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How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population

Overview of attention for article published in BMC Molecular and Cell Biology, June 2013
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Citations

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Title
How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population
Published in
BMC Molecular and Cell Biology, June 2013
DOI 10.1186/1471-2199-14-13
Pubmed ID
Authors

Ellen De Keyser, Laurence Desmet, Erik Van Bockstaele, Jan De Riek

Abstract

Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 2%
Germany 1 <1%
France 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Argentina 1 <1%
Unknown 119 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 24%
Researcher 26 21%
Student > Doctoral Student 12 10%
Student > Master 11 9%
Student > Bachelor 8 6%
Other 21 17%
Unknown 18 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 73 58%
Biochemistry, Genetics and Molecular Biology 19 15%
Social Sciences 3 2%
Environmental Science 2 2%
Chemistry 2 2%
Other 5 4%
Unknown 22 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 June 2013.
All research outputs
#19,945,185
of 25,374,917 outputs
Outputs from BMC Molecular and Cell Biology
#896
of 1,233 outputs
Outputs of similar age
#152,298
of 209,149 outputs
Outputs of similar age from BMC Molecular and Cell Biology
#7
of 11 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,233 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 24th percentile – i.e., 24% 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 209,149 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.