Biology subjects

Yang, X.

Publications and source records attributed to Yang, X..

At least 595 records · Page 33Linked to original sources

bioRxiv2022

Co-infection of Ehrlichia with B. burgdorferi drives emergency myelopoiesis and promotes Lyme arthritis

Lyme disease is caused by the extracellular pathogen Borrelia burgdorferi (Bb), transmitted by the Ixodes scapularis tick. Approximately one-third of infected individuals develop arthritis of weight-bearing joints, though it is unclear why some patients develop arthritis and severe systemic disease while others do not. C57BL/6 (B6) mice are susceptible to Bb infection but do not develop arthritis, providing an in vivo model to evaluate mechanisms regulating development of Lyme arthritis. We demonstrate here that co-infection of B6 mice with the tick-borne pathogens Bb and Ehrlichia muris (Em) induced significant arthritis. Although co-infection did not impact bacterial burden or growth of either pathogen, the resultant Lyme arthritis in co-infected mice correlated with significant hematologic disturbances. Whereas single Bb infection elicited no overt hematologic changes, Em infection resulted in thrombocytopenia, lymphopenia, monocytosis, and granulocytosis, which was consistently observed in mice co-infected with both Bb and Em. Hematologic changes correlated with profound changes to the hematopoietic stem and progenitor cell (HSPC) populations in Em-infected mice. Most notable were dramatic reductions in populations of HSPCs committed to myeloid-biased differentiation. Co-infection resulted in persistent hematologic changes and bone marrow inflammation. Our data demonstrate for the first time that B6 mice, resistant to developing Lyme arthritis, exhibit severe joint pathology in the presence of a second pathogen, correlating with persistent emergency myelopoiesis. Our data support the conclusion that pathogen burden is not sufficient for disease and specific inflammatory signals and cells regulate the development of Lyme arthritis. ImportanceTick-borne illnesses, historically relegated to specific geographic areas, are increasing in prevalence and distribution. Borrelia burgdorferi causes Lyme disease, the most common tick-borne illness in North America, characterized by debilitating arthritis, carditis, and neurologic complications. It remains unclear why certain infected individuals develop severe disease while others are only mildly symptomatic. Human monocytic ehrlichiosis (HME) is another tick-borne disease that often results in profound illness and severe hematological disturbances. We show here that co-infection of B6 mice, resistant to Lyme arthritis, with Borrelia burgdorferi and Ehrlichia muris, used to model HME, results in the development of severe arthritis and emergency myelopoiesis. Our work suggests that immune activation driven by co-infection contributes to the development of Lyme arthritis.

immunology↗

bioRxiv2022

Engineering of NEMO as calcium indicators with ultra-high dynamics and sensitivity

Genetically-encoded calcium indicators (GECI) are indispensable tools for real-time monitoring of intracellular calcium signals and cellular activities in living organisms. Current GECIs face the challenge of sub-optimal peak signal-to-baseline-ratio (SBR) with limited resolution for reporting subtle calcium transients. We report herein the development of a suite of calcium sensors, designated NEMO, with fast kinetics and wide dynamic ranges (>100-fold). NEMO indicators report Ca2+ transients with peak SBRs ~20-fold larger than the top-of-the-range GCaMP series. NEMO sensors further enable the quantification of absolution calcium concentration with ratiometric or photochromic imaging. Compared to GCaMPs, NEMOs could detect single action potentials in neurons with a peak SBR two times higher and a median peak SBR four times larger in vivo, thereby outperforming most existing state-of-the-art GECIs. Given their high sensitivity and resolution to report intracellular Ca2+ signals, NEMO sensors may find broad applications in monitoring neuronal activities and other Ca2+-modulated physiological processes in both mammals and plants.

synthetic biology↗

bioRxiv2022

Age-dependent changes in the dynamic functional organization of the brain at rest - a cross - cultural replication approach

Age-associated changes in brain function play an important role in the development of neurodegenerative diseases. Although previous work has examined age-related changes in static functional connectivity (FC), accumulating evidence suggests that advancing age is especially associated with alterations in the dynamic interactions and transitions between different brain states, which hitherto has received less attention. Moreover, conclusions of previous studies in this domain are limited by suboptimal replicability of resting state fMRI and culturally homogenous cohorts. Here, we investigate the robustness of age-associated changes in dynamic functional connectivity (dFC) by capitalizing on the availability of fMRI cohorts from two cultures (Western European and Chinese). In both cohorts we consistently identify two distinct connectivity states: a more frequent segregated within-network connectivity state (state I) and a less frequent integrated between-network connectivity state (state II). In both cohorts, older (55-80 years) compared to younger participants (20-35 years) exhibited lower occurrence of and spent less time in state I. Moreover, older participants tended to exhibit more transitions between networks and greater variance in global efficiency. Overall, our cross-cultural replication of age-associated changes in key dFC metrics implies that advancing age is robustly associated with a reorganization of dynamic brain activation that favors the use of less functionally-specific networks. HighlightsAging is associated with a reorganization of dynamic functional brain connectivity. Age-dependent dynamic functional connectivity changes are relatively stable across cultures. Dynamic properties are promising neural indexes for brain aging in older healthy populations.

neuroscience↗

bioRxiv2022

BCAA catabolism drives adipogenesis via an intermediate metabolite and promotes subcutaneous adipose tissue expansion during obesity

Branched-chain amino acids (BCAAs, including leucine, isoleucine, and valine) have emerged as major players in metabolic health and diseases, but the underlying mechanisms remain obscure. Here, we report that BCAA catabolism drives adipogenesis via an intermediate metabolite of leucine and promotes subcutaneous white adipose tissue (sWAT) expansion during obesity. Genetic analyses of humans and mice reveal that the BCAA catabolic pathway in WAT is strongly correlated with adipose physiology and obesity traits. Altering BCAA catabolism in mature adipocytes exerts minor effects on adiposity in mice. However, enhancing adipose BCAA catabolism via FABP4-Cre-mediated Bckdk deletion promotes diet-induced obesity while blocking adipose BCAA catabolism through Bckdha ablation does the opposite. Intriguingly, the catabolism of BCAAs elicits fat depot-specific responses and promotes sWAT extension and adipogenesis in a cell-autonomous manner. Mechanistically, BCAA catabolism drives adipocyte differentiation via an intermediate metabolite of leucine, which activates mTORC1 and polyamine synthesis from methionine to promote the expression of adipogenic master regulators. Together, these results demonstrate that BCAA catabolism promotes adipogenesis and sWAT expansion during obesity. The crosstalk between leucine and methionine metabolism driven by the catabolic intermediate highlights an unexpected regulatory role of amino acids in metabolic health and diseases.

physiology↗

bioRxiv2022

SIC50: Determination of IC50 by an optimized Sobel operator and a vision transformer

As a measure of cytotoxic potency, half-maximal inhibitory concentration (IC50) is the concentration at which a drug exerts half of its maximal inhibitory effect against target cells. It can be determined by various methods that require applying additional reagents or lysing the cells. Here, we describe a label-free Sobel-edge-based method, which we name SIC50, for the evaluation of IC50. SIC50 classifies pre-processed phase-contrast images with a state-of-art vision transformer and allows for the continuous assessment of IC50 in a faster and more cost-efficient manner. We have validated this method using four drugs and 1536-well plates, as well as built a first-of-its-kind web application. We anticipate this method will assist in the high-throughput screening of chemical libraries (e.g., small molecule drugs, siRNA, and microRNA and drug discovery.

bioengineering↗

bioRxiv2022

pYtags enable spatiotemporal measurements of receptor tyrosine kinase signaling in living cells

Receptor tyrosine kinases (RTKs) are major signaling hubs in metazoans, playing crucial roles in cell proliferation, migration, and differentiation. However, few tools are available to measure the activity of a specific RTK in individual living cells. Here, we present pYtags, a modular approach for monitoring the activity of a user-defined RTK by live-cell microscopy. pYtags consist of an RTK modified with a tyrosine activation motif that, when phosphorylated, recruits a fluorescently labeled tandem SH2 domain with high specificity. We show that pYtags enable the monitoring of a specific RTK on seconds-to-minutes time scales and across subcellular and multicellular length scales. Using a pYtag biosensor for epidermal growth factor receptor (EGFR), we quantitively characterize how signaling dynamics vary with the identity and dose of activating ligand. We show that orthogonal pYtags can be used to monitor the dynamics of EGFR and ErbB2 activity in the same cell, revealing distinct phases of activation for each RTK. The specificity and modularity of pYtags opens the door to robust biosensors of multiple tyrosine kinases and may enable engineering of synthetic receptors with orthogonal response programs. HighlightsO_LIpYtags report on signaling of user-defined RTKs in living cells C_LIO_LIEGFR signaling dynamics depend on ligand identity and dimer strength C_LIO_LIrthogonal pYtags enable reporter multiplexing C_LIO_LIpYtags can report on signaling of endogenously expressed RTKs C_LI

cell biology↗

bioRxiv2022

Effects of Cr stress on bacterial community structure and diversity in rhizosphere soils of Iris pseudacorus

Rhizosphere microorganisms play an important role in improving soil microenvironment, which contributes to plant growth under heavy metal stress. However, the effect of chromium (Cr) on plant rhizosphere bacterial community is still unknown. In this paper, sole-cultivated pattern, two-cultivated pattern and three-cultivated pattern, combined with 16S rRNA high-throughput sequencing technology, the effects of Cr stress on bacterial community structure and diversity in rhizosphere soil of Iris Pseudacorus were analyzed. The results showed that under Cr stress, I. Pseudacorus showed good tolerance and enrichment. However, under Cr stress, the Alpha diversity indices (Shannon, Chao and Sobs) of rhizosphere bacterial community decreased by 9.1%, 30.3% and 28.0% on average, respectively. The change of bacterial community was 22.6% due to Cr stress, and the common species of bacterial community decreased by 4.2%. Proteobacteria, Actinobacteria, Acidobacteria, Firmicutes and Gemmatimonadetes accounted for more than 78.2% of the total sequence. With the increase of plant diversity, Bacteroides and Pseudomonas appeared successively, and the abundance of the dominant species increased obviously. Through the symbiotic network diagram, it was found that the synergistic effect between dominant species in two-cultivated pattern was significantly enhanced, and the soil microenvironment was significantly improved. In conclusion, the results of this study will provide a reference for understanding the response of rhizosphere bacterial community to heavy metal Cr and the interaction between wetland plants and rhizosphere bacteria during wetland phytoremediation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/503686v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1d5949eorg.highwire.dtl.DTLVardef@1103c11org.highwire.dtl.DTLVardef@d7b700org.highwire.dtl.DTLVardef@2f9df4_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2022

HiCAT: A tool for automatic annotation of centromere structure

Significant improvements in long-read sequencing technologies have unlocked complex genomic areas, such as centromeres, in the genome and introduced the centromere annotation problem. Currently, centromeres are annotated in a semi-manual way. Here, we propose HiCAT, a generalizable automatic centromere annotation tool, based on hierarchical tandem repeat mining and maximization of tandem repeat coverage to facilitate decoding of centromere architecture. We applied HiCAT to human CHM13-T2T and gapless Arabidopsis thaliana genomes. Our results not only were generally consistent with previous inferences but also greatly improved annotation continuity and revealed additional fine structures, demonstrating HiCATs performance and general applicability.

bioinformatics↗

bioRxiv2022

Silent transcription intervals and translational bursting lead to diverse phenotypic switching

Bimodality of gene expression, as a mechanism generating phenotypic diversity, enhances the survival of cells in a fluctuating environment. Growing experimental evidence suggests that silent transcription intervals and translational bursting play important roles in regulating phenotypic switching. Characterizing these kinetics is challenging. Here, we develop an interpretable and tractable model, the generalized telegraph model (GTM), which considers silent transcription intervals described by a general waiting-time distribution and translational bursting characterized by an arbitrary distribution. Using methods of queuing theory, we derive analytical expressions of all moment statistics and distribution of protein counts. We show that non-exponential inactive times and translational bursting can lead to two nonzero bimodalities that cannot be captured in the classical telegraph model (CTM). In addition, we find that both silent-intervals noise and translational burst-size noise can amplify gene expression noise, as well as induce diverse dynamic expressions. Our results not only provide an alternative mechanism for phenotypic switching driven by silent transcription intervals and translational bursting, but also can be used to infer complex promoter structures based on experimental data. SIGNIFICANCEUnderstanding how phenotypic diversity arises among isogenic cell populations is a fundamental problem in biology. Previous studies have shown that the bimodality of gene expression contributing to phenotypic variations is mostly caused by the intrinsic or extrinsic regulations of underlying systems. It is unclear whether bimodality occurs in the absence of these regulations. The CTM has made great success in interpreting many experimental phenomena, but it cannot capture the bimodal distributions with two nonzero peaks that have been demonstrated in experiments. In particular, recent single-cell studies have shown non-exponential inactive periods and non-geometric translational bursting in gene expression. How to model these kinetics is challenging. We develop a stochastic gene model, namely the GTM, to model the silent transcription intervals by a general waiting-time distribution and translational bursting by an arbitrary distribution. By mapping the GTM into a queuing model, we derive the steady-state distribution of gene products that can be used for analyzing phenotypic switching. We find that non-exponential inactive times and translational bursting can lead to two nonzero bimodalities that cannot be captured in the CTM. These results indicate that both silent transcription intervals and translational bursting have important roles in controlling cell phenotypic variations in fluctuating environments.

systems biology↗

bioRxiv2022

The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles

Functional genomics experiments are invaluable for understanding mechanisms of gene regulation. However, comprehensively performing all such experiments, even across a fixed set of sample and assay types, is often infeasible in practice. A promising alternative to performing experiments exhaustively is to, instead, perform a core set of experiments and subsequently use machine learning methods to impute the remaining experiments. However, questions remain as to the quality of the imputations, the best approaches for performing imputations, and even what performance measures meaningfully evaluate performance of such models. In this work, we address these questions by comprehensively analyzing imputations from 23 imputation models submitted to the ENCODE Imputation Challenge. We find that measuring the quality of imputations is significantly more challenging than reported in the literature, and is confounded by three factors: major distributional shifts that arise because of differences in data collection and processing over time, the amount of available data per cell type, and redundancy among performance measures. Our systematic analyses suggest several steps that are necessary, but also simple, for fairly evaluating the performance of such models, as well as promising directions for more robust research in this area.

bioinformatics↗

bioRxiv2022

ID1 functions as an autonomous phosphate (Pi) regulator upstream of the miR399-ZmPHO2 signaling module in maize

The macronutrient phosphorus is essential for plant growth and development. Plants have evolved multiple strategies to increase the efficiency of Pi acquisition to protect themselves from Pi starvation. However, the crosstalk between Pi homeostasis and plant development remains to be explored. Here, we report that overexpressing microRNA399 in maize induced a premature aging syndrome after pollination. Knockout of ZmPHO2, one of the miR399 targets, resulted in a similar premature aging phenotype. Strikingly, we found that INDETERMINATE1 (ID1), a floral transition regulator, inhibits the transcription of ZmMIR399 genes by directly binding to their promoters, alleviating the repression of ZmPHO2 by miR399 and ultimately contributing to the maintenance of Pi homeostasis in maize. Unlike ZmMIR399 genes, whose expression is induced by Pi deficiency, ID1 expression is independent of the Pi status, indicating that ID1 is an autonomous regulator of Pi homeostasis. Furthermore, we found that ZmPHO2 was under selection during maize domestication, resulting in a more sensitive response to phosphate starvation in temperate maize than in tropical maize. Our study reveals a direct functional link between Pi-deprivation sensing by the miR399-ZmPHO2 regulatory module and plant developmental regulation by ID1.

plant biology↗

bioRxiv2022

Metabolic functional redundancy of the CYP9A subfamily members leads to P450-mediated lambda-cyhalothrin resistance in Cydia pomonella

BACKGROUNDThe evolution of insect resistance to pesticides poses a continuing threat to sustainable pest management. While much is known about the molecular mechanisms that confer resistance in model insects and few agricultural pests, far less is known about fruit pests. RESULTSHere we found that functional redundancy and preference of metabolism by cytochrome P450 monooxygenases (P450s) genes in the CYP9A subfamily confer resistance to lambda-cyhalothrin in Cydia pomonella, a major invasive pest of pome fruit. A total of four CYP9A genes, including CYP9A61, CYP9A120, CYP9A121, and CYP9A122, were identified from C. pomonella. Among these, CYP9A120, CYP9A121, and CYP9A122 were predominantly expressed in the midgut of larvae. The expression levels of these P450 genes were significantly induced by LD10 of lambda-cyhalothrin and were overexpressed in a field-evolved lambda-cyhalothrin resistant population. Knockdown of CYP9A120 and CYP9A121 by RNA-mediated interference (RNAi) increased the susceptibility of larvae to lambda-cyhalothrin. In vitro assays demonstrated that recombinant P450s expressed in Sf9 cells can metabolize lambda-cyhalothrin, but with functional redundancy and divergence through regioselectivity of metabolism. CYP9A121 preferred to convert lambda-cyhalothrin to 2'-hydroxy-lambda-cyhalothrin, whereas CYP9A122 only generated 4'-hydroxy metabolite of lambda-cyhalothrin. Although possesses a relatively low metabolic capability, CYP9A120 balanced catalytic competence to generate both 2'- and 4'-metabolites. CONCLUSIONCollectively, these results reveal that metabolic functional redundancy of three members of the CYP9A subfamily leads to P450-mediated lambda-cyhalothrin resistance in C. pomonella, thus representing a potential adaptive evolutionary strategy during its worldwide expansion.

molecular biology↗

bioRxiv2022

Single-nucleus resolution mapping of the adult C. elegans and its application to elucidate inter- and trans-generational response to alcohol.

Single-cell RNA transcriptomic platforms have significantly contributed to our understanding of tissue heterogeneity as well as of developmental and cellular differentiation trajectories. They also provide an opportunity to map an organisms response to environmental cues with high resolution and unbiasedly identify the cell types that are the most transcriptionally sensitive to exposures. Here, we applied single nucleus RNA-seq experimental and computational approaches to C. elegans to establish the transcriptome of the adult nematode and comprehensively characterize the transcriptional impact of ethanol as a model environmental exposure on the entire organism at cell type-resolution over several generations. Clustering, tissue and phenotype enrichment, and gene ontology analyses identified 31 clusters representing a diverse number of adult cell types, including those from syncytial and multi-nucleated tissues which are difficult to assess by single cell RNA-seq, such as the mitotic and meiotic germline, hypodermal cells, and the intestine. We applied this method to identify the impact of inter- and trans-generational exposure to two human-relevant doses of alcohol. Cell type proportions were not significantly altered by ethanol. However, Euclidean distance analysis identified several germline, striated muscle, and neuronal clusters as being major transcriptional targets of ethanol at both the F1 and F3 generations although the relative order of clusters changed between generations. The impact on germline clusters was further confirmed by phenotypic enrichment analysis as well as functional validation, namely a remarkable inter- and trans-generational increase in germline apoptosis, aneuploidy, and embryonic lethality. Together, snRNA-seq of the adult C. elegans represents a powerful approach for the detailed examination of an adult organisms response to environmental cues.

genetics↗

bioRxiv2022

Inferring transcriptional bursting kinetics from single-cell snapshot data using a generalized telegraph model

MotivationGene expression has inherent stochasticity resulting from transcriptions burst manners. Single-cell snapshot data can be exploited to rigorously infer transcriptional burst kinetics, using mathematical models as blueprints. The classical telegraph model (CTM) has been widely used to explain transcriptional bursting with Markovian assumptions (i.e., exponentially distributed dwell time in ON and OFF states). However, growing evidence suggests that the gene-state dwell times are nonexponential, as gene-state switching is a multi-step process in organisms. Therefore, interpretable non-Markovian mathematical models and efficient statistical inference methods are urgently required in investigating transcriptional burst kinetics. ResultsWe develop an interpretable and tractable model, the generalized telegraph model (GTM), to carve transcriptional bursting that allows arbitrary dwell-time distributions, rather than exponential distributions, to be incorporated into the ON and OFF switching process. Based on the GTM, we propose an inference method for transcriptional bursting kinetics using an approximate Bayesian computation framework (BayesGTM). BayesGTM demonstrates efficient and scalable estimation of burst frequency and burst size on synthetic data. Further, the application of BayesGTM to genome-wide data from mouse embryonic fibroblasts reveals that CTM would overestimate burst frequency and underestimate burst size. In conclusion, the GTM and the corresponding BayesGTM are effective tools to infer dynamic transcriptional bursting from static single-cell snapshot data.

systems biology↗

bioRxiv2022

Audiovisual Integration in the Human Brain: A Coordinate-based Meta-analysis

People can seamlessly integrate a vast array of information from what we see and hear in the noisy and uncertain world. However, the neural underpinnings of audiovisual integration continue to be the topic of debate. Using strict inclusion criteria, we performed activation likelihood estimation meta-analysis on 121 neuroimaging experiments with a total of 2,092 participants. We found that audiovisual integration is linked with the coexistence of multiple integration sites including early cortical, subcortical, and higher association areas. Although activity was consistently found within the superior temporal cortex, different portions of this cortical region were identified depending on the analytical contrast used, complexity of the stimuli, and modality within which attention was directed. The context-dependent neural activity related to audiovisual integration suggests a flexible rather than fixed neural pathway for audiovisual integration. Together, our findings highlight a flexible multiple pathways model for audiovisual integration, with superior temporal cortex as the central node in these neural assemblies.

neuroscience↗

bioRxiv2022

Early life stress exposure increases susceptibility to high fat/high sucrose diet in female mice

Exposure to stress early in life has been associated with adult-onset co-morbidities such as chronic pain, metabolic dysregulation, obesity, and inactivity. We have established an early life stress model using neonatal maternal separation (NMS) in mice, which displays evidence of increased body weight and adiposity, widespread mechanical allodynia, and hypothalamic-pituitary-adrenal axis dysregulation in male mice. Early life stress and consumption of a western style diet contribute to the development of obesity, however, relatively few pre-clinical studies have been performed in female rodents, which are known to be protected against diet induced obesity and metabolic dysfunction. In this study we gave naive and NMS female mice access to a high-fat/high-sucrose (HFS) diet beginning at 4 weeks of age. Robust increases in body weight and fat were observed in HFS-fed NMS mice during the first 10 weeks on the diet, driven partly by increased food intake. Female NMS mice on a HFS diet showed widespread mechanical hypersensitivity compared to either naive mice on a HFS diet or NMS mice on a control diet. HFS diet-fed NMS mice also had impaired glucose tolerance and fasting hyperinsulinemia. Strikingly, female NMS mice on a HFS diet showed evidence of hepatic steatosis with increased triglyceride levels and altered glucocorticoid receptor levels and phosphorylation state. They also exhibited increased energy expenditure as observed via indirect calorimetry and expression of pro-inflammatory markers in perigonadal adipose. Altogether, our data suggest that early life stress exposure increased the susceptibility of female mice to develop diet-induced metabolic dysfunction and pain-like behaviors.

physiology↗

bioRxiv2022

FOXP2 confers oncogenic effects in prostate cancer through activating MET signalling

Identification oncogenes is fundamental to revealing the molecular basis of cancer. Here, we found that FOXP2 is overexpressed in human prostate cancer cells and prostate tumors, but its expression is absent in normal prostate epithelial cells and low in benign prostatic hyperplasia. To date, little is known regarding the link of FOXP2 to prostate cancer. We observed that high FOXP2 expression and frequent amplification are significantly associated with high Gleason score. Ectopic expression of FOXP2 induces malignant transformation of mouse NIH3T3 fibroblasts and human prostate epithelial cell RWPE-1. Conversely, FOXP2 knockdown suppresses the proliferation of prostate cancer cells. Transgenic overexpression of FOXP2 in the mouse prostate causes prostatic intraepithelial neoplasia. Overexpression of FOXP2 aberrantly activates oncogenic MET signalling and inhibitors targeting MET signalling effectively reverts the FOXP2-induced oncogenic phenotype. Additionally, the novel recurrent FOXP2-CPED1 fusion identified in prostate tumors results in high expression of truncated FOXP2, which exhibit a similar capacity for malignant transformation. Together, our data demonstrate for the first time that FOXP2 is an oncogene involved in tumorigenicity of prostate.

cancer biology↗

bioRxiv2022

Gene Regulatory Network Reconfiguration in Direct Lineage Reprogramming

In direct lineage reprogramming, transcription factor (TF) overexpression reconfigures Gene Regulatory Networks (GRNs) to convert cell identities between fully differentiated cell types. We previously developed CellOracle, a computational pipeline that integrates single-cell transcriptome and epigenome profiles to infer GRNs. CellOracle leverages these inferred GRNs to simulate gene expression changes in response to TF perturbation, enabling network re-configuration during reprogramming to be interrogated in silico. Here, we integrate CellOracle analysis with lineage tracing of fibroblast to induced endoderm progenitor (iEP) conversion, a prototypical direct lineage reprogramming paradigm. By linking early network state to reprogramming success or failure, we reveal distinct network configurations underlying different reprogramming outcomes. Using these network analyses and in silico simulation of TF perturbation, we identify new factors to coax cells into successfully converting cell identity, uncovering a central role for the AP-1 subunit Fos with the Hippo signaling effector, Yap1. Together, these results demonstrate the efficacy of CellOracle to infer and interpret cell-type-specific GRN configurations at high resolution, providing new mechanistic insights into the regulation and reprogramming of cell identity.

genomics↗