Transcriptome sequencing revealed significant alteration of cortical promoter usage and splicing in schizophrenia

Increased abundance of translation machinery in stem cell-derived neural progenitor cells from four schizophrenia patients

The genetic and epigenetic factors contributing to risk for schizophrenia (SZ) remain unresolved. Here we demonstrate, for the first time, perturbed global protein translation in human-induced pluripotent stem cell (hiPSC)-derived forebrain neural progenitor cells (NPCs) from four SZ patients relative to six unaffected controls. We report increased total protein levels and protein synthesis, together with two independent sets of quantitative mass spectrometry evidence indicating markedly increased levels of ribosomal and translation initiation and elongation factor proteins, in SZ hiPSC NPCs. We posit that perturbed levels of global protein synthesis in SZ hiPSC NPCs represent a novel post-transcriptional mechanism that might contribute to disease progression.

Disturbed macro-connectivity in schizophrenia linked to oligodendrocyte dysfunction: from structural findings to molecules

Schizophrenia is a severe psychiatric disorder with multi-factorial characteristics. A number of findings have shown disrupted synaptic connectivity in schizophrenia patients and emerging evidence suggests that this results from dysfunctional oligodendrocytes, the cells responsible for myelinating axons in white matter to promote neuronal conduction. The exact cause of this is not known, although recent imaging and molecular profiling studies of schizophrenia patients have identified changes in white matter tracts connecting multiple brain regions with effects on protein signaling networks involved in the myelination process. Further understanding of oligodendrocyte dysfunction in schizophrenia could lead to identification of novel drug targets for this devastating disease.

Abnormal subcellular localization of GABAA receptor subunits in schizophrenia brain

Inhibitory neurotransmission is primarily mediated by γ-aminobutyric acid (GABA) activating synaptic GABA type A receptors (GABA(A)R). In schizophrenia, presynaptic GABAergic signaling deficits are among the most replicated findings; however, postsynaptic GABAergic deficits are less well characterized. Our lab has previously demonstrated that although there is no difference in total protein expression of the α1-6, β1-3 or γ2 GABA(A)R subunits in the superior temporal gyrus (STG) in schizophrenia, the α1, β1 and β2 GABA(A)R subunits are abnormally N-glycosylated. N-glycosylation is a posttranslational modification that has important functional roles in protein folding, multimer assembly and forward trafficking. To investigate the impact that altered N-glycosylation has on the assembly and trafficking of GABA(A)Rs in schizophrenia, this study used western blot analysis to measure the expression of α1, α2, β1, β2 and γ2 GABA(A)R subunits in subcellular fractions enriched for endoplasmic reticulum (ER) and synapses (SYN) from STG of schizophrenia (N = 16) and comparison (N = 14) subjects and found evidence of abnormal localization of the β1 and β2 GABA(A)R subunits and subunit isoforms in schizophrenia. The β2 subunit is expressed as three isoforms at 52 kDa (β2(52 kDa)), 50 kDa (β2(50 kDa)) and 48 kDa (β2(48 kDa)). In the ER, we found increased total β2 GABA(A)R subunit (β2(ALL)) expression driven by increased β2(50 kDa), a decreased ratio of β(248 kDa):β2(ALL) and an increased ratio of β2(50 kDa):β2(48 kDa). Decreased ratios of β1:β2(ALL) and β1:β2(50 kDa) in both the ER and SYN fractions and an increased ratio of β2(52 kDa):β(248 kDa) at the synapse were also identified in schizophrenia. Taken together, these findings provide evidence that alterations of N-glycosylation may contribute to GABAergic signaling deficits in schizophrenia by disrupting the assembly and trafficking of GABA(A)Rs.

Understanding complex transcriptome dynamics in schizophrenia and other neurological diseases using RNA sequencing

How the human brain develops and adapts with its trillions of functionally integrated synapses remains one of the greatest mysteries of life. With tremendous advances in neuroscience, genetics, and molecular biology, we are beginning to appreciate the scope of this complexity and define some of the parameters of the systems that make it possible. These same tools are also leading to advances in our understanding of the pathophysiology of neurocognitive and neuropsychiatric disorders. Like the substrate for these problems, the etiology is usually complex-involving an array of genetic and environmental influences. To resolve these influences and derive better interventions, we need to reveal every aspect of this complexity and model their interactions and define the systems and their regulatory structure. This is particularly important at the tissue-specific molecular interface between the underlying genetic and environmental influence defined by the transcriptome. Recent advances in transcriptome analysis facilitated by RNA sequencing (RNA-Seq) can provide unprecedented insight into the functional genomics of neurological disorders. In this review, we outline the advantages of this approach and highlight some early application of this technology in the investigation of the neuropathology of schizophrenia. Recent progress of RNA-Seq studies in schizophrenia has shown that there is extraordinary transcriptome dynamics with significant levels of alternative splicing. These studies only scratch the surface of this complexity and therefore future studies with greater depth and samples size will be vital to fully explore transcriptional diversity and its underlying influences in schizophrenia and provide the basis for new biomarkers and improved treatments.

Glial cells as key players in schizophrenia pathology: recent insights and concepts of therapy

The past decade has witnessed an explosion of knowledge on the impact of glia for the neurobiological foundation of schizophrenia. A plethora of studies have shown structural and functional abnormalities in all three types of glial cells. There is convincing evidence of reduced numbers of oligodendrocytes, impaired cell maturation and altered gene expression of myelin/oligodendrocyte-related genes that may in part explain white matter abnormalities and disturbed inter- and intra-hemispheric connectivity, which are characteristic signs of schizophrenia. Earlier reports of astrogliosis could not be confirmed by later studies, although the expression of a variety of astrocyte-related genes is abnormal in psychosis. Since astrocytes play a key role in the synaptic metabolism of glutamate, GABA, monoamines and purines, astrocyte dysfunction may contribute to certain aspects of disturbed neurotransmission in schizophrenia. Finally, increased densities of microglial cells and aberrant expression of microglia-related surface markers in schizophrenia suggest that immunological/inflammatory factors are of considerable relevance for the pathophysiology of psychosis. This review describes current evidence for the multifaceted role of glial cells in schizophrenia and discusses efforts to develop glia-directed therapies for the treatment of the disease.

Bioinformatic analyses and conceptual synthesis of evidence linking ZNF804A to risk for schizophrenia and bipolar disorder

Advances in molecular genetics, fueled by the results of large-scale genome-wide association studies, meta-analyses, and mega-analyses, have provided the means of identifying genetic risk factors for human disease, thereby enriching our understanding of the functionality of the genome in the post-genomic era. In the past half-decade, research on neuropsychiatric disorders has reached an important milestone: the identification of susceptibility genes reliably associated with complex psychiatric disorders at genome-wide levels of significance. This age of discovery provides the groundwork for follow-up studies designed to elucidate the mechanism(s) by which genetic variants confer susceptibility to these disorders. The gene encoding zinc-finger protein 804 A (ZNF804A) is among these candidate genes, recently being found to be strongly associated with schizophrenia and bipolar disorder via one of its non-coding mutations, rs1344706. Neurobiological, molecular, and bioinformatic analyses have improved our understanding of ZNF804A in general and this variant in particular; however, more work is needed to establish the mechanism(s) by which ZNF804A variants impinge on the biological substrates of the two disorders. Here, we review literature recently published on ZNF804A, and analyze critical concepts related to the biology of ZNF804A and the role of rs1344706 in schizophrenia and bipolar disorder. We synthesize the results of new bioinformatic analyses of ZNF804A with key elements of the existing literature and knowledge base. Furthermore, we suggest some potentially fruitful short- and long-term research goals in the assessment of ZNF804A.

RNA Sequencing in Schizophrenia

Schizophrenia (SCZ) is a serious psychiatric disorder that affects 1% of general population and places a heavy burden worldwide. The underlying genetic mechanism of SCZ remains unknown, but studies indicate that the disease is associated with a global gene expression disturbance across many genes. Next-generation sequencing, particularly of RNA sequencing (RNA-Seq), provides a powerful genome-scale technology to investigate the pathological processes of SCZ. RNA-Seq has been used to analyze the gene expressions and identify the novel splice isoforms and rare transcripts associated with SCZ. This paper provides an overview on the genetics of SCZ, the advantages of RNA-Seq for transcriptome analysis, the accomplishments of RNA-Seq in SCZ cohorts, and the applications of induced pluripotent stem cells and RNA-Seq in SCZ research.

Transcriptome alterations of mitochondrial and coagulation function in schizophrenia by cortical sequencing analysis

Background

Transcriptome sequencing of brain samples provides detailed enrichment analysis of differential expression and genetic interactions for evaluation of mitochondrial and coagulation function of schizophrenia. It is implicated that schizophrenia genetic and protein interactions may give rise to biological dysfunction of energy metabolism and hemostasis. These findings may explain the biological mechanisms responsible for negative and withdraw symptoms of schizophrenia and antipsychotic-induced venous thromboembolism.

We conducted a comparison of schizophrenic candidate genes from literature reviews and constructed the schizophrenia-mediator network (SCZMN) which consists of schizophrenic candidate genes and associated mediator genes by applying differential expression analysis to BA22 RNA-Seq brain data. The network was searched against pathway databases such as PID, Reactome, HumanCyc, and Cell-Map. The candidate complexes were identified by MCL clustering using CORUM for potential pathogenesis of schizophrenia.

Results

Published BA22 RNA-Seq brain data of 9 schizophrenic patients and 9 controls samples were analyzed. The differentially expressed genes in the BA22 brain samples of schizophrenia are proposed as schizophrenia candidate marker genes (SCZCGs). The genetic interactions between mitochondrial genes and many under-expressed SCZCGs indicate the genetic predisposition of mitochondria dysfunction in schizophrenia. The biological functions of SCZCGs, as listed in the Pathway Interaction Database (PID), indicate that these genes have roles in DNA binding transcription factor, signal and cancer-related pathways, coagulation and cell cycle regulation and differentiation pathways.

In the query-query protein-protein interaction (QQPPI) network of SCZCGs, TP53, PRKACA, STAT3 and SP1 were identified as the central "hub" genes. Mitochondrial function was modulated by dopamine inhibition of respiratory complex I activity. The genetic interaction between mitochondria function and schizophrenia may be revealed by DRD2 linked to NDUFS7 through protein-protein interactions of FLNA and ARRB2.

The biological mechanism of signaling pathway of coagulation cascade was illustrated by the PPI network of the SCZCGs and the coagulation-associated genes. The relationship between antipsychotic target genes (DRD2/3 and HTR2A) and coagulation factor genes (F3, F7 and F10) appeared to cascade the following hemostatic process implicating the bottleneck of coagulation genetic network by the bridging of actin-binding protein (FLNA).

Conclusions

It is implicated that the energy metabolism and hemostatic process have important roles in the pathogenesis for schizophrenia. The cross-talk of genetic interaction by these co-expressed genes and reached candidate genes may address the key network in disease pathology. The accuracy of candidate genes evaluated from different quantification tools could be improved by crosstalk analysis of overlapping genes in genetic networks.

The importance of study design for detecting differentially abundant features in high-throughput experiments

High-throughput assays, such as RNA-seq, to detect differential abundance are widely used. Variable performance across statistical tests, normalizations, and conditions leads to resource wastage and reduced sensitivity. EDDA represents a first, general design tool for RNA-seq, Nanostring, and metagenomic analysis, that rationally selects tests, predicts performance, and plans experiments to minimize resource wastage. Case studies highlight EDDA’s ability to model single-cell RNA-seq, suggesting ways to reduce sequencing costs up to five-fold and improving metagenomic biomarker detection through improved test selection. EDDA’s novel mode-based normalization for detecting differential abundance improves robustness by 10% to 20% and precision by up to 140%.

Contrasting changes in DRD1 and DRD2 splice variant expression in schizophrenia and affective disorders, and associations with SNPs in postmortem brain

Dopamine 2 receptor (DRD2) is of major interest to the pathophysiology of schizophrenia (SCZ) both as a target for antipsychotic drug action as well as a SCZ-associated risk gene. The dopamine 1 receptor (DRD1) is thought to mediate some of the cognitive deficits in SCZ, including impairment of working memory that relies on normal dorsolateral prefrontal cortex (DLPFC) function. To better understand the association of dopamine receptors with SCZ, we studied the expression of three DRD2 splice variants and the DRD1 transcript in DLPFC, hippocampus and caudate nucleus in a large cohort of subjects (~700), including patients with SCZ, affective disorders and nonpsychiatric controls (from 14th gestational week to 85 years of age), and examined genotype-expression associations of 278 single-nucleotide polymorphisms (SNPs) located in or near DRD2 and DRD1 genes. Expression of D2S mRNA and D2S/D2-long (D2L) ratio were significantly increased in DLPFC of patients with SCZ relative to controls (P<0.0001 and P<0.0001, respectively), whereas D2L, D2Longer and DRD1 were decreased (P<0.0001). Patients with affective disorders showed an opposite pattern: reduced expression of D2S (major depressive disorder, P<0.0001) and increased expression of D2L and DRD1 (bipolar disorder, P<0.0001). Moreover, SCZ-associated risk alleles at rs1079727, rs1076560 and rs2283265 predicted increased D2S/D2L expression ratio (P<0.05) in control individuals. Our data suggest that altered splicing of DRD2 and expression of DRD1 may constitute a pathophysiological mechanism in risk for SCZ and affective disorders. The association between SCZ risk-associated polymorphism and the ratio of D2S/D2L is consistent with this possibility.

The developmental transcriptome of the human brain: implications for neurodevelopmental disorders

PURPOSE OF REVIEW

Recent characterizations of the transcriptome of the developing human brain by several groups have generated comprehensive datasets on coding and noncoding RNAs that will be instrumental for illuminating the underlying biology of complex neurodevelopmental disorders. This review summarizes recent studies successfully utilizing these data to increase our understanding of the molecular mechanisms of pathogenesis.

RECENT FINDINGS

Several approaches have successfully integrated developmental transcriptome data with gene discovery to generate testable hypotheses about when and where in the developing human brain disease-associated genes converge. Specifically, these include the projection neurons in the prefrontal and primary motor--somatosensory cortex during mid-fetal development in autism spectrum disorder and the frontal cortex during fetal development in schizophrenia.

SUMMARY

Developmental transcriptome data is a key to interpreting disease-associated mutations and transcriptional changes. Novel approaches integrating the spatial and temporal dimensions of these data have increased our understanding of when and where disease occurs. Refinement of spatial and temporal properties and expanding these findings to other neurodevelopmental disorders will provide critical insights for understanding disease biology.

Ontogeny of small RNA in the regulation of mammalian brain development

BACKGROUND

MicroRNAs (miRNAs) play a pivotal role in coordinating messenger RNA (mRNA) transcription and stability in almost all known biological processes, including the development of the central nervous system. Despite our broad understanding of their involvement, we still have a very sparse understanding of specifically how miRNA contribute to the strict regional and temporal regulation of brain development. Accordingly, in the current study we have examined the contribution of miRNA in the developing rat telencephalon and mesencephalon from just after neural tube closure till birth using a genome-wide microarray strategy.

RESULTS

We identified temporally distinct expression patterns in both the telencephalon and mesencephalon for both miRNAs and their target genes. We demonstrate direct miRNA targeting of several genes involved with the migration, differentiation and maturation of neurons.

CONCLUSIONS

Our findings suggest that miRNA have significant implications for the development of neural structure and support important mechanisms that if disrupted, may contribute to or drive neurodevelopmental disorders.

Alteration of imprinted Dlk1-Dio3 miRNA cluster expression in the entorhinal cortex induced by maternal immune activation and adolescent cannabinoid exposure

A significant feature of the cortical neuropathology of schizophrenia is a disturbance in the biogenesis of short non-coding microRNA (miRNA) that regulate translation and stability of mRNA. While the biological origin of this phenomenon has not been defined, it is plausible that it relates to major environmental risk factors associated with the disorder such as exposure to maternal immune activation (MIA) and adolescent cannabis use. To explore this hypothesis, we administered the viral mimic poly I:C to pregnant rats and further exposed some of their maturing offsprings to daily injections of the synthetic cannabinoid HU210 for 14 days starting on postnatal day 35. Whole-genome miRNA expression analysis was then performed on the left and right hemispheres of the entorhinal cortex (EC), a region strongly associated with schizophrenia. Animals exposed to either treatment alone or in combination exhibited significant differences in the expression of miRNA in the left hemisphere, whereas the right hemisphere was less responsive. Hemisphere-associated differences in miRNA expression were greatest in the combined treatment and highly over-represented in a single imprinted locus on chromosome 6q32. This observation was significant as the syntenic 14q32 locus in humans encodes a large proportion of miRNAs differentially expressed in peripheral blood lymphocytes from patients with schizophrenia, suggesting that interaction of early and late environmental insults may affect miRNA expression, in a manner that is relevant to schizophrenia.

Combined analysis of exon splicing and genome wide polymorphism data predict schizophrenia risk loci

Schizophrenia has a strong genetic basis, and genome-wide association studies (GWAS) have shown that effect sizes for individual genetic variants which increase disease risk are small, making detection and validation of true disease-associated risk variants extremely challenging. Specifically, we first identify genes with exons showing differential expression between cases and controls, indicating a splicing mechanism that may contribute to variation in disease risk and focus on those showing consistent differential expression between blood and brain tissue. We then perform a genome-wide screen for SNPs associated with both normalised exon intensity of these genes (so called splicing QTLs) as well as association with schizophrenia. We identified a number of significantly associated loci with a biologically plausible role in schizophrenia, including MCPH1, DLG3, ZC3H13, and BICD2, and additional loci that influence splicing of these genes, including YWHAH. Our approach of integrating genome-wide exon intensity with genome-wide polymorphism data has identified a number of plausible SZ associated loci.

The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing

Schizophrenia (SZ) is a complex disease characterized by impaired neuronal functioning. Although defective alternative splicing has been linked to SZ, the molecular mechanisms responsible are unknown. Additionally, there is limited understanding of the early transcriptomic responses to neuronal activation. Here, we profile these transcriptomic responses and show that long non-coding RNAs (lncRNAs) are dynamically regulated by neuronal activation, including acute downregulation of the lncRNA Gomafu, previously implicated in brain and retinal development. Moreover, we demonstrate that Gomafu binds directly to the splicing factors QKI and SRSF1 (serine/arginine-rich splicing factor 1) and dysregulation of Gomafu leads to alternative splicing patterns that resemble those observed in SZ for the archetypal SZ-associated genes DISC1 and ERBB4. Finally, we show that Gomafu is downregulated in post-mortem cortical gray matter from the superior temporal gyrus in SZ. These results functionally link activity-regulated lncRNAs and alternative splicing in neuronal function and suggest that their dysregulation may contribute to neurological disorders.

Nuclear ARVCF protein binds splicing factors and contributes to the regulation of alternative splicing

The armadillo repeat protein ARVCF is a component of adherens junctions. Similar to related proteins, such as p120-catenin and β-catenin, with known signaling functions, localization studies indicate a cytoplasmic and a nuclear pool of ARVCF. We find that ARVCF interacts with different proteins involved in mRNA-processing: the splicing factor SRSF1 (SF2/ASF), the RNA helicase p68 (DDX5), and the heterogeneous nuclear ribonucleoprotein hnRNP H2. All three proteins bind to ARVCF in an RNA-independent manner. Furthermore, ARVCF occurs in large RNA-containing complexes that contain both spliced and unspliced mRNAs of housekeeping genes. By domain analysis, we show that interactions occur via the ARVCF C terminus. Overexpression of ARVCF, p68, SRSF1, and hnRNP H2 induces a significant increase in splicing activity of a reporter mRNA. Upon depletion of ARVCF followed by RNA sequence analysis, several alternatively spliced transcripts are significantly changed. Therefore, we conclude that nuclear ARVCF influences splicing of pre-mRNAs. We hypothesize that ARVCF is involved in alternative splicing, generating proteomic diversity, and its deregulation may contribute to diseased states, such as cancer and neurological disorders.

Transcriptome profiling of human hippocampus dentate gyrus granule cells in mental illness

This study is, to the best of our knowledge, the first application of whole transcriptome sequencing (RNA-seq) to cells isolated from postmortem human brain by laser capture microdissection. We investigated the transcriptome of dentate gyrus (DG) granule cells in postmortem human hippocampus in 79 subjects with mental illness (schizophrenia, bipolar disorder, major depression) and nonpsychiatric controls. We show that the choice of normalization approach for analysis of RNA-seq data had a strong effect on results; under our experimental conditions a nonstandard normalization method gave superior results. We found evidence of disrupted signaling by miR-182 in mental illness. This was confirmed using a novel method of leveraging microRNA genetic variant information to indicate active targeting. In healthy subjects and those with bipolar disorder, carriers of a high- vs those with a low-expressing genotype of miR-182 had different levels of miR-182 target gene expression, indicating an active role of miR-182 in shaping the DG transcriptome for those subject groups. By contrast, comparing the transcriptome between carriers of different genotypes among subjects with major depression and schizophrenia suggested a loss of DG miR-182 signaling in these conditions.

Immune system disturbances in schizophrenia

Epidemiological, genetic, transcriptome, postmortem, peripheral biomarker, and therapeutic studies of schizophrenia all point to a dysregulation of both innate and adaptive immune systems in the disease, and it is likely that these immune changes actively contribute to disease symptoms. Gene expression disturbances in the brain of subjects with schizophrenia show complex, region-specific changes with consistently replicated and potentially interdependent induction of serpin peptidase inhibitor, clade A member 3 (SERPINA3) and interferon inducible transmembrane protein (IFITM) family transcripts in the prefrontal cortex. Recent data suggest that IFITM3 expression is a critical mediator of maternal immune activation. Because the IFITM gene family is primarily expressed in the endothelial cells and meninges, and because the meninges play a critical role in interneuron development, we suggest that these two non-neuronal cell populations might play an important role in the disease pathophysiology. Finally, we propose that IFITM3 in particular might be a novel, appealing, knowledge-based drug target for treatment of schizophrenia.

Brain pathology in myotonic dystrophy: when tauopathy meets spliceopathy and RNAopathy

Myotonic dystrophy (DM) of type 1 and 2 (DM1 and DM2) are inherited autosomal dominant diseases caused by dynamic and unstable expanded microsatellite sequences (CTG and CCTG, respectively) in the non-coding regions of the genes DMPK and ZNF9, respectively. These mutations result in the intranuclear accumulation of mutated transcripts and the mis-splicing of numerous transcripts. This so-called RNA gain of toxic function is the main feature of an emerging group of pathologies known as RNAopathies. Interestingly, in addition to these RNA inclusions, called foci, the presence of neurofibrillary tangles (NFT) in patient brains also distinguishes DM as a tauopathy. Tauopathies are a group of nearly 30 neurodegenerative diseases that are characterized by intraneuronal protein aggregates of the microtubule-associated protein Tau (MAPT) in patient brains. Furthermore, a number of neurodegenerative diseases involve the dysregulation of splicing regulating factors and have been characterized as spliceopathies. Thus, myotonic dystrophies are pathologies resulting from the interplay among RNAopathy, spliceopathy, and tauopathy. This review will describe how these processes contribute to neurodegeneration. We will first focus on the tauopathy associated with DM1, including clinical symptoms, brain histology, and molecular mechanisms. We will also discuss the features of DM1 that are shared by other tauopathies and, consequently, might participate in the development of a tauopathy. Moreover, we will discuss the determinants common to both RNAopathies and spliceopathies that could interfere with tau-related neurodegeneration.

A genetic deconstruction of neurocognitive traits in schizophrenia and bipolar disorder

Background

Impairments in cognitive functions are common in patients suffering from psychiatric disorders, such as schizophrenia and bipolar disorder. Cognitive traits have been proposed as useful for understanding the biological and genetic mechanisms implicated in cognitive function in healthy individuals and in the dysfunction observed in psychiatric disorders.

Methods

Sets of genes associated with a range of cognitive functions often impaired in schizophrenia and bipolar disorder were generated from a genome-wide association study (GWAS) on a sample comprising 670 healthy Norwegian adults who were phenotyped for a broad battery of cognitive tests. These gene sets were then tested for enrichment of association in GWASs of schizophrenia and bipolar disorder. The GWAS data was derived from three independent single-centre schizophrenia samples, three independent single-centre bipolar disorder samples, and the multi-centre schizophrenia and bipolar disorder samples from the Psychiatric Genomics Consortium.

Results

The strongest enrichments were observed for visuospatial attention and verbal abilities sets in bipolar disorder. Delayed verbal memory was also enriched in one sample of bipolar disorder. For schizophrenia, the strongest evidence of enrichment was observed for the sets of genes associated with performance in a colour-word interference test and for sets associated with memory learning slope.

Conclusions

Our results are consistent with the increasing evidence that cognitive functions share genetic factors with schizophrenia and bipolar disorder. Our data provides evidence that genetic studies using polygenic and pleiotropic models can be used to link specific cognitive functions with psychiatric disorders.

Unique transcriptome patterns of the white and grey matter corroborate structural and functional heterogeneity in the human frontal lobe

The human frontal lobe has undergone accelerated evolution, leading to the development of unique human features such as language and self-reflection. Cortical grey matter and underlying white matter reflect distinct cellular compositions in the frontal lobe. Surprisingly little is known about the transcriptomal landscape of these distinct regions. Here, for the first time, we report a detailed transcriptomal profile of the frontal grey (GM) and white matter (WM) with resolution to alternatively spliced isoforms obtained using the RNA-Seq approach. We observed more vigorous transcriptome activity in GM compared to WM, presumably because of the presence of cellular bodies of neurons in the GM and RNA associated with the nucleus and perinuclear space. Among the top differentially expressed genes, we also identified a number of long intergenic non-coding RNAs (lincRNAs), specifically expressed in white matter, such as LINC00162. Furthermore, along with confirmation of expression of known markers for neurons and oligodendrocytes, we identified a number of genes and splicing isoforms that are exclusively expressed in GM or WM with examples of GABRB2 and PAK2 transcripts, respectively. Pathway analysis identified distinct physiological and biochemical processes specific to grey and white matter samples with a prevalence of synaptic processes in GM and myelination regulation and axonogenesis in the WM. Our study also revealed that expression of many genes, for example, the GPR123, is characterized by isoform switching, depending in which structure the gene is expressed. Our report clearly shows that GM and WM have perhaps surprisingly divergent transcriptome profiles, reflecting distinct roles in brain physiology. Further, this study provides the first reference data set for a normal human frontal lobe, which will be useful in comparative transcriptome studies of cerebral disorders, in particular, neurodegenerative diseases.

Gene set enrichment analysis of RNA-Seq data: integrating differential expression and splicing

BACKGROUND

RNA-Seq has become a key technology in transcriptome studies because it can quantify overall expression levels and the degree of alternative splicing for each gene simultaneously. To interpret high-throughout transcriptome profiling data, functional enrichment analysis is critical. However, existing functional analysis methods can only account for differential expression, leaving differential splicing out altogether.

RESULTS

In this work, we present a novel approach to derive biological insight by integrating differential expression and splicing from RNA-Seq data with functional gene set analysis. This approach designated SeqGSEA, uses count data modelling with negative binomial distributions to first score differential expression and splicing in each gene, respectively, followed by two strategies to combine the two scores for integrated gene set enrichment analysis. Method comparison results and biological insight analysis on an artificial data set and three real RNA-Seq data sets indicate that our approach outperforms alternative analysis pipelines and can detect biological meaningful gene sets with high confidence, and that it has the ability to determine if transcription or splicing is their predominant regulatory mechanism.

CONCLUSIONS

By integrating differential expression and splicing, the proposed method SeqGSEA is particularly useful for efficiently translating RNA-Seq data to biological discoveries.

Genes, behavior and next-generation RNA sequencing

Advances in next-generation sequencing suggest that RNA-Seq is poised to supplant microarray-based approaches for transcriptome analysis. This article briefly reviews the use of microarrays in the brain-behavior context and then illustrates why RNA-Seq is a superior strategy. Compared with microarrays, RNA-Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, detects allele specific expression and can be used to extract genotype information, e.g. nonsynonymous coding single nucleotide polymorphisms. Examples of where RNA-Seq has been used to assess brain gene expression are provided. Despite the advantages of RNA-Seq, some disadvantages remain. These include the high cost of RNA-Seq and the computational complexities associated with data analysis. RNA-Seq embraces the complexity of the transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain-behavior relationship is substantial.