Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult. In this paper, we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI), a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

Moretto, M.; Sonego, P.; Pilati, S.; Malacarne, G.; Costantini, L.; Grzeskowiak, L.S.; Bagagli, G.; Grando, M.S.; Moser, C.; Engelen, K.A. (2016). VESPUCCI: exploring patterns of gene expression in grapevine. FRONTIERS IN PLANT SCIENCE, 7 (633): 1-11. doi: 10.3389/fpls.2016.00633 handle: http://hdl.handle.net/10449/32801

VESPUCCI: exploring patterns of gene expression in grapevine

Moretto, Marco;Sonego, Paolo;Pilati, Stefania;Malacarne, Giulia;Costantini, Laura;Grzeskowiak, Lukasz Sebastian;Bagagli, Giorgia;Grando, Maria Stella;Moser, Claudio;Engelen, Kristof Arthur
2016-01-01

Abstract

Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult. In this paper, we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI), a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.
Gene expression
Grapevine
Transcriptomics
Microarray
RNA-Seq
Compendium
Espressione genica
Vite
Trascrittomica
Microarray
RNA-Seq
Compendium
Settore BIO/11 - BIOLOGIA MOLECOLARE
2016
Moretto, M.; Sonego, P.; Pilati, S.; Malacarne, G.; Costantini, L.; Grzeskowiak, L.S.; Bagagli, G.; Grando, M.S.; Moser, C.; Engelen, K.A. (2016). VESPUCCI: exploring patterns of gene expression in grapevine. FRONTIERS IN PLANT SCIENCE, 7 (633): 1-11. doi: 10.3389/fpls.2016.00633 handle: http://hdl.handle.net/10449/32801
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