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The common transcriptional subnetworks of the grape berry skin in the late stages of ripening

Overview of attention for article published in BMC Plant Biology, May 2017
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  • Good Attention Score compared to outputs of the same age (66th percentile)

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8 tweeters

Citations

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29 Dimensions

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Title
The common transcriptional subnetworks of the grape berry skin in the late stages of ripening
Published in
BMC Plant Biology, May 2017
DOI 10.1186/s12870-017-1043-1
Pubmed ID
Authors

Ryan Ghan, Juli Petereit, Richard L. Tillett, Karen A. Schlauch, David Toubiana, Aaron Fait, Grant R. Cramer

Abstract

Wine grapes are important economically in many countries around the world. Defining the optimum time for grape harvest is a major challenge to the grower and winemaker. Berry skins are an important source of flavor, color and other quality traits in the ripening stage. Senescent-like processes such as chloroplast disorganization and cell death characterize the late ripening stage. To better understand the molecular and physiological processes involved in the late stages of berry ripening, RNA-seq analysis of the skins of seven wine grape cultivars (Cabernet Franc, Cabernet Sauvignon, Merlot, Pinot Noir, Chardonnay, Sauvignon Blanc and Semillon) was performed. RNA-seq analysis identified approximately 2000 common differentially expressed genes for all seven cultivars across four different berry sugar levels (20 to 26 °Brix). Network analyses, both a posteriori (standard) and a priori (gene co-expression network analysis), were used to elucidate transcriptional subnetworks and hub genes associated with traits in the berry skins of the late stages of berry ripening. These independent approaches revealed genes involved in photosynthesis, catabolism, and nucleotide metabolism. The transcript abundance of most photosynthetic genes declined with increasing sugar levels in the berries. The transcript abundance of other processes increased such as nucleic acid metabolism, chromosome organization and lipid catabolism. Weighted gene co-expression network analysis (WGCNA) identified 64 gene modules that were organized into 12 subnetworks of three modules or more and six higher order gene subnetworks. Some gene subnetworks were highly correlated with sugar levels and some subnetworks were highly enriched in the chloroplast and nucleus. The petal R package was utilized independently to construct a true small-world and scale-free complex gene co-expression network model. A subnetwork of 216 genes with the highest connectivity was elucidated, consistent with the module results from WGCNA. Hub genes in these subnetworks were identified including numerous members of the core circadian clock, RNA splicing, proteolysis and chromosome organization. An integrated model was constructed linking light sensing with alternative splicing, chromosome remodeling and the circadian clock. A common set of differentially expressed genes and gene subnetworks from seven different cultivars were examined in the skin of the late stages of grapevine berry ripening. A densely connected gene subnetwork was elucidated involving a complex interaction of berry senescent processes (autophagy), catabolism, the circadian clock, RNA splicing, proteolysis and epigenetic regulation. Hypotheses were induced from these data sets involving sugar accumulation, light, autophagy, epigenetic regulation, and fruit development. This work provides a better understanding of berry development and the transcriptional processes involved in the late stages of ripening.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 72 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 21%
Researcher 13 18%
Student > Master 11 15%
Student > Postgraduate 8 11%
Student > Bachelor 5 7%
Other 9 13%
Unknown 11 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 54%
Biochemistry, Genetics and Molecular Biology 13 18%
Chemistry 3 4%
Environmental Science 2 3%
Psychology 1 1%
Other 1 1%
Unknown 13 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 10 June 2017.
All research outputs
#4,651,331
of 15,920,653 outputs
Outputs from BMC Plant Biology
#401
of 2,304 outputs
Outputs of similar age
#90,906
of 272,674 outputs
Outputs of similar age from BMC Plant Biology
#1
of 1 outputs
Altmetric has tracked 15,920,653 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 2,304 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done well, scoring higher than 82% 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 272,674 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them