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

Reverse engineering human brain evolution using organoid models

Primate brains vary dramatically in size and organization, but the genetic and developmental basis for these differences has been difficult to study due to lack of experimental models. Pluripotent stem cells and brain organoids provide a potential opportunity for comparative and functional studies of evolutionary differences, particularly during the early stages of neurogenesis. However, many challenges remain, including isolating stem cell lines from additional great ape individuals and species to capture the breadth of ape genetic diversity, improving the reproducibility of organoid models to study evolved differences in cell composition and combining multiple brain regions to capture connectivity relationships. Here, we describe strategies for identifying evolved developmental differences between humans and non-human primates and for isolating the underlying cellular and genetic mechanisms using comparative analyses, chimeric organoid culture, and genome engineering. In particular, we focus on how organoid models could ultimately be applied beyond studies of progenitor cell evolution to decode the origin of recent changes in cellular organization, connectivity patterns, myelination, synaptic development, and physiology that have been implicated in human cognition.

Twin-peak temporal regulation during human neocortical development

Understanding the temporal and spatial expression patterns of the human cerebral cortex is essential for expanding knowledge of its functionality. Previous analysis focused on the differentially expressed genes (DEGs) among cortical subregions revealed an hourglass model for interareal differences. However, the overall pattern of transcriptional differences during the development of every region remains to be fully explored. Here, analysing more than 800 neocortex samples from lifespan transcriptional profiles revealed that excitatory neurons are more regulated than inhibitory neurons in the foetal brain. Developmental DEGs tend to be resting state or memory encoding-related and are also involved in autism and Alzheimer’s disease. In addition, twin peaks of DEGs occur during the development of each neocortex region, with a first peak appearing in the perinatal period and an unexpected second peak appearing around childhood. Genes in these peaks have similar functions, but the second peak is more inhibitory neuron related. All these results emphasize the significance of this unique temporal regulatory pattern for human neocortical development.

Maturational Changes in Human Dorsal and Ventral Visual Networks

Developmental neuroimaging studies report the emergence of increasingly diverse cognitive functions as closely entangled with a rise-fall modulation of cortical thickness (CTh), structural cortical and white-matter connectivity, and a time-course for the experience-dependent selective elimination of the overproduced synapses. We examine which of two visual processing networks, the dorsal (DVN; prefrontal, parietal nodes) or ventral (VVN; frontal-temporal, fusiform nodes) matures first, thus leading the neuro-cognitive developmental trajectory. Three age-dependent measures are reported: (i) the CTh at network nodes; (ii) the matrix of intra-network structural connectivity (edges); and (iii) the proficiency in network-related neuropsychological tests. Typically developing children (age ~6 years), adolescents (~11 years), and adults (~21 years) were tested using multiple-acquisition structural T1-weighted magnetic resonance imaging (MRI) and neuropsychology. MRI images reconstructed into a gray/white/pial matter boundary model were used for CTh evaluation. No significant group differences in CTh and in the matrix of edges were found for DVN (except for the left prefrontal), but a significantly thicker cortex in children for VVN with reduced prefrontal ventral-fusiform connectivity and with an abundance of connections in adolescents. The higher performance in children on tests related to DVN corroborates the age-dependent MRI structural connectivity findings. The current findings are consistent with an earlier maturational course of DVN.

BEST: a web server for brain expression Spatio-temporal pattern analysis

Background

Dysregulated gene expression patterns have been reported in several mental disorders. Limited by the difficulty of obtaining samples, psychiatric molecular mechanism research still relies heavily on clues from genetics studies. By using reference data from brain expression studies, multiple types of comprehensive gene expression pattern analysis have been performed on psychiatric genetic results. These systems-level spatial-temporal expression pattern analyses provided evidence on specific brain regions, developmental stages and molecular pathways that are possibly involved in psychiatric pathophysiology. At present, there is no online tool for such systematic analysis, which hinders the applications of analysis by non-informatics researchers such as experimental biologists and clinical molecular biologists.

Results

We developed the BEST web server to support Brain Expression Spatio-Temporal pattern analysis. There are three highlighted features of BEST: 1) visualization: it generates user-friendly visual results that are easy to interpret, including heatmaps, Venn diagrams, gene co-expression networks and cluster-based Manhattan gene plots; these results illustrate the complex spatio-temporal expression patterns, including expression quantification and correlation between genes; 2) integration: it provides comprehensive human brain spatio-temporal expression patterns by integrating data from currently available databases; 3) multi-dimensionality: it analyses input genes as both a whole set and several subsets (clusters) which are enriched according to co-expression patterns, and it also presents the correlation between genetic and expression data.

Conclusions

To the best of our knowledge, BEST is the first data tool to support comprehensive human brain spatial-temporal expression pattern analysis. It helps to bridge disease-related genetic studies and mechanism studies, provides clues for key gene and molecular system identification, and supports the analysis of disease sensitive brain region and age stages. BEST is freely available at http://best.psych.ac.cn.

Comparative analysis of cellular expression pattern of schizophrenia risk genes in human versus mouse cortex

Background

Schizophrenia is a common psychiatric disease with high hereditary. The identification of schizophrenia risk genes (SRG) has shed light on its pathophysiological mechanisms. Mouse genetic models have been widely used to study the function of SRG in the brain with a cell type specific fashion. However, whether the cellular expression pattern of SRG is conserved between human and mouse brain is not thoroughly studied.

Results

We analyzed the single-cell transcription of 180 SRG from human and mouse primary visual cortex (V1). We compared the percentage of glutamatergic, GABAergic and non-neuronal cells that express each SRG between mouse and human V1 cortex. Thirty percent (54/180) of SRG had significantly different expression rate in glutamatergic neurons between mouse and human V1 cortex. By contrast, only 5.6% (10/180) of SRG showed significantly different expression in GABAergic neurons, which is similar with the ratio of SRG (15/180) with species difference in total cell populations. Strikingly, the percentage of non-neuronal cells expressing all SRG are indistinguishable between human and mouse V1 cortex. We further analyzed the biological significance of differentially expressed SRG by gene ontology. The species-different SRG in glutamatergic neurons are highly expressed in dendrite and axon. They are enriched in the biological process of response to stimulus. However, the differentially expressed SRG in GABAergic neurons are enriched in the regulation of organelle organization.

Conclusion

GABAergic neurons are more conserved in the expression of SRG than glutamatergic neurons while the non-neuronal cells show the species conservation for the expression of all SRG. It should be cautious to use mouse models to study those SRG which show different cellular expression pattern between human and mouse cortex.

Long-read assembly of the Chinese rhesus macaque genome and identification of ape-specific structural variants

We present a high-quality de novo genome assembly (rheMacS) of the Chinese rhesus macaque (Macaca mulatta) using long-read sequencing and multiplatform scaffolding approaches. Compared to the current Indian rhesus macaque reference genome (rheMac8), rheMacS increases sequence contiguity 75-fold, closing 21,940 of the remaining assembly gaps (60.8 Mbp). We improve gene annotation by generating more than two million full-length transcripts from ten different tissues by long-read RNA sequencing. We sequence resolve 53,916 structural variants (96% novel) and identify 17,000 ape-specific structural variants (ASSVs) based on comparison to ape genomes. Many ASSVs map within ChIP-seq predicted enhancer regions where apes and macaque show diverged enhancer activity and gene expression. We further characterize a subset that may contribute to ape- or great-ape-specific phenotypic traits, including taillessness, brain volume expansion, improved manual dexterity, and large body size. The rheMacS genome assembly serves as an ideal reference for future biomedical and evolutionary studies.

Comparative genomic analysis of human and primate relatives can reveal important biological and evolutionary insights. Here, the authors present a long-read assembly of the Chinese rhesus macaque genome and identify ape-specific structural variants.

Life history changes accompany increased numbers of cortical neurons: A new framework for understanding human brain evolution

Narratives of human evolution have focused on cortical expansion and increases in brain size relative to body size, but considered that changes in life history, such as in age at sexual maturity and thus the extent of childhood and maternal dependence, or maximal longevity, are evolved features that appeared as consequences of selection for increased brain size, or increased cognitive abilities that decrease mortality rates, or due to selection for grandmotherly contribution to feeding the young. Here I build on my recent finding that slower life histories universally accompany increased numbers of cortical neurons across warm-blooded species to propose a simpler framework for human evolution: that slower development to sexual maturity and increased post-maturity longevity are features that do not require selection, but rather inevitably and immediately accompany evolutionary increases in numbers of cortical neurons, thus fostering human social interactions and cultural and technological evolution as generational overlap increases.

Spectral peculiarity and criticality of a human connectome

We have performed the comparative spectral analysis of structural connectomes for various organisms using open-access data. Our results indicate new peculiar features of connectomes of higher organisms. We found that the spectral density of adjacency matrices of human connectome has maximal deviation from the one of randomized network, compared to other organisms. Considering the network evolution induced by the preference of 3-cycles formation, we discovered that for macaque and human connectomes the evolution with the conservation of local clusterization is crucial, while for primitive organisms the conservation of averaged clusterization is sufficient. Investigating for the first time the level spacing distribution of the spectrum of human connectome Laplacian matrix, we explicitly demonstrate that the spectral statistics corresponds to the critical regime, which is hybrid of Wigner-Dyson and Poisson distributions. This observation provides strong support for debated statement of the brain criticality.

Human evolved regulatory elements modulate genes involved in cortical expansion and neurodevelopmental disease susceptibility

Modern genetic studies indicate that human brain evolution is driven primarily by changes in gene regulation, which requires understanding the biological function of largely non-coding gene regulatory elements, many of which act in tissue specific manner. We leverage chromatin interaction profiles in human fetal and adult cortex to assign three classes of human-evolved elements to putative target genes. We find that human-evolved elements involving DNA sequence changes and those involving epigenetic changes are associated with human-specific gene regulation via effects on different classes of genes representing distinct biological pathways. However, both types of human-evolved elements converge on specific cell types and laminae involved in cerebral cortical expansion. Moreover, human evolved elements interact with neurodevelopmental disease risk genes, and genes with a high level of evolutionary constraint, highlighting a relationship between brain evolution and vulnerability to disorders affecting cognition and behavior. These results provide novel insights into gene regulatory mechanisms driving the evolution of human cognition and mechanisms of vulnerability to neuropsychiatric conditions.

Determining cell type abundance and expression from bulk tissues with digital cytometry

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells.

Transgenic rhesus monkeys carrying the human MCPH1 gene copies show human-like neoteny of brain development

Brain size and cognitive skills are the most dramatically changed traits in humans during evolution and yet the genetic mechanisms underlying these human-specific changes remain elusive. Here, we successfully generated 11 transgenic rhesus monkeys (8 first-generation and 3 second-generation) carrying human copies of MCPH1, an important gene for brain development and brain evolution. Brain-image and tissue-section analyses indicated an altered pattern of neural-cell differentiation, resulting in a delayed neuronal maturation and neural-fiber myelination of the transgenic monkeys, similar to the known evolutionary change of developmental delay (neoteny) in humans. Further brain-transcriptome and tissue-section analyses of major developmental stages showed a marked human-like expression delay of neuron differentiation and synaptic-signaling genes, providing a molecular explanation for the observed brain-developmental delay of the transgenic monkeys. More importantly, the transgenic monkeys exhibited better short-term memory and shorter reaction time compared with the wild-type controls in the delayed-matching-to-sample task. The presented data represent the first attempt to experimentally interrogate the genetic basis of human brain origin using a transgenic monkey model and it values the use of non-human primates in understanding unique human traits.

Single-cell transcriptomic analysis of Alzheimer's disease

Alzheimer's disease is a pervasive neurodegenerative disorder, the molecular complexity of which remains poorly understood. Here, we analysed 80,660 single-nucleus transcriptomes from the prefrontal cortex of 48 individuals with varying degrees of Alzheimer's disease pathology. Across six major brain cell types, we identified transcriptionally distinct subpopulations, including those associated with pathology and characterized by regulators of myelination, inflammation, and neuron survival. The strongest disease-associated changes appeared early in pathological progression and were highly cell-type specific, whereas genes upregulated at late stages were common across cell types and primarily involved in the global stress response. Notably, we found that female cells were overrepresented in disease-associated subpopulations, and that transcriptional responses were substantially different between sexes in several cell types, including oligodendrocytes. Overall, myelination-related processes were recurrently perturbed in multiple cell types, suggesting that myelination has a key role in Alzheimer's disease pathophysiology. Our single-cell transcriptomic resource provides a blueprint for interrogating the molecular and cellular basis of Alzheimer's disease.

Molecular windows into the human brain for psychiatric disorders

Delineating the pathophysiology of psychiatric disorders has been extremely challenging but technological advances in recent decades have facilitated a deeper interrogation of molecular processes in the human brain. Initial candidate gene expression studies of the postmortem brain have evolved into genome wide profiling of the transcriptome and the epigenome, a critical regulator of gene expression. Here, we review the potential and challenges of direct molecular characterization of the postmortem human brain, and provide a brief overview of recent transcriptional and epigenetic studies with respect to neuropsychiatric disorders. Such information can now be leveraged and integrated with the growing number of genome-wide association databases to provide a functional context of trait-associated genetic variants linked to psychiatric illnesses and related phenotypes. While it is clear that the field is still developing and challenges remain to be surmounted, these recent advances nevertheless hold tremendous promise for delineating the neurobiological underpinnings of mental diseases and accelerating the development of novel medication strategies.

Genetics of human brain evolution

During the course of evolution the human brain has increased in size and complexity, ultimately these differences are the result of changes at the genetic level. Identifying and characterizing molecular evolution requires an understanding of both the genetic underpinning of the system as well as the comparative genetic tools to identify signatures of selection. This chapter aims to describe our current understanding of the genetics of human brain evolution. Primarily this is the story of the evolution of the human brain since our last common ape ancestor, but where relevant we will also discuss changes that are unique to the primate brain (compared to other mammals) or various other lineages in the evolution of humans more generally. It will focus on genetic changes that both directly affected the development and function of the brain as well as those that have indirectly influenced brain evolution through both prenatal and postnatal environment. This review is not meant to be exhaustive, but rather to begin to construct a general framework for understanding the full array of data being generated.

Transmembrane protein 100 is expressed in neurons and glia of dorsal root ganglia and is reduced after painful nerve injury

Introduction

Tmem100 modulates interactions between TRPA1 and TRPV1. The cell specificity of Tmem100 expression in dorsal root ganglia (DRGs) is not well defined, nor is the effect of peripheral nerve injury on Tmem100 expression.

Objective

This study was designed to determine the cell specificity of Tmem100 expression in DRG and its subcellular localization, and to examine how Tmem100 expression may be altered in painful conditions.

Methods

Dorsal root ganglion Tmem100 expression was determined by immunohistochemistry, immunoblot, and quantitative real-time PCR, and compared between various experimental rat pain models and controls.

Results

Tmem100 is expressed in both neurons and perineuronal glial cells in the rat DRG. The plasma membrane and intracellular localization of Tmem100 are identified in 83% ± 6% of IB4-positive and 48% ± 6% of calcitonin gene-related peptide-positive neurons, as well as in medium- and large-sized neurons, with its immunopositivity colocalized to TRPV1 (94% ± 5%) and TRPA1 (96% ± 3%). Tmem100 is also detected in the perineuronal satellite glial cells and in some microglia. Tmem100 protein is significantly increased in the lumbar DRGs in the complete Freund adjuvant inflammatory pain. By contrast, peripheral nerve injury by spinal nerve ligation diminishes Tmem100 expression in the injured DRG, with immunoblot and immunohistochemistry experiments showing reduced Tmem100 protein levels in both neurons and satellite glial cells of DRGs proximal to injury, whereas Tmem100 is unchanged in adjacent DRGs. The spared nerve injury model also reduces Tmem100 protein in the injured DRGs.

Conclusion

Our data demonstrate a pain pathology-dependent alteration of DRG Tmem100 protein expression, upregulated during CFA inflammatory pain but downregulated during neuropathic pain.

High-resolution comparative analysis of great ape genomes

Genetic studies of human evolution require high-quality contiguous ape genome assemblies that are not guided by the human reference. We coupled long-read sequence assembly and full-length complementary DNA sequencing with a multiplatform scaffolding approach to produce ab initio chimpanzee and orangutan genome assemblies. By comparing these with two long-read de novo human genome assemblies and a gorilla genome assembly, we characterized lineage-specific and shared great ape genetic variation ranging from single- to mega-base pair-sized variants. We identified ~17,000 fixed human-specific structural variants identifying genic and putative regulatory changes that have emerged in humans since divergence from nonhuman apes. Interestingly, these variants are enriched near genes that are down-regulated in human compared to chimpanzee cerebral organoids, particularly in cells analogous to radial glial neural progenitors.

Identification and characterization of functional modules reflecting transcriptome transition during human neuron maturation

BACKGROUND

Neuron maturation is a critical process in neurogenesis, during which neurons gain their morphological, electrophysiological and molecular characteristics for their functions as the central components of the nervous system.

RESULTS

To better understand the molecular changes during this process, we combined the protein-protein interaction network and public single cell RNA-seq data of mature and immature neurons to identify functional modules relevant to the neuron maturation process in humans. Among the 109 functional modules in total, 33 showed significant gene expression level changes (discriminating modules) which participate in varied functions including energy consumption, synaptic functions and housekeeping functions such as translation and splicing. Based on the identified modules, we trained a neuron maturity index (NMI) model for the quantification of maturation states of single neurons or purified bulk neurons. Applied to multiple single neuron transcriptome data sets of neuron development in humans and mice, the NMI model made estimation of neuron maturity states which were significantly correlated with the neuron maturation trajectories in both species, implying the reproducibility and conservation of the identified transcriptome transition.

CONCLUSION

We identified 33 discriminating modules whose activities were significantly correlated with single neuron maturity states, which may play important roles in the neuron maturation process.

Transcriptomic characterization of MRI contrast with focus on the T1-w/T2-w ratio in the cerebral cortex

Magnetic resonance (MR) images of the brain are of immense clinical and research utility. At the atomic and subatomic levels, the sources of MR signals are well understood. However, we lack a comprehensive understanding of the macromolecular correlates of MR signal contrast. To address this gap, we used genome-wide measurements to correlate gene expression with MR signal intensity across the cerebral cortex in the Allen Human Brain Atlas (AHBA). We focused on the ratio of T1-weighted and T2-weighted intensities (T1-w/T2-w ratio image), which is considered to be a useful proxy for myelin content. As expected, we found enrichment of positive correlations between myelin-associated genes and the ratio image, supporting its use as a myelin marker. Genome-wide, there was an association with protein mass, with genes coding for heavier proteins expressed in regions with high T1-w/T2-w values. Oligodendrocyte gene markers were strongly correlated with the T1-w/T2-w ratio, but this was not driven by myelin-associated genes. Mitochondrial genes exhibit the strongest relationship, showing higher expression in regions with low T1-w/T2-w ratio. This may be due to the pH gradient in mitochondria as genes up-regulated by pH in the brain were also highly correlated with the ratio. While we corroborate associations with myelin and synaptic plasticity, differences in the T1-w/T2-w ratio across the cortex are more strongly linked to molecule size, oligodendrocyte markers, mitochondria, and pH. We evaluate correlations between AHBA transcriptomic measurements and a group averaged T1-w/T2-w ratio image, showing agreement with in-sample results. Expanding our analysis to the whole brain results in strong positive T1-w/T2-w correlations for immune system, inflammatory disease, and microglia marker genes. Genes with negative correlations were enriched for neuron markers and synaptic plasticity genes. Lastly, our findings are similar when performed on T1-w or inverted T2-w intensities alone. These results provide a molecular characterization of MR contrast that will aid interpretation of future MR studies of the brain.

Brain Transcriptome Databases: A User's Guide

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

Mechanisms of radial glia progenitor cell lineage progression

The mammalian cerebral cortex is responsible for higher cognitive functions such as perception, consciousness, and acquiring and processing information. The neocortex is organized into six distinct laminae, each composed of a rich diversity of cell types which assemble into highly complex cortical circuits. Radial glia progenitors (RGPs) are responsible for producing all neocortical neurons and certain glia lineages. Here, we discuss recent discoveries emerging from clonal lineage analysis at the single RGP cell level that provide us with an inaugural quantitative framework of RGP lineage progression. We further discuss the importance of the relative contribution of intrinsic gene functions and non‐cell‐autonomous or community effects in regulating RGP proliferation behavior and lineage progression.

Transcriptional and Post-Transcriptional Mechanisms of the Development of Neocortical Lamination

The neocortex is a laminated brain structure that is the seat of higher cognitive capacity and responses, long-term memory, sensory and emotional functions, and voluntary motor behavior. Proper lamination requires that progenitor cells give rise to a neuron, that the immature neuron can migrate away from its mother cell and past other cells, and finally that the immature neuron can take its place and adopt a mature identity characterized by connectivity and gene expression; thus lamination proceeds through three steps: genesis, migration, and maturation. Each neocortical layer contains pyramidal neurons that share specific morphological and molecular characteristics that stem from their prenatal birth date. Transcription factors are dynamic proteins because of the cohort of downstream factors that they regulate. RNA-binding proteins are no less dynamic, and play important roles in every step of mRNA processing. Indeed, recent screens have uncovered post-transcriptional mechanisms as being integral regulatory mechanisms to neocortical development. Here, we summarize major aspects of neocortical laminar development, emphasizing transcriptional and post-transcriptional mechanisms, with the aim of spurring increased understanding and study of its intricacies.