Dataset Information


Identification and Validation of Reference Genes for RT-qPCR Analysis in Non-Heading Chinese Cabbage Flowers.

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.


PROVIDER: S-EPMC4901065 | BioStudies | 2016-01-01

REPOSITORIES: biostudies

Similar Datasets

1000-01-01 | S-EPMC3998049 | BioStudies
2013-01-01 | S-EPMC3810141 | BioStudies
2016-01-01 | S-EPMC4746309 | BioStudies
2016-01-01 | S-EPMC4923122 | BioStudies
1000-01-01 | S-EPMC6011422 | BioStudies
2019-01-01 | S-EPMC6428831 | BioStudies
1000-01-01 | S-EPMC4230417 | BioStudies
2020-01-01 | S-EPMC7750362 | BioStudies
2020-01-01 | S-EPMC7391075 | BioStudies
2018-01-01 | S-EPMC5834901 | BioStudies