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VESPUCCI: Exploring Patterns of Gene Expression in Grapevine.

Moretto M, Sonego P, Pilati S, Malacarne G, Costantini L, Grzeskowiak L, Bagagli G, Grando MS, Moser C, Engelen K - Front Plant Sci (2016)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Biology, Research and Innovation Center, Fondazione Edmund MachTrento, Italy; Department of Biology, University of PadovaPadova, Italy.

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.

No MeSH data available.


Related in: MedlinePlus

Probe expression values and correlation for cluster 170. (A) Probes expression values measured across more than 500 Nimblegen sample contrasts sorted by values. (B) Probes correlation matrix using uncentered Pearson correlation.
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Figure 2: Probe expression values and correlation for cluster 170. (A) Probes expression values measured across more than 500 Nimblegen sample contrasts sorted by values. (B) Probes correlation matrix using uncentered Pearson correlation.

Mentions: One clear–cut case to present the complexity of the issue is depicted in Figure 1. From this example is clear that each gene is actually measured on average by four probes (as expected) but, except for three probes (VitusP00165181, VitusP00165231, and VitusP00165171) all the other probes align perfectly (or near perfectly) to other genes, making impossible to distinguish one gene from another. In particular these four genes, beside being different among each other, are all annotated as Myb-related, a well-known transcription factor gene family composed by 100s of genes (Matus et al., 2008) and are positioned one after the other across chromosome 2 in a region of approximately 130 kb. This target cross-talk is corroborated by the actual probe-level intensities, which are highly correlated across all sample contrasts included in the compendium (Figure 2).


VESPUCCI: Exploring Patterns of Gene Expression in Grapevine.

Moretto M, Sonego P, Pilati S, Malacarne G, Costantini L, Grzeskowiak L, Bagagli G, Grando MS, Moser C, Engelen K - Front Plant Sci (2016)

Probe expression values and correlation for cluster 170. (A) Probes expression values measured across more than 500 Nimblegen sample contrasts sorted by values. (B) Probes correlation matrix using uncentered Pearson correlation.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862315&req=5

Figure 2: Probe expression values and correlation for cluster 170. (A) Probes expression values measured across more than 500 Nimblegen sample contrasts sorted by values. (B) Probes correlation matrix using uncentered Pearson correlation.
Mentions: One clear–cut case to present the complexity of the issue is depicted in Figure 1. From this example is clear that each gene is actually measured on average by four probes (as expected) but, except for three probes (VitusP00165181, VitusP00165231, and VitusP00165171) all the other probes align perfectly (or near perfectly) to other genes, making impossible to distinguish one gene from another. In particular these four genes, beside being different among each other, are all annotated as Myb-related, a well-known transcription factor gene family composed by 100s of genes (Matus et al., 2008) and are positioned one after the other across chromosome 2 in a region of approximately 130 kb. This target cross-talk is corroborated by the actual probe-level intensities, which are highly correlated across all sample contrasts included in the compendium (Figure 2).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Biology, Research and Innovation Center, Fondazione Edmund MachTrento, Italy; Department of Biology, University of PadovaPadova, Italy.

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.

No MeSH data available.


Related in: MedlinePlus