Breeding histories and selection criteria for oilseed rape in Europe and China identified by genome wide pedigree dissection

Identification of Yellow Seed Color Genes Using Bulked Segregant RNA Sequencing in Brassica juncea L

Yellow seed breeding is an effective method to improve oil yield and quality in rapeseed (Brassica napus L.). However, naturally occurring yellow-seeded genotypes have not been identified in B. napus. Mustard (Brassica juncea L.) has some natural, yellow-seeded germplasms, yet the molecular mechanism underlying this trait remains unclear. In this study, a BC9 population derived from the cross of yellow seed mustard "Wuqi" and brown seed mustard "Wugong" was used to analyze the candidate genes controlling the yellow seed color of B. juncea. Subsequently, yellow-seeded (BY) and brown-seeded (BB) bulks were constructed in the BC9 population and subjected to bulked segregant RNA sequencing (BSR-Seq). A total of 511 differentially expressed genes (DEGs) were identified between the brown and yellow seed bulks. Enrichment analysis revealed that these DEGs were involved in the phenylpropanoid biosynthetic process and flavonoid biosynthetic process, including key genes such as 4CL, C4H, LDOX/TT18, PAL1, PAL2, PAL4, TT10, TT12, TT4, TT8, BAN, DFR/TT3, F3H/TT6, TT19, and CHI/TT5. In addition, 111,540 credible single-nucleotide polymorphisms (SNPs) and 86,319 INDELs were obtained and used for quantitative trait locus (QTL) identification. Subsequently, two significant QTLs on chromosome A09, namely, qSCA09-3 and qSCA09-7, were identified by G' analysis, and five DEGs (BjuA09PAL2, BjuA09TT5, BjuA09TT6, BjuA09TT4, BjuA09TT3) involved in the flavonoid pathway were identified as hub genes based on the protein-to-protein network. Among these five genes, only BjuA09PAL2 and BjuA09F3H had SNPs between BY and BB bulks. Interestingly, the majority of SNPs in BjuA09PAL2 were consistent with the SNPs identified between the high-quality assembled B. juncea reference genome "T84-66" (brown-seed) and "AU213" (yellow-seed). Therefore, BjuA09PAL2, which encodes phenylalanine lyase, was considered as the candidate gene associated with yellow seed color of B. juncea. The identification of a novel gene associated with the yellow seed coloration of B. juncea through this study may play a significant role in enhancing yellow seed breeding in rapeseed.

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.

Magnesium and calcium overaccumulate in the leaves of a schengen3 mutant of Brassica rapa

Magnesium (Mg) and calcium (Ca) are essential mineral nutrients poorly supplied in many human food systems. In grazing livestock, Mg and Ca deficiencies are costly welfare issues. Here, we report a Brassica rapa loss-of-function schengen3 (sgn3) mutant, braA.sgn3.a-1, which accumulates twice as much Mg and a third more Ca in its leaves. We mapped braA.sgn3.a to a single recessive locus using a forward ionomic screen of chemically mutagenized lines with subsequent backcrossing and linked-read sequencing of second back-crossed, second filial generation (BC2F2) segregants. Confocal imaging revealed a disrupted root endodermal diffusion barrier, consistent with SGN3 encoding a receptor-like kinase required for normal formation of Casparian strips, as reported in thale cress (Arabidopsis thaliana). Analysis of the spatial distribution of elements showed elevated extracellular Mg concentrations in leaves of braA.sgn3.a-1, hypothesized to result from preferential export of excessive Mg from cells to ensure suitable cellular concentrations. This work confirms a conserved role of SGN3 in controlling nutrient homeostasis in B. rapa, and reveals mechanisms by which plants are able to deal with perturbed shoot element concentrations resulting from a "leaky" root endodermal barrier. Characterization of variation in leaf Mg and Ca accumulation across a mutagenized population of B. rapa shows promise for using such populations in breeding programs to increase edible concentrations of essential human and animal nutrients.

Omics: The way forward to enhance abiotic stress tolerance in Brassica napus L

Plant abiotic stresses negative affects growth and development, causing a massive reduction in global agricultural production. Rapeseed (Brassica napus L.) is a major oilseed crop because of its economic value and oilseed production. However, its productivity has been reduced by many environmental adversities. Therefore, it is a prime need to grow rapeseed cultivars, which can withstand numerous abiotic stresses. To understand the various molecular and cellular mechanisms underlying the abiotic stress tolerance and improvement in rapeseed, omics approaches have been extensively employed in recent years. This review summarized the recent advancement in genomics, transcriptomics, proteomics, metabolomics, and their imploration in abiotic stress regulation in rapeseed. Some persisting bottlenecks have been highlighted, demanding proper attention to fully explore the omics tools. Further, the potential prospects of the CRISPR/Cas9 system for genome editing to assist molecular breeding in developing abiotic stress-tolerant rapeseed genotypes have also been explained. In short, the combination of integrated omics, genome editing, and speed breeding can alter rapeseed production worldwide.

Pattern recognition based on machine learning identifies oil adulteration and edible oil mixtures

Previous studies have shown that each edible oil type has its own characteristic fatty acid profile; however, no method has yet been described allowing the identification of oil types simply based on this characteristic. Moreover, the fatty acid profile of a specific oil type can be mimicked by a mixture of 2 or more oil types. This has led to fraudulent oil adulteration and intentional mislabeling of edible oils threatening food safety and endangering public health. Here, we present a machine learning method to uncover fatty acid patterns discriminative for ten different plant oil types and their intra-variability. We also describe a supervised end-to-end learning method that can be generalized to oil composition of any given mixtures. Trained on a large number of simulated oil mixtures, independent test dataset validation demonstrates that the model has a 50^th percentile absolute error between 1.4–1.8% and a 90^th percentile error of 4–5.4% for any 3-way mixtures of the ten oil types. The deep learning model can also be further refined with on-line training. Because oil-producing plants have diverse geographical origins and hence slightly varying fatty acid profiles, an online-training method provides also a way to capture useful knowledge presently unavailable. Our method allows the ability to control product quality, determining the fair price of purchased oils and in-turn allowing health-conscious consumers the future of accurate labeling.

Fraudulent adulteration of edible oils is based on the fact that their characteristic fatty acid profile can be mimicked with mixtures of other oil types. Here, the authors use a deep learning method to uncover fatty acid patterns discriminative for ten different plant oil types and to discern composition of mixtures.

Genome-wide selection footprints and deleterious variations in young Asian allotetraploid rapeseed

Brassica napus (AACC, 2n = 38) is an important oilseed crop grown worldwide. However, little is known about the population evolution of this species, the genomic difference between its major genetic groups, such as European and Asian rapeseed, and the impacts of historical large-scale introgression events on this young tetraploid. In this study, we reported the de novo assembly of the genome sequences of an Asian rapeseed (B. napus), Ningyou 7, and its four progenitors and compared these genomes with other available genomic data from diverse European and Asian cultivars. Our results showed that Asian rapeseed originally derived from European rapeseed but subsequently significantly diverged, with rapid genome differentiation after hybridization and intensive local selective breeding. The first historical introgression of B. rapa dramatically broadened the allelic pool but decreased the deleterious variations of Asian rapeseed. The second historical introgression of the double-low traits of European rapeseed (canola) has reshaped Asian rapeseed into two groups (double-low and double-high), accompanied by an increase in genetic load in the double-low group. This study demonstrates distinctive genomic footprints and deleterious SNP (single nucleotide polymorphism) variants for local adaptation by recent intra- and interspecies introgression events and provides novel insights for understanding the rapid genome evolution of a young allopolyploid crop.

CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat

Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High-throughput SNP arrays, or 'SNP chips', can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb (http://snpdb.appliedbioinformatics.com.au), a database for SNP array data produced by the Illumina Infinium™ hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop-breeding activities.

Whole-Genome Resequencing of a Worldwide Collection of Rapeseed Accessions Reveals the Genetic Basis of Ecotype Divergence

Rapeseed (Brassica napus), an important oilseed crop, has adapted to diverse climate zones and latitudes by forming three main ecotype groups, namely winter, semi-winter, and spring types. However, genetic variations underlying the divergence of these ecotypes are largely unknown. Here, we report the global pattern of genetic polymorphisms in rapeseed determined by resequencing a worldwide collection of 991 germplasm accessions. A total of 5.56 and 5.53 million single-nucleotide polymorphisms (SNPs) as well as 1.86 and 1.92 million InDels were identified by mapping reads to the reference genomes of "Darmor-bzh" and "Tapidor," respectively. We generated a map of allelic drift paths that shows splits and mixtures of the main populations, and revealed an asymmetric evolution of the two subgenomes of B. napus by calculating the genetic diversity and linkage disequilibrium parameters. Selective-sweep analysis revealed genetic changes in genes orthologous to those regulating various aspects of plant development and response to stresses. A genome-wide association study identified SNPs in the promoter regions of FLOWERING LOCUS T and FLOWERING LOCUS C orthologs that corresponded to the different rapeseed ecotype groups. Our study provides important insights into the genomic footprints of rapeseed evolution and flowering-time divergence among three ecotype groups, and will facilitate screening of molecular markers for accelerating rapeseed breeding.

Dissection of the genetic architecture of three seed-quality traits and consequences for breeding in Brassica napus

Genome-wide association studies (GWASs) combining high-throughput genome resequencing and phenotyping can accelerate the dissection of genetic architecture and identification of genes for plant complex traits. In this study, we developed a rapeseed genomic variation map consisting of 4 542 011 SNPs and 628 666 INDELs. GWAS was performed for three seed-quality traits, including erucic acid content (EAC), glucosinolate content (GSC) and seed oil content (SOC) using 3.82 million polymorphisms in an association panel. Six, 49 and 17 loci were detected to be associated with EAC, GSC and SOC in multiple environments, respectively. The mean total contribution of these loci in each environment was 94.1% for EAC and 87.9% for GSC, notably higher than that for SOC (40.1%). A high correlation was observed between phenotypic variance and number of favourable alleles for associated loci, which will contribute to breeding improvement by pyramiding these loci. Furthermore, candidate genes were detected underlying associated loci, based on functional polymorphisms in gene regions where sequence variation was found to correlate with phenotypic variation. Our approach was validated by detection of well-characterized FAE1 genes at each of two major loci for EAC on chromosomes A8 and C3, along with MYB28 genes at each of three major loci for GSC on chromosomes A9, C2 and C9. Four novel candidate genes were detected by correlation between GSC and SOC and observed sequence variation, respectively. This study provides insights into the genetic architecture of three seed-quality traits, which would be useful for genetic improvement of B. napus.

Brassicaceae Mustards: Traditional and Agronomic Uses in Australia and New Zealand

Commonly cultivated Brassicaceae mustards, namely garlic mustard (Alliaria petiolata), white mustard (Brassica alba), Ethiopian mustard (B. carinata), Asian mustard (B. juncea), oilseed rape (B. napus), black mustard (B. nigra), rapeseed (B. rapa), white ball mustard (Calepina irregularis), ball mustard (Neslia paniculata), treacle mustard (Erysimum repandum), hedge mustard (Sisymbrium officinale), Asian hedge mustard (S. orientale), smooth mustard (S. erysimoides) and canola are the major economically important oilseed crops in many countries. Mustards were naturalized to Australia and New Zealand and Australia is currently the second largest exporter of Brassicaceae oilseeds to meet the global demand for a healthy plant-derived oil, high in polyunsaturated fats. Apart from providing edible oil, various parts of these plants and many of their phytochemicals have been used traditionally for both agronomic as well as medicinal purposes, with evidence of their use by early Australian and New Zealand settlers and also the indigenous population. This review provides an overview of the current knowledge of traditional and agronomic uses of Brassicaceae oilseeds and mustards with a focus on their importance in Australia and New Zealand.

Development and Applications of a High Throughput Genotyping Tool for Polyploid Crops: Single Nucleotide Polymorphism (SNP) Array

Polypoid species play significant roles in agriculture and food production. Many crop species are polyploid, such as potato, wheat, strawberry, and sugarcane. Genotyping has been a daunting task for genetic studies of polyploid crops, which lags far behind the diploid crop species. Single nucleotide polymorphism (SNP) array is considered to be one of, high-throughput, relatively cost-efficient and automated genotyping approaches. However, there are significant challenges for SNP identification in complex, polyploid genomes, which has seriously slowed SNP discovery and array development in polyploid species. Ploidy is a significant factor impacting SNP qualities and validation rates of SNP markers in SNP arrays, which has been proven to be a very important tool for genetic studies and molecular breeding. In this review, we (1) discussed the pros and cons of SNP array in general for high throughput genotyping, (2) presented the challenges of and solutions to SNP calling in polyploid species, (3) summarized the SNP selection criteria and considerations of SNP array design for polyploid species, (4) illustrated SNP array applications in several different polyploid crop species, then (5) discussed challenges, available software, and their accuracy comparisons for genotype calling based on SNP array data in polyploids, and finally (6) provided a series of SNP array design and genotype calling recommendations. This review presents a complete overview of SNP array development and applications in polypoid crops, which will benefit the research in molecular breeding and genetics of crops with complex genomes.