Results for “DNA Methylation”

DOE OSTI2025

Discovering methylated DNA motifs in bacterial nanopore sequencing data with MIJAMP

Abstract Bacterial DNA methylation is involved in diverse cellular functions, including modulation of gene expression, DNA repair, and restriction–modification systems for defense against viruses and other foreign DNA. Restriction systems hinder efforts to engineer organisms to produce fuels and chemicals from waste and renewable feedstocks by degrading DNA during transformation. Methylome analysis allows identification of motifs within a bacterial chromosome that may be targeted by native restriction enzymes. Further expression of the corresponding methyltransferases in Escherichia coli allows plasmid DNA to be protected from restriction in the target organism, thereby drastically enhancing transformation efficiency. Nanopore sequencing can detect methylated bases, but software is needed to transform modified base coordinates into methylated motifs. Here, we develop MIJAMP (MIJAMP Is Just A MethylBED Parser), a software package that was developed to discover methylated motifs from the output of ONT’s Modkit or other data in the methylBED format. MIJAMP employs a human-driven refinement strategy that empirically validates all motifs against genome-wide methylation data, thus eliminating incorrect motifs. MIJAMP also reports methylation data on specific, user-defined motifs. Using MIJAMP, we determined the methylated motifs both in a control strain (wild-type E. coli) and in Synecococcus sp. strain PCC7002, laying the foundation for improved transformation in this organism. MIJAMP is available at https://code.ornl.gov/alexander-public/mijamp/. One Sentence Summary: Here we describe software written to discover DNA methylation motifs from nanopore sequencing data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Multi-layered heterochromatin interaction as a switch for DIM2-mediated DNA methylation

Functional crosstalk between DNA methylation, histone H3 lysine-9 trimethylation (H3K9me3) and heterochromatin protein 1 (HP1) is essential for proper heterochromatin assembly and genome stability. However, how repressive chromatin cues guide DNA methyltransferases for region-specific DNA methylation remains largely unknown. Here, we report structure-function characterizations of DNA methyltransferase Defective-In-Methylation-2 (DIM2) in Neurospora . The DNA methylation activity of DIM2 requires the presence of both H3K9me3 and HP1. Our structural study reveals a bipartite DIM2-HP1 interaction, leading to a disorder-to-order transition of the DIM2 target-recognition domain that is essential for substrate binding. Furthermore, the structure of DIM2-HP1-H3K9me3-DNA complex reveals a substrate-binding mechanism distinct from that for its mammalian orthologue DNMT1. In addition, the dual recognition of H3K9me3 peptide by the DIM2 RFTS and BAH1 domains allosterically impacts the DIM2-substrate binding, thereby controlling DIM2-mediated DNA methylation. Together, this study uncovers how multiple heterochromatin factors coordinately orchestrate an activity-switching mechanism for region-specific DNA methylation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

DNA methylation–based age prediction and sex-specific epigenetic aging in a lizard with female-biased longevity

Sex differences in life span are widespread across animal taxa, but their causes remain unresolved. Alterations to the epigenome are hypothesized to contribute to vertebrate aging, and DNA methylation–based aging clocks allow for quantitative estimation of biological aging trajectories. Here, we investigate the influence of age, sex, and their interaction on genome-wide DNA methylation patterns in the brown anole (Anolis sagrei), a lizard with pronounced female-biased survival and longevity. We develop a series of age predictor models and find that, contrary to our predictions, rates of epigenetic aging were not slower in female lizards. However, methylation states at loci acquiring age-associated changes appear to be more “youthful” in young females, suggesting that female DNA methylomes are preemptively fortified in early life in opposition to the direction of age-related drift. Collectively, our findings provide insights into epigenetic aging in reptiles and suggest that early-life epigenetic profiles may be more informative than rates of change for predicting sex biases in longevity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Genetic_and_epigenetic_signatures_of_Populus_Trichocarpa_in_response_to_abiotic_stress

Plants respond to abiotic stresses such as drought, heat, and salinity through both shared and stress-specific regulatory pathways. However, the role of epigenetic mechanisms, particularly DNA methylation, in modulating these responses is still underexplored. Here, we integrated transcriptome profiling with whole-genome bisulfite sequencing (WGBS) to investigate the dynamic relationship between gene expression and DNA methylation in Populus trichocarpa during brief early-stage exposure to abiotic stress. Each stress elicited distinct transcriptional and methylation signatures; however, a subset of conserved stress-responsive genes was commonly regulated across treatments. Approximately 5% of differentially expressed genes also displayed differential methylation patterns, suggesting a coordinated role for DNA methylation in regulating gene expression. Motif enrichment analysis of differentially methylated regions revealed binding sites of key transcription factor families, including ERF, bHLH, and ABF, highlighting potential role for methylation in modulating transcription factor targeting. Furthermore, we identified stress-inducible molecular markers with potential applications in early stress detection and functional dissection of gene regulatory pathways. Together, these findings provide new insights into the coordinated genetic and epigenetic responses to abiotic stress and provide a foundation for developing biosensors and breeding strategies to enhance stress resilience woody plants.

CBI↗

DOE OSTI2026

Genetic and epigenetic signatures of Populus trichocarpa in response to abiotic stresses

Plants respond to abiotic stresses such as drought, heat, and salinity through both shared and stress-specific regulatory pathways. However, the role of epigenetic mechanisms, particularly DNA methylation, in modulating these responses is still underexplored. Here, we integrated transcriptome profiling with whole-genome bisulfite sequencing (WGBS) to investigate the dynamic relationship between gene expression and DNA methylation in Populus trichocarpa during brief early-stage exposure to abiotic stress. Each stress elicited distinct transcriptional and methylation signatures; however, a subset of conserved stress-responsive genes was commonly regulated across treatments. We found that ∼5-6% of differentially expressed genes also displayed differential methylation patterns, suggesting a coordinated role for DNA methylation in regulating gene expression. Motif enrichment analysis of differentially methylated regions revealed binding sites of key transcription factor families, including ERF, bHLH, and ABF, highlighting potential role for methylation in modulating transcription factor targeting. Furthermore, we identified stress-inducible molecular markers with potential applications in early stress detection and functional dissection of gene regulatory pathways. Together, these findings provide new insights into the coordinated genetic and epigenetic responses to abiotic stress and provide a foundation for developing biosensors and breeding strategies to enhance stress resilience woody plants.

DNA methylation↗

DOE OSTI2025

Unveiling a pervasive DNA adenine methylation regulatory network in the early-diverging fungus Rhizopus microsporus

Development of the DNA affinity purification and sequencing (DAP-seq) technique has allowed genome-scale studies of transcription factor (TF)-binding sites with high reproducibility. Here, we apply this technique to the human opportunistic pathogen Rhizopus microsporus, a mucoralean fungus belonging to the understudied group of early-diverging fungi. We characterize genome-wide binding sites of 58 TFs encoded by genes regulated through adenine methylation and representing major TF families. This analysis reveals their binding profiles and recognized sequences, expanding and diversifying the catalog of known fungal motifs. By integrating this data with DNA 6-methyladenine profiling, we uncover the extensive direct and indirect impact of this epigenetic modification on the regulation of gene expression. Furthermore, we use the generated data to identify TFs involved in biologically relevant processes such as zinc metabolism and light response. Our work enhances our understanding of regulatory mechanisms in R. microsporus and provides broader insights into gene regulation across the fungal kingdom.

Lax, Carlos [Universidad de Murcia (Spain)] (ORCID↗

DOE OSTI2024

The ICF syndrome protein CDCA7 harbors a unique DNA binding domain that recognizes a CpG dyad in the context of a non-B DNA

CDCA7, encoding a protein with a carboxyl-terminal cysteine-rich domain (CRD), is mutated in immunodeficiency, centromeric instability, and facial anomalies (ICF) syndrome, a disease related to hypomethylation of juxtacentromeric satellite DNA. How CDCA7 directs DNA methylation to juxtacentromeric regions is unknown. Here, we show that the CDCA7 CRD adopts a unique zinc-binding structure that recognizes a CpG dyad in a non-B DNA formed by two sequence motifs. CDCA7, but not ICF mutants, preferentially binds the non-B DNA with strand-specific CpG hemi-methylation. The unmethylated sequence motif is highly enriched at centromeres of human chromosomes, whereas the methylated motif is distributed throughout the genome. At S phase, CDCA7, but not ICF mutants, is concentrated in constitutive heterochromatin foci, and the formation of such foci can be inhibited by exogenous hemi-methylated non-B DNA bound by the CRD. Binding of the non-B DNA formed in juxtacentromeric regions during DNA replication provides a mechanism by which CDCA7 controls the specificity of DNA methylation.

Science & Technology - Other Topics↗

DOE OSTI2025

Pathogenic SIV infection is associated with acceleration of epigenetic age in rhesus macaques

HIV infection accelerates biological aging, but the contribution of the host’s age to this process is unknown. We investigated the influence of SIV infection in macaques (SIVmac) on the risk of comorbidities and aging in young and old rhesus macaques (RMs) by assessing pathogenesis markers, DNA methylation–based epigenetic age (EA), and EA acceleration (EAA) in blood and tissues. Initially, upon SIV infection, the young RMs showed greater resilience to CD4 + T cell depletion, better control of T cell activation, hypercoagulation, and excessive inflammation, yet this resilience was progressively lost in the advanced stages of infection. During the late stages of infection, the young RMs, but not the aged ones, showed an increase in EA in PBMCs; also, EAA in the cerebellum and heart of young RMs was higher compared with old RMs. SIV infection was more pathogenic in aged animals in early stages, leading to a more rapid disease progression; however, accelerated aging mostly affected young animals, so that the levels of multiple key pathogenesis markers in the young RMs converged toward those specific to aged ones in the late stages of infection. We conclude that SIV infection–driven age acceleration is tissue specific, and that host age influences the susceptibility of different tissues to enhanced aging.

Research & Experimental Medicine↗

DOE OSTI2025

Multi-omics data compendium of pancreatic islet and β cell responses to pro-inflammatory cytokines

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 10 (Pck010)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 11 (Pck011)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 12 (Pck012)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 13 (Pck013)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 14 (Pck014)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 15 (Pck015)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 16 (Pck016)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 17 (Pck017)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗

DOE OSTI2025

Multi-omics data compendium: Data package 18 (Pck018)

In type 1 diabetes (T1D), autoimmune response and inflammation cause the death of pancreatic ß cells, leading to the body’s inability to produce insulin and maintain glucose homeostasis. This process is at least in part mediated by pro-inflammatory cytokines, such as interferon (IFN)a, IFN?, interleukin (IL)-1ß, and tumor necrosis factor (TNF)a, which induce ß-cell dysfunction and apoptosis. A deep understanding of the ß-cell signaling and regulatory networks induced by these cytokines could lead to the identification of therapeutic targets to prevent T1D development. To study cytokine-mediated islets/ß-cell signaling and regulatory networks, a variety of omics experiments have been conducted, including transcriptomics, epigenomics (DNA methylation, UMI-4C, ATAC-seq & ChIP-seq), proteomics (bottom-up, top-down, post-translational modification analysis), lipidomics, and metabolomics. The combination of these datasets can be instrumental in identifying signaling components and regulatory factors involved in ß-cell stress/death. Here, we aggregated these multiple omics datasets into a centralized location, providing a quality-controlled and statistically rigorous resource for investigators seeking to holistically study ß-cell regulation by pro-inflammatory cytokines.

Sarkar, Soumyadeep [Pacific Northwest National Lab↗