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The amygdala is one of the most widely studied regions in behavioral neuroscience. A plethora of classical, and new paradigms have dissected its precise involvement in emotional and social sensing, learning, and memory. Several important insights resulted from the use of genetic markers – yet, in the age of single cell transcriptomics, the amygdala remains molecularly underdescribed. Here, we present a molecular cell type taxonomy of the full mouse amygdala in fear learning and consolidation. We performed single-cell RNA-seq on naïve and fear conditioned mice, inferred the 130 neuronal cell types distributions in silico using orthogonal spatial transcriptomic datasets, and describe the cell types’ transcriptional responses to learning and memory consolidation. Only a fraction of cells, within a subset of all neuronal types, were transcriptionally responsive to fear learning, memory and retrieval. These activated engram cells upregulated activity-response genes, and processes of synaptic signaling, plasticity, development and neurite outgrowth. Our transcriptome-wide data confirm known actors, and describe several new candidate genes. The atlas may help pinpoint the amygdala’s circuits in performing emotional sensing and integration, and provide new insights to the global cellular processes involved.

Protein responses to extracellular cues are governed by gene transcription, mRNA degradation and translation, and protein degradation. In order to understand how these time-dependent processes cooperate to generate dynamic responses, we analyzed the response of human mammary cells to the epidermal growth factor (EGF). Integrating time-dependent transcript and protein data into a mathematical model, we inferred for several proteins their pre-and post-stimulus translation and degradation coefficients and found that they exhibit complex, time-dependent variation. Specifically, we identified strategies of protein production and degradation acting in concert to generate rapid, transient protein bursts in response to EGF. Remarkably, for some proteins, for which the response necessitates rapidly decreased abundance, cells exhibit a transient increase in the corresponding degradation coefficient. Our model and analysis allow inference of the kinetics of mRNA translation and protein degradation, without perturbing cells, and open a way to understanding the fundamental processes governing time-dependent protein abundance profiles.

The hypothalamus contains the highest diversity of neurons in the brain. Many of these neurons can co-release neurotransmitters and neuropeptides in a use-dependent manner. Investigators have hitherto relied on candidate protein-based tools to correlate behavioral, endocrine and gender traits with hypothalamic neuron identity. Here we map neuronal identities in the hypothalamus by single-cell RNA sequencing. We distinguished 62 neuronal subtypes producing glutamatergic, dopaminergic or GABAergic markers for synaptic neurotransmission and harboring the ability to engage in task-dependent neurotransmitter switching. We identified dopamine neurons that uniquely coexpress the Onecut3 and Nmur2 genes, and placed these in the periventricular nucleus with many synaptic afferents arising from neuromedin S(+) neurons of the suprachiasmatic nucleus. These neuroendocrine dopamine cells may contribute to the dopaminergic inhibition of prolactin secretion diurnally, as their neuromedin S(+) inputs originate from neurons expressing Per2 and Per3 and their tyrosine hydroxylase phosphorylation is regulated in a circadian fashion. Overall, our catalog of neuronal subclasses provides new understanding of hypothalamic organization and function.

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 throughput 1 . 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.

Summary Striatal locally projecting neurons, or interneurons, act on nearby circuits and shape functional output to the rest of the basal ganglia. We performed single-cell RNA sequencing of striatal cells enriching for interneurons. We find seven discrete interneuron types, six of which are GABAergic. In addition to providing specific markers for the populations previously described, including those expressing Sst/Npy, Th, Npy without Sst, and Chat, we identify two small populations of cells expressing Cck with or without Vip. Surprisingly, the Pvalb-expressing cells do not constitute a discrete cluster but rather are part of a larger group of cells expressing Pthlh with a spatial gradient of Pvalb expression. Using PatchSeq, we show that Pthlh cells exhibit a continuum of electrophysiological properties correlated with expression of Pvalb. Furthermore, we find significant molecular differences that correlate with differences in electrophysiological properties between Pvalb-expressing cells of the striatum and those of the cortex., Graphical Abstract, Highlights • Single-cell RNA sequencing of striatal interneurons reveals seven main classes • Subclass-specific latent factor analysis reveals gradients of gene expression • Pvalb neurons are not a discrete class but belong to a class expressing Pthlh • Interneuron classes vary in their similarity to counterparts from cortex/hippocampus, Muñoz-Manchado et al. describe the molecular and electrophysiological diversity of interneurons from the striatum. They find that in contrast to many other brain regions, cells expressing the gene Pvalb are not a discrete class of cells. This affects the interpretation of studies on striatal networks and their function.

osmFISHisacyclicsinglemolecule fluorescentinsituhybridizationprotocolused toquantify theexpressionlevelof specific transcriptsintissuesections by direct labeling of individualRNAmolecules. The number of transcripts quantified in each round correspondthe numbers offluorophores available in the microscope setup. In order to quantify a large number of genes,osmFISH provides a method toremove theprobes/labelling (stripping) fromtheirtargets and get the tissue ready forthenextroundoflabeling-imaging-stripping. Even though theosmFISH protocol has been developed toperform multiple smFISH rounds, it can also be used asaquick and simple methodfor one-round smFISH. Furthermore, the protocol can be further extended toinclude more complex encoding/barcoding shemes that can be used to resolve a larger number of targets.

The mammalian nervous system executes complex behaviors controlled by specialised, 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 several distinct, regionally restricted, astrocytes types, which 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.

The global efforts towards the creation of a molecular census of the brain using single-cell transcriptomics is generating a large catalog of molecularly defined cell types lacking spatial information. Thus, new methods are needed to map a large number of cell-specific markers simultaneously on large tissue areas. Here, we developed a cyclic single molecule fluorescence in situ hybridization methodology and defined the cellular organization of the somatosensory cortex using markers identified by single-cell transcriptomics.

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.

The dorsal horn of the spinal cord is critical to processing distinct modalities of noxious and innocuous sensation, but little is known of the neuronal subtypes involved, hampering efforts to deduce principles governing somatic sensation. Here we used single-cell RNA sequencing to classify sensory neurons in the mouse dorsal horn. We identified 15 inhibitory and 15 excitatory molecular subtypes of neurons, equaling the complexity in cerebral cortex. Validating our classification scheme in vivo and matching cell types to anatomy of the dorsal horn by spatial transcriptomics reveals laminar enrichment for each of the cell types. Neuron types, when combined, define a multilayered organization with like neurons layered together. Employing our scheme, we find that heat and cold stimuli activate discrete sets of both excitatory and inhibitory neuron types. This work provides a systematic and comprehensive molecular classification of spinal cord sensory neurons, enabling functional interrogation of sensory processing.

Cellular diversity in the brain revealed The mammalian brain has an extraordinarily large number of cells. Although there are quite a few different cell types, many cells in any one category tend to look alike. Zeisel et al. analyzed the transcriptomes of mouse brain cells to reveal more than meets the eye. Interneurons of similar type were found in dissimilar regions of the brain. Oligodendrocytes that seemed to be all of one class were differentiated by their molecular signatures into a half-dozen classes. Microglia associated with blood vessels were distinguished from look-alike perivascular macrophages. Thus, the complex microanatomy of the brain can be revealed by the RNAs expressed in its cells. Science , this issue p. 1138

RNA abundance is a powerful indicator of the state of individual cells, but does not directly reveal dynamic processes such as cellular differentiation. Here we show that RNA velocity—the time derivative of RNA abundance—can be estimated by distinguishing unspliced and spliced mRNAs in standard single-cell RNA sequencing protocols. We show that RNA velocity is a vector that predicts the future state of individual cells on a timescale of hours. We validate the accuracy of RNA velocity in the neural crest lineage, demonstrate its use on multiple technical platforms, reconstruct the branching lineage tree of the mouse hippocampus, and measure RNA kinetics in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

The dentate gyrus in the hippocampal formation is one of few regions in the brain where neurogenesis persists in the adult, and is therefore studied in the context of neurodevelopment and regenerative medicine. However, the relationship between developmental and adult neurogenesis has not been studied in detail. Here, we used extensive and unbiased single-cell RNA-seq to reveal the molecular dynamics and diversity of cell types in perinatal, juvenile and adult mice. We found clearly distinct quiescent and proliferating progenitor cell types, linked by transient intermediate states to neuroblast stages and fully mature granule cells. The molecular identity of quiescent and proliferating radial glia shifted after postnatal day 5, and was then maintained through postnatal and adult stages. A similar shift was observed for granule cells at P20. In contrast, intermediate progenitor cells, neuroblasts and immature granule cells were nearly indistinguishable at all ages. These findings demonstrate the fundamental continunity of postnatal and adult neurogenesis in the hippocampus, and pinpoint the early postnatal transformation of radial glia from embryonic progenitors to adult quiescent stem cells.

BackgroundMost of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16-33% of the total length). Thus, many bacteria may share the same amplified region and the resolution of profiling is inherently limited. Platforms that offer ultra long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others, all allow different ways to circumvent this problem yet suffer various shortcomings. There is need for a simple and low cost 16S rRNA gene based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA.ResultsThis manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. Thede factoamplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution byin silicosimulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about two-fold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200bp (80%) of the 16S rRNA gene we were able to achieve ~100 fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, profiling of aDrosophila melanogastermicrobiome using the set of six primer pairs provided a ~100 fold increase in resolution, and thus enabling efficient downstream analysis.ConclusionsSMURF enables identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of Formalin-fixed and Paraffin-embedded samples, fossil-derived DNA or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in Multilocus Sequence Typing (MLST).

The dentate gyrus of the hippocampus is a brain region in which neurogenesis persists into adulthood; however, the relationship between developmental and adult dentate gyrus neurogenesis has not been examined in detail. Here we used single-cell RNA sequencing to reveal the molecular dynamics and diversity of dentate gyrus cell types in perinatal, juvenile, and adult mice. We found distinct quiescent and proliferating progenitor cell types, linked by transient intermediate states to neuroblast stages and fully mature granule cells. We observed shifts in the molecular identity of quiescent and proliferating radial glia and granule cells during the postnatal period that were then maintained through adult stages. In contrast, intermediate progenitor cells, neuroblasts, and immature granule cells were nearly indistinguishable at all ages. These findings demonstrate the fundamental similarity of postnatal and adult neurogenesis in the hippocampus and pinpoint the early postnatal transformation of radial glia from embryonic progenitors to adult quiescent stem cells.

Collective migration is an important cellular trait, which is intensely studied by both basic and translational researchers. Investigation of the underlying mechanisms necessitates high-throughput assays and computational algorithms capable of generating reproducible quantitative measurements of cell migration. We present a desktop tool that can be used easily by any researcher, to quantify both fluorescent and phase-contrast images produced in the course of commonly used gap closure ("scratch," "wound healing") collective migration assays. The software has a simple graphical interface that allows the user to tune the relevant parameters and process large numbers of images (or movies). The output contains segmented images and the numerical values inferred from them, allowing easy quantitative analysis of the results.

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.

Summary 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., Graphical Abstract, Highlights • Species differences in developmental timing and cell proliferation • Multiple radial glia subtypes biased toward distinct fates • Adult dopaminergic neuron subtypes emerge postnatally • A machine learning method to score dopaminergic differentiation of stem cells, Analyzing the time course of ventral midbrain development in mouse, human, and stem cells by single-cell RNA-sequencing provides insight into dopaminergic neuron development and offers a strategy to assess the composition of stem-cell-derived preparations for clinical applications.

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.

This paper deals with the stability of water waves in a shear flow. Both temporal and spatial growth rates are derived. A carefully designed numerical solver enables us to extend the range of previous calculations, and to obtain results for larger wavelengths (up to 20 cm) and stronger winds (up to a friction-velocity of 1 m s−1). The main finding is the appearance of a second unstable mode which often turns out to be the dominant one. A comparison between results from the viscous model (Orr–Sommerfeld equations) and those of the inviscid model (Rayleigh equations), for 18 cm long waves, reveals some similarity in the structure of the eigenfunctions, but a significant difference in the imaginary part of the eigenvalues (i.e. the growth rate). It is found that the growth rate for the viscous model is 10 fold larger than that of the inviscid one.

Traditionally, neuroscientists have defined the identity of neurons by the cells' location, morphology, connectivity and excitability. However, the direct relationship between these parameters and the molecular phenotypes has remained largely unexplored. Here, we present a method for obtaining full transcriptome data from single neocortical pyramidal cells and interneurons after whole-cell patch-clamp recordings in mouse brain slices. In our approach, termed Patch-seq, a patch-clamp stimulus protocol is followed by the aspiration of the entire somatic compartment into the recording pipette, reverse transcription of RNA including addition of unique molecular identifiers, cDNA amplification, Illumina library preparation and sequencing. We show that Patch-seq reveals a close link between electrophysiological characteristics, responses to acute chemical challenges and RNA expression of neurotransmitter receptors and channels. Moreover, it distinguishes neuronal subpopulations that correspond to both well-established and, to our knowledge, hitherto undescribed neuronal subtypes. Our findings demonstrate the ability of Patch-seq to precisely map neuronal subtypes and predict their network contributions in the brain.

The mammalian cerebral cortex supports cognitive functions such as sensorimotor integration, memory, and social behaviors. Normal brain function relies on a diverse set of differentiated cell types, including neurons, glia, and vasculature. Here, we have used large-scale single-cell RNA sequencing (RNA-seq) to classify cells in the mouse somatosensory cortex and hippocampal CA1 region. We found 47 molecularly distinct subclasses, comprising all known major cell types in the cortex. We identified numerous marker genes, which allowed alignment with known cell types, morphology, and location. We found a layer I interneuron expressing Pax6 and a distinct postmitotic oligodendrocyte subclass marked by Itpr2. Across the diversity of cortical cell types, transcription factors formed a complex, layered regulatory code, suggesting a mechanism for the maintenance of adult cell type identity.

none 27 si Dissemination of primary tumor cells depends on migratory and invasive attributes. Here, we identify Navigator-3 (NAV3), a gene frequently mutated or deleted in human tumors, as a regulator of epithelial migration and invasion. Following induction by growth factors, NAV3 localizes to the plus ends of microtubules and enhances their polarized growth. Accordingly, NAV3 depletion trimmed microtubule growth, prolonged growth factor signaling, prevented apoptosis and enhanced random cell migration. Mathematical modeling suggested that NAV3-depleted cells acquire an advantage in terms of the way they explore their environment. In animal models, silencing NAV3 increased metastasis, whereas ectopic expression of the wild-type form, unlike expression of two, relatively unstable oncogenic mutants from human tumors, inhibited metastasis. Congruently, analyses of > 2,500 breast and lung cancer patients associated low NAV3 with shorter survival. We propose that NAV3 inhibits breast cancer progression by regulating microtubule dynamics, biasing directionally persistent rather than random migration, and inhibiting locomotion of initiated cells. Hadas Cohen-Dvashi1, Nir Ben-Chetrit1, Roslin Russell2, Silvia Carvalho1, Mattia Lauriola1,‡, Sophia Nisani1, Maicol Mancini1, Nishanth Nataraj1, Merav Kedmi1, Lee Roth1, Wolfgang Köstler1,†, Amit Zeisel3, Assif Yitzhaky3, Jacques Zylberg4, Gabi Tarcic1, Raya Eilam1, Yoav Wigelman1, Rainer Will5, Sara Lavi1, Ziv Porat6, Stefan Wiemann5, Sara Ricardo7, Fernando Schmitt7, Carlos Caldas2 & Yosef Yarden1,* Hadas Cohen-Dvashi1, Nir Ben-Chetrit1, Roslin Russell2, Silvia Carvalho1, Mattia Lauriola1,‡, Sophia Nisani1, Maicol Mancini1, Nishanth Nataraj1, Merav Kedmi1, Lee Roth1, Wolfgang Köstler1,†, Amit Zeisel3, Assif Yitzhaky3, Jacques Zylberg4, Gabi Tarcic1, Raya Eilam1, Yoav Wigelman1, Rainer Will5, Sara Lavi1, Ziv Porat6, Stefan Wiemann5, Sara Ricardo7, Fernando Schmitt7, Carlos Caldas2 & Yosef Yarden1,*

This work was supported by the Swedish Research Council (T.Ha., T.Hö.), Hjärnfonden (T.Ha.), the Petrus and Augusta Hedlunds Foundation (T.Ha., T.Hö.), the Novo Nordisk Foundation (T.Ha., T.Hö.), Karolinska Institutet (T.Hö.), the Medical University of Vienna (T.Ha.), ANR (France, ANR-10-INBS-04-01, M.L.), the European Commission (PAINCAGE grant, T.Ha.) and the Wellcome Trust (094476/Z/10/Z, equipment grant, C.H.B. and postdoctoral research fellowship, M.F.). 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 Ca2+ 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. Postprint

Cells cope with replication-blocking lesions via translesion DNA synthesis (TLS). TLS is carried out by low-fidelity DNA polymerases that replicate across lesions, thereby preventing genome instability at the cost of increased point mutations. Here we perform a two-stage siRNA-based functional screen for mammalian TLS genes and identify 17 validated TLS genes. One of the genes, NPM1, is frequently mutated in acute myeloid leukaemia (AML). We show that NPM1 (nucleophosmin) regulates TLS via interaction with the catalytic core of DNA polymerase-η (polη), and that NPM1 deficiency causes a TLS defect due to proteasomal degradation of polη. Moreover, the prevalent NPM1c+ mutation that causes NPM1 mislocalization in ~30% of AML patients results in excessive degradation of polη. These results establish the role of NPM1 as a key TLS regulator, and suggest a mechanism for the better prognosis of AML patients carrying mutations in NPM1., Cells cope with replication-blocking DNA lesions by translesion DNA synthesis (TLS) polymerases, including polη. Here, the authors show that NPM1, a gene frequently mutated in acute myeloid leukaemia, protects polη from proteasomal degradation, and that NPM1 deficiency causes a TLS defect.

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 (Cx43del/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 Cx43del/deloocyte 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 ofEgr1,Rpl21andEif4a1in Cx43del/deloocytes and downregulation ofRpl15andEif4g2in 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.

Signal transduction by receptor tyrosine kinases (RTKs) and nuclear receptors for steroid hormones is essential for body homeostasis, but the cross-talk between these receptor families is poorly understood. We observed that glucocorticoids inhibit signalling downstream of EGFR, an RTK. The underlying mechanism entails suppression of EGFR’s positive feedback loops and simultaneous triggering of negative feedback loops that normally restrain EGFR. Our studies in mice reveal that the regulation of EGFR’s feedback loops by glucocorticoids translates to circadian control of EGFR signalling: EGFR signals are suppressed by high glucocorticoids during the active phase (night-time in rodents), while EGFR signals are enhanced during the resting phase. Consistent with this pattern, treatment of animals bearing EGFR-driven tumours with a specific kinase inhibitor was more effective if administered during the resting phase of the day, when glucocorticoids are low. These findings support a circadian clock-based paradigm in cancer therapy., Glucocorticoids are released in a diurnal pattern. Here, the authors show that EGF receptor (EGFR) signalling is negatively regulated by glucocorticoids, and that EGFR inhibitor has stronger antitumour effects when administered during the resting phase, when glucocorticoids are low, offering potential optimization of cancer therapy regimens.

Commensal gut bacteria in many species including flies are integral part of their host, and are known to influence its development and homeostasis within generation. Here we report an unexpected impact of host-microbe interactions, which mediates multi-generational, non-Mendelian inheritance of a stress-induced phenotype. We have previously shown that exposure of fly larvae to G418 antibiotic induces transgenerationally heritable phenotypes, including a delay in larval development, gene induction in the gut and morphological changes. We now show that G418 selectively depletes commensal Acetobacter species and that this depletion explains the heritable delay, but not the inheritance of the other phenotypes. Notably, the inheritance of the delay was mediated by a surprising trans-generational effect. Specifically, bacterial removal from F1 embryos did not induce significant delay in F1 larvae, but nonetheless led to a considerable delay in F2. This effect maintains a delay induced by bacterial-independent G418 toxicity to the host. In line with these findings, reintroduction of isolated Acetobacter species prevented the inheritance of the delay. We further show that this prevention is partly mediated by vitamin B2 (Riboflavin) produced by these bacteria; exogenous Riboflavin led to partial prevention and inhibition of Riboflavin synthesis compromised the ability of the bacteria to prevent the inheritance.These results identify host-microbe interactions as a hitherto unrecognized factor capable of mediating non-Mendelian inheritance of a stress-induced phenotype.

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.

Signal-induced transcript isoform variation (TIV) includes alternative promoter usage as well as alternative splicing and alternative polyadenylation of mRNA. To assess the phenotypic relevance of signal-induced TIV, we employed exon arrays and breast epithelial cells, which migrate in response to the epidermal growth factor (EGF). We show that EGF rapidly – within one hour – induces widespread TIV in a significant fraction of the transcriptome. Importantly, TIV characterizes many genes that display no differential expression upon stimulus. In addition, similar EGF-dependent changes are shared by a panel of mammary cell lines. A functional screen, which utilized isoform-specific siRNA oligonucleotides, indicated that several isoforms play essential, non-redundant roles in EGF-induced mammary cell migration. Taken together, our findings highlight the importance of TIV in the rapid evolvement of a phenotypic response to extracellular signals.

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.

We describe the Microbial Community Reconstruction (MCR) Problem, which is fundamental for microbiome analysis. In this problem, the goal is to reconstruct the identity and frequency of species comprising a microbial community, using short sequence reads from Massively Parallel Sequencing (MPS) data obtained for specified genomic regions. We formulate the problem mathematically as a convex optimization problem and provide sufficient conditions for identifiability, namely the ability to reconstruct species identity and frequency correctly when the data size (number of reads) grows to infinity. We discuss different metrics for assessing the quality of the reconstructed solution, including a novel phylogenetically-aware metric based on the Mahalanobis distance, and give upper-bounds on the reconstruction error for a finite number of reads under different metrics. We propose a scalable divide-and-conquer algorithm for the problem using convex optimization, which enables us to handle large problems (with $\sim\!10^6$ species). We show using numerical simulations that for realistic scenarios, where the microbial communities are sparse, our algorithm gives solutions with high accuracy, both in terms of obtaining accurate frequency, and in terms of species phylogenetic resolution.

The HER2/neu oncogene encodes a receptor-like tyrosine kinase whose overexpression in breast cancer predicts poor prognosis and resistance to conventional therapies. However, the mechanisms underlying aggressiveness of HER2 (human epidermal growth factor receptor 2)-overexpressing tumors remain incompletely understood. Because it assists epidermal growth factor (EGF) and neuregulin receptors, we overexpressed HER2 in MCF10A mammary cells and applied growth factors. HER2-overexpressing cells grown in extracellular matrix formed filled spheroids, which protruded outgrowths upon growth factor stimulation. Our transcriptome analyses imply a two-hit model for invasive growth: HER2-induced proliferation and evasion from anoikis generate filled structures, which are morphologically and transcriptionally analogous to preinvasive patients’ lesions. In the second hit, EGF escalates signaling and transcriptional responses leading to invasive growth. Consistent with clinical relevance, a gene expression signature based on the HER2/EGF-activated transcriptional program can predict poorer prognosis of a subgroup of HER2-overexpressing patients. In conclusion, the integration of a three-dimensional cellular model and clinical data attributes progression of HER2-overexpressing lesions to EGF-like growth factors acting in the context of the tumor's microenvironment.

The steep rise in availability and usage of high-throughput technologies in biology brought with it a clear need for methods to control the False Discovery Rate (FDR) in multiple tests. Benjamini and Hochberg (BH) introduced in 1995 a simple procedure and proved that it provided a bound on the expected value, $\mathit{FDR}\leq q$. Since then, many authors tried to improve the BH bound, with one approach being designing adaptive procedures, which aim at estimating the number of true null hypothesis in order to get a better FDR bound. Our two main rigorous results are the following: (i) a theorem that provides a bound on the FDR for adaptive procedures that use any estimator for the number of true hypotheses ($m_0$), (ii) a theorem that proves a monotonicity property of general BH-like procedures, both for the case where the hypotheses are independent. We also propose two improved procedures for which we prove FDR control for the independent case, and demonstrate their advantages over several available bounds, on simulated data and on a large number of gene expression data sets. Both applications are simple and involve a similar amount of computation as the original BH procedure. We compare the performance of our proposed procedures with BH and other procedures and find that in most cases we get more power for the same level of statistical significance., Comment: Published in at http://dx.doi.org/10.1214/10-AOAS399 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)

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.

Epidermal growth factor (EGF) stimulates cells by launching gene expression programs that are frequently deregulated in cancer. MicroRNAs, which attenuate gene expression by binding complementary regions in messenger RNAs, are broadly implicated in cancer. Using genome-wide approaches, we showed that EGF stimulation initiates a coordinated transcriptional program of microRNAs and transcription factors. The earliest event involved a decrease in the abundance of a subset of 23 microRNAs. This step permitted rapid induction of oncogenic transcription factors, such as c-FOS, encoded by immediate early genes. In line with roles as suppressors of EGF receptor (EGFR) signaling, we report that the abundance of this early subset of microRNAs is decreased in breast and in brain tumors driven by the EGFR or the closely related HER2. These findings identify specific microRNAs as attenuators of growth factor signaling and oncogenesis.

Signal transduction by receptor tyrosine kinases (RTKs) and nuclear receptors for steroid hormones is essential for body homeostasis, but the crosstalk between these receptor families is poorly understood. We observed that activation of GR, a steroid hormone receptor that binds glucocorticoids, inhibits the transcriptional response downstream to EGFR signaling, an RTK. The underlying mechanism entails suppression of EGFR's positive feedback loops, such as ligands and simultaneous triggering of negative feedback loops that normally restrain EGFR. Our animal studies reveal that the regulation of EGFR's feedback loops by glucocorticoids translates to circadian control of EGFR signaling: EGFR signals are suppressed by high glucocorticoids during the active phase, while EGFR signals are enhanced during the resting phase. Consistent with this pattern, treatment of animals bearing EGFR-driven tumors with a specific kinase inhibitor was more effective if administered during the resting phase of the day, when glucocorticoids are low. These findings support a circadian clock-based paradigm in cancer therapy. Citation Format: Mattia Lauriola, Yehoshua Enuka, Amit Zeisel, Gabriele D'Uva, Lee Roth, Silvia Carvalho, Rossella Solmi, Eytan Domany, Yosef Yarden. Diurnal suppression of EGFR signaling by glucocorticoids: implications for tumor progression and treatment. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3475. doi:10.1158/1538-7445.AM2015-3475

Genome-wide simultaneous measurements of pre-mRNA and mRNA expression reveal unexpected time-dependent transcript production and degradation profiles in response to external stimulus, as well as a striking lack of concordance between mRNA abundance and transcript production profiles., By analyzing the signals from intronic probes of exon arrays, we performed, for the first time, genome-wide measurement of pre-mRNA expression dynamics. We discovered a striking lack of correspondence between mRNA and pre-mRNA temporal expression profiles following stimulus, demonstrating that measurement of mRNA dynamics does not suffice to infer transcript production profiles. By combining simultaneous measurement of pre-mRNA and mRNA profiles with a simple new quantitative theoretical description of transcription, we are able to infer complex time dependence of both transcript production and mRNA degradation. The production profiles of many transcripts reveal an operational strategy we termed Production Overshoot, which is used to accelerate mRNA response. The biological relevance of our findings was substantiated by observing similar results when studying the response of three different mammalian cell types to different 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.

Background: Carcinomas of the breast account for one third of all cancers occurring in woman and responsible for approximately one quarter of cancer-related deaths in females. The HER2/Neu -oncogene is amplified in 20-25% percent of human primary breast cancers and this alteration is associated with disease behaviour. Whereas signalling pathways emanating from HER2 have been characterized, much less is known about the transcriptionally regulated genes that contribute to HER2 tumorigenic effects.Materials and Methods: Normal and HER2 overexpressing mammary epithelial cells (MCF10A) were grown in extracellular matrix to form 3D structures, which allow epithelial cells to organize into structures that resemble their in vivo architecture. RNA was isolated from the 3D structures and hybridized to an Affymetrix HuGene 1.0 ST oligonucleotide array.Results: Upon HER2 overexpression, mammary epithelial cells lost their polarity and formed disorganized structures in matrigel. Using microarrays we analyzed transcriptional events responsible for the morphological changes and found that several sets of genes such as integral proteins, transcription factors, matrix proteases and chemokines were highly altered in the HER2 overexpressing group. Using gene annotation we defined molecular-pathways which are highly altered in HER2 overexpressing cells. More generally, our study proposes a mechanistic description of the processes underlying the HER2 transcriptional network. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 4146.