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

Negative allosteric modulators of metabotropic glutamate receptor 3 target the stem-like phenotype of glioblastoma

Glioblastoma is an invariably deadly disease. A subpopulation of glioma stem-like cells (GSCs) drives tumor progression and treatment resistance. Two recent studies demonstrated that neurons form oncogenic glutamatergic electrochemical synapses with post-synaptic GSCs. This led us to explore whether glutamate signaling through G protein-coupled metabotropic receptors would also contribute to the malignancy of glioblastoma. We found that glutamate metabotropic receptor (Grm)3 is the predominantly expressed Grm in glioblastoma. Associations of GRM3 gene expression levels with survival are confined to the proneural gene expression subtype, which is associated with enrichment of GSCs. Using multiplexed single-cell qRT-PCR, GSC marker-based cell sorting, database interrogations, and functional assays in GSCs derived from patients' tumors, we establish Grm3 as a novel marker and potential therapeutic target in GSCs. We confirm that Grm3 inhibits adenylyl cyclase and regulates extracellular signal-regulated kinase. Targeting Grm3 disrupts self-renewal and promotes differentiation of GSCs. Thus, we hypothesize that Grm3 signaling may complement oncogenic functions of glutamatergic ionotropic receptor activity in neuroglial synapses, supporting a link between neuronal activity and the GSC phenotype. The novel class of highly specific Grm3 inhibitors that we characterize herein have been clinically tested as cognitive enhancers in humans with a favorable safety profile.

Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise

A fundamental step in many data-analysis techniques is the construction of an affinity matrix describing similarities between data points. When the data points reside in Euclidean space, a widespread approach is to from an affinity matrix by the Gaussian kernel with pairwise distances, and to follow with a certain normalization (e.g. the row-stochastic normalization or its symmetric variant). We demonstrate that the doubly-stochastic normalization of the Gaussian kernel with zero main diagonal (i.e., no self loops) is robust to heteroskedastic noise. That is, the doubly-stochastic normalization is advantageous in that it automatically accounts for observations with different noise variances. Specifically, we prove that in a suitable high-dimensional setting where heteroskedastic noise does not concentrate too much in any particular direction in space, the resulting (doubly-stochastic) noisy affinity matrix converges to its clean counterpart with rate m ^-1/2, where m is the ambient dimension. We demonstrate this result numerically, and show that in contrast, the popular row-stochastic and symmetric normalizations behave unfavorably under heteroskedastic noise. Furthermore, we provide examples of simulated and experimental single-cell RNA sequence data with intrinsic heteroskedasticity, where the advantage of the doubly-stochastic normalization for exploratory analysis is evident.

Determinants of Resident Tissue Macrophage Identity and Function

Resident tissue macrophages (RTMs) have a broad spectrum of immune- and non-immune-related tissue-supporting activities. The roots of this heterogeneity and versatility are only beginning to be understood. Here, we propose a conceptual framework for considering the RTM heterogeneity that organizes the factors shaping RTM identity within four cardinal points: (1) ontogeny and the view that adult RTM populations comprise a defined mixture of cells that arise from either embryonic precursors or adult monocytes; (2) local factors unique to the niche of residence, evolving during development and aging; (3) inflammation status; and (4) the cumulative effect of time spent in a specific tissue that contributes to the resilient adaptation of macrophages to their dynamic environment. We review recent findings within this context and discuss the technological advances that are revolutionizing the study of macrophage biology.

Novel Molecular Hallmarks of Group 3 Medulloblastoma by Single-Cell Transcriptomics

Medulloblastoma (MB) is a highly heterogeneous and one of the most malignant pediatric brain tumors, comprising four subgroups: Sonic Hedgehog, Wingless, Group 3, and Group 4. Group 3 MB has the worst prognosis of all MBs. However, the molecular and cellular mechanisms driving the maintenance of malignancy are poorly understood. Here, we employed high-throughput single-cell and bulk RNA sequencing to identify novel molecular features of Group 3 MB, and found that a specific cell cluster displayed a highly malignant phenotype. Then, we identified the glutamate receptor metabotropic 8 (GRM8), and AP-1 complex subunit sigma-2 (AP1S2) genes as two critical markers of Group 3 MB, corresponding to its poor prognosis. Information on 33 clinical cases was further utilized for validation. Meanwhile, a global map of the molecular cascade downstream of the MYC oncogene in Group 3 MB was also delineated using single-cell RNA sequencing. Our data yields new insights into Group 3 MB molecular characteristics and provides novel therapeutic targets for this relentless disease.

Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex. We identified extensive layer-enriched expression signatures and refined associations to previous laminar markers. We overlaid our laminar expression signatures on large-scale single nucleus RNA-sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions in which morphological architecture is not as well defined as cortical laminae. Last, we created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research ( http://research.libd.org/spatialLIBD ).

Single-cell RNA sequencing: An overview for the ophthalmologist

Understanding the molecular composition of pathogenic tissues is a critical step in understanding the pathophysiology of disease and designing therapeutics. First described in 2009, single cell RNA sequencing (scRNAseq) is a methodology whereby thousands of cells are simultaneously isolated into individual micro-environments that can be altered experimentally and the genome-wide RNA expression of each cell is captured. It has undergone significant technological improvement over the last decade and gained tremendous popularity. scRNAseq is an improvement over prior pooled RNA analyses which cannot identify the cellular composition and heterogeneity of a tissue of interest. This new approach offers new opportunity for new discovery, as tissue samples can now be sub-categorized into groups of cell types based on genome-wide gene expression in an unbiased fashion. As ophthalmologists, we are uniquely positioned to obtain pathologic samples from the eye for further study. ScRNAseq has already been applied in ophthalmology to characterize retinal tissue, and it may offer the key to understanding various pathological processes in the future.

FlsnRNA-seq: protoplasting-free full-length single-nucleus RNA profiling in plants

The broad application of single-cell RNA profiling in plants has been hindered by the prerequisite of protoplasting that requires digesting the cell walls from different types of plant tissues. Here, we present a protoplasting-free approach, flsnRNA-seq, for large-scale full-length RNA profiling at a single-nucleus level in plants using isolated nuclei. Combined with 10x Genomics and Nanopore long-read sequencing, we validate the robustness of this approach in Arabidopsis root cells and the developing endosperm. Sequencing results demonstrate that it allows for uncovering alternative splicing and polyadenylation-related RNA isoform information at the single-cell level, which facilitates characterizing cell identities.

Single-cell transcriptomes of developing and adult olfactory receptor neurons in Drosophila

Recognition of environmental cues is essential for the survival of all organisms. Transcriptional changes occur to enable the generation and function of the neural circuits underlying sensory perception. To gain insight into these changes, we generated single-cell transcriptomes of Drosophila olfactory- (ORNs), thermo-, and hygro-sensory neurons at an early developmental and adult stage using single-cell and single-nucleus RNA sequencing. We discovered that ORNs maintain expression of the same olfactory receptors across development. Using receptor expression and computational approaches, we matched transcriptomic clusters corresponding to anatomically and physiologically defined neuron types across multiple developmental stages. We found that cell-type-specific transcriptomes partly reflected axon trajectory choices in development and sensory modality in adults. We uncovered stage-specific genes that could regulate the wiring and sensory responses of distinct ORN types. Collectively, our data reveal transcriptomic features of sensory neuron biology and provide a resource for future studies of their development and physiology.

NECAB1 and NECAB2 are Prevalent Calcium-Binding Proteins of CB1/CCK-Positive GABAergic Interneurons

The molecular repertoire of the "Ca2+-signaling toolkit" supports the specific kinetic requirements of Ca2+-dependent processes in different neuronal types. A well-known example is the unique expression pattern of calcium-binding proteins, such as parvalbumin, calbindin, and calretinin. These cytosolic Ca2+-buffers control presynaptic and somatodendritic processes in a cell-type-specific manner and have been used as neurochemical markers of GABAergic interneuron types for decades. Surprisingly, to date no typifying calcium-binding proteins have been found in CB1 cannabinoid receptor/cholecystokinin (CB1/CCK)-positive interneurons that represent a large population of GABAergic cells in cortical circuits. Because CB1/CCK-positive interneurons display disparate presynaptic and somatodendritic Ca2+-transients compared with other interneurons, we tested the hypothesis that they express alternative calcium-binding proteins. By in silico data mining in mouse single-cell RNA-seq databases, we identified high expression of Necab1 and Necab2 genes encoding N-terminal EF-hand calcium-binding proteins 1 and 2, respectively, in CB1/CCK-positive interneurons. Fluorescent in situ hybridization and immunostaining revealed cell-type-specific distribution of NECAB1 and NECAB2 throughout the isocortex, hippocampal formation, and basolateral amygdala complex. Combination of patch-clamp electrophysiology, confocal, and STORM super-resolution microscopy uncovered subcellular nanoscale differences indicating functional division of labor between the two calcium-binding proteins. These findings highlight NECAB1 and NECAB2 as predominant calcium-binding proteins in CB1/CCK-positive interneurons.

Cntn4, a risk gene for neuropsychiatric disorders, modulates hippocampal synaptic plasticity and behavior

Neurodevelopmental and neuropsychiatric disorders, such as autism spectrum disorders (ASD), anorexia nervosa (AN), Alzheimer's disease (AD), and schizophrenia (SZ), are heterogeneous brain disorders with unknown etiology. Genome wide studies have revealed a wide variety of risk genes for these disorders, indicating a biological link between genetic signaling pathways and brain pathology. A unique risk gene is Contactin 4 (Cntn4), an Ig cell adhesion molecule (IgCAM) gene, which has been associated with several neuropsychiatric disorders including ASD, AN, AD, and SZ. Here, we investigated the Cntn4 gene knockout (KO) mouse model to determine whether memory dysfunction and altered brain plasticity, common neuropsychiatric symptoms, are affected by Cntn4 genetic disruption. For that purpose, we tested if Cntn4 genetic disruption affects CA1 synaptic transmission and the ability to induce LTP in hippocampal slices. Stimulation in CA1 striatum radiatum significantly decreased synaptic potentiation in slices of Cntn4 KO mice. Neuroanatomical analyses showed abnormal dendritic arborization and spines of hippocampal CA1 neurons. Short- and long-term recognition memory, spatial memory, and fear conditioning responses were also assessed. These behavioral studies showed increased contextual fear conditioning in heterozygous and homozygous KO mice, quantified by a gene-dose dependent increase in freezing response. In comparison to wild-type mice, Cntn4-deficient animals froze significantly longer and groomed more, indicative of increased stress responsiveness under these test conditions. Our electrophysiological, neuro-anatomical, and behavioral results in Cntn4 KO mice suggest that Cntn4 has important functions related to fear memory possibly in association with the neuronal morphological and synaptic plasticity changes in hippocampus CA1 neurons.

Area Postrema Cell Types that Mediate Nausea-Associated Behaviors

Nausea, the unpleasant sensation of visceral malaise, remains a mysterious process. The area postrema is implicated in some nausea responses and is anatomically privileged to detect blood-borne signals. To investigate nausea mechanisms, we built an area postrema cell atlas through single-nucleus RNA sequencing, revealing a few neuron types. Using mouse genetic tools for cell-specific manipulation, we discovered excitatory neurons that induce nausea-related behaviors, with one neuron type mediating aversion imposed by multiple poisons. Nausea-associated responses to agonists of identified area postrema receptors were observed and suppressed by targeted cell ablation and/or gene knockout. Anatomical mapping revealed a distributed network of long-range excitatory but not inhibitory projections with subtype-specific patterning. These studies reveal the basic organization of area postrema nausea circuitry and provide a framework toward understanding and therapeutically controlling nausea.

Patch-seq: Past, Present, and Future

Single-cell transcriptomic approaches are revolutionizing neuroscience. Integrating this wealth of data with morphology and physiology, for the comprehensive study of neuronal biology, requires multiplexing gene expression data with complementary techniques. To meet this need, multiple groups in parallel have developed "Patch-seq," a modification of whole-cell patch-clamp protocols that enables mRNA sequencing of cell contents after electrophysiological recordings from individual neurons and morphologic reconstruction of the same cells. In this review, we first outline the critical technical developments that enabled robust Patch-seq experimental efforts and analytical solutions to interpret the rich multimodal data generated. We then review recent applications of Patch-seq that address novel and long-standing questions in neuroscience. These include the following: (1) targeted study of specific neuronal populations based on their anatomic location, functional properties, lineage, or a combination of these factors; (2) the compilation and integration of multimodal cell type atlases; and (3) the investigation of the molecular basis of morphologic and functional diversity. Finally, we highlight potential opportunities for further technical development and lines of research that may benefit from implementing the Patch-seq technique. As a multimodal approach at the intersection of molecular neurobiology and physiology, Patch-seq is uniquely positioned to directly link gene expression to brain function.

CoolMPS for robust sequencing of single-nuclear RNAs captured by droplet-based method

Massively-parallel single-cell and single-nucleus RNA sequencing (scRNA-seq, snRNA-seq) requires extensive sequencing to achieve proper per-cell coverage, making sequencing resources and availability of sequencers critical factors for conducting deep transcriptional profiling. CoolMPS is a novel sequencing-by-synthesis approach that relies on nucleotide labeling by re-usable antibodies, but whether it is applicable to snRNA-seq has not been tested. Here, we use a low-cost and off-the-shelf protocol to chemically convert libraries generated with the widely-used Chromium 10X technology to be sequenceable with CoolMPS technology. To assess the quality and performance of converted libraries sequenced with CoolMPS, we generated a snRNA-seq dataset from the hippocampus of young and old mice. Native libraries were sequenced on an Illumina Novaseq and libraries that were converted to be compatible with CoolMPS were sequenced on a DNBSEQ-400RS. CoolMPS-derived data faithfully replicated key characteristics of the native library dataset, including correct estimation of ambient RNA-contamination, detection of captured cells, cell clustering results, spatial marker gene expression, inter- and intra-replicate differences and gene expression changes during aging. In conclusion, our results show that CoolMPS provides a viable alternative to standard sequencing of RNA from droplet-based libraries.

Changes in genome architecture and transcriptional dynamics progress independently of sensory experience during post-natal brain development

Both transcription and three-dimensional (3D) architecture of the mammalian genome play critical roles in neurodevelopment and its disorders. However, 3D genome structures of single brain cells have not been solved; little is known about the dynamics of single-cell transcriptome and 3D genome after birth. Here, we generated a transcriptome (3,517 cells) and 3D genome (3,646 cells) atlas of the developing mouse cortex and hippocampus by using our high-resolution multiple annealing and looping-based amplification cycles for digital transcriptomics (MALBAC-DT) and diploid chromatin conformation capture (Dip-C) methods and developing multi-omic analysis pipelines. In adults, 3D genome "structure types" delineate all major cell types, with high correlation between chromatin A/B compartments and gene expression. During development, both transcriptome and 3D genome are extensively transformed in the first post-natal month. In neurons, 3D genome is rewired across scales, correlated with gene expression modules, and independent of sensory experience. Finally, we examine allele-specific structure of imprinted genes, revealing local and chromosome (chr)-wide differences. These findings uncover an unknown dimension of neurodevelopment.

Modulatory properties of extracellular matrix glycosaminoglycans and proteoglycans on neural stem cells behavior: Highlights on regenerative potential and bioactivity

Despite the poor regenerative capacity of the adult central nervous system (CNS) in mammals, two distinct regions, subventricular zone (SVZ) and the subgranular zone (SGZ), continue to generate new functional neurons throughout life which integrate into the pre-existing neuronal circuitry. This process is not fixed but highly modulated, revealing many intrinsic and extrinsic mechanisms by which this performance can be optimized for a given environment. The capacity for self-renewal, proliferation, migration, and multi-lineage potency of neural stem cells (NSCs) underlines the necessity of controlling stem cell fate. In this context, the native and local microenvironment plays a critical role, and the application of this highly organized architecture in the CNS has been considered as a fundamental concept in the generation of new effective therapeutic strategies in tissue engineering approaches. The brain extracellular matrix (ECM) is composed of biomacromolecules, including glycosaminoglycans, proteoglycans, and glycoproteins that provide various biological actions through biophysical and biochemical signaling pathways. Herein, we review predominantly the structure and function of the mentioned ECM composition and their regulatory impact on multiple and diversity of biological functions, including neural regeneration, survival, migration, differentiation, and final destiny of NSCs.

The spatial RNA integrity number assay for in situ evaluation of transcriptome quality

The RNA integrity number (RIN) is a frequently used quality metric to assess the completeness of rRNA, as a proxy for the corresponding mRNA in a tissue. Current methods operate at bulk resolution and provide a single average estimate for the whole sample. Spatial transcriptomics technologies have emerged and shown their value by placing gene expression into a tissue context, resulting in transcriptional information from all tissue regions. Thus, the ability to estimate RNA quality in situ has become of utmost importance to overcome the limitation with a bulk rRNA measurement. Here we show a new tool, the spatial RNA integrity number (sRIN) assay, to assess the rRNA completeness in a tissue wide manner at cellular resolution. We demonstrate the use of sRIN to identify spatial variation in tissue quality prior to more comprehensive spatial transcriptomics workflows.

Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes

Single-cell sequencing technologies, including transcriptomic and epigenomic assays, are transforming our understanding of the cellular building blocks of neural circuits. By directly measuring multiple molecular signatures in thousands to millions of individual cells, single-cell sequencing methods can comprehensively characterize the diversity of brain cell types. These measurements uncover gene regulatory mechanisms that shape cellular identity and provide insight into developmental and evolutionary relationships between brain cell populations. Single-cell sequencing data can aid the design of tools for targeted functional studies of brain circuit components, linking molecular signatures with anatomy, connectivity, morphology, and physiology. Here, we discuss the fundamental principles of single-cell transcriptome and epigenome sequencing, integrative computational analysis of the data, and key applications in neuroscience.

Neurogenesis in the adult hypothalamus: A distinct form of structural plasticity involved in metabolic and circadian regulation, with potential relevance for human pathophysiology

The adult brain harbors specific niches where stem cells undergo substantial plasticity and, in some regions, generate new neurons throughout life. This phenomenon is well known in the subventricular zone of the lateral ventricles and the subgranular zone of the hippocampus and has recently also been described in the hypothalamus of several rodent and primate species. After a brief overview of preclinical studies illustrating the pathophysiologic significance of hypothalamic neurogenesis in the control of energy metabolism, reproduction, thermoregulation, sleep, and aging, we review current literature on the neurogenic niche of the human hypothalamus. A comparison of the organization of the niche between humans and rodents highlights some common features, but also substantial differences, e.g., in the distribution and extent of the hypothalamic neural stem cells. Exploring the full dynamics of hypothalamic neurogenesis in humans raises a formidable challenge however, given among others, inherent technical limitations. We close with discussing possible functional role(s) of the human hypothalamic niche, and how gaining more insights into this form of plasticity could be relevant for a better understanding of pathologies associated with disturbed hypothalamic function.

Transcriptomic Changes of Murine Visceral Fat Exposed to Intermittent Hypoxia at Single Cell Resolution

Intermittent hypoxia (IH) is a hallmark of obstructive sleep apnea (OSA) and induces metabolic dysfunction manifesting as inflammation, increased lipolysis and insulin resistance in visceral white adipose tissues (vWAT). However, the cell types and their corresponding transcriptional pathways underlying these functional perturbations are unknown. Here, we applied single nucleus RNA sequencing (snRNA-seq) coupled with aggregate RNA-seq methods to evaluate the cellular heterogeneity in vWAT following IH exposures mimicking OSA. C57BL/6 male mice were exposed to IH and room air (RA) for 6 weeks, and nuclei from vWAT were isolated and processed for snRNA-seq followed by differential expressed gene (DEGs) analyses by cell type, along with gene ontology and canonical pathways enrichment tests of significance. IH induced significant transcriptional changes compared to RA across 14 different cell types identified in vWAT. We identified cell-specific signature markers, transcriptional networks, metabolic signaling pathways, and cellular subpopulation enrichment in vWAT. Globally, we also identify 298 common regulated genes across multiple cellular types that are associated with metabolic pathways. Deconvolution of cell types in vWAT using global RNA-seq revealed that distinct adipocytes appear to be differentially implicated in key aspects of metabolic dysfunction. Thus, the heterogeneity of vWAT and its response to IH at the cellular level provides important insights into the metabolic morbidity of OSA and may possibly translate into therapeutic targets.

sncRiboTag-Seq: cell-type-specific RiboTag-Seq for cells in low abundance in mouse brain tissue

The mammalian brain has over 10,000 types of neurons. Therefore, studying gene regulation in the brain requires effective strategies for targeting specific cell types, especially those in low abundance. Cell isolation may alter gene expression and is disruptive to mature neurons with extensive processes. This protocol describes cell-type-specific expression of tagged ribosome and the use of ribosome tagging followed by RNA-seq to identify translatome of low number and sparse cells in mouse brains without disruptive cell isolation. For complete details on the use and execution of this protocol, please refer to Gao et al. (2020).

Elucidating memory in the brain via single-cell transcriptomics

Elucidating the neural mechanisms of memory in the brain is a central goal of neuroscience. Here, we discuss modern-day transcriptomics methodologies, and how they are well-poised to revolutionize our insight into memory mechanisms at unprecedented resolution and throughput. Focusing on the hippocampus and amygdala, two regions extensively examined in memory research, we show how single-cell transcriptomics technologies have been leveraged to understand the naïve state of these brain regions. Building upon this foundation, we show that these technologies can be applied to single-trial learning paradigms to comprehensively identify molecules and cells that participate in the encoding and retrieval of memory. Transcriptomics also provides an opportunity to understand the cell-type organization of the human hippocampus and amygdala, and due to conservation of these brain regions between humans and rodents, to infer behavioral and causal contributions in the human brain by leveraging rodent cell-type homologies and interventions. Ultimately, such transcriptomic technologies are poised to usher in a qualitatively novel understanding of memory in the brain.

Bidirectional perisomatic inhibitory plasticity of a Fos neuronal network

Behavioral experiences activate the Fos transcription factor (TF) in sparse populations of neurons that are critical for encoding and recalling specific events^1–3. However, there is limited understanding of the mechanisms by which experience drives circuit reorganization to establish a network of Fos-activated cells. It is also unknown if Fos is required in this process beyond serving as a marker of recent neural activity and, if so, which of its many gene targets underlie circuit reorganization. Here we demonstrate that when mice engage in spatial exploration of novel environments, perisomatic inhibition of Fos-expressing hippocampal CA1 pyramidal neurons by parvalbumin (PV)-interneurons (INs) is enhanced, while perisomatic inhibition by cholecystokinin (CCK)-INs is weakened. This bidirectional modulation of inhibition is abolished when the function of the Fos TF complex is disrupted. Single-cell RNA-sequencing, ribosome-associated mRNA profiling, and chromatin analyses, combined with electrophysiology, reveal that Fos activates the transcription of Scg2 (secretogranin II), a gene that encodes multiple distinct neuropeptides, to coordinate these changes in inhibition. As PV- and CCK-INs mediate distinct features of pyramidal cell activity^4–6, the Scg2-dependent reorganization of inhibitory synaptic input might be predicted to affect network function in vivo. Consistent with this prediction, hippocampal gamma rhythms and pyramidal cell coupling to CA1 theta are significantly altered with loss of Scg2. These findings reveal an instructive role for Fos and Scg2 in establishing a network of Fos-activated neurons via the rewiring of local inhibition to form a selectively modulated state. The opposing plasticity mechanisms on distinct inhibitory pathways may support the consolidation of memories over time.

Methods for isolation and transcriptional profiling of individual cells from the human heart

BACKGROUND

Global transcriptional profiling of individual cells represents a powerful approach to systematically survey contributions from cell-specific molecular phenotypes to human disease states but requires tissue-specific protocols. Here we sought to comprehensively evaluate protocols for single cell isolation and transcriptional profiling from heart tissue, focusing particularly on frozen tissue which is necessary for study of human hearts at scale.

METHODS AND RESULTS

Using flow cytometry and high-content screening, we found that enzymatic dissociation of fresh murine heart tissue resulted in a sufficient yield of intact cells while for frozen murine or human heart resulted in low-quality cell suspensions across a range of protocols. These findings were consistent across enzymatic digestion protocols and whether samples were snap-frozen or treated with RNA-stabilizing agents before freezing. In contrast, we show that isolation of cardiac nuclei from frozen hearts results in a high yield of intact nuclei, and leverage expression arrays to show that nuclear transcriptomes reliably represent the cytoplasmic and whole-cell transcriptomes of the major cardiac cell types. Furthermore, coupling of nuclear isolation to PCM1-gated flow cytometry facilitated specific cardiomyocyte depletion, expanding resolution of the cardiac transcriptome beyond bulk tissue transcriptomes which were most strongly correlated with PCM1+ transcriptomes (r = 0.8). We applied these methods to generate a transcriptional catalogue of human cardiac cells by droplet-based RNA-sequencing of 8,460 nuclei from which cellular identities were inferred. Reproducibility of identified clusters was confirmed in an independent biopsy (4,760 additional PCM1- nuclei) from the same human heart.

CONCLUSION

Our results confirm the validity of single-nucleus but not single-cell isolation for transcriptional profiling of individual cells from frozen heart tissue, and establishes PCM1-gating as an efficient tool for cardiomyocyte depletion. In addition, our results provide a perspective of cell types inferred from single-nucleus transcriptomes that are present in an adult human heart.

Neurotoxic microglia promote TDP-43 proteinopathy in progranulin deficiency

Aberrant aggregation of the RNA-binding protein TDP-43 in neurons is a hallmark of frontotemporal lobar degeneration caused by haploinsufficiency in the gene encoding progranulin1,2. However, the mechanism leading to TDP-43 proteinopathy remains unclear. Here we use single-nucleus RNA sequencing to show that progranulin deficiency promotes microglial transition from a homeostatic to a disease-specific state that causes endolysosomal dysfunction and neurodegeneration in mice. These defects persist even when Grn-/- microglia are cultured ex vivo. In addition, single-nucleus RNA sequencing reveals selective loss of excitatory neurons at disease end-stage, which is characterized by prominent nuclear and cytoplasmic TDP-43 granules and nuclear pore defects. Remarkably, conditioned media from Grn-/- microglia are sufficient to promote TDP-43 granule formation, nuclear pore defects and cell death in excitatory neurons via the complement activation pathway. Consistent with these results, deletion of the genes encoding C1qa and C3 mitigates microglial toxicity and rescues TDP-43 proteinopathy and neurodegeneration. These results uncover previously unappreciated contributions of chronic microglial toxicity to TDP-43 proteinopathy during neurodegeneration.

Initiation of Supporting Cell Activation for Hair Cell Regeneration in the Avian Auditory Epithelium: An Explant Culture Model

Sensorineural hearing loss is a common disability often caused by the loss of sensory hair cells in the cochlea. Hair cell (HCs) regeneration has long been the main target for the development of novel therapeutics for sensorineural hearing loss. In the mammalian cochlea, hair cell regeneration is limited, but the auditory epithelia of non-mammalian organisms retain the capacity for hair cell regeneration. In the avian basilar papilla (BP), supporting cells (SCs), which give rise to regenerated hair cells, are usually quiescent. Hair cell loss induces both direct transdifferentiation and mitotic division of supporting cells. Here, we established an explant culture model for hair cell regeneration in chick basilar papillae and validated it for investigating the initial phase of hair cell regeneration. The histological assessment demonstrated hair cell regeneration via direct transdifferentiation of supporting cells. Labeling with 5-ethynyl-2′-deoxyuridine (EdU) revealed the occurrence of mitotic division in the supporting cells at specific locations in the basilar papillae, while no EdU labeling was observed in newly generated hair cells. RNA sequencing indicated alterations in known signaling pathways associated with hair cell regeneration, consistent with previous findings. Also, unbiased analyses of RNA sequencing data revealed novel genes and signaling pathways that may be related to the induction of supporting cell activation in the chick basilar papillae. These results indicate the advantages of our explant culture model of the chick basilar papillae for exploring the molecular mechanisms of hair cell regeneration.

A Synthesis Concerning Conservation and Divergence of Cell Types across Epithelia

Advances in single-cell RNA-seq (scRNA-seq) and computational analysis have enabled the systematic interrogation of the cellular composition of tissues. Combined with tools from developmental biology, cell biology, and genetics, these approaches are revealing fundamental aspects of tissue geometry and physiology, including the distribution, origins, and inferred functions of specialized cell types, and the dynamics of cellular turnover and differentiation. By comparing different tissues, such studies can delineate shared and specialized features of cell types and their lineage. Here, we compare two developmentally related murine epithelia, the airway and the small intestinal epithelia, which are both derived from the embryonic endodermal gut tube. We examine how airway and intestine generate and functionalize common archetypal cell types to fulfill similar shared physiologic functionalities. We point to cases in which similar cell types are repurposed to accommodate each tissue's unique physiologic role, and highlight tissue-specific cells whose specializations contribute to the distinct functional roles of each organ. We discuss how archetypal and unique cell types are incorporated within a cellular lineage, and how the regulation of the proportions of these cell types enables tissue-level organization to meet functional demands and maintain homeostasis.

Defining best practices for tissue procurement in immuno-oncology clinical trials: consensus statement from the Society for Immunotherapy of Cancer Surgery Committee

Immunotherapy is now a cornerstone for cancer treatment, and much attention has been placed on the identification of prognostic and predictive biomarkers. The success of biomarker development is dependent on accurate and timely collection of biospecimens and high-quality processing, storage and shipping. Tumors are also increasingly used as source material for the generation of therapeutic T cells. There have been few guidelines or consensus statements on how to optimally collect and manage biospecimens and source material being used for immunotherapy and related research. The Society for Immunotherapy of Cancer Surgery Committee has brought together surgical experts from multiple subspecialty disciplines to identify best practices and to provide consensus on how best to access and manage specific tissues for immuno-oncology treatments and clinical investigation. In addition, the committee recommends early integration of surgeons and other interventional physicians with expertise in biospecimen collection, especially in clinical trials, to optimize the quality of tissue and the validity of correlative clinical studies in cancer immunotherapy.

snRNA-seq reveals a subpopulation of adipocytes that regulates thermogenesis

Adipose tissue is usually classified on the basis of its function as white, brown or beige (brite)1. It is an important regulator of systemic metabolism, as shown by the fact that dysfunctional adipose tissue in obesity leads to a variety of secondary metabolic complications2,3. In addition, adipose tissue functions as a signalling hub that regulates systemic metabolism through paracrine and endocrine signals4. Here we use single-nucleus RNA-sequencing (snRNA-seq) analysis in mice and humans to characterize adipocyte heterogeneity. We identify a rare subpopulation of adipocytes in mice that increases in abundance at higher temperatures, and we show that this subpopulation regulates the activity of neighbouring adipocytes through acetate-mediated modulation of their thermogenic capacity. Human adipose tissue contains higher numbers of cells of this subpopulation, which could explain the lower thermogenic activity of human compared to mouse adipose tissue and suggests that targeting this pathway could be used to restore thermogenic activity.

Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin

Cell differentiation and function are regulated across multiple layers of gene regulation, including modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of regulatory events leading to cell fate commitment. Here we developed simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq), a highly scalable approach for measurement of chromatin accessibility and gene expression in the same single cell, applicable to different tissues. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define domains of regulatory chromatin (DORCs) that significantly overlap with super-enhancers. During lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for lineage commitment. We computationally infer chromatin potential as a quantitative measure of chromatin lineage-priming and use it to predict cell fate outcomes. SHARE-seq is an extensible platform to study regulatory circuitry across diverse cells in tissues.

Single-Cell Genomics and Epigenomics: Technologies and Applications in Plants

The development of genomics and epigenomics has allowed rapid advances in our understanding of plant biology. However, conventional bulk analysis dilutes cell-specific information by providing only average information, thereby limiting the resolution of genomic and functional genomic studies. Recent advances in single-cell sequencing technology concerning genomics and epigenomics open new avenues to dissect cell heterogeneity in multiple biological processes. Recent applications of these approaches to plants have provided exciting insights into diverse biological questions. We highlight the methodologies underlying the current techniques of single-cell genomics and epigenomics before covering their recent applications, potential significance, and future perspectives in plant biology.

The Human and Mouse Enteric Nervous System at Single-Cell Resolution

The enteric nervous system (ENS) coordinates diverse functions in the intestine but has eluded comprehensive molecular characterization because of the rarity and diversity of cells. Here we develop two methods to profile the ENS of adult mice and humans at single-cell resolution: RAISIN RNA-seq for profiling intact nuclei with ribosome-bound mRNA and MIRACL-seq for label-free enrichment of rare cell types by droplet-based profiling. The 1,187,535 nuclei in our mouse atlas include 5,068 neurons from the ileum and colon, revealing extraordinary neuron diversity. We highlight circadian expression changes in enteric neurons, show that disease-related genes are dysregulated with aging, and identify differences between the ileum and proximal/distal colon. In humans, we profile 436,202 nuclei, recovering 1,445 neurons, and identify conserved and species-specific transcriptional programs and putative neuro-epithelial, neuro-stromal, and neuro-immune interactions. The human ENS expresses risk genes for neuropathic, inflammatory, and extra-intestinal diseases, suggesting neuronal contributions to disease.

Suprachiasmatic VIP neurons are required for normal circadian rhythmicity and comprised of molecularly distinct subpopulations

The hypothalamic suprachiasmatic (SCN) clock contains several neurochemically defined cell groups that contribute to the genesis of circadian rhythms. Using cell-specific and genetically targeted approaches we have confirmed an indispensable role for vasoactive intestinal polypeptide-expressing SCN (SCN^VIP) neurons, including their molecular clock, in generating the mammalian locomotor activity (LMA) circadian rhythm. Optogenetic-assisted circuit mapping revealed functional, di-synaptic connectivity between SCN^VIP neurons and dorsomedial hypothalamic neurons, providing a circuit substrate by which SCN^VIP neurons may regulate LMA rhythms. In vivo photometry revealed that while SCN^VIP neurons are acutely responsive to light, their activity is otherwise behavioral state invariant. Single-nuclei RNA-sequencing revealed that SCN^VIP neurons comprise two transcriptionally distinct subtypes, including putative pacemaker and non-pacemaker populations. Altogether, our work establishes necessity of SCN^VIP neurons for the LMA circadian rhythm, elucidates organization of circadian outflow from and modulatory input to SCN^VIP cells, and demonstrates a subpopulation-level molecular heterogeneity that suggests distinct functions for specific SCN^VIP subtypes.

Cell groups in the hypothalamic suprachiasmatic clock contribute to the genesis of circadian rhythms. The authors identified two populations of vasoactive intestinal polypeptide-expressing neurons in the suprachiasmatic nucleus which regulate locomotor circadian rhythm in mice.

Impact of similarity metrics on single-cell RNA-seq data clustering

Advances in high-throughput sequencing on single-cell gene expressions [single-cell RNA sequencing (scRNA-seq)] have enabled transcriptome profiling on individual cells from complex samples. A common goal in scRNA-seq data analysis is to discover and characterise cell types, typically through clustering methods. The quality of the clustering therefore plays a critical role in biological discovery. While numerous clustering algorithms have been proposed for scRNA-seq data, fundamentally they all rely on a similarity metric for categorising individual cells. Although several studies have compared the performance of various clustering algorithms for scRNA-seq data, currently there is no benchmark of different similarity metrics and their influence on scRNA-seq data clustering. Here, we compared a panel of similarity metrics on clustering a collection of annotated scRNA-seq datasets. Within each dataset, a stratified subsampling procedure was applied and an array of evaluation measures was employed to assess the similarity metrics. This produced a highly reliable and reproducible consensus on their performance assessment. Overall, we found that correlation-based metrics (e.g. Pearson's correlation) outperformed distance-based metrics (e.g. Euclidean distance). To test if the use of correlation-based metrics can benefit the recently published clustering techniques for scRNA-seq data, we modified a state-of-the-art kernel-based clustering algorithm (SIMLR) using Pearson's correlation as a similarity measure and found significant performance improvement over Euclidean distance on scRNA-seq data clustering. These findings demonstrate the importance of similarity metrics in clustering scRNA-seq data and highlight Pearson's correlation as a favourable choice. Further comparison on different scRNA-seq library preparation protocols suggests that they may also affect clustering performance. Finally, the benchmarking framework is available at http://www.maths.usyd.edu.au/u/SMS/bioinformatics/software.html.

Single-Nuclei RNA Sequencing Assessment of the Hepatic Effects of 2,3,7,8-Tetrachlorodibenzo-p-dioxin

BACKGROUND AND AIMS

Characterization of cell specific transcriptional responses to hepatotoxicants is lost in the averages of bulk RNA-sequencing (RNA-seq). Single-cell/nuclei RNA-seq technologies enable the transcriptomes of individual cell (sub)types to be assessed within the context of in vivo models.

METHODS

Single-nuclei RNA-sequencing (snSeq) of frozen liver samples from male C57BL/6 mice gavaged with sesame oil vehicle or 30 μg/kg 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) every 4 days for 28 days was used to demonstrate the application of snSeq for the evaluation of xenobiotics.

RESULTS

A total of 19,907 genes were detected across 16,015 nuclei from control and TCDD-treated livers. Eleven cell (sub)types reflected the expected cell diversity of the liver including distinct pericentral, midzonal, and periportal hepatocyte subpopulations. TCDD altered relative proportions of cell types and elicited cell-specific gene expression profiles. For example, macrophages increased from 0.5% to 24.7%, while neutrophils were only present in treated samples, consistent with histological evaluation. The number of differentially expressed genes (DEGs) in each cell type ranged from 122 (cholangiocytes) to 7625 (midcentral hepatocytes), and loosely correlated with the basal expression level of Ahr, the canonical mediator of TCDD and related compounds. In addition to the expected functions within each cell (sub)types, RAS signaling and related pathways were specifically enriched in nonparenchymal cells while metabolic process enrichment occurred primarily in hepatocytes. snSeq also identified the expansion of a Kupffer cell subtype highly expressing Gpnmb, as reported in a dietary NASH model.

CONCLUSIONS

We show that snSeq of frozen liver samples can be used to assess cell-specific transcriptional changes and population shifts in models of hepatotoxicity when examining freshly isolated cells is not feasible.

Single cell approaches to address adipose tissue stromal cell heterogeneity

A central function of adipose tissue is in the management of systemic energy homeostasis that is achieved through the co-ordinated regulation of energy storage and mobilization, adipokine release, and immune functions. With the dramatic increase in the prevalence of obesity and obesity-related metabolic disease over the past 30 years, there has been extensive interest in targeting adipose tissue for therapeutic benefit. However, in order for this goal to be achieved it is essential to establish a comprehensive atlas of adipose tissue cellular composition and define mechanisms of intercellular communication that mediate pathologic and therapeutic responses. While traditional methods, such as fluorescence-activated cell sorting (FACS) and genetic lineage tracing, have greatly advanced the field, these approaches are inherently limited by the choice of markers and the ability to comprehensively identify and characterize dynamic interactions among stromal cells within the tissue microenvironment. Single cell RNA sequencing (scRNAseq) has emerged as a powerful tool for deconvolving cellular heterogeneity and holds promise for understanding the development and plasticity of adipose tissue under normal and pathological conditions. scRNAseq has recently been used to characterize adipose stem cell (ASC) populations and has provided new insights into subpopulations of macrophages that arise during anabolic and catabolic remodeling in white adipose tissue. The current review summarizes recent findings that use this technology to explore adipose tissue heterogeneity and plasticity.

Distinct subnetworks of the thalamic reticular nucleus

The thalamic reticular nucleus (TRN), the major source of thalamic inhibition, is known to regulate thalamocortical interactions critical for sensory processing, attention and cognition^1-5. TRN dysfunction has been linked to sensory abnormality, attention deficit and sleep disturbance across multiple neurodevelopmental disorders^6-9. Currently, little is known about the organizational principles underlying its divergent functions. We performed an integrative study linking single-cell molecular and electrophysiological features of the mouse TRN to connectivity and systems-level function. We found that TRN cellular heterogeneity is characterized by a transcriptomic gradient of two negatively correlated gene expression profiles, each containing hundreds of genes. Neurons in the extremes of this transcriptomic gradient express mutually exclusive markers, exhibit core/shell-like anatomical structure and have distinct electrophysiological properties. The two TRN subpopulations make differential connections to the functionally distinct first-order and higher-order thalamic nuclei to form molecularly defined TRN-thalamus subnetworks. Selective perturbation of the two subnetworks in vivo revealed their differential role in regulating sleep. Taken together, our study provides a comprehensive atlas for TRN neurons at the single-cell resolution, and links molecularly defined subnetworks to the functional organization of the thalamo-cortical circuits.

Biological and Medical Importance of Cellular Heterogeneity Deciphered by Single-Cell RNA Sequencing

The present review discusses recent progress in single-cell RNA sequencing (scRNA-seq), which can describe cellular heterogeneity in various organs, bodily fluids, and pathologies (e.g., cancer and Alzheimer's disease). We outline scRNA-seq techniques that are suitable for investigating cellular heterogeneity that is present in cell populations with very high resolution of the transcriptomic landscape. We summarize scRNA-seq findings and applications of this technology to identify cell types, activity, and other features that are important for the function of different bodily organs. We discuss future directions for scRNA-seq techniques that can link gene expression, protein expression, cellular function, and their roles in pathology. We speculate on how the field could develop beyond its present limitations (e.g., performing scRNA-seq in situ and in vivo). Finally, we discuss the integration of machine learning and artificial intelligence with cutting-edge scRNA-seq technology, which could provide a strong basis for designing precision medicine and targeted therapy in the future.

Cancer systems immunology

Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.

Single-Cell RNA-Seq Reveals Cellular Hierarchies and Impaired Developmental Trajectories in Pediatric Ependymoma

Ependymoma is a heterogeneous entity of central nervous system tumors with well-established molecular groups. Here, we apply single-cell RNA sequencing to analyze ependymomas across molecular groups and anatomic locations to investigate their intratumoral heterogeneity and developmental origins. Ependymomas are composed of a cellular hierarchy initiating from undifferentiated populations, which undergo impaired differentiation toward three lineages of neuronal-glial fate specification. While prognostically favorable groups of ependymoma predominantly harbor differentiated cells, aggressive groups are enriched for undifferentiated cell populations. The delineated transcriptomic signatures correlate with patient survival and define molecular dependencies for targeted treatment approaches. Taken together, our analyses reveal a developmental hierarchy underlying ependymomas relevant to biological and clinical behavior.

Breathing fresh air into respiratory research with single-cell RNA sequencing

The complex cellular heterogeneity of the lung poses a unique challenge to researchers in the field. While the use of bulk RNA sequencing has become a ubiquitous technology in systems biology, the technique necessarily averages out individual contributions to the overall transcriptional landscape of a tissue. Single-cell RNA sequencing (scRNA-seq) provides a robust, unbiased survey of the transcriptome comparable to bulk RNA sequencing while preserving information on cellular heterogeneity. In just a few years since this technology was developed, scRNA-seq has already been adopted widely in respiratory research and has contributed to impressive advancements such as the discoveries of the pulmonary ionocyte and of a profibrotic macrophage population in pulmonary fibrosis. In this review, we discuss general technical considerations when considering the use of scRNA-seq and examine how leading investigators have applied the technology to gain novel insights into respiratory biology, from development to disease. In addition, we discuss the evolution of single-cell technologies with a focus on spatial and multi-omics approaches that promise to drive continued innovation in respiratory research.

Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM

Single-nucleus RNA sequencing (snRNA-seq) measures gene expression in individual nuclei instead of cells, allowing for unbiased cell type characterization in solid tissues. We observe that snRNA-seq is commonly subject to contamination by high amounts of ambient RNA, which can lead to biased downstream analyses, such as identification of spurious cell types if overlooked. We present a novel approach to quantify contamination and filter droplets in snRNA-seq experiments, called Debris Identification using Expectation Maximization (DIEM). Our likelihood-based approach models the gene expression distribution of debris and cell types, which are estimated using EM. We evaluated DIEM using three snRNA-seq data sets: (1) human differentiating preadipocytes in vitro, (2) fresh mouse brain tissue, and (3) human frozen adipose tissue (AT) from six individuals. All three data sets showed evidence of extranuclear RNA contamination, and we observed that existing methods fail to account for contaminated droplets and led to spurious cell types. When compared to filtering using these state of the art methods, DIEM better removed droplets containing high levels of extranuclear RNA and led to higher quality clusters. Although DIEM was designed for snRNA-seq, our clustering strategy also successfully filtered single-cell RNA-seq data. To conclude, our novel method DIEM removes debris-contaminated droplets from single-cell-based data fast and effectively, leading to cleaner downstream analysis. Our code is freely available for use at https://github.com/marcalva/diem.

Medical Treatment of Lung Cancer: Can Immune Cells Predict the Response? A Systematic Review

The landscape for medical treatment of lung cancer has irreversibly changed since the development of immuno-oncology (IO). Yet, while immune checkpoint blockade (ICB) revealed that T lymphocytes play a major role in lung cancer, the precise dynamic of innate and adaptive immune cells induced by anticancer treatments including chemotherapy, targeted therapy, and/or ICB is poorly understood. In lung cancer, studies evaluating specific immune cell populations as predictors of response to medical treatment are scarce, and knowledge is fragmented. Here, we review the different techniques allowing the detection of immune cells in the tumor and blood (multiplex immunohistochemistry and immunofluorescence, RNA-seq, DNA methylation pattern, mass cytometry, functional tests). In addition, we present data that consider different baseline immune cell populations as predictors of response to medical treatments of lung cancer. We also review the potential for assessing dynamic changes in cell populations during treatment as a biomarker. As powerful tools for immune cell detection and data analysis are available, clinicians and researchers could increase understanding of mechanisms of efficacy and resistance in addition to identifying new targets for IO by developing translational studies that decipher the role of different immune cell populations during lung cancer treatments.

Transcriptome Analysis of iPSC-Derived Neurons from Rubinstein-Taybi Patients Reveals Deficits in Neuronal Differentiation

Rubinstein-Taybi syndrome (RSTS) is a rare multisystem developmental disorder with moderate to severe intellectual disability caused by heterozygous mutations of either CREBBP or EP300 genes encoding CBP/p300 chromatin regulators. We explored the gene programs and processes underlying the morphological and functional alterations shown by iPSC-derived neurons modeling RSTS to bridge the molecular changes resulting from defective CBP/p300 to cognitive impairment. By global transcriptome analysis, we compared the differentially expressed genes (DEGs) marking the transition from iPSC-derived neural progenitors to cortical neurons (iNeurons) of five RSTS patients carrying private CREBBP/EP300 mutations and manifesting differently graded neurocognitive signs with those of four healthy controls. Our data shows a defective and altered neuroprogenitor to neuron transcriptional program in the cells from RSTS patients. First, transcriptional regulation is weaker in RSTS as less genes than in controls are modulated, including genes of key processes of mature functional neurons, such as those for voltage-gated channels and neurotransmitters and their receptors. Second, regulation is subverted as genes acting at pre-terminal stages of neural differentiation in cell polarity and adhesive functions (members of the cadherin family) and axon extension/guidance (members of the semaphorins and SLIT receptors families) are improperly upregulated. Impairment or delay of RSTS neuronal differentiation program is also evidenced by decreased modulation of the overall number of neural differentiation markers, significantly impacting the initial and final stages of the differentiation cascade. Last, extensive downregulation of genes for RNA/DNA metabolic processes confirms that RSTS is a global transcription disorder, consistent with a syndrome driven by chromatin dysregulation. Interestingly, the morphological and functional alterations we have previously appointed as biomarkers of RSTS iNeurons provide functional support to the herein designed transcriptome profile pointing to key dysregulated neuronal genes as main contributors to patients’ cognitive deficit. The impact of RSTS transcriptome may go beyond RSTS as comparison of dysregulated genes across modeled neurodevelopmental disorders could unveil convergent genes of cognitive impairment.

Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data

Motivation

Finding non-linear relationships between biomolecules and a biological outcome is computationally expensive and statistically challenging. Existing methods have important drawbacks, including among others lack of parsimony, non-convexity and computational overhead. Here we propose block HSIC Lasso, a non-linear feature selector that does not present the previous drawbacks.

Results

We compare block HSIC Lasso to other state-of-the-art feature selection techniques in both synthetic and real data, including experiments over three common types of genomic data: gene-expression microarrays, single-cell RNA sequencing and genome-wide association studies. In all cases, we observe that features selected by block HSIC Lasso retain more information about the underlying biology than those selected by other techniques. As a proof of concept, we applied block HSIC Lasso to a single-cell RNA sequencing experiment on mouse hippocampus. We discovered that many genes linked in the past to brain development and function are involved in the biological differences between the types of neurons.

Availability and implementation

Block HSIC Lasso is implemented in the Python 2/3 package pyHSICLasso, available on PyPI. Source code is available on GitHub (https://github.com/riken-aip/pyHSICLasso).

Supplementary information

Supplementary data are available at Bioinformatics online.

Transcriptomics: a Solution for Renal Osteodystrophy?

PURPOSE OF REVIEW

The molecular mechanisms of the bone disease associated with chronic kidney disease (CKD), called renal osteodystrophy (ROD), are poorly understood. New transcriptomics technologies may provide clinically relevant insights into the pathogenesis of ROD. This review summarizes current progress and limitations in the study and treatment of ROD, and in transcriptomics analyses of skeletal tissues.

RECENT FINDINGS

ROD is characterized by poor bone quality and strength leading to increased risk of fracture. Recent studies indicate permanent alterations in bone cell populations during ROD. Single-cell transcriptomics analyses, successful at identifying specialized cell subpopulations in bone, have not yet been performed in ROD. ROD is a widespread poorly understood bone disease with limited treatment options. Transcriptomics analyses of bone are needed to identify the bone cell subtypes and their role in the pathogenesis of ROD, and to develop adequate diagnosis and treatment strategies.

Systematic comparison of single-cell and single-nucleus RNA-sequencing methods

The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling-selecting representative methods based on their usage and our expertise and resources to prepare libraries-including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.

KAT3-dependent acetylation of cell type-specific genes maintains neuronal identity in the adult mouse brain

The lysine acetyltransferases type 3 (KAT3) family members CBP and p300 are important transcriptional co-activators, but their specific functions in adult post-mitotic neurons remain unclear. Here, we show that the combined elimination of both proteins in forebrain excitatory neurons of adult mice resulted in a rapidly progressing neurological phenotype associated with severe ataxia, dendritic retraction and reduced electrical activity. At the molecular level, we observed the downregulation of neuronal genes, as well as decreased H3K27 acetylation and pro-neural transcription factor binding at the promoters and enhancers of canonical neuronal genes. The combined deletion of CBP and p300 in hippocampal neurons resulted in the rapid loss of neuronal molecular identity without de- or transdifferentiation. Restoring CBP expression or lysine acetylation rescued neuronal-specific transcription in cultured neurons. Together, these experiments show that KAT3 proteins maintain the excitatory neuron identity through the regulation of histone acetylation at cell type-specific promoter and enhancer regions.

Neuronal identity maintenance is highly regulated. Here, the authors showed that CBP and p300 safeguard neuronal identity through histone acetylation at promoters and enhancers of neuronal specific genes. The loss of both CBP and p300 impairs gene expression, circuit activity, and behavior in mice.

Single-cell genomic analysis of human cerebral organoids

Investigating early brain development has previously relied on using primary developing brain tissue or two-dimensional cell culture models. Recently, stem cell-derived three-dimensional cell culture systems, collectively called brain organoids, have been developed that can faithfully recapitulate many aspects of early brain development. Together with the ability to reprogram fibroblast or blood cells into induced pluripotent stem cells from humans with neurodevelopmental disorders, this opens new inroads to study patient-specific brain development in a personalized cell culture model. Studying the transcriptomes and regulatory landscape of single cells within brain organoids presents a major advance to understand cell-type specific features and transient states during development, and to link these states to their underlying regulatory logic at high resolution. In this protocol, we describe how to generate single-cell RNA-seq and ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) data from the same suspension of organoid cells and focus on reducing batch effects by multiplexing multiple individuals in one experiment. Moreover, we outline basic data processing, analysis, and strategies to correct for batch effects, to account for variability in organoids and for integrating gene expression and open chromatin data.

APEC: an accesson-based method for single-cell chromatin accessibility analysis

The development of sequencing technologies has promoted the survey of genome-wide chromatin accessibility at single-cell resolution. However, comprehensive analysis of single-cell epigenomic profiles remains a challenge. Here, we introduce an accessibility pattern-based epigenomic clustering (APEC) method, which classifies each cell by groups of accessible regions with synergistic signal patterns termed “accessons”. This python-based package greatly improves the accuracy of unsupervised single-cell clustering for many public datasets. It also predicts gene expression, identifies enriched motifs, discovers super-enhancers, and projects pseudotime trajectories. APEC is available at https://github.com/QuKunLab/APEC.