Biology subjects

Modolo, L.

Publications and source records attributed to Modolo, L..

11 recordsLinked to original sources

bioRxiv2025

Trans-acting mutations reveal non-nuclear modulators of both intrinsic and extrinsic gene expression noise in a eukaryote.

Gene expression regulation is a stochastic process that can be modified by mutations not only in a deterministic manner but also in a probabilistic way, for example by changing the extent of cell-to-cell variability in gene expression (also called "gene expression noise"). Although systematic studies have successfully analyzed the properties of cis-acting mutations that modulate expression noise at their own locus, less is known about the type of genetic changes that alter expression noise in trans (at loci distant from the mutation). Here, we applied genetic mapping on yeast strains (Saccharomyces cerevisiae) generated by random mutagenesis and identified three mutations (in chs1, yme2 and msh1 genes) that changed the expression noise of a reporter gene in the nuclear genome regulated by the yeast TDH3 promoter. These mutations affected either extrinsic noise (variability due to cell-specific factors), intrinsic noise (inherent variability within each cell) or both, and their effects were found to not be specific to the TDH3 promoter. Surprisingly, all three mutations targeted proteins located outside of the nucleus: Yme2 and Msh1 being involved in the maintenance of mitochondrial genome integrity, and Chs1 being necessary for the repair of cell-wall defects in freshly-born daughter cells. Our results reveal that mitochondrial state can modulate the extent of intrinsic expression noise of eukaryotic nuclear genes.

genetics↗

bioRxiv2023

Mechanism of homology search expansion during recombinational DNA break repair

Homology search catalyzed by a RecA/Rad51 nucleoprotein filament (NPF) is a central step of DNA double-strand break (DSB) repair by homologous recombination. How it operates in cells remains elusive. Here we developed a Hi-C-based methodology to map single-stranded DNA (ssDNA) contacts genome-wide in S. cerevisiae, which revealed two main homology search phases. Initial search conducted by short NPFs is confined in cis by cohesin-mediated chromatin loop folding. Progressive growth of stiff NPFs enables exploration of distant genomic sites. Long-range resection by Exo1 drives this transition from local to genome-wide search by providing ssDNA substrates for assembly of extensive NPFs. DSB end-tethering promotes coordinated homology search by NPFs formed on the two DSB ends. Finally, an autonomous genetic element on chromosome III engages the NPF and stimulates homology search in its vicinity. This work reveals the mechanism of the progressive and uneven expansion of homology search orchestrated by chromatin organizers, long-range resection, end-tethering, specialized genetic elements, and that exploits the stiff NPF structure conferred by Rad51 oligomerization. Highlights- Cohesin-mediated chromatin loops constrain homology search in cis for NPF regions close to the resection front - Stiffening of ssDNA by Rad51 enables genome-wide homology search by DSB-proximal sites - Exo1-mediated long-range resection promotes genome-wide homology search - DSB end-tethering promotes coordinated homology search by NPFs formed on both DSB ends - The recombination enhancer focuses homology search in its vicinity

genetics↗

bioRxiv2022

Differentiation is accompanied by a progressive loss in transcriptional memory

Cell differentiation requires the integration of two opposite processes, a stabilizing cellular memory, especially at the transcriptional scale, and a burst of gene expression variability which follows the differentiation induction. Therefore, the actual capacity of a cell to undergo phenotypic change during a differentiation process relies upon a modification in this balance which favors change-inducing gene expression variability. However, there are no experimental data providing insight on how fast the transcriptomes of identical cells would diverge on the scale of the very first two cell divisions during the differentiation process. In order to quantitatively address this question, we developed different experimental methods to recover the transcriptomes of related cells, after one and two divisions, while preserving the information about their lineage at the scale of a single cell division. We analyzed the transcriptomes of related cells from two differentiation biological systems (human CD34+ cells and T2EC chicken primary erythrocytic progenitors) using two different single-cell transcriptomics technologies (sc-RT-qPCR and scRNA-seq). We identified that the gene transcription profiles of differentiating sister-cells are more similar to each-other than to those of non related cells of the same type, sharing the same environment and undergoing similar biological processes. More importantly, we observed greater discrepancies between differentiating sister-cells than between self-renewing sister-cells. Furthermore, a continuous increase in this divergence from first generation to second generation was observed when comparing differentiating cousin-cells to self renewing cousin-cells. Our results are in favor of a continuous and gradual erasure of transcriptional memory during the differentiation process.

cell biology↗

bioRxiv2022

Condensin positioning at telomeres by Taz1 promotes telomere disjunction in anaphase

The localization of condensin along chromosomes is crucial for their accurate segregation in anaphase. Condensin is enriched at telomeres but how and for what purpose had remained elusive. Here we show that fission yeast condensin accumulates at telomere repeats through the balancing acts of Taz1, a core component of the shelterin complex that ensures telomeric functions, and Mit1, a nucleosome-remodeler associated with shelterin. We further show that condensin takes part in sister-telomere separation in anaphase, and that this event can be uncoupled from the prior separation of chromosome arms, implying a telomere-specific separation mechanism. Consistent with a cis-acting process, increasing or decreasing condensin occupancy specifically at telomeres modifies accordingly the efficiency of their separation in anaphase. Genetic evidence suggests that condensin promotes sister-telomere separation by counteracting cohesin. Thus, our results reveal a shelterin-based mechanism that enriches condensin at telomeres to drive in cis their separation during mitosis.

cell biology↗

bioRxiv2022

Evidence for close molecular proximity between reverting and undifferentiated cells

According to Waddingtons epigenetic landscape concept, the differentiation process can be illustrated by a cell akin to a ball rolling down from the top of a hill (proliferation state) and crossing furrows before stopping in basins or "attractor states" to reach its stable differentiated state. However, it is now clear that some committed cells can retain a certain degree of plasticity and reacquire phenotypical characteristics of a more pluripotent cell state. In line with this dynamic model, we have previously shown that differentiating cells (chicken erythrocytic progenitors (T2EC)) retain for 24 hours the ability to self-renew when transferred back in self-renewal conditions. Despite those intriguing and promising results, the underlying molecular state of those "reverting" cells remains unexplored. The aim of the present study was therefore to molecularly characterize the T2EC reversion process by combining advanced statistical tools to make the most of single cell transcriptomic data. For this purpose, T2EC, initially maintained in a self-renewal medium (0H), were induced to differentiate for 24h (24H differentiating cells); then a part of these cells was transferred back to the self-renewal medium (48H reverting cells) and the other part was maintained in the differentiation medium for another 24h (48H differentiating cells). For each time point, cell transcriptomes were generated using scRT-qPCR and scRNAseq. Our results showed a strong overlap between 0H and 48H reverting cells when applying dimensional reduction. Moreover, the statistical comparison of cell distributions and differential expression analysis indicated no significant differences between these two cell groups. Interestingly, gene pattern distributions highlighted that, while 48H reverting cells have gene expression pattern more similar to 0H cells, they retained traces of their engagement in the differentiation process. Finally, Sparse PLS analysis showed that only the expression of 3 genes discriminates 48H reverting and 0H cells. Altogether, we show that reverting cells return to an earlier molecular state almost identical to undifferentiated cells and demonstrate a previously undocumented physiological and molecular plasticity during the differentiation process, which most likely results from the dynamic behavior of the underlying molecular network.

cell biology↗

bioRxiv2020

Translation-dependent and independent mRNA decay occur through mutually exclusive pathways that are defined by ribosome density during T Cell activation.

mRNA translation and degradation are strongly interconnected processes that participate in the fine tuning of gene expression. Particularly, targeting mRNAs to translation-dependent degradation (TDD) could attenuate protein expression by making any increase in mRNA translation self-limiting. However, the extent to which TDD is a general mechanism for limiting protein expression is currently unknown. Here we describe a comprehensive analysis of basal and signal-induced TDD in mouse primary CD4 T cells. Our data indicate that most cellular transcripts are decayed to some extent in a translation-dependent manner, both in resting and activated cells. Our analysis further identifies the length of untranslated regions, the density of ribosomes and the GC content of the coding region as major determinants of TDD magnitude. Consistent with this, all transcripts that undergo changes in ribosome density upon T cell activation display a corresponding change in their TDD level. Surprisingly, the amplitude of translation-independent mRNA decay (TID) appears as a mirror image of TDD. Moreover, TID also responds to changes in ribosome density upon T cell activation but in the opposite direction from the one observed for TDD. Our data demonstrate a strong interconnection between mRNA translation and decay in mammalian cells. Furthermore, they indicate that ribosome density is a major determinant of the pathway by which transcripts are degraded within cells.

genomics↗

bioRxiv2019

Clonally distinct differentiation trajectories shape CD8+ memory T cell heterogeneity after acute viral infections in humans

CD8+ T cells play essential roles in immunity to viral and bacterial infections, and to guard against malignant cells. The CD8+ T cell response to an antigen is composed of many T cell clones with unique T cell receptors, together forming a heterogenous repertoire of phenotypically and functionally distinct effector and memory cells1, 2. How individual T cell clones contribute to this heterogeneity during an immune response is key to understand immunity but remains largely unknown. Here, we longitudinally tracked CD8+ T cell clones expanding in response to yellow fever virus vaccination at the single cell level in humans. We show that only a fraction of the clones detected in the acute response persists as circulating memory T cells, indicative of clonal selection. Clones persisting in the memory phase displayed biased differentiation trajectories along a gradient of stem cell memory (SCM) towards terminally differentiated effector memory (EMRA) fates. Reactivation of single memory CD8+ T cells revealed that they were poised to recapitulate skewed differentiation trajectories in secondary responses, and this was generalizable across individuals for both yellow fever and influenza virus. Together, we show that the sum of distinct clonal differentiation repertoires results in the multifaceted T cell response to acute viral infections in humans.

immunology↗

bioRxiv2019

Interplay between gene nucleotide composition bias and splicing

To characterize the rules governing exon recognition during splicing, we analysed dozens of RNA-seq datasets and identified ~3,200 GC-rich exons and ~4,000 AT-rich exons whose inclusion depends on different sets of splicing factors. We show that GC-rich exons have predicted RNA secondary structures at 5-ss, and are dependent on U1 snRNP-associated proteins. In contrast, AT-rich exons have a large number of branchpoints and SF1-or U2AF2-binding sites and are dependent on U2 snRNP-associated proteins. Nucleotide composition bias also influences local chromatin organization, with consequences for exon recognition during splicing. As the GC content of exons correlates with that of their hosting genes, isochores and topologically-associated domains, we propose that regional nucleotide composition bias leaves a local footprint at the exon level and induces constraints during splicing that can be alleviated by local chromatin organization and recruitment of specific splicing factors. Therefore, nucleotide composition bias establishes a direct link between genome organization and local regulatory processes, like alternative splicing.

molecular biology↗

bioRxiv2018

Interplay between coding and exonic splicing regulatory sequences

The inclusion of exons during the splicing process depends on the binding of splicing factors to short low-complexity regulatory sequences. The relationship between exonic splicing regulatory sequences and coding sequences is still poorly understood. We demonstrate that exons that are coregulated by any splicing factor share a similar nucleotide composition bias. We next demonstrate that coregulated exons preferentially code for amino acids with similar physicochemical properties because of the non-randomness properties of the genetic code. Indeed, amino acids sharing physicochemical properties correspond to codons that have the same nucleotide composition bias. These observations reveal an unanticipated bidirectional interplay between the physicochemical features encoded by exons and exon splicing regulation by splicing factors. We propose that the splicing regulation of an exon by a splicing factor is tightly interconnected with the physicochemical properties of the exon-encoded protein domain depending on the splicing-factor affinity for specific nucleotides.

genomics↗

bioRxiv2018

Condensin controls cellular RNA levels through the accurate segregation of chromosomes instead of directly regulating transcription

Condensins are genome organisers that shape chromosomes and promote their accurate transmission. Several studies have also implicated condensins in gene expression, although the mechanisms have remained enigmatic. Here, we report on the role of condensin in gene expression in fission and budding yeasts. In contrast to previous studies, we provide compelling evidence that condensin plays no direct role in the maintenance of the transcriptome, neither during interphase nor during mitosis. We further show that the changes in gene expression in post-mitotic fission yeast cells that result from condensin inactivation are largely a consequence of chromosome missegregation during anaphase, which notably depletes the RNA-exosome from daughter cells. Crucially, preventing karyotype abnormalities in daughter cells restores a normal transcriptome despite condensin inactivation. Thus, chromosome instability, rather than a direct role of condensin in the transcription process, changes gene expression. This knowledge challenges the concept of gene regulation by canonical condensin complexes.

molecular biology↗

bioRxiv2017

Probabilistic Count Matrix Factorization for Single Cell Expression Data Analysis

The development of high throughput single-cell technologies now allows the investigation of the genome-wide diversity of transcription. This diversity has shown two faces: the expression dynamics (gene to gene variability) can be quantified more accurately, thanks to the measurement of lowly-expressed genes. Second, the cell-to-cell variability is high, with a low proportion of cells expressing the same gene at the same time/level. Those emerging patterns appear to be very challenging from the statistical point of view, especially to represent and to provide a summarized view of single-cell expression data. PCA is one of the most powerful frameworks to provide a suitable representation of high dimensional datasets, by searching for new axes catching the most variability in the data. Unfortunately, classical PCA is based on Euclidean distances and projections that work poorly in presence of over-dispersed counts showing zero-inflation. We propose a probabilistic Count Matrix Factorization (pCMF) approach for single-cell expression data analysis, that relies on a sparse Gamma-Poisson factor model. This hierarchical model is inferred using a variational EM algorithm. We show how this probabilistic framework induces a geometry that is suitable for single-cell data, and produces a compression of the data that is very powerful for clustering purposes. Our method is competed to other standard representation methods like ZIFA and t-SNE, and we illustrate its performance on simulated and publicly available data.

bioinformatics↗