Biology subjects

Desset, S.

Publications and source records attributed to Desset, S..

5 recordsLinked to original sources

bioRxiv2025

Replication-independent eviction of H2B.8 reveals chromatin reprogramming during seed imbibition

The transition from seed to seedling involves major changes in nuclear organization and gene expression, yet the extent to which this developmental transition requires chromatin reprogramming remains largely unexplored. Here, we report that Arabidopsis dry seed embryos accumulate the histone variant H2B.8, which contributes to higher-order chromatin organization by forming spatial clusters that structure the 3D nuclear space. H2B.8 forms heterotypic nucleosomes at euchromatic transposons and lowly expressed genes and, during imbibition, modulates the transcriptional activation of a subset of these genes. Imbibition triggers a decrease in H2B.8 transcripts and the eviction of H2B.8 proteins in a process that operates independently of DNA replication but requires protein translation and de novo transcription. Histone eviction is not limited to H2B.8 as imbibition also induces the turnover of the H3.3 histone variant, thereby initiating a broad, replication-independent chromatin reprogramming process. These findings highlight a fundamental mechanism of epigenetic regulation during early plant development.

molecular biology↗

bioRxiv2024

The dual trxG/PcG protein ULTRAPETALA1 modulates H3K27me3 and directly enhances POLYCOMB REPRESSIVE COMPLEX 2 activity for fine-tuned reproductive transitions

AbstractThe antagonistic POLYCOMB (PcG) REPRESSIVE COMPLEX 2 (PRC2) and trithorax (trxG) chromatin machineries play a major role in orchestrating gene expression during the development of multicellular eukaryotes. These complexes are well known for depositing and maintaining the repressive H3K27me3 and activating H3K4me3 marks, respectively. However, the mechanisms that govern the switch between these functions remains elusive, especially in plants, whose lifelong, flexible development relies heavily on this process. Here we demonstrate that the plant specific ULTRAPETALA1 (ULT1) protein, previously reported as a trxG factor that antagonizes the PRC2 enzymatic subunit CURLY LEAF (CLF), also exhibits a repressive function, increasing H3K27me3 levels at over a thousand genes. We discovered a physical interaction between ULT1 and PRC2 components, particularly the SWINGER (SWN) enzymatic subunit. We further show that in vitro ULT1 significantly enhances the enzymatic activity of PRC2SWN, and to a lesser extent also that of PRC2CLF, corroborating our epigenomic and developmental genetic data that reveal different ULT1 activity depending on the catalytic subunit of the PRC2 complex. This study provides new insights into the relative activities of CLF and SWN and introduces a novel mechanistic framework for a chromatin switch mediated by a bivalent trxG/PcG factor. Key messageULTRAPETALA1 counteracts or promotes PRC2 activity at hundreds of developmental genes in Arabidopsis thaliana, and activates the deposition of the repressive H3K27me3 chromatin mark via direct interaction with PRC2. This is the first instance of a bivalent factor which functions as a cofactor of PRC2 HMTs.

genetics↗

bioRxiv2024

Biom3d, a modular framework to host and develop 3D segmentation methods

U-Net is a convolutional neural network model developed in 2015 and has proven to be one of the most inspiring deep-learning models for image segmentation. Numerous U-Net-based applications have since emerged, constituting a heterogeneous set of tools that illustrate the current reproducibility crisis in the deep-learning field and that remain slow to spread in application fields such as 3D bioimaging. Here we propose a solution named Biom3d, a modular deep learning framework facilitating the integration and development of novel models, metrics, or training schemes for 3D image segmentation. The development philosophy of Biom3d provides an improved code sustainability and reproducibility in line with the FAIR principles and is available as a graphical user interface and an open-source deep-learning framework to target a large community of users, from end users to deep learning developers.

bioinformatics↗

bioRxiv2021

NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects

BackgroundThe three-dimensional nuclear arrangement of chromatin impacts many cellular processes operating at the DNA level in animal and plant systems. Chromatin organization is a dynamic process that can be affected by biotic and abiotic stresses. Three-dimensional imaging technology allows to follow these dynamic changes, but only a few semi-automated processing methods currently exist for quantitative analysis of the 3D chromatin organization. ResultsWe present an automated method, Nuclear Object DetectionJ (NODeJ), developed as an imageJ plugin. This program segments and analyzes high intensity domains in nuclei from 3D images. NODeJ performs a Laplacian convolution on the mask of a nucleus to enhance the contrast of intra-nuclear objects and allows their detection. We reanalyzed public datasets and determined that NODeJ is able to accurately identify heterochromatin domains from a diverse set of Arabidopsis thaliana nuclei stained with DAPI or Hoechst. NODeJ is also able to detect signals in nuclei from DNA FISH experiments, allowing for the analysis of specific targets of interest. Conclusion and availabilityNODeJ allows for efficient automated analysis of subnuclear structures by avoiding the semi-automated steps, resulting in reduced processing time and analytical bias. NODeJ is written in Java and provided as an ImageJ plugin with a command line option to perform more high-throughput analyses. NODeJ can be downloaded from https://gitlab.com/axpoulet/image2danalysis/-/releases with source code, documentation and further information avaliable at https://gitlab.com/axpoulet/image2danalysis. The images used in this study are publicly available at https://www.brookes.ac.uk/indepth/images/ and https://doi.org/10.15454/1HSOIE.

bioinformatics↗

bioRxiv2021

ANCHOR, a technical approach to monitor single-copy locus localization in planta

RESUMEGene expression is governed by several layers of regulation which in addition to genome organization, local chromatin structure, gene accessibility and the presence of transcription factors also includes gene positioning. Although basic mechanisms are expected to be conserved in Eukaryotes, surprisingly little information on the role of gene positioning is available in plant cells, mainly due to the lack of a highly resolutive approach. In this manuscript, we adapted the use of the ANCHOR system to perform real-time single-locus detection in planta. ANCHOR is a DNA-labelling tool derived from the partitioning system. We demonstrate its suitability to monitor a single-locus in planta and used this approach to track chromatin mobility during cell differentiation in Arabidopsis root epidermal cells. Finally, we discuss the potential of this approach to investigate the role of gene positioning during transcription and DNA repair in plants.

plant biology↗