Age-related macular degeneration (AMD) is a significant cause of vision loss in the elderly. The extent to which epigenetic changes regulate AMD progression is unclear. Here we globally profile chromatin accessibility using ATAC-Seq in the retina and retinal pigmented epithelium (RPE) from AMD and control patients. Global decreases in chromatin accessibility occur in the RPE with early AMD, and in the retina of advanced disease, suggesting that dysfunction in the RPE drives disease onset. Footprints of photoreceptor and RPE-specific transcription factors are enriched in differentially accessible regions (DARs). Genes associated with DARs show altered expression in AMD. Cigarette smoke treatment of RPE cells recapitulates chromatin accessibility changes seen in AMD, providing an epigenetic link between a known risk factor for AMD and AMD pathology. Finally, overexpression of HDAC11 is partially responsible for the observed reduction in chromatin accessibility, suggesting that HDAC11 may be a potential new therapeutic target for AMD.

BackgroundNonalcoholic fatty liver disease (NAFLD) is a common liver disorder that currently lacks effective treatment. Berberine (BBR), a botanic compound isolated from traditional Chinese medicine, exhibits a potent therapeutic potential for the metabolic disease. The current study aimed to understand the mechanisms underlying the therapeutic effect of BBR in NAFLD.MethodsWe performed systematical analyses on hepatic expression profiles of mRNAs and long noncoding RNAs (lncRNAs) in a high-fat diet (HFD)-induced steatotic animal model with or without BBR treatment. The study was conducted by using the methods of bioinformatics, including hierarchical clustering, gene enrichment and gene co-expression networks analysis. The effect of BBR on the expression profile of some interesting genes was confirmed by quantitative RT-PCR and further studied in a human hepatic cell line, Huh7.ResultsWe found that a large group of genes including 881 mRNAs and 538 lncRNAs whose expression in the steatotic liver was reversed by BBR treatment, suggesting a global effect of BBR in modulating hepatic gene expression profiles. Among the BBR-regulated genes, we identified several modules and numerous significant genes that were associated with liver metabolism and NAFLD-related functions. Specifically, a conserved lncRNA, MRAK052686, was found strongly correlated with the antioxidant factor Nrf2, and both genes were down-regulated by the steatotic liver. Moreover, the reduced expression of MRAK052686 and Nrf2 was completely reversed by BBR treatment, suggesting a new mechanism accounting for the therapeutic effect of BBR.ConclusionsThe findings for the first time provide a new genetic insight into the pharmaceutical mechanism of BBR in protecting against NAFLD.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-015-0383-6) contains supplementary material, which is available to authorized users.

Co-expression analysis has been employed to predict gene function, identify functional modules, and determine tumor subtypes. Previous co-expression analysis was mainly conducted at bulk tissue level. It is unclear whether co-expression analysis at the single-cell level will provide novel insights into transcriptional regulation. Here we developed a computational approach to compare glioblastoma expression profiles at the single-cell level with those obtained from bulk tumors. We found that the co-expressed genes observed in single cells and bulk tumors have little overlap and show distinct characteristics. The co-expressed genes identified in bulk tumors tend to have similar biological functions, and are enriched for intrachromosomal interactions with synchronized promoter activity. In contrast, single-cell co-expressed genes are enriched for known protein-protein interactions, and are regulated through interchromosomal interactions. Moreover, gene members of some protein complexes are co-expressed only at the bulk level, while those of other complexes are co-expressed at both single-cell and bulk levels. Finally, we identified a set of co-expressed genes that can predict the survival of glioblastoma patients. Our study highlights that comparative analyses of single-cell and bulk gene expression profiles enable us to identify functional modules that are regulated at different levels and hold great translational potential.