Biology subjects

Legewie, S.

Publications and source records attributed to Legewie, S..

9 recordsLinked to original sources

bioRxiv2026

Chromosome segregation synchrony in S. pombe is noise-limited and arises without positive feedback

Anaphase is a key cell cycle transition that ensures faithful genome inheritance. At anaphase onset, sister chromatids separate abruptly and synchronously upon activation of the protease separase. Major cell cycle transitions often involve positive feedback, which contributes to their abruptness and irreversibility; however, whether such feedback is required for anaphase remains unclear. Here, we analyze sister chromatid separation dynamics in fission yeast using high-resolution live-cell imaging and computational modeling. We find that anaphase synchrony relies on fast degradation of the separase inhibitor securin, but does not require separase-mediated positive feedback. Hence, sister chromatid separation, being inherently irreversible, may be one of the few major cell cycle transitions that can proceed without positive feedback. A stochastic model fitted to the data revealed that separation synchrony is limited by stochasticity resulting from small-number effects. Together, these results support a feedback-independent mechanism for anaphase onset and identify molecular noise as a fundamental constraint on its temporal precision.

cell biology↗

bioRxiv2026

RNA G-quadruplexes mediate cooperativity in HNRNPH binding and splicing regulation

Alternative splicing, regulated by RNA-binding proteins (RBPs), enables the generation of diverse transcript isoforms critical for cellular function. However, how RNA secondary structure impacts RBP binding and function remains poorly understood. Here, we unravel how RNA G-quadruplexes (rG4s) facilitate cooperativity in splicing regulation by the RBP heterogeneous nuclear ribonucleoprotein H (HNRNPH). Through high-throughput in vivo and in vitro studies combined with theoretical modeling, we dissect how rG4s mediate cooperative HNRNPH binding to RNA, ultimately modulating the splicing of hundreds of exons. rG4 unfolding by HNRNPH exposes multiple G-rich binding sites, thereby establishing indirect cooperativity, which is further amplified to achieve switch-like splicing regulation. HNRNPH-mediated regulation is evident in breast cancer patients, with tumors showing rG4-disrupting variants and global HNRNPH alterations, driving distinct splicing patterns that distinguish tumor subtypes. Overall, our findings offer valuable insights into the mechanistic role of RNA secondary structures in cooperative RBP binding and splicing regulation and highlight the clinical relevance of HNRNPH-dependent splicing in cancer. HighlightsO_LIHundreds of cassette exons are cooperatively regulated by HNRNPH. C_LIO_LIUnfolding of RNA G-quadruplexes (rG4s) at HNRNPH binding sites facilitates indirect cooperativity in RNA binding. C_LIO_LIMulti-step splicing amplifies the response into highly switch-like regulation. C_LIO_LIrG4-disrupting variants and changing HNRNPH expression are associated with breast cancer phenotypes. C_LI

molecular biology↗

bioRxiv2025

Context-dependent effects of mutations on complex splicing decisions

Alternative pre-mRNA splicing is an essential step in human gene regulation, and mutation-induced aberrant splicing is frequently found in diseases and therapy resistance. Splicing regulation is highly dependent on sequence and cellular context, posing a challenge to predict outcomes of splicing-related disease mutations. Here, we use kinetic modeling to derive the underlying quantitative principles, describing splice site competition and downstream effects on a wide spectrum of splice isoforms. Employing statistical learning on a large-scale mutagenesis dataset for CD19 mRNA splicing, our model quantitatively describes the generation of 93 RNA isoforms. It takes into account various splicing events such as cassette exon skipping, intron retention, and extensive alternative 3 and 5 splice site usage, which are implicated in CART therapy resistance in leukemia. Beyond CD19, by analyzing genome-wide RNA sequencing data and large-scale screening of synthetic splicing decisions, we find that splice site distance is an important parameter controlling the switch from canonical to alternative/cryptic splice site usage, as mutations located in between two nearby splice sites show a pronounced directionality, regulating up- and downstream effectors in opposite direction. Taken together, our work demonstrates that a quantitative description of splice site competition provides insights into context-dependent, complex isoform changes and cryptic splice site activation in health and disease.

systems biology↗

bioRxiv2024

Coordinated alternative splicing decisions via stepwise exon definition

Alternative splicing of pre-mRNA is a fundamental step in human gene regulation and aberrant slic-ing is tightly linked to diseases including cancer. Various splicing events, such as alternative exon (AE) choice and intron retention (IR), are controlled by a common molecular machinery, the spliceo-some. However, it remains elusive how the regulation of spliceosome activity coordinately affects these splicing decisions. Here, we analyze a large-scale mutagenesis screen and genome-wide RNA sequencing data to show that IR and AE choice are tightly coupled, as IR products primarily accu-mulate in alternative exons showing intermediate inclusion levels. Using data-driven mathematical modeling, we reveal that multistep exon recognition by the spliceosome explains the observed AE-IR dependency for cis-acting sequence mutations and upon knockdown of trans-acting RNA-binding proteins. Furthermore, we show that multistep exon definition is frequently perturbed in cancer cells, which leads to the coordinated deregulation of intron retention and AE choice. In conclusion, we showed that the spliceosome coordinates complex splicing decisions via stepwise exon definition, which potentially facilitates the search for common molecular mechanisms for mis-splicing in cancer.

systems biology↗

bioRxiv2024

CRISPR gene and transcriptome engineering (CRISPRgate) improves loss-of-function genetic screening approaches

The CRISPR/Cas9 technology has revolutionized genotype-to-phenotype assignments through large-scale loss-of-function (LOF) screens. However, limitations like editing inefficiencies and unperturbed genes cause significant noise in data collection. To address this, we introduce CRISPR Gene and Transcriptome Engineering (CRISPRgate), which uses two specific sgRNAs to simultaneously repress and cleave the target gene within the same cell, increasing LOF efficiencies and reproducibility. CRISPRgate outperforms conventional CRISPRko, CRISPRi, or CRISPRoff systems in suppressing challenging targets and regulators of cell proliferation. Additionally, it efficiently suppresses modulators of EMT and impairs neuronal differentiation in a human iPSC model. In a multiplexed chromatin-focused phenotypic LOF screen, CRISPRgate exhibits improved depletion efficiency, reduced sgRNA performance variance, and accelerated gene depletion compared to individual CRISPRi or CRISPRko, ensuring consistency in phenotypic effects and identifying more significant gene hits. By combining CRISPRko and CRISPRi, CRISPRgate increases LOF rates without increasing genotoxic stress, facilitating library size reduction for advanced LOF screens. MotivationThe CRISPR technology (CRISPRko/CRISPRi) enables the specific depletion of target genes with fewer off-target effects, facilitating precise investigations of gene function. Despite its benefits, CRISPR applications have limitations. Residual active protein expression mediated by in-frame DNA repair or alternative splicing1-8 as well as strong epigenetic regulation and difficulties in sgRNA design to the transcription start site (TSS)9-12 hinder the full potential of loss-of-function studies using CRISPRko or CRISPRi. We aimed to achieve robust target gene reduction in order to improve the reproducibility of the CRISPR technology by integrating the widely used CRISPRko and CRISPRi approaches into a single application.

biochemistry↗

bioRxiv2024

Transcriptional regulators ensuring specific gene expression and decision making at high TGFβ doses

TGF{beta}-signaling regulates cancer progression by controlling cell division, migration and death. These outcomes are mediated by gene expression changes, but the mechanisms of decision making towards specific fates remain unclear. Here, we combine SMAD transcription factor imaging, genome-wide RNA sequencing and morphological assays to quantitatively link signaling, gene expression and fate decisions in mammary epithelial cells. Fitting genome-wide kinetic models to our time-resolved data, we find that the majority of TGF{beta} target genes can be explained as direct targets of SMAD transcription factors, whereas the remainder show signs of complex regulation, involving delayed regulation and strong amplification at high TGF{beta} doses. Knockdown experiments followed by global RNA sequencing revealed transcription factors interacting with SMADs in feedforward loops to control delayed and dose-discriminating target genes, thereby reinforcing the specific epithelial-to-mesenchymal transition at high TGF{beta} doses. We identified early repressors, preventing premature activation, and a late activator, boosting gene expression responses for a sufficiently strong TGF{beta} stimulus. Taken together, we present a global view of TGF{beta}-dependent gene regulation and describe specificity mechanisms reinforcing cellular decision making.

systems biology↗

bioRxiv2022

Machine learning-assisted identification of factors contributing to the technical variability between bulk and single-cell RNA-seq experiments

BackgroundRecent studies in the area of transcriptomics performed on single-cell and population levels reveal noticeable variability in gene expression measurements provided by different RNA sequencing technologies. Due to increased noise and complexity of single-cell RNA-Seq (scRNA-Seq) data over the bulk experiment, there is a substantial number of variably-expressed genes and so-called dropouts, challenging the subsequent computational analysis and potentially leading to false positive discoveries. In order to investigate factors affecting technical variability between RNA sequencing experiments of different technologies, we performed a systematic assessment of single-cell and bulk RNA-Seq data, which have undergone the same pre-processing and sample preparation procedures. ResultsOur analysis indicates that variability between gene expression measurements as well as dropout events are not exclusively caused by biological variability, low expression levels, or random variation. Furthermore, we propose FAVSeq, a machine learning-assisted pipeline for detection of factors contributing to gene expression variability in matched RNA-Seq data provided by two technologies. Based on the analysis of the matched bulk and single-cell dataset, we found the 3-UTR and transcript lengths as the most relevant effectors of the observed variation between RNA-Seq experiments, while the same factors together with cellular compartments were shown to be associated with dropouts. ConclusionsHere, we investigated the sources of variation in RNA-Seq profiles of matched single-cell and bulk experiments. In addition, we proposed the FAVSeq pipeline for analyzing multimodal RNA sequencing data, which allowed to identify factors affecting quantitative difference in gene expression measurements as well as the presence of dropouts. Hereby, the derived knowledge can be employed further in order to improve the interpretation of RNA-Seq data and identify genes that can be affected by assay-based deviations. Source code is available under the MIT license at https://github.com/slipnitskaya/FAVSeq.

bioinformatics↗

bioRxiv2021

High-throughput mutagenesis identifies mutations and RNA binding proteins controlling CD19 splicing and CART-19 therapy resistance

During CART-19 immunotherapy for B-cell acute lymphoblastic leukaemia (B-ALL), many patients relapse due to loss of the cognate CD19 epitope. Since epitope loss can be caused by aberrant CD19 exon 2 processing, we herein investigate the regulatory code that controls CD19 splicing. We combine high-throughput mutagenesis with mathematical modelling to quantitatively disentangle the effects of all mutations in the region comprising CD19 exons 1-3. Thereupon, we identify ~200 single point mutations that alter CD19 splicing and thus could predispose B-ALL patients to CART-19 resistance. Furthermore, we report almost 100 previously unknown splice isoforms that emerge from cryptic splice sites and likely encode non-functional CD19 proteins. We further identify cis-regulatory elements and trans-acting RNA-binding proteins that control CD19 splicing (e.g., PTBP1 and SF3B4) and validate that loss of these factors leads to enhanced CD19 mis-splicing. Our dataset represents a comprehensive resource for potential prognostic factors predicting success of CART-19 therapy. HighlightsO_LIMutations in relapsed CART-19 patients lead to CD19 mis-splicing C_LIO_LIHigh-throughput mutagenesis uncovers ~200 single point mutations with a potential role in CART-19 therapy resistance C_LIO_LIMany mutations generate non-functional CD19 proteins by activating cryptic splice sites C_LIO_LIRNA-binding proteins such as PTBP1 are key to the expression of properly spliced, CART-19 immunotherapy-sensitive isoforms C_LI

molecular biology↗

bioRxiv2019

Exon definition facilitates reliable control of alternative splicing

Alternative splicing is a key step in eukaryotic gene expression that allows the production of multiple protein isoforms from the same gene. Even though splicing is perturbed in many diseases, we currently lack insights into regulatory mechanisms promoting its precision and efficiency. We analyse high-throughput mutagenesis data obtained for an alternatively spliced exon in the proto-oncogene RON and determine the functional units that control this splicing event. Using mathematical modeling of distinct splicing mechanisms, we show that alternative splicing is based in RON on a so-called exon definition mechanism. Here, the recognition of the adjacent exons by the spliceosome is required for removal of an intron. We use our model to analyze the differences between the exon and intron definition scenarios and find that exon definition is crucial to prevent the accumulation of deleterious, partially spliced retention products during alternative splicing regulation. Furthermore, it modularizes splicing control, as multiple regulatory inputs are integrated into a common net input, irrespective of the location and nature of the corresponding cis-regulatory elements in the pre-mRNA. Our analysis suggests that exon definition promotes robust and reliable splicing outcomes in RON splicing. SIGNIFICANCEDuring mRNA maturation, pieces of the pre-mRNA (introns) are removed during splicing, and remaining parts (exons) are joined together. In alternative splicing, certain exons are either included or excluded, resulting in different splice products. Inclusion of RON alternative exon 11 leads to a functional receptor tyrosine kinase, while skipping results in a constitutively active receptor that promotes epithelial-to-mesenchymal transition and contributes to tumour invasiveness. Intron retention results in to deleterious isoforms that cannot be translated properly. Using kinetic modeling, we investigate the combinatorial regulation of this important splicing decision, and find that the experimental data supports a so-called exon definition mechanism. We show that this mechanism enhances the precision of alternative splicing regulation and prevents the retention of introns in the mature mRNA.

systems biology↗