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SERIZAY, J.

Publications and source records attributed to SERIZAY, J..

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Cyclin O controls entry into the cell-cycle variant required for multiciliated cell differentiation

Multiciliated cells (MCC) ensure proper fluid circulation in various organs in metazoans. Their differentiation is marked by the massive ampliication of cilia-nucleating centrioles and is known to be controlled by various cell cycle components. Tn a companion study, we show that the differentiation of MCC is driven by a genuine cell-cycle variant characterized by sequential and wave-like expression of canonical and non-canonical cyclins such as Cyclin O (CCNO). Patients with CCNO mutations exhibit a subtype of Primary Ciliary Dyskinesia (PCD) designated as Reduced Generation of Multiple Motile Cilia (RGMC), yet the role of CCNO during MCC differentiation remains unclear. Here, using mice and human cellular models, single cell transcriptomics and functional studies, we show that Cena is activated during a strategic temporal window at the crossroads between the onset of MCC differentiation, the entry into the MCC cell cycle variant, and the activation of the centriole biogenesis program. We ind that the absence of Cena leads to a block of MCC progenitor differentiation at the G1/S-like transition, just before the beginning of centriole formation. This leads to a complete lack of centrioles and cilia in mouse brain and human airway MCC. Altogether, our study identifies CCNO as a core regulator of entry into the MCC cell cycle variant and shows that the coupling of centriole biogenesis to an S-like phase, maintained in MCC, is dependent on CCNO. One sentence summaryCyclin O is necessary for multiciliated cells to enter their differentiation cell cycle variant and allows the massive amplification of centrioles, which serve as basal bodies for cilia nucleation.

cell biology↗

Epigenomics coverage data extraction and aggregation in R with tidyCoverage

SummaryThe tidyCoverage R package provides a framework for intuitive investigation of collections of genomic tracks over genomic features, relying on the principle of tidy data manipulation. It defines two data structures, CoverageExperiment and AggregatedCoverage classes, directly extending the SummarizedExperiment fundamental class, and introduces a principled approach to exploring genome-wide data. This infrastructure facilitates the extraction and manipulation of genomic coverage track data across individual or multiple sets of thousands of genomic loci. This allows the end user to rapidly visualize track coverage at individual genomic loci or aggregated coverage profiles over sets of genomic loci. tidyCoverage seamlessly combines with the existing Bioconductor ecosystem to accelerate the integration of genome-wide track data in epigenomic analysis workflows. tidyCoverage emerges as a valuable tool, contributing to the advancement of epigenomics research by promoting consistency, reproducibility, and accessibility in data analysis. Availability and implementationtidyCoverage is an R package freely available from Bioconductor [≥] 3.19 (https://www.bioconductor.org/packages/tidyCoverage) for R [≥] 4.4. The software is distributed under the MIT License and is accompanied by example files and data. Contactjacques.serizay@pasteur.fr Supplementary informationAdditional documentation is available from https://js2264.github.io/tidyCoverage/ and https://js2264.github.io/tidyCoverage/articles/tidyCoverage.html.

bioinformatics↗