Discovery of Genomic Regions and Candidate Genes Controlling Root Development Using a Recombinant Inbred Line Population in Rapeseed ( Brassica napus L.).
Lieqiong KuangNazir AhmadBin SuLintao HuangKeqi LiHanzhong WangXinfa WangXiaoling DunPublished in: International journal of molecular sciences (2022)
Marker-assisted selection enables breeders to quickly select excellent root architectural variations, which play an essential role in plant productivity. Here, ten root-related and shoot biomass traits of a new F 6 recombinant inbred line (RIL) population were investigated under hydroponics and resulted in high heritabilities from 0.61 to 0.83. A high-density linkage map of the RIL population was constructed using a Brassica napus 50k Illumina single nucleotide polymorphism (SNP) array. A total of 86 quantitative trait loci (QTLs) explaining 4.16-14.1% of the phenotypic variances were detected and integrated into eight stable QTL clusters, which were repeatedly detected in different experiments. The codominant markers were developed to be tightly linked with three major QTL clusters, qcA09-2 , qcC08-2 , and qcC08-3 , which controlled both root-related and shoot biomass traits and had phenotypic contributions greater than 10%. Among these, qcA09-2 , renamed RT.A09 , was further fine-mapped to a 129-kb interval with 19 annotated genes in the B. napus reference genome. By integrating the results of real-time PCR and comparative sequencing, five genes with expression differences and/or amino acid differences were identified as important candidate genes for RT.A09 . Our findings laid the foundation for revealing the molecular mechanism of root development and developed valuable markers for root genetic improvement in rapeseed.
Keyphrases
- genome wide
- high density
- dna methylation
- copy number
- wastewater treatment
- amino acid
- high resolution
- poor prognosis
- small molecule
- genome wide identification
- high throughput
- climate change
- gene expression
- long non coding rna
- single cell
- air pollution
- anaerobic digestion
- bioinformatics analysis
- cell free
- mass spectrometry
- hiv infected