Visualization and analysis of RNA-Seq assembly graphs

Dual fluorescence images, transport pathway, and blood-brain barrier penetration of B-Met-W/O/W SE

Borneol is an aromatic traditional Chinese medicine that can improve the permeability of the blood-brain barrier (BBB), enter the brain, and promote the brain tissue distribution of many other drugs. In our previous study, borneol-metformin hydrochloride water/oil/water composite submicron emulsion (B-Met-W/O/W SE) was prepared using borneol and SE to promote BBB penetration, which significantly increased the brain distribution of Met. However, the dynamic images, transport pathway (uptake and efflux), promotion of BBB permeability, and mechanisms of B-Met-W/O/W SE before and after entering cells have not been clarified. In this study, rhodamine B and coumarin-6 were selected as water-soluble and oil-soluble fluorescent probes to prepare B-Met-W/O/W dual-fluorescent SE (B-Met-W/O/W DFSE) with concentric circle imaging. B-Met-W/O/W SE can be well taken up by brain microvascular endothelial cells (BMECs). The addition of three inhibitors (chlorpromazine hydrochloride, methyl-β-cyclodextrin, and amiloride hydrochloride) indicated that its main pathway may be clathrin-mediated and fossa protein-mediated endocytosis. Meanwhile, B-Met-W/O/W SE was obviously shown to inhibit the efflux of BMECs. Next, BMECs were cultured in the Transwell chamber to establish a BBB model, and Western blot was employed to detect the protein expressions of Occludin, Zona Occludens 1 (ZO-1), and p-glycoprotein (P-gp) after B-Met-W/O/W SE treatment. The results showed that B-Met-W/O/W SE significantly down-regulated the expression of Occludin, ZO-1, and P-gp, which increased the permeability of BBB, promoted drug entry into the brain through BBB, and inhibited BBB efflux. Furthermore, 11 differentially expressed genes (DEGs) and 7 related signaling pathways in BMECs treated with B-W/O/W SE were detected by transcriptome sequencing and verified by quantitative real-time polymerase chain reaction (qRT-PCR). These results provide a scientific experimental basis for the dynamic monitoring, transmembrane transport mode, and permeation-promoting mechanism of B-Met-W/O/W SE as a new brain-targeting drug delivery system.

Graphia: A platform for the graph-based visualisation and analysis of high dimensional data

Graphia is an open-source platform created for the graph-based analysis of the huge amounts of quantitative and qualitative data currently being generated from the study of genomes, genes, proteins metabolites and cells. Core to Graphia’s functionality is support for the calculation of correlation matrices from any tabular matrix of continuous or discrete values, whereupon the software is designed to rapidly visualise the often very large graphs that result in 2D or 3D space. Following graph construction, an extensive range of measurement algorithms, routines for graph transformation, and options for the visualisation of node and edge attributes are available, for graph exploration and analysis. Combined, these provide a powerful solution for the interpretation of high-dimensional data from many sources, or data already in the form of a network or equivalent adjacency matrix. Several use cases of Graphia are described, to showcase its wide range of applications in the analysis biological data. Graphia runs on all major desktop operating systems, is extensible through the deployment of plugins and is freely available to download from https://graphia.app/.

Graphia is a new visual analytics platform specifically created for the network-based analysis of large and complex data, such as that generated in huge amounts by modern biological analyses. It works in a data agnostic, hypothesis-free manner to generate correlation networks from any table of numerical or discrete values, thereafter providing a means to rapidly visualise the often very large networks that result, in either 2D or 3D space. Following network construction, the tool offers an extensive range of analysis algorithms, routines for network transformation, and options for the visualisation of metadata. This provides a powerful analysis solution for the exploration and interpretation of high-dimensional data from any source, as well as any data already defined as a network. Several use cases of Graphia are described to showcase its wide range of applications in the analysis biological data. Graphia is open source and free to all.

Transcriptome sequencing of black and white hair follicles in the giant panda

With the completion of the draft assembly of the giant panda genome sequence, RNA sequencing technology has been widely used in genetic research on giant pandas. We used RNA-seq to examine black and white hair follicle samples from adult pandas. By comparison with the giant panda genome, 75 963 SNP loci were labeled, 2 426 differentially expressed genes were identified, and 2 029 new genes were discovered, among which 631 were functionally annotated. A cluster analysis of the differentially expressed genes showed that they were mainly related to the Wnt signaling pathway, ECM-receptor interaction, the p53 signaling pathway and ribosome processing. The enrichment results showed that there were significant differences in the regulatory networks of hair follicles with different colors during the transitional stage of hair follicle resting growth, which may play a regulatory role in melanin synthesis during growth. In conclusion, our results provide new insights and more data support for research on the color formation in giant pandas. This article is protected by copyright. All rights reserved.