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Combined physiological, transcriptome, and cis-regulatory element analyses indicate that key aspects of ripening, metabolism, and transcriptional program in grapes (Vitis vinifera L.) are…

Overview of attention for article published in BMC Genomics, May 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

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6 tweeters
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1 Facebook page

Citations

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35 Dimensions

Readers on

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76 Mendeley
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Title
Combined physiological, transcriptome, and cis-regulatory element analyses indicate that key aspects of ripening, metabolism, and transcriptional program in grapes (Vitis vinifera L.) are differentially modulated accordingly to fruit size
Published in
BMC Genomics, May 2016
DOI 10.1186/s12864-016-2660-z
Pubmed ID
Authors

D. C. J. Wong, R. Lopez Gutierrez, N. Dimopoulos, G. A. Gambetta, S. D. Castellarin

Abstract

In wine grape production, management practices have been adopted to optimize grape and wine quality attributes by producing, or screening for, berries of smaller size. Fruit size and composition are influenced by numerous factors that include both internal (e.g. berry hormone metabolism) and external (e.g. environment and cultural practices) factors. Combined physiological, biochemical, and transcriptome analyses were performed to improve our current understanding of metabolic and transcriptional pathways related to berry ripening and composition in berries of different sizes. The comparison of berry physiology between small and large berries throughout development (from 31 to 121 days after anthesis, DAA) revealed significant differences in firmness, the rate of softening, and sugar accumulation at specific developmental stages. Small berries had significantly higher skin to berry weight ratio, lower number of seeds per berry, and higher anthocyanin concentration compared to large berries. RNA-sequencing analyses of berry skins at 47, 74, 103, and 121 DAA revealed a total of 3482 differentially expressed genes between small and large berries. Abscisic acid, auxin, and ethylene hormone pathway genes were differentially modulated between berry sizes. Fatty acid degradation and stilbenoid pathway genes were upregulated at 47 DAA while cell wall degrading and modification genes were downregulated at 74 DAA in small compared to large berries. In the late ripening stage, concerted upregulation of the general phenylpropanoid and stilbenoid pathway genes and downregulation of flavonoid pathway genes were observed in skins of small compared to large berries. Cis-regulatory element analysis of differentially expressed hormone, fruit texture, flavor, and aroma genes revealed an enrichment of specific regulatory motifs related to bZIP, bHLH, AP2/ERF, NAC, MYB, and MADS-box transcription factors. The study demonstrates that physiological and compositional differences between berries of different sizes parallel transcriptome changes that involve fruit texture, flavor, and aroma pathways. These results suggest that, in addition to direct effects brought about by differences in size, key aspects involved in the regulation of ripening likely contribute to different quality profiles between small and large berries.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Argentina 1 1%
Slovakia 1 1%
Unknown 73 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 21%
Student > Master 11 14%
Researcher 10 13%
Student > Bachelor 9 12%
Student > Doctoral Student 7 9%
Other 11 14%
Unknown 12 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 61%
Biochemistry, Genetics and Molecular Biology 7 9%
Environmental Science 3 4%
Engineering 2 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Other 4 5%
Unknown 13 17%

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 20 June 2016.
All research outputs
#1,853,419
of 7,921,887 outputs
Outputs from BMC Genomics
#1,613
of 5,679 outputs
Outputs of similar age
#81,381
of 270,124 outputs
Outputs of similar age from BMC Genomics
#61
of 191 outputs
Altmetric has tracked 7,921,887 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,679 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 71% 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 270,124 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 69% of its contemporaries.
We're also able to compare this research output to 191 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.