Spatially resolved gene regulatory and disease-related vulnerability map of the adult Macaque cortex

MAPbrain: a multi-omics atlas of the primate brain

The brain is the central hub of the entire nervous system. Its development is a lifelong process guided by a genetic blueprint. Understanding how genes influence brain development is critical for deciphering the formation of human cognitive functions and the underlying mechanisms of neurological disorders. Recent advances in multi-omics techniques have now made it possible to explore these aspects comprehensively. However, integrating and analyzing extensive multi-omics data presents significant challenges. Here, we introduced MAPbrain (http://bigdata.ibp.ac.cn/mapBRAIN/), a multi-omics atlas of the primate brain. This repository integrates and normalizes both our own lab's published data and publicly available multi-omics data, encompassing 21 million brain cells from 38 key brain regions and 436 sub-regions across embryonic and adult stages, with 164 time points in humans and non-human primates. MAPbrain offers a unique, robust, and interactive platform that includes transcriptomics, epigenomics, and spatial transcriptomics data, facilitating a comprehensive exploration of brain development. The platform enables the exploration of cell type- and time point-specific markers, gene expression comparison between brain regions and species, joint analyses across transcriptome and epigenome, and navigation of cell types across species, brain regions, and development stages. Additionally, MAPbrain provides an online integration module for users to navigate and analyze their own data within the platform.

A graph self-supervised residual learning framework for domain identification and data integration of spatial transcriptomics

Spatial transcriptomics (ST) technologies allow for comprehensive characterization of gene expression patterns in the context of tissue microenvironment. However, accurately identifying domains with spatial coherence in both gene expression and histology in situ and effectively integrating data from multi-sample remains challenging. Here, we propose ResST, a graph self-supervised residual learning model based on graph neural network and Margin Disparity Discrepancy (MDD) theory. ResST aggregates gene expression, biological effects, spatial location, and morphological information to capture nonlinear relationships between a cell and surrounding cells for spatial domain identification. Also, ResST integrates multiple ST datasets and aligns latent embeddings based on MDD theory for correcting batch effects. Results show that ResST identifies continuous spatial domains at a finer scale in ten ST datasets acquired with different technologies. Moreover, ResST efficiently integrated data from multiple tissue sections vertically or horizontally while correcting batch effects. Overall, ResST demonstrates exceptional performance in analyzing ST datasets.

Expression of activity-regulated transcripts in pyramidal neurons across the cortical visuospatial working memory network in unaffected comparison individuals and individuals with schizophrenia

Visuospatial working memory (vsWM), which is impaired in schizophrenia (SZ), is mediated by multiple cortical regions including the primary (V1) and association (V2) visual, posterior parietal (PPC) and dorsolateral prefrontal (DLPFC) cortices. In these regions, parvalbumin (PV) or somatostatin (SST) GABA neurons are altered in SZ as reflected in lower levels of activity-regulated transcripts. As PV and SST neurons receive excitatory inputs from neighboring pyramidal neurons, we hypothesized that levels of activity-regulated transcripts are also lower in pyramidal neurons in these regions. Thus, we quantified levels of four activity-regulated, pyramidal neuron-selective transcripts, namely adenylate cyclase-activating polypeptide-1 (ADCYAP1), brain-derived neurotrophic factor (BDNF), neuronal pentraxin-2 (NPTX2) and neuritin-1 (NRN1) mRNAs, in V1, V2, PPC and DLPFC from unaffected comparison and SZ individuals. In SZ, BDNF and NPTX2 mRNA levels were lower across all four regions, whereas ADCYAP1 and NRN1 mRNA levels were lower in V1 and V2. The regional pattern of deficits in BDNF and NPTX2 mRNAs was similar to that in transcripts in PV and SST neurons in SZ. These findings suggest that lower activity of pyramidal neurons expressing BDNF and/or NPTX2 mRNAs might contribute to alterations in PV and SST neurons across the vsWM network in SZ.

Proteomic features of gray matter layers and superficial white matter of the rhesus monkey neocortex: comparison of prefrontal area 46 and occipital area 17

In this novel large-scale multiplexed immunofluorescence study we comprehensively characterized and compared layer-specific proteomic features within regions of interest of the widely divergent dorsolateral prefrontal cortex (A46) and primary visual cortex (A17) of adult rhesus monkeys. Twenty-eight markers were imaged in rounds of sequential staining, and their spatial distribution precisely quantified within gray matter layers and superficial white matter. Cells were classified as neurons, astrocytes, oligodendrocytes, microglia, or endothelial cells. The distribution of fibers and blood vessels were assessed by quantification of staining intensity across regions of interest. This method revealed multivariate similarities and differences between layers and areas. Protein expression in neurons was the strongest determinant of both laminar and regional differences, whereas protein expression in glia was more important for intra-areal laminar distinctions. Among specific results, we observed a lower glia-to-neuron ratio in A17 than in A46 and the pan-neuronal markers HuD and NeuN were differentially distributed in both brain areas with a lower intensity of NeuN in layers 4 and 5 of A17 compared to A46 and other A17 layers. Astrocytes and oligodendrocytes exhibited distinct marker-specific laminar distributions that differed between regions; notably, there was a high proportion of ALDH1L1-expressing astrocytes and of oligodendrocyte markers in layer 4 of A17. The many nuanced differences in protein expression between layers and regions observed here highlight the need for direct assessment of proteins, in addition to RNA expression, and set the stage for future protein-focused studies of these and other brain regions in normal and pathological conditions.

Single-cell mitochondrial sequencing reveals low-frequency mitochondrial mutations in naturally aging mice

Mitochondria play a crucial role in numerous biological processes; however, limited methods and research have focused on revealing mitochondrial heterogeneity at the single-cell level. In this study, we optimized the DNBelab C4 single-cell ATAC (assay for transposase-accessible chromatin) sequencing workflow for single-cell mitochondrial sequencing (C4_mtscATAC-seq). We validated the effectiveness of our C4_mtscATAC-seq protocol by sequencing the HEK-293T cell line with two biological replicates, successfully capturing both mitochondrial content (~68% of total sequencing data) and open chromatin status simultaneously. Subsequently, we applied C4_mtscATAC-seq to investigate two mouse tissues, spleen and bone marrow, obtained from two mice aged 2 months and two mice aged 23 months. Our findings revealed higher mitochondrial DNA (mtDNA) content in young tissues compared to more variable mitochondrial content in aged tissues, consistent with higher activity scores of nuclear genes associated with mitochondrial replication and transcription in young tissues. We detected a total of 22, 15, and 21 mtDNA mutations in the young spleen, aged spleen, and bone marrow, respectively, with most variant allele frequencies (VAF) below 1%. Moreover, we observed a higher number of mtDNA mutations with higher VAF in aged tissues compared to young tissues. Importantly, we identified three mtDNA variations (m.9821A>T, m.15219T>C, and m.15984C>T) with the highest VAF in both aged spleen and aged bone marrow. By comparing cells with and without these mtDNA variations, we analyzed differential open chromatin status to identify potential genes associated with these mtDNA variations, including transcription factors such as KLF15 and NRF1. Our study presents an alternative single-cell mitochondrial sequencing method and provides crude insights into age-related single-cell mitochondrial variations.

Spatiotemporal omics for biology and medicine

The completion of the Human Genome Project has provided a foundational blueprint for understanding human life. Nonetheless, understanding the intricate mechanisms through which our genetic blueprint is involved in disease or orchestrates development across temporal and spatial dimensions remains a profound scientific challenge. Recent breakthroughs in cellular omics technologies have paved new pathways for understanding the regulation of genomic elements and the relationship between gene expression, cellular functions, and cell fate determination. The advent of spatial omics technologies, encompassing both imaging and sequencing-based methodologies, has enabled a comprehensive understanding of biological processes from a cellular ecosystem perspective. This review offers an updated overview of how spatial omics has advanced our understanding of the translation of genetic information into cellular heterogeneity and tissue structural organization and their dynamic changes over time. It emphasizes the discovery of various biological phenomena, related to organ functionality, embryogenesis, species evolution, and the pathogenesis of diseases.

High-depth whole-genome sequencing identifies structure variants, copy number variants and short tandem repeats associated with Parkinson's disease

While numerous single nucleotide variants and small indels have been identified in Parkinson's disease (PD), the contribution of structural variants (SVs), copy number variants (CNVs), and short tandem repeats (STRs) remains poorly understood. Here we investigated the association using the high-depth whole-genome sequencing data from 466 Chinese PD patients and 513 controls. Totally, we identified 29,561 SVs, 32,153 CNVs, and 174,905 STRs, and found that CNV deletions were significantly enriched in the end-proportion of autosomal chromosomes in PD. After genome-wide association analysis and replication in an external cohort of 352 cases and 547 controls, we validated that the 1.6 kb-deletion neighboring MUC19, 12.4kb-deletion near RXFP1 and GGGAAA repeats in SLC2A13 were significantly associated with PD. Moreover, the MUC19 deletion and the SLC2A13 5-copy repeat reduced the penetrance of the LRRK2 G2385R variant. Moreover, genes with these variants were dosage-sensitive. These data provided novel insights into the genetic architecture of PD.

Decoding frontotemporal and cell-type-specific vulnerabilities to neuropsychiatric disorders and psychoactive drugs

Frontotemporal lobe abnormalities are linked to neuropsychiatric disorders and cognition, but the role of cellular heterogeneity between temporal lobe (TL) and frontal lobe (FL) in the vulnerability to genetic risk factors remains to be elucidated. We integrated single-nucleus transcriptome analysis in 'fresh' human FL and TL with genetic susceptibility, gene dysregulation in neuropsychiatric disease and psychoactive drug response data. We show how intrinsic differences between TL and FL contribute to the vulnerability of specific cell types to both genetic risk factors and psychoactive drugs. Neuronal populations, specifically PVALB neurons, were most highly vulnerable to genetic risk factors for psychiatric disease. These psychiatric disease-associated genes were mostly upregulated in the TL, and dysregulated in the brain of patients with obsessive-compulsive disorder, bipolar disorder and schizophrenia. Among these genes, GRIN2A and SLC12A5, implicated in schizophrenia and bipolar disorder, were significantly upregulated in TL PVALB neurons and in psychiatric disease patients' brain. PVALB neurons from the TL were twofold more vulnerable to psychoactive drugs than to genetic risk factors, showing the influence and specificity of frontotemporal lobe differences on cell vulnerabilities. These studies provide a cell type resolved map of the impact of brain regional differences on cell type vulnerabilities in neuropsychiatric disorders.

A Review of the Application of Spatial Transcriptomics in Neuroscience

Since spatial transcriptomics can locate and distinguish the gene expression of functional genes in special regions and tissue, it is important for us to investigate the brain development, the development mechanism of brain diseases, and the relationship between brain structure and function in Neuroscience (or Brain science). While previous studies have introduced the crucial spatial transcriptomic techniques and data analysis methods, there are few studies to comprehensively overview the key methods, data resources, and technological applications of spatial transcriptomics in Neuroscience. For these reasons, we first investigate several common spatial transcriptomic data analysis approaches and data resources. Second, we introduce the applications of the spatial transcriptomic data analysis approaches in Neuroscience. Third, we summarize the integrating spatial transcriptomics with other technologies in Neuroscience. Finally, we discuss the challenges and future research directions of spatial transcriptomics in Neuroscience.

Comparative genomics of macaques and integrated insights into genetic variation and population history

The crab-eating macaques ( Macaca fascicularis ) and rhesus macaques ( M. mulatta ) are widely studied nonhuman primates in biomedical and evolutionary research. Despite their significance, the current understanding of the complex genomic structure in macaques and the differences between species requires substantial improvement. Here, we present a complete genome assembly of a crab-eating macaque and 20 haplotype-resolved macaque assemblies to investigate the complex regions and major genomic differences between species. Segmental duplication in macaques is ∼42% lower, while centromeres are ∼3.7 times longer than those in humans. The characterization of ∼2 Mbp fixed genetic variants and ∼240 Mbp complex loci highlights potential associations with metabolic differences between the two macaque species (e.g., CYP2C76 and EHBP1L1 ). Additionally, hundreds of alternative splicing differences show post-transcriptional regulation divergence between these two species (e.g., PNPO ). We also characterize 91 large-scale genomic differences between macaques and humans at a single-base-pair resolution and highlight their impact on gene regulation in primate evolution (e.g., FOLH1 and PIEZO2 ). Finally, population genetics recapitulates macaque speciation and selective sweeps, highlighting potential genetic basis of reproduction and tail phenotype differences (e.g., STAB1 , SEMA3F , and HOXD13 ). In summary, the integrated analysis of genetic variation and population genetics in macaques greatly enhances our comprehension of lineage-specific phenotypes, adaptation, and primate evolution, thereby improving their biomedical applications in human diseases.

Construction of single-cell cross-species chromatin accessibility landscapes with combinatorial-hybridization-based ATAC-seq

Despite recent advances in single-cell genomics, the lack of maps for single-cell candidate cis-regulatory elements (cCREs) in non-mammal species has limited our exploration of conserved regulatory programs across vertebrates and invertebrates. Here, we developed a combinatorial-hybridization-based method for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) named CH-ATAC-seq, enabling the construction of single-cell accessible chromatin landscapes for zebrafish, Drosophila, and earthworms (Eisenia andrei). By integrating scATAC censuses of humans, monkeys, and mice, we systematically identified 152 distinct main cell types and around 0.8 million cell-type-specific cCREs. Our analysis provided insights into the conservation of neural, muscle, and immune lineages across species, while epithelial cells exhibited a higher organ-origin heterogeneity. Additionally, a large-scale gene regulatory network (GRN) was constructed in four vertebrates by integrating scRNA-seq censuses. Overall, our study provides a valuable resource for comparative epigenomics, identifying the evolutionary conservation and divergence of gene regulation across different species.

Heterogeneity of layer 4 in visual areas of rhesus macaque cortex

Recently, single-cell RNA-sequencing (scRNA-seq) has enabled unprecedented insights to the cellular landscape of the brains of many different species, among them the rhesus macaque as a key animal model. Building on previous, broader surveys of the macaque brain, we closely examined five immediately neighboring areas within the visual cortex of the rhesus macaque: V1, V2, V4, MT and TEO. To facilitate this, we first devised a novel pipeline for brain spatial archive - the BrainSPACE - which enabled robust archiving and sampling from the whole unfixed brain. SnRNA-sequencing of ~100,000 nuclei from visual areas V1 and V4 revealed conservation within the GABAergic neuron subtypes, while seven and one distinct principle neuron subtypes were detected in V1 and V4, respectively, all most likely located in layer 4. Moreover, using small molecule fluorescence in situ hybridization, we identified cell type density gradients across V1, V2, V4, MT, and TEO appearing to reflect the visual hierarchy. These findings demonstrate an association between the clear areal specializations among neighboring areas with the hierarchical levels within the visual cortex of the rhesus macaque.

Drug targeting in psychiatric disorders - how to overcome the loss in translation?

In spite of major efforts and investment in development of psychiatric drugs, many clinical trials have failed in recent decades, and clinicians still prescribe drugs that were discovered many years ago. Although multiple reasons have been discussed for the drug development deadlock, we focus here on one of the major possible biological reasons: differences between the characteristics of drug targets in preclinical models and the corresponding targets in patients. Importantly, based on technological advances in single-cell analysis, we propose here a framework for the use of available and newly emerging knowledge from single-cell and spatial omics studies to evaluate and potentially improve the translational predictivity of preclinical models before commencing preclinical and, in particular, clinical studies. We believe that these recommendations will improve preclinical models and the ability to assess drugs in clinical trials, reducing failure rates in expensive late-stage trials and ultimately benefitting psychiatric drug discovery and development.

ScISOr-ATAC reveals convergent and divergent splicing and chromatin specificities between matched cell types across cortical regions, evolution, and in Alzheimer's Disease

Multimodal measurements have become widespread in genomics, however measuring open chromatin accessibility and splicing simultaneously in frozen brain tissues remains unconquered. Hence, we devised Single-Cell-ISOform-RNA sequencing coupled with the Assay-for-Transposase-Accessible-Chromatin (ScISOr-ATAC). We utilized ScISOr-ATAC to assess whether chromatin and splicing alterations in the brain convergently affect the same cell types or divergently different ones. We applied ScISOr-ATAC to three major conditions: comparing (i) the Rhesus macaque (Macaca mulatta) prefrontal cortex (PFC) and visual cortex (VIS), (ii) cross species divergence of Rhesus macaque versus human PFC, as well as (iii) dysregulation in Alzheimer's disease in human PFC. We found that among cortical-layer biased excitatory neuron subtypes, splicing is highly brain-region specific for L3-5/L6 IT_RORB neurons, moderately specific in L2-3 IT_CUX2.RORB neurons and unspecific in L2-3 IT_CUX2 neurons. In contrast, at the chromatin level, L2-3 IT_CUX2.RORB neurons show the highest brain-region specificity compared to other subtypes. Likewise, when comparing human and macaque PFC, strong evolutionary divergence on one molecular modality does not necessarily imply strong such divergence on another molecular level in the same cell type. Finally, in Alzheimer's disease, oligodendrocytes show convergently high dysregulation in both chromatin and splicing. However, chromatin and splicing dysregulation most strongly affect distinct oligodendrocyte subtypes. Overall, these results indicate that chromatin and splicing can show convergent or divergent results depending on the performed comparison, justifying the need for their concurrent measurement to investigate complex systems. Taken together, ScISOr-ATAC allows for the characterization of single-cell splicing and chromatin patterns and the comparison of sample groups in frozen brain samples.

Spatial and single-nucleus transcriptomics decoding the molecular landscape and cellular organization of avian optic tectum

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.

SCAN: Spatiotemporal Cloud Atlas for Neural cells

The nervous system is one of the most complicated and enigmatic systems within the animal kingdom. Recently, the emergence and development of spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) technologies have provided an unprecedented ability to systematically decipher the cellular heterogeneity and spatial locations of the nervous system from multiple unbiased aspects. However, efficiently integrating, presenting and analyzing massive multiomic data remains a huge challenge. Here, we manually collected and comprehensively analyzed high-quality scRNA-seq and ST data from the nervous system, covering 10 679 684 cells. In addition, multi-omic datasets from more than 900 species were included for extensive data mining from an evolutionary perspective. Furthermore, over 100 neurological diseases (e.g. Alzheimer's disease, Parkinson's disease, Down syndrome) were systematically analyzed for high-throughput screening of putative biomarkers. Differential expression patterns across developmental time points, cell types and ST spots were discerned and subsequently subjected to extensive interpretation. To provide researchers with efficient data exploration, we created a new database with interactive interfaces and integrated functions called the Spatiotemporal Cloud Atlas for Neural cells (SCAN), freely accessible at http://47.98.139.124:8799 or http://scanatlas.net. SCAN will benefit the neuroscience research community to better exploit the spatiotemporal atlas of the neural system and promote the development of diagnostic strategies for various neurological disorders.

STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization

Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their spatial locations at the single-cell level, generating detailed biological insight into biological processes. A comprehensive database could facilitate the sharing of spatial transcriptomic data and streamline the data acquisition process for researchers. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a database that serves as a one-stop hub for spatial transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified spatial regions and genes, and performed cell-cell interaction analysis for these datasets. STOmicsDB features a user-friendly interface for the rapid visualization of millions of cells. To further facilitate the reusability and interoperability of spatial transcriptomic data, we developed standards for spatial transcriptomic data archiving and constructed a spatial transcriptomic data archiving system. Additionally, we offer a distinctive capability of customizing dedicated sub-databases in STOmicsDB for researchers, assisting them in visualizing their spatial transcriptomic analyses. We believe that STOmicsDB could contribute to research insights in the spatial transcriptomics field, including data archiving, sharing, visualization and analysis. STOmicsDB is freely accessible at https://db.cngb.org/stomics/.

Spatial transcriptomics drives a new era in plant research

The plant community lags far behind the animal and human fields concerning the application of single‐cell methodologies. This is primarily due to the challenges associated with plant tissue dissection and the limitations of the available technologies. However, recent advances in spatial transcriptomics enable the study of single‐cells derived from plant tissues from a spatial perspective. This technology is already successfully used to identify cell types, reconstruct cell‐fate lineages, and reveal cell‐to‐cell interactions. Future technological advancements will overcome the challenges in sample processing, data analysis, and the integration of multiple‐omics technologies. Thanks to spatial transcriptomics, we anticipate several plant research projects to significantly advance our understanding of critical aspects of plant biology.

Nuclear lamina erosion-induced resurrection of endogenous retroviruses underlies neuronal aging

The primate frontal lobe (FL) is sensitive to aging-related neurocognitive decline. However, the aging-associated molecular mechanisms remain unclear. Here, using physiologically aged non-human primates (NHPs), we depicted a comprehensive landscape of FL aging with multidimensional profiling encompassing bulk and single-nucleus transcriptomes, quantitative proteome, and DNA methylome. Conjoint analysis across these molecular and neuropathological layers underscores nuclear lamina and heterochromatin erosion, resurrection of endogenous retroviruses (ERVs), activated pro-inflammatory cyclic GMP-AMP synthase (cGAS) signaling, and cellular senescence in post-mitotic neurons of aged NHP and human FL. Using human embryonic stem-cell-derived neurons recapitulating cellular aging in vitro, we verified the loss of B-type lamins inducing resurrection of ERVs as an initiating event of the aging-bound cascade in post-mitotic neurons. Of significance, these aging-related cellular and molecular changes can be alleviated by abacavir, a nucleoside reverse transcriptase inhibitor, either through direct treatment of senescent human neurons in vitro or oral administration to aged mice.

Noncoding transcripts are linked to brain resting-state activity in non-human primates

Brain-derived transcriptomes are known to correlate with resting-state brain activity in humans. Whether this association holds in nonhuman primates remains uncertain. Here, we search for such molecular correlates by integrating 757 transcriptomes derived from 100 macaque cortical regions with resting-state activity in separate conspecifics. We observe that 150 noncoding genes explain variations in resting-state activity at a comparable level with protein-coding genes. In-depth analysis of these noncoding genes reveals that they are connected to the function of nonneuronal cells such as oligodendrocytes. Co-expression network analysis finds that the modules of noncoding genes are linked to both autism and schizophrenia risk genes. Moreover, genes associated with resting-state noncoding genes are highly enriched in human resting-state functional genes and memory-effect genes, and their links with resting-state functional magnetic resonance imaging (fMRI) signals are altered in the brains of patients with autism. Our results highlight the potential for noncoding RNAs to explain resting-state activity in the nonhuman primate brain.

Ischemic stroke-related gene expression profiles across species: a meta-analysis

Stroke patients are often left with permanent disabilities with no regenerative treatment options. Unbiased RNA sequencing studies decoding the transcriptional signature of stroked tissue hold promise to identify new potential targets and pathways directed to improve treatment for stroke patients. Here, gene expression profiles of stroked tissue across different time points, species, and stroke models were compared using NCBI GEO database. In total, 34 datasets from mice, rats, humans, and primates were included, exploring gene expression differences in healthy and stroked brain tissue. Distinct changes in gene expression and pathway enrichment revealed the heterogenicity of the stroke pathology in stroke-related pathways e.g., inflammatory responses, vascular repair, remodelling and cell proliferation and adhesion but also in diverse general, stroke-unrelated pathways that have to be carefully considered when evaluating new promising therapeutic targets.

Brain-wide and cell-specific transcriptomic insights into MRI-derived cortical morphology in macaque monkeys

Integrative analyses of transcriptomic and neuroimaging data have generated a wealth of information about biological pathways underlying regional variability in imaging-derived brain phenotypes in humans, but rarely in nonhuman primates due to the lack of a comprehensive anatomically-defined atlas of brain transcriptomics. Here we generate complementary bulk RNA-sequencing dataset of 819 samples from 110 brain regions and single-nucleus RNA-sequencing dataset, and neuroimaging data from 162 cynomolgus macaques, to examine the link between brain-wide gene expression and regional variation in morphometry. We not only observe global/regional expression profiles of macaque brain comparable to human but unravel a dorsolateral-ventromedial gradient of gene assemblies within the primate frontal lobe. Furthermore, we identify a set of 971 protein-coding and 34 non-coding genes consistently associated with cortical thickness, specially enriched for neurons and oligodendrocytes. These data provide a unique resource to investigate nonhuman primate models of human diseases and probe cross-species evolutionary mechanisms.

Deciphering the distinct transcriptomic and gene regulatory map in adult macaque basal ganglia cells

BACKGROUND

The basal ganglia are a complex of interconnected subcortical structures located beneath the mammalian cerebral cortex. The degeneration of dopaminergic neurons in the basal ganglia is the primary pathological feature of Parkinson's disease. Due to a lack of integrated analysis of multiomics datasets across multiple basal ganglia brain regions, very little is known about the regulatory mechanisms of this area.

FINDINGS

We utilized high-throughput transcriptomic and epigenomic analysis to profile over 270,000 single-nucleus cells to create a cellular atlas of the basal ganglia, characterizing the cellular composition of 4 regions of basal ganglia in adult macaque brain, including the striatum, substantia nigra (SN), globus pallidum, and amygdala. We found a distinct epigenetic regulation on gene expression of neuronal and nonneuronal cells across regions in basal ganglia. We identified a cluster of SN-specific astrocytes associated with neurodegenerative diseases and further explored the conserved and primate-specific transcriptomics in SN cell types across human, macaque, and mouse. Finally, we integrated our epigenetic landscape of basal ganglia cells with human disease heritability and identified a regulatory module consisting of candidate cis-regulatory elements that are specific to medium spiny neurons and associated with schizophrenia.

CONCLUSIONS

In general, our macaque basal ganglia atlas provides valuable insights into the comprehensive transcriptome and epigenome of the most important and populous cell populations in the macaque basal ganglia. We have identified 49 cell types based on transcriptomic profiles and 47 cell types based on epigenomic profiles, some of which exhibit region specificity, and characterized the molecular relationships underlying these brain regions.