TrkB-dependent regulation of molecular signaling across septal cell types.

The lateral septum (LS), a GABAergic structure located in the basal forebrain, is implicated in social behavior, learning, and memory. We previously demonstrated that expression of tropomyosin kinase receptor B (TrkB) in LS neurons is required for social novelty recognition. To better understand molecular mechanisms by which TrkB signaling controls behavior, we locally knocked down TrkB in LS and used bulk RNA-sequencing to identify changes in gene expression downstream of TrkB. TrkB knockdown induces upregulation of genes associated with inflammation and immune responses, and downregulation of genes associated with synaptic signaling and plasticity. Next, we generated one of the first atlases of molecular profiles for LS cell types using single nucleus RNA-sequencing (snRNA-seq). We identified markers for the septum broadly, and the LS specifically, as well as for all neuronal cell types. We then investigated whether the differentially expressed genes (DEGs) induced by TrkB knockdown map to specific LS cell types. Enrichment testing identified that downregulated DEGs are broadly expressed across neuronal clusters. Enrichment analyses of these DEGs demonstrated that downregulated genes are uniquely expressed in the LS, and associated with either synaptic plasticity or neurodevelopmental disorders. Upregulated genes are enriched in LS microglia, associated with immune response and inflammation, and linked to both neurodegenerative disease and neuropsychiatric disorders. In addition, many of these genes are implicated in regulating social behaviors. In summary, the findings implicate TrkB signaling in the LS as a critical regulator of gene networks associated with psychiatric disorders that display social deficits, including schizophrenia and autism, and with neurodegenerative diseases, including Alzheimer's.

TCF4 Mutations Disrupt Synaptic Function Through Dysregulation of RIMBP2 in Patient-Derived Cortical Neurons.

BACKGROUND: Genetic variation in the TCF4 (transcription factor 4) gene is associated with risk for a variety of developmental and psychiatric conditions, which includes a syndromic form of autism spectrum disorder called Pitt-Hopkins syndrome (PTHS). TCF4 encodes an activity-dependent transcription factor that is highly expressed during cortical development and in animal models has been shown to regulate various aspects of neuronal development and function. However, our understanding of how disease-causing mutations in TCF4 confer pathophysiology in a human context is lacking. METHODS: To model PTHS, we differentiated human cortical neurons from human induced pluripotent stem cells that were derived from patients with PTHS and neurotypical individuals. To identify pathophysiology and disease mechanisms, we assayed cortical neurons with whole-cell electrophysiology, Ca2+ imaging, multielectrode arrays, immunocytochemistry, and RNA sequencing. RESULTS: Cortical neurons derived from patients with TCF4 mutations showed deficits in spontaneous synaptic transmission, network excitability, and homeostatic plasticity. Transcriptomic analysis indicated that these phenotypes resulted in part from altered expression of genes involved in presynaptic neurotransmission and identified the presynaptic binding protein RIMBP2 as the most differentially expressed gene in PTHS neurons. Remarkably, TCF4-dependent deficits in spontaneous synaptic transmission and network excitability were rescued by increasing RIMBP2 expression in presynaptic neurons. CONCLUSIONS: Taken together, these results identify TCF4 as a critical transcriptional regulator of human synaptic development and plasticity and specifically identifies dysregulation of presynaptic function as an early pathophysiology in PTHS.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci.

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWAS) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N=52) and nonsmokers (N=171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and using a two-stage multiple testing approach with eigenMT and Bonferroni corrections. We found >2 million significant meQTL variants (padj<0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects; five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTLs for 958 unique eGenes (padj<0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTIN1 and ITIH4 colocalized across all data types (GWAS + meQTL + eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

BiocMAP: a Bioconductor-friendly, GPU-accelerated pipeline for bisulfite-sequencing data.

BACKGROUND: Bisulfite sequencing is a powerful tool for profiling genomic methylation, an epigenetic modification critical in the understanding of cancer, psychiatric disorders, and many other conditions. Raw data generated by whole genome bisulfite sequencing (WGBS) requires several computational steps before it is ready for statistical analysis, and particular care is required to process data in a timely and memory-efficient manner. Alignment to a reference genome is one of the most computationally demanding steps in a WGBS workflow, taking several hours or even days with commonly used WGBS-specific alignment software. This naturally motivates the creation of computational workflows that can utilize GPU-based alignment software to greatly speed up the bottleneck step. In addition, WGBS produces raw data that is large and often unwieldy; a lack of memory-efficient representation of data by existing pipelines renders WGBS impractical or impossible to many researchers. RESULTS: We present BiocMAP, a Bioconductor-friendly methylation analysis pipeline consisting of two modules, to address the above concerns. The first module performs computationally-intensive read alignment using Arioc, a GPU-accelerated short-read aligner. Since GPUs are not always available on the same computing environments where traditional CPU-based analyses are convenient, the second module may be run in a GPU-free environment. This module extracts and merges DNA methylation proportions-the fractions of methylated cytosines across all cells in a sample at a given genomic site. Bioconductor-based output objects in R utilize an on-disk data representation to drastically reduce required main memory and make WGBS projects computationally feasible to more researchers. CONCLUSIONS: BiocMAP is implemented using Nextflow and available at http://research.libd.org/BiocMAP/ . To enable reproducible analysis across a variety of typical computing environments, BiocMAP can be containerized with Docker or Singularity, and executed locally or with the SLURM or SGE scheduling engines. By providing Bioconductor objects, BiocMAP's output can be integrated with powerful analytical open source software for analyzing methylation data.

TrkB-dependent regulation of molecular signaling across septal cell types.

The lateral septum (LS), a GABAergic structure located in the basal forebrain, is implicated in social behavior, learning and memory. We previously demonstrated that expression of tropomyosin kinase receptor B (TrkB) in LS neurons is required for social novelty recognition. To better understand molecular mechanisms by which TrkB signaling controls behavior, we locally knocked down TrkB in LS and used bulk RNA-sequencing to identify changes in gene expression downstream of TrkB. TrkB knockdown induces upregulation of genes associated with inflammation and immune responses, and downregulation of genes associated with synaptic signaling and plasticity. Next, we generated one of the first atlases of molecular profiles for LS cell types using single nucleus RNA-sequencing (snRNA-seq). We identified markers for the septum broadly, and the LS specifically, as well as for all neuronal cell types. We then investigated whether the differentially expressed genes (DEGs) induced by TrkB knockdown map to specific LS cell types. Enrichment testing identified that downregulated DEGs are broadly expressed across neuronal clusters. Enrichment analyses of these DEGs demonstrated that downregulated genes are uniquely expressed in the LS, and associated with either synaptic plasticity or neurodevelopmental disorders. Upregulated genes are enriched in LS microglia, associated with immune response and inflammation, and linked to both neurodegenerative disease and neuropsychiatric disorders. In addition, many of these genes are implicated in regulating social behaviors. In summary, the findings implicate TrkB signaling in the LS as a critical regulator of gene networks associated with psychiatric disorders that display social deficits, including schizophrenia and autism, and with neurodegenerative diseases, including Alzheimer's.

Hypermetabolism in mice carrying a near-complete human chromosome 21.

The consequences of aneuploidy have traditionally been studied in cell and animal models in which the extrachromosomal DNA is from the same species. Here, we explore a fundamental question concerning the impact of aneuploidy on systemic metabolism using a non-mosaic transchromosomic mouse model (TcMAC21) carrying a near-complete human chromosome 21. Independent of diets and housing temperatures, TcMAC21 mice consume more calories, are hyperactive and hypermetabolic, remain consistently lean and profoundly insulin sensitive, and have a higher body temperature. The hypermetabolism and elevated thermogenesis are likely due to a combination of increased activity level and sarcolipin overexpression in the skeletal muscle, resulting in futile sarco(endo)plasmic reticulum Ca2+ ATPase (SERCA) activity and energy dissipation. Mitochondrial respiration is also markedly increased in skeletal muscle to meet the high ATP demand created by the futile cycle and hyperactivity. This serendipitous discovery provides proof-of-concept that sarcolipin-mediated thermogenesis via uncoupling of the SERCA pump can be harnessed to promote energy expenditure and metabolic health.

Genetic and environmental contributions to ancestry differences in gene expression in the human brain.

Ancestral differences in genomic variation are determining factors in gene regulation; however, most gene expression studies have been limited to European ancestry samples or adjusted for ancestry to identify ancestry-independent associations. We instead examined the impact of genetic ancestry on gene expression and DNA methylation (DNAm) in admixed African/Black American neurotypical individuals to untangle effects of genetic and environmental factors. Ancestry-associated differentially expressed genes (DEGs), transcripts, and gene networks, while notably not implicating neurons, are enriched for genes related to immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson's disease, and 30% of heritability for Alzhemier's disease. Ancestry-associated DEGs also show general enrichment for heritability of diverse immune-related traits but depletion for psychiatric-related traits. The cell-type enrichments and direction of effects vary by brain region. These DEGs are less evolutionarily constrained and are largely explained by genetic variations; roughly 15% are predicted by DNAm variation implicating environmental exposures. We also compared Black and White Americans, confirming most of these ancestry-associated DEGs. Our results highlight how environment and genetic background affect genetic ancestry differences in gene expression in the human brain and affect risk for brain illness.

Cross-ancestry, cell-type-informed atlas of gene, isoform, and splicing regulation in the developing human brain.

Genomic regulatory elements active in the developing human brain are notably enriched in genetic risk for neuropsychiatric disorders, including autism spectrum disorder (ASD), schizophrenia, and bipolar disorder. However, prioritizing the specific risk genes and candidate molecular mechanisms underlying these genetic enrichments has been hindered by the lack of a single unified large-scale gene regulatory atlas of human brain development. Here, we uniformly process and systematically characterize gene, isoform, and splicing quantitative trait loci (xQTLs) in 672 fetal brain samples from unique subjects across multiple ancestral populations. We identify 15,752 genes harboring a significant xQTL and map 3,739 eQTLs to a specific cellular context. We observe a striking drop in gene expression and splicing heritability as the human brain develops. Isoform-level regulation, particularly in the second trimester, mediates the greatest proportion of heritability across multiple psychiatric GWAS, compared with eQTLs. Via colocalization and TWAS, we prioritize biological mechanisms for ~60% of GWAS loci across five neuropsychiatric disorders, nearly two-fold that observed in the adult brain. Finally, we build a comprehensive set of developmentally regulated gene and isoform co-expression networks capturing unique genetic enrichments across disorders. Together, this work provides a comprehensive view of genetic regulation across human brain development as well as the stage-and cell type-informed mechanistic underpinnings of neuropsychiatric disorders.

Hypermetabolism in mice carrying a near complete human chromosome 21.

The consequences of aneuploidy have traditionally been studied in cell and animal models in which the extrachromosomal DNA is from the same species. Here, we explore a fundamental question concerning the impact of aneuploidy on systemic metabolism using a non-mosaic transchromosomic mouse model (TcMAC21) carrying a near complete human chromosome 21. Independent of diets and housing temperatures, TcMAC21 mice consume more calories, are hyperactive and hypermetabolic, remain consistently lean and profoundly insulin sensitive, and have a higher body temperature. The hypermetabolism and elevated thermogenesis are due to sarcolipin overexpression in the skeletal muscle, resulting in futile sarco(endo)plasmic reticulum Ca 2+ ATPase (SERCA) activity and energy dissipation. Mitochondrial respiration is also markedly increased in skeletal muscle to meet the high ATP demand created by the futile cycle. This serendipitous discovery provides proof-of-concept that sarcolipin-mediated thermogenesis via uncoupling of the SERCA pump can be harnessed to promote energy expenditure and metabolic health.

Associations of psychiatric disease and ageing with FKBP5 expression converge on superficial layer neurons of the neocortex.

Identification and characterisation of novel targets for treatment is a priority in the field of psychiatry. FKBP5 is a gene with decades of evidence suggesting its pathogenic role in a subset of psychiatric patients, with potential to be leveraged as a therapeutic target for these individuals. While it is widely reported that FKBP5/FKBP51 mRNA/protein (FKBP5/1) expression is impacted by psychiatric disease state, risk genotype and age, it is not known in which cell types and sub-anatomical areas of the human brain this occurs. This knowledge is critical to propel FKBP5/1-targeted treatment development. Here, we performed an extensive, large-scale postmortem study (n = 1024) of FKBP5/1, examining neocortical areas (BA9, BA11 and ventral BA24/BA24a) derived from subjects that lived with schizophrenia, major depression or bipolar disorder. With an extensive battery of RNA (bulk RNA sequencing, single-nucleus RNA sequencing, microarray, qPCR, RNAscope) and protein (immunoblot, immunohistochemistry) analysis approaches, we thoroughly investigated the effects of disease state, ageing and genotype on cortical FKBP5/1 expression including in a cell type-specific manner. We identified consistently heightened FKBP5/1 levels in psychopathology and with age, but not genotype, with these effects strongest in schizophrenia. Using single-nucleus RNA sequencing (snRNAseq; BA9 and BA11) and targeted histology (BA9, BA24a), we established that these disease and ageing effects on FKBP5/1 expression were most pronounced in excitatory superficial layer neurons of the neocortex, and this effect appeared to be consistent in both the granular and agranular areas examined. We then found that this increase in FKBP5 levels may impact on synaptic plasticity, as FKBP5 gex levels strongly and inversely correlated with dendritic mushroom spine density and brain-derived neurotrophic factor (BDNF) levels in superficial layer neurons in BA11. These findings pinpoint a novel cellular and molecular mechanism that has potential to open a new avenue of FKBP51 drug development to treat cognitive symptoms in psychiatric disorders.

Dysregulated systemic metabolism in a Down syndrome mouse model.

OBJECTIVE: Trisomy 21 is one of the most complex genetic perturbations compatible with postnatal survival. Dosage imbalance arising from the triplication of genes on human chromosome 21 (Hsa21) affects multiple organ systems. Much of Down syndrome (DS) research, however, has focused on addressing how aneuploidy dysregulates CNS function leading to cognitive deficit. Although obesity, diabetes, and associated sequelae such as fatty liver and dyslipidemia are well documented in the DS population, only limited studies have been conducted to determine how gene dosage imbalance affects whole-body metabolism. Here, we conduct a comprehensive and systematic analysis of key metabolic parameters across different physiological states in the Ts65Dn trisomic mouse model of DS. METHODS: Ts65Dn mice and euploid littermates were subjected to comprehensive metabolic phenotyping under basal (chow-fed) state and the pathophysiological state of obesity induced by a high-fat diet (HFD). RNA sequencing of liver, skeletal muscle, and two major fat depots were conducted to determine the impact of aneuploidy on tissue transcriptome. Pathway enrichments, gene-centrality, and key driver estimates were performed to provide insights into tissue autonomous and non-autonomous mechanisms contributing to the dysregulation of systemic metabolism. RESULTS: Under the basal state, chow-fed Ts65Dn mice of both sexes had elevated locomotor activity and energy expenditure, reduced fasting serum cholesterol levels, and mild glucose intolerance. Sexually dimorphic deterioration in metabolic homeostasis became apparent when mice were challenged with a high-fat diet. While obese Ts65Dn mice of both sexes exhibited dyslipidemia, male mice also showed impaired systemic insulin sensitivity, reduced mitochondrial activity, and elevated fibrotic and inflammatory gene signatures in the liver and adipose tissue. Systems-level analysis highlighted conserved pathways and potential endocrine drivers of adipose-liver crosstalk that contribute to dysregulated glucose and lipid metabolism. CONCLUSIONS: A combined alteration in the expression of trisomic and disomic genes in peripheral tissues contribute to metabolic dysregulations in Ts65Dn mice. These data lay the groundwork for understanding the impact of aneuploidy on in vivo metabolism.

SUFI: an automated approach to spectral unmixing of fluorescent multiplex images captured in mouse and post-mortem human brain tissues.

BACKGROUND: Multispectral fluorescence imaging coupled with linear unmixing is a form of image data collection and analysis that allows for measuring multiple molecular signals in a single biological sample. Multiple fluorescent dyes, each measuring a unique molecule, are simultaneously measured and subsequently "unmixed" to provide a read-out for each molecular signal. This strategy allows for measuring highly multiplexed signals in a single data capture session, such as multiple proteins or RNAs in tissue slices or cultured cells, but can often result in mixed signals and bleed-through problems across dyes. Existing spectral unmixing algorithms are not optimized for challenging biological specimens such as post-mortem human brain tissue, and often require manual intervention to extract spectral signatures. We therefore developed an intuitive, automated, and flexible package called SUFI: spectral unmixing of fluorescent images. RESULTS: This package unmixes multispectral fluorescence images by automating the extraction of spectral signatures using vertex component analysis, and then performs one of three unmixing algorithms derived from remote sensing. We evaluate these remote sensing algorithms' performances on four unique biological datasets and compare the results to unmixing results obtained using ZEN Black software (Zeiss). We lastly integrate our unmixing pipeline into the computational tool dotdotdot, which is used to quantify individual RNA transcripts at single cell resolution in intact tissues and perform differential expression analysis, and thereby provide an end-to-end solution for multispectral fluorescence image analysis and quantification. CONCLUSIONS: In summary, we provide a robust, automated pipeline to assist biologists with improved spectral unmixing of multispectral fluorescence images.

TCF4 mutations disrupt synaptic function through dysregulation of RIMBP2 in patient-derived cortical neurons.

Genetic variation in the transcription factor 4 ( TCF4) gene is associated with risk for a variety of developmental and psychiatric conditions, which includes a syndromic form of ASD called Pitt Hopkins Syndrome (PTHS). TCF4 encodes an activity-dependent transcription factor that is highly expressed during cortical development and in animal models is shown to regulate various aspects of neuronal development and function. However, our understanding of how disease-causing mutations in TCF4 confer pathophysiology in a human context is lacking. Here we show that cortical neurons derived from patients with TCF4 mutations have deficits in spontaneous synaptic transmission, network excitability and homeostatic plasticity. Transcriptomic analysis indicates these phenotypes result from altered expression of genes involved in presynaptic neurotransmission and identifies the presynaptic binding protein, RIMBP2 as the most differentially expressed gene in PTHS neurons. Remarkably, TCF4-dependent deficits in spontaneous synaptic transmission and network excitability were rescued by increasing RIMBP2 expression in presynaptic neurons. Together, these results identify TCF4 as a critical transcriptional regulator of human synaptic development and plasticity and specifically identifies dysregulation of presynaptic function as an early pathophysiology in PTHS.

Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing.

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

The basolateral amygdala to lateral septum circuit is critical for regulating social novelty in mice.

The lateral septum (LS) is a basal forebrain GABAergic region that is implicated in social novelty. However, the neural circuits and cell signaling pathways that converge on the LS to mediate social behaviors aren't well understood. Multiple lines of evidence suggest that signaling of brain-derived neurotrophic factor (BDNF) through its receptor TrkB plays important roles in social behavior. BDNF is not locally produced in LS, but we demonstrate that nearly all LS GABAergic neurons express TrkB. Local TrkB knock-down in LS neurons decreased social novelty recognition and reduced recruitment of neural activity in LS neurons in response to social novelty. Since BDNF is not synthesized in LS, we investigated which inputs to LS could serve as potential BDNF sources for controlling social novelty recognition. We demonstrate that selectively ablating inputs to LS from the basolateral amygdala (BLA), but not from ventral CA1 (vCA1), impairs social novelty recognition. Moreover, depleting BDNF selectively in BLA-LS projection neurons phenocopied the decrease in social novelty recognition caused by either local LS TrkB knockdown or ablation of BLA-LS inputs. These data support the hypothesis that BLA-LS projection neurons serve as a critical source of BDNF for activating TrkB signaling in LS neurons to control social novelty recognition.

VistoSeg: Processing utilities for high-resolution images for spatially resolved transcriptomics data.

Spatially resolved transcriptomics (SRT) is a growing field that links gene expression to anatomical context. SRT approaches that use next-generation sequencing (NGS) combine RNA sequencing with histological or fluorescent imaging to generate spatial maps of gene expression in intact tissue sections. These technologies directly couple gene expression measurements with high-resolution histological or immunofluorescent images that contain rich morphological information about the tissue under study. While broad access to NGS-based spatial transcriptomic technology is now commercially available through the Visium platform from the vendor 10× Genomics, computational tools for extracting image-derived metrics for integration with gene expression data remain limited. We developed VistoSeg as a MATLAB pipeline to process, analyze and interactively visualize the high-resolution images generated in the Visium platform. VistoSeg outputs can be easily integrated with accompanying transcriptomic data to facilitate downstream analyses in common programing languages including R and Python. VistoSeg provides user-friendly tools for integrating image-derived metrics from histological and immunofluorescent images with spatially resolved gene expression data. Integration of this data enhances the ability to understand the transcriptional landscape within tissue architecture. VistoSeg is freely available at http://research.libd.org/VistoSeg/.

CaPTure: Calcium PeakToolbox for analysis of in vitro calcium imaging data.

BACKGROUND: Calcium imaging is a powerful technique for recording cellular activity across large populations of neurons. However, analysis methods capable of single-cell resolution in cultured neurons, especially for cultures derived from human induced pluripotent stem cells (hiPSCs), are lacking. Existing methods lack scalability to accommodate high-throughput comparisons between multiple lines, across developmental timepoints, or across pharmacological manipulations. RESULTS: To address this need we developed CaPTure, a scalable, automated Ca2+ imaging analysis pipeline ( https://github.com/LieberInstitute/CaPTure ). CaPTuredetects neurons, classifies and quantifies spontaneous activity, quantifies synchrony metrics, and generates cell- and network-specific metrics that facilitate phenotypic discovery. The method is compatible with parallel processing on computing clusters without requiring significant user input or parameter modification. CONCLUSION: CaPTure allows for rapid assessment of neuronal activity in cultured cells at cellular resolution, rendering it amenable to high-throughput screening and phenotypic discovery. The platform can be applied to both human- and rodent-derived neurons and is compatible with many imaging systems.

Analysis of the caudate nucleus transcriptome in individuals with schizophrenia highlights effects of antipsychotics and new risk genes.

Most studies of gene expression in the brains of individuals with schizophrenia have focused on cortical regions, but subcortical nuclei such as the striatum are prominently implicated in the disease, and current antipsychotic drugs target the striatum's dense dopaminergic innervation. Here, we performed a comprehensive analysis of the genetic and transcriptional landscape of schizophrenia in the postmortem caudate nucleus of the striatum of 443 individuals (245 neurotypical individuals, 154 individuals with schizophrenia and 44 individuals with bipolar disorder), 210 from African and 233 from European ancestries. Integrating expression quantitative trait loci analysis, Mendelian randomization with the latest schizophrenia genome-wide association study, transcriptome-wide association study and differential expression analysis, we identified many genes associated with schizophrenia risk, including potentially the dopamine D2 receptor short isoform. We found that antipsychotic medication has an extensive influence on caudate gene expression. We constructed caudate nucleus gene expression networks that highlight interactions involving schizophrenia risk. These analyses provide a resource for the study of schizophrenia and insights into risk mechanisms and potential therapeutic targets.

SCRAP: a bioinformatic pipeline for the analysis of small chimeric RNA-seq data.

MicroRNAs (miRNAs) are small non-coding RNAs (sncRNAs) that function in post-transcriptional gene regulation through imperfect base pairing with mRNA targets which results in inhibition of translation and typically destabilization of bound transcripts. Sequence-based algorithms historically used to predict miRNA targets face inherent challenges in reliably reflecting in vivo interactions. Recent strategies have directly profiled miRNA-target interactions by crosslinking and ligation of sncRNAs to their targets within the RNA-induced silencing complex (RISC), followed by high throughput sequencing of the chimeric sncRNA:target RNAs. Despite the strength of these direct profiling approaches, standardized pipelines for effectively analyzing the resulting chimeric sncRNA:target RNA sequencing data are not readily available. Here we present SCRAP, a robust Small Chimeric RNA Analysis Pipeline for the bioinformatic processing of chimeric sncRNA:target RNA sequencing data. SCRAP consists of two parts, each of which are specifically optimized for the distinctive characteristics of chimeric small RNA sequencing reads: first, read processing and alignment and second, peak calling and annotation. We apply SCRAP to benchmark chimeric sncRNA:target RNA sequencing datasets generated by distinct molecular approaches, and compare SCRAP to existing chimeric RNA analysis pipelines. SCRAP has minimal hardware requirements, is cross-platform, and contains extensive annotation to broaden accessibility for processing small chimeric RNA sequencing data and enable insights about the targets of small non-coding RNAs in regulating diverse biological systems.