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To understand how neurons assemble to form functional circuits, it is necessary to obtain a detailed knowledge of their diversity and to define the developmental specification programs that give rise to this diversity. Invertebrates and vertebrates appear to share common developmental principles of neuronal specification in which cascades of transcription factors temporally pattern progenitors, while spatial cues modify the outcomes of this temporal patterning. Here, we highlight these conserved mechanisms and describe how they are used in distinct neural structures. We present the questions that remain for a better understanding of neuronal specification. Single-cell RNA profiling approaches will potentially shed light on these questions, allowing not only the characterization of neuronal diversity in adult brains, but also the investigation of the developmental trajectories leading to the generation and maintenance of this diversity.

Fundamental to living cells is the capacity to differentiate into subtypes with specialized attributes. Understanding the way cells acquire their fates is a major challenge in developmental biology. How cells adopt a particular fate is usually thought of as being deterministic, and in the large majority of cases it is. That is, cells acquire their fate by virtue of their lineage or their proximity to an inductive signal from another cell. In some cases, however, and in organisms ranging from bacteria to humans, cells choose one or another pathway of differentiation stochastically, without apparent regard to environment or history. Stochasticity has important mechanistic requirements. We speculate on why stochasticity is advantageous--and even critical in some circumstances--to the individual, the colony, or the species.

Temporal patterning of neural progenitors leads to the sequential production of diverse neurons. To understand how extrinsic cues influence intrinsic temporal programs, we studied Drosophila mushroom body progenitors (neuroblasts) that sequentially produce only three neuronal types: γ, then α’β’, followed by αβ. Opposing gradients of two RNA-binding proteins Imp and Syp comprise the intrinsic temporal program. Extrinsic activin signaling regulates the production of α’β’ neurons but whether it affects the intrinsic temporal program was not known. We show that the activin ligand Myoglianin from glia regulates the temporal factor Imp in mushroom body neuroblasts. Neuroblasts missing the activin receptor Baboon have a delayed intrinsic program as Imp is higher than normal during the α’β’ temporal window, causing the loss of α’β’ neurons, a decrease in αβ neurons, and a likely increase in γ neurons, without affecting the overall number of neurons produced. Our results illustrate that an extrinsic cue modifies an intrinsic temporal program to increase neuronal diversity.

Four medulla neurons implement two critical processing steps to incoming signals in Drosophila motion detection. Motion detector neurons identified Motion detection by the fly visual system has long been proposed to rely on a simple neuronal circuit — the Reichardt detector, which connects adjacent sensory neurons with a slight temporal delay — but electrophysiological evidence has been lacking. Claude Desplan and colleagues have performed patch-clamp recordings in the Drosophila medulla in vivo and identify four neurons — Mi1, Tm3, Tm1 and Tm2 — that process delayed and non-delayed inputs to detect light and dark moving edges. Recent neuro-anatomical results have suggested that parts of the motion detection mechanism in the mammalian retina resemble fly Reichardt circuitry. The algorithms and neural circuits that process spatio-temporal changes in luminance to extract visual motion cues have been the focus of intense research. An influential model, the Hassenstein–Reichardt correlator 1 , relies on differential temporal filtering of two spatially separated input channels, delaying one input signal with respect to the other. Motion in a particular direction causes these delayed and non-delayed luminance signals to arrive simultaneously at a subsequent processing step in the brain; these signals are then nonlinearly amplified to produce a direction-selective response. Recent work in Drosophila has identified two parallel pathways that selectively respond to either moving light or dark edges 2 , 3 . Each of these pathways requires two critical processing steps to be applied to incoming signals: differential delay between the spatial input channels, and distinct processing of brightness increment and decrement signals. Here we demonstrate, using in vivo patch-clamp recordings, that four medulla neurons implement these two processing steps. The neurons Mi1 and Tm3 respond selectively to brightness increments, with the response of Mi1 delayed relative to Tm3. Conversely, Tm1 and Tm2 respond selectively to brightness decrements, with the response of Tm1 delayed compared with Tm2. Remarkably, constraining Hassenstein–Reichardt correlator models using these measurements produces outputs consistent with previously measured properties of motion detectors, including temporal frequency tuning and specificity for light versus dark edges. We propose that Mi1 and Tm3 perform critical processing of the delayed and non-delayed input channels of the correlator responsible for the detection of light edges, while Tm1 and Tm2 play analogous roles in the detection of moving dark edges. Our data show that specific medulla neurons possess response properties that allow them to implement the algorithmic steps that precede the correlative operation in the Hassenstein–Reichardt correlator, revealing elements of the long-sought neural substrates of motion detection in the fly.

Peptides from long noncoding RNAs control a muscle calcium pump [Also see Report by Nelson et al. ] A growing body of evidence shows that so-called long noncoding RNAs (lncRNAs) often produce short peptides from small open reading frames (s mORFs) ( 1 ). Whether and how smORF-encoded peptides fulfill specific functions remain poorly understood. Recent studies in flies ( 2 ) and mammals ( 3 ) have revealed that transcripts annotated as lncRNAs encode smORF peptides that bind to, and inhibit, the sarco/endoplasmic reticulum calcium adenosine triphosphatase (SERCA), an ion pump that is a key player in handling calcium in striated muscles. On page 271 of this issue, Nelson et al. ( 4 ) report that a lncRNA-encoded small peptide competes with SERCA-inhibitory peptides, thereby favoring heart contractility in mammals. These findings open new ways to understand cardiac function and pathologies, and show that smORF peptides act as versatile regulators of protein activity.

In the Drosophila optic lobes, 800 retinotopically organized columns in the medulla act as functional units for processing visual information. The medulla contains over 80 types of neuron, which belong to two classes: uni-columnar neurons have a stoichiometry of one per column, while multi-columnar neurons contact multiple columns. Here we show that combinatorial inputs from temporal and spatial axes generate this neuronal diversity: all neuroblasts switch fates over time to produce different neurons; the neuroepithelium that generates neuroblasts is also subdivided into six compartments by the expression of specific factors. Uni-columnar neurons are produced in all spatial compartments independently of spatial input; they innervate the neuropil where they are generated. Multi-columnar neurons are generated in smaller numbers in restricted compartments and require spatial input; the majority of their cell bodies subsequently move to cover the entire medulla. The selective integration of spatial inputs by a fixed temporal neuroblast cascade thus acts as a powerful mechanism for generating neural diversity, regulating stoichiometry and the formation of retinotopy. Combinatorial inputs from temporal and spatial axes act together to promote medullary neural diversity in the optic lobes of Drosophila . Neuronal diversity in the Drosophila optic lobe Photoreceptor neurons in the 800 ommatidia of Drosophila 's compound eye send visual information to 800 matching columns in the medulla, each of which contains more than 80 cell types generated during optic-lobe development. In this paper, Claude Desplan and colleagues distinguish two classes of medulla neurons. Uni-columnar neurons are specified through temporal sequences in the expression of regulatory genes, independently of spatial input, whereas multi-columnar neurons integrate the same temporal signals with spatial input specific to six compartments in the developing optic lobes. The findings extend the repertoire of combinatorial mechanisms generating neuronal diversity during brain development.

In the Drosophila optic lobes, the medulla processes visual information coming from inner photoreceptors R7 and R8 and from lamina neurons. It contains approximately 40,000 neurons belonging to more than 70 different types. Here we describe how precise temporal patterning of neural progenitors generates these different neural types. Five transcription factors—Homothorax, Eyeless, Sloppy paired, Dichaete and Tailless—are sequentially expressed in a temporal cascade in each of the medulla neuroblasts as they age. Loss of Eyeless, Sloppy paired or Dichaete blocks further progression of the temporal sequence. We provide evidence that this temporal sequence in neuroblasts, together with Notch-dependent binary fate choice, controls the diversification of the neuronal progeny. Although a temporal sequence of transcription factors had been identified in Drosophila embryonic neuroblasts, our work illustrates the generality of this strategy, with different sequences of transcription factors being used in different contexts. Five transcription factors are sequentially expressed in a temporal cascade in Drosophila medulla neuroblasts of the visual system; cross-regulations between these transcription factors control the temporal transitions, and temporal switching of neural progenitors may be a common theme in neuronal specification, with different sequences of transcription factors being used in different contexts. Timely nerve cell regeneration The brain is made up of many different types of neuronal and glial cells, but how their parental neural stem cells generate such diversity during development is largely unknown. Several lines of evidence point to a time element in the development pattern of neural stem cells, and two papers in this issue of Nature use Drosophila melanogaster models to demonstrate a role for temporal progression under the control of regulatory cascades. Omer Ali Bayraktar and Chris Doe (using the fly larval brain) and Claude Desplan and colleagues (using the fly visual system) show that neuronal progenitors change over time as they produce successive waves of regulatory proteins, thus increasing both the size and the diversity of their neuronal and glial progeny. As similar neuronal progenitors — and homologous regulatory proteins — have been identified in developing mammalian brains, it is likely that such temporal patterning also contributes to the neuronal complexity of the human neocortex.

This Review covers recent technological developments to label and manipulate genes in selected populations of cells in Drosophila melanogaster . The Review is intended as a user guide to help with the selection of the best expression systems and clonal analysis techniques for developmental studies in the fly. The development of two-component expression systems in Drosophila melanogaster , one of the most powerful genetic models, has allowed the precise manipulation of gene function in specific cell populations. These expression systems, in combination with site-specific recombination approaches, have also led to the development of new methods for clonal lineage analysis. We present a hands-on user guide to the techniques and approaches that have greatly increased resolution of genetic analysis in the fly, with a special focus on their application for lineage analysis. Our intention is to provide guidance and suggestions regarding which genetic tools are most suitable for addressing different developmental questions.

The visual systems of most species contain photoreceptors with distinct spectral sensitivities that allow animals to distinguish lights by their spectral composition. In Drosophila, photoreceptors R1-R6 have the same spectral sensitivity throughout the eye and are responsible for motion detection. In contrast, photoreceptors R7 and R8 exhibit heterogeneity and are important for color vision. We investigated how photoreceptor types contribute to the attractiveness of light by blocking the function of certain subsets and by measuring differential phototaxis between spectrally different lights. In a \"UV vs. blue\" choice, flies with only R1-R6, as well as flies with only R7/R8 photoreceptors, preferred blue, suggesting a nonadditive interaction between the two major subsystems. Flies defective for UV-sensitive R7 function preferred blue, whereas flies defective for either type of R8 (blue- or green-sensitive) preferred UV. In a \"blue vs. green\" choice, flies defective for R8 (blue) preferred green, whereas those defective for R8 (green) preferred blue. Involvement of all photoreceptors [R1-R6, R7, R8 (blue), R8 (green)] distinguishes phototaxis from motion detection that is mediated exclusively by R1-R6.

Sensory systems use stochastic mechanisms to diversify neuronal subtypes. In the Drosophila eye, stochastic expression of the PAS-bHLH transcription factor Spineless (Ss) determines a random binary subtype choice in R7 photoreceptors. Here, we show that a stochastic, cell-autonomous decision to express ss is made intrinsically by each ss locus. Stochastic on or off expression of each ss allele is determined by combinatorial inputs from one enhancer and two silencers acting at long range. However, the two ss alleles also average their frequency of expression through up-regulatory and down-regulatory interallelic cross-talk. This inter- or intrachromosomal long-range regulation does not require endogenous ss chromosomal positioning or pairing. Therefore, although individual ss alleles make independent stochastic choices, interchromosomal communication coordinates expression state between alleles, ensuring that they are both expressed in the same random subset of R7s.