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. 2016 Dec 26;2016:baw146.
doi: 10.1093/database/baw146. Print 2016.

TBro: Visualization and Management of De Novo Transcriptomes

Free PMC article

TBro: Visualization and Management of De Novo Transcriptomes

Markus J Ankenbrand et al. Database (Oxford). .
Free PMC article


RNA sequencing (RNA-seq) has become a powerful tool to understand molecular mechanisms and/or developmental programs. It provides a fast, reliable and cost-effective method to access sets of expressed elements in a qualitative and quantitative manner. Especially for non-model organisms and in absence of a reference genome, RNA-seq data is used to reconstruct and quantify transcriptomes at the same time. Even SNPs, InDels, and alternative splicing events are predicted directly from the data without having a reference genome at hand. A key challenge, especially for non-computational personnal, is the management of the resulting datasets, consisting of different data types and formats. Here, we present TBro, a flexible de novo transcriptome browser, tackling this challenge. TBro aggregates sequences, their annotation, expression levels as well as differential testing results. It provides an easy-to-use interface to mine the aggregated data and generate publication-ready visualizations. Additionally, it supports users with an intuitive cart system, that helps collecting and analysing biological meaningful sets of transcripts. TBro's modular architecture allows easy extension of its functionalities in the future. Especially, the integration of new data types such as proteomic quantifications or array-based gene expression data is straightforward. Thus, TBro is a fully featured yet flexible transcriptome browser that supports approaching complex biological questions and enhances collaboration of numerous researchers. DATABASE URL: :


Figure 1.
Figure 1.
(A) TBro’s architecture is divided into three sections. The TBro environment builds the backbone with the central web server. The web server is connected to the database server and the session server for caching. The analysis environment is used to perform computationally intensive tasks. It is divided into a server and an arbitrary number of workers that can run on heterogeneous systems. The user environment consists of the client (a web browser) which is used to interact with a running instance of TBro and the command line tools which are used to import and manage data by a qualified administrator. (B) A typical data import hierarchically prepares and adds all transcriptomic data sets. Tasks performed by TBro-db are coloured in grey while tasks performed with TBro-import are coloured in white. The complete workflow tightly builds on the reference Chado schema to ease maintenance and usability.
Figure 2.
Figure 2.
(A) Z-transformed expression heatmap of a cart containing putative members of the hydrolytic cocktails secreted by Venus flytrap during its hunting cycle. Two unigenes are being expressed in a non-stimulated gland specific manner. (B) MA plot for the same cart based on DE testing results from DESeq. The plot indicates that most members of the hydrolytic cocktail are being highly expressed compared to the majority of the unigenes. (C) Triangular visualization of the DE testing results for an individual gene (Nepenthesis-1). (D) Simple expression barplot of the Nepenthesin-1 gene with two isoforms showing different expression patterns. All plots were generated directly in TBro. Z-transformation, scaling and layouts were adjusted using functions from CanvasXpress context menu directly in the browser.

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    1. Mortazavi A., Williams B.A., McCue K. et al. (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods, 5, 621–628. - PubMed
    1. Wang Z., Gerstein M., Snyder M. (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet., 10, 57–63. - PMC - PubMed
    1. Trapnell C., Williams B.A., Pertea G. et al. (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol., 28, 511–515. - PMC - PubMed
    1. Garg R., Patel R.K., Tyagi A.K. et al. (2011) De novo assembly of chickpea transcriptome using short reads for gene discovery and marker identification. DNA Res., 18, 53–63. - PMC - PubMed
    1. Wenping H., Yuan Z., Jie S. et al. (2011) De novo transcriptome sequencing in Salvia miltiorrhiza to identify genes involved in the biosynthesis of active ingredients. Genomics, 98, 272–279. - PubMed

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