Biology subjects

Quake, S. R.

Publications and source records attributed to Quake, S. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Single-cell splice isoform usage reveals distinct axes of cellular identity and senescence

Alternative splicing greatly expands the diversity of gene products encoded by the human genome. Single-cell transcriptomic atlases have characterized human cell types through gene-level expression, but short-read sequencing has limited the ability to resolve full-length isoforms and their functional consequences. Here, we present a cross-tissue single-cell long-read isoform atlas spanning 26 human tissues. We identify hundreds of thousands of novel isoforms along with their cell-type-specific usage, and discover that over one-third of expressed isoforms are absent from existing reference databases. We further demonstrate that isoform usage is a structured, measurable axis of cellular identity that is distinct from gene expression. Applying this framework to cellular senescence, we resolve p16INK4a and p14ARF transcripts from the CDKN2A locus in individual cells and uncover cell-type-dependent isoform remodeling associated with the p16INK4a senescence program. This isoform-resolved single-cell atlas offers a versatile framework to dissect the cellular logic of isoform regulation in senescence and beyond.

genomics↗

bioRxiv2026

Hypothalamic Cell Type Evolution across Vertebrates

The hypothalamus regulates vital functions and is highly conserved among vertebrates occupying diverse niches, but little is known about the evolution of its cell types. Using comparative single-cell transcriptomics across major vertebrate classes, we identified deeply conserved and clade-specific cell types. While homologous cell types express conserved transcription factors and neuropeptides, their regulatory linkages are often rewired across evolution. The paraventricular nucleus largely retains its neuropeptide expression and responds to dehydration with fine cellular resolution from amphibians to mammals, whereas lamina terminalis neurons are specific to terrestrial vertebrates and exhibit gene expression divergence in cell types activated by dehydration and heat. We propose that a conserved set of keystone cell types sustain essential functions across vertebrates, while flexible gene regulatory programs alongside numerous clade-specific cell types offer evolutionary fluidity.

evolutionary biology↗

bioRxiv2026

Site-dependent transcriptomic signatures of endometriosis are conserved across hormonal states

Endometriosis, a chronic condition in which endometrial tissue grows at other sites in the body, produces lesions whose gene expression profiles vary by anatomical location and menstrual cycle stage. The extent to which these location-dependent transcriptional differences persist across hormonal states has remained unknown. Here, we compile a comprehensive single-cell RNA sequencing atlas of 672,051 cells across 112 donors from publicly available sources spanning the eutopic endometrium, menstrual effluent, ovaries, peritoneum, and ectopic endometrium from peritoneal and ovarian sites. By training machine learning classifiers on reference tissue signatures, we identify a subset of cells within ectopic lesions that retain a uterine transcriptomic identity, which we term "core" lesion cells, and which are distinguished from surrounding host tissue populations. We show that transcriptomic differences between core lesion cells at both ectopic sites are robust across all phases of the menstrual cycle and in patients receiving exogenous hormonal therapy, and validate these findings in independent datasets. Cell type- and tissue-specific gene signatures derived from these core populations are sufficient to classify disease status and lesion subtype in independent bulk tissue data across 168 patients. These findings establish that although the core lesion cells maintain elements of eutopic endometrium identity, they also contain information about the anatomical site of the lesion. This anatomic-specificity provides a potential framework for cycle-independent endometriosis diagnosis and subtyping.

bioinformatics↗

bioRxiv2026

Engulfment by brain macrophages in a short-lived vertebrate

Engulfment by macrophages is critical for waste clearance in the vertebrate brain. Understanding clearance mechanisms may open new therapeutic possibilities to counter brain aging and neurodegenerative diseases. However, few in vivo models exist to study engulfment in the brain and characterize this process during aging and across species. Here we present a genetic model for secretion of a fluorescent protein by neurons in the brain of the African turquoise killifish, the shortest-lived vertebrate that can be bred in captivity. We use this model to identify a population of brain macrophages in the killifish responsible for engulfment of material from the brain extracellular space. Intriguingly, many of these cells bear similarities to mammalian border-associated and monocyte-derived macrophages, rare subsets of macrophages in mouse and human brains noted for their engulfment capabilities. We also find that in our model, killifish brain macrophages decline in engulfment capacity with age. This work highlights how vertebrate brain macrophages, particularly those at brain border regions, can play a critical role in clearance and provides an opportunity to test interventions that can boost engulfment by these macrophages to promote brain resilience in old age and disease.

cell biology↗

bioRxiv2026

Reciprocal repulsions enforce heterotypic dendrite segregation in an olfactory circuit

How dendrites of different neurons segregate into discrete spatial domains during neural circuit assembly is poorly understood. Here, using the Drosophila olfactory system, we found that heterophilic interactions between two cell-surface proteins Teneurin-m (Ten-m) and Capricious (Caps) drive dendrite segregation. Ten-m and Caps are expressed in largely inverse patterns across projection neuron (PN) types when PNs are establishing their dendritic territories. Loss of Ten-m in Ten-m+ PNs causes their dendrites to invade Caps+ territories, whereas loss of Caps in Caps+ PNs causes dendrite invasion into Ten-m+ territories. Structure-guided mutations that abolish Ten- m-Caps binding disrupt dendrite segregation, whereas the same mutation on Ten-m preserves its homophilic attraction in a synaptic partner matching assay. These results support a model in which mutual repulsions between two inversely expressed cell-surface proteins drive dendrite segregation into discrete glomerular territories.

neuroscience↗

bioRxiv2026

Survival Benefits Outweigh Germline Competition Costs in Kin Chimeras

Chimerism, the coexistence of genetically distinct cells within an organism, is a widespread phenomenon in nature. In the colonial chordate Botryllus schlosseri, fusion between compatible colonies can lead to stem cell competition with a single genotype taking over the gonadal and/or somatic tissue of the chimera. Over five years, we quantified the frequency and consequences of chimeric formation among 809 larvae, assessing the rates of fusion after natural settlement and its long-term impact on colony survival. We found larvae preferentially settle near kin, facilitating high rates of successful fusion. Fusion was concentrated around the first month of life, boosting survival during this period of high mortality. At all timepoints chimerism significantly increased survival relative to naive and rejected colonies and extended overall lifespan. However, fusion triggered intense internal competition: in all cases tested, a single genotype achieved dominance over both germline and somatic tissues within several weeks post-fusion, regardless of initial genotype contribution. We estimate that among kin, the survival benefits of chimerism outweigh the potential costs of germline loss, extending Hamiltons kin selection framework to colonial marine organisms. In this context, chimerism functions as an adaptive strategy that enhances early survival while enabling selection among competing stem cell lineages.

evolutionary biology↗

bioRxiv2026

Tabula Sapiens reveals the non-coding RNA landscape across 22 human organs and tissues

The biological significance of non-coding RNAs has been increasingly appreciated as their roles in various cellular processes are uncovered. However, single-cell transcriptomic profiling of human samples has focused primarily on protein-coding genes by targeting polyadenylated RNA transcripts, leaving the expression patterns of non-coding RNA underexplored. Here, we expand Tabula Sapiens to the non-coding transcriptome with single-cell and single-nucleus total RNA sequencing across 22 human organs and tissues. By simultaneously profiling both polyadenylated and non-polyadenylated transcripts, the resulting dataset enables joint analysis of the protein-coding and non-coding transcriptomes at single-cell and subcellular resolution. Using these data, we assessed the cell type specificity of non-coding genes and found that a greater proportion of non-coding genes are differentially expressed by single cell types compared to protein-coding genes. We then compared single-cell and single-nucleus data from the same samples to infer subcellular localization patterns, revealing cell type-dependent nuclear and cytoplasmic enrichment of specific non-coding RNAs. Next, we showed that tRNA repertoires are cell type-specific and that this specificity is not simply explained by differences in codon usage across cell types. Finally, we characterized dynamic expression patterns of non-coding RNAs across the cell cycle and senescence-associated cell states, identifying non-coding genes with putative roles in cell division and growth arrest. Our work establishes a resource for investigating the landscape of non-coding RNAs across a diverse set of human tissues and cell types.

cell biology↗

bioRxiv2025

Beyond polyA: scalable single-cell total RNA-seq unifies coding and non-coding transcriptomics

Non-coding RNAs represent a widespread and diverse layer of post-transcriptional regulation across cell types and states, yet much of their diversity remains uncharted at single-cell resolution. This gap stems from the limitations of widely used single-cell RNA-sequencing protocols, which focus on polyadenylated transcripts and miss many short or non-polyadenylated RNAs. Here, we adapted single-cell RNA-sequencing on the 10x Genomics platform to capture a broad complement of coding and non-coding RNAs--including miRNAs, tRNAs, lncRNAs, histone RNAs, and non-adenylated viral transcripts. This approach enabled the discovery of rich, dynamic non-coding RNA programs across immune cells, virally infected hepatocytes, and the developing human brain. In dengue virus-infected hepatocytes, we detect non-adenylated viral transcripts and distinguish active from transcriptionally quiescent infected states, each with distinct host regulatory signatures. In brain tissue, we identify biotype-specific, cell-type- restricted non-coding RNAs, including miRNAs whose expression anticorrelates with predicted targets, consistent with post-transcriptional regulatory relationships. We show that MIR137, one of the strongest GWAS loci associated with schizophrenia and intellectual disability, is expressed specifically in Cajal-Retzius cells, an early-born but transient population that guides subsequent cortical neuron migration. These findings demonstrate the importance of non-coding RNAs in defining cell identity and state, and show how expanded transcriptome coverage can reveal additional layers of gene control--now accessible through practical and scalable single-cell profiling.

genomics↗

bioRxiv2025

Cell-free RNA reveals host and microbial correlates of broadly neutralizing antibody development against HIV

A small number of people living with HIV (PLWH) develop broadly neutralizing antibodies (bNAbs) targeting multiple HIV strains. Although several viral and immune factors contribute to bNAb development, the genetic and environmental factors driving this response remain largely unknown. We performed combined cell-free DNA (cfDNA) and cell-free RNA (cfRNA) sequencing in 42 plasma samples from a longitudinal cohort of 14 PLWH (7 who develop bNAbs and 7 matched controls). This approach enabled us to non-invasively monitor the host transcriptome, viral genetic variation, and microbiome composition during HIV infection, and to identify molecular correlates of bNAb development. We find that development of bNAbs is associated with a transcriptomic signature of early immune activation characterized by elevated levels of MHC class I antigen presentation genes. This signature is independent of viral load or CD4 count and declines over time. In addition to host features, we recovered sufficient viral reads to reconstruct HIV consensus sequences, supporting the utility of cfRNA for viral genotyping. Finally, we also identified an enrichment of several microbial taxa in bNAb producers and increased levels of GB virus C (GBV-C), a non-pathogenic lymphotropic virus. Our findings suggest a distinct early immune activation profile in PLWH who develop bNAbs. More broadly, we show that combined cfDNA/cfRNA sequencing can reveal relationships between a protective immunogenic response to HIV infection, the host immune system, and microbiome, highlighting its potential for biomarker discovery in future vaccine and therapeutic studies. Author SummaryA subset of people living with HIV develop broadly neutralizing antibodies (bNAbs), a phenomenon that remains poorly understood but relevant to vaccine development. We applied combined cell-free RNA and DNA sequencing to 42 longitudinal plasma samples (7 bNAb producers, 7 controls) to monitor the host transcriptome, viral variation, and microbiome composition during bNAb development. Early in infection, bNAb producers showed an MHC class I-linked immune activation signature that declined over time, alongside changes in commensal microbial sequences and increased levels of GB virus C in cfRNA. These findings support the use of cfDNA/cfRNA sequencing for biomarker discovery in HIV research.

genomics↗

bioRxiv2025

A Cross-Species Generative Cell Atlas Across 1.5 Billion Years ofEvolution: The TranscriptFormer Single-cell Model

Single-cell transcriptomics has revolutionized our understanding of cellular diversity, yet our understanding of the transcriptional programs across the tree of life remains limited. Here we present TranscriptFormer, a family of generative foundation models trained on up to 112 million cells spanning 1.53 billion years of evolution across 12 species. By jointly modeling gene identities and expression levels using a novel generative architecture, TranscriptFormer encodes multi-scale biological structure, functioning as a queryable virtual cell atlas. We demonstrate state-of-the-art performance on both in-distribution and out-of-distribution cell type classification, with robust performance even for species separated by over 685 million years of evolution. TranscriptFormer can also perform zero-shot disease state identification in human cells and accurately transfers cell state annotations across species boundaries. As a generative model, TranscriptFormer can be prompted to predict cell type-specific transcription factors and gene-gene interactions that align with independent experimental observations. Developmental trajectories, phylogenetic relationships and cellular hierarchies emerge naturally in TranscriptFormers representations without any explicit training on these annotations. This work establishes a powerful framework for quantitative single-cell analysis, and comparative cellular biology, thus demonstrating that universal principles of cellular organization can be learned and predicted across the tree of life.

systems biology↗

bioRxiv2025

Spatial and molecular insights into microglial roles in cerebellar aging

Aging induces region-specific functional decline across the brain. The cerebellum, critical for motor coordination and cognitive function, undergoes significant structural and functional changes with age. The molecular mechanisms driving cerebellar aging--particularly the role of cerebellar glia, including microglia--remain poorly understood. Here, we used single-nuclei RNA sequencing (snRNA-seq), microglial bulk RNA-seq, and multiplexed error-robust fluorescence in situ hybridization (MERFISH) to characterize transcriptional changes associated with cellular aging in the mouse cerebellum. We discovered that microglia exhibited the most pronounced age-related changes of all cell types and that their transcriptional signatures pointed to enhanced neuroprotective immune activation and reduced lipid-droplet accumulation compared to hippocampal microglia. Furthermore, cerebellar microglia in aged mice, compared to young mice, were found in closer proximity to granule cells. This relationship was characterized using the newly defined neuron-associated microglia score, which captures proximity-dependent transcriptional changes and suggests a novel microglial responsiveness. These findings underscore the unique adaptations of the cerebellum during aging and its potential resilience to Alzheimers disease (AD) related pathology, providing crucial insight into region-specific mechanisms that may shape disease susceptibility.

neuroscience↗

bioRxiv2025

Simultaneous analysis of single-cell gene expression and morphology provides new insight into how microglia change with age

Cellular morphology is intimately connected with function. While the link between morphology and functional states has been studied extensively, the role of subcellular transcript localization in cellular function remains unclear. Here we use microglia, the brains resident macrophages, as a model to dissect the interaction of morphology, transcript localization, and function. Using multiplexed error-robust fluorescence in situ hybridization combined with fluorescent immunohistochemistry, we analyzed transcript distribution and morphology simultaneously in young and aged mouse brains. Our approach revealed how mRNA spatial organization varies across microglial states. We identified distinct transcript localization patterns within microglial processes and uncovered morphological heterogeneity within transcriptomically defined populations. Notably, we found a subpopulation of disease-associated microglia with a ramified morphology (displaying numerous processes), challenging the conventional assumption between morphology and microglial states. Finally, we found that aging not only alters the distribution of compartmentalized mRNAs but also reshapes their colocalization networks, shifting microglial functions from synaptic maintenance and phagocytic processes in younger brains to migration and catabolic pathways in older brains. Our findings highlight the role of subcellular transcript organization in shaping microglial morphology and function, offering new avenues for studying and modulating microglial states in health, disease, and aging.

neuroscience↗

bioRxiv2025

Linking molecular pathways and islet cell dysfunction in human type 1 diabetes

Type 1 diabetes (T1D) is characterized by the autoimmune destruction of most insulin-producing {beta}-cells, along with dysregulated glucagon secretion from pancreatic -cells. We conducted an integrated analysis that combines electrophysiological and transcriptomic profiling, along with machine learning, of islet cells from T1D donors to investigate the mechanisms underlying their dysfunction. Surviving {beta}-cells exhibit altered electrophysiological properties and transcriptomic signatures indicative of increased antigen presentation, metabolic reprogramming, and impaired protein translation. In -cells, we observed hyper-responsiveness and increased exocytosis, which are associated with upregulated immune signaling, disrupted transcription factor localization and lysosome homeostasis, as well as dysregulation of mTORC1 complex signaling. Notably, key genetic risk signals for T1D were enriched in transcripts related to -cell dysfunction, including MHC class I which were closely linked with -cell dysfunction. Our data provide novel insights into the molecular underpinnings of islet cell dysfunction in T1D, highlighting pathways that may be leveraged to preserve residual {beta}-cell function and modulate -cell activity. These findings underscore the complex interplay between immune signaling, metabolic stress, and cellular identity in shaping islet cell phenotypes in T1D. HighlightsO_LISurviving {beta}-cells in T1D show disrupted electrical function linked to metabolic reprogramming and immune stress. C_LIO_LITranscripts associated with -cell dysfunction are enriched in genetic risk alleles for T1D. C_LIO_LIUpregulated MHC class I and impaired nuclear localization of key transcription factors associate with -cell dysfunction in T1D. C_LIO_LIT1D -cells exhibit increased hyper-activity, lysosomal imbalance and impaired mTORC1 signaling, which promotes dysregulated glucagon secretion. C_LI

cell biology↗

bioRxiv2025

Spatially-structured inflammatory response in the presence of a uniform stimulus

Inflammatory responses occur within the complex spatial context of tissues and organs, and many questions remain about how tissue structure and cellular communication shape their spatiotemporal dynamics. Here, we use a multiplexed RNA in situ hybridization approach, together with analytical tools, to study inflammatory gene expression in the larval zebrafish tailfin in response to a bath of lipopolysaccharide (LPS). We use this model system to address whether spatial structure emerges in the tissue response even absent the spatial variation introduced by a pathogen. We find that epithelial cells in the tailfin express several pro-inflammatory genes, and that across these genes, the uniform stimulus triggers a spatially non-uniform response. We use a graph-based spectral decomposition method to analyze its structure, and find that long modes dominate, creating zones of activation. Overall, these zones account for a majority of the variation in gene expression. Our results show that epithelial cells are important producers of pro-inflammatory effector molecules in this system, and that tissue induces spatial correlations even absent a structured input.

systems biology↗

bioRxiv2024

Tabula Sapiens reveals transcription factor expression, senescence effects, and sex-specific features in cell types from 28 human organs and tissues

The Tabula Sapiens is a reference human cell atlas containing single cell transcriptomic data from more than two dozen organs and tissues. Here we report Tabula Sapiens 2.0 which includes data from nine new donors, doubles the number of cells in Tabula Sapiens, and adds four new tissues. This new data includes four donors with multiple organs contributed, thus providing a unique data set in which genetic background, age, and epigenetic effects are controlled for. We analyzed the combined Tabula Sapiens data for expression of transcription factors, thereby providing putative cell type specificity for nearly every human transcription factor and as well as new insights into their regulatory roles. We analyzed the molecular phenotypes of senescent cells across the entire data set, providing new insight into both the universal attributes of senescence as well as those aspects of human senescence that are specific to particular organs and cell-types. Similarly, we analyzed sex-specific gene expression across all of the identified cell types and discovered which cell types and genes have the most distinct sex based gene expression profiles. Finally, to enable accessible analysis of the voluminous medical records of Tabula Sapiens donors, we created a web application powered by a large language model that allows users to ask general questions about the health history of the donors.

cell biology↗

bioRxiv2024

An Atlas of Cellular Archetypes

We sought to discover universal organizing principles behind phenotypic variation within cell types. Pareto optimality describes how trade-offs between optimal solutions account for variation, predicting that the boundary points of a data distribution reflect specialized functions. We hypothesized that Pareto optimality dominates transcriptomic variation across all cell types. We used the Tabula Sapiens atlas of single-cell RNA sequencing across cell types and tissues in the human body to test this hypothesis and discovered that most cell types adhere to this theory. This enabled us to use this principled method to characterize the functions performed by each cell type. These phenotypes are derived from an unbiased approach and do not incorporate ideas from existing biological models or theories, and yet in many cases they recapitulate our understanding of the functions of major cell types. Ultimately, we conclude that multi-objective optimization broadly shapes the observed phenotypic variation within cell types. This finding enables us to write explicit representations of the low-dimensional manifolds on which transcriptomes of single cells reside. This can inform the design of the next generation of virtual cell language models, which aim to statistically learn low-dimensional transcriptomic manifolds.

molecular biology↗

bioRxiv2024

Benchmarking Cell Type Annotation by Large Language Models with AnnDictionary

We developed an open-source package called AnnDictionary (https://github.com/ggit12/anndictionary/) to facilitate the parallel, independent analysis of multiple anndata. AnnDictionary is built on top of LangChain and AnnData and supports all common large language model (LLM) providers. AnnDictionary only requires 1 line of code to configure or switch the LLM backend and it contains numerous multithreading optimizations to support the analysis of many anndata and large anndata. We used AnnDictionary to perform the first benchmarking study of all major LLMs at de novo cell-type annotation. LLMs varied greatly in absolute agreement with manual annotation based on model size. Inter-LLM agreement also varied with model size. We find that LLM annotation of most major cell types to be more than 80-90% accurate, and will maintain a leaderboard of LLM cell type annotation at https://singlecellgpt.com/celltype-annotation-leaderboard. Furthermore, we benchmarked these LLMs at functional annotation of gene sets, and found that Claude 3.5 Sonnet recovers close matches of functional gene set annotations in over 80% of test sets.

bioinformatics↗

bioRxiv2024

Craters on the melanoma surface facilitate tumor-immune interactions and demonstrate pathologic response to checkpoint blockade in humans

Immunotherapy leads to cancer eradication despite the tumors immunosuppressive environment. Here, we used extended long-term in-vivo imaging and high-resolution spatial transcriptomics of endogenous melanoma in zebrafish, and multiplex imaging of human melanoma, to identify domains that facilitate immune response during immunotherapy. We identified crater-shaped pockets at the margins of zebrafish and human melanoma, rich with beta-2 microglobulin (B2M) and antigen recognition molecules. The craters harbor the highest density of CD8+ T cells in the tumor. In zebrafish, CD8+ T cells formed prolonged interactions with melanoma cells within craters, characteristic of antigen recognition. Following immunostimulatory treatment, the craters enlarged and became the major site of activated CD8+ T cell accumulation and tumor killing that was B2M dependent. In humans, craters predicted immune response to ICB therapy, showing response better than high T cell infiltration. This marks craters as potential new diagnostic tool for immunotherapy success and targets to enhance ICB response.

cancer biology↗