Biology subjects

Liu, Q.

Publications and source records attributed to Liu, Q..

At least 307 records · Page 17Linked to original sources

bioRxiv2024

Genome-wide analysis of flavonoid biosynthetic genes in Musaceae (Ensete, Musella, and Musa species) reveals amplification of flavonoid 3',5'-hydroxylase

Flavonoids in Musaceae are involved in pigmentation and stress responses, including pathogen defense and UV protection, and are a component of the healthy human diet. Identification and analysis of the sequence and copy number of flavonoid biosynthetic genes are valuable for understanding the nature and diversity of flavonoid evolution in Musaceae species. In this study, we identified 71 to 80 flavonoid biosynthetic genes in chromosome-scale genome sequence assemblies of Musaceae, including those of Ensete glaucum, Musella lasiocarpa, Musa beccarii, M. acuminata, M. balbisiana, and M. schizocarpa, checking annotations with BLAST and determining the presence of conserved domains. The number of genes increased through segmental duplication and tandem duplication. Orthologues of both structural and regulatory genes in the flavonoid biosynthetic pathway are highly conserved across Musaceae. The flavonoid 3,5-hydroxylase gene F35Hs was amplified in Musaceae and ginger compared with grasses (rice, Brachypodium, Avena longiglumis, and sorghum). One group of genes from this gene family amplified near the centromere of chromosome 2 in the x = 11 Musaceae species. Flavonoid biosynthetic genes displayed few consistent responses in the yellow and red bracts of Musella lasiocarpa when subjected to low temperatures. The expression levels of MlDFR2/3 increased while MlLAR was reduced by half. These results establish the range of diversity in both sequence and copy number of flavonoid biosynthetic genes during evolution of Musaceae. The combination of allelic variants of genes, changes in their copy numbers, and variation in transcription factors with the modulation of expression under cold treatments and between bract-colours suggests the variation may be exploited in plant breeding programmes, particularly for improvement of stress-resistance in the banana crop.

genetics↗

bioRxiv2024

Anti-drift pose tracker (ADPT): A transformer-based network for robust animal pose estimation cross-species

Deep learning-based methods have advanced animal pose estimation, enhancing accuracy and efficiency in quantifying animal behavior. However, these methods frequently experience tracking drift, where noise-induced jumps in body point estimates compromise reliability. Here, we present the Anti-Drift Pose Tracker (ADPT), a transformer-based tool that mitigates tracking drift in behavioral analysis. Extensive experiments across cross-species datasets--including proprietary mouse and monkey recordings and public Drosophila and macaque datasets--demonstrate that ADPT significantly reduces drift and surpasses existing models like DeepLabCut and SLEAP in accuracy. Moreover, ADPT achieved 93.16% identification accuracy for 10 unmarked mice and 90.36% accuracy for freely interacting unmarked mice, which can be further refined to 99.72%, enhancing both anti-drift performance and pose estimation accuracy in social interactions. With its end-to-end design, ADPT is computationally efficient and suitable for real-time analysis, offering a robust solution for reproducible animal behavior studies. The ADPT code is available at https://github.com/tangguoling/ADPT.

neuroscience↗

bioRxiv2024

The nanoscale organization of the Nipah virus fusion protein informs new membrane fusion mechanisms.

Paramyxovirus membrane fusion requires an attachment protein for receptor binding and a fusion protein for membrane fusion triggering. Nipah virus (NiV) attachment protein (G) binds to ephrinB2 or -B3 receptors, and fusion protein (F) mediates membrane fusion. NiV-F is a class I fusion protein and is activated by endosomal cleavage. The crystal structure of a soluble GCN4-decorated NiV-F shows a hexamer-of-trimer assembly. Here, we used single-molecule localization microscopy to quantify the NiV-F distribution and organization on cell and virus-like-particle membranes at a nanometer precision. We found that NiV-F on biological membranes forms distinctive clusters that are independent of endosomal cleavage or expression levels. The sequestration of NiV-F into dense clusters favors membrane fusion triggering. The nano-distribution and organization of NiV-F are susceptible to mutations at the hexamer-of-trimer interface, and the putative oligomerization motif on the transmembrane domain. We also show that NiV-F nanoclusters are maintained by NiV-F-AP-2 interactions and the clathrin coat assembly. We propose that the organization of NiV-F into nanoclusters facilitates membrane fusion triggering by a mixed population of NiV-F molecules with varied degrees of cleavage and opportunities for interacting with the NiV-G/receptor complex. These observations provide insights into the in-situ organization and activation mechanisms of the NiV fusion machinery.

microbiology↗

bioRxiv2024

PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization

Single-cell perturbation sequencing techniques (scPerturbation), represented by single cell genetic perturbation sequencing (e.g., Perturb-seq) and single cell chemical perturbation sequencing (e.g., sci-Plex), result from the integration of single-cell toolkits with conventional bulk screening methods. These innovative sequencing techniques empower researchers to dissect perturbation functions and mechanisms in complex biological systems at an unprecedented resolution. Despite these advancements, a notable gap exists in the availability of a dedicated database for exploring and querying scPerturbation data. To address this gap and facilitate seamless data sharing for researchers, we present PerturBase--the first and most comprehensive database designed for the analysis and visualization of scPerturbation data (http://www.perturbase.cn/). PerturBase consolidates 122 datasets from 46 publicly accessible research studies, covering 115 single-modal and 7 multi-modal datasets that include 24254 genetic and 230 chemical perturbations from about 6 million cells. The database provides insights through various software-analyzed results, encompassing quality control, denoising, differential expression gene analysis, perturbation function analysis, and correlation characterization between perturbations. All datasets and in-depth analyses are presented in user-friendly, easy-to-browse pages and can be visualized through intuitive tables and various image formats. In summary, PerturBase stands as a pioneering high-content database, intended for searching, visualizing, and analyzing scPerturbation datasets, contributing to an enhanced understanding of perturbation functions and mechanisms. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/578767v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@15bdfcborg.highwire.dtl.DTLVardef@c1be77org.highwire.dtl.DTLVardef@1bf7e32org.highwire.dtl.DTLVardef@f62e8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Scalable single-cell pooled CRISPR screens with conventional knockout vector libraries

Current methods for single-cell RNA profiling of pooled CRISPR screens are limited, either by indirect capture of single guide RNAs (sgRNAs) or by custom modification of plasmid libraries. Here, we present a direct sgRNA capture platform called Native sgRNA Capture and sequencing (NSC-seq) that enables single-cell CRISPR screens using common knockout plasmid libraries, facilitating genotype-phenotype mapping at multiple scales in vitro and in vivo. Additionally, we characterize sgRNA expression in three whole-genome knockout libraries, revealing a substantial subset of truncated (isoform) spacer reads. We provide this dataset as a reference of expressed sgRNA isoforms that may potentially have compromised CRISPR gene editing efficacy and precision.

genomics↗

bioRxiv2024

Mammalian SWI/SNF complex activity regulates POU2F3 and constitutes a targetable dependency in small cell lung cancer

Small cell lung cancers (SCLC) are comprised of heterogeneous subtypes marked by lineage-specific transcription factors, including ASCL1, NEUROD1, and POU2F3. POU2F3-positive SCLC, [~]12% of all cases, are uniquely dependent on POU2F3 itself; as such, approaches to attenuate POU2F3 expression may represent new therapeutic opportunities. Here using genome-scale screens for regulators of POU2F3 expression and SCLC proliferation, we define mSWI/SNF complexes, including non-canonical BAF (ncBAF) complexes, as top dependencies specific to POU2F3-positive SCLC. Notably, clinical-grade pharmacologic mSWI/SNF inhibition attenuates proliferation of all POU2F3-positive SCLCs, while disruption of ncBAF via BRD9 degradation is uniquely effective in pure non-neuroendocrine POU2F3-SCLCs. mSWI/SNF maintains accessibility over gene loci central to POU2F3-mediated gene regulatory networks. Finally, chemical targeting of SMARCA4/2 mSWI/SNF ATPases and BRD9 decrease POU2F3-SCLC tumor growth and increase survival in vivo. Taken together, these results characterize mSWI/SNF-mediated global governance of the POU2F3 oncogenic program and suggest mSWI/SNF inhibition as a therapeutic strategy for SCLC.

cancer biology↗

bioRxiv2024

miR-100 and miR-125b Contribute to Enhanced Growth and Invasiveness

Extracellular communication via the transfer of vesicles and nanoparticles is now recognized to play an important role in tumor microenvironment interactions. Cancer cells upregulate and secrete abundant levels of miR-100 and miR-125b that can alter gene expression by both cell- and non-cell-autonomous mechanisms. We previously showed that these miRNAs activate Wnt signaling in colorectal cancer (CRC) through noncanonical pairing with 5 negative regulators of Wnt signaling. To identify additional targets of miR-100 and miR-125b, we used bioinformatic approaches comparing multiple CRC cell lines, including knockout lines lacking one or both of these miRNAs. From an initial list of 96 potential mRNA targets, we tested 15 targets with 8 showing significant downregulation in the presence of miR-100 and miR-125b. Among these, Cingulin (CGN) and Protein tyrosine phosphatase receptor type-R (PTPRR) are downregulated in multiple cancers, consistent with regulation by increased levels of miR-100 and miR-125b. We also show that increased cellular levels of miR-100 and miR-125b enhance 3D growth and invasiveness in CRC and glioblastoma cell lines. Lastly, we demonstrate that extracellular transfer of miR-100 and miR-125b can silence both reporter and endogenous mRNA targets in recipient cells and also increase the invasiveness of recipient spheroid colonies when grown under 3D conditions in type I collagen.

cancer biology↗

bioRxiv2024

Toward subtask decomposition-based learning and benchmarking for genetic perturbation outcome prediction and beyond

Deciphering cellular responses to genetic perturbations is fundamental for a wide array of biomedical applications, ranging from uncovering gene roles and interactions to unraveling effective therapeutics. Accurately predicting the transcriptional outcomes of genetic perturbations is indispensable for optimizing experimental perturbations and deciphering cellular response mechanisms; however, three scenarios present principal challenges, i.e., predicting single genetic perturbation outcomes, predicting multiple genetic perturbation outcomes and predicting genetic outcomes across cell lines. In this study, we introduce SubTAsk decomposition Modeling for genetic Perturbation prediction (STAMP), a conceptually novel computational strategy for genetic perturbation outcome prediction and downstream applications. STAMP innovatively formulates genetic perturbation prediction as a subtask decomposition (STD) problem by resolving three progressive subtasks in a divide-and-conquer manner, i.e., identifying differentially expressed gene (DEG) postperturbations, determining the regulatory directions of DEGs and finally estimating the magnitudes of gene expression changes. In addition to facilitating perturbation prediction, STAMP also serves as a robust and generalizable benchmark guide for evaluating various genetic perturbation prediction models. As a result, STAMP exhibits a substantial improvement in terms of its genetic perturbation prediction ability over the existing approaches on three subtasks and beyond, including revealing the ability to identify key regulatory genes and pathways on small samples and to reveal precise genetic interactions. Overall, STAMP serves as a fundamentally novel and effective prediction and generalizable benchmarking strategy that can facilitate genetic perturbation prediction, guide the design of perturbation experiments, and broaden the understanding of perturbation mechanisms.

bioinformatics↗

bioRxiv2024

5-Fluorouracil Treatment Represses Pseudouridine-Containing Small RNA Export into Extracellular Vesicles

5-fluorouracil (5-FU) has been used for chemotherapy for colorectal and other cancers for over 50 years. The prevailing view of its mechanism of action is inhibition of thymidine synthase leading to defects in DNA replication and repair. However, 5-FU is also incorporated into RNA causing toxicity due to defects in RNA metabolism, inhibition of pseudouridine modification, and altered ribosome function. Here, we examine the impact of 5-FU on the expression and export of small RNAs (sRNAs) into small extracellular vesicles (sEVs). Moreover, we assess the role of 5-FU in regulation of post-transcriptional sRNA modifications (PTxM) using mass spectrometry approaches. EVs are secreted by all cells and contain a variety of proteins and RNAs that can function in cell-cell communication. PTxMs on cellular and extracellular sRNAs provide yet another layer of gene regulation. We found that treatment of the colorectal cancer (CRC) cell line DLD-1 with 5-FU led to surprising differential export of miRNA snRNA, and snoRNA transcripts. Strikingly, 5-FU treatment significantly decreased the levels of pseudouridine on both cellular and secreted EV sRNAs. In contrast, 5-FU exposure led to increased levels of cellular sRNAs containing a variety of methyl-modified bases. Our results suggest that 5-FU exposure leads to altered expression, base modifications, and mislocalization of EV base-modified sRNAs.

molecular biology↗

bioRxiv2024

An intracranial dissection of human escape circuits

Predators attack at different spatiotemporal scales, spurring prey to elicit escape responses that range from simple motor reactions and strategic planning that involve more complex cognitive processes. Recent work in humans suggests that escape relies on two distinct circuits: the reactive and cognitive fear circuits. However, the specific involvement of these two circuits in different stages of human escaping remains poorly characterized. In this study, we recorded intracranial electroencephalography (iEEG) from epilepsy patients while they performed a modified flight initiation distance (FID) task. We found brain regions in the cognitive fear circuit, including the ventromedial prefrontal cortex and hippocampus, encoded the threat level during the information processing stage. The actual escaping stage, especially under rapid attack, prominently activated areas within the reactive fear circuit, including the midcingulate cortex and amygdala. Furthermore, we observed a negative correlation between the high gamma activity (HGA) of the amygdala and the HGA of the vmPFC and HPC under rapid attacks. This indicates that the amygdala may suppress the activity of the cognitive fear circuit under rapid attacks, enabling the organism to react quickly to ensure survival under the imminent threat. These findings highlight the distinct roles of the reactive and cognitive fear circuits in human escaping and provide accounts for the importance of fear in human survival decisions.

neuroscience↗

bioRxiv2024

Loss of ZNRF3/RNF43 Unleashes EGFR in Cancer

ZNRF3 and RNF43 are closely related transmembrane E3 ubiquitin ligases with significant roles in development and cancer. Conventionally, their biological functions have been associated with regulating WNT signaling receptor ubiquitination and degradation. However, our proteogenomic studies have revealed EGFR as the protein most negatively correlated with ZNRF3/RNF43 mRNA levels in multiple human cancers. Through biochemical investigations, we demonstrate that ZNRF3/RNF43 interact with EGFR via their extracellular domains, leading to EGFR ubiquitination and subsequent degradation facilitated by the E3 ligase RING domain. Overexpression of ZNRF3 reduces EGFR levels and suppresses cancer cell growth in vitro and in vivo, whereas knockout of ZNRF3/RNF43 stimulates cell growth and tumorigenesis through upregulated EGFR signaling. Together, these data highlight ZNRF3 and RNF43 as novel E3 ubiquitin ligases of EGFR and establish the inactivation of ZNRF3/RNF43 as a driver of increased EGFR signaling, ultimately promoting cancer progression. This discovery establishes a connection between two fundamental signaling pathways, EGFR and WNT, at the level of cytoplasmic membrane receptors, uncovering a novel mechanism underlying the frequent co-activation of EGFR and WNT signaling in development and cancer.

cancer biology↗

bioRxiv2023

Deconer: A comprehensive and systematic evaluation toolkit for reference-based cell type deconvolution algorithms using gene expression data

In recent years, computational methods for quantifying cell type proportions from transcription data have gained significant attention, particularly those reference-based methods which have demonstrated high accuracy. However, there is currently a lack of comprehensive evaluation and guidance for available reference-based deconvolution methods in cell proportion deconvolution analysis. In this study, we propose a comprehensive evaluation toolkit, called Deconer, specifically designed for reference-based deconvolution methods. Deconer provides various simulated and real gene expression datasets, including both bulk and single-cell sequencing data, and offers multiple visualization interfaces. By utilizing Deconer, we conducted systematic comparisons of 14 reference-based deconvolution methods from different perspectives, including method robustness, accuracy in deconvolving rare components, signature gene selection, and building external reference. We also performed an in-depth analysis of the application scenarios and challenges in cell proportion deconvolution methods. Finally, we provided constructive suggestions for users in selecting and developing cell proportion deconvolution algorithms. This work presents novel insights to researchers, assisting them in choosing appropriate toolkits, applying solutions in clinical contexts, and advancing the development of deconvolution tools tailored to gene expression data.

bioinformatics↗

bioRxiv2023

Mechanism of action of Buqing Granule against Diabetic retinopathy based on network pharmacology and animal experiments

ObjectiveFor this study, network pharmacology and animal experiments were used together to get a better idea of how BQKL works at the molecular level to treat DR. MethodsIn this study, we obtained the relevant action target information of BQKL from the TCMSP and also combined the GeneCards, OMIM, TTD, and PharmGKB databases with the GEO database to obtain the relevant target information of DR. The intersection of these targets was determined using a Venn diagram to identify the target of action for the treatment of DR with BQKL. The target proteins of BQKL for DR were then uploaded to the String database. The resultant data were imported into Cytoscape 3.9.0 to construct PPI networks and identify key targets of action. The DAVID database was used to do a GO and KEGG pathway enrichment analysis of target genes for treating DR with BQKL. Molecular docking was performed to validate the core action targets with the core compounds of BQKL. In addition, we induced DR production in rats by a high-fat, high-sugar diet and intraperitoneal injection of STZ and validated the results obtained from the network pharmacological analysis by changes in body weight and blood glucose, serum levels of biochemical markers, HE staining, immunohistochemistry, qRT-PCR, and Western blot experiments in rats. ResultsIn this study, quercetin, kaempferol, {beta}-sitosterol, lignanserin, and stigmasterol were identified as the key components, TP53, AKT1, JUN, CASPASE3, MAPK3, and MAPK1 as the key targets, and PI3K-Akt, AGE-RAGE, and MAPK signaling pathways as the main pathways involved. The results of animal experiments showed that BQKL could not only effectively reduce the degree of blood glucose, blood lipids, and oxidative damage in diabetic rats but also slow down the development process of DR. At the same time, it can significantly up-regulate the expression of AKT1, MAPK1, and MAPK3 and down-regulate the expression of CASPASE3, c-JUN, and TP53 in retinal tissue. ConclusionBQKL ameliorates oxidative stress, apoptosis, and inflammation due to hyperglycemia-related stress by regulating key targets of CASPASE3, AKT1, c-JUN, TP53, MAPK1, and MAPK3, thereby delaying the onset and progression of DR.

molecular biology↗

bioRxiv2023

Sequential Transitions of Male Sexual Behaviours Driven by Dual Acetylcholine-Dopamine Dynamics

The neural mechanisms regulating sequential transitions of male sexual behaviors, such as mounting, intromission, and ejaculation, in the brain remain unclear. Here, we report that dopamine (DA) and acetylcholine (ACh) dynamics in the ventral shell of the nucleus accumbens (vsNAc) closely aligns with serial transitions of sexual behaviors in male mice. During intromission, the vsNAc exhibits dual ACh-DA rhythms generated by reciprocal regulation between ACh and DA signaling via nicotinic acetylcholine (nAChR) and dopamine D2 (D2R) receptors. Knockdown of choline acetyl transferase (ChAT) or D2R in the vsNAc diminished the likelihood of intromission and ejaculation. Optogenetic manipulations reveal that DA signaling sustains male sexual behaviors by suppressing activities of D2RvsNAc neurons. Moreover, ACh signaling promotes the initiation of mounting and intromission, but also induces the intromission-to-ejaculation transition by triggering a slowdown of DA rhythm. Therefore, dual ACh-DA dynamics harmonize in the vsNAc to drive sequential transitions of male mating behaviors.

neuroscience↗

bioRxiv2023

Integrated data models on Receptor-Like Kinases for novel domain discovery and functional inference in the plant kingdom

Receptor-like kinases (RLKs) are the largest signal transduction component in plants, determining how different plants adapt to their ecological environment, resulting in plant-specific ecological niches. Current research on RLKs has focused mainly on a small number of typical RLK members of a few model plants. There is an urgent need to study the composition, distribution, and evolution of RLKs at the holistic level to accelerate the understanding of how RLK assists in the ecological adaptation of different plants. In this study, we have collected 528 plant genomes and established an RLK data model, resulting in the discovery and characterization of 524,948 RLK members. Each member is subject to systematic topology classification and coherent gene ID assignment. Using this data model, we discovered two novel families (Xiao and Xiang) of RLKs. Evolutionary analysis of the RLK families indicates that RLCK-XVII and RLCK-XII-2 exist exclusively in dicots, suggesting that the diversification in RLKs between monocots and dicots could cause differences in downstream cytoplasmic responses. We also use interaction proteome to help empower the data mining of inferring new functions of RLK from a global perspective, with the ultimate goal of understanding how RLKs shape the adaptation of different plants to the environment/ecology. The RLK data model compiled herein, together with the annotations and analytic tools, form an integrated data foundation involving multi-omics data and is publicly accessible via the web portal (http://metaRLK.biocloud.top).

bioinformatics↗

bioRxiv2023

ElectroPhysiomeGAN: Generation of Biophysical Neuron Model Parameters from Recorded Electrophysiological Responses

Recent advances in connectomics, biophysics, and neuronal electrophysiology warrant modeling of neurons with further details in both network interaction and cellular dynamics. Such models may be referred to as ElectroPhysiome, as they incorporate the connectome and individual neuron electrophysiology to simulate neuronal activities. The nervous system of C. elegans is considered a viable framework for such ElectroPhysiome studies due to advances in connectomics of its somatic nervous system and electrophysiological recordings of neuron responses. In order to achieve a simulated ElectroPhysiome, the set of parameters involved in modeling individual neurons need to be estimated from electrophysiological recordings. Here, we address this challenge by developing a deep generative estimation method called ElectroPhysiomeGAN (EP-GAN), which once trained, can instantly generate parameters associated with the Hodgkin-Huxley neuron model (HH-model) for multiple neurons with graded potential response. The method combines Generative Adversarial Network (GAN) architecture with Recurrent Neural Network (RNN) Encoder and can generate an extensive number of parameters (>170) given the neurons membrane potential responses and steady-state current profiles. We validate our method by estimating HH-model parameters for 200 simulated neurons with graded membrane potential followed by 9 experimentally recorded neurons (where 6 of them newly recorded) in the nervous system of C. elegans. Comparison of EP-GAN with existing estimation methods shows EP-GAN advantage in the accuracy of estimated parameters and inference speed for both small and large number of parameters being inferred. In addition, the architecture of EP-GAN permits input with arbitrary clamping protocols, allowing inference of parameters even when partial membrane potential and steady-state currents profile are given as inputs. EP-GAN is designed to leverage the generative capability of GAN to align with the dynamical structure of HH-model, and thus able to achieve such performance.

neuroscience↗

bioRxiv2023

Temporal recording of mammalian development and precancer

Key to understanding many biological phenomena is knowing the temporal ordering of cellular events, which often require continuous direct observations [1, 2]. An alternative solution involves the utilization of irreversible genetic changes, such as naturally occurring mutations, to create indelible markers that enables retrospective temporal ordering [3-8]. Using NSC-seq, a newly designed and validated multi-purpose single-cell CRISPR platform, we developed a molecular clock approach to record the timing of cellular events and clonality in vivo, while incorporating assigned cell state and lineage information. Using this approach, we uncovered precise timing of tissue-specific cell expansion during murine embryonic development and identified new intestinal epithelial progenitor states by their unique genetic histories. NSC-seq analysis of murine adenomas and single-cell multi-omic profiling of human precancers as part of the Human Tumor Atlas Network (HTAN), including 116 scRNA-seq datasets and clonal analysis of 418 human polyps, demonstrated the occurrence of polyancestral initiation in 15-30% of colonic precancers, revealing their origins from multiple normal founders. Thus, our multimodal framework augments existing single-cell analyses and lays the foundation for in vivo multimodal recording, enabling the tracking of lineage and temporal events during development and tumorigenesis.

developmental biology↗

bioRxiv2023

Single-cell transcriptomics reveals heterogenous thymic dendritic cell subsets with distinct functions and requirements for thymocyte-regulated crosstalk

Dendritic cells are essential for establishing thymic central tolerance; however, mechanisms supporting their homeostasis and activation remain unresolved. Through single-cell transcriptomics and functional assays, we identify seven thymic conventional dendritic cell (cDC) subsets and discriminate their abilities to present self-antigens and induce regulatory T cells. Mice blocked at different stages of T-cell development reveal that CD4+ single-positive (SP) and CD8SP thymocytes differentially support homeostasis and activation of cDC1s versus cDC2s/plasmacytoid DCs (pDCs), respectively. CD8SPs indirectly support pDC survival and cDC2 thymic immigration, and they induce interferon signaling in cDCs, partly by promoting Type III interferon expression by medullary thymic epithelial cells (mTECs). In contrast, CD4SPs undergo cognate interactions with cDCs, inducing CD40 signaling required for activation of cDC1s. Activated cDC1s make non-redundant contributions to central tolerance. Altogether, this study comprehensively identifies distinct thymic DC subsets and elucidates requirements for crosstalk with thymocyte subsets that support their homeostasis, activation, and function.

immunology↗