Biology subjects

Kaplan, T.

Publications and source records attributed to Kaplan, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Functional characterization of bat limb regulatory elements

Bats are the only mammals capable of powered flight and roost head-down. However, the molecular changes shaping bat limbs remain largely unknown. Here, we used comparative functional genomics coupled with mouse-bat sequence swaps to identify key regulatory elements important in bat limb development. We generated and compared bat and mouse forelimb and hindlimb genomic datasets at key wing developmental timepoints, followed by mouse enhancer assays to characterize sequences showing differences between species. We then swapped six mouse enhancer sequences with their corresponding bat sequences, obtaining a variety of bat limb associated phenotypes, including ossification delay, longer digits, thicker skin and symmetrical hindlimb digits. Our work provides a genomic catalog of genes and regulatory elements involved in bat limb development and through extensive characterization in mice shows how changes in regulatory elements lead to small phenotypic changes that together contribute to bat limb development.

developmental biology↗

bioRxiv2026

Systematic errors in enzymatic conversion limit cell-free DNA methylation specificity

Enzymatic methylation sequencing (EM-seq) converts unmethylated cytosines to uracils while preserving DNA integrity, making it attractive for liquid biopsies. Here we report a reproducible fragment-level over-conversion error in EM-seq, which is not observed in bisulfite-based conversion or in Oxford Nanopore sequencing. While bisulfite and nanopore errors occur at sporadic CpGs, EM-seq generates molecules that appear fully unmethylated, introducing a false-positive background signal that severely limits deconvolution specificity in cfDNA analysis.

genomics↗

bioRxiv2026

Cell-to-cell variability and gain of methylation at polycomb CpG islands as a hallmark of aging

Aging is a complex multifactorial process that affects cellular function and tissue homeostasis over time. Despite extensive research, the molecular mechanisms driving cellular aging remain poorly understood1,2. Many studies have focused on changes in DNA methylation as an indicator of aging3. In particular, the degree of methylation at polycomb CpG islands has been shown to be predictive of phenotypic changes associated with aging4,5. Since many age-related pathological processes, are thought to be of single-cell origin (e.g. cancer), we questioned whether polycomb DNA methylation also occurs preferentially in a subset of cells within the overall population. Using single-cell whole-genome methylation data from multiple ages and tissues, we identify Average Polycomb CpG Methylation as a hallmark of cellular aging. This revealed that aging occurs at varying rates within specific cells, with faster proliferating cells showing accelerated levels. Gene expression analysis in "young" and "old" single cells identified changes in immune response, translation regulation, tumorigenesis, neurodegeneration and other cellular processes associated with aging. These results challenge traditional models of homogeneous cellular aging and suggest that aging itself is a highly individualized process at the single-cell level that may be driven by programmed changes in polycomb CpG island DNA methylation.

genomics↗

bioRxiv2025

An improved epigenetic age estimation with TFMethyl Clock reveals DNA methylation changes during aging in transcription factor binding sites

Methylation-based epigenetic clocks are among the most accurate tools for predicting chronological age. Although DNA methylation (DNAm) at genomic CpG sites is linked to various regulatory mechanisms, the biological interpretability of epigenetic clocks remains surprisingly limited. One primary mechanism by which DNAm is thought to influence gene regulation is by modulating transcription factor binding activity. In this study, we examine established epigenetic clocks to assess the regulatory potential of their predictive CpGs during the aging process. Our analysis reveals that generally most CpG sites used by epigenetic clocks do not overlap known transcription factor binding sites (TFBSs), indicating that changes in TFBS dynamics may not account for prediction accuracy of these models. On the other hand, by identifying age-associated CpGs that overlap TFBSs, we identified transcription factors that may be involved in the aging process. Specifically, the TFBSs of ZBED1, NFE2, CEBPB, FOXP1, EGR1, SP1, PAX5, and MAZ were particularly enriched for age-associated CpGs, while RBPJ, NFIC, RELA, IKZF1, STAT3, and USF2 were significantly protected against methylation changes. By focusing on TFBS-associated CpGs, combined with additional feature selection and engineering steps, we developed an alternative, TFMethyl Clock model, outperforming several existing approaches. Target genes of model-selected, age-predictive CpGs are enriched in the interleukin-1b production and long- chain fatty acid metabolism pathways. In contrast, these CpGs themselves are enriched mainly at binding sites of NR2C2 TF. Furthermore, approximately three-fourths of the target genes downstream of age- predictive CpGs exhibit significant age-related changes, suggesting that our approach captures deeper insights into possible methylation-driven biological aging processes. Our findings demonstrate that incorporating regulatory loci into the design of epigenetic predictors may provide mechanistic insights into the aging process while maintaining or even improving the predictive power.

bioinformatics↗

bioRxiv2025

Loss of Brain Structural qMRI Signatures in Aging

The human brain undergoes significant changes during aging, affecting its macrostructure and microstructure features and impacting its functionality. These aging-related changes are oftentimes linked to different neurodegenerative diseases. Previous studies using MRI and molecular analyses have proposed that aging in each individual brain leads to increased similarity between different brain regions, whereas on the population level, they show greater variability. We investigated these hypotheses using multi-parametric, microstructural, quantitative MRI (qMRI) approaches. Using seven qMRI parametric methods in data from young and older adults, we created unique microstructural signatures of 128 brain regions. Our results supported both hypotheses: First, that inter-regional microstructural similarity is stronger within older individuals; and second, that the variability in microstructural signatures across individuals is also greater in older than in younger adults. Our findings provide new insights into the brains microstructural changes during aging and demonstrate the potential of using multi-parameter qMRI techniques in neuroscience research.

neuroscience↗

bioRxiv2025

The genetic basis for DNA methylation variation across tissues and development

The mechanisms by which genetic variation shapes the epigenome across cell types and developmental stages have remained elusive. Here, we define a unifying developmental framework for DNA methylation programming, grounded in genome-wide methylation and genetic variation data from both mouse and human. In mice, we identify thousands of differentially methylated regions (DMRs) linked to sequence polymorphisms that disrupt transcription factor binding. These DMRs are programmed either during implantation or later in organogenesis, revealing two distinct periods of epigenetic regulation. Extending this logic to humans, we analyze our atlas of over 200 WGBS samples from 39 purified cell types and map 33,574 regions where common SNPs control allele-specific methylation. These include both early-established and cell-type-specific loci, many of which colocalize with eQTLs, enhancers, silencers, and disease-associated variants. Our results uncover a widespread mechanism by which genetic variation influences the regulatory landscape, linking sequence, methylation, and transcription across tissues. This cross-species atlas of sequence-dependent methylation not only clarifies the logic and timing of epigenetic programming, but also provides a foundational resource for deciphering non-coding variants in development, complex disease, and regenerative medicine.

genomics↗

bioRxiv2024

Time is encoded by methylation changes at clustered CpG sites

Age-dependent changes in DNA methylation allow chronological and biological age inference, but the underlying mechanisms remain unclear. Using ultra-deep sequencing of >300 blood samples from healthy individuals, we show that age-dependent DNA methylation changes are regional and occur at multiple adjacent CpG sites, either stochastically or in a coordinated block-like manner. Deep learning analysis of single-molecule patterns in two genomic loci achieved accurate age prediction with a median error of 1.46-1.7 years on held-out human blood samples, dramatically improving current epigenetic clocks. Factors such as gender, BMI, smoking and other measures of biological aging do not affect chronological age inference. Longitudinal 10-year samples revealed that early deviations from epigenetic age are maintained throughout life and subsequent changes faithfully record time. Lastly, the model inferred chronological age from as few as 50 DNA molecules, suggesting that age is encoded by individual cells. Overall, DNA methylation changes in clustered CpG sites illuminate the principles of time measurement by cells and tissues, and facilitate medical and forensic applications. O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/626674v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@c4dd52org.highwire.dtl.DTLVardef@9e6e62org.highwire.dtl.DTLVardef@160f8c3org.highwire.dtl.DTLVardef@16be7a3_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

wgbstools: A computational suite for DNA methylation sequencing data representation, visualization, and analysis

Next-generation methylation-aware sequencing of DNA sheds light on the fundamental role of methylation in cellular function in health and disease. These data are commonly represented at a single CpG resolution, while single-molecule fragment-level analysis is often overlooked. Here, we present wgbstools, an extensive computational suite tailored for methylation sequencing data. wgbstools allows fast access and ultra-compact anonymized representation of high-throughput methylome data, obtained through various library preparation and sequencing methods. Additionally, wgbstools contains state-of-the-art algorithms for genomic segmentation, biomarker identification, genetic and epigenetic data integration, and more. wgbstools offers fragment-level analysis and informative visualizations, across multiple genomic regions and samples.

bioinformatics↗

bioRxiv2024

Atlas of imprinted and allele-specific DNA methylation in the human body

Allele-specific DNA methylation, determined genetically or epigenetically, is involved in gene regulation and underlies multiple pathologies. Yet, our knowledge of this phenomenon is partial, and largely limited to blood lineages. Here, we present a comprehensive atlas of allele-specific DNA methylation, using deep whole-genome sequencing across 39 normal human cell types. We identified 325k genomic regions, covering 6% of the genome and containing 11% of all CpG sites, that show a bimodal distribution of methylated and unmethylated molecules. In 34K of these regions, genetic variations at individual alleles segregate with methylation patterns, thus validating allele-specific methylation. We also identified 460 regions showing parentally-imprinted methylation, the majority of which were not previously reported. Surprisingly, sequence-dependent and parent-dependent methylation patterns are often restricted to specific cell types, revealing unappreciated variation in the human allele-specific methylation across the human body. The atlas provides a resource for studying allele-specific methylation and regulatory mechanisms underlying imprinted expression in specific human cell types. HighlightsO_LIA comprehensive atlas of allele-specific methylation in primary human cell types C_LIO_LI325k genomic regions show a bimodal pattern of of hyper- and hypo-methylation of DNA C_LIO_LIAllele-specific methylation at 34k genomic regions C_LIO_LITissue-specific effects at known imprinting control regions (ICRs) C_LIO_LI100s of novel loci exhibiting parentally-imprinted methylation C_LIO_LIParentally-imprinting methylation is often cell-type-specific C_LI

genomics↗

bioRxiv2023

Toxinome - The Bacterial Protein Toxin Database

Protein toxins are key molecular weapons in biology that are used to attack neighboring cells. Bacteria use protein toxins to kill or inhibit growth of prokaryotic and eukaryotic cells using various modes of action that target essential cellular components. The toxins are responsible for shaping microbiomes in different habitats, for abortive phage infection, and for severe infectious diseases of animals and plants. Although several toxin databases have been developed, each one is devoted to a specific toxin family and they encompass a relatively small number of toxins. Antimicrobial toxins are often accompanied by antitoxins (or immunity proteins) that neutralize the cognate toxins. Here, we combined toxins and antitoxins from many resources and created Toxinome, a comprehensive and updated bacterial protein toxin database. Toxinome includes a total of 1,483,028 toxins and 491,345 antitoxins encoded in 59,475 bacterial genomes across the tree of life. We identified a depletion of toxin and antitoxin genes in bacteria that dwell in extreme temperatures. We defined 5,161 unique Toxin Islands within phylogenetically diverse bacterial genomes, which are loci dense in toxin and antitoxin genes. By focusing on the unannotated genes within these islands, we characterized a number of these genes as toxins or antitoxins. Finally, we developed an interactive Toxinome website (http://toxinome.pythonanywhere.com) that allows searching and downloading of our database. The Toxinome resource will be useful to the large research community interested in bacterial toxins and can guide toxin discovery and function elucidation, and infectious disease diagnosis and treatment. ImportanceMicrobes use protein toxins as important tools to attack neighboring cells, microbial or eukaryotic, and for self-killing when attacked by viruses. These toxins work by different mechanisms to inhibit cell growth or kill cells. Microbes also use antitoxin proteins to neutralize the toxin activities. Here, we developed a comprehensive database called Toxinome of nearly two million toxin and antitoxins that are encoded in 59,475 bacterial genomes. We described the distribution of bacterial toxins and identified that they are depleted from bacteria that live in hot and cold temperatures. We find 5,161 cases in which toxins and antitoxins are densely clustered in bacterial genomes and termed these areas "Toxin Islands". The Toxinome database is a useful resource for anyone interested in toxin biology and evolution, and it can guide discovery of new toxins.

microbiology↗

bioRxiv2023

Epigenetic liquid biopsies reveal elevated vascular endothelial cell turnover and erythropoiesis in asymptomatic COVID-19 patients

The full spectrum of tissues affected by SARS-CoV-2 infection is crucial for deciphering the heterogenous clinical course of COVID-19. Here, we analyzed DNA methylation and histone modification patterns in circulating chromatin to assess cell type-specific turnover in severe and asymptomatic COVID-19 patients, in relation to clinical outcome. Patients with severe COVID-19 had a massive elevation of circulating cell-free DNA (cfDNA) levels, which originated in lung epithelial cells, cardiomyocytes, vascular endothelial cells and erythroblasts, suggesting increased cell death or turnover in these tissues. The immune response to infection was reflected by elevated B cell and monocyte/macrophage cfDNA levels, and by evidence of an interferon response in cells prior to cfDNA release. Strikingly, monocyte/macrophage cfDNA levels (but not monocyte counts), as well as lung epithelium cfDNA and vascular endothelial cfDNA, predicted clinical deterioration and duration of hospitalization. Asymptomatic patients had elevated levels of immune-derived cfDNA but did not show evidence of pulmonary or cardiac damage. Surprisingly, these patients showed elevated levels of vascular endothelial cell and erythroblast cfDNA, suggesting that sub-clinical vascular and erythrocyte turnover are universal features of COVID-19, independent of disease severity. Epigenetic liquid biopsies provide non-invasive means of monitoring COVID-19 patients, and reveal sub-clinical vascular damage and red blood cell turnover.

microbiology↗

bioRxiv2023

Accurate age prediction from blood using of small set of DNA methylation sites and a cohort-based machine learning algorithm

Chronological age prediction from DNA methylation sheds light on human aging, indicates poor health and predicts lifespan. Current clocks are mostly based on linear models from hundreds of methylation sites, and are not suitable for sequencing-based data. We present GP-age, an epigenetic clock for blood, that uses a non-linear cohort-based model of 11,910 blood methylomes. Using 30 CpG sites alone, GP-age outperforms state-of-the-art models, with a median accuracy of ~2 years on held-out blood samples, for both array and sequencing-based data. We show that aging-related changes occur at multiple neighboring CpGs, with far-reaching implications on aging research at the cellular level. By training three independent clocks, we show consistent deviations between predicted and actual age, suggesting individual rates of biological aging. Overall, we provide a compact yet accurate alternative to array-based clocks for blood, with future applications in longitudinal aging research, forensic profiling, and monitoring epigenetic processes in transplantation medicine and cancer. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/524874v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@14eb626org.highwire.dtl.DTLVardef@98aecdorg.highwire.dtl.DTLVardef@1fc2ca1org.highwire.dtl.DTLVardef@d6138f_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIMachine learning analysis of a large cohort (~12K) of DNA methylomes from blood C_LIO_LIA 30-CpG regression model achieves a 2.1-year median error in predicting age C_LIO_LIImproved accuracy ([≥]1.75 years) from sequencing data, using neighboring CpGs C_LIO_LIPaves the way for easy and accurate age prediction from blood, using NGS data C_LI MotivationEpigenetic clocks that predict age from DNA methylation are a valuable tool in the research of human aging, with additional applications in forensic profiling, disease monitoring, and lifespan prediction. Most existing epigenetic clocks are based on linear models and require hundreds of methylation sites. Here, we present a compact epigenetic clock for blood, which outperforms state-of-the-art models using only 30 CpG sites. Finally, we demonstrate the applicability of our clock to sequencing-based data, with far reaching implications for a better understanding of epigenetic aging.

bioinformatics↗

bioRxiv2022

The H3K27me3 epigenetic mark is crucial for callus cell identity and for the acquisition of new fate during root and shoot regeneration

We combined molecular, genomic and genetic approaches to study the molecular mechanisms underlying cell totipotency and competency to regenerate in Arabidopsis. By performing comparative analysis of mRNA-seq and chromatin landscapes between leaf differentiated cells and callus totipotent cells and between WT callus and calli derived from the emf2 mutant, exhibiting impaired regenerative capacity we revealed the following: 1. That callus cells express numerous genes of many developmental pathways such as root, leaf, embryo, shoot, meristem and seed. This suggests a mechanism to allow rapid response to a signal by maintaining genes of all potential developmental pathways active, without the needs to release transcriptional silencing and to go through the intricate multistep process of transcription. 2. That key transcription factors that are sufficient to derive differentiation or organogenesis are silenced and marked by the H3K27me3. 3. That callus derived from the emf2 mutant which is impaired in setting the H3K27methylation, lost the capacity to regenerate and that 78 transcription factors from which 18 regulate flower development, where up-regulated compared with WT callus. Altogether our results suggest that competency to regenerate is achieved by keeping the chromatin of developmental genes active, and that upon a signal for cell fate switch, a mechanism to repress those genes is required to allow the one desired developmental pathway to dominate. When this mechanism is impaired the capacity to regenerate is decline.

developmental biology↗

bioRxiv2022

Cell-free, methylated DNA in blood samples reveals tissue-specific, cellular damage from radiation treatment

Radiation therapy is an effective cancer treatment although damage to healthy tissues is common. Here we characterize the methylomes of healthy human and mouse tissues to establish sequencing-based, cell-type specific reference DNA methylation atlases. Identified cell-type specific DNA blocks were mostly hypomethylated and located within genes intrinsic to cellular identity. Cell-free DNA fragments released from dying cells into the circulation were captured from serum samples by hybridization to CpG-rich DNA panels. The origins of the circulating DNA fragments were inferred from mapping to the established DNA methylation atlases. Thoracic radiation-induced tissue damages in a mouse model were reflected by dose-dependent increases in lung endothelial, cardiomyocyte and hepatocyte methylated DNA in serum. The analysis of serum samples from breast cancer patients undergoing radiation treatment revealed distinct tissue-specific epithelial and endothelial responses to radiation across multiple organs. Strikingly, patients treated for right-sided breast cancers also showed increased hepatocyte and liver endothelial DNA in the circulation indicating the impact on liver tissues. Thus, changes in cell-free methylated DNA can uncover cell-type specific effects of radiation and provide a quantitative measure of the biologically effective radiation dose received by healthy tissues. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=174 SRC="FIGDIR/small/487966v3_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@129f229org.highwire.dtl.DTLVardef@d999bcorg.highwire.dtl.DTLVardef@1fc3543org.highwire.dtl.DTLVardef@10cebc2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

Remote immune processes revealed by immune-derived circulating cell-free DNA

Blood cell counts often fail to report on immune processes occurring in remote tissues. Here we use immune cell type-specific methylation patterns in circulating cell-free DNA (cfDNA) for studying human immune cell dynamics. We characterized cfDNA released from specific immune cell types in healthy individuals (N=242), cross sectionally and longitudinally. Immune cfDNA levels had no individual steady state as opposed to blood cell counts, suggesting that cfDNA concentration reflects adjustment of cell survival to maintain homeostatic cell numbers. We also observed selective elevation of immune-derived cfDNA upon perturbations of immune homeostasis. Following influenza vaccination (N=92), B-cell-derived cfDNA levels increased prior to elevated B-cell counts and predicted efficacy of antibody production. Patients with Eosinophilic Esophagitis (N=21) and B-cell lymphoma (N=27) showed selective elevation of eosinophil and B-cell cfDNA respectively, which were undetectable by cell counts in blood. Immune-derived cfDNA provides a novel biomarker for monitoring immune responses to physiological and pathological processes that are not accessible using conventional methods.

genomics↗

bioRxiv2020

Comparative Parallel Multi-Omics Analysis During the Induction of Pluripotent and Trophectoderm States

Following fertilization, totipotent cells divide to generate two compartments in the early embryo: the inner cell mass (ICM) and trophectoderm (TE). It is only at the 32-64 -cell stage when a clear segregation between the two cell-types is observed, suggesting a T-shaped model of specification. Here, we examine whether the acquisition of these two states in vitro by nuclear reprogramming share similar dynamics/trajectories. We conducted a comparative parallel multi-omics analysis on cells undergoing reprogramming to Induced pluripotent stem cells (iPSCs) and induced trophoblast stem cells (TSCs), and examined their transcriptome, methylome, chromatin accessibility and activity and genomic stability. Our analysis revealed that cells undergoing reprogramming to pluripotency and TSC state exhibit specific trajectories from the onset of the process, suggesting V-shaped model. Using these analyses, not only we could describe in detail the various trajectories toward the two states, we also identified previously unknown stage-specific reprogramming markers as well as markers for faithful reprogramming and reprogramming blockers. Finally, we show that while the acquisition of the TSC state involves the silencing of embryonic programs by DNA methylation, during the acquisition of pluripotency these specific regions are initially open but then retain inactive by the elimination of the histone mark, H3K27ac.

developmental biology↗

bioRxiv2019

Gene Activation and repression by the glucocorticoid receptor are mediated by sequestering Ep300 and two modes of chromatin binding

The transcription factor glucocorticoid receptor (GR) is a key mediator of stress response and a broad range of physiological processes. How can GR rapidly activate the expression of some genes while repress others, remains an open question due to the challenge to associate GR binding sites (GBSs) to their distant gene targets. Mapping the full 3D scope of GR-responsive promoters using high-resolution 4C-seq unravelled spatial separation between chromatin interaction networks of GR-activated and repressed genes. Analysing GR binding sites and other regulatory loci in their functional 3D context revealed that GR sequesters the co-activator Ep300 from active non-GBS enhancers in both activated and repressed gene compartments. While this is sufficient for rapid gene repression, gene activation is countered by productive recruitment of Ep300 to GBS. Importantly, in GR-activated compartments Klf4 binding at non-GBS regulatory elements cluster in 3D with GBS and antagonizes GR activation. In addition, we revealed ROR and Rev-erb transcription factors as novel co-regulators for GR-mediated gene expression.

molecular biology↗

bioRxiv2019

Genomic Retargeting of Tumor Suppressors p53 and CTCF Promotes Oncogenesis

Gene transcription is substantially regulated by distant regulatory elements via combinatorial binding of transcription factors. It is more and more recognized that alterations in chromatin state and transcription factor binding in these distant regulatory elements may have key roles in cancer development. Here we focused on the first stages of oncogene induced carcinogenic transformation, and characterized the regulatory network underlying transcriptional reprogramming associated with this process. Using Hi-C data, we couple between differentially expressed genes and their differentially active regulatory elements and reveal two candidate transcription factors, p53 and CTCF, as major determinants of transcriptional reprogramming at early stages of HRas-induced transformation. Strikingly, the malignant transcriptional reprograming is promoted by redistribution of chromatin binding of these factors without major variation in their expression level. Our results demonstrate that alterations in the regulatory landscape have a major role in driving oncogene-induced transcriptional reprogramming.

cell biology↗