Tissue-specific Gene Regulation Research Articles

TAD boundary deletion causes PITX2-related cardiac electrical and structural defects

While 3D chromatin organization in topologically associating domains (TADs) and loops mediating regulatory element-promoter interactions is crucial for tissue-specific gene regulation, the extent of their involvement in human Mendelian disease is largely unknown. Here, we identify 7 families presenting a new cardiac entity associated with a heterozygous deletion of 2 CTCF binding sites on 4q25, inducing TAD fusion and chromatin conformation remodeling. The CTCF binding sites are located in a gene desert at 1 Mb from the Paired-like homeodomain transcription factor 2 gene (PITX2). By introducing the ortholog of the human deletion in the mouse genome, we recapitulate the patient phenotype and characterize an opposite dysregulation of PITX2 expression in the sinoatrial node (ectopic activation) and ventricle (reduction), respectively. Chromatin conformation assay performed in human induced pluripotent stem cell-derived cardiomyocytes harboring the minimal deletion identified in family#1 reveals a conformation remodeling and fusion of TADs. We conclude that TAD remodeling mediated by deletion of CTCF binding sites causes a new autosomal dominant Mendelian cardiac disorder.

TOPMed imputed genomics enhances genomic atlas of the human proteome in brain, cerebrospinal fluid, and plasma

Comprehensive expression quantitative trait loci studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein quantitative trait loci in brain, cerebrospinal fluid, and plasma. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in cerebrospinal fluid, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 loci in brain, 30 loci in cerebrospinal fluid, and 22 loci in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These resources are accessible through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer for use by the scientific community.

The genetic regulation of the gastric transcriptome is associated with metabolic and obesity-related traits and diseases.

Tissue-specific gene expression and gene regulation lead to a better understanding of tissue-specific physiology and pathophysiology. We analyzed the transcriptome and genetic regulatory profiles of two distinct gastric sites, corpus and antrum, to identify tissue-specific gene expression and its regulation. Gastric corpus and antrum mucosa biopsies were collected during routine gastroscopies from up to 431 healthy individuals. We obtained genotype and transcriptome data and performed transcriptome profiling and expression quantitative trait locus (eQTL) studies. We further used data from genome-wide association studies (GWAS) of various diseases and traits to partition their heritability and to perform transcriptome-wide association studies (TWAS). The transcriptome data from corpus and antral mucosa highlights the heterogeneity of gene expression in the stomach. We identified enriched pathways revealing distinct and common physiological processes in gastric corpus and antrum. Furthermore, we found an enrichment of the single nucleotide polymorphism (SNP)-based heritability of metabolic, obesity-related, and cardiovascular traits and diseases by considering corpus- and antrum-specifically expressed genes. Particularly, we could prioritize gastric-specific candidate genes for multiple metabolic traits, like NQO1 which is involved in glucose metabolism, MUC1 which contributes to purine and protein metabolism or RAB27B being a regulator of weight and body composition. Our findings show that gastric corpus and antrum vary in their transcriptome and genetic regulatory profiles indicating physiological differences which are mostly related to digestion and epithelial protection. Moreover, our findings demonstrate that the genetic regulation of the gastric transcriptome is linked to biological mechanisms associated with metabolic, obesity-related, and cardiovascular traits and diseases. NEW & NOTEWORTHY We analyzed the transcriptomes and genetic regulatory profiles of gastric corpus and for the first time also of antrum mucosa in 431 healthy individuals. Through tissue-specific gene expression and eQTL analyses, we uncovered unique and common physiological processes across both primary gastric sites. Notably, our findings reveal that stomach-specific eQTLs are enriched in loci associated with metabolic traits and diseases, highlighting the pivotal role of gene expression regulation in gastric physiology and potential pathophysiology.

Chromatin priming elements direct tissue-specific gene activity before hematopoietic specification.

Tissue-specific gene regulation during development involves the interplay between transcription factors and epigenetic regulators binding to enhancer and promoter elements. The pattern of active enhancers defines the cellular differentiation state. However, developmental gene activation involves a previous step called chromatin priming which is not fully understood. We recently developed a genome-wide functional assay that allowed us to functionally identify enhancer elements integrated in chromatin regulating five stages spanning the in vitro differentiation of embryonic stem cells to blood. We also measured global chromatin accessibility, histone modifications, and transcription factor binding. The integration of these data identified and characterised cis-regulatory elements which become activated before the onset of gene expression, some of which are primed in a signalling-dependent fashion. Deletion of such a priming element leads to a delay in the up-regulation of its associated gene in development. Our work uncovers the details of a complex network of regulatory interactions with the dynamics of early chromatin opening being at the heart of dynamic tissue-specific gene expression control.

Human endogenous retroviruses of the HERV-K (HML-2) family are expressed in the brain of healthy individuals and modify the composition of the brain-infiltrating immune cells

Human endogenous retroviruses (HERVs) are remnants of ancient retroviral infections in the human genome. RNA expression of individual HERVs has frequently been observed in various pathologic conditions, but some activity can also be seen in healthy individuals, e.g. in the blood. To quantitate the basal expression levels of HERVs in the brain, we now used high-throughput sequencing-based metagenomic analysis to characterize the expression profiles of the HERV-K (HML-2) family proviruses in different brain regions of healthy brain tissue. To this end, RNA-seq data from the Genotype-Tissue Expression (GTEx) project was used. The GTEx project is a public resource to study tissue-specific gene expression and regulation, consisting of a large selection of sequenced samples from different tissues. The GTEx data used in this study consisted of 378 samples taken from 13 brain regions from 55 individuals. The data demonstrated that out of 99 intact proviruses in the family 58 were expressed, but the expression profiles were highly divergent and there were no significant differences in the expression profiles between the various anatomic regions of the brain. It is known that the brain contains a variety of infiltrating immune cells, which are probably of great importance both in the normal defense mechanisms as well as in the various pathogenic processes. Digital cytometry (CIBERSORTx) was used to quantify the proportions of the infiltrating immune cells in the same brain samples. Six most abundant (>5 % of the total population) cell types were observed to be CD4 memory resting T cells, M0 macrophages, plasma cells, CD8 T cells, CD4 memory activated T cells, and monocytes. Analysis of the correlations between the individual HERVs and infiltrating cell types indicated that a cluster of 6 HERVs had a notable correlation signature between T cell type infiltrating cell proportions and HERV RNA expression intensity. The correlations between inflammatory type infiltrating cells were negative or weak. Taken together, these data indicate that the expression of HERVs is associated with a T cell type immunity.

Historical RNA expression profiles from the extinct Tasmanian tiger.

Paleogenomics continues to yield valuable insights into the evolution, population dynamics, and ecology of our ancestors and other extinct species. However, DNA sequencing cannot reveal tissue-specific gene expression, cellular identity, or gene regulation, which are only attainable at the transcriptional level. Pioneering studies have shown that useful RNA can be extracted from ancient specimens preserved in permafrost and historical skins from extant canids, but no attempts have been made so far on extinct species. We extract, sequence, and analyze historical RNA from muscle and skin tissue of a ∼130-year-old Tasmanian tiger (Thylacinus cynocephalus) preserved in desiccation at room temperature in a museum collection. The transcriptional profiles closely resemble those of extant species, revealing specific anatomical features such as slow muscle fibers or blood infiltration. Metatranscriptomic analysis, RNA damage, tissue-specific RNA profiles, and expression hotspots genome-wide further confirm the thylacine origin of the sequences. RNA sequences are used to improve protein-coding and noncoding annotations, evidencing missing exonic loci and the location of ribosomal RNA genes while increasing the number of annotated thylacine microRNAs from 62 to 325. We discover a thylacine-specific microRNA isoform that could not have been confirmed without RNA evidence. Finally, we detect traces of RNA viruses, suggesting the possibility of profiling viral evolution. Our results represent the first successful attempt to obtain transcriptional profiles from an extinct animal species, providing thought-to-be-lost information on gene expression dynamics. These findings hold promising implications for the study of RNA molecules across the vast collections of natural history museums and from well-preserved permafrost remains.

Improving the annotation of the cattle genome by annotating transcription start sites in a diverse set of tissues and populations using Cap Analysis Gene Expression sequencing.

Understanding the genomic control of tissue-specific gene expression and regulation can help to inform the application of genomic technologies in farm animal breeding programs. The fine mapping of promoters [transcription start sites (TSS)] and enhancers (divergent amplifying segments of the genome local to TSS) in different populations of cattle across a wide diversity of tissues provides information to locate and understand the genomic drivers of breed- and tissue-specific characteristics. To this aim, we used Cap Analysis Gene Expression (CAGE) sequencing, of 24 different tissues from 3 populations of cattle, to define TSS and their coexpressed short-range enhancers (<1 kb) in the ARS-UCD1.2_Btau5.0.1Y reference genome (1000bulls run9) and analyzed tissue and population specificity of expressed promoters. We identified 51,295 TSS and 2,328 TSS-Enhancer regions shared across the 3 populations (dairy, beef-dairy cross, and Canadian Kinsella composite cattle from 2 individuals, 1 of each sex, per population). Cross-species comparative analysis of CAGE data from 7 other species, including sheep, revealed a set of TSS and TSS-Enhancers that were specific to cattle. The CAGE data set will be combined with other transcriptomic information for the same tissues to create a new high-resolution map of transcript diversity across tissues and populations in cattle for the BovReg project. Here we provide the CAGE data set and annotation tracks for TSS and TSS-Enhancers in the cattle genome. This new annotation information will improve our understanding of the drivers of gene expression and regulation in cattle and help to inform the application of genomic technologies in breeding programs.

Modulation of insulin signaling pathway genes by ozone inhalation and the role of glucocorticoids: A multi-tissue analysis

Air pollution is associated with increased risk of metabolic diseases including type 2 diabetes, of which dysregulation of the insulin-signaling pathway is a feature. While studies suggest pollutant exposure alters insulin signaling in certain tissues, there is a lack of comparison across multiple tissues needed for a holistic assessment of metabolic effects, and underlying mechanisms remain unclear. Air pollution increases plasma levels of glucocorticoids, systemic regulators of metabolic function. The objectives of this study were to 1) determine effects of ozone on insulin-signaling genes in major metabolic tissues, and 2) elucidate the role of glucocorticoids. Male Fischer-344 rats were treated with metyrapone, a glucocorticoid synthesis inhibitor, and exposed to 0.8 ppm ozone or clean air for 4 h, with tissue collected immediately or 24 h post exposure. Ozone inhalation resulted in distinct mRNA profiles in the liver, brown adipose, white adipose and skeletal muscle tissues, including effects on insulin-signaling cascade genes (Pik3r1, Irs1, Irs2) and targets involved in glucose metabolism (Hk2, Pgk1, Slc2a1), cell survival (Bcl2l1), and genes associated with diabetes and obesity (Serpine1, Retn, Lep). Glucocorticoid-dependent regulation was observed in the liver and brown and white adipose tissues, while effects in skeletal muscle were largely unaffected by metyrapone treatment. Gene expression changes were accompanied by altered phosphorylation states of insulin-signaling proteins (BAD, GSK, IR-β, IRS-1) in the liver. The results show that systemic effects of ozone inhalation include tissue-specific regulation of insulin-signaling pathway genes via both glucocorticoid-dependent and independent mechanisms, providing insight into mechanisms underlying adverse effects of pollutants.

Standardization and Interpretation of RNA-sequencing for Transplantation.

RNA-sequencing (RNA-seq) is a technique to determine the order of nucleotides in an RNA segment. Modern sequencing platforms simultaneously sequence millions of RNA molecules. Advances in bioinformatics have allowed us to collect, store, analyze, and disseminate data from RNA-seq experiments and decipher biological insights from large sequencing datasets. Although bulk RNA-seq has significantly advanced our understanding of tissue-specific gene expression and regulation, recent advances in single-cell RNA-seq have allowed such information to be mapped to individual cells, thus remarkably enhancing our insight into discrete cellular functions within a biospecimen. These different RNA-seq experimental approaches require specialized computational tools. Herein, we will first review the RNA-seq experimental workflow, discuss the common terminologies used in RNA-seq, and suggest approaches for standardization across multiple studies. Next, we will provide an up-to-date appraisal of the applications of bulk RNA-seq and single-cell/nucleus RNA-seq in preclinical and clinical research on kidney transplantation, as well as typical bioinformatic workflows utilized in such analysis. Lastly, we will deliberate on the limitations of this technology in transplantation research and briefly summarize newer technologies that could be combined with RNA-seq to permit more powerful dissections of biological functions. Because each step in RNA-seq workflow has numerous variations and could potentially impact the results, as conscientious citizens of the research community, we must strive to continuously modernize our analytical pipelines and exhaustively report their technical details.

The role of class IIa histone deacetylases in regulating endothelial function.

Vascular endothelial cells (ECs) are monolayer cells located in the inner layer of the blood vessel. Endothelial function is crucial in maintaining local and systemic homeostasis and is precisely regulated by sophisticated signaling pathways and epigenetic regulation. Endothelial dysfunctions are the main factors for the pathophysiological process of cardiovascular and cerebrovascular diseases like atherosclerosis, hypertension, and stroke. In these pathologic processes, histone deacetylases (HDACs) involve in epigenetic regulation by removing acetyl groups from lysine residues of histones and regulating downstream gene expression. Among all HDACs, Class IIa HDACs (HDAC4, 5, 7, 9) contain only an N-terminal regulatory domain, exert limited HDAC activity, and present tissue-specific gene regulation. Here, we discuss and summarize the current understanding of this distinct subfamily of HDACs in endothelial cell functions (such as angiogenesis and immune response) with their molecular underpinnings. Furthermore, we also present new thoughts for further investigation of HDAC inhibitors as a potential treatment in several vascular diseases.

Multi-omics Investigation of Freeze Tolerance in the Amur Sleeper, an Aquatic Ectothermic Vertebrate.

Freeze tolerance, the ability of an organism to survive internal ice formation, is a striking survival strategy employed by some ectotherms living in cold environments. However, the genetic bases of this remarkable adaptation are largely unknown. The Amur sleeper (Perccottus glenii), the only known freeze-tolerant fish species, can overwinter with its entire body frozen in ice. Here, we sequenced the chromosome-level genome of the Amur sleeper and performed comparative genomic, transcriptomic, and metabolomic analyses to investigate its strategies for surviving freezing. Evolutionary analysis suggested that the Amur sleeper diverged from its closest non-cold-hardy relative about 15.07 million years ago and has experienced a high rate of protein evolution. Transcriptomic and metabolomic data identified a coordinated and tissue-specific regulation of genes and metabolites involved in hypometabolism, cellular stress response, and cryoprotectant accumulation involved in freezing and thawing. Several genes show evidence of accelerated protein sequence evolution or family size expansion were found as adaptive responses to freezing-induced stresses. Specifically, genetic changes associated with cytoskeleton stability, cryoprotectant synthesis, transmembrane transport, and neuroprotective adaptations were identified as potentially key innovations that aid in freezing survival. Our work provides valuable resources and opportunities to unveil the molecular adaptations supporting freeze tolerance in ectothermic vertebrates.

Nutritional and tissue-specific regulation of cytochrome P450 CYP711A MAX1 homologues and strigolactone biosynthesis in wheat.

Strigolactones (SLs) are a class of phytohormones regulating branching/tillering, and their biosynthesis has been associated with nutritional signals and plant adaptation to nutrient-limiting conditions. The enzymes in the SL biosynthetic pathway downstream of carlactone are of interest as they are responsible for structural diversity in SLs, particularly cytochrome P450 CYP711A subfamily members, such as MORE AXILLARY GROWTH1 (MAX1) in Arabidopsis. We identified 13 MAX1 homologues in wheat, clustering in four clades and five homoeologous subgroups. The utilization of RNA-sequencing data revealed a distinct expression pattern of MAX1 homologues in above- and below-ground tissues, providing insights into the distinct roles of MAX1 homologues in wheat. In addition, a transcriptional analysis showed that SL biosynthetic genes were systematically regulated by nitrogen supply. Nitrogen limitation led to larger transcriptional changes in the basal nodes than phosphorus limitation, which was consistent with the observed tillering suppression, as wheat showed higher sensitivity to nitrogen. The opposite was observed in roots, with phosphorus limitation leading to stronger induction of most SL biosynthetic genes compared with nitrogen limitation. The observed tissue-specific regulation of SL biosynthetic genes in response to nutritional signals is likely to reflect the dual role of SLs as rhizosphere signals and branching inhibitors.

Tissue-specific regulation of lipid polyester synthesis genes controlling oxygen permeation into Lotus japonicus nodules

Legumes establish endosymbiotic associations with nitrogen-fixing rhizobia, which they host inside root nodules. Here, specific physiological and morphological adaptations, such as the production of oxygen-binding leghemoglobin proteins and the formation of an oxygen diffusion barrier in the nodule periphery, are essential to protect the oxygen-labile bacterial nitrogenase enzyme. The molecular basis of the latter process remains elusive as the identification of required genes is limited by the epistatic effect of nodule organogenesis over nodule infection and rhizobia accommodation. We overcame this by exploring the phenotypic diversity of Lotus japonicus accessions that uncouple nodule organogenesis from nodule infection when inoculated with a subcompatible Rhizobium strain. Using comparative transcriptomics, we identified genes with functions associated with oxygen homeostasis and deposition of lipid polyesters on cell walls to be specifically up-regulated in infected compared to noninfected nodules. As hydrophobic modification of cell walls is pivotal for creating diffusion barriers like the root endodermis, we focused on two Fatty acyl-CoA Reductase genes that were specifically activated in the root and/or in the nodule endodermis. Mutant lines in a Fatty acyl-CoA Reductase gene expressed exclusively in the nodule endodermis had decreased deposition of polyesters on this cell layer and increased nodule permeability compared to wild-type plants. Oxygen concentrations were significantly increased in the inner cortex of mutant nodules, which correlated with reduced nitrogenase activity, and impaired shoot growth. These results provide the first genetic evidence for the formation of the nodule oxygen diffusion barrier, a key adaptation enabling nitrogen fixation in legume nodules.

Evidence for Light and Tissue Specific Regulation of Genes Involved in Fructan Metabolism in Agave tequilana.

Plant Glycoside Hydrolase Family 32 (PGHF32) contains the fructosyltransferases and fructan exohydrolase enzymes responsible for fructan metabolism, in addition to closely related vacuolar and cell wall acid invertases. Agave species produce complex and dynamic fructan molecules (agavins) requiring 4 different fructosyltransferase activities (1-SST, 1-FFT, 6G-FFT and 6-SFT) for their synthesis. Combined analysis of RNAseq and genome data for A. tequilana led to the characterization of the genes encoding 3 fructosyltransferases for this species and support the hypothesis that no separate 6-SFT type enzyme exists in A. tequilana, suggesting that at least one of the fructosyltransferases identified may have multiple enzymatic activities. Structures for PGHF32 genes varied for A. tequilana and between other plant species but were conserved for different enzyme types within a species. The observed patterns are consistent with the formation of distinct gene structures by intron loss. Promoter analysis of the PGHF32 genes identified abundant putative regulatory motifs for light regulation and tissue-specific expression, and these regulatory mechanisms were confirmed experimentally for leaf tissue. Motifs for phytohormone response, carbohydrate metabolism and dehydration responses were also uncovered. Based on the regulatory motifs, full-length cDNAs for MYB, GATA, DOF and GBF transcription factors were identified and their phylogenetic distribution determined by comparison with other plant species. In silico expression analysis for the selected transcription factors revealed both tissue-specific and developmental patterns of expression, allowing candidates to be identified for detailed analysis of the regulation of fructan metabolism in A. tequilana at the molecular level.

3D Genome Organization as an Epigenetic Determinant of Transcription Regulation in T Cells.

In the heart of innate and adaptive immunity lies the proper spatiotemporal development of several immune cell lineages. Multiple studies have highlighted the necessity of epigenetic and transcriptional regulation in cell lineage specification. This mode of regulation is mediated by transcription factors and chromatin remodelers, controlling developmentally essential gene sets. The core of transcription and epigenetic regulation is formulated by different epigenetic modifications determining gene expression. Apart from “classic” epigenetic modifications, 3D chromatin architecture is also purported to exert fundamental roles in gene regulation. Chromatin conformation both facilitates cell-specific factor binding at specified regions and is in turn modified as such, acting synergistically. The interplay between global and tissue-specific protein factors dictates the epigenetic landscape of T and innate lymphoid cell (ILC) lineages. The expression of global genome organizers such as CTCF, YY1, and the cohesin complexes, closely cooperate with tissue-specific factors to exert cell type-specific gene regulation. Special AT-rich binding protein 1 (SATB1) is an important tissue-specific genome organizer and regulator controlling both long- and short-range chromatin interactions. Recent indications point to SATB1’s cooperation with the aforementioned factors, linking global to tissue-specific gene regulation. Changes in 3D genome organization are of vital importance for proper cell development and function, while disruption of this mechanism can lead to severe immuno-developmental defects. Newly emerging data have inextricably linked chromatin architecture deregulation to tissue-specific pathophysiological phenotypes. The combination of these findings may shed light on the mechanisms behind pathological conditions.

Immuno-Endocrinology of COVID-19: The Key Role of Sex Hormones.

Epidemiological evidence shows clear gender disparities in the Coronavirus 2019 Disease (COVID-19) severity and fatality. This may reflect the contribution of gender-related factors, such as sex hormones, to COVID-19 pathogenesis. However, the mechanism linking gender disparities to COVID-19 severity is still poorly understood. In this review, we will pinpoint several elements involved in COVID-19 pathogenesis that are regulated by the two main sex hormones, estrogen and androgen. These include tissue specific gene regulation of SARS-CoV2 entry factors, innate and adaptive immune responses to infection, immunometabolism, and susceptibility to tissue injury by cytopathic effect or hyper-inflammatory response. We will discuss the mechanistic link between sex hormone regulation of COVID-19 pathogenetic factors and disease severity. Finally, we will summarize current evidence from clinical studies and trials targeting sex hormones and their signalling in COVID-19. A better understanding of the role of sex hormones in COVID-19 may identify targets for therapeutic intervention and allow optimization of treatment outcomes towards gender-based personalised medicine.

Abstract 12437: Network-Based Identification of Tissue-Specific Regulators and Drug Repurposing Candidates for Coronary Artery Disease

Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent genomic studies in human populations and mouse models have revealed numerous novel genetic loci that may affect pathways and gene networks in CAD relevant tissues. In this study, we aim to use network-based systems biology approaches to identify regulators and drug repurposing candidates based on CAD gene networks. Through integration of multiomics datasets encompassing genetic association studies, transcriptomic profiles, and tissue-specific gene regulation from human and mouse populations, we previously modeled gene networks in vascular and liver tissues that are affected by CAD genetic loci in both species. Based on the shared CAD gene networks between human and mouse, we predicted candidate key regulatory genes and further examined multiple single-cell RNA sequencing datasets of vascular and liver tissues to pinpoint the specific cell types and molecular pathways in each tissue through which the top predicted regulators function. We further used network-based drug repositioning approaches to predict drugs targeting the CAD networks in each tissue, revealing both currently used medications and potential novel therapeutic agents. The cross-species networks, predicted key regulatory genes, their cellular and tissue context, and the network-based drug repositioning analyses offer tissue and cell-type specific targets and potential existing drugs that can be repurposed for CAD treatment.

Corrigendum: Ancient microRNA profiles of 14,300-yr-old canid samples confirm taxonomic origin and provide glimpses into tissue-specific gene regulation from the Pleistocene.

Corrigendum: Ancient microRNA profiles of 14,300-yr-old canid samples confirm taxonomic origin and provide glimpses into tissue-specific gene regulation from the Pleistocene.

FIVEx: an interactive eQTL browser across public datasets.

Expression quantitative trait loci (eQTLs) characterize the associations between genetic variation and gene expression to provide insights into tissue-specific gene regulation. Interactive visualization of tissue-specific eQTLs or splice QTLs (sQTLs) can facilitate our understanding of functional variants relevant to disease-related traits. However, combining the multi-dimensional nature of eQTLs/sQTLs into a concise and informative visualization is challenging. Existing QTL visualization tools provide useful ways to summarize the unprecedented scale of transcriptomic data but are not necessarily tailored to answer questions about the functional interpretations of trait-associated variants or other variants of interest. We developed FIVEx, an interactive eQTL/sQTL browser with an intuitive interface tailored to the functional interpretation of associated variants. It features the ability to navigate seamlessly between different data views while providing relevant tissue- and locus-specific information to offer users a better understanding of population-scale multi-tissue transcriptomic profiles. Our implementation of the FIVEx browser on the EBI eQTL catalogue, encompassing 16 publicly available RNA-seq studies, provides important insights for understanding potential tissue-specific regulatory mechanisms underlying trait-associated signals. A FIVEx instance visualizing EBI eQTL catalogue data can be found at https://fivex.sph.umich.edu. Its source code is open source under an MIT license at https://github.com/statgen/fivex. Supplementary data are available at Bioinformatics online.

A graph convolutional neural network for gene expression data analysis with multiple gene networks.

Spectral graph convolutional neural networks (GCN) are proposed to incorporate important information contained in graphs such as gene networks. In a standard spectral GCN, there is only one gene network to describe the relationships among genes. However, for genomic applications, due to condition- or tissue-specific gene function and regulation, multiple gene networks may be available; it is unclear how to apply GCNs to disease classification with multiple networks. Besides, which gene networks may provide more effective prior information for a given learning task is unknown a priori and is not straightforward to discover in many cases. A deep multiple graph convolutional neural network is therefore developed here to meet the challenge. The new approach not only computes a feature of a gene as the weighted average of those of itself and its neighbors through spectral GCNs, but also extracts features from gene-specific expression (or other feature) profiles via a feed-forward neural networks (FNN). We also provide two measures, the importance of a given gene and the relative importance score of each gene network, for the genes' and gene networks' contributions, respectively, to the learning task. To evaluate the new method, we conduct real data analyses using several breast cancer and diffuse large B-cell lymphoma datasets and incorporating multiple gene networks obtained from "GIANT 2.0" Compared with the standard FNN, GCN, and random forest, the new method not only yields high classification accuracy but also prioritizes the most important genes confirmed to be highly associated with cancer, strongly suggesting the usefulness of the new method in incorporating multiple gene networks.