Biology subjects

Chen, G.

Publications and source records attributed to Chen, G..

At least 253 records · Page 14Linked to original sources

bioRxiv2022

Emodin Combined with Multiple Low-frequency Low-intensity Ultrasound to Relieve Osteomyelitis Through Sonoantimicrobial Chemotherapy

Treatment of osteomyelitis is still challenging as conventional antibiotic therapy is limited by the emergence of resistant strains and the formation of biofilms. Sonoantimicrobial chemotherapy (SACT) is a novel therapy of low-frequency and low-intensity ultrasound (LFLIU) combined with sonosensitizer. Therefore, in our study, a sonosensitizer named emodin (EM) was proposed to be combined with LFLIU to relieve acute osteomyelitis caused by Methicillin-resistant Staphylococcus aureus (MRSA) through synergistic antibacterial and anti-biofilm effects. The efficiency of different intensities of ultrasound, single (S-LFLIU, 15 min) and multiple ultrasound (M-LFLIU, 5 min every 4 h, three times) against bacteria and biofilm was compared, contributing to develop the best treatment regimen. Our results demonstrated that EM plus S-LFLIU or M-LFLIU (EM+S-LFLIU or EM+M-LFLIU) have significant synergetic bactericidal and anti-biofilm effects and EM+M-LFLIU exhibits superior performance in anti-biofilm. Furthermore, it was suggested that EM+M-LFLIU could produce a large amount of reactive oxygen species (ROS), destroy the integrity of bacterial membrane and wall, down-regulate the expression of oxidative stress, membrane wall synthesis, bacterial virulence and other related genes (agrB, PBP3, sgtB, GMK, zwf, msrA). In vivo study, micro-CT, H&E staining, ELISA assay and bacterial quantification of bone tissue indicated that EM+M-LFLIU could also relieve osteomyelitis of MRSA infection. Our work proffers an original treating bacterial osteomyelitis approach that weakens drug-resistant bacterial and suppresses biofilm formation through SACT, which may provide new prospects for clinical treatment.

microbiology↗

bioRxiv2022

Topological supramolecular network enabled highly conductive and stretchable organic bioelectronics

Intrinsically stretchable bioelectronic devices based on soft and conducting organic materials have been regarded as the ideal interface for seamless and biocompatible integration with the human body. However, the grand challenge remains for the conducting polymer to possess both high mechanical ductility and good electrical conduction at cellular level feature sizes. This longstanding material limitation in organic bioelectronics has impeded the full exploitation of its unique benefits. Here, we introduce a new molecular engineering strategy based on rationally designed topological supramolecular networks, which allows effective decoupling of competing effects from multiple molecular building blocks to meet complex requirements. We achieve two orders of magnitude improvement in the conductivity under 100% strain in physiological environment, along with the capability for direct photopatterning down to 2 m. These unprecedented capabilities allow us to realize previously inaccessible bioelectronic applications including high-resolution monitoring of soft and malleable creatures, e.g., octopus, and localized neuromodulation down to single nucleus precision for controlling organ-specific activities through delicate tissues, e.g., brainstem.

bioengineering↗

bioRxiv2022

Functional dissection of neural connectivity in generalized anxiety disorder

Differences in the correlated activity of networked brain regions have been reported in individuals with generalized anxiety disorder (GAD) but an overreliance on the null-hypothesis significance testing (NHST) framework limits the identification and characterization of disorder-relevant relationships. In this preregistered study, we applied a Bayesian statistical framework as well as NHST to the analysis of resting-state fMRI scans from females with GAD and demographically matched healthy comparison females. Eleven a-priori hypotheses about functional correlativity (FC) were evaluated using Bayesian (multilevel model) and frequentist (t-test) inference. Reduced FC between the ventromedial prefrontal cortex (vmPFC) and the posterior-mid insula (PMI) was confirmed by both statistical approaches. FC between the vmPFC-anterior insula, the amygdala-PMI, and the amygdala-dorsolateral prefrontal cortex (dlPFC) region pairs did not survive multiple comparison correction using the frequentist approach. However, the Bayesian model provided evidence for these region pairs having decreased FC in the GAD group. Leveraging Bayesian modeling, we demonstrate decreased FC of the vmPFC, insula, amygdala, and dlPFC in females with GAD. Exploiting the Bayesian framework revealed FC abnormalities between region pairs excluded by the frequentist analysis, as well as other previously undescribed regions, demonstrating the benefits of applying this statistical approach to resting state FC data.

neuroscience↗

bioRxiv2022

Hypoxia Dynamically Regulates DBC1 Ubiquitination and Stability by SIAH2 and OTUD5 in Breast Cancer Progression

DBC1 has been characterized as a key regulator of physiological and pathophysiological activities, such as DNA damage, senescence and tumorigenesis. However, the mechanism by which the functional stability of DBC1 is regulated has yet to be elucidated. Here, we report that the ubiquitination-mediated degradation of DBC1 is dynamically regulated by the E3 ubiquitin ligase SIAH2 and deubiquitinase OTUD5 under hypoxic stress. Mechanistically, hypoxia promoted the competitive binding of SIAH2 with OTUD5 to DBC1, resulting in the ubiquitination and subsequent degradation of DBC1 through the ubiquitin-proteasome pathway. Siah2 knockout inhibited tumor cell proliferation and migration, which could be rescued by double knockout of Siah2/DBC1. Human tissue microarray analysis further revealed that the SIAH2/DBC1 axis was responsible for tumor progression under hypoxic stress. These findings define a key role of the hypoxia-mediated SIAH2-DBC1 pathway in the progression of human breast cancer and provide novel insights into the metastatic mechanism of breast cancer.

cell biology↗

bioRxiv2021

Evolutionary learning in the brain by heterosynaptic plasticity

How the brain modifies synapses to improve the performance of complicated networks remains one of the biggest mysteries in neuroscience. Canonical models suppose synaptic weights change according to pre- and post-synaptic activities (i.e., local plasticity rules), implementing gradient-descent algorithms. However, the lack of experimental evidence to confirm these models suggests that there may be important ingredients neglected by these models. For example, heterosynaptic plasticity, non-local rules mediated by inter-cellular signaling pathways, and the biological implementation of evolutionary algorithms (EA), another machine-learning paradigm that successfully trains large-scale neural networks, are seldom explored. Here we propose and systematically investigate an EA model of brain learning with non-local rules alone. Specifically, a population of agents are represented by different information routes in the brain, whose task performances are evaluated through gating on individual routes alternatively. The selection and reproduction of agents are realized by dopamine-guided heterosynaptic plasticity. Our EA model provides a framework to re-interpret the biological functions of dopamine, meta-plasticity of dendritic spines, memory replay, and the cooperative plasticity between the synapses within a dendritic neighborhood from a new and coherent aspect. Neural networks trained with the model exhibit analogous dynamics to the brain in cognitive tasks. Our EA model manifests broad competence to train spiking or analog neural networks with recurrent or feedforward architecture. Our EA model also demonstrates its powerful capability to train deep networks with biologically plausible binary weights in MNIST classification and Atari-game playing tasks with performance comparable with continuous-weight networks trained by gradient-based methods. Overall, our work leads to a fresh understanding of the brain learning mechanism unexplored by local rules and gradient-based algorithms.

neuroscience↗

bioRxiv2021

Spatial Meta-transcriptomes of human and murine intestines

We developed an analysis pipeline that can extract microbial sequences from Spatial Transcriptomic data and assign taxonomic labels to them, generating a spatial microbial abundance matrix in addition to the default host expression one, enabling simultaneous analysis of host expression and microbial distribution. We applied it on both human and murine intestinal datasets and validated the spatial microbial abundance information with alternative assays. Finally, we present a few biological insights that can be gained from this novel data. In summary, this proof of concept work demonstrated the feasibility of Spatial Meta-transcriptomic analysis, and pave the way for future experimental optimization.

systems biology↗

bioRxiv2021

Analysis of visual processing capabilities and neural coding strategies of a detailed model for laminar cortical microcircuits in mouse V1

Neural networks of the brain that process visual information have structural properties that differ significantly from those of neural networks which are commonly used for visual processing in AI, such as Convolutional Neural Networks (CNNs). But it has remained unknown how these structural differences are related to network function. We analyze visual processing capabilities of a large-scale model for area V1 that arguably provides the most comprehensive accumulation of anatomical and neurophysiological data that is currently available. Its network structure turns out to induce a number of characteristic visual processing capabilities of the brain, in particular the capability to multiplex different visual processing tasks, also on temporally dispersed visual information, with remarkable robustness to noise. This V1 model also exhibits a number of characteristic neural coding properties of the brain, which provide explanations for its superior noise robustness. Since visual processing in the brain is substantially more energy-efficient than implementations of CNNs in common computer hardware, such brain-like neural network models are likely to have also an impact on technology: As blueprints for visual processing in more energy-efficient neuromorphic hardware. TeaserA new generation of neural network models based on neurophysiological data can achieve robust multiplexing capabilities.

neuroscience↗

bioRxiv2021

Molecular chaperone ability to inhibit amyloid-derived neurotoxicity, but not amorphous protein aggregation, depends on a conserved pH-sensitive Asp residue

Proteins can self-assemble into amyloid fibrils or amorphous aggregates and thereby cause disease. Molecular chaperones can prevent both these types of protein aggregation, but the respective mechanisms are not fully understood. The BRICHOS domain constitutes a disease-associated small heat shock protein-like chaperone family, with activities against both amyloid toxicity and amorphous protein aggregation. Here, we show that the activity of two BRICHOS domain families against Alzheimers disease associated amyloid-{beta} neurotoxicity to mouse hippocampi in vitro depends on a conserved aspartate residue, while the ability to suppress amorphous protein aggregation is unchanged by Asp to Asn mutations. The conserved Asp in its ionized state promotes structural flexibility of the BRICHOS domain and has a pKa value between pH 6.0-7.0, suggesting that chaperone effects against amyloid toxicity can be affected by physiological pH variations. Finally, the Asp is evolutionarily highly conserved in >3000 analysed BRICHOS domains but is replaced by Asn in some BRICHOS families and animal species, indicating independent evolution of molecular chaperone activities against amyloid fibril formation and non-fibrillar amorphous protein aggregation.

biochemistry↗

bioRxiv2021

Peptide-antibody Fusions Engineered by Phage Display Exhibit Ultrapotent and Broad Neutralization of SARS-CoV-2 Variants

The COVID-19 pandemic has been exacerbated by the emergence of variants of concern (VoCs). Many VoC mutations are found in the viral spike protein (S-protein), and are thus implicated in host infection and response to therapeutics. Bivalent neutralizing antibodies (nAbs) targeting the S-protein receptor-binding domain (RBD) are promising therapeutics for COVID-19, but are limited due to low potency and vulnerability to RBD mutations found in VoCs. To address these issues, we used naive phage-displayed peptide libraries to isolate and optimize 16-residue peptides that bind to the RBD or the N-terminal domain (NTD) of the S-protein. We fused these peptides to the N-terminus of a moderate affinity nAb to generate tetravalent peptide-IgG fusions, and showed that both classes of peptides were able to improve affinities for the S-protein trimer by >100-fold (apparent KD < 1 pM). Critically, cell-based infection assays with a panel of six SARS-CoV-2 variants demonstrate that an RBD-binding peptide was able to enhance the neutralization potency of a high-affinity nAb >100-fold. Moreover, this peptide-IgG was able to neutralize variants that were resistant to the same nAb in the bivalent IgG format. To show that this approach is general, we fused the same peptide to a clinically approved nAb drug, and showed that it rescued neutralization against a resistant variant. Taken together, these results establish minimal peptide fusions as a modular means to greatly enhance affinities, potencies, and breadth of coverage of nAbs as therapeutics for SARS-CoV-2.

synthetic biology↗

bioRxiv2021

Dynamics of deep water and N uptake under varied N and water supply

AimsEnhanced nitrogen (N) and water uptake from deep soil layers may increase resource use efficiency whilst maintaining yield under stressed conditions. Winter oilseed rape (Brassica napus L.) can develop deep roots and access deep-stored resources such as N and water, while this potential has large uncertainties in variable environments. In this study, we aimed to evaluate the effects of reduced N and water supply on deep N and water uptake. MethodsOilseed rape plants grown in outdoor rhizotrons were supplied with 240 and 80 kg N ha-1 respectively in 2019 whereas a well-watered and a water-deficit treatment were established in 2020. To track deep water and N uptake, a mixture of 2H2O and Ca(15NO3)2 was injected into the soil column at 0.5 and 1.7 m depths. {delta}2H in transpiration water and {delta}15N in leaves were measured after injection. {delta}15N in biomass samples were also measured. ResultsDifferences in N or water supply had little effect on root growth. The low N treatment reduced water uptake throughout the soil profile, but caused a non-significant increment in 15N uptake efficiency at both 0.5 and 1.7 m. Water deficit in the upper soil layers led to compensatory deep water, while N uptake was not altered by soil water status. ConclusionOur findings demonstrate that for winter oilseed rape, high N application and water deficiency in shallow layers increases deep water uptake, and that the efficiency of deep N uptake is mainly sensitive to N supply rather than water supply.

plant biology↗

bioRxiv2021

Genome-wide identification and gene expression analysis of clade A protein phosphatase 2C family genes in Brassica juncea var. tumida

Abscisic acid (ABA) plays crucial roles in plant response to environmental stresses and development. The clade A phosphatases (PP2Cs) play a crucial role in ABA signaling. However, little is known about the details regarding PP2Cs family genes in Brassica juncea var. tumida. Here, 20 clade A PP2Cs family genes were identified in tuber mustard genome, including BjuABI1s, BjuABI2s, BjuAHG1s, BjuAHG3s, BjuHAB1, BjuHAB2s, BjuHAI1s, BjuHAI2s and BjuHAI3. The promoters of BjuPP2Cs family genes contained various of cis-acting elements, such as ABRE, GT1GMSCAM4, ARFAT and MYB1AT. We also analyzed the expression pattern of clade A BjuPP2Cs under abiotic stresses (low temperature, NaCl and ABA) treatment, pathogen Plasmodiophora brassicae treatment and different stages of stem swollen. The results suggested that clade A BjuPP2Cs regulated tuber mustard response to P. brassicae to mediate the formation of clubroot and might play roles in stem swelling and response to abiotic stresses. This study provides valuable information for further functional investigations of clade A PP2Cs family genes in B. juncea var. tumida.

bioinformatics↗

bioRxiv2021

Global distribution of anaerobic dichloromethane degradation potential

Anthropogenic activities and natural processes release dichloromethane (DCM), a toxic chemical with substantial ozone-depleting capacity. Specialized anaerobic bacteria metabolize DCM; however, the genetic basis for this process has remained elusive. Comparative genomics of the three known anaerobic DCM-degrading bacterial species revealed a homologous gene cluster, designated the methylene chloride catabolism (mec) gene cassette, comprising eight to ten genes with predicted 79.6 - 99.7% amino acid identity. Functional annotation identified genes encoding a corrinoid-dependent methyltransferase system, and shotgun proteomics applied to two DCM-catabolizing cultures revealed high expression of proteins encoded on the mec gene cluster during anaerobic growth with DCM. In a DCM-contaminated groundwater plume, the abundance of mec genes strongly correlated with DCM concentrations (R2 = 0.71 - 0.85) indicating their value as process-specific bioremediation biomarkers. mec gene clusters were identified in metagenomes representing peat bogs, the deep subsurface, and marine ecosystems including oxygen minimum zones (OMZs), suggesting DCM turnover in diverse habitats. The broad distribution of anaerobic DCM catabolic potential suggests a relevant control function for emissions to the atmosphere, and a role for DCM as a microbial energy source in critical zone environments. The findings imply that the global DCM flux might be far greater than emission measurements suggest. ImportanceDichloromethane (DCM) is an increasing threat to stratospheric ozone with both anthropogenic and natural emission sources. Anaerobic bacterial metabolism of DCM has not yet been taken into consideration as a factor in the global DCM cycle. The discovery of the mec gene cassette associated with anaerobic bacterial DCM metabolism and its widespread distribution in environmental systems highlight a strong attenuation potential for DCM. Knowledge of the mec cassette offers new opportunities to delineate DCM sources, enables more robust estimates of DCM fluxes, supports refined DCM emission modeling and simulation of the stratospheric ozone layer, reveals a novel, ubiquitous C1 carbon metabolic system, and provides prognostic and diagnostic tools supporting bioremediation of groundwater aquifers impacted by DCM.

microbiology↗

bioRxiv2021

Lupus Gut Microbiota Transplants Cause Autoimmunity and Inflammation

BackgroundThe etiology of systemic lupus erythematosus (SLE) is multifactorial. Recently, growing evidence suggests that the microbiota plays a role in SLE, yet whether gut microbiota participates in the development of SLE remains largely unknown. To investigate this issue, we carried out 16s rDNA sequencing analyses in a cohort of 18 female un-treated active SLE patients and 7 female healthy controls, and performed fecal microbiota transplantation from patients and healthy controls to germ-free mice. ResultsCompared to the healthy controls, we found no significant different microbial diversity but some significantly different species in SLE patients including Turicibacter genus and other 5 species. Fecal transfer from SLE patients to germ free (GF) C57BL/6 mice caused GF mice to develop a series of lupus-like phenotyptic features, which including an increased serum autoimmune antibodies, and imbalanced cytokines, altered distribution of immune cells in mucosal and peripheral immune response, and upregulated expression of genes related to SLE in recipient mice that received SLE fecal microbiota transplantation (FMT). Moreover, the metabolism of histidine was significantly altered in GF mice treated with SLE patient feces, as compared to those which received healthy fecal transplants. ConclusionsOverall, our results describe a causal role of aberrant gut microbiota in contributing to the pathogenesis of SLE. The interplay of gut microbial and histidine metabolism may be one of the mechanisms intertwined with autoimmune activation in SLE.

immunology↗

bioRxiv2021

The first crested duck genome reveals clues to genetic compensation and crest cushion formation

The Chinese crested (CC) duck is a unique indigenous waterfowl breed with a phenotypic crest trait that affects its high survival rate. Therefore, the CC duck is an ideal model to investigate the genetic compensation response to maintain genetic stability. In the present study, we first generated a chromosome-level genome of CC ducks. Comparative genomics revealed genes related to tissue repair, immune function, and tumors were under strong positive selection, which suggested that these adaptive changes might enhance cancer resistance and immune response to maintain the genetic stability of CC ducks. We sub-assembled a Chinese spot-billed duck genome and detected genome-assembled structure variants among three ducks. Functional analysis revealed that a large number of structural variants were related to the immune system, which strongly suggests the occurrence of genetic compensation in the anti-tumor and immune systems to further support the survival of CC ducks. Moreover, we confirmed that the CC duck originated from the mallard ducks. Finally, we revealed the physiological and genetic basis of crest traits and identified a causative mutation in TAS2R40 that leads to crest formation. Overall, the findings of this study provide new insights into the role of genetic compensation in adaptive evolution.

genomics↗

bioRxiv2021

The northern gene flow into southeastern East Asians inferred from genome-wide array genotyping

The population history of Southeast China remains poorly understood due to the sparse sampling of present-day populations and far less modeling with ancient genomic data. We here newly reported genome-wide genotyping data from 207 present-day Han Chinese and Hmong-Mien-speaking She people from Fujian and Taiwan, southeast China. We co-analyzed with 66 early-Neolithic to Iron-Age ancient Fujian and Taiwan individuals obtained from literature to explore the genetic continuity and admixture based on the genetic variations of high-resolution time transect. We found the genetic differentiation between northern and southern East Asians defined by a north-south East Asian genetic cline and the studied southern East Asians were clustered in the southern end of this cline. We also found that southeastern coastal continental modern East Asians harbored the genetic differentiation with other southern Tai-Kadai, Hmong-Mien, Austronesian and Austroasiatic speakers, as well as geographically close Neolithic-to-Iron Age populations, but relatedly close to post-Neolithic Yellow River ancients, which suggested the influence of southward gene flow on the modern southern coastal gene pool. Besides, we also identified one new Hmong-Mien genetic cline in East Asia with the coastal Fujian She localizing at the intersection position between Hmong-Mien and Han clines in the principal component analysis. She people show stronger genetic affinity with southern East Asian indigenous populations with the main ancestry deriving from Hanben-related populations. The southeastern Han Chinese could be modeled with the primary ancestry deriving from the group related to the Yellow River Basin millet farmers and the remaining from groups related to southeastern ancient indigenous rice farmers, which was consistent with the northern China origin of modern southeastern Han Chinese and in line with the historically and archaeologically attested southward migrations of Han people and their ancestors. Interestingly, f4-statistics and three-way admixture model results showed both coastal ancient sources related to Austronesian speakers and inland ancient sources related to Austroasiatic speakers complexed the modern observed fine-scale genetic structure here. Our estimated north-south admixture time ranges based on the decay of the linkage disequilibrium spanned from the Bronze age to historic periods, suggesting the recent large-scale population migrations and subsequent admixture participated in the formation of modern Han in Southeast Asia.

genetics↗

bioRxiv2021

Genomic insights into the differentiated population admixture structure and demographic history of North East Asians

North China and South Siberia, mainly populated by Altaic-speaking populations, possess extensive ethnolinguistic diversity and serve as the crossroad for the initial peopling of America and western-eastern trans-continental communication. Yet, the complex scenarios of genetic origin, population structure, and admixture history of North-East Asia remain to be fully characterized, especially for Mongolic people in China with a genome-wide perspective. Thus, we genotyped genome-wide SNPs for 510 individuals from 38 Chinese Mongolic, Tungusic, and Sinitic populations to explore the sharing alleles and haplotypes within the studied groups and following merged it with 3508 modern and ancient Eurasian individuals to reconstruct the deep evolutionary and natural selection history of northern East Asians. We identified significant substructures within Altaic-speaking populations with the primary common ancestry linked to the Neolithic northern East Asians: Western Turkic people harbored more western Eurasian ancestry; Northern Mongolic people in Siberia and eastern Tungusic people in Amur River Basin (ARB) possessed dominant Neolithic Mongolian Plateau (MP) or ARB ancestry; Southern Mongolic people in China owned obvious genetic impact from Neolithic Yellow River Basin (YRB) farmers. Additionally, we found the differentiated admixture history between western and eastern Mongolians and geographically close Northeast Hans: the former received a genetic impact from western Eurasians and the latter retained the dominant YRB and ARB Neolithic ancestry. Moreover, we demonstrated that Kalmyk people from the northern Caucasus Mountain possessed a strong genetic affinity with Neolithic MP people, supporting the hypothesis of their eastern Eurasian origin and long-distance migration history. We also illuminated that historic pastoral empires in the MP contributed considerably to the gene pool of northern Mongolic people but rarely to southern ones. We finally found natural signatures in Mongolians associated with alcohol metabolism. Generally, our results not only illuminated that complex population migration and admixture of Neolithic ancestral sources from the MP or ARB played an important role in the spread of Altaic-speaking populations and Proto-Altaic language, which partly supported the Northeast Asia-origin hypothesis, but also demonstrated that the observed multi-sources of genetic diversity contributed significantly to the modern existing extensive ethnolinguistic diversity in North-East Asia.

genomics↗

bioRxiv2021

Hyperbolic trade-off: the importance of balancing trial and subject sample sizes in neuroimaging

Here we investigate the crucial role of trials in task-based neuroimaging from the perspectives of statistical efficiency and condition-level generalizability. Big data initiatives have gained popularity for leveraging a large sample of subjects to study a wide range of effect magnitudes in the brain. On the other hand, most taskbased FMRI designs feature a relatively small number of subjects, so that resulting parameter estimates may be associated with compromised precision. Nevertheless, little attention has been given to another important dimension of experimental design, which can equally boost a studys statistical efficiency: the trial sample size. The common practice of condition-level modeling implicitly assumes no cross-trial variability. Here, we systematically explore the different factors that impact effect uncertainty, drawing on evidence from hierarchical modeling, simulations and an FMRI dataset of 42 subjects who completed a large number of trials of cognitive control task. We find that, due to the hyperbolic relationship between trial and subject sample sizes and the presence of relatively large cross-trial variability, 1) trial sample size has nearly the same impact as subject sample size on statistical efficiency; 2) increasing both the number of trials and subjects improves statistical efficiency more effectively than focusing on subjects alone; 3) trial sample size can be leveraged alongside subject sample size to improve the cost-effectiveness of an experimental design; 4) for small trial sample sizes, trial-level modeling, rather than condition-level modeling through summary statistics, may be necessary to accurately assess the standard error of an effect estimate. We close by making practical suggestions for improving experimental designs across neuroimaging and behavioral studies.

neuroscience↗

bioRxiv2021

Heterogeneity and molecular programming of progenitors for motor neurons and oligodendrocytes

The pMN domain is a restricted domain in the ventral spinal cords, defined by the expression of olig2 gene. The fate determination of pMN progenitors is highly temporally and spatially regulated, with motor neurons and oligodendrocyte progenitor cells (OPCs) developing sequentially. Insight into the heterogeneity and molecular programs of pMN progenitors is currently lacking. With the zebrafish model, we identified multiple states of neural progenitors using single-cell sequencing: proliferating progenitors, common progenitors for both motor neurons and OPCs, and restricted precursors for either motor neurons or OPCs. We found specific molecular programs for neural progenitor fate transition, and manipulations of representative genes in the motor neuron or OPC lineage confirmed their critical role in cell fate determination. The transcription factor NPAS3 is necessary for the development of the OPC lineage and can interact with many known genes associated with schizophrenia. Deciphering progenitor heterogeneity and molecular mechanisms for these transitions will elucidate the formation of complex neuron-glia networks in the central nervous system during development, and understand the basis of neurodevelopmental disorders.

neuroscience↗