Bioinformatics analysis to identify the differentially expressed genes of glaucoma

A ZFP42/MARK2 regulatory network reduces the damage of retinal ganglion cells in glaucoma: a study based on GEO dataset and in vitro experiments

Glaucoma is a common disorder in which the death of retinal ganglion cells (RGCs) results in a progressive loss of sight, even blindness. This study was performed to reveal the key molecular mechanism of RGC damage in glaucoma based on the Gene Expression Omnibus database. Glaucoma-related microarray datasets were identified, followed by collection of differentially expressed genes (DEGs) with the key genes discovered by weighted gene co-expression network analysis. Through LASSO regression analysis, candidate genes involved in the pathogenesis of glaucoma were identified with their accuracy evaluated by receiver operating characteristic curve analysis. The glaucoma-specific transcriptional regulatory network was constructed to determine the key transcription factor regulatory axis. Then, in vitro cell models were established using H₂O₂ for further verifying the regulatory role of identified ZFP42/MARK2 axis in RGC damage in glaucoma. Differential analysis of GSE27276, GSE45570, and GSE101727 microarray datasets yielded 165 DEGs, and 22 key genes were identified following. Then, 9 candidate genes involved in the pathogenesis of glaucoma was collected and the key ZFP42/MARK2 regulatory axis was found. In vitro cell experiments further confirmed that ZFP42 and MARK2 were down-regulated in RGCs treated with H₂O₂. In addition, overexpression of ZFP42 increased the expression of MARK2 to increase RGC cell viability, and reduce cell apoptosis and ROS levels, while silencing MARK2 could reverse the protective effect of ZFP42. We confirmed that ZFP42 reduced the damage of RGCs in glaucoma by up-regulating the expression of MARK2.

Profiles of microRNA in aqueous humor of normal tension glaucoma patients using RNA sequencing

We aimed to identify and compare microRNAs (miRNAs) from individual aqueous humor samples between normal-tension glaucoma (NTG) patients and normal controls. Aqueous humor (80 to 120 µl) was collected before cataract surgery. Six stable NTG patients and seven age-matched controls were included in the final analysis. RNA sequencing was conducted for RNA samples extracted from the 13 aqueous humor samples, and bioinformatics analysis was employed for the miRNA targets and related pathways. Two hundred and twenty-eight discrete miRNAs were detected in the aqueous humor and consistently expressed in all samples. Eight significantly upregulated miRNAs were found in the NTG patients compared to the controls (fold-change > 2, p < 0.05). They were hsa-let-7a-5p, hsa-let-7c-5p, hsa-let-7f-5p, hsa-miR-192-5p, hsa-miR-10a-5p, hsa-miR-10b-5p, hsa-miR-375, and hsa-miR-143-3p. These miRNAs were predicted to be associated with the biological processes of apoptosis, autophagy, neurogenesis, and aging in the gene ontology categories. The related Kyoto encyclopedia of genes and genomes pathways were extracellular matrix-receptor interaction, mucin-type O-glycan biosynthesis, biotin metabolism, and signaling pathways regulating the pluripotency of stem cells. The differentially expressed miRNA in the NTG samples compared to the controls suggest the possible roles of miRNA in the pathogenesis of NTG. The underlying miRNA-associated pathways further imply novel targets for the pathogenesis of NTG.

New insights into the Manila clam and PAMPs interaction based on RNA-seq analysis of clam through in vitro challenges with LPS, PGN, and poly(I:C)

Background

Manila clam (Ruditapes philippinarum) is a worldwide commercially important marine bivalve species. In recent years, however, microbial diseases caused high economic losses and have received increasing attention. To understand the molecular basis of the immune response to pathogen-associated molecular patterns (PAMPs) in R. philippinarum, transcriptome libraries of clam hepatopancreas were constructed at 24 h post-injection with Lipopolysaccharide (LPS), peptidoglycan (PGN), and polyinosinic-polycytidylic acid (poly(I:C)) and phosphate-buffered saline (PBS) control by using RNA sequencing technology (RNA-seq).

Results

A total of 832, 839, and 188 differentially expressed genes (DEGs) were found in LPS, PGN, and poly(I:C) challenge group compared with PBS control, respectively. Several immune-related genes and pathways were activated in response to the different PAMPs, suggesting these genes and pathways might specifically participate in the immune response to pathogens. Besides, the analyses provided useful complementary data to compare different PAMPs challenges in vivo. Functional enrichment analysis of DEGs demonstrated that PAMPs responsive signal pathways were related to apoptosis, signal transduction, immune system, and signaling molecules and interaction. Several shared or specific DEGs response to different PAMPs were revealed in R. philippinarum, including pattern recognition receptors (PRRs), antimicrobial peptides (AMPs), interferon-induced proteins (IFI), and some other immune-related genes were found in the present work.

Conclusions

This is the first study employing high throughput transcriptomic sequencing to provide valuable genomic resources and investigate Manila clam response to different PAMPs through in vivo challenges with LPS, PGN, and poly(I:C). The results obtained here provide new insights to understanding the immune characteristics of R. philippinarum response to different PAMPs. This information is critical to elucidate the molecular basis of R. philippinarum response to different pathogens invasion, which potentially can be used to develop effective control strategies for different pathogens.

Microarray Missing Value Imputation: A Regularized Local Learning Method

Microarray experiments on gene expression inevitably generate missing values, which impedes further downstream biological analysis. Therefore, it is key to estimate the missing values accurately. Most of the existing imputation methods tend to suffer from the over-fitting problem. In this study, we propose two regularized local learning methods for microarray missing value imputation. Motivated by the grouping effect of L2 regularization, after selecting the target gene, we train an L2 Regularized Local Least Squares imputation model (RLLSimpute_L2) on the target gene and its neighbors to estimate the missing values of the target gene. Furthermore, RLLSimpute_L2 imputes the missing values in an ascending order based on the associated missing rate with each target gene. This contributes to fully utilizing the previously estimated values. Besides L2, we further explore L1 regularization and propose an L1 Regularized Local Least Squares imputation model (RLLSimpute_L1). To evaluate their effectiveness, we conducted extensive experimental studies on six benchmark datasets covering both time series and non-time series cases. Nine state-of-the-art imputation methods are compared with RLLSimpute_L2 and RLLSimpute_L1 in terms of three performance metrics. The comparative experimental results indicate that RLLSimpute_L2 outperforms its competitors by achieving smaller imputation errors and better structure preservation of differentially expressed genes.

Increased intraocular pressure alters the cellular distribution of HuR protein in retinal ganglion cells - A possible sign of endogenous neuroprotection failure

The RNA-binding protein, HuR, modulates mRNA processing and gene expression of several stress response proteins i.e. Hsp70 and p53 that have been postulated to be involved in the pathogenesis of glaucoma, a chronic optic neuropathy leading to irreversible blindness. We evaluated HuR protein expression in retinas and optic nerves of glaucomatous rats and human primary open angle glaucoma patients and its possible impact on stress response mechanisms. We found that the cytoplasmic content of HuR was reduced more extensively in glaucomatous retinas than in optic nerves and this was linked with a declined cytoplasmic Hsp70 level and p53 nuclear translocation. In the optic nerve, the p53 content was decreased as a feature of reactive gliosis. Based on our findings, we conclude that the alteration in the HuR content, observed both in rat glaucoma model and human glaucoma samples, affects post-transcriptionally the expression of genes crucial for maintaining cell homeostasis; therefore, we postulate that HuR may be involved in the pathogenesis of glaucoma.

Integrated microarray analysis provided novel insights to the pathogenesis of glaucoma

Glaucoma is characterized as a visual field defect, which is the second most common cause of blindness. The present study performed an integrated analysis of microarray studies of glaucoma derived from Gene Expression Omnibus (GEO). Following the identification of the differentially expressed genes (DEGs) in glaucoma compared with normal control (NC) tissues, the functional annotation, glaucoma-specific protein-protein interaction (PPI) network and transcriptional regulatory network constructions were performed. The acute intraocular pressure (IOP) elevation rat models were established and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed for DEGs expression confirmation. Three datasets were downloaded from GEO. A total of 97 DEGs, 82 upregulated and 15 downregulated were identified in glaucoma compared with NC groups with false discovery rate <0.05. Response to virus and immune response were two significantly enriched GO terms in glaucoma. Valine, leucine and isoleucine degradation was a significantly enriched pathway of DEGs in glaucoma. According to the PPI network, HDAC1, HBN, UBR4 and PDK1 were hub proteins in glaucoma. FOXD3, HNF-4 and AP-1 were the three transcription factors (TFs) derived from top 10 TFs which covered the majority of downstream DEGs in glaucoma. Based on the RT-qPCR results, the expression levels of 3 DEGs, raftlin, lipid raft linker 1 (RFTN1), PBX homeobox 1 (PBX1), HDAC1 were significantly upregulated and the expression of GEM was significantly downregulated in acute IOP elevation rat model at the first and fifth day. These four DEGs had the same expression pattern with our integrated analysis. Therefore, the current study concluded that 6 DEGs, including HEPH, SELENBP1, RFTN1, ID1, HDAC-1 and PBX1 and three TFs, including FOXD3, HNF-4 and AP-1 may be involved with the pathogenesis of glaucoma. The findings of the current study may improve diagnosis and drug design for glaucoma.

Circular RNA Profiling and Bioinformatic Modeling Identify Its Regulatory Role in Hepatic Steatosis

Circular RNAs (circRNAs) exhibit a wide range of physiological and pathological activities. To uncover their role in hepatic steatosis, we investigated the expression profile of circRNAs in HepG2-based hepatic steatosis induced by high-fat stimulation. Differentially expressed circRNAs were subjected to validation using QPCR and functional analyses using principal component analysis, hierarchical clustering, target prediction, gene ontology (GO), and pathway annotation, respectively. Bioinformatic integration established the circRNA-miRNA-mRNA regulatory network so as to identify the mechanisms underlying circRNAs' metabolic effect. Here we reported that hepatic steatosis was associated with a total of 357 circRNAs. Enrichment of transcription-related GOs, especially GO: 0006355, GO: 004589, GO: 0045944, GO: 0045892, and GO: 0000122, demonstrated their specific actions in transcriptional regulation. Lipin 1 (LPIN1) was recognized to mediate the transcriptional regulatory effect of circRNAs on metabolic pathways. circRNA-miRNA-mRNA network further identified the signaling cascade of circRNA_021412/miR-1972/LPIN1, which was characterized by decreased level of circRNA_021412 and miR-1972-based inhibition of LPIN1. LPIN1-induced downregulation of long chain acyl-CoA synthetases (ACSLs) expression finally resulted in the hepatosteatosis. These findings identify circRNAs to be important regulators of hepatic steatosis. Transcription-dependent modulation of metabolic pathways may underlie their effects, partially by the circRNA_021412/miR-1972/LPIN1 signaling.