In recent years, the emphasis of scientific inquiry has shifted from whole-genome analyses to an understanding of cellular responses specific to tissue, developmental stage or environmental conditions. One of the central mechanisms underlying the diversity and adaptability of the contextual responses is alternative splicing (AS). It enables a single gene to encode multiple isoforms with distinct biological functions. However, to date, the functions of the vast majority of differentially spliced protein isoforms are not known. Integration of genomic, proteomic, functional, phenotypic and contextual information is essential for supporting isoform-based modeling and analysis. Such integrative proteogenomics approaches promise to provide insights into the functions of the alternatively spliced protein isoforms and provide high-confidence hypotheses to be validated experimentally. This manuscript provides a survey of the public databases supporting isoform-based biology. It also presents an overview of the potential global impact of AS on the human canonical gene functions, molecular interactions and cellular pathways.

Next generation sequencing (NGS) technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the "Globus Genomics" system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-endNGS analysis requirements. The Globus Genomics system is built on Amazon 's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research.

The relationship between retinal disease, diet, and the gut microbiome has shown increasing importance over recent years. In particular, high-fat diets (HFDs) are associated with development and progression of several retinal diseases, including age-related macular degeneration (AMD) and diabetic retinopathy. However, the complex, overlapping interactions between diet, gut microbiome, and retinal homeostasis are poorly understood. Using high-throughput RNA-sequencing (RNA-seq) of whole retinas, we compare the retinal transcriptome from germ-free (GF) mice on a regular diet (ND) and HFD to investigate transcriptomic changes without influence of gut microbiome. After correction of raw data, 53 differentially expressed genes (DEGs) were identified, of which 19 were upregulated and 34 were downregulated in GF-HFD mice. Key genes involved in retinal inflammation, angiogenesis, and RPE function were identified. Enrichment analysis revealed that the top 3 biological processes affected were regulation of blood vessel diameter, inflammatory response, and negative regulation of endopeptidase. Molecular functions altered include endopeptidase inhibitor activity, protease binding, and cysteine-type endopeptidase inhibitor activity. Human and mouse pathway analysis revealed that the complement and coagulation cascades are significantly affected by HFD. This study demonstrates novel data that diet can directly modulate the retinal transcriptome independently of the gut microbiome.

Background: Cavernous angiomas (CAs) affect 0.5% of the population, predisposing to serious neurologic sequelae from brain bleeding. A leaky gut epithelium associated with a permissive gut microbiome, was identified in patients who develop CAs, favoring lipid polysaccharide producing bacterial species. Micro-ribonucleic acids along with plasma levels of proteins reflecting angiogenesis and inflammation were also previously correlated with CA and CA with symptomatic hemorrhage. Methods: The plasma metabolome of CA patients and CA patients with symptomatic hemorrhage was assessed using liquid-chromatography mass spectrometry. Differential metabolites were identified using partial least squares-discriminant analysis (p < 0.05, FDR corrected). Interactions between these metabolites and the previously established CA transcriptome, microbiome, and differential proteins were queried for mechanistic relevance. Differential metabolites in CA patients with symptomatic hemorrhage were then validated in an independent, propensity matched cohort. A machine learning-implemented, Bayesian approach was used to integrate proteins, micro-RNAs and metabolites to develop a diagnostic model for CA patients with symptomatic hemorrhage. Results: Here we identify plasma metabolites, including cholic acid and hypoxanthine distinguishing CA patients, while arachidonic and linoleic acids distinguish those with symptomatic hemorrhage. Plasma metabolites are linked to the permissive microbiome genes, and to previously implicated disease mechanisms. The metabolites distinguishing CA with symptomatic hemorrhage are validated in an independent propensity-matched cohort, and their integration, along with levels of circulating miRNAs, enhance the performance of plasma protein biomarkers (up to 85% sensitivity and 80% specificity). Conclusions: Plasma metabolites reflect CAs and their hemorrhagic activity. A model of their multiomic integration is applicable to other pathologies.

Relationships between retinal disease, diet, and the gut microbiome have started to emerge. In particular, high-fat diets (HFDs) are associated with the prevalence and progression of several retinal diseases, including age-related macular degeneration (AMD) and diabetic retinopathy (DR). These effects are thought to be partly mediated by the gut microbiome, which modulates interactions between diet and host homeostasis. Nevertheless, the effects of HFDs on the retina and adjacent retinal pigment epithelium (RPE) and choroid at the transcriptional level, independent of gut microbiota, are not well-understood. In this study, we performed the high-throughput RNA-sequencing of germ-free (GF) mice to explore the transcriptional changes induced by HFD in the RPE/choroid. After filtering and cleaning the data, 649 differentially expressed genes (DEGs) were identified, with 616 genes transcriptionally upregulated and 33 genes downregulated by HFD compared to a normal diet (ND). Enrichment analysis for gene ontology (GO) using the DEGs was performed to analyze over-represented biological processes in the RPE/choroid of GF-HFD mice relative to GF-ND mice. GO analysis revealed the upregulation of processes related to angiogenesis, immune response, and the inflammatory response. Additionally, molecular functions that were altered involved extracellular matrix (ECM) binding, ECM structural constituents, and heparin binding. This study demonstrates novel data showing that HFDs can alter RPE/choroid tissue transcription in the absence of the gut microbiome.

Background and aims: Connections between the gut microbiome and retinal diseases such as age-related macular degeneration (AMD), diabetic retinopathy (DR), retinopathy of prematurity (ROP), and primary open-angle glaucoma (POAG) are recently being established. Communication between the gut microbiome and retina, referred to as the gut-retina axis, has been proposed; however, the biologic pathways and mediators involved in the interactions have not yet been elucidated. Using high-throughput RNA sequencing (RNA-seq) of whole retinas, we compare the retinal transcriptome from germ-free (GF) and specific pathogen-free (SPF) mice to investigate the effects of the gut-microbiome on both retinal gene expression and biologic pathways. Methods: RNA was extracted from whole retinas of GF and SPF mice (four animals per group) and cDNA libraries were created. RNA-seq was performed on NovaSEQ6000 using the paired-end method. After preprocessing the RNA-seq data, gene expression value was calculated by count per million (CPM). The differentially expressed genes (DEGs) were identified with the limma package from Bioconductor on the expression data. Functional enrichment and protein-protein interaction STRING protein-protein association network analyses were created for the differentially expressed genes (DEGs). Results: RNA-sequencing reveals a cohort of 396 DEGs, of which, 173 are upregulated and 223 are downregulated in GF mouse retina. Enrichment analysis reveals that the DEGs are involved in glucocorticoid effects, transcription factor binding, cytoskeletal stability, lipid metabolism, and mitogen-activated protein kinase (MAPK). Multiple biologic pathways, including obesity/metabolic syndrome, longevity, insulin-like growth factor (IGF) signaling pathway, vascular endothelial growth factor (VEGF), hypoxia-inducible factor ( HIF ) -1 transcription pathway, and 5’ AMP-activated protein kinas e (AMPK) signaling pathway are affected in the GF retinas. PPARG1a (PGC1a) gene is involved in 13 of the 35 significantly modulated pathways. Proteins with the greatest number of interactions in the PPI are E1A binding protein P300(EP300), forkhead box O3(FOXO3), and PGC1a. Conclusions: To our knowledge, this is the first study demonstrating the involvement of the gut microbiome in driving the retinal transcriptome, providing evidence for the presence of a gut-retina axis. Future studies are needed to define the precise role of the gut-retina axis in the pathogenesis of retinal diseases.