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Development of a waxy gene real-time PCR assay for the quantification of sorghum waxy grain in mixed cereal products

Overview of attention for article published in BMC Biotechnology, March 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#49 of 393)
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

news
1 news outlet
twitter
1 tweeter

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
26 Mendeley
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Title
Development of a waxy gene real-time PCR assay for the quantification of sorghum waxy grain in mixed cereal products
Published in
BMC Biotechnology, March 2015
DOI 10.1186/s12896-015-0134-z
Pubmed ID
Authors

Jaemin Cho, Taewook Jung, Jungin Kim, Seokbo Song, Jeeyeon Ko, Koansik Woo, Jaesaeng Lee, Myeongeun Choe, Inseok Oh

Abstract

Waxy-grain sorghum is used in most of the commercial cereal products in Korea. Worldwide, three waxy mutant alleles have been identified in the sorghum germplasm, and DNA markers for these alleles have been developed to identify the waxy genotype. However, that detection method cannot be used to determine the proportion of waxy content in samples containing both waxy and non-waxy sorghum. This study developed an assay that can be used to detect and quantify the waxy content of mixed cereal samples. All Korean waxy-grain sorghum used in this study contained the wx (a) allele, and one wx (a) allele-containing individual was also heterozygous for the wx (c) allele. No individuals possessed the wx (b) allele. The genotyping results were confirmed by iodine staining and amylose content analysis. Based on the sequence of the wx (a) allele, three different types of primers (wx (a) allele-specific, non-waxy allele-specific, and nonspecific) were designed for a quantitative real-time PCR (qPCR) assay; the primers were evaluated for qPCR using the following criteria: analytical specificity, sensitivity and repeatability. Use of this qPCR assay to analyze mixed cereal products demonstrated that it could accurately detect the waxy content of samples containing both waxy and non-waxy sorghum. We developed a qPCR assay to identify and quantify the waxy content of mixed waxy and non-waxy sorghum samples as well as mixtures of cereals including sorghum, rice and barley. The qPCR assay was highly specific; the allele-specific primers did not amplify PCR products from non-target templates. It was also highly sensitive, detecting a tiny amount (>0.5%) of waxy sorghum in the mixed samples; and it was simple and repeatable, implying the robust use of the assay.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 23%
Researcher 5 19%
Student > Ph. D. Student 3 12%
Student > Doctoral Student 1 4%
Lecturer 1 4%
Other 0 0%
Unknown 10 38%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 62%
Biochemistry, Genetics and Molecular Biology 1 4%
Psychology 1 4%
Unknown 8 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 24 March 2015.
All research outputs
#463,004
of 4,912,613 outputs
Outputs from BMC Biotechnology
#49
of 393 outputs
Outputs of similar age
#23,162
of 146,237 outputs
Outputs of similar age from BMC Biotechnology
#12
of 27 outputs
Altmetric has tracked 4,912,613 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 393 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 83% 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 146,237 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.