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Cellular transcriptomics reveals evolutionary identities of songbird vocal circuits
Abstract
The cells of songbird motor circuits
Birds have complex motor and cognitive abilities that rival or exceed the performance of many mammals, but their brains are organized in a notably different way. Parts of the bird brain have been functionally compared to the mammalian neocortex. However, it is still controversial to what extent these regions are truly homologous with the neocortex or if instead they are examples of evolutionary convergence. Colquitt et al. used single-cell sequencing to identify and characterize the major classes of neurons that comprise the song-control system in birds (see the Perspective by Tosches). They found multiple previously unknown neural classes in the bird telencephalon and shed new light on the long-standing controversy regarding the nature of homology between avian and mammalian brains.
Science , this issue p. eabd9704 ; see also p. 676
... Modern single cell and spatial omics technologies are powerful tools to address these longstanding questions. Recent studies in different tetrapod lineages have begun to utilize these techniques to investigate vertebrate brain evolution at an unprecedented resolution [7][8][9][10][11][12] . Advances in methods for comparative analysis of these data have further increased the ability to establish homologous cell-types across distant phyla 13,14 . ...
... To investigate the evolution of cell-types within the telencephalon, we analyzed conserved transcriptional signatures present in comparable cichlid 15 and mouse 37 forebrain datasets. To conduct these comparisons, previous studies [7][8][9] have correlated the expression of common one-to-one marker genes. Recently, a novel integrative approach, SAMap, has been designed for comparisons of cell-types from distantly related species, accounting for protein sequence divergence. ...
... Across vertebrate lineages, the telencephalon demonstrates both commonalities shared between taxa as well as marked, specialized differences and many hypothesized brain region homologies in non-mammalian vertebrates are unclear and actively debated. To further investigate conserved telencephalic populations in vertebrates, we performed cross-species comparisons between cichlid cell-types and cell-types from tetrapod forebrain regions ( Fig. 5a-c; Supplementary Data 8), including the axolotl telencephalon 9 , turtle pallium 7 , and songbird HVC, RA, and Area X regions 8 . The HVC and RA are involved in songbird vocal circuits and located in the DVR, a sauropsid pallial structure 8 . ...
The telencephalon has undergone remarkable diversification and expansion throughout vertebrate evolution, exhibiting striking variations in structural and functional complexity. Nevertheless, fundamental features are shared across vertebrate taxa, such as the presence of distinct regions including the pallium, subpallium, and olfactory structures. Teleost fishes have a uniquely “everted” telencephalon, which has confounded comparisons of their brain regions to other vertebrates. Here we combine spatial transcriptomics and single nucleus RNA-sequencing to generate a spatially-resolved transcriptional atlas of the Mchenga conophorus cichlid fish telencephalon. We then compare cell-types and anatomical regions in the cichlid telencephalon with those in amphibians, reptiles, birds, and mammals. We uncover striking transcriptional similarities between cell-types in the fish telencephalon and subpallial, hippocampal, and cortical cell-types in tetrapods, and find support for partial eversion of the teleost telencephalon. Ultimately, our work lends new insights into the organization and evolution of conserved cell-types and regions in the vertebrate forebrain.
... Different homologies between structures of the vertebrate telencephalon have been suggested based on their developmental origin and circuitry (19)(20)(21). Single cell sequencing has been used to compare the transcriptome of cells from the mammalian neocortex, reptilian three-layered cortex, and three telencephalic nuclei in song birds (22)(23)(24). Both non-neuronal and neuronal cortical cell types have overall conserved molecular identities between human, marmoset, and mouse despite transcriptomic differences (24). ...
... However, groups of turtle excitatory neurons resemble either upper layer or deep layer neurons of the mammalian neocortex (22). For songbirds, two nuclei related to vocal learning (HVC and robust nucleus of the arcopallium) have been suggested to exhibit similarities to distinct mammalian neocortical neurons but do not have the same developmental origin as their potential mammalian counterparts (23). Thus, how the majority of the avian telencephalic cell types relate to those of other vertebrates has yet to be deciphered. ...
... Besides nonneuronal cell types, we identified seven clusters of GABAergic and eight clusters of glutamatergic neurons using known marker genes for mammalian brain cell types (Fig. 2B). We detected clusters corresponding to the major interneuron subclasses PVALB+, SST+ and LAMP5+ by their cognate markers supporting previous findings, and VIP-like interneurons by known marker genes though not by expression of VIP itself (23). Similarly, cell types of the striatum, D1/D2 medium spiny neurons (D1/2MSN) and other striatal-like GABAergic neurons express mammalian marker genes. ...
Combinations of transcription factors govern the identity of cell types, which is reflected by enhancer codes in cis-regulatory genomic regions. Cell type-specific enhancer codes at nucleotide-level resolution have not yet been characterized for the mammalian neocortex. It is currently unknown whether these codes are conserved in other vertebrate brains, and whether they are informative to resolve homology relationships for species that lack a neocortex such as birds. To compare enhancer codes of cell types from the mammalian neocortex with those from the bird pallium, we generated single-cell multiome and spatially-resolved transcriptomics data of the chicken telencephalon. We then trained deep learning models to characterize cell type-specific enhancer codes for the human, mouse, and chicken telencephalon. We devised three metrics that exploit enhancer codes to compare cell types between species. Based on these metrics, non-neuronal and GABAergic cell types show a high degree of regulatory similarity across vertebrates. Proposed homologies between mammalian neocortical and avian pallial excitatory neurons are still debated. Our enhancer code based comparison shows that excitatory neurons of the mammalian neocortex and the avian pallium exhibit a higher degree of divergence than other cell types. In contrast to existing evolutionary models, the mammalian deep layer excitatory neurons are most similar to mesopallial neurons; and mammalian upper layer neurons to hyper- and nidopallial neurons based on their enhancer codes. In addition to characterizing the enhancer codes in the mammalian and avian telencephalon, and revealing unexpected correspondences between cell types of the mammalian neocortex and the chicken pallium, we present generally applicable deep learning approaches to characterize and compare cell types across species via the genomic regulatory code.
... These new neurons are added to a variety of regions, including HVC, a nucleus in the song circuit, which is involved in learned vocal communication. 1 In HVC, the addition of new projection neurons and interneurons is thought to play an important role in behavioral plasticity and tissue resilience. [2][3][4][5][6] These new neurons are born from neural stem cells in the ventricular zone (VZ) and migrate hundreds of micrometers to reach their integration targets in HVC and beyond. 4,7 How these new neurons migrate through the adult brain is unknown. ...
... Fluorescent in situ hybridization chain reaction (HCR-FISH) Fluorescent in situ hybridization chain reaction (HCR-FISH) was performed using custom probes designed by Molecular Instruments for detection of zebra finch GAD1, VGLUT2, PDGFRA, CSF1R, SLC15A2, and UTS2B mRNA (See Key Resources table), which are cell type markers selected from previous scRNAseq studies. 6 Birds were perfused with formalin and brains were post-fixed in formalin overnight at 4 C. Brains were sectioned on a LEICA VT 1000S into 150 mm slices and collected in 1X RNAse-free PBS. Slices were incubated in 90% DMSO/RNAse-free PBS for 2 h at room temperature and then in 1% NaBH4/RNAse-free PBS for 15 min at room temperature. ...
... (C) 2P microscopy image of a single plane in HVC showing GFP expression (green) and DiI+ HVC X cells (red).(legend continued on next page)6 Cell Reports 43, ...
... Importantly, however, avian pallial circuits engage genetically separate classes of excitatory and inhibitory neurons that are not present in the mammalian neocortex. Colquitt et al. (2021) showed that excitatory (glutamatergic) neurons have transcription factor profiles similar to the mammalian ventral pallium but not to the neocortex, which develops from the dorsal pallium (Colquitt et al. 2021). In addition, and consistent with the assumption that avian nido-/arcopallial regions are of ventral pallial origins, the most abundant inhibitory (GABA-releasing) neuron type in these avian brain regions resembles inhibitory neurons in mammalian ventral pallial derivatives but is absent from the neocortex (Colquitt et al. 2021). ...
... Importantly, however, avian pallial circuits engage genetically separate classes of excitatory and inhibitory neurons that are not present in the mammalian neocortex. Colquitt et al. (2021) showed that excitatory (glutamatergic) neurons have transcription factor profiles similar to the mammalian ventral pallium but not to the neocortex, which develops from the dorsal pallium (Colquitt et al. 2021). In addition, and consistent with the assumption that avian nido-/arcopallial regions are of ventral pallial origins, the most abundant inhibitory (GABA-releasing) neuron type in these avian brain regions resembles inhibitory neurons in mammalian ventral pallial derivatives but is absent from the neocortex (Colquitt et al. 2021). ...
... Colquitt et al. (2021) showed that excitatory (glutamatergic) neurons have transcription factor profiles similar to the mammalian ventral pallium but not to the neocortex, which develops from the dorsal pallium (Colquitt et al. 2021). In addition, and consistent with the assumption that avian nido-/arcopallial regions are of ventral pallial origins, the most abundant inhibitory (GABA-releasing) neuron type in these avian brain regions resembles inhibitory neurons in mammalian ventral pallial derivatives but is absent from the neocortex (Colquitt et al. 2021). Thus, the songbird nidopallium and the mammalian neocortex contain transcriptionally relatively similar neurons, which, however, have distinct developmental origins. ...
Categorization is crucial for behavioral flexibility because it enables animals to group stimuli into meaningful classes that can easily be generalized to new circumstances. A most abstract quantitative category is set size, the number of elements in a set. This review explores how categorical number representations are realized by the operations of excitatory and inhibitory neurons in associative telencephalic microcircuits in primates and songbirds. Despite the independent evolution of the primate prefrontal cortex and the avian nidopallium caudolaterale, the neuronal computations of these associative pallial circuits show surprising correspondence. Comparing cellular functions in distantly related taxa can inform about the evolutionary principles of circuit computations for cognition in distinctly but convergently realized brain structures.
... RA expresses numerous molecular markers thought to reflect specialized roles in the production of learned vocalizations. [19][20][21][22][23] Many RA markers are convergently evolved specializations shared with other avian vocal learners (e.g., hummingbirds) and LMC in humans, 19 and a recent transcriptomics effort provided insights into molecularly defined cell types within RA. 24 For the most part, however, these studies did not examine whether the identified markers or cell type definitions might reflect broader features of cortical motor circuits. For example, roughly half of the markers shared between RA and LMC have been found in adjacent non-vocal somatic motor areas, rendering them not true RA-specific markers. ...
... The AI has diverse molecular properties and connectivity 21,23,24,29,38 including distinct electrophysiological properties of RA excitatory cells. 15,16 It is considered analogous to deep layers of the mammalian cortex, which has a large diversity of pyramidal cell types. ...
... 7,58 While known markers of RA show mostly a homogeneous pattern, 21,23 recent evidence suggests possible molecular differences along the Cd-to-Rv axis. 24 To further examine a molecular topography within RA, we performed bulk RNA-seq of Cd and Rv domains microdissected from parasagittal sections through the core of RA ( Figures S3A and S3B). The two regions were remarkably similar in gene expression, with very few differences ( Figures S3C and S3D). ...
Identifying molecular specializations in cortical circuitry supporting complex behaviors, like learned vocalizations, requires understanding of the neuroanatomical context from which these circuits arise. In songbirds, the robust arcopallial nucleus (RA) provides descending cortical projections for fine vocal-motor control. Using single-nuclei transcriptomics and spatial gene expression mapping in zebra finches, we have defined cell types and molecular specializations that distinguish RA from adjacent regions involved in non-vocal motor and sensory processing. We describe an RA-specific projection neuron, differential inhibitory subtypes, and glia specializations and have probed predicted GABAergic interneuron subtypes electrophysiologically within RA. Several cell-specific markers arise developmentally in a sex-dependent manner. Our interactive apps integrate cellular data with developmental and spatial distribution data from the gene expression brain atlas ZEBrA. Users can explore molecular specializations of vocal-motor neurons and support cells that likely reflect adaptations key to the physiology and evolution of vocal control circuits and refined motor skills.
... After establishing a circuit-wide view of gene expression responses to song destabilization, we investigated the cellular specificity of these responses to understand what cell classes exhibit the most substantial transcriptional changes and may play a role in deafening-induced song plasticity. To do so, we integrated the SLCR-seq data with a previously generated single-nucleus and single-cell RNAsequencing dataset from HVC and RA of hearing adult male finches (Colquitt et al., 2021; Figure 5A). In that work, we compared songbird neuronal classes in HVC and RA to those in mammals and identified a high degree of transcriptional similarity across several neuronal classes ( Figure 5B). ...
... (A) Schematic of the approach to determine the cell type expression biases of genes that are differentially regulated with song destabilization. A previously generated cell-resolved gene expression dataset for RA (robust nucleus of the arcopallium) and HVC (proper name) (Colquitt et al., 2021) was combined with RA and HVC song destabilization regression coefficients from this study to compute a cell-type bias score (see Methods). Shown also is a uniform manifold approximate projection (UMAP) plot of the full dataset with major cell type groups indicated. ...
... OPC, oligodendrocyte precursor cell. (B) Schematic of neuronal cell types in the song motor pathway, as previously defined in Colquitt et al., 2021. HVC glutamatergic neurons are broadly similar to intratelencephalic (IT) mammalian neocortical neurons from multiple layers, and RA neurons are similar to extratelencephalic (ET) neurons from layer 5. Eight primary GABAergic clusters are found equally in both HVC and RA and are organized into clusters corresponding to subpallial regions of origin -lateral, medial, and caudal ganglionic eminences (LGE/MGE/CGE). ...
Sensory feedback is required for the stable execution of learned motor skills, and its loss can severely disrupt motor performance. The neural mechanisms that mediate sensorimotor stability have been extensively studied at systems and physiological levels, yet relatively little is known about how disruptions to sensory input alter the molecular properties of associated motor systems. Songbird courtship song, a model for skilled behavior, is a learned and highly structured vocalization that is destabilized following deafening. Here, we sought to determine how the loss of auditory feedback modifies gene expression and its coordination across the birdsong sensorimotor circuit. To facilitate this system-wide analysis of transcriptional responses, we developed a gene expression profiling approach that enables the construction of hundreds of spatially-defined RNA-sequencing libraries. Using this method, we found that deafening preferentially alters gene expression across birdsong neural circuitry relative to surrounding areas, particularly in premotor and striatal regions. Genes with altered expression are associated with synaptic transmission, neuronal spines, and neuromodulation and show a bias toward expression in glutamatergic neurons and Pvalb/Sst-class GABAergic interneurons. We also found that connected song regions exhibit correlations in gene expression that were reduced in deafened birds relative to hearing birds, suggesting that song destabilization alters the inter-region coordination of transcriptional states. Finally, lesioning LMAN, a forebrain afferent of RA required for deafening-induced song plasticity, had the largest effect on groups of genes that were also most affected by deafening. Combined, this integrated transcriptomics analysis demonstrates that the loss of peripheral sensory input drives a distributed gene expression response throughout associated sensorimotor neural circuitry and identifies specific candidate molecular and cellular mechanisms that support the stability and plasticity of learned motor skills.
... After establishing a circuit-wide view of gene expression responses to song destabilization, we investigated the cellular specificity of these responses to understand what cell classes exhibit the most substantial transcriptional changes and may play a role in deafening-induced song plasticity. To do so, we integrated the SLCR-seq data with a previously generated single-nucleus and single-cell RNAsequencing dataset from HVC and RA of hearing adult male finches (Colquitt et al., 2021; Figure 5A). In that work, we compared songbird neuronal classes in HVC and RA to those in mammals and identified a high degree of transcriptional similarity across several neuronal classes ( Figure 5B). ...
... (A) Schematic of the approach to determine the cell type expression biases of genes that are differentially regulated with song destabilization. A previously generated cell-resolved gene expression dataset for RA (robust nucleus of the arcopallium) and HVC (proper name) (Colquitt et al., 2021) was combined with RA and HVC song destabilization regression coefficients from this study to compute a cell-type bias score (see Methods). Shown also is a uniform manifold approximate projection (UMAP) plot of the full dataset with major cell type groups indicated. ...
... OPC, oligodendrocyte precursor cell. (B) Schematic of neuronal cell types in the song motor pathway, as previously defined in Colquitt et al., 2021. HVC glutamatergic neurons are broadly similar to intratelencephalic (IT) mammalian neocortical neurons from multiple layers, and RA neurons are similar to extratelencephalic (ET) neurons from layer 5. Eight primary GABAergic clusters are found equally in both HVC and RA and are organized into clusters corresponding to subpallial regions of origin -lateral, medial, and caudal ganglionic eminences (LGE/MGE/CGE). ...
Sensory feedback is required for the stable execution of learned motor skills, and its loss can severely disrupt motor performance. The neural mechanisms that mediate sensorimotor stability have been extensively studied at systems and physiological levels, yet relatively little is known about how disruptions to sensory input alter the molecular properties of associated motor systems. Songbird courtship song, a model for skilled behavior, is a learned and highly structured vocalization that is destabilized following deafening. Here, we sought to determine how the loss of auditory feedback modifies gene expression and its coordination across the birdsong sensorimotor circuit. To facilitate this system-wide analysis of transcriptional responses, we developed a gene expression profiling approach that enables the construction of hundreds of spatially-defined RNA-sequencing libraries. Using this method, we found that deafening preferentially alters gene expression across birdsong neural circuitry relative to surrounding areas, particularly in premotor and striatal regions. Genes with altered expression are associated with synaptic transmission, neuronal spines, and neuromodulation and show a bias toward expression in glutamatergic neurons and Pvalb/Sst-class GABAergic interneurons. We also found that connected song regions exhibit correlations in gene expression that were reduced in deafened birds relative to hearing birds, suggesting that song destabilization alters the inter-region coordination of transcriptional states. Finally, lesioning LMAN, a forebrain afferent of RA required for deafening-induced song plasticity, had the largest effect on groups of genes that were also most affected by deafening. Combined, this integrated transcriptomics analysis demonstrates that the loss of peripheral sensory input drives a distributed gene expression response throughout associated sensorimotor neural circuitry and identifies specific candidate molecular and cellular mechanisms that support the stability and plasticity of learned motor skills.
... After establishing a circuit-wide view of gene expression responses to song destabilization, we investigated the cellular specificity of these responses to understand what cell classes exhibit the most substantial transcriptional changes and may play a role in deafening-induced song plasticity. To do so, we integrated the SLCR-seq data with a previously generated single-nucleus and single-cell RNAsequencing dataset from HVC and RA of hearing adult male finches (Colquitt et al., 2021; Figure 5A). In that work, we compared songbird neuronal classes in HVC and RA to those in mammals and identified a high degree of transcriptional similarity across several neuronal classes ( Figure 5B). ...
... (A) Schematic of the approach to determine the cell type expression biases of genes that are differentially regulated with song destabilization. A previously generated cell-resolved gene expression dataset for RA (robust nucleus of the arcopallium) and HVC (proper name) (Colquitt et al., 2021) was combined with RA and HVC song destabilization regression coefficients from this study to compute a cell-type bias score (see Methods). Shown also is a uniform manifold approximate projection (UMAP) plot of the full dataset with major cell type groups indicated. ...
... OPC, oligodendrocyte precursor cell. (B) Schematic of neuronal cell types in the song motor pathway, as previously defined in Colquitt et al., 2021. HVC glutamatergic neurons are broadly similar to intratelencephalic (IT) mammalian neocortical neurons from multiple layers, and RA neurons are similar to extratelencephalic (ET) neurons from layer 5. Eight primary GABAergic clusters are found equally in both HVC and RA and are organized into clusters corresponding to subpallial regions of origin -lateral, medial, and caudal ganglionic eminences (LGE/MGE/CGE). ...
Sensory feedback is required for the stable execution of learned motor skills, and its loss can severely disrupt motor performance. The neural mechanisms that mediate sensorimotor stability have been extensively studied at systems and physiological levels, yet relatively little is known about how disruptions to sensory input alter the molecular properties of associated motor systems. Songbird courtship song, a model for skilled behavior, is a learned and highly structured vocalization that is destabilized following deafening. Here, we sought to determine how the loss of auditory feedback modifies gene expression and its coordination across the birdsong sensorimotor circuit. To facilitate this system-wide analysis of transcriptional responses, we developed a gene expression profiling approach that enables the construction of hundreds of spatially-defined RNA-sequencing libraries. Using this method, we found that deafening preferentially alters gene expression across birdsong neural circuitry relative to surrounding areas, particularly in premotor and striatal regions. Genes with altered expression are associated with synaptic transmission, neuronal spines, and neuromodulation and show a bias toward expression in glutamatergic neurons and Pvalb/Sst-class GABAergic interneurons. We also found that connected song regions exhibit correlations in gene expression that were reduced in deafened birds relative to hearing birds, suggesting that song destabilization alters the inter-region coordination of transcriptional states. Finally, lesioning LMAN, a forebrain afferent of RA required for deafening-induced song plasticity, had the largest effect on groups of genes that were also most affected by deafening. Combined, this integrated transcriptomics analysis demonstrates that the loss of peripheral sensory input drives a distributed gene expression response throughout associated sensorimotor neural circuitry and identifies specific candidate molecular and cellular mechanisms that support the stability and plasticity of learned motor skills.
... After establishing a circuit-wide view of gene expression responses to song destabilization, we investigated the cellular specificity of these responses to understand what cell classes exhibit the most substantial transcriptional changes and may play a role in deafening-induced song plasticity. To do so, we integrated the SLCR-seq data with a previously generated single-nucleus and single-cell RNAsequencing dataset from HVC and RA of hearing adult male finches (Colquitt et al., 2021; Figure 5A). In that work, we compared songbird neuronal classes in HVC and RA to those in mammals and identified a high degree of transcriptional similarity across several neuronal classes ( Figure 5B). ...
... (A) Schematic of the approach to determine the cell type expression biases of genes that are differentially regulated with song destabilization. A previously generated cell-resolved gene expression dataset for RA (robust nucleus of the arcopallium) and HVC (proper name) (Colquitt et al., 2021) was combined with RA and HVC song destabilization regression coefficients from this study to compute a cell-type bias score (see Methods). Shown also is a uniform manifold approximate projection (UMAP) plot of the full dataset with major cell type groups indicated. ...
... OPC, oligodendrocyte precursor cell. (B) Schematic of neuronal cell types in the song motor pathway, as previously defined in Colquitt et al., 2021. HVC glutamatergic neurons are broadly similar to intratelencephalic (IT) mammalian neocortical neurons from multiple layers, and RA neurons are similar to extratelencephalic (ET) neurons from layer 5. Eight primary GABAergic clusters are found equally in both HVC and RA and are organized into clusters corresponding to subpallial regions of origin -lateral, medial, and caudal ganglionic eminences (LGE/MGE/CGE). ...
Sensory feedback is required for the stable execution of learned motor skills, and its loss can severely disrupt motor performance. The neural mechanisms that mediate sensorimotor stability have been extensively studied at systems and physiological levels, yet relatively little is known about how disruptions to sensory input alter the molecular properties of associated motor systems. Songbird courtship song, a model for skilled behavior, is a learned and highly structured vocalization that is destabilized following deafening. Here, we sought to determine how the loss of auditory feedback modifies gene expression and its coordination across the birdsong sensorimotor circuit. To facilitate this system-wide analysis of transcriptional responses, we developed a gene expression profiling approach that enables the construction of hundreds of spatially-defined RNA-sequencing libraries. Using this method, we found that deafening preferentially alters gene expression across birdsong neural circuitry relative to surrounding areas, particularly in premotor and striatal regions. Genes with altered expression are associated with synaptic transmission, neuronal spines, and neuromodulation and show a bias toward expression in glutamatergic neurons and Pvalb/Sst-class GABAergic interneurons. We also found that connected song regions exhibit correlations in gene expression that were reduced in deafened birds relative to hearing birds, suggesting that song destabilization alters the inter-region coordination of transcriptional states. Finally, lesioning LMAN, a forebrain afferent of RA required for deafening-induced song plasticity, had the largest effect on groups of genes that were also most affected by deafening. Combined, this integrated transcriptomics analysis demonstrates that the loss of peripheral sensory input drives a distributed gene expression response throughout associated sensorimotor neural circuitry and identifies specific candidate molecular and cellular mechanisms that support the stability and plasticity of learned motor skills.
... In order to further classify GABAergic neurons, medial ganglionic eminence (MGE-class neuron; cluster 1,5,6,9), caudal ganglionic eminence (CGE-class neuron; cluster: 7,11), and lateral ganglionic eminence (LGE-class neuron; cluster: 0,2,3,4,8,10) were obtained according to a previous study 21 (Fig. 4A). MGEclass neuron signi cantly expressed SST cortical interneurons, including sst, sox6 and trps1. ...
... During brain development, most interneurons originate from ganglia protrusions (GEs), which can be divided into LGE, MGE, and CGE 33 . In our study, we also further divide GABA neurons into LGE, MGE, and CGE, referring to the reported marker genes 21,34 . MGE-class neuron signi cantly expresses SST cortical interneurons, which is consistent with human research that SST cortical interneurons derive primarily from the MGE-class neuron 34 . ...
... Marker genes for cortical interneurons and olfactory bulb interneurons have not been clearly distinguished in poultry. However, of the marker genes, we nd MGE-class neuron is similar to the SST cortical interneurons, LGE-class neuron similar to the olfactory bulb interneurons, and CGE-class neuron similar to CGE generated cortical interneurons according to the mammals and songbird studies 21,34 . The increase of GABA neurotransmission in the amygdala will lead to the behavioral changes induced by social stressor, and provide protection in dominant animals when suffer stress 41 . ...
Dominance hierarchy, is described as the priority to feed, resting and territory in term of aggressive interactions. Increased studies have revealed the underpinned mechanism mediating social hierarchy in mammal, vertebrate and fishes, however, there is rare studies conducting on how brain amydala on social hierarchy in poultry. We performed cross-species analysis with mammalian amygdala, and find that cell types of human and rhesus monkeys were more closely related and that of chickens were more distant. We identified 26 clusters and divided it into 10 main clusters. Of which, GABAnic and glutamatergic neurons are associated with social behaviors, and their sub-neurons GABA_LEG and Glu3, and hub genes RHOB and CDK14 , are considered mediating the social hierarchy of chickens. Additionally, high-rank chickens may have better immune functions and stress tolerance than low-rank chickens. Our results provide to serve the developmental studies of amygdala neuron system, and new insights into the underpinned mechanism of social hierarchy in poultry.
... The first applications of scRNA-seq in neuroscience profiled cell types in mice [83,84]. More recently, scRNAseq was used to classify neuron types also in reptiles [85] and songbirds [86]. The evolutionary relationships of reptiles, birds and mammals suggest that a feature found in all three lineages predates their divergence, while a feature found exclusively in the mammalian lineage is, in fact, a mammalian invention. ...
... These results extend earlier findings that found similarities between turtle and mammalian interneurons based on marker genes and morphology [87,88]. Colquitt et al. [86] recently made analogous observations regarding the similarity of songbird and mouse interneurons (Fig. 2b,c). The most parsimonious explanation of this sharing of interneuron types is that similar types already existed in a common ancestor of the three lineages, rather than convergent evolution in three lineages. ...
... CC-BY-NC 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made Mouse data from ref. [74], songbird data and correlation analysis from ref. [86]. ...
Cortical inhibitory interneurons form a broad spectrum of subtypes. This diversity suggests a division of labour, in which each cell type supports a distinct function. In the present era of optimisation-based algorithms, it is tempting to speculate that these functions were the evolutionary or developmental driving force for the spectrum of interneurons we see in the mature mammalian brain. In this study, we evaluated this hypothesis using the two most common interneuron types, parvalbumin (PV) and somatostatin (SST) expressing cells, as examples. PV and SST interneurons control the activity in the cell bodies and the apical dendrites of excitatory pyramidal cells, respectively. But was this compartment-specific inhibition indeed the function for which PV and SST cells originally evolved? Does the compartmental structure of pyramidal cells shape the diversification of PV and SST interneurons over development? To address these questions, we reviewed and reanalysed publicly available data on the development and evolution of PV and SST interneurons on one hand, and pyramidal cell morphology on the other. These data speak against the idea that the compartment structure of pyramidal cells drove the diversification into PV and SST interneurons. In particular, pyramidal cells mature late, while interneurons are likely committed to a particular fate (PV vs. SST) during early development. Moreover, comparative anatomy and single cell RNA-sequencing data indicate that PV and SST cells, but not the compartment structure of pyramidal cells, existed in the last common ancestor of mammals and reptiles. Specifically, turtle and songbird SST cells also express genes that are thought to play a role in compartment-specific inhibition in mammals. PV and SST cells therefore evolved and developed the properties that allow them to provide compartment-specific inhibition before there was selective pressure for this function. This suggests that interneuron diversity originally resulted from a different evolutionary driving force and was only later co-opted for the compartment-specific inhibition it seems to serve in mammals today.
... The precise identification of amygdala subnuclei in sauropsids remains controversial due to the obvious differences in brain organization between mammals and sauropsids. Recent studies suggest that the caudal part of the dorsal ventricular ridge (DVR), which is present in all sauropsids, and the surrounding subpallial regions are homologous counterparts of the mammalian amygdala 17,62,63 . To characterize sauropsid amygdala homologs at the single-cell level and compare evolutionary conservation and divergence with the mammalian amygdala, we dissected the chicken caudal DVR (including the arcopallium (APall) and caudal nidopallium (NPall)) and extended amygdala (EA) for snRNA-seq ( Fig. 5a; Supplementary Fig. S9a) 64 . ...
... However, PRKCD + neurons were not only located in the EA, but also broadly distributed in the APall and NPall (Fig. 5h). Given that the PRKCD and DRD2 clusters were LGE-derived neurons showing high expression of LGE marker genes ( Supplementary Fig. S9e), this observation is consistent with recent research showing that LGE-derived interneurons are broadly distributed in bird brains 62 . Furthermore, our results showed that chickens contained more LGE-derived neurons, while mammals possessed more MGE/CGE-derived neurons in the amygdala (Fig. 5i, j). ...
... Inhibitory neuronal cell types were much more conserved than excitatory neuronal cell types in the datasets, consistent with that found in other brain regions 23,62 . Many clusters of inhibitory neuronal cells were matched one-to-one between species. ...
The amygdala, or an amygdala-like structure, is found in the brains of all vertebrates and plays a critical role in survival and reproduction. However, the cellular architecture of the amygdala and how it has evolved remain elusive. Here, we generated single-nucleus RNA-sequencing data for more than 200,000 cells in the amygdala of humans, macaques, mice, and chickens. Abundant neuronal cell types from different amygdala subnuclei were identified in all datasets. Cross-species analysis revealed that inhibitory neurons and inhibitory neuron-enriched subnuclei of the amygdala were well-conserved in cellular composition and marker gene expression, whereas excitatory neuron-enriched subnuclei were relatively divergent. Furthermore, LAMP5 ⁺ interneurons were much more abundant in primates, while DRD2 ⁺ inhibitory neurons and LAMP5 ⁺ SATB2 ⁺ excitatory neurons were dominant in the human central amygdalar nucleus (CEA) and basolateral amygdalar complex (BLA), respectively. We also identified CEA-like neurons and their species-specific distribution patterns in chickens. This study highlights the extreme cell-type diversity in the amygdala and reveals the conservation and divergence of cell types and gene expression patterns across species that may contribute to species-specific adaptations.
... The evolutionary origin of these amniote circuits is a matter of intense debate. These could be homologues to neocortical circuits -and so derived from the same ancestral circuit-or analogues, having convergently evolved separately (4)(5)(6) . ...
... This mouse cluster corresponded to intratelencephalic cortical neurons (28), and its cells were likely the latest generated in our experiment. Then, we performed label transfer analysis (6) to interrogate each cell from a dataset what cell cluster from the other species dataset were transcriptionally more similar to. ...
The amniote pallium contains sensory circuits structurally and functionally equivalent, yet their evolutionary relationship remains unresolved. Our study employs birthdating analysis, single-cell RNA and spatial transcriptomics, and mathematical modeling to compare the development and evolution of known pallial circuits across birds (chick), lizards (gecko) and mammals (mouse). We reveal that neurons within these circuits' stations are generated at varying developmental times and brain regions across species, and found an early developmental divergence in the transcriptomic progression of glutamatergic neurons. Together, we show divergent developmental and evolutionary trajectories in the pallial cell types of sauropsids and mammals. Our research highlights significant differences in circuit construction rules among species and pallial regions. Interestingly, despite these developmental distinctions, the sensory circuits in birds and mammals appear functionally similar, which suggest the convergence of high-order sensory processing across amniote lineages.
... After QC, we obtained 29,281 single-nuclei transcriptomes and identified seven major populations of neuronal and nonneuronal cells ( Figure 4A). Like before, referring to well-established marker genes, [51][52][53]61 we annotated clusters of excitatory neurons (EXN; SLC17A6+), inhibitory neurons (INN; GAD2+), oligodendrocytes (OLI; PLP1+), astrocytes (AST; SLC1A2+), dendrocyte precursor cells (OPC; PDGFRA+), microglial cells (MIC; C1QB+), and blood cells (HBAD+) ( Figure 4B). We mainly focused on the 23,514 neurons in our single-cell data. ...
... For subsequent analysis, we focused exclusively on the integral part of the tectum. After filtering out the lowquality cells, we obtained 89,521 segmented cells, with an average of 782 UMIs and 421 genes per cell (Figure 3B).Upon dimension reduction and clustering, we annotated these cells into six major cell types based on known markers for neural cells51-53 : excitatory neurons (EXN; SLC17A6+), inhibitory neurons (INN; GAD2+), oligodendrocytes (OLI; PLP1+), astrocytes (AST; AQP4+), dendrocyte precursor cells (OPC; OLIG2+), vascular leptomeningeal cells (VLMC; DCN+), and acetylcholinergic neurons (ACH; SLC18A3+) (Figures 3C and ...
The avian optic tectum (OT) has been studied for its diverse functions, yet a comprehensive molecular landscape at the cellular level has been lacking. In this study, we applied spatial transcriptome sequencing and single-nucleus RNA sequencing (snRNA-seq) to explore the cellular organization and molecular characteristics of the avian OT from two species: Columba livia and Taeniopygia guttata. We identified precise layer structures and provided comprehensive layer-specific signatures of avian OT. Furthermore, we elucidated diverse functions in different layers, with the stratum griseum periventriculare (SGP) potentially playing a key role in advanced functions of OT, like fear response and associative learning. We characterized detailed neuronal subtypes and identified a population of FOXG1+ excitatory neurons, resembling those found in the mouse neocortex, potentially involved in neocortex-related functions and expansion of avian OT. These findings could contribute to our understanding of the architecture of OT, shedding light on visual perception and multifunctional association.
... Piriform cortex is central to the historical definition of paleocortex, as its three-layered cytoarchitecture resembles the pallium of amphibians and reptiles (14,15,19). This raises the question whether neurons from conserved cytoarchitectures exhibit similar molecular profiles (Fig. 4A), as speculated based on single-cell RNA sequencing studies in non-mammals (19,35). ...
... We integrated single cell RNA sequencing (sc-RNA seq) data from lizard Pogona vitticeps (35,36), turtle Trachemys scripta (37), salamander Pleurodeles waltl (19) and mouse Mus musculus (this study -lab dataset; (17)). We subsetted the original datasets to include only cells from ontogenetically equivalent brain regions. ...
The cerebral cortex diversified extensively during vertebrate evolution. Intriguingly, the three-layered mammalian olfactory cortex resembles the cortical cytoarchitecture of non-mammals yet evolved alongside the six-layered neocortex, enabling unique comparisons for investigating cortical neuron diversification. We performed single-nucleus multiome sequencing across mouse three- to six-layered cortices and compared neuron types across mice, reptiles and salamander. We identified neurons that are olfactory cortex-specific or conserved across mouse cortical areas. However, transcriptomically similar neurons exhibited area-specific epigenetic states. Additionally, the olfactory cortex showed transcriptomic divergence between lab and wild-derived mice, suggesting enhanced circuit plasticity through adult immature neurons. Finally, olfactory cortex neurons displayed marked transcriptomic similarities to reptile and salamander neurons. Together, these data indicate that the mammalian olfactory cortex retains molecular signatures representative of ancestral cortical traits.
... Furthermore, Heavner et al. (2020) have defined many subclasses of developing projection neurons in the cerebral cortex according to the transcription factor expression, which is in line with singlecell RNA-seq subtypes, as confirmed through multidimensional approaches. In this chapter, involved cortical neurons associated with neural circuit formation and changes mainly include intratelencephalic neurons, glutamatergic neurons, GABAergic neurons, LGE-class neurons, and intermediate progenitor cells (Paul et al., 2017;Tasic et al., 2018;Zhong et al., 2018;Colquitt et al., 2021;Zhang et al., 2021). More recently, Endo and coworkers have comprehensively reviewed the emerging technologies for studying local neural circuits in the cerebral cortex and given new insight into local neural circuits obtained by these technologies, such as single-cell sequencing and tissue clearing, etc. (Endo et al., 2021). ...
... Therefore, these transcriptomic findings together outline general characteristics of different neuronal populations that may actively participate in cortical circuits. Interestingly enough, Colquitt et al. (2021) have studied another species except for humans and mice, birds, using 10X Genomics, and demonstrated that glutamatergic vocal neurons of birds are quite similar to neocortical projection neurons of mammals concerning their transcriptional activities. As shown in Table 2, glutamatergic neurons have been especially investigated in mouse hippocampus using 10X Genomics, which will be discussed in the next paragraph (Tasic et al., 2018;Ding et al., 2020). ...
Neural circuits are characterized as interconnecting neuron networks connected by synapses. Some kinds of gene expression and/or functional changes of neurons and synaptic connections may result in aberrant neural circuits, which has been recognized as one crucial pathological mechanism for the onset of many neurological diseases. Gradual advances in single-cell sequencing approaches with strong technological advantages, as exemplified by high throughput and increased resolution for live cells, have enabled it to assist us in understanding neuronal diversity across diverse brain regions and further transformed our knowledge of cellular building blocks of neural circuits through revealing numerous molecular signatures. Currently published transcriptomic studies have elucidated various neuronal subpopulations as well as their distribution across prefrontal cortex, hippocampus, hypothalamus, and dorsal root ganglion, etc. Better characterization of brain region-specific circuits may shed light on new pathological mechanisms involved and assist in selecting potential targets for the prevention and treatment of specific neurological disorders based on their established roles. Given diverse neuronal populations across different brain regions, we aim to give a brief sketch of current progress in understanding neuronal diversity and neural circuit complexity according to their locations. With the special focus on the application of single-cell sequencing, we thereby summarize relevant region-specific findings. Considering the importance of spatial context and connectivity in neural circuits, we also discuss a few published results obtained by spatial transcriptomics. Taken together, these single-cell sequencing data may lay a mechanistic basis for functional identification of brain circuit components, which links their molecular signatures to anatomical regions, connectivity, morphology, and physiology. Furthermore, the comprehensive characterization of neuron subtypes, their distributions, and connectivity patterns via single-cell sequencing is critical for understanding neural circuit properties and how they generate region-dependent interactions in different context.
... In agreement with previous reports in ZFs [60][61][62], we identi ed marker genes representing speci c cell types reported for the song nuclei, such as Area X medium spiny neurons (MSNs), Area X pallidal-like neurons, RA glutamatergic projecting neurons, GABAergic neurons, astrocytes, microglia, oligodendrocytes, oligo precursor cells, and RA surrouding arcopallium glutamatergic neurons (Fig. 5A). Based on single nucleotide polymorphism (SNP) variations of the transcripts in each cell, we identi ed the cellular transcripts associated with each individual bird, and labeled these "cells" with a color scheme to match individuals in the uniform manifold approximation and projection (UMAP) plot (Fig. 5A). ...
... Subclusters in MSNs and pallidal-like neurons were identi ed with FOXP2, FOXP4, MTNR1A, and PENK based on a previous report [62]. Subclusters in glutamatergic neurons in RA were identi ed based on a previous report [60,61] and in situ hybridization database, ZEBrA [96]; Song features and development of F 1 hybrids tutored using the song conspeci c to a single-parental species A: Examples of individual differences in the adult songs of F 1 hybrids tutored using ZF or OF songs (three birds each). Motif and repetitive song structures are shown as red-solid and blue-dotted lines above each spectrogram. ...
The emergence of individuality during learned behavior is a general feature of animal species, yet the biological bases of its development remain unknown. Similar to human speech, songbirds develop individually-unique songs with species-specific traits through vocal learning. By taking advantage of songbirds as a model system for studying the neural basis of vocal learning and development, we utilized F 1 hybrid songbirds ( Taeniopygia guttata cross with T. bichenovii ) to examine the developmental and molecular mechanisms underlying individuality in vocal learning. When tutoring with songs from both parental species, F 1 pupils showed vast individual differences in their acquired songs. Approximately 30% of F 1 hybrids selectively learned either song of the two parental species, whereas others developed merged songs between the parental species. Vocal acoustic biases during vocal babbling were initially observed as individual differences in songs among F 1 juveniles, which were maintained through the sensitive period of song vocal learning. These individual differences in vocal acoustic biases appeared independently from the auditory experience of hearing biological farther’s and passive tutored songs. Furthermore, the idiosyncratic traits of F 1 hybrids’ songs were not correlated with peripheral vocal organ morphology. However, we identified unique transcriptional signatures from the glutamatergic neurons projecting from the cortical vocal output nucleus to the hypoglossal nuclei associated with individual differences in the acoustic vocal biases, even at the initial stage of vocal learning. These results indicate that a predisposed motor bias influences the individuality observed when learning new motor skills.
... Recent results of cellular transcriptomics further revealed the evolutionary features of songbird VMP. Although HVC and RA are not homologous with the mammalian neocortex, their similarity in cell types and connection mode suggests that VMP may have evolved to functionally resemble the mammalian neocortex (Colquitt et al., 2021). With the further study, the results of gene expression lineage analysis showed that the types of songbird HVC neurons are similar to those of human LMC layers 2-3, and human LMC layers 2-3 neurons project to LMC layer 5, just like songbird HVC neurons project to RA (Pfenning et al., 2014;Jarvis, 2019;Gedman et al., 2022). ...
... Optogenetics, chemogenetics and other targeted neural pathway manipulation techniques can be a key link between behavior and neural activity (Singh Alvarado et al., 2021). In the meantime, the related cell types and gene expression patterns of birds and mammals were compared by single-cell sequencing technology to reveal their evolutionary analogy (Colquitt et al., 2021). Commonly used songbird models were gene-edited using CRISPR/Cas9 technology to make them more widely applicable for multi-purpose studies . ...
Vocal learning is a complex acquired social behavior that has been found only in very few animals. The process of animal vocal learning requires the participation of sensorimotor function. By accepting external auditory input and cooperating with repeated vocal imitation practice, a stable pattern of vocal information output is eventually formed. In parallel evolutionary branches, humans and songbirds share striking similarities in vocal learning behavior. For example, their vocal learning processes involve auditory feedback, complex syntactic structures, and sensitive periods. At the same time, they have evolved the hierarchical structure of special forebrain regions related to vocal motor control and vocal learning, which are organized and closely associated to the auditory cortex. By comparing the location, function, genome, and transcriptome of vocal learning-related brain regions, it was confirmed that songbird singing and human language-related neural control pathways have certain analogy. These common characteristics make songbirds an ideal animal model for studying the neural mechanisms of vocal learning behavior. The neural process of human language learning may be explained through similar neural mechanisms, and it can provide important insights for the treatment of language disorders.
... To identify the cell type of each cell cluster, the expression of established marker genes was used (Fig. 5B) (58,78,79). The marker genes used were as follows: GFRA1 for HVC GLUT neurons projecting to RA [HVC (RA) neuron]; SRD5A2 for HVC GLUT neurons projecting to Area X [HVC (X) neuron]; ADCYAP1 for GLUT neurons in arcopallium surrounding RA; GAD1 and GAD2 for GABA neurons; SLC1A2 and ASPA for astrocytes; PDGFRA for OPCs; ST18 for oligodendrocytes; CSF1R for microglia; and SRD5A2 and SCUBE1 for the GLUT neurons in RA projecting to the nucleus of cranial nerve XII. ...
Learned behavior, a fundamental adaptive trait in fluctuating environments, is shaped by species-specific constraints. This phenomenon is evident in songbirds, which acquire their species-specific songs through vocal learning. To explore the neurogenetic mechanisms underlying species-specific song learning, we generated F 1 hybrid songbirds by crossing Taeniopygia guttata with Aidemosyne modesta . These F 1 hybrids demonstrate expanded learning capacities, adeptly mimicking songs from both parental species and other heterospecific songs more extensively than their parental counterparts. Despite the conserved size of brain regions and neuron numbers in the neural circuits for song learning and production, single-cell transcriptomics reveals distinctive transcriptional characteristics in the F 1 hybrids, especially in vocal-motor projection neurons. These neurons exhibit enrichment for nonadditively expressed genes, particularly those related to ion channel activity and cell adhesion, which are associated with the degree of song learning among F 1 individuals. Our findings provide insights into the emergence of altered learning capabilities through hybridization, linked to cell type–specific transcriptional changes.
... But even this approach is not without complications since homologous neural entities can change their function in evolutionary time as, in parallel, non-homologous structures can functionally converge (Güntürkün et al., 2024). Thus, early embryonic brain domains with few master developmental regulatory genes show much more ontogenetic plasticity than previously assumed, turning classic neurogenetic homology arguments into slippery slopes (Colquitt et al., 2021). ...
Big Team Science (BTS) offers immense potential for comparative cognition research, enabling larger and more diverse sample sizes, promoting open science practices, and fostering global collaboration. However, implementing BTS in comparative cognition also presents unique challenges, such as making comparisons “species fair,” dealing with multi-site variation, reaching consensus among researchers from diverse backgrounds, and incentivizing participation in BTS. Here, we explore these challenges and propose potential solutions. These include capitalizing on the collective expertise of a diverse team to facilitate species-fair experimental designs, implementing thorough documentation and data analysis techniques to account for cross-site variability, employing consensus-building strategies to foster collaboration and address theoretical discrepancies, and advocating for the value of BTS contributions in promoting cultural shifts within academia. We conclude that BTS is well-positioned to pave the way for groundbreaking discoveries in comparative cognition research—BTS holds the potential to transform the field by leveraging its collaborative power and addressing long-standing and highly complex questions with unprecedented scope.
... Moreover, parenchymal glia associated with support functions are present in all major branches of bilaterians 60 . To estimate the time of emergence of this astrocytic gene set we asked whether its genes were expressed across Planulozoa by recovering and analyzing datasets from over 20 species [9][10][11][12][13][14][15][16][17][18][19][20][21][22]38,39,53,59,[61][62][63] , identifying existing orthologs and assessing their expression in glial clusters or among ectodermal cells (Fig. 5). We found expression of the astrocytic gene set in all vertebrate RG, but not in Ciona ependymoglia (Supplementary data Fig. ...
Macroglia fulfill essential functions in the adult vertebrate brain, producing and maintaining neurons and regulating neuronal communication. However, we still know little about their emergence and diversification. We used the zebrafish D. rerio as a distant vertebrate model with moderate glial diversity as anchor to reanalyze datasets covering over 600 million years of evolution. We identify core features of adult neurogenesis and innovations in the mammalian lineage with a potential link to the rarity of radial glia-like cells in adult humans. Our results also suggest that functions associated with astrocytes originated in a multifunctional cell type fulfilling both neural stem cell and astrocytic functions before these diverged. Finally, we identify conserved elements of macroglial cell identity and function and their time of emergence during evolution.
... This means that birds are so far the only animal model for studying the development and processing of speech information in the brain, which has greatly stimulated research within the field of comparative neuroanatomy and pallial evolution (Brenowitz et al., 1997;Brainard & Doupe, 2002;Jarvis, 2004;Nottebohm, 2005;Jarvis, 2019). Further, after more than 365 million years of separate evolution birds have evolved a different pallial (neocortical) brain organisation compared to mammals but show similar connectivity between relevant brain areas, neurochemical features, neuron numbers and gene expression profiles of cells that are functionally related to cognition (Herold et al., 2011;Shanahan et al., 2013;Herold et al., 2014;Colquitt et al., 2021;Kverková et al., 2022;Ströckens et al., 2022). Such comparisons can yield basic insights into the links between brain structure and function and offer the unprecedented chance of gaining deep conceptual insights into fundamental brain functions. ...
In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales— from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, to identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research.
... . However, comparisons of gene expression profiles and cell-type markers indicate that the HVC may be anatomically homologous to the LMC28,[30][31][32] . Modified, with permission, from Brainard and Doupe29 . ...
Juvenile male zebra finches (Taeniopygia guttata) must be exposed to an adult tutor during a sensitive period to develop normal adult song. The pre-motor nucleus HVC (acronym used as a proper name), plays a critical role in song learning and production (cf. Broca’s area in humans). In the human brain, left-side hemispheric dominance in some language regions is positively correlated with proficiency in linguistic skills. However, it is unclear whether this pattern depends upon language learning, develops with normal maturation of the brain, or is the result of pre-existing functional asymmetries. In juvenile zebra finches, even though both left and right HVC contribute to song production, baseline molecular activity in HVC is left-dominant. To test if HVC exhibits hemispheric dominance prior to song learning, we raised juvenile males in isolation from adult song and measured neuronal activity in the left and right HVC upon first exposure to an auditory stimulus. Activity in the HVC was measured using the immediate early gene (IEG) zenk (acronym for zif-268, egr-1, NGFI-a, and krox-24) as a marker for neuronal activity. We found that neuronal activity in the HVC of juvenile male zebra finches is not lateralized when raised in the absence of adult song, while normally-reared juvenile birds are left-dominant. These findings show that there is no pre-existing asymmetry in the HVC prior to song exposure, suggesting that lateralization of the song system depends on learning through early exposure to adult song and subsequent song-imitation practice.
... We chose these two song nuclei, while excluding the smaller LMAN and DLM nuclei in the AFP, to ensure an adequate collection of cells from individual birds for conducting snRNA-seq. Consistent with previous reports in ZFs (57,58), we identified marker genes representing specific cell types within the song nuclei and identified Area X medium spiny neurons (MSNs), Area X pallidal-like neurons, RA glutamatergic projection neurons (RAPNs), GABAergic neurons, astrocytes, microglia, oligodendrocytes, oligo precursor cells, and RA surrounding arcopallium glutamatergic neurons ( Fig. 4F and SI Appendix, Fig. S5). By examining single nucleotide polymorphism (SNP) variations in the transcripts of each cell, we associated the cellular transcripts with individual birds, and labeled these "cells" with a color scheme to match individuals in the uniform manifold approximation and projection (UMAP) plot (Fig. 4F). ...
The development of individuality during learned behavior is a common trait observed across animal species; however, the underlying biological mechanisms remain understood. Similar to human speech, songbirds develop individually unique songs with species-specific traits through vocal learning. In this study, we investigate the developmental and molecular mechanisms underlying individuality in vocal learning by utilizing F 1 hybrid songbirds ( Taeniopygia guttata cross with Taeniopygia bichenovii ), taking an integrating approach combining experimentally controlled systematic song tutoring, unbiased discriminant analysis of song features, and single-cell transcriptomics. When tutoring with songs from both parental species, F 1 hybrid individuals exhibit evident diversity in their acquired songs. Approximately 30% of F 1 hybrids selectively learn either song of the two parental species, while others develop merged songs that combine traits from both species. Vocal acoustic biases during vocal babbling initially appear as individual differences in songs among F 1 juveniles and are maintained through the sensitive period of song vocal learning. These vocal acoustic biases emerge independently of the initial auditory experience of hearing the biological father’s and passive tutored songs. We identify individual differences in transcriptional signatures in a subset of cell types, including the glutamatergic neurons projecting from the cortical vocal output nucleus to the hypoglossal nuclei, which are associated with variations of vocal acoustic features. These findings suggest that a genetically predisposed vocal motor bias serves as the initial origin of individual variation in vocal learning, influencing learning constraints and preferences.
... Given that evidence for neurons actively signaling the experienced absence of stimuli stem exclusively from primates, one hypothesis is that this way of implementing conscious percepts might have emerged with the advent of a mammalspecific and computationally powerful layered neocortex. Alternatively, this way of representing two subjective states by two specialized neuron populations may constitute a computational advantage that therefore might be implemented in other vertebrate classes, such as birds, with distinctly evolved endbrains (telencephala) lacking a cerebral cortex ( Jarvis et al., 2005) and neuronal circuits of distinct developmental origin (Colquitt, Merullo, Konopka, Roberts, & Brainard, 2021). Recently, we reported a neuronal correlate of perceptual consciousness in the associative endbrain area nidopallium caudolaterale (NCL) of carrion crows (Nieder et al., 2020). ...
The emergence of consciousness from brain activity constitutes one of the great riddles in biology. It is commonly assumed that only the conscious perception of the presence of a stimulus elicits neuronal activation to signify a “neural correlate of consciousness,” whereas the subjective experience of the absence of a stimulus is associated with a neuronal resting state. Here, we demonstrate that the two subjective states “stimulus present” and “stimulus absent” are represented by two specialized neuron populations in crows, corvid birds. We recorded single-neuron activity from the nidopallium caudolaterale of crows trained to report the presence or absence of images presented near the visual threshold. Because of the task design, neuronal activity tracking the conscious “present” versus “absent” percept was dissociated from that involved in planning a motor response. Distinct neuron populations signaled the subjective percepts of “present” and “absent” by increases in activation. The response selectivity of these two neuron populations was similar in strength and time course. This suggests a balanced code for subjective “presence” versus “absence” experiences, which might be beneficial when both conscious states need to be maintained active in the service of goal-directed behavior.
... It is easy to see that these models are quite often at odds with each other: While the field homology model sees, for example, the NCL as part of the avian amygdala since it is part of the ventral pallium, the cell type/circuit homology model could easily see it as cortical [47,115]. Colquitt et al. [116] offered a solution by studying neurons in two nuclei of the song system that are both located in the DVR. According to the field homology model, they should be part of the ventral pallium and therefore cannot be cortical. ...
Many cognitive neuroscientists believe that both a large brain and an isocortex are crucial for complex cognition. Yet corvids and parrots possess non-cortical brains of just 1–25 g, and these birds exhibit cognitive abilities comparable with those of great apes such as chimpanzees, which have brains of about 400 g. This opinion explores how this cognitive equivalence is possible. We propose four features that may be required for complex cognition: a large number of associative pallial neurons, a prefrontal cortex (PFC)-like area, a dense dopaminergic innervation of association areas, and dynamic neurophysiological fundaments for working memory. These four neural features have convergently evolved and may therefore represent ‘hard to replace’ mechanisms enabling complex cognition.
... Therefore, it is difficult to understand the homology of brain regions between different species by comparing the properties of the adult traits and terminal functional molecules alone. The results of recent single-cell RNA sequencing analyses strongly support the homologous relationship between the avian and mammalian brain regions described above, based on similarities such as the combinatorial profiles of transcription factors that determine cell properties (Tosches et al., 2018;Colquitt et al., 2021). ...
Serotonin (5-hydroxytryptamine, 5-HT) is a phylogenetically conserved neurotransmitter and modulator. Neurons utilizing serotonin have been identified in the central nervous systems of all vertebrates. In the central serotonergic system of vertebrate species examined so far, serotonergic neurons have been confirmed to exist in clusters in the brainstem. Although many serotonin-regulated cognitive, behavioral, and emotional functions have been elucidated in mammals, equivalents remain poorly understood in non-mammalian vertebrates. The purpose of this review is to summarize current knowledge of the anatomical organization and molecular features of the avian central serotonergic system. In addition, selected key functions of serotonin are briefly reviewed. Gene association studies between serotonergic system related genes and behaviors in birds have elucidated that the serotonergic system is involved in the regulation of behavior in birds similar to that observed in mammals. The widespread distribution of serotonergic modulation in the central nervous system and the evolutionary conservation of the serotonergic system provide a strong foundation for understanding and comparing the evolutionary continuity of neural circuits controlling corresponding brain functions within vertebrates. The main focus of this review is the chicken brain, with this type of poultry used as a model bird. The chicken is widely used not only as a model for answering questions in developmental biology and as a model for agriculturally useful breeding, but also in research relating to cognitive, behavioral, and emotional processes. In addition to a wealth of prior research on the projection relationships of avian brain regions, detailed subdivision similarities between avian and mammalian brains have recently been identified. Therefore, identifying the neural circuits modulated by the serotonergic system in avian brains may provide an interesting opportunity for detailed comparative studies of the function of serotonergic systems in mammals.
... This means that birds are so far the only animal model for studying the development and processing of speech information in the brain, which has greatly stimulated research within the field of comparative neuroanatomy and pallial evolution (Brenowitz et al., 1997;Brainard & Doupe, 2002;Jarvis, 2004;Nottebohm, 2005;Jarvis, 2019). Further, after more than 365 million years of separate evolution birds have evolved a different pallial (neocortical) brain organisation compared to mammals but show similar connectivity between relevant brain areas, neurochemical features, neuron numbers and gene expression profiles of cells that are functionally related to cognition (Herold et al., 2011;Shanahan et al., 2013;Herold et al., 2014;Colquitt et al., 2021;Kverková et al., 2022;Ströckens et al., 2022). Such comparisons can yield basic insights into the links between brain structure and function and offer the unprecedented chance of gaining deep conceptual insights into fundamental brain functions. ...
Brain research has in recent years indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modeling at multiple scales – from molecules to the whole system. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain integrates high-quality basic research, systematic data integration across multiple scales, a new culture of large-scale collaboration and translation into applications. A systematic approach, as pioneered in Europe’s Human Brain Project (HBP), will be essential in meeting the pressing medical and technological challenges of the coming decade. The aims of this paper are
To develop a concept for the coming decade of digital brain research
To discuss it with the research community at large, with the aim of identifying points of convergence and common goals
To provide a scientific framework for current and future development of EBRAINS
To inform and engage stakeholders, funding organizations and research institutions regarding future digital brain research
To identify and address key ethical and societal issues
While we do not claim that there is a ‘one size fits all’ approach to addressing these aspects, we are convinced that discussions around the theme of digital brain research will help drive progress in the broader field of neuroscience.
... from a mouse tissue transcription factor atlas 34 . A unique list of 471 TFs falling into fetal brain and adult brain tissue categories were retained for gene regulatory network analysis using an Arboreto and grnboost2 based approach 35 . First, raw counts corresponding to expressed (446/471) TFs was fetched separately for both dSPNs and iSPNs. ...
The striatum integrates dense neuromodulatory inputs from many brain regions to coordinate complex behaviors. This integration relies on the coordinated responses from distinct striatal cell types. While previous studies have characterized the cellular and molecular composition of the striatum using single-cell RNA-sequencing at distinct developmental timepoints, the molecular changes spanning embryonic through postnatal development at the single-cell level have not been examined. Here, we combine published mouse striatal single-cell datasets from both embryonic and postnatal timepoints to analyze the developmental trajectory patterns and transcription factor regulatory networks within striatal cell types. Using this integrated dataset, we found that dopamine receptor-1 expressing spiny projection neurons have an extended period of transcriptional dynamics and greater transcriptional complexity over postnatal development compared to dopamine receptor-2 expressing neurons. Moreover, we found the transcription factor, FOXP1, exerts indirect changes to oligodendrocytes. These data can be accessed and further analyzed through an interactive website (https://mouse-striatal-dev.cells.ucsc.edu).
... 81 Compared with the mammalian neocortex, the avian telencephalic integration centers originate from different pallial territories during embryology, 82 show distinct neural architectures, 83 and have evolved classes of excitatory and inhibitory pallial neurons that have no counterpart in the mammalian neocortex. [84][85][86] Despite all this independent brain evolution, crows and monkeys seem to be equipped with equivalent neuronal circuits that can flexibly represent abstract learned magnitude categories. 19,87 ...
The ability to group abstract continuous magnitudes into meaningful categories is cognitively demanding but key to intelligent behavior. To explore its neuronal mechanisms, we trained carrion crows to categorize lines of variable lengths into arbitrary "short" and "long" categories. Single-neuron activity in the nidopallium caudolaterale (NCL) of behaving crows reflected the learned length categories of visual stimuli. The length categories could be reliably decoded from neuronal population activity to predict the crows' conceptual decisions. NCL activity changed with learning when a crow was retrained with the same stimuli assigned to more categories with new boundaries ("short", "medium," and "long"). Categorical neuronal representations emerged dynamically so that sensory length information at the beginning of the trial was transformed into behaviorally relevant categorical representations shortly before the crows' decision making. Our data show malleable categorization capabilities for abstract spatial magnitudes mediated by the flexible networks of the crow NCL.
... Of these, only 31% of tissue-specific differences were consistent in expression among fish originating from three populations along the U.S. east coast. Even within a single organ, differences between cell types of that tissue can be substantial (Colquitt et al., 2021;Seyfferth et al., 2021). Therefore, it is necessary to have careful consideration of which tissue is chosen and acknowledgement of the limits of inference created by that choice. ...
Landscape transcriptomics is an emerging field studying how genome-wide expression patterns reflect dynamic landscape-scale environmental drivers, including habitat, weather, climate, and contaminants, and the subsequent effects on organismal function. This field is benefitting from advancing and increasingly accessible molecular technologies, which in turn are allowing the necessary characterization of transcriptomes from wild individuals distributed across natural landscapes. This research is especially important given the rapid pace of anthropogenic environmental change and potential impacts that span levels of biological organization. We discuss three major themes in landscape transcriptomic research: connecting transcriptome variation across landscapes to environmental variation, generating and testing hypotheses about the mechanisms and evolution of transcriptomic responses to the environment, and applying this knowledge to species conservation and management. We discuss challenges associated with this approach and suggest potential solutions. We conclude that landscape transcriptomics has great promise for addressing fundamental questions in organismal biology, ecology, and evolution, while providing tools needed for conservation and management of species.
... Recent advances in single-cell RNA sequencing (scRNA-seq) have had significant effects on the study of complex tissues, leading to the discovery of novel cell types, cell states, and biomarkers [Stuart and Satija, 2019;Luecken and Theis, 2019;Alfieri et al., 2022;Zeng, 2022]. The scRNA-seq technology has opened up a plethora of opportunities to perform novel studies using new and classic model animals, including chickens (Gallus gallus) [Yamagata, 2022] and other birds Colquitt et al., 2021]. A chicken cell atlas project (aka, Tabula Gallus) has been proposed to create a cell atlas of all tissues in the mature and developing chicken [Yamagata, 2022]. ...
The chicken continues to hold its position as a leading model organism within many areas of research, as well as a being major source of protein for human consumption. The First Report on Chicken Genes and Chromosomes [Schmid et al., 2000], which was published in 2000, was the brainchild of the late, and sadly missed, Prof Michael Schmid of the University of Würzburg. It was a publication bringing together updates on the latest research and resources in chicken genomics and cytogenetics. The success of this First report led to the subsequent publication of the Second [Schmid et al., 2005] and Third [Schmid et al., 2015] reports proving popular references for the research community. It is now our pleasure to be able to introduce publication of the Fourth report. Being seven years since the last report, this publication captures the many advances that have taken place during that time. This includes presentation of the detailed genomic resources that are now available, largely due to increasing capabilities of sequencing technologies and which herald the pangenomic age, allowing for a much richer and more complete knowledge of the avian genome. Ongoing cytogenetic work also allows for examination of chromosomes, specific elements within chromosomes and the evolutionary history and comparison of karyotypes. We also examine chicken research efforts with a much more ‘global’ outlook with a greater impact on food security and the impact of climate change, and highlight the efforts of international consortia, such as the Chicken Diversity Consortium. We dedicate this Report to Michael.
... Previous anatomical, cytological, and molecular studies of the brain have been conducted in cyclostomes and amniotes, including jawless fish (lampreys) (Lamanna et al., 2022), reptiles (turtles and lizards) (Tosches et al., 2018), birds (Colquitt et al., 2021), and mammals (mice and humans) (Hodge et al., 2019). These studies revealed conserved and species-specific cell type components pertaining to their divergent structural and functional evolution. ...
Animals plastically adjust their physiological and behavioural phenotypes to conform to their social environment—social niche conformance. The degree of sexual competition is a critical part of the social environment to which animals adjust their phenotypes, but the underlying genetic mechanisms are poorly understood. We conducted a study to investigate how differences in sperm competition risk affect the gene expression profiles of the testes and two brain areas (posterior pallium and optic tectum) in breeding male zebra finches ( Taeniopygia castanotis ). In this pre-registered study, we investigated a large sample of 59 individual transcriptomes. We compared two experimental groups: males held in single pairs (low sexual competition) versus those held in two pairs (elevated sexual competition) per breeding cage. Using weighted gene co-expression network analysis (WGCNA), we observed significant effects of the social treatment in all three tissues. However, only the treatment effects found in the pallium were confirmed by an additional randomisation test for statistical robustness. Likewise, the differential gene expression analysis revealed treatment effects only in the posterior pallium (ten genes) and optic tectum (six genes). No treatment effects were found in the testis at the single gene level. Thus, our experiments do not provide strong evidence for transcriptomic adjustment specific to manipulated sperm competition risk. However, we did observe transcriptomic adjustments to the manipulated social environment in the posterior pallium. These effects were polygenic rather than based on few individual genes with strong effects. Our findings are discussed in relation to an accompanying paper using the same animals, which reports behavioural results consistent with the results presented here.
The advanced cognitive abilities of birds rival those of mammals and have been attributed to evolutionary innovations in the pallium. However, a comprehensive cellular characterization of this brain region in birds has been lacking. We scrutinized the structures, cell types and evolutionary origins of the avian pallium based on single-cell and spatial transcriptomics atlases for the adult and developing chicken, and comparisons to corresponding data from mammals and non-avian reptiles. We found that the avian pallium shares most inhibitory neuron types with other amniotes. While excitatory neuron repertoires in the (medial) hippocampal formation show high conservation, they substantially diverged in other pallial regions during avian evolution, defining novel structures like the avian-specific (dorsal) hyperpallium, whose neuronal gene expression identities partly converge during late development with those of the (ventral) nidopallium. Our work also unveils the evolutionary relationships of pallial structures across amniotes, like the previously unknown homology between avian (lateral) mesopallial and mammalian deep layer cortical neurons.
One-Sentence Summary
An avian neural cell type atlas illuminates the developmental origins and evolution of the amniote pallium.
The efficiency of motor skill acquisition is age-dependent, making it increasingly challenging to learn complex maneuvers later in life. Zebra finches, for instance, acquire a complex vocal motor program during a developmental critical period after which the learned song is essentially impervious to modification. Although inhibitory interneurons are implicated in critical period closure, it is unclear whether manipulating them can reopen heightened motor plasticity windows. Using pharmacology and a novel cell-type specific optogenetic approach, we manipulated inhibitory neuron activity in a premotor area of adult zebra finches beyond their critical period. When exposed to auditory stimulation in the form of novel song, manipulated birds added new vocal syllables to their stable song sequence. By lifting inhibition in a premotor area during sensory experience, we reintroduced vocal plasticity, promoting an expansion of the syllable repertoire without compromising pre-existing song production. Our findings provide insights into motor skill learning capacities, offer potential for motor recovery after injury, and suggest avenues for treating neurodevelopmental disorders involving inhibitory dysfunctions.
The house wren shows complex song, and the rufous-tailed hummingbird has a simple song. The location of vocal brain areas supports the song’s complexity; however, these still need to be studied. The astrocytic population in songbirds appears to be associated with change in vocal control nuclei; however, astrocytic distribution and morphology have not been described in these species. Consequently, we compared the distribution and volume of the vocal brain areas: HVC, RA, Area X, and LMAN, cell density, and the morphology of astrocytes in the house wren and the rufous-tailed hummingbird. Individuals of the two species were collected, and their brains were analyzed using serial Nissl- NeuN- and MAP2-stained tissue scanner imaging, followed by 3D reconstructions of the vocal areas; and GFAP and S100β astrocytes were analyzed in both species. We found that vocal areas were located close to the cerebral midline in the house wren and a more lateralized position in the rufous-tailed hummingbird. The LMAN occupied a larger volume in the rufous-tailed hummingbird, while the RA and HVC were larger in the house wren. While Area X showed higher cell density in the house wren than the rufous-tailed hummingbird, the LMAN showed a higher density in the rufous-tailed hummingbird. In the house wren, GFAP astrocytes in the same bregma where the vocal areas were located were observed at the laminar edge of the pallium (LEP) and in the vascular region, as well as in vocal motor relay regions in the pallidum and mesencephalon. In contrast, GFAP astrocytes were found in LEP, but not in the pallidum and mesencephalon in hummingbirds. Finally, when comparing GFAP astrocytes in the LEP region of both species, house wren astrocytes exhibited significantly more complex morphology than those of the rufous-tailed hummingbird. These findings suggest a difference in the location and cellular density of vocal circuits, as well as morphology of GFAP astrocytes between the house wren and the rufous-tailed hummingbird.
Background:
The phylotypic or intermediate stages are thought to be the most evolutionary conserved stages throughout embryonic development. The contrast with divergent early and later stages derived from the concept of the evo-devo hourglass model. Nonetheless, this developmental constraint has been studied as a whole embryo process, not at organ level. In this review, we explore brain development to assess the existence of an equivalent brain developmental hourglass. In the specific case of vertebrates, we propose to split the brain developmental stages into: (1) Early: Neurulation, when the neural tube arises after gastrulation. (2) Intermediate: Brain patterning and segmentation, when the neuromere identities are established. (3) Late: Neurogenesis and maturation, the stages when the neurons acquire their functionality. Moreover, we extend this analysis to other chordates brain development to unravel the evolutionary origin of this evo-devo constraint.
Summary:
Based on the existing literature, we hypothesise that a major conservation of the phylotypic brain might be due to the pleiotropy of the inductive regulatory networks, which are predominantly expressed at this stage. In turn, earlier stages such as neurulation are rather mechanical processes, whose regulatory networks seem to adapt to environment or maternal geometries. The later stages are also controlled by inductive regulatory networks, but their effector genes are mostly tissue-specific and functional, allowing diverse developmental programs to generate current brain diversity. Nonetheless, all stages of the hourglass are highly interconnected: divergent neurulation must have a vertebrate shared end product to reproduce the vertebrate phylotypic brain, and the boundaries and transcription factor code established during the highly conserved patterning will set the bauplan for the specialised and diversified adult brain.
Key messages:
The vertebrate brain is conserved at phylotypic stages, but the highly conserved mechanisms that occur during these brain mid-development stages (Inducing Regulatory Networks) are also present during other stages. Oppositely, other processes as cell interactions and functional neuronal genes are more diverse and majoritarian in early and late stages of development, respectively. These phenomena create an hourglass of transcriptomic diversity during embryonic development and evolution, with a really conserved bottleneck that set the bauplan for the adult brain around the phylotypic stage.
Parvalbumin (PV) neurons play an integral role in regulating neural dynamics and plasticity. Therefore, understanding the factors that regulate PV expression is important for revealing modulators of brain function. While the contribution of PV neurons to neural processes has been studied in mammals, relatively little is known about PV function in non-mammalian species, and discerning similarities in the regulation of PV across species can provide insight into evolutionary conservation in the role of PV neurons. Here we investigated factors that affect the abundance of PV in PV neurons in sensory and motor circuits of songbirds and rodents. In particular, we examined the degree to which perineuronal nets (PNNs), extracellular matrices that preferentially surround PV neurons, modulate PV abundance as well as how the relationship between PV and PNN expression differs across brain areas and species and changes over development. We generally found that cortical PV neurons that are surrounded by PNNs (PV+PNN neurons) are more enriched with PV than PV neurons without PNNs (PV-PNN neurons) across both rodents and songbirds. Interestingly, the relationship between PV and PNN expression in the vocal portion of the basal ganglia of songbirds (Area X) differed from that in other areas, with PV+PNN neurons having lower PV expression compared to PV-PNN neurons. These relationships remained consistent across development in vocal motor circuits of the songbird brain. Finally, we discovered a causal contribution of PNNs to PV expression in songbirds because degradation of PNNs led to a diminution of PV expression in PV neurons. These findings reveal a conserved relationship between PV and PNN expression in sensory and motor cortices and across songbirds and rodents and suggest that PV neurons could modulate plasticity and neural dynamics in similar ways across songbirds and rodents.
Neuroscience courses can be enriched by including an evolutionary perspective. To that end, this essay identifies several concepts critical to understanding nervous system evolution and offers numerous examples that can be used to illustrate those concepts. One critical concept is that the distribution of features among today’s species can be used to reconstruct a feature’s evolutionary history, which then makes it possible to distinguish cases of homology from convergent evolution. Another key insight is that evolution did not simply add new features to old nervous systems, leaving the old features unchanged. Instead, both new and old features have changed, and they generally did so along divergent trajectories in different lineages, not in a linear sequence. Some changes in nervous system organization can be linked to selective pressures (i.e, adaptation), especially if they occurred convergently in different lineages. However, nervous system evolution has also been subject to various constraints, which is why many neural features are, in a sense, suboptimal. An overarching theme is that evolution has brought forth tremendous diversity across all levels of the nervous system and at all levels of organization, from molecules to neural circuits and behavior. This diversity provides excellent research opportunities, but it can also complicate the extrapolation of research findings across species.
Spiders are renowned for their efcient capture of fying insects using
intricate aerial webs. How the spider nervous systems evolved to cope with
this specialized hunting strategy and various environmental clues in an
aerial space remains unknown. Here we report a brain-cell atlas of >30,000
single-cell transcriptomes from a web-building spider (Hylyphantes
graminicola). Our analysis revealed the preservation of ancestral neuron
types in spiders, including the potential coexistence of noradrenergic and
octopaminergic neurons, and many peptidergic neuronal types that are lost
in insects. By comparing the genome of two newly sequenced plesiomorphic
burrowing spiders with three aerial web-building spiders, we found that the
positively selected genes in the ancestral branch of web-building spiders
were preferentially expressed (42%) in the brain, especially in the three
mushroom body-like neuronal types. By gene enrichment analysis and RNAi
experiments, these genes were suggested to be involved in the learning and
memory pathway and may infuence the spiders’ web-building and hunting
behaviour. Our results provide key sources for understanding the evolution
of behaviour in spiders and reveal how molecular evolution drives neuron
innovation and the diversifcation of associated complex behaviours.
Parvalbumin (PV) neurons play an integral role in regulating neural dynamics and plasticity. Therefore, understanding the factors that regulate PV expression is important for revealing modulators of brain function. While the contribution of PV neurons to neural processes has been studied in mammals, relatively little is known about PV function in non-mammalian species, and discerning similarities in the regulation of PV across species can provide insight into evolutionary conservation in the role of PV neurons. Here we investigated factors that affect the abundance of PV in PV neurons in sensory and motor circuits of songbirds and rodents. In particular, we examined the degree to which perineuronal nets (PNNs), extracellular matrices that preferentially surround PV neurons, modulate PV abundance as well as how the relationship between PV and PNN expression differs across brain areas and species and changes over development. We generally found that cortical PV neurons that are surrounded by PNNs (PV+PNN neurons) are more enriched with PV than PV neurons without PNNs (PV-PNN neurons) across both rodents and songbirds. Interestingly, the relationship between PV and PNN expression in the vocal portion of the basal ganglia of songbirds (Area X) differed from that in other areas, with PV+PNN neurons having lower PV expression compared to PV-PNN neurons. These relationships remained consistent across development in vocal motor circuits of the songbird brain. Finally, we discovered a causal contribution of PNNs to PV expression in songbirds because degradation of PNNs led to a diminution of PV expression in PV neurons. These findings in reveal a conserved relationship between PV and PNN expression in sensory and motor cortices and across songbirds and rodents and suggest that PV neurons could modulate plasticity and neural dynamics in similar ways across songbirds and rodents.
The telencephalon has undergone remarkable diversification and expansion throughout vertebrate evolution, exhibiting striking differences in structural and functional complexity. Nevertheless, fundamental features are shared across vertebrate taxa, such as the presence of distinct regions including the pallium, subpallium, and olfactory structures. Teleost fishes have a uniquely 'everted' telencephalon, which has made it challenging to compare brain regions in fish to those in other vertebrates. Here we combine spatial transcriptomics and single-nucleus RNA-sequencing to generate a spatially-resolved transcriptional atlas of the cichlid fish telencephalon. We then compare cell-types and anatomical regions in the cichlid telencephalon with those in amphibians, reptiles, birds, and mammals. We uncover striking transcriptional similarities between cell populations in the fish telencephalon and subpallial, hippocampal, and cortical cell populations in tetrapods. Ultimately, our work lends new insights into the organization and evolution of conserved cell-types and regions in the vertebrate forebrain.
Variations in size and complexity of the cerebral cortex result from differences in neuron number and composition, rooted in evolutionary changes in direct and indirect neurogenesis (dNG and iNG) that are mediated by radial glia and intermediate progenitors (IPs), respectively. How dNG and iNG differentially contribute to neuronal number, diversity, and connectivity are unknown. Establishing a genetic fate-mapping method to differentially visualize dNG and iNG in mice, we found that while both dNG and iNG contribute to all cortical structures, iNG contributes the largest relative proportions to the hippocampus and neocortex. Within the neocortex, whereas dNG generates all major glutamatergic projection neuron (PN) classes, iNG differentially amplifies and diversifies PNs within each class; the two pathways generate distinct PN types and assemble fine mosaics of lineage-based cortical subnetworks. Our results establish a ground-level lineage framework for understanding cortical development and evolution by linking foundational progenitor types and neurogenic pathways to PN types.
The mammalian entorhinal cortex routes inputs from diverse sources into the hippocampus. This information is mixed and expressed in the activity of many specialized entorhinal cell types, which are considered indispensable for hippocampal function. However, functionally similar hippocampi exist even in non-mammals that lack an obvious entorhinal cortex or, generally, any layered cortex. To address this dilemma, we mapped extrinsic hippocampal connections in chickadees, whose hippocampi are used for remembering numerous food caches. We found a well-delineated structure in these birds that is topologically similar to the entorhinal cortex and interfaces between the hippocampus and other pallial regions. Recordings of this structure revealed entorhinal-like activity, including border and multi-field grid-like cells. These cells were localized to the subregion predicted by anatomical mapping to match the dorsomedial entorhinal cortex. Our findings uncover an anatomical and physiological equivalence of vastly different brains, suggesting a fundamental nature of entorhinal-like computations for hippocampal function.
Maintaining motor skills is crucial for an animal’s survival, enabling it to endure diverse perturbations throughout its lifespan, such as trauma, disease, and aging. What mechanisms orchestrate brain circuit reorganization and recovery to preserve the stability of behavior despite the continued presence of a disturbance? To investigate this question, we chronically silenced inhibitory neurons, which altered brain activity and severely perturbed a complex learned behavior for around two months, after which it was precisely restored. Electrophysiology recordings revealed abnormal offline dynamics resulting from chronic inhibition loss, while subsequent recovery of the behavior occurred despite partial normalization of brain activity. Single-cell RNA sequencing revealed that chronic silencing of interneurons leads to elevated levels of microglia and MHC I. These experiments demonstrate that the adult brain can overcome extended periods of drastic abnormal activity. The reactivation of mechanisms employed during learning, including offline neuronal dynamics and upregulation of MHC I and microglia, could facilitate the recovery process following perturbation of the adult brain. These findings indicate that some forms of brain plasticity may persist in a dormant state in the adult brain, until they are recruited for circuit restoration.
Graphical Abstract
Schematic overview of the experiments performed in this study
To investigate how a complex motor behavior recovers after chronic loss of inhibitory tone, we blocked the function of zebra finch HVC inhibitory neurons by bilateral stereotaxic injection of an AAV viral vector into HVC. Throughout various timepoints in this perturbation paradigm, we recorded song behavioral data, electrophysiological measurements (chronic and acute within HVC), and measured changes in gene expression at single-cell resolution.
Cortical inhibitory interneurons form a broad spectrum of subtypes. This diversity suggests a division of labor, in which each cell type supports a distinct function. In the present era of optimisation-based algorithms, it is tempting to speculate that these functions were the evolutionary or developmental driving force for the spectrum of interneurons we see in the mature mammalian brain. In this study, we evaluated this hypothesis using the two most common interneuron types, parvalbumin (PV) and somatostatin (SST) expressing cells, as examples. PV and SST interneurons control the activity in the cell bodies and the apical dendrites of excitatory pyramidal cells, respectively, due to a combination of anatomical and synaptic properties. But was this compartment-specific inhibition indeed the function for which PV and SST cells originally evolved? Does the compartmental structure of pyramidal cells shape the diversification of PV and SST interneurons over development? To address these questions, we reviewed and reanalyzed publicly available data on the development and evolution of PV and SST interneurons on one hand, and pyramidal cell morphology on the other. These data speak against the idea that the compartment structure of pyramidal cells drove the diversification into PV and SST interneurons. In particular, pyramidal cells mature late, while interneurons are likely committed to a particular fate (PV vs. SST) during early development. Moreover, comparative anatomy and single cell RNA-sequencing data indicate that PV and SST cells, but not the compartment structure of pyramidal cells, existed in the last common ancestor of mammals and reptiles. Specifically, turtle and songbird SST cells also express the Elfn1 and Cbln4 genes that are thought to play a role in compartment-specific inhibition in mammals. PV and SST cells therefore evolved and developed the properties that allow them to provide compartment-specific inhibition before there was selective pressure for this function. This suggest that interneuron diversity originally resulted from a different evolutionary driving force and was only later co-opted for the compartment-specific inhibition it seems to serve in mammals today. Future experiments could further test this idea using our computational reconstruction of ancestral Elfn1 protein sequences.
Disruption of the transcription factor FoxP2, which is enriched in the basal ganglia, impairs vocal development in humans and songbirds. The basal ganglia are important for the selection and sequencing of motor actions, but the circuit mechanisms governing accurate sequencing of learned vocalizations are unknown. Here, we show that expression of FoxP2 in the basal ganglia is vital for the fluent initiation and termination of birdsong, as well as the maintenance of song syllable sequencing in adulthood. Knockdown of FoxP2 imbalances dopamine receptor expression across striatal direct-like and indirect-like pathways, suggesting a role of dopaminergic signaling in regulating vocal motor sequencing. Confirming this prediction, we show that phasic dopamine activation, and not inhibition, during singing drives repetition of song syllables, thus also impairing fluent initiation and termination of birdsong. These findings demonstrate discrete circuit origins for the dysfluent repetition of vocal elements in songbirds, with implications for speech disorders.
Background
Droplet-based single-cell RNA sequence analyses assume that all acquired RNAs are endogenous to cells. However, any cell-free RNAs contained within the input solution are also captured by these assays. This sequencing of cell-free RNA constitutes a background contamination that confounds the biological interpretation of single-cell transcriptomic data.
Results
We demonstrate that contamination from this "soup" of cell-free RNAs is ubiquitous, with experiment-specific variations in composition and magnitude. We present a method, SoupX, for quantifying the extent of the contamination and estimating "background-corrected" cell expression profiles that seamlessly integrate with existing downstream analysis tools. Applying this method to several datasets using multiple droplet sequencing technologies, we demonstrate that its application improves biological interpretation of otherwise misleading data, as well as improving quality control metrics.
Conclusions
We present SoupX, a tool for removing ambient RNA contamination from droplet-based single-cell RNA sequencing experiments. This tool has broad applicability, and its application can improve the biological utility of existing and future datasets.
Adult male zebra finches (Taeniopygia guttata) continually incorporate adult-born neurons into HVC, a telencephalic brain region necessary for the production of learned song. These neurons express immediate early genes following song production, suggesting a role for neurogenesis in song production throughout the lifespan. Half of these adult-born HVC neurons (HVC NNs) send their axons to RA as part of the vocal motor pathway underlying learned song production, but the other half do not, and their identity remains unknown. Here we used cell birth-dating, retrograde tract tracing, and immunofluorescence to demonstrate that half of all HVC NNs express the neuron-specific phosphoprotein DARPP-32, a protein associated with DA receptor expression. We also demonstrate that DARPP-32+ HVC NNs are contacted by tyrosine hydroxylase immunoreactive fibers suggesting that they receive catecholaminergic input, are transiently larger than DARPP-32-negative HVC NNs, and do not send axons to RA as part of the vocal motor pathway. Taken together, these findings indicate the existence of a class of HVC NNs that do not project to RA and may constitute the aforementioned unknown half of all HVC NNs.
Acetylcholine is well-understood to enhance cortical sensory responses and perceptual sensitivity in aroused or attentive states. Yet little is known about cholinergic influences on motor cortical regions. Here we use the quantifiable nature of birdsong to investigate how acetylcholine modulates the cortical (pallial) premotor nucleus HVC and shapes vocal output. We found that dialyzing the cholinergic agonist carbachol into HVC increased the pitch, amplitude, tempo and stereotypy of song, similar to the natural invigoration of song that occurs when males direct their songs to females. These carbachol-induced effects were associated with increased neural activity in HVC and occurred independently of basal ganglia circuitry. Moreover, we discovered that the normal invigoration of female-directed song was also accompanied by increased HVC activity and was attenuated by blocking muscarinic acetylcholine receptors. These results indicate that, analogous to its influence on sensory systems, acetylcholine can act directly on cortical premotor circuitry to adaptively shape behavior.
Production of learned vocalizations requires precise selection and accurate sequencing of appropriate vocal-motor actions. The basal ganglia are essential for the selection and sequencing of motor actions, but the cellular specializations and circuit mechanisms governing accurate sequencing of vocalizations are unknown. Here, we use single-nucleus RNA sequencing and genetic manipulations to map basal ganglia cell types and circuits involved in the production of songbird vocal sequences. We identify cell-type specializations in direct-like and indirect-like basal ganglia pathways, including evolutionary expansion of striatal and arkypallidal cell-types that could facilitate vocal sequencing. Surprisingly, we find that FoxP2, a gene important for vocal development, can potently and reversibly control accurate sequencing of adult birdsong, and that phasic dopamine selectively regulates repetition of syllables independent of its role in reinforcement-based learning of how they are sung. These findings identify key evolutionary specializations and circuits essential for selection and sequencing of vocal-motor actions necessary for vocal communication.
The mammalian claustrum, owing to its widespread connectivity with other forebrain structures, has been hypothesized to mediate functions that range from decision-making to consciousness¹. Here we report that a homologue of the claustrum, identified by single-cell transcriptomics and viral tracing of connectivity, also exists in a reptile—the Australian bearded dragon Pogona vitticeps. In Pogona, the claustrum underlies the generation of sharp waves during slow-wave sleep. The sharp waves, together with superimposed high-frequency ripples², propagate to the entire neighbouring pallial dorsal ventricular ridge (DVR). Unilateral or bilateral lesions of the claustrum suppress the production of sharp-wave ripples during slow-wave sleep in a unilateral or bilateral manner, respectively, but do not affect the regular and rapidly alternating sleep rhythm that is characteristic of sleep in this species³. The claustrum is thus not involved in the generation of the sleep rhythm itself. Tract tracing revealed that the reptilian claustrum projects widely to a variety of forebrain areas, including the cortex, and that it receives converging inputs from, among others, areas of the mid- and hindbrain that are known to be involved in wake–sleep control in mammals4,5,6. Periodically modulating the concentration of serotonin in the claustrum, for example, caused a matching modulation of sharp-wave production there and in the neighbouring DVR. Using transcriptomic approaches, we also identified a claustrum in the turtle Trachemys scripta, a distant reptilian relative of lizards. The claustrum is therefore an ancient structure that was probably already present in the brain of the common vertebrate ancestor of reptiles and mammals. It may have an important role in the control of brain states owing to the ascending input it receives from the mid- and hindbrain, its widespread projections to the forebrain and its role in sharp-wave generation during slow-wave sleep.
Single-cell RNA-seq (scRNA-seq) data exhibits significant cell-to-cell variation due to technical factors, including the number of molecules detected in each cell, which can confound biological heterogeneity with technical effects. To address this, we present a modeling framework for the normalization and variance stabilization of molecular count data from scRNA-seq experiments. We propose that the Pearson residuals from "regularized negative binomial regression," where cellular sequencing depth is utilized as a covariate in a generalized linear model, successfully remove the influence of technical characteristics from downstream analyses while preserving biological heterogeneity. Importantly, we show that an unconstrained negative binomial model may overfit scRNA-seq data, and overcome this by pooling information across genes with similar abundances to obtain stable parameter estimates. Our procedure omits the need for heuristic steps including pseudocount addition or log-transformation and improves common downstream analytical tasks such as variable gene selection, dimensional reduction, and differential expression. Our approach can be applied to any UMI-based scRNA-seq dataset and is freely available as part of the R package sctransform, with a direct interface to our single-cell toolkit Seurat.
The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony (https://github.com/immunogenomics/harmony), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~10⁶ cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data.
Significance
We addressed the question, “How do corticobasal ganglia projecting neurons contribute to vocal learning?” We performed specific ablation of the vocal cortical neurons projecting to the basal ganglia, HVC (X) neurons in a songbird, which generate temporally precise firing during singing. Specific ablation of HVC (X) neurons in juveniles caused deficits in learning the tutor song’s acoustics and less consistency of song sequence. In contrast, adult HVC (X) neuron ablation did not affect the degree of vocal fluctuations or cause alteration in song structure by auditory feedback inhibition. These results support the hypothesis that HVC (X) neurons are a neural substrate for transferring temporal signals, but not for regulating vocal fluctuations or conveying auditory feedback, to the basal ganglia for vocal learning and maintenance.
Although language, and therefore spoken language or speech, is often considered unique to humans, the past several decades have seen a surge in nonhuman animal studies that inform us about human spoken language. Here, I present a modern, evolution-based synthesis of these studies, from behavioral to molecular levels of analyses. Among the key concepts drawn are that components of spoken language are continuous between species, and that the vocal learning component is the most specialized and rarest and evolved by brain pathway duplication from an ancient motor learning pathway. These concepts have important implications for understanding brain mechanisms and disorders of spoken language.
In the adult rodent brain, neural stem cells (NSCs) persist in the ventricular-subventricular zone (V-SVZ) and the subgranular zone (SGZ), which are specialized niches in which young neurons for the olfactory bulb (OB) and hippocampus, respectively, are generated. Recent studies have significantly modified earlier views on the mechanisms of NSC self-renewal and neurogenesis in the adult brain. Here, we discuss the molecular control, heterogeneity, regional specification and cell division modes of V-SVZ NSCs, and draw comparisons with NSCs in the SGZ. We highlight how V-SVZ NSCs are regulated by local signals from their immediate neighbors, as well as by neurotransmitters and factors that are secreted by distant neurons, the choroid plexus and vasculature. We also review recent advances in single cell RNA analyses that reveal the complexity of adult neurogenesis. These findings set the stage for a better understanding of adult neurogenesis, a process that one day may inspire new approaches to brain repair.
Songbirds communicate through learned vocalizations, using a forebrain circuit with convergent similarity to vocal-control circuitry in humans. This circuit is incomplete in female zebra finches, hence only males sing. We show that the UTS2B gene, encoding Urotensin-Related Peptide (URP), is uniquely expressed in a key pre-motor vocal nucleus (HVC), and specifically marks the neurons that form a male-specific projection that encodes timing features of learned song. UTS2B-expressing cells appear early in males, prior to projection formation, but are not observed in the female nucleus. We find no expression evidence for canonical receptors within the vocal circuit, suggesting either signalling to other brain regions via diffusion or transduction through other receptor systems. Urotensins have not previously been implicated in vocal control, but we find an annotation in Allen Human Brain Atlas of increased UTS2B expression within portions of human inferior frontal cortex implicated in human speech and singing. Thus UTS2B (URP) is a novel neural marker that may have conserved functions for vocal communication.
eggNOG is a public database of orthology relationships, gene evolutionary histories and functional annotations. Here, we present version 5.0, featuring a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes, as well as 477 eukaryotic organisms and 2502 viral proteomes that were selected for diversity and filtered by genome quality. In total, 4.4M orthologous groups (OGs) distributed across 379 taxonomic levels were computed together with their associated sequence alignments, phylogenies, HMM models and functional descriptors. Precomputed evolutionary analysis provides fine-grained resolution of duplication/speciation events within each OG. Our benchmarks show that, despite doubling the amount of genomes, the quality of orthology assignments and functional annotations (80% coverage) has persisted without significant changes across this update. Finally, we improved eggNOG online services for fast functional annotation and orthology prediction of custom genomics or metagenomics datasets. All precomputed data are publicly available for downloading or via API queries at http://eggnog.embl.de.
The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.
The cultural transmission of behaviour depends on the ability of the pupil to identify and emulate an appropriate tutor1–4. How the brain of the pupil detects a suitable tutor and encodes the behaviour of the tutor is largely unknown. Juvenile zebra finches readily copy the songs of the adult tutors that they interact with, but not the songs that they listen to passively through a speaker5,6, indicating that social cues generated by the tutor facilitate song imitation. Here we show that neurons in the midbrain periaqueductal grey of juvenile finches are selectively excited by a singing tutor and—by releasing dopamine in the cortical song nucleus HVC—help to encode the song representations of the tutor used for vocal copying. Blocking dopamine signalling in the HVC of the pupil during tutoring blocked copying, whereas pairing stimulation of periaqueductal grey terminals in the HVC with a song played through a speaker was sufficient to drive copying. Exposure to a singing tutor triggered the rapid emergence of responses to the tutor song in the HVC of the pupil and a rapid increase in the complexity of the song of the pupil, an early signature of song copying7,8. These findings reveal that a dopaminergic mesocortical circuit detects the presence of a tutor and helps to encode the performance of the tutor, facilitating the cultural transmission of vocal behaviour.
The mammalian nervous system executes complex behaviors controlled by specialized, precisely positioned, and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse and were grouped by developmental anatomical units and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission, and membrane conductance. We discovered seven distinct, regionally restricted astrocyte types that obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system and enables genetic manipulation of specific cell types.
Author summary
The “big-data revolution” has struck biology: it is now common for robots to prepare cell samples and take thousands of microscopy images. Looking at the resulting images by eye would be extremely tedious, not to mention subjective. Thus, many biologists find they need software to analyze images easily and accurately. The third major release of our free open-source software CellProfiler is designed to help biologists working with images, whether a few or thousands. Researchers can download an online example workflow (that is, a “pipeline”) or create their own from scratch. Pipelines are easy to save, reuse, and share, helping improve scientific reproducibility. In this release, we’ve added the capability to find and measure objects in three-dimensional (3D) images. We’ve also made changes to CellProfiler’s underlying code to make it faster to run and easier to install, and we’ve added the ability to process images in the cloud and using neural networks (deep learning). We’ve also added more explanations to CellProfiler’s settings to help new users get started. We hope these changes will make CellProfiler an even better tool for current users and will provide new users better ways to get started doing quantitative image analysis.
Evolution of the brain
Just how related are reptilian and mammalian brains? Tosches et al. used single-cell transcriptomics to study turtle, lizard, mouse, and human brain samples. They assessed how the mammalian six-layered cortex might be derived from the reptilian three-layered cortex. Despite a lack of correspondence between layers, mammalian astrocytes and adult neural stem cells shared evolutionary origins. General classes of interneuron types were represented across the evolutionary span, although subtypes were species-specific. Pieces of the much-folded mammalian hippocampus were represented as adjacent fields in the reptile brains.
Science , this issue p. 881
Background
Vocal learning in songbirds has emerged as a powerful model for sensorimotor learning. Neuro-behavioral studies of Bengalese finch (Lonchura striata domestica) song, naturally more variable and plastic than songs of other finch species, have demonstrated the importance of behavioral variability for initial learning, maintenance, and plasticity of vocalizations. However, the molecular and genetic underpinnings of this variability, and the learning it supports, are poorly understood.
Findings
To establish a platform for the molecular analysis of behavioral variability and plasticity, we have generated an initial draft assembly of the Bengalese finch genome from a single male animal to 151x coverage and an N50 of 3.0 MB. Furthermore, we have developed an initial set of gene models using RNA-seq data from eight samples that comprise liver, muscle, cerebellum, brainstem/midbrain and forebrain tissue from juvenile and adult Bengalese finches of both sexes.
Conclusions
We provide a draft Bengalese finch genome and gene annotation to facilitate the study of the molecular-genetic influences on behavioral variability and the process of vocal learning. These data will directly support many avenues for the identification of genes involved in learning, including differential expression analysis, comparative genomic analysis (through comparison to existing avian genome assemblies), and derivation of genetic maps for linkage analysis. Bengalese finch gene models and sequences will be essential for subsequent manipulation (molecular or genetic) of genes and gene products, enabling novel mechanistic investigations into the role of variability in learned behavior.
Skill learning is instantiated by changes to functional connectivity within premotor circuits, but whether the specificity of learning depends on structured changes to inhibitory circuitry remains unclear. We used slice electrophysiology to measure connectivity changes associated with song learning in the avian analog of primary motor cortex (robust nucleus of the arcopallium, RA) in Bengalese Finches. Before song learning, fast-spiking interneurons (FSIs) densely innervated glutamatergic projection neurons (PNs) with apparently random connectivity. After learning, there was a profound reduction in the overall strength and number of inhibitory connections, but this was accompanied by a more than two-fold enrichment in reciprocal FSI-PN connections. Moreover, in singing birds, we found that pharmacological manipulations of RA's inhibitory circuitry drove large shifts in learned vocal features, such as pitch and amplitude, without grossly disrupting the song. Our results indicate that skill learning establishes nonrandom inhibitory connectivity, and implicates this patterning in encoding specific features of learned movements.
Quality Control (QC) and preprocessing are essential steps for sequencing data analysis to ensure the accuracy of results. However, existing tools cannot provide a satisfying solution with integrated comprehensive functions, proper architectures and highly-scalable acceleration. In this article, we demonstrate SOAPnuke as a tool with abundant functions for a “QC-Preprocess-QC” workflow and MapReduce acceleration framework. Four modules with different preprocessing functions are designed for processing datasets from genomic, small RNA (sRNA), Digital Gene Expression (DGE) and metagenomic experiments respectively. As a workflow-like tool, SOAPnuke centralizes processing functions in one executable and predefine their order to avoid the necessity of reformatting different files when switching tools. Furthermore, the MapReduce framework enables large scalability to distribute all the processing works to an entire compute cluster.
We conducted a benchmarking where SOAPnuke and other tools are used to preprocess ∼30x NA12878 dataset published by GIAB. The standalone operation of SOAPnuke struck a balance between resource occupancy and performance. When accelerated on 16 working nodes with MapReduce, SOAPnuke achieved ∼5.7 times of the fastest speed of other tools.
Cortical interneurons are a diverse group of neurons that project locally and are crucial for regulating information processing and flow throughout the cortex. Recent studies in mice have advanced our understanding of how these neurons are specified, migrate and mature. Here, we evaluate new findings that provide insights into the development of cortical interneurons and that shed light on when their fate is determined, on the influence that regional domains have on their development, and on the role that key transcription factors and other crucial regulatory genes play in these events. We focus on cortical interneurons that are derived from the medial ganglionic eminence, as most studies have examined this interneuron population. We also assess how these data inform our understanding of neuropsychiatric disease and discuss the potential role of cortical interneurons in cellbased therapies.
Although single-cell RNA-seq is revolutionizing biology, data interpretation remains a challenge. We present SCENIC for the simultaneous reconstruction of gene regulatory networks and identification of cell states. We apply SCENIC to a compendium of single-cell data from tumors and brain, and demonstrate that the genomic regulatory code can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.
Nectin-3, a cell adhesion molecule enriched in hippocampal neurons, has been implicated in stress-related cognitive disorders. Nectin-3 is expressed by granule cells in the dentate gyrus (DG), but it remains unclear whether nectin-3 in DG modulates the structural plasticity of dentate granule cells and hippocampus-dependent memory. In this study, we found that DG nectin-3 expression levels were developmentally regulated and reduced by early postnatal stress exposure in adult mice. Most importantly, knockdown of nectin-3 levels in all DG neuron populations by adeno-associated virus (AAV) mimicked the cognitive effects of early-life stress, and impaired long-term spatial memory and temporal order memory. Moreover, AAV-mediated DG nectin-3 knockdown increased the density of doublecortin-immunoreactive differentiating cells under proliferation and calretinin-immunoreactive immature neurons, but markedly decreased calbindin immunoreactivity, indicating that nectin-3 modulates the differentiation and maturation of adult-born DG granule cells. Using retrovirus to target newly generated DG neurons, we found that selective nectin-3 knockdown in new DG neurons also impaired long-term spatial memory. In addition, suppressing nectin-3 expression in new DG neurons evoked a reduction of dendritic spines, especially thin spines. Our data indicate that nectin-3 expressed in DG neurons may modulate adult neurogenesis, dendritic spine plasticity and the cognitive effects of early-life stress.
Orthology assignment is ideally suited for functional inference. However, because predicting orthology is computationally intensive at large scale, and most pipelines are relatively inaccessible (e.g. new assignments only available through database updates), less precise homology-based functional transfer is still the default for (meta-)genome annotation. We therefore developed eggNOG-mapper, a tool for functional annotation of large sets of sequences based on fast orthology assignments using precomputed clusters and phylogenies from the eggNOG database. To validate our method, we benchmarked Gene Ontology predictions against two widely used homology-based approaches: BLAST and InterProScan. Orthology filters applied to BLAST results reduced the rate of false positive assignments by 11%, and increased the ratio of experimentally validated terms recovered over all terms assigned per protein by 15%. Compared to InterProScan, eggNOG-mapper achieved similar proteome coverage and precision while predicting, on average, 41 more terms per protein and increasing the rate of experimentally validated terms recovered over total term assignments per protein by 35%. EggNOG-mapper predictions scored within the top-5 methods in the three Gene Ontology categories using the CAFA2 NK-partial benchmark. Finally, we evaluated eggNOG-mapper for functional annotation of metagenomics data, yielding better performance than interProScan. eggNOG-mapper runs ∼15x faster than BLAST and at least 2.5x faster than InterProScan. The tool is available standalone and as an online service at http://eggnog-mapper.embl.de.
The pallium of birds and reptiles is analyzed in detail with regard to the classification of its natural subdivisions on the basis of the tetrapartite pallium model proposed in 2014 by the first author. The possibility to use genoarchitectural data for this task is connected with the fundamental criteria of homology, namely conserved topological position within a Bauplan and conserved developmental makeup. It is argued that systematic employment of a model facilitates the production of homology hypothesis. The case of the sauropsidian claustrum and insula is detailed. Finally, comments are offered about how models should be improved and on some recent publications discussed in this context. Informative figures accompany the text step by step.
Among the extant vertebrates, nonavian reptiles are probably those that are most closely related to the first animals to evolve a clearly layered cerebral cortex. Thus, a good understanding of the structure and connections of reptilian cortex is critical to understanding cortical evolution. We review the cellular and functional architecture of reptilian brains and aim to identify knowledge gaps and promising avenues for research using novel techniques and diverse species. We argue that analyzing the simpler cortical circuits of reptiles is, besides being useful to understanding cortical evolution, of central importance to understanding cortical function in general.
The principle of homology is central to conceptualizing the comparative aspects of morphological evolution. The distinctions between homologous or non-homologous structures have become blurred, however, as modern evolutionary developmental biology (evo-devo) has shown that novel features often result from modification of pre-existing developmental modules, rather than arising completely de novo. With this realization in mind, the term ‘deep homology’ was coined, in recognition of the remarkably conserved gene expression during the development of certain animal structures that would not be considered homologous by previous strict definitions. At its core, it can help to formulate an understanding of deeper layers of ontogenetic conservation for anatomical features that lack any clear phylogenetic continuity. Here, we review deep homology and related concepts in the context of a gene expression-based homology discussion. We then focus on how these conceptual frameworks have profited from the recent rise of high-throughput next-generation sequencing. These techniques have greatly expanded the range of organisms amenable to such studies. Moreover, they helped to elevate the traditional gene-by-gene comparison to a transcriptome-wide level. We will end with an outlook on the next challenges in the field and how technological advances might provide exciting new strategies to tackle these questions.
This article is part of the themed issue ‘Evo-devo in the genomics era, and the origins of morphological diversity’.
The lamprey belongs to the phylogenetically oldest group of vertebrates that diverged from the mammalian evolutionary line 560 million years ago. A comparison between the lamprey and mammalian basal ganglia establishes a detailed similarity regarding its input from cortex/pallium and thalamus, as well as its intrinsic organisation and projections of the output nuclei. This means that the basal ganglia circuits now present in rodents and primates most likely had evolved already at the dawn of vertebrate evolution. This includes the 'direct pathway' with striatal projection neurons (SPNs) expressing dopamine D1 receptors, which act to inhibit the tonically active GABAergic output neurons in globus pallidus interne and substantia nigra pars reticulate that at rest keep the brainstem motor centres under tonic inhibition. The 'indirect pathway' with dopamine D2 receptor-expressing SPNs and intrinsic basal ganglia nuclei is also conserved. The net effect of the direct pathway is to disinhibit brainstem motor centres and release motor programs, while the indirect pathway instead will suppress motor activity. Transmitters, connectivity and membrane properties are virtually identical in lamprey and rodent basal ganglia. We predict that the basal ganglia contains a series of modules each controlling a given pattern of behaviour including locomotion, eye-movements, posture, and chewing that contain both the direct pathway to release a motor program and the indirect pathway to inhibit competing behaviours. The phasic dopamine input serves value-based decisions and motor learning. During vertebrate evolution with a progressively more diverse motor behaviour, the number of modules will have increased progressively. These new modules with a similar design will be used to control newly developed patterns of behaviour a process referred to as exaptation.
Sequential activation of neurons has been observed during various behavioral and cognitive processes, but the underlying circuit mechanisms remain poorly understood. Here, we investigate premotor sequences in HVC (proper name) of the adult zebra finch forebrain that are central to the performance of the temporally precise courtship song. We use high-density silicon probes to measure song-related population activity, and we compare these observations with predictions from a range of network models. Our results support a circuit architecture in which heterogeneous delays between sequentially active neurons shape the spatiotemporal patterns of HVC premotor neuron activity. We gauge the impact of several delay sources, and we find the primary contributor to be slow conduction through axonal collaterals within HVC, which typically adds between 1 and 7.5 ms for each link within the sequence. Thus, local axonal “delay lines” can play an important role in determining the dynamical repertoire of neural circuits.
Homology—a similar trait shared by different species and derived from common ancestry, such as a seal's fin and a bird's wing—is one of the most fundamental yet challenging concepts in evolutionary biology. This book provides the first mechanistically based theory of what homology is and how it arises in evolution. The book argues that homology, or character identity, can be explained through the historical continuity of character identity networks—that is, the gene regulatory networks that enable differential gene expression. It shows how character identity is independent of the form and function of the character itself because the same network can activate different effector genes and thus control the development of different shapes, sizes, and qualities of the character. Demonstrating how this theoretical model can provide a foundation for understanding the evolutionary origin of novel characters, the book applies it to the origin and evolution of specific systems, such as cell types; skin, hair, and feathers; limbs and digits; and flowers. The first major synthesis of homology to be published in decades, this book reveals how a mechanistically based theory can serve as a unifying concept for any branch of science concerned with the structure and development of organisms, and how it can help explain major transitions in evolution and broad patterns of biological diversity.
Basic principles of bird and mammal brains
Mammals can be very smart. They also have a brain with a cortex. It has thus often been assumed that the advanced cognitive skills of mammals are closely related to the evolution of the cerebral cortex. However, birds can also be very smart, and several bird species show amazing cognitive abilities. Although birds lack a cerebral cortex, they do have pallium, and this is considered to be analogous, if not homologous, to the cerebral cortex. An outstanding feature of the mammalian cortex is its layered architecture. In a detailed anatomical study of the bird pallium, Stacho et al. describe a similarly layered architecture. Despite the nuclear organization of the bird pallium, it has a cyto-architectonic organization that is reminiscent of the mammalian cortex.
Science , this issue p. eabc5534
Much is conserved in vertebrate evolution, but significant changes in the nervous system occurred at the origin of vertebrates and in most of the major vertebrate lineages. This book examines these innovations and relates them to evolutionary changes in other organ systems, animal behavior, and ecological conditions at the time. The resulting perspective clarifies what makes the major vertebrate lineages unique and helps explain their varying degrees of ecological success. One of the book’s major conclusions is that vertebrate nervous systems are more diverse than commonly assumed, at least among neurobiologists. Examples of important innovations include not only the emergence of novel brain regions, such as the cerebellum and neocortex, but also major changes in neuronal circuitry and functional organization. A second major conclusion is that many of the apparent similarities in vertebrate nervous systems resulted from convergent evolution, rather than inheritance from a common ancestor. For example, brain size and complexity increased numerous times, in many vertebrate lineages. In conjunction with these changes, olfactory inputs to the telencephalic pallium were reduced in several different lineages, and this reduction was associated with the emergence of pallial regions that process non-olfactory sensory inputs. These conclusions cast doubt on the widely held assumption that all vertebrate nervous systems are built according to a single, common plan. Instead, the book encourages readers to view both species similarities and differences as fundamental to a comprehensive understanding of nervous systems.
Although neuroscientists focus on only very few animal species today, there are many important reasons to take advantage of model system diversity and embrace (anew) a comparative approach in modern brain research. Recent technological advances make this increasingly possible.
Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
FOXP transcription factors are an evolutionarily ancient protein subfamily coordinating the development of several organ systems in the vertebrate body. Association of their genes with neurodevelopmental disorders has sparked particular interest in their expression patterns and functions in the brain. Here, FOXP1, FOXP2, and FOXP4 are expressed in distinct cell type‐specific spatiotemporal patterns in multiple regions, including the cortex, hippocampus, amygdala, basal ganglia, thalamus, and cerebellum. These varied sites and timepoints of expression have complicated efforts to link FOXP1 and FOXP2 mutations to their respective developmental disorders, the former affecting global neural functions and the latter specifically affecting speech and language. However, the use of animal models, particularly those with brain region‐ and cell type‐specific manipulations, has greatly advanced our understanding of how FOXP expression patterns could underlie disorder‐related phenotypes. While many questions remain regarding FOXP expression and function in the brain, studies to date have illuminated the roles of these transcription factors in vertebrate brain development and have greatly informed our understanding of human development and disorders.
This article is categorized under:
• Nervous System Development > Vertebrates: General Principles
• Gene Expression and Transcriptional Hierarchies > Gene Networks and Genomics
• Nervous System Development > Vertebrates: Regional Development
The dramatic evolutionary expansion of the neocortex, together with a proliferation of specialized cortical areas, is believed to underlie the emergence of human cognitive abilities. In a broader phylogenetic context, however, neocortex evolution in mammals, including humans, is remarkably conservative, characterized largely by size variations on a shared six-layered neuronal architecture. By contrast, the telencephalon in non-mammalian vertebrates, including reptiles, amphibians, bony and cartilaginous fishes, and cyclostomes, features a great variety of very different tissue structures. Our understanding of the evolutionary relationships of these telencephalic structures, especially those of basally branching vertebrates and invertebrate chordates, remains fragmentary and is impeded by conceptual obstacles. To make sense of highly divergent anatomies requires a hierarchical view of biological organization, one that permits the recognition of homologies at multiple levels beyond neuroanatomical structure. Here we review the origin and diversification of the telencephalon with a focus on key evolutionary innovations shaping the neocortex at multiple levels of organization.
To understand neocortex evolution, we must define a theory for the elaboration of cell types, circuits, and architectonics from an ancestral structure that is consistent with developmental, molecular, and genetic data. To this end, cross-species comparison of cortical cell types emerges as a very informative approach. We review recent results that illustrate the contribution of molecular and transcriptomic data to the construction of plausible models of cortical cell-type evolution.
Inferring a Gene Regulatory Network (GRN) from gene expression data is a computationally expensive task, exacerbated by increasing data sizes due to advances in high-throughput gene profiling technology, such as single-cell RNA-seq. To equip researchers with a toolset to infer GRNs from large expression datasets, we propose GRNBoost2 and the Arboreto framework. GRNBoost2 is an efficient algorithm for regulatory network inference using gradient boosting, based on the GENIE3 architecture. Arboreto is a computational framework that scales up GRN inference algorithms complying with this architecture. Arboreto includes both GRNBoost2 and an improved implementation of GENIE3, as a user-friendly open source Python package.
Availability:
Arboreto is available under the 3-Clause BSD license at http://arboreto.readthedocs.io.
Supplementary information:
Supplementary data are available at Bioinformatics online.
In the cerebral cortex, GABAergic interneurons have evolved as a highly heterogeneous collection of cell types that are characterized by their unique spatial and temporal capabilities to influence neuronal circuits. Current estimates suggest that up to 50 different types of GABAergic neurons may populate the cerebral cortex, all derived from progenitor cells in the subpallium, the ventral aspect of the embryonic telencephalon. In this review, we provide an overview of the mechanisms underlying the generation of the distinct types of interneurons and their integration in cortical circuits. Interneuron diversity seems to emerge through the implementation of cell-intrinsic genetic programs in progenitor cells, which unfold over a protracted period of time until interneurons acquire mature characteristics. The developmental trajectory of interneurons is also modulated by activity-dependent, non-cell-autonomous mechanisms that influence their ability to integrate in nascent circuits and sculpt their final distribution in the adult cerebral cortex. GABAergic interneurons are critical for information processing in the cerebral cortex. Here, Lim and colleagues review recent advances on the cellular and molecular mechanisms regulating the emergence of interneuron diversity during development and their integration in cortical circuits.
The six-layered neocortex of the mammalian pallium has no clear homolog in birds or non-avian reptiles. Recent research indicates that although these extant amniotes possess a variety of divergent and nonhomologous pallial structures, they share a conserved set of neuronal cell types and circuitries. These findings suggest a principle of brain evolution: that natural selection preferentially preserves the integrity of information-processing pathways, whereas other levels of biological organization, such as the three-dimensional architectures of neuronal assemblies, are less constrained. We review the similarities of pallial neuronal cell types in amniotes, delineate candidate gene regulatory networks for their cellular identities, and propose a model of developmental evolution for the divergence of amniote pallial structures.
The mammalian brain is composed of diverse, specialized cell populations. To systematically ascertain and learn from these cellular specializations, we used Drop-seq to profile RNA expression in 690,000 individual cells sampled from 9 regions of the adult mouse brain. We identified 565 transcriptionally distinct groups of cells using computational approaches developed to distinguish biological from technical signals. Cross-region analysis of these 565 cell populations revealed features of brain organization, including a gene-expression module for synthesizing axonal and presynaptic components, patterns in the co-deployment of voltage-gated ion channels, functional distinctions among the cells of the vasculature and specialization of glutamatergic neurons across cortical regions. Systematic neuronal classifications for two complex basal ganglia nuclei and the striatum revealed a rare population of spiny projection neurons. This adult mouse brain cell atlas, accessible through interactive online software (DropViz), serves as a reference for development, disease, and evolution.
Long-range projection neurons of the neocortex form the major tracts of the mammalian brain and are crucial for sensory-motor, associative and executive functions. Development of such circuits involves neuronal proliferation, specification and migration, as well as axonal elongation, navigation and targeting, where growing axons encounter multiple guidance cues and integrate these signals to execute guidance decisions. The complexity of axon guidance mechanisms in the formation of long-range neuronal projections has suggested that they might be under control of transcription factors, which are DNA-binding proteins that regulate the expression of downstream genes. Here we discuss recent advances in our understanding of the control of axon guidance by transcriptional regulation, as well as future directions for the elucidation of the mechanisms and pathological relevance of this process.
A vast number of different neuronal activity patterns could each induce a different set of activity-regulated genes. Mapping this coupling between activity pattern and gene induction would allow inference of a neuron's activity-pattern history from its gene expression and improve our understanding of activity-pattern-dependent synaptic plasticity. In genome-scale experiments comparing brief and sustained activity patterns, we reveal that activity-duration history can be inferred from gene expression profiles. Brief activity selectively induces a small subset of the activity-regulated gene program that corresponds to the first of three temporal waves of genes induced by sustained activity. Induction of these first-wave genes is mechanistically distinct from that of the later waves because it requires MAPK/ERK signaling but does not require de novo translation. Thus, the same mechanisms that establish the multi-wave temporal structure of gene induction also enable different gene sets to be induced by different activity durations. Tyssowski et al. report that different durations of neuronal activity induce different gene expression profiles, enabling inference of past neuronal activity from gene expression data. Furthermore, they show that MAPK/ERK signaling partially establishes this activity-pattern-to-gene-induction coupling.
Transcription factors (TFs) recognize specific DNA sequences to control chromatin and transcription, forming a complex system that guides expression of the genome. Despite keen interest in understanding how TFs control gene expression, it remains challenging to determine how the precise genomic binding sites of TFs are specified and how TF binding ultimately relates to regulation of transcription. This review considers how TFs are identified and functionally characterized, principally through the lens of a catalog of over 1,600 likely human TFs and binding motifs for two-thirds of them. Major classes of human TFs differ markedly in their evolutionary trajectories and expression patterns, underscoring distinct functions. TFs likewise underlie many different aspects of human physiology, disease, and variation, highlighting the importance of continued effort to understand TF-mediated gene regulation.
Synaptic inhibition critically influences sensory processing throughout the mammalian brain, including the main olfactory bulb (MOB), the first station of sensory processing in the olfactory system. Decades of research across numerous laboratories have established a central role for granule cells (GCs), the most abundant GABAergic interneuron type in the MOB, in the precise regulation of principal mitral and tufted cell (M/TC) firing rates and synchrony through lateral and recurrent inhibitory mechanisms. In addition to GCs, however, the MOB contains a vast diversity of other GABAergic interneuron types, and recent findings suggest that, while fewer in number, these oft-ignored interneurons are just as important as GCs in shaping odor-evoked M/TC activity. Here, I challenge the prevailing centrality of GCs. In this review, I first outline the specific properties of each GABAergic interneuron type in the rodent MOB, with particular emphasis placed on direct interneuron recordings and cell type-selective manipulations. On the basis of these properties, I then critically re-evaluate the contribution of GCs versus other interneuron types to the regulation of odor-evoked M/TC firing rates and synchrony via lateral, recurrent, and other inhibitory mechanisms. This analysis yields a novel model in which multiple interneuron types with distinct abundances, connectivity patterns, and physiologies complement one another to regulate M/TC activity and sensory processing.
Learning to vocalize depends on the ability to adaptively modify the temporal and spectral features of vocal elements. Neurons that convey motor-related signals to the auditory system are theorized to facilitate vocal learning, but the identity and function of such neurons remain unknown. Here we identify a previously unknown neuron type in the songbird brain that transmits vocal motor signals to the auditory cortex. Genetically ablating these neurons in juveniles disrupted their ability to imitate features of an adult tutor's song. Ablating these neurons in adults had little effect on previously learned songs but interfered with their ability to adaptively modify the duration of vocal elements and largely prevented the degradation of songs' temporal features that is normally caused by deafening. These findings identify a motor to auditory circuit essential to vocal imitation and to the adaptive modification of vocal timing.
A fundamental question in developmental neuroscience is how hundreds of diverse cell types are generated to form specialized brain regions. The ganglionic eminences (GEs) are embryonic brain structures located in the ventral telencephalon that produce many inhibitory GABA (γ-Aminobutyric acid)-ergic cell types, including long-range projection neurons and local interneurons (INs), which disperse widely throughout the brain. While much has been discovered about the origin and wiring of these cells, a major question remains: how do neurons originating in the GEs become specified during development as one differentiated subtype versus another? This review will cover recent work that has advanced our knowledge of the mechanisms governing cortical interneuron subtype specification, particularly progenitors’ spatial origin, birthdates, lineage, and mode of division.