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Part 1: Document Description
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Citation |
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Title: |
NGS data related to Rajaram et al.: Development of super-specific epigenome editing by targeted allele-specific DNA methylation |
Identification Number: |
doi:10.18419/darus-3581 |
Distributor: |
DaRUS |
Date of Distribution: |
2023-11-21 |
Version: |
2 |
Bibliographic Citation: |
Jeltsch, Albert; Bashtrykov, Pavel; Rajaram, Nivethika, 2023, "NGS data related to Rajaram et al.: Development of super-specific epigenome editing by targeted allele-specific DNA methylation", https://doi.org/10.18419/darus-3581, DaRUS, V2 |
Citation |
|
Title: |
NGS data related to Rajaram et al.: Development of super-specific epigenome editing by targeted allele-specific DNA methylation |
Identification Number: |
doi:10.18419/darus-3581 |
Authoring Entity: |
Jeltsch, Albert (Universität Stuttgart) |
Bashtrykov, Pavel (Universität Stuttgart) |
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Rajaram, Nivethika (Universität Stuttgart) |
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Grant Number: |
AllEpi, ID09 |
Distributor: |
DaRUS |
Access Authority: |
Jeltsch, Albert |
Depositor: |
Jeltsch, Albert |
Date of Deposit: |
2023-06-27 |
Holdings Information: |
https://doi.org/10.18419/darus-3581 |
Study Scope |
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Keywords: |
Medicine, Health and Life Sciences, DNA Methylation, DNA methyltransferase, Epigenome editing, Allele, Gene expression |
Topic Classification: |
General Genetics and Functional Genome Biology |
Abstract: |
<b>Method overview </b><br> To achieve targeted ASM, transient transfection of the dCas9-10X SunTag-BFP, scFv-DNMT3A-3L-sfGFP, and sgRNA-DsRed plasmids was performed in HEK293 cells. Control experiments were conducted with a scrambled sgRNA that does not have a binding site in the human genome. Initial studies showed that cells positive for all three plasmids exhibited highest fluorescence of the corresponding reporter proteins on day 3 post-transfection. Hence FACS sorting was conducted at this time point. Genomic DNA was isolated from the FACS-sorted cells at day 3 after transfection and subjected to bisulfite treatment. Library preparation was performed using the bisulfite-converted samples, followed by NGS and data analysis. Most methylation experiments were conducted in three independent biological replicates.<br> <b>Method details </b><br> Genomic DNA was extracted using QIAmp DNA Mini Kit (Qiagen). 500 ng of genomic DNA was subjected to overnight digestion with EcoRV which is not cutting in any of the target amplicons. Zymo EZ DNA Methylation-Lightning Kit (D5030-E) was used for bisulfite conversion. The library for NGS was prepared by two consecutive PCR reactions (Leitao et al, 2018). Firstly, bisulfite converted genomic DNA of each sample was amplified with target gene specific primers. The gene specific optimized amount of a product from the first PCR was used as a template for the second PCR to add the Illumina TruSeq sequencing adapters. Final products were quantified, pooled in equimolar amounts and purified using SPRIselect beads (Beckman Coulter). Ready-to-use pools of libraries were sequenced on NovaSeq 6000 using a PE250 flow cell (Novogene). NGS data were obtained in the form of FASTQ files.<br> <b>Data analysis </b><br> FASTQ files were processed on the local instance of Galaxy server as described earlier (Bashtrykov & Jeltsch, 2018) with some modifications. Briefly, an adaptor and low-quality trimming was conducted using Trim Galore! (developed by Felix Krueger at the Babraham Institute). The two associated paired reads were merged using PEAR (Zhang et al, 2014). Experiment specific combinations of Illumina indices and barcodes were used to extract reads for the individual experiments from the pool of reads. This information is provided in the included Excel file. Reads corresponding to different alleles of the same target gene were identified based on the presence of the SNP. Two files of reads corresponding to alleles were generated and their methylation level was analyzed independently. First, reads were mapped against a reference sequence of the target region using bwameth (Pedersen et al, 2014) and then methylation of individual CpG sites was computed using MethylDackel (https://github.com/dpryan79/MethylDackel). Final visualization and statistics were prepared using Microsoft Excel.<br> <b>References </b><br> <li>Bashtrykov P, Jeltsch A (2018). DNA Methylation Analysis by Bisulfite Conversion Coupled to Double Multiplexed Amplicon-Based Next-Generation Sequencing (NGS). Methods Mol Biol 1767: 367-382 <li>Leitao E, Beygo J, Zeschnigk M, Klein-Hitpass L, Bargull M, Rahmann S, Horsthemke B (2018). Locus-Specific DNA Methylation Analysis by Targeted Deep Bisulfite Sequencing. Methods Mol Biol 1767: 351-366 <li>Pedersen JS, Valen E, Velazquez AM, Parker BJ, Rasmussen M, Lindgreen S, et al., Orlando L (2014). Genome-wide nucleosome map and cytosine methylation levels of an ancient human genome. Genome Res 24: 454-466 <li>Zhang J, Kobert K, Flouri T, Stamatakis A (2014). PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30: 614-620 |
Kind of Data: |
Raw DNA sequences provided as Fastq NGS files after bisulfite conversion of genomic DNA |
Notes: |
<a href="https://pubmed.ncbi.nlm.nih.gov/37864244/">PMID: 37864244</a> |
Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Title: |
Rajaram N, Kouroukli AG, Bens S, Bashtrykov P, Jeltsch A. (2023) Development of super-specific epigenome editing by targeted allele-specific DNA methylation. Epigenetics & Chromatin 16, 41. |
Identification Number: |
10.1186/s13072-023-00515-5 |
Bibliographic Citation: |
Rajaram N, Kouroukli AG, Bens S, Bashtrykov P, Jeltsch A. (2023) Development of super-specific epigenome editing by targeted allele-specific DNA methylation. Epigenetics & Chromatin 16, 41. |
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Information about connections of experiments and sequencing data |
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