Multi-omics enrichment analysis using the GeneTrail2 web service

Whole-genome resequencing reveals diversity and selective signals in Longlin goat

The Longlin goat is one of the most valuable livestock species in Guangxi Autonomous Region of China, but its genomic diversity and selective signals are not clearly elucidated. Here we compared 20 genomes of Longlin goat to 66 genomes of other seven goat breeds worldwide to analyze patterns of Longlin goat genetic variation. We found the lowest linkage disequilibrium at the large distances between SNPs associated with the highest effective population size in the recent generations ago in Longlin goat. The eight goat breeds could be divided into Euro-African and East Asian goat population. Interestingly, like East Asian taurine, the same two migration phases might have occurred in the history of East Asian goat. More importantly, we identified selective signals implicated in immune resistance to disease, especially for skin disease, in Longlin goat. Our findings will not only help understand the evolutionary history and breed characteristic but can provide valuable resources for conservation of germplasm resources and implementation of crossbreeding programs.

The mRNA Binding Proteome of Proliferating and Differentiated Muscle Cells

Muscle formation is a coordinated process driven by extensive gene expression changes where single cells fuse together to form multinucleated muscle fibers. Newly synthesized mRNAs are then regulated by RNA binding proteins (RBPs), affecting post-transcriptional transcript metabolism. Here, we determined how large-scale gene expression changes affect the catalog of RBPs by studying proliferating and differentiated muscle cells in healthy and dystrophic conditions. Transcriptomic analysis showed that the expression of more than 7000 genes was affected during myogenesis. We identified 769 RBPs, of which 294 were muscle-specific and 49 were uniquely shared with cardiomyocytes. A subset of 32 RBPs (half of which were muscle-specific) was found to be preferentially associated with target mRNAs in either myoblasts (MBs) or myotubes (MTs). A large proportion of catalytic proteins were bound to mRNAs even though they lack classical RNA binding domains. Finally, we showed how the identification of cell-specific RBPs enabled the identification of biomarkers that can separate healthy individuals from dystrophic patients. Our data show how interactome data can shed light on new basic RNA biology as well as provide cell-specific data that can be used for diagnostic purposes.

GeneTrail 3: advanced high-throughput enrichment analysis

We present GeneTrail 3, a major extension of our web service GeneTrail that offers rich functionality for the identification, analysis, and visualization of deregulated biological processes. Our web service provides a comprehensive collection of biological processes and signaling pathways for 12 model organisms that can be analyzed with a powerful framework for enrichment and network analysis of transcriptomic, miRNomic, proteomic, and genomic data sets. Moreover, GeneTrail offers novel workflows for the analysis of epigenetic marks, time series experiments, and single cell data. We demonstrate the capabilities of our web service in two case-studies, which highlight that GeneTrail is well equipped for uncovering complex molecular mechanisms. GeneTrail is freely accessible at: http://genetrail.bioinf.uni-sb.de.

miEAA 2.0: integrating multi-species microRNA enrichment analysis and workflow management systems

Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from ten frequently investigated organisms. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miRBase miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualizations such as heatmaps and running sum curves with background distributions. We demonstrate the new features with case studies for human kidney cancer, a biomarker study on Parkinson’s disease from the PPMI cohort, and a mouse model for breast cancer. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.

Targeting the ubiquitin-proteasome system in a pancreatic cancer subtype with hyperactive MYC

The myelocytomatosis oncogene (MYC) is an important driver in a subtype of pancreatic ductal adenocarcinoma (PDAC). However, MYC remains a challenging therapeutic target; therefore, identifying druggable synthetic lethal interactions in MYC‐active PDAC may lead to novel precise therapies. First, to identify networks with hyperactive MYC, we profiled transcriptomes of established human cell lines, murine primary PDAC cell lines, and accessed publicly available repositories to analyze transcriptomes of primary human PDAC. Networks active in MYC‐hyperactive subtypes were analyzed by gene set enrichment analysis. Next, we performed an unbiased pharmacological screen to define MYC‐associated vulnerabilities. Hits were validated by analysis of drug response repositories and genetic gain‐ and loss‐of‐function experiments. In these experiments, we discovered that the proteasome inhibitor bortezomib triggers a MYC‐associated vulnerability. In addition, by integrating publicly available data, we found the unfolded protein response as a signature connected to MYC. Furthermore, increased sensitivity of MYC‐hyperactive PDACs to bortezomib was validated in genetically modified PDAC cells. In sum, we provide evidence that perturbing the ubiquitin–proteasome system (UPS) might be an option to target MYC‐hyperactive PDAC cells. Our data provide the rationale to further develop precise targeting of the UPS as a subtype‐specific therapeutic approach.

Sex-Dependent Molecular Mechanisms of Lipotoxic Injury in Brain Microvasculature: Implications for Dementia

Cardiovascular risk factors and biologic sex play a role in vascular dementia which is characterized by progressive reduction in cognitive function and memory. Yet, we lack understanding about the role sex plays in the molecular mechanisms whereby lipid stress contributes to cognitive decline. Five-week-old low-density lipoprotein deficient (LDL-R -/-) male and female mice and C57BL/6J wild types (WT) were fed a control or Western Diet for 8 weeks. Differential expression of protein coding and non-protein coding genes (DEG) were determined in laser captured hippocampal microvessels using genome-wide microarray, followed by bioinformatic analysis of gene networks, pathways, transcription factors and sex/gender-based analysis (SGBA). Cognitive function was assessed by Y-maze. Bioinformatic analysis revealed more DEGs in females (2412) compared to males (1972). Hierarchical clusters revealed distinctly different sex-specific gene expression profiles irrespective of diet and genotype. There were also fewer and different biologic responses in males compared to females, as well as different cellular pathways and gene networks (favoring greater neuroprotection in females), together with sex-specific transcription factors and non-protein coding RNAs. Hyperlipidemic stress also resulted in less severe cognitive dysfunction in females. This sex-specific pattern of differential hippocampal microvascular RNA expression might provide therapeutic targets for dementia in males and females.

Double hit viral parasitism, polymicrobial CNS residency and perturbed proteostasis in Alzheimer's disease: A data driven, in silico analysis of gene expression data

The aim of this study was to determine the interaction of peripheral immunity vs. the CNS in the setting of AD pathogenesis at the transcriptomic level in a data driven manner. For this purpose, publicly available gene expression data from the GEO Datasets repository. We performed differential gene expression and functional enrichment analyses were performed on the five retrieved studies: (a) three hippocampal cortex (HC) studies (b) one study of peripheral blood mononuclear cells (PBMC) and (c) one involving neurofibrillary tangle - containing neurons of the entorhinal cortex (NFT EC). Subsequently, BLAST was used to determine protein conservation between human proteins vs. microbial, whereas putative protein / oligopeptide antigenicity were determined via RANKPep. Gene ontology and pathway analyses revealed significantly enriched viral parasitism pathways in both PBMC and NFT - EC datasets, mediated by ribosomal protein families and epigenetic regulators. Among these, a salient viral pathway referred to Influenza A infection. NFT - EC annotations included leukocyte chemotaxis and immune response pathways. All datasets were significantly enriched for infectious pathways, as well as pathways involved in impaired proteostasis and non - phagocytic cell phagosomal cascades. In conclusion, our in silico analysis outlined an ad hoc model of AD pathophysiology in which double hit (PBMC and NFT-EC) viral parasitism is mediated by eukaryotic translational hijacking, and may be further implicated by impaired immune responses. Overall, our results overlap with the antimicrobial protection hypothesis of AD pathogenesis and support the notion of a pathogen - driven etiology.

Epigenetic regulation of apoptosis via the PARK7 interactome in peripheral blood mononuclear cells donated by tuberculosis patients vs. healthy controls and the response to treatment: A systems biology approach

AIMS

The aims of our study were to determine for the first time differentially expressed genes (DEGs) and enriched molecular pathways involving the PARK7 interactome in PBMCs donated from tuberculosis patients.

METHODS

Data on a previously reconstructed PARK7 interactome (Vavougios et al., 2017) from datasets GDS4966 (Case-Control) and GDS4781 (Treatment Series) were retrieved from the Gene Expression Omnibus (GEO) repository. Gene Enrichment analysis was performed via the STRING algorithm and the GeneTrail2 software.

RESULTS

17 and 22 PARK7 interactores were determined as DEGs in the active TB vs HD and Treatment Series subset analyses, correspondingly, associated with significantly enriched pathways (FDR <0.05) involving p53 and PTEN mediated, stress responsive apoptosis regulation pathways. The treatment subset was characterized by the emergence of an additional layer of transcriptional regulation mediated by polycomb proteins among others, as well as TLR-mediated and cytokine survival signaling. Finally, the enrichment of a Parkinson's disease signature including PARK7 interactors was determined by its differential regulation both in the exploratory analyses (FDR = 0.024), as well as the confirmatory analyses (FDR = 1.81e^-243).

CONCLUSIONS

Our in silico analysis revealed for the first time the role of PARK7's interactome in regulating the epigenetics of the PBMC lifecycle and Mtb symbiosis.

SUMO pathway inhibition targets an aggressive pancreatic cancer subtype

OBJECTIVE

Pancreatic ductal adenocarcinoma (PDAC) still carries a dismal prognosis with an overall 5-year survival rate of 9%. Conventional combination chemotherapies are a clear advance in the treatment of PDAC; however, subtypes of the disease exist, which exhibit extensive resistance to such therapies. Genomic MYC amplifications represent a distinct subset of PDAC with an aggressive tumour biology. It is clear that hyperactivation of MYC generates dependencies that can be exploited therapeutically. The aim of the study was to find and to target MYC-associated dependencies.

DESIGN

We analysed human PDAC gene expression datasets. Results were corroborated by the analysis of the small ubiquitin-like modifier (SUMO) pathway in a large PDAC cohort using immunohistochemistry. A SUMO inhibitor was used and characterised using human and murine two-dimensional, organoid and in vivo models of PDAC.

RESULTS

We observed that MYC is connected to the SUMOylation machinery in PDAC. Components of the SUMO pathway characterise a PDAC subtype with a dismal prognosis and we provide evidence that hyperactivation of MYC is connected to an increased sensitivity to pharmacological SUMO inhibition.

CONCLUSION

SUMO inhibitor-based therapies should be further developed for an aggressive PDAC subtype.

A family-based genome-wide association study of recurrent aphthous stomatitis

OBJECTIVES

The aetiology of recurrent aphthous stomatitis (RAS) remains unknown. Individuals may share features of genetic susceptibility, and there may also be a hereditary component. The aim was to identify patterns of association and segregation for genetic variants and to identify the genes and signalling pathways that determine the risk of developing RAS, through a family-based genome-wide association study (GWAS).

SUBJECTS AND METHODS

DNA was extracted from buccal swabs of 91 individuals in 16 families and analysed in an Illumina core exome single nucleotide polymorphism (SNP) array. A family-based association test (dFAM) was used to derive SNP association values across all chromosomes.

RESULTS

None of the final 288,452 SNPs reached the genome-wide significant threshold of 5 × 10^-8 . The most significant pathways were the Ras and PI3K-Akt signalling pathways, pathways in cancer, circadian entrainment and the Rap 1 signalling pathway.

CONCLUSIONS

This confirms that RAS is not monogenic but results as a consequence of interactions between multiple host genes and possibly also environmental factors. The present approach provides novel insights into the mechanisms underlying RAS and raises the possibility of identifying individuals at risk of acquiring this condition.

ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification

Motivation

Breast cancer is the second leading cause of cancer death among women. Tumors, even of the same histopathological subtype, exhibit a high genotypic diversity that impedes therapy stratification and that hence must be accounted for in the treatment decision-making process.

Results

Here, we present ClinOmicsTrail^bc, a comprehensive visual analytics tool for breast cancer decision support that provides a holistic assessment of standard-of-care targeted drugs, candidates for drug repositioning and immunotherapeutic approaches. To this end, our tool analyzes and visualizes clinical markers and (epi-)genomics and transcriptomics datasets to identify and evaluate the tumor’s main driver mutations, the tumor mutational burden, activity patterns of core cancer-relevant pathways, drug-specific biomarkers, the status of molecular drug targets and pharmacogenomic influences. In order to demonstrate ClinOmicsTrail^bc’s rich functionality, we present three case studies highlighting various ways in which ClinOmicsTrail^bc can support breast cancer precision medicine. ClinOmicsTrail^bc is a powerful integrated visual analytics tool for breast cancer research in general and for therapy stratification in particular, assisting oncologists to find the best possible treatment options for their breast cancer patients based on actionable, evidence-based results.

Availability and implementation

ClinOmicsTrail^bc can be freely accessed at https://clinomicstrail.bioinf.uni-sb.de.

Supplementary information

Supplementary data are available at Bioinformatics online.

Lipotoxic Injury Differentially Regulates Brain Microvascular Gene Expression in Male Mice

The Western diet (WD) and hyperlipidemia are risk factors for vascular disease, dementia, and cognitive impairment. However, the molecular mechanisms are poorly understood. This pilot study investigated the genomic pathways by which the WD and hyperlipidemia regulate gene expression in brain microvessels. Five-week-old C57BL/6J wild type (WT) control and low-density lipoprotein receptor deficient (LDL-R-/-) male mice were fed the WD for eight weeks. Differential gene expression, gene networks and pathways, transcription factors, and non-protein coding RNAs were evaluated by a genome-wide microarray and bioinformatics analysis of laser-captured hippocampal microvessels. The WD resulted in the differential expression of 1972 genes. Much of the differentially expressed gene (DEG) was attributable to the differential regulation of cell signaling proteins and their transcription factors, approximately 4% was attributable to the differential expression of miRNAs, and 10% was due to other non-protein coding RNAs, primarily long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs) not previously described to be modified by the WD. Lipotoxic injury resulted in complex and multilevel molecular regulation of the hippocampal microvasculature involving transcriptional and post-transcriptional regulation and may provide a molecular basis for a better understanding of hyperlipidemia-associated dementia risk.

Induction of the Endoplasmic-Reticulum-Stress Response: MicroRNA-34a Targeting of the IRE1α-Branch

Neurodegenerative disorders such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) are characterized by the accumulation of misfolded proteins in the endoplasmic reticulum (ER) and the unfolded protein response (UPR). Modulating the UPR is one of the major challenges to counteract the development of neurodegenerative disorders and other diseases with affected UPR. Here, we show that miR-34a-5p directly targets the IRE1α branch of the UPR, including the genes BIP, IRE1α, and XBP1. Upon induction of ER stress in neuronal cells, miR-34a-5p overexpression impacts the resulting UPR via a significant reduction in IRE1α and XBP1s that in turn leads to decreased viability, increased cytotoxicity and caspase activity. The possibility to modify the UPR signaling pathway by a single miRNA that targets central genes of the IRE1α branch offers new perspectives for future therapeutic approaches against neurodegeneration.

Epigenetic Regulation of Alternative mRNA Splicing in Dilated Cardiomyopathy

In recent years, the genetic architecture of dilated cardiomyopathy (DCM) has been more thoroughly elucidated. However, there is still insufficient knowledge on the modifiers and regulatory principles that lead to the failure of myocardial function. The current study investigates the association of epigenome-wide DNA methylation and alternative splicing, both of which are important regulatory principles in DCM. We analyzed screening and replication cohorts of cases and controls and identified distinct transcriptomic patterns in the myocardium that differ significantly, and we identified a strong association of intronic DNA methylation and flanking exons usage (p < 2 × 10^-16). By combining differential exon usage (DEU) and differential methylation regions (DMR), we found a significant change of regulation in important sarcomeric and other DCM-associated pathways. Interestingly, inverse regulation of Titin antisense non-coding RNA transcript splicing and DNA methylation of a locus reciprocal to TTN substantiate these findings and indicate an additional role for non-protein-coding transcripts. In summary, this study highlights for the first time the close interrelationship between genetic imprinting by DNA methylation and the transport of this epigenetic information towards the dynamic mRNA splicing landscape. This expands our knowledge of the genome-environment interaction in DCM besides simple gene expression regulation.

Machine learning-based analysis of multi-omics data on the cloud for investigating gene regulations

Gene expressions are subtly regulated by quantifiable measures of genetic molecules such as interaction with other genes, methylation, mutations, transcription factor and histone modifications. Integrative analysis of multi-omics data can help scientists understand the condition or patient-specific gene regulation mechanisms. However, analysis of multi-omics data is challenging since it requires not only the analysis of multiple omics data sets but also mining complex relations among different genetic molecules by using state-of-the-art machine learning methods. In addition, analysis of multi-omics data needs quite large computing infrastructure. Moreover, interpretation of the analysis results requires collaboration among many scientists, often requiring reperforming analysis from different perspectives. Many of the aforementioned technical issues can be nicely handled when machine learning tools are deployed on the cloud. In this survey article, we first survey machine learning methods that can be used for gene regulation study, and we categorize them according to five different goals: gene regulatory subnetwork discovery, disease subtype analysis, survival analysis, clinical prediction and visualization. We also summarize the methods in terms of multi-omics input types. Then, we explain why the cloud is potentially a good solution for the analysis of multi-omics data, followed by a survey of two state-of-the-art cloud systems, Galaxy and BioVLAB. Finally, we discuss important issues when the cloud is used for the analysis of multi-omics data for the gene regulation study.

Characterization of the human GnRH neuron developmental transcriptome using a GNRH1-TdTomato reporter line in human pluripotent stem cells

Gonadotropin-releasing hormone (GnRH) neurons provide a fundamental signal for the onset of puberty and subsequent reproductive functions by secretion of gonadotropin-releasing hormone. Their disrupted development or function leads to congenital hypogonadotropic hypogonadism (CHH). To model the development of human GnRH neurons, we generated a stable GNRH1-TdTomato reporter cell line in human pluripotent stem cells (hPSCs) using CRISPR-Cas9 genome editing. RNA-sequencing of the reporter clone, differentiated into GnRH neurons by dual SMAD inhibition and FGF8 treatment, revealed 6461 differentially expressed genes between progenitors and GnRH neurons. Expression of the transcription factor ISL1, one of the top 50 most upregulated genes in the TdTomato-expressing GnRH neurons, was confirmed in 10.5 gestational week-old human fetal GnRH neurons. Among the differentially expressed genes, we detected 15 genes that are implicated in CHH and several genes that are implicated in human puberty timing. Finally, FGF8 treatment in the neuronal progenitor pool led to upregulation of 37 genes expressed both in progenitors and in TdTomato-expressing GnRH neurons, which suggests upstream regulation of these genes by FGF8 signaling during GnRH neuron differentiation. These results illustrate how hPSC-derived human GnRH neuron transcriptomic analysis can be utilized to dissect signaling pathways and gene regulatory networks involved in human GnRH neuron development.This article has an associated First Person interview with the first author of the paper.

Genomic evidence for two phylogenetic species and long-term population bottlenecks in red pandas

The red panda (Ailurus fulgens), an endangered Himalaya-endemic mammal, has been classified as two subspecies or even two species - the Himalayan red panda (A. fulgens) and the Chinese red panda (Ailurus styani) - based on differences in morphology and biogeography. However, this classification has remained controversial largely due to lack of genetic evidence, directly impairing scientific conservation management. Data from 65 whole genomes, 49 Y-chromosomes, and 49 mitochondrial genomes provide the first comprehensive genetic evidence for species divergence in red pandas, demonstrating substantial inter-species genetic divergence for all three markers and correcting species-distribution boundaries. Combined with morphological evidence, these data thus clearly define two phylogenetic species in red pandas. We also demonstrate different demographic trajectories in the two species: A. styani has experienced two population bottlenecks and one large population expansion over time, whereas A. fulgens has experienced three bottlenecks and one very small expansion, resulting in very low genetic diversity, high linkage disequilibrium, and high genetic load.

Circulatory miRNA biomarkers of metabolic syndrome

AIMS

Circulatory microRNAs (c-miRNAs) exert important roles in the molecular dysregulation of cardio-metabolic diseases. However, little is known whether dysregulated miRNA expression occurs when risk factors are elevated, as in the metabolic syndrome (MetS). This study quantified c-miRNA expression in individuals with MetS compared to healthy, further examining the relationship of gene pathways with the underlying pathogenesis.

METHODS

Expression of 26 miRNAs was quantified in plasma from 40 women (20 healthy and 20 MetS) and 39 men (20 healthy and 19 MetS) by qPCR. In silico analysis was performed to investigate biological effects of the dysregulated miRNAs. Dysregulated miRNA expression was further validated in an independent cohort of 20 women (10 healthy and 10 MetS).

RESULTS

Regression model adjusted for age and sex identified miR-15a-5p, miR-17-5p, miR-370-3p and miR-375 as important predictors of MetS presence. Analysis of predictive miRNAs in the validation cohort strengthened the relationship with miR-15a-5p and miR-17-5p expression. These miRNAs share genes involved in the regulation of metabolic pathways including insulin, wnt, fatty acid metabolism and AMPK.

CONCLUSIONS

miR-15a-5p and miR-17-5p were identified as predictive biomarkers of MetS, irrespective of sexes, further demonstrating the relationship of c-miRNAs to known pathways of metabolic disturbances present in cardio-metabolic diseases.

Interactome networks between the human respiratory syncytial virus (HRSV), the human metapneumovirus (ΗMPV), and their host: In silico investigation and comparative functional enrichment analysis

BACKGROUND AND OBJECTIVES

Human respiratory syncytial virus (HRSV) and human metapneumovirus (HMPV) are leading causes of upper and lower respiratory tract infections in non-immunocompetent subjects, yet the mechanisms by which they induce their pathogenicity differ significantly and remain elusive. In this study we aimed at identifying the gene interaction networks between the HRSV, HMPV respiratory pathogens and their host along with the different cell-signaling pathways associated with the above interactomes.

MATERIALS AND METHODS

The Viruses STRING database (http://viruses.string-db.org/) was used for the identification of the host-viruses interaction networks. The two lists of the predicted functional partners were entered in the FunRich tool (http://www.funrich.org) for the construction of the Venn diagram and the comparative Funcional Enrichment Analysis (FEA) with respect to biological pathways. The sets of the common and unique human genes identified in the two networks were also analyzed. The computational predictions regarding the shared human genes in the host-HRSV and the host-HMPV interactomes were further evaluated via the analysis of the GSE111732 dataset. miRNA transcriptomics data were mapped to gene targets using the miRNomics pipeline of the GeneTrail2 database (https://genetrail2.bioinf.uni-sb.de/).

RESULTS

Eleven out of twenty predicted human genes were common in the two interactomes (TLR4, SOCS3, SFXN1, AKT1, SFXN3, LY96, SFXN2, SOCS7, CISH, SOCS6, SOCS1). FEA of these common genes identified the kit receptor and the GH receptor signaling pathways as the most significantly enriched annotations. The remaining nine genes of the host-HRSV and the host-HMPV interaction networks were the IFIH1, DDX58, NCL, IRF3, STAT2, HSPA4, CD209, KLF6, CHKA and the MYD88, SOCS4, SOCS2, SOCS5 AKT2, AKT3, SFXN4, SFXN5 and TLR3 respectively. Distinct cell-signaling pathways were enriched per interactome. The comparative FEA highlighted the association of the host-HRSV functional partners with the negative regulation of RIG-I/MDA5 signaling. The analysis with respect to miRNAs mapping to gene targets of the GSE111732 dataset indicated that nine out of the eleven common host genes are either enriched or depleted in the sample sets (HRSV or HMPV infected) as compared with the reference set (non-infected), although with no significant scores.

CONCLUSIONS

We have identified both shared and unique host genes as members of the HRSV and HMPV interaction networks. The disparate human genes likely contribute to distinct responses in airway epithelial cells.

miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database

Since the initial release of miRPathDB, tremendous progress has been made in the field of microRNA (miRNA) research. New miRNA reference databases have emerged, a vast amount of new miRNA candidates has been discovered and the number of experimentally validated target genes has increased considerably. Hence, the demand for a major upgrade of miRPathDB, including extended analysis functionality and intuitive visualizations of query results has emerged. Here, we present the novel release 2.0 of the miRNA Pathway Dictionary Database (miRPathDB) that is freely accessible at https://mpd.bioinf.uni-sb.de/. miRPathDB 2.0 comes with a ten-fold increase of pre-processed data. In total, the updated database provides putative associations between 27 452 (candidate) miRNAs, 28 352 targets and 16 833 pathways for Homo sapiens, as well as interactions of 1978 miRNAs, 24 898 targets and 6511 functional categories for Mus musculus. Additionally, we analyzed publications citing miRPathDB to identify common use-cases and further extensions. Based on this evaluation, we added new functionality for interactive visualizations and down-stream analyses of bulk queries. In summary, the updated version of miRPathDB, with its new custom-tailored features, is one of the most comprehensive and advanced resources for miRNAs and their target pathways.

TCTEX1D1 is a genetic modifier of disease progression in Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is caused by pathogenic variants in the DMD gene leading to the lack of dystrophin. Variability in the disease course suggests that other factors influence disease progression. With this study we aimed to identify genetic factors that may account for some of the variability in the clinical presentation. We compared whole-exome sequencing (WES) data in 27 DMD patients with extreme phenotypes to identify candidate variants that could affect disease progression. Validation of the candidate SNPs was performed in two independent cohorts including 301 (BIO-NMD cohort) and 109 (CINRG cohort of European ancestry) DMD patients, respectively. Variants in the Tctex1 domain containing 1 (TCTEX1D1) gene on chromosome 1 were associated with age of ambulation loss. The minor alleles of two independent variants, known to affect TCTEX1D1 coding sequence and induce skipping of its exon 4, were associated with earlier loss of ambulation. Our data show that disease progression of DMD is affected by a new locus on chromosome 1 and demonstrate the possibility to identify genetic modifiers in rare diseases by studying WES data in patients with extreme phenotypes followed by multiple layers of validation.

Evolutionary Basis of High-Frequency Hearing in the Cochleae of Echolocators Revealed by Comparative Genomics

High-frequency hearing is important for the survival of both echolocating bats and whales, but our understanding of its genetic basis is scattered and segmented. In this study, we combined RNA-Seq and comparative genomic analyses to obtain insights into the comprehensive gene expression profile of the cochlea and the adaptive evolution of hearing-related genes. A total of 144 genes were found to have been under positive selection in various species of echolocating bats and toothed whales, 34 of which were identified to be related to hearing behavior or auditory processes. Subsequently, multiple physiological processes associated with those genes were found to have adaptively evolved in echolocating bats and toothed whales, including cochlear bony development, antioxidant activity, ion balance, and homeostatic processes, along with signal transduction. In addition, abundant convergent/parallel genes and sites were detected between different pairs of echolocator species; however, no specific hearing-related physiological pathways were enriched by them and almost all of the convergent/parallel signals were selectively neutral, as previously reported. Notably, two adaptive parallel evolved sites in TECPR2 were shown to have been under positive selection, indicating their functional importance for the evolution of echolocation and high-frequency hearing in laryngeal echolocating bats. This study deepens our understanding of the genetic bases underlying high-frequency hearing in the cochlea of echolocating bats and toothed whales.

The Western Diet Regulates Hippocampal Microvascular Gene Expression: An Integrated Genomic Analyses in Female Mice

Hyperlipidemia is a risk factor for dementia, and chronic consumption of a Western Diet (WD) is associated with cognitive impairment. However, the molecular mechanisms underlying the development of microvascular disease in the memory centers of the brain are poorly understood. This pilot study investigated the nutrigenomic pathways by which the WD regulates gene expression in hippocampal brain microvessels of female mice. Five-week-old female low-density lipoprotein receptor deficient (LDL-R−/−) and C57BL/6J wild type (WT) mice were fed a chow or WD for 8 weeks. Metabolics for lipids, glucose and insulin were determined. Differential gene expression, gene networks and pathways, transcription factors, and non-protein coding RNAs were evaluated by genome-wide microarray and bioinformatics analysis of laser captured hippocampal microvessels. The WD resulted in differential expression of 2,412 genes. The majority of differential gene expression was attributable to differential regulation of cell signaling proteins and their transcription factors, approximately 7% was attributable to differential expression of miRNAs, and a lesser proportion was due to other non-protein coding RNAs, primarily long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs) not previously described to be modified by the WD in females. Our findings revealed that chronic consumption of the WD resulted in integrated multilevel molecular regulation of the hippocampal microvasculature of female mice and may provide one of the mechanisms underlying vascular dementia.

Characterisation of transcription factor profiles in polycystic kidney disease (PKD): identification and validation of STAT3 and RUNX1 in the injury/repair response and PKD progression

Abstract

Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic renal disease, caused in the majority of the cases by a mutation in either the PKD1 or the PKD2 gene. ADPKD is characterised by a progressive increase in the number and size of cysts, together with fibrosis and distortion of the renal architecture, over the years. This is accompanied by alterations in a complex network of signalling pathways. However, the underlying molecular mechanisms are not well characterised. Previously, we defined the PKD Signature, a set of genes typically dysregulated in PKD across different disease models from a meta-analysis of expression profiles. Given the importance of transcription factors (TFs) in modulating disease, we focused in this paper on characterising TFs from the PKD Signature. Our results revealed that out of the 1515 genes in the PKD Signature, 92 were TFs with altered expression in PKD, and 32 of those were also implicated in tissue injury/repair mechanisms. Validating the dysregulation of these TFs by qPCR in independent PKD and injury models largely confirmed these findings. STAT3 and RUNX1 displayed the strongest activation in cystic kidneys, as demonstrated by chromatin immunoprecipitation (ChIP) followed by qPCR. Using immunohistochemistry, we showed a dramatic increase of expression after renal injury in mice and cystic renal tissue of mice and humans. Our results suggest a role for STAT3 and RUNX1 and their downstream targets in the aetiology of ADPKD and indicate that the meta-analysis approach is a viable strategy for new target discovery in PKD.

Key messages

We identified a list of transcription factors (TFs) commonly dysregulated in ADPKD.

Out of the 92 TFs identified in the PKD Signature, 35% are also involved in injury/repair processes.

STAT3 and RUNX1 are the most significantly dysregulated TFs after injury and during PKD progression.

STAT3 and RUNX1 activity is increased in cystic compared to non-cystic mouse kidneys.

Increased expression of STAT3 and RUNX1 is observed in the nuclei of renal epithelial cells, also in human ADPKD samples.

Electronic supplementary material

The online version of this article (10.1007/s00109-019-01852-3) contains supplementary material, which is available to authorized users.

(-)-Epicatechin metabolites promote vascular health through epigenetic reprogramming of endothelial-immune cell signaling and reversing systemic low-grade inflammation

Ingestion of (-)-epicatechin flavanols reverses endothelial dysfunction by increasing flow mediated dilation and by reducing vascular inflammation and oxidative stress, monocyte-endothelial cell adhesion and transendothelial monocyte migration in vitro and in vivo. This involves multiple changes in gene expression and epigenetic DNA methylation by poorly understood mechanisms. By in silico docking and molecular modeling we demonstrate favorable binding of different glucuronidated, sulfated or methylated (-)-epicatechin metabolites to different DNA methyltransferases (DNMT1/DNMT3A). In favor of this model, genome-wide DNA methylation profiling of endothelial cells treated with TNF and different (-)-epicatechin metabolites revealed specific DNA methylation changes in gene networks controlling cell adhesion-extravasation endothelial hyperpermeability as well as gamma-aminobutyric acid, renin-angiotensin and nitric oxide hypertension pathways. Remarkably, blood epigenetic profiles of an 8 weeks intervention with monomeric and oligomeric flavanols (MOF) including (-)-epicatechin in male smokers revealed individual epigenetic gene changes targeting similar pathways as the in vitro exposure experiments in endothelial cells. Furthermore, epigenetic changes following MOF diet intervention oppose atherosclerosis associated epigenetic changes. In line with biological data, the individual epigenetic response to a MOF diet is associated with different vascular health parameters (glutathione peroxidase 1 and endothelin-1 expression, acetylcholine-mediated microvascular response), in part involving systemic shifts in blood immune cell types which reduce the neutrophil-lymphocyte ratio (NLR). Altogether, our study suggests that different (-)-epicatechin metabolites promote vascular health in part via epigenetic reprogramming of endothelial-immune cell signaling and reversing systemic low-grade inflammation.

Automated workflow composition in mass spectrometry-based proteomics

Motivation

Numerous software utilities operating on mass spectrometry (MS) data are described in the literature and provide specific operations as building blocks for the assembly of on-purpose workflows. Working out which tools and combinations are applicable or optimal in practice is often hard. Thus researchers face difficulties in selecting practical and effective data analysis pipelines for a specific experimental design.

Results

We provide a toolkit to support researchers in identifying, comparing and benchmarking multiple workflows from individual bioinformatics tools. Automated workflow composition is enabled by the tools’ semantic annotation in terms of the EDAM ontology. To demonstrate the practical use of our framework, we created and evaluated a number of logically and semantically equivalent workflows for four use cases representing frequent tasks in MS-based proteomics. Indeed we found that the results computed by the workflows could vary considerably, emphasizing the benefits of a framework that facilitates their systematic exploration.

Availability and implementation

The project files and workflows are available from https://github.com/bio-tools/biotoolsCompose/tree/master/Automatic-Workflow-Composition.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genome-Wide Analysis of the Nucleosome Landscape in Individuals with Coffin-Siris Syndrome

The switch/sucrose non-fermenting (SWI/SNF) complex is an ATP-dependent chromatin remodeller that regulates the spacing of nucleosomes and thereby controls gene expression. Heterozygous mutations in genes encoding subunits of the SWI/SNF complex have been reported in individuals with Coffin-Siris syndrome (CSS), with the majority of the mutations in ARID1B. CSS is a rare congenital disorder characterized by facial dysmorphisms, digital anomalies, and variable intellectual disability. We hypothesized that mutations in genes encoding subunits of the ubiquitously expressed SWI/SNF complex may lead to alterations of the nucleosome profiles in different cell types. We performed the first study on CSS-patient samples and investigated the nucleosome landscapes of cell-free DNA (cfDNA) isolated from blood plasma by whole-genome sequencing. In addition, we studied the nucleosome landscapes of CD14+ monocytes from CSS-affected individuals by nucleosome occupancy and methylome-sequencing (NOMe-seq) as well as their expression profiles. In cfDNA of CSS-affected individuals with heterozygous ARID1B mutations, we did not observe major changes in the nucleosome profile around transcription start sites. In CD14+ monocytes, we found few genomic regions with different nucleosome occupancy when compared to controls. RNA-seq analysis of CD14+ monocytes of these individuals detected only few differentially expressed genes, which were not in proximity to any of the identified differential nucleosome-depleted regions. In conclusion, we show that heterozygous mutations in the human SWI/SNF subunit ARID1B do not have a major impact on the nucleosome landscape or gene expression in blood cells. This might be due to functional redundancy, cell-type specificity, or alternative functions of ARID1B.

REGGAE: a novel approach for the identification of key transcriptional regulators

Motivation

Transcriptional regulators play a major role in most biological processes. Alterations in their activities are associated with a variety of diseases and in particular with tumor development and progression. Hence, it is important to assess the effects of deregulated regulators on pathological processes.

Results

Here, we present REGulator-Gene Association Enrichment (REGGAE), a novel method for the identification of key transcriptional regulators that have a significant effect on the expression of a given set of genes, e.g. genes that are differentially expressed between two sample groups. REGGAE uses a Kolmogorov-Smirnov-like test statistic that implicitly combines associations between regulators and their target genes with an enrichment approach to prioritize the influence of transcriptional regulators. We evaluated our method in two different application scenarios, which demonstrate that REGGAE is well suited for uncovering the influence of transcriptional regulators and is a valuable tool for the elucidation of complex regulatory mechanisms.

Availability and implementation

REGGAE is freely available at https://regulatortrail.bioinf.uni-sb.de.

Supplementary information

Supplementary data are available at Bioinformatics online.

KH-Type Splicing Regulatory Protein Controls Colorectal Cancer Cell Growth and Modulates the Tumor Microenvironment

KH-type splicing regulatory protein (KHSRP) is a multifunctional nucleic acid binding protein implicated in key aspects of cancer cell biology: inflammation and cell-fate determination. However, the role KHSRP plays in colorectal cancer (CRC) tumorigenesis remains largely unknown. Using a combination of in silico analysis of large data sets, ex vivo analysis of protein expression in patients, and mechanistic studies using in vitro models of CRC, we investigated the oncogenic role of KHSRP. We demonstrated KHSRP expression in the epithelial and stromal compartments of both primary and metastatic tumors. Elevated expression was found in tumor versus matched normal tissue, and these findings were validated in larger independent cohorts in silico. KHSRP expression was a prognostic indicator of worse overall survival (hazard ratio, 3.74; 95% CI, 1.43-22.97; P = 0.0138). Mechanistic data in CRC cell line models supported a role of KHSRP in driving epithelial cell proliferation in both a primary and metastatic setting, through control of the G1/S transition. In addition, KHSRP promoted a proangiogenic extracellular environment by regulating the secretion of oncogenic proteins involved in diverse cellular processes, such as migration and response to cellular stress. Our study provides novel mechanistic insight into the tumor-promoting effects of KHSRP in CRC.

Loss of SATB1 Induces p21-Dependent Cellular Senescence in Post-mitotic Dopaminergic Neurons

Cellular senescence is a mechanism used by mitotic cells to prevent uncontrolled cell division. As senescent cells persist in tissues, they cause local inflammation and are harmful to surrounding cells, contributing to aging. Generally, neurodegenerative diseases, such as Parkinson's, are disorders of aging. The contribution of cellular senescence to neurodegeneration is still unclear. SATB1 is a DNA binding protein associated with Parkinson's disease. We report that SATB1 prevents cellular senescence in post-mitotic dopaminergic neurons. Loss of SATB1 causes activation of a cellular senescence transcriptional program in dopamine neurons both in human stem cell-derived dopaminergic neurons and in mice. We observed phenotypes that are central to cellular senescence in SATB1 knockout dopamine neurons in vitro and in vivo. Moreover, we found that SATB1 directly represses expression of the pro-senescence factor p21 in dopaminergic neurons. Our data implicate senescence of dopamine neurons as a contributing factor in the pathology of Parkinson's disease.

Discovery of Genomic Characteristics and Selection Signatures in Korean Indigenous Goats Through Comparison of 10 Goat Breeds

Indigenous breeds develop their own genomic characteristics by adapting to local environments or cultures over long periods of time. Most of them are not particularly productive in commercial terms, but they have abilities to survive in harsh environments or tolerate to specific diseases. Their adaptive characteristics play an important role as genetic materials for improving commercial breeds. As a step toward this goal, we analyzed the genome of Korean indigenous goats within 10 goat breeds. We collected 136 goat individuals by sequencing 46 new goats and employing 90 publicly available goats. Our whole-genome data was comprised of three indigenous breeds (Korean indigenous goat, Iranian indigenous goat, and Moroccan indigenous goat; n = 29, 18, 20), six commercial breeds (Saanen, Boer, Anglo-Nubian, British Alpine, Alpine, and Korean crossbred; n = 16, 11, 5, 5, 2, 13), and their ancestral species (Capra aegagrus; n = 17). We identified that the Iranian indigenous goat and the Moroccan indigenous goat have relatively similar genomic characteristics within a large category of genomic diversity but found that the Korean indigenous goat has unique genomic characteristics distinguished from the other nine breeds. Through population analysis, we confirmed that these characteristics have resulted from a near-isolated environment with strong genetic drift. The Korean indigenous goat experienced a severe genetic bottleneck upon entering the Korean Peninsula about 2,000 years ago, and has subsequently rarely experienced genetic interactions with other goat breeds. From selection analysis and gene-set enrichment analysis, we revealed selection signals for Salmonella infection and cardiomyopathy in the genome of the Korean indigenous goat. These adaptive characteristics were further identified with genomic-based evidence. We uncovered genomic regions of selective sweeps in the LBP and BPI genes (Salmonella infection) and the TTN and ITGB6 genes (cardiomyopathy), among several candidate genes. Our research presents unique genomic characteristics and distinctive selection signals of the Korean indigenous goat based on the extensive comparison. Although the adaptive traits require further validation through biological experiments, our findings are expected to provide a direction for future biodiversity conservation strategies and to contribute another option to genomic-based breeding programmes for improving the viability of Capra hircus.

miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer

BACKGROUND

MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In silico-based functional analysis of miRNAs usually consists of miRNA target prediction and functional enrichment analysis of miRNA targets. Since miRNA target prediction methods generate a large number of false positive target genes, further validation to narrow down interesting candidate miRNA targets is needed. One commonly used method correlates miRNA and mRNA expression to assess the regulatory effect of a particular miRNA. The aim of this study was to build a bioinformatics pipeline in R for miRNA functional analysis including correlation analyses between miRNA expression levels and its targets on mRNA and protein expression levels available from the cancer genome atlas (TCGA) and the cancer proteome atlas (TCPA). TCGA-derived expression data of specific mature miRNA isoforms from pancreatic cancer tissue was used.

RESULTS

Fifteen circulating miRNAs with significantly altered expression levels detected in pancreatic cancer patients were queried separately in the pipeline. The pipeline generated predicted miRNA target genes, enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Predicted miRNA targets were evaluated by correlation analyses between each miRNA and its predicted targets. MiRNA functional analysis in combination with Kaplan-Meier survival analysis suggest that hsa-miR-885-5p could act as a tumor suppressor and should be validated as a potential prognostic biomarker in pancreatic cancer.

CONCLUSIONS

Our miRNA functional analysis (miRFA) pipeline can serve as a valuable tool in biomarker discovery involving mature miRNAs associated with pancreatic cancer and could be developed to cover additional cancer types. Results for all mature miRNAs in TCGA pancreatic adenocarcinoma dataset can be studied and downloaded through a shiny web application at https://emmbor.shinyapps.io/mirfa/ .

miR-34a as hub of T cell regulation networks

BACKGROUND

Micro(mi)RNAs are increasingly recognized as central regulators of immune cell function. While it has been predicted that miRNAs have multiple targets, the majority of these predictions still await experimental confirmation. Here, miR-34a, a well-known tumor suppressor, is analyzed for targeting genes involved in immune system processes of leucocytes.

METHODS

Using an in-silico approach, we combined miRNA target prediction with GeneTrail2, a web tool for Multi-omics enrichment analysis, to identify miR-34a target genes, which are involved in the immune system process subcategory of Gene Ontology.

RESULTS

Out of the 193 predicted target genes in this subcategory we experimentally tested 22 target genes and confirmed binding of miR-34a to 14 target genes including VAMP2, IKBKE, MYH9, MARCH8, KLRK1, CD11A, TRAFD1, CCR1, PYDC1, PRF1, PIK3R2, PIK3CD, AP1B1, and ADAM10 by dual luciferase assays. By transfecting Jurkat, primary CD4⁺ and CD8⁺ T cells with miR-34a, we demonstrated that ectopic expression of miR-34a leads to reduced levels of endogenous VAMP2 and CD11A, which are central to the analyzed subcategories. Functional downstream analysis of miR-34a over-expression in activated CD8⁺ T cells exhibits a distinct decrease of PRF1 secretion.

CONCLUSIONS

By simultaneous targeting of 14 mRNAs miR-34a acts as major hub of T cell regulatory networks suggesting to utilize miR-34a as target of intervention towards a modulation of the immune responsiveness of T-cells in a broad tumor context.

Assessment of mixture toxicity of (tri)azoles and their hepatotoxic effects in vitro by means of omics technologies

Consumers are constantly exposed to chemical mixtures such as multiple residues of different pesticides via the diet. This raises questions concerning potential combination effects, especially because these substances are tested for regulatory purposes on an individual basis. With approximately 500 active substances approved as pesticides, there are too many possible combinations to be tested in standard animal experiments generally requested for regulatory purposes. Therefore, the development of in vitro tools and alternative testing strategies for the assessment of mixture effects is extremely important. As a first step in the development of such in vitro tools, we used (tri)azoles as model substances in a set of different cell lines derived from the primary target organ of these substances, the liver (human: HepaRG, rat: H4IIE). Concentrations were reconciled with measured tissue concentrations obtained from in vivo experiments to ensure comparable effect levels. The effects of the substances were subsequently analyzed by transcriptomics and metabolomics techniques and compared to data from corresponding in vivo studies. The results show that similar toxicity pathways are affected by substances and combinations, thus indicating a similar mode of action and additive effects. Two biomarkers obtained by the approach, CAR and Cyp1A1, were used for mixture toxicity modeling and confirmed the concentration-additive effects, thus supporting the selected testing strategy and raising hope for the development of in vitro methods suitable to detect combination effects and prioritize mixtures of concern for further testing.

Differential analysis of combinatorial protein complexes with CompleXChange

BACKGROUND

Although a considerable number of proteins operate as multiprotein complexes and not on their own, organism-wide studies so far are only able to quantify individual proteins or protein-coding genes in a condition-specific manner for a sizeable number of samples, but not their assemblies. Consequently, there exist large amounts of transcriptomic data and an increasing amount of data on proteome abundance, but quantitative knowledge on complexomes is missing. This deficiency impedes the applicability of the powerful tool of differential analysis in the realm of macromolecular complexes. Here, we present a pipeline for differential analysis of protein complexes based on predicted or manually assigned complexes and inferred complex abundances, which can be easily applied on a whole-genome scale.

RESULTS

We observed for simulated data that results obtained by our complex abundance estimation algorithm were in better agreement with the ground truth and physicochemically more reasonable compared to previous efforts that used linear programming while running in a fraction of the time. The practical usability of the method was assessed in the context of transcription factor complexes in human monocyte and lymphoblastoid samples. We demonstrated that our new method is robust against false-positive detection and reports deregulated complexomes that can only be partially explained by differential analysis of individual protein-coding genes. Furthermore we showed that deregulated complexes identified by the tool potentially harbor significant yet unused information content.

CONCLUSIONS

CompleXChange allows to analyze deregulation of the protein complexome on a whole-genome scale by integrating a plethora of input data that is already available. A platform-independent Java binary, a user guide with example data and the source code are freely available at https://sourceforge.net/projects/complexchange/ .

Artificial microenvironment of in vitro glioblastoma cell cultures changes profile of miRNAs related to tumor drug resistance

Purpose: The in vitro environment can influence not only the molecular background of glioblastoma drug-resistance and treatment efficiency, but also the mechanisms and pathways of cell death. Both crucial molecular pathways and the deregulation of miRNAs are thought to participate in tumor therapy-resistance. The aim of our study is to examine the potential influence of ex vivo conditions on the expression of miRNAs engaged in the machinery of tumor-drug resistance, since in vitro models are commonly used for testing new therapeutics.

Methods: Glioblastoma-derived cells, cultured under three different sets of conditions, were used as experimental models in vitro. The expression of 84 miRNAs relevant to brain tumorigenesis was evaluated by multi-miRNA profiling for initial tumors and their corresponding cultures. Finally, the expression of selected miRNAs related to temozolomide-resistance (miR-125b, miR-130a, miR-21, miR-221, miR-222, miR-31, miR-149, miR-210, miR-181a) was assessed by real-time PCR for each tumor and neoplastic cells in cultures.

Results: Our results demonstrate significant discrepancies in the expression of several miRNAs between tumor cells in vivo and in vitro, with miR-130a, miR-221, miR-31, miR-21, miR-222, miR-210 being the most marked. Also differences were observed between particular models in vitro. The results of computational analysis revealed the interplay between examined miRNAs and their targets involved in processes of glioblastoma chemosensitivity, including the genes relevant to temozolomide response (MGMT, PTEN, MDM2, TP53, BBC3A).

Conclusion: The artificial environment may influence the selective proliferation of cell populations carrying specific patterns of miRNAs and/or the phenotype of neoplastic cells (eg differentiation) by the action of molecular events including miRNAs. These phenomena may influence the tumor-responsiveness to particular drugs, disturbing the evaluation of their efficacy in vitro, with unpredictable results caused by the interdependency of molecular pathways.

Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.

With the increasing obtainability of multi-OMICs data comes the need for easy to use data analysis tools. Here, the authors introduce Metascape, a biologist-oriented portal that provides a gene list annotation, enrichment and interactome resource and enables integrated analysis of multi-OMICs datasets.

Data and knowledge management in translational research: implementation of the eTRIKS platform for the IMI OncoTrack consortium

Background

For large international research consortia, such as those funded by the European Union’s Horizon 2020 programme or the Innovative Medicines Initiative, good data coordination practices and tools are essential for the successful collection, organization and analysis of the resulting data. Research consortia are attempting ever more ambitious science to better understand disease, by leveraging technologies such as whole genome sequencing, proteomics, patient-derived biological models and computer-based systems biology simulations.

Results

The IMI eTRIKS consortium is charged with the task of developing an integrated knowledge management platform capable of supporting the complexity of the data generated by such research programmes. In this paper, using the example of the OncoTrack consortium, we describe a typical use case in translational medicine. The tranSMART knowledge management platform was implemented to support data from observational clinical cohorts, drug response data from cell culture models and drug response data from mouse xenograft tumour models. The high dimensional (omics) data from the molecular analyses of the corresponding biological materials were linked to these collections, so that users could browse and analyse these to derive candidate biomarkers.

Conclusions

In all these steps, data mapping, linking and preparation are handled automatically by the tranSMART integration platform. Therefore, researchers without specialist data handling skills can focus directly on the scientific questions, without spending undue effort on processing the data and data integration, which are otherwise a burden and the most time-consuming part of translational research data analysis.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2748-y) contains supplementary material, which is available to authorized users.

MGSEA - a multivariate Gene set enrichment analysis

BACKGROUND

Gene Set Enrichment Analysis (GSEA) is a powerful tool to identify enriched functional categories of informative biomarkers. Canonical GSEA takes one-dimensional feature scores derived from the data of one platform as inputs. Numerous extensions of GSEA handling multimodal OMIC data are proposed, yet none of them explicitly captures combinatorial relations of feature scores from multiple platforms.

RESULTS

We propose multivariate GSEA (MGSEA) to capture combinatorial relations of gene set enrichment among multiple platform features. MGSEA successfully captures designed feature relations from simulated data. By applying it to the scores of delineating breast cancer and glioblastoma multiforme (GBM) subtypes from The Cancer Genome Atlas (TCGA) datasets of CNV, DNA methylation and mRNA expressions, we find that breast cancer and GBM data yield both similar and distinct outcomes. Among the enriched functional categories, subtype-specific biomarkers are dominated by mRNA expression in many functional categories in both cancer types and also by CNV in many functional categories in breast cancer. The enriched functional categories belonging to distinct combinatorial patterns are involved different oncogenic processes: cell proliferation (such as cell cycle control, estrogen responses, MYC and E2F targets) for mRNA expression in breast cancer, invasion and metastasis (such as cell adhesion and epithelial-mesenchymal transition (EMT)) for CNV in breast cancer, and diverse processes (such as immune and inflammatory responses, cell adhesion, angiogenesis, and EMT) for mRNA expression in GBM. These observations persist in two external datasets (Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) for breast cancer and Repository for Molecular Brain Neoplasia Data (REMBRANDT) for GBM) and are consistent with knowledge of cancer subtypes. We further compare the characteristics of MGSEA with several extensions of GSEA and point out the pros and cons of each method.

CONCLUSIONS

We demonstrated the utility of MGSEA by inferring the combinatorial relations of multiple platforms for cancer subtype delineation in three multi-OMIC datasets: TCGA, METABRIC and REMBRANDT. The inferred combinatorial patterns are consistent with the current knowledge and also reveal novel insights about cancer subtypes. MGSEA can be further applied to any genotype-phenotype association problems with multimodal OMIC data.

Grade-specific diagnostic and prognostic biomarkers in breast cancer

An integrative approach is presented to identify grade-specific biomarkers for breast cancer. Grade-specific molecular interaction networks were constructed with differentially expressed genes (DEGs) of cancer grade 1, 2, and 3. We observed that the molecular network of grade3 is predominantly associated with cancer-specific processes. Among the top ten connected DEGs in the grade3, the increase in the expression of UBE2C and CCNB2 genes was statistically significant across different grades. Along with UBE2C and CCNB2 genes, the CDK1, KIF2C, NDC80, and CCNB2 genes are also profoundly expressed in different grades and reduce the patient's survival. Gene set enrichment analysis of these six genes reconfirms their role in metastatic phenotype. Moreover, the coexpression network shows a strong association of these six genes promotes cancer specific biological processes and possibly drives cancer from lower to a higher grade. Collectively the identified genes can act as potential biomarkers for breast cancer diagnosis and prognosis.

3D Cellular Architecture Affects MicroRNA and Protein Cargo of Extracellular Vesicles

The success of malignant tumors is conditioned by the intercellular communication between tumor cells and their microenvironment, with extracellular vesicles (EVs) acting as main mediators. While the value of 3D conditions to study tumor cells is well established, the impact of cellular architecture on EV content and function is not investigated yet. Here, a recently developed 3D cell culture microwell array is adapted for EV production and a comprehensive comparative analysis of biochemical features, RNA and proteomic profiles of EVs secreted by 2D vs 3D cultures of gastric cancer cells, is performed. 3D cultures are significantly more efficient in producing EVs than 2D cultures. Global upregulation of microRNAs and downregulation of proteins in 3D are observed, indicating their dynamic coregulation in response to cellular architecture, with the ADP-ribosylation factor 6 signaling pathway significantly downregulated in 3D EVs. The data strengthen the biological relevance of cellular architecture for production and cargo of EVs.

Expression of long non-coding RNA ENSG00000226738 (LncKLHDC7B) is enriched in the immunomodulatory triple-negative breast cancer subtype and its alteration promotes cell migration, invasion, and resistance to cell death

Triple negative breast cancer (TNBC) represents an aggressive phenotype with poor prognosis compared with ER, PR, and HER2‐positive tumors. TNBC is a heterogeneous disease, and gene expression analysis has identified seven molecular subtypes. Accumulating evidence demonstrates that long non‐coding RNA (lncRNA) are involved in regulation of gene expression and cancer biology, contributing to essential cancer cell functions. In this study, we analyzed the expression profile of lncRNA in TNBC subtypes from 156 TNBC samples, and then characterized the functional role of LncKLHDC7B (ENSG00000226738). A total of 710 lncRNA were found to be differentially expressed between TNBC subtypes, and a subset of these altered lncRNA were independently validated. We discovered that LncKLHDC7B (ENSG00000226738) acts as a transcriptional modulator of its neighboring coding gene KLHDC7B in the immunomodulatory subtype. Furthermore, LncKLHDC7B knockdown enhanced migration and invasion, and promoted resistance to cellular death. Our findings confirmed the contribution of LncKLHDC7B to induction of apoptosis and inhibition of cell migration and invasion, suggesting that TNBC tumors with enrichment of LncKLHDC7B may exhibit distinct regulatory activity, or that this may be a generalized process in breast cancer. Additionally, in silico analysis confirmed for the first time that the low expression of KLHDC7B and LncKLHDC7B is associated with poor prognosis in patients with breast cancer.

Micro-RNA-Regulated Proangiogenic Signaling in Arteriovenous Loops in Patients with Combined Vascular and Soft-Tissue Reconstructions: Revisiting the Nutrient Flap Concept

BACKGROUND

The placement of arteriovenous loops can enable microvascular anastomoses of free flaps when recipient vessels are scarce. In animal models, elevated fluid shear stress in arteriovenous loops promotes neoangiogenesis. Anecdotal reports in patients indicate that vein grafts used in free flap reconstructions of ischemic lower extremities are able to induce capillary formation. However, flow-stimulated angiogenesis has never been systematically investigated in humans, and it is unclear whether shear stress alters proangiogenic signaling pathways within the vascular wall of human arteriovenous loops.

METHODS

Eight patients with lower extremity soft-tissue defects underwent two-stage reconstruction with arteriovenous loop placement, and free flap anastomoses to the loops 10 to 14 days later. Micro-RNA (miRNA) and gene expression profiles were determined in tissue samples harvested from vein grafts of arteriovenous loops by microarray analysis and quantitative real-time polymerase chain reaction. Samples from untreated veins served as controls.

RESULTS

A strong deregulation of miRNA and gene expression was detected in arteriovenous loops, showing an overexpression of angiopoietic cytokines, oxygenation-associated genes, vascular growth factors, and connexin-43. The authors discovered inverse correlations along with validated and bioinformatically predicted interactions between angiogenesis-regulating genes and miRNAs in arteriovenous loops.

CONCLUSIONS

The authors' findings demonstrate that elevated shear stress triggers proangiogenic signaling pathways in human venous tissue, indicating that arteriovenous loops may have the ability to induce neoangiogenesis in humans. The authors' data corroborate the nutrient flap hypothesis and provide a molecular background for arteriovenous loop-based tissue engineering with potential clinical applications for soft-tissue defect reconstruction.

MicroRNA-regulated pathways of flow-stimulated angiogenesis and vascular remodeling in vivo

BACKGROUND

Vascular shear stress promotes endothelial cell sprouting in vitro. The impact of hemodynamic forces on microRNA (miRNA) and gene expression within growing vascular networks in vivo, however, remain poorly investigated. Arteriovenous (AV) shunts are an established model for induction of neoangiogenesis in vivo and can serve as a tool for analysis of hemodynamic effects on miRNA and gene expression profiles over time.

METHODS

AV shunts were microsurgically created in rats and explanted on postoperative days 5, 10 and 15. Neoangiogenesis was confirmed by histologic analysis and micro-computed tomography. MiRNA and gene expression profiles were determined in tissue specimens from AV shunts by microarray analysis and quantitative real-time polymerase chain reaction and compared with sham-operated veins by bioinformatics analysis. Changes in protein expression within AV shunt endothelial cells were determined by immunohistochemistry.

RESULTS

Samples from AV shunts exhibited a strong overexpression of proangiogenic cytokines, oxygenation-associated genes (HIF1A, HMOX1), and angiopoetic growth factors. Significant inverse correlations of the expressions of miR-223-3p, miR-130b-3p, miR-19b-3p, miR-449a-5p, and miR-511-3p which were up-regulated in AV shunts, and miR-27b-3p, miR-10b-5p, let-7b-5p, and let-7c-5p, which were down-regulated in AV shunts, with their predicted interacting targets C-X-C chemokine receptor 2 (CXCR2), interleukin-1 alpha (IL1A), ephrin receptor kinase 2 (EPHA2), synaptojanin-2 binding protein (SYNJ2BP), forkhead box C1 (FOXC1) were present. CXCL2 and IL1A overexpression in AV shunt endothelium was confirmed at the protein level by immunohistochemistry.

CONCLUSIONS

Our data indicate that flow-stimulated angiogenesis is determined by an upregulation of cytokines, oxygenation associated genes and miRNA-dependent regulation of FOXC1, EPHA2 and SYNJ2BP.

Cohesin-mediated NF-κB signaling limits hematopoietic stem cell self-renewal in aging and inflammation

Organism aging is characterized by increased inflammation and decreased stem cell function, yet the relationship between these factors remains incompletely understood. This study shows that aged hematopoietic stem and progenitor cells (HSPCs) exhibit increased ground-stage NF-κB activity, which enhances their responsiveness to undergo differentiation and loss of self-renewal in response to inflammation. The study identifies Rad21/cohesin as a critical mediator of NF-κB signaling, which increases chromatin accessibility in the vicinity of NF-κB target genes in response to inflammation. Rad21 is required for normal differentiation, but limits self-renewal of hematopoietic stem cells (HSCs) during aging and inflammation in an NF-κB-dependent manner. HSCs from aged mice fail to down-regulate Rad21/cohesin and inflammation/differentiation signals in the resolution phase of inflammation. Inhibition of cohesin/NF-κB reverts hypersensitivity of aged HSPCs to inflammation-induced differentiation and myeloid-biased HSCs with disrupted/reduced expression of Rad21/cohesin are increasingly selected during aging. Together, Rad21/cohesin-mediated NF-κB signaling limits HSPC function during aging and selects for cohesin-deficient HSCs with myeloid-skewed differentiation.

Integrated omics: tools, advances and future approaches

With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing and data archiving. The ultimate goal is toward the holistic realization of a 'systems biology' understanding of the biological question. Commonly used approaches are currently limited by the 3 i's - integration, interpretation and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.

Large-scale validation of miRNAs by disease association, evolutionary conservation and pathway activity

The validation of microRNAs (miRNAs) identified by next generation sequencing involves amplification-free and hybridization-based detection of transcripts as criteria for confirming valid miRNAs. Since respective validation is frequently not performed, miRNA repositories likely still contain a substantial fraction of false positive candidates while true miRNAs are not stored in the repositories yet. Especially if downstream analyses are performed with these candidates (e.g. target or pathway prediction), the results may be misleading. In the present study, we evaluated 558 mature miRNAs from miRBase and 1,709 miRNA candidates from next generation sequencing experiments by amplification-free hybridization and investigated their distributions in patients with various disease conditions. Notably, the most significant miRNAs in diseases are often not contained in the miRBase. However, these candidates are evolutionary highly conserved. From the expression patterns, target gene and pathway analyses and evolutionary conservation analyses, we were able to shed light on the complexity of miRNAs in humans. Our data also highlight that a more thorough validation of miRNAs identified by next generation sequencing is required. The results are available in miRCarta ( https://mircarta.cs.uni-saarland.de ).

The role of TCF3 as potential master regulator in blastemal Wilms tumors

Wilms tumors are the most common type of pediatric kidney tumors. While the overall prognosis for patients is favorable, especially tumors that exhibit a blastemal subtype after preoperative chemotherapy have a poor prognosis. For an improved risk assessment and therapy stratification, it is essential to identify the driving factors that are distinctive for this aggressive subtype. In our study, we compared gene expression profiles of 33 tumor biopsies (17 blastemal and 16 other tumors) after neoadjuvant chemotherapy. The analysis of this dataset using the Regulator Gene Association Enrichment algorithm successfully identified several biomarkers and associated molecular mechanisms that distinguish between blastemal and nonblastemal Wilms tumors. Specifically, regulators involved in embryonic development and epigenetic processes like chromatin remodeling and histone modification play an essential role in blastemal tumors. In this context, we especially identified TCF3 as the central regulatory element. Furthermore, the comparison of ChIP-Seq data of Wilms tumor cell cultures from a blastemal mouse xenograft and a stromal tumor provided further evidence that the chromatin states of blastemal cells share characteristics with embryonic stem cells that are not present in the stromal tumor cell line. These stem-cell like characteristics could potentially add to the increased malignancy and chemoresistance of the blastemal subtype. Along with TCF3, we detected several additional biomarkers that are distinctive for blastemal Wilms tumors after neoadjuvant chemotherapy and that may provide leads for new therapeutic regimens.

Molecular parallelism in fast-twitch muscle proteins in echolocating mammals

Detecting associations between genomic changes and phenotypic differences is fundamental to understanding how phenotypes evolved. By systematically screening for parallel amino acid substitutions, we detected known as well as novel cases (Strc, Tecta, and Cabp2) of parallelism between echolocating bats and toothed whales in proteins that could contribute to high-frequency hearing adaptations. Our screen also showed that echolocating mammals exhibit an unusually high number of parallel substitutions in fast-twitch muscle fiber proteins. Both echolocating bats and toothed whales produce an extremely rapid call rate when homing in on their prey, which was shown in bats to be powered by specialized superfast muscles. We show that these genes with parallel substitutions (Casq1, Atp2a1, Myh2, and Myl1) are expressed in the superfast sound-producing muscle of bats. Furthermore, we found that the calcium storage protein calsequestrin 1 of the little brown bat and the bottlenose dolphin functionally converged in its ability to form calcium-sequestering polymers at lower calcium concentrations, which may contribute to rapid calcium transients required for superfast muscle physiology. The proteins that our genomic screen detected could be involved in the convergent evolution of vocalization in echolocating mammals by potentially contributing to both rapid Ca²⁺ transients and increased shortening velocities in superfast muscles.