Blood extracellular vesicles carrying brain-specific mRNAs are potential biomarkers for detecting gene expression changes in the female brain.

The absence of non-invasive tests that can monitor the status of the brain is a major obstacle for psychiatric care. In order to address this need, we assessed the feasibility of using tissue-specific gene expression to determine the origin of extracellular vesicle (EV) mRNAs in peripheral blood. Using the placenta as a model, we discovered that 26 messenger RNAs that are specifically expressed in the placenta are present in EVs circulating in maternal blood. Twenty-three of these transcripts were either exclusively or highly expressed in maternal blood during pregnancy only and not in the postpartum period, verifying the feasibility of using tissue-specific gene expression to infer the tissue of origin for EV mRNAs. Using the same bioinformatic approach, which provides better specificity than isolating L1 cell-adhesion molecule containing EVs, we discovered that 181 mRNAs that are specifically expressed in the female brain are also present in EVs circulating in maternal blood. Gene set enrichment analysis revealed that these transcripts, which are involved in synaptic functions and myelination, are enriched for genes implicated in mood disorders, schizophrenia, and substance use disorders. The EV mRNA levels of 13 of these female brain-specific transcripts are associated with postpartum depression (adjusted p-vals = 3 × 10-5 to 0.08), raising the possibility that they can be used to infer the state of the brain. In order to determine the extent to which EV mRNAs reflect transcription in the brain, we compared mRNAs isolated from cells and EVs in an iPSC-derived brain microphysiological system differentiated for 3 and 9 weeks. We discovered that, although cellular and extracellular mRNA levels are not identical, they do correlate, and it is possible to extrapolate cellular RNA expression changes in the brain via EV mRNA levels. Our findings bring EV mRNAs to the forefront of peripheral biomarker development efforts in psychiatric diseases by demonstrating the feasibility of inferring transcriptional changes in the brain via blood EV mRNA levels.

Altered extracellular mRNA communication in postpartum depression is associated with decreased autophagy.

We investigated whether extracellular RNA communication, which is a recently discovered mode of intercellular communication that is involved in a variety of important biological processes including pregnancy, is associated with postpartum depression (PPD). Extracellular RNA communication is increased during pregnancy and is involved in embryo implantation, uterine spiral artery remodeling, parturition, preterm birth, immunity, and the inflammatory response. Since immune anomalies are associated with PPD, we characterized the mRNA content of extracellular vesicles (EV) in a cohort of prospectively collected blood plasma samples at six time-points throughout pregnancy and the postpartum (2nd trimester, 3rd trimester, 2 weeks postpartum, 6 weeks postpartum, 3 months postpartum, and 6 months postpartum) in an academic medical setting from women who went on to develop PPD (N = 7, defined as euthymic in pregnancy with postpartum-onset depressive symptoms assessed by Edinburgh Postnatal Depression Scale ≥13 at any postpartum time point) and matched unaffected controls (N = 7, defined as euthymic throughout pregnancy and postpartum). Blood samples were available for all participants at the T2 and W6 timepoints, with fewer samples available at other time points. This analysis revealed that EV mRNA levels during pregnancy and the postpartum period were extensively altered in women who went on to develop PPD. Gene set enrichment analysis revealed that mRNAs associated with autophagy were decreased in PPD cases. In contrast, EV mRNAs from ribosomes and mitochondria, two organelles that are selectively targeted by autophagy, were elevated in PPD cases. Cellular deconvolution analysis discovered that EV mRNAs associated with PPD originated from monocytes and macrophages. Quantitative PCR analysis for four relevant genes in another cohort replicated these findings and confirmed that extracellular RNA levels are altered in PPD. We demonstrate that EV mRNA communication is robustly altered during pregnancy and the postpartum period in women who go on to develop PPD. Our work also establishes a direct link between reduced autophagy and PPD in patient samples. These data warrant investigating the feasibility of developing EV mRNA based biomarkers and therapeutic agents for PPD.

Expression of HLA and Autoimmune Pathway Genes in Liver Biopsies of Young Subjects With Autoimmune Hepatitis Type 1.

OBJECTIVES: To test the hypothesis that autoimmune hepatitis (AIH type I) in young subjects is due to genetic differences in proinflammatory genes responding to viral triggers in patients and controls. METHODS: Intrahepatic gene expression was compared between AIH type I (n = 24, age 9-30 years) patients (hereafter referred to as the AIH group) and controls (n = 21, age 4-25 years). RNA sequencing was performed on complementary DNA (cDNA) libraries made from total RNA extracted from formalin-fixed paraffin-embedded (FFPE) liver biopsy samples. Gene expression levels were quantified, and differentially expressed genes were functionally analyzed. Pathway analysis was performed using the databases Kyoto Encyclopedia of Genes and Genomes (KEGG) and PANTHER. The remaining sequences were mapped to the RefSeq complete set of viral genomes. RESULTS: Differential gene analysis identified 181 genes that were significantly differentially expressed (136 upregulated in the AIH group). Autoimmune pathway genes such as CD19 and CD20 which are important in B cell regulation and maturation as well as, CD8 and LY9 , which are T-cell related, were upregulated in our AIH group. Genes implicated in AIH pathogenesis including CXCL10 , which is thought to be associated with AIH severity and progression, complement genes ( C1QA, C1QB , and C1QC ), and human leucocyte antigen ( HLA ) genes ( HLA-DRB1, HLA-DRA, HLA-B , and HLA-C ) were upregulated in samples from the AIH group. Specific viral etiologies were not found. CONCLUSIONS: Unbiased next-generation sequencing and differential gene expression analysis of the AIH group has not only added support for the role of B cells in the pathogenesis and treatment of AIH but also has introduced potential new therapeutic targets: CXCL10 (anti- CXCL10 ) and several complement system-related genes.

Microbiome profiles are associated with cognitive functioning in 45-month-old children.

Prenatal, perinatal, and postnatal factors have been shown to shape neurobiological functioning and alter the risk for mental disorders later in life. The gut microbiome is established early in life, and interacts with the brain via the brain-immune-gut axis. However, little is known about how the microbiome relates to early-life cognitive functioning in children. The present study, where the fecal microbiome of 380 children was characterized using 16S rDNA and metagenomic sequencing aimed to investigate the association between the microbiota and cognitive functioning of children at the age of 45 months measured with the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). Overall the microbiome profile showed a significant association with cognitive functioning. A strong correlation was found between cognitive functioning and the relative abundance of an unidentified genus of the family Enterobacteriaceae. Follow-up mediation analyses revealed significant mediation effects of the level of this genus on the association of maternal smoking during pregnancy and current cigarette smoking with cognitive function. Metagenomic sequencing of a subset of these samples indicated that the identified genus was most closely related to Enterobacter asburiae. Analysis of metabolic potential showed a nominally significant association of cognitive functioning with the microbial norspermidine biosynthesis pathway. Our results indicate that alteration of the gut microflora is associated with cognitive functioning in childhood. Furthermore, they suggest that the altered microflora might interact with other environmental factors such as maternal cigarette smoking. Interventions directed at altering the microbiome should be explored in terms of improving cognitive functioning in young children.

Differentially methylated regions in bipolar disorder and suicide.

The addition of a methyl group to, typically, a cytosine-guanine dinucleotide (CpG) creates distinct DNA methylation patterns across the genome that can regulate gene expression. Aberrant DNA methylation of CpG sites has been associated with many psychiatric disorders including bipolar disorder (BD) and suicide. Using the SureSelectXT system, Methyl-Seq, we investigated the DNA methylation status of CpG sites throughout the genome in 50 BD individuals (23 subjects who died by suicide and 27 subjects who died from other causes) and 31 nonpsychiatric controls. We identified differentially methylated regions (DMRs) from three analyses: (a) BD subjects compared to nonpsychiatric controls (BD-NC), (b) BD subjects who died by suicide compared to nonpsychiatric controls (BDS-NC), and (c) BDS subjects compared to BD subjects who died from other causes (BDS-BDNS). One DMR from the BDS-NC analysis, located in ARHGEF38, was significantly hypomethylated (23.4%) in BDS subjects. This finding remained significant after multiple testing (PBootstrapped = 9.0 × 10-3 ), was validated using pyrosequencing, and was more significant in males. A secondary analysis utilized Ingenuity Pathway Analysis to identify enrichment in nominally significant DMRs. This identified an association with several pathways including axonal guidance signaling, calcium signaling, ß-adrenergic signaling, and opioid signaling. Our comprehensive study provides further support that DNA methylation alterations influence the risk for BD and suicide. However, further investigation is required to confirm these associations and identify their functional consequences.

Widespread splicing of repetitive element loci into coding regions of gene transcripts.

We performed a thorough characterization of expressed repetitive element loci (RE) in the human orbitofrontal cortex (OFC) using directional RNA sequencing data. Considering only sequencing reads that map uniquely onto the human genome, we discovered that the overwhelming majority of intronic and exonic RE are expressed in the same orientation as the gene in which they reside. Our mapping approach enabled the identification of novel differentially expressed RE transcripts between the OFC and peripheral blood lymphocytes. Further analysis revealed that RE are extensively spliced into coding regions of gene transcripts yielding thousands of novel mRNA variants with altered coding potential. Lower frequency splicing of RE into untranslated regions of gene transcripts was also observed. The same pattern of RE splicing in the brain was also detected for Drosophila, zebrafish, mouse, rat, dog and rabbit. RE splicing occurs largely at canonical GT-AG splice junctions with LINE and SINE elements forming the most RE splice junctions in the human OFC. This type of splicing usually gives rise to a minor splice variant of the endogenous gene and in silico analysis suggests that RE splicing has the potential to introduce novel open reading frames. Reanalysis of previously published sequencing data performed in the mouse cerebellum revealed that thousands of RE splice variants are associated with translating ribosomes. Our results demonstrate that RE expression is more complex than previously envisioned and raise the possibility that RE splicing might generate functional protein isoforms.

CLASS2: accurate and efficient splice variant annotation from RNA-seq reads.

Next generation sequencing of cellular RNA is making it possible to characterize genes and alternative splicing in unprecedented detail. However, designing bioinformatics tools to accurately capture splicing variation has proven difficult. Current programs can find major isoforms of a gene but miss lower abundance variants, or are sensitive but imprecise. CLASS2 is a novel open source tool for accurate genome-guided transcriptome assembly from RNA-seq reads based on the model of splice graph. An extension of our program CLASS, CLASS2 jointly optimizes read patterns and the number of supporting reads to score and prioritize transcripts, implemented in a novel, scalable and efficient dynamic programming algorithm. When compared against reference programs, CLASS2 had the best overall accuracy and could detect up to twice as many splicing events with precision similar to the best reference program. Notably, it was the only tool to produce consistently reliable transcript models for a wide range of applications and sequencing strategies, including ribosomal RNA-depleted samples. Lightweight and multi-threaded, CLASS2 requires <3GB RAM and can analyze a 350 million read set within hours, and can be widely applied to transcriptomics studies ranging from clinical RNA sequencing, to alternative splicing analyses, and to the annotation of new genomes.

Large-scale hypomethylated blocks associated with Epstein-Barr virus-induced B-cell immortalization.

Altered DNA methylation occurs ubiquitously in human cancer from the earliest measurable stages. A cogent approach to understanding the mechanism and timing of altered DNA methylation is to analyze it in the context of carcinogenesis by a defined agent. Epstein-Barr virus (EBV) is a human oncogenic herpesvirus associated with lymphoma and nasopharyngeal carcinoma, but also used commonly in the laboratory to immortalize human B-cells in culture. Here we have performed whole-genome bisulfite sequencing of normal B-cells, activated B-cells, and EBV-immortalized B-cells from the same three individuals, in order to identify the impact of transformation on the methylome. Surprisingly, large-scale hypomethylated blocks comprising two-thirds of the genome were induced by EBV immortalization but not by B-cell activation per se. These regions largely corresponded to hypomethylated blocks that we have observed in human cancer, and they were associated with gene-expression hypervariability, similar to human cancer, and consistent with a model of epigenomic change promoting tumor cell heterogeneity. We also describe small-scale changes in DNA methylation near CpG islands. These results suggest that methylation disruption is an early and critical step in malignant transformation.

Chlorovirus ATCV-1 is part of the human oropharyngeal virome and is associated with changes in cognitive functions in humans and mice.

Chloroviruses (family Phycodnaviridae) are large DNA viruses known to infect certain eukaryotic green algae and have not been previously shown to infect humans or to be part of the human virome. We unexpectedly found sequences homologous to the chlorovirus Acanthocystis turfacea chlorella virus 1 (ATCV-1) in a metagenomic analysis of DNA extracted from human oropharyngeal samples. These samples were obtained by throat swabs of adults without a psychiatric disorder or serious physical illness who were participating in a study that included measures of cognitive functioning. The presence of ATCV-1 DNA was confirmed by quantitative PCR with ATCV-1 DNA being documented in oropharyngeal samples obtained from 40 (43.5%) of 92 individuals. The presence of ATCV-1 DNA was not associated with demographic variables but was associated with a modest but statistically significant decrease in the performance on cognitive assessments of visual processing and visual motor speed. We further explored the effects of ATCV-1 in a mouse model. The inoculation of ATCV-1 into the intestinal tract of 9-11-wk-old mice resulted in a subsequent decrease in performance in several cognitive domains, including ones involving recognition memory and sensory-motor gating. ATCV-1 exposure in mice also resulted in the altered expression of genes within the hippocampus. These genes comprised pathways related to synaptic plasticity, learning, memory formation, and the immune response to viral exposure.

Differential expression analysis of RNA-seq data at single-base resolution.

RNA-sequencing (RNA-seq) is a flexible technology for measuring genome-wide expression that is rapidly replacing microarrays as costs become comparable. Current differential expression analysis methods for RNA-seq data fall into two broad classes: (1) methods that quantify expression within the boundaries of genes previously published in databases and (2) methods that attempt to reconstruct full length RNA transcripts. The first class cannot discover differential expression outside of previously known genes. While the second approach does possess discovery capabilities, statistical analysis of differential expression is complicated by the ambiguity and variability incurred while assembling transcripts and estimating their abundances. Here, we propose a novel method that first identifies differentially expressed regions (DERs) of interest by assessing differential expression at each base of the genome. The method then segments the genome into regions comprised of bases showing similar differential expression signal, and then assigns a measure of statistical significance to each region. Optionally, DERs can be annotated using a reference database of genomic features. We compare our approach with leading competitors from both current classes of differential expression methods and highlight the strengths and weaknesses of each. A software implementation of our method is available on github (https://github.com/alyssafrazee/derfinder).

Transcriptional derepression of the ERVWE1 locus following influenza A virus infection.

UNLABELLED: Syncytin-1, a fusogenic protein encoded by a human endogenous retrovirus of the W family (HERV-W) element (ERVWE1), is expressed in the syncytiotrophoblast layer of the placenta. This locus is transcriptionally repressed in adult tissues through promoter CpG methylation and suppressive histone modifications. Whereas syncytin-1 appears to be crucial for the development and functioning of the human placenta, its ectopic expression has been associated with pathological conditions, such as multiple sclerosis and schizophrenia. We previously reported on the transactivation of HERV-W elements, including ERVWE1, during influenza A/WSN/33 virus infection in a range of human cell lines. Here we report the results of quantitative PCR analyses of transcripts encoding syncytin-1 in both cell lines and primary fibroblast cells. We observed that spliced ERVWE1 transcripts and those encoding the transcription factor glial cells missing 1 (GCM1), acting as an enhancer element upstream of ERVWE1, are prominently upregulated in response to influenza A/WSN/33 virus infection in nonplacental cells. Knockdown of GCM1 by small interfering RNA followed by infection suppressed the transactivation of ERVWE1. While the infection had no influence on CpG methylation in the ERVWE1 promoter, chromatin immunoprecipitation assays detected decreased H3K9 trimethylation (H3K9me3) and histone methyltransferase SETDB1 levels along with influenza virus proteins associated with ERVWE1 and other HERV-W loci in infected CCF-STTG1 cells. The present findings suggest that an exogenous influenza virus infection can transactivate ERVWE1 by increasing transcription of GCM1 and reducing H3K9me3 in this region and in other regions harboring HERV-W elements. IMPORTANCE: Syncytin-1, a protein encoded by the env gene in the HERV-W locus ERVWE1, appears to be crucial for the development and functioning of the human placenta and is transcriptionally repressed in nonplacental tissues. Nevertheless, its ectopic expression has been associated with pathological conditions, such as multiple sclerosis and schizophrenia. In the present paper, we report findings suggesting that an exogenous influenza A virus infection can transactivate ERVWE1 by increasing the transcription of GCM1 and reducing the repressive histone mark H3K9me3 in this region and in other regions harboring HERV-W elements. These observations have implications of potential relevance for viral pathogenesis and for conditions associated with the aberrant transcription of HERV-W loci.

Visualization and probability-based scoring of structural variants within repetitive sequences.

MOTIVATION: Repetitive sequences account for approximately half of the human genome. Accurately ascertaining sequences in these regions with next generation sequencers is challenging, and requires a different set of analytical techniques than for reads originating from unique sequences. Complicating the matter are repetitive regions subject to programmed rearrangements, as is the case with the antigen-binding domains in the Immunoglobulin (Ig) and T-cell receptor (TCR) loci. RESULTS: We developed a probability-based score and visualization method to aid in distinguishing true structural variants from alignment artifacts. We demonstrate the usefulness of this method in its ability to separate real structural variants from false positives generated with existing upstream analysis tools. We validated our approach using both target-capture and whole-genome experiments. Capture sequencing reads were generated from primary lymphoid tumors, cancer cell lines and an EBV-transformed lymphoblast cell line over the Ig and TCR loci. Whole-genome sequencing reads were from a lymphoblastoid cell-line. AVAILABILITY: We implement our method as an R package available at https://github.com/Eitan177/targetSeqView. Code to reproduce the figures and results are also available.

Predicting Alu exonization in the human genome with a deep learning model.

Alu exonization, or the recruitment of intronic Alu elements into gene sequences, has contributed to functional diversification; however, its extent and the ways in which it influences gene regulation are not fully understood. We developed an unbiased approach to predict Alu exonization events from genomic sequences implemented in a deep learning model, eXAlu, that overcomes the limitations of tissue or condition specificity and the computational burden of RNA-seq analysis. The model captures previously reported characteristics of exonized Alu sequences and can predict sequence elements important for Alu exonization. Using eXAlu, we estimate the number of Alu elements in the human genome undergoing exonization to be between 55-110K, 11-21 fold more than represented in the GENCODE gene database. Using RT-PCR we were able to validate selected predicted Alu exonization events, supporting the accuracy of our method. Lastly, we highlight a potential application of our method to identify polymorphic Alu insertion exonizations in individuals and in the population from whole genome sequencing data.

Comprehensive and scalable quantification of splicing differences with MntJULiP.

Tools for differential splicing detection have failed to provide a comprehensive and consistent view of splicing variation. We present MntJULiP, a novel method for comprehensive and accurate quantification of splicing differences between two or more conditions. MntJULiP detects both changes in intron splicing ratios and changes in absolute splicing levels with high accuracy, and can find classes of variation overlooked by other tools. MntJULiP identifies over 29,000 differentially spliced introns in 1398 GTEx brain samples, including 11,242 novel introns discovered in this dataset. Highly scalable, MntJULiP can process thousands of samples within hours to reveal splicing constituents of phenotypic differentiation.

Differential expression of NPAS4 in the dorsolateral prefrontal cortex following opioid overdose.

Background: Although preclinical models reveal the neurobiological pathways altered through opioid abuse, comprehensive assessments of gene expression in human brain samples are needed. Moreover, less is known about gene expression in response to fatal overdose. The primary goal of the present study was to compare gene expression in the dorsolateral prefrontal cortex (DLPFC) between brain samples of individuals who died of acute opioid intoxication and group-matched controls. Methods: Postmortem tissue samples of the DLPFC from 153 deceased individuals (Mage  = 35.4; 62% male; 77% European ancestry). Study groups included 72 brain samples from individuals who died of acute opioid intoxication, 53 psychiatric controls, and 28 normal controls. Whole transcriptome RNA-sequencing was used to generate exon counts, and differential expression was tested using limma-voom. Analyses were adjusted for relevant sociodemographic characteristics, technical covariates, and cryptic relatedness using quality surrogate variables. Weighted correlation network analysis and gene set enrichment analyses also were conducted. Results: Two genes were differentially expressed in opioid samples compared to control samples. The top gene, NPAS4, was downregulated in opioid samples (log2FC = -2.47, adj. p = .049) and has been implicated in opioid, cocaine, and methamphetamine use. Weighted correlation network analysis revealed 15 gene modules associated with opioid overdose, though no intramodular hub genes were related to opioid overdose, nor were pathways related to opioid overdose enriched for differential expression. Conclusions: Results provide preliminary evidence that NPAS4 is implicated in opioid overdose, and more research is needed to understand its role in opioid abuse and associated outcomes.

Epigenome-wide association analyses of active injection drug use.

BACKGROUND: Injection drug use (IDU) is prevalent in the US and is associated with substantial risk of blood-borne infections, morbidity, and mortality. However, the spectrum of its biologic effects on DNA methylation in blood is not well characterized. METHODS: 401 participants (Mage = 47.9; 68% male; 90% African American) over several timepoints (1054 visits) were drawn from a longitudinal cohort of people who inject drugs. DNA methylation was measured among buffy coat samples from the 1054 visits. Compared to samples collected after ≥ 6 months of abstinence, separate EWAS were conducted for active injecting of any drug, quantitative injection frequency, injecting of heroin and injecting of cocaine. Linear mixed effect models were used and analyses were adjusted for repeated measurements and key technical, biological, and sociodemographic characteristics. RESULTS: We found epigenome-wide significant CpG sites associated with active injection (cg10636246, AIM2, p = 2.33 × 10-8) and injection intensity (cg13117953, p = 4.30 × 10-8). We found converging evidence that cg10636246 (AIM2), cg23110600 (PRKCH), cg03546163 (FKBP5), cg04590956 (GMCL1), and cg16317961 (MAPRE2) were among the top 0.1% significantly differentially methylated CpG sites shared across the five EWAS. Top ranked CpGs among the five EWAS were enriched (p < 0.0001) in AIM2 inflammasome complex, T cell migration, insulin regulation and epinephrine synthesis pathways. During periods of active injection, samples had 0.46 years of epigenetic age acceleration relative to the abstinence period, within the same subject (p = 0.03). CONCLUSIONS: Findings from this study demonstrate modest, common, and specific effects on DNA methylation during a relatively short time between periods of active drug injection and abstinence.

Establishing the baseline level of repetitive element expression in the human cortex.

BACKGROUND: Although nearly half of the human genome is comprised of repetitive sequences, the expression profile of these elements remains largely uncharacterized. Recently developed high throughput sequencing technologies provide us with a powerful new set of tools to study repeat elements. Hence, we performed whole transcriptome sequencing to investigate the expression of repetitive elements in human frontal cortex using postmortem tissue obtained from the Stanley Medical Research Institute. RESULTS: We found a significant amount of reads from the human frontal cortex originate from repeat elements. We also noticed that Alu elements were expressed at levels higher than expected by random or background transcription. In contrast, L1 elements were expressed at lower than expected amounts. CONCLUSIONS: Repetitive elements are expressed abundantly in the human brain. This expression pattern appears to be element specific and can not be explained by random or background transcription. These results demonstrate that our knowledge about repetitive elements is far from complete. Further characterization is required to determine the mechanism, the control, and the effects of repeat element expression.

No difference in antibody titers against xenotropic MLV related virus in prostate cancer cases and cancer-free controls.

New ELISA assays were developed to measure immunoreactivity for XMRV. Antibody titers were measured in a cohort of prostate cancer cases and cancer free controls from the central United States. No statistically significant differences were observed in immunoreactivity between cases and controls for either the XMRV-env or the XMRV-gag antigen.

Studying the virome in psychiatric disease.

An overlooked aspect of current microbiome studies is the role of viruses in human health. Compared to bacterial studies, laboratory and analytical methods to study the entirety of viral communities in clinical samples are rudimentary and need further refinement. In order to address this need, we developed Virobiome-Seq, a sequence capture method and an accompanying bioinformatics analysis pipeline, that identifies viral reads in human samples. Virobiome-Seq is able to enrich for and detect multiple types of viruses in human samples, including novel subtypes that diverge at the sequence level. In addition, Virobiome-Seq is able to detect RNA transcripts from DNA viruses and may provide a sensitive method for detecting viral activity in vivo. Since Virobiome-Seq also yields the viral sequence, it makes it possible to investigate associations between viral genotype and psychiatric illness. In this proof of concept study, we detected HIV1, Torque Teno, Pegi, Herpes and Papilloma virus sequences in Peripheral Blood Mononuclear Cells, plasma and stool samples collected from individuals with psychiatric disorders. We also detected the presence of numerous novel circular RNA viruses but were unable to determine whether these viruses originate from the sample or represent contaminants. Despite this challenge, we demonstrate that our knowledge of viral diversity is incomplete and opportunities for novel virus discovery exist. Virobiome-Seq will enable a more sophisticated analysis of the virome and has the potential of uncovering complex interactions between viral activity and psychiatric disease.