Alu vs. LINE-1 Alu vs. Strong island Alu vs. Weak island Alu vs. Non-island LINE-1 vs. Strong island LINE-1 vs. Weak island LINE-1 vs. Non-island Strong island vs. Weak island Strong island vs. Non-island Weak island 0.64* -0.66* 0.79*,† 0.76*,† -0.16 0.54 0.50 -0.50 -0.50 0.94*,† 0.29 -0.04 0.54 0.45 0.37 0.68* 0.37 0.10 -0.42 0.80*,† 0.62 -0.49 -0.14 0.53 -0.58 -0.39 0.13 0.66* -0.16 0.44 Brain 0.74* 0.21 0.43 0.05 0.43 0.88* 0.07 0.21 -0.79* 0.33 -0.09 -0.14 0.06 0.13 -0.35 -0.21 0.35 0.42 -0.52 0.32 0.26 0.60 0.48 0.25 -0.12 -0.26 0.31 0.50 -0.45 -0.13 -0.03 -0.27 -0.47 -0.13 0.49 0.25 -0.18 0.53 -0.48 0.38 0.20 0.17 0.14 0.13 0.48*,† 0.48*,† 0.50*,† 0.78*,† 0.56*,† 0.91*,† Table 1. s pearman correlation of DNa methylation at five ReDs Villi-1st trimester Villi-2nd trimester Villi-term Kidney Muscle Blood Merged somatic s pearman correlation values (r) are stated; *indicates correlations with p ≤ 0.05; †indicates significant correlations (p ≤ 0.05) after Benjamini-h ochberg correction for multiple comparisons. and adult blood were used to compare tissue-specific DNA meth- within each bin (p < 0.0001) but was not dependant on probe ylation at each ReDS (Fig. 3). After correction for multiple com- direction to TSS (upstream vs. downstream, p = 0.73), thus parisons, there were no significant tissue-to-tissue differences direction to TSS was not considered in further analyses. We next in average Alu DNA methylation (Fig. 3A). However, average assessed tissue-specific patterns of DNA methylation in 2nd tri- LINE-1 DNA methylation in vi©lli(622.520%1±42.60)Lwaassnigndif- emsestBer tiisosuesscandi eadnult cbleood. for probes of each CpG island icantly lower than in somatic tissues (Fig. 3B; brain, 84.89% density within each of the three TSS bins: (1) ±0 to 500 bps, ± 3.32; muscle, 82.82% ± 2.44 and blood, 85.79% ± 1.92; all (2) ±501 to 1000 bps and (3) ±1001 to 1500 bps. Average DNA p < 0.001). Reduced average non-island proDbe moethnylaotiontwdas ismtetrhyilabtiounotfetiss.ues followed the same rank-order within each also observed in villi (49.60% ± 1.20) compared with somatic of the three TSS groups for strong, weak, and non-island probe tissues (Fig. 3E; brain, 60.89% ± 1.48; kidney, 57.91% ± 0.93 groups (data shown for strong islands Fig. 4B–D). These pat- and blood, 63.64% ± 0.58; all p < 0.001) and at weak island terns were also the same as those observed when probes were not probes (Fig. 3D; villi, 37.44% ± 0.65 vs. brain, 41.31% ± 0.49; separated by distance to closest TSS (Fig. 3C–E). Between tis- kidney 38.83% ± 0.47 and blood, 43.53% ± 0.36; all p < 0.001). sue differences in strong islands were largest at CpGs distal to Interestingly, strong island DNA methylation in villi (11.21% a TSS (Fig. 4D; villi 16.91% ± 0.7 vs. kidney 15.00% ± 0.63, ± 0.49) was greater than in other tissues (Fig. 3C; muscle, 9.83% p < 0.0001; blood 18.10% ± 0.74, vs. brain 16.13% ± 0.64, kid- ± 0.32 and kidney, 9.80% ± 0.47; all p < 0.0001), although these ney 15.00% ± 0.63 and muscle 16.20% ± 0.42, all p < 0.05) and small differences in DNA methylation may not be biologically smallest at CpGs close to a TSS (Fig. 4B; villi 9.63% ± 0.67 vs. significant. The similarity in the patterns of tissue-specific DNA kidney 8.27% ± 0.46 and muscle 8.10% ± 0.32, all p < 0.001). To methylation assessed by LINE-1, weak island and non-island test for an association between distance to nearest TSS and CpG probe methylation further suggest that these ReDS may follow island density, we compared the observed to expected number similar trends in DNA methylation. of array probes in each of the three TSS bins (Fig. S11). There Distance to transcription start site is associated with pro- was an overrepresentation of strong island probes and underrep- moter CpG island density and distinct trends in DNA methyla- resentation of non-island probes close to a TSS (±0 to 500 bps). tion. Since 98% of the array probes examined in the strong, weak Conversely, there was an overrepresentation of non-island probes and non-island groups were within 1,500 bps from a known tran- and an underrepresentation of strong island probes distal to a scription start site (TSS), they are considered to be in gene pro- TSS (±1,001 to 1,500 bps). Taken together, these results imply moters. We investigated whether probe distance to a TSS within that within promoters, distance to nearest TSS is linked to CpG each of the CpG island groups affected average DNA methyla- island density, which influences DNA methylation of promoters. tion. We present here the data from the merged somatic tissues; Preliminary within-individual correlation of dispersed however, merged villi yielded similar results. Probes were binned DNA methylation. After examining tissue-specific patterns of into six 500 bp windows based on distance to nearest TSS: dispersed DNA methylation, we investigated whether there were (1) -1,500 to -1,001 bps (n = 575), (2) -1,000 to -501 bps within-individual trends at each of the five ReDS. This is of par- (n = 1,989), (3) -500 to 0 bps (n = 8,628), (4) 1 to 500 bps ( ticular interest in studies of environmental exposure and patho- n = 8,707), (5) 501 to 1,000 bps (n = 2,036) and (6) 1,001 to logical conditions, to determine if changes in DNA methylation 1,500 bps (n = 558) (Fig. 4A). DNA methylation was signifi- are localized to one tissue or are more widespread. The 2nd tri- cantly different between strong, weak and non island CpGs mester fetal samples including villi, brain, kidney and muscle 656 Epigenetics Volume 7 Issue 6