Transcriptome Profiling of Atlantic Salmon (Salmo salar) Parr With Higher and Lower Pathogen Loads Following Piscirickettsia salmonis Infection

Salmonid rickettsial septicemia (SRS), caused by Piscirickettsia salmonis, is one of the most devastating diseases of salmonids. However, the transcriptomic responses of Atlantic salmon (Salmon salar) in freshwater to an EM-90-like isolate have not been explored. Here, we infected Atlantic salmon parr with an EM-90-like isolate and conducted time-course qPCR analyses of pathogen load and four biomarkers (campb, hampa, il8a, tlr5a) of innate immunity on the head kidney samples. Transcript expression of three of these genes (except hampa), as well as pathogen level, peaked at 21 days post-injection (DPI). Multivariate analyses of infected individuals at 21 DPI revealed two infection phenotypes [lower (L-SRS) and higher (H-SRS) infection level]. Five fish from each group (Control, L-SRS, and H-SRS) were selected for transcriptome profiling using a 44K salmonid microarray platform. We identified 1,636 and 3,076 differentially expressed probes (DEPs) in the L-SRS and H-SRS groups compared with the control group, respectively (FDR = 1%). Gene ontology term enrichment analyses of SRS-responsive genes revealed the activation of a large number of innate (e.g. “phagocytosis”, “defense response to bacterium”, “inflammatory response”) and adaptive (e.g. “regulation of T cell activation”, “antigen processing and presentation of exogenous antigen”) immune processes, while a small number of general physiological processes (e.g. “apoptotic process”, development and metabolism relevant) was enriched. Transcriptome results were confirmed by qPCR analyses of 42 microarray-identified transcripts. Furthermore, the comparison of individuals with differing levels of infection (H-SRS vs. L-SRS) generated insights into the biological processes possibly involved in disease resistance or susceptibility. This study demonstrated a low mortality (~30%) EM-90-like infection model and broadened the current understanding of molecular pathways underlying P. salmonis-triggered responses of Atlantic salmon, identifying biomarkers that may assist to diagnose and combat this pathogen.

RORα contributes to the maintenance of genome ploidy in the liver of mice with diet-induced nonalcoholic steatohepatitis

Hepatic polyploidization is closely linked to the progression of nonalcoholic fatty liver disease (NAFLD); however, the underlying molecular mechanism is not clearly understood. In this study, we demonstrated the role of RORα in the maintenance of genomic integrity, particularly in the pathogenesis of NAFLD, using the high-fat diet (HFD)-fed liver-specific RORα knockout (RORα-LKO) mouse model. First, we observed that the loss of hepatic retinoic acid receptor-related orphan receptor α (RORα) accelerated hepatocyte nuclear polyploidization after HFD feeding. In 70% partial hepatectomy experiments, enrichment of hepatocyte polyploidy was more obvious in the RORα-LKO animals, which was accompanied by early progression to the S phase and blockade of the G2/M transition, suggesting a potential role of RORα in suppressing hepatocyte polyploidization in the regenerating liver. An analysis of a publicly available RNA-seq and chromatin immunoprecipitation-seq dataset, together with the Search Tool of the Retrieval of Interacting Genes/Proteins database resource, revealed that DNA endoreplication was the top enriched biological process gene ontology term. Furthermore, we found that E2f7 and E2f8, which encode key transcription factors for DNA endoreplication, were the downstream targets of RORα-induced transcriptional repression. Finally, we showed that the administration of JC1-40, an RORα activator (5 mg/kg body weight), significantly reduced hepatic nuclear polyploidization in the HFD-fed mice. Together, our observations suggest that the RORα-induced suppression of hepatic polyploidization may provide new insights into the pathological polyploidy of NAFLD and may contribute to the development of therapeutic strategies for the treatment of NAFLD.

Transcriptome Analysis Reveals Dynamic Cultivar-Dependent Patterns of Gene Expression in Potato Spindle Tuber Viroid-Infected Pepper

Potato spindle tuber viroid (PSTVd) infects various plants. PSTVd pathogenesis is associated with interference with the cellular metabolism and defense signaling pathways via direct interaction with host factors or via the transcriptional or post-transcriptional modulation of gene expression. To better understand host defense mechanisms to PSTVd infection, we analyzed the gene expression in two pepper cultivars, Capsicum annuum Kurtovska kapia (KK) and Djulunska shipka (DS), which exhibit mild symptoms of PSTVd infection. Deep sequencing-based transcriptome analysis revealed differential gene expression upon infection, with some genes displaying contrasting expression patterns in KK and DS plants. More genes were downregulated in DS plants upon infection than in KK plants, which could underlie the more severe symptoms seen in DS plants. Gene ontology enrichment analysis revealed that most of the downregulated differentially expressed genes in both cultivars were enriched in the gene ontology term photosynthesis. The genes upregulated in DS plants fell in the biological process of gene ontology term defense response. We validated the expression of six overlapping differentially expressed genes that are involved in photosynthesis, plant hormone signaling, and defense pathways by quantitative polymerase chain reaction. The observed differences in the responses of the two cultivars to PSTVd infection expand the understanding of the fine-tuning of plant gene expression that is needed to overcome the infection.

A Novel Calibration Step in Gene Co-Expression Network Construction

High-throughput technologies such as DNA microarrays and RNA-sequencing are used to measure the expression levels of large numbers of genes simultaneously. To support the extraction of biological knowledge, individual gene expression levels are transformed to Gene Co-expression Networks (GCNs). In a GCN, nodes correspond to genes, and the weight of the connection between two nodes is a measure of similarity in the expression behavior of the two genes. In general, GCN construction and analysis includes three steps; 1) calculating a similarity value for each pair of genes 2) using these similarity values to construct a fully connected weighted network 3) finding clusters of genes in the network, commonly called modules. The specific implementation of these three steps can significantly impact the final output and the downstream biological analysis. GCN construction is a well-studied topic. Existing algorithms rely on relatively simple statistical and mathematical tools to implement these steps. Currently, software package WGCNA appears to be the most widely accepted standard. We hypothesize that the raw features provided by sequencing data can be leveraged to extract modules of higher quality. A novel preprocessing step of the gene expression data set is introduced that in effect calibrates the expression levels of individual genes, before computing pairwise similarities. Further, the similarity is computed as an inner-product of positive vectors. In experiments, this provides a significant improvement over WGCNA, as measured by aggregate p-values of the gene ontology term enrichment of the computed modules.

Long non-coding RNA expression in silicosis and MRAK050699 function in epithelial–mesenchymal transition

Silicosis is a lung fibrotic disease caused by chronic silica exposure. Aberrations in long non-coding RNA (lncRNA) expression are associated with fibrotic diseases, but the role of lncRNAs in silicosis pathogenesis remains unclear. Here, we investigated the expression of lncRNAs during silicosis and the role of MRAK050699 in epithelial–mesenchymal transition (EMT). Differentially expressed lncRNAs in the lung tissues of normal and silicosis rats were compared, and their biological effects were determined using the Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. There were 1077 differentially expressed lncRNAs (378 upregulated and 699 downregulated). MRAK052509, MRAK139674, AY539881, MRAK050699, XR_6113, and BC167061 were selected to verify expression in silicosis rats using quantitative reverse transcription polymerase chain reaction. MRAK050699 was knocked down in rat alveolar type II epithelial cells, and the molecular mechanism of transforming growth factor-β (TGF-β)-induced EMT in these cells was studied. All selected lncRNAs were upregulated in the silicosis rats, consistent with the sequencing results. MRAK050699 knockdown inhibited EMT of RLE-6TN cells by regulating the TGF-β/Smad3 signaling pathway. Thus, the differential expression of lncRNAs is related to silicosis development, and MRAK050699 plays an important role in EMT, suggesting a potential therapeutic target for silicosis.

Proliferative diabetic retinopathy transcriptomes reveal angiogenesis, anti-angiogenic therapy escape mechanisms, fibrosis and lymphatic involvement

Proliferative diabetic retinopathy (PDR) is a sight-threatening diabetic complication in urgent need of new therapies. In this study we identify potential molecular mechanisms and target candidates in the pathogenesis of PDR fibrovascular tissue formation. We performed mRNA sequencing of RNA isolated from eleven excised fibrovascular membranes of type 1 diabetic PDR patients and two non-diabetic patients with rhegmatogenous retinal detachment with proliferative vitreoretinopathy. We determined differentially expressed genes between these groups and performed pathway and gene ontology term enrichment analyses to identify potential underlying mechanisms, pathways, and regulators. Multiple pro-angiogenic processes, including VEGFA-dependent and -independent pathways, as well as processes related to lymphatic development, epithelial to mesenchymal transition (EMT), wound healing, inflammation, fibrosis, and extracellular matrix (ECM) composition, were overrepresented in PDR. Overrepresentation of different angiogenic processes may help to explain the transient nature of the benefits that many patients receive from current intravitreal anti-angiogenic therapies, highlighting the importance of combinatorial treatments. Enrichment of genes and pathways related to lymphatic development indicates that targeting lymphatic involvement in PDR progression could have therapeutic relevance. Together with overrepresentation of EMT and fibrosis as well as differential ECM composition, these findings demonstrate the complexity of PDR fibrovascular tissue formation and provide avenues for the development of novel treatments.

TFTenricher: a python toolbox for annotation enrichment analysis of transcription factor target genes

Background Transcription factors (TFs) are the upstream regulators that orchestrate gene expression, and therefore a centrepiece in bioinformatics studies. While a core strategy to understand the biological context of genes and proteins includes annotation enrichment analysis, such as Gene Ontology term enrichment, these methods are not well suited for analysing groups of TFs. This is particularly true since such methods do not aim to include downstream processes, and given a set of TFs, the expected top ontologies would revolve around transcription processes. Results We present the TFTenricher, a Python toolbox that focuses specifically at identifying gene ontology terms, cellular pathways, and diseases that are over-represented among genes downstream of user-defined sets of human TFs. We evaluated the inference of downstream gene targets with respect to false positive annotations, and found an inference based on co-expression to best predict downstream processes. Based on these downstream genes, the TFTenricher uses some of the most common databases for gene functionalities, including GO, KEGG and Reactome, to calculate functional enrichments. By applying the TFTenricher to differential expression of TFs in 21 diseases, we found significant terms associated with disease mechanism, while the gene set enrichment analysis on the same dataset predominantly identified processes related to transcription. Conclusions and availability The TFTenricher package enables users to search for biological context in any set of TFs and their downstream genes. The TFTenricher is available as a Python 3 toolbox at https://github.com/rasma774/Tftenricher, under a GNU GPL license and with minimal dependencies.

Abstract MP256: CCCTC-binding Factor Site Mutation In Sirt1 Promoter Reduces Systolic Cardiac Function In Mice

Regulation of the geroprotective histone-deacetylase SIRT1 is an important physiological strategy to protect against cardiovascular disease. SIRT1 activity regulates the oxidative stress response, DNA damage pathways, cell death, and cardioprotective SIRT1 levels decreases with age. Based on this and GWAS studies implicating misregulation linked to myocardial infarction risk, we hypothesized that disrupting proximal promoter regulation of SIRT1 causes cardiac stress. Focusing on Single Nucleotide Polymorphisms (SNPs) in the SIRT1 promoter, we used reporter gene assays to test if the transcriptional regulation of SIRT1 after oxidative stress is altered by the SNPs. Identifying a candidate A/G polymorphism at the -92 position in the promoter of SIRT1 , we show that the presence of the minority allele causes a disrupted epigenetic activation of SIRT1 . In model cell systems, binding of CCCTC-binding factor (CTCF) in the promoter of SIRT1 is reduced after oxidative stress in cells carrying the minority allele, correlating with a lack of activation of stress-protective SIRT1 expression in iPSC-derived cardiomyocytes. To investigate the physiological consequences of this mutation, we used Crispr/Cas9 to generate global Sirt1 promoter CTCF site mutant (Sirt1-mut) mice. Echocardiography in 7-month-old male mice shows reduced FS% (control 31.1±1.5%, Sirt1-mut 20.9±0.8%, mean±sem, p<0.0001, n=10-12 each), as well as increased LVIDs and decreased LVPWd wall dimensions in Sirt1-mut mice. RNA-seq on left ventricular cardiac tissue of 8-month-old control and Sirt1-mut mice identified 130 genes that are differentially regulated. Gene Ontology term enrichment analysis finds the differentially expressed genes are in pathways linked to regulation in response to reactive oxygen species and oxidative stress. In conclusion, we show that a mutation in the Sirt1 promoter critical for oxidative stress responses leads to systolic cardiac dysfunction. The transcriptional regulation of cardioprotective SIRT1 is an important and hitherto overlooked factor in the pathophysiology of heart failure.

Using Cell Type–Specific Genes to Identify Cell-Type Transitions Between Different in vitro Culture Conditions

In vitro differentiation or expansion of stem and progenitor cells under chemical stimulation or genetic manipulation is used for understanding the molecular mechanisms of cell differentiation and self-renewal. However, concerns around the cell identity of in vitro–cultured cells exist. Bioinformatics methods, which rely heavily on signatures of cell types, have been developed to estimate cell types in bulk samples. The Tabula Muris Senis project provides an important basis for the comprehensive identification of signatures for different cell types. Here, we identified 46 cell type–specific (CTS) gene clusters for 83 mouse cell types. We conducted Gene Ontology term enrichment analysis on the gene clusters and revealed the specific functions of the relevant cell types. Next, we proposed a simple method, named CTSFinder, to identify different cell types between bulk RNA-Seq samples using the 46 CTS gene clusters. We applied CTSFinder on bulk RNA-Seq data from 17 organs and from developing mouse liver over different stages. We successfully identified the specific cell types between organs and captured the dynamics of different cell types during liver development. We applied CTSFinder with bulk RNA-Seq data from a growth factor–induced neural progenitor cell culture system and identified the dynamics of brain immune cells and nonimmune cells during the long-time cell culture. We also applied CTSFinder with bulk RNA-Seq data from reprogramming induced pluripotent stem cells and identified the stage when those cells were massively induced. Finally, we applied CTSFinder with bulk RNA-Seq data from in vivo and in vitro developing mouse retina and captured the dynamics of different cell types in the two development systems. The CTS gene clusters and CTSFinder method could thus serve as promising toolkits for assessing the cell identity of in vitro culture systems.

Web crawling and mRNA sequencing analyze mechanisms of photobiomodulation

Background Photobiomodulation (PBM) is praised as a promising physical therapy, which has many advantages, such as noninvasive, painless. However, the mechanisms are not fully elucidated. Methods Using web crawling, mRNA sequence and bioinformatics analysis to select genes, functional annotation, and mechanisms. The expressions of inflammatory cytokines were measured using RT-qPCR. Results A total of 146 human genes and 57 pathways were identified about PBM. The 630nm LED-stimulated-MH7A cells were sequenced for further analyzing the mechanism of PBM. 2950 differentially expressed genes were identified, and the gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. The 12 pathways were matched with the KEGG results of PBM and MH7A cells. A protein-protein interaction network was performed among genes in 12 pathways, and 10 outstanding proteins were identified. Importantly, the 9 genes were predicted with potential research value.And we also demonstrated that expression of inflammatory factors (IL-6, IL-1β, IL-8, and MMP-3) was reduced; meanwhile, the expression of anti-inflammatory factor IL-10 was promoted after 630nm LED. In conclusion, using web crawling, bioinformatics analysis, and mRNA sequence, we obtained 9 key genes and 10 important pathways about PBM. Importantly, we demonstrated the anti-inflammatory effect of 630nm LED red light by RT-qPCR.