Neurons gating behavior-developmental, molecular and functional features of neurons in the Substantia Nigra pars reticulata

The Substantia Nigra pars reticulata (SNpr) is the major information output site of the basal ganglia network and instrumental for the activation and adjustment of movement, regulation of the behavioral state and response to reward. Due to both overlapping and unique input and output connections, the SNpr might also have signal integration capacity and contribute to action selection. How the SNpr regulates these multiple functions remains incompletely understood. The SNpr is located in the ventral midbrain and is composed primarily of inhibitory GABAergic projection neurons that are heterogeneous in their properties. In addition, the SNpr contains smaller populations of other neurons, including glutamatergic neurons. Here, we discuss regionalization of the SNpr, in particular the division of the SNpr neurons to anterior (aSNpr) and posterior (pSNpr) subtypes, which display differences in many of their features. We hypothesize that unique developmental and molecular characteristics of the SNpr neuron subtypes correlate with both region-specific connections and notable functional specializations of the SNpr. Variation in both the genetic control of the SNpr neuron development as well as signals regulating cell migration and axon guidance may contribute to the functional diversity of the SNpr neurons. Therefore, insights into the various aspects of differentiation of the SNpr neurons can increase our understanding of fundamental brain functions and their defects in neurological and psychiatric disorders, including movement and mood disorders, as well as epilepsy.Peer reviewe

Regulation of GABAergic neuron identity and diversity in the developing midbrain

Gamma-aminobutyric acid (GABA) is the most abundant inhibitory neurotransmitter in the vertebrate brain. In the midbrain, GABAergic neurons contribute to the regulation of locomotion, nociception, defensive behaviours, fear and anxiety, as well as sensing reward and addiction. Despite the clinical relevance of this group of neurons, the mechanisms regulating their development are largely unknown. In addition, their migration and connectivity patterns are poorly characterized. This study focuses on the molecular mechanisms specifying the GABAergic fate, and the developmental origins of midbrain GABAergic neurons. First, we have characterized the function of a zink-finger transcription factor Gata2. Using a tissue-specific mutagenesis in mouse midbrain and anteror hindbrain, we showed that Gata2 is a crucial determinant of the GABAergic fate in midbrain. In the absence of Gata2, no GABAergic neurons are produced from the otherwise competent midbrain neuroepithelium. Instead, the Gata2-mutant cells acquire a glutamatergic neuron phenotype. Ectopic expression of Gata2 was also sufficient to induce GABAergic in chicken midbrain. Second, we have analyzed the midbrain phenotype of mice mutant for a proneural gene Ascl1, and described the variable and region-dependent requirements for Ascl1 in the midbrain GABAergic neurogenesis. These studies also have implications on the origin of distinct anatomical and functional GABAergic subpopulations in midbrain. Third, we have identified unique developmental properties of GABAergic neurons that are associated with the midbrain dopaminergic nuclei, the substantia nigra pars reticulata (SNpr) and ventral tegmental area (VTA). Namely, the genetic regulation of GABAergic fate in these cells is distinct from the rest of midbrain. In accordance to this phenomenon, our detailed fate-mapping analyses indicated that the SNpr-VTA GABAergic neurons are generated outside midbrain, in the neuroepithelium of anterior hindbrain.Keskiaivojen GABAergiset hermosolut ovat keskeisiä mm. mielialan ja motivaation säätelyssä. Ne ovat myös osallisina psyykkisissä sairauksissa kuten ahdistuksessa ja masennuksessa sekä erilaisten riippuvaisuuksien synnyssä. Lääketieteellisestä merkityksestään huolimatta keskiaivojen GABAergiset hermosolut tunnetaan huonosti molekulaariselta koostumukseltaan ja yksilönkehityksen aikaisilta säätelymekanismeiltaan. Tässä tutkimuksessa olemme kartoittaneet keskiaivojen alueet, jotka tuottavat GABAergisiä hermosoluja. Hiiren ja kanan alkioita tutkimusmalleina käyttäen olemme osoittaneet miten tietyt transkriptiotekijät ohjaavat GABAergisen soluidentiteetin syntyä. Lisäksi olemme karakterisoineet eri GABAergisten hermosolujen osapopulaatioiden ominaisuuksia, keskittyen muista keskiaivon GABAergisista soluista poikkeavien ventraalisten GABAergisten hermosolujen syntyhistoriaan. Tutkimus lisää ymmärrystämme keskiaivojen GABAergisten hermosolujen kehityksestä ja monimutkaisuudesta

Gata2 and Gata3 regulate the differentiation of serotonergic and glutamatergic neuron subtypes of the dorsal raphe

Peer reviewe

Whole-body single-cell sequencing reveals transcriptional domains in the annelid larval body.

Animal bodies comprise diverse arrays of cells. To characterise cellular identities across an entire body, we have compared the transcriptomes of single cells randomly picked from dissociated whole larvae of the marine annelid Platynereis dumerilii. We identify five transcriptionally distinct groups of differentiated cells, each expressing a unique set of transcription factors and effector genes that implement cellular phenotypes. Spatial mapping of cells into a cellular expression atlas, and wholemount in situ hybridisation of group-specific genes reveals spatially coherent transcriptional domains in the larval body, comprising e.g. apical sensory-neurosecretory cells vs. neural/epidermal surface cells. These domains represent new, basic subdivisions of the annelid body based entirely on differential gene expression, and are composed of multiple, transcriptionally similar cell types. They do not represent clonal domains, as revealed by developmental lineage analysis. We propose that the transcriptional domains that subdivide the annelid larval body represent families of related cell types that have arisen by evolutionary diversification. Their possible evolutionary conservation makes them a promising tool for evo-devo research. (167/250).KA and JM were supported by the Marie Curie COFUND programme from the European Commission and by EMBL core funding. NE, PC, VB, and DA were supported by core funding from EMBL. KA, HMV, PYB, PV were supported by the Advanced grant “Brain Evo-Devo” from the European Research Council. JCM was supported by core funding from EMBL and Cancer Research UK

Molecular Fingerprint and Developmental Regulation of the Tegmental GABAergic and Glutamatergic Neurons Derived from the Anterior Hindbrain

Tegmental nuclei in the ventral midbrain and anterior hindbrain control motivated behavior, mood, memory, and movement. These nuclei contain inhibitory GABAergic and excitatory glutamatergic neurons, whose molecular diversity and development remain largely unraveled. Many tegmental neurons originate in the embryonic ventral rhombomere 1 (r1), where GABAergic fate is regulated by the transcription factor (TF) Tal1. We used single-cell mRNA sequencing of the mouse ventral r1 to characterize the Tal1-dependent and independent neuronal precursors. We describe gene expression dynamics during bifurcation of the GABAergic and glutamatergic lineages and show how active Notch signaling promotes GABAergic fate selection in postmitotic precursors. We identify GABAergic precursor subtypes that give rise to distinct tegmental nuclei and demonstrate that Sox14 and Zfpm2, two TFs downstream of Tal1, are necessary for the differentiation of specific tegmental GABAergic neurons. Our results provide a framework for understanding the development of cellular diversity in the tegmental nuclei.Peer reviewe

The role of Tal2 and Tal1 in the differentiation of midbrain GABAergic neuron precursors.

Peer reviewe

Identifying Cell Types from Spatially Referenced Single-Cell Expression Datasets

<div><p>Complex tissues, such as the brain, are composed of multiple different cell types, each of which have distinct and important roles, for example in neural function. Moreover, it has recently been appreciated that the cells that make up these sub-cell types themselves harbour significant cell-to-cell heterogeneity, in particular at the level of gene expression. The ability to study this heterogeneity has been revolutionised by advances in experimental technology, such as Wholemount in Situ Hybridizations (WiSH) and single-cell RNA-sequencing. Consequently, it is now possible to study gene expression levels in thousands of cells from the same tissue type. After generating such data one of the key goals is to cluster the cells into groups that correspond to both known and putatively novel cell types. Whilst many clustering algorithms exist, they are typically unable to incorporate information about the spatial dependence between cells within the tissue under study. When such information exists it provides important insights that should be directly included in the clustering scheme. To this end we have developed a clustering method that uses a Hidden Markov Random Field (HMRF) model to exploit both quantitative measures of expression and spatial information. To accurately reflect the underlying biology, we extend current HMRF approaches by allowing the degree of spatial coherency to differ between clusters. We demonstrate the utility of our method using simulated data before applying it to cluster single cell gene expression data generated by applying WiSH to study expression patterns in the brain of the marine annelid <i>Platynereis dumereilii</i>. Our approach allows known cell types to be identified as well as revealing new, previously unexplored cell types within the brain of this important model system.</p></div

Light contamination in in-situ hybridization luminescence data.

<p>Panel A shows the raw fluorescent microscopy capture of the gene Ascl's expression for one layer in the brain of Platynereis. Panel B shows the light intensity measured along the red line in panel A. Panel C shows the expected light intensity profile without light contamination. Because of the small scale of study, voxels surrounded by other voxels expressing a particular gene will have a higher intensity values because of nearby light contamination. Panel D shows errors introduced by the voxel cell model. Path <i>a</i> shows how regions with highly expressed genes can introduce errors through light contamination. Path <i>b</i> shows how some voxels may appear artificially void of expression because of the uneven distribution of transcripts inside the cytoplasm especially for large cells.</p