这项工作得到了生物技术和生物科学研究理事会的支持 [BB/N005759/1 ar]。NRFH 由 Rosetrees 信托基金和 Stoneygate 信托基金 (A1130/M546) 资助。蔡司 Elyra PS 1 显微镜, 处理计算机和软件由 BBSRC BB/L013827/1 (诺丁汉大学补助金多学科超分辨率显微镜设施) 资助

1. 共焦图像的生成 <ol> <li> 在准备对胞嘧啶的修饰形式进行分析时, 按照 Abakir 和 #160 的描述进行免疫组化染色; et al. 34 . </li> <li> 使用显微镜对幻灯片进行成像, 并以 LSM 格式保存文件. 
	注: 在比较样品之间的强度剖面时, 必须在整个影像过程中保持用于激光功率和增益的值, 以便在图像分析阶段进行直接比较. </li>
</ol> 2。2.5D 强度图的生成 <ol> <li> 打开软件 ( 如 、禅宗黑) 和选择和 #39; 图像处理和 #39;. </li>
	<li> 转到 "文件" 菜单并选择 "打开"。选择需要处理的图像. </li>
	<li> 单击并 #39; 显示所有和 #39; 在图像下方, 使所有图形控件可见。在屏幕的下半部分有三标签;#39;D imensions 和 #39; #39;D isplay 和 #39; #39; 图形和 #39; 选择 #39; 图形和 #39; 选项卡. 
	<ol> <li> 选择 #39; 矩形和 #39; 工具选择原子核/感兴趣区域. </li>
		<li> 选择和 #39; 剪切区域和 #39; 裁剪图像。这将在单独的选项卡中为裁剪区域生成新图像. </li>
		<li> 转到 "文件" 菜单并选择 "另存为". 为文件命名并将其另存为 LSM 或 CZI 文件. </li>
	</ol> </li> <li> 打开软件 (, 如 , 禅宗蓝色), 并选择和 #39; 禅宗办公桌和 #39;. </li>
	<li> 通过选择文件并单击 "文件" 菜单, 然后选择 "发送到禅宗 2012-蓝色版", 将剪裁的图像从禅宗黑色发送到禅宗蓝色。裁剪后的图像将在相关程序中打开. 
	注意: 由于禅宗黑色2012中的2.5D 强度绘图功能不同时显示多个通道图像, 因此会传输图像文件. </li>
	<li> 在图像的左侧, 选择标签标签和 #39; 2.5D 和 #39, 这样可以在2.5D 中实现图像的可视化。单击并 #39; 显示所有和 #39; 使所有图形控件可见. </li>
	<li> 使用位于图像左侧和下方的四灰色条形图来更改可视化设置. 
	注: 左手杆, 屏幕顶部 = 变焦。左手杆, 屏幕的底部 = 在轴上打开图像。屏幕底部, 左手杆 = 图像的旋转。屏幕底部, 右手栏 = 展开和收缩缩放条形图. </li>
	<li> 确保选择的渲染模式是曲面, 因为这给出了单个峰值的最佳可视化效果. </li>
	<li> 通过更改百分比来更改网格距离, 百分比越低, 每个单个峰值的定义就越多. </li>
	<li> 保存2.5D 图像, 首先, 通过单击2.5D 绘图下的灰色箭头 (旁边的 #39; 显示 "全部" 和 #39;), 这将隐藏图形选项卡, 允许图像扩展以填充碎石要保存2.5D 绘图, 请按 #39;P rtsc 和 #39; 键盘上的键。这将捕获显示的屏幕截图。将屏幕截图粘贴到 Microsoft 画图中, 并在保存之前裁剪图像. </li>
</ol> 3。强度分析 <ol> <li> 打开软件 (如 , 禅黑) 并选择图像处理. </li>
	<li> 转到 "文件" 菜单并选择 "打开"。选择需要处理的图像. </li>
	<li> 当图像显示在屏幕上时, 在图像的左侧选择标签标签和 #39;P 简介和 #39;. </li>
	<li> 在屏幕的下半部分选择 (滴答) 和 #39; 显示所有和 #39; 选项卡。这将启用对所有格式设置选项的访问. </li>
	<li> 在屏幕的下半部分有三选项卡; #39;D imensions 和 #39;, #39;D isplay 和 #39; #39;P 简介和 #39; 选择和 #39;P 简介和 #39; 选择 (滴答) #39; 表和 #39; 框。选择 #39; 箭头和 #39; 按钮. </li>
	<li> 在图像上使用鼠标选择起点并将鼠标拖动到连续的单元格数上。释放鼠标以产生沿直线上的单元格的强度图;此外, 该表还将按每个波长的像素线的强度测量数据进行填充. 
	注: 该表将提供距离 (和 #181; m), 其中像素强度是读取红色, 绿色和蓝色荧光. </li>
	<li> 若要导出此数据, 请右键单击表, 选择和 #39; 保存表和 #8230; #39; 并将其保存为 .txt 文件的适当位置 </li>
	<li> 保存所选强度配置文件图像选择 "文件" 菜单并选择和 #39; 导出和 #8230; #39;。在弹出窗口中选择和 #39; 标记的图像文件 (格式) 和 #39; 和 #39; 图像窗口的内容-单窗格 (数据) 和 #39; 依次单击和 #39; 选择文件名和保存和 #8230; #39; 选择合适的位置, 然后单击并 #39; 保存和 #39;. </li>
	<li> 根据视场和要分析的配置文件数量, 对每个单独的强度配置文件重复该过程. </li>
	<li> 导入强度配置文件保存的数据 (参见 3.7) 并在电子表格中进行分析, 然后进行统计分析. </li>
</ol> 4。协同本地化分析 <ol> <li> 打开软件并选择和 #39; 图像处理和 #39;. </li>
	<li> 转到 "文件" 菜单并选择 "打开"。选择需要处理的图像. </li>
	<li> 当图像显示在屏幕上时, 在图像的左侧选择标签标签和 #39; Coloc 和 #39;. </li>
	<li> 在屏幕的下半部分选择 (滴答) 和 #39; 显示所有和 #39; 选项卡。这将启用对所有格式设置选项的访问. </li>
	<li> 在屏幕的下半部分有四选项卡; #39;D imensions 和 #39; #39;D isplay 和 #39; #39; 图形和 #39; #39; 定位和 #39; 选择和 #39; 定位和 #39; 和 #39; 表和 #39; 和 #39; 图像和 #39;... 
	<ol> <li> 选择此选项卡顶部的第三个图标 (当鼠标悬停在该工具上时, 将显示关闭的贝塞尔文本), 然后使用此工具包围单个原子核, 此核的值将随后出现在表中. 
		注: 对于每个被包围的原子核, 散布图是为红色和绿色荧光, 这是在屏幕上的左手面板可视化产生。然后移动轴, 以便根据阈值将单元格移出。由于在图像中手动选择了感兴趣的原子核, 因此不需要调整在零以上的浇口阈值。在核周长范围内观测到的所有像素强度值都被视为正信号. </li>
	</ol> </li> <li> 重复此过程, 方法是选择选项卡中的第三个图标并包围后续的原子核, 直到数据集完成为止. </li>
	<li> 若要导出此数据, 请右键单击该表, 选择 "保存表" 并保存到适当的位置. </li>
	<li> 要保存定位图像, 请选择 "文件" 菜单并选择和 #39; 导出和 #8230; #39; 然后选择;标记的图像文件 (格式) 和 #39; 图像窗口和 #8211 的内容; 单平面 (数据) 和 #39; 依次单击和 #39; 选择文件名和保存和 #8230; #39;, 选择合适的位置, 然后单击并 #39; 保存和 #39;. </li>
	<li> 在电子表格中绘制定位数据, 然后进行统计分析. </li>
</ol>

<ol>
	<li>Bird, A. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+restriction+enzymes+to+study+eukaryotic+DNA+methylation:+II.+The+symmetry+of+methylated+sites+supports+semi-conservative+copying+of+the+methylation+pattern.">Use of restriction enzymes to study eukaryotic DNA methylation: II. The symmetry of methylated sites supports semi-conservative copying of the methylation pattern.</a> J Mol Biol. 118 (1), 49-60 (1978).</li><li>Youssoufian, H., 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=Recurrent+mutations+in+haemophilia+A+give+evidence+for+CpG+mutation+hotspots.">Recurrent mutations in haemophilia A give evidence for CpG mutation hotspots.</a> Nature. 324 (6095), 380-382 (1985).</li><li>Holliday, R., Pugh, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+modification+mechanisms+and+gene+activity+during+development.">DNA modification mechanisms and gene activity during development.</a> Cold Spring Harbor Monograph Series. 32, 639-645 (1996).</li><li>Christman, J. K., Price, P., Pedrinan, L., Acs, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Correlation+between+hypomethylation+of+DNA+and+expression+of+globin+genes+in+Friend+erythroleukemia+cells.">Correlation between hypomethylation of DNA and expression of globin genes in Friend erythroleukemia cells.</a> European J Biochem. 81 (1), 53-61 (1977).</li><li>Bird, A. P., Southern, E. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+restriction+enzymes+to+study+eukaryotic+DNA+methylation:+I.+The+methylation+pattern+in+ribosomal+DNA+from+Xenopus+laevis.">Use of restriction enzymes to study eukaryotic DNA methylation: I. The methylation pattern in ribosomal DNA from Xenopus laevis.</a> J Mol Biol. 118 (1), 27-47 (1978).</li><li>Kim, G. D., Ni, J., Kelesoglu, N., Roberts, R. J., Pradhan, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Co-operation+and+communication+between+the+human+maintenance+and+de+novo+DNA+(cytosine-5)+methyltransferases.">Co-operation and communication between the human maintenance and de novo DNA (cytosine-5) methyltransferases.</a> EMBO J. 21 (15), 4183-4195 (2002).</li><li>Reik, W., Kelsey, G., Walter, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dissecting+de+novo+methylation.">Dissecting de novo methylation.</a> Nature genetics. 23 (4), 380-382 (1999).</li><li>Okano, M., Bell, D. W., Haber, D. A., Li, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+methyltransferases+Dnmt3a+and+Dnmt3b+are+essential+for+de+novo+methylation+and+mammalian+development.">DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development.</a> Cell. 99 (3), 247-257 (1999).</li><li>Eckhardt, F., 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=DNA+methylation+profiling+of+human+chromosomes+6,+20+and+22.">DNA methylation profiling of human chromosomes 6, 20 and 22.</a> Nat Genet. 38 (12), 1378-1385 (2006).</li><li>Lees-Murdock, D. J., Lau, H. -. T., Castrillon, D. H., De Felici, M., Walsh, C. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+methyltransferase+loading,+but+not+de+novo+methylation,+is+an+oocyte-autonomous+process+stimulated+by+SCF+signalling.">DNA methyltransferase loading, but not de novo methylation, is an oocyte-autonomous process stimulated by SCF signalling.</a> Dev Biol. 321 (1), 238-250 (2008).</li><li>Leonhardt, H., Page, A. W., Weier, H. -. U., Bestor, T. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+targeting+sequence+directs+DNA+methyltransferase+to+sites+of+DNA+replication+in+mammalian+nuclei.">A targeting sequence directs DNA methyltransferase to sites of DNA replication in mammalian nuclei.</a> Cell. 71 (5), 865-873 (1992).</li><li>Jones, P. A., Taylor, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cellular+differentiation,+cytidine+analogs+and+DNA+methylation.">Cellular differentiation, cytidine analogs and DNA methylation.</a> Cell. 20 (1), 85-93 (1980).</li><li>J&#228;hner, D., Jaenisch, 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> DNA methylation: DNA Methylation in Early mammalian Development. , 189-219 (1984).</li><li>Chalitchagorn, K., 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=Distinctive+pattern+of+LINE-1+methylation+level+in+normal+tissues+and+the+association+with+carcinogenesis.">Distinctive pattern of LINE-1 methylation level in normal tissues and the association with carcinogenesis.</a> Oncogene. 23 (54), 8841-8846 (2004).</li><li>Fatemi, M., Hermann, A., Gowher, H., Jeltsch, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dnmt3a+and+Dnmt1+functionally+cooperate+during+de+novo+methylation+of+DNA.">Dnmt3a and Dnmt1 functionally cooperate during de novo methylation of DNA.</a> Eur J Biochem. 269 (20), 4981-4984 (2002).</li><li>Gruenbaum, Y., Cedar, H., Razin, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Substrate+and+sequence+specificity+of+a+eukaryotic+DNA+methylase.">Substrate and sequence specificity of a eukaryotic DNA methylase.</a> Nature. 295 (5850), 620-622 (1982).</li><li>Dean, W., Santos, F., Reik, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Epigenetic+reprogramming+in+early+mammalian+development+and+following+somatic+nuclear+transfer.">Epigenetic reprogramming in early mammalian development and following somatic nuclear transfer.</a> Seminars in cell &amp; developmental biology (Elsevier). 14 (1), 93-100 (2003).</li><li>Wu, S. C., Zhang, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Active+DNA+demethylation:+many+roads+lead+to+Rome.">Active DNA demethylation: many roads lead to Rome.</a> Nat Rev Mol Cell Biol. 11 (9), 607-620 (2010).</li><li>Ito, S., 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=Tet+proteins+can+convert+5-methylcytosine+to+5-formylcytosine+and+5-carboxylcytosine.">Tet proteins can convert 5-methylcytosine to 5-formylcytosine and 5-carboxylcytosine.</a> Science. 333 (6047), 1300-1303 (2011).</li><li>Tahiliani, M., 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=Conversion+of+5-methylcytosine+to+5-hydroxymethylcytosine+in+mammalian+DNA+by+MLL+partner+TET1.">Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1.</a> Science. 324 (5929), 930-935 (2009).</li><li>Bachman, M., 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=5-Formylcytosine+can+be+a+stable+DNA+modification+in+mammals.">5-Formylcytosine can be a stable DNA modification in mammals.</a> Nat Chem Biol. 11 (8), 555-557 (2015).</li><li>Bachman, M., 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=5-Hydroxymethylcytosine+is+a+predominantly+stable+DNA+modification.">5-Hydroxymethylcytosine is a predominantly stable DNA modification.</a> Nat Chem. 6 (12), 1049-1055 (2014).</li><li>Lurlaro, M., 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=In+vivo+genome-wide+profiling+reveals+a+tissue-specific+role+for+5-formylcytosine.">In vivo genome-wide profiling reveals a tissue-specific role for 5-formylcytosine.</a> Genome Biol. 17 (1), 141 (2016).</li><li>Tamanaha, E., Guan, S., Marks, K., Saleh, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Distributive+Processing+by+the+Iron+(II)/&#945;-Ketoglutarate-Dependent+Catalytic+Domains+of+the+TET+Enzymes+Is+Consistent+with+Epigenetic+Roles+for+Oxidized+5-Methylcytosine+Bases.">Distributive Processing by the Iron (II)/&#945;-Ketoglutarate-Dependent Catalytic Domains of the TET Enzymes Is Consistent with Epigenetic Roles for Oxidized 5-Methylcytosine Bases.</a> J Am Chem Soc. 138 (30), 9345-9348 (2016).</li><li>He, Y. -. F., 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=Tet-mediated+formation+of+5-carboxylcytosine+and+its+excision+by+TDG+in+mammalian+DNA.">Tet-mediated formation of 5-carboxylcytosine and its excision by TDG in mammalian DNA.</a> Science. 333 (6047), 1303-1307 (2011).</li><li>Herman, J. G., Graff, J. R., My&#246;h&#228;nen, S., Nelkin, B. D., Baylin, S. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methylation-specific+PCR:+a+novel+PCR+assay+for+methylation+status+of+CpG+islands.">Methylation-specific PCR: a novel PCR assay for methylation status of CpG islands.</a> Proc Natl Acad Sci. 93 (18), 9821-9826 (1996).</li><li>Nagae, G., 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=Tissue-specific+demethylation+in+CpG-poor+promoters+during+cellular+differentiation.">Tissue-specific demethylation in CpG-poor promoters during cellular differentiation.</a> Hum Mol Genet. 20 (14), 2710-2721 (2011).</li><li>Ficz, G., 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=Dynamic+regulation+of+5-hydroxymethylcytosine+in+mouse+ES+cells+and+during+differentiation.">Dynamic regulation of 5-hydroxymethylcytosine in mouse ES cells and during differentiation.</a> Nature. 473 (7347), 398-402 (2011).</li><li>Jin, S. -. G., Wu, X., Li, A. X., Pfeifer, G. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genomic+mapping+of+5-hydroxymethylcytosine+in+the+human+brain.">Genomic mapping of 5-hydroxymethylcytosine in the human brain.</a> Nucleic Acids Res. 39 (12), 5015-5024 (2011).</li><li>Liu, J., 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=Abundant+DNA+6mA+methylation+during+early+embryogenesis+of+zebrafish+and+pig.">Abundant DNA 6mA methylation during early embryogenesis of zebrafish and pig.</a> Nat Commun. 7, (2016).</li><li>Wu, T. P., 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=DNA+methylation+on+N6-adenine+in+embryonic+stem+cells.">DNA methylation on N6-adenine in embryonic stem cells.</a> Nature. 532 (7599), 329-333 (2016).</li><li>Kriaucionis, S., Heintz, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+nuclear+DNA+base+5-hydroxymethylcytosine+is+present+in+Purkinje+neurons+and+the+brain.">The nuclear DNA base 5-hydroxymethylcytosine is present in Purkinje neurons and the brain.</a> Science. 324 (5929), 929-930 (2009).</li><li>Globisch, D., 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=Tissue+distribution+of+5-hydroxymethylcytosine+and+search+for+active+demethylation+intermediates.">Tissue distribution of 5-hydroxymethylcytosine and search for active demethylation intermediates.</a> PloS one. 5 (12), e15367 (2010).</li><li>Abakir, A., Wheldon, L. M., Ruzov, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Epigenetic Methods in Neuroscience Research: Immunohistochemical Detection of Oxidized Forms of 5-Methylcytosine in Embryonic and Adult Brain Tissue. , 125-137 (2016).</li><li>Alioui, 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=5-Carboxylcytosine+is+localized+to+euchromatic+regions+in+the+nuclei+of+follicular+cells+in+axolotl+ovary.">5-Carboxylcytosine is localized to euchromatic regions in the nuclei of follicular cells in axolotl ovary.</a> Nucleus. 3 (6), 565-569 (2012).</li><li>Chen, Y., Damayanti, N., Irudayaraj, J., Dunn, K., Zhou, F. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diversity+of+two+forms+of+DNA+methylation+in+the+brain.">Diversity of two forms of DNA methylation in the brain.</a> Front Genet. 5, 46 (2014).</li><li>Dunn, K. W., Kamocka, M. M., McDonald, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+practical+guide+to+evaluating+colocalization+in+biological+microscopy.">A practical guide to evaluating colocalization in biological microscopy.</a> Am J Physiol Cell Physiol. 300 (4), C723-C742 (2011).</li><li>Lachmanovich, E., 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=Co-localization+analysis+of+complex+formation+among+membrane+proteins+by+computerized+fluorescence+microscopy:+application+to+immunofluorescence+co-patching+studies.">Co-localization analysis of complex formation among membrane proteins by computerized fluorescence microscopy: application to immunofluorescence co-patching studies.</a> J Microsc. 212 (Pt 2), 122-131 (2003).</li></ol>

没有潜在的利益冲突的披露。

该协议描述了在细胞核内生成 DNA 修饰的视觉表示的逐步过程。这些技术虽然敏感和有影响力, 但确实有许多限制。
有必要强调的是, 从2.5D 地块产生的数据, 信号强度剖面和定位分析是半定量的性质。在激光扫描共聚焦显微镜上, 由于样品在图像采集过程中点照点光照, 记录了各通道的绝对信号强度。然而, 这些不是绝对大小的5hmC 和5caC 被检测到, 只代表的存在, 缺席或规模的这些后生标记的迹象。
由于信号放大的重复性, 限制与机械的大小相一致, 用于增强信号不可避免地混淆了这些标记的真实物理基因组的近似值34。这些标记的真正的基因组定位可能会被这些笨重的蛋白质所遮蔽, 即使在 200-300 nm34的最佳共焦分辨率限制下, 物理占据区域无法。此外, 由于抗体敏感性和荧光共轭34的差异, 每个标记的单个通道的信号强度不能相互比较。然而获得的信息与成像棚光在基因组标记的空间和世俗组织。
为了准确定量的5hmC 和5caC 信号, 原子核是突出和包围对 DAPI counterstain, 明确划定的区域进行分析。该程序不符合校准门阀阈值的要求, 因为背景噪声是通过选择原子核1的手动过程而忽略的。这一过程的自动化可以实现在最新的软件, 允许进行核分割。虽然有免费的替代软件包, 如斐济可用于定位分析, 缺点, 如要求转换成二进制8位格式的图像, 掩蔽图像和输入大小排除数据, 以选择感兴趣的区域限制此程序的用户可访问性。此外, 考虑到在基因组中的5hmC 和5caC 的总体有限水平, 加上它们在 euchromatic 地区的主要位置, 以及一般的基因组 CpG 序列的耗尽, 人工包围的细胞核引入了用户偏倚。因此, 突出的原子核自动假设所有事件发生在标定区域是积极的, 并无视任何背景像素可能存在。因此, 基于像素强度的图像分析可能更有意义。在考虑使用 Mander 的定位系数来分析两个信号之间的空间重叠程度时, 这些因素是很重要的, 不管它们的信号强度是反对皮尔逊的相关系数, 这是假定信号之间的线性关系。
总的来说, 这里概述的技术以直观的格式进行生物数据的可视化表示的主题。虽然半定量图像分析不能取代强大的技术, 如质谱的灵敏度或单一的基本分辨率基因组宽测序, 它提供补充数据, 允许推论和假说用精确的图像分析来构思。

DNA 甲基化, 一个完整的机制与转录调控需要修改的胞嘧啶的残留在 5 "-胞嘧啶磷酸-鸟嘌呤-3" (CpG) 核苷酸上下文通过添加一个甲基组 (CH3) 到5胞嘧啶嘧啶环的碳原子形成 5-嘧啶 (5mC)1。在哺乳动物中, 大约70% 的 cpg 是甲基化的, 只有1% 的基因组, 因为它们已经耗尽了这复发序列, 由于5mC 诱变倾向自发 deaminate 嘧啶2。甲基组对基因启动子序列的存在与脊椎动物的转录抑制表现出强烈的相关性3,4,5。这些甲基基团的添加是由高度保守的 DNA 甲基 (DNMT) 酶 DNMT3a, 3b 和 3L, 和 DNMT1 修改 CpG cytosines 在de 诺和维护甲基化上下文分别6。胚胎干细胞和叶发育过程中 DNMT3A/B 表达升高;然而它的被减少的表示在分化以后被观察多能细胞世系承诺到躯体命运8。虽然共享功能冗余, DNMT3a 和3b 显示组织特异性表达模式, 与3a 检测一致的小鼠胚胎, 但3b 主要本地化为外胚层和绒毛膜外胚层组织8。
甲基化签名可以在有丝分裂和减数分裂期间继承10。维护甲基化涉及 DNMT1 促进的 CpG 胞嘧啶残留在半甲基化回文的双 DNA 中存在的修饰, 即11。DNMT1 将 DNA 绑定在复制叉11上, 因此, 在单元周期的 S 阶段中, 基因组甲基化水平达到峰值12。DNMT1 methylates 未经修改的 cytosines 从而区分新合成的 DNA 链, 促进 X 染色体失活和维持转录抑制配置文件13。通过对半甲基化 DNA CpG 序列的识别, DNMT1 保持了已建立的甲基化模式, 由de 诺甲基化,例如对长散核元素1的压制 (LINE1)座子促进剂抑制其潜在的致癌传播14。虽然拥有半甲基化 DNA 优先结合亲和性, DNMT1 可以甲醇化 CpG 岛 (CGI) 序列在DNMT3a/b -/- 突变细胞, 实现紧急de 诺的甲基化角色15.因此, 由于 DNA 复制的 semi-conservative 性质16, 维护甲基化可以忠实地重述从父单元到子细胞17的甲基化特征。
然而, 对于基因表达进行动态调制, 必须消除压制性甲基化修饰, 这可以通过被动和主动甲基机制18实现。十-十一 Translocase (春节) 蛋白属于一个保守的酶蛋白家族, 可以在 CpG 残留物上进行迭代氧化甲基基团19。这些在锥 bruceii中发现的与 J 基结合蛋白 (JBP) 同源的春节蛋白, 识别并绑定修改后的 DNA 碱基, 如5mC 和氧这些残留物到 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) 和 5-carboxylcytosine (5caC)20。蛋白质促进氧化的5mC 结果在逐步构象改变从甲基到羟基, 羰基和羧酸盐的配置, 但5fC 和5caC 的修改可以直接合成从5mC 氧化21,22,23,24。
在了解其规律的同时, 对氧化的蛋白质活性进行了详细的说明, 研究了甲基-胞嘧啶标记的分布和丰度。与化 cpg 富地区相比, 在 cpg 低的启动子上有明显的5mC 存在, 后者是 cpg 群岛25的特征。在组织中, 最高组织特异性甲基化在脑、睾丸和血液中观察, 而口腔粘膜表现出最大的化, 表明在组织特异启动子26中发生的差异甲基化模式。
通过在选择性甲基/羟甲基 DNA 沉淀 (meDIP/hmeDIP) 和随后的高通量测序中利用敏感的 anti-5mC 和 anti-5hmC 抗体, Ficz et al.在促进者中展示了高5hmC 的占有率,显和 LINE-1 座子序列在小鼠胚胎干细胞的这些位置与减少的5mC 水平相关,27。相反, 最大的5mC 富集被观察在重复的卫星序列, 5hmC 存在被限制28。对人额叶脑组织的研究显示高度显著的5hmC 富集, 四倍高于小鼠胚胎干细胞28。与先前的观测结果一致, 高吞吐量测序的额叶组织图显示大多数55-59% 的5hmC 信号在低密度 CpG 启动子区, 35-38% 在基因体内和大约6% 的占有率在基因地区.相比之下, 5mC 在基因地区 (25-26%) 和更高的基因体 (52-55%), 但减少 (22-24%) 在启动子序列29。这些研究表明, 胚胎干细胞和体细胞组织的丰度为 5hmC, 尤其是大脑, 但对5fC 和5caC 分布的调查却有限。
有趣的是, 最近发现在真核生物, 甲基化的腺嘌呤残留在位置6氮 (N6) (6mA) 显示一个基因组丰度剖面反转到 5mC30。液相色谱联用串联质谱法观察发现斑马鱼和猪早期胚胎中存在的6mA 绝对水平比精子的水平 (0.003% 的基因组 adenines) 在受精时稳步增加,峰值在桑椹发育阶段 (33 倍高于精子) 和达到稳态体细胞水平的0.004% 的基因组 adenines31。沉淀的6mA 丰富的 DNA 序列已经证明了占主导地位 (约80% 丰富) 的这个标志在重复元素地区和转录开始网站32。这些观察处境并验证了6mA 甲基的发现--空 e与野生细胞中的转录活性元素相比, mbryonic 干细胞表现为6mA 介导的 LINE-1 座子沉默。这些数据显示了 6mA33的转录调节功能。
虽然共轭生化标签耦合到随后的 DIP 化验表明存在或没有氧化嘧啶衍生物 (氧化-mCs), 他们不能传授空间分布或这些标记的可量化信息34,35. 5hmC 和5caC 的敏感免疫检测的协议最近被开发了36。这种荧光共轭的二次抗体免疫方法与利用扫描激光共聚焦显微镜具有独特的优势, 提供这些 DNA 修饰的视觉定位在细胞内, 从而,强调个体正或负染色细胞与这些标记的异质存在相对应。由共轭抗体放大的5hmC 和5caC 绝对信号强度使半定量解释被提议关于这些标记的大小和位置在核例如异和 euchromatic 区域37,38. 本文描述了共焦显微图像的计算分析技术。展示了2.5D 空间分布图的生成, 用于显示每个像素的不同5hmC 和5caC 信号峰值及其在原子核中的位置。5hmC 和5caC 信号强度剖面图的直方图图可以说明这些标记的丰度趋势, 因为峰值和波谷被绘制为单独的不重叠通道。最后, 通过实现定位函数, 可以确定一个信号与另一讯号的接近度, 因此, 可以确定它们各自的基因组坐标。

<table>
	<tbody>
		<tr>
			<td>Zeiss Elyra PS1. Super resolution microscope equipped with LSM780 confocal head</td>
			<td>Zeiss</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Zeiss Zen Black 2012</td>
			<td>Zeiss</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Zen Blue 2012</td>
			<td>Zeiss</td>
			<td>NA</td>
			<td></td>
		</tr>
		<tr>
			<td>Microsoft Excel</td>
			<td>Microsoft</td>
			<td>NA</td>
			<td></td>
		</tr>
	</tbody>
</table>

immunostaining for dna modifications: computational analysis of confocal images

几十年来, 5-嘧啶 (5mC) 被认为是唯一的 DNA 修饰, 具有功能意义的后生。发现酶氧化5mC 到 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) 和 5-carboxylcytosine (5caC), 以及检测 N6-methyladenine (6mA) 的 DNA 多细胞生物体提供了额外的程度复杂性对后生研究。根据越来越多的实验证据, 这些新的 DNA 修饰可能在不同的细胞和发育过程中扮演特定的角色。重要的是, 由于这些标记 (例如5hmC、5fC 和 5caC) 在脊椎动物中表现出组织和发育阶段的具体发生, 免疫代表了一个重要的工具, 可以评估 DNA 修饰的空间分布不同的生物环境。本文介绍了用免疫和共焦显微镜进行 DNA 修饰的计算分析方法。具体说明了2.5 维 (2.5D) 信号强度图的生成、信号强度分布、多细胞染色强度的量化以及信号定位系数的确定。总的来说, 这些技术可以用于评估细胞核内这些 DNA 修饰的水平和定位, 有助于阐明它们在后生中的生物学作用。

为了确定5hmC 和5caC 在鉴别肝祖 immunostained 的空间分布, 对这些 DNA 的修饰用显微镜成像。
对这些氧化-mCs 的空间分布进行了初步分析, 并通过生成2.5D 强度图形 (图 1A, 1B) 进行。红色和绿色的山峰似乎是很好的定义与有限的存在橙色峰表明只有一个小重叠的5caC 和5hmC 信号。与这些结果一致的是, 对应单元格中5hmC 和5caC 强度的截面梁之间不强烈重合 (图 1C)。这表明, 5caC 和5hmC 在肝祖细胞中表现出明显的细胞核分布模式, 这表明, 在特定染色质中, 对5mC 的氧化作用导致了不同的氧化衍生物的产生。地区.
为了比较 Daoy 髓和 BXD-1425EPN 瘤细胞中的5caC 和5hmC 的水平, 在相同的实验条件下, 对这些免疫-mCs 进行了氧化。5caC 和5hmC 信号的强度, 然后比较了20配置文件产生的3-5 细胞记录每一个单元格线 (图 2A-2D)。这些结果的量化表明, 与 Daoy 细胞 (图 2D) 相比, BXD-1425EPN 细胞的5hmC 和5caC 免疫的水平明显降低。
考虑两个通道的红色 (5hmC) 和绿色 (5caC), 可以分别表示为 r 和 G, 皮尔逊的相关系数 (PCC) 描述的空间重叠程度和 co-segregation 的 r 和 #38; G 假设两个标记存在于一个线性关系, 用 R 统计34表示。将 PCC 值平方, 用 R2表示, 可以测量受红色信号强度影响的绿色信号强度变化34。这是多余的我们的 5caC vs 5hmC 共存分析。
为了检测5caC 和5hmC 在未分化 (Undiff) hiPSCs 和肝脏内胚层24小时 (HE24) 的空间分布, 在诱导后, 对这些 DNA 修饰的定位分析在相同的共焦图像上进行, R 值为20分析每个细胞线的细胞核 (图 3A-3C)。
这些结果的量化表明, 与 Undiff (图 3c) 相比, HE24 的定位度显著提高 (P 和 #60; 0.05)。这可能是由于5caC 的存在量减少, 从而降低了 Undiff 细胞的信号强度。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56318/56318fig1.jpg"> 
图 1: 肝内胚层祖细胞免疫组化染色72小时后诱导分化.(A) 共染色 5hmC (红色), 5caC (绿色) 和 DAPI 核计数器染色 (蓝色)。白色虚线箭头 "B" 表示通过原子核取样的分析方向, 如1C中所示。缩放条代表5µm. 红色通道: 增益 800, 激光1%。绿色通道: 增益 750, 激光2.4%。DAPI 通道: 增益 750, 激光2.6%。(B) 2.5D 5hmC、5caC 和 DAPI 信号的强度图。单个峰值代表每个像素的绝对信号强度。显示合并视图和单个通道。(C) 肝祖细胞5hmC、5caC 和 DAPI 信号的强度分布, 在72小时后诱导分化。峰值强度沿白色虚线箭头 "B" 的尺寸记录, 并沿强度剖面 x 轴用黑色虚线箭头表示。<a href="//ecsource.jove.com/files/ftp_upload/56318/56318fig1large.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/56318/56318fig2.jpg"> 
图 2: 分析 Daoy 髓和 BXD-1425EPN 瘤细胞线的5hmC 和5caC 信号强度.(A) 荧光 Daoy 和 BXD-1425EPN 细胞中的 5hmC (红色) 和 5caC (绿色) 染色。图像被抓获与63x 油浸泡物镜, 在相同的设置。显示合并视图和单个通道。刻度线代表10µm. 红色通道: 增益 746, 激光1%。绿色通道: 增益 750, 激光2.4%。单个 (B) Daoy 和 (C) BXD-1425EPN 单元格在相邻的图中展开。缩放条形图 (B) 和 (C) 表示5µm. (D) 平均荧光强度为5hmC 与5caC 信号在 Daoy 和 BXD-1425EPN 细胞 (n = 20, SD)。使用 F 检验和两样本 t 检验对其意义进行评估. 星号表示 p 和 #60 的统计显著 p 值; 0.01 和 ** #60; 0.001。<a href="//ecsource.jove.com/files/ftp_upload/56318/56318fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56318/56318fig3.jpg"> 
图 3: 与肝内胚层24小时 post-differentiated 祖细胞 (HE24) 相比, 未分化 hiPSCs (Undiff) 中5hmC 和5caC 绝对信号的定位分析.共焦显微图像 (A) 未分化的 hiPSCs 和 (B) HE24 细胞染色为 5hmC (红色), 5caC (绿色) 和 DAPI (蓝色)。在相同的设置下, 用63X 油浸透镜对细胞进行成像。20被包围的细胞核说明了为定位分析取样的细胞。刻度线代表20µm. 红色通道: 增益 800, 激光1%。绿色通道: 增益 750, 激光2.4%。DAPI 通道: 增益 750, 激光2.6%。(C) 定位分析在 undiff 和 HE24 (n = 20, SD) 的5hmC 接近度范围内的5caC 信号的存在。意义的评估使用 F 检验和两个样本 t 检验. 星号表示 p 和 #60 的统计意义上的 p 值; 0.05。<a href="//ecsource.jove.com/files/ftp_upload/56318/56318fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about Immunostaining for DNA Modifications: Computational Analysis of Confocal Images at JoVE.com

Immunostaining for DNA Modifications: Computational Analysis of Confocal Images

DNA 修饰的免疫: 共焦图像的计算分析

新发现的 5-嘧啶 (氧化-mCs), 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) 和 5-carboxylcytosine (5caC) 的氧化形式, 可能代表独特的功能作用的 DNA 修饰。本文介绍了氧化-mCs 空间分布、信号强度剖面和定位的半定量可视化工作流。

For several decades, 5-methylcytosine (5mC) has been thought to be the only DNA modification with a functional significance in metazoans. The discovery of ...

immunostaining-for-dna-modifications-computational-analysis-confocal

Research

JoVE Journal

Genetics

9.6K 次观看.  University of Nottingham. 新发现的 5-嘧啶 (氧化-mCs), 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) 和 5-carboxylcytosine (5caC) 的氧化形式, 可能代表独特的功能作用的 DNA 修饰。本文介绍了氧化-mCs 空间分布、信号强度剖面和定位的半定量可视化工作流。

视频: Immunostaining for DNA Modifications: Computational Analysis of Confocal Images

Methyl-binding DNA capture Sequencing for Patient Tissues

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable development and differentiation of different tissue types. Dysregulation of this process is often the hallmark of various diseases like cancer. Here, we outline one of the recent sequencing techniques, Methyl-Binding DNA Capture sequencing (MBDCap-seq), used to quantify methylation in various normal and disease tissues for large patient cohorts. We describe a detailed protocol of this affinity enrichment approach along with a bioinformatics pipeline to achieve optimal quantification. This technique has been used to sequence hundreds of patients across various cancer types as a part of the 1,000 methylome project (Cancer Methylome System).

Here we present a protocol to investigate genome wide DNA methylation in large scale clinical patient screening studies using the Methyl-Binding DNA Capture sequencing (MBDCap-seq or MBD-seq) technology and the subsequent bioinformatics analysis pipeline.

为患者组织甲基结合DNA序列捕获

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable ...

科研

遗传学

Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells

The processing of most eukaryotic RNAs is mediated by RNA Binding Proteins (RBPs) with modular configurations, including an RNA recognition module, which specifically binds the pre-mRNA target and an effector domain. Previously, we have taken advantage of the unique RNA binding mode of the PUF domain in human Pumilio 1 to generate a programmable RNA binding scaffold, which was used to engineer various artificial RBPs to manipulate RNA metabolism. Here, a detailed protocol is described to construct Engineered Splicing Factors (ESFs) that are specifically designed to modulate the alternative splicing of target genes. The protocol includes how to design and construct a customized PUF scaffold for a specific RNA target, how to construct an ESF expression plasmid by fusing a designer PUF domain and an effector domain, and how to use ESFs to manipulate the splicing of target genes. In the representative results of this method, we have also described the common assays of ESF activities using splicing reporters, the application of ESF in cultured human cells, and the subsequent effect of splicing changes. By following the detailed protocols in this report, it is possible to design and generate ESFs for the regulation of different types of Alternative Splicing (AS), providing a new strategy to study splicing regulation and the function of different splicing isoforms. Moreover, by fusing different functional domains with a designed PUF domain, researchers can engineer artificial factors that target specific RNAs to manipulate various steps of RNA processing.

This report describes a bioengineering method to design and construct novel Artificial Splicing Factors (ASFs) that specifically modulate the splicing of target genes in mammalian cells. This method can be further expanded to engineer various artificial factors to manipulate other aspects of RNA metabolism.

工程人为因素来特异性地操纵人细胞中的选择性剪接

The processing of most eukaryotic RNAs is mediated by RNA Binding Proteins (RBPs) with modular configurations, including an RNA recognition module, which ...

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic fragments. Organellar genomes also exist in admixtures within a given cell or tissue type (heteroplasmy), and an abundance of subtypes may change throughout development or when under stress (sub-stoichiometric shifting). Next-generation sequencing (NGS) technologies are required to obtain deeper understanding of organellar genome structure and function. Traditional sequencing studies use several methods to obtain organellar DNA: (1) If a large amount of starting tissue is used, it is homogenized and subjected to differential centrifugation and/or gradient purification. (2) If a smaller amount of tissue is used (i.e., if seeds, material, or space is limited), the same process is performed as in (1), followed by whole-genome amplification to obtain sufficient DNA. (3) Bioinformatics analysis can be used to sequence the total genomic DNA and to parse out organellar reads. All these methods have inherent challenges and tradeoffs. In (1), it may be difficult to obtain such a large amount of starting tissue; in (2), whole-genome amplification could introduce a sequencing bias; and in (3), homology between nuclear and organellar genomes could interfere with assembly and analysis. In plants with large nuclear genomes, it is advantageous to enrich for organellar DNA to reduce sequencing costs and sequence complexity for bioinformatics analyses. Here, we compare a traditional differential centrifugation method with a fourth method, an adapted CpG-methyl pulldown approach, to separate the total genomic DNA into nuclear and organellar fractions. Both methods yield sufficient DNA for NGS, DNA that is highly enriched for organellar sequences, albeit at different ratios in mitochondria and chloroplasts. We present the optimization of these methods for wheat leaf tissue and discuss major advantages and disadvantages of each approach in the context of sample input, protocol ease, and downstream application.

The comparison and optimization of two plant organellar DNA enrichment methods are presented: traditional differential centrifugation and fractionation of the total gDNA based on methylation status. We assess the resulting DNA quantity and quality, demonstrate performance in short-read next-generation sequencing, and discuss the potential for use in long-read single-molecule sequencing.

适用于下一代测序的植物细菌DNA富集方法的优化与比较分析

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic ...

Chromatin Immunoprecipitation (ChIP) of Histone Modifications from Saccharomyces cerevisiae

Histone post-translational modifications (PTMs), such as acetylation, methylation and phosphorylation, are dynamically regulated by a series of enzymes that add or remove these marks in response to signals received by the cell. These PTMS are key contributors to the regulation of processes such as gene expression control and DNA repair. Chromatin immunoprecipitation (chIP) has been an instrumental approach for dissecting the abundance and localization of many histone PTMs throughout the genome in response to diverse perturbations to the cell. Here, a versatile method for performing chIP of post-translationally modified histones from the budding yeast Saccharomyces cerevisiae (S. cerevisiae) is described. This method relies on crosslinking of proteins and DNA using formaldehyde treatment of yeast cultures, generation of yeast lysates by bead beating, solubilization of chromatin fragments by micrococcal nuclease, and immunoprecipitation of histone-DNA complexes. DNA associated with the histone mark of interest is purified and subjected to quantitative PCR analysis to evaluate its enrichment at multiple loci throughout the genome. Representative experiments probing the localization of the histone marks H3K4me2 and H4K16ac in wildtype and mutant yeast are discussed to demonstrate data analysis and interpretation. This method is suitable for a variety of histone PTMs and can be performed with different mutant strains or in the presence of diverse environmental stresses, making it an excellent tool for investigating changes in chromatin dynamics under different conditions.

Chromatin Immunoprecipitation ChIP of Histone Modifications from Saccharomyces cerevisiae

Here, we describe a protocol for chromatin immunoprecipitation of modified histones from the budding yeast Saccharomyces cerevisiae. Immunoprecipitated DNA is subsequently used for quantitative PCR to interrogate the abundance and localization of histone post-translational modifications throughout the genome.

从酿酒酵母中组蛋白修饰的染色质沉淀 (芯片)

Histone post-translational modifications (PTMs), such as acetylation, methylation and phosphorylation, are dynamically regulated by a series of enzymes ...

Methodology for Accurate Detection of Mitochondrial DNA Methylation

Quantification of DNA methylation can be achieved using bisulfite sequencing, which takes advantage of the property of sodium bisulfite to convert unmethylated cytosine into uracil, in a single-stranded DNA context. Bisulfite sequencing can be targeted (using PCR) or performed on the whole genome and provides absolute quantification of cytosine methylation at the single base-resolution. Given the distinct nature of nuclear- and mitochondrial DNA, notably in the secondary structure, adaptions of bisulfite sequencing methods for investigating cytosine methylation in mtDNA should be made. Secondary and tertiary structure of mtDNA can indeed lead to bisulfite sequencing artifacts leading to false-positives due to incomplete denaturation poor access of bisulfite to single-stranded DNA. Here, we describe a protocol using an enzymatic digestion of DNA with BamHI coupled with bioinformatic analysis pipeline to allow accurate quantification of cytosine methylation levels in mtDNA. In addition, we provide guidelines for designing the bisulfite sequencing primers specific to mtDNA, in order to avoid targeting undesirable NUclear MiTochondrial segments (NUMTs) inserted into the nuclear genome.

Here, we present a protocol to allow accurate quantification of mitochondrial DNA (mtDNA) methylation. In this protocol, we describe an enzymatic digestion of DNA with BamHI coupled with a bioinformatic analysis pipeline which can be used to avoid overestimation of mtDNA methylation levels caused by the secondary structure of mtDNA.

线粒体 DNA 甲基化的精确检测方法

Quantification of DNA methylation can be achieved using bisulfite sequencing, which takes advantage of the property of sodium bisulfite to convert ...

Single-Molecule F&ouml;rster Resonance Energy Transfer Methods for Real-Time Investigation of the Holliday Junction Resolution by GEN1

Bulk methods measure the ensemble behavior of molecules, in which individual reaction rates of the underlying steps are averaged throughout the population. Single-molecule F&#246;rster resonance energy transfer (smFRET) provides a recording of the conformational changes taking place by individual molecules in real-time. Therefore, smFRET is powerful in measuring structural changes in the enzyme or substrate during binding and catalysis. This work presents a protocol for single-molecule imaging of the interaction of a four-way Holliday junction (HJ) and gap endonuclease I (GEN1), a cytosolic homologous recombination enzyme. Also presented are single-color and two-color alternating excitation (ALEX) smFRET experimental protocols to follow the resolution of the HJ by GEN1 in real-time. The kinetics of GEN1 dimerization are determined at the HJ, which has been suggested to play a key role in the resolution of the HJ and has remained elusive until now. The techniques described here can be widely applied to obtain valuable mechanistic insights of many enzyme-DNA systems.

Single-Molecule F&#246;rster Resonance Energy Transfer Methods for Real-Time Investigation of the Holliday Junction Resolution by GEN1

Presented here is a protocol for performing single-molecule F&#246;rster resonance energy transfer to study HJ resolution. Two-color alternating excitation is used for determining the dissociation constants. Single-color time lapse smFRET is then applied in real-time cleavage assays to obtain the dwell time distribution prior to HJ resolution.

单分子Fürster共振能量传递方法，用于GEN1对霍利迪结分辨率进行实时调查

Bulk methods measure the ensemble behavior of molecules, in which individual reaction rates of the underlying steps are averaged throughout the ...

Generation of Defined Genomic Modifications Using CRISPR-CAS9 in Human Pluripotent Stem Cells

Human pluripotent stem cells offer a powerful system to study gene function and model specific mutations relevant to disease. The generation of precise heterozygous genetic modifications is challenging due to CRISPR-CAS9 mediated indel formation in the second allele. Here, we demonstrate a protocol to help overcome this difficulty by using two repair templates in which only one expresses the desired sequence change, while both templates contain silent mutations to prevent re-cutting and indel formation. This methodology is most advantageous for gene editing coding regions of DNA to generate isogenic control and mutant human stem cell lines for studying human disease and biology. In addition, optimization of transfection and screening methodologies have been performed to reduce labor and cost of a gene editing experiment. Overall, this protocol is widely applicable to many genome editing projects utilizing the human pluripotent stem cell model.

This protocol provides a method to facilitate the generation of defined heterozygous or homozygous nucleotide changes using CRISPR-CAS9 in human pluripotent stem cells.

在人类多能干细胞中使用CRISPR-CAS9生成定义的基因组修饰

Human pluripotent stem cells offer a powerful system to study gene function and model specific mutations relevant to disease. The generation of precise ...

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Genome-wide association studies (GWAS) have successfully identified hundreds of genomic loci that are associated with human traits and disease. However, because the majority of the genome-wide significant (GWS) loci fall onto the non-coding genome, the functional impact of many remain unknown. Three-dimensional chromatin interactions identified by Hi-C or its derivatives can provide useful tools to annotate these loci by linking non-coding variants to their actionable genes. Here, we outline a protocol to map GWAS non-coding variants to their putative genes using Alzheimer&#39;s disease (AD) GWAS and Hi-C datasets from human adult brain tissue. Putative causal single-nucleotide polymorphisms (SNPs) are identified by application of fine-mapping algorithms. SNPs are then mapped to their putative target genes using enhancer-promoter interactions based on Hi-C. The resulting gene set represents AD risk genes, as they are potentially regulated by AD risk variants. To garner further biological insights into molecular mechanisms underlying AD, we characterize AD risk genes using developmental brain expression data and brain single-cell expression profiles. This protocol can be expanded to any GWAS and Hi-C datasets to identify putative target genes and molecular mechanisms underlying various human traits and diseases.

We present a protocol to identify functional implications of non-coding variants identified by genome-wide association studies (GWAS) using three-dimensional chromatin interactions.

利用染色质配置的计算分析，将阿尔茨海默氏病变异体映射到其目标基因

Genome-wide association studies (GWAS) have successfully identified hundreds of genomic loci that are associated with human traits and disease. However, ...

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding of the basis of various diseases as well as resistance and/or susceptibility mechanisms. However, FFPE tissues, which represent the most common method for preserving tissue morphology in clinical specimens, are not the best sources for gene expression profiling analysis. The RNA obtained from such samples is often degraded, fragmented, and chemically modified, which leads to suboptimal sequencing libraries. In turn, these generate poor quality sequence data that may not be reliable for gene expression analysis and mutation discovery. In order to make the most of FFPE samples and obtain the best possible data from low quality samples, it is important to take certain precautions while planning experimental design, preparing sequencing libraries, and during data analysis. This includes the use of appropriate metrics for precise sample quality control (QC), identifying the best methods for various steps during the sequencing library generation, and careful library QC. In addition, applying correct software tools and parameters for sequence data analysis is critical in order to identify artifacts in RNA-seq data, filter out contamination and low quality reads, assess uniformity of gene coverage, and measure the reproducibility of gene expression profiles among biological replicates. These steps can ensure high accuracy and reproducibility for profiling of very heterogeneous RNA samples. Here we describe the various steps for sample QC, library preparation and QC, sequencing, and data analysis that can help to increase the amount of useful data obtained from low quality RNA, such as that obtained from FFPE-RNA tissues.

This method describes the steps to improve the quality and quantity of sequence data that can be obtained from formalin-fixed paraffin-embedded (FFPE) RNA samples. We describe the methodology to more accurately assess the quality of FFPE-RNA samples, prepare sequencing libraries, and analyze the data from FFPE-RNA samples.

降解FFPE-RNA样品测序与分析优化

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding ...

Application of DNA Fingerprinting using the D1S80 Locus in Lab Classes

In biological sciences, DNA fingerprinting has been widely used for paternity testing, forensic applications and phylogenetic studies. Here, we describe a reliable and robust method for genotyping individuals by Variable Number of Tandem Repeat (VNTR) analysis in the context of undergraduate laboratory classes. The human D1S80 VNTR locus is used in this protocol as a highly polymorphic marker based on variation in the number of repetitive sequences.
This simple protocol conveys useful information for teachers and the implementation of DNA fingerprinting in practical laboratory classes. In the presented laboratory exercise, DNA extraction followed by PCR amplification is used to determine genetic variation at the D1S80 VNTR locus. Differences in the fragment size of PCR products are visualized by agarose gel electrophoresis. The fragment sizes and repeat numbers are calculated based on a linear regression of the size and migration distance of a DNA size standard.
Following this guide, students should be able to:
&#8226;&#160; Harvest and extract DNA from buccal mucosa epithelial cells 
&#8226;&#160; Perform a PCR experiment and understand the function of various reaction components 
&#8226;&#160; Analyze the amplicons by agarose gel electrophoresis and interpret the results 
&#8226;&#160; Understand the use of VNTRs in DNA fingerprinting and its application in biological sciences

Application of DNA Fingerprinting using the D1S80 Locus in Lab Classes

Here we describe a simple protocol to generate DNA fingerprinting profiles by amplifying the VNTR locus D1S80 from epithelial cell DNA.

使用 D1S80 轨迹在实验室类中应用 DNA 指纹

In biological sciences, DNA fingerprinting has been widely used for paternity testing, forensic applications and phylogenetic studies. Here, we describe a ...