James Briggs

The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing

Schizophrenia (SZ) is a complex disease characterized by impaired neuronal functioning. Although defective alternative splicing has been linked to SZ, the molecular mechanisms responsible are unknown. Additionally, there is limited understanding of the early transcriptomic responses to neuronal activation. Here, we profile these transcriptomic responses and show that long non-coding RNAs (lncRNAs) are dynamically regulated by neuronal activation, including acute downregulation of the lncRNA Gomafu, previously implicated in brain and retinal development. Moreover, we demonstrate that Gomafu binds directly to the splicing factors QKI and SRSF1 (serine/arginine-rich splicing factor 1) and dysregulation of Gomafu leads to alternative splicing patterns that resemble those observed in SZ for the archetypal SZ-associated genes DISC1 and ERBB4. Finally, we show that Gomafu is downregulated in post-mortem cortical gray matter from the superior temporal gyrus in SZ. These results functionally link activity-regulated lncRNAs and alternative splicing in neuronal function and suggest that their dysregulation may contribute to neurological disorders.

Mechanisms of Long Non-coding RNAs in Mammalian Nervous System Development, Plasticity, Disease, and Evolution

Only relatively recently has it become clear that mammalian genomes encode tens of thousands of long non-coding RNAs (lncRNAs). A striking 40% of these are expressed specifically in the brain, where they show precisely regulated temporal and spatial expression patterns. This begs the question, what is the functional role of these many lncRNA transcripts in the brain? Here we canvass a growing number of mechanistic studies that have elucidated central roles for lncRNAs in the regulation of nervous system development and function. We also survey studies indicating that neurological and psychiatric disorders may ensue when these mechanisms break down. Finally, we synthesize these insights with evidence from comparative genomics to argue that lncRNAs may have played important roles in brain evolution, by virtue of their abundant sequence innovation in mammals and plausible mechanistic connections to the adaptive processes that occurred recently in the primate and human lineages.

Integration‐Free Induced Pluripotent Stem Cells Model Genetic and Neural Developmental Features of Down Syndrome Etiology

Down syndrome (DS) is the most frequent cause of human congenital mental retardation. Cognitive deficits in DS result from perturbations of normal cellular processes both during development and in adult tissues, but the mechanisms underlying DS etiology remain poorly understood. To assess the ability of induced pluripotent stem cells (iPSCs) to model DS phenotypes, as a prototypical complex human disease, we generated bona fide DS and wild‐type (WT) nonviral iPSCs by episomal reprogramming. DS iPSCs selectively overexpressed chromosome 21 genes, consistent with gene dosage, which was associated with deregulation of thousands of genes throughout the genome. DS and WT iPSCs were neurally converted at >95% efficiency and had remarkably similar lineage potency, differentiation kinetics, proliferation, and axon extension at early time points. However, at later time points DS cultures showed a twofold bias toward glial lineages. Moreover, DS neural cultures were up to two times more sensitive to oxidative stress‐induced apoptosis, and this could be prevented by the antioxidant N‐acetylcysteine. Our results reveal a striking complexity in the genetic alterations caused by trisomy 21 that are likely to underlie DS developmental phenotypes, and indicate a central role for defective early glial development in establishing developmental defects in DS brains. Furthermore, oxidative stress sensitivity is likely to contribute to the accelerated neurodegeneration seen in DS, and we provide proof of concept for screening corrective therapeutics using DS iPSCs and their derivatives. Nonviral DS iPSCs can therefore model features of complex human disease in vitro and provide a renewable and ethically unencumbered discovery platform. STEM CELLS2013;31:467–478

Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo

Mapping the vertebrate developmental landscape As embryos develop, numerous cell types with distinct functions and morphologies arise from pluripotent cells. Three research groups have used single-cell RNA sequencing to analyze the transcriptional changes accompanying development of vertebrate embryos (see the Perspective by Harland). Wagner et al. sequenced the transcriptomes of more than 90,000 cells throughout zebrafish development to reveal how cells differentiate during axis patterning, germ layer formation, and early organogenesis. Farrell et al. profiled the transcriptomes of tens of thousands of embryonic cells and applied a computational approach to construct a branching tree describing the transcriptional trajectories that lead to 25 distinct zebrafish cell types. The branching tree revealed how cells change their gene expression as they become more and more specialized. Briggs et al. examined whole frog embryos, spanning zygotic genome activation through early organogenesis, to map cell states and differentiation across all cell lineages over time. These data and approaches pave the way for the comprehensive reconstruction of transcriptional trajectories during development. Science, this issue p. 981, p. eaar3131, p. eaar5780; see also p. 967 Single-cell RNA sequencing reveals cell type trajectories and cell lineage in the developing zebrafish embryo. High-throughput mapping of cellular differentiation hierarchies from single-cell data promises to empower systematic interrogations of vertebrate development and disease. Here we applied single-cell RNA sequencing to >92,000 cells from zebrafish embryos during the first day of development. Using a graph-based approach, we mapped a cell-state landscape that describes axis patterning, germ layer formation, and organogenesis. We tested how clonally related cells traverse this landscape by developing a transposon-based barcoding approach (TracerSeq) for reconstructing single-cell lineage histories. Clonally related cells were often restricted by the state landscape, including a case in which two independent lineages converge on similar fates. Cell fates remained restricted to this landscape in embryos lacking the chordin gene. We provide web-based resources for further analysis of the single-cell data.

The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution

Mapping the vertebrate developmental landscape As embryos develop, numerous cell types with distinct functions and morphologies arise from pluripotent cells. Three research groups have used single-cell RNA sequencing to analyze the transcriptional changes accompanying development of vertebrate embryos (see the Perspective by Harland). Wagner et al. sequenced the transcriptomes of more than 90,000 cells throughout zebrafish development to reveal how cells differentiate during axis patterning, germ layer formation, and early organogenesis. Farrell et al. profiled the transcriptomes of tens of thousands of embryonic cells and applied a computational approach to construct a branching tree describing the transcriptional trajectories that lead to 25 distinct zebrafish cell types. The branching tree revealed how cells change their gene expression as they become more and more specialized. Briggs et al. examined whole frog embryos, spanning zygotic genome activation through early organogenesis, to map cell states and differentiation across all cell lineages over time. These data and approaches pave the way for the comprehensive reconstruction of transcriptional trajectories during development. Science, this issue p. 981, p. eaar3131, p. eaar5780; see also p. 967 A single-cell transcriptome analysis of whole frog embryos reveals cell states and provides a map of differentiation over time. INTRODUCTION Metazoan development represents a big jump in complexity compared with unicellular life in two aspects: cell-type differentiation and cell spatial organization. In vertebrate embryos, many distinct cell types appear within just a single day of life after fertilization. Studying the developmental dynamics of all embryonic cell types is complicated by factors such as the speed of early development, complex cellular spatial organization, and scarcity of raw material for conventional analysis. Genetics and experimental embryology have clarified major transcription factors and secreted signaling molecules involved in the specification of early lineages. However, development involves parallel alterations in many cellular circuits, not just a few well-described factors. RATIONALE We recently developed a microfluidics-based single-cell RNA sequencing method capable of efficiently profiling tens of thousands of individual transcriptomes. Building on earlier studies that showed how single-cell transcriptomics can reveal cell states within complex tissues, we reasoned that a series of such measurements from embryos, if collected with sufficient time resolution, could allow reconstruction of developmental cell-state hierarchies. We focused on the western claw-toed frog, Xenopus tropicalis, which serves as one of the best-studied model systems of early vertebrate development. We profiled these embryos from just before the onset of zygotic transcription up to a point at which dozens of distinct cell types have formed encompassing progenitors of most major organs. To establish aspects of development general to vertebrates, we additionally incorporated data from the copublished paper by Wagner et al. on zebrafish embryos, which separated from frogs about 400 million years ago. RESULTS We profiled 136,966 single-cell transcriptomes over the first day of life of Xenopus tropicalis. Our analysis classifies 259 gene expression clusters across 10 time points, which belong to 69 annotated embryonic cell types and capture further substructure. Using a computational approach to link cell states between time points, a resulting cell-state graph agrees well with previous lineage-tracing studies and shows that developmental fate choices can be well approximated by a treelike model. Many cell states are detected considerably earlier than previously understood, thus revealing the earliest events in their differentiation. The data lends clarity to numerous specific developmental processes, such as the developmental origin of the vertebrate neural crest. Through an evolutionary comparison with zebrafish, we identified diverging features of developmental dynamics, including many genes showing cell-type specificity in one organism but not in another. Yet, we also identified conserved patterns in the reuse of transcription factors across lineages and in multilineage priming at fate branch points. The resulting resource is available in an interactive online browser that allows in silico exploration of any gene in any cell state (tinyurl.com/scXen2018). CONCLUSION The approaches and results presented here, along with the copublished paper by Wagner et al., establish the first steps toward a data-driven dissection of developmental dynamics at the scale of entire organisms. They provide a useful, annotated resource for developmental biologists, comprehensively tracking differentiation programs as they unfold on a high-dimensional gene expression landscape. Although demonstrated on model organisms, the same approaches could be transformative to the study of nonmodel organisms by allowing rapid and quantitative description of differentiation processes across the tree of life, opening up a new front in evolutionary biology. Single-cell analysis of whole developing vertebrate embryos. Xenopus embryos at 10 time points over the first day of life were dissociated, barcoded, and sequenced, yielding 136,966 single-cell transcriptomes. These data were clustered and connected over time to reveal a complete view of transcriptional changes in each embryonic lineage and clarify numerous features of early development. hpf, hours postfertilization. Time series of single-cell transcriptome measurements can reveal dynamic features of cell differentiation pathways. From measurements of whole frog embryos spanning zygotic genome activation through early organogenesis, we derived a detailed catalog of cell states in vertebrate development and a map of differentiation across all lineages over time. The inferred map recapitulates most if not all developmental relationships and associates new regulators and marker genes with each cell state. We find that many embryonic cell states appear earlier than previously appreciated. We also assess conflicting models of neural crest development. Incorporating a matched time series of zebrafish development from a companion paper, we reveal conserved and divergent features of vertebrate early developmental gene expression programs.

The long non-coding RNA NEAT1 is responsive to neuronal activity and is associated with hyperexcitability states.

Despite their abundance, the molecular functions of long non-coding RNAs in mammalian nervous systems remain poorly understood. Here we show that the long non-coding RNA, NEAT1, directly modulates neuronal excitability and is associated with pathological seizure states. Specifically, NEAT1 is dynamically regulated by neuronal activity in vitro and in vivo, binds epilepsy-associated potassium channel-interacting proteins including KCNAB2 and KCNIP1, and induces a neuronal hyper-potentiation phenotype in iPSC-derived human cortical neurons following antisense oligonucleotide knockdown. Next generation sequencing reveals a strong association of NEAT1 with increased ion channel gene expression upon activation of iPSC-derived neurons following NEAT1 knockdown. Furthermore, we show that while NEAT1 is acutely down-regulated in response to neuronal activity, repeated stimulation results in NEAT1 becoming chronically unresponsive in independent in vivo rat model systems relevant to temporal lobe epilepsy. We extended previous studies showing increased NEAT1 expression in resected cortical tissue from high spiking regions of patients suffering from intractable seizures. Our results indicate a role for NEAT1 in modulating human neuronal activity and suggest a novel mechanistic link between an activity-dependent long non-coding RNA and epilepsy.

Mouse embryonic stem cells can differentiate via multiple paths to the same state

In embryonic development, cells differentiate through stereotypical sequences of intermediate states to generate particular mature fates. By contrast, driving differentiation by ectopically expressing terminal transcription factors (direct programming) can generate similar fates by alternative routes. How differentiation in direct programming relates to embryonic differentiation is unclear. We applied single-cell RNA sequencing to compare two motor neuron differentiation protocols: a standard protocol approximating the embryonic lineage, and a direct programming method. Both initially undergo similar early neural commitment. Later, the direct programming path diverges into a novel transitional state rather than following the expected embryonic spinal intermediates. The novel state in direct programming has specific and uncharacteristic gene expression. It forms a loop in gene expression space that converges separately onto the same final motor neuron state as the standard path. Despite their different developmental histories, motor neurons from both protocols structurally, functionally, and transcriptionally resemble motor neurons isolated from embryos.

Concise Review: New Paradigms for Down Syndrome Research Using Induced Pluripotent Stem Cells: Tackling Complex Human Genetic Disease

Down syndrome (DS) is a complex developmental disorder with diverse pathologies that affect multiple tissues and organ systems. Clear mechanistic description of how trisomy of chromosome 21 gives rise to most DS pathologies is currently lacking and is limited to a few examples of dosage‐sensitive trisomic genes with large phenotypic effects. The recent advent of cellular reprogramming technology offers a promising way forward, by allowing derivation of patient‐derived human cell types in vitro. We present general strategies that integrate genomics technologies and induced pluripotent stem cells to identify molecular networks driving different aspects of DS pathogenesis and describe experimental approaches to validate the causal requirement of candidate network defects for particular cellular phenotypes. This overall approach should be applicable to many poorly understood complex human genetic diseases, whose pathogenic mechanisms might involve the combined effects of many genes.