Age-associated changes in lineage composition of the enteric nervous system regulate gut health and disease

The enteric nervous system (ENS), a collection of neural cells contained in the wall of the gut, is of fundamental importance to gastrointestinal and systemic health. According to the prevailing paradigm, the ENS arises from progenitor cells migrating from the neural crest and remains largely unchanged thereafter. Here, we show that the lineage composition of maturing ENS changes with time, with a decline in the canonical lineage of neural-crest derived neurons and their replacement by a newly identified lineage of mesoderm-derived neurons. Single cell transcriptomics and immunochemical approaches establish a distinct expression profile of mesoderm-derived neurons. The dynamic balance between the proportions of neurons from these two different lineages in the post-natal gut is dependent on the availability of their respective trophic signals, GDNF-RET and HGF-MET. With increasing age, the mesoderm-derived neurons become the dominant form of neurons in the ENS, a change associated with significant functional effects on intestinal motility which can be reversed by GDNF supplementation. Transcriptomic analyses of human gut tissues show reduced GDNF-RET signaling in patients with intestinal dysmotility which is associated with reduction in neural crest-derived neuronal markers and concomitant increase in transcriptional patterns specific to mesoderm-derived neurons. Normal intestinal function in the adult gastrointestinal tract therefore appears to require an optimal balance between these two distinct lineages within the ENS.

Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS

Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional post hoc statistics and annotation for interpretation of learned features. Here, we introduce a suite of computational tools that implement NMF and provide methods for accurate and clear biological interpretation and analysis. A generalized discussion of NMF covering its benefits, limitations and open questions is followed by four procedures for the Bayesian NMF algorithm Coordinated Gene Activity across Pattern Subsets (CoGAPS). Each procedure will demonstrate NMF analysis to quantify cell state transitions in a public domain single-cell RNA-sequencing dataset. The first demonstrates PyCoGAPS, our new Python implementation that enhances runtime for large datasets, and the second allows its deployment in Docker. The third procedure steps through the same single-cell NMF analysis using our R CoGAPS interface. The fourth introduces a beginner-friendly CoGAPS platform using GenePattern Notebook, aimed at users with a working conceptual knowledge of data analysis but without a basic proficiency in the R or Python programming language. We also constructed a user-facing website to serve as a central repository for information and instructional materials about CoGAPS and its application programming interfaces. The expected timing to setup the packages and conduct a test run is around 15 min, and an additional 30 min to conduct analyses on a precomputed result. The expected runtime on the user's desired dataset can vary from hours to days depending on factors such as dataset size or input parameters.

Semaphorin 6A in Retinal Ganglion Cells Regulates Functional Specialization of the Inner Retina

To form functional circuits, neurons must settle in their appropriate cellular locations and then project and elaborate neurites to contact their target synaptic neuropils. Laminar organization within the vertebrate retinal inner plexiform layer (IPL) facilitates pre- and postsynaptic neurite targeting, yet, the precise mechanisms underlying establishment of functional IPL subdomains are not well understood. Here we explore mechanisms defining the compartmentalization of OFF and ON neurites generally, and OFF and ON direction-selective neurites specifically, within the developing IPL. We show that semaphorin 6A (Sema6A), a repulsive axon guidance cue, is required for delineation of OFF versus ON circuits within the IPL: in the Sema6a null IPL, the boundary between OFF and ON domains is blurred. Furthermore, Sema6A expressed by retinal ganglion cells (RGCs) directs laminar segregation of OFF and ON starburst amacrine cell (SAC) dendritic scaffolds, which themselves serve as a substrate upon which other retinal neurites elaborate. These results demonstrate for the first time that RGCs, the first neuron-type born within the retina, play an active role in functional specialization of the IPL. Retinal ganglion cell-dependent regulation of OFF and ON starburst amacrine cell dendritic scaffold segregation prevents blurring of OFF versus ON functional domains in the murine inner plexiform layer.

Pumping the brakes on RNA velocity by understanding and interpreting RNA velocity estimates

BACKGROUND

RNA velocity analysis of single cells offers the potential to predict temporal dynamics from gene expression. In many systems, RNA velocity has been observed to produce a vector field that qualitatively reflects known features of the system. However, the limitations of RNA velocity estimates are still not well understood.

RESULTS

We analyze the impact of different steps in the RNA velocity workflow on direction and speed. We consider both high-dimensional velocity estimates and low-dimensional velocity vector fields mapped onto an embedding. We conclude the transition probability method for mapping velocity estimates onto an embedding is effectively interpolating in the embedding space. Our findings reveal a significant dependence of the RNA velocity workflow on smoothing via the k-nearest-neighbors (k-NN) graph of the observed data. This reliance results in considerable estimation errors for both direction and speed in both high- and low-dimensional settings when the k-NN graph fails to accurately represent the true data structure; this is an unknown feature of real data. RNA velocity performs poorly at estimating speed in both low- and high-dimensional spaces, except in very low noise settings. We introduce a novel quality measure that can identify when RNA velocity should not be used.

CONCLUSIONS

Our findings emphasize the importance of choices in the RNA velocity workflow and highlight critical limitations of data analysis. We advise against over-interpreting expression dynamics using RNA velocity, particularly in terms of speed. Finally, we emphasize that the use of RNA velocity in assessing the correctness of a low-dimensional embedding is circular.

Ret deficiency decreases neural crest progenitor proliferation and restricts fate potential during enteric nervous system development

The receptor tyrosine kinase RET plays a critical role in the fate specification of enteric neural crest-derived cells (ENCDCs) during enteric nervous system (ENS) development. RET loss of function (LoF) is associated with Hirschsprung disease (HSCR), which is marked by aganglionosis of the gastrointestinal (GI) tract. Although the major phenotypic consequences and the underlying transcriptional changes from Ret LoF in the developing ENS have been described, cell type- and state-specific effects are unknown. We performed single-cell RNA sequencing on an enriched population of ENCDCs from the developing GI tract of Ret null heterozygous and homozygous mice at embryonic day (E)12.5 and E14.5. We demonstrate four significant findings: 1) Ret-expressing ENCDCs are a heterogeneous population comprising ENS progenitors as well as glial- and neuronal-committed cells; 2) neurons committed to a predominantly inhibitory motor neuron developmental trajectory are not produced under Ret LoF, leaving behind a mostly excitatory motor neuron developmental program; 3) expression patterns of HSCR-associated and Ret gene regulatory network genes are impacted by Ret LoF; and 4) Ret deficiency leads to precocious differentiation and reduction in the number of proliferating ENS precursors. Our results support a model in which Ret contributes to multiple distinct cellular phenotypes during development of the ENS, including the specification of inhibitory neuron subtypes, cell cycle dynamics of ENS progenitors, and the developmental timing of neuronal and glial commitment.

Psychedelics reopen the social reward learning critical period

Psychedelics are a broad class of drugs defined by their ability to induce an altered state of consciousness1,2. These drugs have been used for millennia in both spiritual and medicinal contexts, and a number of recent clinical successes have spurred a renewed interest in developing psychedelic therapies3-9. Nevertheless, a unifying mechanism that can account for these shared phenomenological and therapeutic properties remains unknown. Here we demonstrate in mice that the ability to reopen the social reward learning critical period is a shared property across psychedelic drugs. Notably, the time course of critical period reopening is proportional to the duration of acute subjective effects reported in humans. Furthermore, the ability to reinstate social reward learning in adulthood is paralleled by metaplastic restoration of oxytocin-mediated long-term depression in the nucleus accumbens. Finally, identification of differentially expressed genes in the 'open state' versus the 'closed state' provides evidence that reorganization of the extracellular matrix is a common downstream mechanism underlying psychedelic drug-mediated critical period reopening. Together these results have important implications for the implementation of psychedelics in clinical practice, as well as the design of novel compounds for the treatment of neuropsychiatric disease.

The transcription factor Tbx5 regulates direction-selective retinal ganglion cell development and image stabilization

The diversity of visual input processed by the mammalian visual system requires the generation of many distinct retinal ganglion cell (RGC) types, each tuned to a particular feature. The molecular code needed to generate this cell-type diversity is poorly understood. Here, we focus on the molecules needed to specify one type of retinal cell: the upward-preferring ON direction-selective ganglion cell (up-oDSGC) of the mouse visual system. Single-cell transcriptomic profiling of up- and down-oDSGCs shows that the transcription factor Tbx5 is selectively expressed in up-oDSGCs. The loss of Tbx5 in up-oDSGCs results in a selective defect in the formation of up-oDSGCs and a corresponding inability to detect vertical motion. A downstream effector of Tbx5, Sfrp1, is also critical for vertical motion detection but not up-oDSGC formation. These results advance our understanding of the molecular mechanisms that specify a rare retinal cell type and show how disrupting this specification leads to a corresponding defect in neural circuitry and behavior.

Prenatal immune stress blunts microglia reactivity, impairing neurocircuitry

Recent studies suggested that microglia, the primary brain immune cells, can affect circuit connectivity and neuronal function1,2. Microglia infiltrate the neuroepithelium early in embryonic development and are maintained in the brain throughout adulthood3,4. Several maternal environmental factors-such as an aberrant microbiome, immune activation and poor nutrition-can influence prenatal brain development5,6. Nevertheless, it is unknown how changes in the prenatal environment instruct the developmental trajectory of infiltrating microglia, which in turn affect brain development and function. Here we show that, after maternal immune activation (MIA) in mice, microglia from the offspring have a long-lived decrease in immune reactivity (blunting) across the developmental trajectory. The blunted immune response was accompanied by changes in chromatin accessibility and reduced transcription factor occupancy of the open chromatin. Single-cell RNA-sequencing analysis revealed that MIA does not induce a distinct subpopulation but, rather, decreases the contribution to inflammatory microglia states. Prenatal replacement of microglia from MIA offspring with physiological infiltration of naive microglia ameliorated the immune blunting and restored a decrease in presynaptic vesicle release probability onto dopamine receptor type-two medium spiny neurons, indicating that aberrantly formed microglia due to an adverse prenatal environment affect the long-term microglia reactivity and proper striatal circuit development.

Postnatal Smad3 Inactivation in Murine Smooth Muscle Cells Elicits a Temporally and Regionally Distinct Transcriptional Response

Heterozygous, loss of function mutations in positive regulators of the Transforming Growth Factor-β (TGF-β) pathway cause hereditary forms of thoracic aortic aneurysm. It is unclear whether and how the initial signaling deficiency triggers secondary signaling upregulation in the remaining functional branches of the pathway, and if this contributes to maladaptive vascular remodeling. To examine this process in a mouse model in which time-controlled, partial interference with postnatal TGF-β signaling in vascular smooth muscle cells (VSMCs) could be assessed, we used a VSMC-specific tamoxifen-inducible system, and a conditional allele, to inactivate Smad3 at 6 weeks of age, after completion of perinatal aortic development. This intervention induced dilation and histological abnormalities in the aortic root, with minor involvement of the ascending aorta. To analyze early and late events associated with disease progression, we performed a comparative single cell transcriptomic analysis at 10- and 18-weeks post-deletion, when aortic dilation is undetectable and moderate, respectively. At the early time-point, Smad3-inactivation resulted in a broad reduction in the expression of extracellular matrix components and critical components of focal adhesions, including integrins and anchoring proteins, which was reflected histologically by loss of connections between VSMCs and elastic lamellae. At the later time point, however, expression of several transcripts belonging to the same functional categories was normalized or even upregulated; this occurred in association with upregulation of transcripts coding for TGF-β ligands, and persistent downregulation of negative regulators of the pathway. To interrogate how VSMC heterogeneity may influence this transition, we examined transcriptional changes in each of the four VSMC subclusters identified, regardless of genotype, as partly reflecting the proximal-to-distal anatomic location based on in situ RNA hybridization. The response to Smad3-deficiency varied depending on subset, and VSMC subsets over-represented in the aortic root, the site most vulnerable to dilation, most prominently upregulated TGF-β ligands and pro-pathogenic factors such as thrombospondin-1, angiotensin converting enzyme, and pro-inflammatory mediators. These data suggest that Smad3 is required for maintenance of focal adhesions, and that loss of contacts with the extracellular matrix has consequences specific to each VSMC subset, possibly contributing to the regional susceptibility to dilation in the aorta.

Follistatin promotes LIN28B-mediated supporting cell reprogramming and hair cell regeneration in the murine cochlea

Hair cell (HC) loss within the inner ear cochlea is a leading cause for deafness in humans. Before the onset of hearing, immature supporting cells (SCs) in neonatal mice have some limited capacity for HC regeneration. Here, we show that in organoid culture, transient activation of the progenitor-specific RNA binding protein LIN28B and Activin antagonist follistatin (FST) enhances regenerative competence of maturing/mature cochlear SCs by reprogramming them into progenitor-like cells. Transcriptome profiling and mechanistic studies reveal that LIN28B drives SC reprogramming, while FST is required to counterbalance hyperactivation of transforming growth factor-β-type signaling by LIN28B. Last, we show that LIN28B and FST coactivation enhances spontaneous cochlear HC regeneration in neonatal mice and that LIN28B may be part of an endogenous repair mechanism that primes SCs for HC regeneration. These findings indicate that SC dedifferentiation is critical for HC regeneration and identify LIN28B and FST as main regulators.

Universal prediction of cell-cycle position using transfer learning

BACKGROUND

The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data.

RESULTS

Here, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the use of transfer learning. We estimate a cell-cycle embedding using a fixed reference dataset and project new data into this reference embedding, an approach that overcomes key limitations of learning a dataset-dependent embedding. Tricycle then predicts a cell-specific position in the cell cycle based on the data projection. The accuracy of tricycle compares favorably to gold-standard experimental assays, which generally require specialized measurements in specifically constructed in vitro systems. Using internal controls which are available for any dataset, we show that tricycle predictions generalize to datasets with multiple cell types, across tissues, species, and even sequencing assays.

CONCLUSIONS

Tricycle generalizes across datasets and is highly scalable and applicable to atlas-level single-cell RNA-seq data.

An in vivo screen of noncoding loci reveals that Daedalus is a gatekeeper of an Ikaros-dependent checkpoint during haematopoiesis

Haematopoiesis relies on tightly controlled gene expression patterns as development proceeds through a series of progenitors. While the regulation of hematopoietic development has been well studied, the role of noncoding elements in this critical process is a developing field. In particular, the discovery of new regulators of lymphopoiesis could have important implications for our understanding of the adaptive immune system and disease. Here we elucidate how a noncoding element is capable of regulating a broadly expressed transcription factor, Ikaros, in a lymphoid lineage-specific manner, such that it imbues Ikaros with the ability to specify the lymphoid lineage over alternate fates. Deletion of the Daedalus locus, which is proximal to Ikaros, led to a severe reduction in early lymphoid progenitors, exerting control over the earliest fate decisions during lymphoid lineage commitment. Daedalus locus deletion led to alterations in Ikaros isoform expression and a significant reduction in Ikaros protein. The Daedalus locus may function through direct DNA interaction as Hi-C analysis demonstrated an interaction between the two loci. Finally, we identify an Ikaros-regulated erythroid-lymphoid checkpoint that is governed by Daedalus in a lymphoid-lineage-specific manner. Daedalus appears to act as a gatekeeper of Ikaros's broad lineage-specifying functions, selectively stabilizing Ikaros activity in the lymphoid lineage and permitting diversion to the erythroid fate in its absence. These findings represent a key illustration of how a transcription factor with broad lineage expression must work in concert with noncoding elements to orchestrate hematopoietic lineage commitment.

Parallel Social Information Processing Circuits Are Differentially Impacted in Autism

Parallel processing circuits are thought to dramatically expand the network capabilities of the nervous system. Magnocellular and parvocellular oxytocin neurons have been proposed to subserve two parallel streams of social information processing, which allow a single molecule to encode a diverse array of ethologically distinct behaviors. Here we provide the first comprehensive characterization of magnocellular and parvocellular oxytocin neurons in male mice, validated across anatomical, projection target, electrophysiological, and transcriptional criteria. We next use novel multiple feature selection tools in Fmr1-KO mice to provide direct evidence that normal functioning of the parvocellular but not magnocellular oxytocin pathway is required for autism-relevant social reward behavior. Finally, we demonstrate that autism risk genes are enriched in parvocellular compared with magnocellular oxytocin neurons. Taken together, these results provide the first evidence that oxytocin-pathway-specific pathogenic mechanisms account for social impairments across a broad range of autism etiologies.

projectR: an R/Bioconductor package for transfer learning via PCA, NMF, correlation and clustering

MOTIVATION

Dimension reduction techniques are widely used to interpret high-dimensional biological data. Features learned from these methods are used to discover both technical artifacts and novel biological phenomena. Such feature discovery is critically importent in analysis of large single-cell datasets, where lack of a ground truth limits validation and interpretation. Transfer learning (TL) can be used to relate the features learned from one source dataset to a new target dataset to perform biologically driven validation by evaluating their use in or association with additional sample annotations in that independent target dataset.

RESULTS

We developed an R/Bioconductor package, projectR, to perform TL for analyses of genomics data via TL of clustering, correlation and factorization methods. We then demonstrate the utility TL for integrated data analysis with an example for spatial single-cell analysis.

AVAILABILITY AND IMPLEMENTATION

projectR is available on Bioconductor and at https://github.com/genesofeve/projectR.

CONTACT

gsteinobrien@jhmi.edu or ejfertig@jhmi.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Developmental, cellular, and behavioral phenotypes in a mouse model of congenital hypoplasia of the dentate gyrus

In the hippocampus, a widely accepted model posits that the dentate gyrus improves learning and memory by enhancing discrimination between inputs. To test this model, we studied conditional knockout mice in which the vast majority of dentate granule cells (DGCs) fail to develop – including nearly all DGCs in the dorsal hippocampus – secondary to eliminating Wntless (Wls) in a subset of cortical progenitors with Gfap-Cre. Other cells in the Wls^fl/-;Gfap-Cre hippocampus were minimally affected, as determined by single nucleus RNA sequencing. CA3 pyramidal cells, the targets of DGC-derived mossy fibers, exhibited normal morphologies with a small reduction in the numbers of synaptic spines. Wls^fl/-;Gfap-Cre mice have a modest performance decrement in several complex spatial tasks, including active place avoidance. They were also modestly impaired in one simpler spatial task, finding a visible platform in the Morris water maze. These experiments support a role for DGCs in enhancing spatial learning and memory.

Screening non-MAPT genes of the Chr17q21 H1 haplotype in Parkinson's disease

INTRODUCTION

The microtubule-associated protein tau (MAPT) gene is considered a strong genetic risk factor for Parkinson's disease (PD) in Caucasians. MAPT is located within an inversion region of high linkage disequilibrium designated as H1 and H2 haplotype, and contains eight other genes which have been implicated in neurodegeneration. The aim of the current study was to identify common coding variants in strong linkage disequilibrium (LD) within the associated loci on chr17q21 harboring MAPT.

METHODS

Sanger sequencing of coding exons in 90 Caucasian late-onset PD (LOPD) patients was performed. Specific gene sequencing for LRRC37A, LRRC37A2, ARL17A and ARL17B was not possible given the high homology, presence of pseudogenes and copy number variants that are in the region, and therefore four genes (NSF, KANSL1, SPPL2C, and CRHR1) were included in the analysis. Coding variants from these four genes that did not perfectly tag (r² = 1) the MAPT H1/H2 haplotype were genotyped in an independent replication series of Caucasian PD cases (N = 851) and controls (N = 730).

RESULTS

In the 90 LOPD cases we identified 30 coding variants. Eleven non-synonymous variants tagged the MAPT H1/H2 haplotype, including two SPPL2C variants (rs12185233 and rs12373123) that had high pathogenic combined annotation dependent depletion (CADD) scores of >20. In the replication series, the non-synonymous KANSL1 rs17585974 variant was in very strong LD with MAPT H1/H2 and had a high CADD score of 24.7.

CONCLUSION

We have identified several non-synonymous variants across neighboring genes of MAPT that may warrant further genetic and functional investigation within the biological etiology of PD.

Increased expression of anion transporter SLC26A9 delays diabetes onset in cystic fibrosis

Diabetes is a common complication of cystic fibrosis (CF) that affects approximately 20% of adolescents and 40%-50% of adults with CF. The age at onset of CF-related diabetes (CFRD) (marked by clinical diagnosis and treatment initiation) is an important measure of the disease process. DNA variants associated with age at onset of CFRD reside in and near SLC26A9. Deep sequencing of the SLC26A9 gene in 762 individuals with CF revealed that 2 common DNA haplotypes formed by the risk variants account for the association with diabetes. Single-cell RNA sequencing (scRNA-Seq) indicated that SLC26A9 is predominantly expressed in pancreatic ductal cells and frequently coexpressed with CF transmembrane conductance regulator (CFTR) along with transcription factors that have binding sites 5' of SLC26A9. These findings were replicated upon reanalysis of scRNA-Seq data from 4 independent studies. DNA fragments derived from the 5' region of SLC26A9-bearing variants from the low-risk haplotype generated 12%-20% higher levels of expression in PANC-1 and CFPAC-1 cells compared with the high- risk haplotype. Taken together, our findings indicate that an increase in SLC26A9 expression in ductal cells of the pancreas delays the age at onset of diabetes, suggesting a CFTR-agnostic treatment for a major complication of CF.

Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species

Analysis of gene expression in single cells allows for decomposition of cellular states as low-dimensional latent spaces. However, the interpretation and validation of these spaces remains a challenge. Here, we present scCoGAPS, which defines latent spaces from a source single-cell RNA-sequencing (scRNA-seq) dataset, and projectR, which evaluates these latent spaces in independent target datasets via transfer learning. Application of developing mouse retina to scRNA-Seq reveals intrinsic relationships across biological contexts and assays while avoiding batch effects and other technical features. We compare the dimensions learned in this source dataset to adult mouse retina, a time-course of human retinal development, select scRNA-seq datasets from developing brain, chromatin accessibility data, and a murine-cell type atlas to identify shared biological features. These tools lay the groundwork for exploratory analysis of scRNA-seq data via latent space representations, enabling a shift in how we compare and identify cells beyond reliance on marker genes or ensemble molecular identity.

Mitoregulin Controls β-Oxidation in Human and Mouse Adipocytes

We previously discovered in mouse adipocytes an lncRNA (the homolog of human LINC00116) regulating adipogenesis that contains a highly conserved coding region. Here, we show human protein expression of a peptide within LINC00116, and demonstrate that this peptide modulates triglyceride clearance in human adipocytes by regulating lipolysis and mitochondrial β-oxidation. This gene has previously been identified as mitoregulin (MTLN). We conclude that MTLN has a regulatory role in adipocyte metabolism as demonstrated by systemic lipid phenotypes in knockout mice. We also assert its adipocyte-autonomous phenotypes in both isolated murine adipocytes as well as human stem cell-derived adipocytes. MTLN directly interacts with the β subunit of the mitochondrial trifunctional protein, an enzyme critical in the β-oxidation of long-chain fatty acids. Our human and murine models contend that MTLN could be an avenue for further therapeutic research, albeit not without caveats, for example, by promoting white adipocyte triglyceride clearance in obese subjects.

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MTLN is expressed in human stem cell-derived adipocytes and murine adipose tissue

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MTLN localizes to mitochondria and associates with mitochondrial trifunctional enzyme

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Adipocytes display decreased fatty acid oxidation upon MTLN knockout

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MTLN KO affects murine serum lipid levels and adipocyte triglyceride accumulation

A screen of 1,049 schizophrenia and 30 Alzheimer's-associated variants for regulatory potential

Recent genome-wide association studies (GWAS) identified numerous schizophrenia (SZ) and Alzheimer's disease (AD) associated loci, most outside protein-coding regions and hypothesized to affect gene transcription. We used a massively parallel reporter assay to screen, 1,049 SZ and 30 AD variants in 64 and nine loci, respectively for allele differences in driving reporter gene expression. A library of synthetic oligonucleotides assaying each allele five times was transfected into K562 chronic myelogenous leukemia lymphoblasts and SK-SY5Y human neuroblastoma cells. One hundred forty eight variants showed allelic differences in K562 and 53 in SK-SY5Y cells, on average 2.6 variants per locus. Nine showed significant differences in both lines, a modest overlap reflecting different regulatory landscapes of these lines that also differ significantly in chromatin marks. Eight of nine were in the same direction. We observe no preference for risk alleles to increase or decrease expression. We find a positive correlation between the number of SNPs in linkage disequilibrium and the proportion of functional SNPs supporting combinatorial effects that may lead to haplotype selection. Our results prioritize future functional follow up of disease associated SNPs to determine the driver GWAS variant(s), at each locus and enhance our understanding of gene regulation dynamics.

Precocious neuronal differentiation and disrupted oxygen responses in Kabuki syndrome

Chromatin modifiers act to coordinate gene expression changes critical to neuronal differentiation from neural stem/progenitor cells (NSPCs). Lysine-specific methyltransferase 2D (KMT2D) encodes a histone methyltransferase that promotes transcriptional activation and is frequently mutated in cancers and in the majority (>70%) of patients diagnosed with the congenital, multisystem intellectual disability disorder Kabuki syndrome 1 (KS1). Critical roles for KMT2D are established in various non-neural tissues, but the effects of KMT2D loss in brain cell development have not been described. We conducted parallel studies of proliferation, differentiation, transcription, and chromatin profiling in KMT2D-deficient human and mouse models to define KMT2D-regulated functions in neurodevelopmental contexts, including adult-born hippocampal NSPCs in vivo and in vitro. We report cell-autonomous defects in proliferation, cell cycle, and survival, accompanied by early NSPC maturation in several KMT2D-deficient model systems. Transcriptional suppression in KMT2D-deficient cells indicated strong perturbation of hypoxia-responsive metabolism pathways. Functional experiments confirmed abnormalities of cellular hypoxia responses in KMT2D-deficient neural cells and accelerated NSPC maturation in vivo. Together, our findings support a model in which loss of KMT2D function suppresses expression of oxygen-responsive gene programs important to neural progenitor maintenance, resulting in precocious neuronal differentiation in a mouse model of KS1.

Differential Variation Analysis Enables Detection of Tumor Heterogeneity Using Single-Cell RNA-Sequencing Data

Tumor heterogeneity provides a complex challenge to cancer treatment and is a critical component of therapeutic response, disease recurrence, and patient survival. Single-cell RNA-sequencing (scRNA-seq) technologies have revealed the prevalence of intratumor and intertumor heterogeneity. Computational techniques are essential to quantify the differences in variation of these profiles between distinct cell types, tumor subtypes, and patients to fully characterize intratumor and intertumor molecular heterogeneity. In this study, we adapted our algorithm for pathway dysregulation, Expression Variation Analysis (EVA), to perform multivariate statistical analyses of differential variation of expression in gene sets for scRNA-seq. EVA has high sensitivity and specificity to detect pathways with true differential heterogeneity in simulated data. EVA was applied to several public domain scRNA-seq tumor datasets to quantify the landscape of tumor heterogeneity in several key applications in cancer genomics such as immunogenicity, metastasis, and cancer subtypes. Immune pathway heterogeneity of hematopoietic cell populations in breast tumors corresponded to the amount of diversity present in the T-cell repertoire of each individual. Cells from head and neck squamous cell carcinoma (HNSCC) primary tumors had significantly more heterogeneity across pathways than cells from metastases, consistent with a model of clonal outgrowth. Moreover, there were dramatic differences in pathway dysregulation across HNSCC basal primary tumors. Within the basal primary tumors, there was increased immune dysregulation in individuals with a high proportion of fibroblasts present in the tumor microenvironment. These results demonstrate the broad utility of EVA to quantify intertumor and intratumor heterogeneity from scRNA-seq data without reliance on low-dimensional visualization. SIGNIFICANCE: This study presents a robust statistical algorithm for evaluating gene expression heterogeneity within pathways or gene sets in single-cell RNA-seq data.

Abstract 3399: Uncovering hidden sources of transcriptional dysregulation arising from inter- and intra-tumor heterogeneity

Introduction: This study develops an innovative computational framework, Expression Variation Analysis (EVA), to model transcriptional dysregulation in cancer. Heterogeneity poses a major challenge in translational research. For example, inter-tumor heterogeneity limits the biomarker discovery and intra-tumor heterogeneity enables therapeutic resistance. Moreover, in some cancers driver mutations are insufficient to account for the widespread transcriptional variation responsible for these outcomes. Thus, new computational tools to model transcriptional variation are essential.

Methods: EVA is a unified computational framework to model transcriptional variation in cancer. Briefly, EVA quantifies transcriptional heterogeneity for one set of samples or cells from one phenotype using the expected dissimilarity between pairs of expression profiles. U-statistics theory can then quantify the statistical significance of the difference in transcriptional heterogeneity between phenotypes.

Results: We apply EVA to perform a comprehensive characterization of transcriptional variation in head and neck squamous cell carcinoma (HNSCC). At a pathway level, transcriptional variation in HNSCC tumors is higher than normal controls. Applying EVA to integrate ChIP-seq data with RNA-seq reveals that these pervasive transcriptional differences occur in enhancers. Similarly, applying EVA at a gene level to model splicing reveals more heterogeneity in transcript usage in tumor samples than normals. HPV- HNSCC tumors are unique in having mutations in genes that regulate the splicing machinery, and the HPV- tumors with these alterations have a greater number of dysregulated splice variants than those without. Nonetheless, the EVA analysis identifies a similar number of alternative splice variants in HPV+ as HPV- tumors suggesting an alternative mechanism of transcriptional heterogeneity in HPV+ disease. Adapting EVA to single cell data demonstrates that increased fibroblast composition is associated with greater variation in immune pathway activity in HNSCC. Moreover, we observe greater transcriptional heterogeneity in HNSCC primary tumors than lymph node metastasis consistent with a clonal outgrowth.

Conclusions: We demonstrate that the statistical framework from EVA enables differential heterogeneity analysis in HNSCC ranging from pathway dysregulation, splice variation, epigenetic regulation, and single cell analysis. This algorithm provides a critical framework to model the hidden multi-molecular mechanisms underlying the complex patient outcomes that are pervasive in cancer.

Citation Format: Bahman Afsari, Leslie Cope, Daria A. Gaykalova, Donald Geman, Sidharth Puram, Loyal A. Goff, Alexander Favorov, Elana Judith Fertig. Uncovering hidden sources of transcriptional dysregulation arising from inter- and intra-tumor heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3399.

Abstract 4697: Expression variation analysis for tumor heterogeneity in single-cell RNA-sequencing data

Introduction: Tumor heterogeneity provides a complex challenge to cancer treatment and is a critical component of therapeutic response, disease recurrence, and patient survival. Single-cell RNA-sequencing (scRNA-seq) technologies reveal the prevalence of intra- and inter-tumor heterogeneity. Computational techniques are essential to quantify the differences in variation of these profiles between distinct cell types, tumor subtypes, and patients to fully characterize intra- and inter-tumor molecular heterogeneity. To address this, we devised a new algorithm, Expression Variation Analysis in Single Cells (EVAsc), to perform multivariate statistical analyses of differential variation of expression in gene sets for scRNA-seq.

Methods: EVAsc provides a robust statistical test to compare the heterogeneity of transcriptional profiles of genes in a pathway between groups of cells from two phenotypes. Using simulated data, we demonstrated that this method is robust for imputed scRNA-seq data with high sensitivity and specificity to detect pathways with true differential heterogeneity. We then applied EVAsc to public domain scRNA-seq tumor datasets in breast cancer and head and neck squamous cell carcinoma (HNSCC) to quantify the landscape of tumor heterogeneity in several key applications in cancer genomics, i.e. immunogenicity, cancer subtypes, and metastasis.

Results: We demonstrated that immune pathway heterogeneity in hematopoietic cell populations in breast tumors corresponded to the amount diversity present in the T-cell repertoire of each individual. In HNSCC patients, we found dramatic differences in pathway dysregulation across basal primary tumors, indicative of inter-tumor heterogeneity within a single subtype. Within the basal primary tumors we also identified increased immune dysregulation in individuals with a high proportion of fibroblasts present in the tumor microenvironment. Moreover, cells in HNSCC primary tumors had significantly more heterogeneity across pathways than their matched metastatic cells, consistent with a model of clonal outgrowth.

Conclusions: The results of these analyses demonstrate the broad utility of EVAsc to quantify inter- and intra-tumor heterogeneity from scRNA-seq data without reliance on low dimensional visualization. EVAsc is a robust multivariate statistical method to quantify differential variation of pathway gene expression and provides the ability to explore transcriptional variation in numerous disease and normal contexts at a single cell resolution. Accurate characterization of inter-sample variation from scRNA-seq data of tumors is critical to quantify the cellular heterogeneity that drives tumor progression through dysregulation of key cancer pathways. Thus, identifying dysregulated pathways in individual tumors may be an important biomarker for clinical response to immunotherapy.

Citation Format: Emily F. Davis-Marcisak, Pranay Orugunta, Genevieve Stein-O'Brien, Sidharth V. Puram, Evanthia Roussos Torres, Alexander Hopkins, Elizabeth M. Jaffee, Alexander V. Favorov, Bahman Afsari, Loyal A. Goff, Elana J. Fertig. Expression variation analysis for tumor heterogeneity in single-cell RNA-sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4697.

Single-Cell RNA-Seq Analysis of Retinal Development Identifies NFI Factors as Regulating Mitotic Exit and Late-Born Cell Specification

Precise temporal control of gene expression in neuronal progenitors is necessary for correct regulation of neurogenesis and cell fate specification. However, the cellular heterogeneity of the developing CNS has posed a major obstacle to identifying the gene regulatory networks that control these processes. To address this, we used single-cell RNA sequencing to profile ten developmental stages encompassing the full course of retinal neurogenesis. This allowed us to comprehensively characterize changes in gene expression that occur during initiation of neurogenesis, changes in developmental competence, and specification and differentiation of each major retinal cell type. We identify the NFI transcription factors (Nfia, Nfib, and Nfix) as selectively expressed in late retinal progenitor cells and show that they control bipolar interneuron and Müller glia cell fate specification and promote proliferative quiescence.

Linear models enable powerful differential activity analysis in massively parallel reporter assays

Background

Massively parallel reporter assays (MPRAs) have emerged as a popular means for understanding noncoding variation in a variety of conditions. While a large number of experiments have been described in the literature, analysis typically uses ad-hoc methods. There has been little attention to comparing performance of methods across datasets.

Results

We present the mpralm method which we show is calibrated and powerful, by analyzing its performance on multiple MPRA datasets. We show that it outperforms existing statistical methods for analysis of this data type, in the first comprehensive evaluation of statistical methods on several datasets. We investigate theoretical and real-data properties of barcode summarization methods and show an unappreciated impact of summarization method for some datasets. Finally, we use our model to conduct a power analysis for this assay and show substantial improvements in power by performing up to 6 replicates per condition, whereas sequencing depth has smaller impact; we recommend to always use at least 4 replicates. An R package is available from the Bioconductor project.

Conclusions

Together, these results inform recommendations for differential analysis, general group comparisons, and power analysis and will help improve design and analysis of MPRA experiments.

Enter the Matrix: Factorization Uncovers Knowledge from Omics

Omics data contain signals from the molecular, physical, and kinetic inter- and intracellular interactions that control biological systems. Matrix factorization (MF) techniques can reveal low-dimensional structure from high-dimensional data that reflect these interactions. These techniques can uncover new biological knowledge from diverse high-throughput omics data in applications ranging from pathway discovery to timecourse analysis. We review exemplary applications of MF for systems-level analyses. We discuss appropriate applications of these methods, their limitations, and focus on the analysis of results to facilitate optimal biological interpretation. The inference of biologically relevant features with MF enables discovery from high-throughput data beyond the limits of current biological knowledge - answering questions from high-dimensional data that we have not yet thought to ask.

Transcriptional and epigenomic landscapes of CNS and non-CNS vascular endothelial cells

Vascular endothelial cell (EC) function depends on appropriate organ-specific molecular and cellular specializations. To explore genomic mechanisms that control this specialization, we have analyzed and compared the transcriptome, accessible chromatin, and DNA methylome landscapes from mouse brain, liver, lung, and kidney ECs. Analysis of transcription factor (TF) gene expression and TF motifs at candidate cis-regulatory elements reveals both shared and organ-specific EC regulatory networks. In the embryo, only those ECs that are adjacent to or within the central nervous system (CNS) exhibit canonical Wnt signaling, which correlates precisely with blood-brain barrier (BBB) differentiation and Zic3 expression. In the early postnatal brain, single-cell RNA-seq of purified ECs reveals (1) close relationships between veins and mitotic cells and between arteries and tip cells, (2) a division of capillary ECs into vein-like and artery-like classes, and (3) new endothelial subtype markers, including new validated tip cell markers.

Group 1 Innate Lymphoid Cell Lineage Identity Is Determined by a cis-Regulatory Element Marked by a Long Non-coding RNA

Commitment to the innate lymphoid cell (ILC) lineage is determined by Id2, a transcriptional regulator that antagonizes T and B cell-specific gene expression programs. Yet how Id2 expression is regulated in each ILC subset remains poorly understood. We identified a cis-regulatory element demarcated by a long non-coding RNA (lncRNA) that controls the function and lineage identity of group 1 ILCs, while being dispensable for early ILC development and homeostasis of ILC2s and ILC3s. The locus encoding this lncRNA, which we termed Rroid, directly interacted with the promoter of its neighboring gene, Id2, in group 1 ILCs. Moreover, the Rroid locus, but not the lncRNA itself, controlled the identity and function of ILC1s by promoting chromatin accessibility and deposition of STAT5 at the promoter of Id2 in response to interleukin (IL)-15. Thus, non-coding elements responsive to extracellular cues unique to each ILC subset represent a key regulatory layer for controlling the identity and function of ILCs.

The long non-coding RNA Morrbid regulates Bim and short-lived myeloid cell lifespan

Neutrophils, eosinophils and “classical” monocytes collectively account for ~70% of human blood leukocytes and are among the shortest-lived cells in the body^1,2. Precise regulation of the lifespan of these myeloid cells is critical to maintain protective immune responses while minimizing the deleterious consequences of prolonged inflammation^1,2. However, how the lifespan of these cells is strictly controlled remains largely unknown. Here, we identify a novel long non-coding RNA (lncRNA) that we termed Morrbid, which tightly controls the survival of neutrophils, eosinophils and “classical” monocytes in response to pro-survival cytokines. To control the lifespan of these cells, Morrbid regulates the transcription of its neighboring pro-apoptotic gene, Bcl2l11 (Bim), by promoting the enrichment of the PRC2 complex at the Bcl2l11 promoter to maintain this gene in a poised state. Notably, Morrbid regulates this process in cis, enabling allele-specific control of Bcl2l11 transcription. Thus, in these highly inflammatory cells, changes in Morrbid levels provide a locus-specific regulatory mechanism that allows for rapid control of apoptosis in response to extracellular pro-survival signals. As MORRBID is present in humans and dysregulated in patients with hypereosinophilic syndrome, this lncRNA may represent a potential therapeutic target for inflammatory disorders characterized by aberrant short-lived myeloid cell lifespan.

Investigating long noncoding RNAs using animal models

The number of long noncoding RNAs (lncRNAs) has grown rapidly; however, our understanding of their function remains limited. Although cultured cells have facilitated investigations of lncRNA function at the molecular level, the use of animal models provides a rich context in which to investigate the phenotypic impact of these molecules. Promising initial studies using animal models demonstrated that lncRNAs influence a diverse number of phenotypes, ranging from subtle dysmorphia to viability. Here, we highlight the diversity of animal models and their unique advantages, discuss the use of animal models to profile lncRNA expression, evaluate experimental strategies to manipulate lncRNA function in vivo, and review the phenotypes attributable to lncRNAs. Despite a limited number of studies leveraging animal models, lncRNAs are already recognized as a notable class of molecules with important implications for health and disease.

Linking RNA biology to lncRNAs

The regulatory potential of RNA has never ceased to amaze: from RNA catalysis, to RNA-mediated splicing, to RNA-based silencing of an entire chromosome during dosage compensation. More recently, thousands of long noncoding RNA (lncRNA) transcripts have been identified, the majority with unknown function. Thus, it is tempting to think that these lncRNAs represent a cadre of new factors that function through ribonucleic mechanisms. Some evidence points to several lncRNAs with tantalizing physiological contributions and thought-provoking molecular modalities. However, dissecting the RNA biology of lncRNAs has been difficult, and distinguishing the independent contributions of functional RNAs from underlying DNA elements, or the local act of transcription, is challenging. Here, we aim to survey the existing literature and highlight future approaches that will be needed to link the RNA-based biology and mechanisms of lncRNAs in vitro and in vivo.

Long noncoding RNAs: Central to nervous system development

The development of the central nervous system (CNS) is a complex orchestration of stem cells, transcription factors, growth/differentiation factors, and epigenetic control. Noncoding RNAs have been identified, classified, and studied for their functional roles in many systems including the CNS. In particular, the class of long noncoding RNAs (lncRNAs) has generated both enthusiasm and skepticism due to the unexpected discovery, the diversity of mechanisms, and the lower level of expression than found in protein-coding RNAs. Here we describe evidence supporting the role of lncRNAs in driving CNS-specific differentiation. It is clear that lncRNAs exhibit a functional diversity that makes their study and compartmentalization more challenging than other classes of noncoding RNAs. We predict, however, that lncRNAs will be essential for the characterization of discrete neuronal cell types in the age of single-cell transcriptomics and that these regulatory RNAs contribute to the multitude of functional mechanisms during CNS differentiation that will rival the diversities of protein-based mechanisms.

DeCoN: genome-wide analysis of in vivo transcriptional dynamics during pyramidal neuron fate selection in neocortex

Neuronal development requires a complex choreography of transcriptional decisions to obtain specific cellular identities. Realizing the ultimate goal of identifying genome-wide signatures that define and drive specific neuronal fates has been hampered by enormous complexity in both time and space during development. Here, we have paired high-throughput purification of pyramidal neuron subclasses with deep profiling of spatiotemporal transcriptional dynamics during corticogenesis to resolve lineage choice decisions. We identified numerous features ranging from spatial and temporal usage of alternative mRNA isoforms and promoters to a host of mRNA genes modulated during fate specification. Notably, we uncovered numerous long noncoding RNAs with restricted temporal and cell-type-specific expression. To facilitate future exploration, we provide an interactive online database to enable multidimensional data mining and dissemination. This multifaceted study generates a powerful resource and informs understanding of the transcriptional regulation underlying pyramidal neuron diversity in the neocortex.

VIDEO ABSTRACT

A positive feedback mechanism that regulates expression of miR-9 during neurogenesis

MiR-9, a neuron-specific miRNA, is an important regulator of neurogenesis. In this study we identify how miR-9 is regulated during early differentiation from a neural stem-like cell. We utilized two immortalized rat precursor clones, one committed to neurogenesis (L2.2) and another capable of producing both neurons and non-neuronal cells (L2.3), to reproducibly study early neurogenesis. Exogenous miR-9 is capable of increasing neurogenesis from L2.3 cells. Only one of three genomic loci capable of encoding miR-9 was regulated during neurogenesis and the promoter region of this locus contains sufficient functional elements to drive expression of a luciferase reporter in a developmentally regulated pattern. Furthermore, among a large number of potential regulatory sites encoded in this sequence, Mef2 stood out because of its known pro-neuronal role. Of four Mef2 paralogs, we found only Mef2C mRNA was regulated during neurogenesis. Removal of predicted Mef2 binding sites or knockdown of Mef2C expression reduced miR-9-2 promoter activity. Finally, the mRNA encoding the Mef2C binding partner HDAC4 was shown to be targeted by miR-9. Since HDAC4 protein could be co-immunoprecipitated with Mef2C protein or with genomic Mef2 binding sequences, we conclude that miR-9 regulation is mediated, at least in part, by Mef2C binding but that expressed miR-9 has the capacity to reduce inhibitory HDAC4, stabilizing its own expression in a positive feedback mechanism.

Poly-combing the genome for RNA

An unresolved question in mammalian epigenetic regulation is how ubiquitously expressed chromatin-modifying complexes such as Polycomb group complex 2 (PRC2) find their specific target sites across an intricate choreography of localization events in time and space. Two recent studies now provide critical new insights into an intriguing genome-wide role for RNA in PRC2 regulation.

Multiple knockout mouse models reveal lincRNAs are required for life and brain development

Many studies are uncovering functional roles for long noncoding RNAs (lncRNAs), yet few have been tested for in vivo relevance through genetic ablation in animal models. To investigate the functional relevance of lncRNAs in various physiological conditions, we have developed a collection of 18 lncRNA knockout strains in which the locus is maintained transcriptionally active. Initial characterization revealed peri- and postnatal lethal phenotypes in three mutant strains (Fendrr, Peril, and Mdgt), the latter two exhibiting incomplete penetrance and growth defects in survivors. We also report growth defects for two additional mutant strains (linc–Brn1b and linc–Pint). Further analysis revealed defects in lung, gastrointestinal tract, and heart in Fendrr^−/− neonates, whereas linc–Brn1b^−/− mutants displayed distinct abnormalities in the generation of upper layer II–IV neurons in the neocortex. This study demonstrates that lncRNAs play critical roles in vivo and provides a framework and impetus for future larger-scale functional investigation into the roles of lncRNA molecules.

DOI:http://dx.doi.org/10.7554/eLife.01749.001

The mammalian genome is comprised of DNA sequences that contain the templates for proteins, and other DNA sequences that do not code for proteins. The coding DNA sequences are transcribed to make messenger RNA molecules, which are then translated to make proteins. Researchers have known for many years that some of the noncoding DNA sequences are also transcribed to make other types of RNA molecules, such as transfer and ribosomal RNA. However, the true breadth and diversity of the roles played by these other RNA molecules have only recently begun to be fully appreciated.

Mammalian genomes contain thousands of noncoding DNA sequences that are transcribed. Recent in vitro studies suggest that the resulting long noncoding RNA molecules can act as regulators of transcription, translation, and cell cycle. In vitro studies also suggest that these long noncoding RNA molecules may play a role in mammalian development and disease. Yet few in vivo studies have been performed to support or confirm such hypotheses.

Now Sauvageau et al. have developed several lines of knockout mice to investigate a subset of noncoding RNA molecules known as long intergenic noncoding RNAs (lincRNAs). These experiments reveal that lincRNAs have a strong influence on the overall viability of mice, and also on a number of developmental processes, including the development of lungs and the cerebral cortex.

Given that the vast majority of the human genome is transcribed, the mouse models developed by Sauvageau et al. represent an important step in determining the physiological relevance, on a genetic level, of the noncoding portion of the genome in vivo.

DOI:http://dx.doi.org/10.7554/eLife.01749.002

The microRNA miR-181 is a critical cellular metabolic rheostat essential for NKT cell ontogenesis and lymphocyte development and homeostasis

Regulation of metabolic pathways in the immune system provides a mechanism to actively control cellular function, growth, proliferation, and survival. Here, we report that miR-181 is a nonredundant determinant of cellular metabolism and is essential for supporting the biosynthetic demands of early NKT cell development. As a result, miR-181-deficient mice showed a complete absence of mature NKT cells in the thymus and periphery. Mechanistically, miR-181 modulated expression of the phosphatase PTEN to control PI3K signaling, which was a primary stimulus for anabolic metabolism in immune cells. Thus miR-181-deficient mice also showed severe defects in lymphoid development and T cell homeostasis associated with impaired PI3K signaling. These results uncover miR-181 as essential for NKT cell development and establish this family of miRNAs as central regulators of PI3K signaling and global metabolic fitness during development and homeostasis.

Computational analysis of noncoding RNAs

Noncoding RNAs have emerged as important key players in the cell. Understanding their surprisingly diverse range of functions is challenging for experimental and computational biology. Here, we review computational methods to analyze noncoding RNAs. The topics covered include basic and advanced techniques to predict RNA structures, annotation of noncoding RNAs in genomic data, mining RNA-seq data for novel transcripts and prediction of transcript structures, computational aspects of microRNAs, and database resources.

Expression profiling of synaptic microRNAs from the adult rat brain identifies regional differences and seizure-induced dynamic modulation

In recent years, microRNAs or miRNAs have been proposed to target neuronal mRNAs localized near the synapse, exerting a pivotal role in modulating local protein synthesis, and presumably affecting adaptive mechanisms such as synaptic plasticity. In the present study we have characterized the distribution of miRNAs in five regions of the adult mammalian brain and compared the relative abundance between total fractions and purified synaptoneurosomes (SN), using three different methodologies. The results show selective enrichment or depletion of some miRNAs when comparing total versus SN fractions. These miRNAs were different for each brain region explored. Changes in distribution could not be attributed to simple diffusion or to a targeting sequence inside the miRNAs. In silico analysis suggest that the differences in distribution may be related to the preferential concentration of synaptically localized mRNA targeted by the miRNAs. These results favor a model of co-transport of the miRNA-mRNA complex to the synapse, although further studies are required to validate this hypothesis. Using an in vivo model for increasing excitatory activity in the cortex and the hippocampus indicates that the distribution of some miRNAs can be modulated by enhanced neuronal (epileptogenic) activity. All these results demonstrate the dynamic modulation in the local distribution of miRNAs from the adult brain, which may play key roles in controlling localized protein synthesis at the synapse.

Rapid induction of genes associated with tissue protection and neural development in contused adult spinal cord after radial glial cell transplantation

Cell-based therapy has been widely evaluated in spinal cord injury (SCI) animal models and shown to improve functional recovery. However, host response to cell transplants at gene expression level is rarely discussed. We reported previously that acute transplantation of radial glial cells RG3.6 following SCI promoted early locomotion improvement within 1 week post-injury. To identify rapid molecular changes induced by RG3.6 transplantation in the host tissue, distal spinal cord segments were subjected to microarray analysis. Although RG3.6 transplantation, reduced activity of macrophages as early as 1-2 weeks post-injury, the expression levels of inflammatory genes (e.g., IL-6, MIP-2, MCP-1) were not decreased by RG3.6 treatment as compared to medium or other cell controls at 6-12 h post-injury. However, genes associated with tissue protection (Hsp70 and Hsp32) and neural cell development (Foxg1, Top2a, Sox11, Nkx2.2, Vimentin) were found to be significantly up-regulated by RG3.6 transplants. Foxg1 was the most highly induced gene in the RG3.6-treated spinal cords, and its expression by immunocytochemistry was confirmed in the host tissue. Moreover, RG3.6 treatment boosted the number of Nkx2.2 cells in the spinal cord, and these cells frequently co-expressed NG2, which marks progenitor cells. Taken together, these results demonstrate that radial glial transplants induced rapid and specific gene expression in the injured host tissue, and suggest that these early responses are associated with mechanisms of tissue protection and activation of endogenous neural progenitor cells.

Differential regulation of microRNA stability

MicroRNAs (miRNAs) are endogenous single-stranded RNA molecules of about 21 nucleotides in length that are fundamental post-transcriptional regulators of gene expression. Although the transcriptional and processing events involved in the generation of miRNAs have been extensively studied, very little is known pertaining to components that regulate the stability of individual miRNAs. All RNAs have distinct inherent half-lives that dictate their level of accumulation and miRNAs would be expected to follow a similar principle. Here we demonstrate that although most miRNA appear to be stable, like mRNAs, miRNAs possess differential stability in human cells. In particular, we found that miR-382, a miRNA that contributes to HIV-1 provirus latency, is unstable in cells. To determine the region of miR-382 responsible for its rapid decay, we developed a cell-free system that recapitulated the observed cell-based-regulated miR-382 turnover. The system utilizes in vitro-processed mature miRNA derived from pre-miRNA and follows the decay of the processed miRNA. Using this system, we demonstrate that instability of miR-382 is driven by sequences outside its seed region and required the 3' terminal seven nucleotides where mutations in this region increased the stability of the RNA. Moreover, the exosome 3'-5' exoribonuclease complex was identified as the primary nuclease involved in miR-382 decay with a more modest contribution by the Xrn1 and no detectable contribution by Xrn2. These studies provide evidence for an miRNA element essential for rapid miRNA decay and implicate the exosome in this process. The development of a biochemically amendable system to analyze the mechanism of differential miRNA stability provides an important step in efforts to regulate gene expression by modulating miRNA stability.

Ago2 immunoprecipitation identifies predicted microRNAs in human embryonic stem cells and neural precursors

Background

MicroRNAs are required for maintenance of pluripotency as well as differentiation, but since more microRNAs have been computationally predicted in genome than have been found, there are likely to be undiscovered microRNAs expressed early in stem cell differentiation.

Methodology/Principal Findings

SOLiD ultra-deep sequencing identified >10⁷ unique small RNAs from human embryonic stem cells (hESC) and neural-restricted precursors that were fit to a model of microRNA biogenesis to computationally predict 818 new microRNA genes. These predicted genomic loci are associated with chromatin patterns of modified histones that are predictive of regulated gene expression. 146 of the predicted microRNAs were enriched in Ago2-containing complexes along with 609 known microRNAs, demonstrating association with a functional RISC complex. This Ago2 IP-selected subset was consistently expressed in four independent hESC lines and exhibited complex patterns of regulation over development similar to previously-known microRNAs, including pluripotency-specific expression in both hESC and iPS cells. More than 30% of the Ago2 IP-enriched predicted microRNAs are new members of existing families since they share seed sequences with known microRNAs.

Conclusions/Significance

Extending the classic definition of microRNAs, this large number of new microRNA genes, the majority of which are less conserved than their canonical counterparts, likely represent evolutionarily recent regulators of early differentiation. The enrichment in Ago2 containing complexes, the presence of chromatin marks indicative of regulated gene expression, and differential expression over development all support the identification of 146 new microRNAs active during early hESC differentiation.

Functional differentiation of a clone resembling embryonic cortical interneuron progenitors

We have generated clones (L2.3 and RG3.6) of neural progenitors with radial glial properties from rat E14.5 cortex that differentiate into astrocytes, neurons, and oligodendrocytes. Here, we describe a different clone (L2.2) that gives rise exclusively to neurons, but not to glia. Neuronal differentiation of L2.2 cells was inhibited by bone morphogenic protein 2 (BMP2) and enhanced by Sonic Hedgehog (SHH) similar to cortical interneuron progenitors. Compared with L2.3, differentiating L2.2 cells expressed significantly higher levels of mRNAs for glutamate decarboxylases (GADs), DLX transcription factors, calretinin, calbindin, neuropeptide Y (NPY), and somatostatin. Increased levels of DLX-2, GADs, and calretinin proteins were confirmed upon differentiation. L2.2 cells differentiated into neurons that fired action potentials in vitro, and their electrophysiological differentiation was accelerated and more complete when cocultured with developing astroglial cells but not with conditioned medium from these cells. The combined results suggest that clone L2.2 resembles GABAergic interneuron progenitors in the developing forebrain.

MicroRNA expression pattern of undifferentiated and differentiated human embryonic stem cells

Many of the currently established human embryonic stem (hES) cell lines have been characterized extensively in terms of their gene expression profiles and genetic stability in culture. Recent studies have indicated that microRNAs (miRNAs), a class of noncoding small RNAs that participate in the regulation of gene expression, may play a key role in stem cell self-renewal and differentiation. Using both microarrays and quantitative PCR, we report here the differences in miRNA expression between undifferentiated hES cells and their corresponding differentiated cells that underwent differentiation in vitro over a period of 2 weeks. Our results confirm the identity of a signature miRNA profile in pluripotent cells, comprising a small subset of differentially expressed miRNAs in hES cells. Examining both mRNA and miRNA profiles under multiple conditions using cross-correlation, we find clusters of miRNAs grouped with specific, biologically interpretable mRNAs. We identify patterns of expression in the progression from hES cells to differentiated cells that suggest a role for selected miRNAs in maintenance of the undifferentiated, pluripotent state. Profiling of the hES cell "miRNA-ome" provides an insight into molecules that control cellular differentiation and maintenance of the pluripotent state, findings that have broad implications in development, homeostasis, and human disease states.

Bioinformatic analysis of neural stem cell differentiation

Regulated mRnAs during differentiation of rat neural stem cells were analyzed using the ABi1700 microarray platform. This microarray, while technically advanced, suffers from the difficulty of integrating hybridization results into public databases for systems-level analysis. This is particularly true for the rat array, since many of the probes were designed for transcripts based on predicted human and mouse homologs. using several strategies, we increased the public annotation of the 27,531 probes from 43% to over 65%. To increase the dynamic range of annotation, probes were mapped to numerous public keys from several data sources. consensus annotation from multiple sources was determined for well-scoring alignments, and a confidence-based ranking system established for probes with less agreement across multiple data sources. previous attempts at genomic interpretation using the celera annotation model resulted in poor overlap with expected genomic sequences. since the public keys are more precisely mapped to the genome, we could now analyze the relationships between predicted transcription-factor binding sites and expression clusters. Results collected from a differentiation time course of two neural stem cell clones were clustered using a model-based algorithm. Transcription-factor binding sites were predicted from upstream regions of mapped transcripts using position weight matrices from either JAspAR or TRAnsFAc, and the resulting scores were used to discriminate between observed expression clusters. A classification and regression tree analysis was conducted using cluster numbers as gene identifiers and TFBs scores as predictors, pruning back to obtain a tree with the lowest gene class prediction error rate. Results identify several transcription factors, the presence or absence of which are sufficient to describe clusters of mRnAs changing over time-those that are static, as well as clusters describing cell line differences. public annotation of the AB1700 rat genome array will be valuable for integrating results into future systems-level analyses.

Rational probe optimization and enhanced detection strategy for microRNAs using microarrays

MicroRNAs (miRNAs) are post-transcriptional regulators participating in biological processes ranging from differentiation to carcinogenesis. We developed a rational probe design algorithm and a sensitive labelling scheme for optimizing miRNA microarrays. Our microarray contains probes for all validated miRNAs from five species, with the potential for drawing on species conservation to identify novel miRNAs with homologous probes. These methods are useful for high-throughput analysis of micro RNAs from various sources, and allow analysis with limiting quantities of RNA. The system design can also be extended for use on Luminex beads or on 96-well plates in an ELISA-style assay. We optimized hybridization temperatures using sequence variations on 20 of the probes and determined that all probes distinguish wild-type from 2 nt mutations, and most probes distinguish a 1 nt mutation, producing good selectivity between closely-related small RNA sequences. Results of tissue comparisons on our microarrays reveal patterns of hybridization that agree with results from Northern blots and other methods.