Biology subjects

Wexler, J.

Publications and source records attributed to Wexler, J..

5 recordsLinked to original sources

bioRxiv2025

Dynamic Ribosomal RNA Methylation Regulates Translation in the Hematopoietic System and is Essential for Stem Cell Fitness

Self-renewal and differentiation are at the basis of hematopoiesis. While it is known that tight regulation of translation is vital for hematopoietic stem cells (HSCs) biology, the mechanisms underlying translation regulation across the hematopoietic system remain obscure. Here we reveal a novel mechanism of translation regulation in the hematopoietic hierarchy, which is mediated by ribosomal RNA (rRNA) methylation dynamics. Using ultra-low input ribosome-profiling, we characterized cell-type-specific translation capacity during erythroid differentiation. We found that translation efficiency changes progressively with differentiation and can distinguish between discrete cell populations as well as to define differentiation trajectories. To reveal the underlying mechanism, we performed comprehensive mapping of the most abundant rRNA modification - 2-O-methyl (2OMe). We found that, like translation efficiency, 2OMe dynamics followed a distinct trajectory during erythroid differentiation. Genetic perturbation of individual 2OMe sites demonstrated their distinct roles in modulating proliferation and differentiation. By combining CRISPR screening, molecular and functional analyses, we identified a specific methylation site, 28S-Gm4588, which is progressively lost during differentiation, as a key regulator of HSC self-renewal. We showed that low methylation at this site led to translational skewing, mediated mainly by codon frequency, which promoted differentiation. Functionally, HSCs with diminished 28S-Gm4588 methylation exhibited impaired self-renewal capacity ex-vivo, and loss of fitness in-vivo in bone marrow transplantations. Extending our findings beyond the hematopoietic system, we also found distinct dynamics of 2OMe profiles during differentiation of non-hematopoietic stem cells. Our findings reveal rRNA methylation dynamics as a general mechanism for cell-type-specific translation, required for cell function and differentiation. KEY POINTSO_LIHematopoietic differentiation is associated with rRNA methylation dynamics to control cell-type-specific translation. C_LIO_LITranslation efficiency can distinguish discrete cell types and define differentiation trajectories. C_LIO_LIHSC fitness is regulated by a single rRNA methylation. C_LI

molecular biology↗

bioRxiv2021

OpenNeuro: An open resource for sharing of neuroimaging data

The sharing of research data is essential to ensure reproducibility and maximize the impact of public investments in scientific research. Here we describe OpenNeuro, a BRAIN Initiative data archive that provides the ability to openly share data from a broad range of brain imaging data types following the FAIR principles for data sharing. We highlight the importance of the Brain Imaging Data Structure (BIDS) standard for enabling effective curation, sharing, and reuse of data. The archive presently shares more than 600 datasets including data from more than 20,000 participants, comprising multiple species and measurement modalities and a broad range of phenotypes. The impact of the shared data is evident in a growing number of published reuses, currently totalling more than 150 publications. We conclude by describing plans for future development and integration with other ongoing open science efforts.

neuroscience↗

bioRxiv2021

High-sensitivity detection of facial features on MRI brain scans with a convolutional network

Platforms and institutions that support MRI data sharing need to ensure that identifiable facial features are not present in shared images. Currently, this assessment requires manual effect as no auto-mated tools exist that can efficiently and accurately detect if an image has been "defaced". The scarcity of publicly available data with pre-served facial features, as well as the meager incentives to create such a cohort privately, have averted the development of face-detection models. Here, we introduce a framework to detect whether an input MRI brain scan has been defaced, with the ultimate goal of streamlining it within the submission protocols of MRI data archiving and sharing platforms. We present a binary (defaced/"nondefaced") classifier based on a custom convolutional neural network architecture. We train the model on 980 de-faced MRI scans from 36 different studies that are publicly available at OpenNeuro.org. To overcome the unavailability of nondefaced examples, we augment the dataset by inpainting synthetic faces into each training image. We show the adequacy of such a data augmentation in a cross-validation evaluation. We demonstrate the performance estimated with cross-validation matches that of an evaluation on a held-out dataset (N =581) preserving real faces, and obtain accuracy/sensitivity/speci-ficity scores of 0.978/0.983/0.972, respectively. Data augmentations are key to boosting the performance of models bounded by limited sample sizes and insufficient diversity. Our model contributes towards developing classifiers with[~] 100% sensitivity detecting faces, which is crucial to ensure that no identifiable data are inadvertently made public.

neuroscience↗

bioRxiv2019

Hemimetabolous insects elucidate the origin of sexual development via alternative splicing

Insects are the only animals in which sexual differentiation is controlled by sex-specific RNA splicing. The doublesex (dsx) transcription factor produces distinct male and female protein isoforms (DsxM and DsxF) under the control of the RNA splicing factor transformer (tra). tra itself is also alternatively spliced so that a functional Tra protein is only present in females; thus, DsxM is produced by default, while DsxF expression requires Tra. The sex-specific Dsx isoforms are essential for both male and female sexual differentiation. This pathway is profoundly different from the molecular mechanisms that control sex-specific development in other animal groups. In animals as different as vertebrates, nematodes, and crustaceans, sexual differentiation involves male-specific transcription of dsx-related transcription factors that are not alternatively spliced and play no role in female sexual development. To understand how the unique splicing-based mode of sexual differentiation found in insects evolved from a more ancestral transcription-based mechanism, we examined dsx and tra expression in three basal, hemimetabolous insect orders. We find that functional Tra protein is limited to females in the kissing bug Rhodnius prolixus (Hemiptera), but is present in both sexes in the louse Pediculus humanus (Phthiraptera) and the cockroach Blattella germanica (Blattodea). Although alternatively spliced dsx isoforms are seen in all these insects, they are sex-specific in the cockroach and the kissing bug but not in the louse. In B. germanica, RNAi experiments show that dsx is necessary for male, but not female, sexual differentiation, while tra controls female development via a dsx-independent pathway. Our results suggest that the distinctive insect mechanism based on the tra-dsx splicing cascade evolved in a gradual, mosaic process: sex-specific splicing of dsx predates its role in female sexual differentiation, while the role of tra in regulating dsx splicing and in sexual development more generally predates sex-specific expression of the Tra protein. We present a model where the canonical tra-dsx axis originated via merger between expanding dsx function (from males to both sexes) and narrowing tra function (from a general splicing factor to the dedicated regulator of dsx).

developmental biology↗

bioRxiv2017

MEG-BIDS: an extension to the Brain Imaging Data Structure for magnetoencephalography

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG provides direct measurement of brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS has provided a solution to structure the organization of magnetic resonance imaging (MRI) data, which nature and acquisition parameters are different. Despite the lack of standard data format for MEG, MEG-BIDS is a principled solution to store, organize and share the typically-large data volumes produced. It builds on BIDS for MRI, and therefore readily yields a multimodal data organization by construction. This is particularly valuable for the anatomical and functional registration of MEG source imaging with MRI. With MEG-BIDS and a growing range of software adopting the standard, the MEG community has a solution to minimize curation overheads, reduce data handling errors and optimize usage of computational resources for analytics. The standard also includes well-defined metadata, to facilitate future data harmonization and sharing efforts.

neuroscience↗