New light on cortical neuropeptides and synaptic network plasticity

Breaking the neural code of a cnidarian: Learning principles of neuroscience from the "vulgar" Hydra

The cnidarian Hydra vulgaris is a small polyp with a nervous system of few hundred neurons belonging to a dozen cell types, organized in two nerve nets without cephalization or ganglia. Using this simple neural "chassis", Hydra can maintain a stable repertoire of behaviors, even performing complex fixed-action patterns, such as somersaulting and feeding. The ability to image the activity of Hydra's entire neural and muscle tissue has revealed that Hydra's nerve nets are divided into coactive ensembles of neurons, associated with specific movements. These ensembles can be activated by neuropeptides and interact using cross-inhibition circuits and implement integrate-to-threshold algorithms. In addition, Hydra's nervous system can self-assemble from dissociated cells in a stepwise modular architecture. Studies of Hydra and other cnidarians could enable the systematic deciphering of the neural basis of its behavior and help provide perspective on basic principles of neuroscience.

Molecular organization of neuronal cell types and neuromodulatory systems in the zebrafish telencephalon

The function of neuronal networks is determined not only by synaptic connectivity but also by neuromodulatory systems that broadcast information via distributed connections and volume transmission. To understand the molecular constraints that organize neuromodulatory signaling in the telencephalon of adult zebrafish, we used transcriptomics and additional approaches to delineate cell types, to determine their phylogenetic conservation, and to map the expression of marker genes at high granularity. The combinatorial expression of GPCRs and cell-type markers indicates that all neuronal cell types are subject to modulation by multiple monoaminergic systems and distinct combinations of neuropeptides. Individual cell types were associated with multiple (typically >30) neuromodulatory signaling networks but expressed only a few diagnostic GPCRs at high levels, suggesting that different neuromodulatory systems act in combination, albeit with unequal weights. These results provide a detailed map of cell types and brain areas in the zebrafish telencephalon, identify core components of neuromodulatory networks, highlight the cell-type specificity of neuropeptides and GPCRs, and begin to decipher the logic of combinatorial neuromodulation.

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

The mammalian brain consists of millions to billions of cells that are organized into many cell types with specific spatial distribution patterns and structural and functional properties1-3. Here we report a comprehensive and high-resolution transcriptomic and spatial cell-type atlas for the whole adult mouse brain. The cell-type atlas was created by combining a single-cell RNA-sequencing (scRNA-seq) dataset of around 7 million cells profiled (approximately 4.0 million cells passing quality control), and a spatial transcriptomic dataset of approximately 4.3 million cells using multiplexed error-robust fluorescence in situ hybridization (MERFISH). The atlas is hierarchically organized into 4 nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 clusters. We present an online platform, Allen Brain Cell Atlas, to visualize the mouse whole-brain cell-type atlas along with the single-cell RNA-sequencing and MERFISH datasets. We systematically analysed the neuronal and non-neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell-type organization in different brain regions-in particular, a dichotomy between the dorsal and ventral parts of the brain. The dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. Our study also uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types. Finally, we found that transcription factors are major determinants of cell-type classification and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole mouse brain transcriptomic and spatial cell-type atlas establishes a benchmark reference atlas and a foundational resource for integrative investigations of cellular and circuit function, development and evolution of the mammalian brain.

Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain

Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 technologies to generate 301,626 methylomes and 176,003 chromatin conformation-methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell taxonomy with 4,673 cell groups and 274 cross-modality-annotated subclasses. We identified 2.6 million differentially methylated regions across the genome that represent potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide spatial transcriptomics data validated the association of spatial epigenetic diversity with transcription and improved the anatomical mapping of our epigenetic datasets. Furthermore, chromatin conformation diversities occurred in important neuronal genes and were highly associated with DNA methylation and transcription changes. Brain-wide cell-type comparisons enabled the construction of regulatory networks that incorporate transcription factors, regulatory elements and their potential downstream gene targets. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a whole-brain SMART-seq2 dataset. Our study establishes a brain-wide, single-cell DNA methylome and 3D multi-omic atlas and provides a valuable resource for comprehending the cellular-spatial and regulatory genome diversity of the mouse brain.

A tool kit of highly selective and sensitive genetically encoded neuropeptide sensors

Neuropeptides are key signaling molecules in the endocrine and nervous systems that regulate many critical physiological processes. Understanding the functions of neuropeptides in vivo requires the ability to monitor their dynamics with high specificity, sensitivity, and spatiotemporal resolution. However, this has been hindered by the lack of direct, sensitive, and noninvasive tools. We developed a series of GRAB (G protein-coupled receptor activation‒based) sensors for detecting somatostatin (SST), corticotropin-releasing factor (CRF), cholecystokinin (CCK), neuropeptide Y (NPY), neurotensin (NTS), and vasoactive intestinal peptide (VIP). These fluorescent sensors, which enable detection of specific neuropeptide binding at nanomolar concentrations, establish a robust tool kit for studying the release, function, and regulation of neuropeptides under both physiological and pathophysiological conditions.

History of key regulatory peptide systems and perspectives for future research

Throughout the 20th Century, regulatory peptide discovery advanced from the identification of gut hormones to the extraction and characterization of hypothalamic hypophysiotropic factors, and to the isolation and cloning of multiple brain neuropeptides. These discoveries were followed by the discovery of G-protein-coupled and other membrane receptors for these peptides. Subsequently, the systems physiology associated with some of these multiple regulatory peptides and receptors has been comprehensively elucidated and has led to improved therapeutics and diagnostics and their approval by the US Food and Drug Administration. In light of this wealth of information and further potential, it is truly a time of renaissance for regulatory peptides. In this perspective, we review what we have learned from the pioneers in exemplified fields of gut peptides, such as cholecystokinin, enterochromaffin-like-cell peptides, and glucagon, from the trailblazing studies on the key stress hormone, corticotropin-releasing factor, as well as from more recently characterized relaxin-family peptides and receptors. The historical viewpoints are based on our understanding of these topics in light of the earliest phases of research and on subsequent studies and the evolution of knowledge, aiming to sharpen our vision of the current state-of-the-art and those studies that should be prioritized in the future.

Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain

Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brain's 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brain's cellular-spatial and regulatory genome diversity.

Mathematical models of learning and what can be learned from them

Learning is a multi-faceted phenomenon of critical importance and hence attracted a great deal of research, both experimental and theoretical. In this review, we will consider some of the paradigmatic examples of learning and discuss the common themes in theoretical learning research, such as levels of modeling and their corresponding relation to experimental observations and mathematical ideas common to different types of learning.

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled, and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.

Inferring neuron-neuron communications from single-cell transcriptomics through NeuronChat

Neural communication networks form the fundamental basis for brain function. These communication networks are enabled by emitted ligands such as neurotransmitters, which activate receptor complexes to facilitate communication. Thus, neural communication is fundamentally dependent on the transcriptome. Here we develop NeuronChat, a method and package for the inference, visualization and analysis of neural-specific communication networks among pre-defined cell groups using single-cell expression data. We incorporate a manually curated molecular interaction database of neural signaling for both human and mouse, and benchmark NeuronChat on several published datasets to validate its ability in predicting neural connectivity. Then, we apply NeuronChat to three different neural tissue datasets to illustrate its functionalities in identifying interneural communication networks, revealing conserved or context-specific interactions across different biological contexts, and predicting communication pattern changes in diseased brains with autism spectrum disorder. Finally, we demonstrate NeuronChat can utilize spatial transcriptomics data to infer and visualize neural-specific cell-cell communication.

Thyroid Hormone Transporters MCT8 and OATP1C1 Are Expressed in Pyramidal Neurons and Interneurons in the Adult Motor Cortex of Human and Macaque Brain

Monocarboxylate transporter 8 (MCT8) and organic anion transporter polypeptide 1C1 (OATP1C1) are thyroid hormone (TH) transmembrane transporters that play an important role in the availability of TH for neural cells, allowing their proper development and function. It is important to define which cortical cellular subpopulations express those transporters to explain why MCT8 and OATP1C1 deficiency in humans leads to dramatic alterations in the motor system. By means of immunohistochemistry and double/multiple labeling immunofluorescence in adult human and monkey motor cortices, we demonstrate the presence of both transporters in long-projection pyramidal neurons and in several types of short-projection GABAergic interneurons in both species, suggesting a critical position of these transporters for modulating the efferent motor system. MCT8 is present at the neurovascular unit, but OATP1C1 is only present in some of the large vessels. Both transporters are expressed in astrocytes. OATP1C1 was unexpectedly found, only in the human motor cortex, inside the Corpora amylacea complexes, aggregates linked to substance evacuation towards the subpial system. On the basis of our findings, we propose an etiopathogenic model that emphasizes these transporters' role in controlling excitatory/inhibitory motor cortex circuits in order to understand some of the severe motor disturbances observed in TH transporter deficiency syndromes.

Inferring neuron-neuron communications from single-cell transcriptomics through NeuronChat

Neural communication networks form the fundamental basis for brain function. These communication networks are enabled by emitted ligands such as neurotransmitters, which activate receptor complexes to facilitate communication. Thus, neural communication is fundamentally dependent on the transcriptome. Here we develop NeuronChat, a method and package for the inference, visualization and analysis of neural-specific communication networks among pre-defined cell groups using single-cell expression data. We incorporate a manually curated molecular interaction database of neural signaling for both human and mouse, and benchmark NeuronChat on several published datasets to validate its ability in predicting neural connectivity. Then, we apply NeuronChat to three different neural tissue datasets to illustrate its functionalities in identifying interneural communication networks, revealing conserved or context-specific interactions across different biological contexts, and predicting communication pattern changes in diseased brains with autism spectrum disorder. Finally, we demonstrate NeuronChat can utilize spatial transcriptomics data to infer and visualize neural-specific cell-cell communication.

Somatodendritic Release of Cholecystokinin Potentiates GABAergic Synapses Onto Ventral Tegmental Area Dopamine Cells

BACKGROUND

Neuropeptides are contained in nearly every neuron in the central nervous system and can be released not only from nerve terminals but also from somatodendritic sites. Cholecystokinin (CCK), among the most abundant neuropeptides in the brain, is expressed in the majority of midbrain dopamine neurons. Despite this high expression, CCK function within the ventral tegmental area (VTA) is not well understood.

METHODS

We confirmed CCK expression in VTA dopamine neurons through immunohistochemistry and in situ hybridization and detected optogenetically induced CCK release using an enzyme-linked immunosorbent assay. To investigate whether CCK modulates VTA circuit activity, we used whole-cell patch clamp recordings in mouse brain slices. We infused CCK locally in vivo and tested food intake and locomotion in fasted mice. We also used in vivo fiber photometry to measure Ca²⁺ transients in dopamine neurons during feeding.

RESULTS

Here we report that VTA dopamine neurons release CCK from somatodendritic regions, where it triggers long-term potentiation of GABAergic (gamma-aminobutyric acidergic) synapses. The somatodendritic release occurs during trains of optogenetic stimuli or prolonged but modest depolarization and is dependent on synaptotagmin-7 and T-type Ca²⁺ channels. Depolarization-induced long-term potentiation is blocked by a CCK₂ receptor antagonist and mimicked by exogenous CCK. Local infusion of CCK in vivo inhibits food consumption and decreases distance traveled in an open field test. Furthermore, intra-VTA-infused CCK reduced dopamine cell Ca²⁺ signals during food consumption after an overnight fast and was correlated with reduced food intake.

CONCLUSIONS

Our experiments introduce somatodendritic neuropeptide release as a previously unknown feedback regulator of VTA dopamine cell excitability and dopamine-related behaviors.

Emerging approaches for decoding neuropeptide transmission

Neuropeptides produce robust effects on behavior across species, and recent research has benefited from advances in high-resolution techniques to investigate peptidergic transmission and expression throughout the brain in model systems. Neuropeptides exhibit distinct characteristics which includes their post-translational processing, release from dense core vesicles, and ability to activate G-protein-coupled receptors (GPCRs). These complex properties have driven the need for development of specialized tools that can sense neuropeptide expression, cell activity, and release. Current research has focused on isolating when and how neuropeptide transmission occurs, as well as the conditions in which neuropeptides directly mediate physiological and adaptive behavioral states. Here we describe the current technological landscape in which the field is operating to decode key questions regarding these dynamic neuromodulators.

Oxytocin signaling is necessary for synaptic maturation of adult-born neurons

Neural circuit plasticity and sensory response dynamics depend on forming new synaptic connections. Despite recent advances toward understanding the consequences of circuit plasticity, the mechanisms driving circuit plasticity are unknown. Adult-born neurons within the olfactory bulb have proven to be a powerful model for studying circuit plasticity, providing a broad and accessible avenue into neuron development, migration, and circuit integration. We and others have shown that efficient adult-born neuron circuit integration hinges on presynaptic activity in the form of diverse signaling peptides. Here, we demonstrate a novel oxytocin-dependent mechanism of adult-born neuron synaptic maturation and circuit integration. We reveal spatial and temporal enrichment of oxytocin receptor expression within adult-born neurons in the murine olfactory bulb, with oxytocin receptor expression peaking during activity-dependent integration. Using viral labeling, confocal microscopy, and cell type-specific RNA-seq, we demonstrate that oxytocin receptor signaling promotes synaptic maturation of newly integrating adult-born neurons by regulating their morphological development and expression of mature synaptic AMPARs and other structural proteins.

A Molecular Landscape of Mouse Hippocampal Neuromodulation

Adaptive neuronal circuit function requires a continual adjustment of synaptic network parameters known as “neuromodulation.” This process is now understood to be based primarily on the binding of myriad secreted “modulatory” ligands such as dopamine, serotonin and the neuropeptides to G protein-coupled receptors (GPCRs) that, in turn, regulate the function of the ion channels that establish synaptic weights and membrane excitability. Many of the basic molecular mechanisms of neuromodulation are now known, but the organization of neuromodulation at a network level is still an enigma. New single-cell RNA sequencing data and transcriptomic neurotaxonomies now offer bright new lights to shine on this critical “dark matter” of neuroscience. Here we leverage these advances to explore the cell-type-specific expression of genes encoding GPCRs, modulatory ligands, ion channels and intervening signal transduction molecules in mouse hippocampus area CA1, with the goal of revealing broad outlines of this well-studied brain structure’s neuromodulatory network architecture.

The regulatory role of NAAG-mGluR3 signaling on cortical synaptic plasticity after hypoxic ischemia

Background

Synapses can adapt to changes in the intracerebral microenvironment by regulation of presynaptic neurotransmitter release and postsynaptic neurotransmitter receptor expression following hypoxic ischemia (HI) injury. The peptide neurotransmitter N-acetylaspartylglutamate (NAAG) exerts a protective effect on neurons after HI and may be involved in maintaining the function of synaptic networks. In this study, we investigated the changes in the expression of NAAG, glutamic acid (Glu) and metabotropic glutamate receptors (mGluRs), as well as the dynamic regulation of neurotransmitters in the brain after HI, and assessed their effects on synaptic plasticity of the cerebral cortex.

Methods

Thirty-six Yorkshire newborn pigs (3-day-old, males, 1.0–1.5 kg) were selected and randomly divided into normal saline (NS) group (n = 18) and glutamate carboxypeptidase II inhibition group (n = 18), both groups were divided into control group, 0–6 h, 6–12 h, 12–24 h, 24–48 h and 48–72 h groups (all n = 3) according to different post-HI time. The content of Glu and NAAG after HI injury were detected by 1H-MRS scanning, immunofluorescence staining of mGluRs, synaptophysin (syph) along with postsynaptic density protein-95 (PSD95) and transmission electron microscopy were performed. ANOVA, Tukey and LSD test were used to compare the differences in metabolite and protein expression levels among subgroups. Correlation analysis was performed using Pearson analysis with a significance level of α = 0.05.

Results

We observed that the NAAG and mGluR3 expression levels in the brain increased and then decreased after HI and was significantly higher in the 12–24 h (P < 0.05, Tukey test). There was a significant positive correlation between Glu content and the expression of mGluR1/mGluR5 after HI with r = 0.521 (P = 0.027) and r = 0.477 (P = 0.045), respectively. NAAG content was significantly and positively correlated with the level of mGluR3 expression (r = 0.472, P = 0.048). When hydrolysis of NAAG was inhibited, the expression of synaptic protein PSD95 and syph decreased significantly.

Conclusions

After 12–24 h of HI injury, there was a one-time elevation in NAAG levels, which was consistent with the corresponding mGluR3 receptor expression trend; the NAAG maintains cortical synaptic plasticity and neurotransmitter homeostasis by inhibiting presynaptic glutamate vesicle release, regulating postsynaptic density proteins and postsynaptic receptor expression after pathway activation.

Cell-type-specific neuromodulation guides synaptic credit assignment in a spiking neural network

Synaptic connectivity provides the foundation for our present understanding of neuronal network function, but static connectivity cannot explain learning and memory. We propose a computational role for the diversity of cortical neuronal types and their associated cell-type–specific neuromodulators in improving the efficiency of synaptic weight adjustments for task learning in neuronal networks.

Brains learn tasks via experience-driven differential adjustment of their myriad individual synaptic connections, but the mechanisms that target appropriate adjustment to particular connections remain deeply enigmatic. While Hebbian synaptic plasticity, synaptic eligibility traces, and top-down feedback signals surely contribute to solving this synaptic credit-assignment problem, alone, they appear to be insufficient. Inspired by new genetic perspectives on neuronal signaling architectures, here, we present a normative theory for synaptic learning, where we predict that neurons communicate their contribution to the learning outcome to nearby neurons via cell-type–specific local neuromodulation. Computational tests suggest that neuron-type diversity and neuron-type–specific local neuromodulation may be critical pieces of the biological credit-assignment puzzle. They also suggest algorithms for improved artificial neural network learning efficiency.

Transcriptomic evidence for dense peptidergic networks within forebrains of four widely divergent tetrapods

The primary function common to every neuron is communication with other neurons. Such cell-cell signaling can take numerous forms, including fast synaptic transmission and slower neuromodulation via secreted messengers, such as neuropeptides, dopamine, and many other diffusible small molecules. Individual neurons are quite diverse, however, in all particulars of both synaptic and neuromodulatory communication. Neuron classification schemes have therefore proven very useful in exploring the emergence of network function, behavior, and cognition from the communication functions of individual neurons. Recently published single-cell mRNA sequencing data and corresponding transcriptomic neuron classifications from turtle, songbird, mouse, and human provide evidence for a long evolutionary history and adaptive significance of localized peptidergic signaling. Across all four species, sets of at least twenty orthologous cognate pairs of neuropeptide precursor protein and receptor genes are expressed in individually sparse but heavily overlapping patterns suggesting that all forebrain neuron types are densely interconnected by local peptidergic signals.

Consistent cross-modal identification of cortical neurons with coupled autoencoders

Consistent identification of neurons in different experimental modalities is a key problem in neuroscience. Although methods to perform multimodal measurements in the same set of single neurons have become available, parsing complex relationships across different modalities to uncover neuronal identity is a growing challenge. Here we present an optimization framework to learn coordinated representations of multimodal data and apply it to a large multimodal dataset profiling mouse cortical interneurons. Our approach reveals strong alignment between transcriptomic and electrophysiological characterizations, enables accurate cross-modal data prediction, and identifies cell types that are consistent across modalities.

Effects of maternal immune activation in porcine transcript isoforms of neuropeptide and receptor genes

The prolonged effects of maternal immune activation in response stressors during gestation on the offspring's molecular pathways after birth are beginning to be understood. An association between maternal immune activation and neurodevelopmental and behavior disorders such as autism and schizophrenia spectrum disorders has been detected in long-term gene dysregulation. The incidence of alternative splicing among neuropeptides and neuropeptide receptor genes, critical cell-cell signaling molecules, associated with behavior may compromise the replicability of reported maternal immune activation effects at the gene level. This study aims to advance the understanding of the effect of maternal immune activation on transcript isoforms of the neuropeptide system (including neuropeptide, receptor and connecting pathway genes) underlying behavior disorders later in life. Recognizing the wide range of bioactive peptides and functional receptors stemming from alternative splicing, we studied the effects of maternal immune activation at the transcript isoform level on the hippocampus and amygdala of three-week-old pigs exposed to maternal immune activation due to viral infection during gestation. In the hippocampus and amygdala, 29 and 9 transcript isoforms, respectively, had maternal immune activation effects (P-value < 0.01). We demonstrated that the study of the effect of maternal immune activation on neuropeptide systems at the isoform level is necessary to expose opposite effects among transcript isoforms from the same gene. Genes were maternal immune activation effects have also been associated with neurodevelopmental and behavior disorders. The characterization of maternal immune activation effects at the transcript isoform level advances the understanding of neurodevelopmental disorders and identifies precise therapeutic targets.