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.

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.

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.

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.

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.

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.

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.

Epigenome-wide study of brain DNA methylation following acute opioid intoxication.

BACKGROUND: Opioid abuse poses significant risk to individuals in the United States and epigenetic changes are a leading potential biomarker of opioid abuse. Current evidence, however, is mostly limited to candidate gene analysis in whole blood. To clarify the association between opioid abuse and DNA methylation, we conducted an epigenome-wide analysis of DNA methylation in brain samples of individuals who died from acute opioid intoxication and group-matched controls. METHODS: Tissue samples were extracted from the dorsolateral prefrontal cortex of 153 deceased individuals (Mage = 35.42; 62 % male; 77 % European ancestry). The study included 72 opioid samples, 53 psychiatric controls, and 28 normal controls. The epigenome-wide analysis was implemented using the Illumina MethylationEPIC BeadChip; analyses adjusted for sociodemographic characteristics, negative control principal components, ancestry principal components, cellular composition, and surrogate variables. Horvath's epigenetic age and Levine's PhenoAge were calculated, and gene set enrichment analyses were performed. RESULTS: Although no CpG sites survived false-discovery rate correction for multiple testing, 13 sites surpassed a relaxed significance threshold (p < 1.0 × 10-5). One of these sites was located within Netrin-1, a gene implicated in kappa opioid receptor activity. There was an association between opioid use and accelerated PhenoAge (b = 2.24, se = 1.11, p = .045). Gene set enrichment analyses revealed enrichment of differential methylation in GO and KEGG pathways broadly related to substance use. CONCLUSIONS: Netrin-1 may be associated with opioid overdose, and future research with larger samples across stages of opioid use will elucidate the complex genomics of opioid abuse.

Epigenome-wide association scan identifies methylation sites associated with HIV infection.

Aim: To investigate the role of epigenetics in HIV pathophysiology. Materials & methods: We conducted an epigenome-wide association scan on HIV infection status among people who inject drugs in the AIDS Linked to the IntraVenous Experience study with primary (n = 397) and validation samples (n = 390). DNA methylation from blood was measured by the Illumina EPIC BeadChip. We controlled for cell type heterogeneity by HIV status. Results: HIV infection status was associated (p < 10-8) with DNA methylation at 49 CpG sites. Sites were enriched in response to virus, interferon signaling pathway, etc. Among these sites, discovery and validation t-statistics were highly correlated (r = 0.96). Conclusion: In a cohort of people who inject drugs, HIV status was associated with differential DNA methylation at biologically meaningful sites.

A multi-sample approach increases the accuracy of transcript assembly.

Transcript assembly from RNA-seq reads is a critical step in gene expression and subsequent functional analyses. Here we present PsiCLASS, an accurate and efficient transcript assembler based on an approach that simultaneously analyzes multiple RNA-seq samples. PsiCLASS combines mixture statistical models for exonic feature selection across multiple samples with splice graph based dynamic programming algorithms and a weighted voting scheme for transcript selection. PsiCLASS achieves significantly better sensitivity-precision tradeoff, and renders precision up to 2-3 fold higher than the StringTie system and Scallop plus TACO, the two best current approaches. PsiCLASS is efficient and scalable, assembling 667 GEUVADIS samples in 9 h, and has robust accuracy with large numbers of samples.

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.

Gene Expression Profiles Associated with Brain Aging are Altered in Schizophrenia.

Existence of aging associated transcriptional differences in the schizophrenia brain was investigated in RNA sequencing data from 610 postmortem Dorso-Lateral Pre-Frontal Cortex (DLPFC) samples in the CommondMind Consortium (CMC) and the psychENCODE cohorts. This analysis discovered that the trajectory of gene expression changes that occur during brain aging differed between schizophrenia cases and unaffected controls. Mainly, the identified gene expression differences between the diagnosis groups shrank in magnitude following 60 years of age. A differential expression analysis restricted to the 40 to 60 year age group identified 556 statistically significant loci that replicated and had highly consistent gene expression fold changes in the two cohorts. An interaction between age and diagnosis in the wider psychENCODE cohort was also detected. Gene set enrichment analysis discovered disruptions in mitochondria, RNA splicing and phosphoprotein gene pathways. The identified differentially expressed genes in the two cohorts were also significantly enriched in genomic regions associated with schizophrenia although no enrichment was observed for differentially expressed genes identified in the 40 to 60 year age group. This work implicates disruptions to the normal brain aging processes in the pathology of schizophrenia and demonstrates the need for age stratification in schizophrenia postmortem brain gene expression studies.

Transcription of human endogenous retroviruses in human brain by RNA-seq analysis.

BACKGROUND: Human endogenous retroviruses (HERV) comprise 8% of the human genome and can be classified into at least 31 families. Increased levels of transcripts from the W and H families of HERV have been observed in association with human diseases, such as multiple sclerosis and schizophrenia. Although HERV transcripts have been detected in many tissues and cell-types based on microarray and PCR studies, the extent of HERV expression in different cell-types and diseases state has been less comprehensively studied. RESULTS: We examined overall transcription of HERV, and particularly of HERV-W and HERV-H elements in human postmortem brain samples obtained from individuals with psychiatric diagnoses (n = 111) and healthy controls (n = 51) by analyzing publicly available RNA sequencing datasets. Sequence reads were aligned to prototypical sequences representing HERV, downloaded from Repbase. We reported a consistent expression (0.1~0.2% of mappable reads) of different HERV families across three regions of human brains. Spearman correlations revealed highly correlated expression levels between three brain regionsacross 475 consensus sequences. By mapping sequences that aligned to the consensus sequences of HERV-W and HERV-H families to individual loci on chromosome 7, more than 60 loci from each family were identified, part of which are being transcribed. The ERVWE1, locus located at chr7q21.2, exhibited high levels of transcription across the three datasets. Notably, we demonstrated a trend of increased expression of overall HERV, as well as HERV-W family in samples from both schizophrenia and bipolar disorder patients. CONCLUSIONS: The current analyses indicate that RNA sequencing is a useful approach for investigating global expression of repetitive elements, such as HERV, in the human genome. HERV-W/H with the tendency of transcription up-regulation in patients suggests potential implication of HERV-W/H in psychiatric diseases.

Toxoplasma gondii-Induced Long-Term Changes in the Upper Intestinal Microflora during the Chronic Stage of Infection.

Toxoplasma gondii is an obligate intracellular parasite with worldwide distribution. Felines are the definitive hosts supporting the complete life cycle of T. gondii. However, other warm-blooded animals such as rodents and humans can also be infected. Infection of such secondary hosts results in long-term infection characterized by the presence of tissue cysts in the brain and other organs. While it is known that T. gondii infection in rodents is associated with behavioral changes, the mechanisms behind these changes remain unclear. Alterations of the host intestinal microflora are recognized as a prominent role player in shaping host behavior and cognition. It has been shown that acute T. gondii infection of mice results in microflora changes as a result of gastrointestinal inflammation in inbred mouse models. The long-term effects of chronic T. gondii infection on microbial communities, however, are unknown. In this study, after we verified using our model in terms of measuring microflora changes during an acute episode of toxoplasmosis, we assessed the microbiome changes that occur during a long-term infection; then we further investigated these changes in a follow-up study of chronic infection. These analyses were performed by constructing and sequencing 16S rRNA amplicon DNA libraries from small intestine fecal specimens. We found that acute infection with the GT1 strain of T. gondii caused an enrichment of Bacteroidetes compared with controls in CD1 mice. Strikingly, this enrichment upheld throughout long-term chronic infection. The potential biological consequences of this alteration in rodents and humans should be subjected to further exploration.

Analysis of microbiota in first episode psychosis identifies preliminary associations with symptom severity and treatment response.

The effects of gut microbiota on the central nervous system, along its possible role in mental disorders, have received increasing attention. Here we investigated differences in fecal microbiota between 28 patients with first-episode psychosis (FEP) and 16 healthy matched controls and explored whether such differences were associated with response after up to 12months of treatment. Numbers of Lactobacillus group bacteria were elevated in FEP-patients and significantly correlated with severity along different symptom domains. A subgroup of FEP patients with the strongest microbiota differences also showed poorer response after up to 12months of treatment. The present findings support the involvement of microbiota alterations in psychotic illness and may provide the basis for exploring the benefit of their modulation on treatment response and remission.

Association of DNA Methylation Differences With Schizophrenia in an Epigenome-Wide Association Study.

IMPORTANCE: DNA methylation may play an important role in schizophrenia (SZ), either directly as a mechanism of pathogenesis or as a biomarker of risk. OBJECTIVE: To scan genome-wide DNA methylation data to identify differentially methylated CpGs between SZ cases and controls. DESIGN, SETTING, AND PARTICIPANTS: Epigenome-wide association study begun in 2008 using DNA methylation levels of 456 513 CpG loci measured on the Infinium HumanMethylation450 array (Illumina) in a consortium of case-control studies for initial discovery and in an independent replication set. Primary analyses used general linear regression, adjusting for age, sex, race/ethnicity, smoking, batch, and cell type heterogeneity. The discovery set contained 689 SZ cases and 645 controls (n = 1334), from 3 multisite consortia: the Consortium on the Genetics of Endophenotypes in Schizophrenia, the Project among African-Americans To Explore Risks for Schizophrenia, and the Multiplex Multigenerational Family Study of Schizophrenia. The replication set contained 247 SZ cases and 250 controls (n = 497) from the Genomic Psychiatry Cohort. MAIN OUTCOMES AND MEASURES: Identification of differentially methylated positions across the genome in SZ cases compared with controls. RESULTS: Of the 689 case participants in the discovery set, 477 (69%) were men and 258 (37%) were non-African American; of the 645 controls, 273 (42%) were men and 419 (65%) were non-African American. In our replication set, cases/controls were 76% male and 100% non-African American. We identified SZ-associated methylation differences at 923 CpGs in the discovery set (false discovery rate, <0.2). Of these, 625 showed changes in the same direction including 172 with P < .05 in the replication set. Some replicated differentially methylated positions are located in a top-ranked SZ region from genome-wide association study analyses. CONCLUSIONS AND RELEVANCE: This analysis identified 172 replicated new associations with SZ after careful correction for cell type heterogeneity and other potential confounders. The overlap with previous genome-wide association study data can provide potential insights into the functional relevance of genetic signals for SZ.

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.

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.