Mouse methylome studies SRP371845 Track Settings
 
Raw WGBS reads of mice zygotes [Oocyte, Sperm, Zygotes From The Control, zygotes from the Tet1, zygotes from the Tet2]

Track collection: Mouse methylome studies

+  All tracks in this collection (604)

Maximum display mode:       Reset to defaults   
Select views (Help):
AMR       CpG reads ▾       CpG methylation ▾       PMD       HMR      
Select subtracks by views and experiment:
 All views AMR  CpG reads  CpG methylation  PMD  HMR 
experiment
SRX14978860 
SRX14978861 
SRX14978862 
SRX14978863 
SRX14978864 
List subtracks: only selected/visible    all    ()
  experiment↓1 views↓2   Track Name↓3  
hide
 SRX14978860  AMR  Sperm / SRX14978860 (AMR)   Schema 
hide
 Configure
 SRX14978860  CpG reads  Sperm / SRX14978860 (CpG reads)   Schema 
hide
 Configure
 SRX14978860  CpG methylation  Sperm / SRX14978860 (CpG methylation)   Schema 
hide
 SRX14978860  PMD  Sperm / SRX14978860 (PMD)   Schema 
hide
 SRX14978860  HMR  Sperm / SRX14978860 (HMR)   Schema 
hide
 SRX14978861  AMR  Oocyte / SRX14978861 (AMR)   Schema 
hide
 Configure
 SRX14978861  CpG methylation  Oocyte / SRX14978861 (CpG methylation)   Schema 
hide
 SRX14978861  PMD  Oocyte / SRX14978861 (PMD)   Schema 
hide
 Configure
 SRX14978861  CpG reads  Oocyte / SRX14978861 (CpG reads)   Schema 
hide
 SRX14978862  AMR  Zygotes From The Control / SRX14978862 (AMR)   Schema 
hide
 Configure
 SRX14978862  CpG reads  Zygotes From The Control / SRX14978862 (CpG reads)   Schema 
hide
 Configure
 SRX14978862  CpG methylation  Zygotes From The Control / SRX14978862 (CpG methylation)   Schema 
hide
 SRX14978862  PMD  Zygotes From The Control / SRX14978862 (PMD)   Schema 
hide
 SRX14978863  AMR  zygotes from the Tet1 / SRX14978863 (AMR)   Schema 
hide
 Configure
 SRX14978863  CpG reads  zygotes from the Tet1 / SRX14978863 (CpG reads)   Schema 
hide
 Configure
 SRX14978863  CpG methylation  zygotes from the Tet1 / SRX14978863 (CpG methylation)   Schema 
hide
 SRX14978863  PMD  zygotes from the Tet1 / SRX14978863 (PMD)   Schema 
hide
 SRX14978864  AMR  zygotes from the Tet2 / SRX14978864 (AMR)   Schema 
hide
 Configure
 SRX14978864  CpG reads  zygotes from the Tet2 / SRX14978864 (CpG reads)   Schema 
hide
 Configure
 SRX14978864  CpG methylation  zygotes from the Tet2 / SRX14978864 (CpG methylation)   Schema 
hide
 SRX14978864  PMD  zygotes from the Tet2 / SRX14978864 (PMD)   Schema 
    

Study title: Raw WGBS reads of mice zygotes
SRA: SRP371845
GEO: not found
Pubmed: not found

Experiment Label Methylation Coverage HMRs HMR size AMRs AMR size PMDs PMD size Conversion Details
SRX14978860 Sperm 0.691 5.3 62081 1530.5 330 837.0 1050 172225.5 0.989 title: WGBS of Mus musculus, DBA/2J; {"strain": "DAB/2J", "age": "4-6week", "dev_stage": "MI", "sex": "male", "tissue": "sperm"}
SRX14978861 Oocyte 0.390 2.2 6043 40952.0 34 1405.4 2745 393258.7 0.929 title: WGBS of Mus musculus, C57BL/6J; {"strain": "C57BL/6J", "age": "4-6week", "dev_stage": "MII", "sex": "female", "tissue": "oocyte"}
SRX14978862 Zygotes From The Control 0.451 4.5 6308 39849.1 2015 927.6 135 1047487.7 0.963 title: WGBS of Mus musculus, C57BL/6J; {"strain": "C57BL/6J", "age": "4-6week", "dev_stage": "pronucleus stage", "sex": "female", "tissue": "zygotes from the control"}
SRX14978863 zygotes from the Tet1 0.424 4.7 10786 17002.5 1788 893.0 620 413827.7 0.968 title: WGBS of Mus musculus, C57BL/6J; {"strain": "C57BL/6J", "age": "4-6week", "dev_stage": "pronucleus stage", "sex": "female", "tissue": "zygotes from the Tet1"}
SRX14978864 zygotes from the Tet2 0.259 4.0 0 0.0 334 855.6 1 95620500.0 0.969 title: WGBS of Mus musculus, C57BL/6J; {"strain": "C57BL/6J", "age": "4-6week", "dev_stage": "pronucleus stage", "sex": "female", "tissue": "zygotes from the Tet2"}

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.