Differential Methylation

Introduction: Differential Methylation of Sample Groups

Differential methylation analysis was conducted on site and region level according to the sample groups specified in the analysis.

Comparisons

The following comparisons were made:

The table below summarizes information on the comparisons.

comparison adjustment covariateTable
1 mono vs. neut (based on cmp_ct_mono_vs_neut) tissueTypeShort,DONOR_SEX csv
2 mono vs. neut (based on cmp_ct_mono_vs_neut_VB) DONOR_SEX csv
3 Mf vs. mono (based on cmp_ct_mono_vs_mf) tissueTypeShort,DONOR_SEX csv
4 Mf vs. mono (based on cmp_ct_mono_vs_mf_VB) DONOR_SEX csv
5 EM vs. TN (based on cmp_ct_TCD4_TN_vs_CM) DONOR_SEX csv
6 EM vs. TN (based on cmp_ct_TCD4_TN_vs_EM) DONOR_SEX csv
7 CM vs. EM (based on cmp_ct_TCD4_CM_vs_EM) DONOR_SEX csv
8 EM vs. TN (based on cmp_ct_TCD8_TN_vs_CM) tissueTypeShort,DONOR_SEX csv
9 EM vs. TN (based on cmp_ct_TCD8_TN_vs_EM) tissueTypeShort,DONOR_SEX csv
10 CM vs. EM (based on cmp_ct_TCD8_CM_vs_EM) DONOR_SEX csv
11 meta vs. myel (based on cmp_ct_neut_myel_vs_meta) DONOR_SEX csv
12 band vs. meta (based on cmp_ct_neut_meta_vs_band) DONOR_SEX csv
13 band vs. segm (based on cmp_ct_neut_band_vs_segm) DONOR_SEX csv
14 early vs. mature (based on cmp_ct_neut_early_vs_mature) tissueTypeShort,DONOR_SEX csv

P-values

In the following anlyses, p-values on the site level were computed using the limma method. I.e. hierarchical linear models from the limma package were employed and fitted using an empirical Bayes approach on derived M-values.

Region Level

Differential methylation on the region level was computed based on a variety of metrics. Of particular interest for the following plots and analyses are the following quantities for each region: the mean methylation difference in a region of the two groups being and of quotient of mean methylation levelsas well as a p-value obtained from statistical testing (limma or t-test; depending on parameter settings). Additionally each region was assigned a rank based on each of these three criteria. A combined rank is computed as the maximum (i.e. worst) value among the three ranks. The smaller the combined rank for a region, the more evidence for differential methylation it exhibits. Regions were defined based on the region types specified in the analysis. This section includes scatterplots of the region group means as well as volcano plots of each pairwise comparison colored according to the combined rank of a given region.

The following rank cutfoffs have been automatically selected for the analysis of differentially methylated regions:

cpgislands genes promoters tiling1kb gencode22promoters ensembleRegBuildBPall
mono vs. neut (based on cmp_ct_mono_vs_neut) 0 0 0 0 0 0
mono vs. neut (based on cmp_ct_mono_vs_neut_VB) 0 0 0 0 0 0
Mf vs. mono (based on cmp_ct_mono_vs_mf) 0 0 0 0 0 0
Mf vs. mono (based on cmp_ct_mono_vs_mf_VB) 0 0 0 0 0 0
EM vs. TN (based on cmp_ct_TCD4_TN_vs_CM) 0 0 0 0 0 0
EM vs. TN (based on cmp_ct_TCD4_TN_vs_EM) 0 0 0 0 0 0
CM vs. EM (based on cmp_ct_TCD4_CM_vs_EM) 0 0 0 0 0 0
EM vs. TN (based on cmp_ct_TCD8_TN_vs_CM) 0 0 0 0 0 0
EM vs. TN (based on cmp_ct_TCD8_TN_vs_EM) 0 0 0 0 0 0
CM vs. EM (based on cmp_ct_TCD8_CM_vs_EM) 0 0 0 0 0 0
meta vs. myel (based on cmp_ct_neut_myel_vs_meta) 0 0 0 0 0 0
band vs. meta (based on cmp_ct_neut_meta_vs_band) 0 0 0 0 0 0
band vs. segm (based on cmp_ct_neut_band_vs_segm) 0 0 0 0 0 0
early vs. mature (based on cmp_ct_neut_early_vs_mature) 0 0 0 0 0 0
comparison
regions
differential methylation measure

Figure 1

Figure 1

Scatterplot for differential methylation (regions). If the selected criterion is not rankGradient: The transparency corresponds to point density. The 1% of the points in the sparsest populated plot regions are drawn explicitly. Additionally, the colored points represent differentially methylated regions (according to the selected criterion). If the selected criterion is rankGradient: median combined ranks accross hexagonal bins are shown as a gradient according to the color legend.

comparison
regions
difference metric
significance metric

Figure 2

Figure 2

Volcano plot for differential methylation quantified by various metrics. Color scale according to combined ranking.

Differential Methylation Tables

A tabular overview of measures for differential methylation on the region level for the individual comparisons are provided in this section.

The tables for the individual comparisons can be found here:

cpgislands genes promoters tiling1kb gencode22promoters ensembleRegBuildBPall
mono vs. neut (based on cmp_ct_mono_vs_neut) csv csv csv csv csv csv
mono vs. neut (based on cmp_ct_mono_vs_neut_VB) csv csv csv csv csv csv
Mf vs. mono (based on cmp_ct_mono_vs_mf) csv csv csv csv csv csv
Mf vs. mono (based on cmp_ct_mono_vs_mf_VB) csv csv csv csv csv csv
EM vs. TN (based on cmp_ct_TCD4_TN_vs_CM) csv csv csv csv csv csv
EM vs. TN (based on cmp_ct_TCD4_TN_vs_EM) csv csv csv csv csv csv
CM vs. EM (based on cmp_ct_TCD4_CM_vs_EM) csv csv csv csv csv csv
EM vs. TN (based on cmp_ct_TCD8_TN_vs_CM) csv csv csv csv csv csv
EM vs. TN (based on cmp_ct_TCD8_TN_vs_EM) csv csv csv csv csv csv
CM vs. EM (based on cmp_ct_TCD8_CM_vs_EM) csv csv csv csv csv csv
meta vs. myel (based on cmp_ct_neut_myel_vs_meta) csv csv csv csv csv csv
band vs. meta (based on cmp_ct_neut_meta_vs_band) csv csv csv csv csv csv
band vs. segm (based on cmp_ct_neut_band_vs_segm) csv csv csv csv csv csv
early vs. mature (based on cmp_ct_neut_early_vs_mature) csv csv csv csv csv csv

Differential Variability

Differential variability on the region level was computed similar to differential methylation, but the mean of variances, the log-ratio of the quotient of variances as well as the p-values from the differentiality test were employed. Ranking was performed in line with the ranking of differential methylation.

The following rank cutoffs have been automatically selected for the analysis of differentially variable regions:

cpgislands genes promoters tiling1kb gencode22promoters ensembleRegBuildBPall
mono vs. neut (based on cmp_ct_mono_vs_neut) 0 0 0 0 0 0
mono vs. neut (based on cmp_ct_mono_vs_neut_VB) 0 0 0 0 0 0
Mf vs. mono (based on cmp_ct_mono_vs_mf) 0 0 0 0 0 0
Mf vs. mono (based on cmp_ct_mono_vs_mf_VB) 0 0 0 0 0 0
EM vs. TN (based on cmp_ct_TCD4_TN_vs_CM) 0 0 0 0 0 0
EM vs. TN (based on cmp_ct_TCD4_TN_vs_EM) 0 0 0 0 0 0
CM vs. EM (based on cmp_ct_TCD4_CM_vs_EM) 0 0 0 0 0 0
EM vs. TN (based on cmp_ct_TCD8_TN_vs_CM) 0 0 0 0 0 0
EM vs. TN (based on cmp_ct_TCD8_TN_vs_EM) 0 0 0 0 0 0
CM vs. EM (based on cmp_ct_TCD8_CM_vs_EM) 0 0 0 0 0 0
meta vs. myel (based on cmp_ct_neut_myel_vs_meta) 0 0 0 0 0 0
band vs. meta (based on cmp_ct_neut_meta_vs_band) 0 0 0 0 0 0
band vs. segm (based on cmp_ct_neut_band_vs_segm) 0 0 0 0 0 0
early vs. mature (based on cmp_ct_neut_early_vs_mature) 0 0 0 0 0 0
comparison
regions
differential variability measure

Figure 3

Figure 3

Scatterplot for differential variable regions. The transparency corresponds to point density. The 1% of the points in the sparsest populated plot regions are drawn explicitly. Additionally, the colored points represent differentially methylated regions (according to the selected criterion).

comparison
regions
difference metric
significance metric

Figure 4

Figure 4

Volcano plot for differential variability quantified by various metrics. Color scale according to combined ranking.

comparison
regions
rankCutoff

Figure 5

Figure 5

Scatterplot comparing differentially methylated (DMRs) and variable regions (DVRs), as well as regions that are both differentially methylated and variable.

GO Enrichment Analysis

GO Enrichment Analysis was conducted. The wordclouds and tables below contains significant GO terms as determined by a hypergeometric test.

comparison
Hypermethylation/hypomethylation
ontology
regions
differential methylation measure

Figure 6

Figure 6

Wordclouds for GO enrichment terms.

comparison
Hypermethylation/hypomethylation
ontology
regions
differential methylation measure

GOMFID Pvalue OddsRatio ExpCount Count Size Term
GO:0070942 0 648.24 0.0089 3 8 neutrophil mediated cytotoxicity
GO:0051873 0 360.0444 0.0133 3 12 killing by host of symbiont cells
GO:0031640 0 88.7857 0.0621 4 56 killing of cells of other organism
GO:0043312 0 21.7899 0.518 7 467 neutrophil degranulation
GO:0045055 0 17.7004 0.7864 8 709 regulated exocytosis
GO:0042119 0 21.2662 0.5302 7 478 neutrophil activation
GO:0002275 0 19.5123 0.5756 7 519 myeloid cell activation involved in immune response
GO:0002444 0 19.3561 0.5801 7 523 myeloid leukocyte mediated immunity
GO:0051818 0 215.9467 0.02 3 18 disruption of cells of other organism involved in symbiotic interaction
GO:0044663 0 Inf 0.0022 2 2 establishment or maintenance of cell type involved in phenotypic switching
GO:0002263 0 15.1375 0.7331 7 661 cell activation involved in immune response
GO:0060414 0 675.3333 0.0055 2 5 aorta smooth muscle tissue morphogenesis
GO:0035821 0 33.771 0.1553 4 140 modification of morphology or physiology of other organism
GO:0045123 0 68.783 0.0555 3 50 cellular extravasation
GO:1900239 0 337.6042 0.0089 2 8 regulation of phenotypic switching
GO:0016192 0 8.1639 1.972 9 1778 vesicle-mediated transport
GO:0051851 0 52.9508 0.071 3 64 modification by host of symbiont morphology or physiology
GO:0032940 1e-04 8.694 1.5239 8 1374 secretion by cell
GO:0050829 1e-04 50.8582 0.0744 3 71 defense response to Gram-negative bacterium
GO:0038166 1e-04 225.0278 0.0122 2 11 angiotensin-activated signaling pathway
GO:0044130 1e-04 168.7396 0.0155 2 14 negative regulation of growth of symbiont in host
GO:0098542 1e-04 13.3187 0.5102 5 460 defense response to other organism
GO:0045321 1e-04 8.5992 1.2467 7 1124 leukocyte activation
GO:0044144 1e-04 144.6161 0.0177 2 16 modulation of growth of symbiont involved in interaction with host
GO:0043207 2e-04 9.5316 0.9028 6 814 response to external biotic stimulus
GO:0042089 2e-04 32.222 0.1142 3 103 cytokine biosynthetic process
GO:0044110 2e-04 119.0735 0.0211 2 19 growth involved in symbiotic interaction
GO:0009617 2e-04 11.6058 0.5823 5 525 response to bacterium
GO:0040012 2e-04 9.1265 0.9405 6 848 regulation of locomotion
GO:1990776 3e-04 101.1937 0.0244 2 22 response to angiotensin
GO:0019730 3e-04 88.5824 0.0278 2 30 antimicrobial humoral response
GO:0019731 5e-04 71.8933 0.0335 2 32 antibacterial humoral response
GO:0070944 0.001 Inf 0.001 1 1 neutrophil mediated killing of bacterium
GO:0009620 0.001 48.9758 0.0482 2 46 response to fungus
GO:0033002 0.0011 17.3254 0.2085 3 188 muscle cell proliferation
GO:0002777 0.0011 Inf 0.0011 1 1 antimicrobial peptide biosynthetic process
GO:0002812 0.0011 Inf 0.0011 1 1 biosynthetic process of antibacterial peptides active against Gram-negative bacteria
GO:0032644 0.0011 Inf 0.0011 1 1 regulation of fractalkine production
GO:0033367 0.0011 Inf 0.0011 1 1 protein localization to mast cell secretory granule
GO:0033371 0.0011 Inf 0.0011 1 1 T cell secretory granule organization
GO:0033373 0.0011 Inf 0.0011 1 1 maintenance of protease location in mast cell secretory granule
GO:0033375 0.0011 Inf 0.0011 1 1 protease localization to T cell secretory granule
GO:0033377 0.0011 Inf 0.0011 1 1 maintenance of protein location in T cell secretory granule
GO:0033382 0.0011 Inf 0.0011 1 1 maintenance of granzyme B location in T cell secretory granule
GO:0050754 0.0011 Inf 0.0011 1 1 positive regulation of fractalkine biosynthetic process
GO:0050756 0.0011 Inf 0.0011 1 1 fractalkine metabolic process
GO:0070946 0.0011 Inf 0.0011 1 1 neutrophil mediated killing of gram-positive bacterium
GO:1904676 0.0011 Inf 0.0011 1 1 negative regulation of somatic stem cell division
GO:1905175 0.0011 Inf 0.0011 1 1 negative regulation of vascular smooth muscle cell dedifferentiation
GO:0048662 0.0011 47 0.0499 2 45 negative regulation of smooth muscle cell proliferation
GO:2000147 0.0013 10.1933 0.4947 4 446 positive regulation of cell motility
GO:0061844 0.0014 41.2296 0.0566 2 51 antimicrobial humoral immune response mediated by antimicrobial peptide
GO:0035904 0.0015 40.4025 0.0577 2 52 aorta development
GO:0051270 0.002 6.9335 0.9505 5 857 regulation of cellular component movement
GO:0006940 0.0022 33.0943 0.0699 2 63 regulation of smooth muscle contraction
GO:0050725 0.0022 953.5294 0.0022 1 2 positive regulation of interleukin-1 beta biosynthetic process
GO:0070947 0.0022 953.5294 0.0022 1 2 neutrophil mediated killing of fungus
GO:0048844 0.0023 32.0397 0.0721 2 65 artery morphogenesis
GO:0010631 0.0024 13.0877 0.274 3 247 epithelial cell migration
GO:0050764 0.0025 30.5777 0.0754 2 68 regulation of phagocytosis
GO:0090130 0.0027 12.615 0.2839 3 256 tissue migration
GO:0032602 0.0032 27.2584 0.0843 2 76 chemokine production
GO:0045079 0.0033 476.7353 0.0033 1 3 negative regulation of chemokine biosynthetic process
GO:0045360 0.0033 476.7353 0.0033 1 3 regulation of interleukin-1 biosynthetic process
GO:0090678 0.0033 476.7353 0.0033 1 3 cell dedifferentiation involved in phenotypic switching
GO:1903238 0.0033 476.7353 0.0033 1 3 positive regulation of leukocyte tethering or rolling
GO:1905111 0.0033 476.7353 0.0033 1 3 positive regulation of pulmonary blood vessel remodeling
GO:0048644 0.0037 24.892 0.0921 2 83 muscle organ morphogenesis
GO:0019732 0.0044 317.8039 0.0044 1 4 antifungal humoral response
GO:0045415 0.0044 317.8039 0.0044 1 4 negative regulation of interleukin-8 biosynthetic process
GO:0060474 0.0044 317.8039 0.0044 1 4 positive regulation of flagellated sperm motility involved in capacitation
GO:0090191 0.0044 317.8039 0.0044 1 4 negative regulation of branching involved in ureteric bud morphogenesis
GO:0097029 0.0044 317.8039 0.0044 1 4 mature conventional dendritic cell differentiation
GO:2000724 0.0044 317.8039 0.0044 1 4 positive regulation of cardiac vascular smooth muscle cell differentiation
GO:2001274 0.0044 317.8039 0.0044 1 4 negative regulation of glucose import in response to insulin stimulus
GO:0022617 0.0045 22.6433 0.1009 2 91 extracellular matrix disassembly
GO:0032496 0.0046 10.3266 0.3449 3 311 response to lipopolysaccharide
GO:0008626 0.0055 238.3382 0.0055 1 5 granzyme-mediated apoptotic signaling pathway
GO:0036446 0.0055 238.3382 0.0055 1 5 myofibroblast differentiation
GO:0070945 0.0055 238.3382 0.0055 1 5 neutrophil mediated killing of gram-negative bacterium
GO:1900028 0.0055 238.3382 0.0055 1 5 negative regulation of ruffle assembly
GO:1904673 0.0055 238.3382 0.0055 1 5 negative regulation of somatic stem cell population maintenance
GO:0098657 0.0057 6.617 0.7487 4 675 import into cell
GO:0051234 0.0062 3.6541 5.4192 11 4886 establishment of localization
GO:0001878 0.0066 190.6588 0.0067 1 6 response to yeast
GO:0002778 0.0066 190.6588 0.0067 1 6 antibacterial peptide production
GO:0045416 0.0066 190.6588 0.0067 1 6 positive regulation of interleukin-8 biosynthetic process
GO:0006508 0.0073 4.3799 1.8489 6 1667 proteolysis
GO:0030334 0.0075 6.0853 0.8108 4 731 regulation of cell migration
GO:0010668 0.0077 158.8725 0.0078 1 7 ectodermal cell differentiation
GO:0032963 0.0078 16.9034 0.1342 2 121 collagen metabolic process
GO:0048870 0.0087 6.1229 0.8613 4 971 cell motility
GO:0042117 0.0088 136.1681 0.0089 1 8 monocyte activation
GO:0043696 0.0088 136.1681 0.0089 1 8 dedifferentiation
GO:0045348 0.0088 136.1681 0.0089 1 8 positive regulation of MHC class II biosynthetic process
GO:2000035 0.0088 136.1681 0.0089 1 8 regulation of stem cell division
GO:0006909 0.0097 15.2333 0.1505 2 152 phagocytosis

Differential Variability

GO enrichment analysis was also performed for differentially variable regions.

comparison
Hypermethylation/hypomethylation
ontology
regions
differential methylation measure

Figure 7

Figure 7

Workclouds for GO enrichment terms (Differential Variability)

comparison
Hypermethylation/hypomethylation
ontology
regions
differential methylation measure

GOMFID Pvalue OddsRatio ExpCount Count Size Term
GO:0030728 2e-04 134.9583 0.019 2 22 ovulation
GO:0031648 6e-04 67.3958 0.0362 2 42 protein destabilization
GO:1904109 9e-04 Inf 9e-04 1 1 positive regulation of cholesterol import
GO:0010507 0.0014 42.0599 0.0569 2 66 negative regulation of autophagy
GO:0044663 0.0017 1247.2308 0.0017 1 2 establishment or maintenance of cell type involved in phenotypic switching
GO:0045105 0.0017 1247.2308 0.0017 1 2 intermediate filament polymerization or depolymerization
GO:1903937 0.0017 1247.2308 0.0017 1 2 response to acrylamide
GO:0033693 0.0026 623.5769 0.0026 1 3 neurofilament bundle assembly
GO:1905111 0.0026 623.5769 0.0026 1 3 positive regulation of pulmonary blood vessel remodeling
GO:0031133 0.0034 415.6923 0.0035 1 4 regulation of axon diameter
GO:0043553 0.0034 415.6923 0.0035 1 4 negative regulation of phosphatidylinositol 3-kinase activity
GO:2000909 0.0034 415.6923 0.0035 1 4 regulation of sterol import
GO:2001274 0.0034 415.6923 0.0035 1 4 negative regulation of glucose import in response to insulin stimulus
GO:0040038 0.0043 311.75 0.0043 1 5 polar body extrusion after meiotic divisions
GO:0060414 0.0043 311.75 0.0043 1 5 aorta smooth muscle tissue morphogenesis
GO:1903935 0.0043 311.75 0.0043 1 5 response to sodium arsenite
GO:0009725 0.0047 7.3491 0.7255 4 841 response to hormone
GO:0014012 0.0052 249.3846 0.0052 1 6 peripheral nervous system axon regeneration
GO:0090306 0.006 207.8077 0.006 1 7 spindle assembly involved in meiosis
GO:0099638 0.006 207.8077 0.006 1 7 endosome to plasma membrane protein transport
GO:1900239 0.0069 178.1099 0.0069 1 8 regulation of phenotypic switching
GO:0008090 0.0077 155.8365 0.0078 1 9 retrograde axonal transport
GO:0002468 0.0086 138.5128 0.0086 1 10 dendritic cell antigen processing and presentation
GO:0019896 0.0086 138.5128 0.0086 1 10 axonal transport of mitochondrion
GO:0038166 0.0095 124.6538 0.0095 1 11 angiotensin-activated signaling pathway

LOLA Enrichment Analysis

LOLA Enrichment Analysis [2] was conducted. The plots and tables below show enrichments across annotations in the supplied LOLA reference databases for the following collections:

comparison
Hypermethylation/hypomethylation
regions
differential methylation measure
color

Figure 8

Figure 8

Scatter plot showing the effect size (log-odds ratio) vs. the significance (-log10(q-value)), similar to a 'volcano plot' as it is called in other contexts.

comparison
Hypermethylation/hypomethylation
regions
differential methylation measure

Figure 9

Open PDF Figure 9

Boxplots showing log-odds ratios from LOLA enrichment analysis. Shown are those groups of terms per category that share the same putative target. Only terms that exhibit statistical significance (p-value < 0.01) are included. If more than 100 terms are enriched, the 100 terms receiving the highest joined LOLA ranks are shown. Coloring of the bars reflects the putative targets of the terms.

comparison
Hypermethylation/hypomethylation
regions
differential methylation measure

Figure 10

Open PDF Figure 10

Barplots showing log-odds ratios from LOLA enrichment analysis. Shown are those terms that exhibit statistical significance (p-value < 0.01). If more than 100 terms are enriched, the 100 terms receiving the highest joined LOLA ranks are shown. Coloring of the bars reflects the putative targets of the terms.

Differential Variability

LOLA enrichment analysis was also conducted for differentially variable regions.

comparison
Hypermethylation/hypomethylation
regions
differential methylation measure
color

Figure 11

Figure 11

Barplots showing log-odds ratios from LOLA enrichment analysis. Shown are those terms that exhibit statistical significance (p-value < 0.01). If more than 100 terms are enriched, the 100 terms receiving the highest joined LOLA ranks are shown. Coloring of the bars reflects the putative targets of the terms.

comparison
Hypermethylation/hypomethylation
regions
differential methylation measure

Figure 12

Open PDF Figure 12

Barplots showing log-odds ratios from LOLA enrichment analysis. Shown are those terms that exhibit statistical significance (p-value < 0.01). If more than 100 terms are enriched, the 100 terms receiving the highest joined LOLA ranks are shown. Coloring of the bars reflects the putative targets of the terms.

comparison
Hypermethylation/hypomethylation
regions
differential methylation measure

Figure 13

Open PDF Figure 13

Barplots showing log-odds ratios from LOLA enrichment analysis. Shown are those terms that exhibit statistical significance (p-value < 0.01). If more than 100 terms are enriched, the 100 terms receiving the highest joined LOLA ranks are shown. Coloring of the bars reflects the putative targets of the terms.

References

  1. Makambi, K. (2003) Weighted inverse chi-square method for correlated significance tests. Journal of Applied Statistics, 30(2), 225234
  2. Sheffield, N. C., & Bock, C. (2016). LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor. Bioinformatics, 32(4), 587-589