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Comprehensive Transcriptome Profiling Reveals Long Noncoding RNA Expression and Alternative Splicing Regulation during Fruit Development and Ripening in Kiwifruit (Actinidia chinensis)

Overview of attention for article published in Frontiers in Plant Science, March 2016
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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Title
Comprehensive Transcriptome Profiling Reveals Long Noncoding RNA Expression and Alternative Splicing Regulation during Fruit Development and Ripening in Kiwifruit (Actinidia chinensis)
Published in
Frontiers in Plant Science, March 2016
DOI 10.3389/fpls.2016.00335
Pubmed ID
Authors

Wei Tang, Yi Zheng, Jing Dong, Jia Yu, Junyang Yue, Fangfang Liu, Xiuhong Guo, Shengxiong Huang, Michael Wisniewski, Jiaqi Sun, Xiangli Niu, Jian Ding, Jia Liu, Zhangjun Fei, Yongsheng Liu

Abstract

Genomic and transcriptomic data on kiwifruit (Actinidia chinensis) in public databases are very limited despite its nutritional and economic value. Previously, we have constructed and sequenced nine fruit RNA-Seq libraries of A. chinensis "Hongyang" at immature, mature, and postharvest ripening stages of fruit development, and generated over 66.2 million paired-end and 24.4 million single-end reads. From this dataset, here we have identified 7051 long noncoding RNAs (lncRNAs), 29,327 alternative splicing (AS) events and 2980 novel protein-coding genes that were not annotated in the draft genome of "Hongyang." AS events were demonstrated in genes involved in the synthesis of nutritional metabolites in fruit, such as ascorbic acids, carotenoids, anthocyanins, and chlorophylls, and also in genes in the ethylene signaling pathway, which plays an indispensable role in fruit ripening. Additionally, transcriptome profiles and the contents of sugars, organic and main amino acids were compared between immature, mature, and postharvest ripening stages in kiwifruits. A total of 5931 differentially expressed genes were identified, including those associated with the metabolism of sugar, organic acid, and main amino acids. The data generated in this study provide a foundation for further studies of fruit development and ripening in kiwifruit, and identify candidate genes and regulatory elements that could serve as targets for improving important agronomic traits through marker assisted breeding and biotechnology.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 2%
Unknown 57 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 16%
Student > Master 9 16%
Researcher 8 14%
Student > Doctoral Student 5 9%
Student > Postgraduate 3 5%
Other 10 17%
Unknown 14 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 34%
Biochemistry, Genetics and Molecular Biology 12 21%
Chemical Engineering 1 2%
Nursing and Health Professions 1 2%
Unspecified 1 2%
Other 2 3%
Unknown 21 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 07 September 2016.
All research outputs
#13,515,676
of 23,318,744 outputs
Outputs from Frontiers in Plant Science
#6,237
of 21,159 outputs
Outputs of similar age
#144,230
of 302,121 outputs
Outputs of similar age from Frontiers in Plant Science
#138
of 504 outputs
Altmetric has tracked 23,318,744 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 21,159 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 68% 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 302,121 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 51% of its contemporaries.
We're also able to compare this research output to 504 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 71% of its contemporaries.