scholarly journals BrainEXP-NPD: a database of transcriptomic profiles of human brains of six neuropsychiatric disorders

2021 ◽  
Author(s):  
Cuihua Xia ◽  
Teng Ma ◽  
Chuan Jiao ◽  
Chao Chen ◽  
Chunyu Liu
Keyword(s):  
Bipolar Disorder ◽  
Differential Expression ◽  
Differentially Expressed Genes ◽  
Neuropsychiatric Disorders ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Network Analyses ◽  
Gene Differential Expression

Background: Spatio-temporal gene expression has been widely used to study gene functions and biological mechanisms in diseases. Numerous microarray and RNA sequencing data focusing on brain transcriptomes in neuropsychiatric disorders have accumulated. However, their consistency, reproducibility has not been properly evaluated. Except for a few psychiatric disorders, like schizophrenia, bipolar disorder and autism, most have not been compared to each other for cross-disorder comparisons. Methods: We organized 48 human brain transcriptome datasets from six sources. The original brain donors include patients with schizophrenia (SCZ, N=427), bipolar disorder (BD, N=312), major depressive disorder (MDD, N=219), autism spectrum disorder (ASD, N=53), Alzheimer's disease (AD, N=765), Parkinson's disease (PD, N=163) as well as controls as unaffected by such disorders (CTRL, N=6,378), making it a total of 8,317 samples. Raw data included multiple brain regions of both sexes, with ages ranging from embryonic to seniors. After standardization, quality control, filtering and removal of known and unknown covariates, we performed comprehensive meta- and mega- analyses, including gene differential expression and gene co-expression network. Results: A total of 6922, 3011, 2703, 4389, 3507, 4279 significantly differentially expressed genes (FDR q < 0.05) were detected in the comparisons of 6 brain regions of SCZ-CTRL, 5 brain regions of BD-CTRL, 6 brain regions of MDD-CTRL, 4 brain regions of ASD-CTRL, 7 brain regions of AD-CTRL, and 6 brain regions of PD-CTRL, respectively. Most differentially expressed genes were brain region-specific and disease-specific. SCZ and BD have a maximal transcriptome similarity in striatum (ρ=0.42) among the four brain regions, as measured by Spearman's correlation of differential expression log2 FC values. SCZ and MDD have a maximal transcriptome similarity in hippocampus (ρ=0.30) among the five brain regions. BD and MDD have a maximal transcriptome similarity in frontal cortex (ρ=0.45) among the five brain regions. Other disease pairs have a less transcriptome similarity (ρ<0.1) in all brain regions. PD is negatively correlated with SCZ, BD, and MDD in cerebellum and striatum. We also performed coexpression network analyses for different disorders and controls separately. We developed a database named BrainEXP-NPD (http://brainexpnpd.org:8088/BrainEXPNPD/), to provide a user-friendly web interface for accessing the data, and analytical results of meta- and mega-analyses, including gene differential expression and gene co-expression networks between cases and controls on different brain regions, sexes and age groups. Discussion: BrainEXP-NPD compiled the largest collection of brain transcriptomic data of major neuropsychiatric disorders and presented lists of differentially expressed genes and coexpression modules in multiple brain regions of six major disorders.

scholarly journals Transcriptome analysis following EV-A71 and CV-A16 infection in respiratory epithelial cells

2020 ◽  
Author(s):  
Jie Song ◽  
Weiyu Li ◽  
Yajie Hu ◽  
Hui Li ◽  
Huiwen Zheng ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Transcriptome Sequencing ◽  
Enterovirus 71 ◽  
Foot And Mouth Disease ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Respiratory Epithelial Cells ◽  
Network Analyses ◽  
Qrt Pcr ◽  
Respiratory Epithelial

Abstract Background: Enterovirus 71 (EV-A71) and coxsackievirus A16 (CV-A16) are the major pathogens responsible for hand, foot and mouth disease (HFMD), but the detailed mechanism caused by the two viruses remains unclear. Methods: In this study, we aimed to adopt transcriptome sequencing technology to investigate changes in the transcriptome profiles after infection with EV-A71 and CV-A16 in human bronchial epithelial (16HBE) cells. Results: Through systematic bioinformatics analysis, we then searched for useful clues regarding the pathogenesis of HFMD. As a result, a total of 111 common differentially expressed genes were present in both the EV-A71- and CV-A16-infected groups. A trend analysis of these 111 genes showed that there were 91 genes displaying the same trend in the EV-A71 and CV-A16 infection groups, including 49 upregulated genes and 42 downregulated genes. These 91 genes were further used to conduct GO, pathway, and coexpression network analyses. It was discovered that the enriched GO terms (such as Histone acetylation and positive regulation of phosphorylation) and pathways (such as glycosylphosphatidylinositol (GPI)-anchor biosynthesis and DNA replication) might be closely associated with the pathogenic mechanism of the two viruses, and key genes (such as TBCK and GPC) might be involved in the progression of HFMD. Finally, we randomly selected 10 differentially expressed genes for qRT-PCR to validate the transcriptome sequencing data. The experimental qRT-PCR results were roughly in agreement with the results of transcriptome sequencing. Conclusions: Collectively, our results provide clues for the pathogenesis of HFMD induced by EV-A71 and CV-A16.

scholarly journals Developmental effects of maternal smoking during pregnancy on the human frontal cortex transcriptome

2017 ◽  
Author(s):  
Stephen A. Semick ◽  
Leonardo Collado-Torres ◽  
Christina A. Markunas ◽  
Joo Heon Shin ◽  
Amy Deep-Soboslay ◽  
...  
Keyword(s):  
Differential Expression ◽  
Maternal Smoking ◽  
Neuropsychiatric Disorders ◽  
Autism Spectrum ◽  
Differentially Expressed ◽  
Health Concern ◽  
Post Mortem ◽  
Smoking During Pregnancy ◽  
Smoking Exposure ◽  
Maternal Smoking During Pregnancy

AbstractCigarette smoking during pregnancy is a major public health concern. While there are well-described consequences in early child development, there is very little known about the effects of maternal smoking on human cortical biology during prenatal life. We therefore performed a genome-wide differential gene expression analysis using RNA sequencing (RNA-seq) on prenatal (N=33; 16 smoking-exposed) as well as adult (N=207; 57 active smokers) human post-mortem prefrontal cortices. Smoking exposure during the prenatal period was directly associated with differential expression of 14 genes; in contrast, during adulthood, despite a much larger sample size, only 2 genes showed significant differential expression (FDR<10%). Moreover, 1,315 genes showed significantly different exposure effects between maternal smoking during pregnancy and direct exposure in adulthood (FDR<10%) – these differences were largely driven by prenatal differences that were enriched for pathways previously implicated in addiction and synaptic function. Furthermore, prenatal and age-dependent differentially expressed genes were enriched for genes implicated in non-syndromic autism spectrum disorder (ASD) and were differentially expressed as a set between patients with ASD and controls in post-mortem cortical regions. These results underscore the enhanced sensitivity to the biological effect of smoking exposure in the developing brain and offer novel insight into the effects of maternal smoking during pregnancy on the prenatal human brain. They also begin to address the relationship between in utero exposure to smoking and the heightened risks for the subsequent development of neuropsychiatric disorders.One Sentence SummaryMaternal smoking during pregnancy alters the expression of genes within the developing human cortex and these changes are enriched for genes implicated in neuropsychiatric disorders.

scholarly journals Differential Gene Expression between Fungal Mating Types Is Associated with Sequence Degeneration

2020 ◽  
Vol 12 (4) ◽  
pp. 243-258 ◽  
Author(s):  
Wen-Juan Ma ◽  
Fantin Carpentier ◽  
Tatiana Giraud ◽  
Michael E Hood
Keyword(s):  
Differential Expression ◽  
Differentially Expressed Genes ◽  
Mating Type ◽  
Sex Chromosomes ◽  
Sex Chromosome ◽  
Gc Content ◽  
Differentially Expressed ◽  
Mating Types ◽  
Sexual Antagonism ◽  
Recombination Suppression

Abstract Degenerative mutations in non-recombining regions, such as in sex chromosomes, may lead to differential expression between alleles if mutations occur stochastically in one or the other allele. Reduced allelic expression due to degeneration has indeed been suggested to occur in various sex-chromosome systems. However, whether an association occurs between specific signatures of degeneration and differential expression between alleles has not been extensively tested, and sexual antagonism can also cause differential expression on sex chromosomes. The anther-smut fungus Microbotryum lychnidis-dioicae is ideal for testing associations between specific degenerative signatures and differential expression because 1) there are multiple evolutionary strata on the mating-type chromosomes, reflecting successive recombination suppression linked to mating-type loci; 2) separate haploid cultures of opposite mating types help identify differential expression between alleles; and 3) there is no sexual antagonism as a confounding factor accounting for differential expression. We found that differentially expressed genes were enriched in the four oldest evolutionary strata compared with other genomic compartments, and that, within compartments, several signatures of sequence degeneration were greater for differentially expressed than non-differentially expressed genes. Two particular degenerative signatures were significantly associated with lower expression levels within differentially expressed allele pairs: upstream insertion of transposable elements and mutations truncating the protein length. Other degenerative mutations associated with differential expression included nonsynonymous substitutions and altered intron or GC content. The association between differential expression and allele degeneration is relevant for a broad range of taxa where mating compatibility or sex is determined by genes located in large regions where recombination is suppressed.

scholarly journals Transcriptome-(phospho)proteome characterization of brain of a germline model of cytoplasmic-predominant Pten expression with autism-like phenotypes

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Stetson Thacker ◽  
Charis Eng
Keyword(s):  
Autism Spectrum ◽  
Pten Expression ◽  
Differentially Expressed ◽  
Risk Genes ◽  
Animal Modeling ◽  
Network Analyses ◽  
Phosphorylated Proteins ◽  
Mass Spectrometry Technology ◽  
Neurological Processes

AbstractPTEN has a strong Mendelian association with autism spectrum disorder (ASD), representing a special case in autism’s complex genetic architecture. Animal modeling for constitutional Pten mutation creates an opportunity to study how disruption of Pten affects neurobiology and glean potential insight into ASD pathogenesis. Subsequently, we comprehensively characterized the neural (phospho)proteome of Ptenm3m4/m3m4 mice, which exhibits cytoplasmic-predominant Pten expression, by applying mass spectrometry technology to their brains at two-weeks- (P14) and six-weeks-of-age (P40). The differentially expressed/phosphorylated proteins were subjected to gene enrichment, pathway, and network analyses to assess the affected biology. We identified numerous differentially expressed/phosphorylated proteins, finding greater dysregulation at P40 consistent with prior transcriptomic data. The affected pathways were largely related to PTEN function or neurological processes, while scant direct overlap was found across datasets. Network analysis pointed to ASD risk genes like Pten and Psd-95 as major regulatory hubs, suggesting they likely contribute to initiation or maintenance of cellular and perhaps organismal phenotypes related to ASD.

scholarly journals Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders

2021 ◽  
Author(s):  
Nevena V. Radonjić ◽  
Jonathan L. Hess ◽  
Paula Rovira ◽  
Ole Andreassen ◽  
Jan K. Buitelaar ◽  
...  
Keyword(s):  
Association Studies ◽  
Genetic Correlations ◽  
Neuropsychiatric Disorders ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Genetic Etiology ◽  
Compulsive Disorder ◽  
Pairwise Correlations ◽  
Genomewide Association ◽  
Structural Brain

AbstractGenomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

scholarly journals Integration of mRNA and miRNA Analysis Reveals the Molecular Mechanism of Cotton Response to Salt Stress

2021 ◽  
Vol 12 ◽  
Author(s):  
Jingjing Zhan ◽  
Yangyang Diao ◽  
Guo Yin ◽  
Muhammad Sajjad ◽  
Xi Wei ◽  
...  
Keyword(s):  
Salt Stress ◽  
Differential Expression ◽  
Signal Transduction Pathway ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Regulatory Relationship ◽  
Significant Differential Expression ◽  
Amplification Bias ◽  
Before And After ◽  
Increased Sensitivity

To identify the regulatory network of known and novel microRNAs (miRNAs) and their targets responding to salt stress, a combined analysis of mRNA libraries, small RNA libraries, and degradome libraries were performed. In this study, we used unique molecular identifiers (UMIs), which are more sensitive, accurate, and reproducible than traditional methods of sequencing, to quantify the number of molecules and correct for amplification bias. We identified a total of 312 cotton miRNAs using seedlings at 0, 1, 3, and 6 h after NaCl treatment, including 80 known ghr-miRNAs and 232 novel miRNAs and found 155 miRNAs that displayed significant differential expression under salt stress. Among them, fifty-nine differentially expressed miRNAs were simultaneously induced in two or three tissues, while 66, 11, and 19 were specifically expressed in the roots, leaves, and stems, respectively. It is indicated there were different populations of miRNAs against salt stress in roots, leaves and stems. 399 candidate targets of salt-induced miRNAs showed significant differential expression before and after salt treatment, and 72 targets of 25 miRNAs were verified by degradome sequencing data. Furthermore, the regulatory relationship of miRNA-target gene was validated experimentally via 5′RLM-RACE, proving our data reliability. Gene ontology and KEGG pathway analysis found that salt-responsive miRNA targets among the differentially expressed genes were significantly enriched, and mainly involved in response to the stimulus process and the plant hormone signal transduction pathway. Furthermore, the expression levels of newly identified miRNA mir1 and known miRNAs miR390 and miR393 gradually decreased when subjected to continuous salt stress, while overexpression of these miRNAs both increased sensitivity to salt stress. Those newly identified miRNAs and mRNA pairs were conducive to genetic engineering and better understanding the mechanisms responding to salt stress in cotton.

scholarly journals Palmitate and Fructose Interact to Induce Human Hepatocytes to Produce Pro-Fibrotic Transcriptional Responses in Hepatic Stellate Cells Exposed to Conditioned Media

2020 ◽  
Vol 54 (5) ◽  
pp. 1068-1082
Keyword(s):  
Differential Expression ◽  
Differentially Expressed Genes ◽  
Hepatic Stellate Cells ◽  
Stellate Cell ◽  
Stellate Cells ◽  
Human Hepatocytes ◽  
Conditioned Media ◽  
Differentially Expressed ◽  
Transcriptional Responses ◽  
Significant Differential Expression

BACKGROUND/AIMS: Excessive consumption of dietary fat and sugar is associated with an elevated risk of nonalcoholic fatty liver disease (NAFLD). Hepatocytes exposed to saturated fat or sugar exert effects on nearby hepatic stellate cells (HSCs); however, the mechanisms by which this occurs are poorly understood. We sought to determine whether paracrine effects of hepatocytes exposed to palmitate and fructose produced profibrotic transcriptional responses in HSCs. METHODS: We performed expression profiling of mRNA and lncRNA from HSCs treated with conditioned media (CM) from human hepatocytes treated with palmitate (P), fructose (F), or both (PF). RESULTS: In HSCs exposed to CM from palmitate-treated hepatocytes, we identified 374 mRNAs and 607 lncRNAs showing significant differential expression (log2 foldchange ≥ |1|; FDR ≤0.05) compared to control cells. In HSCs exposed to CM from PF-treated hepatocytes, the number of differentially expressed genes was much higher (1198 mRNAs and 3348 lncRNAs); however, CM from fructose-treated hepatocytes elicited no significant changes in gene expression. Pathway analysis of differentially expressed genes showed enrichment for hepatic fibrosis and hepatic stellate cell activation in P- (FDR =1.30E-04) and PF-(FDR =9.24E-06)
groups. We observed 71 lncRNA/nearby mRNA pairs showing differential expression under PF conditions. There were 90 mRNAs and 264 lncRNAs strongly correlated between the PF group and differentially expressed transcripts from a comparison of activated and quiescent HSCs, suggesting that some of the transcriptomic changes occurring in response to PF overlap with HSC activation. CONCLUSION: The results reported here have implications for dietary modifications in the prevention and treatment of NAFLD.

scholarly journals Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis (TRPCA) Method

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yue Hu ◽  
Jin-Xing Liu ◽  
Ying-Lian Gao ◽  
Sheng-Jun Li ◽  
Juan Wang
Keyword(s):  
Principal Component Analysis ◽  
Differentially Expressed Genes ◽  
Principal Component ◽  
Component Analysis ◽  
Differentially Expressed ◽  
Low Rank ◽  
Cancer Gene ◽  
Sequencing Data ◽  
Robust Principal Component Analysis ◽  
The Matrix

In the big data era, sequencing technology has produced a large number of biological sequencing data. Different views of the cancer genome data provide sufficient complementary information to explore genetic activity. The identification of differentially expressed genes from multiview cancer gene data is of great importance in cancer diagnosis and treatment. In this paper, we propose a novel method for identifying differentially expressed genes based on tensor robust principal component analysis (TRPCA), which extends the matrix method to the processing of multiway data. To identify differentially expressed genes, the plan is carried out as follows. First, multiview data containing cancer gene expression data from different sources are prepared. Second, the original tensor is decomposed into a sum of a low-rank tensor and a sparse tensor using TRPCA. Third, the differentially expressed genes are considered to be sparse perturbed signals and then identified based on the sparse tensor. Fourth, the differentially expressed genes are evaluated using Gene Ontology and Gene Cards tools. The validity of the TRPCA method was tested using two sets of multiview data. The experimental results showed that our method is superior to the representative methods in efficiency and accuracy aspects.

scholarly journals Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

2020 ◽  
Author(s):  
Kristen R. Maynard ◽  
Leonardo Collado-Torres ◽  
Lukas M. Weber ◽  
Cedric Uytingco ◽  
Brianna K. Barry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prefrontal Cortex ◽  
Web Application ◽  
Dorsolateral Prefrontal Cortex ◽  
Large Scale ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Sequencing Data ◽  
Dorsolateral Prefrontal ◽  
Transcriptomics Data

AbstractWe used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex (DLPFC). We identified extensive layer-enriched expression signatures, and refined associations to previous laminar markers. We overlaid our laminar expression signatures onto large-scale single nuclei RNA sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially-defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions where morphological architecture is not as well-defined as cortical laminae. We lastly created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research (http://research.libd.org/spatialLIBD).

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