TCF7L2 regulates postmitotic differentiation programmes and excitability patterns in the thalamus

Disentangling cell-intrinsic and extrinsic factors underlying evolution

A key goal of developmental biology is to determine the extent to which cells and organs develop autonomously, as opposed to requiring interactions with other cells or environmental factors. Chimeras have played a foundational role in this by enabling qualitative classification of cell-intrinsically vs. extrinsically driven processes. Here, we extend this framework to precisely decompose evolutionary divergence in any quantitative trait into cell-intrinsic, extrinsic, and intrinsic-extrinsic interaction components. Applying this framework to thousands of gene expression levels in reciprocal rat-mouse chimeras, we found that the majority of their divergence is attributable to cell-intrinsic factors, though extrinsic factors also play an integral role. For example, a rat-like extracellular environment extrinsically up-regulates the expression of a key transcriptional regulator of the endoplasmic reticulum (ER) stress response in some but not all cell types, which in turn strongly predicts extrinsic up-regulation of its target genes and of the ER stress response pathway as a whole. This effect is also seen at the protein level, suggesting propagation through multiple regulatory levels. Applying our framework to a cellular trait, neuronal differentiation, revealed a complex interaction of intrinsic and extrinsic factors. Finally, we show that imprinted genes are dramatically mis-expressed in species-mismatched environments, suggesting that mismatch between rapidly evolving intrinsic and extrinsic mechanisms controlling gene imprinting may contribute to barriers to interspecies chimerism. Overall, our conceptual framework opens new avenues to investigate the mechanistic basis of developmental processes and evolutionary divergence across myriad quantitative traits in any multicellular organism.

The Phylotypic Brain of Vertebrates, from Neural Tube Closure to Brain Diversification

BACKGROUND

The phylotypic or intermediate stages are thought to be the most evolutionary conserved stages throughout embryonic development. The contrast with divergent early and later stages derived from the concept of the evo-devo hourglass model. Nonetheless, this developmental constraint has been studied as a whole embryo process, not at organ level. In this review, we explore brain development to assess the existence of an equivalent brain developmental hourglass. In the specific case of vertebrates, we propose to split the brain developmental stages into: (1) Early: Neurulation, when the neural tube arises after gastrulation. (2) Intermediate: Brain patterning and segmentation, when the neuromere identities are established. (3) Late: Neurogenesis and maturation, the stages when the neurons acquire their functionality. Moreover, we extend this analysis to other chordates brain development to unravel the evolutionary origin of this evo-devo constraint.

SUMMARY

Based on the existing literature, we hypothesise that a major conservation of the phylotypic brain might be due to the pleiotropy of the inductive regulatory networks, which are predominantly expressed at this stage. In turn, earlier stages such as neurulation are rather mechanical processes, whose regulatory networks seem to adapt to environment or maternal geometries. The later stages are also controlled by inductive regulatory networks, but their effector genes are mostly tissue-specific and functional, allowing diverse developmental programs to generate current brain diversity. Nonetheless, all stages of the hourglass are highly interconnected: divergent neurulation must have a vertebrate shared end product to reproduce the vertebrate phylotypic brain, and the boundaries and transcription factor code established during the highly conserved patterning will set the bauplan for the specialised and diversified adult brain.

KEY MESSAGES

The vertebrate brain is conserved at phylotypic stages, but the highly conserved mechanisms that occur during these brain mid-development stages (Inducing Regulatory Networks) are also present during other stages. Oppositely, other processes as cell interactions and functional neuronal genes are more diverse and majoritarian in early and late stages of development, respectively. These phenomena create an hourglass of transcriptomic diversity during embryonic development and evolution, with a really conserved bottleneck that set the bauplan for the adult brain around the phylotypic stage.

Astrocytic β-catenin signaling via TCF7L2 regulates synapse development and social behavior

The Wnt/β-catenin pathway contains multiple high-confidence risk genes that are linked to neurodevelopmental disorders, including autism spectrum disorder. However, its ubiquitous roles across brain cell types and developmental stages have made it challenging to define its impact on neural circuit development and behavior. Here, we show that TCF7L2, which is a key transcriptional effector of the Wnt/β-catenin pathway, plays a cell-autonomous role in postnatal astrocyte maturation and impacts adult social behavior. TCF7L2 was the dominant Wnt effector that was expressed in both mouse and human astrocytes, with a peak during astrocyte maturation. The conditional knockout of Tcf7l2 in postnatal astrocytes led to an enlargement of astrocytes with defective tiling and gap junction coupling. These mice also exhibited an increase in the number of cortical excitatory and inhibitory synapses and a marked increase in social interaction by adulthood. These data reveal an astrocytic role for developmental Wnt/β-catenin signaling in restricting excitatory synapse numbers and regulating adult social behavior.

Neurogenesis redirects β-catenin from adherens junctions to the nucleus to promote axonal growth

Here, we show that, in the developing spinal cord, after the early Wnt-mediated Tcf transcription activation that confers dorsal identity to neural stem cells, neurogenesis redirects β-catenin from the adherens junctions to the nucleus to stimulate Tcf-dependent transcription in a Wnt-independent manner. This new β-catenin activity regulates genes implicated in several aspects of contralateral axon growth, including axon guidance and adhesion. Using live imaging of ex-vivo chick neural tube, we showed that the nuclear accumulation of β-catenin and the rise in Tcf-dependent transcription both initiate before the dismantling of the adherens junctions and remain during the axon elongation process. Notably, we demonstrated that β-catenin activity in post-mitotic cells depends on TCF7L2 and is central to spinal commissural axon growth. Together, our results reveal Wnt-independent Tcf/β-catenin regulation of genes that control the growth and guidance of commissural axons in chick spinal cord.

The embryonic patterning gene Dbx1 governs the survival of the auditory midbrain via Tcf7l2-Ap2δ transcriptional cascade

At the top of the midbrain is the inferior colliculus (IC), which functions as the major hub for processing auditory information. Despite the functional significance of neurons in the IC, our understanding of their formation is limited. In this study, we identify the embryonic patterning gene Dbx1 as a key molecular player that governs genetic programs for IC survival. We find that Dbx1 plays a critical role in preventing apoptotic cell death in postnatal IC by transcriptionally repressing c-Jun and pro-apoptotic BH3 only factors. Furthermore, by employing combined approaches, we uncover that Tcf7l2 functions downstream of Dbx1. Loss of Tcf7l2 function causes IC phenotypes with striking similarity to those of Dbx1 mutant mice, which include defective embryonic maturation and postnatal deletion of the IC. Finally, we demonstrate that the Dbx1-Tcf7l2 cascade functions upstream of Ap-2δ, which is essential for IC development and survival. Together, these results unravel a novel molecular mechanism for IC maintenance, which is indispensable for normal brain development.

TCF7L2 acts as a molecular switch in midbrain to control mammal vocalization through its DNA binding domain but not transcription activation domain

Vocalization is an essential medium for social signaling in birds and mammals. Periaqueductal gray (PAG) a conserved midbrain structure is believed to be responsible for innate vocalizations, but its molecular regulation remains largely unknown. Here, through a mouse forward genetic screening we identified one of the key Wnt/β-catenin effectors TCF7L2/TCF4 controls ultrasonic vocalization (USV) production and syllable complexity during maternal deprivation and sexual encounter. Early developmental expression of TCF7L2 in PAG excitatory neurons is necessary for the complex trait, while TCF7L2 loss reduces neuronal gene expressions and synaptic transmission in PAG. TCF7L2-mediated vocal control is independent of its β-catenin-binding domain but dependent of its DNA binding ability. Patient mutations associated with developmental disorders, including autism spectrum disorders, disrupt the transcriptional repression effect of TCF7L2, while mice carrying those mutations display severe USV impairments. Therefore, we conclude that TCF7L2 orchestrates gene expression in midbrain to control vocal production through its DNA binding but not transcription activation domain.

TCF7l2, a nuclear marker that labels premyelinating oligodendrocytes and promotes oligodendroglial lineage progression

Clinical and basic neuroscience research is greatly benefited from the identification and characterization of lineage specific and developmental stage-specific markers. In the glial research community, histological markers that specifically label newly differentiated premyelinating oligodendrocytes are still scarce. Premyelinating oligodendrocyte markers, especially those of nuclear localization, enable researchers to easily quantify the rate of oligodendrocyte generation regardless of developmental ages. We propose that the transcription factor 7-like 2 (TCF7l2, mouse gene symbol Tcf7l2) is a useful nuclear marker that specifically labels newly generated premyelinating oligodendrocytes and promotes oligodendroglial lineage progression. Here, we highlight the controversial research history of TCF7l2 expression and function in oligodendroglial field and discuss previous experimental data justifying TCF7l2 as a specific nuclear marker for premyelinating oligodendrocytes during developmental myelination and remyelination. We conclude that TCF7l2 can be used alone or combined with pan-oligodendroglial lineage markers to identify newly differentiated or newly regenerated oligodendrocytes and quantify the rate of oligodendrocyte generation.

A model-based constrained deep learning clustering approach for spatially resolved single-cell data

Spatially resolved scRNA-seq (sp-scRNA-seq) technologies provide the potential to comprehensively profile gene expression patterns in tissue context. However, the development of computational methods lags behind the advances in these technologies, which limits the fulfillment of their potential. In this study, we develop a deep learning approach for clustering sp-scRNA-seq data, named Deep Spatially constrained Single-cell Clustering (DSSC). In this model, we integrate the spatial information of cells into the clustering process in two steps: (1) the spatial information is encoded by using a graphical neural network model, and (2) cell-to-cell constraints are built based on the spatial expression pattern of the marker genes and added in the model to guide the clustering process. Then, a deep embedding clustering is performed on the bottleneck layer of autoencoder by Kullback-Leibler (KL) divergence along with the learning of feature representation. DSSC is the first model that can use information from both spatial coordinates and marker genes to guide cell/spot clustering. Extensive experiments on both simulated and real data sets show that DSSC boosts clustering performance significantly compared with the state-of-the-art methods. It has robust performance across different data sets with various cell type/tissue organization and/or cell type/tissue spatial dependency. We conclude that DSSC is a promising tool for clustering sp-scRNA-seq data.

Integrated Omic Analyses Identify Pathways and Transcriptomic Regulators Associated with Chemical Alterations of in Vitro Neural Network Formation

Development of in vitro new approach methodologies (NAMs) has been driven by the need for developmental neurotoxicity (DNT) hazard data on thousands of chemicals. The network formation assay (NFA) characterizes DNT hazard based on changes in network formation but provides no mechanistic information. This study investigated nervous system signaling pathways and upstream physiological regulators underlying chemically-induced neural network dysfunction. Rat primary cortical neural networks grown on microelectrode arrays were exposed for 12 days in vitro (DIV) to cytosine arabinoside (CA), 5 fluorouracil (5FU), domoic acid (DA), cypermethrin (CM), deltamethrin (DM), or haloperidol (HP) as these exposures altered network formation in previous studies. RNA-seq from cells and GC/MS analysis of media extracts collected on DIV 12 provided gene expression and metabolomic identification, respectively. The integration of differentially expressed genes and metabolites for each neurotoxicant was analyzed using Ingenuity Pathway Analysis (IPA). All six compounds altered gene expression that linked to developmental disorders and neurological diseases. Other enriched canonical pathways overlapped among compounds of the same class; for example, genes and metabolites altered by both CA and 5FU exposures are enriched in axonal guidance pathways. Integrated analysis of upstream regulators was heterogeneous across compounds, but identified several transcriptomic regulators including CREB1, SOX2, NOTCH1, and PRODH. These results demonstrate that changes in network formation are accompanied by transcriptomic and metabolomic changes and that different classes of compounds produce differing responses. This approach can enhance information obtained from NAMs and contribute to the identification and development of adverse outcome pathways (AOPs) associated with DNT.

Spatial tissue profiling by imaging-free molecular tomography

Several techniques are currently being developed for spatially resolved omics profiling, but each new method requires the setup of specific detection strategies or specialized instrumentation. Here we describe an imaging-free framework to localize high-throughput readouts within a tissue by cutting the sample into thin strips in a way that allows subsequent image reconstruction. We implemented this framework to transform a low-input RNA sequencing protocol into an imaging-free spatial transcriptomics technique (called STRP-seq) and validated it by profiling the spatial transcriptome of the mouse brain. We applied the technique to the brain of the Australian bearded dragon, Pogona vitticeps. Our results reveal the molecular anatomy of the telencephalon of this lizard, providing evidence for a marked regionalization of the reptilian pallium and subpallium. We expect that STRP-seq can be used to derive spatially resolved data from a range of other omics techniques.

Zebrafish Tools for Deciphering Habenular Network-Linked Mental Disorders

Simple Summary

Everything that we think, feel or do depends on the function of neural networks in the brain. These are highly complex structures made of cells (neurons) and their interconnections (axons), which develop dependent on precisely coordinated interactions of genes. Any gene mutation can result in unwanted alterations in neural network formation and concomitant brain disorders. The habenula neural network is one of these important circuits, which has been linked to autism, schizophrenia, depression and bipolar disorder. Studies using the zebrafish have uncovered genes involved in the development of this network. Intriguingly, some of these genes have also been identified as risk genes of human brain disorders highlighting the power of this animal model to link risk genes and the affected network to human disease. But can we use the advantages of this model to identify new targets and compounds with ameliorating effects on brain dysfunction? In this review, we summarise the current knowledge on techniques to manipulate the habenula neural network to study the consequences on behavior. Moreover, we give an overview of existing behavioral test to mimic aspects of mental disorders and critically discuss the applicability of the zebrafish model in this field of research.

Abstract

The prevalence of patients suffering from mental disorders is substantially increasing in recent years and represents a major burden to society. The underlying causes and neuronal circuits affected are complex and difficult to unravel. Frequent disorders such as depression, schizophrenia, autism, and bipolar disorder share links to the habenular neural circuit. This conserved neurotransmitter system relays cognitive information between different brain areas steering behaviors ranging from fear and anxiety to reward, sleep, and social behaviors. Advances in the field using the zebrafish model organism have uncovered major genetic mechanisms underlying the formation of the habenular neural circuit. Some of the identified genes involved in regulating Wnt/beta-catenin signaling have previously been suggested as risk genes of human mental disorders. Hence, these studies on habenular genetics contribute to a better understanding of brain diseases. We are here summarizing how the gained knowledge on the mechanisms underlying habenular neural circuit development can be used to introduce defined manipulations into the system to study the functional behavioral consequences. We further give an overview of existing behavior assays to address phenotypes related to mental disorders and critically discuss the power but also the limits of the zebrafish model for identifying suitable targets to develop therapies.