A High-Density SNP Map for Accurate Mapping of Seed Fibre QTL in Brassica napus L

Liu, Liezhao; Qu, Cunmin; Wittkop, Benjamin; Yi, Bin; Xiao, Yang; He, Ying; Snowdon, Rod J.; Li, Jiana

doi:10.1371/journal.pone.0083052

Cited by 97 publications

(89 citation statements)

References 47 publications

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“…Additional SNPs associated with SGC found on chromosomes A2, A3, C4, C6 and C9 could represent a novel genomic variation for this trait; however, additional studies are necessary to confirm this finding. Similarly, the SNPs associated with SHC (located on chromosomes A8 and C3) did not coincide with the positions found in a previous work (chromosomes A3 and A9, Liu et al 2013) and could represent novel genomic regions controlling this trait.…”

Section: Association Mapping Using Gwas and Cqtl Approachescontrasting

confidence: 62%

Association mapping of seed quality traits in Brassica napus L. using GWAS and candidate QTL approaches

et al. 2015

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Single nucleotide polymorphisms (SNPs) have rapidly become the molecular marker of choice in plant and animal association mapping (AM) studies. In this work, a genome-wide association study (GWAS) and candidate quantitative trait loci (cQTL) approaches were used to identify SNP markers associated with seed quality traits, in a Brassica napus L. association panel composed of 89 adapted winter oilseed rape accessions. Six seed quality traits (oil and protein content, linolenic acid, total glucosinolates, hemicellulose and cellulose content) were evaluated in two different locations for two seasons. For GWAS, 4025 SNP markers evenly distributed along the B. napus genome were genotyped using a 6K Illumina array platform. For cQTL, 100 SNP markers previously discovered in genomic regions underlying seed quality QTL were genotyped using a competitive allele-specific PCR (KASPar). Analysis of the population structure revealed the presence of two weakly differentiated subpopulations (F ST = 0.037), with 82 % of the pairwise kinship comparisons ranging from 0 to 0.1. The GWAS approach resulted in the identification of 17 and 5 significant associations for seed glucosinolate content and seed hemicellulose content, respectively. The cQTL approach identified 4 significant associations for seed glucosinolate content and 6 significant associations for seed hemicellulose content. The associated SNPs were consistently identified across environments and were mapped to previously reported QTL. These results illustrate the suitability of AM to identify SNP markers associated with seed quality traits in B. napus.

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Section: Association Mapping Using Gwas and Cqtl Approachescontrasting

confidence: 62%

Association mapping of seed quality traits in Brassica napus L. using GWAS and candidate QTL approaches

et al. 2015

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“…This study is based on a published dataset from the bi-parental TN DH population comprising 202 DH lines, which has been intensively used to study the genetic architecture of important agronomic traits [9–11, 22, 23] and were genotyped with an Infinium 60K-SNP array [52] being extensively used in Brassica [24, 53, 54]. The two parents of the TN DH mapping population originated from the European and Chinese genepools and have been used widely for rapeseed breeding programs in both target regions.…”

Section: Introductionmentioning

confidence: 99%

Seed Quality Traits Can Be Predicted with High Accuracy in Brassica napus Using Genomic Data

et al. 2016

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Improving seed oil yield and quality are central targets in rapeseed (Brassica napus) breeding. The primary goal of our study was to examine and compare the potential and the limits of marker-assisted selection and genome-wide prediction of six important seed quality traits of B. napus. Our study is based on a bi-parental population comprising 202 doubled haploid lines and a diverse validation set including 117 B. napus inbred lines derived from interspecific crosses between B. rapa and B. carinata. We used phenotypic data for seed oil, protein, erucic acid, linolenic acid, stearic acid, and glucosinolate content. All lines were genotyped with a 60k SNP array. We performed five-fold cross-validations in combination with linkage mapping and four genome-wide prediction approaches in the bi-parental population. Quantitative trait loci (QTL) with large effects were detected for erucic acid, stearic acid, and glucosinolate content, blazing the trail for marker-assisted selection. Despite substantial differences in the complexity of the genetic architecture of the six traits, genome-wide prediction models had only minor impacts on the prediction accuracies. We evaluated the effects of training population size, marker density and phenotyping intensity on the prediction accuracy. The prediction accuracy in the independent and genetically very distinct validation set still amounted to 0.14 for protein content and 0.17 for oil content reflecting the utility of the developed calibration models even in very diverse backgrounds.

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“…Moreover, many traits of agronomic importance in B. napus , such as seed coat color, oil content, and seed yield, are quantitative with complex genetic bases. Recently, a high-density linkage map was constructed using the Brassica 60 K Infinium BeadChip Array (Zou et al, 2012; Delourme et al, 2013; Liu et al, 2013; Zhang et al, 2014; Wang et al, 2015). Genome-specific SSR markers have been widely used for genetic mapping, association mapping, comparative mapping, QTL analysis, and marker-assisted selection (Li et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Molecular Mapping and QTL for Expression Profiles of Flavonoid Genes in Brassica napus

Zhao

et al. 2016

Front. Plant Sci.

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Flavonoids are secondary metabolites that are extensively distributed in the plant kingdom and contribute to seed coat color formation in rapeseed. To decipher the genetic networks underlying flavonoid biosynthesis in rapeseed, we constructed a high-density genetic linkage map with 1089 polymorphic loci (including 464 SSR loci, 97 RAPD loci, 451 SRAP loci, and 75 IBP loci) using recombinant inbred lines (RILs). The map consists of 19 linkage groups and covers 2775 cM of the B. napus genome with an average distance of 2.54 cM between adjacent markers. We then performed expression quantitative trait locus (eQTL) analysis to detect transcript-level variation of 18 flavonoid biosynthesis pathway genes in the seeds of the 94 RILs. In total, 72 eQTLs were detected and found to be distributed among 15 different linkage groups that account for 4.11% to 52.70% of the phenotypic variance atrributed to each eQTL. Using a genetical genomics approach, four eQTL hotspots together harboring 28 eQTLs associated with 18 genes were found on chromosomes A03, A09, and C08 and had high levels of synteny with genome sequences of A. thaliana and Brassica species. Associated with the trans-eQTL hotspots on chromosomes A03, A09, and C08 were 5, 17, and 1 genes encoding transcription factors, suggesting that these genes have essential roles in the flavonoid biosynthesis pathway. Importantly, bZIP25, which is expressed specifically in seeds, MYC1, which controls flavonoid biosynthesis, and the R2R3-type gene MYB51, which is involved in the synthesis of secondary metabolites, were associated with the eQTL hotspots, and these genes might thus be involved in different flavonoid biosynthesis pathways in rapeseed. Hence, further studies of the functions of these genes will provide insight into the regulatory mechanism underlying flavonoid biosynthesis, and lay the foundation for elaborating the molecular mechanism of seed coat color formation in B. napus.

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A High-Density SNP Map for Accurate Mapping of Seed Fibre QTL in Brassica napus L

Cited by 97 publications

References 47 publications

Association mapping of seed quality traits in Brassica napus L. using GWAS and candidate QTL approaches

Association mapping of seed quality traits in Brassica napus L. using GWAS and candidate QTL approaches

Seed Quality Traits Can Be Predicted with High Accuracy in Brassica napus Using Genomic Data

Molecular Mapping and QTL for Expression Profiles of Flavonoid Genes in Brassica napus

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