Biology subjects

Margalit, S.

Publications and source records attributed to Margalit, S..

7 recordsLinked to original sources

bioRxiv2025

Single cell transcriptomics reveals enrichment of aggregation-prone alpha-synuclein isoforms across synucleinopathies

Alpha-synuclein (-Syn) is the primary component of Lewy bodies, the pathological hallmark of neurodegenerative synucleinopathies, including Parkinsons disease (PD) and dementia with Lewy bodies (DLB). Dysregulated expression of its encoding gene, SNCA, has been identified in association with both PD and DLB in short-read sequencing studies. However, such studies do not capture variation in transcript isoforms expressed. Here we combine for the first time SNCA-targeted long-read multiplexed arrays isoform sequencing (MAS-Iso-seq) with unbiased short-read single nucleus (sn) RNA-seq for simultaneous characterization of the SNCA transcript isoform landscape and mapping of isoform expression to specific cell types and subtypes in PD, DLB, and control sample cortical tissues. This approach enabled discovery of numerous SNCA transcript isoforms displaying novel splicing patterns and incorporating novel exons. We further identified an abundant class of transcript isoforms encoding a previously unreported -Syn protein variant (-Syn-115) and displaying increased proportional detection in excitatory neurons of PD and DLB tissues in comparison to controls. The proportion of these isoforms was found to be especially high within several specific glutamatergic neuron subtypes. In-depth characterization of the predicted structural and biochemical properties of -Syn-115 using an in silico modeling approach revealed a greater aggregative affinity compared with canonical -Syn-140, suggesting the potential for increased cytosolic -Syn-115 abundance to induce aggregation between heterogeneous -Syn isoforms, potentially driving fibril formation and disease progression. Together, our findings provide new insights into the molecular mechanisms underlying -Syn involvement in multiple synucleinopathies and have translational implications for the development of new precision medicine strategies to combat these diseases, indicating the potential for treatments targeting both specific transcript and protein isoforms, as well as disease-driving cell subtypes.

neuroscience↗

bioRxiv2024

Long-Read Structural and Epigenetic Profiling of a Kidney Tumor-matched Sample with Nanopore Sequencing and Optical Genome Mapping

Carcinogenesis often involves significant alterations in the cancer genome architecture, marked by large structural and copy number variations (SVs and CNVs) that are difficult to capture with short-read sequencing. Traditionally, cytogenetic techniques are applied to detect such aberrations, but they are limited in resolution and do not cover features smaller than several hundred kilobases. Optical genome mapping and nanopore sequencing are attractive technologies that bridge this resolution gap and offer enhanced performance for cytogenetic applications. These methods profile native, individual DNA molecules, thus capturing epigenetic information. We applied both techniques to characterize a clear cell renal cell carcinoma (ccRCC) tumors structural and copy number landscape, highlighting the relative strengths of each method in the context of variant size and average read length. Additionally, we assessed their utility for methylome and hydroxymethylome profiling, emphasizing differences in epigenetic analysis applicability.

genomics↗

bioRxiv2022

DeepOM: Single-molecule optical genome mapping via deep learning

Efficient tapping into genomic information from a single microscopic image of an intact DNA molecule fragment is an outstanding challenge and its solution will open new frontiers in molecular diagnostics. Here, a new computational method for optical genome mapping utilizing Deep Learning is presented, termed DeepOM. Utilization of a Convolutional Neural Network (CNN), trained on simulated images of labeled DNA molecules, improves the success rate in alignment of DNA images to genomic references. The method is evaluated on acquired images of human DNA molecules stretched in nano-channels. The accuracy of the method is benchmarked against state-of-the-art commercial software Bionano Solve. The results show a significant advantage in alignment success rate for molecules shorter than 50 kb. DeepOM improves yield, sensitivity and throughput of optical genome mapping experiments in applications of human genomics and microbiology.

bioinformatics↗

bioRxiv2022

Simultaneous global labeling (SiGL) of 5-methylcytosine and 5-hydroxymethylcytosine by DNA alkylation with a synthetic cofactor and engineered methyltransferase

5-methylcytosine and 5-hydroxymethylcytosine are epigenetic modifications involved in gene regulation and cancer. Here, we describe a new, simple, and high-throughput platform for multi-colour epigenetic analysis. The novelty of our approach is the ability to multiplex methylation and de-methylation signals in the same assay. We utilize an engineered methyltransferase enzyme that recognizes and labels all unmodified CpG sites with a fluorescent cofactor. In combination with the already established labelling of the de-methylation mark 5-hydroxymethylcytosine via enzymatic glycosylation, we obtained a robust platform for simultaneous epigenetic analysis of these marks. We assessed the global epigenetic levels in multiple samples of colorectal cancer and observed a reduction in 5-hydroxymethylcytosine levels, but no change in DNA methylation levels between sick and healthy individuals. We also measured epigenetic modifications in chronic lymphocytic leukaemia and observed a decrease in both modification levels. Our results indicate that this assay may be used for the epigenetic characterization of clinical samples for research and patient management.

genetics↗

bioRxiv2022

Optical Genome and Epigenome Mapping of Clear Cell Renal Cell Carcinoma

Cancer cells display complex genomic aberrations that include large-scale genetic rearrangements and epigenetic modulation that are not easily characterized by short-read sequencing. We present a method for simultaneous profiling of long-range genetic/epigenetic changes in matched cancer samples. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer. Most ccRCC cases demonstrate somatic genomic alterations involving the short arm of chromosome 3 (3p), most often targeting the von Hippel-Lindau (VHL) gene. Aiming to identify somatic alterations that characterize early stage ccRCC, we performed comprehensive genetic, cytogenetic and epigenetic analyses comparing ccRCC tumor to adjacent non-tumorous tissue. Optical genome mapping identified genomic aberrations such as structural and copy number variations, complementing exome-sequencing results. Single-molecule methylome and hydroxymethylome mapping revealed multiple differential regions, some of them known to be associated with ccRCC pathogenesis. Among them, metabolic pathways were significantly enriched. Moreover, significant global epigenetic differences were detected between the tumor and the adjacent non-tumorous tissue, and a correlation between epigenetic signals and gene expression was found. This is the first reported comparison of a human tumor and a matched tissue by optical genome/epigenome mapping, revealing well-established and novel somatic aberrations.

genomics↗

bioRxiv2021

Genome wide mapping of DNA lesions by Repair Assisted Damage Detection sequencing - RADD-Seq

Mapping DNA damage and its repair has immense potential in understanding environmental exposures, their genotoxicity, and their impact on human health. Monitoring changes in genomic stability also aids in the diagnosis of numerous DNA-related diseases, like cancer, and assists in monitoring their progression and prognosis. However, genome-wide maps of DNA damage distribution are challenging to produce. Here we describe the localization of DNA damage and repair loci by Repair Assisted Damage Detection sequencing - RADD-Seq. Based on the enrichment of damage lesions coupled with a pull-down assay and followed by next generation sequencing, this method is easy to perform and can produce compelling results with minimal coverage. RADD-seq enables the localization of both DNA damage and repair sites for a wide range of single-strand damage types. Using this technique, we created a genome-wide map of oxidative DNA damage loci before and after repair. Oxidative lesions were heterogeneously distributed along the human genome, with less damage occurring in tight chromatin regions. Furthermore, we showed repair is prioritized for highly expressed, essential genes and in open chromatin regions. RADD-seq sheds light on cellular repair mechanisms and capable of identifying genomic hotspots prone to mutation.

genomics↗

bioRxiv2021

Long Reads Capture Simultaneous Enhancer-Promoter Methylation Status for Cell-type Deconvolution

MotivationWhile promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long-reads that report on the methylation status of enhancer-promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer-promoter methylation profiles. ResultsTo evaluate our hypothesis we examine long-read optical methylome data for the GM12787 cell line and myoblast cell lines from two donors. We identified over 100,000 enhancer-promoter pairs that co-exist on at least 30 individual DNA molecules per pair. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures based on analyzing their enhancer-promoter pairwise methylation. We found our methodology to lead to very accurate estimates, outperforming our promoter-based deconvolutions. Moreover, we show that it can be generalized from deconvolving different cell types to subtle scenarios where one wishes to deconvolve different cell populations of the same cell-type. AvailabilityThe code used in this work to analyze single-molecule Bionano Genomics optical maps is available via the GitHub repository https://github.com/ebensteinLab/Single_molecule_methylation_in_EP. Contactuv@post.tau.ac.il (Y.E), roded@tauex.tau.ac.il (R.S)

bioinformatics↗