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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Transcriptome Analysis of Capsicum Chlorosis Virus-Induced Hypersensitive Resistance Response in Bell Capsicum
|
|---|---|
| Published in |
PLOS ONE, July 2016
|
| DOI | 10.1371/journal.pone.0159085 |
| Pubmed ID | |
| Authors |
Shirani M. K. Widana Gamage, Desmond J. McGrath, Denis M. Persley, Ralf G. Dietzgen |
| Abstract |
Capsicum chlorosis virus (CaCV) is an emerging pathogen of capsicum, tomato and peanut crops in Australia and South-East Asia. Commercial capsicum cultivars with CaCV resistance are not yet available, but CaCV resistance identified in Capsicum chinense is being introgressed into commercial Bell capsicum. However, our knowledge of the molecular mechanisms leading to the resistance response to CaCV infection is limited. Therefore, transcriptome and expression profiling data provide an important resource to better understand CaCV resistance mechanisms. We assembled capsicum transcriptomes and analysed gene expression using Illumina HiSeq platform combined with a tag-based digital gene expression system. Total RNA extracted from CaCV/mock inoculated CaCV resistant (R) and susceptible (S) capsicum at the time point when R line showed a strong hypersensitive response to CaCV infection was used in transcriptome assembly. Gene expression profiles of R and S capsicum in CaCV- and buffer-inoculated conditions were compared. None of the genes were differentially expressed (DE) between R and S cultivars when mock-inoculated, while 2484 genes were DE when inoculated with CaCV. Functional classification revealed that the most highly up-regulated DE genes in R capsicum included pathogenesis-related genes, cell death-associated genes, genes associated with hormone-mediated signalling pathways and genes encoding enzymes involved in synthesis of defense-related secondary metabolites. We selected 15 genes to confirm DE expression levels by real-time quantitative PCR. DE transcript profiling data provided comprehensive gene expression information to gain an understanding of the underlying CaCV resistance mechanisms. Further, we identified candidate CaCV resistance genes in the CaCV-resistant C. annuum x C. chinense breeding line. This knowledge will be useful in future for fine mapping of the CaCV resistance locus and potential genetic engineering of resistance into CaCV-susceptible crops. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 2 | 40% |
| United States | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 18% |
| Researcher | 6 | 14% |
| Student > Doctoral Student | 6 | 14% |
| Student > Master | 3 | 7% |
| Professor | 2 | 5% |
| Other | 8 | 18% |
| Unknown | 11 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 39% |
| Biochemistry, Genetics and Molecular Biology | 9 | 20% |
| Economics, Econometrics and Finance | 1 | 2% |
| Earth and Planetary Sciences | 1 | 2% |
| Medicine and Dentistry | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 15 | 34% |
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 27 July 2016.
All research outputs
#6,979,392
of 22,880,230 outputs
Outputs from PLOS ONE
#82,696
of 195,163 outputs
Outputs of similar age
#115,708
of 354,317 outputs
Outputs of similar age from PLOS ONE
#1,614
of 4,419 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 195,163 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has gotten more attention than average, scoring higher than 56% 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 354,317 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 4,419 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 61% of its contemporaries.