A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution

Zhu, Tianyu; Liu, Jacklyn; Beck, Stephan; Sun, Ping; Capper, David; Lechner, Matt; Thirlwell, Chrissie; Breeze, Charles E.; Teschendorff, Andrew E.

doi:10.1038/s41592-022-01412-7

Cited by 63 publications

(82 citation statements)

References 102 publications

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“…We did not observe a significant difference in proportions of proliferative respiratory suprabasal cells, confirming that the model uses more than a simple panel of proliferation genes to map tumor cell identity. Finally, there have been conflicting data on the existence of a positive correlation between tumor grade and degree of T cell infiltration in ENB 19,23,24 . With our model, we find that higher grade ENBs do have a higher proportion of CD8 T cells.…”

Section: Resultsmentioning

confidence: 99%

“…The copyright holder for this preprint this version posted October 21, 2022. ; https://doi.org/10.1101/2022.10.18.512713 doi: bioRxiv preprint proliferation genes to map tumor cell identity. Finally, there have been conflicting data on the existence of a positive correlation between tumor grade and degree of T cell infiltration in ENB 19,23,24 . With our model, we find that higher grade ENBs do have a higher proportion of CD8 T cells.…”

Section: Pseudo Deconvolution Of Normal Oe and Enb Bulk Rna-seq Samplesmentioning

confidence: 99%

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Deconstructing olfactory epithelium developmental pathways in esthesioneuroblastoma

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Hachem

Jang

et al. 2022

Preprint

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ImportanceEsthesioneuroblastoma (ENB) is a rare tumor arising from the olfactory cleft region of the nasal cavity. Due to the low incidence of this tumor, as well as an absence of established reagents such as cell lines or murine models, understanding the mechanisms driving ENB pathobiology has been challenging.ObjectiveHere, we sought to apply advances from research on the human olfactory epithelial neurogenic niche, along with new biocomputational approaches, to better understand the cellular and molecular factors in low and high grade ENB and how specific transcriptomic markers may predict prognosis.Design, Setting, and ParticipantsThis was a retrospective biocomputational analysis utilizing human ENB and normal olfactory mucosal tissue and clinical outcomes data. The setting was a large academic medical center. Participants were selected based on available datasets, and included ENB patients across all four tumor grades, and patients with normal olfactory mucosa.Main Outcomes and MeasuresOutcomes include deconvolution analysis, differential gene expression analysis, overall survival, and immunohistochemistry. A machine learning model was used to predict cell-type proportion signatures in ENB, and Kaplan-Meier curves with associated log-rank tests were used to estimate differences in overall survival.ResultsWe analyzed a total of 19 ENB samples (9 low grade I/II, 10 high grade III/IV) with available bulk RNA-Sequencing and survival data, along with 10 samples from normal olfactory mucosa (3 bulk RNA-Sequencing, 7 single cell RNA-Sequencing). The bulk RNA-Sequencing deconvolution model identified a significant increase in globose basal cell (GBC) and CD8 T cell identities in high grade tumors (GBC from approximately 0% to 8%, CD8 T cell from 0.7% to 2.2%), and significant decreases in mature neuronal, Bowman’s gland, and olfactory ensheathing programs, in high grade tumors (mature neuronal from 3.7% to approximately 0%, Bowman’s gland from 18.6% to 10.5%, olfactory ensheathing from 3.4% to 1.1%). Trajectory analysis identified potential regulatory pathways in proliferative ENB cells, including PRC2. Survival analysis guided by gene expression in bulk RNA-Sequencing data identified favorable prognostic markers such as SOX9, S100B, and PLP1 expression.Conclusions and RelevanceOur analyses provide a basis for additional translational research on ENB management, as well as identification of potential new prognostic markers.

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Section: Resultsmentioning

confidence: 99%

Section: Pseudo Deconvolution Of Normal Oe and Enb Bulk Rna-seq Samplesmentioning

confidence: 99%

Deconstructing olfactory epithelium developmental pathways in esthesioneuroblastoma

Finlay

Hachem

Jang

et al. 2022

Preprint

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“…DNA methylation plays key roles in immune system homeostasis and inflammatory responses [ 50 ]. However, due to the current limitations of single-cell methylation sequencing technology and the cost [ 13 ], studies of DNA methylation in COVID-19 patients were only carried out at the bulk-tissue level, which may not explain cell-type-specific DNA methylation variations. We developed an effective new analytical pipeline that attempts to transfer bulk-tissue phenomena to the single-cell DNA methylation dimension to reveal specific cell types of DNA methylation variations in COVID-19 by integrating multi-omics data.…”

Section: Discussionmentioning

confidence: 99%

“…Single-cell DNA methylation sequencing makes it possible to explore cellular epigenetic heterogeneity [ 12 ]. Unfortunately, it is unscalable to large cohort studies because the technologies are costly and not yet mature [ 13 , 14 , 15 ]. Bulk-tissue studies in the past ten years have resulted in the accumulation of massive data and corresponding phenotype information [ 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Identification of COVID-19-Associated DNA Methylation Variations by Integrating Methylation Array and scRNA-Seq Data at Cell-Type Resolution

Wang

Xiong

Yang

et al. 2022

Genes

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Single-cell transcriptome studies have revealed immune dysfunction in COVID-19 patients, including lymphopenia, T cell exhaustion, and increased levels of pro-inflammatory cytokines, while DNA methylation plays an important role in the regulation of immune response and inflammatory response. The specific cell types of immune responses regulated by DNA methylation in COVID-19 patients will be better understood by exploring the COVID-19 DNA methylation variation at the cell-type level. Here, we developed an analytical pipeline to explore single-cell DNA methylation variations in COVID-19 patients by transferring bulk-tissue-level knowledge to the single-cell level. We discovered that the methylation variations in the whole blood of COVID-19 patients showed significant cell-type specificity with remarkable enrichment in gamma-delta T cells and presented a phenomenon of hypermethylation and low expression. Furthermore, we identified five genes whose methylation variations were associated with several cell types. Among them, S100A9, AHNAK, and CX3CR1 have been reported as potential COVID-19 biomarkers previously, and the others (TRAF3IP3 and LFNG) are closely associated with the immune and virus-related signaling pathways. We propose that they might serve as potential epigenetic biomarkers for COVID-19 and could play roles in important biological processes such as the immune response and antiviral activity.

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“…Consequently, important differences could be missed or overlooked when using bulk tissue analysis methods. Single‐cell approaches are becoming more feasible as evidenced by increasing number of publications, including the recent creation of a human “pan‐tissue DNA methylation atlas…at cell‐type resolution” (Zhu et al, 2022). Application of this approach to TOF should help to shed new light on how alterations in DNA methylation status are conserved across tissue types and provide further insight on how they may contribute to TOF (Zhu et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Comparison of DNA methylation patterns across tissue types in infants with tetralogy of Fallot

Nelson

Kwok

Braganca

et al. 2022

Birth Defects Research

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Background Environmental factors may influence the development of tetralogy of Fallot (TOF), and DNA methylation patterns may reveal specific chemical signatures of perturbations during cardiac development. We investigated whether blood and buccal cells could be viable surrogates for myocardium. Methods We measured epigenome‐wide DNA methylation at 866,895 5’‐cytosine‐phosphate‐guanine‐3’ (CpG) sites in blood (n=3), buccal cells (n=3), and right ventricular myocardium (n=4) collected from infants with TOF and compared the percent of differentially methylated CpG sites across tissue types. Gene‐specific DNA methylation profiles were also analyzed for ten representative genes associated with heart development. Welch's ANOVAs compared general methylation between tissue types. Results Comparison of DNA methylation profiles across blood, buccal, and myocardium suggested myocardium and buccal samples were most similar, differing in DNA methylation at only 1.3% (11,386) of CpG sites whereas myocardium and blood were most dissimilar, having 146,857 statistically dissimilar methylated CpG sites (~17% dissimilarity; adjusted p < 0.01 for each site). Buccal swabs were significantly more variable (p < .001) than either blood or myocardial samples. In gene‐specific analyses, SCO2, GATA4, NOTCH4, WNT7A, and DKK2 showed conserved DNA methylation profiles across tissue types, while HAND1, JAG1, NKX2‐5, TBX5 and TBX20 showed more distinctive tissue‐specific patterns of DNA methylation. Conclusions Compared with blood, buccal tissue more closely mirrors the myocardial methylome, with >10‐fold similarity. Nevertheless, both buccal and blood tissue capture highly conserved DNA methylation patterns at specific genetic loci related to cardiac development. Buccal cheek swabs may be a useful surrogate tissue type for future investigations of TOF‐specific epigenetic profiles.

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A pan-tissue DNA methylation atlas enables in silico decomposition of human tissue methylomes at cell-type resolution

Cited by 63 publications

References 102 publications

Deconstructing olfactory epithelium developmental pathways in esthesioneuroblastoma

Deconstructing olfactory epithelium developmental pathways in esthesioneuroblastoma

Identification of COVID-19-Associated DNA Methylation Variations by Integrating Methylation Array and scRNA-Seq Data at Cell-Type Resolution

Comparison of DNA methylation patterns across tissue types in infants with tetralogy of Fallot

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