Genetic regulation of human brain proteome reveals proteins implicated in psychiatric disorders.

Psychiatric disorders are highly heritable yet polygenic, potentially involving hundreds of risk genes. Genome-wide association studies have identified hundreds of genomic susceptibility loci with susceptibility to psychiatric disorders; however, the contribution of these loci to the underlying psychopathology and etiology remains elusive. Here we generated deep human brain proteomics data by quantifying 11,608 proteins across 268 subjects using 11-plex tandem mass tag coupled with two-dimensional liquid chromatography-tandem mass spectrometry. Our analysis revealed 788 cis-acting protein quantitative trait loci associated with the expression of 883 proteins at a genome-wide false discovery rate <5%. In contrast to expression at the transcript level and complex diseases that are found to be mainly influenced by noncoding variants, we found protein expression level tends to be regulated by non-synonymous variants. We also provided evidence of 76 shared regulatory signals between gene expression and protein abundance. Mediation analysis revealed that for most (88%) of the colocalized genes, the expression levels of their corresponding proteins are regulated by cis-pQTLs via gene transcription. Using summary data-based Mendelian randomization analysis, we identified 4 proteins and 19 genes that are causally associated with schizophrenia. We further integrated multiple omics data with network analysis to prioritize candidate genes for schizophrenia risk loci. Collectively, our findings underscore the potential of proteome-wide linkage analysis in gaining mechanistic insights into the pathogenesis of psychiatric disorders.

Transcriptome-wide profiling of acute stress induced changes in ribosome occupancy level using external standards.

Acute cellular stress is known to induce a global reduction in mRNA translation through suppression of cap dependent translation. Selective translation in response to acute stress has been shown to play important roles in regulating the stress response. However, accurately profiling translational changes transcriptome-wide in response to acute cellular stress has been challenging. Commonly used data normalization methods operate on the assumption that any systematic shifts are experimental artifacts. Consequently, if applied to profiling acute cellular stress-induced mRNA translation changes, these methods are expected to produce biased estimates. To address this issue, we designed, produced, and evaluated a panel of 16 oligomers to serve as external standards for ribosome profiling studies. Using Sodium Arsenite treatment-induced oxidative stress in lymphoblastoid cell lines as a model system, we applied spike-in oligomers as external standards. We found our spike-in oligomers to display a strong linear correlation between the observed and the expected quantification, with small ratio compression at the lower concentration range. Using the expected fold changes constructed from spike-in controls, we found in our dataset that TMM normalization, a popular global scaling normalization approach, produced 87.5% false positives at a significant cutoff that is expected to produce only 10% false positive discoveries. In addition, TMM normalization produced a systematic shift of fold change by 3.25 fold. These results highlight the consequences of applying global scaling approaches to conditions that clearly violate their key assumptions. In contrast, we found RUVg normalization using spike-in oligomers as control genes recapitulated the expected stress induced global reduction of translation and resulted in little, if any, systematic shifts in the expected fold change. Our results clearly demonstrated the utility of our spike-in oligomers, both for constructing expected results as controls and for data normalization.

The impact of common variants on gene expression in the human brain: from RNA to protein to schizophrenia risk.

Background: The impact of genetic variants on gene expression has been intensely studied at the transcription level, yielding in valuable insights into the association between genes and the risk of complex disorders, such as schizophrenia (SCZ). However, the downstream impact of these variants and the molecular mechanisms connecting transcription variation to disease risk are not well understood. Results: We quantitated ribosome occupancy in prefrontal cortex samples of the BrainGVEX cohort. Together with transcriptomics and proteomics data from the same cohort, we performed cis-Quantitative Trait Locus (QTL) mapping and identified 3,253 expression QTLs (eQTLs), 1,344 ribosome occupancy QTLs (rQTLs), and 657 protein QTLs (pQTLs) out of 7,458 genes quantitated in all three omics types from 185 samples. Of the eQTLs identified, only 34% have their effects propagated to the protein level. Further analysis on the effect size of prefrontal cortex eQTLs identified from an independent dataset showed clear post-transcriptional attenuation of eQTL effects. To investigate the biological relevance of the attenuated eQTLs, we identified 70 expression-specific QTLs (esQTLs), 51 ribosome-occupancy-specific QTLs (rsQTLs), and 107 protein-specific QTLs (psQTLs). Five of these omics-specific QTLs showed strong colocalization with SCZ GWAS signals, three of them are esQTLs. The limited number of GWAS colocalization discoveries from omics-specific QTLs and the apparent prevalence of eQTL attenuation prompted us to take a complementary approach to investigate the functional relevance of attenuated eQTLs. Using S-PrediXcan we identified 74 SCZ risk genes, 34% of which were novel, and 67% of these risk genes were replicated in a MR-Egger test. Notably, 52 out of 74 risk genes were identified using eQTL data and 70% of these SCZ-risk-gene-driving eQTLs show little to no evidence of driving corresponding variations at the protein level. Conclusion: The effect of eQTLs on gene expression in the prefrontal cortex is commonly attenuated post-transcriptionally. Many of the attenuated eQTLs still correlate with SCZ GWAS signal. Further investigation is needed to elucidate a mechanistic link between attenuated eQTLs and SCZ disease risk.

Disease modeling and gene correction of LGMDR21 iPSCs elucidates the role of POGLUT1 in skeletal muscle maintenance, regeneration, and the satellite cell niche.

Autosomal recessive limb-girdle muscular dystrophy 21 (LGMDR21) is caused by pathogenic variants in protein O-glucosyltransferase 1 (POGLUT1), which is responsible for O-glucosylation of specific epidermal growth factor (EGF) repeats found in ∼50 mammalian proteins, including Notch receptors. Previous data from patient biopsies indicated that impaired Notch signaling, reduction of muscle stem cells, and accelerated differentiation are probably involved in disease etiopathology. Using patient induced pluripotent stem cells (iPSCs), their corrected isotypes, and control iPSCs, gene expression profiling indicated dysregulation of POGLUT1, NOTCH, muscle development, extracellular matrix (ECM), cell adhesion, and migration as involved pathways. They also exhibited reduced in vitro POGLUT1 enzymatic activity and NOTCH signaling as well as defective myogenesis, proliferation, migration and differentiation. Furthermore, in vivo studies demonstrated significant reductions in engraftment, muscle stem cell formation, PAX7 expression, and maintenance, along with an increased percentage of mislocalized PAX7+ cells in the interstitial space. Gene correction in patient iPSCs using CRISPR-Cas9 nickase led to the rescue of the main in vitro and in vivo phenotypes. These results demonstrate the efficacy of iPSCs and gene correction in disease modeling and rescue of the phenotypes and provide evidence of the involvement of muscle stem cell niche localization, PAX7 expression, and cell migration as possible mechanisms in LGMDR21.

Unraveling the epigenomic and transcriptomic interplay during alcohol-induced anxiolysis.

Positive effects of alcohol drinking such as anxiolysis and euphoria appear to be a crucial factor in the initiation and maintenance of alcohol use disorder (AUD). However, the mechanisms that lead from chromatin reorganization to transcriptomic changes after acute ethanol exposure remain unknown. Here, we used Assay for Transposase-Accessible Chromatin followed by high throughput sequencing (ATAC-seq) and RNA-seq to investigate epigenomic and transcriptomic changes that underlie anxiolytic effects of acute ethanol using an animal model. Analysis of ATAC-seq data revealed an overall open or permissive chromatin state that was associated with transcriptomic changes in the amygdala after acute ethanol exposure. We identified a candidate gene, Hif3a (Hypoxia-inducible factor 3, alpha subunit), that had 'open' chromatin regions (ATAC-seq peaks), associated with significantly increased active epigenetic histone acetylation marks and decreased DNA methylation at these regions. The mRNA levels of Hif3a were increased by acute ethanol exposure, but decreased in the amygdala during withdrawal after chronic ethanol exposure. Knockdown of Hif3a expression in the central nucleus of amygdala attenuated acute ethanol-induced increases in Hif3a mRNA levels and blocked anxiolysis in rats. These data indicate that chromatin accessibility and transcriptomic signatures in the amygdala after acute ethanol exposure underlie anxiolysis and possibly prime the chromatin for the development of AUD.

Absence of coding somatic single nucleotide variants within well-known candidate genes in late-onset sporadic Alzheimer's Disease based on the analysis of multi-omics data.

Somatic mutations arise randomly or are induced by environmental factors, which may increase the risk of Alzheimer's disease (AD). Identifying somatic mutations in sporadic AD (SAD) may provide new insight of the disease. To evaluate the potential contribution of somatic single nucleotide variations (SNVs), particularly that of well-known AD-candidate genes, we investigated sequencing data sets from four platforms: whole-genome sequencing (WGS), deep whole-exome sequencing (WES) on paired brain and liver samples, RNA sequencing (RNA-seq), and single-cell whole-genome sequencing (scWGS) of brain samples from 16 AD patients and 16 non-AD individuals. We found that the average number, mean variant allele fractions (VAFs) and mutational signatures of somatic SNVs have similar distributions between AD brains and non-AD brains. We did not identify any somatic SNVs within coding regions of the APP, PSEN1, PSEN2, nor in APOE. This study shows that somatic SNVs within the coding region of AD-candidate genes are unlikely to be a common causal factor for SAD.

CpG-creating mutations are costly in many human viruses.

Mutations can occur throughout the virus genome and may be beneficial, neutral or deleterious. We are interested in mutations that yield a C next to a G, producing CpG sites. CpG sites are rare in eukaryotic and viral genomes. For the eukaryotes, it is thought that CpG sites are rare because they are prone to mutation when methylated. In viruses, we know less about why CpG sites are rare. A previous study in HIV suggested that CpG-creating transition mutations are more costly than similar non-CpG-creating mutations. To determine if this is the case in other viruses, we analyzed the allele frequencies of CpG-creating and non-CpG-creating mutations across various strains, subtypes, and genes of viruses using existing data obtained from Genbank, HIV Databases, and Virus Pathogen Resource. Our results suggest that CpG sites are indeed costly for most viruses. By understanding the cost of CpG sites, we can obtain further insights into the evolution and adaptation of viruses.

DRAMS: A tool to detect and re-align mixed-up samples for integrative studies of multi-omics data.

Studies of complex disorders benefit from integrative analyses of multiple omics data. Yet, sample mix-ups frequently occur in multi-omics studies, weakening statistical power and risking false findings. Accurately aligning sample information, genotype, and corresponding omics data is critical for integrative analyses. We developed DRAMS (https://github.com/Yi-Jiang/DRAMS) to Detect and Re-Align Mixed-up Samples to address the sample mix-up problem. It uses a logistic regression model followed by a modified topological sorting algorithm to identify the potential true IDs based on data relationships of multi-omics. According to tests using simulated data, the more types of omics data used or the smaller the proportion of mix-ups, the better that DRAMS performs. Applying DRAMS to real data from the PsychENCODE BrainGVEX project, we detected and corrected 201 (12.5% of total data generated) mix-ups. Of the 21 mix-ups involving errors of racial identity, DRAMS re-assigned all data to the correct racial group in the 1000 Genomes project. In doing so, quantitative trait loci (QTL) (FDR<0.01) increased by an average of 1.62-fold. The use of DRAMS in multi-omics studies will strengthen statistical power of the study and improve quality of the results. Even though very limited studies have multi-omics data in place, we expect such data will increase quickly with the needs of DRAMS.

Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder.

Most genetic risk for psychiatric disease lies in regulatory regions, implicating pathogenic dysregulation of gene expression and splicing. However, comprehensive assessments of transcriptomic organization in diseased brains are limited. In this work, we integrated genotypes and RNA sequencing in brain samples from 1695 individuals with autism spectrum disorder (ASD), schizophrenia, and bipolar disorder, as well as controls. More than 25% of the transcriptome exhibits differential splicing or expression, with isoform-level changes capturing the largest disease effects and genetic enrichments. Coexpression networks isolate disease-specific neuronal alterations, as well as microglial, astrocyte, and interferon-response modules defining previously unidentified neural-immune mechanisms. We integrated genetic and genomic data to perform a transcriptome-wide association study, prioritizing disease loci likely mediated by cis effects on brain expression. This transcriptome-wide characterization of the molecular pathology across three major psychiatric disorders provides a comprehensive resource for mechanistic insight and therapeutic development.

The transcription factor POU3F2 regulates a gene coexpression network in brain tissue from patients with psychiatric disorders.

Schizophrenia and bipolar disorder are complex psychiatric diseases with risks contributed by multiple genes. Dysregulation of gene expression has been implicated in these disorders, but little is known about such dysregulation in the human brain. We analyzed three transcriptome datasets from 394 postmortem brain tissue samples from patients with schizophrenia or bipolar disorder or from healthy control individuals without a known history of psychiatric disease. We built genome-wide coexpression networks that included microRNAs (miRNAs). We identified a coexpression network module that was differentially expressed in the brain tissue from patients compared to healthy control individuals. This module contained genes that were principally involved in glial and neural cell genesis and glial cell differentiation, and included schizophrenia risk genes carrying rare variants. This module included five miRNAs and 545 mRNAs, with six transcription factors serving as hub genes in this module. We found that the most connected transcription factor gene POU3F2, also identified on a genome-wide association study for bipolar disorder, could regulate the miRNA hsa-miR-320e and other putative target mRNAs. These regulatory relationships were replicated using PsychENCODE/BrainGVEX datasets and validated by knockdown and overexpression experiments in SH-SY5Y cells and human neural progenitor cells in vitro. Thus, we identified a brain gene expression module that was enriched for rare coding variants in genes associated with schizophrenia and that contained the putative bipolar disorder risk gene POU3F2 The transcription factor POU3F2 may be a key regulator of gene expression in this disease-associated gene coexpression module.

A Myogenic Double-Reporter Human Pluripotent Stem Cell Line Allows Prospective Isolation of Skeletal Muscle Progenitors.

Myogenic differentiation of human pluripotent stem cells (hPSCs) has been done by gene overexpression or directed differentiation. However, viral integration, long-term culture, and the presence of unwanted cells are the main obstacles. By using CRISPR/Cas9n, a double-reporter human embryonic stem cell (hESC) line was generated for PAX7/MYF5, allowing prospective readout. This strategy allowed pathway screen to define efficient myogenic induction in hPSCs. Next, surface marker screen allowed identification of CD10 and CD24 for purification of myogenic progenitors and exclusion of non-myogenic cells. CD10 expression was also identified on human satellite cells and skeletal muscle progenitors. In vitro and in vivo studies using transgene and/or reporter-free hPSCs further validated myogenic potential of the cells by formation of new fibers expressing human dystrophin as well as donor-derived satellite cells in NSG-mdx4Cv mice. This study provides biological insights for myogenic differentiation of hPSCs using a double-reporter cell resource and defines an improved myogenic differentiation and purification strategy.

Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia.

Schizophrenia genome-wide association studies have identified >150 regions of the genome associated with disease risk, yet there is little evidence that coding mutations contribute to this disorder. To explore the mechanism of non-coding regulatory elements in schizophrenia, we performed ATAC-seq on adult prefrontal cortex brain samples from 135 individuals with schizophrenia and 137 controls, and identified 118,152 ATAC-seq peaks. These accessible chromatin regions in the brain are highly enriched for schizophrenia SNP heritability. Accessible chromatin regions that overlap evolutionarily conserved regions exhibit an even higher heritability enrichment, indicating that sequence conservation can further refine functional risk variants. We identify few differences in chromatin accessibility between cases and controls, in contrast to thousands of age-related differential accessible chromatin regions. Altogether, we characterize chromatin accessibility in the human prefrontal cortex, the effect of schizophrenia and age on chromatin accessibility, and provide evidence that our dataset will allow for fine mapping of risk variants.

LIA5 is required for nuclear reorganization and programmed DNA rearrangements occurring during tetrahymena macronuclear differentiation.

During macronuclear differentiation of the ciliate Tetrahymena thermophila, genome-wide DNA rearrangements eliminate nearly 50 Mbp of germline derived DNA, creating a streamlined somatic genome. The transposon-like and other repetitive sequences to be eliminated are identified using a piRNA pathway and packaged as heterochromatin prior to their removal. In this study, we show that LIA5, which encodes a zinc-finger protein likely of transposon origin, is required for both chromosome fragmentation and DNA elimination events. Lia5p acts after the establishment of RNAi-directed heterochromatin modifications, but prior to the excision of the modified sequences. In ∆LIA5 cells, DNA elimination foci, large nuclear sub-structures containing the sequences to be eliminated and the essential chromodomain protein Pdd1p, do not form. Lia5p, unlike Pdd1p, is not stably associated with these structures, but is required for their formation. In the absence of Lia5p, we could recover foci formation by ectopically inducing DNA damage by UV treatment. Foci in both wild-type or UV-treated ∆LIA5 cells contain dephosphorylated Pdd1p. These studies of LIA5 reveal that DNA elimination foci form after the excision of germ-line limited sequences occurs and indicate that Pdd1p reorganization is likely mediated through a DNA damage response.

The conjugation-specific Die5 protein is required for development of the somatic nucleus in both Paramecium and Tetrahymena.

Development in ciliated protozoa involves extensive genome reorganization within differentiating macronuclei, which shapes the somatic genome of the next vegetative generation. Major events of macronuclear differentiation include excision of internal eliminated sequences (IESs), chromosome fragmentation, and genome amplification. Proteins required for these events include those with homology throughout eukaryotes as well as proteins apparently unique to ciliates. In this study, we identified the ciliate-specific Defective in IES Excision 5 (DIE5) genes of Paramecium tetraurelia (PtDIE5) and Tetrahymena thermophila (TtDIE5) as orthologs that encode nuclear proteins expressed exclusively during development. Abrogation of PtDie5 protein (PtDie5p) function by RNA interference (RNAi)-mediated silencing or TtDie5p by gene disruption resulted in the failure of developing macronuclei to differentiate into new somatic nuclei. Tetrahymena DeltaDIE5 cells arrested late in development and failed to complete genome amplification, whereas RNAi-treated Paramecium cells highly amplified new macronuclear DNA before the failure in differentiation, findings that highlight clear differences in the biology of these distantly related species. Nevertheless, IES excision and chromosome fragmentation failed to occur in either ciliate, which strongly supports that Die5p is a critical player in these processes. In Tetrahymena, loss of zygotic expression during development was sufficient to block nuclear differentiation. This observation, together with the finding that knockdown of Die5p in Paramecium still allows genome amplification, indicates that this protein acts late in macronuclear development. Even though DNA rearrangements in these two ciliates look to be quite distinct, analysis of DIE5 establishes the action of a conserved mechanism within the genome reorganization pathway.