Biology subjects

Tarbier, M.

Publications and source records attributed to Tarbier, M..

7 recordsLinked to original sources

bioRxiv2026

RNA degradation by DIS3 is a necessary step in the resolution of backtracked transcription complexes

The RNA exosome is known to participate in transcription, but the contribution of its ribonuclease activities to this process remains unclear. Here we investigated the role of DIS3, one of the exosome ribonucleases, in transcription by RNA polymerase II (RNAPII). Rapid depletion of DIS3 reduced RNA synthesis and induced RNAPII elongation defects that were exacerbated by UV irradiation, a treatment that generates transcription-blocking DNA lesions and promotes RNAPII backtracking. Notably, DIS3 itself was redistributed following UV irradiation in a manner that closely paralleled RNAPII dynamics, which suggested that DIS3 acts in concert with the transcription machinery. We also investigated whether RNA degradation by DIS3 was required for transcription elongation and found that the 3-5 exoribonucleolytic activity of DIS3, but not its endonucleolytic activity, is essential for efficient transcription elongation. More specifically, DIS3 degrades the 3 ends of backtracked RNA, as shown by sequencing of RNA fragments released by TFIIS-induced transcript cleavage in vitro. This DIS3-dependent degradation of backtracked RNA is critical for resolving stalled RNAPII complexes and enabling productive transcription elongation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/703186v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@c080dorg.highwire.dtl.DTLVardef@1e4b375org.highwire.dtl.DTLVardef@1c1f575org.highwire.dtl.DTLVardef@d9d640_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDIS3 depletion leads to severely reduced rates of RNA synthesis in human cells. C_LIO_LITranscription-blocking lesions reveal a critical role for DIS3 in RNA polymerase II elongation. C_LIO_LIThe 3 to 5 exoribonuclease activity of DIS3 is necessary for transcription elongation. C_LIO_LIDIS3-mediated degradation of backtracked RNA is required for the resolution of stalled transcription complexes. C_LI

molecular biology↗

bioRxiv2025

CycleVI: Isolating cell cycle variation with an interpretable deep generative model

MotivationCell cycle progression is a dominant source of variation in single-cell RNA sequencing (scRNA-seq) data, often obscuring other transcriptional signals of interest. Several methods have been developed to infer continuous cell-cycle phase from transcriptomic data, but their estimates tend to be unstable when proliferation is intertwined with other biological processes or technical sources of heterogeneity. ResultsWe present CycleVI, a deep generative model that disentangles cell cycle-driven variation from other signals in scRNA-seq data using a partitioned latent representation with a dedicated circular subspace. CycleVI accurately infers a continuous cell cycle phase, validated against orthogonal protein-level measurements, and yields a residual latent space free of cell cycle artifacts. This disentangled representation helps resolve biological processes intertwined with the cell cycle, clarifying hematopoietic differentiation and preserving drug-response signals better than standard cell cycle regression. By iso-lating cell cycle-related variation rather than removing it, CycleVI provides a principled framework for analyzing cellular heterogeneity in proliferating systems. Availability and ImplementationCycleVI is available at www.github.com/jeuken/CycleVI.

systems biology↗

bioRxiv2024

Landscape of microRNA and target expression variation and covariation in single mouse embryonic stem cells

MicroRNAs are small RNA molecules that can repress the expression of protein coding genes post-transcriptionally. Previous studies have shown that microRNAs can also have alternative functions including target noise buffering and co-expression, but these observations have been limited to a few microRNAs. Here we systematically study microRNA alternative functions in mouse embryonic stem cells, by genetically deleting Drosha - leading to global loss of microRNAs. We apply complementary single-cell RNA-seq methods to study the variation of the targets and the microRNAs themselves, and transcriptional inhibition to measure target half-lives. We find that microRNAs form four distinct co-expression groups across single cells. In particular the mir-290 and the mir-182 clusters are abundantly, variably and inversely expressed. Intriguingly, some cells have global biases towards specific miRNAs originating from either end of the hairpin precursor, suggesting the presence of unknown regulatory cofactors. We find that miRNAs generally increase variation and covariation of their targets at the RNA level, but we also find miRNAs such as miR-182 that appear to have opposite functions. In particular, miRNAs that are themselves variable in expression, such as miR-291a, are more likely to induce covariations. In summary, we apply genetic perturbation and multi-omics to give the first global picture of microRNA dynamics at the single cell level.

genomics↗

bioRxiv2022

Barcode-free prediction of cell lineages from scRNA-seq datasets

The integration of lineage tracing with scRNA-seq has transformed our understanding of gene expression heritability during development, regeneration, and disease. However, lineage tracing is technically demanding and most existing scRNA-seq datasets are devoid of lineage information. Here we introduce Gene Expression Memory-based Lineage Inference (GEMLI), a computational pipeline allowing to predict cell lineages over several cell divisions solely from scRNA-seq datasets. GEMLI leverages genes displaying conserved expression levels over cell divisions, and allows i.a. identifying cell lineages in a broad range of cultured cell types, in intestinal organoids, and in crypts from adult mice. GEMLI recovers GO-terms enriched for heritable gene expression, allows to discriminate symmetric and asymmetric cell fate decisions and to reconstruct individual cellular structures from pooled scRNA-seq datasets. GEMLI considerably extends the pool of datasets from which lineage information can be obtained, thereby facilitating the study of gene expression heritability in a broad range of contexts. GEMLI is available at (https://github.com/UPSUTER/GEMLI).

developmental biology↗

bioRxiv2019

Ancient microRNA profiles of a 14,300-year-old canid are taxonomically informative and give glimpses into gene regulation from the Pleistocene

Ancient DNA sequencing is the key technology for paleogenomic studies and today a routine method in many laboratories. Recent analyses have shown that, under favoring conditions, also RNA can be sequenced from historical and even ancient samples. We have re-analyzed ancient RNA data from a Pleistocene canid and find - in addition to the previously described messenger RNA fragments - intact microRNAs, which are short transcripts with important gene regulatory functions. With an extraordinary age of 14,300 years, the canid microRNA profiles are the oldest ever reported. Despite their age, we show that the microRNA profiles are conclusive of taxonomic origin, tissue identity with organ- and cell-type specific signatures, and that they yield glimpses into gene regulatory activity and biological processes from the Pleistocene. In summary, we here show that straightforward microRNA analyses hold great promise for deeper insights into gene regulation in extinct animals.

evolutionary biology↗

bioRxiv2019

Nuclear gene proximity and protein interactions shape transcript covariances in mammalian single cells

Single-cell RNA sequencing studies into gene co-expression patterns could yield important new regulatory and functional insights, but have so far been limited by the confounding effects of cell differentiation and the cell cycle. We apply a tailored experimental design that eliminates these confounders, and report >80,000 intrinsically covarying gene pairs in mouse embryonic stem cells. These covariances form a network with biological properties, outlining known and novel gene interactions. We provide the first evidence that miRNAs naturally induce transcriptome-wide covariances, and compare the relative importance of nuclear organization, transcriptional and post-transcriptional regulation in defining covariances. We find that nuclear organization has the greatest impact, and that genes encoding for physically interacting proteins specifically tend to covary, suggesting importance for protein complex stoichiometry. Our results lend support to the concept of post-transcriptional RNA operons, but we further present evidence that nuclear proximity of genes on the same or even distinct chromosomes also provides substantial functional regulation in mammalian single cells.

systems biology↗

bioRxiv2019

Combined mRNA and protein single cell analysis in a dynamic cellular system using SPARC

Combined measurements of mRNA and protein expression in single cells enables in-depth analysis of cellular states. We present single-cell protein and RNA co-profiling (SPARC), an approach to simultaneously measure global mRNA and large sets of intracellular protein in individual cells. Using SPARC, we show that mRNA expression fails to accurately reflect protein abundance at the time of measurement in human embryonic stem cells, although the direction of changes of mRNA and protein expression are in agreement during cellular differentiation. Moreover, protein levels of transcription factors better predict their downstream effects than do the corresponding transcripts. We further show that changes of the balance between protein and mRNA expression levels can be applied to infer expression kinetic trajectories, revealing future states of individual cells. Finally, we highlight that mRNA expression may be more varied among cells than levels of the corresponding proteins. Overall, our results demonstrate that mRNA and protein measurements in single cells provide different and complementary information regarding cell states. Accordingly, SPARC can offer valuable insights in gene expression programs of single cells.

cell biology↗