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Transcriptomic network analyses of leaf dehydration responses identify highly connected ABA and ethylene signaling hubs in three grapevine species differing in drought tolerance

Overview of attention for article published in BMC Plant Biology, May 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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1 blog
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3 X users

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118 Mendeley
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Title
Transcriptomic network analyses of leaf dehydration responses identify highly connected ABA and ethylene signaling hubs in three grapevine species differing in drought tolerance
Published in
BMC Plant Biology, May 2016
DOI 10.1186/s12870-016-0804-6
Pubmed ID
Authors

Daniel W. Hopper, Ryan Ghan, Karen A. Schlauch, Grant R. Cramer

Abstract

Grapevine is a major food crop that is affected by global climate change. Consistent with field studies, dehydration assays of grapevine leaves can reveal valuable information of the plant's response at physiological, transcript, and protein levels. There are well-known differences in grapevine rootstocks responses to dehydration. We used time-series transcriptomic approaches combined with network analyses to elucidate and identify important physiological processes and network hubs that responded to dehydration in three different grapevine species differing in their drought tolerance. Transcriptomic analyses of the leaves of Cabernet Sauvignon, Riparia Gloire, and Ramsey were evaluated at different times during a 24-h controlled dehydration. Analysis of variance (ANOVA) revealed that approximately 11,000 transcripts changed significantly with respect to the genotype x treatment interaction term and approximately 6000 transcripts changed significantly according to the genotype x treatment x time interaction term indicating massive differential changes in gene expression over time. Standard analyses determined substantial effects on the transcript abundance of genes involved in the metabolism and signaling of two known plant stress hormones, abscisic acid (ABA) and ethylene. ABA and ethylene signaling maps were constructed and revealed specific changes in transcript abundance that were associated with the known drought tolerance of the genotypes including genes such as VviABI5, VviABF2, VviACS2, and VviWRKY22. Weighted-gene coexpression network analysis (WGCNA) confirmed these results. In particular, WGCNA identified 30 different modules, some of which had highly enriched gene ontology (GO) categories for photosynthesis, phenylpropanoid metabolism, ABA and ethylene signaling. The ABA signaling transcription factors, VviABI5 and VviABF2, were highly connected hubs in two modules, one being enriched in gaseous transport and the other in ethylene signaling. VviABI5 was distinctly correlated with an early response and high expression for the drought tolerant Ramsey and with little response from the drought sensitive Riparia Gloire. These ABA signaling transcription factors were highly connected to VviSnRK1 and other gene hubs associated with sugar, ethylene and ABA signaling. A leaf dehydration assay provided transcriptomic evidence for differential leaf responses to dehydration between genotypes differing in their drought tolerance. WGCNA proved to be a powerful network analysis approach; it identified 30 distinct modules (networks) with highly enriched GO categories and enabled the identification of gene hubs in these modules. Some of these genes were highly connected hubs in both the ABA and ethylene signaling pathways, supporting the hypothesis that there is substantial crosstalk between the two hormone pathways. This study identifies solid gene candidates for future investigations of drought tolerance in grapevine.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 <1%
Unknown 117 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 18%
Researcher 21 18%
Student > Master 12 10%
Student > Doctoral Student 10 8%
Student > Postgraduate 8 7%
Other 19 16%
Unknown 27 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 48%
Biochemistry, Genetics and Molecular Biology 14 12%
Environmental Science 3 3%
Engineering 3 3%
Computer Science 2 2%
Other 4 3%
Unknown 35 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 June 2016.
All research outputs
#3,617,725
of 22,873,031 outputs
Outputs from BMC Plant Biology
#220
of 3,263 outputs
Outputs of similar age
#62,409
of 333,421 outputs
Outputs of similar age from BMC Plant Biology
#5
of 62 outputs
Altmetric has tracked 22,873,031 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,263 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,421 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.