↓ Skip to main content

Genome-Wide Identification and Evaluation of Reference Genes for Quantitative RT-PCR Analysis during Tomato Fruit Development

Overview of attention for article published in Frontiers in Plant Science, August 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
40 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Genome-Wide Identification and Evaluation of Reference Genes for Quantitative RT-PCR Analysis during Tomato Fruit Development
Published in
Frontiers in Plant Science, August 2017
DOI 10.3389/fpls.2017.01440
Pubmed ID
Authors

Yuan Cheng, Wuying Bian, Xin Pang, Jiahong Yu, Golam J. Ahammed, Guozhi Zhou, Rongqing Wang, Meiying Ruan, Zhimiao Li, Qingjing Ye, Zhuping Yao, Yuejian Yang, Hongjian Wan

Abstract

Gene expression analysis in tomato fruit has drawn increasing attention nowadays. Quantitative real-time PCR (qPCR) is a routine technique for gene expression analysis. In qPCR operation, reliability of results largely depends on the choice of appropriate reference genes (RGs). Although tomato is a model for fruit biology study, few RGs for qPCR analysis in tomato fruit had yet been developed. In this study, we initially identified 38 most stably expressed genes based on tomato transcriptome data set, and their expression stabilities were further determined in a set of tomato fruit samples of four different fruit developmental stages (Immature, mature green, breaker, mature red) using qPCR analysis. Two statistical algorithms, geNorm and Normfinder, concordantly determined the superiority of these identified putative RGs. Notably, SlFRG05 (Solyc01g104170), SlFRG12 (Solyc04g009770), SlFRG16 (Solyc10g081190), SlFRG27 (Solyc06g007510), and SlFRG37 (Solyc11g005330) were proved to be suitable RGs for tomato fruit development study. Further analysis using geNorm indicate that the combined use of SlFRG03 (Solyc02g063070) and SlFRG27 would provide more reliable normalization results in qPCR experiments. The identified RGs in this study will be beneficial for future qPCR analysis of tomato fruit developmental study, as well as for the potential identification of optimal normalization controls in other plant species.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 28%
Student > Ph. D. Student 8 20%
Student > Master 7 18%
Student > Postgraduate 2 5%
Student > Bachelor 2 5%
Other 4 10%
Unknown 6 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 53%
Biochemistry, Genetics and Molecular Biology 9 23%
Veterinary Science and Veterinary Medicine 1 3%
Medicine and Dentistry 1 3%
Unknown 8 20%
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 14 September 2017.
All research outputs
#20,447,499
of 23,002,898 outputs
Outputs from Frontiers in Plant Science
#16,388
of 20,497 outputs
Outputs of similar age
#275,884
of 315,942 outputs
Outputs of similar age from Frontiers in Plant Science
#416
of 485 outputs
Altmetric has tracked 23,002,898 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,497 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 1st percentile – i.e., 1% 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 315,942 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 485 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.