ArticleFrontiers in plant science2015
High-Density SNP Map Construction and QTL Identification for the Apetalous Character in Brassica napus L.
Article in Frontiers in plant science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Integrating QTL mapping and GWAS to decipher the genetic mechanisms behind the calcium contents ofFrontiers in plant science · 2025Article
- Identification of candidate genes associated with double flowers via integrating BSA-seq and RNA-seq in Brassica napus.BMC genomics · 2024Article
- Article
- QTL Mapping and Transcriptome Analysis Reveal Candidate Genes Regulating Seed Color inInternational journal of molecular sciences · 2023Article
- Whole-genome sequence of synthetically derived Brassica napus inbred cultivar Da-Ae.G3 (Bethesda, Md.) · 2023Article
- Genetic Dissection and Germplasm Selection of the Low Crude Fiber Component inFoods (Basel, Switzerland) · 2023Article
- A small chromosomal inversion mediated by MITE transposons confers cleistogamy in Brassica napus.Plant physiology · 2022Article
- Further insight into decreases in seed glucosinolate content based on QTL mapping and RNA-seq in Brassica napus L.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Quantitative Trait Locus Mapping Combined with RNA Sequencing Reveals the Molecular Basis of Seed Germination in Oilseed Rape.Biomolecules · 2021Article
- QTL Mapping and GWAS Reveal the Genetic Mechanism Controlling Soluble Solids Content inFoods (Basel, Switzerland) · 2021Article
- Detection of ploidy and chromosomal aberrations in commercial oil palm using high-throughput SNP markers.Planta · 2021Article
- QTL Analysis of Five Silique-Related Traits inFrontiers in plant science · 2021Article
- Linkage mapping and QTL analysis of flowering time using ddRAD sequencing with genotype error correction in Brassica napus.BMC plant biology · 2020Article
- Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review.Plants (Basel, Switzerland) · 2020Review
- Genetic mapping and identification of new major loci for tolerance to low phosphorus stress in rice.Physiology and molecular biology of plants : an international journal of functional plant biology · 2020Article
- Fine-mapping and transcriptome analysis of a candidate gene controlling plant height inBiotechnology for biofuels · 2020Article
- Integration of proteomic and genomic approaches to dissect seed germination vigor in Brassica napus seeds differing in oil content.BMC plant biology · 2019Article
- Article
- Finding invisible quantitative trait loci with missing data.Plant biotechnology journal · 2018Article
- DetectingG3 (Bethesda, Md.) · 2018Article
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9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The apetalous genotype is a morphological ideotype for increasing seed yield and should be of considerable agricultural use; however, only a few studies have focused on the genetic control of this trait in Brassica napus. In the present study, a recombinant inbred line, the AH population, containing 189 individuals was derived from a cross between an apetalous line 'APL01' and a normally petalled variety 'Holly'. The Brassica 60 K Infinium BeadChip Array harboring 52,157 single nucleotide polymorphism (SNP) markers was used to genotype the AH individuals. A high-density genetic linkage map was constructed based on 2,755 bins involving 11,458 SNPs and 57 simple sequence repeats, and was used to identify loci associated with petalous degree (PDgr). The linkage map covered 2,027.53 cM, with an average marker interval of 0.72 cM. The AH map had good collinearity with the B. napus reference genome, indicating its high quality and accuracy. After phenotypic analyses across five different experiments, a total of 19 identified quantitative trait loci (QTLs) distributed across chromosomes A3, A5, A6, A9 and C8 were obtained, and these QTLs were further integrated into nine consensus QTLs by a meta-analysis. Interestingly, the major QTL qPD.C8-2 was consistently detected in all five experiments, and qPD.A9-2 and qPD.C8-3 were stably expressed in four experiments. Comparative mapping between the AH map and the B. napus reference genome suggested that there were 328 genes underlying the confidence intervals of the three steady QTLs. Based on the Gene Ontology assignments of 52 genes to the regulation of floral development in published studies, 146 genes were considered as potential candidate genes for PDgr. The current study carried out a QTL analysis for PDgr using a high-density SNP map in B. napus, providing novel targets for improving seed yield. These results advanced our understanding of the genetic control of PDgr regulation in B. napus.
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