- Temporal changes in DNA methylation and RNA expression in a small song bird:. - Background: DNA methylation is likely a key mechanism regulating changes in gene transcription in traits that show temporal fluctuations in response to environmental conditions. - To understand the transcriptional role of DNA methylation we need simultaneous within-individual assessment of methylation changes and gene expression changes over time. - Here, we explore to what extend between-individual changes in DNA methylation in a tissue accessible for repeated sampling (red blood cells (RBCs)) reflect such patterns in a tissue unavailable for repeated sampling (liver) and how these DNA methylation patterns are associated with gene expression in such inaccessible tissues (hypothalamus, ovary and liver). - Results: We simultaneously assessed DNA methylation changes (via reduced representation bisulfite sequencing) and changes in gene expression (via RNA-seq and qPCR) over time. - Conclusion: Temporal changes in DNA methylation are largely tissue-general, indicating that changes in RBC methylation can reflect changes in DNA methylation in other, often less accessible, tissues such as the liver in our case. - However, associations between temporal changes in DNA methylation with changes in gene expression are mostly tissue- and genomic location-dependent. - The observation that temporal changes in DNA methylation within RBCs can relate to changes in gene expression in less accessible tissues is important for a better understanding of how environmental conditions shape traits that temporally change in expression in wild populations.. - Indeed, changes in DNA methylation were found as a common factor for aging in mammals with a striking tissue-specificity for age related DNA methylation changes [8, 9]. - Most studies on associations between temporal changes in DNA methylation and trait changes are based on between-individual samples, since it is often not feas- ible to repeatedly sample tissues of biological relevance within the same individual. - 1 μg) to determine genome- wide DNA methylation profiles via reduced representa- tion bisulfite sequencing (RRBS) [16, 17]. - The availability of such a tissue for repeated sampling opens up the pos- sibility to examine within-individual short-term changes in DNA methylation. - However, repeated sampling in such inaccess- ible tissues in order to assess within-individual changes in DNA methylation is impossible as it requires sacri- ficing each individual. - Therefore, DNA methylation in blood is proposed to be a biomarker for DNA methylation in other tissues. - Here, we explore to what extend temporal changes in DNA methylation are tissue-general or tissue-specific and how tissue-general temporal changes relate to changes in gene expression in the inaccessible tissues of interest. - Potentially, the presence of tissue-general temporal changes in DNA methylation that cause a predictable change in gene expression in inaccessible tissues, will open up the possibility to monitor how environmental conditions affect temporally expressed traits via repeated blood sampling, even in wild populations.. - Tissue-general and tissue-specific changes in DNA methylation between red blood cells and liver. - Table S1), 2377 CpG sites showed a significant change in methylation between time point 1 and 2 (Δ 1,2 ) and 3934 CpG sites changed significantly between time point 2 and 3 (Δ 2,3 ) (Additional files 9 and 10. - 1 Correlation between CpG sites in RBCs and liver data that show a significant change in methylation for Δ 1,2 (a) and Δ 2,3 (b). - We depict sites that significantly change in methylation in both tissues (tissue-general change) in red (n = 537 for Δ 1,2 and 853 for Δ 2,3 ) or in one of the tissues (tissue-specific change) in grey (n = 1840 for Δ 1,2 and 3081 for Δ 2,3. - Correlation between change in methylation and candidate gene expression in liver. - Genome-wide associations between changes in methylation and gene expression. - 2 Correlation between the change in methylation of CpG sites in promoter and TSS regions in RBC data with the change in methylation of those in liver data that showed a significant change in methylation for Δ 1,2 (a) and Δ 2,3 (b). - expected quadrants (Q1 and Q3) when comparing (a) the change in liver methylation to the change in liver gene expression, (b) the change in RBC methylation re- lated to the change in liver gene expression and (d) the change in RBC methylation related to the change in hypothalamus gene expression (Additional files and 32. - S12-S19), although the number of associations for the change in gene expres- sion and change in CpG site methylation was limited (max. - When comparing (c) the change in RBC methylation in the TSS region with changes in gene expression in ovary, as- sociations in Q1 or Q3 were overrepresented between time point 2 and 3 when compared to associations within the 10 kb downstream region, where we did not expect this effect a priori (Fisher’s Exact Test: p = 0.001, Fig. - what extent temporal changes in DNA methylation are established in a tissue-general or tissue-specific manner and to what extent possible tissue-general changes in DNA methylation are associated with changes in gene expression in various tissues. - Here, we explored whether DNA methylation changes over time were tissue-specific or tissue-general (based on change in methylation in RBCs and liver) and how changes in DNA methylation were associated with changes in gene expression of some target tissues unavailable for repeated sampling (hypo- thalamus, ovary and liver). - For a set of seven candidate genes related to timing of reproduction, we found no correl- ation between the change in DNA methylation in liver data and the change in gene expression in liver tissue over time. - As expected, we found no such association between changes in DNA methylation and expression changes of the respective gene when the site was situated in the gene body or in the 10 kb up- or 10 kb downstream regions, irrespective of which tissues were compared.. - Here, we suggest and discuss four possible groups of DMS that categorize how DNA methylation changes over time can differ across tissues and how these changes are associated to differences in changes in gene expression across tissues. - The first two groups contain DMS showing a tissue-specific change in DNA methyla- tion that correlates with a change in gene expression in (1) a tissue-specific or (2) tissue-general manner. - These groups cannot be used as biomarkers for temporally expressed traits, because of their tissue-specific change in methylation and/or gene expression. - 1 and 2) that correlates with a change in gene expression in (3) a tissue-specific or (4) a tissue-general manner. - In contrast to other studies we did not find a negative correlation between absolute levels of pro- moter DNA methylation and gene expression, but we have to emphasize here that these studies did not in- vestigate the relationship between the change in DNA methylation and the change in gene expression. - Recent studies in great tits, found temporal vari- ation in genome-wide DNA methylation in RBCs col- lected throughout the breeding season [6] and a correlation between changes in DNA methylation levels and a female’s reproductive timing [18]. - We calculated the change in methylation level based on samples of individuals and the log2Fold-change in gene expression level based on pooled samples. - As such, we only had enough data points to test for an association between the change in RBC methyla- tion and change in gene expression in the ovary. - In general, we found that temporal changes in DNA methylation correlate well between tissues. - This indi- cates that the mechanisms underlying these DNA methylation changes over time do not act in the target. - However, the vast majority of changes in DNA methylation were not associated with gene expression changes in target tissues in a predictable way. - This shows that general patterns of DNA methylation in any tissue cannot be taken as predictive values for gene ex- pression changes in other tissues and the effects of methylation changes are likely very targeted. - See Additional file 42;. - calculated the change in CpG site methylation between time points within liver and RBCs.. - and time point 2 and 3 (Δ 2,3 ) in ei- ther blood or liver (tissue-specific change) or in both tis- sues (tissue-general change) (Additional file 9. - In order to evaluate the association between DNA methylation changes and RNA expression changes in the TSS region, we found CpG sites with 10x cover- age across all samples for five from the total candidate. - Genome-wide associations between change in methylation and gene expression. - To associate DNA methylation changes with gene-expression changes, CpG sites that showed a time-point effect were identified using a differential methylation analysis with time-point (levels 1,2 and 3) as a fixed factor, and genes with a significant time effect were identified using a dif- ferential gene expression analysis performed in [22].. - Thereafter, to examine the association between DNA methylation change and change in gene expression in tissue compari- sons a-d, we quantified the change between time point 1 and 2 (Δ 1,2 ) and time point 2 and 3 (Δ 2,3 ) for both the methylation level of CpG sites and gene expression levels. - We quantified the change in methylation level, by first calculating the average methylation levels (i.e.. - We quantified the change in gene expression be- tween time point 1 and 2 (Δ 1,2. - We furthermore trimmed the data sets by excluding CpG sites with a change in methylation level <. - To better understand the effect of the genomic location on the re- lationship between changes in DNA methylation and gene expression, we differentiated between genomic lo- cations (i.e. - For each combination of comparison (a-d), time contrast (first and second) and genomic location, we plotted the gene expression as log 2 Foldchange against the change in methylation level. - There are four possible quadrants of association between change in gene expression and change in methylation level: hypo- methylation and increased gene expression (Q1), hyper- methylation and increased gene expression (Q2), hyper-. - We used the 10 kb downstream re- gion as a control region for CpG sites randomly distrib- uted across Q1-Q4 as we do not expect any relationship between DNA methylation changes and gene expression changes in this region [21, 24]. - Additional file 1: Figure S1. - Additional file 2: Figure S2. - Additional file 3: Figure S3. - Additional file 4: Figure S4. - Additional file 5: Figure S5. - Additional file 6: Figure S6. - Additional file 7: Figure S7. - Additional file 8: Table S1. - Additional file 9: Table S2. - Correlations between the change in individual gene expression and change in methylation for both promoter and TSS regions. - Mean (±s.e.) difference in both DNA methylation in promoter regions and RNA expression per female in time point 1 (in grey) across all females in time point 2, and vice versa (in black) for the individual genes.. - Mean (±s.e.) difference in both DNA methylation in promoter regions and RNA expression per female in time point 2 (in grey) across all females in time point 3, and vice versa (in black) for the individual genes.. - Mean (±s.e.) difference in both DNA methylation in TSS and RNA methylation per female in time point 1 (in grey) across all females in time point 2, and vice versa (in black) for the individual genes.. - Mean (±s.e.) difference in both DNA methylation in TSS and RNA methylation per female in time point 2 (in grey) across all females in time point 3, and vice versa (in black) for the individual genes.. - CpG sites in liver with a significant change in methylation across time points.. - CpG sites in RBCs with a significant change in methylation across time points.. - Log2 fold change for the expression of genes in liver in relation to change in methylation level of a CpG site in liver within the 10 kb downstream region, gene body, promoter region, and 10 kb upstream region that gene for Δ 1,2 . - Within the TSS region we did not find a significant change CpG site methylation located within a gene with significant change in expression. - Log2 fold change for the expression of genes in liver in relation to change in methylation level of a CpG site in liver within the 10 kb downstream region, gene body, promoter region, TSS region, and 10 kb upstream region of that gene for Δ 2,3 . - Log2 fold change for the expression of genes in hypothalamus in relation to change in methylation level of a CpG site in red blood cells within the 10 kb downstream region and gene body of that gene Δ 1,2 . - Within the 10 kb upstream region, promoter region, and TSS region we did not find a significant change CpG site methylation located within a gene with significant change in expression. - Log2 fold change for the expression of genes in hypothalamus in relation to change in methylation level of a CpG site in red blood cells within the 10 kb downstream region, promoter region, TSS region, and 10 kb upstream region of that gene for Δ 2,3 . - Within the gene body we did not find a significant change CpG site methylation located within a gene with significant change in expression.. - Log2 fold change for the expression of genes in ovary in relation to change in methylation level of a CpG site in red blood cells within the 10 kb downstream region, gene body, promoter region, TSS region, and 10 kb upstream region of that gene for Δ 1,2 . - Log2 fold change for the expression of genes in ovary in relation to change in methylation level of a CpG site in red blood cells within the 10 kb downstream region, gene body, promoter region, TSS region, and 10 kb upstream region of that gene for Δ 2,3 . - Log2 fold change for the expression of genes in liver in relation to change in methylation level of a CpG site in red blood cells within 10 kb downstream region, gene body, promoter region, TSS region, and 10 kb upstream region of that gene for Δ 1,2 . - Log2 fold change for the expression of genes in liver in relation to change in methylation level of a CpG site in red blood cells within 10 kb downstream region, gene body, promoter region, TSS region, and 10 kb upstream region of that gene for Δ 2,3 . - DNA methylation patterns and epigenetic memory. - Aging, cancer and nutrition: the DNA methylation connection. - Reversible DNA methylation regulates seasonal photoperiodic time measurement. - Seasonal variation in genome-wide DNA methylation patterns and the onset of seasonal timing of reproduction in great tits. - Widespread and tissue specific age-related DNA methylation changes in mice. - Age-related DNA methylation changes are tissue-specific with ELOVL2 promoter methylation as exception. - Dynamic changes in global and gene-specific DNA methylation during hibernation in adult thirteen-lined ground squirrels, Ictidomys tridecemlineatus. - DNA methylation changes induced by long and short photoperiods in Nasonia. - Temporally replicated DNA methylation patterns in great tit using reduced representation bisulfite sequencing. - Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. - On the use of blood samples for measuring DNA methylation in ecological epigenetic studies. - Integrated analysis of DNA methylation profiling and gene expression profiling identifies novel markers in lung cancer in Xuanwei, China. - Multiple correlation analyses revealed complex relationship between DNA methylation and mRNA expression in human peripheral blood mononuclear cells. - Cell and tissue type independent age-associated DNA methylation changes are not rare but common. - Alterations in DNA methylation of Fkbp5 as a determinant of blood-brain correlation of glucocorticoid exposure. - Gel-free multiplexed reduced representation bisulfite sequencing for large-scale DNA methylation profiling. - methylKit: a comprehensive R package for the analysis of genome- wide DNA methylation profiles
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