Genome-wide identification of splicing QTLs in the human brain and their enrichment among schizophrenia-associated loci

Interacting effects of the MAM model of schizophrenia and antipsychotic treatment: Untargeted proteomics approach in adipose tissue

Schizophrenia is a severe neuropsychiatric disease associated with substantially higher mortality. Reduced life expectancy in schizophrenia relates to an increased prevalence of metabolic disturbance, and antipsychotic medication is a major contributor. Molecular mechanisms underlying adverse metabolic effects of antipsychotics are not fully understood; however, adipose tissue homeostasis deregulation appears to be a critical factor. We employed mass spectrometry-based untargeted proteomics to assess the effect of chronic olanzapine, risperidone, and haloperidol treatment in visceral adipose tissue of prenatally methylazoxymethanol (MAM) acetate exposed rats, a well-validated neurodevelopmental animal model of schizophrenia. Bioinformatics analysis of differentially expressed proteins was performed to highlight the pathways affected by MAM and the antipsychotics treatment. MAM model was associated with the deregulation of the TOR (target of rapamycin) signalling pathway. Notably, alterations in protein expression triggered by antipsychotics were observed only in schizophrenia-like MAM animals where we revealed hundreds of affected proteins according to our two-fold threshold, but not in control animals. Treatments with all antipsychotics in MAM rats resulted in the downregulation of mRNA processing and splicing, while drug-specific effects included among others upregulation of insulin resistance (olanzapine), upregulation of fatty acid metabolism (risperidone), and upregulation of nucleic acid metabolism (haloperidol). Our data indicate that deregulation of several energetic and metabolic pathways in adipose tissue is associated with APs administration and is prominent in MAM schizophrenia-like model but not in control animals.

Cis-effects on gene expression in the human prenatal brain associated with genetic risk for neuropsychiatric disorders

The majority of common risk alleles identified for neuropsychiatric disorders reside in noncoding regions of the genome and are therefore likely to impact gene regulation. However, the genes that are primarily affected and the nature and developmental timing of these effects remain unclear. Given the hypothesized role for early neurodevelopmental processes in these conditions, we here define genetic predictors of gene expression in the human fetal brain with which we perform transcriptome-wide association studies (TWASs) of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder, bipolar disorder, major depressive disorder, and schizophrenia. We identify prenatal cis-regulatory effects on 63 genes and 166 individual transcripts associated with genetic risk for these conditions. We observe pleiotropic effects of expression predictors for a number of genes and transcripts, including those of decreased DDHD2 expression in association with risk for schizophrenia and bipolar disorder, increased expression of a ST3GAL3 transcript with risk for schizophrenia and ADHD, and increased expression of an XPNPEP3 transcript with risk for schizophrenia, bipolar disorder, and major depression. For the protocadherin alpha cluster genes PCDHA7 and PCDHA8, we find that predictors of low expression are associated with risk for major depressive disorder while those of higher expression are associated with risk for schizophrenia. Our findings support a role for altered gene regulation in the prenatal brain in susceptibility to various neuropsychiatric disorders and prioritize potential risk genes for further neurobiological investigation.

WEVar: a novel statistical learning framework for predicting noncoding regulatory variants

Understanding the functional consequence of noncoding variants is of great interest. Though genome-wide association studies or quantitative trait locus analyses have identified variants associated with traits or molecular phenotypes, most of them are located in the noncoding regions, making the identification of causal variants a particular challenge. Existing computational approaches developed for prioritizing noncoding variants produce inconsistent and even conflicting results. To address these challenges, we propose a novel statistical learning framework, which directly integrates the precomputed functional scores from representative scoring methods. It will maximize the usage of integrated methods by automatically learning the relative contribution of each method and produce an ensemble score as the final prediction. The framework consists of two modes. The first 'context-free' mode is trained using curated causal regulatory variants from a wide range of context and is applicable to predict regulatory variants of unknown and diverse context. The second 'context-dependent' mode further improves the prediction when the training and testing variants are from the same context. By evaluating the framework via both simulation and empirical studies, we demonstrate that it outperforms integrated scoring methods and the ensemble score successfully prioritizes experimentally validated regulatory variants in multiple risk loci.

Meta-Analyses of Splicing and Expression Quantitative Trait Loci Identified Susceptibility Genes of Glioma

Background

The functions of most glioma risk alleles are unknown. Very few studies had evaluated expression quantitative trait loci (eQTL), and insights of susceptibility genes were limited due to scarcity of available brain tissues. Moreover, no prior study had examined the effect of glioma risk alleles on alternative RNA splicing.

Objective

This study explored splicing quantitative trait loci (sQTL) as molecular QTL and improved the power of QTL mapping through meta-analyses of both cis eQTL and sQTL.

Methods

We first evaluated eQTLs and sQTLs of the CommonMind Consortium (CMC) and Genotype-Tissue Expression Project (GTEx) using genotyping, or whole-genome sequencing and RNA-seq data. Alternative splicing events were characterized using an annotation-free method that detected intron excision events. Then, we conducted meta-analyses by pooling the eQTL and sQTL results of CMC and GTEx using the inverse variance-weighted model. Afterward, we integrated QTL meta-analysis results (Q < 0.05) with the Glioma International Case Control Study (GICC) GWAS meta-analysis (case:12,496, control:18,190), using a summary statistics-based mendelian randomization (SMR) method.

Results

Between CMC and GTEx, we combined the QTL data of 354 unique individuals of European ancestry. SMR analyses revealed 15 eQTLs in 11 loci and 32 sQTLs in 9 loci relevant to glioma risk. Two loci only harbored sQTLs (1q44 and 16p13.3). In seven loci, both eQTL and sQTL coexisted (2q33.3, 7p11.2, 11q23.3 15q24.2, 16p12.1, 20q13.33, and 22q13.1), but the target genes were different for five of these seven loci. Three eQTL loci (9p21.3, 20q13.33, and 22q13.1) and 4 sQTL loci (11q23.3, 16p13.3, 16q12.1, and 20q13.33) harbored multiple target genes. Eight target genes of sQTLs (C2orf80, SEC61G, TMEM25, PHLDB1, RP11-161M6.2, HEATR3, RTEL1-TNFRSF6B, and LIME1) had multiple alternatively spliced transcripts.

Conclusion

Our study revealed that the regulation of transcriptome by glioma risk alleles is complex, with the potential for eQTL and sQTL jointly affecting gliomagenesis in risk loci. QTLs of many loci involved multiple target genes, some of which were specific to alternative splicing. Therefore, quantitative trait loci that evaluate only total gene expression will miss many important target genes.

Splicing regulation in brain and testis: common themes for highly specialized organs

Expansion of the coding and regulatory capabilities of eukaryotic transcriptomes by alternative splicing represents one of the evolutionary forces underlying the increased structural complexity of metazoans. Brain and testes stand out as the organs that mostly exploit the potential of alternative splicing, thereby expressing the largest repertoire of splice variants. Herein, we will review organ-specific as well as common mechanisms underlying the high transcriptome complexity of these organs and discuss the impact exerted by this widespread alternative splicing regulation on the functionality and differentiation of brain and testicular cells.

Genetic Effects on Transcriptome Profiles in Colon Epithelium Provide Functional Insights for Genetic Risk Loci

BACKGROUND & AIMS

The association of genetic variation with tissue-specific gene expression and alternative splicing guides functional characterization of complex trait-associated loci and may suggest novel genes implicated in disease. Here, our aims were as follows: (1) to generate reference profiles of colon mucosa gene expression and alternative splicing and compare them across colon subsites (ascending, transverse, and descending), (2) to identify expression and splicing quantitative trait loci (QTLs), (3) to find traits for which identified QTLs contribute to single-nucleotide polymorphism (SNP)-based heritability, (4) to propose candidate effector genes, and (5) to provide a web-based visualization resource.

METHODS

We collected colonic mucosal biopsy specimens from 485 healthy adults and performed bulk RNA sequencing. We performed genome-wide SNP genotyping from blood leukocytes. Statistical approaches and bioinformatics software were used for QTL identification and downstream analyses.

RESULTS

We provided a complete quantification of gene expression and alternative splicing across colon subsites and described their differences. We identified thousands of expression and splicing QTLs and defined their enrichment at genome-wide regulatory regions. We found that part of the SNP-based heritability of diseases affecting colon tissue, such as colorectal cancer and inflammatory bowel disease, but also of diseases affecting other tissues, such as psychiatric conditions, can be explained by the identified QTLs. We provided candidate effector genes for multiple phenotypes. Finally, we provided the Colon Transcriptome Explorer web application.

CONCLUSIONS

We provide a large characterization of gene expression and splicing across colon subsites. Our findings provide greater etiologic insight into complex traits and diseases influenced by transcriptomic changes in colon tissue.

Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome

Alternative splicing (AS) is a fundamental step in eukaryotic mRNA biogenesis. Here, we develop an efficient and reproducible pipeline for the discovery of genetic variants that affect AS (splicing QTLs, sQTLs). We use it to analyze the GTEx dataset, generating a comprehensive catalog of sQTLs in the human genome. Downstream analysis of this catalog provides insight into the mechanisms underlying splicing regulation. We report that a core set of sQTLs is shared across multiple tissues. sQTLs often target the global splicing pattern of genes, rather than individual splicing events. Many also affect the expression of the same or other genes, uncovering regulatory loci that act through different mechanisms. sQTLs tend to be located in post-transcriptionally spliced introns, which would function as hotspots for splicing regulation. While many variants affect splicing patterns by altering the sequence of splice sites, many more modify the binding sites of RNA-binding proteins. Genetic variants affecting splicing can have a stronger phenotypic impact than those affecting gene expression.

Exploiting the GTEx resources to decipher the mechanisms at GWAS loci

The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.

Expression quantitative trait loci in sheep liver and muscle contribute to variations in meat traits

Background

Variants that regulate transcription, such as expression quantitative trait loci (eQTL), have shown enrichment in genome-wide association studies (GWAS) for mammalian complex traits. However, no study has reported eQTL in sheep, although it is an important agricultural species for which many GWAS of complex meat traits have been conducted. Using RNA sequence data produced from liver and muscle from 149 sheep and imputed whole-genome single nucleotide polymorphisms (SNPs), our aim was to dissect the genetic architecture of the transcriptome by associating sheep genotypes with three major molecular phenotypes including gene expression (geQTL), exon expression (eeQTL) and RNA splicing (sQTL). We also examined these three types of eQTL for their enrichment in GWAS of multi-meat traits and fatty acid profiles.

Results

Whereas a relatively small number of molecular phenotypes were significantly heritable (h² > 0, P < 0.05), their mean heritability ranged from 0.67 to 0.73 for liver and from 0.71 to 0.77 for muscle. Association analysis between molecular phenotypes and SNPs within ± 1 Mb identified many significant cis-eQTL (false discovery rate, FDR < 0.01). The median distance between the eQTL and transcription start sites (TSS) ranged from 68 to 153 kb across the three eQTL types. The number of common variants between geQTL, eeQTL and sQTL within each tissue, and the number of common variants between liver and muscle within each eQTL type were all significantly (P < 0.05) larger than expected by chance. The identified eQTL were significantly (P < 0.05) enriched in GWAS hits associated with 56 carcass traits and fatty acid profiles. For example, several geQTL in muscle mapped to the FAM184B gene, hundreds of sQTL in liver and muscle mapped to the CAST gene, and hundreds of sQTL in liver mapped to the C6 gene. These three genes are associated with body composition or fatty acid profiles.

Conclusions

We detected a large number of significant eQTL and found that the overlap of variants between eQTL types and tissues was prevalent. Many eQTL were also QTL for meat traits. Our study fills a gap in the knowledge on the regulatory variants and their role in complex traits for the sheep model.

Clinical significance and potential molecular mechanism of miRNA-222-3p in metastatic prostate cancer

The clinical significance and underlying molecular mechanism of miRNA-222-3p in metastatic prostate cancer (MPCa) remain unclear. The present study used a large number of cases (n = 1,502) based on miRNA chip and miRNA sequencing datasets to evaluate the expression and diagnostic potential of miRNA-222-3p in MPCa. We applied a variety of meta-analytic methods, including forest maps, sensitivity analysis, subgroup analysis and summary receiver operating characteristic curves, to prove the final results. MiRNA-222-3p was reduced in MPCa and had a moderate diagnostic potential in MPCa. We screened 118 miRNA-222-3p targets using three different methods including miRNA-222-3p transfected MPCa cell lines, online prediction databases and differently upregulated genes in MPCa. Moreover, functional enrichment analysis performed to explore the potential molecular mechanism of miRNA-222-3p showed that the potential target genes of miRNA-222-3p were significantly enriched in the p53 signal pathway. In the protein–protein interaction network analysis, SNAP91 was identified as a hub gene that may be closely related to MPCa. Gene chip and RNA sequencing datasets containing 1,237 samples were used to determine the expression level and diagnostic potential of SNAP91 in MPCa. SNAP91 was found to be overexpressed in MPCa and had a moderate diagnostic potential in MPCa. In addition, miRNA-222-3p expression was negatively correlated with SNAP91 expression in MPCa (r = −0.636, P = 0.006). These results demonstrated that miRNA-222-3p might play an important role in MPCa by negatively regulating SNAP91 expression. Thus, miRNA-222-3p might be a potential biomarker and therapeutic target of MPCa.

Variations and expression features of CYP2D6 contribute to schizophrenia risk

Genome-wide association studies (GWAS) have successfully identified 145 loci implicated in schizophrenia (SCZ). However, the underlying mechanisms remain largely unknown. Here, we analyze 1497 RNA-seq data in combination with their genotype data and identify SNPs that are associated with expression throughout the genome by dissecting expression features to genes (eGene) and exon-exon junctions (eJunction). Then, we colocalize eGene and eJunction with SCZ GWAS using SMR and fine mapping. Multiple ChIP-seq data and DNA methylation data generated from brain were used for identifying the causal variants. Finally, we used a hypothesis-free (no SCZ risk loci considered) enrichment analysis to determine implicated pathways. We identified 171 genes and eight splicing junctions located within four genes (SNX19, ARL6IP4, APOPT1, and CYP2D6) that potentially contribute to SCZ susceptibility. Among the genes, CYP2D6 is significantly associated with SCZ SNPs in eGene and eJunction. In-depth examination of the CYP2D6 region revealed that a nonsynonymous single nucleotide variant rs16947 is strongly associated with a higher abundance of CYP2D6 exon 3 skipping junctions. While we found rs133377 and other functional SNPs in high linkage disequilibrium with rs16947 (r² = 0.9539), histone acetylation analysis showed they are located within active transcription start sites. Furthermore, our data-driven enrichment analysis showed that CYP2D6 is significantly involved in drug metabolism of codeine, tamoxifen, and citalopram. Our study facilitates an understanding of the genetic architecture of SCZ and provides new drug targets.

Transcriptomic Insight Into the Polygenic Mechanisms Underlying Psychiatric Disorders

Over the past decade, large-scale genetic studies have successfully identified hundreds of genetic variants robustly associated with risk for psychiatric disorders. However, mechanistic insight and clinical translation continue to lag the pace of risk variant identification, hindered by the sheer number of targets and their predominant noncoding localization, as well as pervasive pleiotropy and incomplete penetrance. Successful next steps require identification of "causal" genetic variants and their proximal biological consequences; placing variants within biologically defined functional contexts, reflecting specific molecular pathways, cell types, circuits, and developmental windows; and characterizing the downstream, convergent neurobiological impact of polygenicity within an individual. Here, we discuss opportunities and challenges of high-throughput transcriptomic profiling in the human brain, and how transcriptomic approaches can help pinpoint mechanisms underlying genetic risk for psychiatric disorders at a scale necessary to tackle daunting levels of polygenicity. These include transcriptome-wide association studies for risk gene prioritization through integration of genome-wide association studies with expression quantitative trait loci. We outline transcriptomic results that inform our understanding of the brain-level molecular pathology of psychiatric disorders, including autism spectrum disorder, bipolar disorder, major depressive disorder, and schizophrenia. Finally, we discuss systems-level approaches for integration of distinct genetic, genomic, and phenotypic levels, including combining spatially resolved gene expression and human neuroimaging maps. Results highlight the importance of understanding gene expression (dys)regulation across human brain development as a major contributor to psychiatric disease pathogenesis, from common variants acting as expression quantitative trait loci to rare variants enriched for gene expression regulatory pathways.

FMRP and CYFIP1 at the Synapse and Their Role in Psychiatric Vulnerability

There is increasing awareness of the role genetic risk variants have in mediating vulnerability to psychiatric disorders such as schizophrenia and autism. Many of these risk variants encode synaptic proteins, influencing biological pathways of the postsynaptic density and, ultimately, synaptic plasticity. Fragile-X mental retardation 1 (FMR1) and cytoplasmic fragile-X mental retardation protein (FMRP)-interacting protein 1 (CYFIP1) contain 2 such examples of highly penetrant risk variants and encode synaptic proteins with shared functional significance. In this review, we discuss the biological actions of FMRP and CYFIP1, including their regulation of (i) protein synthesis and specifically FMRP targets, (ii) dendritic and spine morphology, and (iii) forms of synaptic plasticity such as long-term depression. We draw upon a range of preclinical studies that have used genetic dosage models of FMR1 and CYFIP1 to determine their biological function. In parallel, we discuss how clinical studies of fragile X syndrome or 15q11.2 deletion patients have informed our understanding of FMRP and CYFIP1, and highlight the latest psychiatric genomic findings that continue to implicate FMRP and CYFIP1. Lastly, we assess the current limitations in our understanding of FMRP and CYFIP1 biology and how they must be addressed before mechanism-led therapeutic strategies can be developed for psychiatric disorders.

Multi-omics study for interpretation of genome-wide association study

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with complex traits, including a wide variety of diseases. Despite the successful identification of associated loci, interpreting GWAS findings remains challenging and requires other biological resources. Omics, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics, are increasingly used in a broad range of research fields. Integrative analyses applying GWAS with these omics data are expected to expand our knowledge of complex traits and provide insight into the pathogenesis of complex diseases and their causative factors. Recently, associations between genetic variants and omics data have been comprehensively evaluated, providing new information on the influence of genetic variants on omics. Furthermore, recent advances in analytic methods, including single-cell technologies, have revealed previously unknown disease mechanisms. To advance our understanding of complex traits, integrative analysis using GWAS with multi-omics data is needed. In this review, I describe successful examples of integrative analyses based on omics and GWAS, discuss the limitations of current multi-omics analyses, and provide a perspective on future integrative studies.

High Levels of Genetic Diversity within Nilo-Saharan Populations: Implications for Human Adaptation

Africa contains more human genetic variation than any other continent, but the majority of the population-scale analyses of the African peoples have focused on just two of the four major linguistic groups, the Niger-Congo and Afro-Asiatic, leaving the Nilo-Saharan and Khoisan populations under-represented. In order to assess genetic variation and signatures of selection within a Nilo-Saharan population and between the Nilo-Saharan and Niger-Congo and Afro-Asiatic, we sequenced 50 genomes from the Nilo-Saharan Lugbara population of North-West Uganda and 250 genomes from 6 previously unsequenced Niger-Congo populations. We compared these data to data from a further 16 Eurasian and African populations including the Gumuz, another putative Nilo-Saharan population from Ethiopia. Of the 21 million variants identified in the Nilo-Saharan population, 3.57 million (17%) were not represented in dbSNP and included predicted non-synonymous mutations with possible phenotypic effects. We found greater genetic differentiation between the Nilo-Saharan Lugbara and Gumuz populations than between any two Afro-Asiatic or Niger-Congo populations. F3 tests showed that Gumuz contributed a genetic component to most Niger-Congo B populations whereas Lugabara did not. We scanned the genomes of the Lugbara for evidence of selective sweeps. We found selective sweeps at four loci (SLC24A5, SNX13, TYRP1, and UVRAG) associated with skin pigmentation, three of which already have been reported to be under selection. These selective sweeps point toward adaptations to the intense UV radiation of the Sahel.

Fragile X-related protein family: a double-edged sword in neurodevelopmental disorders and cancer

The fragile X-related (FXR) family proteins FMRP, FXR1, and FXR2 are RNA binding proteins that play a critical role in RNA metabolism, neuronal plasticity, and muscle development. These proteins share significant homology in their protein domains, which are functionally and structurally similar to each other. FXR family members are known to play an essential role in causing fragile X mental retardation syndrome (FXS), the most common genetic form of autism spectrum disorder. Recent advances in our understanding of this family of proteins have occurred in tandem with discoveries of great importance to neurological disorders and cancer biology via the identification of their novel RNA and protein targets. Herein, we review the FXR family of proteins as they pertain to FXS, other mental illnesses, and cancer. We emphasize recent findings and analyses that suggest contrasting functions of this protein family in FXS and tumorigenesis based on their expression patterns in human tissues. Finally, we discuss current gaps in our knowledge regarding the FXR protein family and their role in FXS and cancer and suggest future studies to facilitate bench to bedside translation of the findings.

Genetic analyses support the contribution of mRNA N6-methyladenosine (m6A) modification to human disease heritability

N6-methyladenosine (m6A) plays important roles in regulating messenger RNA processing. Despite rapid progress in this field, little is known about the genetic determinants of m6A modification and their role in common diseases. In this study, we mapped the quantitative trait loci (QTLs) of m6A peaks in 60 Yoruba (YRI) lymphoblastoid cell lines. We found that m6A QTLs are largely independent of expression and splicing QTLs and are enriched with binding sites of RNA-binding proteins, RNA structure-changing variants and transcriptional features. Joint analysis of the QTLs of m6A and related molecular traits suggests that the downstream effects of m6A are heterogeneous and context dependent. We identified proteins that mediate m6A effects on translation. Through integration with data from genome-wide association studies, we show that m6A QTLs contribute to the heritability of various immune and blood-related traits at levels comparable to splicing QTLs and roughly half of expression QTLs. By leveraging m6A QTLs in a transcriptome-wide association study framework, we identified putative risk genes of these traits.

Identification of de novo mutations in prenatal neurodevelopment-associated genes in schizophrenia in two Han Chinese patient-sibling family-based cohorts

Schizophrenia (SCZ) is a severe psychiatric disorder with a strong genetic component. High heritability of SCZ suggests a major role for transmitted genetic variants. Furthermore, SCZ is also associated with a marked reduction in fecundity, leading to the hypothesis that alleles with large effects on risk might often occur de novo. In this study, we conducted whole-genome sequencing for 23 families from two cohorts with unaffected siblings and parents. Two nonsense de novo mutations (DNMs) in GJC1 and HIST1H2AD were identified in SCZ patients. Ten genes (DPYSL2, NBPF1, SDK1, ZNF595, ZNF718, GCNT2, SNX9, AACS, KCNQ1, and MSI2) were found to carry more DNMs in SCZ patients than their unaffected siblings by burden test. Expression analyses indicated that these DNM implicated genes showed significantly higher expression in prefrontal cortex in prenatal stage. The DNM in the GJC1 gene is highly likely a loss function mutation (pLI = 0.94), leading to the dysregulation of ion channel in the glutamatergic excitatory neurons. Analysis of rare variants in independent exome sequencing dataset indicates that GJC1 has significantly more rare variants in SCZ patients than in unaffected controls. Data from genome-wide association studies suggested that common variants in the GJC1 gene may be associated with SCZ and SCZ-related traits. Genes co-expressed with GJC1 are involved in SCZ, SCZ-associated pathways, and drug targets. These evidences suggest that GJC1 may be a risk gene for SCZ and its function may be involved in prenatal and early neurodevelopment, a vulnerable period for developmental disorders such as SCZ.

Regional Variation of Splicing QTLs in Human Brain

A major question in human genetics is how sequence variants of broadly expressed genes produce tissue- and cell type-specific molecular phenotypes. Genetic variation of alternative splicing is a prevalent source of transcriptomic and proteomic diversity in human populations. We investigated splicing quantitative trait loci (sQTLs) in 1,209 samples from 13 human brain regions, using RNA sequencing (RNA-seq) and genotype data from the Genotype-Tissue Expression (GTEx) project. Hundreds of sQTLs were identified in each brain region. Some sQTLs were shared across brain regions, whereas others displayed regional specificity. These “regionally ubiquitous” and “regionally specific” sQTLs showed distinct positional distributions of single-nucleotide polymorphisms (SNPs) within and outside essential splice sites, respectively, suggesting their regulation by distinct molecular mechanisms. Integrating the binding motifs and expression patterns of RNA binding proteins with exon splicing profiles, we uncovered likely causal variants underlying brain region-specific sQTLs. Notably, SNP rs17651213 created a putative binding site for the splicing factor RBFOX2 and was associated with increased splicing of MAPT exon 3 in cerebellar tissues, where RBFOX2 was highly expressed. Overall, our study reveals a more comprehensive spectrum and regional variation of sQTLs in human brain and demonstrates that such regional variation can be used to fine map potential causal variants of sQTLs and their associated neurological diseases.

The Role of Noncoding Variants in Heritable Disease

The genetic basis of disease has largely focused on coding regions. However, it has become clear that a large proportion of the noncoding genome is functional and harbors genetic variants that contribute to disease etiology. Here, we review recent examples of inherited noncoding alterations that are responsible for Mendelian disorders or act to influence complex traits. We explore both rare and common genetic variants and discuss the wide range of mechanisms by which they affect gene regulation to promote disease. We also debate the challenges and progress associated with identifying and interpreting the functional and clinical significance of genetic variation in the context of the noncoding regulatory landscape.

Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants

Most neuropsychiatric disease risk variants are in noncoding sequences and lack functional interpretation. Because regulatory sequences often reside in open chromatin, we reasoned that neuropsychiatric disease risk variants may affect chromatin accessibility during neurodevelopment. Using human induced pluripotent stem cell (iPSC)-derived neurons that model developing brains, we identified thousands of genetic variants exhibiting allele-specific open chromatin (ASoC). These neuronal ASoCs were partially driven by altered transcription factor binding, overrepresented in brain gene enhancers and expression quantitative trait loci, and frequently associated with distal genes through chromatin contacts. ASoCs were enriched for genetic variants associated with brain disorders, enabling identification of functional schizophrenia risk variants and their cis-target genes. This study highlights ASoC as a functional mechanism of noncoding neuropsychiatric risk variants, providing a powerful framework for identifying disease causal variants and genes.

A Human-Specific Schizophrenia Risk Tandem Repeat Affects Alternative Splicing of a Human-Unique Isoform AS3MTd2d3 and Mushroom Dendritic Spine Density

Recent advances in functional genomics have facilitated the identification of multiple genes and isoforms associated with the genetic risk of schizophrenia, yet the causal variations remain largely unclear. A previous study reported that the schizophrenia risk single-nucleotide polymorphism (SNP) rs7085104 at 10q24.32 was in high linkage disequilibrium (LD) with a human-specific variable number of tandem repeat (VNTR), and both were significantly associated with the brain mRNA expression of a human-unique AS3MTd2d3 isoform in Europeans and African Americans. In this study, we have shown the direct regulation of the AS3MTd2d3 mRNA expression by this VNTR through an in vitro minigene splicing assay, suggesting that it is likely a causative functional variation. Intriguingly, we have further confirmed that the VNTR and rs7085104 are significantly associated with AS3MTd2d3 mRNA expression in brains of Han Chinese donors, and rs7085104 is also associated with risk of schizophrenia in East Asians. Finally, the overexpression of AS3MTd2d3 in cultured primary hippocampal neurons results in significantly reduced densities of mushroom dendritic spines, implicating its potential functional impact. Considering the crucial roles of dendritic spines in neuroplasticity, these results reveal the potential regulatory impact of the schizophrenia risk VNTR on AS3MTd2d3 and provide insights into the underlying biological mechanisms.

Innovative Therapeutic and Delivery Approaches Using Nanotechnology to Correct Splicing Defects Underlying Disease

Alternative splicing of pre-mRNA contributes strongly to the diversity of cell- and tissue-specific protein expression patterns. Global transcriptome analyses have suggested that >90% of human multiexon genes are alternatively spliced. Alterations in the splicing process cause missplicing events that lead to genetic diseases and pathologies, including various neurological disorders, cancers, and muscular dystrophies. In recent decades, research has helped to elucidate the mechanisms regulating alternative splicing and, in some cases, to reveal how dysregulation of these mechanisms leads to disease. The resulting knowledge has enabled the design of novel therapeutic strategies for correction of splicing-derived pathologies. In this review, we focus primarily on therapeutic approaches targeting splicing, and we highlight nanotechnology-based gene delivery applications that address the challenges and barriers facing nucleic acid-based therapeutics.

Unravelling the complex genetics of common kidney diseases: from variants to mechanisms

Genome-wide association studies (GWAS) have identified hundreds of loci associated with kidney-related traits such as glomerular filtration rate, albuminuria, hypertension, electrolyte and metabolite levels. However, these impressive, large-scale mapping approaches have not always translated into an improved understanding of disease or development of novel therapeutics. GWAS have several important limitations. Nearly all disease-associated risk loci are located in the non-coding region of the genome and therefore, their target genes, affected cell types and regulatory mechanisms remain unknown. Genome-scale approaches can be used to identify associations between DNA sequence variants and changes in gene expression (quantified through bulk and single-cell methods), gene regulation and other molecular quantitative trait studies, such as chromatin accessibility, DNA methylation, protein expression and metabolite levels. Data obtained through these approaches, used in combination with robust computational methods, can deliver robust mechanistic inferences for translational exploitation. Understanding the genetic basis of common kidney diseases means having a comprehensive picture of the genes that have a causal role in disease development and progression, of the cells, tissues and organs in which these genes act to affect the disease, of the cellular pathways and mechanisms that drive disease, and of potential targets for disease prevention, detection and therapy.

The Genetic Regulation of Alternative Splicing in Populus deltoides

Alternative splicing (AS) is a mechanism of regulation of the proteome via enabling the production of multiple mRNAs from a single gene. To date, the dynamics of AS and its effects on the protein sequences of individuals in a large and genetically unrelated population of trees have not been investigated. Here we describe the diversity of AS events within a previously genotyped population of 268 individuals of Populus deltoides and their putative downstream functional effects. Using a robust bioinformatics pipeline, the AS events and resulting transcript isoforms were discovered and quantified for each individual in the population. Analysis of the AS revealed that, as expected, most AS isoforms are conserved. However, we also identified a substantial collection of new, unannotated splice junctions and transcript isoforms. Heritability estimates for the expression of transcript isoforms showed that approximately half of the isoforms are heritable. The genetic regulators of these AS isoforms and splice junction usage were then identified using a genome-wide association analysis. The expression of AS isoforms was predominately cis regulated while splice junction usage was generally regulated in trans. Additionally, we identified 696 genes encoding alternatively spliced isoforms that changed putative protein domains relative to the longest protein coding isoform of the gene, and 859 genes exhibiting this same phenomenon relative to the most highly expressed isoform. Finally, we found that 748 genes gained or lost micro-RNA binding sites relative to the longest protein coding isoform of a given gene, while 940 gained or lost micro-RNA binding sites relative to the most highly expressed isoform. These results indicate that a significant fraction of AS events are genetically regulated and that this isoform usage can result in protein domain architecture changes.

SNP2APA: a database for evaluating effects of genetic variants on alternative polyadenylation in human cancers

Alternative polyadenylation (APA) is an important post-transcriptional regulation that recognizes different polyadenylation signals (PASs), resulting in transcripts with different 3' untranslated regions, thereby influencing a series of biological processes and functions. Recent studies have revealed that some single nucleotide polymorphisms (SNPs) could contribute to tumorigenesis and development through dysregulating APA. However, the associations between SNPs and APA in human cancers remain largely unknown. Here, using genotype and APA data of 9082 samples from The Cancer Genome Atlas (TCGA) and The Cancer 3'UTR Altas (TC3A), we systematically identified SNPs affecting APA events across 32 cancer types and defined them as APA quantitative trait loci (apaQTLs). As a result, a total of 467 942 cis-apaQTLs and 30 721 trans-apaQTLs were identified. By integrating apaQTLs with survival and genome-wide association studies (GWAS) data, we further identified 2154 apaQTLs associated with patient survival time and 151 342 apaQTLs located in GWAS loci. In addition, we designed an online tool to predict the effects of SNPs on PASs by utilizing PAS motif prediction tool. Finally, we developed SNP2APA, a user-friendly and intuitive database (http://gong_lab.hzau.edu.cn/SNP2APA/) for data browsing, searching, and downloading. SNP2APA will significantly improve our understanding of genetic variants and APA in human cancers.

CancerSplicingQTL: a database for genome-wide identification of splicing QTLs in human cancer

Alternative splicing (AS) is a widespread process that increases structural transcript variation and proteome diversity. Aberrant splicing patterns are frequently observed in cancer initiation, progress, prognosis and therapy. Increasing evidence has demonstrated that AS events could undergo modulation by genetic variants. The identification of splicing quantitative trait loci (sQTLs), genetic variants that affect AS events, might represent an important step toward fully understanding the contribution of genetic variants in disease development. However, no database has yet been developed to systematically analyze sQTLs across multiple cancer types. Using genotype data from The Cancer Genome Atlas and corresponding AS values calculated by TCGASpliceSeq, we developed a computational pipeline to identify sQTLs from 9 026 tumor samples in 33 cancer types. We totally identified 4 599 598 sQTLs across all cancer types. We further performed survival analyses and identified 17 072 sQTLs associated with patient overall survival times. Furthermore, using genome-wide association study (GWAS) catalog data, we identified 1 180 132 sQTLs overlapping with known GWAS linkage disequilibrium regions. Finally, we constructed a user-friendly database, CancerSplicingQTL (http://www.cancersplicingqtl-hust.com/) for users to conveniently browse, search and download data of interest. This database provides an informative sQTL resource for further characterizing the potential functional roles of SNPs that control transcript isoforms in human cancer.

Prenatal NO2 exposure and neurodevelopmental disorders in offspring mice: Transcriptomics reveals sex-dependent changes in cerebral gene expression

BACKGROUND

Early-life exposure to nitrogen dioxide (NO₂) is associated with an increased risk of developing a neurodevelopmental disorder during childhood or later in life.

OBJECTIVES

We investigated whether prenatal NO₂ inhalation causes neurodevelopmental abnormalities and cognitive deficits in weanling offspring without subsequent postnatal NO₂ exposure and how this prenatal exposure contributes to postnatal consequences.

METHODS

Pregnant C57BL/6 mice were exposed to air or NO₂ (2.5 ppm, 5 h/day) throughout gestation, and the offspring were sacrificed on postnatal days (PNDs) 1, 7, 14 and 21. We determined the mRNA profiles of different postnatal developmental windows, detected the long noncoding RNA (lncRNA) profiles and cognitive function in weanling offspring, and analyzed the effects of hub lncRNAs on differentially expressed genes (DEGs).

RESULTS

Prenatal NO₂ inhalation significantly impaired cognitive function in the weanling male, but not female, offspring. The male-specific response was coupled with abnormal neuropathologies and transcriptional profiles in the cortex during different postnatal developmental windows. Consistently, Gene Ontology (GO) analysis of the DEGs revealed persistent disruptions in neurodevelopment-associated biological processes and cellular components in the male offspring, and Apolipoprotein E (ApoE) was one of key factors contributing to prenatal exposure-induced male-specific neurological dysfunction. In addition, distinct sex-dependent lncRNA expression was identified in the weanling offspring, and metastasis-associated lung adenocarcinoma transcript 1 (Malat1) acted as a hub lncRNA and was coexpressed with most coding genes in the lncRNA-mRNA coexpressed pairs in the male offspring. Importantly, lncRNA Malat1 expression was elevated, and Malat1 modulated ApoE expression through NF-κB activation during this process.

CONCLUSIONS

Prenatal NO₂ exposure is related to sex-dependent neurocognitive deficits and transcriptomic profile changes in the cortices of the prenatally exposed offspring. Male-specific neurological dysfunction is associated with the constant alteration of genes during postnatal neurodevelopment and their transcriptional modulation by hub lncRNAs.

Alternative splicing related genetic variants contribute to bladder cancer risk

Emerging evidence has shown that aberrant alternative splicing (AS) events are involved in the carcinogenesis. The association between genetic variants in AS and bladder cancer susceptibility remains to be fully elucidated. We searched for single nucleotide polymorphisms (SNPs) which are located in splicing quantitative trait loci (sQTLs) in bladder cancer through CancerSplicingQTL database and the 1000 Genomes Project. A case-control study including 580 cases and 1,101 controls was conducted to assess the association between the functional genetic variants and bladder cancer risk. Next, we used GTEx, TCGA, and GEO databases conducting sQTL analysis and gene expression differences analysis to evaluate the potential biological function of the candidate SNPs and related genes. We found that SNP rs4383 C>G was remarkably related with the reduced risk of bladder cancer (odds ratio = 0.68, 95% confidence interval = 0.59-0.79, P = 3.91 × 10^-7 ). Similar results were obtained in codominant, dominant and recessive model. Stratified analyses revealed that the effect of SNP rs4383 C>G on bladder cancer was more significant in the older subjects (age > 65), female and nonsmokers. sQTL analysis showed that SNP rs4383 was associated with the AS events of its downstream gene MAFF with a splicing event of alternative 5' splice site. The messenger RNA expression of MAFF in bladder tumor tissues was lowered compared with normal tissues. Patients with high expression of MAFF had higher survival rates. These findings indicated that SNP rs4383 related with the AS events of MAFF was associated with bladder cancer risk and could represent a possible biomarker for bladder cancer susceptibility.

Profiling haplotype specific CpG and CpH methylation within a schizophrenia GWAS locus on chromosome 14 in schizophrenia and healthy subjects

Interrogating DNA methylation within schizophrenia risk loci holds promise to identify mechanisms by which genes influence the disease. Based on the hypothesis that allele specific methylation (ASM) of a single CpG, or perhaps CpH, might mediate or mark the effects of genetic variants on disease risk and phenotypes, we explored haplotype specific methylation levels of individual cytosines within a genomic region harbouring the BAG5, APOPT1 and KLC1 genes in peripheral blood of schizophrenia patients and healthy controls. Three DNA fragments located in promoter, intronic and intergenic areas were studied by single-molecule real-time bisulfite sequencing enabling the analysis of long reads of DNA with base-pair resolution and the determination of haplotypes directly from sequencing data. Among 1,012 cytosines studied, we did not find any site where methylation correlated with the disease or cognitive deficits after correction for multiple testing. At the same time, we determined the methylation profile associated with the schizophrenia risk haplotype within the KLC1 fourth intron and confirmed ASM for cytosines located in the vicinity of rs67899457. These genetically associated DNA methylation variations may be related to the pathophysiological mechanism differentiating the risk and non-risk haplotypes and merit further investigation.

IGREX for quantifying the impact of genetically regulated expression on phenotypes

By leveraging existing GWAS and eQTL resources, transcriptome-wide association studies (TWAS) have achieved many successes in identifying trait-associations of genetically regulated expression (GREX) levels. TWAS analysis relies on the shared GREX variation across GWAS and the reference eQTL data, which depends on the cellular conditions of the eQTL data. Considering the increasing availability of eQTL data from different conditions and the often unknown trait-relevant cell/tissue-types, we propose a method and tool, IGREX, for precisely quantifying the proportion of phenotypic variation attributed to the GREX component. IGREX takes as input a reference eQTL panel and individual-level or summary-level GWAS data. Using eQTL data of 48 tissue types from the GTEx project as a reference panel, we evaluated the tissue-specific IGREX impact on a wide spectrum of phenotypes. We observed strong GREX effects on immune-related protein biomarkers. By incorporating trans-eQTLs and analyzing genetically regulated alternative splicing events, we evaluated new potential directions for TWAS analysis.

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

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

Regulation of gene expression and splicing are thought to be tissue-specific. Here, the authors obtain genomic and transcriptomic data from putamen and substantia nigra of 117 neurologically healthy human brains and find that splicing eQTLs are enriched for neuron-specific regulatory information.

Identification of 34 genes conferring genetic and pharmacological risk for the comorbidity of schizophrenia and smoking behaviors

The prevalence of smoking is significantly higher in persons with schizophrenia (SCZ) than in the general population. However, the biological mechanisms of the comorbidity of smoking and SCZ are largely unknown. This study aimed to reveal shared biological pathways for the two diseases by analyzing data from two genome-wide association studies with a total sample size of 153,898. With pathway-based analysis, we first discovered 18 significantly enriched pathways shared by SCZ and smoking, which were classified into five groups: postsynaptic density, cadherin binding, dendritic spine, long-term depression, and axon guidance. Then, by using an integrative analysis of genetic, epigenetic, and expression data, we found not only 34 critical genes (e.g., PRKCZ, ARHGEF3, and CDKN1A) but also various risk-associated SNPs in these genes, which convey susceptibility to the comorbidity of the two disorders. Finally, using both in vivo and in vitro data, we demonstrated that the expression profiles of the 34 genes were significantly altered by multiple psychotropic drugs. Together, this multi-omics study not only reveals target genes for new drugs to treat SCZ but also reveals new insights into the shared genetic vulnerabilities of SCZ and smoking behaviors.

ABCA7 Gene Expression and Genetic Association Study in Schizophrenia

INTRODUCTION

Although ATP-binding cassette sub-family A member 7 gene (ABCA7) is known to be associated with Alzheimer's disease, the relationship between ABCA7 and schizophrenia has been unknown.

METHODS

Schizophrenia patients (n = 50; 24 males, 62.1 ± 0.50 years old) and age- and sex-matched healthy controls (n = 50) were recruited for the mRNA analysis. Additionally, a case-control study for the rs3764650 genotypes was performed with 1308 samples (control subjects; n = 527, schizophrenia patients; n = 781). All participants were Japanese, unrelated to each other, and living in the same area.

RESULTS

The distributions of the rs3764650 genotypes in schizophrenia patients were not different from that of controls. However, the ABCA7 mRNA expression levels in schizophrenia patients were significantly higher than those in controls by a logistic regression analysis. Additionally, the ABCA7 mRNA expression levels in schizophrenia patients were correlated with the rs3764650 genotypes in a dose-dependent manner.

DISCUSSION

The ABCA7 mRNA expression levels in peripheral blood with the rs3764650 genotypes may be related to pathological mechanisms in schizophrenia and may be a biological marker for schizophrenia.

Genetics' Piece of the PI: Inferring the Origin of Complex Traits and Diseases from Proteome-Wide Protein-Protein Interaction Dynamics

How do common and rare genetic polymorphisms contribute to quantitative traits or disease risk and progression? Multiple human traits have been extensively characterized at the genomic level, revealing their complex genetic architecture. However, it is difficult to resolve the mechanisms by which specific variants contribute to a phenotype. Recently, analyses of variant effects on molecular traits have uncovered intermediate mechanisms that link sequence variation to phenotypic changes. Yet, these methods only capture a fraction of genetic contributions to phenotype. Here, in reviewing the field, it is proposed that complex traits can be understood by characterizing the dynamics of biochemical networks within living cells, and that the effects of genetic variation can be captured on these networks by using protein-protein interaction (PPI) methodologies. This synergy between PPI methodologies and the genetics of complex traits opens new avenues to investigate the molecular etiology of human diseases and to facilitate their prevention or treatment.

Exploring the RNA Gap for Improving Diagnostic Yield in Primary Immunodeficiencies

Challenges in diagnosing primary immunodeficiency are numerous and diverse, with current whole-exome and whole-genome sequencing approaches only able to reach a molecular diagnosis in 25–60% of cases. We assess these problems and discuss how RNA-focused analysis has expanded and improved in recent years and may now be utilized to gain an unparalleled insight into cellular immunology. We review how investigation into RNA biology can give information regarding the differential expression, monoallelic expression, and alternative splicing—which have important roles in immune regulation and function. We show how this information can inform bioinformatic analysis pipelines and aid in the variant filtering process, expediting the identification of causal variants—especially those affecting splicing—and enhance overall diagnostic ability. We also demonstrate the challenges, which remain in the design of this type of investigation, regarding technological limitation and biological considerations and suggest potential directions for the clinical applications.

Identification of human genetic variants controlling circular RNA expression

Circular RNAs (circRNAs) are abundant in eukaryotic transcriptomes and have been linked to various human disorders. However, understanding genetic control of circular RNA expression is in the early stages. Here we present the first integrated analysis of circRNAs and genome sequence variation from lymphoblastoid cell lines of the 1000 Genomes Project. We identified thousands of circRNAs in the RNA-seq data and show their association with local single-nucleotide polymorphic sites, referred to as circQTLs, which influence the circRNA transcript abundance. Strikingly, we found that circQTLs exist independently of eQTLs with most circQTLs having no effect on mRNA expression. Only a fraction of the polymorphic sites are shared and linked to both circRNA and mRNA expression with mostly similar effects on circular and linear RNA. A shared intronic QTL, rs55928920, of HMSD gene drives the circular and linear expression in opposite directions, potentially modulating circRNA levels at the expense of mRNA. Finally, circQTLs and eQTLs are largely independent and exist in separate linkage disequilibrium (LD) blocks with circQTLs highly enriched for functional genomic elements and regulatory regions. This study reveals a previously uncharacterized role of DNA sequence variation in human circular RNA regulation.

Selective Genetic Overlap Between Amyotrophic Lateral Sclerosis and Diseases of the Frontotemporal Dementia Spectrum

Importance

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by loss of upper and lower motor neurons. Although novel ALS genetic variants have been identified, the shared genetic risk between ALS and other neurodegenerative disorders remains poorly understood.

Objectives

To examine whether there are common genetic variants that determine the risk for ALS and other neurodegenerative diseases and to identify their functional pathways.

Design, Setting, and Participants

In this study conducted from December 1, 2016, to August 1, 2017, the genetic overlap between ALS, sporadic frontotemporal dementia (FTD), FTD with TDP-43 inclusions, Parkinson disease (PD), Alzheimer disease (AD), corticobasal degeneration (CBD), and progressive supranuclear palsy (PSP) were systematically investigated in 124 876 cases and controls. No participants were excluded from this study. Diagnoses were established using consensus criteria.

Main Outcomes and Measures

The primary outcomes were a list of novel loci and their functional pathways in ALS, FTD, PSP, and ALS mouse models.

Results

Among 124 876 cases and controls, genome-wide conjunction analyses of ALS, FTD, PD, AD, CBD, and PSP revealed significant genetic overlap between ALS and FTD at known ALS loci: rs13302855 and rs3849942 (nearest gene, C9orf72; P = .03 for rs13302855 and P = .005 for rs3849942) and rs4239633 (nearest gene, UNC13A; P = .03). Significant genetic overlap was also found between ALS and PSP at rs7224296, which tags the MAPT H1 haplotype (nearest gene, NSF; P = .045). Shared risk genes were enriched for pathways involving neuronal function and development. At a conditional FDR P < .05, 22 novel ALS polymorphisms were found, including rs538622 (nearest gene, ERGIC1; P = .03 for ALS and FTD), which modifies BNIP1 expression in human brains (35 of 137 females; mean age, 59 years; P = .001). BNIP1 expression was significantly reduced in spinal cord motor neurons from patients with ALS (4 controls: mean age, 60.5 years, mean [SE] value, 3984 [760.8] arbitrary units [AU]; 7 patients with ALS: mean age, 56 years, mean [SE] value, 1999 [274.1] AU; P = .02), in an ALS mouse model (mean [SE] value, 13.75 [0.09] AU for 2 SOD1 WT mice and 11.45 [0.03] AU for 2 SOD1 G93A mice; P = .002) and in brains of patients with PSP (80 controls: 39 females; mean age, 82 years, mean [SE] value, 6.8 [0.2] AU; 84 patients with PSP: 33 females, mean age 74 years, mean [SE] value, 6.8 [0.1] AU; β = -0.19; P = .009) or FTD (11 controls: 4 females; mean age, 67 years; mean [SE] value, 6.74 [0.05] AU; 17 patients with FTD: 10 females; mean age, 69 years; mean [SE] value, 6.53 [0.04] AU; P = .005).

Conclusions and Relevance

This study found novel genetic overlap between ALS and diseases of the FTD spectrum, that the MAPT H1 haplotype confers risk for ALS, and identified the mitophagy-associated, proapoptotic protein BNIP1 as an ALS risk gene. Together, these findings suggest that sporadic ALS may represent a selectively pleiotropic, polygenic disorder.

Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms

Tissue-specific regulatory regions harbor substantial genetic risk for disease. Because brain development is a critical epoch for neuropsychiatric disease susceptibility, we characterized the genetic control of the transcriptome in 201 mid-gestational human brains, identifying 7,962 expression quantitative trait loci (eQTL) and 4,635 spliceQTL (sQTL), including several thousand prenatal-specific regulatory regions. We show that significant genetic liability for neuropsychiatric disease lies within prenatal eQTL and sQTL. Integration of eQTL and sQTL with genome-wide association studies (GWAS) via transcriptome-wide association identified dozens of novel candidate risk genes, highlighting shared and stage-specific mechanisms in schizophrenia (SCZ). Gene network analysis revealed that SCZ and autism spectrum disorder (ASD) affect distinct developmental gene co-expression modules. Yet, in each disorder, common and rare genetic variation converges within modules, which in ASD implicates superficial cortical neurons. More broadly, these data, available as a web browser and our analyses, demonstrate the genetic mechanisms by which developmental events have a widespread influence on adult anatomical and behavioral phenotypes.

Genome-Wide Identification of Splicing Quantitative Trait Loci (sQTLs) in Diverse Ecotypes of Arabidopsis thaliana

Alternative splicing (AS) of pre-mRNAs contributes to transcriptome diversity and enables plants to generate different protein isoforms from a single gene and/or fine-tune gene expression during different development stages and environmental changes. Although AS is pervasive, the genetic basis for differential isoform usage in plants is still emerging. In this study, we performed genome-wide analysis in 666 geographically distributed diverse ecotypes of Arabidopsis thaliana to identify genomic regions [splicing quantitative trait loci (sQTLs)] that may regulate differential AS. These ecotypes belong to different microclimatic conditions and are part of the relict and non-relict populations. Although sQTLs were spread across the genome, we observed enrichment for trans-sQTL (trans-sQTLs hotspots) on chromosome one. Furthermore, we identified several sQTL (911) that co-localized with trait-linked single nucleotide polymorphisms (SNP) identified in the Arabidopsis genome-wide association studies (AraGWAS). Many sQTLs were enriched among circadian clock, flowering, and stress-responsive genes, suggesting a role for differential isoform usage in regulating these important processes in diverse ecotypes of Arabidopsis. In conclusion, the current study provides a deep insight into SNPs affecting isoform ratios/genes and facilitates a better mechanistic understanding of trait-associated SNPs in GWAS studies. To the best of our knowledge, this is the first report of sQTL analysis in a large set of Arabidopsis ecotypes and can be used as a reference to perform sQTL analysis in the Brassicaceae family. Since whole genome and transcriptome datasets are available for these diverse ecotypes, it could serve as a powerful resource for the biological interpretation of trait-associated loci, splice isoform ratios, and their phenotypic consequences to help produce more resilient and high yield crop varieties.

Synergistic effects of common schizophrenia risk variants

The mechanisms by which common risk variants of small effect interact to contribute to complex genetic disorders are unclear. Here, we apply a genetic approach, using isogenic human induced pluripotent stem cells, to evaluate the effects of schizophrenia (SZ)-associated common variants predicted to function as SZ expression quantitative trait loci (eQTLs). By integrating CRISPR-mediated gene editing, activation and repression technologies to study one putative SZ eQTL (FURIN rs4702) and four top-ranked SZ eQTL genes (FURIN, SNAP91, TSNARE1 and CLCN3), our platform resolves pre- and postsynaptic neuronal deficits, recapitulates genotype-dependent gene expression differences and identifies convergence downstream of SZ eQTL gene perturbations. Our observations highlight the cell-type-specific effects of common variants and demonstrate a synergistic effect between SZ eQTL genes that converges on synaptic function. We propose that the links between rare and common variants implicated in psychiatric disease risk constitute a potentially generalizable phenomenon occurring more widely in complex genetic disorders.

DNA Variant in the RPGRIP1L Gene Influences Alternative Splicing

The retinitis pigmentosa GTPase regulator interacting protein 1-like (RPGRIP1L) gene encodes a ciliary protein that is critical for processes related to brain development, including development of left-right asymmetry, sonic hedgehog signaling, and neural tube formation. RPGRIP1L is a risk factor for retinal degeneration, and rare, deleterious variants in the RPGRIP1L gene cause Joubert syndrome and Meckel syndrome, both autosomal recessive disorders. These syndromes are characterized by dysfunctional primary cilia that result in abnormal development - and even lethality in the case of Meckel syndrome. Genetic studies have also implicated RPGRIP1L in psychiatric disorders by suggestive findings from genome-wide association studies and findings from rare-variant exome analyses for bipolar disorder and de novo mutations in autism. In this study we identify a common variant in RPGRIP1L, rs7203525, that influences alternative splicing, increasing the inclusion of exon 20 of RPGRIP1L. We detected this alternative splicing association in human postmortem brain tissue samples and, using a minigene assay combined with in vitro mutagenesis, confirmed that the alternative splicing is attributable to the alleles of this variant. The predominate RPGRIP1L isoform expressed in adult brains does not contain exon 20; thus, a shift to include this exon may impact brain function.

Genetic association of molecular traits: A help to identify causative variants in complex diseases

In the past 15 years, major progresses have been made in the understanding of the genetic basis of regulation of gene expression. These new insights have revolutionized our approach to resolve the genetic variation underlying complex diseases. Gene transcript levels were the first expression phenotypes that were studied. They are heritable and therefore amenable to genome-wide association studies. The genetic variants that modulate them are called expression quantitative trait loci. Their study has been extended to other molecular quantitative trait loci (molQTLs) that regulate gene expression at the various levels, from chromatin state to cellular responses. Altogether, these studies have generated a wealth of basic information on the genome-wide patterns of gene expression and their inter-individual variation. Most importantly, molQTLs have become an invaluable asset in the genetic study of complex diseases. Although the identification of the disease-causing variants on the basis of their overlap with molQTLs requires caution, molQTLs can help to prioritize the relevant candidate gene(s) in the disease-associated regions and bring a functional interpretation of the associated variants, therefore, bridging the gap between genotypes and clinical phenotypes.

The Length of the Expressed 3' UTR Is an Intermediate Molecular Phenotype Linking Genetic Variants to Complex Diseases

In the last decades, genome-wide association studies (GWAS) have uncovered tens of thousands of associations between common genetic variants and complex diseases. However, these statistical associations can rarely be interpreted functionally and mechanistically. As the majority of the disease-associated variants are located far from coding sequences, even the relevant gene is often unclear. A way to gain insight into the relevant mechanisms is to study the genetic determinants of intermediate molecular phenotypes, such as gene expression and transcript structure. We propose a computational strategy to discover genetic variants affecting the relative expression of alternative 3′ untranslated region (UTR) isoforms, generated through alternative polyadenylation, a widespread posttranscriptional regulatory mechanism known to have relevant functional consequences. When applied to a large dataset in which whole genome and RNA sequencing data are available for 373 European individuals, 2,530 genes with alternative polyadenylation quantitative trait loci (apaQTL) were identified. We analyze and discuss possible mechanisms of action of these variants, and we show that they are significantly enriched in GWAS hits, in particular those concerning immune-related and neurological disorders. Our results point to an important role for genetically determined alternative polyadenylation in affecting predisposition to complex diseases, and suggest new ways to extract functional information from GWAS data.

Detection of circular RNA expression and related quantitative trait loci in the human dorsolateral prefrontal cortex

BACKGROUND

Circular RNAs (circRNAs) are implicated in various biological processes. As a layer of the gene regulatory network, circRNA expression is also an intermediate phenotype bridging genetic variation and phenotypic changes. Thus, analyzing circRNA expression variation will shed light on molecular fundamentals of complex traits and diseases.

RESULTS

We systematically characterize 10,559 high-quality circRNAs in 589 human dorsolateral prefrontal cortex samples. We identify biological and technical factors contributing to expression heterogeneity associated with the expression levels of many circRNAs, including the well-known circRNA CDR1as. Combining the expression levels of circRNAs with genetic cis-acting SNPs, we detect 196,255 circRNA quantitative trait loci (circQTLs). By characterizing circQTL SNPs, we find that partial circQTL SNPs might influence circRNA formation by altering the canonical splicing site or the reverse complementary sequence match. Additionally, we find that a subset of these circQTL SNPs is highly linked to genome-wide association study signals of complex diseases, especially schizophrenia, inflammatory bowel disease, and type II diabetes mellitus.

CONCLUSIONS

Our results reveal technical, biological, and genetic factors affecting circRNA expression variation among individuals, which lead to further understanding of circRNA regulation and thus of the genetic architecture of complex traits or diseases.

[Pathophysiological implication of the VPAC2 receptor in psychiatric disorders]

The advent of the genomic era has led to the discovery of linkages of several genes and pathways to schizophrenia and autism spectrum disorder (ASD) that may serve as new biomarkers or therapeutic targets for these diseases. Two large-scale genetic studies published early in 2011 provided evidence that functional microduplications at 7q36.3, containing VIPR2, are a risk factor for schizophrenia. 7q36.3 microduplications were also reported to be significantly increased in ASD. VIPR2 encodes VPAC2, a seven transmembrane heterotrimeric G protein-coupled receptor that binds two homologous neuropeptides with high affinity, PACAP and VIP. These clinical studies demonstrate a VIPR2 genetic linkage to schizophrenia and ASD and should lead to novel insights into the etiology of these mental health disorders. However, the mechanism by which overactive VPAC2 signaling may lead to schizophrenia and ASD is unknown. In the present review, we will describe recent advances in the genetics of schizophrenia and attempt to discuss the pathophysiological role of altered VPAC2 signaling in psychiatric disorders.

Genome-wide identification and analysis of the eQTL lncRNAs in multiple sclerosis based on RNA-seq data

The pathogenesis of multiple sclerosis (MS) is significantly regulated by long noncoding RNAs (lncRNAs), the expression of which is substantially influenced by a number of MS-associated risk single nucleotide polymorphisms (SNPs). It is thus hypothesized that the dysregulation of lncRNA induced by genomic variants may be one of the key molecular mechanisms for the pathology of MS. However, due to the lack of sufficient data on lncRNA expression and SNP genotypes of the same MS patients, such molecular mechanisms underlying the pathology of MS remain elusive. In this study, a bioinformatics strategy was applied to obtain lncRNA expression and SNP genotype data simultaneously from 142 samples (51 MS patients and 91 controls) based on RNA-seq data, and an expression quantitative trait loci (eQTL) analysis was conducted. In total, 2383 differentially expressed lncRNAs were identified as specifically expressing in brain-related tissues, and 517 of them were affected by SNPs. Then, the functional characterization, secondary structure changes and tissue and disease specificity of the cis-eQTL SNPs and lncRNA were assessed. The cis-eQTL SNPs were substantially and specifically enriched in neurological disease and intergenic region, and the secondary structure was altered in 17.6% of all lncRNAs in MS. Finally, the weighted gene coexpression network and gene set enrichment analyses were used to investigate how the influence of SNPs on lncRNAs contributed to the pathogenesis of MS. As a result, the regulation of lncRNAs by SNPs was found to mainly influence the antigen processing/presentation and mitogen-activated protein kinases (MAPK) signaling pathway in MS. These results revealed the effectiveness of the strategy proposed in this study and give insight into the mechanism (SNP-mediated modulation of lncRNAs) underlying the pathology of MS.

S-CAP extends pathogenicity prediction to genetic variants that affect RNA splicing

Exome analysis of patients with a likely monogenic disease does not identify a causal variant in over half of cases. Splice-disrupting mutations make up the second largest class of known disease-causing mutations. Each individual (singleton) exome harbors over 500 rare variants of unknown significance (VUS) in the splicing region. The existing relevant pathogenicity prediction tools tackle all non-coding variants as one amorphic class and/or are not calibrated for the high sensitivity required for clinical use. Here we calibrate seven such tools and devise a novel tool called Splicing Clinically Applicable Pathogenicity prediction (S-CAP) that is over twice as powerful as all previous tools, removing 41% of patient VUS at 95% sensitivity. We show that S-CAP does this by using its own features and not via meta-prediction over previous tools, and that splicing pathogenicity prediction is distinct from predicting molecular splicing changes. S-CAP is an important step on the path to deriving non-coding causal diagnoses.

A Multiplexed Assay for Exon Recognition Reveals that an Unappreciated Fraction of Rare Genetic Variants Cause Large-Effect Splicing Disruptions

Mutations that lead to splicing defects can have severe consequences on gene function and cause disease. Here, we explore how human genetic variation affects exon recognition by developing a multiplexed functional assay of splicing using Sort-seq (MFASS). We assayed 27,733 variants in the Exome Aggregation Consortium (ExAC) within or adjacent to 2,198 human exons in the MFASS minigene reporter and found that 3.8% (1,050) of variants, most of which are extremely rare, led to large-effect splice-disrupting variants (SDVs). Importantly, we find that 83% of SDVs are located outside of canonical splice sites, are distributed evenly across distinct exonic and intronic regions, and are difficult to predict a priori. Our results indicate extant, rare genetic variants can have large functional effects on splicing at appreciable rates, even outside the context of disease, and MFASS enables their empirical assessment at scale.

Estimating contribution of rare non-coding variants to neuropsychiatric disorders

Owing to recent advances in DNA sequencing technology, a number of large-scale comprehensive analyses of genetic variations in protein-coding regions (i.e., whole-exome sequencing studies), have been conducted for neuropsychiatric and neurodevelopmental disorders, such as autism spectrum disorders, intellectual disability, and schizophrenia. These studies, especially those focusing on de novo (newly arising) mutations and extremely rare variants, have successfully identified previously unrecognized disease genes/mutations with a large effect size and deepen our understanding of the biology of neuropsychiatric diseases. Along with the continuously dropping sequencing cost, now the target of sequencing studies is expanding from the exome to the whole human genome. Several pioneering works have provided important insights into the contribution of rare non-coding variants to neuropsychiatric diseases. At the same time, these studies highlight need for further larger sample sizes and improvement in annotation of non-coding regulatory variants. In this review, key findings from recent studies as well as likely future directions are overviewed.