Biology subjects

Katsman, E.

Publications and source records attributed to Katsman, E..

4 recordsLinked to original sources

bioRxiv2026

Improved deconvolution of circulating tumor DNA from ultra-low-pass whole-genome methylation sequencing using CelFiE-ISH

Liquid biopsy using ultra-low-pass whole-genome sequencing (ULP-WGS, [~]0.25x coverage) is a promising tool to detect circulating tumor DNA (ctDNA) for cancer management, and the use of the native Oxford Nanopore (ONT) sequencing platform adds DNA methylation to the set of detectable features. Here, we test the performance of methylation-based cell-type deconvolution in ULP-WGS samples from diverse epithelial malignancies and investigate several new computational strategies using our CelFiE-ISH deconvolution framework. We find that incorporating larger numbers of markers restricted to the epithelial cell lineage can reduce the cancer fraction limit of detection down to 1.7-3.1%, matching or exceeding the 3% floor of established copy-number alteration (CNA) benchmarks. Our study provides a useful strategy for analysis of ULP-WGS ONT data and indicates that marker selection remains a key challenge for analyzing methylation-based cancer datasets.

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↗

bioRxiv2023

Multi-cell type deconvolution using a probabilistic model for single-molecule DNA methylation haplotypes

BackgroundDeconvolution is used to estimate the proportion of mixed cell types from tissue or blood samples based on genomic profiling. DNA methylation is commonly used because specific CpG positions reflect cell type identity and can be accurately measured at either the population or single-molecule level. Methylation sequencing techniques can profile multiple individual CpGs on a single DNA molecule, but few deconvolution models have been developed to exploit these single-molecule methylation haplotypes for cell type deconvolution. Results and ConclusionsWe used simulated whole-genome methylation data and in silico mixtures of real data to compare existing deconvolution tools with two new models developed here. We found that adapting an existing model CelFiE to incorporate methylation haplotype information improved deconvolution accuracy by [~]30% over other tools, including the original CelFiE. In addition to overall higher accuracy, our new tool CelFiE Integrated Single-molecule Haplotypes (or CelFiE-ISH) outperformed others in detecting rare cell types present at 0.1% and below. Detection of rare cell types is important for the analysis of circulating DNA, which we demonstrate using a patient-derived plasma sequencing dataset.Finally,we show that marker selection strategy has a strong effect on deconvolution accuracy, concluding that haplotype-aware deconvolution can take advantage of markers tailored for that purpose.

bioinformatics↗

bioRxiv2021

Detecting cell-of-origin and cancer-specific features of cell-free DNA with Nanopore sequencing

The Oxford Nanopore (ONT) platform provides portable and rapid genome sequencing, and its ability to natively profile DNA methylation without complex sample processing is attractive for clinical sequencing. We recently demonstrated ONT shallow whole-genome sequencing to detect copy number alterations (CNA) from the circulating tumor DNA (ctDNA) of cancer patients. Here, we show that cell-type and cancer-specific methylation changes can also be detected, as well as cancer-associated fragmentation signatures. This feasibility study suggests that ONT shallow WGS could be a powerful tool for liquid biopsy, especially real-time medical applications.

genomics↗