Catechol-O-methyltransferase (COMT) is a key enzyme in the elimination of dopamine in the prefrontal cortex of the human brain. Genetic variation in the COMT gene (MIM 116790) has been associated with altered prefrontal cortex function and higher risk for schizophrenia, but the specific alleles and their functional implications have been controversial. We analyzed the effects of several single-nucleotide polymorphisms (SNPs) within COMT on mRNA expression levels (using reverse-transcriptase polymerase chain reaction analysis), protein levels (using Western blot analysis), and enzyme activity (using catechol methylation) in a large sample (n = 108) of postmortem human prefrontal cortex tissue, which predominantly expresses the -membrane-bound isoform. A common coding SNP, Val158Met (rs4680), significantly affected protein abundance and enzyme activity but not mRNA expression levels, suggesting that differences in protein integrity account for the difference in enzyme activity between alleles. A SNP in intron 1 (rs737865) and a SNP in the 3' flanking region (rs165599)--both of which have been reported to contribute to allelic expression differences and to be associated with schizophrenia as part of a haplotype with Val--had no effect on mRNA expression levels, protein immunoreactivity, or enzyme activity. In lymphocytes from 47 subjects, we confirmed a similar effect on enzyme activity in samples with the Val/Met genotype but no effect in samples with the intron 1 or 3' SNPs. Separate analyses revealed that the subject's sex, as well as the presence of a SNP in the P2 promoter region (rs2097603), had small effects on COMT enzyme activity. Using site-directed mutagenesis of mouse COMT cDNA, followed by in vitro translation, we found that the conversion of Leu at the homologous position into Met or Val progressively and significantly diminished enzyme activity. Thus, although we cannot exclude a more complex genetic basis for functional effects of COMT, Val is a predominant factor that determines higher COMT activity in the prefrontal cortex, which presumably leads to lower synaptic dopamine levels and relatively deleterious prefrontal function.

RegulonDB (http://regulondb.ccg.unam.mx/) is the primary reference database of the best-known regulatory network of any free-living organism, that of Escherichia coli K-12. The major conceptual change since 3 years ago is an expanded biological context so that transcriptional regulation is now part of a unit that initiates with the signal and continues with the signal transduction to the core of regulation, modifying expression of the affected target genes responsible for the response. We call these genetic sensory response units, or Gensor Units. We have initiated their high-level curation, with graphic maps and superreactions with links to other databases. Additional connectivity uses expandable submaps. RegulonDB has summaries for every transcription factor (TF) and TF-binding sites with internal symmetry. Several DNA-binding motifs and their sizes have been redefined and relocated. In addition to data from the literature, we have incorporated our own information on transcription start sites (TSSs) and transcriptional units (TUs), obtained by using high-throughput whole-genome sequencing technologies. A new portable drawing tool for genomic features is also now available, as well as new ways to download the data, including web services, files for several relational database manager systems and text files including BioPAX format.

Differential expression analysis of RNA sequencing (RNA-seq) data typically relies on reconstructing transcripts or counting reads that overlap known gene structures. We previously introduced an intermediate statistical approach called differentially expressed region (DER) finder that seeks to identify contiguous regions of the genome showing differential expression signal at single base resolution without relying on existing annotation or potentially inaccurate transcript assembly.We present the derfinder software that improves our annotation-agnostic approach to RNA-seq analysis by: (i) implementing a computationally efficient bump-hunting approach to identify DERs that permits genome-scale analyses in a large number of samples, (ii) introducing a flexible statistical modeling framework, including multi-group and time-course analyses and (iii) introducing a new set of data visualizations for expressed region analysis. We apply this approach to public RNA-seq data from the Genotype-Tissue Expression (GTEx) project and BrainSpan project to show that derfinder permits the analysis of hundreds of samples at base resolution in R, identifies expression outside of known gene boundaries and can be used to visualize expressed regions at base-resolution. In simulations, our base resolution approaches enable discovery in the presence of incomplete annotation and is nearly as powerful as feature-level methods when the annotation is complete.derfinder analysis using expressed region-level and single base-level approaches provides a compromise between full transcript reconstruction and feature-level analysis. The package is available from Bioconductor at www.bioconductor.org/packages/derfinder.

Genetic variation and early adverse environmental events work together to increase risk for schizophrenia. γ-aminobutyric acid (GABA), the major inhibitory neurotransmitter in adult mammalian brain, plays a major role in normal brain development, and has been strongly implicated in the pathobiology of schizophrenia. GABA synthesis is controlled by two glutamic acid decarboxylase (GAD) genes, GAD1 and GAD2, both of which produce a number of alternative transcripts. Genetic variants in the GAD1 gene are associated with increased risk for schizophrenia, and reduced expression of its major transcript in the human dorsolateral prefrontal cortex (DLPFC). No consistent changes in GAD2 expression have been found in brains from patients with schizophrenia. In this work, with the use of RNA sequencing and PCR technologies, we confirmed and tracked the expression of an alternative truncated transcript of GAD2 (ENST00000428517) in human control DLPFC homogenates across lifespan besides the well-known full length transcript of GAD2. In addition, using quantitative RT-PCR, expression of GAD2 full length and truncated transcripts were measured in the DLPFC of patients with schizophrenia, bipolar disorder and major depression. The expression of GAD2 full length transcript is decreased in the DLPFC of schizophrenia and bipolar disorder patients, while GAD2 truncated transcript is increased in bipolar disorder patients but decreased in schizophrenia patients. Moreover, the patients with schizophrenia with completed suicide or positive nicotine exposure showed significantly higher expression of GAD2 full length transcript. Alternative transcripts of GAD2 may be important in the growth and development of GABA-synthesizing neurons as well as abnormal GABA signaling in the DLPFC of patients with schizophrenia and affective disorders.

Brain development and function depend on the precise regulation of gene expression. However, our understanding of the complexity and dynamics of the transcriptome of the human brain is incomplete. Here we report the generation and analysis of exon-level transcriptome and associated genotyping data, representing males and females of different ethnicities, from multiple brain regions and neocortical areas of developing and adult post-mortem human brains. We found that 86 per cent of the genes analysed were expressed, and that 90 per cent of these were differentially regulated at the whole-transcript or exon level across brain regions and/or time. The majority of these spatio-temporal differences were detected before birth, with subsequent increases in the similarity among regional transcriptomes. The transcriptome is organized into distinct co-expression networks, and shows sex-biased gene expression and exon usage. We also profiled trajectories of genes associated with neurobiological categories and diseases, and identified associations between single nucleotide polymorphisms and gene expression. This study provides a comprehensive data set on the human brain transcriptome and insights into the transcriptional foundations of human neurodevelopment.

A subset of human neocortical neurons harbors complex karyotypes wherein megabase-scale copy-number variants (CNVs) alter allelic diversity. Divergent levels of neurons with complex karyotypes (CNV neurons) are reported in different individuals, yet genome-wide and familial studies implicitly assume a single brain genome when assessing the genetic risk architecture of neurological disease. We assembled a brain CNV atlas using a robust computational approach applied to a new dataset (>800 neurons from 5 neurotypical individuals) and to published data from 10 additional neurotypical individuals. The atlas reveals that the frequency of neocortical neurons with complex karyotypes varies widely among individuals, but this variability is not readily accounted for by tissue quality or CNV detection approach. Rather, the age of the individual is anti-correlated with CNV neuron frequency. Fewer CNV neurons are observed in aged individuals than in young individuals.

Antipsychotics are the most widely used medications for the treatment of schizophrenia spectrum disorders. While such drugs generally ameliorate positive symptoms, clinical responses are highly variable in terms of negative symptoms and cognitive impairments. However, predictors of individual responses have been elusive. Here, we report a pharmacogenetic interaction related to a core cognitive dysfunction in patients with schizophrenia. We show that genetic variations reducing dysbindin-1 expression can identify individuals whose executive functions respond better to antipsychotic drugs, both in humans and in mice. Multilevel ex vivo and in vivo analyses in postmortem human brains and genetically modified mice demonstrate that such interaction between antipsychotics and dysbindin-1 is mediated by an imbalance between the short and long isoforms of dopamine D2 receptors, leading to enhanced presynaptic D2 function within the prefrontal cortex. These findings reveal one of the pharmacodynamic mechanisms underlying individual cognitive response to treatment in patients with schizophrenia, suggesting a potential approach for improving the use of antipsychotic drugs.

Publicly available genomic data are a valuable resource for studying normal human variation and disease, but these data are often not well labeled or annotated. The lack of phenotype information for public genomic data severely limits their utility for addressing targeted biological questions. We develop an in silico phenotyping approach for predicting critical missing annotation directly from genomic measurements using well-annotated genomic and phenotypic data produced by consortia like TCGA and GTEx as training data. We apply in silico phenotyping to a set of 70 000 RNA-seq samples we recently processed on a common pipeline as part of the recount2 project. We use gene expression data to build and evaluate predictors for both biological phenotypes (sex, tissue, sample source) and experimental conditions (sequencing strategy). We demonstrate how these predictions can be used to study cross-sample properties of public genomic data, select genomic projects with specific characteristics, and perform downstream analyses using predicted phenotypes. The methods to perform phenotype prediction are available in the phenopredict R package and the predictions for recount2 are available from the recount R package. With data and phenotype information available for 70,000 human samples, expression data is available for use on a scale that was not previously feasible.

Increased African-American research participation is critical to the applicability and generalizability of biomedical research, as population diversity continues to increase both domestically and abroad. Yet numerous studies document historical origins of mistrust, as well as other barriers that may contribute to resistance in the African-American community towards participation in biomedical research. However, a growing body of more recent scientific evidence suggests that African-Americans value research and are willing to participate when asked. In the present study, we set out to determine factors associated with research participation of African-American families in postmortem human brain tissue donation for neuropsychiatric disorders as compared with Caucasian families, from same-day medical examiner autopsy referrals. We retrospectively reviewed brain donation rates, as well as demographic and clinical factors associated with donation in 1,421 consecutive referrals to three medical examiner's offices from 2010-2015. Overall, 69.7% of all next-of-kin contacted agreed to brain donation. While Caucasian families consented to donate brain tissue at a significantly higher rate (74.1%) than African-American families (57.0%) (p<0.001), African-American brain donation rates were as high as 60.5% in referrals from Maryland. Neither African-American nor Caucasian donors differed significantly from non-donors on any demographic or clinical factors ascertained, including age, sex, diagnosis of the donor, or in the relationship of the next-of-kin being contacted (p>0.05). However, Caucasian donors were significantly older, had more years of education, were more likely to be referred for study due to a psychiatric diagnosis, more likely to have comorbid substance abuse, and more likely to have died via suicide, as compared with African-American donors (p<0.05). When African-American participants are identified and approached, African-American families as well as Caucasian families are indeed willing to donate brain tissue on the spot for neuropsychiatric research, which supports the belief that African-American attitudes towards biomedical research may be more favorable than previously thought.

In this study, we established induced pluripotent stem (iPS) cell lines from postmortem dura-derived fibroblasts of four control individuals with low polygenic risk score for psychiatric disorders including schizophrenia and bipolar disorder. The fibroblasts were reprogrammed into iPS cells using episomal vectors carrying OCT3/4, SOX2, KLF4, L-Myc, LIN28 and shRNA-p53. All iPS cell lines showed the same genotype with parental postmortem brain tissues, expressed pluripotency markers, and exhibited the differentiation potency into three embryonic germ layers.

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/.

Glioblastoma (GB) is a highly invasive type of brain cancer exhibiting poor prognosis. As such, its microenvironment plays a crucial role in its progression. Among the brain stromal cells, the microglia were shown to facilitate GB invasion and immunosuppression. However, the reciprocal mechanisms by which GB cells alter microglia/macrophages behavior are not fully understood. We propose that these mechanisms involve adhesion molecules such as the Selectins family. These proteins are involved in immune modulation and cancer immunity. We show that P-selectin mediates microglia-enhanced GB proliferation and invasion by altering microglia/macrophages activation state. We demonstrate these findings by pharmacological and molecular inhibition of P-selectin which leads to reduced tumor growth and increased survival in GB mouse models. Our work sheds light on tumor-associated microglia/macrophage function and the mechanisms by which GB cells suppress the immune system and invade the brain, paving the way to exploit P-selectin as a target for GB therapy.

There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challenging to identify causal genetic variations that drive DNAm levels by population-based genetic association studies. This limits the utility of mQTLs for fine-mapping risk loci underlying psychiatric disorders identified by genome-wide association studies (GWAS). Here we present INTERACT, a deep learning model that integrates convolutional neural networks with transformer, to predict effects of genetic variations on DNAm levels at CpG sites in the human brain. We show that INTERACT-derived DNAm regulatory variants are not confounded by LD, are concentrated in regulatory genomic regions in the human brain, and are convergent with mQTL evidence from genetic association analysis. We further demonstrate that predicted DNAm regulatory variants are enriched for heritability of brain-related traits and improve polygenic risk prediction for schizophrenia across diverse ancestry samples. Finally, we applied predicted DNAm regulatory variants for fine-mapping schizophrenia GWAS risk loci to identify potential novel risk genes. Our study shows the power of a deep learning approach to identify functional regulatory variants that may elucidate the genetic basis of complex traits.

RNA sequencing offers advantages over other quantification methods for microRNA (miRNA), yet numerous biases make reliable quantification challenging. Previous evaluations of these biases have focused on adapter ligation bias with limited evaluation of reverse transcription bias or amplification bias. Furthermore, evaluations of the quantification of isomiRs (miRNA isoforms) or the influence of starting amount on performance have been very limited. No study had yet evaluated the quantification of isomiRs of altered length or compared the consistency of results derived from multiple moderate starting inputs. We therefore evaluated quantifications of miRNA and isomiRs using four library preparation kits, with various starting amounts, as well as quantifications following removal of duplicate reads using unique molecular identifiers (UMIs) to mitigate reverse transcription and amplification biases.

Understanding the molecular profile of every human cell type is essential for understanding its role in normal physiology and disease. Technological advancements in DNA sequencing, mass spectrometry, and computational methods allow us to carry out multiomics analyses although such approaches are not routine yet. Human umbilical vein endothelial cells (HUVECs) are a widely used model system to study pathological and physiological processes associated with the cardiovascular system. In this study, next-generation sequencing and high-resolution mass spectrometry to profile the transcriptome and proteome of primary HUVECs is employed. Analysis of 145 million paired-end reads from next-generation sequencing confirmed expression of 12 186 protein-coding genes (FPKM ≥0.1), 439 novel long non-coding RNAs, and revealed 6089 novel isoforms that were not annotated in GENCODE. Proteomics analysis identifies 6477 proteins including confirmation of N-termini for 1091 proteins, isoforms for 149 proteins, and 1034 phosphosites. A database search to specifically identify other post-translational modifications provide evidence for a number of modification sites on 117 proteins which include ubiquitylation, lysine acetylation, and mono-, di- and tri-methylation events. Evidence for 11 "missing proteins," which are proteins for which there was insufficient or no protein level evidence, is provided. Peptides supporting missing protein and novel events are validated by comparison of MS/MS fragmentation patterns with synthetic peptides. Finally, 245 variant peptides derived from 207 expressed proteins in addition to alternate translational start sites for seven proteins and evidence for novel proteoforms for five proteins resulting from alternative splicing are identified. Overall, it is believed that the integrated approach employed in this study is widely applicable to study any primary cell type for deeper molecular characterization.

Antibody class switch recombination (CSR) to IgG, IgA, or IgE is a hallmark of adaptive immunity, allowing antibody function diversification beyond IgM. CSR involves a deletion of the IgM/IgD constant region genes placing a new acceptor Constant gene, downstream of the VDJH exon. CSR depends on non-coding (CSRnc) transcription of donor Iμ and acceptor IH exons, located 5' upstream of each CH coding gene. Although, our knowledge of the role of CSRnc transcription has advanced greatly, its extension and importance in healthy and diseased humans is scarce. We analyzed CSRnc transcription in 70,603 publicly available RNA-seq samples, including GTEx, TCGA, and the Sequence Read Archive using recount2, an online resource consisting of normalized RNA-seq gene and exon counts, as well as, coverage BigWig files that can be programmatically accessed through R. CSRnc transcription was validated with a qRT-PCR assay for Iμ, Iγ3, and Iγ1 in humans in response to vaccination. We mapped IH transcription for the human IGH locus, including the less understood IGHD gene. CSRnc transcription was restricted to B cells and is widely distributed in normal adult tissues, but predominant in blood, spleen, MALT-containing tissues, visceral adipose tissue and some so-called "immune privileged" tissues. However, significant Iγ4 expression was found even in non-lymphoid fetal tissues. CSRnc expression in cancer tissues mimicked the expression of their normal counterparts, with notable pattern changes in some common cancer subsets. CSRnc transcription in tumors appears to result from tumor infiltration by B cells, since CSRnc transcription was not detected in corresponding tumor-derived immortal cell lines. Additionally, significantly increased Iδ transcription in ileal mucosa in Crohn's disease with ulceration was found. In conclusion, CSRnc transcription occurs in multiple anatomical locations beyond classical secondary lymphoid organs, representing a potentially useful marker of effector B cell responses in normal and pathological immune responses. The pattern of IH exon expression may reveal clues of the local immune response (i.e., cytokine milieu) in health and disease. This is a great example of how the public recount2 data can be used to further our understanding of transcription, including regions outside the known transcriptome.

Metabotropic glutamate receptor 3 (mGlu3, mGluR3), encoded by GRM3, is a risk gene for schizophrenia and a therapeutic target. It is unclear whether expression of the receptor is altered in the disorder or related to GRM3 risk genotype. Antibodies used to date to assess mGlu3 in schizophrenia have not been well validated.

Organized neuronal firing is crucial for cortical processing and is disrupted in schizophrenia. Using rapid amplification of 5' complementary DNA ends in human brain, we identified a primate-specific isoform (3.1) of the ether-a-go-go-related K(+) channel KCNH2 that modulates neuronal firing. KCNH2-3.1 messenger RNA levels are comparable to full-length KCNH2 (1A) levels in brain but three orders of magnitude lower in heart. In hippocampus from individuals with schizophrenia, KCNH2-3.1 expression is 2.5-fold greater than KCNH2-1A expression. A meta-analysis of five clinical data sets (367 families, 1,158 unrelated cases and 1,704 controls) shows association of single nucleotide polymorphisms in KCNH2 with schizophrenia. Risk-associated alleles predict lower intelligence quotient scores and speed of cognitive processing, altered memory-linked functional magnetic resonance imaging signals and increased KCNH2-3.1 mRNA levels in postmortem hippocampus. KCNH2-3.1 lacks a domain that is crucial for slow channel deactivation. Overexpression of KCNH2-3.1 in primary cortical neurons induces a rapidly deactivating K(+) current and a high-frequency, nonadapting firing pattern. These results identify a previously undescribed KCNH2 channel isoform involved in cortical physiology, cognition and psychosis, providing a potential new therapeutic drug target.

Beyond being one the most widely used psychoactive drugs in the world, cannabis has been identified as an environmental risk factor for psychosis. Though the relationship between cannabis use and psychiatric disorders remains controversial, consistent association between early adolescent cannabis use and the subsequent risk of psychosis suggested adolescence may be a particularly vulnerable period. Previous findings on gene by environment interactions indicated that cannabis use may only increase the risk for psychosis in the subjects who have a specific genetic vulnerability. The type 1 cannabinoid receptor (CB1), encoded by the CNR1 gene, is a key component of the endocannabinoid system. As the primary endocannabinoid receptor in the brain, CB1 is the main molecular target of the endocannabinoid ligand, as well as tetrahydrocannabinol (THC), the principal psychoactive ingredient of cannabis. In this study, we have examined mRNA expression and DNA methylation of CNR1 in human prefrontal cortex (PFC), hippocampus, and caudate samples. The expression of CNR1 is higher in fetal PFC and hippocampus, then drops down dramatically after birth. The lifespan trajectory of CNR1 expression in the DLPFC differentially correlated with age by allelic variation at rs4680, a functional polymorphism in the COMT gene. Compared with COMT methionine158 carriers, Caucasian carriers of the COMT valine158 allele have a stronger negative correlation between the expression of CNR1 in DLPFC and age. In contrast, the methylation level of cg02498983, which is negatively correlated with the expression of CNR1 in PFC, showed the strongest positive correlation with age in PFC of Caucasian carriers of COMT valine158. Additionally, we have observed decreased mRNA expression of CNR1 in the DLPFC of patients with schizophrenia. Further analysis revealed a positive eQTL SNP, rs806368, which predicted the expression of a novel transcript of CNR1 in human DLPFC, hippocampus and caudate. This SNP has been associated with addiction and other psychiatric disorders. THC or ethanol are each significantly associated with dysregulated expression of CNR1 in the PFC of patients with affective disorder, and the expression of CNR1 is significantly upregulated in the PFC of schizophrenia patients who completed suicide. Our results support previous studies that have implicated the endocannabinoid system in the pathology of schizophrenia and provided additional insight into the mechanism of increasing risk for schizophrenia in the adolescent cannabis users.

X-linked Dystonia-Parkinsonism (XDP) is an inherited, X-linked, adult-onset movement disorder characterized by degeneration in the neostriatum. No therapeutics alter disease progression. The mechanisms underlying regional differences in degeneration and adult onset are unknown. Developing therapeutics requires a deeper understanding of how XDP-relevant features vary in health and disease. XDP is possibly due, in part, to a partial loss of TAF1 function. A disease-specific SINE-VNTR-Alu (SVA) retrotransposon insertion occurs within intron 32 of TAF1, a subunit of TFIID involved in transcription initiation. While all XDP males are usually clinically affected, females are heterozygous carriers generally not manifesting the full syndrome. As a resource for disease modeling, we characterized eight iPSC lines from three XDP female carrier individuals for X chromosome inactivation status and identified clonal lines that express either the wild-type X or XDP haplotype. Furthermore, we characterized XDP-relevant transcript expression in neurotypical humans, and found that SVA-F expression decreases after 30 years of age in the brain and that TAF1 is decreased in most female samples. Uniquely in the caudate nucleus, TAF1 expression is not sexually dimorphic and decreased after adolescence. These findings indicate that regional-, age- and sex-specific mechanisms regulate TAF1, highlighting the importance of disease-relevant models and postmortem tissue. We propose that the decreased TAF1 expression in the adult caudate may synergize with the XDP-specific partial loss of TAF1 function in patients, thereby passing a minimum threshold of TAF1 function, and triggering degeneration in the neostriatum.Significance StatementXDP is an inherited, X-linked, adult-onset movement disorder characterized by degeneration in the neostriatum. No therapeutics alter disease progression. Developing therapeutics requires a deeper understanding of how XDP-relevant features vary in health and disease. XDP is possibly due to a partial loss of TAF1 function. While all XDP males are usually affected, females are heterozygous carriers generally not manifesting the full syndrome. As a resource for disease modeling, we characterized eight stem cell lines from XDP female carrier individuals. Furthermore, we found that, uniquely in the caudate nucleus, TAF1 expression decreases after adolescence in healthy humans. We hypothesize that the decrease of TAF1 after adolescence in human caudate, in general, may underlie the vulnerability of the adult neostriatum in XDP.