Temporal progression of Drosophila medulla neuroblasts generates the transcription factor combination to control T1 neuron morphogenesis

Single nuclei RNA-sequencing of adult brain neurons derived from type 2 neuroblasts reveals transcriptional complexity in the insect central complex

In both Drosophila and mammals, the brain contains the most diverse population of cell types of any tissue. It is generally accepted that transcriptional diversity is an early step in generating neuronal and glial diversity, followed by the establishment of a unique gene expression profile that determines morphology, connectivity, and function. In Drosophila, there are two types of neural stem cells, called Type 1 (T1) and Type 2 (T2) neuroblasts. The diversity of T2-derived neurons contributes a large portion of the central complex (CX), a conserved brain region that plays a role in sensorimotor integration. Recent work has revealed much of the connectome of the CX, but how this connectome is assembled remains unclear. Mapping the transcriptional diversity of T2-derived neurons is a necessary step in linking transcriptional profile to the assembly of the adult brain. Here we perform single nuclei RNA sequencing of T2 neuroblast-derived adult neurons and glia. We identify clusters containing all known classes of glia, clusters that are male/female enriched, and 161 neuron-specific clusters. We map neurotransmitter and neuropeptide expression and identify unique transcription factor combinatorial codes for each cluster. This is a necessary step that directs functional studies to determine whether each transcription factor combinatorial code specifies a distinct neuron type within the CX. We map several columnar neuron subtypes to distinct clusters and identify two neuronal classes (NPF+ and AstA+) that both map to two closely related clusters. Our data support the hypothesis that each transcriptional cluster represents one or a few closely related neuron subtypes.

From genes to patterns: a framework for modeling the emergence of embryonic development from transcriptional regulation

Understanding embryonic patterning, the process by which groups of cells are partitioned into distinct identities defined by gene expression, is a central challenge in developmental biology. This complex phenomenon is driven by precise spatial and temporal regulation of gene expression across many cells, resulting in the emergence of highly organized tissue structures. While similar emergent behavior is well understood in other fields, such as statistical mechanics, the regulation of gene expression in development remains less clear, particularly regarding how molecular-level gene interactions lead to the large-scale patterns observed in embryos. In this study, we present a modeling framework that bridges the gap between molecular gene regulation and tissue-level embryonic patterning. Beginning with basic chemical reaction models of transcription at the single-gene level, we progress to model gene regulatory networks (GRNs) that mediate specific cellular functions. We then introduce phenomenological models of pattern formation, including the French Flag and Temporal Patterning/Speed Regulation models, and integrate them with molecular/GRN realizations. To facilitate understanding and application of our models, we accompany our mathematical framework with computer simulations, providing intuitive and simple code for each model. A key feature of our framework is the explicit articulation of underlying assumptions at each level of the model, from transcriptional regulation to tissue patterning. By making these assumptions clear, we provide a foundation for future experimental and theoretical work to critically examine and challenge them, thereby improving the accuracy and relevance of gene regulatory models in developmental biology. As a case study, we explore how different strategies for integrating enhancer activity affect the robustness and evolvability of GRNs that govern embryonic pattern formation. Our simulations suggest that a two-step regulation strategy, enhancer activation followed by competitive integration at the promoter, ensures more standardized integration of new enhancers into developmental GRNs, highlighting the adaptability of eukaryotic transcription. These findings shed new light on the transcriptional mechanisms underlying embryonic patterning, while the overall modeling framework serves as a foundation for future experimental and theoretical investigations.

Transcriptional complexity in the insect central complex: single nuclei RNA-sequencing of adult brain neurons derived from type 2 neuroblasts

In both invertebrates such as Drosophila and vertebrates such as mouse or human, the brain contains the most diverse population of cell types of any tissue. It is generally accepted that transcriptional diversity is an early step in generating neuronal and glial diversity, followed by the establishment of a unique gene expression profile that determines morphology, connectivity, and function. In Drosophila, there are two types of neural stem cells, called Type 1 (T1) and Type 2 (T2) neuroblasts. In contrast to T1 neuroblasts, T2 neuroblasts generate intermediate neural progenitors (INPs) that expand the number and diversity of cell types. The diversity of T2-derived neurons contributes a large portion of the central complex (CX), a conserved brain region that plays a role in sensorimotor integration. Recent work has revealed much of the connectome of the CX, but how this connectome is assembled remains unclear. Mapping the transcriptional diversity of neurons derived from T2 neuroblasts is a necessary step in linking transcriptional profile to the assembly of the adult brain. Here we perform single nuclei RNA sequencing of T2 neuroblast-derived adult neurons and glia. We identify clusters containing all known classes of glia, clusters that are male/female enriched, and 161 neuron-specific clusters. We map neurotransmitter and neuropeptide expression and identify unique transcription factor combinatorial codes for each cluster (presumptive neuron subtype). This is a necessary step that directs functional studies to determine whether each transcription factor combinatorial code specifies a distinct neuron type within the CX. We map several columnar neuron subtypes to distinct clusters and identify two neuronal classes (NPF+ and AstA+) that both map to two closely related clusters. Our data support the hypothesis that each transcriptional cluster represents one or a few closely related neuron subtypes.

Establishment of terminal selector combinations in optic lobe neurons

The medulla is the part of the Drosophila optic lobe with the greatest neuronal diversity, in which the identity of each neuronal type is specified in progenitors and newborn neurons via the integration of temporal, spatial, and Notch-driven patterning mechanisms. This identity is maintained in differentiating and adult neurons by the expression of neuronal type-specific combinations of terminal selectors, which are transcription factors expressed continuously during development and in the adult that are thought to control all neuronal type-specific gene expression. However, how the patterning mechanisms establish terminal selector expression is unknown. We have previously characterized the temporal and Notch origin of medulla neurons. Here we have used single-cell mRNA-sequencing to characterize their spatial origins and identified two new spatial subdomains. Together, this makes the medulla the first complex brain structure for which the patterning mechanisms specifying the identity of each neuronal type are known. This knowledge allowed us to identify correlations between patterning information, terminal selector expression and neuronal features. Our results suggest that different subsets of the patterning information accessible to a given neuronal type control the expression of each of its terminal selectors and of modules of terminal features, including neurotransmitter identity. Therefore, the evolution of new neuronal types could rely on the acquisition of modules of neuronal features predetermined by their developmental origin.

Tango-seq: overlaying transcriptomics on connectomics to identify neurons downstream of Drosophila clock neurons

Knowing how neural circuits change with neuronal plasticity and differ between individuals is important to fully understand behavior. Connectomes are typically assembled using electron microscopy, but this is low throughput and impractical for analyzing plasticity or mutations. Here, we modified the trans-Tango genetic circuit-tracing technique to identify neurons synaptically downstream of Drosophila s-LNv clock neurons, which show 24hr plasticity rhythms. s-LNv target neurons were labeled specifically in adult flies using a nuclear reporter gene, which facilitated their purification and then single cell sequencing. We call this Tango-seq, and it allows transcriptomic data - and thus cell identity - to be overlayed on top of anatomical data. We found that s-LNvs preferentially make synaptic connections with a subset of the CNMa+ DN1p clock neurons, and that these are likely plastic connections. We also identified synaptic connections between s-LNvs and mushroom body Kenyon cells. Tango-seq should be a useful addition to the connectomics toolkit.

From temporal patterning to neuronal connectivity in Drosophila type I neuroblast lineages

The development of the central nervous system (CNS) in flies and mammals requires the production of distinct neurons in different locations and times. Here we review progress on how Drosophila stem cells (neuroblasts; NBs) generate distinct neurons over time. There are two types of NBs: type I and type II NBs (defined below); here we focus on type I NBs; type II NBs are reviewed elsewhere in this issue. Type I NBs generate neural diversity via the cascading expression of specific temporal transcription factors (TTFs). TTFs are sequentially expressed in neuroblasts and required for the identity of neurons born during each TTF expression window. In this way TTFs specify the "temporal identity" or birth-order dependent identity of neurons. Recent studies have shown that TTF expression in neuroblasts alter the identity of their progeny, including directing motor neurons to form proper connectivity to the proper muscle targets, independent of their birth-order. Similarly, optic lobe (OL) type I NBs express a series of TTFs that promote proper neuron morphology and targeting to the four OL neuropils. Together, these studies demonstrate how temporal identity is crucial in promoting proper circuit assembly within the Drosophila CNS. In addition, TTF orthologs in mouse are good candidates for specifying neuron types in the neocortex and retina. In this review we highlight the recent advances in understanding the role of TTFs in CNS circuit assembly in Drosophila and reflect on the conservation of these mechanisms in mammalian CNS development.

The Drivers of Diversity: Integrated genetic and hormonal cues regulate neural diversity

Proper functioning of the nervous system relies not only on the generation of a vast repertoire of distinct neural cell types but also on the precise neural circuitry within them. How the generation of highly diverse neural populations is regulated during development remains a topic of interest. Landmark studies in Drosophila have identified the genetic and temporal cues regulating neural diversity and thus have provided valuable insights into our understanding of temporal patterning of the central nervous system. The development of the Drosophila central complex, which is mostly derived from type II neural stem cell (NSC) lineages, showcases how a small pool of NSCs can give rise to vast and distinct progeny. Similar to the human outer subventricular zone (OSVZ) neural progenitors, type II NSCs generate intermediate neural progenitors (INPs) to expand and diversify lineages that populate higher brain centers. Each type II NSC has a distinct spatial identity and timely regulated expression of many transcription factors and mRNA binding proteins. Additionally, INPs derived from them show differential expression of genes depending on their birth order. Together type II NSCs and INPs display a combinatorial temporal patterning that expands neural diversity of the central brain lineages. We cover advances in current understanding of type II NSC temporal patterning and discuss similarities and differences in temporal patterning mechanisms of various NSCs with a focus on how cell-intrinsic and extrinsic hormonal cues regulate temporal transitions in NSCs during larval development. Cell extrinsic ligands activate conserved signaling pathways and extrinsic hormonal cues act as a temporal switch that regulate temporal progression of the NSCs. We conclude by elaborating on how a progenitor's temporal code regulates the fate specification and identity of distinct neural types. At the end, we also discuss open questions in linking developmental cues to neural identity, circuits, and underlying behaviors in the adult fly.

Temporal regulation of neural diversity in Drosophila and vertebrates

The generation of neuronal diversity involves temporal patterning mechanisms by which a given progenitor sequentially produces multiple cell types. Several parallels are evident between the brain development programs of Drosophila and vertebrates, such as the successive emergence of specific cell types and the use of combinations of transcription factors to specify cell fates. Furthermore, cell-extrinsic cues such as hormones and signaling pathways have also been shown to be regulatory modules of temporal patterning. Recently, transcriptomic and epigenomic studies using large single-cell sequencing datasets have provided insights into the transcriptional dynamics of neurogenesis in the Drosophila and mammalian central nervous systems. We review these commonalities in the specification of neuronal identity and highlight the conserved or convergent strategies of brain development by discussing temporal patterning mechanisms found in flies and vertebrates.

Axon targeting of Drosophila medulla projection neurons requires diffusible Netrin and is coordinated with neuroblast temporal patterning

How axon guidance pathways are utilized in coordination with temporal and spatial patterning of neural progenitors to regulate neuropil assembly is not well understood. We study this question in the Drosophila medulla using the transmedullary (Tm) projection neurons that target lobula through the inner optic chiasm (IOC). We demonstrate that the Netrin pathway plays multiple roles in guidance of Tm axons and that temporal patterning of medulla neuroblasts determines pioneer versus follower Tm neurons during this process. Loss of Frazzled (Fra) in early-born pioneer Tm neurons leads to IOC defects, while loss of Fra from follower neurons does not affect the IOC. In the follower projection neurons, Fra is required in other targeting steps including lobula branch extension and layer-specific targeting. Furthermore, different from other identified scenarios of Netrin/Fra involved axon guidance in Drosophila, we demonstrate that diffusible Netrin is required for the correct axon targeting and optic lobe organization.

Cutting edge technologies expose the temporal regulation of neurogenesis in the Drosophila nervous system

During the development of the central nervous system (CNS), extremely large numbers of neurons are produced in a regular fashion to form precise neural circuits. During this process, neural progenitor cells produce different neurons over time due to their intrinsic gene regulatory mechanisms as well as extrinsic mechanisms. The Drosophila CNS has played an important role in elucidating the temporal mechanisms that control neurogenesis over time. It has been shown that a series of temporal transcription factors are sequentially expressed in neural progenitor cells and regulate the temporal specification of neurons in the embryonic CNS. Additionally, similar mechanisms are found in the developing optic lobe and central brain in the larval CNS. However, it is difficult to elucidate the function of numerous molecules in many different cell types solely by molecular genetic approaches. Recently, omics analysis using single-cell RNA-seq and other methods has been used to study the Drosophila nervous system on a large scale and is making a significant contribution to the understanding of the temporal mechanisms of neurogenesis. In this article, recent findings on the temporal patterning of neurogenesis and the contributions of cutting-edge technologies will be reviewed.

A complete temporal transcription factor series in the fly visual system

The brain consists of thousands of neuronal types that are generated by stem cells producing different neuronal types as they age. In Drosophila, this temporal patterning is driven by the successive expression of temporal transcription factors (tTFs)1-6. Here we used single-cell mRNA sequencing to identify the complete series of tTFs that specify most Drosophila optic lobe neurons. We verify that tTFs regulate the progression of the series by activating the next tTF(s) and repressing the previous one(s), and also identify more complex mechanisms of regulation. Moreover, we establish the temporal window of origin and birth order of each neuronal type in the medulla and provide evidence that these tTFs are sufficient to explain the generation of all of the neuronal diversity in this brain region. Finally, we describe the first steps of neuronal differentiation and show that these steps are conserved in humans. We find that terminal differentiation genes, such as neurotransmitter-related genes, are present as transcripts, but not as proteins, in immature larval neurons. This comprehensive analysis of a temporal series of tTFs in the optic lobe offers mechanistic insights into how tTF series are regulated, and how they can lead to the generation of a complete set of neurons.

A comprehensive temporal patterning gene network in Drosophila medulla neuroblasts revealed by single-cell RNA sequencing

During development, neural progenitors are temporally patterned to sequentially generate a variety of neural types. In Drosophila neural progenitors called neuroblasts, temporal patterning is regulated by cascades of Temporal Transcription Factors (TTFs). However, known TTFs were mostly identified through candidate approaches and may not be complete. In addition, many fundamental questions remain concerning the TTF cascade initiation, progression, and termination. In this work, we use single-cell RNA sequencing of Drosophila medulla neuroblasts of all ages to identify a list of previously unknown TTFs, and experimentally characterize their roles in temporal patterning and neuronal specification. Our study reveals a comprehensive temporal gene network that patterns medulla neuroblasts from start to end. Furthermore, the speed of the cascade progression is regulated by Lola transcription factors expressed in all medulla neuroblasts. Our comprehensive study of the medulla neuroblast temporal cascade illustrates mechanisms that may be conserved in the temporal patterning of neural progenitors.

During development, neural progenitors generate a variety of neural types sequentially. Here the authors examine gene expression patterns in Drosophila neural progenitors at single-cell level, and identify a gene regulatory network controlling the sequential generation of different neural types.

Decoding gene regulation in the fly brain

The Drosophila brain is a frequently used model in neuroscience. Single-cell transcriptome analysis^1-6, three-dimensional morphological classification⁷ and electron microscopy mapping of the connectome^8,9 have revealed an immense diversity of neuronal and glial cell types that underlie an array of functional and behavioural traits in the fly. The identities of these cell types are controlled by gene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. Here, to characterize GRNs at the cell-type level in the fly brain, we profiled the chromatin accessibility of 240,919 single cells spanning 9 developmental timepoints and integrated these data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which 70,000 are linked to developmental trajectories involving neurogenesis, reprogramming and maturation. For 40 cell types, uniquely accessible regions were associated with their expressed transcription factors and downstream target genes through a combination of motif discovery, network inference and deep learning, creating enhancer GRNs. The enhancer architectures revealed by DeepFlyBrain lead to a better understanding of neuronal regulatory diversity and can be used to design genetic driver lines for cell types at specific timepoints, facilitating their characterization and manipulation.

Transcriptional and epigenetic regulation of temporal patterning in neural progenitors

During development, neural progenitors undergo temporal patterning as they age to sequentially generate differently fated progeny. Temporal patterning of neural progenitors is relatively well-studied in Drosophila. Temporal cascades of transcription factors or opposing temporal gradients of RNA-binding proteins are expressed in neural progenitors as they age to control the fates of the progeny. The temporal progression is mostly driven by intrinsic mechanisms including cross-regulations between temporal genes, but environmental cues also play important roles in certain transitions. Vertebrate neural progenitors demonstrate greater plasticity in response to extrinsic cues. Recent studies suggest that vertebrate neural progenitors are also temporally patterned by a combination of transcriptional and post-transcriptional mechanisms in response to extracellular signaling to regulate neural fate specification. In this review, we summarize recent advances in the study of temporal patterning of neural progenitors in Drosophila and vertebrates. We also discuss the involvement of epigenetic mechanisms, specifically the Polycomb group complexes and ATP-dependent chromatin remodeling complexes, in the temporal patterning of neural progenitors.

Patterning with clocks and genetic cascades: Segmentation and regionalization of vertebrate versus insect body plans

Oscillatory and sequential processes have been implicated in the spatial patterning of many embryonic tissues. For example, molecular clocks delimit segmental boundaries in vertebrates and insects and mediate lateral root formation in plants, whereas sequential gene activities are involved in the specification of regional identities of insect neuroblasts, vertebrate neural tube, vertebrate limb, and insect and vertebrate body axes. These processes take place in various tissues and organisms, and, hence, raise the question of what common themes and strategies they share. In this article, we review 2 processes that rely on the spatial regulation of periodic and sequential gene activities: segmentation and regionalization of the anterior-posterior (AP) axis of animal body plans. We study these processes in species that belong to 2 different phyla: vertebrates and insects. By contrasting 2 different processes (segmentation and regionalization) in species that belong to 2 distantly related phyla (arthropods and vertebrates), we elucidate the deep logic of patterning by oscillatory and sequential gene activities. Furthermore, in some of these organisms (e.g., the fruit fly Drosophila), a mode of AP patterning has evolved that seems not to overtly rely on oscillations or sequential gene activities, providing an opportunity to study the evolution of pattern formation mechanisms.

Single-cell transcriptomics in the Drosophila visual system: Advances and perspectives on cell identity regulation, connectivity, and neuronal diversity evolution

The Drosophila visual system supports complex behaviors and shares many of its anatomical and molecular features with the vertebrate brain. Yet, it contains a much more manageable number of neurons and neuronal types. In addition to the extensive Drosophila genetic toolbox, this relative simplicity has allowed decades of work to yield a detailed account of its neuronal type diversity, morphology, connectivity and specification mechanisms. In the past three years, numerous studies have applied large scale single-cell transcriptomic approaches to the Drosophila visual system and have provided access to the complete gene expression profile of most neuronal types throughout development. This makes the fly visual system particularly well suited to perform detailed studies of the genetic mechanisms underlying the evolution and development of neuronal systems. Here, we highlight how these transcriptomic resources allow exploring long-standing biological questions under a new light. We first present the efforts made to characterize neuronal diversity in the Drosophila visual system and suggest ways to further improve this description. We then discuss current advances allowed by the single-cell datasets, and envisage how these datasets can be further leveraged to address fundamental questions regarding the regulation of neuronal identity, neuronal circuit development and the evolution of neuronal diversity.

Integrated Patterning Programs During Drosophila Development Generate the Diversity of Neurons and Control Their Mature Properties

During the approximately 5 days of Drosophila neurogenesis (late embryogenesis to the beginning of pupation), a limited number of neural stem cells produce approximately 200,000 neurons comprising hundreds of cell types. To build a functional nervous system, neuronal types need to be produced in the proper places, appropriate numbers, and correct times. We discuss how neural stem cells (neuroblasts) obtain so-called area codes for their positions in the nervous system (spatial patterning) and how they keep time to sequentially produce neurons with unique fates (temporal patterning). We focus on specific examples that demonstrate how a relatively simple patterning system (Notch) can be used reiteratively to generate different neuronal types. We also speculate on how different modes of temporal patterning that operate over short versus long time periods might be linked. We end by discussing how specification programs are integrated and lead to the terminal features of different neuronal types.