Mapping loci controlling fatty acid profiles, oil and protein content by genome-wide association study in Brassica napus

Lipid Metabolism and Improvement in Oilseed Crops: Recent Advances in Multi-Omics Studies

Oilseed crops are rich in plant lipids that not only provide essential fatty acids for the human diet but also play important roles as major sources of biofuels and indispensable raw materials for the chemical industry. The regulation of lipid metabolism genes is a major factor affecting oil production. In this review, we systematically summarize the metabolic pathways related to lipid production and storage in plants and highlight key research advances in characterizing the genes and regulatory factors influencing lipid anabolic metabolism. In addition, we integrate the latest results from multi-omics studies on lipid metabolism to provide a reference to better understand the molecular mechanisms underlying oil anabolism in oilseed crops.

High-Throughput Association Mapping in Brassica napus L.: Methods and Applications

Oil seed rape (Braasica napus L.) is ranked second among oil seed crops cultivated globally for edible oil for human, and seed cake for animal consumption. Recent genetic and genomics advancements highlighted the diversity that exists within B. napus, which is largely discovered using the most promising genetic markers called single nucleotide polymorphism (SNP). Their calling rate is also enhanced to ~100 folds after the continuous advancements in the next generation sequencing (NGS) technologies. As the high throughput of NGS resulted in multi-Giga bases data, the detailed quality control (QC) prior to downstream analyses is a pre-requisite. It mainly involved the removal of false positives, missing proportions, filtering of low-quality SNPs, and adjustments of minor-allele frequency and heterozygosity. After marker-trait association, for conformation of target SNPs, validations of SNPs can be performed using various methods, especially allele-specific PCR assay-based methods have been utilized for SNP genotyping of genes targeting agronomic traits and somaclonal variations occurred during transgenic studies. In the present study, the authors mainly argue on the genotypic progress, and pipelines/methods that are being used for detection, calling, filtering, and validation of SNPs. Also, insight is provided into the application of SNPs in linkage and association mapping, including QTL mapping and genome-wide association studies targeting mainly developmental traits related to the root system and plant architecture, flowering time, silique, and oil quality. Briefly, the present study provides the recent information and recommendations on the SNP genotyping methods and its applications, which can be useful for marker-assisted breeding in B. napus and other crops.

Genomic Regions Associated With Seed Meal Quality Traits in Brassica napus Germplasm

The defatted Brassica napus (rapeseed) meal can be high-protein feed for livestock as the protein value of rapeseed meal is higher than that of the majority of other vegetable proteins. Extensive work has already been carried out on developing canola rapeseed where the focus was on reducing erucic acid and glucosinolate content, with less consideration to other antinutritional factors such as tannin, phytate, sinapine, crude fiber, etc. The presence of these antinutrients limits the use and marketing of rapeseed meals and a significant amount of it goes unused and ends up as waste. We investigated the genetic architecture of crude protein, methionine, tryptophan, total phenols, β-carotene, glucosinolates (GLSs), phytate, tannins, sinapine, and crude fiber content of defatted seed meal samples by conducting a genome-wide association study (GWAS), using a diversity panel comprising 96 B. napus genotypes. Genotyping by sequencing was used to identify 77,889 SNPs, spread over 19 chromosomes. Genetic diversity and phenotypic variations were generally high for the studied traits. A total of eleven genotypes were identified which showed high-quality protein, high antioxidants, and lower amount of antinutrients. A significant negative correlation between protein and limiting amino acids and a significant positive correlation between GLS and phytic acid were observed. General and mixed linear models were used to estimate the association between the SNP markers and the seed quality traits and quantile-quantile (QQ) plots were generated to allow the best-fit algorithm. Annotation of genomic regions around associated SNPs helped to predict various trait-related candidates such as ASP2 and EMB1027 (amino acid biosynthesis); HEMA2, GLU1, and PGM (tryptophan biosynthesis); MS3, CYSD1, and MTO1 (methionine biosynthesis); LYC (β-carotene biosynthesis); HDR and ISPF (MEP pathway); COS1 (riboflavin synthesis); UGT (phenolics biosynthesis); NAC073 (cellulose and hemicellulose biosynthesis); CYT1 (cellulose biosynthesis); BGLU45 and BGLU46 (lignin biosynthesis); SOT12 and UGT88A1 (flavonoid pathway); and CYP79A2, DIN2, and GSTT2 (GLS metabolism), etc. The functional validation of these candidate genes could confirm key seed meal quality genes for germplasm enhancement programs directed at improving protein quality and reducing the antinutritional components in B. napus.

Genome-Wide Association Analysis Combined With Quantitative Trait Loci Mapping and Dynamic Transcriptome Unveil the Genetic Control of Seed Oil Content in Brassica napus L

Rapeseed, an allotetraploid oil crop, provides vegetable oil for human consumption. The growing demand for oilseeds has necessitated the development of rapeseed varieties with improved quality. Therefore, a clear understanding of the genetic basis underlying the seed oil content (SOC) is required. In this study, a natural population comprising 204 diverse accessions and recombinant inbred lines (RILs) derived from Brassica napus and Sinapis alba via distant hybridization were collected for genome-wide association analysis (GWAS) and quantitative trait loci (QTL) mapping of the SOC trait, respectively. The variable coefficient of the RIL and natural populations ranged from 7.43 to 10.43% and 8.40 to 10.91%. Then, a high-density linkage map was constructed based on whole genome re-sequencing (WGS); the map harbored 2,799 bin markers and covered a total distance of 1,835.21 cM, with an average marker interval of 0.66 cM. The QTLs for SOC on chromosome A07 were stably detected in both single and multiple environments. Finally, a novel locus qA07.SOC was identified as the major QTL for SOC based on the GWAS and RIL populations. In addition, the RNA-seq results showed that photosynthesis, lipid biosynthesis proteins, fatty acid metabolism, and unsaturated fatty acid biosynthesis were significantly different between the developed seeds of the two parents of the RIL population. By comparing the variation information and expression levels of the syntenic genes within qA07.SOC and its syntenic genomic regions, as well as through haplotype analysis via GWAS, BnaA07.STR18, BnaA07.NRT1, and BnaA07g12880D were predicted as candidate genes in the qA07.SOC interval. These stable QTLs containing candidate genes and haplotypes can potentially provide a reliable basis for marker-assisted selection in B. napus breeding for SOC.

Physicochemical properties, content, composition and partial least squares models of A. trifoliata seeds oil

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Feasibility of using A. trifoliata seed oil (ASO) as an edible oil was studied.

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A partial least squares regression model for the ASO content was established.

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The PLS model was well suited for the determination of ASO and UFA content.

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Based on the study, High ASO content germplasm could be used in A. trifoliata breeding.

Physicochemical properties, oil content, and fatty acids (FAs) composition are key for determining the value of oil crops. The aim of this study was to illustrate the potential of exploiting A. trifoliata as an edible oil crop, and establish a rapid measurement model for the A. trifoliata seeds oil (ASO) content and composition. In 130 A. trifoliata germplasms, the highest content of ASO was 51.27%, and unsaturated fatty acids (UFAs) mainly accounted for 74–78% of ASO. The partial least squares (PLS) model based on GC–MS and near-infrared spectroscopy was well-suited for the determination of ASO and UFA content; however, the PLS model for oleic acid (OA) and linoleic acid (LA) was not effective. The acid values and peroxide values for ASO also conformed to the Chinese food safety standards. Our findings will provide new insights and guidance for the use of A. trifoliata as oil crops..

Asymmetric Divergence in Transmitted SNPs of DNA Replication/Transcription and Their Impact on Gene Expression in Polyploid Brassica napus

The marked increase in plant genomic data has provided valuable resources for investigating the dynamic evolution of duplicate genes in polyploidy. Brassica napus is an ideal model species for investigating polyploid genome evolution. The present study comprehensively analyzed DNA and RNA variation of two representative B. napus inbredlines, Zhongshuang11 and Zhongyou821, and we investigated gene expression levels of A_n and C_n subgenomes in multiple tissues of the two lines. The distribution of transmitted single nucleotide polymorphisms (SNPs) was significantly different in two subgenomes of B. napus. Gene expression levels were significantly negatively correlated with number of variations in replication and transcription of the corresponding genes, but were positively correlated with the ratios of transmitted SNPs from DNA to RNA. We found a higher density of SNP variation in A_n than that in C_n during DNA replication and more SNPs were transmitted to RNA during transcription, which may contribute to A_n expression dominance. These activities resulted in asymmetrical gene expression in polyploid B. napus. The SNPs transmitted from DNA to RNA could be an important complement feature in comparative genomics, and they may play important roles in asymmetrical genome evolution in polyploidy.

Breeding Canola (Brassica napus L.) for Protein in Feed and Food

Interest in canola (Brassica napus L.). In response to this interest, scientists have been tasked with altering and optimizing the protein production chain to ensure canola proteins are safe for consumption and economical to produce. Specifically, the role of plant breeders in developing suitable varieties with the necessary protein profiles is crucial to this interdisciplinary endeavour. In this article, we aim to provide an overarching review of the canola protein chain from the perspective of a plant breeder, spanning from the genetic regulation of seed storage proteins in the crop to advancements of novel breeding technologies and their application in improving protein quality in canola. A review on the current uses of canola meal in animal husbandry is presented to underscore potential limitations for the consumption of canola meal in mammals. General discussions on the allergenic potential of canola proteins and the regulation of novel food products are provided to highlight some of the challenges that will be encountered on the road to commercialization and general acceptance of canola protein as a dietary protein source.

Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed

Yield is one of the most important agronomic traits for the breeding of rapeseed (Brassica napus L), but its genetic dissection for the formation of high yield remains enigmatic, given the rapid population growth. In the present review, we review the discovery of major loci underlying important agronomic traits and the recent advancement in the selection of complex traits. Further, we discuss the benchmark summary of high-throughput techniques for the high-resolution genetic breeding of rapeseed. Biparental linkage analysis and association mapping have become powerful strategies to comprehend the genetic architecture of complex agronomic traits in crops. The generation of improved crop varieties, especially rapeseed, is greatly urged to enhance yield productivity. In this sense, the whole-genome sequencing of rapeseed has become achievable to clone and identify quantitative trait loci (QTLs). Moreover, the generation of high-throughput sequencing and genotyping techniques has significantly enhanced the precision of QTL mapping and genome-wide association study (GWAS) methodologies. Furthermore, this study demonstrates the first attempt to identify novel QTLs of yield-related traits, specifically focusing on ovule number per pod (ON). We also highlight the recent breakthrough concerning single-locus-GWAS (SL-GWAS) and multi-locus GWAS (ML-GWAS), which aim to enhance the potential and robust control of GWAS for improved complex traits.

Regional association analysis coupled with transcriptome analyses reveal candidate genes affecting seed oil accumulation in Brassica napus

Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions in combination with co-expression analysis reveal candidate genes affecting oil accumulation in Brassica napus. One of the breeding goals in rapeseed production is to enhance the seed oil content to cater to the increased demand for vegetable oils due to a growing global population. To investigate the genetic basis of variation in seed oil content, we used 60 K Brassica Infinium SNP array along with phenotype data of 203 Chinese semi-winter rapeseed accessions to perform a genome-wide analysis of haplotype blocks associated with the oil content. Nine haplotype regions harbouring lipid synthesis/transport-, carbohydrate metabolism- and photosynthesis-related genes were identified as significantly associated with the oil content and were mapped to chromosomes A02, A04, A05, A07, C03, C04, C05, C08 and C09, respectively. Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions combined with transcriptome datasets from 13 accessions was further performed on these nine haplotype regions. This revealed natural variation in the BnTGD3-A02 and BnSSE1-A05 gene regions correlated with the phenotypic variation of the oil content within the A02 and A04 chromosome haplotype regions, respectively. Moreover, co-expression network analysis revealed that BnTGD3-A02 and BnSSE1-A05 were directly linked with fatty acid beta-oxidation-related gene BnKAT2-C04, thus forming a molecular network involved in the potential regulation of seed oil accumulation. The results of this study could be used to combine favourable haplotype alleles for further improvement of the seed oil content in rapeseed.

Development and Validation of Kompetitive Allele-Specific PCR Assays for Erucic Acid Content in Indian Mustard [Brassica juncea (L.) Czern and Coss.]

Brassica juncea L. is the most widely cultivated oilseed crop in Indian subcontinent. Its seeds contain oil with very high concentration of erucic acid (≈50%). Of late, there is increasing emphasis on the development of low erucic acid varieties because of reported association of the consumption of high erucic acid oil with cardiac lipidosis. Erucic acid is synthesized from oleic acid by an elongation process involving two cycles of four sequential steps. Of which, the first step is catalyzed by β-ketoacyl-CoA synthase (KCS) encoded by the fatty acid elongase 1 (FAE1) gene in Brassica. Mutations in the coding region of the FAE1 lead to the loss of KCS activity and consequently a drastic reduction of erucic acid in the seeds. Molecular markers have been developed on the basis of variation available in the coding or promoter region(s) of the FAE1. However, majority of these markers are not breeder friendly and are rarely used in the breeding programs. Present studies were planned to develop robust kompetitive allele-specific PCR (KASPar) assays with high throughput and economics of scale. We first cloned and sequenced FAE1.1 and FAE1.2 from high and low erucic acid (<2%) genotypes of B. juncea (AABB) and its progenitor species, B. rapa (AA) and B. nigra (BB). Sequence comparisons of FAE1.1 and FAE1.2 genes for low and high erucic acid genotypes revealed single nucleotide polymorphisms (SNPs) at 8 and 3 positions. Of these, three SNPs for FAE1.1 and one SNPs for FAE1.2 produced missense mutations, leading to amino acid modifications and inactivation of KCS enzyme. We used SNPs at positions 735 and 1,476 for genes FAE1.1 and FAE1.2, respectively, to develop KASPar assays. These markers were validated on a collection of diverse genotypes and a segregating backcross progeny. KASPar assays developed in this study will be useful for marker-assisted breeding, as these can track recessive alleles in their heterozygous state with high reproducibility.

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.