Droplet-based transcriptome profiling of individual synapses

Evolutionary neurogenomics at single-cell resolution

The human brain is composed of increasingly recognized heterogeneous cell types. Applying single-cell genomics to brain tissue can elucidate relative cell type proportions as well as differential gene expression and regulation among humans and other species. Here, we review recent studies that utilized high-throughput genomics approaches to compare brains among species at single-cell resolution. These studies identified genomic elements that are similar among species as well as evolutionary novelties on the human lineage. We focus on those human-relevant innovations and discuss the biological implications of these modifications. Finally, we discuss areas of comparative single-cell genomics that remain unexplored either due to needed technological advances or due to biological availability at the brain region or species level.

Transcriptional determinism and stochasticity contribute to the complexity of autism-associated SHANK family genes

Precision of transcription is critical because transcriptional dysregulation is disease causing. Traditional methods of transcriptional profiling are inadequate to elucidate the full spectrum of the transcriptome, particularly for longer and less abundant mRNAs. SHANK3 is one of the most common autism causative genes. Twenty-four Shank3-mutant animal lines have been developed for autism modeling. However, their preclinical validity has been questioned due to incomplete Shank3 transcript structure. We apply an integrative approach combining cDNA-capture and long-read sequencing to profile the SHANK3 transcriptome in humans and mice. We unexpectedly discover an extremely complex SHANK3 transcriptome. Specific SHANK3 transcripts are altered in Shank3-mutant mice and postmortem brain tissues from individuals with autism spectrum disorder. The enhanced SHANK3 transcriptome significantly improves the detection rate for potential deleterious variants from genomics studies of neuropsychiatric disorders. Our findings suggest that both deterministic and stochastic transcription of the genome is associated with SHANK family genes.

Single-cell total-RNA profiling unveils regulatory hubs of transcription factors

Recent development of RNA velocity uses master equations to establish the kinetics of the life cycle of RNAs from unspliced RNA to spliced RNA (i.e., mature RNA) to degradation. To feed this kinetic analysis, simultaneous measurement of unspliced RNA and spliced RNA in single cells is greatly desired. However, the majority of single-cell RNA-seq chemistry primarily captures mature RNA species to measure gene expressions. Here, we develop a one-step total-RNA chemistry-based single-cell RNA-seq method: snapTotal-seq. We benchmark this method with multiple single-cell RNA-seq assays in their performance in kinetic analysis of cell cycle by RNA velocity. Next, with LASSO regression between transcription factors, we identify the critical regulatory hubs mediating the cell cycle dynamics. We also apply snapTotal-seq to profile the oncogene-induced senescence and identify the key regulatory hubs governing the entry of senescence. Furthermore, from the comparative analysis of unspliced RNA and spliced RNA, we identify a significant portion of genes whose expression changes occur in spliced RNA but not to the same degree in unspliced RNA, indicating these gene expression changes are mainly controlled by post-transcriptional regulation. Overall, we demonstrate that snapTotal-seq can provide enriched information about gene regulation, especially during the transition between cell states.

A single-cell transcriptomic atlas of sensory-dependent gene expression in developing mouse visual cortex

Sensory experience drives the refinement and maturation of neural circuits during postnatal brain development through molecular mechanisms that remain to be fully elucidated. One likely mechanism involves the sensory-dependent expression of genes that encode direct mediators of circuit remodeling within developing cells. However, while studies in adult systems have begun to uncover crucial roles for sensory-induced genes in modifying circuit connectivity, the gene programs induced by brain cells in response to sensory experience during development remain to be fully characterized. Here, we present a single-nucleus RNA-sequencing dataset describing the transcriptional responses of cells in mouse visual cortex to sensory deprivation or sensory stimulation during a developmental window when visual input is necessary for circuit refinement. We sequenced 118,529 individual nuclei across sixteen neuronal and non-neuronal cortical cell types isolated from control, sensory deprived, and sensory stimulated mice, identifying 1,268 unique sensory-induced genes within the developing brain. To demonstrate the utility of this resource, we compared the architecture and ontology of sensory-induced gene programs between cell types, annotated transcriptional induction and repression events based upon RNA velocity, and discovered Neurexin and Neuregulin signaling networks that underlie cell-cell interactions via CellChat . We find that excitatory neurons, especially layer 2/3 pyramidal neurons, are highly sensitive to sensory stimulation, and that the sensory-induced genes in these cells are poised to strengthen synapse-to-nucleus crosstalk by heightening protein serine/threonine kinase activity. Altogether, we expect this dataset to significantly broaden our understanding of the molecular mechanisms through which sensory experience shapes neural circuit wiring in the developing brain.

A genome-wide association study reveals a polygenic architecture of speech-in-noise deficits in individuals with self-reported normal hearing

Speech-in-noise (SIN) perception is a primary complaint of individuals with audiometric hearing loss. SIN performance varies drastically, even among individuals with normal hearing. The present genome-wide association study (GWAS) investigated the genetic basis of SIN deficits in individuals with self-reported normal hearing in quiet situations. GWAS was performed on 279,911 individuals from the UB Biobank cohort, with 58,847 reporting SIN deficits despite reporting normal hearing in quiet. GWAS identified 996 single nucleotide polymorphisms (SNPs), achieving significance (p < 5*10-8) across four genomic loci. 720 SNPs across 21 loci achieved suggestive significance (p < 10-6). GWAS signals were enriched in brain tissues, such as the anterior cingulate cortex, dorsolateral prefrontal cortex, entorhinal cortex, frontal cortex, hippocampus, and inferior temporal cortex. Cochlear cell types revealed no significant association with SIN deficits. SIN deficits were associated with various health traits, including neuropsychiatric, sensory, cognitive, metabolic, cardiovascular, and inflammatory conditions. A replication analysis was conducted on 242 healthy young adults. Self-reported speech perception, hearing thresholds (0.25-16 kHz), and distortion product otoacoustic emissions (1-16 kHz) were utilized for the replication analysis. 73 SNPs were replicated with a self-reported speech perception measure. 211 SNPs were replicated with at least one and 66 with at least two audiological measures. 12 SNPs near or within MAPT, GRM3, and HLA-DQA1 were replicated for all audiological measures. The present study highlighted a polygenic architecture underlying SIN deficits in individuals with self-reported normal hearing.

The diversification of methods for studying cell-cell interactions and communication

No cell lives in a vacuum, and the molecular interactions between cells define most phenotypes. Transcriptomics provides rich information to infer cell-cell interactions and communication, thus accelerating the discovery of the roles of cells within their communities. Such research relies heavily on algorithms that infer which cells are interacting and the ligands and receptors involved. Specific pressures on different research niches are driving the evolution of next-generation computational tools, enabling new conceptual opportunities and technological advances. More sophisticated algorithms now account for the heterogeneity and spatial organization of cells, multiple ligand types and intracellular signalling events, and enable the use of larger and more complex datasets, including single-cell and spatial transcriptomics. Similarly, new high-throughput experimental methods are increasing the number and resolution of interactions that can be analysed simultaneously. Here, we explore recent progress in cell-cell interaction research and highlight the diversification of the next generation of tools, which have yielded a rich ecosystem of tools for different applications and are enabling invaluable discoveries.

Large-scale neurophysiology and single-cell profiling in human neuroscience

Advances in large-scale single-unit human neurophysiology, single-cell RNA sequencing, spatial transcriptomics and long-term ex vivo tissue culture of surgically resected human brain tissue have provided an unprecedented opportunity to study human neuroscience. In this Perspective, we describe the development of these paradigms, including Neuropixels and recent brain-cell atlas efforts, and discuss how their convergence will further investigations into the cellular underpinnings of network-level activity in the human brain. Specifically, we introduce a workflow in which functionally mapped samples of human brain tissue resected during awake brain surgery can be cultured ex vivo for multi-modal cellular and functional profiling. We then explore how advances in human neuroscience will affect clinical practice, and conclude by discussing societal and ethical implications to consider. Potential findings from the field of human neuroscience will be vast, ranging from insights into human neurodiversity and evolution to providing cell-type-specific access to study and manipulate diseased circuits in pathology. This Perspective aims to provide a unifying framework for the field of human neuroscience as we welcome an exciting era for understanding the functional cytoarchitecture of the human brain.

Unique Properties of Synaptosomes and Prospects for Their Use for the Treatment of Alzheimer's Disease

Alzheimer's disease (AD) is a severe neurodegenerative condition affecting millions worldwide. Prevalence of AD correlates with increased life expectancy and aging population in the developed countries. Considering that AD is a multifactorial disease involving various pathological processes such as synaptic dysfunction, neuroinflammation, oxidative stress, and improper protein folding, a comprehensive approach targeting multiple pathways may prove effective in slowing the disease progression. Cellular therapy and its further development in the form of cell vesicle and particularly mitochondrial transplantation represent promising approaches for treating neurodegeneration. The use of synaptosomes, due to uniqueness of their contents, could mark a new stage in the development of comprehensive therapies for neurodegenerative diseases, particularly AD. Synaptosomes contain unique memory mitochondria, which differ not only in size but also in functionality compared to the mitochondria in the neuronal soma. These synaptosomal mitochondria actively participate in cellular communication and signal transmission within synapses. Synaptosomes also contain other elements such as their own protein synthesis machinery, synaptic vesicles with neurotransmitters, synaptic adhesion molecules, and microRNAs - all crucial for synaptic transmission and, consequently, cognitive processes. Complex molecular ensemble ensures maintenance of the synaptic autonomy of mitochondria. Additionally, synaptosomes, with their affinity for neurons, can serve as an optimal platform for targeted drug delivery to nerve cells. This review discusses unique composition of synaptosomes, their capabilities and advantages, as well as limitations of their suggested use as therapeutic agents for treating neurodegenerative pathologies, particularly AD.

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation

The dentate gyrus of the hippocampus is important for many cognitive functions, including learning, memory, and mood. Here, we investigated age-associated changes in transcriptome-wide spatial gene expression in the human dentate gyrus across the lifespan. Genes associated with neurogenesis and the extracellular matrix were enriched in infants, while gene markers of inhibitory neurons and cell proliferation showed increases and decreases in post-infancy, respectively. While we did not find evidence for neural proliferation post-infancy, we did identify molecular signatures supporting protracted maturation of granule cells. We also identified a wide-spread hippocampal aging signature and an age-associated increase in genes related to neuroinflammation. Our findings suggest major changes to the putative neurogenic niche after infancy and identify molecular foci of brain aging in glial and neuropil enriched tissue.

Differential nanoscale organization of excitatory synapses onto excitatory vs. inhibitory neurons

A key feature of excitatory synapses is the existence of subsynaptic protein nanoclusters (NCs) whose precise alignment across the cleft in a transsynaptic nanocolumn influences the strength of synaptic transmission. However, whether nanocolumn properties vary between excitatory synapses functioning in different cellular contexts is unknown. We used a combination of confocal and DNA-PAINT super-resolution microscopy to directly compare the organization of shared scaffold proteins at two important excitatory synapses-those forming onto excitatory principal neurons (Ex→Ex synapses) and those forming onto parvalbumin-expressing interneurons (Ex→PV synapses). As in Ex→Ex synapses, we find that in Ex→PV synapses, presynaptic Munc13-1 and postsynaptic PSD-95 both form NCs that demonstrate alignment, underscoring synaptic nanostructure and the transsynaptic nanocolumn as conserved organizational principles of excitatory synapses. Despite the general conservation of these features, we observed specific differences in the characteristics of pre- and postsynaptic Ex→PV nanostructure. Ex→PV synapses contained larger PSDs with fewer PSD-95 NCs when accounting for size than Ex→Ex synapses. Furthermore, the PSD-95 NCs were larger and denser. The identity of the postsynaptic cell was also represented in Munc13-1 organization, as Ex→PV synapses hosted larger Munc13-1 puncta that contained less dense but larger and more numerous Munc13-1 NCs. Moreover, we measured the spatial variability of transsynaptic alignment in these synapse types, revealing protein alignment in Ex→PV synapses over a distinct range of distances compared to Ex→Ex synapses. We conclude that while general principles of nanostructure and alignment are shared, cell-specific elements of nanodomain organization likely contribute to functional diversity of excitatory synapses.

Transcriptional Determinism and Stochasticity Contribute to the Complexity of Autism Associated SHANK Family Genes

Precision of transcription is critical because transcriptional dysregulation is disease causing. Traditional methods of transcriptional profiling are inadequate to elucidate the full spectrum of the transcriptome, particularly for longer and less abundant mRNAs. SHANK3 is one of the most common autism causative genes. Twenty-four Shank3 mutant animal lines have been developed for autism modeling. However, their preclinical validity has been questioned due to incomplete Shank3 transcript structure. We applied an integrative approach combining cDNA-capture and long-read sequencing to profile the SHANK3 transcriptome in human and mice. We unexpectedly discovered an extremely complex SHANK3 transcriptome. Specific SHANK3 transcripts were altered in Shank3 mutant mice and postmortem brains tissues from individuals with ASD. The enhanced SHANK3 transcriptome significantly improved the detection rate for potential deleterious variants from genomics studies of neuropsychiatric disorders. Our findings suggest the stochastic transcription of genome associated with SHANK family genes.

Nanopore DNA sequencing technologies and their applications towards single-molecule proteomics

Sequencing of nucleic acids with nanopores has emerged as a powerful tool offering rapid readout, high accuracy, low cost and portability. This label-free method for sequencing at the single-molecule level is an achievement on its own. However, nanopores also show promise for the technologically even more challenging sequencing of polypeptides, something that could considerably benefit biological discovery, clinical diagnostics and homeland security, as current techniques lack portability and speed. Here we survey the biochemical innovations underpinning commercial and academic nanopore DNA/RNA sequencing techniques, and explore how these advances can fuel developments in future protein sequencing with nanopores.

The role of microglia heterogeneity in synaptic plasticity and brain disorders: Will sequencing shed light on the discovery of new therapeutic targets?

Microglia play a crucial role in interacting with neuronal synapses and modulating synaptic plasticity. This function is particularly significant during postnatal development, as microglia are responsible for removing excessive synapses to prevent neurodevelopmental deficits. Dysregulation of microglial synaptic function has been well-documented in various pathological conditions, notably Alzheimer's disease and multiple sclerosis. The recent application of RNA sequencing has provided a powerful and unbiased means to decipher spatial and temporal microglial heterogeneity. By identifying microglia with varying gene expression profiles, researchers have defined multiple subgroups of microglia associated with specific pathological states, including disease-associated microglia, interferon-responsive microglia, proliferating microglia, and inflamed microglia in multiple sclerosis, among others. However, the functional roles of these distinct subgroups remain inadequately characterized. This review aims to refine our current understanding of the potential roles of heterogeneous microglia in regulating synaptic plasticity and their implications for various brain disorders, drawing from recent sequencing research and functional studies. This knowledge may aid in the identification of pathogenetic biomarkers and potential factors contributing to pathogenesis, shedding new light on the discovery of novel drug targets. The field of sequencing-based data mining is evolving toward a multi-omics approach. With advances in viral tools for precise microglial regulation and the development of brain organoid models, we are poised to elucidate the functional roles of microglial subgroups detected through sequencing analysis, ultimately identifying valuable therapeutic targets.

Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq

Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.

Functional genomics and systems biology in human neuroscience

Neuroscience research has entered a phase of key discoveries in the realm of neurogenomics owing to strong financial and intellectual support for resource building and tool development. The previous challenge of tissue heterogeneity has been met with the application of techniques that can profile individual cells at scale. Moreover, the ability to perturb genes, gene regulatory elements and neuronal activity in a cell-type-specific manner has been integrated with gene expression studies to uncover the functional underpinnings of the genome at a systems level. Although these insights have necessarily been grounded in model systems, we now have the opportunity to apply these approaches in humans and in human tissue, thanks to advances in human genetics, brain imaging and tissue collection. We acknowledge that there will probably always be limits to the extent to which we can apply the genomic tools developed in model systems to human neuroscience; however, as we describe in this Perspective, the neuroscience field is now primed with an optimal foundation for tackling this ambitious challenge. The application of systems-level network analyses to these datasets will facilitate a deeper appreciation of human neurogenomics that cannot otherwise be achieved from directly observable phenomena.

Differential nanoscale organization of excitatory synapses onto excitatory vs inhibitory neurons

A key feature of excitatory synapses is the existence of subsynaptic protein nanoclusters whose precise alignment across the cleft in a trans-synaptic nanocolumn influences the strength of synaptic transmission. However, whether nanocolumn properties vary between excitatory synapses functioning in different cellular contexts is unknown. We used a combination of confocal and DNA-PAINT super-resolution microscopy to directly compare the organization of shared scaffold proteins at two important excitatory synapses - those forming onto excitatory principal neurons (Ex→Ex synapses) and those forming onto parvalbumin-expressing interneurons (Ex→PV synapses). As in Ex→Ex synapses, we find that in Ex→PV synapses presynaptic Munc13-1 and postsynaptic PSD-95 both form nanoclusters that demonstrate alignment, underscoring synaptic nanostructure and the trans-synaptic nanocolumn as conserved organizational principles of excitatory synapses. Despite the general conservation of these features, we observed specific differences in the characteristics of pre- and postsynaptic Ex→PV nanostructure. Ex→PV synapses contained larger PSDs with fewer PSD-95 NCs when accounting for size than Ex→Ex synapses. Furthermore, the PSD-95 NCs were larger and denser. The identity of the postsynaptic cell also had a retrograde impact on Munc13-1 organization, as Ex→PV synapses hosted larger Munc13-1 puncta that contained less dense but larger and more numerous Munc13-1 NCs. Moreover, we measured the spatial variability of transsynaptic alignment in these synapse types, revealing protein alignment in Ex→PV synapses over a distinct range of distances compared to Ex→Ex synapses. We conclude that while general principles of nanostructure and alignment are shared, cell-specific elements of nanodomain organization likely contribute to functional diversity of excitatory synapses. Understanding the rules of synapse nanodomain assembly, which themselves are cell-type specific, will be essential for illuminating brain network dynamics.

A multi-omics view of neuronal subcellular protein synthesis

While it has long been known that protein synthesis is necessary for long-term memory in the brain, the logistics of neuronal protein synthesis is complicated by the extensive subcellular compartmentalization of the neuron. Local protein synthesis solves many of the logistic problems posed by the extreme complexity of dendritic and axonal arbors and the huge number of synapses. Here we review recent multi-omic and quantitative studies that elaborate a systems view of decentralized neuronal protein synthesis. We highlight recent insights from the transcriptomic, translatomic, and proteomic levels, discuss the nuanced logic of local protein synthesis for different protein features, and list the missing information needed to build a comprehensive logistic model for neuronal protein supply.