expVIP: a Customizable RNA-seq Data Analysis and Visualization Platform

Abstract

The majority of transcriptome sequencing (RNA-seq) expression studies in plants remain underutilized and inaccessible due to the use of disparate transcriptome references and the lack of skills and resources to analyze and visualize these data. We have developed expVIP, an expression visualization and integration platform, which allows easy analysis of RNA-seq data combined with an intuitive and interactive interface. Users can analyze public and user-specified data sets with minimal bioinformatics knowledge using the expVIP virtual machine. This generates a custom Web browser to visualize, sort, and filter the RNA-seq data and provides outputs for differential gene expression analysis. We demonstrate expVIP's suitability for polyploid crops and evaluate its performance across a range of biologically relevant scenarios. To exemplify its use in crop research, we developed a flexible wheat (Triticum aestivum) expression browser (www.wheat-expression.com) that can be expanded with user-generated data in a local virtual machine environment. The open-access expVIP platform will facilitate the analysis of gene expression data from a wide variety of species by enabling the easy integration, visualization, and comparison of RNA-seq data across experiments.The global demand for staple crops is predicted to double by 2050 (FAO, 2009;Tilman et al., 2011), which will require an annual increase in yield of approximately 2.4% (Ray et al., 2013). However, currently, yields of the major crops maize (Zea mays), rice (Oryza sativa), wheat (Triticum aestivum), and soybean (Glycine max) are increasing only at 1.6%, 1%, 0.9%, and 1.3% per year, respectively (Ray et al., 2013). The advent of the genomics era represents a great opportunity to accelerate the pace of yield increase in staple crops, for example, by facilitating novel breeding strategies (Heffner et al., 2009) and providing unprecedented numbers of genetic markers (Bevan and Uauy, 2013). In particular, transcriptome sequencing (RNA-seq) is a widely adopted genomics approach in crops due to its relatively low cost (Wang et al., 2009), its suitability for nonmodel organisms (Ekblom and Galindo, 2011), and the multiple downstream applications of the data generated. These features have driven the generation of a wealth of expression data with over 9,000 RNAseq samples currently available at public repositories, such as the National Center for Biotechnology Information (NCBI)/ENA for the major agricultural crops (Table I).Although several public databases containing gene expression data for plant species exist (Lawrence et al., 2007;Ouyang et al., 2007;Dash et al., 2012), these resources do not make full use of the expression data available in SRAs, frequently relying on a subset of experiments or microarray data. Similarly, pipelines have been proposed to allow the reanalysis of expression data that provide useful functionality but limit the number of samples that can be analyzed (D'Antonio et al., 2015), have limited visualization outputs (Fonseca et al., 2014), or require t...

Wheat Vacuolar Iron Transporter TaVIT2 Transports Fe and Mn and Is Effective for Biofortification

“…The tree was plotted with BioNJ with the Jones-Taylor-Thornton matrix and rendered using TreeDyn 198.3. RNA-seq data were obtained from the expVIP database (Borrill et al, 2016; http://www.wheat-expression.com). Full details of the data sets used are given in Supplemental Table S2.…”

Altering expression of a vacuolar iron transporter doubles iron content in white wheat flour

“…RNA was reverse transcribed using oligo dT primer and Superscript II reverse transcriptase (ThermoFisher) according to manufacturer's instructions. Quantitative real time PCR was used to analyse expression of TaVIT2 and the housekeeping gene (HKG) Traes_4AL_8CEA69D2F, chosen because it was shown to be the most stable gene expression across grain development in over 400 RNAseq samples (Borrill et al, 2016), using primer pairs qRT-TaVIT2-F, qRT-TaVIT2-R and qRT-HKG-F, qRT-HKG-R, respectively. Samples were run in a CFX96 Real-Time System (Bio-Rad) with the following conditions: 3 min at 95°C, 35 cycles of (5 s at 95°C, 10 s at 62°C, 7 s at 72°C), melt curve of 5 s at 65°C and 5 s at 95°C.…”

“…The tree was plotted with BioNJ with the Jones-Taylor-Thornton matrix and rendered using TreeDyn 198.3. RNA-seq data was obtained from the expVIP database (Borrill et al, 2016; http://www.wheat-expression.com). Full details of the data-sets used are given in Table S2.…”

“…The gene expression profiles of TaVIT1 and TaVIT2 were queried across 418 RNA-seq samples (Borrill et al, 2016). All homoeologues of TaVIT2 were in general more highly expressed than TaVIT1 homoeologues.…”

BacHBerry: BACterial Hosts for production of Bioactive phenolics from bERRY fruits

“…Analyses of expression of these genes from different developmental stages of selected berry species were performed with the expVIP tool (Borrill et al 2016).…”