extension in vitro. Cotransformation of the repair template and vector into C. albicans leads to genome editing. Depending on the repair template used, the investigator can introduce nucleotide changes, insertions, or deletions. As C. albicans is a diploid, mutations are made in both alleles of a gene, provided that the A and B alleles do not harbor SNPs that interfere with guide targeting or repair template incorporation. Multimember gene families can be edited in parallel if suitable conserved sequences exist in all family members. The C. albicans CRISPR system described is flanked by FRT sites and encodes flippase. Upon induction of flippase, the antibiotic marker (CaCas9) and guide RNA are removed from the genome. This allows the investigator to perform subsequent edits to the genome. C. albicans CRISPR is a powerful fungal genetic engineering tool, and minor alterations to the described protocols permit the modification of other fungal species including C. glabrata, N. castellii, and S. cerevisiae.

CRISPR-mediated Genome Editing of the Human Fungal Pathogen Candida albicans

Efficient genome engineering of Candida albicans is critical to understanding the pathogenesis and development of therapeutics. Here, we described a protocol to quickly and accurately edit the C. albicans genome using CRISPR. The protocol allows investigators to introduce a wide variety of genetic modifications including point mutations, insertions, and deletions.

crispr 介导的人类真菌病原体白色念珠菌基因组编辑

This method describes the efficient CRISPR mediated genome editing of the diploid human fungal pathogen Candida albicans. CRISPR-mediated genome editing ...