Transcriptional architecture of the primate neocortex

MECP2 Duplication Causes Aberrant GABA Pathways, Circuits and Behaviors in Transgenic Monkeys: Neural Mappings to Patients with Autism

MECP2 gain-of-function and loss-of-function in genetically engineered monkeys recapitulates typical phenotypes in patients with autism, yet where MECP2 mutation affects the monkey brain and whether/how it relates to autism pathology remain unknown. Here we report a combination of gene-circuit-behavior analyses including MECP2 coexpression network, locomotive and cognitive behaviors, and EEG and fMRI findings in 5 MECP2 overexpressed monkeys (Macaca fascicularis; 3 females) and 20 wild-type monkeys (Macaca fascicularis; 11 females). Whole-genome expression analysis revealed MECP2 coexpressed genes significantly enriched in GABA-related signaling pathways, whereby reduced β-synchronization within fronto-parieto-occipital networks was associated with abnormal locomotive behaviors. Meanwhile, MECP2-induced hyperconnectivity in prefrontal and cingulate networks accounted for regressive deficits in reversal learning tasks. Furthermore, we stratified a cohort of 49 patients with autism and 72 healthy controls of 1112 subjects using functional connectivity patterns, and identified dysconnectivity profiles similar to those in monkeys. By establishing a circuit-based construct link between genetically defined models and stratified patients, these results pave new avenues to deconstruct clinical heterogeneity and advance accurate diagnosis in psychiatric disorders.SIGNIFICANCE STATEMENT Autism spectrum disorder (ASD) is a complex disorder with co-occurring symptoms caused by multiple genetic variations and brain circuit abnormalities. To dissect the gene-circuit-behavior causal chain underlying ASD, animal models are established by manipulating causative genes such as MECP2 However, it is unknown whether such models have captured any circuit-level pathology in ASD patients, as demonstrated by human brain imaging studies. Here, we use transgenic macaques to examine the causal effect of MECP2 overexpression on gene coexpression, brain circuits, and behaviors. For the first time, we demonstrate that the circuit abnormalities linked to MECP2 and autism-like traits in the monkeys can be mapped to a homogeneous ASD subgroup, thereby offering a new strategy to deconstruct clinical heterogeneity in ASD.

Deep Neural Networks for In Situ Hybridization Grid Completion and Clustering

Transcriptome in brain plays a crucial role in understanding the cortical organization and the development of brain structure and function. Two challenges, incomplete data and high dimensionality of transcriptome, remain unsolved. Here, we present a novel training scheme that successfully adapts the U-net architecture to the problem of volume recovery. By analogy to denoising autoencoder, we hide a portion of each training sample so that the network can learn to recover missing voxels from context. Then on the completed volumes, we show that Restricted Boltzmann Machines (RBMs) can be used to infer co-occurrences among voxels, providing foundations for dividing the cortex into discrete subregions. As we stack multiple RBMs to form a deep belief network (DBN), we progressively map the high-dimensional raw input into abstract representations and create a hierarchy of transcriptome architecture. A coarse to fine organization emerges from the network layers. This organization incidentally corresponds to the anatomical structures, suggesting a close link between structures and the genetic underpinnings. Thus, we demonstrate a new way of learning transcriptome-based hierarchical organization using RBM and DBN.

A Distinct Class of Bursting Neurons with Strong Gamma Synchronization and Stimulus Selectivity in Monkey V1

Cortical computation depends on interactions between excitatory and inhibitory neurons. The contributions of distinct neuron types to sensory processing and network synchronization in primate visual cortex remain largely undetermined. We show that in awake monkey V1, there exists a distinct cell type (››30% of neurons) that has narrow-waveform (NW) action potentials and high spontaneous discharge rates and fires in high-frequency bursts. These neurons are more stimulus selective and phase locked to 30- to 80-Hz gamma oscillations than other neuron types. Unlike other neuron types, their gamma-phase locking is highly predictive of orientation tuning. We find evidence for strong rhythmic inhibition in these neurons, suggesting that they interact with interneurons to act as excitatory pacemakers for the V1 gamma rhythm. We did not find a similar class of NW bursting neurons in L2-L4 of mouse V1. Given its properties, this class of NW bursting neurons should be pivotal for the encoding and transmission of stimulus information.

The use of nonhuman primates in studies of noise injury and treatment

Exposure to prolonged or high intensity noise increases the risk for permanent hearing impairment. Over several decades, researchers characterized the nature of harmful noise exposures and worked to establish guidelines for effective protection. Recent laboratory studies, primarily conducted in rodent models, indicate that the auditory system may be more vulnerable to noise-induced hearing loss (NIHL) than previously thought, driving renewed inquiries into the harmful effects of noise in humans. To bridge the translational gaps between rodents and humans, nonhuman primates (NHPs) may serve as key animal models. The phylogenetic proximity of NHPs to humans underlies tremendous similarity in many features of the auditory system (genomic, anatomical, physiological, behavioral), all of which are important considerations in the assessment and treatment of NIHL. This review summarizes the literature pertaining to NHPs as models of hearing and noise-induced hearing loss, discusses factors relevant to the translation of diagnostics and therapeutics from animals to humans, and concludes with some of the practical considerations involved in conducting NHP research.

Application of Computational Biology to Decode Brain Transcriptomes

The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases, providing great opportunities for systematically investigating gene expression characteristics across various brain regions throughout a series of developmental stages. Recent studies have revealed that the transcriptional architecture is the key to interpreting the molecular mechanisms of brain complexity. However, our knowledge of brain transcriptional characteristics remains very limited. With the immense efforts to generate high-quality brain transcriptome atlases, new computational approaches to analyze these high-dimensional multivariate data are greatly needed. In this review, we summarize some public resources for brain transcriptome atlases and discuss the general computational pipelines that are commonly used in this field, which would aid in making new discoveries in brain development and disorders.

Distinct Properties of Layer 3 Pyramidal Neurons from Prefrontal and Parietal Areas of the Monkey Neocortex

In primates, working memory function depends on activity in a distributed network of cortical areas that display different patterns of delay task-related activity. These differences are correlated with, and might depend on, distinctive properties of the neurons located in each area. For example, layer 3 pyramidal neurons (L3PNs) differ significantly between primary visual and dorsolateral prefrontal (DLPFC) cortices. However, to what extent L3PNs differ between DLPFC and other association cortical areas is less clear. Hence, we compared the properties of L3PNs in monkey DLPFC versus posterior parietal cortex (PPC), a key node in the cortical working memory network. Using patch-clamp recordings and biocytin cell filling in acute brain slices, we assessed the physiology and morphology of L3PNs from monkey DLPFC and PPC. The L3PN transcriptome was studied using laser microdissection combined with DNA microarray or quantitative PCR. We found that in both DLPFC and PPC, L3PNs were divided into regular spiking (RS-L3PNs) and bursting (B-L3PNs) physiological subtypes. Whereas regional differences in single-cell excitability were modest, B-L3PNs were rare in PPC (RS-L3PN:B-L3PN, 94:6), but were abundant in DLPFC (50:50), showing greater physiological diversity. Moreover, DLPFC L3PNs display larger and more complex basal dendrites with higher dendritic spine density. Additionally, we found differential expression of hundreds of genes, suggesting a transcriptional basis for the differences in L3PN phenotype between DLPFC and PPC. These data show that the previously observed differences between DLPFC and PPC neuron activity during working memory tasks are associated with diversity in the cellular/molecular properties of L3PNs.SIGNIFICANCE STATEMENT In the human and nonhuman primate neocortex, layer 3 pyramidal neurons (L3PNs) differ significantly between dorsolateral prefrontal (DLPFC) and sensory areas. Hence, L3PN properties reflect, and may contribute to, a greater complexity of computations performed in DLPFC. However, across association cortical areas, L3PN properties are largely unexplored. We studied the physiology, dendrite morphology and transcriptome of L3PNs from macaque monkey DLPFC and posterior parietal cortex (PPC), two key nodes in the cortical working memory network. L3PNs from DLPFC had greater diversity of physiological properties and larger basal dendrites with higher spine density. Moreover, transcriptome analysis suggested a molecular basis for the differences in the physiological and morphological phenotypes of L3PNs from DLPFC and PPC.

Identification of genetic markers for cortical areas using a Random Forest classification routine and the Allen Mouse Brain Atlas

The mammalian neocortex is subdivided into a series of cortical areas that are functionally and anatomically distinct and are often distinguished in brain sections using histochemical stains and other markers of protein expression. We searched the Allen Mouse Brain Atlas, a database of gene expression, for novel markers of cortical areas. To screen for genes that change expression at area borders, we employed a random forest algorithm and binary region classification. Novel genetic markers were identified for 19 of 39 areas and provide code that quickly and efficiently searches the Allen Mouse Brain Atlas. Our results demonstrate the utility of the random forest algorithm for cortical area classification and we provide code that may be used to facilitate the identification of genetic markers of cortical and subcortical structures and perhaps changes in gene expression in disease states.

Human visual cortex is organized along two genetically opposed hierarchical gradients with unique developmental and evolutionary origins

Human visual cortex is organized with striking consistency across individuals. While recent findings demonstrate an unexpected coupling between functional and cytoarchitectonic regions relative to the folding of human visual cortex, a unifying principle linking these anatomical and functional features of the cortex remains elusive. To fill this gap in knowledge, we combined independent and ground truth measurements of cytoarchitectonic regions and genetic tissue characterization within human occipitotemporal cortex. Using a data-driven approach, we examined whether differential gene expression among cytoarchitectonic areas could contribute to the arealization of occipitotemporal cortex into a hierarchy based on transcriptomics. This approach revealed two opposing gene expression gradients: one that contains a series of genes with expression magnitudes that ascend from posterior (e.g., areas human occipital [hOc]1, hOc2, hOc3, etc.) to anterior cytoarchitectonic areas (e.g., areas fusiform gyrus [FG]1–FG4) and another that contains a separate series of genes that show a descending gradient from posterior to anterior areas. Using data from the living human brain, we show that each of these gradients correlates strongly with variations in measures related to either thickness or myelination of cortex, respectively. We further reveal that these genetic gradients emerge along unique trajectories in human development: the ascending gradient is present at 10–12 gestational weeks, while the descending gradient emerges later (19–24 gestational weeks). Interestingly, it is not until early childhood (before 5 years of age) that the two expression gradients achieve their adult-like mean expression values. Additional analyses in nonhuman primates (NHPs) reveal that homologous genes do not generate the same ascending and descending expression gradients as in humans. We discuss these findings relative to previously proposed hierarchies based on functional and cytoarchitectonic features of visual cortex. Altogether, these findings bridge macroscopic features of human cytoarchitectonic areas in visual cortex with microscopic features of cellular organization and genetic expression, which, despite the complexity of this multiscale correspondence, can be described by a sparse subset (approximately 200) of genes. These findings help pinpoint the genes contributing to healthy cortical development and explicate the cortical biology distinguishing humans from other primates, as well as establishing essential groundwork for understanding future work linking genetic mutations with the function and development of the human brain.

The expression of a sparse subset of human genes forms two opposed gradients that capture the processing hierarchy of visual cortex; these transcription gradients emerge at different points during human development and distinguish human from nonhuman primates.

Homozygous variants in the gene SCAPER cause syndromic intellectual disability

The S-Phase Cyclin A Associated Protein In The ER (SCAPER) gene is a ubiquitously expressed gene with unknown function in the brain. Recently, biallelic SCAPER variants were described in four patients from three families with retinitis pigmentosa (RP) and intellectual disability (ID). Here, we expand the spectrum of pathogenic variants in SCAPER and report on 10 further patients from four families with ID, RP, and additional dysmorphic features carrying homozygous variants in SCAPER. The variants found comprise frameshift, nonsense, and missense variants as well as an intragenic homozygous deletion, which spans SCAPER exons 15 and 16 and introduces a frameshift and a premature stop codon. Analyses of SCAPER expression in human and mouse brain revealed an upregulation of SCAPER expression during cortical development and a higher expression of SCAPER in neurons compared to neural progenitors. In the adult brain SCAPER is expressed in several regions including the cerebral cortex where it shows a layer-specific expression with an expression peak in lower layer glutamatergic neurons. Our study supports the role of SCAPER variants in the pathogenesis of ID and RP, expands the variant spectrum and highlights the need for functional studies concerning the role of SCAPER during brain development and function.

The spatiotemporal expression pattern of microRNAs in the developing mouse nervous system

MicroRNAs (miRNAs) control various biological processes by inducing translational repression and transcript degradation of the target genes. In mammalian development, knowledge of the timing and expression pattern of each miRNA is important to determine and predict its function in vivo So far, no systematic analyses of the spatiotemporal expression pattern of miRNAs during mammalian neurodevelopment have been performed. Here, we isolated total RNAs from the embryonic dorsal forebrain of mice at different developmental stages and subjected these RNAs to microarray analyses. We selected 279 miRNAs that exhibited high signal intensities or ascending or descending expression dynamics. To ascertain the expression patterns of these miRNAs, we used locked nucleic acid (LNA)-modified miRNA probes in in situ hybridization experiments. Multiple miRNAs exhibited spatially restricted/enriched expression in anatomically distinct regions or in specific neuron subtypes in the embryonic brain and spinal cord, such as in the ventricular area, the striatum (and other basal ganglia), hypothalamus, choroid plexus, and the peripheral nervous system. These findings provide new insights into the expression and function of miRNAs during the development of the nervous system and could be used as a resource to facilitate studies in neurodevelopment.

Sex-biased gene expression in the frontal cortex of common marmosets (Callithrix jacchus) and potential behavioral correlates

INTRODUCTION

The common marmoset (Callithrix jacchus), a small New World monkey, has been widely used as a biological model in neuroscience to elucidate neural circuits involved in cognition and to understand brain dysfunction in neuropsychiatric disorders. In this regard, the availability of gene expression data derived from next-generation sequencing (NGS) technologies represents an opportunity for a molecular contextualization. Sexual dimorphism account for differences in diseases prevalence and prognosis. Here, we explore sex differences on frontal cortex of gene expression in common marmoset's adults.

METHODS

Gene expression profiles in six different tissues (cerebellum, frontal cortex, liver, heart, and kidney) were analyzed in male and female marmosets. To emphasize the translational value of this species for behavioral studies, we focused on sex-biased gene expression from the frontal cortex of male and female in common marmosets and compared to humans (Homo sapiens).

RESULTS

In this study, we found that frontal cortex genes whose expression is male-biased are conserved between marmosets and humans and enriched with "house-keeping" functions. On the other hand, female-biased genes are more related to neural plasticity functions involved in remodeling of synaptic circuits, stress cascades, and visual behavior. Additionally, we developed and made available an application-the CajaDB-to provide a friendly interface for genomic, expression, and alternative splicing data of marmosets together with a series of functionalities that allow the exploration of these data. CajaDB is available at cajadb.neuro.ufrn.br.

CONCLUSION

The data point to differences in gene expression of male and female common marmosets in all tissues analyzed. In frontal cortex, female-biased expression in synaptic plasticity, stress, and visual processing might be linked to biological and behavioral mechanisms of this sex. Due to the limited sample size, the data here analyzed are for exploratory purposes.

Cross-species molecular dissection across alcohol behavioral domains

This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 9-12, 2017. Psychiatric diseases, including alcohol-use disorders (AUDs), are influenced through complex interactions of genes, neurobiological pathways, and environmental influences. A better understanding of the common neurobiological mechanisms underlying an AUD necessitates an integrative approach, involving a systematic assessment of diverse species and phenotype measures. As part of the World Congress on Stress and Alcoholism, this symposium provided a detailed account of current strategies to identify mechanisms underlying the development and progression of AUDs. Dr. Sean Farris discussed the integration and organization of transcriptome and postmortem human brain data to identify brain regional- and cell type-specific differences related to excessive alcohol consumption that are conserved across species. Dr. Brien Riley presented the results of a genome-wide association study of DSM-IV alcohol dependence; although replication of genetic associations with alcohol phenotypes in humans remains challenging, model organism studies show that COL6A3, KLF12, and RYR3 affect behavioral responses to ethanol, and provide substantial evidence for their role in human alcohol-related traits. Dr. Rob Williams expanded upon the systematic characterization of extensive genetic-genomic resources for quantifying and clarifying phenotypes across species that are relevant to precision medicine in human disease. The symposium concluded with Dr. Robert Hitzemann's description of transcriptome studies in a mouse model selectively bred for high alcohol ("binge-like") consumption and a non-human primate model of long-term alcohol consumption. Together, the different components of this session provided an overview of systems-based approaches that are pioneering the experimental prioritization and validation of novel genes and gene networks linked with a range of behavioral phenotypes associated with stress and AUDs.

Isoform-Level Interpretation of High-Throughput Proteomics Data Enabled by Deep Integration with RNA-seq

Cellular control of gene expression is a complex process that is subject to multiple levels of regulation, but ultimately it is the protein produced that determines the biosynthetic state of the cell. One way that a cell can regulate the protein output from each gene is by expressing alternate isoforms with distinct amino acid sequences. These isoforms may exhibit differences in localization and binding interactions that can have profound functional implications. High-throughput liquid chromatography tandem mass spectrometry proteomics (LC-MS/MS) relies on enzymatic digestion and has lower coverage and sensitivity than transcriptomic profiling methods such as RNA-seq. Digestion results in predictable fragmentation of a protein, which can limit the generation of peptides capable of distinguishing between isoforms. Here we exploit transcript-level expression from RNA-seq to set prior likelihoods and enable protein isoform abundances to be directly estimated from LC-MS/MS, an approach derived from the principle that most genes appear to be expressed as a single dominant isoform in a given cell type or tissue. Through this deep integration of RNA-seq and LC-MS/MS data from the same sample, we show that a principal isoform can be identified in >80% of gene products in homogeneous HEK293 cell culture and >70% of proteins detected in complex human brain tissue. We demonstrate that the incorporation of translatome data from ribosome profiling further refines this process. Defining isoforms in experiments with matched RNA-seq/translatome and proteomic data increases the functional relevance of such data sets and will further broaden our understanding of multilevel control of gene expression.

The Allen Brain Atlas as a Resource for Teaching Undergraduate Neuroscience

The open science movement has resulted in a growing field of data- and tool-sharing platforms that serve as a resource not only for sharing data and results in the field of brain science but has allowed students and researchers to learn neuroscientific skills and concepts. For over a decade, the Allen Institute for Brain Science has been meticulously collecting high quality data mapping gene expression, connectivity and, more recently, functional data from the brains of mice, macaques and humans. These open data have been paired with unique navigation and visualization tools such that the neuroscience researcher can explore, utilize and even incorporate these data into their publications. The tools created to explore and analyze the Allen Brain Atlas datasets have also been widely utilized to teach neuroscientific concepts to undergraduate and graduate students. This article aims to outline how to use the Allen Brain Atlas resources as teaching tools to impart neuroanatomic concepts to undergraduate and graduate neuroscience students.

Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes

It is widely assumed that cells must be physically isolated to study their molecular profiles. However, intact tissue samples naturally exhibit variation in cellular composition, which drives covariation of cell-class-specific molecular features. By analyzing transcriptional covariation in 7,221 intact CNS samples from 840 neurotypical individuals, representing billions of cells, we reveal the core transcriptional identities of major CNS cell classes in humans. By modeling intact CNS transcriptomes as a function of variation in cellular composition, we identify cell-class-specific transcriptional differences in Alzheimer's disease, among brain regions, and between species. Among these, we show that PMP2 is expressed by human but not mouse astrocytes and significantly increases mouse astrocyte size upon ectopic expression in vivo, causing them to more closely resemble their human counterparts. Our work is available as an online resource ( http://oldhamlab.ctec.ucsf.edu/ ) and provides a generalizable strategy for determining the core molecular features of cellular identity in intact biological systems.

hPSC Modeling Reveals that Fate Selection of Cortical Deep Projection Neurons Occurs in the Subplate

Cortical deep projection neurons (DPNs) are implicated in neurodevelopmental disorders. Although recent findings emphasize post-mitotic programs in projection neuron fate selection, the establishment of primate DPN identity during layer formation is not well understood. The subplate lies underneath the developing cortex and is a post-mitotic compartment that is transiently and disproportionately enlarged in primates in the second trimester. The evolutionary significance of subplate expansion, the molecular identity of its neurons, and its contribution to primate corticogenesis remain open questions. By modeling subplate formation with human pluripotent stem cells (hPSCs), we show that all classes of cortical DPNs can be specified from subplate neurons (SPNs). Post-mitotic WNT signaling regulates DPN class selection, and DPNs in the caudal fetal cortex appear to exclusively derive from SPNs. Our findings indicate that SPNs have evolved in primates as an important source of DPNs that contribute to cortical lamination prior to their known role in circuit formation.

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks.

Mapping of neuron soma size as an effective approach to delineate differences between neural populations

BACKGROUND

A single histological marker applied to a slice of tissue often reveals myriad cytoarchitectonic characteristics that can obscure differences between neuron populations targeted for study. Isolation and measurement of a single feature from the tissue is possible through a variety of approaches, however, visualizing the data numerically or through graphs alone can preclude being able to identify important features and effects that are not obvious from direct observation of the tissue.

NEW METHOD

We demonstrate an efficient, effective, and robust approach to quantify and visualize cytoarchitectural features in histologically prepared brain sections. We demonstrate that this approach is able to reveal small differences between populations of neurons that might otherwise have gone undiscovered.

RESULTS & COMPARISON WITH EXISTING METHOD(S)

We used stereological methods to record the cross-sectional soma area and in situ position of neurons within sections of the cat, monkey, and human visual system. The two-dimensional coordinate of every measured cell was used to produce a scatter plot that recapitulated the natural spatial distribution of cells, and each point in the plot was color-coded according to its respective soma area. The final graphic display was a multi-dimensional map of neuron soma size that revealed subtle differences across neuron aggregations, permitted delineation of regional boundaries, and identified small differences between populations of neurons modified by a period of sensory deprivation.

CONCLUSIONS

This approach to collecting and displaying cytoarchitectonic data is simple, efficient, and provides a means of investigating small differences between neuron populations.

Transcriptome Architecture of Adult Mouse Brain Revealed by Sparse Coding of Genome-Wide In Situ Hybridization Images

Highly differentiated brain structures with distinctly different phenotypes are closely correlated with the unique combination of gene expression patterns. Using a genome-wide in situ hybridization image dataset released by Allen Mouse Brain Atlas, we present a data-driven method of dictionary learning and sparse coding. Our results show that sparse coding can elucidate patterns of transcriptome organization of mouse brain. A collection of components obtained from sparse coding display robust region-specific molecular signatures corresponding to the canonical neuroanatomical subdivisions including fiber tracts and ventricular systems. Other components revealed finer anatomical delineation of domains previously considered homogeneous. We also build an open-access informatics portal that contains the detail of each component along with its ontology and expressed genes. This portal allows intuitive visualization, interpretation and explorations of the transcriptome architecture of a mouse brain.

Multimodal Connectomics in Psychiatry: Bridging Scales From Micro to Macro

The human brain is a highly complex system, with a large variety of microscale cellular morphologies and macroscale global properties. Working at multiple scales, it forms an efficient system for processing and integration of multimodal information. Studies have repeatedly demonstrated strong associations between modalities of both microscales and macroscales of brain organization. These consistent observations point toward potential common organization principles where regions with a microscale architecture supportive of a larger computational load have more and stronger connections in the brain network on the macroscale. Conversely, disruptions observed on one organizational scale could modulate the other. First neuropsychiatric micro-macro comparisons in, among other conditions, Alzheimer's disease and schizophrenia, have, for example, shown overlapping alterations across both scales. We give an overview of recent findings on associations between microscale and macroscale organization observed in the healthy brain, followed by a summary of microscale and macroscale findings reported in the context of brain disorders. We conclude with suggestions for future multiscale connectome comparisons linking multiple scales and modalities of organization and suggest how such comparisons could contribute to a more complete fundamental understanding of brain organization and associated disease-related alterations.

Altered Gradients of Glutamate and Gamma-Aminobutyric Acid Transcripts in the Cortical Visuospatial Working Memory Network in Schizophrenia

BACKGROUND

Visuospatial working memory (vsWM), which is impaired in schizophrenia, requires information transfer across multiple nodes in the cerebral cortex, including visual, posterior parietal, and dorsolateral prefrontal regions. Information is conveyed across these regions via the excitatory projections of glutamatergic pyramidal neurons located in layer 3, whose activity is modulated by local inhibitory gamma-aminobutyric acidergic (GABAergic) neurons. Key properties of these neurons differ across these cortical regions. Consequently, in schizophrenia, alterations in the expression of gene products regulating these properties could disrupt vsWM function in different ways, depending on the region(s) affected.

METHODS

Here, we quantified the expression of markers of glutamate and GABA neurotransmission selectively in layer 3 of four cortical regions in the vsWM network from 20 matched pairs of schizophrenia and unaffected comparison subjects.

RESULTS

In comparison subjects, levels of glutamate transcripts tended to increase, whereas GABA transcript levels tended to decrease, from caudal to rostral, across cortical regions of the vsWM network. Composite measures across all transcripts revealed a significant effect of region, with the glutamate measure lowest in the primary visual cortex and highest in the dorsolateral prefrontal cortex, whereas the GABA measure showed the opposite pattern. In schizophrenia subjects, the expression levels of many of these transcripts were altered. However, this disease effect differed across regions, such that the caudal-to-rostral increase in the glutamate measure was blunted and the caudal-to-rostral decline in the GABA measure was enhanced in the illness.

CONCLUSIONS

Differential alterations in layer 3 glutamate and GABA neurotransmission across cortical regions may contribute to vsWM deficits in schizophrenia.

Gene expression links functional networks across cortex and striatum

The human brain is comprised of a complex web of functional networks that link anatomically distinct regions. However, the biological mechanisms supporting network organization remain elusive, particularly across cortical and subcortical territories with vastly divergent cellular and molecular properties. Here, using human and primate brain transcriptional atlases, we demonstrate that spatial patterns of gene expression show strong correspondence with limbic and somato/motor cortico-striatal functional networks. Network-associated expression is consistent across independent human datasets and evolutionarily conserved in non-human primates. Genes preferentially expressed within the limbic network (encompassing nucleus accumbens, orbital/ventromedial prefrontal cortex, and temporal pole) relate to risk for psychiatric illness, chloride channel complexes, and markers of somatostatin neurons. Somato/motor associated genes are enriched for oligodendrocytes and markers of parvalbumin neurons. These analyses indicate that parallel cortico-striatal processing channels possess dissociable genetic signatures that recapitulate distributed functional networks, and nominate molecular mechanisms supporting cortico-striatal circuitry in health and disease.

The functional connectivity of brain regions can be reflected in a shared molecular architecture. This cross-modal study demonstrates correspondence of spatial patterns of gene expression to limbic and somato/motor cortico-striatal networks in human and non-human primates.

Brain Transcriptome Databases: A User's Guide

Transcriptional programs instruct the generation and maintenance of diverse subtypes of neural cells, establishment of distinct brain regions, formation and function of neural circuits, and ultimately behavior. Spatiotemporal and cell type-specific analyses of the transcriptome, the sum total of all RNA transcripts in a cell or an organ, can provide insights into the role of genes in brain development and function, and their potential contribution to disorders of the brain. In the previous decade, advances in sequencing technology and funding from the National Institutes of Health and private foundations for large-scale genomics projects have led to a growing collection of brain transcriptome databases. These valuable resources provide rich and high-quality datasets with spatiotemporal, cell type-specific, and single-cell precision. Most importantly, many of these databases are publicly available via user-friendly web interface, making the information accessible to individual scientists without the need for advanced computational expertise. Here, we highlight key publicly available brain transcriptome databases, summarize the tissue sources and methods used to generate the data, and discuss their utility for neuroscience research.

Layer- and Cell Type-Specific Modulation of Excitatory Neuronal Activity in the Neocortex

From an anatomical point of view the neocortex is subdivided into up to six layers depending on the cortical area. This subdivision has been described already by Meynert and Brodmann in the late 19/early 20. century and is mainly based on cytoarchitectonic features such as the size and location of the pyramidal cell bodies. Hence, cortical lamination is originally an anatomical concept based on the distribution of excitatory neuron. However, it has become apparent in recent years that apart from the layer-specific differences in morphological features, many functional properties of neurons are also dependent on cortical layer or cell type. Such functional differences include changes in neuronal excitability and synaptic activity by neuromodulatory transmitters. Many of these neuromodulators are released from axonal afferents from subcortical brain regions while others are released intrinsically. In this review we aim to describe layer- and cell-type specific differences in the effects of neuromodulator receptors in excitatory neurons in layers 2–6 of different cortical areas. We will focus on the neuromodulator systems using adenosine, acetylcholine, dopamine, and orexin/hypocretin as examples because these neuromodulator systems show important differences in receptor type and distribution, mode of release and functional mechanisms and effects. We try to summarize how layer- and cell type-specific neuromodulation may affect synaptic signaling in cortical microcircuits.

Morphometric Similarity Networks Detect Microscale Cortical Organization and Predict Inter-Individual Cognitive Variation

Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organization comprising modules and high-degree hubs. Human MSN modules recapitulate known cortical cytoarchitectonic divisions, and greater inter-regional morphometric similarity was associated with stronger inter-regional co-expression of genes enriched for neuronal terms. Comparing macaque MSNs with tract-tracing data confirmed that morphometric similarity was related to axonal connectivity. Finally, variation in the degree of human MSN nodes accounted for about 40% of between-subject variability in IQ. Morphometric similarity mapping provides a novel, robust, and biologically plausible approach to understanding how human cortical networks underpin individual differences in psychological functions.

Stress amplifies sex differences in primate prefrontal profiles of gene expression

BACKGROUND

Stress is a recognized risk factor for mood and anxiety disorders that occur more often in women than men. Prefrontal brain regions mediate stress coping, cognitive control, and emotion. Here, we investigate sex differences and stress effects on prefrontal cortical profiles of gene expression in squirrel monkey adults.

METHODS

Dorsolateral, ventrolateral, and ventromedial prefrontal cortical regions from 18 females and 12 males were collected after stress or no-stress treatment conditions. Gene expression profiles were acquired using HumanHT-12v4.0 Expression BeadChip arrays adapted for squirrel monkeys.

RESULTS

Extensive variation between prefrontal cortical regions was discerned in the expression of numerous autosomal and sex chromosome genes. Robust sex differences were also identified across prefrontal cortical regions in the expression of mostly autosomal genes. Genes with increased expression in females compared to males were overrepresented in mitogen-activated protein kinase and neurotrophin signaling pathways. Many fewer genes with increased expression in males compared to females were discerned, and no molecular pathways were identified. Effect sizes for sex differences were greater in stress compared to no-stress conditions for ventromedial and ventrolateral prefrontal cortical regions but not dorsolateral prefrontal cortex.

CONCLUSIONS

Stress amplifies sex differences in gene expression profiles for prefrontal cortical regions involved in stress coping and emotion regulation. Results suggest molecular targets for new treatments of stress disorders in human mental health.

The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas

A comprehensive characterization of neuronal cell types, their distributions, and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium, ten pilot projects funded by the U.S. BRAIN Initiative, in developing, validating, and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans.

Big Science, Team Science, and Open Science for Neuroscience

The Allen Institute for Brain Science is a non-profit private institution dedicated to basic brain science with an internal organization more commonly found in large physics projects-large teams generating complete, accurate and permanent resources for the mouse and human brain. It can also be viewed as an experiment in the sociology of neuroscience. We here describe some of the singular differences to more academic, PI-focused institutions.

Enhancing our brains: Genomic mechanisms underlying cortical evolution

Our most distinguishing higher cognitive functions are controlled by the cerebral cortex. Comparative studies detail abundant anatomical and cellular features unique to the human developing and adult neocortex. Emerging genomic studies have further defined vast differences distinguishing developing human neocortices from related primates. These human-specific changes can affect gene function and/or expression, and result from structural variations such as chromosomal deletions and duplications, or from point mutations in coding and noncoding regulatory regions. Here, we review this rapidly growing field which aims to identify and characterize genetic loci unique to the human cerebral cortex. We catalog known human-specific genomic changes distinct from other primates, including those whose function has been interrogated in animal models. We also discuss how new model systems and technologies such as single cell RNA sequencing, primate iPSCs, and gene editing, are enabling the field to gain unprecedented resolution into function of these human-specific changes. Some neurological disorders are thought to uniquely present in humans, thus reinforcing the need to comprehensively understand human-specific gene expression in the developing brain.

A Laminar Organization for Selective Cortico-Cortical Communication

The neocortex is central to mammalian cognitive ability, playing critical roles in sensory perception, motor skills and executive function. This thin, layered structure comprises distinct, functionally specialized areas that communicate with each other through the axons of pyramidal neurons. For the hundreds of such cortico-cortical pathways to underlie diverse functions, their cellular and synaptic architectures must differ so that they result in distinct computations at the target projection neurons. In what ways do these pathways differ? By originating and terminating in different laminae, and by selectively targeting specific populations of excitatory and inhibitory neurons, these “interareal” pathways can differentially control the timing and strength of synaptic inputs onto individual neurons, resulting in layer-specific computations. Due to the rapid development in transgenic techniques, the mouse has emerged as a powerful mammalian model for understanding the rules by which cortical circuits organize and function. Here we review our understanding of how cortical lamination constrains long-range communication in the mammalian brain, with an emphasis on the mouse visual cortical network. We discuss the laminar architecture underlying interareal communication, the role of neocortical layers in organizing the balance of excitatory and inhibitory actions, and highlight the structure and function of layer 1 in mouse visual cortex.

Opportunities and challenges in modeling human brain disorders in transgenic primates

Molecular genetic tools have had a profound impact on neuroscience, but until recently their application has largely been confined to a few model species, most notably mouse, zebrafish, Drosophila melanogaster and Caenorhabditis elegans. With the development of new genome engineering technologies such as CRISPR, it is becoming increasingly feasible to apply these molecular tools in a wider range of species, including nonhuman primates. This will lead to many opportunities for brain research, but it will also pose challenges. Here we identify some of these opportunities and challenges in light of recent and foreseeable technological advances and offer some suggestions. Our main focus is on the creation of new primate disease models for understanding the pathological mechanisms of brain disorders and for developing new approaches to effective treatment. However, we also emphasize that primate genetic models have great potential to address many fundamental questions about brain function, providing an essential foundation for future progress in disease research.

Transcriptomic Perspectives on Neocortical Structure, Development, Evolution, and Disease

The cerebral cortex is the source of our most complex cognitive capabilities and a vulnerable target of many neurological and neuropsychiatric disorders. Transcriptomics offers a new approach to understanding the cortex at the level of its underlying genetic code, and rapid technological advances have propelled this field to the high-throughput study of the complete set of transcribed genes at increasingly fine resolution to the level of individual cells. These tools have revealed features of the genetic architecture of adult cortical areas, layers, and cell types, as well as spatiotemporal patterning during development. This has allowed a fresh look at comparative anatomy as well, illustrating surprisingly large differences between mammals while at the same time revealing conservation of some features from avians to mammals. Finally, transcriptomics is fueling progress in understanding the causes of neurodevelopmental diseases such as autism, linking genetic association studies to specific molecular pathways and affected brain regions.

BrainScope: interactive visual exploration of the spatial and temporal human brain transcriptome

Spatial and temporal brain transcriptomics has recently emerged as an invaluable data source for molecular neuroscience. The complexity of such data poses considerable challenges for analysis and visualization. We present BrainScope: a web portal for fast, interactive visual exploration of the Allen Atlases of the adult and developing human brain transcriptome. Through a novel methodology to explore high-dimensional data (dual t-SNE), BrainScope enables the linked, all-in-one visualization of genes and samples across the whole brain and genome, and across developmental stages. We show that densities in t-SNE scatter plots of the spatial samples coincide with anatomical regions, and that densities in t-SNE scatter plots of the genes represent gene co-expression modules that are significantly enriched for biological functions. We also show that the topography of the gene t-SNE maps reflect brain region-specific gene functions, enabling hypothesis and data driven research. We demonstrate the discovery potential of BrainScope through three examples: (i) analysis of cell type specific gene sets, (ii) analysis of a set of stable gene co-expression modules across the adult human donors and (iii) analysis of the evolution of co-expression of oligodendrocyte specific genes over developmental stages. BrainScope is publicly accessible at www.brainscope.nl.

Transcriptional Profiling of Cholinergic Neurons From Basal Forebrain Identifies Changes in Expression of Genes Between Sleep and Wake

Study objective

To assess differences in gene expression in cholinergic basal forebrain cells between sleeping and sleep-deprived mice sacrificed at the same time of day.

Methods

Tg(ChAT-eGFP)86Gsat mice expressing enhanced green fluorescent protein (eGFP) under control of the choline acetyltransferase (Chat) promoter were utilized to guide laser capture of cholinergic cells in basal forebrain. Messenger RNA expression levels in these cells were profiled using microarrays. Gene expression in eGFP(+) neurons was compared (1) to that in eGFP(-) neurons and to adjacent white matter, (2) between 7:00 am (lights on) and 7:00 pm (lights off), (3) between sleep-deprived and sleeping animals at 0, 3, 6, and 9 hours from lights on.

Results

There was a marked enrichment of ChAT and other markers of cholinergic neurons in eGFP(+) cells. Comparison of gene expression in these eGFP(+) neurons between 7:00 am and 7:00 pm revealed expected differences in the expression of clock genes (Arntl2, Per1, Per2, Dbp, Nr1d1) as well as mGluR3. Comparison of expression between spontaneous sleep and sleep-deprived groups sacrificed at the same time of day revealed a number of transcripts (n = 55) that had higher expression in sleep deprivation compared to sleep. Genes upregulated in sleep deprivation predominantly were from the protein folding pathway (25 transcripts, including chaperones). Among 42 transcripts upregulated in sleep was the cold-inducible RNA-binding protein.

Conclusions

Cholinergic cell signatures were characterized. Whether the identified genes are changing as a consequence of differences in behavioral state or as part of the molecular regulatory mechanism remains to be determined.

Subtype-Specific Genes that Characterize Subpopulations of Callosal Projection Neurons in Mouse Identify Molecularly Homologous Populations in Macaque Cortex

Callosal projection neurons (CPN) interconnect the neocortical hemispheres via the corpus callosum and are implicated in associative integration of multimodal information. CPN have undergone differential evolutionary elaboration, leading to increased diversity of cortical neurons-and more extensive and varied connections in neocortical gray and white matter-in primates compared with rodents. In mouse, distinct sets of genes are enriched in discrete subpopulations of CPN, indicating the molecular diversity of rodent CPN. Elements of rodent CPN functional and organizational diversity might thus be present in the further elaborated primate cortex. We address the hypothesis that genes controlling mouse CPN subtype diversity might reflect molecular patterns shared among mammals that arose prior to the divergence of rodents and primates. We find that, while early expression of the examined CPN-enriched genes, and postmigratory expression of these CPN-enriched genes in deep layers are highly conserved (e.g., Ptn, Nnmt, Cited2, Dkk3), in contrast, the examined genes expressed by superficial layer CPN show more variable levels of conservation (e.g., EphA3, Chn2). These results suggest that there has been evolutionarily differential retraction and elaboration of superficial layer CPN subpopulations between mouse and macaque, with independent derivation of novel populations in primates. Together, these data inform future studies regarding CPN subpopulations that are unique to primates and rodents, and indicate putative evolutionary relationships.

Brain transcriptome atlases: a computational perspective

The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.

Comprehensive transcriptome analysis of neocortical layers in humans, chimpanzees and macaques

While human cognitive abilities are clearly unique, underlying changes in brain organization and function remain unresolved. Here we characterized the transcriptome of the cortical layers and adjacent white matter in the prefrontal cortexes of humans, chimpanzees and rhesus macaques using unsupervised sectioning followed by RNA sequencing. More than 20% of detected genes were expressed predominantly in one layer, yielding 2,320 human layer markers. While the bulk of the layer markers were conserved among species, 376 switched their expression to another layer in humans. By contrast, only 133 of such changes were detected in the chimpanzee brain, suggesting acceleration of cortical reorganization on the human evolutionary lineage. Immunohistochemistry experiments further showed that human-specific expression changes were not limited to neurons but affected a broad spectrum of cortical cell types. Thus, despite apparent histological conservation, human neocortical organization has undergone substantial changes affecting more than 5% of its transcriptome.

Cognitive genomics: Linking genes to behavior in the human brain

Correlations of genetic variation in DNA with functional brain activity have already provided a starting point for delving into human cognitive mechanisms. However, these analyses do not provide the specific genes driving the associations, which are complicated by intergenic localization as well as tissue-specific epigenetics and expression. The use of brain-derived expression datasets could build upon the foundation of these initial genetic insights and yield genes and molecular pathways for testing new hypotheses regarding the molecular bases of human brain development, cognition, and disease. Thus, coupling these human brain gene expression data with measurements of brain activity may provide genes with critical roles in brain function. However, these brain gene expression datasets have their own set of caveats, most notably a reliance on postmortem tissue. In this perspective, I summarize and examine the progress that has been made in this realm to date, and discuss the various frontiers remaining, such as the inclusion of cell-type-specific information, additional physiological measurements, and genomic data from patient cohorts.

Toward understanding thalamocortical dysfunction in schizophrenia through computational models of neural circuit dynamics

The thalamus is implicated in the neuropathology of schizophrenia, and multiple modalities of noninvasive neuroimaging provide converging evidence for altered thalamocortical dynamics in the disorder, such as functional connectivity and oscillatory power. However, it remains a challenge to link these neuroimaging biomarkers to underlying neural circuit mechanisms. One potential path forward is a "Computational Psychiatry" approach that leverages computational models of neural circuits to make predictions for the dynamical impact dynamical impact on specific thalamic disruptions hypothesized to occur in the pathophysiology of schizophrenia. Here we review biophysically-based computational models of neural circuit dynamics for large-scale resting-state networks which have been applied to schizophrenia, and for thalamic oscillations. As a key aspect of thalamocortical dysconnectivity in schizophrenia is its regional specificity, it is important to consider potential sources of intrinsic heterogeneity of cellular and circuit properties across cortical and thalamic structures.

Molecular investigations of development and diseases of the brain of higher mammals using the ferret

The brains of higher mammals such as primates and carnivores contain well-developed unique brain structures. Uncovering the physiological functions, developmental mechanisms and evolution of these brain structures would greatly facilitate our understanding of the human brain and its diseases. Although the anatomical and electrophysiological features of these brain structures have been intensively investigated, our knowledge about their molecular bases is still limited. To overcome this limitation, genetic techniques for the brains of carnivores and primates have been established, and molecules whose expression patterns correspond to these brain structures were identified recently. To investigate the functional roles of these molecules, rapid and efficient genetic manipulation methods for higher mammals have been explored. In this review, recent advances in molecular investigations of the brains of higher mammals are discussed, mainly focusing on ferrets (Mustela putorius furo).

Receptor Tyrosine Kinase MET Interactome and Neurodevelopmental Disorder Partners at the Developing Synapse

BACKGROUND

Atypical synapse development and plasticity are implicated in many neurodevelopmental disorders (NDDs). NDD-associated, high-confidence risk genes have been identified, yet little is known about functional relationships at the level of protein-protein interactions, which are the dominant molecular bases responsible for mediating circuit development.

METHODS

Proteomics in three independent developing neocortical synaptosomal preparations identified putative interacting proteins of the ligand-activated MET receptor tyrosine kinase, an autism risk gene that mediates synapse development. The candidates were translated into interactome networks and analyzed bioinformatically. Additionally, three independent quantitative proximity ligation assays in cultured neurons and four independent immunoprecipitation analyses of synaptosomes validated protein interactions.

RESULTS

Approximately 11% (8/72) of MET-interacting proteins, including SHANK3, SYNGAP1, and GRIN2B, are associated with NDDs. Proteins in the MET interactome were translated into a novel MET interactome network based on human protein-protein interaction databases. High-confidence genes from different NDD datasets that encode synaptosomal proteins were analyzed for being enriched in MET interactome proteins. This was found for autism but not schizophrenia, bipolar disorder, major depressive disorder, or attention-deficit/hyperactivity disorder. There is correlated gene expression between MET and its interactive partners in developing human temporal and visual neocortices but not with highly expressed genes that are not in the interactome. Proximity ligation assays and biochemical analyses demonstrate that MET-protein partner interactions are dynamically regulated by receptor activation.

CONCLUSIONS

The results provide a novel molecular framework for deciphering the functional relations of key regulators of synaptogenesis that contribute to both typical cortical development and to NDDs.

lncRNA expression in the auditory forebrain during postnatal development

The biological processes governing brain development and maturation depend on complex patterns of gene and protein expression, which can be influenced by many factors. One of the most overlooked is the long noncoding class of RNAs (lncRNAs), which are known to play important regulatory roles in an array of biological processes. Little is known about the distribution of lncRNAs in the sensory systems of the brain, and how lncRNAs interact with other mechanisms to guide the development of these systems. In this study, we profiled lncRNA expression in the mouse auditory forebrain during postnatal development at time points before and after the onset of hearing (P7, P14, P21, adult). First, we generated lncRNA profiles of the primary auditory cortex (A1) and medial geniculate body (MG) at each age. Then, we determined the differential patterns of expression by brain region and age. These analyses revealed that the lncRNA expression profile was distinct between both brain regions and between each postnatal age, indicating spatial and temporal specificity during maturation of the auditory forebrain. Next, we explored potential interactions between functionally-related lncRNAs, protein coding RNAs (pcRNAs), and associated proteins. The maturational trajectories (P7 to adult) of many lncRNA - pcRNA pairs were highly correlated, and predictive analyses revealed that lncRNA-protein interactions tended to be strong. A user-friendly database was constructed to facilitate inspection of the expression levels and maturational trajectories for any lncRNA or pcRNA in the database. Overall, this study provides an in-depth summary of lncRNA expression in the developing auditory forebrain and a broad-based foundation for future exploration of lncRNA function during brain development.