Mouse methylome studies SRP564359 Track Settings
 
PKM2 mediated mitochondrial reprogramming supports enhanced effector functions in CD8 T cells increasing the anti-tumor efficacy of anti-PD1 therapy [WGBS] [C57BL/6J OT1 mice]

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 SRX27703760  AMR  C57BL/6J OT1 mice / SRX27703760 (AMR)   Schema 
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 SRX27703760  CpG methylation  C57BL/6J OT1 mice / SRX27703760 (CpG methylation)   Schema 
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 SRX27703760  PMD  C57BL/6J OT1 mice / SRX27703760 (PMD)   Schema 
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 SRX27703760  CpG reads  C57BL/6J OT1 mice / SRX27703760 (CpG reads)   Schema 
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 SRX27703761  AMR  C57BL/6J OT1 mice / SRX27703761 (AMR)   Schema 
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 SRX27703761  CpG reads  C57BL/6J OT1 mice / SRX27703761 (CpG reads)   Schema 
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 SRX27703761  CpG methylation  C57BL/6J OT1 mice / SRX27703761 (CpG methylation)   Schema 
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 SRX27703761  PMD  C57BL/6J OT1 mice / SRX27703761 (PMD)   Schema 
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 SRX27703761  HMR  C57BL/6J OT1 mice / SRX27703761 (HMR)   Schema 
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 SRX27703762  AMR  C57BL/6J OT1 mice / SRX27703762 (AMR)   Schema 
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 SRX27703762  CpG reads  C57BL/6J OT1 mice / SRX27703762 (CpG reads)   Schema 
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 SRX27703762  CpG methylation  C57BL/6J OT1 mice / SRX27703762 (CpG methylation)   Schema 
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 SRX27703762  PMD  C57BL/6J OT1 mice / SRX27703762 (PMD)   Schema 
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 SRX27703762  HMR  C57BL/6J OT1 mice / SRX27703762 (HMR)   Schema 
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 SRX27703763  AMR  C57BL/6J OT1 mice / SRX27703763 (AMR)   Schema 
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 SRX27703763  HMR  C57BL/6J OT1 mice / SRX27703763 (HMR)   Schema 
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 SRX27703763  CpG reads  C57BL/6J OT1 mice / SRX27703763 (CpG reads)   Schema 
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 SRX27703763  CpG methylation  C57BL/6J OT1 mice / SRX27703763 (CpG methylation)   Schema 
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 SRX27703763  PMD  C57BL/6J OT1 mice / SRX27703763 (PMD)   Schema 
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 SRX27703764  AMR  C57BL/6J OT1 mice / SRX27703764 (AMR)   Schema 
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 SRX27703764  CpG reads  C57BL/6J OT1 mice / SRX27703764 (CpG reads)   Schema 
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 SRX27703764  CpG methylation  C57BL/6J OT1 mice / SRX27703764 (CpG methylation)   Schema 
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 SRX27703764  PMD  C57BL/6J OT1 mice / SRX27703764 (PMD)   Schema 
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 SRX27703764  HMR  C57BL/6J OT1 mice / SRX27703764 (HMR)   Schema 
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 SRX27703765  AMR  C57BL/6J OT1 mice / SRX27703765 (AMR)   Schema 
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 SRX27703765  CpG reads  C57BL/6J OT1 mice / SRX27703765 (CpG reads)   Schema 
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 SRX27703765  CpG methylation  C57BL/6J OT1 mice / SRX27703765 (CpG methylation)   Schema 
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 SRX27703765  PMD  C57BL/6J OT1 mice / SRX27703765 (PMD)   Schema 
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 SRX27703765  HMR  C57BL/6J OT1 mice / SRX27703765 (HMR)   Schema 
    

Study title: PKM2 mediated mitochondrial reprogramming supports enhanced effector functions in CD8 T cells increasing the anti-tumor efficacy of anti-PD1 therapy [WGBS]
SRA: SRP564359
GEO: not found
Pubmed: not found

Experiment Label Methylation Coverage HMRs HMR size AMRs AMR size PMDs PMD size Conversion Details
SRX27703760 C57BL/6J OT1 mice 0.785 28.9 57716 986.0 1013 1059.4 3048 8182.3 0.979 title: GSM8798277 CD8 T cells activated with Ova peptide (0.5 μM) replicate 1, Mus musculus, Bisulfite-Seq; {"source_name": "C57BL/6J OT1 mice", "tissue": "C57BL/6J OT1 mice", "cell_type": "CD8 T cells", "geo_loc_name": "missing", "collection_date": "missing"}
SRX27703761 C57BL/6J OT1 mice 0.779 27.6 57532 983.5 996 1050.6 3031 8197.5 0.979 title: GSM8798278 CD8 T cells activated with Ova peptide (0.5 μM) replicate 2, Mus musculus, Bisulfite-Seq; {"source_name": "C57BL/6J OT1 mice", "tissue": "C57BL/6J OT1 mice", "cell_type": "CD8 T cells", "geo_loc_name": "missing", "collection_date": "missing"}
SRX27703762 C57BL/6J OT1 mice 0.778 23.2 56078 990.4 933 1053.2 3168 7876.6 0.979 title: GSM8798279 CD8 T cells activated with Ova peptide (0.5 μM) replicate 3, Mus musculus, Bisulfite-Seq; {"source_name": "C57BL/6J OT1 mice", "tissue": "C57BL/6J OT1 mice", "cell_type": "CD8 T cells", "geo_loc_name": "missing", "collection_date": "missing"}
SRX27703763 C57BL/6J OT1 mice 0.786 28.8 58194 986.7 1029 1069.2 3493 7792.7 0.978 title: GSM8798280 CD8 T cells activated with Ova peptide (0.5 μM) in combination with TEPP46 replicate 1, Mus musculus, Bisulfite-Seq; {"source_name": "C57BL/6J OT1 mice", "tissue": "C57BL/6J OT1 mice", "cell_type": "CD8 T cells", "geo_loc_name": "missing", "collection_date": "missing"}
SRX27703764 C57BL/6J OT1 mice 0.788 38.7 59884 989.4 1084 1067.2 3081 8730.9 0.979 title: GSM8798281 CD8 T cells activated with Ova peptide (0.5 μM) in combination with TEPP46 replicate 2, Mus musculus, Bisulfite-Seq; {"source_name": "C57BL/6J OT1 mice", "tissue": "C57BL/6J OT1 mice", "cell_type": "CD8 T cells", "geo_loc_name": "missing", "collection_date": "missing"}
SRX27703765 C57BL/6J OT1 mice 0.788 30.8 58923 983.9 1013 1082.1 3377 8094.6 0.979 title: GSM8798282 CD8 T cells activated with Ova peptide (0.5 μM) in combination with TEPP46 replicate 3, Mus musculus, Bisulfite-Seq; {"source_name": "C57BL/6J OT1 mice", "tissue": "C57BL/6J OT1 mice", "cell_type": "CD8 T cells", "geo_loc_name": "missing", "collection_date": "missing"}

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.