Biology subjects

Replogle, J. M.

Publications and source records attributed to Replogle, J. M..

13 recordsLinked to original sources

bioRxiv2026

Global cell-state and gene-program representations reveal conserved and context-specific perturbation responses of cells

Understanding how cell states change in response to genetic perturbations is critical for gene-function and therapeutics discovery. However, state-of-the-art deep-learning models trained on large single-cell omics datasets still struggle to accurately predict cellular responses to perturbations, highlighting the need for a better understanding of the cell-state space and how cells move through this space. Here, we present a contrastive learning model that integrates diverse scRNA-seq datasets into a global, interpretable cell-state manifold. We further develop a framework to integrate this global cell-state manifold with genome-scale perturbation data to identify gene-expression programs that define principal axes of cell-state transitions and functional embeddings of genes that define major perturbation classes. Applying this framework across Perturb-seq datasets on different cell types reveals conserved cellular responses to perturbations, as well as cell-type-specific rewiring of stress responses. Moreover, we perform a genome-scale Perturb-seq screen in human embryonic stem cells, validating and extending these findings and uncovering a class of mesenchymal transitions induced by diverse perturbations to cellular stress-response pathways.

systems biology↗

bioRxiv2026

Neurodegeneration risk variants promote lysosomal TMEM106B fibrilaccumulation

Variants in TMEM106B and GRN, which encode lysosomal proteins, interact through unknown mechanisms to increase the risk of age-related cognitive decline and neurodegeneration. Here, we show that these variants converge on a single molecular intermediate: the cleaved intra-lysosomal fibril core of TMEM106B, a precursor to amyloid fibrils that accumulate in the aging brain. A protein-coding TMEM106B risk variant (p.T185) drives fibril core accumulation by impairing its degradation and GRN risk variants amplify this effect. Mice over-expressing the fibril core develop hallmarks of neurodegeneration, and cryo-electron tomography reveals intra-lysosomal fibrils in cultured neurons, mice, and diseased human brain. In GRN-mutation carriers, in whom fibril burden is greatest, fibrils extrude through ruptured lysosomal membranes. These findings identify intra-lysosomal TMEM106B fibrillization as a convergent neurodegeneration mechanism and potential therapeutic target.

cell biology↗

bioRxiv2024

Transcriptome-wide characterization of genetic perturbations

Single cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are often noisy due to cost and technical constraints, limiting power to detect true effects with conventional differential expression analyses. Here, we introduce TRanscriptome-wide Analysis of Differential Expression (TRADE), a statistical framework which estimates the transcriptome-wide distribution of true differential expression effects from noisy gene-level measurements. Within TRADE, we derive multiple novel, interpretable statistical metrics, including the "transcriptome-wide impact", an estimator of the overall transcriptional effect of a perturbation which is stable across sampling depths. We analyze new and published large-scale Perturb-seq datasets to show that many true transcriptional effects are not statistically significant, but detectable in aggregate with TRADE. In a genome-scale Perturb-seq screen, we find that a typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene perturbation affects over 500 genes. An advantage of our approach is its ability to compare the transcriptomic effects of genetic perturbations across contexts and dosages despite differences in power. We use this ability to identify perturbations with cell-type dependent effects and to find examples of perturbations where transcriptional responses are not only larger in magnitude, but also qualitatively different, as a function of dosage. Lastly, we expand our analysis to case/control comparison of gene expression for neuropsychiatric conditions, finding that transcriptomic effect correlations are greater than genetic correlations for these diagnoses. TRADE lays an analytic foundation for the systematic comparison of genetic perturbation atlases, as well as differential expression experiments more broadly.

genomics↗

bioRxiv2022

MTCH2 is a mitochondrial outer membrane protein insertase

In the mitochondrial outer membrane, tail-anchored (TA) proteins play critical roles in cytoplasmic-mitochondrial communication. Using genome-wide CRISPRi screens, we identify factors involved in mitochondrial TA biogenesis in human cells. We show that MTCH2, and its paralog MTCH1, are required for insertion of biophysically diverse mitochondrial TAs, but not outer membrane {beta}-barrel proteins. In a reconstituted system, purified MTCH2 is sufficient to mediate insertion into proteoliposomes. Functional and mutational studies reveal that MTCH2 uses membrane-embedded hydrophilic residues to function as a gatekeeper for outer membrane protein biogenesis, controlling mislocalization of TAs into the endoplasmic reticulum and the sensitivity of leukemia cells to apoptosis. Our identification of MTCH2 as an insertase provides a mechanistic explanation for the diverse phenotypes and disease states associated with MTCH2 dysfunction. One-Sentence SummaryMTCH2 is both necessary and sufficient for insertion of diverse -helical proteins into the mitochondrial outer membrane, and is the defining member of a family of insertases that have co-opted the SLC25 transporter fold.

cell biology↗

bioRxiv2022

Nucleotide depletion promotes cell fate transitions by inducing DNA replication stress

Control of cellular identity requires coordination of developmental programs with environmental factors such as nutrient availability, suggesting that modulating aspects of metabolism could alter cell state along differentiation trajectories. Here we find that nucleotide depletion and DNA replication stress are common drivers of cell state progression across a variety of normal and transformed hematopoietic systems. DNA replication stress-induced cell state transitions begin during S phase and are independent of ATR/ATM checkpoint signaling, double-stranded DNA break formation, and changes in cell cycle length. In systems where differentiation is blocked by oncogenic transcription factor expression, replication stress leads to increased activity at primed regulatory loci and expression of lineage-appropriate maturation genes while progenitor TF activity is still present. Altering the baseline cell state by manipulating the cohort of transcription factors expressed redirects the effect of replication stress towards induction of a different set of lineage-specific genes. The ability of replication stress to selectively activate primed maturation programs across different cellular contexts suggests a general mechanism by which metabolism can promote lineage-appropriate and potentially therapeutically relevant cell state transitions.

cancer biology↗

bioRxiv2022

Systematic functional interrogation of SARS-CoV-2 host factors using Perturb-seq

Genomic and proteomic screens have identified numerous host factors of SARS-CoV-2, but efficient delineation of their molecular roles during infection remains a challenge. Here we use Perturb-seq, combining genetic perturbations with a single-cell readout, to investigate how inactivation of host factors changes the course of SARS-CoV-2 infection and the host response in human lung epithelial cells. Our high-dimensional data resolve complex phenotypes such as shifts in the stages of infection and modulations of the interferon response. However, only a small percentage of host factors showed such phenotypes upon perturbation. We further identified the NF-{kappa}B inhibitor I{kappa}B (NFKBIA), as well as the translation factors EIF4E2 and EIF4H as strong host dependency factors acting early in infection. Overall, our study provides massively parallel functional characterization of host factors of SARS-CoV-2 and quantitatively defines their roles both in virus-infected and bystander cells.

systems biology↗

bioRxiv2022

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

CRISPR interference (CRISPRi) enables programmable, reversible, and titratable repression of gene expression (knockdown) in mammalian cells. Initial CRISPRi-mediated genetic screens have showcased the potential to address basic questions in cell biology, genetics, and biotechnology, but wider deployment of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and challenges in generating cell models with consistent CRISPRi-mediated knockdown. Here, we present next-generation CRISPRi sgRNA libraries and effector expression constructs that enable strong and consistent knockdown across mammalian cell models. First, we combine empirical sgRNA selection with a dual-sgRNA library design to generate an ultra-compact (1-3 elements per gene), highly active CRISPRi sgRNA library. Next, we rigorously compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides the best balance between strong on-target knockdown and minimal nonspecific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines with stable expression of Zim3-dCas9 and robust on-target knockdown. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

genomics↗

bioRxiv2022

Microfluidics-free single-cell genomics with templated emulsification

Single-cell RNA sequencing is now a standard method used to reveal the molecular details of cellular heterogeneity, but current approaches have limitations on speed, scale, and ease of use that stem from the complex microfluidic devices or fluid handling steps required for sample processing. We, therefore, developed a method that does not require specialized microfluidic devices, expertise, or hardware. Our approach is based on particle-templated emulsification, which allows single-cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. PIP-seq accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse-human mixing studies, is compatible with multi-omics measurements, and can accurately characterize cell types in human breast tissue when compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq revealed the emergence of heterogeneity within chemotherapy-resistant cell subsets that were hidden by standard immunophenotyping. PIP-seq is a simple, flexible, and scalable next-generation workflow that extends single-cell sequencing to new applications, including screening, diagnostics, and disease monitoring.

genomics↗

bioRxiv2021

Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq

A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (pooled CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells and present a framework to power biological discovery with the resulting genotype-phenotype map. We use transcriptional phenotypes to predict the function of poorly-characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena - from RNA processing to differentiation. We leverage this ability to systematically identify the genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene function and cellular behavior.

genomics↗

bioRxiv2021

Lineage Recording Reveals the Phylodynamics, Plasticity and Paths of Tumor Evolution

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth, expansion to neighboring and distal tissues, and therapeutic resistance. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma which enabled us to track tumor evolution from single transformed cells to metastatic tumors at unprecedented resolution. We found that loss of the initial, stable alveolar-type2-like state was accompanied by transient increase in plasticity. This was followed by adoption of distinct fitness-associated transcriptional programs which enable rapid expansion and ultimately clonal sweep of rare, stable subclones capable of metastasizing to distant sites. Finally, we showed that tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates tumor progression by creating novel evolutionary paths. Overall, our study elucidates the hierarchical nature of tumor evolution, and more broadly enables the in-depth study of tumor progression.

cancer biology↗

bioRxiv2019

GIGYF2 and 4EHP Inhibit Translation Initiation of Defective Messenger RNAs to Assist Ribosome-Associated Quality Control

Ribosome-associated Quality Control (RQC) pathways protect cells from toxicity caused by incomplete protein products resulting from translation of damaged or problematic mRNAs. Extensive work in yeast has identified highly conserved mechanisms that lead to the degradation of the faulty mRNA and partially synthesized polypeptide. Here, we used CRISPR-Cas9-based screening to search for additional RQC strategies in mammals. We found that failed translation leads to specific silencing of translation initiation on that message. This negative feedback loop is mediated by two translation inhibitors, GIGYF2 and 4EHP. Their recruitment to defective messages can be mediated by different factors, including potentially the collision sensor ZNF598. Both model substrates and growth-based assays established that inhibition of additional rounds of translation acts in concert with known RQC pathways to prevent buildup of toxic proteins. Inability to block translation of faulty mRNAs, and subsequent accumulation of partially synthesized polypeptides, could explain the neurodevelopmental and neuropsychiatric disorders observed in mice and humans with compromised GIGYF2 function.

genetics↗

bioRxiv2019

Exploring genetic interaction manifolds constructed from rich phenotypes

Synergistic interactions between gene functions drive cellular complexity. However, the combinatorial explosion of possible genetic interactions (GIs) has necessitated the use of scalar interaction readouts (e.g. growth) that conflate diverse outcomes. Here we present an analytical framework for interpreting manifolds constructed from high-dimensional interaction phenotypes. We applied this framework to rich phenotypes obtained by Perturb-seq (single-cell RNA-seq pooled CRISPR screens) profiling of strong GIs mined from a growth-based, gain-of-function GI map. Exploration of this manifold enabled ordering of regulatory pathways, principled classification of GIs (e.g. identifying true suppressors), and mechanistic elucidation of synthetic lethal interactions, including an unexpected synergy between CBL and CNN1 driving erythroid differentiation. Finally, we apply recommender system machine learning to predict interactions, facilitating exploration of vastly larger GI manifolds.\n\nOne Sentence SummaryPrinciples and mechanisms of genetic interactions are revealed by rich phenotyping using single-cell RNA sequencing.

genomics↗

bioRxiv2018

Direct capture of CRISPR guides enables scalable, multiplexed, and multi-omic Perturb-seq

Pairing CRISPR-based genetic screens with single-cell transcriptional phenotypes (Perturb-seq) has advanced efforts to explore the function of mammalian genes and genetic networks. We present strategies for Perturb-seq that enable direct capture of CRISPR sgRNAs within 3 or 5 single-cell RNA-sequencing libraries using the 10x Genomics platform. This technology greatly expands the accessibility, scalability, and flexibility of Perturb-seq, specifically enabling use with programmed combinatorial perturbations and multiplexing with multi-omic measurements.

genomics↗