Identification and Characterization of the MIKC-Type MADS-Box Gene Family in Brassica napus and Its Role in Floral Transition.
Enqiang ZhouYin ZhangHuadong WangZhibo JiaXuejun WangJing WenJinxiong ShenTingdong FuBin YiPublished in: International journal of molecular sciences (2022)
Increasing rapeseed yield has always been a primary goal of rapeseed research and breeding. However, flowering time is a prerequisite for stable rapeseed yield and determines its adaptability to ecological regions. MIKC-type MADS-box (MICK) genes are a class of transcription factors that are involved in various physiological and developmental processes in plants. To understand their role in floral transition-related pathways, a genome-wide screening was conducted with Brassica napus ( B. napus ), which revealed 172 members. Using previous data from a genome-wide association analysis of flowering traits, BnaSVP and BnaSEP1 were identified as candidate flowering genes. Therefore, we used the CRISPR/Cas9 system to verify the function of BnaSVP and BnaSEP1 in B. napus . T0 plants were edited efficiently at the BnaSVP and BnaSEP1 target sites to generate homozygous and heterozygous mutants with most mutations stably inherited by the next generation. Notably, the mutant only showed the early flowering phenotype when all homologous copies of BnaSVP were edited, indicating functional redundancy between homologous copies. However, no changes in flowering were observed in the BnaSEP1 mutant. Quantitative analysis of the pathway-related genes in the BnaSVP mutant revealed the upregulation of SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 ( SOC1 ) and FLOWERING LOCUS T ( FT ) genes, which promoted early flowering in the mutant. In summary, our study created early flowering mutants, which provided valuable resources for early maturing breeding, and provided a new method for improving polyploid crops.
Keyphrases
- arabidopsis thaliana
- genome wide
- genome wide identification
- crispr cas
- transcription factor
- wild type
- genome editing
- dna methylation
- cell proliferation
- genome wide analysis
- single cell
- dna damage
- dna repair
- binding protein
- gene expression
- climate change
- electronic health record
- genome wide association
- risk assessment
- long non coding rna
- artificial intelligence
- deep learning
- data analysis