In silico integration of quantitative trait loci for seed yield and yield-related traits in Brassica napus

Zhou, Qinghong; Fu, Donghui; Mason, Annaliese S.; Zeng, Yong-Chun; Zhao, Chaoxian; Huang, Yongji

doi:10.1007/s11032-013-0002-2

Cited by 36 publications

(26 citation statements)

References 73 publications

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“…Four markers were associated with grain yield, three with seed size, two with secondary branches and one marker each with plant height, seeds/pod, root diameter and root length. Identification of grain yield-related QTLs on chromosomes A2 and A3 of the A-genome validated the QTLs reported by Zhou et al (2014) in B. rapa, the A-genome donor for B. juncea. The grain yields QTLs observed for chromosomes 2 and 3 of the B-genome are novel.…”

Section: Discussionsupporting

confidence: 68%

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Genome-wide association mapping for grain yield components and root traits in Brassica juncea (L.) Czern & Coss.

Akhatar

Banga

2015

Mol Breeding

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We used a Diversity Fixed Foundation Set comprising 48 inbred lines of Brassica juncea and representing all the adaption zones of the crop for association mapping. Extensive phenotypic variations were observed for all the grain yield components and root traits under both irrigated and restricted moisture conditions. The genotypes differed in their responses to moisture stress. Trait averages declined numerically under restricted moisture conditions when compared to a standard irrigation schedule. Canonical analysis demonstrated the importance of primary branches and seed size as the traits of significance for drought susceptibility index. Microsatellite markers (158), representing all the 18 chromosomes, were used to assess the population structure, linkage disequilibrium (LD) in the association panel and marker-trait associations (MTA's). A comparison of four association models [general linear model/GLM(Q-matrix/Q), mixed linear model: MLM(Q?kinship matrix/K), GLM (principal components/PC) and MLM(PC ? K)] showed that GLM(PC) and MLM(PC ? K), incorporating principal components and kinship matrix, were the best models. Maximum proportions of significant results were observed in the models GLM(PC) and MLM(PC ? K). MLM was preferred as there were fewer false positives than GLM. Thirteen significant associations were detected between the molecular markers and agronomic traits. Of these, seven were identified under normal moisture conditions, and six under restricted moisture conditions. Marker-trait associations included four markers associated with grain yield, three with seed size, two with secondary branches and one marker each with plant height, root diameter and root length. A single marker SB1822-1, was repeatedly detected for seed size and grain yield, and was localized at 17.5 cM (centiMorgans) on chromosome B3. Marker SB3872-3 revealed a significant effect under normal moisture conditions on seed size (R 2 % = 15.16) at 60.9 cM on chromosome B5 during the first year. Among the favorable alleles, SB1822-1 had the average positive phenotypic effect for seed size and grain yield. Marker cnu316-3 had maximum positive phenotypic effects on grain yield.

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Section: Discussionsupporting

confidence: 68%

“…Of these, 47 were associated with the seed grain yield. Many QTLs controlling productivity traits have been assigned to different genetic maps and mapping populations in rapeseed-mustard (Zhang et al 2011;Ding et al 2012;Cai et al 2013;Zhou et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Genome-wide association mapping for grain yield components and root traits in Brassica juncea (L.) Czern & Coss.

Akhatar

Banga

2015

Mol Breeding

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“…The integration of those data into meta-analyses may allow the identification of important genomic regions that are potentially usable in breeding programs. For example, Zhou et al (2014) integrated information from 1960 QTLs for seed yield traits that were detected in 15 independent studies, identifying 142 loci that were conserved between the different analyses, including 25 multifunctional loci. Such information represents a first step toward the identification of candidate genes, although fine mapping is complicated in rapeseed by the highly complex genome, the long generation time, and the low recombination rates.…”

Section: Genetic Control Of Traits Related To Seed Yieldmentioning

confidence: 99%

Nitrogen use efficiency in rapeseed. A review

Bouchet

Laperche

Bissuel-Bélaygue

et al. 2016

Agron. Sustain. Dev.

179

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Mineral nitrogen fertilization has improved crop yield over the last century but has also caused air and water pollution. Reduction of nitrogen inputs and maintaining high yields are therefore essential to ensure a more sustainable agriculture. Improving the nitrogen use efficiency (NUE) of crops is therefore needed. Rapeseed, Brassica napus, depends on nitrogen fertilization due to its low NUE, with the ratio of plant nitrogen content to nitrogen supplied often not exceeding 60 %. Here, we review the major phenotypic traits associated with NUE in B. napus, with special emphasis on winter oilseed rape. We discuss the genetic diversity available and potential breeding strategies. The major points are the following: (1) rapeseed seed yield elaboration is complex, with overlapping phases of nitrogen uptake and remobilization during the crop cycle; (2) traits related to nitrogen uptake, such as root length and the amount of nitrogen absorbed after flowering, and traits related to nitrogen remobilization, such as the "staygreen" phenotype, have been identified as possible levers to improve NUE in rapeseed; (3) a substantial body of studies investigating the genetic control of NUE traits have already published and potential candidate genes identified; and (4) rapeseed genetic diversity may be enriched by exploiting interpopulation genetic variation and the closely related gene pools of Brassica rapa and Brassica oleracea.

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“…This combination of resources now permits high-throughput genotyping of large numbers of samples across more than 50 000 SNPs located on the sequenced genome. Large quantities of phenotypic data have also been produced for this crop species, and numerous quantitative trait loci (QTL) identified using linkage or association mapping approaches can now be integrated on to the reference genome sequence (Körber et al 2016;Liu et al 2016;Xu et al 2016;Zhou et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Agricultural selection and presence–absence variation in spring-type canola germplasm

et al. 2018

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Brassica napus (rapeseed, canola) is an important oilseed crop worldwide as well as a recent agricultural hybrid species, resulting from crosses between progenitor B. rapa (turnip) and B. oleracea (cabbage) species in the last few thousand years. No wild form of B. napus is known to exist, making B. napus an interesting model for studies of genetic and genomic evolution in a polyploid under agricultural selective pressure. We generated genotype (Illumina Infinium 60K Brassica array) and phenotype data for elite spring-type B. napus lines from Australia, China and India (only one line). Phenotypically, plant growth, silique development and flowering traits were more likely to differentiate Chinese germplasm, whereas resistance to blackleg disease, secondary branching and seed traits were more likely to differentiate Australian germplasm. Genetic differentiation between the Australian and Chinese populations was low (FST = 0.035). Genetic relationship was not a predictor of similarity in yield traits between lines. Presence–absence variants were detected across the population: variants shared by at least three lines were present in every chromosome in the B. napus genome, and large missing chromosome segments (>1 Mbp) putatively due to A–C genome translocations were observed on chromosomes A7, A10, C1, C2, C6, C8 and C9. Our results highlight that widespread presence–absence variation is usual in B. napus, and may suggest that phenotypic and genetic diversity are not closely linked within spring-type B. napus from Australia and China, although the low sample numbers in our study prevent strong conclusions. We propose that inbreeding and low levels of genetic diversity, coupled with exchanges between the A and C genomes, were major driving forces behind genome evolution in this recent agricultural crop species.

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In silico integration of quantitative trait loci for seed yield and yield-related traits in Brassica napus

Cited by 36 publications

References 73 publications

Genome-wide association mapping for grain yield components and root traits in Brassica juncea (L.) Czern & Coss.

Genome-wide association mapping for grain yield components and root traits in Brassica juncea (L.) Czern & Coss.

Nitrogen use efficiency in rapeseed. A review

Agricultural selection and presence–absence variation in spring-type canola germplasm

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