06-project-slidedeck

Kathleen Durkin

2025-05-09

Experimental Design

C.virginica oyster, larval and zygote stages
Parents exposed to OA conditions
Whole genome bisulfite sequencing (WGBS) to map DNA methylation

Goal

Evaluate intergenerational heritability of environmentally-induced DNA methylation

Methods

Trimming. Raw WGBS FastQs were concatenated, trimmed using fastp, repaired if necessary using BBtools, and QC’d using FastQC and MultiQC
Alignment. Trimmed WGBS FastQs were aligned to C. virginica genome using Bismark and Bowtie, summarized using MultiQC. (Re-analysis in progress)
Deduplication. Aligned reads were deduplicated using Bismark to remove read duplication caused by PCR amplification during WGBS. (Re-analysis in progress)
Methylation extraction. Bismark was used to call the methylation state of all sequenced cytosine positions. (Re-analysis in progress)
Differential methylation analysis. methylKit used to identify differential methylation between parental treatment groups and between life stages.

Methylation calls

Code

meth <- read.csv("../output/06-differential-methylation/filtered-CpGs-parental-treatment.csv")
head(meth)

  X         chr    start      end strand coverage1 numCs1 numTs1 coverage2
1 3 NC_007175.2     5862     5862      *        16      0     16        16
2 4 NC_035780.1      105      105      *        14      0     14       101
3 5 NC_035780.1  3432807  3432807      *        15      0     15        14
4 6 NC_035780.1  7496939  7496939      *        12      0     12        59
5 7 NC_035780.1  7496980  7496980      *        12      0     12        49
6 8 NC_035780.1 10255935 10255935      *        14      5      9        53
  numCs2 numTs2 coverage3 numCs3 numTs3 coverage4 numCs4 numTs4 coverage5
1      0     16        36      0     36        56      2     54        54
2      1    100        25      1     24        27      1     26        49
3      1     13        67      2     65        74      5     69        22
4      3     56       107     33     74        97      8     89       111
5      1     48       106     26     80        98      6     92       106
6     25     28        25     13     12        22      5     17        32
  numCs5 numTs5 coverage6 numCs6 numTs6 coverage7 numCs7 numTs7 coverage8
1      1     53        29      0     29       218      0    218        13
2      0     49        55      3     52        36      1     35       113
3      1     21        16      0     16        57      1     56        16
4      7    104        73      5     68       143      9    134        69
5      2    104        68      2     66       135      6    129        68
6      5     27        57     22     35        25      8     18        64
  numCs8 numTs8 coverage9 numCs9 numTs9 coverage10 numCs10 numTs10 coverage11
1      0     13       196      2    194         52       1      51         12
2      1    112        38      1     37         34       0      34         17
3      0     16        30      0     30         78       0      78         36
4      3     66        50      6     44        127      17     110         41
5      3     65        49      5     44        129      17     112         37
6     28     36        49     22     27         44      29      15         25
  numCs11 numTs11 coverage12 numCs12 numTs12 coverage13 numCs13 numTs13
1       1      11        321       5     316         57       1      56
2       2      15         37       0      37         17       0      17
3       1      35         33       0      33         97       0      97
4       5      36         45       3      42         82       6      76
5       5      32         40       5      35         77       1      76
6      10      15         21       4      17         32      11      21
  coverage14 numCs14 numTs14 coverage15 numCs15 numTs15 coverage16 numCs16
1        108       6     102        162       4     158         44       5
2         23       0      23         70       0      70         12       0
3         60       1      59         21       0      21         75       1
4         57       4      53         27       0      27         81      10
5         55       4      51         25       0      25         76       9
6         26      11      15         60      22      38         22      13
  numTs16 coverage17 numCs17 numTs17 coverage18 numCs18 numTs18 coverage19
1      39         42       0      42         38       0      38         35
2      12         85       2      83         64       2      62         55
3      74         25       0      25         27       1      26         16
4      71         32       7      25         53       6      47         24
5      67         34       2      32         49       6      43         23
6       9         63      27      36         47      21      26         55
  numCs19 numTs19 coverage20 numCs20 numTs20 coverage21 numCs21 numTs21
1       0      35         21       0      21         33       0      33
2       0      55         89       2      87         62       1      61
3       1      15         12       0      12         11       1      10
4       0      24         80       1      79         47       2      45
5       0      23         81       0      81         45       2      43
6      24      31         37      14      23         27      11      16
  coverage22 numCs22 numTs22 coverage23 numCs23 numTs23 coverage24 numCs24
1         43       0      43         73       7      66         18       0
2         16       0      16         51       3      48        147       3
3         12       0      12         26       0      26         21       2
4         16       4      12        118       9     109         84       1
5         14       3      11        107       9      98         85       0
6         16      10       6         55      16      39         41      11
  numTs24 coverage25 numCs25 numTs25 coverage26 numCs26 numTs26 coverage27
1      18         23       0      23        104       4     100        119
2     144         51       0      51         17       0      17         48
3      19         12       0      12         23       0      23         25
4      83         33       0      33         49       1      48         43
5      85         33       0      33         45       4      41         41
6      30         52      22      30         33      15      18         49
  numCs27 numTs27 coverage28 numCs28 numTs28 coverage29 numCs29 numTs29
1       0     119         32       0      32         18       1      17
2       0      48         69       1      68         61       0      61
3       0      25         15       0      15         12       2      10
4       0      43         65       3      62         85       0      85
5       0      41         62       2      60         84       0      84
6      26      23         31      16      15         43      19      24
  coverage30 numCs30 numTs30
1         12       1      11
2         69       1      68
3         17       0      17
4         47       2      45
5         47       0      47
6         53      14      39

Differential Methylation Analysis


### Normalize the coverage values among samples.
myobj.filt.norm <- normalizeCoverage(myobj.filt, method = "median")

### Filter to retain most variable CpGs
# get percent methylation matrix
pm=percMethylation(meth)
# calculate standard deviation of CpGs
sds=matrixStats::rowSds(pm)
# keep only CpG with standard deviations larger than 2
meth <- meth[sds > 2]

### Test for differential methylation
myDiff <- calculateDiffMeth(meth,
                            overdispersion = "MN",
                            adjust="BH")

Preliminary Results

CpG sites are differentially methylated by parental treatment

Code

# Load packages
library(ggplot2)
library(dplyr)
# Read in data
myDiff <- read.csv("../output/06-differential-methylation/DM-CpGs-parental-treatment.csv")
# Label significance
myDiff$significant <- myDiff$pvalue < 0.05

# Plot
ggplot(myDiff, aes(x = -log10(qvalue), y = meth.diff, color = significant)) +
  geom_point(size = 1.5) +
  scale_color_manual(values = c("gray" = "gray", "TRUE" = "red", "FALSE" = "gray")) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "black") +
  theme_minimal() +
  labs(
    x = expression(-log[10](qvalue)),
    y = "Methylation Difference",
    color = "Significant (p < 0.05)",
    title = "CpGs Differentially Methylated by Parental Treatment"
  )

Preliminary Results

CpG sites are differentially methylated by parental treatment

Code

myDiff %>% filter(significant == "TRUE") %>% select(-X, -significant)

          chr    start      end strand     pvalue    qvalue  meth.diff
1 NC_007175.2     5862     5862      * 0.04129263 0.6971628   1.818849
2 NC_035780.1 61090732 61090732      * 0.02331151 0.6971628 -11.414277
3 NC_035787.1 73185630 73185630      * 0.04928128 0.6971628   4.253793

Next steps

Complete re-analysis steps (alignment, methylation extraction)
Analyze regional differential methylation between parental treatments
Differential methylation analysis between life stages