Amy Bernard

An anatomically comprehensive atlas of the adult human brain transcriptome

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ∼900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography—the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.

A mesoscale connectome of the mouse brain

Comprehensive knowledge of the brain’s wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.

Transcriptional landscape of the prenatal human brain

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.

Highly multiplexed subcellular RNA sequencing in situ

Transcripts Visualized in Situ Despite advances, current methods for single-cell sequencing are unable to resolve transcript location within the cell, so Lee et al. (p. 1360, published online 27 February) developed a method of fluorescent in situ RNA sequencing (FISSEQ) that works in vivo to show messenger RNA localization within cells. The method amplifies complementary DNA targets by rolling circle amplification, and then in situ cross-linking locks amplicons to produce ample, highly localized templates for three-dimensional sequencing. The technique was tested in fibroblasts to reveal the differences between individual cells during wound repair. Reads of cellular RNA transcripts demonstrate spatial expression differences during simulated wound healing. Understanding the spatial organization of gene expression with single-nucleotide resolution requires localizing the sequences of expressed RNA transcripts within a cell in situ. Here, we describe fluorescent in situ RNA sequencing (FISSEQ), in which stably cross-linked complementary DNA (cDNA) amplicons are sequenced within a biological sample. Using 30-base reads from 8102 genes in situ, we examined RNA expression and localization in human primary fibroblasts with a simulated wound-healing assay. FISSEQ is compatible with tissue sections and whole-mount embryos and reduces the limitations of optical resolution and noisy signals on single-molecule detection. Our platform enables massively parallel detection of genetic elements, including gene transcripts and molecular barcodes, and can be used to investigate cellular phenotype, gene regulation, and environment in situ.

Adult mouse cortical cell taxonomy revealed by single cell transcriptomics

Nervous systems are composed of various cell types, but the extent of cell type diversity is poorly understood. We constructed a cellular taxonomy of one cortical region, primary visual cortex, in adult mice on the basis of single-cell RNA sequencing. We identified 49 transcriptomic cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types. We also analyzed cell type–specific mRNA processing and characterized genetic access to these transcriptomic types by many transgenic Cre lines. Finally, we found that some of our transcriptomic cell types displayed specific and differential electrophysiological and axon projection properties, thereby confirming that the single-cell transcriptomic signatures can be associated with specific cellular properties.

Genomic Anatomy of the Hippocampus

Availability of genome-scale in situ hybridization data allows systematic analysis of genetic neuroanatomical architecture. Within the hippocampus, electrophysiology and lesion and imaging studies demonstrate functional heterogeneity along the septotemporal axis, although precise underlying circuitry and molecular substrates remain uncharacterized. Application of unbiased statistical component analyses to genome-scale hippocampal gene expression data revealed robust septotemporal molecular heterogeneity, leading to the identification of a large cohort of genes with robust regionalized hippocampal expression. Manual mapping of heterogeneous CA3 pyramidal neuron expression patterns demonstrates an unexpectedly complex molecular parcellation into a relatively coherent set of nine expression domains in the septal/temporal and proximal/distal axes with reciprocal, nonoverlapping boundaries. Unique combinatorial profiles of adhesion molecules within these domains suggest corresponding differential connectivity, which is demonstrated for CA3 projections to the lateral septum using retrograde labeling. This complex, discrete molecular architecture provides a novel paradigm for predicting functional differentiation across the full septotemporal extent of the hippocampus.

Convergent transcriptional specializations in the brains of humans and song-learning birds.

INTRODUCTION Vocal learning, the ability to imitate sounds, is a trait that has undergone convergent evolution in several lineages of birds and mammals, including song-learning birds and humans. This behavior requires cortical and striatal vocal brain regions, which form unique connections in vocal-learning species. These regions have been found to have specialized gene expression within some species, but the patterns of specialization across vocal-learning bird and mammal species have not been systematically explored. Identifying molecular brain similarities across species. Brain region gene expression specializations were hierarchically organized into specialization trees of each species (blue lines), including for circuits that control learned vocalizations (highlighted green, purple, and orange regions). A set of comparative genomic algorithms found the most similarly specialized regions between songbird and human (orange lines), some of which are convergently evolved. RATIONALE The sequencing of genomes representing all major vocal-learning and vocal-nonlearning avian lineages has allowed us to develop the genomic tools to measure anatomical gene expression across species. Here, we asked whether behavioral and anatomical convergence is associated with gene expression convergence in the brains of vocal-learning birds and humans. RESULTS We developed a computational approach that discovers homologous and convergent specialized anatomical gene expression profiles. This includes generating hierarchically organized gene expression specialization trees for each species and a dynamic programming algorithm that finds the optimal alignment between species brain trees. We applied this approach to brain region gene expression databases of thousands of samples and genes that we and others generated from multiple species, including humans and song-learning birds (songbird, parrot, and hummingbird) as well as vocal-nonlearning nonhuman primates (macaque) and birds (dove and quail). Our results confirmed the recently revised understanding of the relationships between avian and mammalian brains. We further found that songbird Area X, a striatal region necessary for vocal learning, was most similar to a part of the human striatum activated during speech production. The RA (robust nucleus of the arcopallium) analog of song-learning birds, necessary for song production, was most similar to laryngeal motor cortex regions in humans that control speech production. More than 50 genes contributed to their convergent specialization and were enriched in motor control and neural connectivity functions. These patterns were not found in vocal nonlearners, but songbird RA was similar to layer 5 of primate motor cortex for another set of genes, supporting previous hypotheses about the similarity of these cell types between bird and mammal brains. CONCLUSION Our approach can accurately and quantitatively identify functionally and molecularly analogous brain regions between species separated by as much as 310 million years from a common ancestor. We were able to identify analogous brain regions for song and speech between birds and humans, and broader homologous brain regions in which these specialized song and speech regions are located, for tens to hundreds of genes. These genes now serve as candidates involved in developing and maintaining the unique connectivity and functional properties of vocal-learning brain circuits shared across species. The finding that convergent neural circuits for vocal learning are accompanied by convergent molecular changes of multiple genes in species separated by millions of years from a common ancestor indicates that brain circuits for complex traits may have limited ways in which they could have evolved from that ancestor. Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes of song-learning birds and humans relative to vocal nonlearners identified convergent gene expression specializations in specific song and speech brain regions of avian vocal learners and humans. The strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively, with human laryngeal motor cortex and parts of the striatum that control speech production and learning. Most of the associated genes function in motor control and brain connectivity. Thus, convergent behavior and neural connectivity for a complex trait are associated with convergent specialized expression of multiple genes.

An anatomic gene expression atlas of the adult mouse brain

Studying gene expression provides a powerful means of understanding structure-function relationships in the nervous system. The availability of genome-scale in situ hybridization datasets enables new possibilities for understanding brain organization based on gene expression patterns. The Anatomic Gene Expression Atlas (AGEA) is a new relational atlas revealing the genetic architecture of the adult C57Bl/6J mouse brain based on spatial correlations across expression data for thousands of genes in the Allen Brain Atlas (ABA). The AGEA includes three discovery tools for examining neuroanatomical relationships and boundaries: (1) three-dimensional expression-based correlation maps, (2) a hierarchical transcriptome-based parcellation of the brain and (3) a facility to retrieve from the ABA specific genes showing enriched expression in local correlated domains. The utility of this atlas is illustrated by analysis of genetic organization in the thalamus, striatum and cerebral cortex. The AGEA is a publicly accessible online computational tool integrated with the ABA (http://mouse.brain-map.org/agea).

Wnt signaling is required at distinct stages of development for the induction of the posterior forebrain

One of the earliest manifestations of anteroposterior pattering in the developing brain is the restricted expression of Six3 and Irx3 in the anterior and posterior forebrain, respectively. Consistent with the role of Wnts as posteriorizing agents in neural tissue, we found that Wnt signaling was sufficient to induce Irx3 and repress Six3 expression in forebrain explants. The position of the zona limitans intrathalamica (zli), a boundary-cell population that develops between the ventral (vT) and dorsal thalamus (dT), is predicted by the apposition of Six3 and Irx3 expression domains. The expression patterns of several inductive molecules are limited by the zli, including Wnt3, which is expressed posterior to the zli in the dT. Wnt3 and Wnt3a were sufficient to induce the dT marker Gbx2 exclusively in explants isolated posterior to the presumptive zli. Blocking the Wnt response allowed the induction of the vT-specific marker Dlx2 in prospective dT tissue. Misexpression of Six3 in the dT induced Dlx2 expression and inhibited the expression of both Gbx2 and Wnt3. These results demonstrate a dual role for Wnt signaling in forebrain development. First, Wnts directed the initial expression of Irx3 and repression of Six3 in the forebrain, delineating posterior and anterior forebrain domains. Later, continued Wnt signaling resulted in the induction of dT specific markers, but only in tissues that expressed Irx3.

Transcriptional Architecture of the Primate Neocortex

Genome-wide transcriptional profiling was used to characterize the molecular underpinnings of neocortical organization in rhesus macaque, including cortical areal specialization and laminar cell-type diversity. Microarray analysis of individual cortical layers across sensorimotor and association cortices identified robust and specific molecular signatures for individual cortical layers and areas, prominently involving genes associated with specialized neuronal function. Overall, transcriptome-based relationships were related to spatial proximity, being strongest between neighboring cortical areas and between proximal layers. Primary visual cortex (V1) displayed the most distinctive gene expression compared to other cortical regions in rhesus and human, both in the specialized layer 4 as well as other layers. Laminar patterns were more similar between macaque and human compared to mouse, as was the unique V1 profile that was not observed in mouse. These data provide a unique resource detailing neocortical transcription patterns in a nonhuman primate with great similarity in gene expression to human.