Identification of QTL influencing seed oil content, fatty acid profile and days to flowering in Brassica napus L.

Javed, Nasir; Geng, Jianfeng; Tahir, Muhammad; McVetty, P. B. E.; Li, Genyi; Duncan, Robert

doi:10.1007/s10681-015-1565-2

Cited by 38 publications

(37 citation statements)

References 51 publications

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“…The parameter DYSFLB did not have any relationship with YIELD, and although there were several QTLs explaining a larger portion of the variation within specific environments, these QTLs did not respond differently across treatments. The QTL that explained the most variation (45.3% CT, 54.0% ST) at Viluco 2015 was located on linkage group A02, which aligns with the existing literature for this trait within B. napus (Chen et al 2010;Nelson et al 2014;Javed et al 2016). Given that this QTL was found within the environment that had shorter days, it may be a candidate QTL if germplasm is being transferred from long-day to short-day environments.…”

Section: Discussionsupporting

confidence: 83%

“…Although the difference in photoperiod was minor between these two treatments, this difference, combined with the increased temperatures in the ST, could potentially strengthen the genetic signal and thereby increase the amount of genetic variation explained by the QTL in the ST. In the absence of photoperiod differences or vernalisation requirements, days to initiation of flowering has proven to be a quantitative trait (Javed et al 2016). The results in this study show that DYSFLB can be predicted accurately with WGP.…”

Section: Discussionmentioning

confidence: 62%

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Linkage mapping and whole-genome predictions in canola (Brassica napus) subjected to differing temperature treatments

Koscielny¹,

Gardner

Technow³

et al. 2020

Crop Pasture Sci.

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Canola (Brassica napus L.) is grown on >8 Mha in Canada and is sensitive to high temperatures; therefore, research on breeding methodologies to improve heat-stress tolerance is warranted. This study utilised a doubled-haploid population created from two parents (PB36 and PB56) that differed in their ability to set seed following growth at high temperatures. The experiment was designed to identify potential quantitative trait loci (QTLs) responsible for conferring tolerance to increased temperatures, and to utilise this population as a test case for evaluating the prospects of whole-genome prediction. The population was phenotyped in a split-plot, randomised complete block experimental design at three locations with two planting-date treatments. The first planting date was during the normal planting period (control), and the second planting was timed to experience increased average temperatures (1.7°C, 2.0°C and 1.2°C) and increased number of days with maximum temperatures above the critical temperature of 29.5°C (4, 12 and 3 days). The stress treatment reduced yield on average by 16.7%. There were 66 QTLs discovered across the nine traits collected. Given the quantitative nature of the traits collected, the ability to use whole-genome prediction was investigated. The prediction accuracies ranged from 0.14 (yield) to 0.66 (1000-seed weight). Prediction had higher accuracy within the stress treatment than within the control treatment for seven of the nine traits, demonstrating that phenotyping within a stress environment can provide valuable data for whole-genome predictions.

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Section: Discussionsupporting

confidence: 83%

Section: Discussionmentioning

confidence: 62%

Linkage mapping and whole-genome predictions in canola (Brassica napus) subjected to differing temperature treatments

Koscielny¹,

Gardner

Technow³

et al. 2020

Crop Pasture Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The genomic regions of QTLs from other populations, DY (‘Darmor-bzh’ × ‘Yudal’, RNSL (‘Rapid’ × ‘NSL96/25’)75, Z5 (‘zy036’ × ‘51,070’)76, SG (‘Sollux’ × ‘Gaoyou’)77, TN (‘Tapidor’ × ‘Ningyou7’)42, SO (‘Sansibar’ × ‘Oase’)78, PT (‘Polo’ × ‘Topas’)79, and M201 × M20280, were obtained via electronic PCR (e-PCR)81, which was performed with the primer sequences of the molecular markers flanking the QTL confidence intervals using the genomic sequences of ‘Darmor- bzh ’ as templates.…”

Section: Methodsmentioning

confidence: 99%

Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus

Chao

Wang

et al. 2017

Sci Rep

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High-density linkage maps can improve the precision of QTL localization. A high-density SNP-based linkage map containing 3207 markers covering 3072.7 cM of the Brassica napus genome was constructed in the KenC-8 × N53-2 (KNDH) population. A total of 67 and 38 QTLs for seed oil and protein content were identified with an average confidence interval of 5.26 and 4.38 cM, which could explain up to 22.24% and 27.48% of the phenotypic variation, respectively. Thirty-eight associated genomic regions from BSA overlapped with and/or narrowed the SOC-QTLs, further confirming the QTL mapping results based on the high-density linkage map. Potential candidates related to acyl-lipid and seed storage underlying SOC and SPC, respectively, were identified and analyzed, among which six were checked and showed expression differences between the two parents during different embryonic developmental periods. A large primary carbohydrate pathway based on potential candidates underlying SOC- and SPC-QTLs, and interaction networks based on potential candidates underlying SOC-QTLs, was constructed to dissect the complex mechanism based on metabolic and gene regulatory features, respectively. Accurate QTL mapping and potential candidates identified based on high-density linkage map and BSA analyses provide new insights into the complex genetic mechanism of oil and protein accumulation in the seeds of rapeseed.

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“…Many studies have been undertaken to detect and map the QTL of oil content in crops for use in marker-assisted breeding selection as well as for important oil biosynthesis gene identification [55][56][57][58][59][60][61]. Soybean and sesame are among the different crops that have adopted this strategy [61][62][63][64][65].…”

Section: Omics Studies Of Seed Oil Cropsmentioning

confidence: 99%

Review: Omics and Strategic Yield Improvement in Oil Crops

Teh

Neoh

Ithnin

et al. 2017

J Americ Oil Chem Soc

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Crop yield improvement is essential for feeding the growing world population without concomitant increases in land allocated to agriculture. Oil crops are critical components of food supply as well as non-food applications. Oil palm is of particular value due to its significantly higher yield per unit area of land as compared to other oil crops. In the context of sustainable production of edible oils, this review will discuss the role of biochemical-omics techniques, including metabolomics, transcriptomics and proteomics research for yield improvement through plant breeding; in particular, the unique challenges of the mesocarp-oil bearing perennial crop, oil palm, are specifically discussed along with perspectives on what is needed for future crop improvement. Future oil crop improvement will need to go beyond classical trait selection, and omics research needs to go beyond looking at oil biosynthesis and fruit development. We need to explore carbon supply and flux, plant stress response, nutrient uptake and water use through a combination of genetics, biochemistry, epigenetics and gene interaction coupled to more detailed and continuous phenotypic data analysis.

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Identification of QTL influencing seed oil content, fatty acid profile and days to flowering in Brassica napus L.

Cited by 38 publications

References 51 publications

Linkage mapping and whole-genome predictions in canola (Brassica napus) subjected to differing temperature treatments

Linkage mapping and whole-genome predictions in canola (Brassica napus) subjected to differing temperature treatments

Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus

Review: Omics and Strategic Yield Improvement in Oil Crops

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