Mouse methylome studies SRP474397 Track Settings
 
De novo Assembly and Delivery of Synthetic Megabase-Scale Human DNA into Mouse Early Embryos [Early Embryo]

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Study title: De novo Assembly and Delivery of Synthetic Megabase-Scale Human DNA into Mouse Early Embryos
SRA: SRP474397
GEO: not found
Pubmed: not found

Experiment Label Methylation Coverage HMRs HMR size AMRs AMR size PMDs PMD size Conversion Details
SRX22649080 Early Embryo 0.311 5.8 16848 36420.3 3795 977.2 5384 210527.4 0.945 title: scWGBS of mouse 1-cell embryo1; {"strain": "C57", "dev_stage": "mouse 1cell embryo", "collection_date": "2022-09-18", "geo_loc_name": "China:Tianjin", "sex": "not determined", "tissue": "early embryo"}
SRX22649081 Early Embryo 0.312 6.3 17806 36034.8 5420 1050.0 6139 189548.2 0.945 title: scWGBS of mouse 1-cell embryo2; {"strain": "C57", "dev_stage": "mouse 1cell embryo", "collection_date": "2022-09-19", "geo_loc_name": "China:Tianjin", "sex": "not determined", "tissue": "early embryo"}
SRX22649082 Early Embryo 0.314 7.1 24448 31477.3 3312 950.9 7315 172317.6 0.949 title: scWGBS of mouse 1-cell embryo3; {"strain": "C57", "dev_stage": "mouse 1cell embryo", "collection_date": "2022-09-20", "geo_loc_name": "China:Tianjin", "sex": "not determined", "tissue": "early embryo"}
SRX28353993 Early Embryo 0.371 3.7 15212 37296.8 294 902.5 4725 213186.1 0.948 title: scWGBS of mouse 2-cell embryo1; {"strain": "C57", "dev_stage": "mouse 2cell embryo", "collection_date": "2022-10-17", "geo_loc_name": "China:Tianjin", "sex": "not determined", "tissue": "early embryo"}
SRX28353994 Early Embryo 0.349 7.1 34879 25462.7 1352 948.9 7643 149661.0 0.958 title: scWGBS of mouse 2-cell embryo2; {"strain": "C57", "dev_stage": "mouse 2cell embryo", "collection_date": "2022-10-18", "geo_loc_name": "China:Tianjin", "sex": "not determined", "tissue": "early embryo"}
SRX28353995 Early Embryo 0.377 3.5 14815 37286.0 286 925.7 4781 212332.2 0.943 title: scWGBS of mouse 2-cell embryo3; {"strain": "C57", "dev_stage": "mouse 2cell embryo", "collection_date": "2022-10-19", "geo_loc_name": "China:Tianjin", "sex": "not determined", "tissue": "early embryo"}
SRX28353996 Early Embryo 0.373 4.0 19574 32696.5 261 1009.7 5259 200037.5 0.973 title: scWGBS of mouse 4-cell embryo1; {"strain": "C57", "dev_stage": "mouse 4cell embryo", "collection_date": "2022-10-23", "geo_loc_name": "China:Tianjin", "sex": "not determined", "tissue": "early embryo"}
SRX28353997 Early Embryo 0.368 8.4 43874 22538.2 1235 1353.2 8747 136648.9 0.976 title: scWGBS of mouse 4-cell embryo2; {"strain": "C57", "dev_stage": "mouse 4cell embryo", "collection_date": "2022-10-24", "geo_loc_name": "China:Tianjin", "sex": "not determined", "tissue": "early embryo"}

Methods

All analysis was done using a bisulfite sequnecing data analysis pipeline DNMTools developed in the Smith lab at USC.

Mapping reads from bisulfite sequencing: Bisulfite treated reads are mapped to the genomes with the abismal program. Input reads are filtered by their quality, and adapter sequences in the 3' end of reads are trimmed. This is done with cutadapt. Uniquely mapped reads with mismatches/indels below given threshold are retained. For pair-end reads, if the two mates overlap, the overlapping part of the mate with lower quality is discarded. After mapping, we use the format command in dnmtools to merge mates for paired-end reads. We use the dnmtools uniq command to randomly select one from multiple reads mapped exactly to the same location. Without random oligos as UMIs, this is our best indication of PCR duplicates.

Estimating methylation levels: After reads are mapped and filtered, the dnmtools counts command is used to obtain read coverage and estimate methylation levels at individual cytosine sites. We count the number of methylated reads (those containing a C) and the number of unmethylated reads (those containing a T) at each nucleotide in a mapped read that corresponds to a cytosine in the reference genome. The methylation level of that cytosine is estimated as the ratio of methylated to total reads covering that cytosine. For cytosines in the symmetric CpG sequence context, reads from the both strands are collapsed to give a single estimate. Very rarely do the levels differ between strands (typically only if there has been a substitution, as in a somatic mutation), and this approach gives a better estimate.

Bisulfite conversion rate: The bisulfite conversion rate for an experiment is estimated with the dnmtools bsrate command, which computes the fraction of successfully converted nucleotides in reads (those read out as Ts) among all nucleotides in the reads mapped that map over cytosines in the reference genome. This is done either using a spike-in (e.g., lambda), the mitochondrial DNA, or the nuclear genome. In the latter case, only non-CpG sites are used. While this latter approach can be impacted by non-CpG cytosine methylation, in practice it never amounts to much.

Identifying hypomethylated regions (HMRs): In most mammalian cells, the majority of the genome has high methylation, and regions of low methylation are typically the interesting features. (This seems to be true for essentially all healthy differentiated cell types, but not cells of very early embryogenesis, various germ cells and precursors, and placental lineage cells.) These are valleys of low methylation are called hypomethylated regions (HMR) for historical reasons. To identify the HMRs, we use the dnmtools hmr command, which uses a statistical model that accounts for both the methylation level fluctations and the varying amounts of data available at each CpG site.

Partially methylated domains: Partially methylated domains are large genomic regions showing partial methylation observed in immortalized cell lines and cancerous cells. The pmd program is used to identify PMDs.

Allele-specific methylation: Allele-Specific methylated regions refers to regions where the parental allele is differentially methylated compared to the maternal allele. The program allelic is used to compute allele-specific methylation score can be computed for each CpG site by testing the linkage between methylation status of adjacent reads, and the program amrfinder is used to identify regions with allele-specific methylation.

For more detailed description of the methods of each step, please refer to the DNMTools documentation.