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. 2021 Jan 18;13:12. doi: 10.1186/s13148-020-00998-z

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© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 4 — Discovery and characterization of extreme phenotype CpGs among STS and LTS groups. a Hexbin plot of the mean methylation of each CpG for the LTS group versus Δβ_(STS-LTS). Upper left and bottom right regions demarcated by dashed lines indicate CpGs deviating from the extremes in STS and analyzed further. The top-left represents CpGs that are lowly methylated in LTS (β = 0 to 0.1; n = 1204) and gain a minimum of 10% methylation value in STS. The bottom-right represents CpGs highly methylated in LTS (β = 0.9 to 1; n = 821) that lose at least 10% methylation in STS. b Scatterplot showing methylation changes of LTS (open circles) and STS (solid circles) against normal kidney (CON) plotted against normal kidney methylation levels on the x-axis. Unmethylated CpGs in LTS are colored in black (n = 701) and fully methylated CpGs in LTS are represented in red (n = 514). c Flowchart denoting relationships between the 5929 DMCpGs (from Fig. 1), and the 2025 CpGs deviating from the extremes analyzed here. The overlap of the LTS fully methylated and unmethylated CpGs with TCGA-KIRC is shown in the blue boxes. The progressive analysis of the overlapping CpGs for survival, and methylation-expression correlation are indicated in the flow diagram. This analysis was conducted using 318 KIRC ccRCCs for which both 450K and RNA-seq data were available. d Heatmap showing the nine hypermethylated and three hypomethylated CpGs significantly associated with survival and correlated with expression of their respective genes from panel c. Red color in the heatmap represents a positive correlation between the methylation of the CpG and expression of its respective gene; blue color represents a negative correlation. The color bar on the left of the heatmap indicates the genomic feature where each site in located: body (blue), promoter (red). All promoter CpGs are inversely correlated with the expression of their respective genes. The information on the right indicates the methylation status linked to longer patient survival (hyper or hypo) for the CpG in KIRC, the identifier for each CpG, and the name of the associated gene (per Illumina 450K manifest). CpGs in red text are associated with better survival when hypermethylated. CpGs in blue text are associated with better patient survival if hypomethylated. e PCA plot of 2025 CpG deviating from extremes in STS showing the ability of these sites to separate LTS (red) and STS (blue) groups. Percentages of variance that can be explained by each principal component are indicated