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De novo transcriptome analysis in radish (Raphanus sativus L.) and identification of critical genes involved in bolting and flowering

Overview of attention for article published in BMC Genomics, May 2016
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5 tweeters

Citations

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29 Dimensions

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40 Mendeley
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Title
De novo transcriptome analysis in radish (Raphanus sativus L.) and identification of critical genes involved in bolting and flowering
Published in
BMC Genomics, May 2016
DOI 10.1186/s12864-016-2633-2
Pubmed ID
Authors

Shanshan Nie, Chao Li, Liang Xu, Yan Wang, Danqiong Huang, Everlyne M. Muleke, Xiaochuan Sun, Yang Xie, Liwang Liu

Abstract

The appropriate timing of bolting and flowering is pivotal for reproductive success in Brassicaceae crops including radish (Raphanus sativus L.). Although several flowering regulatory pathways had been described in some plant species, no study on genetic networks of bolting and flowering regulation was performed in radish. In this study, to generate dataset of radish unigene sequences for large-scale gene discovery and functional pathway identification, a cDNA library from mixed radish leaves at different developmental stages was subjected to high-throughput RNA sequencing (RNA-seq). A total of 54.64 million clean reads and 111,167 contigs representing 53,642 unigenes were obtained from the radish leaf transcriptome. Among these, 50,385 unigenes were successfully annotated by BLAST searching against the public protein databases. Functional classification and annotation indicated that 42,903 and 15,382 unique sequences were assigned to 55 GO terms and 25 COG categories, respectively. KEGG pathway analysis revealed that 25,973 unigenes were classified into 128 functional pathways, among which 24 candidate genes related to plant circadian rhythm were identified. Moreover, 142 potential bolting and flowering-related genes involved in various flowering pathways were identified. In addition, seven critical bolting and flowering-related genes were isolated and profiled by T-A cloning and RT-qPCR analysis. Finally, a schematic network model of bolting and flowering regulation and pathways was put forward in radish. This study is the first report on systematic identification of bolting and flowering-related genes based on transcriptome sequencing and assembly in radish. These results could provide a foundation for further investigating bolting and flowering regulatory networks in radish, and facilitate dissecting molecular genetic mechanisms underlying bolting and flowering in Brassicaceae vegetable crops.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 39 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 30%
Student > Doctoral Student 5 13%
Researcher 5 13%
Student > Master 5 13%
Student > Bachelor 4 10%
Other 7 18%
Unknown 2 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 75%
Biochemistry, Genetics and Molecular Biology 5 13%
Environmental Science 1 3%
Chemistry 1 3%
Engineering 1 3%
Other 0 0%
Unknown 2 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 May 2016.
All research outputs
#9,813,699
of 16,638,522 outputs
Outputs from BMC Genomics
#4,744
of 9,107 outputs
Outputs of similar age
#130,156
of 269,288 outputs
Outputs of similar age from BMC Genomics
#11
of 14 outputs
Altmetric has tracked 16,638,522 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,107 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 269,288 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.