Molecular Architecture of the Mouse Nervous System.

The mammalian nervous system executes complex behaviors controlled by specialized, precisely positioned, and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse and were grouped by developmental anatomical units and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission, and membrane conductance. We discovered seven distinct, regionally restricted astrocyte types that obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system and enables genetic manipulation of specific cell types.

Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells.

Understanding human embryonic ventral midbrain is of major interest for Parkinson's disease. However, the cell types, their gene expression dynamics, and their relationship to commonly used rodent models remain to be defined. We performed single-cell RNA sequencing to examine ventral midbrain development in human and mouse. We found 25 molecularly defined human cell types, including five subtypes of radial glia-like cells and four progenitors. In the mouse, two mature fetal dopaminergic neuron subtypes diversified into five adult classes during postnatal development. Cell types and gene expression were generally conserved across species, but with clear differences in cell proliferation, developmental timing, and dopaminergic neuron development. Additionally, we developed a method to quantitatively assess the fidelity of dopaminergic neurons derived from human pluripotent stem cells, at a single-cell level. Thus, our study provides insight into the molecular programs controlling human midbrain development and provides a foundation for the development of cell replacement therapies.

RNA velocity of single cells.

RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput1. However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity-the time derivative of the gene expression state-can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols. RNA velocity is a high-dimensional vector that predicts the future state of individual cells on a timescale of hours. We validate its accuracy in the neural crest lineage, demonstrate its use on multiple published datasets and technical platforms, reveal the branching lineage tree of the developing mouse hippocampus, and examine the kinetics of transcription in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

Spatial organization of the somatosensory cortex revealed by osmFISH.

Global efforts to create a molecular census of the brain using single-cell transcriptomics are producing a large catalog of molecularly defined cell types. However, spatial information is lacking and new methods are needed to map a large number of cell type-specific markers simultaneously on large tissue areas. Here, we describe a cyclic single-molecule fluorescence in situ hybridization methodology and define the cellular organization of the somatosensory cortex.

A secretagogin locus of the mammalian hypothalamus controls stress hormone release.

A hierarchical hormonal cascade along the hypothalamic-pituitary-adrenal axis orchestrates bodily responses to stress. Although corticotropin-releasing hormone (CRH), produced by parvocellular neurons of the hypothalamic paraventricular nucleus (PVN) and released into the portal circulation at the median eminence, is known to prime downstream hormone release, the molecular mechanism regulating phasic CRH release remains poorly understood. Here, we find a cohort of parvocellular cells interspersed with magnocellular PVN neurons expressing secretagogin. Single-cell transcriptome analysis combined with protein interactome profiling identifies secretagogin neurons as a distinct CRH-releasing neuron population reliant on secretagogin's Ca(2+) sensor properties and protein interactions with the vesicular traffic and exocytosis release machineries to liberate this key hypothalamic releasing hormone. Pharmacological tools combined with RNA interference demonstrate that secretagogin's loss of function occludes adrenocorticotropic hormone release from the pituitary and lowers peripheral corticosterone levels in response to acute stress. Cumulatively, these data define a novel secretagogin neuronal locus and molecular axis underpinning stress responsiveness.

Quantitative single-cell RNA-seq with unique molecular identifiers.

Single-cell RNA sequencing (RNA-seq) is a powerful tool to reveal cellular heterogeneity, discover new cell types and characterize tumor microevolution. However, losses in cDNA synthesis and bias in cDNA amplification lead to severe quantitative errors. We show that molecular labels--random sequences that label individual molecules--can nearly eliminate amplification noise, and that microfluidic sample preparation and optimized reagents produce a fivefold improvement in mRNA capture efficiency.

High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions.

The emergence of massively parallel sequencing technology has revolutionized microbial profiling, allowing the unprecedented comparison of microbial diversity across time and space in a wide range of host-associated and environmental ecosystems. Although the high-throughput nature of such methods enables the detection of low-frequency bacteria, these advances come at the cost of sequencing read length, limiting the phylogenetic resolution possible by current methods. Here, we present a generic approach for integrating short reads from large genomic regions, thus enabling phylogenetic resolution far exceeding current methods. The approach is based on a mapping to a statistical model that is later solved as a constrained optimization problem. We demonstrate the utility of this method by analyzing human saliva and Drosophila samples, using Illumina single-end sequencing of a 750 bp amplicon of the 16S rRNA gene. Phylogenetic resolution is significantly extended while reducing the number of falsely detected bacteria, as compared with standard single-region Roche 454 Pyrosequencing. Our approach can be seamlessly applied to simultaneous sequencing of multiple genes providing a higher resolution view of the composition and activity of complex microbial communities.

An accessible database for mouse and human whole transcriptome qPCR primers.

MOTIVATION: Real time quantitative polymerase chain reaction (qPCR) is an important tool in quantitative studies of DNA and RNA molecules; especially in transcriptome studies, where different primer combinations allow identification of specific transcripts such as splice variants or precursor messenger RNA. Several softwares that implement various rules for optimal primer design are available. Nevertheless, as designing qPCR primers needs to be done manually, the repeated task is tedious, time consuming and prone to errors. RESULTS: We used a set of rules to automatically design all possible exon-exon and intron-exon junctions in the human and mouse transcriptomes. The resulting database is included as a track in the UCSC genome browser, making it widely accessible and easy to use. AVAILABILITY: The database is available from the UCSC genome browser (http://genome.ucsc.edu/), track name 'Whole Transcriptome qPCR Primers' for the hg19 (Human) and mm10 (Mouse) genome versions. Batch query is available in the following: http://www.weizmann.ac.il/complex/compphys/software/Amit/primers/batch_query_qpcr_primers.htm CONTACT: amit.zeisel@weizmann.ac.il or eytan.domany@weizmann.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Blastocyst implantation failure relates to impaired translational machinery gene expression.

Oocyte quality is a well-established determinant of embryonic fate. However, the molecular participants and biological markers that affect and may predict adequate embryonic development are largely elusive. Our aim was to identify the components of the oocyte molecular machinery that part take in the production of a healthy embryo. For this purpose, we used an animal model, generated by us previously, the oocytes of which do not express Cx43 (Cx43(del/del)). In these mice, oogenesis appears normal, fertilisation does occur, early embryonic development is successful but implantation fails. We used magnetic resonance imaging analysis combined with histological examination to characterise the embryonic developmental incompetence. Reciprocal embryo transfer confirmed that the blastocyst evolved from the Cx43(del/del) oocyte is responsible for the implantation disorder. In order to unveil the genes, the impaired expression of which brings about the development of defective embryos, we carried out a genomic screening of both the oocytes and the resulting blastocysts. This microarray analysis revealed a low expression of Egr1, Rpl21 and Eif4a1 in Cx43(del/del) oocytes and downregulation of Rpl15 and Eif4g2 in the resulting blastocysts. We propose that global deficiencies in genes related to the expression of ribosomal proteins and translation initiation factors in apparently normal oocytes bring about accumulation of defects, which significantly compromise their developmental capacity. The blastocysts resulting from such oocytes, which grow within a confined space until implantation, may be unable to generate enough biological mass to allow their expansion. This information could be implicated to diagnosis and treatment of infertility, particularly to IVF.

Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets.

MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miR's targets is a considerable bioinformatic challenge of great importance for inferring the miR's function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methods--it identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs' function in a specific context.

Placental senescence pathophysiology is shared between peripartum cardiomyopathy and preeclampsia in mouse and human.

Peripartum cardiomyopathy (PPCM) is an idiopathic form of pregnancy-induced heart failure associated with preeclampsia. Circulating factors in late pregnancy are thought to contribute to both diseases, suggesting a common underlying pathophysiological process. However, what drives this process remains unclear. Using serum proteomics, we identified the senescence-associated secretory phenotype (SASP), a marker of cellular senescence associated with biological aging, as the most highly up-regulated pathway in young women with PPCM or preeclampsia. Placentas from women with preeclampsia displayed multiple markers of amplified senescence and tissue aging, as well as overall increased gene expression of 28 circulating proteins that contributed to SASP pathway enrichment in serum samples from patients with preeclampsia or PPCM. The most highly expressed placental SASP factor, activin A, was associated with cardiac dysfunction or heart failure severity in women with preeclampsia or PPCM. In a murine model of PPCM induced by cardiomyocyte-specific deletion of the gene encoding peroxisome proliferator-activated receptor γ coactivator-1α, inhibiting activin A signaling in the early postpartum period with a monoclonal antibody to the activin type II receptor improved heart function. In addition, attenuating placental senescence with the senolytic compound fisetin in late pregnancy improved cardiac function in these animals. These findings link senescence biology to cardiac dysfunction in pregnancy and help to elucidate the pathogenesis underlying cardiovascular diseases of pregnancy.

BMP-mediated inhibition of FGF signaling promotes cardiomyocyte differentiation of anterior heart field progenitors.

The anterior heart field (AHF) encompasses a niche in which mesoderm-derived cardiac progenitors maintain their multipotent and undifferentiated nature in response to signals from surrounding tissues. Here, we investigate the signaling mechanism that promotes the shift from proliferating cardiac progenitors to differentiating cardiomyocytes in chick embryos. Genomic and systems biology approaches, as well as perturbations of signaling molecules, in vitro and in vivo, reveal tight crosstalk between the bone morphogenetic protein (BMP) and fibroblast growth factor (FGF) signaling pathways within the AHF niche: BMP4 promotes myofibrillar gene expression and cardiomyocyte contraction by blocking FGF signaling. Furthermore, inhibition of the FGF-ERK pathway is both sufficient and necessary for these processes, suggesting that FGF signaling blocks premature differentiation of cardiac progenitors in the AHF. We further revealed that BMP4 induced a set of neural crest-related genes, including MSX1. Overexpression of Msx1 was sufficient to repress FGF gene expression and cell proliferation, thereby promoting cardiomyocyte differentiation. Finally, we show that BMP-induced cardiomyocyte differentiation is diminished following cranial neural crest ablation, underscoring the key roles of these cells in the regulation of AHF cell differentiation. Hence, BMP and FGF signaling pathways act via inter- and intra-regulatory loops in multiple tissues, to coordinate the balance between proliferation and differentiation of cardiac progenitors.

Sexual dimorphism in synaptic inputs to the mouse amygdala and orbital cortex.

The medial amygdala (MeA) is a sexually dimorphic brain region that regulates fear responses, emotional memories, and social behaviors. It is known to be larger and contains more cells in males. The MeA integrates information through input connections from olfactory regions, bed nucleus of the stria terminalis, ventral hippocampus, and thalamic and hypothalamic structures. We hypothesize that in addition to the size differences, there are differences in regional connectivity between the sexes. In this study, we utilized G-deleted rabies monosynaptic retrograde tracing to compare amygdala presynaptic cells in male and female whole mouse brains. We report differences in connection patterns to the amygdala, with higher overall connectivity (presynaptic per starter) in males and a larger fraction of inputs originating from the bed nucleus of the stria terminalis, lateral septum, and medial preoptic area. Furthermore, we examined input connections to the orbital cortex (ORB), a brain region shown to be larger in volume in females, and found the opposite trend, where females had more total inputs. Together, our findings extend the evidence for sexual dimorphism in the brain to the neuronal wiring pattern, with likely impacts on behavior and disease susceptibility.

Sex, strain, and lateral differences in brain cytoarchitecture across a large mouse population.

The mouse brain is by far the most intensively studied among mammalian brains, yet basic measures of its cytoarchitecture remain obscure. For example, quantifying cell numbers, and the interplay of sex, strain, and individual variability in cell density and volume is out of reach for many regions. The Allen Mouse Brain Connectivity project produces high-resolution full brain images of hundreds of brains. Although these were created for a different purpose, they reveal details of neuroanatomy and cytoarchitecture. Here, we used this population to systematically characterize cell density and volume for each anatomical unit in the mouse brain. We developed a DNN-based segmentation pipeline that uses the autofluorescence intensities of images to segment cell nuclei even within the densest regions, such as the dentate gyrus. We applied our pipeline to 507 brains of males and females from C57BL/6J and FVB.CD1 strains. Globally, we found that increased overall brain volume does not result in uniform expansion across all regions. Moreover, region-specific density changes are often negatively correlated with the volume of the region; therefore, cell count does not scale linearly with volume. Many regions, including layer 2/3 across several cortical areas, showed distinct lateral bias. We identified strain-specific or sex-specific differences. For example, males tended to have more cells in extended amygdala and hypothalamic regions (MEA, BST, BLA, BMA, and LPO, AHN) while females had more cells in the orbital cortex (ORB). Yet, inter-individual variability was always greater than the effect size of a single qualifier. We provide the results of this analysis as an accessible resource for the community.

Two distinct molecular faces of preeclampsia revealed by single-cell transcriptomics.

INTRODUCTION: Preeclampsia is a multisystemic, pregnancy-specific disorder united by new-onset hypertension but with considerable variation in clinical manifestation, onset, and severity. For symptoms to regress, delivery of the placenta is required. For symptoms to regress, delivery of the placenta is required, making the placenta central to preeclampsia pathophysiology. To dissect which placental functions were impacted in two forms of preeclampsia, we studied molecular changes across the cell types of the placenta. METHODS: We performed a transcriptomic survey of single-cells and single-nuclei on cases of early- and late-onset preeclampsia with gestation-matched controls. FINDINGS: Our data revealed massive dysregulation of gene expression in all cell classes that was almost exclusive to early preeclampsia. For example, an important known receptor/ligand imbalance hallmarking angiogenic disfunction, sFLT1/placental growth factor (PGF), was reflected in striking, cell-autonomous dysregulation of FLT1 and PGF transcription in the syncytium in early preeclampsia only. Stromal cells and vasculature echoed an inflamed, stressed, anti-angiogenic environment. Finally, the placental immune niche set the tone for inflammation in early but not late preeclampsia. Here, fetal-origin Hofbauer and maternal-origin TREM2 macrophages were revealed as surprising main actors, while local cells of the adaptive immune system were largely unaffected. Late preeclampsia showed minimal cellular impact on the placenta. CONCLUSIONS: Our survey provides systematic molecular evidence for two distinct diseases. We resolved systematic molecular dysregulation to individual cell types with strong implications for definition, early detection, diagnosis, and treatment. FUNDING: Funded by the Preeclampsia Foundation through the Peter Joseph Pappas Research Grant.

Neuronal types in the mouse amygdala and their transcriptional response to fear conditioning.

The amygdala is a brain region primarily associated with emotional response. The use of genetic markers and single-cell transcriptomics can provide insights into behavior-associated cell state changes. Here we present a detailed cell-type taxonomy of the adult mouse amygdala during fear learning and memory consolidation. We perform single-cell RNA sequencing on naïve and fear-conditioned mice, identify 130 neuronal cell types and validate their spatial distributions. A subset of all neuronal types is transcriptionally responsive to fear learning and memory retrieval. The activated engram cells upregulate activity-response genes and coordinate the expression of genes associated with neurite outgrowth, synaptic signaling, plasticity and development. We identify known and previously undescribed candidate genes responsive to fear learning. Our molecular atlas may be used to generate hypotheses to unveil the neuron types and neural circuits regulating the emotional component of learning and memory.

A telencephalon cell type atlas for goldfish reveals diversity in the evolution of spatial structure and cell types.

Teleost fish form the largest group of vertebrates and show a tremendous variety of adaptive behaviors, making them critically important for the study of brain evolution and cognition. The neural basis mediating these behaviors remains elusive. We performed a systematic comparative survey of the goldfish telencephalon. We mapped cell types using single-cell RNA sequencing and spatial transcriptomics, resulting in de novo molecular neuroanatomy parcellation. Glial cells were highly conserved across 450 million years of evolution separating mouse and goldfish, while neurons showed diversity and modularity in gene expression. Specifically, somatostatin interneurons, famously interspersed in the mammalian isocortex for local inhibitory input, were curiously aggregated in a single goldfish telencephalon nucleus but molecularly conserved. Cerebral nuclei including the striatum, a hub for motivated behavior in amniotes, had molecularly conserved goldfish homologs. We suggest elements of a hippocampal formation across the goldfish pallium. Last, aiding study of the teleostan everted telencephalon, we describe substantial molecular similarities between goldfish and zebrafish neuronal taxonomies.

Expert review: preeclampsia Type I and Type II.

Pregnancy involves an interplay between maternal and fetal factors affecting changes to maternal anatomy and physiology to support the developing fetus and ensure the well-being of both the mother and offspring. A century of research has provided evidence of the imperative role of the placenta in the development of preeclampsia. Recently, a growing body of evidence has supported the adaptations of the maternal cardiovascular system during normal pregnancy and its maladaptation in preeclampsia. Debate surrounds the roles of the placenta vs the maternal cardiovascular system in the pathophysiology of preeclampsia. We proposed an integrated model of the maternal cardiac-placental-fetal array and the development of preeclampsia, which reconciles the disease phenotypes and their proposed origins, whether placenta-dominant or maternal cardiovascular system-dominant. These phenotypes are sufficiently diverse to define 2 distinct types: preeclampsia Type I and Type II. Type I preeclampsia may present earlier, characterized by placental dysfunction or malperfusion, shallow trophoblast invasion, inadequate spiral artery conversion, profound syncytiotrophoblast stress, elevated soluble fms-like tyrosine kinase-1 levels, reduced placental growth factor levels, high peripheral vascular resistance, and low cardiac output. Type I is more often accompanied by fetal growth restriction, and low placental growth factor levels have a measurable impact on maternal cardiac remodeling and function. Type II preeclampsia typically occurs in the later stages of pregnancy and entails an evolving maternal cardiovascular intolerance to the demands of pregnancy, with a moderately dysfunctional placenta and inadequate blood supply. The soluble fms-like tyrosine kinase-1-placental growth factor ratio may be normal or slightly disturbed, peripheral vascular resistance is low, and cardiac output is high, but these adaptations still fail to meet demand. Emergent placental dysfunction, coupled with an increasing inability to meet demand, more often appears with fetal macrosomia, multiple pregnancies, or prolonged pregnancy. Support for the notion of 2 types of preeclampsia observable on the molecular level is provided by single-cell transcriptomic survey of gene expression patterns across different cell classes. This revealed widespread dysregulation of gene expression across all cell types, and significant imbalance in fms-like tyrosine kinase-1 (FLT1) and placental growth factor, particularly marked in the syncytium of early preeclampsia cases. Classification of preeclampsia into Type I and Type II can inform future research to develop targeted screening, prevention, and treatment approaches.

Coupled pre-mRNA and mRNA dynamics unveil operational strategies underlying transcriptional responses to stimuli.

Transcriptional responses to extracellular stimuli involve tuning the rates of transcript production and degradation. Here, we show that the time-dependent profiles of these rates can be inferred from simultaneous measurements of precursor mRNA (pre-mRNA) and mature mRNA profiles. Transcriptome-wide measurements demonstrate that genes with similar mRNA profiles often exhibit marked differences in the amplitude and onset of their production rate. The latter is characterized by a large dynamic range, with a group of genes exhibiting an unexpectedly strong transient production overshoot, thereby accelerating their induction and, when combined with time-dependent degradation, shaping transient responses with precise timing and amplitude.

Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes.

BACKGROUND: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one searches for differentially expressed genes, the small number of samples gives rise to an inaccurate estimation of the experimental noise. This, in turn, leads to loss of statistical power. RESULTS: We show that the measurement noise of genes with similar expression levels (intensity) is identically and independently distributed, and that this (intensity dependent) distribution is approximately normal. Our method can be easily adapted and used to test whether these statement hold for data from any particular microarray experiment. We propose a method that provides an accurate estimation of the intensity-dependent variance of the noise distribution, and demonstrate that using this estimation we can detect differential expression with much better statistical power than that of standard t-test, and can compare the noise levels of different experiments and platforms. CONCLUSIONS: When the number of samples is small, the simple method we propose improves significantly the statistical power in identifying differentially expressed genes.