Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons

BCOR and ZC3H12A suppress a core stemness program in exhausted CD8+ T cells

In chronic viral infections, sustained CD8+ T cell response relies on TCF1+ precursor-exhausted T cells (TPEX) exhibiting stem-like properties. TPEX self-renew and respond to PD-1 blockade, underscoring their paramount importance. However, strategies for effectively augmenting TPEX remain limited. Here, we demonstrate that ZC3H12A deficiency initiates a stemness program in TPEX but also increases cell death, whereas BCOR deficiency predominantly promotes TPEX proliferation. Consequently, co-targeting of both BCOR and ZC3H12A imparts exceptional stemness and functionality to TPEX, thereby enhancing viral control. Mechanistically, BCOR and ZC3H12A collaboratively suppress a core stemness program in TPEX characterized by heightened expression of ∼216 factors. While TCF1 plays a role, this core stemness program relies on novel factors, including PDZK1IP1, IFIT3, PIM2, LTB, and POU2F2. Crucially, overexpressing POU2F2 robustly boosts TPEX and enhances antiviral immunity. Thus, a core stemness program exists in exhausted T cells, jointly repressed by BCOR and ZC3H12A, robustly controlling TPEX differentiation and providing new targets for addressing T cell exhaustion.

Alternatively spliced mini-exon B in PTPδ regulates excitatory synapses through cell-type-specific trans-synaptic PTPδ-IL1RAP interaction

PTPδ, encoded by PTPRD, is implicated in various neurological, psychiatric, and neurodevelopmental disorders, but the underlying mechanisms remain unclear. PTPδ trans-synaptically interacts with multiple postsynaptic adhesion molecules, which involves its extracellular alternatively spliced mini-exons, meA and meB. While PTPδ-meA functions have been studied in vivo, PTPδ-meB has not been studied. Here, we report that, unlike homozygous PTPδ-meA-mutant mice, homozygous PTPδ-meB-mutant (Ptprd-meB-/-) mice show markedly reduced early postnatal survival. Heterozygous Ptprd-meB+/- male mice show behavioral abnormalities and decreased excitatory synaptic density and transmission in dentate gyrus granule cells (DG-GCs). Proteomic analyses identify decreased postsynaptic density levels of IL1RAP, a known trans-synaptic partner of meB-containing PTPδ. Accordingly, IL1RAP-mutant mice show decreased excitatory synaptic transmission in DG-GCs. Ptprd-meB+/- DG interneurons with minimal IL1RAP expression show increased excitatory synaptic density and transmission. Therefore, PTPδ-meB is important for survival, synaptic, and behavioral phenotypes and regulates excitatory synapses in cell-type-specific and IL1RAP-dependent manners.

RAPID LEAF FALLING 1 facilitates chemical defoliation and mechanical harvesting in cotton

Chemical defoliation stands as the ultimate tool in enabling the mechanical harvest of cotton, offering economic and environmental advantages. However, the underlying molecular mechanism that triggers leaf abscission through defoliant remains unsolved. In this study, we meticulously constructed a transcriptomic atlas through single-nucleus mRNA sequencing (snRNA-seq) of the abscission zone (AZ) from cotton petiole. We identified two newly-formed cell types, abscission cells and protection layer cells in cotton petiole AZ after defoliant treatment. GhRLF1 (RAPID LEAF FALLING 1), as one of the members of the cytokinin oxidase/dehydrogenase (CKX) gene family, was further characterized as a key marker gene unique to the abscission cells following defoliant treatment. Overexpression of GhRLF1 resulted in reduced cytokinin accumulation and accelerated leaf abscission. Conversely, CRISPR/Cas9-mediated loss of GhRLF1 function appeared to delay this process. Its interacting regulators, GhWRKY70, acting as "Pioneer" activator, and GhMYB108, acting as "Successor" activator, orchestrate a sequential modulation of GhWRKY70/GhMYB108-GhRLF1-CTK (cytokinin) within the AZ to regulate cotton leaf abscission. GhRLF1 not only regulates leaf abscission but also reduces cotton yield. Consequently, transgenic lines that exhibit rapid leaf falling and require less defoliant but show unaffected cotton yield were developed for mechanical harvesting. This was achieved using a defoliant-induced petiole-specific promoter, proPER21, to drive GhRLF1 (proPER21::RLF1). This pioneering biotechnology offers a new strategy for the chemical defoliation of machine-harvested cotton, ensuring stable production and reducing leaf debris in harvested cotton, thereby enhancing environmental sustainability.

Integrating physiological and transcriptomic analyses at the single-neuron level

Neurons generate various spike patterns to execute different functions. Understanding how these physiological neuronal spike patterns are related to their molecular characteristics is a long-standing issue in neuroscience. Herein, we review the results of recent studies that have addressed this issue by integrating physiological and transcriptomic techniques. A sequence of experiments, including in vivo recording and/or labeling, brain tissue slicing, cell collection, and transcriptomic analysis, have identified the gene expression profiles of brain neurons at the single-cell level, with activity patterns recorded in living animals. Although these techniques are still in the early stages, this methodological idea is principally applicable to various brain regions and neuronal activity patterns. Accumulating evidence will contribute to a deeper understanding of neuronal characteristics by integrating insights from molecules to cells, circuits, and behaviors.

Deciphering the longitudinal trajectories of glioblastoma ecosystems by integrative single-cell genomics

The evolution of isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) after standard-of-care therapy remains poorly understood. Here we analyzed matched primary and recurrent GBMs from 59 patients using single-nucleus RNA sequencing and bulk DNA sequencing, assessing the longitudinal evolution of the GBM ecosystem across layers of cellular and molecular heterogeneity. The most consistent change was a lower malignant cell fraction at recurrence and a reciprocal increase in glial and neuronal cell types in the tumor microenvironment (TME). The predominant malignant cell state differed between most matched pairs, but no states were exclusive or highly enriched in either time point, nor was there a consistent longitudinal trajectory across the cohort. Nevertheless, specific trajectories were enriched in subsets of patients. Changes in malignant state abundances mirrored changes in TME composition and baseline profiles, reflecting the co-evolution of the GBM ecosystem. Our study provides a blueprint of GBM's diverse longitudinal trajectories and highlights the treatment and TME modifiers that shape them.

The multilayered transcriptional architecture of glioblastoma ecosystems

In isocitrate dehydrogenase wildtype glioblastoma (GBM), cellular heterogeneity across and within tumors may drive therapeutic resistance. Here we analyzed 121 primary and recurrent GBM samples from 59 patients using single-nucleus RNA sequencing and bulk tumor DNA sequencing to characterize GBM transcriptional heterogeneity. First, GBMs can be classified by their broad cellular composition, encompassing malignant and nonmalignant cell types. Second, in each cell type we describe the diversity of cellular states and their pathway activation, particularly an expanded set of malignant cell states, including glial progenitor cell-like, neuronal-like and cilia-like. Third, the remaining variation between GBMs highlights three baseline gene expression programs. These three layers of heterogeneity are interrelated and partially associated with specific genetic aberrations, thereby defining three stereotypic GBM ecosystems. This work provides an unparalleled view of the multilayered transcriptional architecture of GBM. How this architecture evolves during disease progression is addressed in the companion manuscript by Spitzer et al.

Single-cell genomics of the mouse olfactory cortex reveals contrasts with neocortex and ancestral signatures of cell type evolution

Understanding the molecular logic of cortical cell-type diversity can illuminate cortical circuit function and evolution. Here, we performed single-nucleus transcriptome and chromatin accessibility analyses to compare neurons across three- to six-layered cortical areas of adult mice and across tetrapod species. We found that, in contrast to the six-layered neocortex, glutamatergic neurons of the three-layered mouse olfactory (piriform) cortex displayed continuous rather than discrete variation in transcriptomic profiles. Subsets of piriform and neocortical glutamatergic cells with conserved transcriptomic profiles were distinguished by distinct, area-specific epigenetic states. Furthermore, we identified a prominent population of immature neurons in piriform cortex and observed that, in contrast to the neocortex, piriform cortex exhibited divergence between glutamatergic cells in laboratory versus wild-derived mice. Finally, we showed that piriform neurons displayed greater transcriptomic similarity to cortical neurons of turtles, lizards and salamanders than to those of the neocortex. In summary, despite over 200 million years of coevolution alongside the neocortex, olfactory cortex neurons retain molecular signatures of ancestral cortical identity.

Regional and aging-specific cellular architecture of non-human primate brains

BACKGROUND

Deciphering the functionality and dynamics of brain networks across different regions and age groups in non-human primates (NHPs) is crucial for understanding the evolution of human cognition as well as the processes underlying brain pathogenesis. However, systemic delineation of the cellular composition and molecular connections among multiple brain regions and their alterations induced by aging in NHPs remain largely unresolved.

METHODS

In this study, we performed single-nucleus RNA sequencing on 39 samples collected from 10 brain regions of two young and two aged rhesus macaques using the DNBelab C4 system. Validation of protein expression of signatures specific to particular cell types, brain regions, and aging was conducted through a series of immunofluorescence and immunohistochemistry staining experiments. Loss-of-function experiments mediated by short hairpin RNA (shRNA) targeting two age-related genes (i.e., VSNL1 and HPCAL4) were performed in U251 glioma cells to verify their aging effects. Senescence-associated beta-galactosidase (SA-β-gal) staining and quantitative PCR (qPCR) of senescence marker genes were employed to assess cellular senescence in U251 cells.

RESULTS

We have established a large-scale cell atlas encompassing over 330,000 cells for the rhesus macaque brain. Our analysis identified numerous gene expression signatures that were specific to particular cell types, subtypes, brain regions, and aging. These datasets greatly expand our knowledge of primate brain organization and highlight the potential involvement of specific molecular and cellular components in both the regionalization and functional integrity of the brain. Our analysis also disclosed extensive transcriptional alterations and cell-cell connections across brain regions in the aging macaques. Finally, by examining the heritability enrichment of human complex traits and diseases, we determined that neurological traits were significantly enriched in neuronal cells and multiple regions with aging-relevant gene expression signatures, while immune-related traits exhibited pronounced enrichment in microglia.

CONCLUSIONS

Taken together, our study presents a valuable resource for investigating the cellular and molecular architecture of the primate nervous system, thereby expanding our understanding of the mechanisms underlying brain function, aging, and disease.

RyR2-mediated calcium signaling regulates T-cell activation and Th1 differentiation

T helper cell differentiation is one of the key developmental events in the peripheral immune regulations, resulting in better adaptation to the nature of infection and inflammation. While it is known that several factors are involved in this differentiation, including subsets of antigen-presenting cells, cytokine environment, and metabolic activation, how calcium signaling plays a role in this event has remained elusive and sometimes controversial. In this report, we show that ER membrane Ca2+ ion channel ryanodine receptor 2 (RyR2) may be an important regulator in this event. RyR2-deficient T cells show greater retention of Ca2+ in the ER and have reduced SOCE activation, leading a delayed entry of NFAT2 into the nuclei. This delay causes a significant bias toward Th1 both in cytokine profiles and in T-bet expression, likely as a result of increased Il12rb2 and Stat4 expression. Interestingly, such a bias permits better host protection against intracellular Listeria Monocytogenes infection. Our work suggests the possibility that RyR2 may be regulated in T-cell activation for biased Th polarization, which may provide a target for fine-tuning T-cell differentiation in future clinical settings.

A simplified preparation method for single-nucleus RNA-sequencing using long-term frozen brain tumor tissues

Single-cell RNA-sequencing has provided intriguing new insights into research areas such as developmental processes and tumor heterogeneity. Most approaches, however, rely on the availability of fresh surgical specimens, thereby dramatically reducing the ability to profile particularly rare tissue types. Here, we optimized a method to isolate intact nuclei from long-term frozen pediatric glioma tissues. We performed a technical comparison between different single-nucleus RNA-sequencing (snRNA-seq) systems and applied the established nucleus isolation method to analyze frozen primary glioma tissues. The results show that our fast, simple and low-cost nuclear isolation protocol provides intact nuclei, which can be used in both droplet- and plate-based single-cell sequencing platforms - allowing the identification of distinct tumor cell populations and infiltrating microglia. Additional optimization to include shorter RNA fragments in the 3' sequencing library improved gene detection and cell type annotation. Taken together, the method dramatically increases the potential of studying rare tumor entities and is specifically tailored for using frozen brain tumor tissue.

Therapeutic modulation of neurogenesis to improve hippocampal plasticity and cognition in aging and Alzheimer's disease

Alzheimer's disease is characterized by progressive memory loss and cognitive decline. The hippocampal formation is the most vulnerable brain area in Alzheimer's disease. Neurons in layer II of the entorhinal cortex and the CA1 region of the hippocampus are lost at early stages of the disease. A unique feature of the hippocampus is the formation of new neurons that incorporate in the dentate gyrus of the hippocampus. New neurons form synapses with neurons in layer II of the entorhinal cortex and with the CA3 region. Immature and new neurons are characterized by high level of plasticity. They play important roles in learning and memory. Hippocampal neurogenesis is impaired early in mouse models of Alzheimer's disease and in human patients. In fact, neurogenesis is compromised in mild cognitive impairment (MCI), suggesting that rescuing neurogenesis may restore hippocampal plasticity and attenuate neuronal vulnerability and memory loss. This review will discuss the current understanding of therapies that target neurogenesis or modulate it, for the treatment of Alzheimer's disease.

Translatome analysis reveals cellular network in DLK-dependent hippocampal glutamatergic neuron degeneration

The conserved MAP3K12/Dual Leucine Zipper Kinase (DLK) plays versatile roles in neuronal development, axon injury and stress responses, and neurodegeneration, depending on cell-type and cellular contexts. Emerging evidence implicates abnormal DLK signaling in several neurodegenerative diseases. However, our understanding of the DLK-dependent gene network in the central nervous system remains limited. Here, we investigated the roles of DLK in hippocampal glutamatergic neurons using conditional knockout and induced overexpression mice. We found that dorsal CA1 and dentate gyrus neurons are vulnerable to elevated expression of DLK, while CA3 neurons appear less vulnerable. We identified the DLK-dependent translatome that includes conserved molecular signatures and displays cell-type specificity. Increasing DLK signaling is associated with disruptions to microtubules, potentially involving STMN4. Additionally, primary cultured hippocampal neurons expressing different levels of DLK show altered neurite outgrowth, axon specification, and synapse formation. The identification of translational targets of DLK in hippocampal glutamatergic neurons has relevance to our understanding of selective neuron vulnerability under stress and pathological conditions.

Aged hippocampal single-cell atlas screening unveils disrupted neuroglial system in postoperative cognitive impairment

Glia-neuron interaction is a crucial feature in aged hippocampus during the occurrence of postoperative cognitive impairment. However, the regulatory effects of microglia, astrocytes, and oligodendrocytes in this glia-neuron interaction, the potential mechanisms and gene targets are still to be elucidated. Here, single-cell RNA sequencing was performed to detect the perioperative genomic expression characteristics of neuroglial system in the hippocampus of aged mice, and to investigate the potential cross-cellular mechanisms and valuable treatment options for glia-neuron interaction-related cognitive impairment. We found that postoperative neurons and glia cells exhibited protein dysmetabolism and mitochondrial electron misrouting. Impaired autophagy and circadian rhythm worsened microglia activation/neuroinflammation, and exacerbated these metabolic alterations. Reactive microglia also aggravated astrocyte and oligodendrocyte cytotoxicity through the PGD2/DP and complement pathways, altering glutamate level and synaptic function via the "tripartite synapses" model, and affecting neuronal myelination. Ligand-receptor communication also indicated these synaptic and axonal dysfunctions via enhanced MDK and PTN pathways. Additionally, we found that anesthetic dexmedetomidine hold therapeutic potential within the disrupted neuroglial system. It enhanced neuronal metabolic rebalance (Atf3-related) and reduced neuroinflammation from a multicellular perspective, therefore improving postoperative cognitive impairment. Together, our study proposes an aged hippocampal cell atlas and provides insights into the role of disrupted glia-neuron cycle in postoperative cognitive impairment. Our findings also elucidate the therapeutic potential and mechanism of dexmedetomidine intervention.

Persistent dopamine-dependent remodeling of the neural transcriptome in response to pregnancy and postpartum

Pregnancy and postpartum experiences represent transformative physiological states that impose lasting demands on the maternal body and brain, resulting in lifelong neural adaptations. However, the precise molecular mechanisms driving these persistent alterations remain poorly understood. Here, we used brain-wide transcriptomic profiling to define the molecular landscape of parity-induced neural plasticity, identifying the dorsal hippocampus (dHpc) as a key site of transcriptional remodeling. Combining single-cell RNA sequencing with a maternal-pup separation paradigm, we additionally demonstrated that chronic postpartum stress significantly disrupts dHpc adaptations by altering dopamine dynamics, leading to dysregulated transcription, altered cellular plasticity, and impaired behavior. We further established the sufficiency of dopamine modulation in the regulation of these parity-induced adaptations via chemogenetic suppression of dopamine release into dHpc, which recapitulated key transcriptional and behavioral features of parity in virgin females. In sum, our findings establish dopamine as a central regulator of parity-induced neuroadaptations, revealing a fundamental transcriptional mechanism by which female reproductive experiences remodel the maternal brain to sustain long-term behavioral adaptations.

Suprachiasmatic Neuromedin-S Neurons Regulate Arousal

Mammalian circadian rhythms, which orchestrate the daily temporal structure of biological processes, including the sleep-wake cycle, are primarily regulated by the circadian clock in the hypothalamic suprachiasmatic nucleus (SCN). The SCN clock is also implicated in providing an arousal 'signal,' particularly during the wake-maintenance zone (WMZ) of our biological day, essential for sustaining normal levels of wakefulness in the presence of mounting sleep pressure. Here we identify a role for SCN Neuromedin-S (SCN NMS ) neurons in regulating the level of arousal, especially during the WMZ. We used chemogenetic and optogenetic methods to activate SCN NMS neurons in vivo, which potently drove wakefulness. Fiber photometry confirmed the wake-active profile of SCN NM neurons. Genetically ablating SCN NMS neurons disrupted the sleep-wake cycle, reducing wakefulness during the dark period and abolished the circadian rhythm of body temperature. SCN NMS neurons target the dorsomedial hypothalamic nucleus (DMH), and photostimulation of their terminals within the DMH rapidly produces arousal from sleep. Pre-synaptic inputs to SCN NMS neurons were also identified, including regions known to influence SCN clock regulation. Unexpectedly, we discovered strong input from the preoptic area (POA), which itself receives substantial inhibitory input from the DMH, forming a possible arousal-promoting circuit (SCN->DMH->POA->SCN). Finally, we analyzed the transcriptional profile of SCN NMS neurons via single-nuclei RNA-Seq, revealing three distinct subtypes. Our findings link molecularly-defined SCN neurons to sleep-wake patterns, body temperature rhythms, and arousal control.

Significance Statement

Our study's findings provide a cellular and neurobiological understanding of how Neuromedin-S (NMS)-containing SCN neurons contribute to regulating circadian rhythms, sleep-wake patterns, body temperature, and arousal control in mammals. This research illuminates the circuit, cellular, and synaptic mechanisms through which SCN neurons regulate daily cycles of wakefulness and sleep, with implications for understanding and potentially manipulating these processes in health and disease.

Synaptic Vesicle Glycoprotein 2A Knockout in Parvalbumin and Somatostatin Interneurons Drives Seizures in the Postnatal Mouse Brain

Synaptic vesicle glycoprotein 2A (SV2A) is a presynaptic protein targeted by the antiseizure drug levetiracetam. One or more of the three SV2 genes is expressed in all neurons and is essential to normal neurotransmission. Loss of SV2A results in a seizure phenotype in mice and mutations in humans are also linked to congenital seizures. How SV2A action impacts the epileptic phenotype remains unclear, especially among the diverse neuronal populations that regulate network excitability. This study explored how brain structure and function are affected by SV2A conditional knock-out (SV2A-cKO) in specific neural cell subtypes. We show that SV2A-cKO in all neurons of the postnatal brain triggers lethal seizures, suggesting that the seizures observed in earlier knock-out models were not due to aberrant brain development. Similar lethal seizures are detected in mice in which the loss of SV2A is limited to GABAergic neurons, whereas loss in excitatory neurons produces no noticeable phenotype. No apparent gender difference was ever observed. Further investigation revealed that SV2A-cKO in different GABAergic interneuron populations induces seizure, with variable timescales and severity. Most notably SV2A-cKO in parvalbumin interneurons (PV+) leads to lethal seizures in young animals, while SV2A-cKO in somatostatin (SST) inhibitory neurons results in seizures that were scarcely observed only in adult mice. These results support the crucial role SV2A plays in PV and SST interneurons and suggest that the action of levetiracetam may be due largely to effects on a subset of GABAergic interneurons.

Comparative molecular landscapes of immature neurons in the mammalian dentate gyrus across species reveal special features in humans

Immature dentate granule cells (imGCs) arising from adult hippocampal neurogenesis contribute to plasticity, learning and memory, but their evolutionary changes across species and specialized features in humans remain poorly understood. Here we performed machine learning-augmented analysis of published single-cell RNA-sequencing datasets and identified macaque imGCs with transcriptome-wide immature neuronal characteristics. Our cross-species comparisons among humans, monkeys, pigs, and mice showed few shared (such as DPYSL5), but mostly species-specific gene expression in imGCs that converged onto common biological processes regulating neuronal development. We further identified human-specific transcriptomic features of imGCs and demonstrated functional roles of human imGC-enriched expression of a family of proton-transporting vacuolar-type ATPase subtypes in development of imGCs derived from human pluripotent stem cells. Our study reveals divergent gene expression patterns but convergent biological processes in the molecular characteristics of imGCs across species, highlighting the importance of conducting independent molecular and functional analyses for adult neurogenesis in different species.

A platform for multimodal in vivo pooled genetic screens reveals regulators of liver function

Organ function requires coordinated activities of thousands of genes in distinct, spatially organized cell types. Understanding the basis of emergent tissue function requires approaches to dissect the genetic control of diverse cellular and tissue phenotypes in vivo. Here, we develop paired imaging and sequencing methods to construct large-scale, multi-modal genotype-phenotypes maps in tissue with pooled genetic perturbations. Using imaging, we identify genetic perturbations in individual cells while simultaneously measuring their gene expression and subcellular morphology. Using single-cell sequencing, we measure transcriptomic responses to the same genetic perturbations. We apply this approach to study hundreds of genetic perturbations in the mouse liver. Our study reveals regulators of hepatocyte zonation and liver unfolded protein response, as well as distinct pathways that cause hepatocyte steatosis. Our approach enables new ways of interrogating the genetic basis of complex cellular and organismal physiology and provides crucial training data for emerging machine-learning models of cellular function.

Early-age efferocytosis directs macrophage arachidonic acid metabolism for tissue regeneration

In response to organ injury in adults, macrophages often promote scarring, yet during early life, they are required for tissue regeneration. To elucidate the mechanisms underlying age-associated regeneration, we compared the macrophage injury response in newborn versus adult hearts. Single-cell analysis revealed an accumulation of tissue-resident macrophages in neonates that were selectively polarized for apoptotic cell recognition and uptake (efferocytosis). Ablation of the apoptotic cell recognition receptor Mertk in newborns prevented cardiac regeneration. These findings could be attributed to reprogramming of macrophage gene expression that was required for biosynthesis of the eicosanoid thromboxane A2, which unexpectedly activated parenchymal cell proliferation. Markers of thromboxane A2 production were suppressed in adult macrophages after efferocytosis. Moreover, macrophage-neighboring neonatal cardiomyocytes expressed the thromboxane A2 receptor, whose activation induced a metabolic shift that supported cellular proliferation. Our data reveal a fundamental age-defined macrophage response in which lipid mitogens produced during efferocytosis support receptor-mediated tissue regeneration.

Experimental and Computational Methods for Allelic Imbalance Analysis from Single-Nucleus RNA-seq Data

Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq), and introns are under lower purifying selection and thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. To further investigate ASE in the context of human disease, we applied our methods to a Parkinson's disease cohort of 94 individuals and show that ASE analysis had more power than eQTL analysis to identify significant SNP/gene pairs in our direct comparison of the two methods. Overall, we provide an end-to-end experimental and computational approach for future studies.

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Single-cell RNA sequencing in stroke and traumatic brain injury: Current achievements, challenges, and future perspectives on transcriptomic profiling

Single-cell RNA sequencing (scRNA-seq) is a high-throughput transcriptomic approach with the power to identify rare cells, discover new cellular subclusters, and describe novel genes. scRNA-seq can simultaneously reveal dynamic shifts in cellular phenotypes and heterogeneities in cellular subtypes. Since the publication of the first protocol on scRNA-seq in 2009, this evolving technology has continued to improve, through the use of cell-specific barcodes, adoption of droplet-based systems, and development of advanced computational methods. Despite induction of the cellular stress response during the tissue dissociation process, scRNA-seq remains a popular technology, and commercially available scRNA-seq methods have been applied to the brain. Recent advances in spatial transcriptomics now allow the researcher to capture the positional context of transcriptional activity, strengthening our knowledge of cellular organization and cell-cell interactions in spatially intact tissues. A combination of spatial transcriptomic data with proteomic, metabolomic, or chromatin accessibility data is a promising direction for future research. Herein, we provide an overview of the workflow, data analyses methods, and pros and cons of scRNA-seq technology. We also summarize the latest achievements of scRNA-seq in stroke and acute traumatic brain injury, and describe future applications of scRNA-seq and spatial transcriptomics.

Cellular trafficking and fate mapping of cells within the nervous system after in utero hematopoietic cell transplantation

In utero hematopoietic cell transplantation (IUHCT) utilizes fetal immune tolerance to achieve durable chimerism without conditioning or immunosuppression during a unique window in fetal development. Though donor cells have been observed within the nervous system following in utero injection, the timeline and distribution of cellular trafficking across the blood-brain barrier following IUHCT is not well understood. We injected 20 × 106 adult bone marrow mononuclear cells intravenously at gestational age (GA) 12-17 days and found that donor cells were maximally concentrated in the brain with treatment between GA 13-14. Donor cell engraftment persisted within the brain at every timepoint analyzed and concentrated within the hindbrain with significantly more grafted cells than in the forebrain. Additionally, transplanted cells terminally differentiated into various nervous system cellular morphologies and also populated the enteric nervous system. This study is the first to document the timeline and distribution of donor cell trafficking into the immune-protected nervous system and serves as a foundation for the application of IUHCT to treat neurogenetic diseases.

The single-cell opioid responses in the context of HIV (SCORCH) consortium

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

Molecular connectomics reveals a glucagon-like peptide 1-sensitive neural circuit for satiety

Liraglutide and other glucagon-like peptide 1 receptor agonists (GLP-1RAs) are effective weight loss drugs, but how they suppress appetite remains unclear. One potential mechanism is by activating neurons that inhibit the hunger-promoting Agouti-related peptide (AgRP) neurons of the arcuate hypothalamus (Arc). To identify these afferents, we developed a method combining rabies-based connectomics with single-nucleus transcriptomics. Here, we identify at least 21 afferent subtypes of AgRP neurons in the mouse mediobasal and paraventricular hypothalamus, which are predicted by our method. Among these are thyrotropin-releasing hormone (TRH)+ Arc (TRHArc) neurons, inhibitory neurons that express the Glp1r gene and are activated by the GLP-1RA liraglutide. Activating TRHArc neurons inhibits AgRP neurons and feeding, probably in an AgRP neuron-dependent manner. Silencing TRHArc neurons causes overeating and weight gain and attenuates liraglutide's effect on body weight. Our results demonstrate a widely applicable method for molecular connectomics, comprehensively identify local inputs to AgRP neurons and reveal a circuit through which GLP-1RAs suppress appetite.

Decoding neuronal genes in stroke-induced pain: insights from single-nucleus sequencing in mice

BACKGROUND

The role of neurons in central post-stroke pain (CPSP) following thalamic hemorrhage remains unclear. This study aimed to identify key genes associated with post-thalamic hemorrhage pain and to explore their functions in neurons. Single-nucleus RNA sequencing (snRNA-seq) data from a mouse model was used for this analysis.

METHODS

First, snRNA-seq data were analyzed to identify cell types associated with CPSP induced by thalamic hemorrhage. Differentially expressed genes (DEGs) in neurons were then screened between control and model groups, followed by the construction of a protein-protein interaction (PPI) network for the DEGs. CytoNCA was used to assess node connectivity in the PPI network, and the top 5 key genes were identified. Subsequently, transcription factor (TF)-mRNA and miRNA-mRNA networks were constructed, and small-molecule drugs potentially targeting these key genes were predicted. Finally, the expression differences of key genes in neurons were compared between the model and control groups.

RESULTS

A total of 13 cell clusters were identified, categorized into 8 cell types: T cells, endothelial cells, monocytes, neural progenitor cells (NPCs), microglia, astrocytes, neurons, and oligodendrocytes. A total of 228 DEGs were detected in neurons when comparing the model group with the control group. The PPI network of the DEGs consisted of 126 nodes and 209 edges, identifying the top 5 key genes: Dlgap1, Cacna1c, Gria2, Hsp90ab1, and Gapdh. The miRNA-mRNA network included 68 miRNA-mRNA pairs, 62 miRNAs, and 5 mRNAs, while the TF-mRNA network consisted of 66 TF-mRNA pairs, 56 TFs, and 5 mRNAs. Drug prediction identified 110 small-molecule drugs (e.g., purpurogallin, nifedipine, and novobiocin) potentially targeting these key genes. Additionally, Cacna1c were significantly upregulated in model mice.

CONCLUSION

This study identified the role of key genes in thalamic hemorrhage-induced CPSP through snRNA-seq, providing a scientific basis for further exploration of the molecular mechanisms underlying CPSP.

Single-Nucleus RNA Sequencing Reveals the Transcriptome Profiling of Ovarian Cells in Adolescent Cyprinus carpio

The common carp (Cyprinus carpio) is a crucial freshwater species cultivated worldwide for food consumption. Female carp have better growth performance than males, which fascinates scholars to uncover the mechanism of gonadal differentiation and produce mono-sex populations. However, the mechanism of ovarian development at single-cell resolution is limited. Here, we conducted single-nucleus RNA sequencing in adolescent common carp ovaries. Our study obtained transcriptional profiles of 13,155 nuclei and revealed 13 distinct cell clusters in the ovaries, including three subtypes of germ cells and four subtypes of granulosa cells. We subsequently performed pseudotime trajectory analysis to delineate potential mechanisms underlying the development of germ cells and granulosa cells. We identified 1250 dynamic expression genes in germ cells and 1815 in granulosa cells (q-value < 0.01), including zp3, eif4a2 and aspm in germ cells and fshr and esr1 in granulosa cells. The functional annotation showed that dynamic expression genes in germ cells were involved in sperm-egg recognition and some terms related to meiosis, such as sister chromatid segregation and homologous recombination. Genes expressed dynamically in granulosa cells were related to the TGF-β signaling pathway, response to gonadotropin, and development of primary female sexual characteristics. In addition, the dynamic genes expressed in granulosa cells might relate to the complex communication between different cell types. In summary, our study provided a transcriptome profile of common carp ovaries at single-nucleus resolution, and we further revealed the potential cell type-specific mechanisms underlying oogenesis and the differentiation of granulosa cells, which will facilitate breeding all-female common carp populations.

Beyond the Heartbeat: Single-Cell Omics Redefining Cardiovascular Research

PURPOSE OF REVIEW

This review aims to explore recent advances in single-cell omics techniques as applied to various regions of the human heart, illuminating cellular diversity, regulatory networks, and disease mechanisms. We examine the contributions of single-cell transcriptomics, genomics, proteomics, epigenomics, and spatial transcriptomics in unraveling the complexity of cardiac tissues.

RECENT FINDINGS

Recent strides in single-cell omics technologies have revolutionized our understanding of the heart's cellular composition, cell type heterogeneity, and molecular dynamics. These advancements have elucidated pathological conditions as well as the cellular landscape in heart development. We highlight emerging applications of integrated single-cell omics, particularly for cardiac regeneration, disease modeling, and precision medicine, and emphasize the transformative potential of these technologies to advance cardiovascular research and clinical practice.

NBAtlas: A harmonized single-cell transcriptomic reference atlas of human neuroblastoma tumors

Neuroblastoma, a rare embryonic tumor arising from neural crest development, is responsible for 15% of pediatric cancer-related deaths. Recently, several single-cell transcriptome studies were performed on neuroblastoma patient samples to investigate the cell of origin and tumor heterogeneity. However, these individual studies involved a small number of tumors and cells, limiting the conclusions that could be drawn. To overcome this limitation, we integrated seven single-cell or single-nucleus datasets into a harmonized cell atlas covering 362,991 cells across 61 patients. We use this atlas to decipher the transcriptional landscape of neuroblastoma at single-cell resolution, revealing associations between transcriptomic profiles and clinical outcomes within the tumor compartment. In addition, we characterize the complex immune-cell landscape and uncover considerable heterogeneity among tumor-associated macrophages. Finally, we showcase the utility of our atlas as a resource by expanding it with additional data and using it as a reference for data-driven cell-type annotation.

Implementing distinct spatial proteogenomic technologies: opportunities, challenges, and key considerations

Our ability to understand the cellular complexity of tissues has been revolutionized in recent years with significant advances in proteogenomic technologies including those enabling spatial analyses. This has led to numerous consortium efforts, such as the human cell atlas initiative which aims to profile all cells in the human body in healthy and diseased contexts. The availability of such information will subsequently lead to the identification of novel biomarkers of disease and of course therapeutic avenues. However, before such an atlas of any given healthy or diseased tissue can be generated, several factors should be considered including which specific techniques are optimal for the biological question at hand. In this review, we aim to highlight some of the considerations we believe to be important in the experimental design and analysis process, with the goal of helping to navigate the rapidly changing landscape of technologies available.

Septo-dentate gyrus cholinergic circuits modulate function and morphogenesis of adult neural stem cells through granule cell intermediaries

Cholinergic neurons in the basal forebrain play a crucial role in regulating adult hippocampal neurogenesis (AHN). However, the circuit and molecular mechanisms underlying cholinergic modulation of AHN, especially the initial stages of this process related to the generation of newborn progeny from quiescent radial neural stem cells (rNSCs), remain unclear. Here, we report that stimulation of the cholinergic circuits projected from the diagonal band of Broca (DB) to the dentate gyrus (DG) neurogenic niche promotes proliferation and morphological development of rNSCs, resulting in increased neural stem/progenitor pool and rNSCs with longer radial processes and larger busy heads. Interestingly, DG granule cells (GCs) are required for DB-DG cholinergic circuit-dependent modulation of proliferation and morphogenesis of rNSCs. Furthermore, single-nucleus RNA sequencing of DG reveals cell type-specific transcriptional changes in response to cholinergic circuit stimulation, with GCs (among all the DG niche cells) exhibiting the most extensive transcriptional changes. Our findings shed light on how the DB-DG cholinergic circuits orchestrate the key niche components to support neurogenic function and morphogenesis of rNSCs at the circuit and molecular levels.

Scywalker: scalable end-to-end data analysis workflow for long-read single-cell transcriptome sequencing

MOTIVATION

Existing nanopore single-cell data analysis tools showed severe limitations in handling current data sizes.

RESULTS

We introduce scywalker, an innovative and scalable package developed to comprehensively analyze long-read sequencing data of full-length single-cell or single-nuclei cDNA. We developed novel scalable methods for cell barcode demultiplexing and single-cell isoform calling and quantification and incorporated these in an easily deployable package. Scywalker streamlines the entire analysis process, from sequenced fragments in FASTQ format to demultiplexed pseudobulk isoform counts, into a single command suitable for execution on either server or cluster. Scywalker includes data quality control, cell type identification, and an interactive report. Assessment of datasets from the human brain, Arabidopsis leaves, and previously benchmarked data from mixed cell lines demonstrate excellent correlation with short-read analyses at both the cell-barcoding and gene quantification levels. At the isoform level, we show that scywalker facilitates the direct identification of cell-type-specific expression of novel isoforms.

AVAILABILITY AND IMPLEMENTATION

Scywalker is available on github.com/derijkp/scywalker under the GNU General Public License (GPL) and at https://zenodo.org/records/13359438/files/scywalker-0.108.0-Linux-x86_64.tar.gz.

Cellular communities reveal trajectories of brain ageing and Alzheimer's disease

Alzheimer's disease (AD) has recently been associated with diverse cell states1-11, yet when and how these states affect the onset of AD remains unclear. Here we used a data-driven approach to reconstruct the dynamics of the brain's cellular environment and identified a trajectory leading to AD that is distinct from other ageing-related effects. First, we built a comprehensive cell atlas of the aged prefrontal cortex from 1.65 million single-nucleus RNA-sequencing profiles sampled from 437 older individuals, and identified specific glial and neuronal subpopulations associated with AD-related traits. Causal modelling then prioritized two distinct lipid-associated microglial subpopulations-one drives amyloid-β proteinopathy while the other mediates the effect of amyloid-β on tau proteinopathy-as well as an astrocyte subpopulation that mediates the effect of tau on cognitive decline. To model the dynamics of cellular environments, we devised the BEYOND methodology, which identified two distinct trajectories of brain ageing, each defined by coordinated progressive changes in certain cellular communities that lead to (1) AD dementia or (2) alternative brain ageing. Thus, we provide a cellular foundation for a new perspective on AD pathophysiology that informs personalized therapeutic development, targeting different cellular communities for individuals on the path to AD or to alternative brain ageing.

A brain cell atlas integrating single-cell transcriptomes across human brain regions

While single-cell technologies have greatly advanced our comprehension of human brain cell types and functions, studies including large numbers of donors and multiple brain regions are needed to extend our understanding of brain cell heterogeneity. Integrating atlas-level single-cell data presents a chance to reveal rare cell types and cellular heterogeneity across brain regions. Here we present the Brain Cell Atlas, a comprehensive reference atlas of brain cells, by assembling single-cell data from 70 human and 103 mouse studies of the brain throughout major developmental stages across brain regions, covering over 26.3 million cells or nuclei from both healthy and diseased tissues. Using machine-learning based algorithms, the Brain Cell Atlas provides a consensus cell type annotation, and it showcases the identification of putative neural progenitor cells and a cell subpopulation of PCDH9high microglia in the human brain. We demonstrate the gene regulatory difference of PCDH9high microglia between hippocampus and prefrontal cortex and elucidate the cell-cell communication network. The Brain Cell Atlas presents an atlas-level integrative resource for comparing brain cells in different environments and conditions within the Human Cell Atlas.

STIE: Single-cell level deconvolution, convolution, and clustering in in situ capturing-based spatial transcriptomics

In in situ capturing-based spatial transcriptomics, spots of the same size and printed at fixed locations cannot precisely capture the randomly-located single cells, therefore inherently failing to profile transcriptome at the single-cell level. To this end, we present STIE, an Expectation Maximization algorithm that aligns the spatial transcriptome to its matched histology image-based nuclear morphology and recovers missing cells from ~70% gap area, thereby achieving the real single-cell level and whole-slide scale deconvolution, convolution, and clustering for both low- and high-resolution spots. STIE characterizes cell-type-specific gene expression and demonstrates outperforming concordance with true cell-type-specific transcriptomic signatures than the other spot- and subspot-level methods. Furthermore, STIE reveals the single-cell level insights, for instance, lower actual spot resolution than its reported spot size, unbiased evaluation of cell type colocalization, superior power of high-resolution spot in distinguishing nuanced cell types, and spatial cell-cell interactions at the single-cell level other than spot level.

Spatial multi-omics analysis of the microenvironment in traumatic spinal cord injury: a narrative review

Traumatic spinal cord injury (tSCI) is a severe injury to the central nervous system that is categorized into primary and secondary injuries. Among them, the local microenvironmental imbalance in the spinal cord caused by secondary spinal cord injury includes accumulation of cytokines and chemokines, reduced angiogenesis, dysregulation of cellular energy metabolism, and dysfunction of immune cells at the site of injury, which severely impedes neurological recovery from spinal cord injury (SCI). In recent years, single-cell techniques have revealed the heterogeneity of multiple immune cells at the genomic, transcriptomic, proteomic, and metabolomic levels after tSCI, further deepening our understanding of the mechanisms underlying tSCI. However, spatial information about the tSCI microenvironment, such as cell location and cell-cell interactions, is lost in these approaches. The application of spatial multi-omics technology can solve this problem by combining the data obtained from immunohistochemistry and multiparametric analysis to reveal the changes in the microenvironment at different times of secondary injury after SCI. In this review, we systematically review the progress of spatial multi-omics techniques in the study of the microenvironment after SCI, including changes in the immune microenvironment and discuss potential future therapeutic strategies.

Host-pathogen interactions in the Plasmodium-infected mouse liver at spatial and single-cell resolution

Upon infecting its vertebrate host, the malaria parasite initially invades the liver where it undergoes massive replication, whilst remaining clinically silent. The coordination of host responses across the complex liver tissue during malaria infection remains unexplored. Here, we perform spatial transcriptomics in combination with single-nuclei RNA sequencing over multiple time points to delineate host-pathogen interactions across Plasmodium berghei-infected liver tissues. Our data reveals significant changes in spatial gene expression in the malaria-infected tissues. These include changes related to lipid metabolism in the proximity to sites of Plasmodium infection, distinct inflammation programs between lobular zones, and regions with enrichment of different inflammatory cells, which we term 'inflammatory hotspots'. We also observe significant upregulation of genes involved in inflammation in the control liver tissues of mice injected with mosquito salivary gland components. However, this response is considerably delayed compared to that observed in P. berghei-infected mice. Our study establishes a benchmark for investigating transcriptome changes during host-parasite interactions in tissues, it provides informative insights regarding in vivo study design linked to infection and offers a useful tool for the discovery and validation of de novo intervention strategies aimed at malaria liver stage infection.

A Single-Cell Transcriptomic Analysis of the Mouse Hippocampus After Voluntary Exercise

Exercise has been recognized as a beneficial factor for cognitive health, particularly in relation to the hippocampus, a vital brain region responsible for learning and memory. Previous research has demonstrated that exercise-mediated improvement of learning and memory in humans and rodents correlates with increased adult neurogenesis and processes related to enhanced synaptic plasticity. Nevertheless, the underlying molecular mechanisms are not fully understood. With the aim to further elucidate these mechanisms, we provide a comprehensive dataset of the mouse hippocampal transcriptome at the single-cell level after 4 weeks of voluntary wheel-running. Our analysis provides a number of interesting observations. For example, the results suggest that exercise affects adult neurogenesis by accelerating the maturation of a subpopulation of Prdm16-expressing neurons. Moreover, we uncover the existence of an intricate crosstalk among multiple vital signaling pathways such as NF-κB, Wnt/β-catenin, Notch, and retinoic acid (RA) pathways altered upon exercise in a specific cluster of excitatory neurons within the Cornu Ammonis (CA) region of the hippocampus. In conclusion, our study provides an important resource dataset and sheds further light on the molecular changes induced by exercise in the hippocampus. These findings have implications for developing targeted interventions aimed at optimizing cognitive health and preventing age-related cognitive decline.

Neuronal A2A receptor exacerbates synapse loss and memory deficits in APP/PS1 mice

Early pathological upregulation of adenosine A2A receptors (A2ARs), one of the caffeine targets, by neurons is thought to be involved in the development of synaptic and memory deficits in Alzheimer's disease (AD) but mechanisms remain ill-defined. To tackle this question, we promoted a neuronal upregulation of A2AR in the hippocampus of APP/PS1 mice developing AD-like amyloidogenesis. Our findings revealed that the early upregulation of A2AR in the presence of an ongoing amyloid pathology exacerbates memory impairments of APP/PS1 mice. These behavioural changes were not linked to major change in the development of amyloid pathology but rather associated with increased phosphorylated tau at neuritic plaques. Moreover, proteomic and transcriptomic analyses coupled with quantitative immunofluorescence studies indicated that neuronal upregulation of the receptor promoted both neuronal and non-neuronal autonomous alterations, i.e. enhanced neuroinflammatory response but also loss of excitatory synapses and impaired neuronal mitochondrial function, presumably accounting for the detrimental effect on memory. Overall, our results provide compelling evidence that neuronal A2AR dysfunction, as seen in the brain of patients, contributes to amyloid-related pathogenesis and underscores the potential of A2AR as a relevant therapeutic target for mitigating cognitive impairments in this neurodegenerative disorder.

Molecular Organization of Autonomic, Respiratory, and Spinally-Projecting Neurons in the Mouse Ventrolateral Medulla

The ventrolateral medulla (VLM) is a crucial region in the brain for visceral and somatic control, serving as a significant source of synaptic input to the spinal cord. Experimental studies have shown that gene expression in individual VLM neurons is predictive of their function. However, the molecular and cellular organization of the VLM has remained uncertain. This study aimed to create a comprehensive dataset of VLM cells using single-cell RNA sequencing in male and female mice. The dataset was enriched with targeted sequencing of spinally-projecting and adrenergic/noradrenergic VLM neurons. Based on differentially expressed genes, the resulting dataset of 114,805 VLM cells identifies 23 subtypes of neurons, excluding those in the inferior olive, and five subtypes of astrocytes. Spinally-projecting neurons were found to be abundant in seven subtypes of neurons, which were validated through in situ hybridization. These subtypes included adrenergic/noradrenergic neurons, serotonergic neurons, and neurons expressing gene markers associated with premotor neurons in the ventromedial medulla. Further analysis of adrenergic/noradrenergic neurons and serotonergic neurons identified nine and six subtypes, respectively, within each class of monoaminergic neurons. Marker genes that identify the neural network responsible for breathing were concentrated in two subtypes of neurons, delineated from each other by markers for excitatory and inhibitory neurons. These datasets are available for public download and for analysis with a user-friendly interface. Collectively, this study provides a fine-scale molecular identification of cells in the VLM, forming the foundation for a better understanding of the VLM's role in vital functions and motor control.

Transcriptional dynamics orchestrating the development and integration of neurons born in the adult hippocampus

The adult hippocampus generates new granule cells (aGCs) with functional capabilities that convey unique forms of plasticity to the preexisting circuits. While early differentiation of adult radial glia-like cells (RGLs) has been studied extensively, the molecular mechanisms guiding the maturation of postmitotic neurons remain unknown. Here, we used a precise birthdating strategy to study aGC differentiation using single-nuclei RNA sequencing. Transcriptional profiling revealed a continuous trajectory from RGLs to mature aGCs, with multiple immature stages bearing increasing levels of effector genes supporting growth, excitability, and synaptogenesis. Analysis of differential gene expression, pseudo-time trajectory, and transcription factors (TFs) revealed critical transitions defining four cellular states: quiescent RGLs, proliferative progenitors, immature aGCs, and mature aGCs. Becoming mature aGCs involved a transcriptional switch that shuts down pathways promoting cell growth, such SoxC TFs, to activate programs that likely control neuronal homeostasis. aGCs overexpressing Sox4 or Sox11 remained immature. Our results unveil precise molecular mechanisms driving adult RGLs through the pathway of neuronal differentiation.

sNucConv: A bulk RNA-seq deconvolution method trained on single-nucleus RNA-seq data to estimate cell-type composition of human adipose tissues

Deconvolution algorithms mostly rely on single-cell RNA-sequencing (scRNA-seq) data applied onto bulk RNA-sequencing (bulk RNA-seq) to estimate tissues' cell-type composition, with performance accuracy validated on deposited databases. Adipose tissues' cellular composition is highly variable, and adipocytes can only be captured by single-nucleus RNA-sequencing (snRNA-seq). Here we report the development of sNucConv, a Scaden deep-learning-based deconvolution tool, trained using 5 hSAT and 7 hVAT snRNA-seq-based data corrected by (i) snRNA-seq/bulk RNA-seq highly correlated genes and (ii) individual cell-type regression models. Applying sNucConv on our bulk RNA-seq data resulted in cell-type proportion estimation of 15 and 13 cell types, with accuracy of R = 0.93 (range: 0.76-0.97) and R = 0.95 (range: 0.92-0.98) for hVAT and hSAT, respectively. This performance level was further validated on an independent set of samples (5 hSAT; 5 hVAT). The resulting model was depot specific, reflecting depot differences in gene expression patterns. Jointly, sNucConv provides proof-of-concept for producing validated deconvolution models for tissues un-amenable to scRNA-seq.

Molecular Connectomics Reveals a Glucagon-Like Peptide 1 Sensitive Neural Circuit for Satiety

Liraglutide and other agonists of the glucagon-like peptide 1 receptor (GLP-1RAs) are effective weight loss drugs, but how they suppress appetite remains unclear. One potential mechanism is by activating neurons which inhibit hunger-promoting Agouti-related peptide (AgRP) neurons of the arcuate hypothalamus (Arc). To identify these afferents, we developed a method combining rabies-based connectomics with single-nuclei transcriptomics. Applying this method to AgRP neurons predicted at least 21 afferent subtypes in the mouse mediobasal and paraventricular hypothalamus. Among these are Trh+ Arc neurons, inhibitory neurons which express the Glp1r gene and are activated by the GLP-1RA liraglutide. Activating Trh+ Arc neurons inhibits AgRP neurons and feeding in an AgRP neuron-dependent manner. Silencing Trh+ Arc neurons causes over-eating and weight gain and attenuates liraglutide's effect on body weight. Our results demonstrate a widely applicable method for molecular connectomics, comprehensively identify local inputs to AgRP neurons, and reveal a circuit through which GLP-1RAs suppress appetite.

Transcriptomic Approaches to Cardiomyocyte-Biomaterial Interactions: A Review

Biomaterials, essential for supporting, enhancing, and repairing damaged tissues, play a critical role in various medical applications. This Review focuses on the interaction of biomaterials and cardiomyocytes, emphasizing the unique significance of transcriptomic approaches in understanding their interactions, which are pivotal in cardiac bioengineering and regenerative medicine. Transcriptomic approaches serve as powerful tools to investigate how cardiomyocytes respond to biomaterials, shedding light on the gene expression patterns, regulatory pathways, and cellular processes involved in these interactions. Emerging technologies such as bulk RNA-seq, single-cell RNA-seq, single-nucleus RNA-seq, and spatial transcriptomics offer promising avenues for more precise and in-depth investigations. Longitudinal studies, pathway analyses, and machine learning techniques further improve the ability to explore the complex regulatory mechanisms involved. This review also discusses the challenges and opportunities of utilizing transcriptomic techniques in cardiomyocyte-biomaterial research. Although there are ongoing challenges such as costs, cell size limitation, sample differences, and complex analytical process, there exist exciting prospects in comprehensive gene expression analyses, biomaterial design, cardiac disease treatment, and drug testing. These multimodal methodologies have the capacity to deepen our understanding of the intricate interaction network between cardiomyocytes and biomaterials, potentially revolutionizing cardiac research with the aim of promoting heart health, and they are also promising for studying interactions between biomaterials and other cell types.

Single-cell nascent RNA sequencing unveils coordinated global transcription

Transcription is the primary regulatory step in gene expression. Divergent transcription initiation from promoters and enhancers produces stable RNAs from genes and unstable RNAs from enhancers1,2. Nascent RNA capture and sequencing assays simultaneously measure gene and enhancer activity in cell populations3. However, fundamental questions about the temporal regulation of transcription and enhancer-gene coordination remain unanswered, primarily because of the absence of a single-cell perspective on active transcription. In this study, we present scGRO-seq-a new single-cell nascent RNA sequencing assay that uses click chemistry-and unveil coordinated transcription throughout the genome. We demonstrate the episodic nature of transcription and the co-transcription of functionally related genes. scGRO-seq can estimate burst size and frequency by directly quantifying transcribing RNA polymerases in individual cells and can leverage replication-dependent non-polyadenylated histone gene transcription to elucidate cell cycle dynamics. The single-nucleotide spatial and temporal resolution of scGRO-seq enables the identification of networks of enhancers and genes. Our results suggest that the bursting of transcription at super-enhancers precedes bursting from associated genes. By imparting insights into the dynamic nature of global transcription and the origin and propagation of transcription signals, we demonstrate the ability of scGRO-seq to investigate the mechanisms of transcription regulation and the role of enhancers in gene expression.

Quantification and statistical modeling of droplet-based single-nucleus RNA-sequencing data

In complex tissues containing cells that are difficult to dissociate, single-nucleus RNA-sequencing (snRNA-seq) has become the preferred experimental technology over single-cell RNA-sequencing (scRNA-seq) to measure gene expression. To accurately model these data in downstream analyses, previous work has shown that droplet-based scRNA-seq data are not zero-inflated, but whether droplet-based snRNA-seq data follow the same probability distributions has not been systematically evaluated. Using pseudonegative control data from nuclei in mouse cortex sequenced with the 10x Genomics Chromium system and mouse kidney sequenced with the DropSeq system, we found that droplet-based snRNA-seq data follow a negative binomial distribution, suggesting that parametric statistical models applied to scRNA-seq are transferable to snRNA-seq. Furthermore, we found that the quantification choices in adapting quantification mapping strategies from scRNA-seq to snRNA-seq can play a significant role in downstream analyses and biological interpretation. In particular, reference transcriptomes that do not include intronic regions result in significantly smaller library sizes and incongruous cell type classifications. We also confirmed the presence of a gene length bias in snRNA-seq data, which we show is present in both exonic and intronic reads, and investigate potential causes for the bias.

Deciphering the functional specialization of whole-brain spatiomolecular gradients in the adult brain

Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, whether similar gradients are maintained in the adult brain remains unknown. Here, we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral, and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately reconstructs the position of brain tissue samples, ii) delineates known functional territories, and iii) can model the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical axes differentiating the primary sensory cortex from the association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two nonhuman primate datasets and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well-known transcription factors (e.g., PAX6 and SIX3), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.

Dual-role transcription factors stabilize intermediate expression levels

Precise control of gene expression levels is essential for normal cell functions, yet how they are defined and tightly maintained, particularly at intermediate levels, remains elusive. Here, using a series of newly developed sequencing, imaging, and functional assays, we uncover a class of transcription factors with dual roles as activators and repressors, referred to as condensate-forming level-regulating dual-action transcription factors (TFs). They reduce high expression but increase low expression to achieve stable intermediate levels. Dual-action TFs directly exert activating and repressing functions via condensate-forming domains that compartmentalize core transcriptional unit selectively. Clinically relevant mutations in these domains, which are linked to a range of developmental disorders, impair condensate selectivity and dual-action TF activity. These results collectively address a fundamental question in expression regulation and demonstrate the potential of level-regulating dual-action TFs as powerful effectors for engineering controlled expression levels.