DNA methylation disruption reshapes the hematopoietic differentiation landscape

Izzo, Franco; Lee, Stanley Chun-Wei; Poran, Asaf; Chaligné, Ronan; Gaiti, Federico; Gross, Baptiste; Murali, Rekha; Deochand, Sunil; Ang, Chelston; Jones, Philippa Wyndham; Nam, Anna S.; Kim, Kyu‐Tae; Kothen-Hill, Steven; Schulman, Rafael C.; Ki, Michelle; Lhoumaud, Priscillia; Skok, Jane A.; Viny, Aaron D.; Levine, Ross L.; Kenigsberg, Ephraim; Abdel‐Wahab, Omar; Landau, Dan A.

doi:10.1038/s41588-020-0595-4

Cited by 173 publications

(182 citation statements)

References 86 publications

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“…Such methods may be particularly helpful in studying early clonal expansions in human tissues 93 . Recently, clonal expansions within morphologically normal tissues, resulting in somatically acquired mosaicisms, were identified throughout the body [4][5][6] .…”

Section: Somatic Genotyping In High-throughput Single-cellmentioning

confidence: 99%

Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics

2020

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Cancer represents an evolutionary process through which growing malignant populations genetically diversify, leading to tumour progression, relapse and resistance to therapy. In addition to genetic diversity, the cell-to-cell variation that fuels evolutionary selection also manifests in cellular states, epigenetic profiles, spatial distributions and interactions with the microenvironment. Therefore, the study of cancer requires the integration of multiple heritable dimensions at the resolution of the single cell-the atomic unit of somatic evolution. In this Review, we discuss emerging analytic and experimental technologies for single-cell multi-omics that enable the capture and integration of multiple data modalities to inform the study of cancer evolution. These data show that cancer results from a complex interplay between genetic and non-genetic determinants of somatic evolution.

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Section: Somatic Genotyping In High-throughput Single-cellmentioning

confidence: 99%

Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics

2020

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“…DNA methylation (DNAm) refers to the addition of a methyl group (CH3) to a CpG dinucleotide (5'-C-phosphate-G-3'). In most cases, DNAm is associated with transcriptional repression via its effect on chromatin organization, and is thought to control a number of cellular properties, including differentiation [10], replication [11], Xinactivation [12], stress response [13], and genomic imprinting [14]. Initially, de novo methyltransferases establish methylation patterns that are necessary for organismal development [15,16].…”

Section: Introductionmentioning

confidence: 99%

Cellular aging in vitro recapitulates multi-tissue epigenetic aging in vivo

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Morselli

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et al. 2020

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Aging is known to elicit dramatic changes to DNA methylation (DNAm). However, the causes and consequences of such alterations to the epigenome remain unclear. Therefore, the utility of biomarkers of aging based on DNAm patterns will depend on our ability to link them to cellular features, such as proliferation, differentiation, transcriptional repression/activation, senescence, and transformation. Using DNAm from serially passaged mouse embryonic fibroblasts (MEFs), we developed a predictor of replication that is able to accurately predict passage number in independent sample. Our measure, termed DNAmRep, was shown to strongly increase with age when examined in multiple tissues (blood, liver, kidney, lung and adipose). Furthermore, we observed replicative deceleration in animal undergoing caloric restriction. Upon reprogramming to iPSCs, cells derived from both lung and kidney fibroblasts exhibited resetting of our DNAmRep measure. This measure also increased in response to differentiation among B-cell populations. Enrichment analysis implicated CBX7, RNF2 and HDAC2 as potentially important transcription factors and chromatin regulators in the DNAm replication signature. Finally, DNAmRep correlated with beta-galactosidase activity in replicative senescent MEFs, but not in radiation or drug induced senescent MEFs, and was partially separated by immortalization with Large T antigen K1 mutant (LTK1), suggesting that it reflects mitotic history, rather than senescent state. Overall, this study identifies mitotically-derived alterations to the methylome, which partially underlie known epigenetic aging phenomena.

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“…Interestingly, DNA methylation by DNMT3A or the Tet methylcytosine dioxygenase (TET2) was shown to regulate hematopoietic differentiation by controlling accessible binding sites for hematopoietic transcription factors including GATA1. 7 Moreover, very recent work has shown that precise DNA methylation patterning can control the binding and regulation of GATA1 activity. 8 Collectively, these findings suggest that the erythroleukemia-like phenotype in Nsd1 -/mice is probably the consequence of altered crosstalk between histone and DNA methylation.…”

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confidence: 99%