Dataset Information

Deconvolution of cellular subsets in human tissue based on targeted DNA methylation analysis at individual CpG sites.

ABSTRACT: BACKGROUND:The complex composition of different cell types within a tissue can be estimated by deconvolution of bulk gene expression profiles or with various single-cell sequencing approaches. Alternatively, DNA methylation (DNAm) profiles have been used to establish an atlas for multiple human tissues and cell types. DNAm is particularly suitable for deconvolution of cell types because each CG dinucleotide (CpG site) has only two states per DNA strand-methylated or non-methylated-and these epigenetic modifications are very consistent during cellular differentiation. So far, deconvolution of DNAm profiles implies complex signatures of many CpGs that are often measured by genome-wide analysis with Illumina BeadChip microarrays. In this study, we investigated if the characterization of cell types in tissue is also feasible with individual cell type-specific CpG sites, which can be addressed by targeted analysis, such as pyrosequencing. RESULTS:We compiled and curated 579 Illumina 450k BeadChip DNAm profiles of 14 different non-malignant human cell types. A training and validation strategy was applied to identify and test for cell type-specific CpGs. We initially focused on estimating the relative amount of fibroblasts using two CpGs that were either hypermethylated or hypomethylated in fibroblasts. The combination of these two DNAm levels into a "FibroScore" correlated with the state of fibrosis and was associated with overall survival in various types of cancer. Furthermore, we identified hypomethylated CpGs for leukocytes, endothelial cells, epithelial cells, hepatocytes, glia, neurons, fibroblasts, and induced pluripotent stem cells. The accuracy of this eight CpG signature was tested in additional BeadChip datasets of defined cell mixtures and the results were comparable to previously published signatures based on several thousand CpGs. Finally, we established and validated pyrosequencing assays for the relevant CpGs that can be utilized for classification and deconvolution of cell types. CONCLUSION:This proof of concept study demonstrates that DNAm analysis at individual CpGs reflects the cellular composition of cellular mixtures and different tissues. Targeted analysis of these genomic regions facilitates robust methods for application in basic research and clinical settings.

SUBMITTER: Schmidt M

PROVIDER: S-EPMC7687708 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Deconvolution of cellular subsets in human tissue based on targeted DNA methylation analysis at individual CpG sites.

Schmidt Marco M Maié Tiago T Dahl Edgar E Costa Ivan G IG Wagner Wolfgang W

BMC biology 20201124 1

<h4>Background</h4>The complex composition of different cell types within a tissue can be estimated by deconvolution of bulk gene expression profiles or with various single-cell sequencing approaches. Alternatively, DNA methylation (DNAm) profiles have been used to establish an atlas for multiple human tissues and cell types. DNAm is particularly suitable for deconvolution of cell types because each CG dinucleotide (CpG site) has only two states per DNA strand-methylated or non-methylated-and th ...[more]

PMID: 33234153

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Project description:Kaposi's sarcoma-associated herpesvirus (KSHV, HHV-8) is a gammaherpesvirus associated with several human malignancies. DNA methylation at CpG dinucleotides is an epigenetic mark dysregulated in many cancer types and in KSHV-infected cells. Several previous studies have analyzed in detail the CpG methylation of the KSHV episomal genomes, but little is known about the impact of KSHV on the human genome. Our knowledge of cellular CpG methylation in the context of KSHV infection is currently limited to four hypermethylated human gene promoters. Therefore, we undertook a comprehensive CpG methylation analysis of the human methylome in KSHV-infected cells and KSHV-associated primary effusion lymphoma (PEL). We performed Infinium HumanMethylation450K and MethylationEpic BeadChip arrays and identified panels of hyper- and hypomethylated cellular promoters in KSHV-infected cells. We combined our genome-wide methylation analysis with high-throughput RNA sequencing (RNA-seq) to add functional outcomes to the virally induced methylation changes. We were able to correlate many downregulated genes with promoter hypermethylation and upregulated genes with hypomethylation. In addition, we show that treating the cells with a demethylating agent leads to reexpression of these downregulated genes, indicating that, indeed, DNA methylation plays a role in the repression of these human genes. Comparison between de novo infection and PEL suggests that the virus induces initial hypermethylation followed by a slow increase in genome-wide hypomethylation. This study extends our understanding of the relationship between epigenetic changes induced by KSHV infection and tumorigenesis.IMPORTANCE In cancer cells, certain promoters become aberrantly methylated, contributing to the phenotype of the tumor. KSHV infection seems to modify cellular CpG methylation, but only a few methylated promoters have been identified in KSHV-infected cells. Here, we investigated the CpG methylation of the human genome in KSHV-associated primary effusion lymphoma (PEL) and KSHV-infected cells. We have identified many hyper- and hypomethylated gene promoters and correlated their methylation with cellular gene expression. These differentially methylated cellular promoters can distinguish KSHV-positive cells from uninfected cells and may serve as the foundation for the use of these differentially methylated regions as potential biomarkers for KSHV-associated malignancies. Drugs that reverse these cancerous methylation patterns have the potential to inhibit tumor growth. Here, we show that treating PEL cells with a demethylating drug (5-aza-2'-deoxycytidine) led to inhibition of cell growth, raising the possibility of testing this drug for the treatment of PEL.

Project description:BACKGROUND: The Human Papillomavirus (HPV) genome is divided into early and late coding sequences, including 8 open reading frames (ORFs) and a regulatory region (LCR). Viral gene expression may be regulated through epigenetic mechanisms, including cytosine methylation at CpG dinucleotides. We have analyzed the distribution of CpG sites and CpG islands/clusters (CGI) among 92 different HPV genomes grouped in function of their preferential tropism: cutaneous or mucosal. We calculated the proportion of CpG sites (PCS) for each ORF and calculated the expected CpG values for each viral type. RESULTS: CpGs are underrepresented in viral genomes. We found a positive correlation between CpG observed and expected values, with mucosal high-risk (HR) virus types showing the smallest O/E ratios. The ranges of the PCS were similar for most genomic regions except E4, where the majority of CpGs are found within islands/clusters. At least one CGI belongs to each E2/E4 region. We found positive correlations between PCS for each viral ORF when compared with the others, except for the LCR against four ORFs and E6 against three other ORFs. The distribution of CpG islands/clusters among HPV groups is heterogeneous and mucosal HR-HPV types exhibit both lower number and shorter island sizes compared to cutaneous and mucosal Low-risk (LR) HPVs (all of them significantly different). CONCLUSIONS: There is a difference between viral and cellular CpG underrepresentation. There are significant correlations between complete genome PCS and a lack of correlations between several genomic region pairs, especially those involving LCR and E6. L2 and L1 ORF behavior is opposite to that of oncogenes E6 and E7. The first pair possesses relatively low numbers of CpG sites clustered in CGIs while the oncogenes possess a relatively high number of CpG sites not associated to CGIs. In all HPVs, E2/E4 is the only region with at least one CGI and shows a higher content of CpG sites in every HPV type with an identified E4. The mucosal HR-HPVs show either the shortest CGI size, followed by the mucosal LR-HPVs and lastly by the cutaneous viral subgroup, and a trend to the lowest CGI number, followed by the cutaneous viral subgroup and lastly by the mucosal LR-HPVs.

Dataset Information

Deconvolution of cellular subsets in human tissue based on targeted DNA methylation analysis at individual CpG sites.

Publications

Deconvolution of cellular subsets in human tissue based on targeted DNA methylation analysis at individual CpG sites.

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