Conserved Epigenetic Regulatory Logic Infers Genes Governing Cell Identity

TGF-β modulates cell fate in human ES cell-derived foregut endoderm by inhibiting Wnt and BMP signaling

Genetic differences between pluripotent stem cell lines cause variable activity of extracellular signaling pathways, limiting reproducibility of directed differentiation protocols. Here we used human embryonic stem cells (hESCs) to interrogate how exogenous factors modulate endogenous signaling events during specification of foregut endoderm lineages. We find that transforming growth factor β1 (TGF-β1) activates a putative human OTX2/LHX1 gene regulatory network which promotes anterior fate by antagonizing endogenous Wnt signaling. In contrast to Porcupine inhibition, TGF-β1 effects cannot be reversed by exogenous Wnt ligands, suggesting that induction of SHISA proteins and intracellular accumulation of Fzd receptors render TGF-β1-treated cells refractory to Wnt signaling. Subsequently, TGF-β1-mediated inhibition of BMP and Wnt signaling suppresses liver fate and promotes pancreas fate. Furthermore, combined TGF-β1 treatment and Wnt inhibition during pancreatic specification reproducibly and robustly enhance INSULIN+ cell yield across hESC lines. This modification of widely used differentiation protocols will enhance pancreatic β cell yield for cell-based therapeutic applications.

Genome-Wide CRISPR Screen Identifies an NF2-Adherens Junction Mechanistic Dependency for Cardiac Lineage

BACKGROUND

Cardiomyocyte differentiation involves a stepwise clearance of repressors and fate-restricting regulators through the modulation of BMP (bone morphogenic protein)/Wnt-signaling pathways. However, the mechanisms and how regulatory roadblocks are removed with specific developmental signaling pathways remain unclear.

METHODS

We conducted a genome-wide CRISPR screen to uncover essential regulators of cardiomyocyte specification in human embryonic stem cells using a myosin heavy chain 6 (MYH6)-GFP (green fluorescence protein) reporter system. After an independent secondary single guide ribonucleic acid validation of 25 candidates, we identified NF2 (neurofibromin 2), a moesin-ezrin-radixin like (MERLIN) tumor suppressor, as an upstream driver of early cardiomyocyte lineage specification. Independent monoclonal NF2 knockouts were generated using CRISPR-Cas9, and cell states were inferred through bulk RNA sequencing and protein expression analysis across differentiation time points. Terminal lineage differentiation was assessed by using an in vitro 2-dimensional-micropatterned gastruloid model, trilineage differentiation, and cardiomyocyte differentiation. Protein interaction and post-translation modification of NF2 with its interacting partners were assessed using site-directed mutagenesis, coimmunoprecipitation, and proximity ligation assays.

RESULTS

Transcriptional regulation and trajectory inference from NF2-null cells reveal the loss of cardiomyocyte identity and the acquisition of nonmesodermal identity. Sustained elevation of early mesoderm lineage repressor SOX2 and upregulation of late anticardiac regulators CDX2 and MSX1 in NF2 knockout cells reflect a necessary role for NF2 in removing regulatory roadblocks. Furthermore, we found that NF2 and AMOT (angiomotin) cooperatively bind to YAP (yes-associated protein) during mesendoderm formation, thereby preventing YAP activation, independent of canonical MST (mammalian sterile 20-like serine-threonine protein kinase)-LATS (large tumor suppressor serine-threonine protein kinase) signaling. Mechanistically, cardiomyocyte lineage identity was rescued by wild-type and NF2 serine-518 phosphomutants, but not NF2 FERM (ezrin-radixin-meosin homology protein) domain blue-box mutants, demonstrating that the critical FERM domain-dependent formation of the AMOT-NF2-YAP scaffold complex at the adherens junction is required for early cardiomyocyte lineage differentiation.

CONCLUSIONS

These results provide mechanistic insight into the essential role of NF2 during early epithelial-mesenchymal transition by sequestering the repressive effect of YAP and relieving regulatory roadblocks en route to cardiomyocytes.

Wnt dose escalation during the exit from pluripotency identifies tranilast as a regulator of cardiac mesoderm

Wnt signaling is a critical determinant of cell lineage development. This study used Wnt dose-dependent induction programs to gain insights into molecular regulation of stem cell differentiation. We performed single-cell RNA sequencing of hiPSCs responding to a dose escalation protocol with Wnt agonist CHIR-99021 during the exit from pluripotency to identify cell types and genetic activity driven by Wnt stimulation. Results of activated gene sets and cell types were used to build a multiple regression model that predicts the efficiency of cardiomyocyte differentiation. Cross-referencing Wnt-associated gene expression profiles to the Connectivity Map database, we identified the small-molecule drug, tranilast. We found that tranilast synergistically activates Wnt signaling to promote cardiac lineage differentiation, which we validate by in vitro analysis of hiPSC differentiation and in vivo analysis of developing quail embryos. Our study provides an integrated workflow that links experimental datasets, prediction models, and small-molecule databases to identify drug-like compounds that control cell differentiation.

HOPX-associated molecular programs control cardiomyocyte cell states underpinning cardiac structure and function

Genomic regulation of cardiomyocyte differentiation is central to heart development and function. This study uses genetic loss-of-function human-induced pluripotent stem cell-derived cardiomyocytes to evaluate the genomic regulatory basis of the non-DNA-binding homeodomain protein HOPX. We show that HOPX interacts with and controls cardiac genes and enhancer networks associated with diverse aspects of heart development. Using perturbation studies in vitro, we define how upstream cell growth and proliferation control HOPX transcription to regulate cardiac gene programs. We then use cell, organoid, and zebrafish regeneration models to demonstrate that HOPX-regulated gene programs control cardiomyocyte function in development and disease. Collectively, this study mechanistically links cell signaling pathways as upstream regulators of HOPX transcription to control gene programs underpinning cardiomyocyte identity and function.

Systematic analysis of the transcriptional landscape of melanoma reveals drug-target expression plasticity

Metastatic melanoma originates from melanocytes of the skin. Melanoma metastasis results in poor treatment prognosis for patients and is associated with epigenetic and transcriptional changes that reflect the developmental program of melanocyte differentiation from neural crest stem cells. Several studies have explored melanoma transcriptional heterogeneity using microarray, bulk and single-cell RNA-sequencing technologies to derive data-driven models of the transcriptional-state change which occurs during melanoma progression. No study has systematically examined how different models of melanoma progression derived from different data types, technologies and biological conditions compare. Here, we perform a cross-sectional study to identify averaging effects of bulk-based studies that mask and distort apparent melanoma transcriptional heterogeneity; we describe new transcriptionally distinct melanoma cell states, identify differential co-expression of genes between studies and examine the effects of predicted drug susceptibilities of different cell states between studies. Importantly, we observe considerable variability in drug-target gene expression between studies, indicating potential transcriptional plasticity of melanoma to down-regulate these drug targets and thereby circumvent treatment. Overall, observed differences in gene co-expression and predicted drug susceptibility between studies suggest bulk-based transcriptional measurements do not reliably gauge heterogeneity and that melanoma transcriptional plasticity is greater than described when studies are considered in isolation.

Evaluation of deep learning-based feature selection for single-cell RNA sequencing data analysis

BACKGROUND

Feature selection is an essential task in single-cell RNA-seq (scRNA-seq) data analysis and can be critical for gene dimension reduction and downstream analyses, such as gene marker identification and cell type classification. Most popular methods for feature selection from scRNA-seq data are based on the concept of differential distribution wherein a statistical model is used to detect changes in gene expression among cell types. Recent development of deep learning-based feature selection methods provides an alternative approach compared to traditional differential distribution-based methods in that the importance of a gene is determined by neural networks.

RESULTS

In this work, we explore the utility of various deep learning-based feature selection methods for scRNA-seq data analysis. We sample from Tabula Muris and Tabula Sapiens atlases to create scRNA-seq datasets with a range of data properties and evaluate the performance of traditional and deep learning-based feature selection methods for cell type classification, feature selection reproducibility and diversity, and computational time.

CONCLUSIONS

Our study provides a reference for future development and application of deep learning-based feature selection methods for single-cell omics data analyses.

Tbx5 maintains atrial identity in post-natal cardiomyocytes by regulating an atrial-specific enhancer network

Understanding how the atrial and ventricular heart chambers maintain distinct identities is a prerequisite for treating chamber-specific diseases. Here, we selectively knocked out (KO) the transcription factor Tbx5 in the atrial working myocardium to evaluate its requirement for atrial identity. Atrial Tbx5 inactivation downregulated atrial cardiomyocyte (aCM) selective gene expression. Using concurrent single nucleus transcriptome and open chromatin profiling, genomic accessibility differences were identified between control and Tbx5 KO aCMs, revealing that 69% of the control-enriched ATAC regions were bound by TBX5. Genes associated with these regions were downregulated in KO aCMs, suggesting they function as TBX5-dependent enhancers. Comparing enhancer chromatin looping using H3K27ac HiChIP identified 510 chromatin loops sensitive to TBX5 dosage, and 74.8% of control-enriched loops contained anchors in control-enriched ATAC regions. Together, these data demonstrate TBX5 maintains the atrial gene expression program by binding to and preserving the tissue-specific chromatin architecture of atrial enhancers.

Low RNA stability signifies increased post-transcriptional regulation of cell identity genes

Cell identity genes are distinct from other genes with respect to the epigenetic mechanisms to activate their transcription, e.g. by super-enhancers and broad H3K4me3 domains. However, it remains unclear whether their post-transcriptional regulation is also unique. We performed a systematic analysis of transcriptome-wide RNA stability in nine cell types and found that unstable transcripts were enriched in cell identity-related pathways while stable transcripts were enriched in housekeeping pathways. Joint analyses of RNA stability and chromatin state revealed significant enrichment of super-enhancers and broad H3K4me3 domains at the gene loci of unstable transcripts. Intriguingly, the RNA m6A methyltransferase, METTL3, preferentially binds to chromatin at super-enhancers, broad H3K4me3 domains and their associated genes. METTL3 binding intensity is positively correlated with RNA m6A methylation and negatively correlated with RNA stability of cell identity genes, probably due to co-transcriptional m6A modifications promoting RNA decay. Nanopore direct RNA-sequencing showed that METTL3 knockdown has a stronger effect on RNA m6A and mRNA stability for cell identity genes. Our data suggest a run-and-brake model, where cell identity genes undergo both frequent transcription and fast RNA decay to achieve precise regulation of RNA expression.

Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity

Methods for cell clustering and gene expression from single-cell RNA sequencing (scRNA-seq) data are essential for biological interpretation of cell processes. Here, we present TRIAGE-Cluster which uses genome-wide epigenetic data from diverse bio-samples to identify genes demarcating cell diversity in scRNA-seq data. By integrating patterns of repressive chromatin deposited across diverse cell types with weighted density estimation, TRIAGE-Cluster determines cell type clusters in a 2D UMAP space. We then present TRIAGE-ParseR, a machine learning method which evaluates gene expression rank lists to define gene groups governing the identity and function of cell types. We demonstrate the utility of this two-step approach using atlases of in vivo and in vitro cell diversification and organogenesis. We also provide a web accessible dashboard for analysis and download of data and software. Collectively, genome-wide epigenetic repression provides a versatile strategy to define cell diversity and study gene regulation of scRNA-seq data.

A transposable element into the human long noncoding RNA CARMEN is a switch for cardiac precursor cell specification

AIMS

The major cardiac cell types composing the adult heart arise from common multipotent precursor cells. Cardiac lineage decisions are guided by extrinsic and cell-autonomous factors, including recently discovered long noncoding RNAs (lncRNAs). The human lncRNA CARMEN, which is known to dictate specification toward the cardiomyocyte (CM) and the smooth muscle cell (SMC) fates, generates a diversity of alternatively spliced isoforms.

METHODS AND RESULTS

The CARMEN locus can be manipulated to direct human primary cardiac precursor cells (CPCs) into specific cardiovascular fates. Investigating CARMEN isoform usage in differentiating CPCs represents therefore a unique opportunity to uncover isoform-specific functions in lncRNAs. Here, we identify one CARMEN isoform, CARMEN-201, to be crucial for SMC commitment. CARMEN-201 activity is encoded within an alternatively spliced exon containing a MIRc short interspersed nuclear element. This element binds the transcriptional repressor REST (RE1 Silencing Transcription Factor), targets it to cardiogenic loci, including ISL1, IRX1, IRX5, and SFRP1, and thereby blocks the CM gene program. In turn, genes regulating SMC differentiation are induced.

CONCLUSIONS

These data show how a critical physiological switch is wired by alternative splicing and functional transposable elements in a long noncoding RNA. They further demonstrated the crucial importance of the lncRNA isoform CARMEN-201 in SMC specification during heart development.

Improved Genome Editing in the Ascidian Ciona with CRISPR/Cas9 and TALEN

The ascidian Ciona intestinalis type A (or Ciona robusta) is an important organism for elucidating the mechanisms that make the chordate body plan. CRISPR/Cas9 and TAL effector nuclease (TALEN) are widely used to quickly address genetic functions in Ciona. Our previously reported method of CRISPR/Cas9-mediated mutagenesis in this animal has inferior mutation rates compared to those of TALENs. We here describe an updated way to effectively mutate genes with CRISPR/Cas9 in Ciona. Although the construction of TALENs is much more laborious than that of CRISPR/Cas9, this technique is useful for tissue-specific knockouts that are not easy even by the optimized CRISPR/Cas9 method.

Repressive epigenetic mechanisms, such as the H3K27me3 histone modification, were predicted to affect muscle gene expression and its mineral content in Nelore cattle

Epigenetic repression has been linked to the regulation of different cell states. In this study, we focus on the influence of this repression, mainly by H3K27me3, over gene expression in muscle cells, which may affect mineral content, a phenotype that is relevant to muscle function and beef quality. Based on the inverse relationship between H3K27me3 and gene expression (i.e., epigenetic repression) and on contrasting sample groups, we computationally predicted regulatory genes that affect muscle mineral content. To this end, we applied the TRIAGE predictive method followed by a rank product analysis. This methodology can predict regulatory genes that might be affected by repressive epigenetic regulation related to mineral concentration. Annotation of orthologous genes, between human and bovine, enabled our investigation of gene expression in the Longissimus thoracis muscle of Bos indicus cattle. The animals under study had a contrasting mineral content in their muscle cells. We identified candidate regulatory genes influenced by repressive epigenetic mechanisms, linking histone modification to mineral content in beef samples. The discovered candidate genes take part in multiple biological pathways, i.e., impulse transmission, cell signalling, immunological, and developmental pathways. Some of these genes were previously associated with mineral content or regulatory mechanisms. Our findings indicate that epigenetic repression can partially explain the gene expression profiles observed in muscle samples with contrasting mineral content through the candidate regulators here identified.

Breast cancer plasticity is restricted by a LATS1-NCOR1 repressive axis

Breast cancer, the most frequent cancer in women, is generally classified into several distinct histological and molecular subtypes. However, single-cell technologies have revealed remarkable cellular and functional heterogeneity across subtypes and even within individual breast tumors. Much of this heterogeneity is attributable to dynamic alterations in the epigenetic landscape of the cancer cells, which promote phenotypic plasticity. Such plasticity, including transition from luminal to basal-like cell identity, can promote disease aggressiveness. We now report that the tumor suppressor LATS1, whose expression is often downregulated in human breast cancer, helps maintain luminal breast cancer cell identity by reducing the chromatin accessibility of genes that are characteristic of a "basal-like" state, preventing their spurious activation. This is achieved via interaction of LATS1 with the NCOR1 nuclear corepressor and recruitment of HDAC1, driving histone H3K27 deacetylation near NCOR1-repressed "basal-like" genes. Consequently, decreased expression of LATS1 elevates the expression of such genes and facilitates slippage towards a more basal-like phenotypic identity. We propose that by enforcing rigorous silencing of repressed genes, the LATS1-NCOR1 axis maintains luminal cell identity and restricts breast cancer progression.

Organization of gene programs revealed by unsupervised analysis of diverse gene-trait associations

Genome wide association studies provide statistical measures of gene–trait associations that reveal how genetic variation influences phenotypes. This study develops an unsupervised dimensionality reduction method called UnTANGLeD (Unsupervised Trait Analysis of Networks from Gene Level Data) which organizes 16,849 genes into discrete gene programs by measuring the statistical association between genetic variants and 1,393 diverse complex traits. UnTANGLeD reveals 173 gene clusters enriched for protein–protein interactions and highly distinct biological processes governing development, signalling, disease, and homeostasis. We identify diverse gene networks with robust interactions but not associated with known biological processes. Analysis of independent disease traits shows that UnTANGLeD gene clusters are conserved across all complex traits, providing a simple and powerful framework to predict novel gene candidates and programs influencing orthogonal disease phenotypes. Collectively, this study demonstrates that gene programs co-ordinately orchestrating cell functions can be identified without reliance on prior knowledge, providing a method for use in functional annotation, hypothesis generation, machine learning and prediction algorithms, and the interpretation of diverse genomic data.

Temporal perturbation of histone deacetylase activity reveals a requirement for HDAC1-3 in mesendoderm cell differentiation

Histone deacetylases (HDACs) are a class of enzymes that control chromatin state and influence cell fate. We evaluated the chromatin accessibility and transcriptome dynamics of zinc-containing HDACs during cell differentiation in vitro coupled with chemical perturbation to identify the role of HDACs in mesendoderm cell fate specification. Single-cell RNA sequencing analyses of HDAC expression during human pluripotent stem cell (hPSC) differentiation in vitro and mouse gastrulation in vivo reveal a unique association of HDAC1 and -3 with mesendoderm gene programs during exit from pluripotency. Functional perturbation with small molecules reveals that inhibition of HDAC1 and -3, but not HDAC2, induces mesoderm while impeding endoderm and early cardiac progenitor specification. These data identify unique biological functions of the structurally homologous enzymes HDAC1-3 in influencing hPSC differentiation from pluripotency toward mesendodermal and cardiac progenitor populations.

Single-cell transcriptomics provides insights into hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a genetic heart disease that is characterized by unexplained segmental hypertrophy that is usually most pronounced in the septum. While sarcomeric gene mutations are often the genetic basis for HCM, the mechanistic origin for the heterogeneous remodeling remains largely unknown. A better understanding of the gene networks driving the cardiomyocyte (CM) hypertrophy is required to improve therapeutic strategies. Patients suffering from HCM often receive a septal myectomy surgery to relieve outflow tract obstruction due to hypertrophy. Using single-cell RNA sequencing (scRNA-seq) on septal myectomy samples from patients with HCM, we identify functional links between genes, transcription factors, and cell size relevant for HCM. The data show the utility of using scRNA-seq on the human hypertrophic heart, highlight CM heterogeneity, and provide a wealth of insights into molecular events involved in HCM that can eventually contribute to the development of enhanced therapies.

Characterizing cellular heterogeneity in chromatin state with scCUT&Tag-pro

Technologies that profile chromatin modifications at single-cell resolution offer enormous promise for functional genomic characterization, but the sparsity of the measurements and integrating multiple binding maps represent substantial challenges. Here we introduce scCUT&Tag-pro, a multimodal assay for profiling protein-DNA interactions coupled with the abundance of surface proteins in single cells. In addition, we introduce scChromHMM, which integrates data from multiple experiments to infer and annotate chromatin states based on combinatorial histone modification patterns. We apply these tools to perform an integrated analysis across nine different molecular modalities in circulating human immune cells. We demonstrate how these two approaches can characterize dynamic changes in the function of individual genomic elements across both discrete cell states and continuous developmental trajectories, nominate associated motifs and regulators that establish chromatin states, and identify extensive and cell type-specific regulatory priming. Finally, we demonstrate how our integrated reference can serve as a scaffold to map and improve the interpretation of additional scCUT&Tag datasets.

Systematic reconstruction of cellular trajectories across mouse embryogenesis

Mammalian embryogenesis is characterized by rapid cellular proliferation and diversification. Within a few weeks, a single-cell zygote gives rise to millions of cells expressing a panoply of molecular programs. Although intensively studied, a comprehensive delineation of the major cellular trajectories that comprise mammalian development in vivo remains elusive. Here, we set out to integrate several single-cell RNA-sequencing (scRNA-seq) datasets that collectively span mouse gastrulation and organogenesis, supplemented with new profiling of ~150,000 nuclei from approximately embryonic day 8.5 (E8.5) embryos staged in one-somite increments. Overall, we define cell states at each of 19 successive stages spanning E3.5 to E13.5 and heuristically connect them to their pseudoancestors and pseudodescendants. Although constructed through automated procedures, the resulting directed acyclic graph (TOME (trajectories of mammalian embryogenesis)) is largely consistent with our contemporary understanding of mammalian development. We leverage TOME to systematically nominate transcription factors (TFs) as candidate regulators of each cell type's specification, as well as 'cell-type homologs' across vertebrate evolution.

Variational autoencoding of gene landscapes during mouse CNS development uncovers layered roles of Polycomb Repressor Complex 2

A prominent aspect of most, if not all, central nervous systems (CNSs) is that anterior regions (brain) are larger than posterior ones (spinal cord). Studies in Drosophila and mouse have revealed that Polycomb Repressor Complex 2 (PRC2), a protein complex responsible for applying key repressive histone modifications, acts by several mechanisms to promote anterior CNS expansion. However, it is unclear what the full spectrum of PRC2 action is during embryonic CNS development and how PRC2 intersects with the epigenetic landscape. We removed PRC2 function from the developing mouse CNS, by mutating the key gene Eed, and generated spatio-temporal transcriptomic data. To decode the role of PRC2, we developed a method that incorporates standard statistical analyses with probabilistic deep learning to integrate the transcriptomic response to PRC2 inactivation with epigenetic data. This multi-variate analysis corroborates the central involvement of PRC2 in anterior CNS expansion, and also identifies several unanticipated cohorts of genes, such as proliferation and immune response genes. Furthermore, the analysis reveals specific profiles of regulation via PRC2 upon these gene cohorts. These findings uncover a differential logic for the role of PRC2 upon functionally distinct gene cohorts that drive CNS anterior expansion. To support the analysis of emerging multi-modal datasets, we provide a novel bioinformatics package that integrates transcriptomic and epigenetic datasets to identify regulatory underpinnings of heterogeneous biological processes.

Integrating single-cell genomics pipelines to discover mechanisms of stem cell differentiation

Pluripotent stem cells underpin a growing sector that leverages their differentiation potential for research, industry, and clinical applications. This review evaluates the landscape of methods in single-cell transcriptomics that are enabling accelerated discovery in stem cell science. We focus on strategies for scaling stem cell differentiation through multiplexed single-cell analyses, for evaluating molecular regulation of cell differentiation using new analysis algorithms, and methods for integration and projection analysis to classify and benchmark stem cell derivatives against in vivo cell types. By discussing the available methods, comparing their strengths, and illustrating strategies for developing integrated analysis pipelines, we provide user considerations to inform their implementation and interpretation.

Comprehensive cell type decomposition of circulating cell-free DNA with CelFiE

Circulating cell-free DNA (cfDNA) in the bloodstream originates from dying cells and is a promising noninvasive biomarker for cell death. Here, we propose an algorithm, CelFiE, to accurately estimate the relative abundances of cell types and tissues contributing to cfDNA from epigenetic cfDNA sequencing. In contrast to previous work, CelFiE accommodates low coverage data, does not require CpG site curation, and estimates contributions from multiple unknown cell types that are not available in external reference data. In simulations, CelFiE accurately estimates known and unknown cell type proportions from low coverage and noisy cfDNA mixtures, including from cell types composing less than 1% of the total mixture. When used in two clinically-relevant situations, CelFiE correctly estimates a large placenta component in pregnant women, and an elevated skeletal muscle component in amyotrophic lateral sclerosis (ALS) patients, consistent with the occurrence of muscle wasting typical in these patients. Together, these results show how CelFiE could be a useful tool for biomarker discovery and monitoring the progression of degenerative disease.

Tissue damage and turnover lead to the release of DNA in the blood and can be used to monitor changes in tissue state. Here, the authors developed a tool to accurately estimate the proportion of cell types contributing to cell-free DNA in the blood, with an application to pregnant women and ALS patients.

Elp2 mutations perturb the epitranscriptome and lead to a complex neurodevelopmental phenotype

Intellectual disability (ID) and autism spectrum disorder (ASD) are the most common neurodevelopmental disorders and are characterized by substantial impairment in intellectual and adaptive functioning, with their genetic and molecular basis remaining largely unknown. Here, we identify biallelic variants in the gene encoding one of the Elongator complex subunits, ELP2, in patients with ID and ASD. Modelling the variants in mice recapitulates the patient features, with brain imaging and tractography analysis revealing microcephaly, loss of white matter tract integrity and an aberrant functional connectome. We show that the Elp2 mutations negatively impact the activity of the complex and its function in translation via tRNA modification. Further, we elucidate that the mutations perturb protein homeostasis leading to impaired neurogenesis, myelin loss and neurodegeneration. Collectively, our data demonstrate an unexpected role for tRNA modification in the pathogenesis of monogenic ID and ASD and define Elp2 as a key regulator of brain development.