Optimization of quantitative reverse transcription PCR method for analysis of weakly expressed genes in crops based on rapeseed.
Front Plant Sci
; 13: 954976, 2022.
Article
em En
| MEDLINE
| ID: mdl-36017265
ABSTRACT
Rapeseed (Brassica napus) is an allopolyploid hybrid (AACC genome) of turnip rape (B. rapa, genome AA) and vegetable cabbage (B. oleraceae, genome CC). Rapeseed oil is one of the main vegetable oils used worldwide for food and other technical purposes. Therefore, breeding companies worldwide are interested in developing rapeseed varieties with high yields and increased adaptation to harsh climatic conditions such as heat and prolonged drought. One approach to studying the mechanism of the epigenetically regulated stress response is to analyze the transcriptional changes it causes. In addition, comparing the expression of certain genes between stress- and non-stress-tolerant varieties will help guide breeding in the desired direction. Quantitative reverse transcription PCR (RT-qPCR) has been intensively used for gene expression analysis for several decades. However, the transfer of this method from model plants to crop species has several limitations due to the high accumulation of secondary metabolites, the higher water content in some tissues and therefore problems with their grinding and other factors. For allopolyploid rapeseed, the presence of two genomes, often with different levels of expression of homeologous genes, must also be considered. In this study, we describe the optimization of transcriptional RT-qPCR analysis of low-expression epigenetic genes in rapeseed, using Kinetochore Null2 (KNL2), a regulator of kinetochore complex assembly, as an example. We demonstrated that a combination of various factors, such as tissue homogenization and RNA extraction with TRIzol, synthesis of cDNA with gene-specific primers, and RT-qPCR in white plates, significantly increased the sensitivity of RT-qPCR for the detection of BnKNL2A and BnKNL2C gene expression.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Front Plant Sci
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Alemanha