NGS data related to Adam et al.: On the accuracy of the epigenetic copy machine - comprehensive specificity analysis of the DNMT1 DNA methyltransferase

Expression and purification of DNMT1 for biochemical work Full length murine DNMT1 (UniProtKB P13864) was overexpressed and purified as described (Adam, et al. 2020) using the Bac-to-Bac baculovirus expression system (Invitrogen). The expression construct of the DNMT1 with mutated CXXC domain was taken from Bashtrykov, et al. (2012). Synthesis long DNA substrate and methylation reactions with them The sequence of the 349 bp substrate with 44 CpG sites was taken from Adam et al. 2020. It was used in unmethylated and hemimethylated form. Generation of the substrates and the methylation reaction were conducted as described (Adam, et al. 2020). In brief, for the generation of hemimethylated substrates, the unmethylated DNA was methylated in vitro by M.SssI (purified as described in Adam, et al. 2020) to introduce methylation at all CpG sites, or by M.HhaI (NEB) together with M.MspI (NEB) to introduce methylation at GCGC and CCGG sites. For the synthesis of hemimethylated substrates, the upper strand of the methylated substrate was digested with lambda exonuclease, the ss-DNA purified and finally ds hemimethylated DNA was generated by by primer extension using Phusion® HF DNA Polymerase (Thermo). Methylation reaction were conducted using mixtures of UM, fully hemimethylated and patterned substrate (total DNA concentration 200 ng in 20 µL) in methylation buffer (100 mM HEPES, 1 mM EDTA, 0.5 mM DTT, 0.1 mg mL-1 BSA, pH 7.2 with KOH) containing 1 mM AdoMet. DNMT1 concentrations and incubation times are indicated in the text. Methylation was followed by bisulfite conversion using the EZ DNA Methylation-LightningTM Kit (ZYMO RESEARCH) followed by library generation and Illumina paired-end sequencing (Novogene). Flanking sequence preference analysis with randomized single-site substrates Methylation reactions of the randomized substrate with DNMT1 were performed similarly as described (Adam, et al. 2020; Gao, et al. 2020). Briefly, single-stranded oligonucleotides containing a methylated, hydroxymethylated or unmethylated CpG site embedded in a 10 nucleotide random context were obtained from IDT and used for generation of 67 bps long double-stranded DNA substrates by primer extension. Pools of these randomized substrates were then mixed in different combination, methylated by DNMT1 in methylation buffer (100 mM HEPES, 1 mM EDTA, 0.5 mM DTT, 0.1 mg mL-1 BSA, pH 7.2 with KOH) containing 1 mM AdoMet. DNMT1 concentrations and incubation times are indicated in the text. Methylation was followed by bisulfite conversion using the EZ DNA Methylation-LightningTM Kit (ZYMO RESEARCH) followed by library generation and Illumina paired-end sequencing (Novogene). Bioinformatics analysis NGS data sets were bioinformatically analyzed using a local instance of the Galaxy server as described (Adam, et al. 2020; Dukatz, et al. 2020; Dukatz, et al. 2022). In brief, for the long substrate, reads were trimmed, filtered by quality, mapped against the reference sequence and demultiplexed using substrate type and experiment specific barcodes. Afterwards, methylation information was assigned and retrieved by home-made skripts. For the randomized substrate, reads were trimmed and filtered according to the expected DNA size. The original DNA sequence was then reconstituted based on the bisulfite converted upper and lower strands to investigate the average methylation state of both CpG sites and the NNCGNN flanks using home-made skripts. Methylation rates of 256 NNCGNN sequence contexts in the competitive methylation experiments with the mixed single-site substrates were determined by fitting to monoexponential reaction progress curves with variable time points with MatLab skripts as described (Adam, et al. 2022). Pearson correlation factors were calculated with Excel using the correl function. Structure of the deposited data Methylation data of long substrates are placed in the “long DNA substrates” folder. Methylation data of short single-site substrates with randomized flanks are placed in the “single sites substrates” folder. In both folder an explanatory pdf file gives further information. Subfolders are arranged by enzyme (CXXC mutant or DNMT1 WT). Then, for each enzyme, the different substrates or substrate mixtures are provided in separate subfolders. References Adam S, Bräcker J, Klingel V, Osteresch B, Radde NE, Brockmeyer J, Bashtrykov P, Jeltsch A. Flanking sequences influence the activity of TET1 and TET2 methylcytosine dioxygenases and affect genomic 5hmC patterns. Communications Biology 5, 92 (2022) Adam S, Anteneh H, Hornisch M, Wagner V, Lu J, Radde NE, Bashtrykov P, Song J, Jeltsch A. DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation. Nature Commun 11, 3723 (2020) Bashtrykov P, et al. Specificity of Dnmt1 for methylation of hemimethylated CpG sites resides in its catalytic domain. Chem Biol 19, 572-578 (2012) Dukatz M, Dittrich M, Stahl E, Adam S, de Mendoza A,...

表达与纯化DNMT1用于生化研究 全长小鼠DNMT1（UniProtKB P13864）通过Bac-to-Bac杆状病毒表达系统（Invitrogen）进行过表达和纯化，具体方法如Adam等（2020年）所述。DNMT1中突变CXXC结构域的表达构建体来自Bashtrykov等（2012年）。以之合成长DNA底物及其甲基化反应 349碱基的底物序列包含44个CpG位点，源自Adam等（2020年）。该底物以未甲基化和半甲基化形式使用。底物合成及其甲基化反应的实施方法详见Adam等（2020年）所述。简而言之，为生成半甲基化底物，未甲基化的DNA通过M.SssI（如Adam等（2020年）所述进行纯化）在所有CpG位点引入甲基化，或通过M.HhaI（NEB）与M.MspI（NEB）共同作用在GCGC和CCGG位点引入甲基化。为合成半甲基化底物，甲基化底物的上游链用λ外切酶消化，单链DNA纯化后，通过引物延伸使用Phusion® HF DNA聚合酶（Thermo）生成双链半甲基化DNA。甲基化反应使用UM、全半甲基化和模式底物混合物（总DNA浓度为200 ng，在20 µL中）在甲基化缓冲液（100 mM HEPES，1 mM EDTA，0.5 mM DTT，0.1 mg mL-1 BSA，pH 7.2，用KOH调节）中进行，含有1 mM AdoMet。DNMT1浓度和孵育时间在文中指出。甲基化后，使用EZ DNA Methylation-LightningTM试剂盒（ZYMO RESEARCH）进行亚硫酸氢盐转化，随后进行文库构建和Illumina双端测序（Novogene）。以随机单位点底物进行侧翼序列偏好性分析 DNMT1与随机底物的甲基化反应实施方法与Adam等（2020年）；Gao等（2020年）所述类似。简言之，含有嵌入10核苷酸随机背景中的甲基化、羟甲基化或未甲基化CpG位点的单链寡核苷酸从IDT获得，通过引物延伸生成67碱基长的双链DNA底物。这些随机底物的混合物以不同的组合混合，在含1 mM AdoMet的甲基化缓冲液（100 mM HEPES，1 mM EDTA，0.5 mM DTT，0.1 mg mL-1 BSA，pH 7.2，用KOH调节）中由DNMT1甲基化。DNMT1浓度和孵育时间在文中指出。甲基化后，使用EZ DNA Methylation-LightningTM试剂盒（ZYMO RESEARCH）进行亚硫酸氢盐转化，随后进行文库构建和Illumina双端测序（Novogene）。生物信息学分析 NGS数据集使用Galaxy服务器的本地实例进行生物信息学分析，方法如Adam等（2020年）；Dukatz等（2020年）；Dukatz等（2022年）所述。简而言之，对于长底物，读取数据经过修剪、按质量过滤、针对参考序列进行映射并使用底物类型和实验特异性条形码进行去分组。之后，通过自定义脚本分配和检索甲基化信息。对于随机底物，读取数据经过修剪和按预期的DNA大小进行过滤。然后，基于亚硫酸氢盐转化的上、下游链重建原始DNA序列，使用自定义脚本来研究两个CpG位点和NNCGNN侧翼的平均甲基化状态。在混合单位点底物的竞争甲基化实验中，256个NNCGNN序列背景的甲基化率通过使用MatLab脚本拟合具有可变时间点的单指数反应进度曲线进行确定，如Adam等（2022年）所述。使用Excel的correl函数计算Pearson相关系数。存档数据结构 长底物的甲基化数据放置在“长DNA底物”文件夹中。短单位点底物（随机侧翼）的甲基化数据放置在“单位点底物”文件夹中。在两个文件夹中，均提供了一个解释性pdf文件提供更多信息。子文件夹按酶（CXXC突变体或DNMT1 WT）分类。然后，对于每种酶，不同的底物或底物混合物分别放置在单独的子文件夹中。参考文献 Adam S, Bräcker J, Klingel V, Osteresch B, Radde NE, Brockmeyer J, Bashtrykov P, Jeltsch A. Flanking sequences influence the activity of TET1 and TET2 methylcytosine dioxygenases and affect genomic 5hmC patterns. Communications Biology 5, 92 (2022) Adam S, Anteneh H, Hornisch M, Wagner V, Lu J, Radde NE, Bashtrykov P, Song J, Jeltsch A. DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation. Nature Commun 11, 3723 (2020) Bashtrykov P, et al. Specificity of Dnmt1 for methylation of hemimethylated CpG sites resides in its catalytic domain. Chem Biol 19, 572-578 (2012) Dukatz M, Dittrich M, Stahl E, Adam S, de Mendoza A, et al. ...