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Metabolic dysfunction–associated steatotic liver disease (MASLD) — characterized by excess accumulation of fat in the liver — now affects one-third of the world’s population. As MASLD progresses, extracellular matrix components including collagen accumulate in the liver, causing tissue fibrosis, a major determinant of disease severity and mortality. To identify transcriptional regulators of fibrosis, we computationally inferred the activity of transcription factors (TFs) relevant to fibrosis by profiling the matched transcriptomes and epigenomes of 108 human liver biopsies from a deeply characterized cohort of patients spanning the full histopathologic spectrum of MASLD. CRISPR-based genetic KO of the top 100 TFs identified ZNF469 as a regulator of collagen expression in primary human hepatic stellate cells (HSCs). Gain- and loss-of-function studies established that ZNF469 regulates collagen genes and genes involved in matrix homeostasis through direct binding to gene bodies and regulatory elements. By integrating multiomic large-scale profiling of human biopsies with extensive experimental validation, we demonstrate that ZNF469 is a transcriptional regulator of collagen in HSCs. Overall, these data nominate ZNF469 as a previously unrecognized determinant of MASLD-associated liver fibrosis.

Signaling pathways drive cell fate transitions largely by changing gene expression. However, the mechanisms for rapid and selective transcriptome rewiring in response to signaling cues remain elusive. Here we use deep learning to deconvolve both the sequence determinants and the trans -acting regulators that trigger extracellular signal-regulated kinase (ERK)–mitogen-activated protein kinase kinase (MEK)-induced decay of the naive pluripotency mRNAs. Timing of decay is coupled to embryo implantation through ERK–MEK phosphorylation of LIN28A, which repositions pLIN28A to the highly A+U-rich 3′ untranslated region (3′UTR) termini of naive pluripotency mRNAs. Interestingly, these A+U-rich 3′UTR termini serve as poly(A)-binding protein (PABP)-binding hubs, poised for signal-induced convergence with LIN28A. The multivalency of AUU motifs determines the efficacy of pLIN28A–PABP convergence, which enhances PABP 3′UTR binding, decreases the protection of poly(A) tails and activates mRNA decay to enable progression toward primed pluripotency. Thus, the signal-induced convergence of LIN28A with PABP–RNA hubs drives the rapid selection of naive mRNAs for decay, enabling the transcriptome remodeling that ensures swift developmental progression. Here the authors show that, upon embryo implantation, signaling triggers a large-scale rearrangement of protein–RNA interactions. Phosphorylated LIN28A reassembles onto the 3′ untranslated region termini of pluripotency-associated mRNAs, where it converges with the binding of poly(A)-binding protein and drives selective mRNA decay.

Abstract Non-negative matrix factorization (NMF) has been widely used for the analysis of genomic data to perform feature extraction and signature identification due to the interpretability of the decomposed signatures. However, running a basic NMF analysis requires the installation of multiple tools and dependencies, along with a steep learning curve and computing time. To mitigate such obstacles, we developed ShinyButchR, a novel R/Shiny application that provides a complete NMF-based analysis workflow, allowing the user to perform matrix decomposition using NMF, feature extraction, interactive visualization, relevant signature identification, and association to biological and clinical variables. ShinyButchR builds upon the also novel R package ButchR, which provides new TensorFlow solvers for algorithms of the NMF family, functions for downstream analysis, a rational method to determine the optimal factorization rank and a novel feature selection strategy.

The embryonic progression from naïve to primed pluripotency is accompanied by the rapid decay of pluripotency-associated mRNAs and a concomitant radical morphogenetic sequence of epiblast polarization, rosette formation and lumenogenesis. The mechanisms triggering and linking these events remain poorly understood. Guided by machine learning and metabolic RNA sequencing, we identified RNA binding proteins (RBPs), especially LIN28A, as primary mRNA decay factors. Using mRNA-RBP interactome capture, we revealed a dramatic increase in LIN28A mRNA binding during the naïve-rosette-primed pluripotency transition, driven by its nucleolar-to-cytoplasmic translocation. Cytoplasmic LIN28A binds to 3’UTRs of pluripotency-associated mRNAs to directly stimulate their decay and drive lumenogenesis. Accordingly, forced nuclear retention of LIN28A impeded lumenogenesis, impaired gastrulation, and caused an unforeseen embryonic multiplication. Selective mRNA decay, driven by nucleo-cytoplasmic RBP translocation, therefore acts as an intrinsic mechanism linking cell identity switches to the control of embryonic growth and morphogenesis. Competing Interest Statement The authors have declared no competing interest.

Neural induction in vertebrates generates a central nervous system that extends the rostral-caudal length of the body. The prevailing view is that neural cells are initially induced with anterior (forebrain) identity, with caudalising signals then converting a proportion to posterior fates (spinal cord). To test this model, we used chromatin accessibility assays to define how cells adopt region-specific neural fates. Together with genetic and biochemical perturbations this identified a developmental time window in which genome-wide chromatin remodeling events preconfigure epiblast cells for neural induction. Contrary to the established model, this revealed that cells commit to a regional identity before acquiring neural identity. This 'primary regionalization' allocates cells to anterior or posterior regions of the nervous system, explaining how cranial and spinal neurons are generated at appropriate axial positions. These findings prompt a revision to models of neural induction and support the proposed dual evolutionary origin of the vertebrate central nervous system.

Spatiotemporal regulation of gene expression is controlled by transcription factor (TF) binding to regulatory elements, resulting in a plethora of cell types and cell states from the same genetic information. Due to the importance of regulatory elements, various sequencing methods have been developed to localise them in genomes, for example using ChIP-seq profiling of the histone mark H3K27ac that marks active regulatory regions. Moreover, multiple tools have been developed to predict TF binding to these regulatory elements based on DNA sequence. As altered gene expression is a hallmark of disease phenotypes, identifying TFs driving such gene expression programs is critical for the identification of novel drug targets. In this study, we curated 84 chromatin profiling experiments (H3K27ac ChIP-seq) where TFs were perturbed through e.g., genetic knockout or overexpression. We ran nine published tools to prioritize TFs using these real-world data sets and evaluated the performance of the methods in identifying the perturbed TFs. This allowed the nomination of three frontrunner tools, namely RcisTarget, MEIRLOP and monaLisa. Our analyses revealed opportunities and commonalities of tools that will help to guide further improvements and developments in the field.

Non-alcoholic fatty liver disease (NAFLD) - characterized by excess accumulation of fat in the liver - now affects one third of the world's population. As NAFLD progresses, extracellular matrix components including collagen accumulate in the liver causing tissue fibrosis, a major determinant of disease severity and mortality. To identify transcriptional regulators of fibrosis, we computationally inferred the activity of transcription factors (TFs) relevant to fibrosis by profiling the matched transcriptomes and epigenomes of 108 human liver biopsies from a deeply-characterized cohort of patients spanning the full histopathologic spectrum of NAFLD. CRISPR-based genetic knockout of the top 100 TFs identified ZNF469 as a regulator of collagen expression in primary human hepatic stellate cells (HSCs). Gain- and loss-of-function studies established that ZNF469 regulates collagen genes and genes involved in matrix homeostasis through direct binding to gene bodies and regulatory elements. By integrating multiomic large-scale profiling of human biopsies with extensive experimental validation we demonstrate that ZNF469 is a transcriptional regulator of collagen in HSCs. Overall, these data nominate ZNF469 as a previously unrecognized determinant of NAFLD-associated liver fibrosis.

Transcription factors (TFs) regulate gene expression by recognising and binding specific DNA sequences. At times, these regulatory elements may be occluded by nucleosomes, making them inaccessible for TF-binding. The competition for DNA occupancy between TFs and nucleosomes, and associated gene regulatory outputs, are important consequences of the cis-regulatory information encoded in the genome. However, these sequence patterns are subtle and remain difficult to interpret. Here, we introduce ChromWave, a deep-learning model that, for the first time, predicts the competing profiles for TF and nucleosomes occupancies with remarkable accuracy. Models trained using short- and long-fragment MNase-Seq data successfully learn the sequence preferences underlying TF and nucleosome occupancies across the entire yeast genome. They recapitulate nucleosome evictions from regions containing \"strong\" TF binding sites and knock-out simulations show nucleosomes gaining occupancy in the absence of these TFs, accompanied by lateral rearrangement of adjacent nucleosomes. At a local level, models anticipate with high accuracy the outcomes of detailed experimental analysis of partially unwrapped nucleosomes at the GAL4 UAS locus. Finally, we trained a ChromWave model that successfully predicts nucleosome positions at promoters in the human genome. We find that human promoters generally contain few sites at which simple sequence changes can alter nucleosome occupancies and that these positions align well with causal variants linked to DNase hypersensitivity.Competing Interest StatementThe authors have declared no competing interest.Footnotes* General clarifications and small corrections throughout the text; Typo in Fig 2A corrected.* https://github.com/luslab/ChromWave* https://github.com/luslab/chromWaveR

RNA-binding proteins (RBPs) play diverse roles in regulating co-transcriptional RNA-processing and chromatin functions, but our knowledge of the repertoire of chromatin-associated RBPs (caRBPs) and their interactions with chromatin remains limited. Here, we developed SPACE (Silica Particle Assisted Chromatin Enrichment) to isolate global and regional chromatin components with high specificity and sensitivity, and SPACEmap to identify the chromatin-contact regions in proteins. Applied to mouse embryonic stem cells, SPACE identified 1,459 chromatin-associated proteins, ~48% of which are annotated as RBPs, indicating their dual roles in chromatin and RNA-binding. Additionally, SPACEmap stringently verified chromatin-binding of 404 RBPs and identified their chromatin-contact regions. Notably, SPACEmap showed that about half of the caRBPs bind to chromatin by intrinsically disordered regions (IDRs). Studying SPACE and total proteome dynamics from mES cells grown in 2iL and serum medium indicates significant correlation (R = 0.62). One of the most dynamic caRBPs is Dazl, which we find co-localized with PRC2 at transcription start sites of genes that are distinct from Dazl mRNA binding. Dazl and other PRC2-colocalised caRBPs are rich in intrinsically disordered regions (IDRs), which could contribute to the formation and regulation of phase-separated PRC condensates. Together, our approach provides an unprecedented insight into IDR-mediated interactions and caRBPs with moonlighting functions in native chromatin. Competing Interest Statement The authors have declared no competing interest. Footnotes * SPACEmap was developed to identify chromatin contact sites of proteins SPACE sensitivity was assessed to be as few as 20,000 cells Dazl ChIP-SPACE was added Comparison with RICK, CARIC, Chromatin pelleting and Dm-ChP was added. Data analysis was revised. In summary, proteins quantified with at least one forward and 1 reverse SILAC experiments were considered for statistical analysis.

Aberrant expression of MYC family members predicts poor clinical outcome in many human cancers. Oncogenic MYC profoundly alters metabolism and mediates an antioxidant response to maintain redox balance. Here we show that MYC induces massive lipid peroxidation upon depletion of cysteine, the rate-limiting amino acid for glutathione biosynthesis and sensitizes cells to ferroptosis, an oxidative, non-apoptotic and iron-dependent type of cell death. In MYCN-amplified childhood neuroblastoma, MYCN mediates resistance to ferroptosis by activating transsulfuration of methionine to cysteine. MYCN may contribute to spontaneous tumor regression in low-risk neuroblastomas by promoting ferroptosis in cells with epigenetically silenced cystathionine-beta-synthase, the rate-limiting enzyme for transsulfuration. We identified enzymes and antiporter proteins crucial to ferroptotic escape, providing multiple previously unknown sites that may be acted on therapeutically. Competing Interest Statement The authors have declared no competing interest.