Alternative splicing generates extraordinary transcriptomic complexity in the human brain, yet the full-length isoform landscape across human cortical cell types remains uncharted. Combining fluorescence-activated nuclei sorting with long- and short-read RNA sequencing, we generated isoform-resolved transcriptomes for five major lineages of the adult human prefrontal and orbitofrontal cortex: GABAergic neurons, glutamatergic neurons, oligodendrocytes, astrocytes, and microglia. We cataloged over 220,000 full-length isoforms, ~35-56% previously unannotated; novel transcripts were longer, more exon-rich, and predominantly protein-coding. Contrary to the neuron-centric view of cortical complexity, glial lineages, particularly oligodendrocytes and microglia, emerged as the most isoform-diverse populations in the cortex. Differential transcript usage and dominant isoform switching defined cell identity, with ~59-62% of differentially regulated transcripts absent from current annotations. Critically, pathogenic variants were enriched >2-fold at novel splice boundaries within disease genes including POGZ, TARDBP, and PLP1, establishing isoform selection as a primary axis of cortical identity and exposing a layer of pathogenic variation invisible to canonical gene annotations.

Healthy brain development requires a coordinated process of postnatal cellular maturation throughout the first two decades of life that transforms neuronal morphology, connectivity, physiology, and gene expression. The maturation and stable maintenance of neuron identity is driven, in part, by large-scale reconfiguration of the neuronal DNA methylome. Neurons have uniquely high levels of 5-hydroxy-methyl-cytosine (hmC) compared to other cell types, yet the relative contributions of 5hmC and 5-methyl-cytosine (mC) remain unknown because most experimental assays do not distinguish these marks. We measured mC and hmC using bisulfite- and oxidative-bisulfite sequencing in excitatory and inhibitory neurons, along with mRNA and histone modifications, from the prefrontal cortex of 103 human donors, ranging from 38 days to 77 years of age. Up to half of all CG dinucleotides convert from mC to hmC in a gradual process extending throughout the first decade of life, dramatically reshaping the neuronal methylome. Asymmetric enrichment of hmC on the sense strand of actively transcribed genes increases in a linear, clock-like fashion throughout the lifespan, indicating a mechanistic link between transcription and hmC. We found that sex differences in X-linked DNA methylation in the human brain are primarily driven by hmCG rather than mCG, suggesting an important role for hmC in X-chromosome inactivation (XCI) and escape gene expression. We found key changes in 5hmC at dynamic cis-regulatory elements marked by changing cell type-specific levels of active and repressive histone modifications. Collectively, our findings reveal the dynamic trajectory of hmC in human neurons across the lifespan and highlight the association of DNA hydroxymethylation with transcription, chromatin state, and sex-specific gene regulation.

Amyotrophic lateral sclerosis (ALS) is frequently driven by GGGGCC short tandem repeat (STR) expansions in C9orf72 , yet the mechanisms by which these expansions lead to neurodegeneration remain incompletely understood. Here, we propose a novel mechanism involving higher-order chromatin architecture where C9orf72 -STR expansions induce widespread, neuron-specific gains in chromatin loops that are closely linked to transcriptomic dysregulation in ALS. These ectopic loops colocalize with the genomic binding sites of C9orf72 -STR RNAs and the architectural protein CTCF, supporting a model in which RNA-DNA interactions promote aberrant loop formation. Together, our findings demonstrate how C9orf72 -STR expansions remodel the neuronal genome and disrupt gene expression, uncovering an RNA-driven mechanism of chromatin reorganization in C9-ALS that connects altered nuclear topology to gene dysregulation in neurodegeneration.

Most genetic variants contributing to complex diseases reside in the noncoding genome. While common variants uncovered by genome-wide association studies often fail to explain much of the observed heritability of these diseases, rare variants often have higher effect sizes and cumulatively explain a larger portion of heritability. However, rare variants, particularly rare noncoding variants, have remained under-characterized largely due to the difficulties of accurately predicting variant functionality at scale, given that each individual carries an average of ~10,000 rare variants. Here, we generated multi-omic data from >3.3 million nuclei sampled from five brain regions across a cohort of 80 individuals with Parkinson's disease (PD) and 21 neurologically normal control individuals with matched 30x whole-genome sequencing. We use this data to identify cell type-specific features of PD, map cell type-specific chromatin accessibility and expression quantitative trait loci, and train machine learning models to predict the effect of variants on gene regulation. We identify rare noncoding variants statistically associated with sporadic PD and extend our approaches to predict drivers of familial PD of unknown genetic origin. Our results underscore the significance of rare noncoding variants in complex diseases and provide a roadmap for applying similar approaches in other disease systems.

Human brain development spans from embryogenesis to adulthood, with dynamic gene expression controlled by cell-type-specific cis-regulatory element activity and three-dimensional genome organization. To advance our understanding of postnatal brain development, we simultaneously profiled gene expression and chromatin accessibility in 101,924 single nuclei from four brain regions across ten donors, covering five key postnatal stages from infancy to late adulthood. Using this dataset and chromosome conformation capture data, we constructed enhancer-based gene regulatory networks to identify cell-type-specific regulators of brain development and interpret genome-wide association study loci for ten main brain disorders. Our analysis connected 2,318 cell-specific loci to 1,149 unique genes, representing 41% of loci linked to the investigated traits, and highlighted 55 genes influencing several disease phenotypes. Pseudotime analysis revealed distinct stages of postnatal oligodendrogenesis and their regulatory programs. These findings provide a comprehensive dataset of cell-type-specific gene regulation at critical timepoints in postnatal brain development.

Alternative splicing generates extensive transcriptomic diversity in the human brain, but the full cell type-resolved landscape of isoform variation remains unresolved due to the constraints of short-read sequencing. Here, we integrated fluorescence-activated nuclei sorting with long-read (PacBio Iso-Seq) and short-read (Illumina) RNA sequencing to generate isoform-resolved transcriptomes of five major cortical cell types, including MGE-derived GABAergic neurons, glutamatergic neurons, oligodendrocytes, astrocytes, and microglia from adult dorsolateral and orbitofrontal cortex. We identified more than 220,000 unique full-length isoforms, 35–56% of which were previously unannotated depending on cell type and region. These novel isoforms were longer, contained more exons, and displayed greater coding potential than annotated transcripts. Glial populations, particularly oligodendrocytes and microglia, exhibited the greatest isoform diversity, with more than half of all isoforms displaying strong cell type–specific expression. Differential transcript usage revealed pervasive cell-specific splicing, including in genes central to neuronal and glial function such as SLC5A6 and TWF1 . Many newly discovered isoforms intersected with genetic risk variants for neurological disorders, including for POGZ , FOXP1 , and DYRK1A , suggesting that isoform diversification may contribute to disease risk. This resource provides a comprehensive, cell type–resolved atlas of isoform diversity in the human cortex and establishes a foundation for mechanistic studies of RNA regulation and disease vulnerability in the brain. ### Competing Interest Statement The authors have declared no competing interest.

The neurodegenerative disorders Alzheimer's disease (AD) and Lewy body dementia (LBD) share genetic and clinicopathological overlap and may constitute a disease spectrum. Common variant genome-wide association studies (GWASs) have uncovered AD and LBD etiology. However, common variant GWASs identify loci not genes, hence post-GWAS functional mapping analyses are needed to elucidate genetic risk mechanisms and drive therapeutic development. AD and LBD genetic risk mechanisms and their overlap are poorly understood. We performed functional mapping, integrating AD and LBD GWAS sumstats with brain cell type-specific epigenomic datasets and enrichment analysis to nominate candidate causal disease risk genes and pathways. Building on multi-marker analysis of genomic annotation (MAGMA), we developed the novel tool annotation- and interaction-based MAGMA (AI-MAGMA). AI-MAGMA integrates GWAS sumstats with chromatin annotation and interaction data to nominate candidate causal risk genes (Figure 1). We used AI-MAGMA to integrate AD and LBD GWAS sumstats with microglial, neuronal, and oligodendroglial (oligodendrocytes and oligodendrocyte precursor cells) bulk chromatin immunoprecipitation-sequencing (ChIP-seq) (annotation) and bulk proximity ligation-assisted chromatin immunoprecipitation-seq (PLAC-seq) (interaction) data to nominate candidate causal genes mediating disease risk in these brain cell types. We performed enrichment analysis with gProfiler to identify disease pathways implicated by these genes. Integrative functional mapping nominated AD (354 microglial, 203 neuronal, and 144 oligodendroglial) and LBD (40 microglial, 16 neuronal, and 22 oligodendroglial) candidate causal risk genes achieving study-wide significance ( p -value < 0.05/n genes analyzed). AD pathway enrichment highlighted: amyloid, lipid metabolism, endocytosis, phagocytosis, and immunity in microglia; amyloid and neurofibrillary tangles in neurons; and amyloid, lipid metabolism, and blood-brain barrier in oligodendroglia. LBD pathway enrichment revealed: lipid metabolism, endocytosis, and mitochondria in microglia; synuclein in neurons; and amyloid, lipid metabolism, synapse, and blood-brain barrier in oligodendroglia. Functional mapping nominated dozens of AD and LBD candidate causal risk genes. Pathway enrichment implicated microglial lipid metabolism and endocytosis as well as oligodendroglial amyloid, lipid metabolism, and blood-brain barrier as pathophysiological mechanisms shared across AD and LBD. These analyses also suggested roles for mitochondria and synapses in LBD microglia and oligodendroglia, respectively, enhancing our understanding of LBD genetic risk mechanisms.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, yet its epigenetic underpinnings remain elusive. Here, we generate and integrate single-cell epigenomic and transcriptomic profiles of 3.5 million cells from 384 postmortem brain samples across 6 regions in 111 AD and control individuals. We identify over 1 million candidate cis-regulatory elements (cCREs), organized into 123 regulatory modules across 67 cell subtypes. We define large-scale epigenomic compartments and single-cell epigenomic information and delineate their dynamics in AD, revealing widespread epigenome relaxation and brain-region-specific and cell-type-specific epigenomic erosion signatures during AD progression. These epigenomic stability dynamics are closely associated with cell-type proportion changes, glial cell-state transitions, and coordinated epigenomic and transcriptomic dysregulation linked to AD pathology, cognitive impairment, and cognitive resilience. This study provides critical insights into AD progression and cognitive resilience, presenting a comprehensive single-cell multiomic atlas to advance the understanding of AD.

BACKGROUND:Identifying neurobiological targets predictive of the molecular neuropathophysiological signature of human opioid use disorder (OUD) could expedite new treatments. OUD is characterized by dysregulated cognition and goal-directed behavior mediated by the orbitofrontal cortex (OFC), and next-generation sequencing could provide insights regarding novel targets. METHODS:Here, we used machine learning to evaluate human postmortem OFC RNA sequencing datasets from heroin users and control participants to identify transcripts that were predictive of heroin use. To determine a causal link to OUD-related behaviors, we examined the effects of overexpressing the top target gene in a translational rat model of heroin seeking and behavioral updating. Additionally, we determined the effects of overexpression on the rat OFC transcriptome compared with that of human heroin users. Co-immunoprecipitation/mass spectrometry (co-IP/MS) from the rat OFC elucidated the protein complex of the novel target. RESULTS:Our machine learning approach identified SHISA7 as predictive of human heroin users. Shisa7 is understudied but appears to be an auxiliary protein of GABAA (gamma-aminobutyric acid A) or AMPA receptors. In rats, Shisa7 expression positively correlated with heroin-seeking behavior. Overexpressing Shisa7 in the OFC augmented heroin seeking and impaired behavioral updating for sucrose-based operant contingency. RNA sequencing of rat OFC revealed gene coexpression networks regulated by Shisa7 overexpression similar to human heroin users. Finally, co-IP/MS showed that heroin influenced Shisa7 binding to glutamatergic and GABAergic receptor subunits. Both gene expression signatures and Shisa7 protein complex emphasized perturbations of neurodegenerative and neuroimmune processes. CONCLUSIONS:Our findings suggest that OFC Shisa7 is a critical driver of neurobehavioral pathology related to drug-seeking behavior and behavioral updating, thus identifying a potential therapeutic target for OUD.

Supplementary Methods Supplementary Figure 1 Unsupervised DNA methylation analysis of the training cohort. Supplementary Figure 2 Comparison between the Illumina Infinium Human Methylation450K BeadChip and the Methylation EPIC BeadChip 850K array platforms. Supplementary Figure 3 Specificity of the epigenetic biomarkers for medulloblastoma subgroups. Supplementary Figure 4 Assay performance for low-input titration series. Supplementary Figure 5 Validation of the epigenetic classifier Panel EpiWNT-SHH using DNA methylation microarray data of medulloblastoma samples. Supplementary Figure 6 Validation of the methylation pattern of Panel EpiWNT-SHH using pyrosequencing and direct bisulfite sequencing. Supplementary Figure 7 Schematic overview of the experimental strategy applied for identification of the epigenetic biomarkers and the development of the classifier EpiG3-G4. Supplementary Figure 8 Validation of the epigenetic classifier Panel EpiG3-G4 using DNA methylation microarray data.

A repeat expansion in the C9orf72 (C9) gene is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here we investigate single nucleus transcriptomics (snRNA-seq) and epigenomics (snATAC-seq) in postmortem motor and frontal cortices from C9-ALS, C9-FTD, and control donors. C9-ALS donors present pervasive alterations of gene expression with concordant changes in chromatin accessibility and histone modifications. The greatest alterations occur in upper and deep layer excitatory neurons, as well as in astrocytes. In neurons, the changes imply an increase in proteostasis, metabolism, and protein expression pathways, alongside a decrease in neuronal function. In astrocytes, the alterations suggest activation and structural remodeling. Conversely, C9-FTD donors have fewer high-quality neuronal nuclei in the frontal cortex and numerous gene expression changes in glial cells. These findings highlight a context-dependent molecular disruption in C9-ALS and C9-FTD, indicating unique effects across cell types, brain regions, and diseases.

Supplementary Table 1 SampleSheet Supplementary Table 2 GEO_IDs Supplementary Table 3 EpiWNT-SHH_data Supplementary Table 4 EpiWNT-SHH_test Supplementary Table 5 EpiG3-G4_data Supplementary Table 6 EpiG3-G4_test

Oligodendrocyte precursor cells (OPCs) generate differentiated mature oligodendrocytes (MOs) during development. In adult brain, OPCs replenish MOs in adaptive plasticity, neurodegenerative disorders, and after trauma. The ability of OPCs to differentiate to MOs decreases with age and is compromised in disease. Here we explored the cell specific and age-dependent differences in gene expression and H3K27ac histone mark in these two cell types. H3K27ac is indicative of active promoters and enhancers. We developed a novel flow-cytometry-based approach to isolate OPC and MO nuclei from human postmortem brain and profiled gene expression and H3K27ac in adult and infant OPCs and MOs genome-wide. In adult brain, we detected extensive H3K27ac differences between the two cell types with high concordance between gene expression and epigenetic changes. Notably, the expression of genes that distinguish MOs from OPCs appears to be under a strong regulatory control by the H3K27ac modification in MOs but not in OPCs. Comparison of gene expression and H3K27ac between infants and adults uncovered numerous developmental changes in each cell type, which were linked to several biological processes, including cell proliferation and glutamate signaling. A striking example was a subset of histone genes that were highly active in infant samples but fully lost activity in adult brain. Our findings demonstrate a considerable rearrangement of the H3K27ac landscape that occurs during the differentiation of OPCs to MOs and during postnatal development of these cell types, which aligned with changes in gene expression. The uncovered regulatory changes justify further in-depth epigenetic studies of OPCs and MOs in development and disease.

Schizophrenia is a complex neuropsychiatric disorder which affects approximately 1% of the population. GWAS has enabled the discovery of risk genes associated with schizophrenia while functional studies have explored alterations in gene expression and regulation. There is an increasing focus on studying the molecular mechanisms of this disorder at cell-type resolution. Cell-type specific gene expression changes in schizophrenia are largely unexplored, particularly at the transcript level. As such, we aimed to investigate disease-specific changes in gene expression across a range of cell-types. RNA-seq was carried out to profile gene expression in prefrontal cortex tissue from schizophrenia cases (n=50) and controls (n=50). For each individual, four cell-types were isolated via fluorescence activated nuclear sorting (FANS), including GABAergic neurons (neuN+/sox6+), glutamatergic neurons (neuN+/sox6-), oligodendrocytes (neuN-/sox10+) and microglia/astrocytes (neuN-/sox10-). Differential analysis was carried out using DREAM and remaCor. MAGMA was used to test differentially expressed genes and transcripts for enrichment of common genetic variants associated with schizophrenia while gene-set enrichment analysis was used to identify perturbed pathways and biological processes. The cell-type specific profiles were also used as a reference to identify cell-type proportions in bulk RNA-seq data (n=870 samples) and subsequently impute expression profiles for the four cell-types using bMIND. Differential analysis at both gene and transcript levels yielded marked differences in terms of genes implicated. A large majority of the significant genes identified in the transcript analysis were not observed in the gene level analysis, indicating the need to study differences in transcript expression at cell-type resolution. Different isoforms of KMT5A, a known schizophrenia risk gene, were implicated in GABAergic neurons and oligodendrocytes, and were not observed in traditional gene or transcript level analysis. CACNA1C isoforms were also differentially expressed only in oligodendrocytes, again highlighting the need to explore these changes at the cell-type level. Enrichment analysis for the gene sets identified in both analyses returned differing results with the gene-level analysis implicating synaptic density and dysfunction. Cell-type specific imputed gene and transcript expression profiles for 870 individuals were created using the FANS data as a reference. This greatly increased our power to identify disease associated expression changes in comparison to the FANS analysis and enabled a QTL analysis to link expression changes to genetic variants. Overall, these analyses explored altered biology in schizophrenia on a cell-type specific basis and placed particular emphasis on transcript changes which have been understudied at the cell-type level to date. The identification of altered transcript expression may further our understanding of the neurobiology of schizophrenia.

Neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), are strongly influenced by inherited genetic variation, but environmental and epigenetic factors also play key roles in the course of these diseases. A hexanucleotide repeat expansion in the C9orf72 (C9) gene is the most common genetic cause of ALS and FTD. To determine the cellular alterations associated with the C9 repeat expansion, we performed single nucleus transcriptomics (snRNA-seq) and epigenomics (snATAC-seq) in postmortem samples of motor and frontal cortices from C9-ALS and C9-FTD donors. We found pervasive alterations of gene expression across multiple cortical cell types in C9-ALS, with the largest number of affected genes in astrocytes and excitatory neurons. Astrocytes increased expression of markers of activation and pathways associated with structural remodeling. Excitatory neurons in upper and deep layers increased expression of genes related to proteostasis, metabolism, and protein expression, and decreased expression of genes related to neuronal function. Epigenetic analyses revealed concordant changes in chromatin accessibility, histone modifications, and gene expression in specific cell types. C9-FTD patients had a distinct pattern of changes, including loss of neurons in frontal cortex and altered expression of thousands of genes in astrocytes and oligodendrocyte-lineage cells. Overall, these findings demonstrate a context-dependent molecular disruption in C9-ALS and C9-FTD, resulting in distinct effects across cell types, brain regions, and disease phenotypes. One Sentence Summary C9orf72-associated ALS and FTD showed a distinct pattern of transcriptome changes, with the largest number of affected genes in C9-ALS in astrocytes and excitatory neurons in upper and deep layers. ### Competing Interest Statement The authors have declared no competing interest.

Posttranscriptional adenosine-to-inosine modifications amplify the functionality of RNA molecules in the brain, yet the cellular and genetic regulation of RNA editing is poorly described. We quantify base-specific RNA editing across three major cell populations from the human prefrontal cortex: glutamatergic neurons, medial ganglionic eminence-derived GABAergic neurons, and oligodendrocytes. We identify more selective editing and hyper-editing in neurons relative to oligodendrocytes. RNA editing patterns are highly cell type-specific, with 189,229 cell type-associated sites. The cellular specificity for thousands of sites is confirmed by single nucleus RNA-sequencing. Importantly, cell type-associated sites are enriched in GTEx RNA-sequencing data, edited ~twentyfold higher than all other sites, and variation in RNA editing is largely explained by neuronal proportions in bulk brain tissue. Finally, we uncover 661,791 cis-editing quantitative trait loci across thirteen brain regions, including hundreds with cell type-associated features. These data reveal an expansive repertoire of highly regulated RNA editing sites across human brain cell types and provide a resolved atlas linking cell types to editing variation and genetic regulatory effects.

BACKGROUND:While schizophrenia differs between males and females in the age of onset, symptomatology, and disease course, the molecular mechanisms underlying these differences remain uncharacterized. METHODS:To address questions about the sex-specific effects of schizophrenia, we performed a large-scale transcriptome analysis of RNA sequencing data from 437 controls and 341 cases from two distinct cohorts from the CommonMind Consortium. RESULTS:Analysis across the cohorts identified a reproducible gene expression signature of schizophrenia that was highly concordant with previous work. Differential expression across sex was reproducible across cohorts and identified X- and Y-linked genes, as well as those involved in dosage compensation. Intriguingly, the sex expression signature was also enriched for genes involved in neurexin family protein binding and synaptic organization. Differential expression analysis testing a sex-by-diagnosis interaction effect did not identify any genome-wide signature after multiple testing corrections. Gene coexpression network analysis was performed to reduce dimensionality from thousands of genes to dozens of modules and elucidate interactions among genes. We found enrichment of coexpression modules for sex-by-diagnosis differential expression signatures, which were highly reproducible across the two cohorts and involved a number of diverse pathways, including neural nucleus development, neuron projection morphogenesis, and regulation of neural precursor cell proliferation. CONCLUSIONS:Overall, our results indicate that the effect size of sex differences in schizophrenia gene expression signatures is small and underscore the challenge of identifying robust sex-by-diagnosis signatures, which will require future analyses in larger cohorts.

Chromosomal organization, scaling from the 147-base pair (bp) nucleosome to megabase-ranging domains encompassing multiple transcriptional units, including heritability loci for psychiatric traits, remains largely unexplored in the human brain. In this study, we constructed promoter- and enhancer-enriched nucleosomal histone modification landscapes for adult prefrontal cortex from H3-lysine 27 acetylation and H3-lysine 4 trimethylation profiles, generated from 388 controls and 351 individuals diagnosed with schizophrenia (SCZ) or bipolar disorder (BD) (n = 739). We mapped thousands of cis-regulatory domains (CRDs), revealing fine-grained, 104–106-bp chromosomal organization, firmly integrated into Hi-C topologically associating domain stratification by open/repressive chromosomal environments and nuclear topography. Large clusters of hyper-acetylated CRDs were enriched for SCZ heritability, with prominent representation of regulatory sequences governing fetal development and glutamatergic neuron signaling. Therefore, SCZ and BD brains show coordinated dysregulation of risk-associated regulatory sequences assembled into kilobase- to megabase-scaling chromosomal domains. Girdhar et al. constructed chromosomal domains from prefrontal histone acetylation and methylation maps and discovered, in a large cohort of schizophrenia and bipolar brains, converging alignment by genetic risk, neuronal function and three-dimensional genomics.

Aim: Identify grey- and white-matter-specific DNA-methylation differences between schizophrenia (SCZ) patients and controls in postmortem brain cortical tissue. Materials & methods: Grey and white matter were separated from postmortem brain tissue of the superior temporal and medial frontal gyrus from SCZ (n = 10) and control (n = 11) cases. Genome-wide DNA-methylation analysis was performed using the Infinium EPIC Methylation Array (Illumina, CA, USA). Results: Four differentially methylated regions associated with SCZ status and tissue type (grey vs white matter) were identified within or near KLF9, SFXN1, SPRED2 and ALS2CL genes. Gene-expression analysis showed differential expression of KLF9 and SFXN1 in SCZ. Conclusion: Our data show distinct differences in DNA methylation between grey and white matter that are unique to SCZ, providing new leads to unravel the pathogenesis of SCZ.

Elucidating brain cell type specific gene expression patterns is critical towards a better understanding of how cell-cell communications may influence brain functions and dysfunctions. We set out to compare and contrast five human and murine cell type-specific transcriptome-wide RNA expression data sets that were generated within the past several years. We defined three measures of brain cell type-relative expression including specificity, enrichment, and absolute expression and identified corresponding consensus brain cell “signatures,” which were well conserved across data sets. We validated that the relative expression of top cell type markers are associated with proxies for cell type proportions in bulk RNA expression data from postmortem human brain samples. We further validated novel marker genes using an orthogonal ATAC-seq dataset. We performed multiscale coexpression network analysis of the single cell data sets and identified robust cell-specific gene modules. To facilitate the use of the cell type-specific genes for cell type proportion estimation and deconvolution from bulk brain gene expression data, we developed an R package, BRETIGEA. In summary, we identified a set of novel brain cell consensus signatures and robust networks from the integration of multiple datasets and therefore transcend limitations related to technical issues characteristic of each individual study.