Alina Isakova

All Publications

• Connectome-seq: high-throughput mapping of neuronal connectivity at single-synapse resolution via barcode sequencing. Nature methods Chen, D., Isakova, A., Wan, Z., Wagner, M. J., Wu, Y., Zhao, B. S. 2026

  Abstract

  Understanding neuronal connectivity at single-cell resolution remains a fundamental challenge in neuroscience, with current methods particularly limited in mapping long-distance circuits and preserving cell type information. Here we present Connectome-seq, a high-throughput method that combines engineered synaptic proteins, RNA barcoding and parallel single-nucleus and single-synaptosome sequencing to map neuronal connectivity at single-synapse resolution. This adeno-associated virus-based approach enables simultaneous capture of both synaptic connections and molecular identities of connected neurons. We validated this approach in the mouse pontocerebellar circuit, identifying both established and potentially uncharacterized synaptic connections. Through integrated analysis of connectivity and gene expression, we identified molecular markers enriched in connected neurons, suggesting potential molecular determinants of circuit-specific connectivity. By enabling systematic mapping of neuronal connectivity across brain regions with single-cell precision and gene expression information, Connectome-seq provides a scalable platform for comprehensive circuit analysis across different experimental conditions and biological states.

  View details for DOI 10.1038/s41592-026-03026-9

  View details for PubMedID 41820665

  View details for PubMedCentralID 11446842

• Cellular Aging Signatures in the Plasma Proteome Record Human Health and Disease. bioRxiv : the preprint server for biology Ding, D. Y., Bot, V. A., Chen, K. L., Groves, J., Pálovics, R., Masuda, D., Farinas, A., Oh, H. S., Wagner, V., Lu, N., Cruchaga, C., Isakova, A., Schott, J. M., Wyss-Coray, T. 2026

  Abstract

  Aging is asynchronous across cells and organs, but whether plasma proteins can capture cell type-specific aging and predict disease and mortality remains unknown. We developed machine learning models to estimate the biological age of more than 40 distinct cell types-spanning neuronal, immune, glial, endocrine, epithelial, and musculoskeletal origins-using over 7,000 plasma proteins measured in 60,000 individuals across three cohorts, comprising the largest human plasma proteomics aging study to date. Individuals showed heterogeneous aging profiles, with 20-25% exhibiting accelerated aging in a single cell type and 1-3% across ten or more cell types. APOE genotype showed antagonistic aging effects in different cell types: APOE4 carriers exhibited older astrocytes but younger macrophages, while APOE2 carriers showed the inverse. Cellular aging signatures were uniquely associated with disease status and predicted incident disease and mortality over 15 years of follow-up. Amyotrophic lateral sclerosis (ALS) showed the strongest association with skeletal myocyte aging (hazard ratio = 12.7 for extreme accelerated versus youthful aging). In Alzheimer's disease (AD), prevalent cases showed accelerated aging across multiple neural and peripheral cell types, with extreme astrocyte aging conferring AD risk comparable to APOE4 carrier status. Moreover, extreme astrocyte aging increased AD risk in APOE4/4 carriers threefold, while youthful astrocytes strikingly reduced risk. Beyond neurodegeneration, respiratory cell aging identified smokers at 58% higher lung cancer risk, and myeloid aging identified normoglycemic individuals at higher diabetes risk. Both specific cellular vulnerabilities and cumulative aging burden influenced survival, wherein youthful immune or neuronal profiles were protective. A polycellular aging risk score provided robust mortality risk stratification across platforms and cohorts. These findings establish a framework for quantifying biological aging at the cellular resolution using plasma proteomics, revealing heterogeneity in aging trajectories and their impact on disease susceptibility and resilience.

  View details for DOI 10.64898/2026.02.10.704909

  View details for PubMedID 41727111

  View details for PubMedCentralID PMC12919083

• Cell-type resolved protein atlas of brain lysosomes identifies SLC45A1-associated disease as a lysosomal disorder. Cell Ghoochani, A., Heiby, J. C., Rawat, E. S., Medoh, U. N., Di Fraia, D., Dong, W., Gastou, M., Rastogi, M., Hernandez, V., Nyame, K., Laqtom, N. N., Durso, W., Valkova, C., Isakova, A., Kaether, C., Wernig, M., Gomez-Ospina, N., Franke, C., Ori, A., Abu-Remaileh, M. 2026

  Abstract

  Mutations in lysosomal genes cause neurodegeneration and neuronopathic lysosomal storage disorders (LSDs). Despite their essential role in brain homeostasis, the cell-type-specific composition and function of lysosomes remain poorly understood. Here, we report a quantitative protein atlas of lysosomes from mouse neurons, astrocytes, oligodendrocytes, and microglia. We identify dozens of proteins not previously annotated as lysosomal and reveal the diversity of lysosomal composition across brain cell types. Notably, we identified SLC45A1, a gene whose mutations cause a monogenic neurological disease, as a neuron-specific lysosomal protein. Loss of SLC45A1 causes lysosomal dysfunction in vitro and in vivo. SLC45A1 functions as a lysosomal sugar transporter and impacts the stability of the V1 subunits of the vacuolar ATPase (V-ATPase). Consistently, SLC45A1 loss reduces lysosomal V1 subunits, elevates lysosomal pH, and disrupts iron homeostasis, causing mitochondrial dysfunction. Altogether, our work redefines SLC45A1-associated disease as an LSD and establishes a comprehensive map to study lysosome biology at cell-type resolution.

  View details for DOI 10.1016/j.cell.2025.12.012

  View details for PubMedID 41576950

• Biomarkers. Alzheimer's & dementia : the journal of the Alzheimer's Association Groves, J., Oh, H. S., Farinas, A., Bot, V. A., Williams, D. M., Wong, A., Coath, W., Keshavan, A., Moran-Losada, P., James, S. N., Richards, M., Nicholas, J. M., Isakova, A., Wyss-Coray, T., Schott, J. M. 2025; 21 Suppl 2 (Suppl 2): e100995

  Abstract

  Ageing is the strongest risk factor for Alzheimer's disease (AD), but the molecular mechanisms underpinning this link are not established. In an identically aged birth cohort, we: 1) tracked proteomic brain ageing trajectories across the seventh decade; 2) tested associations between ageing trajectories and AD pathology; 3) identified which individual proteins influenced associations.n = 414 from the 1946 British Birth Cohort had plasma assayed with SomaScan 11k v5 at baseline (age=63.4±1.1yr) and follow-up (70.6±0.7yr). Brain age was estimated from a proteomic clock using 202 brain-enriched proteins. 'Brain age gap' (BAG) quantified whether a participant's brain age estimate was older (positive) or younger (negative) than their chronological age. 'BAG change score' [ (BAG at follow-up) - (BAG at baseline) ], reflected accelerating (positive) or decelerating (negative) trajectory. Primary outcomes were amyloid-PET positivity (CL cut-point=11.9) and log-transformed plasma p-tau217 (ALZpath SIMOA). Secondary outcomes in a subset (n = 114, 72.9±0.59yr) were log-transformed CSF p-tau217 and Aβ42/40 ratio. We used linear/logistic regression for continuous/binary outcomes, adjusted for sex. Individual protein analysis used Feature Importance for Biological Ageing (FIBA).BAG at baseline ranged from -9.1 to +17.6yrs. Even greater divergence was seen at follow-up (range: -16.93, 19.16 years). Whilst measurements were correlated (r=0.59), we observed heterogenous brain ageing trajectories across the seventh decade (BAG change score range: -21.3 to 17.3 years, Figure 1). Baseline BAG did not predict biomarker outcomes some ∼10yr later. BAG at follow-up associated with higher plasma p-tau217 (b=0.18, p = 1.4x10-4) but not amyloid-PET status. Higher BAG change score (i.e., accelerating brain ageing) was associated with amyloid-PET positivity (OR 1.89, p = 6.4x10-3, Figure 2), higher plasma p-tau217 (b=0.26, p = 6.2x10-4), higher CSF p-tau217 (b=0.30, p = 9.5x10-3) and lower CSF Aβ 42/40 ratio (b=-0.35, p = 2.2 x10-3). Associations remained significant adjusting for APOE4 status, plasma neurofilament light and GFAP. Influential proteins in associations included Aldolase C, NPTXR and LRRTM2 (Figure 3).An identically-aged population experienced heterogenous trajectories of proteomic brain ageing across their seventh decade. Accelerating brain ageing was predictive of AD biomarker positivity, independent of non-specific measures of neurodegeneration and genetic risk. Future research will explore how implicated proteins may couple brain ageing to AD pathology.

  View details for DOI 10.1002/alz70856_100995

  View details for PubMedID 41442411

  View details for PubMedCentralID PMC12733636

• Spatial and single-cell transcriptomics reveal the reorganization of cerebellar microglia with aging. Cell reports Tsai, A. P., Henze, D. E., Ramirez Lopez, E., Haberberger, J., Dong, C., Lu, N., Atkins, M., Costa, E. K., Farinas, A., Oh, H. S., Moran-Losada, P., Le Guen, Y., Isakova, A., Quake, S. R., Wyss-Coray, T. 2025; 44 (12): 116624

  Abstract

  The cerebellum, essential for motor coordination and increasingly recognized for its role in cognition, is typically considered more resilient to aging and largely spared from hallmark Alzheimer's disease (AD) pathology. However, transcriptomic analyses across fifteen mouse brain regions revealed that the cerebellum undergoes some of the earliest and most pronounced age-related changes. To investigate cerebellar aging, we applied single-nucleus RNA sequencing (RNA-seq), microglial bulk RNA-seq, and multiplexed error-robust fluorescence in situ hybridization (MERFISH)-based spatial transcriptomics. Microglia showed the most prominent changes, including elevated expression of a neuroprotective signature and reduced expression of a lipid-droplet-accumulating signature compared to hippocampal microglia. Spatial analyses further revealed that aged cerebellar microglia were positioned in close proximity to granule cells. Utilizing this relationship, we identified a proximity-dependent transcriptional state defined by the neuron-associated microglial signature. This signature reveals a region-specific microglial adaptation, highlighting cerebellar reorganization with age and potential resilience to AD.

  View details for DOI 10.1016/j.celrep.2025.116624

  View details for PubMedID 41307999

• Benchmarking cell type and gene set annotation by large language models with AnnDictionary. Nature communications Crowley, G., Quake, S. R. 2025; 16 (1): 9511

  Abstract

  We develop an open-source package called 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 use AnnDictionary to perform the first benchmarking study of all major LLMs at de novo cell-type annotation. LLMs vary greatly in absolute agreement with manual annotation based on model size. Inter-LLM agreement also varies 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. Furthermore, we benchmark these LLMs at functional annotation of gene sets, and find that Claude 3.5 Sonnet recovers close matches of functional gene set annotations in over 80% of test sets.

  View details for DOI 10.1038/s41467-025-64511-x

  View details for PubMedID 41152246

  View details for PubMedCentralID 8080633

• Scalable single-cell total RNA-seq reveals non-coding programs in immunity, infection, and brain development. Research square Isakova, A., Quake, S., Liu, D., Cvijovic, I., Sinha, R., Eastman, A., Saul, S., Detweiler, A., Neff, N., Einav, S., Weissman, I. 2025

  Abstract

  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.

  View details for DOI 10.21203/rs.3.rs-7294776/v1

  View details for PubMedID 40964041

  View details for PubMedCentralID PMC12440072

• Connectome-seq: High-throughput Mapping of Neuronal Connectivity at Single-Synapse Resolution via Barcode Sequencing. bioRxiv : the preprint server for biology Chen, D., Isakova, A., Wan, Z. J., Wagner, M. J., Wu, Y., Zhao, B. S. 2025

  Abstract

  Understanding neuronal connectivity at single-cell resolution remains a fundamental challenge in neuroscience, with current methods particularly limited in mapping long-distance circuits and preserving cell type information. Here we present Connectome-seq, a high-throughput method that combines engineered synaptic proteins, RNA barcoding, and parallel single-nucleus and single-synaptosome sequencing to map neuronal connectivity at single-synapse resolution. This AAV-based approach enables simultaneous capture of both synaptic connections and molecular identities of connected neurons. We validated this approach in the mouse pontocerebellar circuit, identifying both established projections and potentially novel synaptic partnerships. Through integrated analysis of connectivity and gene expression, we identified molecular markers enriched in connected neurons, suggesting potential determinants of circuit organization. By enabling systematic mapping of neuronal connectivity across brain regions with single-cell precision and gene expression information, Connectome-seq provides a scalable platform for comprehensive circuit analysis across different experimental conditions and biological states. This advance in connectivity mapping methodology opens new possibilities for understanding circuit organization in complex mammalian brains.

  View details for DOI 10.1101/2025.02.13.638129

  View details for PubMedID 41030982

  View details for PubMedCentralID PMC12478398

• Characterizing expression changes in noncoding RNAs during aging and heterochronic parabiosis across mouse tissues. Nature biotechnology Wagner, V., Kern, F., Hahn, O., Schaum, N., Ludwig, N., Fehlmann, T., Engel, A., Henn, D., Rishik, S., Isakova, A., Tan, M., Sit, R., Neff, N., Hart, M., Meese, E., Quake, S., Wyss-Coray, T., Keller, A. 2023

  Abstract

  Molecular mechanisms of organismal and cell aging remain incompletely understood. We, therefore, generated a body-wide map of noncoding RNA (ncRNA) expression in aging (16 organs at ten timepoints from 1 to 27 months) and rejuvenated mice. We found molecular aging trajectories are largely tissue-specific except for eight broadly deregulated microRNAs (miRNAs). Their individual abundance mirrors their presence in circulating plasma and extracellular vesicles (EVs) whereas tissue-specific ncRNAs were less present. For miR-29c-3p, we observe the largest correlation with aging in solid organs, plasma and EVs. In mice rejuvenated by heterochronic parabiosis, miR-29c-3p was the most prominent miRNA restored to similar levels found in young liver. miR-29c-3p targets the extracellular matrix and secretion pathways, known to be implicated in aging. We provide a map of organism-wide expression of ncRNAs with aging and rejuvenation and identify a set of broadly deregulated miRNAs, which may function as systemic regulators of aging via plasma and EVs.

  View details for DOI 10.1038/s41587-023-01751-6

  View details for PubMedID 37106037

  View details for PubMedCentralID 3836174

• Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy. Nature communications Parikh, V. N., Ioannidis, A. G., Jimenez-Morales, D., Gorzynski, J. E., De Jong, H. N., Liu, X., Roque, J., Cepeda-Espinoza, V. P., Osoegawa, K., Hughes, C., Sutton, S. C., Youlton, N., Joshi, R., Amar, D., Tanigawa, Y., Russo, D., Wong, J., Lauzon, J. T., Edelson, J., Mas Montserrat, D., Kwon, Y., Rubinacci, S., Delaneau, O., Cappello, L., Kim, J., Shoura, M. J., Raja, A. N., Watson, N., Hammond, N., Spiteri, E., Mallempati, K. C., Montero-Martín, G., Christle, J., Kim, J., Kirillova, A., Seo, K., Huang, Y., Zhao, C., Moreno-Grau, S., Hershman, S. G., Dalton, K. P., Zhen, J., Kamm, J., Bhatt, K. D., Isakova, A., Morri, M., Ranganath, T., Blish, C. A., Rogers, A. J., Nadeau, K., Yang, S., Blomkalns, A., O'Hara, R., Neff, N. F., DeBoever, C., Szalma, S., Wheeler, M. T., Gates, C. M., Farh, K., Schroth, G. P., Febbo, P., deSouza, F., Cornejo, O. E., Fernandez-Vina, M., Kistler, A., Palacios, J. A., Pinsky, B. A., Bustamante, C. D., Rivas, M. A., Ashley, E. A. 2022; 13 (1): 5107

  Abstract

  The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

  View details for DOI 10.1038/s41467-022-32397-8

  View details for PubMedID 36042219

• Single-Cell Transcriptomic Atlas of the Human Endometrium During the Menstrual Cycle OBSTETRICAL & GYNECOLOGICAL SURVEY Wang, W., Vilella, F., Alama, P., Moreno, I., Mignardi, M., Isakova, A., Pan, W., Simon, C., Quake, S. R. 2022; 77 (2): 98-99

  View details for DOI 10.1097/OGX.0000000000001009

  View details for Web of Science ID 000754035100016

• Single-cell quantification of a broad RNA spectrum reveals unique noncoding patterns associated with cell types and states. Proceedings of the National Academy of Sciences of the United States of America Isakova, A., Neff, N., Quake, S. R. 1800; 118 (51)

  Abstract

  The ability to interrogate total RNA content of single cells would enable better mapping of the transcriptional logic behind emerging cell types and states. However, current single-cell RNA-sequencing (RNA-seq) methods are unable to simultaneously monitor all forms of RNA transcripts at the single-cell level, and thus deliver only a partial snapshot of the cellular RNAome. Here we describe Smart-seq-total, a method capable of assaying a broad spectrum of coding and noncoding RNA from a single cell. Smart-seq-total does not require splitting the RNA content of a cell and allows the incorporation of unique molecular identifiers into short and long RNA molecules for absolute quantification. It outperforms current poly(A)-independent total RNA-seq protocols by capturing transcripts of a broad size range, thus enabling simultaneous analysis of protein-coding, long-noncoding, microRNA, and other noncoding RNA transcripts from single cells. We used Smart-seq-total to analyze the total RNAome of human primary fibroblasts, HEK293T, and MCF7 cells, as well as that of induced murine embryonic stem cells differentiated into embryoid bodies. By analyzing the coexpression patterns of both noncoding RNA and mRNA from the same cell, we were able to discover new roles of noncoding RNA throughout essential processes, such as cell cycle and lineage commitment during embryonic development. Moreover, we show that independent classes of short-noncoding RNA can be used to determine cell-type identity.

  View details for DOI 10.1073/pnas.2113568118

  View details for PubMedID 34911763

• A mouse tissue atlas of small noncoding RNA. Proceedings of the National Academy of Sciences of the United States of America Isakova, A., Fehlmann, T., Keller, A., Quake, S. R. 2020

  Abstract

  Small noncoding RNAs (ncRNAs) play a vital role in a broad range of biological processes both in health and disease. A comprehensive quantitative reference of small ncRNA expression would significantly advance our understanding of ncRNA roles in shaping tissue functions. Here, we systematically profiled the levels of five ncRNA classes (microRNA [miRNA], small nucleolar RNA [snoRNA], small nuclear RNA [snRNA], small Cajal body-specific RNA [scaRNA], and transfer RNA [tRNA] fragments) across 11 mouse tissues by deep sequencing. Using 14 biological replicates spanning both sexes, we identified that 30% of small ncRNAs are distributed across the body in a tissue-specific manner with some also being sexually dimorphic. We found that some miRNAs are subject to "arm switching" between healthy tissues and that tRNA fragments are retained within tissues in both a gene- and a tissue-specific manner. Out of 11 profiled tissues, we confirmed that brain contains the largest number of unique small ncRNA transcripts, some of which were previously annotated while others are identified in this study. Furthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, we were able to connect identified brain-specific ncRNAs with their cell types of origin. These results yield the most comprehensive characterization of specific and ubiquitous small RNAs in individual murine tissues to date, and we expect that these data will be a resource for the further identification of ncRNAs involved in tissue function in health and dysfunction in disease.

  View details for DOI 10.1073/pnas.2002277117

  View details for PubMedID 32978296

• Single-cell transcriptomic atlas of the human endometrium during the menstrual cycle. Nature medicine Wang, W., Vilella, F., Alama, P., Moreno, I., Mignardi, M., Isakova, A., Pan, W., Simon, C., Quake, S. R. 2020

  Abstract

  In a human menstrual cycle the endometrium undergoes remodeling, shedding and regeneration, all of which are driven by substantial gene expression changes in the underlying cellular hierarchy. Despite its importance in human fertility and regenerative biology, our understanding of this unique type of tissue homeostasis remains rudimentary. We characterized the transcriptomic transformation of human endometrium at single-cell resolution across the menstrual cycle, resolving cellular heterogeneity in multiple dimensions. We profiled the behavior of seven endometrial cell types, including a previously uncharacterized ciliated cell type, during four major phases of endometrial transformation, and found characteristic signatures for each cell type and phase. We discovered that the human window of implantation opens with an abrupt and discontinuous transcriptomic activation in the epithelia, accompanied with a widespread decidualization feature in the stromal fibroblasts. Our study provides a high-resolution molecular and cellular characterization of human endometrial transformation across the menstrual cycle, providing insights into this essential physiological process.

  View details for DOI 10.1038/s41591-020-1040-z

  View details for PubMedID 32929266

• miRSwitch: detecting microRNA arm shift and switch events. Nucleic acids research Kern, F., Amand, J., Senatorov, I., Isakova, A., Backes, C., Meese, E., Keller, A., Fehlmann, T. 2020

  Abstract

  Arm selection, the preferential expression of a 3' or 5' mature microRNA (miRNA), is a highly dynamic and tissue-specific process. Time-dependent expression shifts or switches between the arms are also relevant for human diseases. We present miRSwitch, a web server to facilitate the analysis and interpretation of arm selection events. Our species-independent tool evaluates pre-processed small non-coding RNA sequencing (sncRNA-seq) data, i.e. expression matrices or output files from miRNA quantification tools (miRDeep2, miRMaster, sRNAbench). miRSwitch highlights potential changes in the distribution of mature miRNAs from the same precursor. Group comparisons from one or several user-provided annotations (e.g. disease states) are possible. Results can be dynamically adjusted by choosing from a continuous range of highly specific to very sensitive parameters. Users can compare potential arm shifts in the provided data to a human reference map of pre-computed arm shift frequencies. We created this map from 46 tissues and 30 521 samples. As case studies we present novel arm shift information in a Alzheimer's disease biomarker data set and from a comparison of tissues in Homo sapiens and Mus musculus. In summary, miRSwitch offers a broad range of customized arm switch analyses along with comprehensive visualizations, and is freely available at: https://www.ccb.uni-saarland.de/mirswitch/.

  View details for DOI 10.1093/nar/gkaa323

  View details for PubMedID 32356893

• Single-cell transcriptomes and whole-brain projections of serotonin neurons in the mouse dorsal and median raphe nuclei. eLife Ren, J. n., Isakova, A. n., Friedmann, D. n., Zeng, J. n., Grutzner, S. M., Pun, A. n., Zhao, G. Q., Kolluru, S. S., Wang, R. n., Lin, R. n., Li, P. n., Li, A. n., Raymond, J. L., Luo, Q. n., Luo, M. n., Quake, S. R., Luo, L. n. 2019; 8

  Abstract

  Serotonin neurons of the dorsal and median raphe nuclei (DR, MR) collectively innervate the entire forebrain and midbrain, modulating diverse physiology and behavior. To gain a fundamental understanding of their molecular heterogeneity, we used plate-based single-cell RNA-sequencing to generate a comprehensive dataset comprising eleven transcriptomically distinct serotonin neuron clusters. Systematic in situ hybridization mapped specific clusters to the principal DR, caudal DR, or MR. These transcriptomic clusters differentially express a rich repertoire of neuropeptides, receptors, ion channels, and transcription factors. We generated novel intersectional viral-genetic tools to access specific subpopulations. Whole-brain axonal projection mapping revealed that DR serotonin neurons co-expressing vesicular glutamate transporter-3 preferentially innervate the cortex, whereas those co-expressing thyrotropin-releasing hormone innervate subcortical regions in particular the hypothalamus. Reconstruction of 50 individual DR serotonin neurons revealed diverse and segregated axonal projection patterns at the single-cell level. Together, these results provide a molecular foundation of the heterogenous serotonin neuronal phenotypes.

  View details for DOI 10.7554/eLife.49424

  View details for PubMedID 31647409