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Attention Score in Context
| Title |
Identification and Validation of Reference Genes for RT-qPCR Analysis in Non-Heading Chinese Cabbage Flowers
|
|---|---|
| Published in |
Frontiers in Plant Science, June 2016
|
| DOI | 10.3389/fpls.2016.00811 |
| Pubmed ID | |
| Authors |
Cheng Wang, Hong-Mi Cui, Tian-Hong Huang, Tong-Kun Liu, Xi-Lin Hou, Ying Li |
| Abstract |
Non-heading Chinese cabbage (Brassica rapa ssp. chinensis Makino) is an important vegetable member of Brassica rapa crops. It exhibits a typical sporophytic self-incompatibility (SI) system and is an ideal model plant to explore the mechanism of SI. Gene expression research are frequently used to unravel the complex genetic mechanism and in such studies appropriate reference selection is vital. Validation of reference genes have neither been conducted in Brassica rapa flowers nor in SI trait. In this study, 13 candidate reference genes were selected and examined systematically in 96 non-heading Chinese cabbage flower samples that represent four strategic groups in compatible and self-incompatible lines of non-heading Chinese cabbage. Two RT-qPCR analysis software, geNorm and NormFinder, were used to evaluate the expression stability of these genes systematically. Results revealed that best-ranked references genes should be selected according to specific sample subsets. DNAJ, UKN1, and PP2A were identified as the most stable reference genes among all samples. Moreover, our research further revealed that the widely used reference genes, CYP and ACP, were the least suitable reference genes in most non-heading Chinese cabbage flower sample sets. To further validate the suitability of the reference genes identified in this study, the expression level of SRK and Exo70A1 genes which play important roles in regulating interaction between pollen and stigma were studied. Our study presented the first systematic study of reference gene(s) selection for SI study and provided guidelines to obtain more accurate RT-qPCR results in non-heading Chinese cabbage. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 22% |
| Student > Doctoral Student | 5 | 19% |
| Other | 3 | 11% |
| Researcher | 3 | 11% |
| Student > Postgraduate | 2 | 7% |
| Other | 5 | 19% |
| Unknown | 3 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 63% |
| Biochemistry, Genetics and Molecular Biology | 5 | 19% |
| Business, Management and Accounting | 1 | 4% |
| Unspecified | 1 | 4% |
| Unknown | 3 | 11% |
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 10 June 2016.
All research outputs
#20,332,117
of 22,876,619 outputs
Outputs from Frontiers in Plant Science
#16,164
of 20,268 outputs
Outputs of similar age
#297,733
of 345,197 outputs
Outputs of similar age from Frontiers in Plant Science
#400
of 521 outputs
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