DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse

Zhou, Wanding; Hinoue, Toshinori; Barnes, Bret; Mitchell, Owen; Iqbal, Waleed; Lee, Sol Moe; Foy, Kelly K.; Lee, Kwang-Ho; Moyer, Ethan Jacob; VanderArk, Alexandra; Koeman, Julie; Ding, Wubin; Kalkat, Manpreet; Spix, Nathan J; Eagleson, Bryn; Pospisilik, J. Andrew; Szabó, Piroska E.; Bartolomei, Marisa S.; Schaaf, Nicole A. Vander; Kang, Liang; Wiseman, Ashley K.; Jones, Peter A.; Krawczyk, Connie M.; Adams, Marie; Porecha, Rishi; Chen, Brian H.; Shen, Hui; Laird, Peter W.

doi:10.1016/j.xgen.2022.100144

Cited by 70 publications

(95 citation statements)

References 177 publications

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“…We also did not assess the effect of SNPs on MMB probe behavior, but Zhou et al. (2022) published work describing the design and annotation of MMB.…”

Section: Discussionmentioning

confidence: 99%

Comparative analysis of Illumina Mouse Methylation BeadChip and reduced-representation bisulfite sequencing for routine DNA methylation analysis

Fennell

Härtel²,

McKeone³

et al. 2022

Cell Reports Methods

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“…We also did not assess the effect of SNPs on MMB probe behavior, but Zhou et al. (2022) published work describing the design and annotation of MMB.…”

Section: Discussionmentioning

confidence: 99%

Comparative analysis of Illumina Mouse Methylation BeadChip and reduced-representation bisulfite sequencing for routine DNA methylation analysis

Fennell

Härtel²,

McKeone³

et al. 2022

Cell Reports Methods

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“…4k). In contrast, the recently described BeadChip multi-tissue epigenetic clock 35 —the only mouse microarray-based clock that is commercially available—uniformly underpredicted the age of samples, possibly owing to a skewed age and sample distribution in the original study 35 . Finally, the RRBS-based mouse blood clock 11 predicted samples with more accuracy than the BeadChip clock but with more variation than TIME-Seq.…”

Section: Resultsmentioning

confidence: 92%

“…For clock analysis, the TIME-Seq mouse blood and multi-tissue clocks were applied to TIME-Seq data as described above, whereas the RRBS-based mouse blood clock was applied in a similar fashion using the reported loci, weights, and formula 12 , replacing any missing values with the mean methylation from all other samples. The BeadChip clock was applied to BeadChip data as reported 56 .…”

Section: Benchmarking Time-seq Against Beadchip and Rrbsmentioning

confidence: 99%

TIME-Seq Enables Scalable and Inexpensive Epigenetic Age Predictions

Griffin¹,

Kane²,

Trapp

et al. 2021

Preprint

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Epigenetic “clocks” based on DNA methylation (DNAme) are the most robust and widely employed aging biomarker. They have been built for numerous species and reflect gold-standard interventions that extend lifespan. However, conventional methods for measuring epigenetic clocks are expensive and low-throughput. Here, we describe Tagmentation-based Indexing for Methylation Sequencing (TIME-Seq) for ultra-cheap and scalable targeted methylation sequencing of epigenetic clocks and other DNAme biomarkers. Using TIME-Seq, we built and validated inexpensive epigenetic clocks based on genomic and ribosomal DNAme in hundreds of mice and human samples. We also discover it is possible to accurately predict age from extremely low-cost shallow sequencing (e.g., 10,000 reads) of TIME-Seq libraries using scAge, a probabilistic age-prediction algorithm originally applied to single cells. Together, these methods reduce the cost of DNAme biomarker analysis by more than two orders of magnitude, thereby expanding and democratizing their use in aging research, clinical trials, and disease diagnosis.

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“…Array BeadChips were scanned on the Illumina iScan system and signals where assigned by using Illumina Genome Studio v2011.1 software, to produce IDAT files. CpG probe selection (Zhou et al, 2022) included an array of target and random, controls sequences. The DNA methylation array analysis was performed using SeSAMe (Zhou et al, 2018) and its wrapper pipeline SeSAMeStr (10.5281/zenodo.7510575).…”

Section: Dna Methylation Arraymentioning

confidence: 99%

Identification of two β-cell subtypes by 7 independent criteria

Dror¹,

Fagnocchi²,

Wegert³

et al. 2023

Preprint

Self Cite

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Despite the recent explosion in surveys of cell-type heterogeneity, the mechanisms that specify and stabilize highly related cell subtypes remain poorly understood. Here, focusing initially on exploring quantitative histone mark heterogeneity, we identify two major sub-types of pancreatic β-cells (βHIand βLO). βHIand βLOcells differ in their size, morphology, cytosolic and nuclear ultrastructure, transcriptional output, epigenomes, cell surface marker, and function. Importantly, βHIand βLOcells can be FACS separated live into CD24+ (βHI) and CD24- (βLO) fractions. From an epigenetic viewpoint, βHI-cells exhibit ~4-fold higher levels of H3K27me3, more compacted chromatin, and distinct chromatin organization that associates with a specific pattern of transcriptional output. Functionally, βHIcells have increased mitochondrial mass, activity, and insulin secretion both in vivo and ex vivo. Critically, Eed and Jmjd3 loss-of-function studies demonstrate that H3K27me3 dosage is a significant regulator of βHI/ βLOcell ratio in vivo, yielding some of the first-ever specific models of β-cell sub-type distortion. βHIand βLOsub-types are conserved in humans with βHI-cells enriched in human Type-2 diabetes. These data identify two novel and fundamentally distinct β-cell subtypes and identify epigenetic dosage as a novel regulator of β-cell subtype specification and heterogeneity.

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DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse

Cited by 70 publications

References 177 publications

Comparative analysis of Illumina Mouse Methylation BeadChip and reduced-representation bisulfite sequencing for routine DNA methylation analysis

Comparative analysis of Illumina Mouse Methylation BeadChip and reduced-representation bisulfite sequencing for routine DNA methylation analysis

TIME-Seq Enables Scalable and Inexpensive Epigenetic Age Predictions

Identification of two β-cell subtypes by 7 independent criteria

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