Genome-Wide Association Study Dissects the Genetic Architecture of Seed Weight and Seed Quality in Rapeseed (Brassica napus L.)

Feng, Li; Xu, Kun; Wu, Jinfeng; Song, Weilin; Bancroft, Ian; Harper, Andrea L.; Trick, Martin; S, Liu; Gao, Guizhen; Wang, Nian; Yan, Guiqin; Qiao, Jiangwei; Li, Jun; Li, Hao; Xiao, Xin; Wang, Ziyang; Wu, Xiaoming

doi:10.1093/dnares/dsu002

Cited by 194 publications

(240 citation statements)

References 75 publications

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“…In our previous study, we performed genotype analysis of an association panel with 472 accessions using a 60k Brassica Infinium ® SNP array, the SNPs of which, were in silico mapped in the B. napus pseudomolecules created by Harper et al [36]. We then performed a GWAS of B. napus seed weight and seed quality [35]. We identified several loci or candidate genes consistent with previous studies, indicating that our rapeseed panel is suitable for fine mapping complex traits.…”

Section: Introductionsupporting

confidence: 71%

“…Recent studies have shown that GWAS is a powerful tool to detect the genetic architecture of traits in many crops, and it can identify multiple related candidate genes [33][34][35]. In our previous study, we performed genotype analysis of an association panel with 472 accessions using a 60k Brassica Infinium ® SNP array, the SNPs of which, were in silico mapped in the B. napus pseudomolecules created by Harper et al [36].…”

Section: Introductionmentioning

confidence: 99%

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A genome-wide association study of plant height and primary branch number in rapeseed ( Brassica napus )

Chen

et al. 2016

Plant Science

107

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Section: Introductionsupporting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

A genome-wide association study of plant height and primary branch number in rapeseed ( Brassica napus )

Chen

et al. 2016

Plant Science

107

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“…These have helped to identify and/or confirm QTL underlying seed quality traits (Hasan et al 2008;Honsdorf et al 2010;Fritsche et al 2012;Harper et al 2012;Li et al 2014), demonstrating the power of AM to discover marker-trait associations in genetically diverse panels or populations (reviewed in Gupta et al 2005;Soto-Cerda and Cloutier 2012). Taking into account the low extension of LD and rapid LD decay observed in different B. napus populations (Bus et al 2011;Xiao et al 2012;Delourme et al 2013), the use of 4025 evenly spaced SNP markers provided an adequate genome coverage to conduct GWAS.…”

Section: Association Mapping Using Gwas and Cqtl Approachesmentioning

confidence: 99%

“…2, 3). The incorporation of both Q and K matrices into a mixed lineal model (MLM) has been successfully used previously in B. napus and others species (Yu et al 2006;Yang et al 2010;Pasam et al 2012;Upadhyaya et al 2013;Li et al 2014). When the MLM ?…”

Section: Association Mapping Using Gwas and Cqtl Approachesmentioning

confidence: 99%

“…Both types of AM approaches have been used in genetic studies in oilseed rape. For instance, GWAS has been used to identify markers associated with phenological and morphological traits ) and seed quality traits (Zou et al 2010;Rezaeizad et al 2011;Harper et al 2012;Li et al 2014). CG has been used to identify polymorphisms in genes involved in glucosinolate biosynthesis (Hasan et al 2008), genes associated with tocopherol content and composition (Fritsche et al 2012) and allelic resistance to Leptosphaeria maculans (Jestin et al 2011) in B. napus. In this study, two different AM approaches, GWAS and candidate QTL (cQTL), were used to identify SNP markers associated with six B. napus seed quality traits.…”

Section: Introductionmentioning

confidence: 99%

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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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Genome‐Wide Association Studies of Important Agronomic Traits in Brassica napus : What We Have Learned and Where We Are Headed

Liu

Wang

Yang

et al. 2022

Annual Plant Reviews Online

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Oilseed rape ( Brassica napus L.; B. napus ) is one of the main oil crops in China as well as in the world. Genome‐wide association studies (GWAS) have revolutionised the field of complex agronomic traits. In B. napus, these include seed yield and yield‐related traits, seed oil content, and abiotic and biotic stress‐tolerance traits over the past decade in which hundreds of thousands to millions of genetic variants across the genomes of hundreds of individuals have been tested to identify genotype–phenotype associations. In this review, we assess the current status of GWAS in terms of genotypes, phenotypes, statistical models, and candidate genes for these agronomic traits in B. napus . Post‐GWAS, the combination of QTL mapping, transcriptomics, and new statistical methods, has allowed us to identify candidate genes associated with specific agronomic traits. In addition, we can use diverse populations, increase the population size, or look for rare variants and structural variations of B. napus by whole‐genome sequencing to minimise the ‘missing heritability’ effects. These approaches are essential for uncovering the genetic mechanisms defining or regulating complex agronomic traits and the delivery of molecular marker‐assisted breeding in B. napus to breed new varieties that are higher yielding but resilient to our changing climate.

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Genome-Wide Association Study Dissects the Genetic Architecture of Seed Weight and Seed Quality in Rapeseed (Brassica napus L.)

Cited by 194 publications

References 75 publications

A genome-wide association study of plant height and primary branch number in rapeseed ( Brassica napus )

A genome-wide association study of plant height and primary branch number in rapeseed ( Brassica napus )

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

Genome‐Wide Association Studies of Important Agronomic Traits in Brassica napus : What We Have Learned and Where We Are Headed

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