fRNAkenseq: a fully powered-by-CyVerse cloud integrated RNA-sequencing analysis tool

Critical Differential Expression Assessment for Individual Bulk RNA-Seq Projects

Finding the right balance of quality and quantity can be important, and it is essential that project quality does not drop below the level where important main conclusions are missed or misstated. We use knock-out and over-expression studies as a simplification to test recovery of a known causal gene in RNA-Seq cell line experiments. When single-end RNA-Seq reads are aligned with STAR and quantified with htseq-count, we found potential value in testing the use of the Generalized Linear Model (GLM) implementation of edgeR with robust dispersion estimation more frequently for either single-variate or multi-variate 2-group comparisons (with the possibility of defining criteria less stringent than |fold-change| > 1.5 and FDR < 0.05). When considering a limited number of patient sample comparisons with larger sample size, there might be some decreased variability between methods (except for DESeq1). However, at the same time, the ranking of the gene identified using immunohistochemistry (for ER/PR/HER2 in breast cancer samples from The Cancer Genome Atlas) showed as possible shift in performance compared to the cell line comparisons, potentially highlighting utility for standard statistical tests and/or limma-based analysis with larger sample sizes. If this continues to be true in additional studies and comparisons, then that could be consistent with the possibility that it may be important to allocate time for potential methods troubleshooting for genomics projects. Analysis of public data presented in this study does not consider all experimental designs, and presentation of downstream analysis is limited. So, any estimate from this simplification would be an underestimation of the true need for some methods testing for every project. Additionally, this set of independent cell line experiments has a limitation in being able to determine the frequency of missing a highly important gene if the problem is rare (such as 10% or lower). For example, if there was an assumption that only one method can be tested for "initial" analysis, then it is not completely clear to the extent that using edgeR-robust might perform better than DESeq2 in the cell line experiments. Importantly, we do not wish to cause undue concern, and we believe that it should often be possible to define a gene expression differential expression workflow that is suitable for some purposes for many samples. Nevertheless, at the same time, we provide a variety of measures that we believe emphasize the need to critically assess every individual project and maximize confidence in published results.

BioViz Connect: Web Application Linking CyVerse Cloud Resources to Genomic Visualization in the Integrated Genome Browser

Genomics researchers do better work when they can interactively explore and visualize data. Due to the vast size of experimental datasets, researchers are increasingly using powerful, cloud-based systems to process and analyze data. These remote systems, called science gateways, offer user-friendly, Web-based access to high performance computing and storage resources, but typically lack interactive visualization capability. In this paper, we present BioViz Connect, a middleware Web application that links CyVerse science gateway resources to the Integrated Genome Browser (IGB), a highly interactive native application implemented in Java that runs on the user's personal computer. Using BioViz Connect, users can 1) stream data from the CyVerse data store into IGB for visualization, 2) improve the IGB user experience for themselves and others by adding IGB specific metadata to CyVerse data files, including genome version and track appearance, and 3) run compute-intensive visual analytics functions on CyVerse infrastructure to create new datasets for visualization in IGB or other applications. To demonstrate how BioViz Connect facilitates interactive data visualization, we describe an example RNA-Seq data analysis investigating how heat and desiccation stresses affect gene expression in the model plant Arabidopsis thaliana. The RNA-Seq use case illustrates how interactive visualization with IGB can help a user identify problematic experimental samples, sanity-check results using a positive control, and create new data files for interactive visualization in IGB (or other tools) using a Docker image deployed to CyVerse via the Terrain API. Lastly, we discuss limitations of the technologies used and suggest opportunities for future work. BioViz Connect is available from https://bioviz.org.

Multiplexed Molecular Imaging Strategy Integrated with RNA Sequencing in the Assessment of the Therapeutic Effect of Wharton's Jelly Mesenchymal Stem Cell-Derived Extracellular Vesicles for Osteoporosis

Introduction

Osteoporosis is a result of an imbalance in bone remodeling. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) have been considered as a potentially promising treatment for osteoporosis. However, the therapeutic effect, genetic alterations, and in vivo behavior of exogenous EVs for osteoporosis in mice models remain poorly understood.

Methods

A multiplexed molecular imaging strategy was constructed by micro-positron emission tomography (µPET)/computed tomography (CT), µCT, and optical imaging modality which reflected the osteoblastic activity, microstructure, and in vivo behavior of EVs, respectively. RNA sequencing was used to analyze the cargo of EVs, and the bone tissues of ovariectomized (OVX) mice post EV treatment.

Results

The result of [¹⁸F]NaF µPET showed an increase in osteoblastic activity in the distal femur of EV-treated mice, and the bone structural parameters derived from µCT were also improved. In terms of in vivo behavior of exogenous EVs, fluorescent dye-labeled EVs could target the distal femur of mice, whereas the uptakes of bone tissues were not significantly different between OVX mice and healthy mice. RNA sequencing demonstrated upregulation of ECM-related genes, which might associate with the PI3K/AKT signaling pathway, in line with the results of microRNA analysis showing that mir-21, mir-29, mir-221, and let-7a were enriched in Wharton’s jelly-MSC-EVs and correlated to the BMP and PI3K/AKT signaling pathways.

Conclusion

The therapeutic effect of exogenous WJ-MSC-EVs in the treatment of osteoporosis was successfully assessed by a multiplexed molecular imaging strategy. The RNA sequencing demonstrated the possible molecular targets in the regulation of bone remodeling. The results highlight the novelty of diagnostic and therapeutic strategies of EV-based treatment for osteoporosis.