瑞典研究委员会，瑞典癌症协会，Knut和爱丽丝·瓦伦贝格基金会（KAW）以及FoUVästraGötalandsregionen都支持这项研究。

收集CLL样本的道德准许是2007-05-21，具有以下注册号:EPN Gbg dnr 239/07。所有CLL患者根据最近修订的标准8诊断，并在诊断时收集样品。在获得书面同意后，研究中的患者被纳入瑞典西部不同血液学部门。本研究仅选择了白血病细胞百分率≥70％的CLL外周血单个核细胞（PBMC）样本。 准备工作<ol><li>根据制造商的说明书，使用商业分离试剂盒（参见材料表 ），从CLL和正常的健康外周血样品中分离PBMC进行DNA提取。 </li><li>高压灭菌1.5 mL管。解冻甲基化DNA结合试剂盒中的所有试剂（参见材料表 ）/ LI&gt; <li>使用无DNA酶的水从试剂盒提供的5x储备洗涤缓冲液中制备10 mL 1x珠洗涤缓冲液以洗涤珠粒并稀释试剂盒提供的MBD蛋白质。 </li><li>事先获得或准备以下物品:3M乙酸钠，无水乙醇和70％乙醇用于DNA沉淀（ 材料表 ）。 </li></ol> 2.基因组DNA提取和超声处理<ol><li>使用市售的DNA提取试剂盒（ 材料表 ）根据制造商的方案从患者和正常PBMC样品中分离基因组DNA。使用分光光度计在260nm定量基因组DNA。 注:DNA提取柱容量为5-6万个细胞，最大;因此，对于超过500万个细胞的样品使用多于一个色谱柱是很重要的。将DNA洗脱两次，共计100μL10 mM Tris EDTA（TE）缓冲液。用于甲基的MBD-生物素蛋白用于MBD测序的矿工试剂盒不会与单链DNA结合。因此，保持洗脱的DNA冷冻或在4℃保持其双链性质是非常重要的。 </li><li>使用TE缓冲液（pH8）将每个样品的5μg基因组DNA稀释至总共200μL，最后浓度为25ng /μL。 </li><li>使用超声波仪（ 材料表 ）在特殊设计的管中进行超声处理，总共30个循环（每个循环30秒和30秒;每5个循环后，短暂旋转管以将样品收集到底部）。 注意:这将产生150 bp和300 bp之间的片段DNA，这对于该方案是最佳的。 </li><li>检查所有样品的超声处理范围，然后通过使用DNA电泳成像设备，在市售的预制2％琼脂糖凝胶上运行1μL片段DNA样品和DNA大小梯度，进行下一步的MBD测序。可视化t他使用标准的紫外线透射仪DNA。 </li></ol> 3.与MBD-生物素蛋白结合之前的珠粒制备<ol><li>从试剂盒提供的储备管中重新悬浮磁性链亲和素珠，轻轻上下移液以获得均匀的悬浮液。不要涡旋珠子或让它们干燥。 </li><li>将50μL珠（每个5μg片段化的DNA样品）放在分开的，干净的和标记的1.5mL管中。加入50μL的1x珠洗涤缓冲液，达到100μL的最终体积。 注意:当使用小的0.5 mL聚合酶链反应（PCR）条纹用于洗涤珠子时，如试剂盒方案中所述，使用约150-200μL的每个洗涤缓冲液。然而，在1.5mL管的情况下，每管加入至少250μL至300μL洗涤缓冲液用于珠洗涤。 </li><li>将管置于磁性架上1分钟，以使所有的磁珠集中在管的内壁上面对磁铁。取出液体，不用珠子接触，使用200μL移液管。 </li><li>从磁性支架上取出管子，加入250μL的1x珠洗涤缓冲液，并用移液管轻轻混合。 </li><li>对所有样品重复步骤3.3和3.4至少4-5次，最后重悬于250μL的1x珠洗涤缓冲液中。把它们放在冰上。 </li></ol> 4.将MBD-生物素蛋白与洗涤的珠结合<ol><li>加入35μLMBD蛋白（7μL1μgDNA样品）分离管，并使用1倍珠洗涤缓冲液将总体积达250μL。 </li><li>将250μL稀释的MBD蛋白加入到250μL洗涤的珠中，使其在室温下端对端旋转1小时。 </li><li> 将珠粒和蛋白质混合1小时后，用磁性链亲和素珠清洗MBD蛋白质生物素。 <ol><li>将管置于磁性架上1分钟，取出t他使用移液器不接触珠子。加入250μL的1x珠洗涤缓冲液，并将管置于旋转混合器中5分钟。 </li></ol></li><li>重复步骤4.3.1两次，最后将洗涤的MBD-生物素珠重悬于200μL的1倍珠洗涤缓冲液中，使珠准备好进行甲基化DNA捕获。 注意:以这种方式洗2-3次，除去所有背景未结合的MBD蛋白质珠，并改善MBD蛋白偶联珠与片段化基因组DNA的有效结合。 </li></ol> 5.将MBD-生物素珠与片段基因组DNA结合<ol><li>在干净的1.5 mL无DNA酶的管中，加入100μL5倍珠洗涤缓冲液和180μL片段化基因组DNA（步骤2.3）。使用无DNA酶的水，使最终体积达到500μL。 </li><li>向剩余的20μL片段化的基因组DNA中加入380μL无DNA酶的水并冷冻。使用这些样品作为输入DNA随后与最终洗脱的甲基化DNA样品一起控制和沉淀，（见步骤7.1）。 </li><li>将含有洗涤的MBD-生物素珠（步骤4.4）的管置于磁性架上1分钟，并除去液体，而不干扰珠粒。加入500μL在珠洗涤缓冲液中稀释的片段化基因组DNA。 </li><li>用石蜡膜密封所有的管子，并在4℃下以8-10rpm在端对端的旋转架上放置过夜。 注意:DNA和生物素 - 珠粒结合反应可以在室温下进行1小时，但在4℃下保持过夜可以提高最终甲基化DNA的回收率。 </li></ol> 6.去除未结合的DNA并从珠中洗脱甲基化的DNA <ol><li> DNA和MBD-珠粒结合反应后，将管置于磁性架上1分钟，将所有的珠粒集中在管内壁上。 </li><li>用移液器取出上清液而不接触并将此未结合的DNA样品级分保存在冰上。 </li><li>向珠中加入200μL的1x珠洗涤缓冲液，并将管在室温下放置在旋转架上3分钟。将管放在磁性支架上并取出液体。重复洗涤两次以除去残留的未结合的DNA。 </li><li>最终洗涤后，加入200μL高盐洗脱缓冲液（2,000 mM NaCl），在试剂盒中洗脱DNA。 </li><li>将管在室温下放置在旋转架上15分钟。将它们放在磁性架上1分钟，并使用移液管小心地将上清液转移到新的干净的1.5 mL管中。 </li><li>加入200μL高盐洗脱缓冲液，并在室温下旋转管重复洗脱15分钟。将第二个洗脱液加入含有200μL第一个洗脱液的同一根管中。 注意:最终的400μL总洗脱DNA现在可以进行乙醇沉淀，以提取纯化的适合下一代测序的DNA。 </li></ol>乙醇沉淀和甲基化DNA的富集<ol><li>加入1μL糖原（20μg/μL;包含在试剂盒中）; 40μL3M乙酸钠，pH 5.2;和800μL冰冷的无水乙醇至400μL洗脱的DNA，以及步骤5.2中制备的400μL的输入DNA样品。 </li><li>通过涡旋混合管并在-80℃下孵育过夜。 </li><li>以12,000 xg（最大速度）和4°C离心管。仔细弃去上清液，不会干扰沉淀，加入500μL70％乙醇，并涡旋管。 </li><li>在4℃下以最大速度再次离心15分钟，小心地用移液管除去上清液。在室温下以最大速度离心管1分钟，并用移液管吸头彻底清除残留的乙醇。 </li><li>在室温下将颗粒空气干燥5分钟rature。向DNA沉淀中加入10μL无DNA酶的水。进行甲基化DNA定量（步骤7.6），MBD测序（步骤7.7）和分析（第8和9节）。 </li><li>根据制造商的说明书，使用市售的荧光定量试剂盒（参见材料表 ）量化最终回收的甲基化DNA样品。 </li><li>注意:使用该方案，从每个样品中回收30-50ng的最终DNA。 DNA样本准备在干冰上发送用于下游文库构建和高通量MBD测序</li><li>使用商业平台（ 材料表 ）进行DNA文库构建和高通量MBD测序，如参考文献9所述。 注意:对于最终甲基化DNA的初始质量控制，使用所有样品的50 bp双末端测序进行文库制备。处理原始数据进行后序测序质量控制，a在步骤8.1中阐述，并且使用生物信息学方法和统计方法进一步处理它，如下所述（步骤8.2-9.6）。 </li></ol> 8.生物信息学分析方法1:鉴定CLL相关差异甲基化区域（cllDMRs） <ol><li>使用可用的质量控制工具（如Trimmomatic 10或Cutadapt）清洁获得的49-bp读取（FASTQ格式）的适配器。使用FastQC工具包交叉检查修剪读取的质量: java -jar trimmomatic.jar SE SAMPLE_uncleaned.fastq SAMPLE.fastq ILLUMINACLIP:adapters.fasta:2:30:10 </li><li> 将清洁的FASTQ文件与短读基因组对齐器Bowtie对齐参考基因组11 。指定参数如下: <ol><li>允许最多两个不匹配（Bowtie参数: -v 2）。 </li><li>将报告限制为每次读取六个最佳对齐（Bowtie参数: -m 6）进行控制用于多映射读取。 bowtie -v 2 -a -m 6 HG19_INDEX -S SAMPLE.fastq&gt; SAMPLE.sam 注意:使用SAMtools将对齐后的各个样本生成的SAM文件转换为BAM。 samtools视图-bS -o SAMPLE.bam SAMPLE.sam </li></ol></li><li>使用对齐样本（BAM）的ChIP-Seq（MACS）峰值呼叫者的基于模型的分析来预测来自CLL亚组12的富集/甲基化区域。 注意:比较I:使用输入样品作为对照组，将正常和CLL患者样品作为治疗组。此步骤是收集所有负峰（丰富输入/背景的峰）。比较二:使用正常样本组作为对照组，CLL患者样本组作为治疗组。获得的正峰是CLL高甲基化区，负峰是正常或差异甲基化区（DMR）的CLL低甲基化区。 macs14 -t SAMPLE_TREATMENT.bam -c SAMPLE_CONTROL.bam - 格式BAM -g hs </li><li>使用BED工具去除差异甲基化区域（DMR）中的比较I背景峰13 。 bedtools subtract -a &lt;CLL_enriched_regions&gt; -b &lt;Input_enriched_regions&gt; </li><li> 预测富集DMR的重复元素（SINE-Alu，LINE 等 ）的百分比。 <ol><li>使用fastacmd通过参考基因组HG19的染色体坐标提取DMR的FASTA序列。 fastacmd -d HG19_genome.fa -s染色体-L开始，结束-1 50000&gt; DMRs.fasta </li><li>使用RepeatMasker命令行工具来预测DMR中FASTA序列中存在的重复元素的百分比。 RepeatMasker -gc -gccalc -s -species human -html DMRs.fasta </li></ol></li><li>使用荷马"annotatePeaks.pl"与可用的Ensembl [PMC4919035] o注释预测的DMRr代码[PMID 22955987]转录本注释（蛋白质编码和非编码转录本）。 annotatePeaks.pl DMRs.bed &lt;GENOME&gt; -gtf &lt;Ensembl或Gencode GTF&gt; 注意:这提供了关于不同基因区域（ 即启动子，外显子，内含子，3&#39;UTR和5&#39;UTR）和基因间区域的峰分布的信息。与DMR相关的转录物或基因称为差异甲基化基因（DMG）。 </li><li>使用富集工具与更新的或当前的功能数据库来查找CLL DMGs（仅蛋白质编码基因）丰富的功能14 。 注意:基于功能注释的基因集聚簇（GeneSCF） 14是一种基于实时的功能丰富分析工具，使用更新的KEGG和基因本体作为参考数据库。 </li></ol> 9.生物信息学分析方法2:识别CLL相关显着差异甲基化区域（cll sigDMR） <ol><li>按照方法I（第8节）中的步骤8.1-8.5，并使用基于读数计数的差异浓缩分析，利用步骤9.2 - 9.6中详细介绍的可用工具，将更多的统计信息添加到分析流程中。 </li><li>使用"Subread"软件包15中的"featureCounts"量化在普通和CLL患者样本中映射到单独峰值或DMR的读数。 subread / bin / featureCounts -Q 30 -F SAF -a DMRs.SAF -o DMRs_counts.table SAMPLE_TREATMENT.bam SAMPLE_CONTROL.bam 注意:可以引入映射质量过滤器来避免量化不良品质的读取（ 例如，-Q 30）。为此步骤，准备获得的DMR的SAF文件。有关SAF文件格式的更多信息，请使用此链接http://bioinf.wehi.edu.au/featureCounts/。 </li><li>使用RAW读数计数表，其中包含Normal a中各个峰的读数d CLL患者样本组在edgeR中作为输入16 。 注意:比较正常与CLL患者样本组以找到sigDMRs。对于差异富集分析，请按照edgeR的指南详细分步说明（https://bioconductor.org/packages/release/bioc/vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf）。 </li><li>过滤sigDMRs使用false discovery rate（FDR）和log-fold更改由edgeR 16预测。 </li><li>使用可用的Ensembl或Gencode转录本注释（蛋白质编码和非编码转录本），使用Homer"annotatePeaks.pl"注释预测的sigDMR。 annotatePeaks.pl sigDMRs.bed HG19_genome.fa -gtf &lt;Ensembl或Gencode GTF&gt; -CpG 注意:这提供了关于不同基因区域（ 即启动子，外显子，内含子，3&#39;UTR和5&#39;UTR）和基因间区域的峰分布的信息。与si相关的转录物或基因gDMR称为sigDMG。 </li><li>使用更新或当前功能数据库的浓缩工具来查找CLL sigDMG（仅蛋白编码基因）富集的功能14 。 注:GeneSCF是功能丰富分析的实时工具之一，使用KEGG和Gene本体作为参考数据库。 </li></ol>

<ol>
	<li>Kanduri, 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=Differential+genome-wide+array-based+methylation+profiles+in+prognostic+subsets+of+chronic+lymphocytic+leukemia.">Differential genome-wide array-based methylation profiles in prognostic subsets of chronic lymphocytic leukemia.</a> Blood. 115 (2), 296-305 (2010).</li><li>Cahill, N., 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=450K-array+analysis+of+chronic+lymphocytic+leukemia+cells+reveals+global+DNA+methylation+to+be+relatively+stable+over+time+and+similar+in+resting+and+proliferative+compartments.">450K-array analysis of chronic lymphocytic leukemia cells reveals global DNA methylation to be relatively stable over time and similar in resting and proliferative compartments.</a> Leukemia. 27 (1), 150-158 (2013).</li><li>Kanduri, 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=Distinct+transcriptional+control+in+major+immunogenetic+subsets+of+chronic+lymphocytic+leukemia+exhibiting+subset-biased+global+DNA+methylation+profiles.">Distinct transcriptional control in major immunogenetic subsets of chronic lymphocytic leukemia exhibiting subset-biased global DNA methylation profiles.</a> Epigenetics. 7 (12), 1435-1442 (2012).</li><li>Kulis, 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=Epigenomic+analysis+detects+widespread+gene-body+DNA+hypomethylation+in+chronic+lymphocytic+leukemia.">Epigenomic analysis detects widespread gene-body DNA hypomethylation in chronic lymphocytic leukemia.</a> Nat Genet. 44 (11), 1236-1242 (2012).</li><li>Booth, M. 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=Quantitative+sequencing+of+5-methylcytosine+and+5-hydroxymethylcytosine+at+single-base+resolution.">Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine at single-base resolution.</a> Science. 336 (6083), 934-937 (2012).</li><li>Yu, 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=Base-resolution+analysis+of+5-hydroxymethylcytosine+in+the+mammalian+genome.">Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome.</a> Cell. 149 (6), 1368-1380 (2012).</li><li>Subhash, S., Andersson, P. O., Kosalai, S. T., Kanduri, C., Kanduri, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+DNA+methylation+profiling+reveals+new+insights+into+epigenetically+deregulated+protein+coding+and+long+noncoding+RNAs+in+CLL.">Global DNA methylation profiling reveals new insights into epigenetically deregulated protein coding and long noncoding RNAs in CLL.</a> Clin Epigenetics. 8, 106 (2016).</li><li>Hallek, 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=Guidelines+for+the+diagnosis+and+treatment+of+chronic+lymphocytic+leukemia:+a+report+from+the+International+Workshop+on+Chronic+Lymphocytic+Leukemia+updating+the+National+Cancer+Institute-Working+Group+1996+guidelines.">Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines.</a> Blood. 111 (12), 5446-5456 (2008).</li><li>De Meyer, T., 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=Quality+evaluation+of+methyl+binding+domain+based+kits+for+enrichment+DNA-methylation+sequencing.">Quality evaluation of methyl binding domain based kits for enrichment DNA-methylation sequencing.</a> PLoS One. 8 (3), e59068 (2013).</li><li>Bolger, A. M., Lohse, M., Usadel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trimmomatic:+a+flexible+trimmer+for+Illumina+sequence+data.">Trimmomatic: a flexible trimmer for Illumina sequence data.</a> Bioinformatics. 30 (15), 2114-2120 (2014).</li><li>Langmead, B., Trapnell, C., Pop, M., Salzberg, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+and+memory-efficient+alignment+of+short+DNA+sequences+to+the+human+genome.">Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.</a> Genome Biol. 10 (3), R25 (2009).</li><li>Zhang, 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=Model-based+analysis+of+ChIP-Seq+(MACS).">Model-based analysis of ChIP-Seq (MACS).</a> Genome Biol. 9 (9), R137 (2008).</li><li>Quinlan, A. R., Hall, I. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BEDTools:+a+flexible+suite+of+utilities+for+comparing+genomic+features.">BEDTools: a flexible suite of utilities for comparing genomic features.</a> Bioinformatics. 26 (6), 841-842 (2010).</li><li>Subhash, S., Kanduri, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GeneSCF:+a+real-time+based+functional+enrichment+tool+with+support+for+multiple+organisms.">GeneSCF: a real-time based functional enrichment tool with support for multiple organisms.</a> BMC Bioinformatics. 17 (1), 365 (2016).</li><li>Liao, Y., Smyth, G. K., Shi, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=featureCounts:+an+efficient+general+purpose+program+for+assigning+sequence+reads+to+genomic+features.">featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.</a> Bioinformatics. 30 (7), 923-930 (2014).</li><li>Robinson, M. D., McCarthy, D. J., Smyth, G. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=edgeR:+a+Bioconductor+package+for+differential+expression+analysis+of+digital+gene+expression+data.">edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.</a> Bioinformatics. 26 (1), 139-140 (2010).</li><li>Martinelli, 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=ANGPT2+promoter+methylation+is+strongly+associated+with+gene+expression+and+prognosis+in+chronic+lymphocytic+leukemia.">ANGPT2 promoter methylation is strongly associated with gene expression and prognosis in chronic lymphocytic leukemia.</a> Epigenetics. 8 (7), 720-729 (2013).</li><li>Kopparapu, P. 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=Epigenetic+silencing+of+miR-26A1+in+chronic+lymphocytic+leukemia+and+mantle+cell+lymphoma:+Impact+on+EZH2+expression.">Epigenetic silencing of miR-26A1 in chronic lymphocytic leukemia and mantle cell lymphoma: Impact on EZH2 expression.</a> Epigenetics. 11 (5), 335-343 (2016).</li><li>Robinson, M. 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=Evaluation+of+affinity-based+genome-wide+DNA+methylation+data:+effects+of+CpG+density,+amplification+bias,+and+copy+number+variation.">Evaluation of affinity-based genome-wide DNA methylation data: effects of CpG density, amplification bias, and copy number variation.</a> Genome Res. 20 (12), 1719-1729 (2010).</li></ol>

作者没有什么可以披露的。

MBD-seq是一种经济有效的基于免疫沉淀的技术，可用于研究具有完整全基因组范围覆盖的甲基化模式。 MeDIP seq（甲基化DNA免疫沉淀随后测序）和MBD-seq均导致富含CpG的甲基化DNA的富集。然而，与MeDIP seq 19相比，MBD-seq对结合高度富含CpG的区域具有更强的亲和力。使用甲基结合富集试剂盒，可以分别通过高盐和低盐缓冲液洗脱DNA将DNA分馏成高CpG和低CpG富集区。在该研究中，仅进行单次洗脱以捕获覆盖大多数CpG岛的富含富含CpG的区域。 MBD-seq可以是WGBS的强大替代品，它通常用于CLL和其他白血病调查。尽管与亚硫酸氢盐相比，MBD-seq需要相对较高量的输入DNA基于转换的方法，它允许调查仅针对5mC修饰的特异性的全局甲基化变化，而没有在转化后产生任何PCR扩增偏倚。因此，MBD-seq是解决cllDMG的理想方法，其可能是具有预后价值的潜在的基于表观遗传学的CLL特征基因。 执行该方法的关键因素是在结合反应之前使用的片段DNA的质量和超声处理范围。所有样品显示较短的片段范围，在150至300 bp之间（ 图4 ），从而产生优质的测序结果，数据过滤和清洗后每个样品与基因组的映射关系约为25-33百万次。 最后，在独立样品队列中，使用焦磷酸测序法，对少数几个基因已经验证了超低级和低甲基化的cllDMG的甲基化状态。这种方法给出了感知取决于在单个CpG位点的C-T与基于序列延伸期间掺入的C和T量的比例。与正常样品相比，超甲基化的cllDMG在CLL样品中显示高百分比的甲基化。同样，低甲基化的cllDMG显示相反的。 图3显示了两个cllDMG的焦磷酸测序数据。 与基于阵列的方法相比，该方法允许对整个基因组的序列进行更广泛的检查，包括跨越蛋白质编码区域的先前注释的区域和跨越重复元件和lncRNA的非注释序列。因此，CLL患者的这种方法鉴定了跨越lncRNA和重复元件的几种新型cllDMG。由于这些研究以前尚未在CLL患者样本中进行，因此本研究作为识别CLL相关差异甲基化区域的宝贵资源不同的预后亚组。这些cllDMG将作为表观遗传药物治疗的新型生物标志物和靶标。

近年来，使用下一代测序技术分析全球DNA甲基化谱已越来越受欢迎。基于全基因组的甲基化测定，包括基于微阵列和非微阵列的方法，基于以下方法开发:基因组DNA的亚硫酸氢盐转化，甲基化敏感的限制酶消化和甲基化DNA的免疫沉淀，使用甲基CpG特异性抗体。 异常DNA甲基化是白血病和淋巴瘤的标志之一，包括慢性淋巴细胞性白血病（CLL）。早些时候，包括我们在内的几个组织表征不同CLL预后亚组和正常健康B细胞对照的DNA甲基化谱，使用基因组DNA的亚硫酸氢盐转化，然后是基于微阵列的方法或全基因组测序1,2,3 ， &lt;sup class ="xref"&gt; 4。基因组DNA的亚硫酸氢盐转化导致未修饰的胞嘧啶脱氨酸尿嘧啶，留下基因组中修饰的甲基化胞嘧啶。一旦转化，DNA的甲基化状态可以通过PCR扩增和使用不同的定量或定性方法如基于微阵列或全基因组亚硫酸氢盐测序（WGBS）的测序来测定。尽管基于亚硫酸氢盐转化的方法具有许多优点，并且广泛用于不同的癌症类型以分析DNA甲基化水平，但与该技术相关的一些缺点是。 WGBS测序允许单碱基对分辨率较低的DNA，是分析大量样品的最佳选择。然而，这种方法不能区分基因组中5mC和5mmC水平之间的修饰。此外，基于微阵列的方法不提供完整的c基因组超量。 在我们实验室7最近的一项研究中，基于免疫沉淀的方法，而不是亚硫酸氢盐转化，用于在CLL患者和正常健康对照组中在全球范围内鉴定高度富含CpG的差异甲基化区域。在甲基CpG结合域（MBD）下一代测序（MBD-seq）中，双链片段化DNA的富集取决于CpG甲基化程度。该方法可以克服亚硫酸氢盐转化方法的缺点，并且还可以以无偏差和不依赖PCR的方式提供CpG甲基化的全基因组覆盖。此外，与基于亚硫酸氢盐转化的微阵列方法不同，MBD-seq可用于分析重复元件的甲基化状态，例如长散布核元素（LINE），短散点核元素（SINE），长末端重复序列（LTRS） 等等然而，与亚硫酸氢盐转化方法相比，MBD-seq协议需要相当大量的输入DNA。此外，测序的质量读数和数据取决于所用抗体的特异性，亲和性和质量。 目前的研究解释了详细的MBD-seq方案来丰富用于下一代测序的甲基化DNA。它使用商业甲基化DNA结合浓缩试剂盒（在材料表中列出 ），以及计算流程，用于显示和解释甲基化测序数据，以鉴定与正常健康对照相比的CLL特异性高和低甲基化区域。基本上，这种方法利用人类MBD2蛋白与甲基化CpG相互作用的MBD的能力来提取富含甲基化CpG的DNA，其次是甲基化DNA的高通量测序。

<table><tbody><tr><td>Dneasy Blood and tissue kit</td><td>Qaigen</td><td>69504</td><td></td></tr><tr><td>Lymphoprep solution</td><td>A X I S-S H I E L D</td><td>1114544</td><td></td></tr><tr><td>Nano drop 2000</td><td>Thermo Fischersceintific</td><td></td><td></td></tr><tr><td>TE buffer pH 8</td><td>Sigma aldrich</td><td>93283</td><td></td></tr><tr><td>Bioruptor standard sonication device</td><td>Diagenode</td><td>UCD-200</td><td></td></tr><tr><td>TPX bioruptor tubes 1.5 mL</td><td>Diagenode</td><td>C30010010-300</td><td></td></tr><tr><td>3 M Sodium acetate</td><td>Diagenode</td><td>C03030002</td><td></td></tr><tr><td>E-gel iBase safe imager combo kit</td><td>Thermo Fischersceintific</td><td>G6465EU</td><td></td></tr><tr><td>E-gel 2% Agarose gels</td><td>Thermo Fischersceintific</td><td>G441002</td><td></td></tr><tr><td>Methylminer Methylated DNA enrichment kit</td><td>Thermo Fischersceintific</td><td>ME10025</td><td></td></tr><tr><td>Labquake Tube Shaker/Rotators</td><td>Thermo Fischersceintific</td><td>415110</td><td></td></tr><tr><td>Dynal MPC-S</td><td>Thermo Fischersceintific</td><td>A13346</td><td></td></tr><tr><td>Vortex mixer</td><td>VWR</td><td>12620-848</td><td></td></tr><tr><td>Absolute Ethanol</td><td>Any company</td><td></td><td></td></tr><tr><td>70% Ethanool</td><td>Any company</td><td></td><td></td></tr><tr><td>DNAse free water</td><td>Milli Q</td><td></td><td></td></tr><tr><td>DNA precipitant (3M sodium acetate)</td><td>Diagenode</td><td>C03030002</td><td></td></tr><tr><td>Safe seal 1.5 mL eppendorf tubes</td><td>Eppendorf</td><td>4036-3204</td><td></td></tr><tr><td>Qubit dsDNA HS Assay Kit</td><td>Thermo Fischersceintific</td><td>Q32851</td><td></td></tr><tr><td>Qubit 0.5 mL tubes</td><td>Thermo Fischersceintific</td><td>Q32856</td><td></td></tr><tr><td>Qubit</td><td>Thermo Fischersceintific</td><td>Q32866</td><td></td></tr><tr><td>Illumina Hiseq2000 Platform</td><td>Illumina</td><td></td><td></td></tr><tr><td>Water&amp;nbsp; Bath</td><td>Grant</td><td></td><td></td></tr><tr><td>Heat block</td><td>grant</td><td></td><td></td></tr><tr><td>Tube rotater</td><td>Labquake</td><td></td><td></td></tr></tbody></table>

comprehensive dna methylation analysis using a methyl-cpg-binding domain capture-based method in chronic lymphocytic leukemia patients

长期非编码RNA（lncRNA）在癌症中的作用已经走在前列，因为在癌症发展和进展期间越来越需要了解其机械功能。尽管如此，在癌症中lncRNA和重复序列的全球表观遗传调控尚未得到很好的研究，特别是在慢性淋巴细胞性白血病（CLL）中。本研究着重于一种独特的方法:使用甲基结合结构域（MBD）蛋白进行基于免疫沉淀的双链甲基化DNA片段捕获，随后进行下一代测序（MBD-seq）。本研究使用属于两个预后亚组（5个IGVH突变样本+ 5个IGVH未突变样本）的CLL患者样本。与正常健康对照相比，分析显示5,800个高甲基化和12,570个低甲基化的CLL特异性差异甲基化基因（cllDMG）。重要的是，这些结果确定了几种CLL特异性差异甲基化的lncRNA具有潜在预后价值的蛋白质编码基因。该工作概述了MBD-seq和生物信息学管道的详细协议，用于使用CLL患者样本全面分析高CpG丰富地区的全球甲基化谱。最后，使用焦磷酸测序验证蛋白质编码基因和lncRNA，这是一种高度定量的方法来分析CpG甲基化水平，以进一步证实MBD-seq方案的发现。

最近对CLL患者和匹配的正常健康对照进行了MBD-seq，以鉴定CLL特异性差异超低和低甲基化基因7 。用于分析CLL和正常健康样品产生的数据的实验和生物信息管道如图1A和1B所示 。这些分析确定了几个CLL特异性差异甲基化区域（cllDMR），与对照样品相比，IGHV突变和IGHV未突变样品显着高/低甲基化，p值&lt;0.00001。 图2A显示从正常B细胞​​和正常PMBC比较两者获得的所有clDDMR。所有的cllDMR被映射到不同类型的蛋白质编码和非编码基因， 如图2B所示 。重要的是，在这个分析中，比较是比较的在CLL患者样本之间，两个不同的正常对照，B细胞和PMBCs分选。有趣的是，与正常的B细胞对照和正常的PBMC对照样品相比，分析导致常见的CLL特异性差异甲基化基因（cllDMG; 851高甲基化和2,061低甲基化）的重叠大（ 图2C ），表明这些cllDMG可以是可能的CLL特征基因在疾病发病过程中具有重要作用。为了加强分析的数据，如先前的出版物7,17,18所述，使用焦磷酸测序法验证了位于一个高甲基化蛋白质编码基因SKOR1和一个低甲基化长非编码核苷酸AC012065.7中的几个CpG位点（ 图3A和B ）。 图4显示剪切的DNA超声处理协议后。碎片DNA的范围在150到300 bp之间，使其成为测序目的的理想选择。 <img alt="图1" class="xfigimg" src="/files/ftp_upload/55773/55773fig1.jpg" /> 图1:本研究中使用的工作流程概述。从我们最近的出版物7获得的这一数字显示了用于鉴定慢性淋巴细胞性白血病（CLL）患者样品中差异甲基化区域（DMR）的整体分析的设计。 （ a ）基于甲基化DNA的MBD富集的实验设计。 （ b ）用于鉴定CLL特异性差异甲基化区域（cllDMR）的生物信息学分析流程。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55773/55773fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> 图2:与正常，健康，分类的B细胞相比，CLL患者样品的超甲基化和低甲基化cllDMR和cllDMG 7 。 （ a ）所有慢性淋巴细胞性白血病（CLL）相关的差异甲基化区域具有从比较IGHV突变和失活的CLL样品与正常分选的B细胞（上图）和正常PBMC样品获得的显着p值（&lt;0.00001） （下图）。热图中显示的浓缩物在差异甲基化区域（DMR）的±3-kb窗口内。 （ b ）Venn图显示IGHV突变和IGHV未突变组之间的CLL特异性差异甲基化基因（cllDMG，超甲基化和低甲基化）的重叠。饼图表示属于不同分类的基因的百分比，如蛋白质编码，长非编码RNA（lncRNA），假基因，反义和其他非编码RNA。 （ c ）Venn图显示了B细胞和PBMC比较中常见的差异甲基化基因（IGHV突变和IGHV未突变的预后组）的重叠。维恩图的左侧面板显示了超甲基化基因的重叠和低甲基化基因的右侧面板。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55773/55773fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图3" class="xfigimg" src="/files/ftp_upload/55773/55773fig3.jpg" /> 图3:确定所选显着差异甲基化靶基因上个别CpG位点的DNA甲基化状态。使用独立慢性淋巴细胞定量两个选定基因的DNA甲基化百分比的Pyrosquencing数据白血病（CLL）样本队列包含54个样本和6个正常，健康，年龄匹配的B细胞样品。 （ A ）箱形图表示使用焦磷酸测序的超甲基化SKOR1基因的3个个体CpG位点的甲基化水平百分比。 （ B ）箱形图显示了使用焦磷酸测序的5个个别CpG位点的低甲基化AC012065.7基因的甲基化程度。方框表示四分之一范围（25-75％），而内部水平线表示中值。晶须代表最小值和最大值。对应于CLL样品与正常B细胞​​差异甲基化程度的p值显示在每个CpG位点的箱体图中。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55773/55773fig3large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <imgalt ="图4"class ="xfigimg"src ="/ files / ftp_upload / 55773 / 55773fig4.jpg"/&gt; 图4:剪切基因组DNA。在超声处理后，四种慢性淋巴细胞（CLL）DNA样品的代表性结果以及超声（0分钟）之前的一个CLL样品在2％预制琼脂糖凝胶中进行，在UV光下染色和可视化。 DNA大小梯形图显示在1号线上。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55773/55773fig4large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>

Watch this Scientific Journal Video about Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients at JoVE.com

Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients

该工作描述了优化的甲基CpG结合结构域（MBD）测序方案和用于鉴定慢性淋巴细胞性白血病（CLL）患者中差异甲基化CpG富集区的计算管道。

在慢性淋巴细胞性白血病患者中使用甲基CpG结合域捕获法进行综合DNA甲基化分析

The role of long noncoding RNAs (lncRNAs) in cancer is coming to the forefront due to growing interest in understanding their mechanistic functions during ...

comprehensive-dna-methylation-analysis-using-methyl-cpg-binding

Nanyang Technological University

Research

JoVE Journal

Genetics

9.8K 次观看.  Gothenburg University. 该工作描述了优化的甲基CpG结合结构域（MBD）测序方案和用于鉴定慢性淋巴细胞性白血病（CLL）患者中差异甲基化CpG富集区的计算管道。 

视频: Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients

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

Immunostaining for DNA Modifications: Computational Analysis of Confocal Images

For several decades, 5-methylcytosine (5mC) has been thought to be the only DNA modification with a functional significance in metazoans. The discovery of enzymatic oxidation of 5mC to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC) as well as detection of N6-methyladenine (6mA) in the DNA of multicellular organisms provided additional degrees of complexity to the epigenetic research. According to a growing body of experimental evidence, these novel DNA modifications may play specific roles in different cellular and developmental processes. Importantly, as some of these marks (e. g. 5hmC, 5fC and 5caC) exhibit tissue- and developmental stage-specific occurrence in vertebrates, immunochemistry represents an important tool allowing assessment of spatial distribution of DNA modifications in different biological contexts. Here the methods for computational analysis of DNA modifications visualized by immunostaining followed by confocal microscopy are described. Specifically, the generation of 2.5 dimension (2.5D) signal intensity plots, signal intensity profiles, quantification of staining intensity in multiple cells and determination of signal colocalization coefficients are shown. Collectively, these techniques may be operational in evaluating the levels and localization of these DNA modifications in the nucleus, contributing to elucidating their biological roles in metazoans.

Newly discovered oxidized forms of 5-methylcytosine (oxi-mCs), 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC) may represent distinct DNA modifications with unique functional roles. Here a semi-quantitative workflow for visualization of oxi-mCs' spatial distribution, signal intensity profiling and colocalization is described.

DNA 修饰的免疫: 共焦图像的计算分析

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

LINE-1 Methylation Analysis in Mesenchymal Stem Cells Treated with Osteosarcoma-Derived Extracellular Vesicles

Methylation-specific probe amplification (MSPA) is a simple and robust technique that can be used to detect relative differences in methylation levels of DNA samples. It is resourceful, requires small amounts of DNA, and takes around 4&#8211;5 h of hands-on work. In the presented technique, DNA samples are first denatured then hybridized to probes that target DNA at either methylated or reference sites as a control. Hybridized DNA is separated into parallel reactions, one undergoing only ligation and the other undergoing ligation followed by HhaI-mediated digestion at unmethylated GCGC sequences. The resultant DNA fragments are amplified by PCR and separated by capillary electrophoresis. Methylated GCGC sites are not digested by HhaI and produce peak signals, while unmethylated GCGC sites are digested and no peak signals are generated. Comparing the control-normalized peaks of digested and undigested versions of each sample provides the methylation dosage ratio of a DNA sample. Here, MSPA is used to detect the effects of osteosarcoma-derived extracellular vesicles (EVs) on the methylation status of long interspersed nuclear element-1 (LINE-1) in mesenchymal stem cells. LINE-1s are repetitive DNA elements that typically undergo hypomethylation in cancer and, in this capacity, may serve as a biomarker. Ultracentrifugation is also used as a cost-effective method to separate extracellular vesicles from biological fluids (i.e., when preparing EV-depleted fetal bovine serum [FBS] and isolating EVs from osteosarcoma conditioned media [differential centrifugation]). For methylation analysis, custom LINE-1 probes are designed to target three methylation sites in the LINE-1 promoter sequence and seven control sites. This protocol demonstrates the use of MSPA for LINE-1 methylation analysis and describes the preparation of EV-depleted FBS by ultracentrifugation.

Described here is the use of a methylation-specific probe amplification method to analyze methylation levels of LINE-1 elements in mesenchymal stem cells treated with osteosarcoma-derived extracellular vesicles. Ultracentrifugation, a popular procedure for separating extracellular vesicles from fetal bovine serum, is also demonstrated.

用骨肉瘤衍生细胞外囊泡处理的美相干细胞中的LINE-1甲基化分析

Methylation-specific probe amplification (MSPA) is a simple and robust technique that can be used to detect relative differences in methylation levels of ...

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

DNA methylation is an important epigenetic change that is biologically meaningful and a frequent focus of cancer research. Genome-wide DNA methylation is a useful measure to provide an accurate analysis of the methylation status of gastrointestinal (GI) malignancies. Given the multiple potential translational uses of DNA methylation analysis, practicing clinicians and others new to DNA methylation studies need to be able to understand step by step how these genome-wide analyses are performed. The goal of this protocol is to provide a detailed description of how this method is used for the biomarker identification in GI malignancies. Importantly, we describe three critical steps that are needed to obtain accurate results during genome-wide analysis. Clearly and concisely written, these three methods are often lacking and not noticeable to those new to epigenetic studies. We used 48 samples of a GI malignancy (gastric cancer) to highlight practically how genome-wide DNA methylation analysis can be performed for GI malignancies.

Herein, we describe a procedure for genome-wide analysis of DNA methylation in gastrointestinal cancers. The procedure is of relevance to studies that investigate relationships between methylation patterns of genes and factors contributing to carcinogenesis in gastrointestinal cancers.

胃肠癌DNA甲基化基因组全谱分析

DNA methylation is an important epigenetic change that is biologically meaningful and a frequent focus of cancer research. Genome-wide DNA methylation is ...

癌症研究

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Obesity is directly connected to lifestyle and has been associated with DNA methylation changes that may cause alterations in the adipogenesis and lipid storage processes contributing to the development of the disease. We demonstrate a complete protocol from selection to epigenetic data analysis of patients with and without obesity. All steps from the protocol were tested and validated in a pilot study. 32 women participated in the study, in which 15 individuals were classified with obesity according to Body Mass Index (BMI) (45.1 &#177; 5.4 kg/m2); and 17 individuals were classified without obesity according to BMI (22.6 &#177; 1.8 kg/m2). In the group with obesity, 564 CpG sites related to fat mass were identified by linear regression analysis. The CpG sites were in the promoter regions. The differential analysis found 470 CpGs hypomethylated and 94 hypermethylated sites in individuals with obesity. The most hypomethylated enriched pathwayswere in the RUNX, WNT signaling, and response to hypoxia. The hypermethylated pathways were related to insulin secretion, glucagon signaling, and Ca2+. We conclude that the protocol effectively identified DNA methylation patterns and trait-related DNA methylation. These patterns could be associated with altered gene expression, affecting adipogenesis and lipid storage. Our results confirmed that an obesogenic lifestyle could promote epigenetic changes in human DNA.

The present study describes the workflow to manage DNA methylation data obtained by microarray technologies. The protocol demonstrates steps from sample preparation to data analysis. All procedures are described in detail, and the video shows the significant steps.

DNA甲基化生物信息学分析的样品制备:肥胖和相关性状研究的关联策略

Obesity is directly connected to lifestyle and has been associated with DNA methylation changes that may cause alterations in the adipogenesis and lipid ...

DNA Methylation: Bisulphite Modification and Analysis

Epigenetics describes the heritable changes in gene function that occur independently to the DNA sequence. The molecular basis of epigenetic gene regulation is complex, but essentially involves modifications to the DNA itself or the proteins with which DNA associates. The predominant epigenetic modification of DNA in mammalian genomes is methylation of cytosine nucleotides (5-MeC). DNA methylation provides instruction to gene expression machinery as to where and when the gene should be expressed. The primary target sequence for DNA methylation in mammals is 5'-CpG-3' dinucleotides (Figure 1). CpG dinucleotides are not uniformly distributed throughout the genome, but are concentrated in regions of repetitive genomic sequences and CpG "islands" commonly associated with gene promoters (Figure 1). DNA methylation patterns are established early in development, modulated during tissue specific differentiation and disrupted in many disease states including cancer. To understand the biological role of DNA methylation and its role in human disease, precise, efficient and reproducible methods are required to detect and quantify individual 5-MeCs.
This protocol for bisulphite conversion is the "gold standard" for DNA methylation analysis and facilitates identification and quantification of DNA methylation at single nucleotide resolution. The chemistry of cytosine deamination by sodium bisulphite involves three steps (Figure 2). (1) Sulphonation: The addition of bisulphite to the 5-6 double bond of cytosine (2) Hydrolic Deamination: hydrolytic deamination of the resulting cytosine-bisulphite derivative to give a uracil-bisulphite derivative (3) Alkali Desulphonation: Removal of the sulphonate group by an alkali treatment, to give uracil. Bisulphite preferentially deaminates cytosine to uracil in single stranded DNA, whereas 5-MeC, is refractory to bisulphite-mediated deamination. Upon PCR amplification, uracil is amplified as thymine while 5-MeC residues remain as cytosines, allowing methylated CpGs to be distinguished from unmethylated CpGs by presence of a cytosine "C" versus thymine "T" residue during sequencing.
DNA modification by bisulphite conversion is a well-established protocol that can be exploited for many methods of DNA methylation analysis. Since the detection of 5-MeC by bisulphite conversion was first demonstrated by Frommer et al.1 and Clark et al.2, methods based around bisulphite conversion of genomic DNA account for the majority of new data on DNA methylation. Different methods of post PCR analysis may be utilized, depending on the degree of specificity and resolution of methylation required. Cloning and sequencing is still the most readily available method that can give single nucleotide resolution for methylation across the DNA molecule.

The gold standard for DNA methylation analysis is genomic sequencing of bisulphite converted DNA. This method takes advantage of the increased sensitivity of cytosine compared with 5-methylcytosine (5-MeC) to bisulphite deamination under acidic conditions. Unmethylated cytosines can be distinguished from methylated cytosines after PCR amplification of the target genomic DNA.

DNA甲基化：亚硫酸氢修改和分析

Epigenetics describes the heritable changes in gene function that occur independently to the DNA sequence. The molecular basis of epigenetic gene ...

生物学

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

DNA methylation pattern mapping is heavily studied in normal and diseased tissues. A variety of methods have been established to interrogate the cytosine methylation patterns in cells. Reduced representation of whole genome bisulfite sequencing was developed to detect quantitative base pair resolution cytosine methylation patterns at GC-rich genomic loci. This is accomplished by combining the use of a restriction enzyme followed by bisulfite conversion. Enhanced Reduced Representation Bisulfite Sequencing (ERRBS) increases the biologically relevant genomic loci covered and has been used to profile cytosine methylation in DNA from human, mouse and other organisms. ERRBS initiates with restriction enzyme digestion of DNA to generate low molecular weight fragments for use in library preparation. These fragments are subjected to standard library construction for next generation sequencing. Bisulfite conversion of unmethylated cytosines prior to the final amplification step allows for quantitative base resolution of cytosine methylation levels in covered genomic loci. The protocol can be completed within four days. Despite low complexity in the first three bases sequenced, ERRBS libraries yield high quality data when using a designated sequencing control lane. Mapping and bioinformatics analysis is then performed and yields data that can be easily integrated with a variety of genome-wide platforms. ERRBS can utilize small input material quantities making it feasible to process human clinical samples and applicable in a range of research applications. The video produced demonstrates critical steps of the ERRBS protocol.

Enhanced Reduced Representation Bisulfite Sequencing is a method for the preparation of sequencing libraries for DNA methylation analysis based on restriction enzyme digestion combined with cytosine bisulfite conversion. This protocol requires 50 ng of starting material and yields base pair resolution data at GC-rich genomic regions.

增强的减少表示亚硫酸氢盐测序的DNA甲基化的评估，在碱基对决议

DNA methylation pattern mapping is heavily studied in normal and diseased tissues. A variety of methods have been established to interrogate the cytosine ...

Targeted DNA Methylation Analysis by Next-generation Sequencing

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

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

有针对性的DNA甲基化分析通过新一代测序

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

DNA Methylation Analysis

Methylation at CpG dinucleotides is a chemical modification of DNA hypothesized to play important roles in regulating gene expression. In particular, the methylation of clusters of methylation sites, called &#8220;CpG islands&#8221;, near promoters and other gene regulatory elements may contribute to the stable silencing of genes, for example, during epigenetic processes such as genomic imprinting and X-chromosome inactivation. At the same time, aberrant CpG methylation has been shown to be associated with cancer.In this video, the biological functions and mechanisms of DNA methylation will be presented, along with various techniques used to identify methylation sites in the genome. We will then examine the steps of bisulfite analysis, one of the most commonly used methods for detecting DNA methylation, as well as several applications of this technique.

DNA 甲基化分析

Methylation at CpG dinucleotides is a chemical modification of DNA hypothesized to play important roles in regulating gene expression. In particular, the ...

教育

JoVE Science Education

高级生物学

5-Methylcytosine Dot Blot to Determine the Extent of DNA Methylation

Source: Jia, Z. et al., <a href="https://app-jove-com.bdigitaluss.remotexs.co/v/55565">A 5-mC Dot Blot Assay Quantifying the DNA Methylation Level of Chondrocyte Dedifferentiation In Vitro.</a>&#160;J. Vis. Exp.&#160;(2017)
This video describes the technique of dot-blot to determine the level of DNA methylation in human chondrocytes in vitro via the blotting of DNA samples on a nylon membrane and the subsequent visualization using monoclonal antibodies. This helps to determine the chondrocytes&#39; phenotype at various stages in culture.