A high-density SNP genotyping array for Brassica napus and its ancestral diploid species based on optimised selection of single-locus markers in the allotetraploid genome

Phenomic Selection for Hybrid Rapeseed Breeding

Phenomic selection is a recent approach suggested as a low-cost, high-throughput alternative to genomic selection. Instead of using genetic markers, it employs spectral data to predict complex traits using equivalent statistical models. Phenomic selection has been shown to outperform genomic selection when using spectral data that was obtained within the same generation as the traits that were predicted. However, for hybrid breeding, the key question is whether spectral data from parental genotypes can be used to effectively predict traits in the hybrid generation. Here, we aimed to evaluate the potential of phenomic selection for hybrid rapeseed breeding. We performed predictions for various traits in a structured population of 410 test hybrids, grown in multiple environments, using near-infrared spectroscopy data obtained from harvested seeds of both the hybrids and their parental lines with different linear and nonlinear models. We found that phenomic selection within the hybrid generation outperformed genomic selection for seed yield and plant height, even when spectral data was collected at single locations, while being less affected by population structure. Furthermore, we demonstrate that phenomic prediction across generations is feasible, and selecting hybrids based on spectral data obtained from parental genotypes is competitive with genomic selection. We conclude that phenomic selection is a promising approach for rapeseed breeding that can be easily implemented without any additional costs or efforts as near-infrared spectroscopy is routinely assessed in rapeseed breeding.

Genomic prediction in Brassica napus: evaluating the benefit of imputed whole-genome sequencing data

Advances in sequencing technology allow whole plant genomes to be sequenced with high quality. Combining genotypic and phenotypic data in genomic prediction helps breeders to select crossing partners in partially phenotyped populations. In plant breeding programs, the cost of sequencing entire breeding populations still exceeds available genotyping budgets. Hence, the method for genotyping is still mainly single nucleotide polymorphism (SNP) arrays; however, arrays are unable to assess the entire genome- and population-wide diversity. A compromise involves genotyping the entire population using an SNP array and a subset of the population with whole-genome sequencing. Both datasets can then be used to impute markers from whole-genome sequencing onto the entire population. Here, we evaluate whether imputation of whole-genome sequencing data enhances genomic predictions, using data from a nested association mapping population of rapeseed (Brassica napus). Employing two cross-validation schemes that mimic scenarios for the prediction of close and distant relatives, we show that imputed marker data do not significantly improve prediction accuracy, likely due to redundancy in relationship estimates and imputation errors. In simulation studies, only small improvements were observed, further corroborating the findings. We conclude that SNP arrays are already equipped with the information that is added by imputation through relationship and linkage disequilibrium.

A chromosome-scale assembly of Brassica carinata (BBCC) accession HC20 containing resistance to multiple pathogens and an early generation assessment of introgressions into B. juncea (AABB)

Brassica carinata (BBCC) commonly referred to as Ethiopian mustard is a natural allotetraploid containing the genomes of Brassica nigra (BB) and Brassica oleracea (CC). It is an oilseed crop endemic to the northeastern regions of Africa. Although it is under limited cultivation, B. carinata is valuable as it is resistant/highly tolerant to most of the pathogens affecting widely cultivated Brassica species of the U's triangle. We report a chromosome-scale genome assembly of B. carinata accession HC20 using long-read Oxford Nanopore sequencing and Bionano optical maps. The assembly has a scaffold N50 of ~39.8 Mb and covers ~1.11 Gb of the genome. We compared the long-read genome assemblies of the U's triangle species and found extensive gene collinearity between the diploids and allopolyploids with no evidence of major gene losses. Therefore, B. juncea (AABB), B. napus (AACC), and B. carinata can be regarded as strict allopolyploids. We cataloged the nucleotide-binding and leucine-rich repeat immune receptor (NLR) repertoire of B. carinata and, identified 465 NLRs, and compared these with the NLRs in the other Brassica species. We investigated the extent and nature of early-generation genomic interactions between the constituent genomes of B. carinata and B. juncea in interspecific crosses between the two species. Besides the expected recombination between the constituent B genomes, extensive homoeologous exchanges were observed between the A and C genomes. Interspecific crosses, therefore, can be used for transferring disease resistance from B. carinata to B. juncea and broadening the genetic base of the two allotetraploid species.

Envirotyping within a multi-environment trial allowed identifying genetic determinants of winter oilseed rape yield stability

KEY MESSAGE

A comprehensive environmental characterization allowed identifying stable and interactive QTL for seed yield: QA09 and QC09a were detected across environments; whereas QA07a was specifically detected on the most stressed environments. A main challenge for rapeseed consists in maintaining seed yield while adapting to climate changes and contributing to environmental-friendly cropping systems. Breeding for cultivar adaptation is one of the keys to meet this challenge. Therefore, we propose to identify the genetic determinant of seed yield stability for winter oilseed rape using GWAS coupled with a multi-environmental trial and to interpret them in the light of environmental characteristics. Due to a comprehensive characterization of a multi-environmental trial using 79 indicators, four contrasting envirotypes were defined and used to identify interactive and stable seed yield QTL. A total of four QTLs were detected, among which, QA09 and QC09a, were stable (detected at the multi-environmental trial scale or for different envirotypes and environments); and one, QA07a, was specifically detected into the most stressed envirotype. The analysis of the molecular diversity at QA07a showed a lack of genetic diversity within modern lines compared to older cultivars bred before the selection for low glucosinolate content. The results were discussed in comparison with other studies and methods as well as in the context of breeding programs.

Genomic and phenomic predictions help capture low-effect alleles promoting seed germination in oilseed rape in addition to QTL analyses

KEY MESSAGE

Phenomic prediction implemented on a large diversity set can efficiently predict seed germination, capture low-effect favorable alleles that are not revealed by GWAS and identify promising genetic resources. Oilseed rape faces many challenges, especially at the beginning of its developmental cycle. Achieving rapid and uniform seed germination could help to ensure a successful establishment and therefore enabling the crop to compete with weeds and tolerate stresses during the earliest developmental stages. The polygenic nature of seed germination was highlighted in several studies, and more knowledge is needed about low- to moderate-effect underlying loci in order to enhance seed germination effectively by improving the genetic background and incorporating favorable alleles. A total of 17 QTL were detected for seed germination-related traits, for which the favorable alleles often corresponded to the most frequent alleles in the panel. Genomic and phenomic predictions methods provided moderate-to-high predictive abilities, demonstrating the ability to capture small additive and non-additive effects for seed germination. This study also showed that phenomic prediction estimated phenotypic values closer to phenotypic values than GEBV. Finally, as the predictive ability of phenomic prediction was less influenced by the genetic structure of the panel, it is worth using this prediction method to characterize genetic resources, particularly with a view to design prebreeding populations.

A systems genomics and genetics approach to identify the genetic regulatory network for lignin content in Brassica napus seeds

Seed quality traits of oilseed rape, Brassica napus (B. napus), exhibit quantitative inheritance determined by its genetic makeup and the environment via the mediation of a complex genetic architecture of hundreds to thousands of genes. Thus, instead of single gene analysis, network-based systems genomics and genetics approaches that combine genotype, phenotype, and molecular phenotypes offer a promising alternative to uncover this complex genetic architecture. In the current study, systems genetics approaches were used to explore the genetic regulation of lignin traits in B. napus seeds. Four QTL (qLignin_A09_1, qLignin_A09_2, qLignin_A09_3, and qLignin_C08) distributed on two chromosomes were identified for lignin content. The qLignin_A09_2 and qLignin_C08 loci were homologous QTL from the A and C subgenomes, respectively. Genome-wide gene regulatory network analysis identified eighty-three subnetworks (or modules); and three modules with 910 genes in total, were associated with lignin content, which was confirmed by network QTL analysis. eQTL (expression quantitative trait loci) analysis revealed four cis-eQTL genes including lignin and flavonoid pathway genes, cinnamoyl-CoA-reductase (CCR1), and TRANSPARENT TESTA genes TT4, TT6, TT8, as causal genes. The findings validated the power of systems genetics to identify causal regulatory networks and genes underlying complex traits. Moreover, this information may enable the research community to explore new breeding strategies, such as network selection or gene engineering, to rewire networks to develop climate resilience crops with better seed quality.

Genetic control of root morphology in response to nitrogen across rapeseed diversity

Rapeseed (Brassica napus L.) is an oil-containing crop of great economic value but with considerable nitrogen requirement. Breeding root systems that efficiently absorb nitrogen from the soil could be a driver to ensure genetic gains for more sustainable rapeseed production. The aim of this study is to identify genomic regions that regulate root morphology in response to nitrate availability. The natural variability offered by 300 inbred lines was screened at two experimental locations. Seedlings grew hydroponically with low or elevated nitrate levels. Fifteen traits related to biomass production and root morphology were measured. On average across the panel, a low nitrate level increased the root-to-shoot biomass ratio and the lateral root length. A large phenotypic variation was observed, along with important heritability values and genotypic effects, but low genotype-by-nitrogen interactions. Genome-wide association study and bulk segregant analysis were used to identify loci regulating phenotypic traits. The first approach nominated 319 SNPs that were combined into 80 QTLs. Three QTLs identified on the A07 and C07 chromosomes were stable across nitrate levels and/or experimental locations. The second approach involved genotyping two groups of individuals from an experimental F2 population created by crossing two accessions with contrasting lateral root lengths. These individuals were found in the tails of the phenotypic distribution. Co-localized QTLs found in both mapping approaches covered a chromosomal region on the A06 chromosome. The QTL regions contained some genes putatively involved in root organogenesis and represent selection targets for redesigning the root morphology of rapeseed.

Integrated multi-omics analyses and genome-wide association studies reveal prime candidate genes of metabolic and vegetative growth variation in canola

Genome-wide association studies (GWAS) identified thousands of genetic loci associated with complex plant traits, including many traits of agronomical importance. However, functional interpretation of GWAS results remains challenging because of large candidate regions due to linkage disequilibrium. High-throughput omics technologies, such as genomics, transcriptomics, proteomics and metabolomics open new avenues for integrative systems biological analyses and help to nominate systems information supported (prime) candidate genes. In the present study, we capitalise on a diverse canola population with 477 spring-type lines which was previously analysed by high-throughput phenotyping of growth-related traits and by RNA sequencing and metabolite profiling for multi-omics-based hybrid performance prediction. We deepened the phenotypic data analysis, now providing 123 time-resolved image-based traits, to gain insight into the complex relations during early vegetative growth and reanalysed the transcriptome data based on the latest Darmor-bzh v10 genome assembly. Genome-wide association testing revealed 61 298 robust quantitative trait loci (QTL) including 187 metabolite QTL, 56814 expression QTL and 4297 phenotypic QTL, many clustered in pronounced hotspots. Combining information about QTL colocalisation across omics layers and correlations between omics features allowed us to discover prime candidate genes for metabolic and vegetative growth variation. Prioritised candidate genes for early biomass accumulation include A06p05760.1_BnaDAR (PIAL1), A10p16280.1_BnaDAR, C07p48260.1_BnaDAR (PRL1) and C07p48510.1_BnaDAR (CLPR4). Moreover, we observed unequal effects of the Brassica A and C subgenomes on early biomass production.

Genome-Wide Mapping of Quantitative Trait Loci for Yield-Attributing Traits of Peanut

Peanuts (Arachis hypogaea L.) are important high-protein and oil-containing legume crops adapted to arid to semi-arid regions. The yield and quality of peanuts are complex quantitative traits that show high environmental influence. In this study, a recombinant inbred line population (RIL) (Valencia-C × JUG-03) was developed and phenotyped for nine traits under two environments. A genetic map was constructed using 1323 SNP markers spanning a map distance of 2003.13 cM. Quantitative trait loci (QTL) analysis using this genetic map and phenotyping data identified seventeen QTLs for nine traits. Intriguingly, a total of four QTLs, two each for 100-seed weight (HSW) and shelling percentage (SP), showed major and consistent effects, explaining 10.98% to 14.65% phenotypic variation. The major QTLs for HSW and SP harbored genes associated with seed and pod development such as the seed maturation protein-encoding gene, serine-threonine phosphatase gene, TIR-NBS-LRR gene, protein kinase superfamily gene, bHLH transcription factor-encoding gene, isopentyl transferase gene, ethylene-responsive transcription factor-encoding gene and cytochrome P450 superfamily gene. Additionally, the identification of 76 major epistatic QTLs, with PVE ranging from 11.63% to 72.61%, highlighted their significant role in determining the yield- and quality-related traits. The significant G × E interaction revealed the existence of the major role of the environment in determining the phenotype of yield-attributing traits. Notably, the seed maturation protein-coding gene in the vicinity of major QTLs for HSW can be further investigated to develop a diagnostic marker for HSW in peanut breeding. This study provides understanding of the genetic factor governing peanut traits and valuable insights for future breeding efforts aimed at improving yield and quality.

Simulation-based establishment of base pools for a hybrid breeding program in winter rapeseed

KEY MESSAGE

Simulation planned pre-breeding can increase the efficiency of starting a hybrid breeding program. Starting a hybrid breeding program commonly comprises a grouping of the initial germplasm in two pools and subsequent selection on general combining ability. Investigations on pre-breeding steps before starting the selection on general combining ability are not available. Our goals were (1) to use computer simulations on the basis of DNA markers and testcross data to plan crosses that separate genetically two initial germplasm pools of rapeseed, (2) to carry out the planned crosses, and (3) to verify experimentally the pool separation as well as the increase in testcross performance. We designed a crossing program consisting of four cycles of recombination. In each cycle, the experimentally generated material was used to plan the subsequent crossing cycle with computer simulations. After finishing the crossing program, the initially overlapping pools were clearly separated in principal coordinate plots. Doubled haploid lines derived from the material of crossing cycles 1 and 2 showed an increase in relative testcross performance for yield of about 5% per cycle. We conclude that simulation-designed pre-breeding crossing schemes, that were carried out before the general combining ability-based selection of a newly started hybrid breeding program, can save time and resources, and in addition conserve more of the initial genetic variation than a direct start of a hybrid breeding program with general combining ability-based selection.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Haplotype blocks for genomic prediction: a comparative evaluation in multiple crop datasets

In modern plant breeding, genomic selection is becoming the gold standard for selection of superior genotypes. The basis for genomic prediction models is a set of phenotyped lines along with their genotypic profile. With high marker density and linkage disequilibrium (LD) between markers, genotype data in breeding populations tends to exhibit considerable redundancy. Therefore, interest is growing in the use of haplotype blocks to overcome redundancy by summarizing co-inherited features. Moreover, haplotype blocks can help to capture local epistasis caused by interacting loci. Here, we compared genomic prediction methods that either used single SNPs or haplotype blocks with regards to their prediction accuracy for important traits in crop datasets. We used four published datasets from canola, maize, wheat and soybean. Different approaches to construct haplotype blocks were compared, including blocks based on LD, physical distance, number of adjacent markers and the algorithms implemented in the software "Haploview" and "HaploBlocker". The tested prediction methods included Genomic Best Linear Unbiased Prediction (GBLUP), Extended GBLUP to account for additive by additive epistasis (EGBLUP), Bayesian LASSO and Reproducing Kernel Hilbert Space (RKHS) regression. We found improved prediction accuracy in some traits when using haplotype blocks compared to SNP-based predictions, however the magnitude of improvement was very trait- and model-specific. Especially in settings with low marker density, haplotype blocks can improve genomic prediction accuracy. In most cases, physically large haplotype blocks yielded a strong decrease in prediction accuracy. Especially when prediction accuracy varies greatly across different prediction models, prediction based on haplotype blocks can improve prediction accuracy of underperforming models. However, there is no "best" method to build haplotype blocks, since prediction accuracy varied considerably across methods and traits. Hence, criteria used to define haplotype blocks should not be viewed as fixed biological parameters, but rather as hyperparameters that need to be adjusted for every dataset.

Genetic Diversity and Population Structure in Ethiopian Mustard (Brassica carinata A. Braun) as Revealed by Single Nucleotide Polymorphism Markers

Ethiopian mustard (Brassica carinata A. Braun) is currently one of the potential oilseeds dedicated to the production for biofuel and other bio-industrial applications. The crop is assumed to be native to Ethiopia where a number of diversified B. carinata germplasms are found and conserved ex situ. However, there is very limited information on the genetic diversity and population structure of the species. This study aimed to investigate the genetic diversity and population structure of B. carinata genotypes of different origins using high-throughput single nucleotide polymorphism (SNP) markers. We used Brassica 90K Illumina InfiniumTM SNP array for genotyping 90 B. carinata genotypes, and a total of 11,499 informative SNP markers were used for investigating the population structure and genetic diversity. The structure analysis, principal coordinate analysis (PcoA) and neighbor-joining tree analysis clustered the 90 B. carinata genotypes into two distinct subpopulations (Pop1 and Pop2). The majority of accessions (65%) were clustered in Pop1, mainly obtained from Oromia and South West Ethiopian People (SWEP) regions. Pop2 constituted dominantly of breeding lines and varieties, implying target selection contributed to the formation of distinct populations. Analysis of molecular variance (AMOVA) revealed a higher genetic variation (93%) within populations than between populations (7%), with low genetic differentiation (PhiPT = 0.07) and poor correlation between genetic and geographical distance (R = 0.02). This implies the presence of gene flow (Nm > 1) and weak geographical structure of accessions. Genetic diversity indices showed the presence of moderate genetic diversity in B. carinata populations with an average genetic diversity value (HE = 0.31) and polymorphism information content (PIC = 0.26). The findings of this study provide important and relevant information for future breeding and conservation efforts of B. carinata.

Genetic and molecular analysis of stem rot (Sclerotinia sclerotiorum) resistance in Brassica napus (canola type)

Identifying the molecular and genetic basis of resistance to Sclerotinia stem rot (Sclerotinia sclerotiorum) is critical for developing long-term and cost-effective management of this disease in rapeseed/canola (Brassica napus). Current cultural or chemical management options provide, at best, only partial and/or sporadic control. Towards this, a B. napus breeding population (Mystic x Rainbow), including the parents, F1, F2, BC1P1 and BC1P2, was utilized in a field study to determine the inheritance pattern of Sclerotinia stem rot resistance (based on stem lesion length, SLL). Broad sense heritability was 0.58 for SLL and 0.44 for days to flowering (DTF). There was a significant negative correlation between SLL and stem diameter (SD) (r = -0.39) and between SLL and DTF (r = -0.28), suggesting co-selection of SD and DTF traits, along with SLL, should assist in improving overall resistance. Non-additive genetic variance was evident for SLL, DTF, and SD. In a genome wide association study (GWAS), a significant quantitative trait locus (QTL) was identified for SLL. Several putative candidate marker trait associations (MTA) were located within this QTL region. Overall, this study has provided valuable new understanding of inheritance of resistance to S. sclerotiorum, and has identified QTL, MTAs and transgressive segregants with high-level resistances. Together, these will foster more rapid selection for multiple traits associated with Sclerotinia stem rot resistance, by enabling breeders to make critical choices towards selecting/developing cultivars with enhanced resistance to this devastating pathogen.

Genome composition in Brassica interspecific hybrids affects chromosome inheritance and viability of progeny

Interspecific hybridization is widespread in nature and can result in the formation of new hybrid species as well as the transfer of traits between species. However, the fate of newly formed hybrid lineages is relatively understudied. We undertook pairwise crossing between multiple genotypes of three Brassica allotetraploid species Brassica juncea (2n = AABB), Brassica carinata (2n = BBCC), and Brassica napus (2n = AACC) to generate AABC, BBAC, and CCAB interspecific hybrids and investigated chromosome inheritance and fertility in these hybrids and their self-pollinated progeny. Surprisingly, despite the presence of a complete diploid genome in all hybrids, hybrid fertility was very low. AABC and BBAC first generation (F1) hybrids both averaged ~16% pollen viability compared to 3.5% in CCAB hybrids: most CCAB hybrid flowers were male-sterile. AABC and CCAB F1 hybrid plants averaged 5.5 and 0.5 seeds per plant, respectively, and BBAC F1 hybrids ~56 seeds/plant. In the second generation (S1), all confirmed self-pollinated progeny resulting from CCAB hybrids were sterile, producing no self-pollinated seeds. Three AABC S1 hybrids putatively resulting from unreduced gametes produced 3, 14, and 182 seeds each, while other AABC S1 hybrids averaged 1.5 seeds/plant (0-8). BBAC S1 hybrids averaged 44 seeds/plant (range 0-403). We also observed strong bias towards retention rather than loss of the haploid genomes, suggesting that the subgenomes in the Brassica allotetraploids are already highly interdependent, such that loss of one subgenome is detrimental to fertility and viability. Our results suggest that relationships between subgenomes determine hybridization outcomes in these species.

Genetic factors inherited from both diploid parents interact to affect genome stability and fertility in resynthesized allotetraploid Brassica napus

Established allopolyploids are known to be genomically stable and fertile. However, in contrast, most newly resynthesized allopolyploids are infertile and meiotically unstable. Identifying the genetic factors responsible for genome stability in newly formed allopolyploid is key to understanding how 2 genomes come together to form a species. One hypothesis is that established allopolyploids may have inherited specific alleles from their diploid progenitors which conferred meiotic stability. Resynthesized Brassica napus lines are often unstable and infertile, unlike B. napus cultivars. We tested this hypothesis by characterizing 41 resynthesized B. napus lines produced by crosses between 8 Brassica rapa and 8 Brassica oleracea lines for copy number variation resulting from nonhomologous recombination events and fertility. We resequenced 8 B. rapa and 5 B. oleracea parent accessions and analyzed 19 resynthesized lines for allelic variation in a list of meiosis gene homologs. SNP genotyping was performed using the Illumina Infinium Brassica 60K array for 3 individuals per line. Self-pollinated seed set and genome stability (number of copy number variants) were significantly affected by the interaction between both B. rapa and B. oleracea parental genotypes. We identified 13 putative meiosis gene candidates which were significantly associated with frequency of copy number variants and which contained putatively harmful mutations in meiosis gene haplotypes for further investigation. Our results support the hypothesis that allelic variants inherited from parental genotypes affect genome stability and fertility in resynthesized rapeseed.

Meta-analysis of seed weight QTLome using a consensus and highly dense genetic map in Brassica napus L

KEY MESSAGE

We report here the discovery of high-confidence MQTL regions and of putative candidate genes associated with seed weight in B. napus using a highly dense consensus genetic map and by comparing various large-scale multiomics datasets. Seed weight (SW) is a direct determinant of seed yield in Brassica napus and is controlled by many loci. To unravel the main genomic regions associated with this complex trait, we used 13 available genetic maps to construct a consensus and highly dense map, comprising 40,401 polymorphic markers and 9191 genetic bins, harboring a cumulative length of 3047.8 cM. Then, we performed a meta-analysis using 639 projected SW quantitative trait loci (QTLs) obtained from studies conducted since 1999, enabling the identification of 57 meta-QTLS (MQTLs). The confidence intervals of our MQTLs were 9.8 and 4.3 times lower than the average CIs of the original QTLs for the A and C subgenomes, respectively, resulting in the detection of some key genes and several putative novel candidate genes associated with SW. By comparing the genes identified in MQTL intervals with multiomics datasets and coexpression analyses of common genes, we defined a more reliable and shorter list of putative candidate genes potentially involved in the regulation of seed maturation and SW. As an example, we provide a list of promising genes with high expression levels in seeds and embryos (e.g., BnaA03g04230D, BnaC03g08840D, BnaA10g29580D and BnaA03g27410D) that can be more finely studied through functional genetics experiments or that may be useful for MQTL-assisted breeding for SW. The high-density genetic consensus map and the single nucleotide polymorphism (SNP) physical map generated from the latest B. napus cv. Darmor-bzh v10 assembly will be a valuable resource for further mapping and map-based cloning of other important traits.

Fine mapping of BnDM1-the gene regulating indeterminate inflorescence in Brassica napus

KEY MESSAGE

A candidate gene Bndm1 related to determinate inflorescence was mapped to a 128-kb interval on C02 in Brassica napus. Brassica napus plants with determinate inflorescence exhibit improved traits in field production, such as lower plant height, improved lodging resistance, and consistent maturity. Compared to plants with indeterminate inflorescence, such features are favorable for mechanized harvesting techniques. Here, using a natural mutant 6138 with determinate inflorescence, it is demonstrated that determinate inflorescence reduces plant height significantly without affecting thousand-grain weight and yield per plant. Determinacy was regulated by a single recessive gene, Bndm1. Using a combination of SNP arrays and map-based cloning, we mapped the locus of determinacy to a 128-kb region on C02. Based on sequence comparisons and the reported functions of candidate genes in this region, we predicted BnaC02.knu (a homolog of KNU in Arabidopsis) as a possible candidate gene of Bndm1 for controlling determinate inflorescence. We found a 623-bp deletion in a region upstream of the KNU promoter in the mutant. This deletion led to the significant overexpression of BnaC02.knu in the mutant compared to that in the ZS11 line. The correlation between this deletion and determinate inflorescence was examined in natural populations. The results indicated that the deletion affected the normal transcription of BnaC02.knu in the plants with determinate inflorescence and played an important role in maintaining flower development. This study presents as a new material for optimizing plant architecture and breeding novel canola varieties suitable for mechanized production. Moreover, our findings provide a theoretical basis for analyzing the molecular mechanisms underlying the formation of determinate inflorescence in B. napus.

Elucidating the process of SNPs identification in non-reference genome crops

Advances in the next generation sequencing technologies, genome reduction techniques and bioinformatics tools have given a big impetus to the identification of genome-wide single nucleotide polymorphisms (SNPs) in crops. NGS technologies can make available a large amount of sequence data in a short span of time. The huge data requires detailed bioinformatics analysis steps, including preprocessing, mapping, and identification of sequence variants. A plethora of available software meant for sequence analysis is used for different sequence analysis steps. However, SNPs identification is far more challenging for orphaned crops or non-reference genome crops. The current article reports different steps for in silico SNPs identification in a sequential manner and proposes some mapping approaches using CLC Genomics software that could provide an alternative method for SNPs identification in orphan crops having no reference genome. The three mapping approaches: Common reference map from progenitor genomes (CRMPG), step-wise use of progenitor genomes (SWPG) and de novo assembly of sequence read (DASR) were validated with the dd-RAD sequenced data of two genotypes from Brassica juncea.Communicated by Ramaswamy H. Sarma.

Key Advances in the New Era of Genomics-Assisted Disease Resistance Improvement of Brassica Species

Disease resistance improvement remains a major focus in breeding programs as diseases continue to devastate Brassica production systems due to intensive cultivation and climate change. Genomics has paved the way to understand the complex genomes of Brassicas, which has been pivotal in the dissection of the genetic underpinnings of agronomic traits driving the development of superior cultivars. The new era of genomics-assisted disease resistance breeding has been marked by the development of high-quality genome references, accelerating the identification of disease resistance genes controlling both qualitative (major) gene and quantitative resistance. This facilitates the development of molecular markers for marker assisted selection and enables genome editing approaches for targeted gene manipulation to enhance the genetic value of disease resistance traits. This review summarizes the key advances in the development of genomic resources for Brassica species, focusing on improved genome references, based on long-read sequencing technologies and pangenome assemblies. This is further supported by the advances in pathogen genomics, which have resulted in the discovery of pathogenicity factors, complementing the mining of disease resistance genes in the host. Recognizing the co-evolutionary arms race between the host and pathogen, it is critical to identify novel resistance genes using crop wild relatives and synthetic cultivars or through genetic manipulation via genome-editing to sustain the development of superior cultivars. Integrating these key advances with new breeding techniques and improved phenotyping using advanced data analysis platforms will make disease resistance improvement in Brassica species more efficient and responsive to current and future demands.

Investigation of mutation load and rate in androgenic mutant lines of rapeseed in early generations evaluated by high-density SNP genotyping

Oilseed rape (Brassica napus) is an important oil crop distributed worldwide with a broad adaptation to different climate zones. The cultivation of rapeseed is one of the most commercially viable areas in crop production. Altogether 269,093 ha of rapeseed are cultivated in Kazakhstan. However, all rapeseed cultivars and lines cultivated in Kazakhstan on an industrial scale predominantly belong to the foreign breeding system. Therefore, the formation of a diverse genetic pool for breeding new, highly productive cultivars adopted to the environmental conditions of Kazakhstan is the most important goal in country selection programs. In this work, we have developed ethyl methanesulfonate (EMS) doubled haploid mutant lines from plant material of cultivars 'Galant' and 'Kris' to broad diversity of rapeseed in Kazakhstan. The development of mutant lines was performed via embryo callusogenesis or embryo secondary callusogenesis. Mutants were investigated by Brassica90k SNP array, and we were able to locate 24,657 SNPs from 26,256 SNPs filtered by quality control on the genome assembly (Bra_napus_v2.0). Only 18,831 SNPs were assigned to the available annotated genomic features. The most frequent combination of mutations according to reference controls was adenine with guanine (70%), followed by adenine with cytosine (28.8%), and only minor fractions were cytosine with guanine (0.54%) and adenine with thymine (0.59%). We revealed 5606.27 markers for 'Kris' and 4893.01 markers for 'Galant' by mutation occurrence. Most mutation occurrences were occupied by double mutations where progenitors and offspring were homozygous by different alleles, enabling the selection of appropriate genotypes in a short period of time. Regarding the biological impact of mutations, 861 variants were reported as having a low predicted impact, with 1042 as moderate and 121 as high; all others were reported as belonging to non-coding sequences, intergenic regions, and other features with the effect of modifiers. Protein encoding genes, such as wall-associated receptor kinase-like protein 5, TAO1-like disease resistance protein, receptor-like protein 12, and At5g42460-like F-box protein, contained more than two variable positions, with an impact on their biological activities. Nevertheless, the obtained mutant lines were able to survive and reproduce. Mutant lines, which include moderate and high impact mutations in encoding genes, are a perfect pool not only for MAS but also for the investigation of the fundamental basis of protein functions. For the first time, a collection of mutant lines was developed in our country to improve the selection of local rapeseed cultivars.

Systematic trait dissection in oilseed rape provides a comprehensive view, further insight, and exact roadmap for yield determination

Background

Yield is the most important and complex trait that is influenced by numerous relevant traits with very complicated interrelations. While there are a large number of studies on the phenotypic relationship and genetic basis of yield traits, systematic studies with further dissection focusing on yield are limited. Therefore, there is still lack of a comprehensive and in-depth understanding of the determination of yield.

Results

In this study, yield was systematically dissected at the phenotypic, genetic to molecular levels in oilseed rape (Brassica napus L.). The analysis of correlation, network, and principal component for 21 traits in BnaZN-RIL population showed that yield was determined by a complex trait network with key contributors. The analysis of the constructed high-density single nucleotide polymorphism (SNP) linkage map revealed the concentrated distribution of distorted and heterozygous markers, likely due to selection on genes controlling the growth period and yield heterosis. A total of 134 consensus quantitative trait loci (QTL) were identified for 21 traits, of which all were incorporated into an interconnecting QTL network with dozens of hub-QTL. Four representative hub-QTL were further dissected to the target or candidate genes that governed the causal relationships between the relevant traits.

Conclusions

The highly consistent results at the phenotypic, genetic, and molecular dissecting demonstrated that yield was determined by a multilayer composite network that involved numerous traits and genes showing complex up/down-stream and positive/negative regulation. This provides a systematic view, further insight, and exact roadmap for yield determination, which represents a significant advance toward the understanding and dissection of complex traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13068-022-02134-w.

Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L

Brassica oleracea is an agronomically important species of the Brassicaceae family, including several nutrient-rich vegetables grown and consumed across the continents. But its sustainability is heavily constrained by a range of destructive pathogens, among which, clubroot disease, caused by a biotrophic protist Plasmodiophora brassicae, has caused significant yield and economic losses worldwide, thereby threatening global food security. To counter the pathogen attack, it demands a better understanding of the complex phenomenon of Brassica-P. brassicae pathosystem at the physiological, biochemical, molecular, and cellular levels. In recent years, multiple omics technologies with high-throughput techniques have emerged as successful in elucidating the responses to biotic and abiotic stresses. In Brassica spp., omics technologies such as genomics, transcriptomics, ncRNAomics, proteomics, and metabolomics are well documented, allowing us to gain insights into the dynamic changes that transpired during host-pathogen interactions at a deeper level. So, it is critical that we must review the recent advances in omics approaches and discuss how the current knowledge in multi-omics technologies has been able to breed high-quality clubroot-resistant B. oleracea. This review highlights the recent advances made in utilizing various omics approaches to understand the host resistance mechanisms adopted by Brassica crops in response to the P. brassicae attack. Finally, we have discussed the bottlenecks and the way forward to overcome the persisting knowledge gaps in delivering solutions to breed clubroot-resistant Brassica crops in a holistic, targeted, and precise way.

Genetic Diversity and Selection Signatures in Synthetic-Derived Wheats and Modern Spring Wheat

Synthetic hexaploid wheats and their derived advanced lines were subject to empirical selection in developing genetically superior cultivars. To investigate genetic diversity, patterns of nucleotide diversity, population structure, and selection signatures during wheat breeding, we tested 422 wheat accessions, including 145 synthetic-derived wheats, 128 spring wheat cultivars, and 149 advanced breeding lines from Pakistan. A total of 18,589 high-quality GBS-SNPs were identified that were distributed across the A (40%), B (49%), and D (11%) genomes. Values of population diversity parameters were estimated across chromosomes and genomes. Genome-wide average values of genetic diversity and polymorphic information content were estimated to be 0.30 and 0.25, respectively. Neighbor-joining (NJ) tree, principal component analysis (PCA), and kinship analyses revealed that synthetic-derived wheats and advanced breeding lines were genetically diverse. The 422 accessions were not separated into distinct groups by NJ analysis and confirmed using the PCA. This conclusion was validated with both relative kinship and Rogers' genetic distance analyses. EigenGWAS analysis revealed that 32 unique genome regions had undergone selection. We found that 50% of the selected regions were located in the B-genome, 29% in the D-genome, and 21% in the A-genome. Previously known functional genes or QTL were found within the selection regions associated with phenology-related traits such as vernalization, adaptability, disease resistance, and yield-related traits. The selection signatures identified in the present investigation will be useful for understanding the targets of modern wheat breeding in Pakistan.

Brassica napus Bacterial Assembly Processes Vary with Plant Compartment and Growth Stage but Not between Lines

Holobiont bacterial community assembly processes are an essential element to understanding the plant microbiome. To elucidate these processes, leaf, root, and rhizosphere samples were collected from eight lines of Brassica napus in Saskatchewan over the course of 10 weeks. We then used ecological null modeling to disentangle the community assembly processes over the growing season in each plant part. The root was primarily dominated by stochastic community assembly processes, which is inconsistent with previous studies that suggest of a highly selective root environment. Leaf assembly processes were primarily stochastic as well. In contrast, the rhizosphere was a highly selective environment. The dominant rhizosphere selection process leads to more similar communities. Assembly processes in all plant compartments were dependent on plant growth stage with little line effect on community assembly. The foundations of assembly in the leaf were due to the harsh environment, leading to dominance of stochastic effects, whereas the stochastic effects in the root interior likely arise due to competitive exclusion or priority effects. Engineering canola microbiomes should occur during periods of strong selection assuming strong selection could promote beneficial bacteria. For example, engineering the microbiome to resist pathogens, which are typically aerially born, should focus on the flowering period, whereas microbiomes to enhance yield should likely be engineered postflowering as the rhizosphere is undergoing strong selection. IMPORTANCE In order to harness the microbiome for more sustainable crop production, we must first have a better understanding of microbial community assembly processes that occurring during plant development. This study examines the bacterial community assembly processes of the leaf, root, and rhizosphere of eight different lines of Brassica napus over the growing season. The influence of growth stage and B. napus line were examined in conjunction with the assembly processes. Understanding what influences the assembly processes of crops might allow for more targeted breeding efforts by working with the plant to manipulate the microbiome when it is undergoing the strongest selection pressure.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

Development of the PARMS Marker of the Dominant Genic Male Sterility (DGMS) Line and Its Utilization in Rapeseed (Brassica napus L.) Breeding

The 8029AB line is a dominant genic male sterility (DGMS) two-type line in Brassica napus L., which can be used in a three-line approach for the seed production of rapeseed hybrids. Genetic analyses have demonstrated that the sterility of 8029A is controlled by a single dominant nuclear gene (BnMS5^e) interacting with one recessive gene (BnMS5^c). Six pairs of penta-primer amplification refractory mutation system (PARMS) markers were designed according to the sequence of BnMS5^a, BnMS5^c and BnMS5^e. Two pairs of these PARMS markers were successfully identified and validated. The PARMS markers MS5-1Fc/MS5-1Ft/MS5-1R12 could distinguish BnMS5^c from BnMS5^a/BnMS5^e, and the PARMS markers MS5-2Ft/MS5-2Fa/MS5-1R12 could genotype BnMS5^a and BnMS5^c/BnMS5^e. The combination of these two pairs of PARMS markers could be used to identify the presence or absence of BnMS5^a/BnMS5^c/BnMS5^e effectively. Consequently, marker-assisted selection can be carried out in the early generation to shorten the breeding period and improve the breeding efficiency.

Different Shades of Kale-Approaches to Analyze Kale Variety Interrelations

Brassica oleracea is a vegetable crop with an amazing morphological diversity. Among the various crops derived from B. oleracea, kale has been in the spotlight globally due to its various health-benefitting compounds and many different varieties. Knowledge of the existing genetic diversity is essential for the improved breeding of kale. Here, we analyze the interrelationships, population structures, and genetic diversity of 72 kale and cabbage varieties by extending our previous diversity analysis and evaluating the use of summed potential lengths of shared haplotypes (SPLoSH) as a new method for such analyses. To this end, we made use of the high-density Brassica 60K SNP array, analyzed SNPs included in an available Brassica genetic map, and used these resources to generate and evaluate the information from SPLoSH data. With our results we could consistently differentiate four groups of kale across all analyses: the curly kale varieties, Italian, American, and Russian varieties, as well as wild and cultivated types. The best results were achieved by using SPLoSH information, thus validating the use of this information in improving analyses of interrelations in kale. In conclusion, our definition of kale includes the curly varieties as the kales in a strict sense, regardless of their origin. These results contribute to a better understanding of the huge diversity of kale and its interrelations.

Exploiting High-Throughput Indoor Phenotyping to Characterize the Founders of a Structured B. napus Breeding Population

Phenotyping is considered a significant bottleneck impeding fast and efficient crop improvement. Similar to many crops, Brassica napus, an internationally important oilseed crop, suffers from low genetic diversity, and will require exploitation of diverse genetic resources to develop locally adapted, high yielding and stress resistant cultivars. A pilot study was completed to assess the feasibility of using indoor high-throughput phenotyping (HTP), semi-automated image processing, and machine learning to capture the phenotypic diversity of agronomically important traits in a diverse B. napus breeding population, SKBnNAM, introduced here for the first time. The experiment comprised 50 spring-type B. napus lines, grown and phenotyped in six replicates under two treatment conditions (control and drought) over 38 days in a LemnaTec Scanalyzer 3D facility. Growth traits including plant height, width, projected leaf area, and estimated biovolume were extracted and derived through processing of RGB and NIR images. Anthesis was automatically and accurately scored (97% accuracy) and the number of flowers per plant and day was approximated alongside relevant canopy traits (width, angle). Further, supervised machine learning was used to predict the total number of raceme branches from flower attributes with 91% accuracy (linear regression and Huber regression algorithms) and to identify mild drought stress, a complex trait which typically has to be empirically scored (0.85 area under the receiver operating characteristic curve, random forest classifier algorithm). The study demonstrates the potential of HTP, image processing and computer vision for effective characterization of agronomic trait diversity in B. napus, although limitations of the platform did create significant variation that limited the utility of the data. However, the results underscore the value of machine learning for phenotyping studies, particularly for complex traits such as drought stress resistance.

Construction of transgenic detection system of Brassica napus L. based on single nucleotide polymorphism chip

Brassica napus L. is a vital oil crop in China. As auxiliary tools for rapeseed breeding, transgenic technologies play a considerable role in heterosis, variety improvement, and pest resistance. Research on transgenic detection technologies is of great significance for the introduction, supervision, and development of transgenic rapeseed in China. However, the transgenic detection methods currently in use are complex and time-consuming, with low output. A single nucleotide polymorphism (SNP) chip can effectively overcome such limitations. In the present study, we collected 40 transgenic elements and designed 291 probes. The probe sequences were submitted to Illumina Company, and the Infinium chip technology was used to prepare SNP chips. In the present Brassica napus transgenic detection experiment, 84 high-quality probes of 17 transgenic elements were preliminarily screened, and genotyping effect was optimised for the probe signal value. Ultimately, a transgenic detection system for B. napus was developed. The developed system has the advantages of simple operation, minimal technical errors, and stable detection outcomes. A transgenic detection sensitivity test revealed that the probe designed could accurately detect 1% of transgenic samples and had high detection sensitivity. In addition, in repeatability tests, the CaMV35S promoter coefficient of variation was approximately 3.58%. Therefore, the SNP chip had suitable repeatability in transgene detection. The SNP chip developed could be used to construct transgenic detection systems for B. napus.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-03062-6.

Evolutionary divergence in embryo and seed coat development of U's Triangle Brassica species illustrated by a spatiotemporal transcriptome atlas

The economically valuable Brassica species include the six related members of U's Triangle. Despite the agronomic and economic importance of these Brassicas, the impacts of evolution and relatively recent domestication events on the genetic landscape of seed development have not been comprehensively examined in these species. Here we present a 3D transcriptome atlas for the six species of U's Triangle, producing a unique resource that captures gene expression data for the major subcompartments of the seed, from the unfertilized ovule to the mature embryo and seed coat. This comprehensive dataset for seed development in tetraploid and ancestral diploid Brassicas provides new insights into evolutionary divergence and expression bias at the gene and subgenome levels during the domestication of these valued crop species. Comparisons of gene expression associated with regulatory networks and metabolic pathways operating in the embryo and seed coat during seed development reveal differences in storage reserve accumulation and fatty acid metabolism among the six Brassica species. This study illustrates the genetic underpinnings of seed traits and the selective pressures placed on seed production, providing an immense resource for continued investigation of Brassica polyploid biology, genomics and evolution.

Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review

Linking phenotypes and genotypes to identify genetic architectures that regulate important traits is crucial for plant breeding and the development of plant genomics. In recent years, genome-wide association studies (GWASs) have been applied extensively to interpret relationships between genes and traits. Successful GWAS application requires comprehensive genomic and phenotypic data from large populations. Although multiple high-throughput DNA sequencing approaches are available for the generation of genomics data, the capacity to generate high-quality phenotypic data is lagging far behind. Traditional methods for plant phenotyping mostly rely on manual measurements, which are laborious, inaccurate, and time-consuming, greatly impairing the acquisition of phenotypic data from large populations. In contrast, high-throughput phenotyping has unique advantages, facilitating rapid, non-destructive, and high-throughput detection, and, in turn, addressing the shortcomings of traditional methods. Aim of Review: This review summarizes the current status with regard to the integration of high-throughput phenotyping and GWAS in plants, in addition to discussing the inherent challenges and future prospects. Key Scientific Concepts of Review: High-throughput phenotyping, which facilitates non-contact and dynamic measurements, has the potential to offer high-quality trait data for GWAS and, in turn, to enhance the unraveling of genetic structures of complex plant traits. In conclusion, high-throughput phenotyping integration with GWAS could facilitate the revealing of coding information in plant genomes.

Utilization of a Sugarcane100K Single Nucleotide Polymorphisms Microarray-Derived High-Density Genetic Map in Quantitative Trait Loci Mapping and Function Role Prediction of Genes Related to Chlorophyll Content in Sugarcane

Chlorophyll is the most important pigment for plant photosynthesis that plays an important role in crop growth and production. In this study, the chlorophyll content trait was explored to improve sugarcane yield. Two hundred and eighty-five F₁ progenies from the cross YT93-159 × ROC22 with significantly different chlorophyll contents were included as test materials. The chlorophyll content of the +1 leaves during elongation phase was measured using a SPAD-502 meter through a three-crop cycle (plant cane, first ratoon, and second ratoon). Linkage analysis was conducted on a high-density genetic map constructed based on the sugarcane 100K SNP chip. In addition, Fv/Fm, plant height, stalk diameter, brix data were collected on plant cane during the elongation and maturation phases. The results showed that the +1 leaf SPAD values, which can be used as an important reference to evaluate the growth potential of sugarcane, were significantly and positively correlated with the Fv/Fm during elongation phase, as well as with plant height, stalk diameter, and brix during maturity phase (P < 0.01). The broad sense heritability (H ²) of the chlorophyll content trait was 0.66 for plant cane crop, 0.67 for first ratoon crop, and 0.73 for second ratoon crop, respectively, indicating that this trait was mainly controlled by genetic factors. Thirty-one quantitative trait loci (QTL) were detected by QTL mapping. Among them, a major QTL, qCC-R1, could account for 12.95% of phenotypic variation explained (PVE), and the other 30 minor QTLs explained 2.37-7.99% PVE. Twenty candidate genes related to chlorophyll content were identified in the QTLs plus a 200-Kb extension region within either sides, of which four were homologous genes involved in the chlorophyll synthesis process and the remaining 16 played a certain role in chlorophyll catabolic pathway, chloroplast organization, or photosynthesis. These results provide a theoretical reference for analyzing the genetic mechanism of chlorophyll synthesis and subsequent improvement of photosynthetic characteristics in sugarcane.

Quantitative Trait Locus Mapping of Resistance to Turnip Yellows Virus in Brassica rapa and Brassica oleracea and Introgression of These Resistances by Resynthesis Into Allotetraploid Plants for Deployment in Brassica napus

Turnip yellows virus (TuYV) is aphid-transmitted and causes considerable yield losses in oilseed rape (OSR, Brassica napus, genome: AACC) and vegetable brassicas. Insecticide control of the aphid vector is limited due to insecticide resistance and the banning of the most effective active ingredients in the EU. There is only one source of TuYV resistance in current commercial OSR varieties, which has been mapped to a single dominant quantitative trait locus (QTL) on chromosome A04. We report the identification, characterisation, and mapping of TuYV resistance in the diploid progenitor species of OSR, Brassica rapa (genome: AA), and Brassica oleracea (genome: CC). Phenotyping of F₁ populations, produced from within-species crosses between resistant and susceptible individuals, revealed the resistances were quantitative and partially dominant. QTL mapping of segregating backcross populations showed that the B. rapa resistance was controlled by at least two additive QTLs, one on chromosome A02 and the other on chromosome A06. Together, they explained 40.3% of the phenotypic variation. In B. oleracea, a single QTL on chromosome C05 explained 22.1% of the phenotypic variation. The TuYV resistance QTLs detected in this study are different from those in the extant commercial resistant varieties. To exploit these resistances, an allotetraploid (genome: AACC) plant line was resynthesised from the interspecific cross between the TuYV-resistant B. rapa and B. oleracea lines. Flow cytometry confirmed that plantlets regenerated from the interspecific cross had both A and C genomes and were mixoploid. To stabilise ploidy, a fertile plantlet was self-pollinated to produce seed that had the desired resynthesised, allotetraploid genome AACC. Phenotyping of the resynthesised plants confirmed their resistance to TuYV. Genotyping with resistance-linked markers identified during the mapping in the progenitors confirmed the presence of all TuYV resistance QTLs from B. rapa and B. oleracea. This is the first report of TuYV resistance mapped in the Brassica C genome and of an allotetraploid AACC line possessing dual resistance to TuYV originating from both of its progenitors. The introgression into OSR can now be accelerated, utilising marker-assisted selection, and this may reduce selection pressure for TuYV isolates that are able to overcome existing sources of resistance to TuYV.

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.

Status and advances in mining for blackleg (Leptosphaeria maculans) quantitative resistance (QR) in oilseed rape (Brassica napus)

KEY MESSAGE

Quantitative resistance (QR) loci discovered through genetic and genomic analyses are abundant in the Brassica napus genome, providing an opportunity for their utilization in enhancing blackleg resistance. Quantitative resistance (QR) has long been utilized to manage blackleg in Brassica napus (canola, oilseed rape), even before major resistance genes (R-genes) were extensively explored in breeding programmes. In contrast to R-gene-mediated qualitative resistance, QR reduces blackleg symptoms rather than completely eliminating the disease. As a polygenic trait, QR is controlled by numerous genes with modest effects, which exerts less pressure on the pathogen to evolve; hence, its effectiveness is more durable compared to R-gene-mediated resistance. Furthermore, combining QR with major R-genes has been shown to enhance resistance against diseases in important crops, including oilseed rape. For these reasons, there has been a renewed interest among breeders in utilizing QR in crop improvement. However, the mechanisms governing QR are largely unknown, limiting its deployment. Advances in genomics are facilitating the dissection of the genetic and molecular underpinnings of QR, resulting in the discovery of several loci and genes that can be potentially deployed to enhance blackleg resistance. Here, we summarize the efforts undertaken to identify blackleg QR loci in oilseed rape using linkage and association analysis. We update the knowledge on the possible mechanisms governing QR and the advances in searching for the underlying genes. Lastly, we lay out strategies to accelerate the genetic improvement of blackleg QR in oilseed rape using improved phenotyping approaches and genomic prediction tools.

The metabolic environment of the developing embryo: A multidisciplinary approach on oilseed rapeseed

Brassicaceae seeds consist of three genetically distinct structures: the embryo, endosperm and seed coat, all of which are involved in assimilate allocation during seed development. The complexity of their metabolic interrelations remains unresolved to date. In the present study, we apply state-of-the-art imaging and analytical approaches to assess the metabolic environment of the Brassica napus embryo. Nuclear magnetic resonance imaging (MRI) provided volumetric data on the living embryo and endosperm, revealing how the endosperm envelops the embryo, determining endosperm's priority in assimilate uptake from the seed coat during early development. MRI analysis showed higher levels of sugars in the peripheral endosperm facing the seed coat, but a lower sugar content within the central vacuole and the region surrounding the embryo. Feeding intact siliques with ¹³C-labeled sucrose allowed tracing of the post-phloem route of sucrose transfer within the seed at the heart stage of embryogenesis, by means of mass spectrometry imaging. Quantification of over 70 organic and inorganic compounds in the endosperm revealed shifts in their abundance over different stages of development, while sugars and potassium were the main determinants of osmolality throughout these stages. Our multidisciplinary approach allows access to the hidden aspects of endosperm metabolism, a task which remains unattainable for the small-seeded model plant Arabidopsis thaliana.

Development of B. carinata with super-high erucic acid content through interspecific hybridization

KEY MESSAGE

Disomic alien chromosome addition Brassica carinata lines with super-high erucic acid content were developed through interspecific hybridization with B. juncea and characterized using molecular, cytological and biochemical techniques. Brassica carinata [A.] Braun (BBCC, 2n = 34) is a climate-resilient oilseed. Its seed oil is high in erucic acid (> 40%), rendering it well suited for the production of biofuel and other bio-based applications. To enhance the competitiveness of B. carinata with high erucic B. napus (HEAR), lines with super-high erucic acid content were developed through interspecific hybridization. To this end, a fad2B null allele from Brassica juncea (AABB, 2n = 36) was introgressed into B. carinata, resulting in a B. carinata fad2B mutant with erucic acid levels of over 50%. Subsequently, the FAE allele from B. rapa spp. yellow sarson (AA, 2n = 20) was transferred to the fad2B B. carinata line, yielding lines with erucic acid contents of up to 57.9%. Molecular analysis using the Brassica 90 K Illumina Infinium™ SNP genotyping array identified these lines as disomic alien chromosome addition lines, with two extra A08 chromosomes containing the BrFAE gene. The alien chromosomes from B. rapa were clearly distinguished by molecular cytogenetics in one of the addition lines. Analysis of microspore-derived offspring and hybrids from crosses with a CMS B. carinata line showed that the transfer rate of the A08 chromosome into male gametes was over 98%, resulting in almost completely stable transmission of an A08 chromosome copy into the progeny. The increase in erucic acid levels was accompanied by changes in the proportions of other fatty acids depending on the genetic changes that were introduced in the interspecific hybrids, providing valuable insights into erucic acid metabolism in Brassica.

Genomic background selection to reduce the mutation load after random mutagenesis

Random mutagenesis is a standard procedure to increase allelic variation in a crop species, especially in countries where the use of genetically modified crops is limited due to legal constraints. The chemical mutagen EMS is used in many species to induce random mutations throughout the genome with high mutation density. The major drawback for functional analysis is a high background mutation load in a single plant that must be eliminated by subsequent backcrossing, a time and resource-intensive activity. Here, we demonstrate that genomic background selection combined with marker-assisted selection is an efficient way to select individuals with reduced background mutations within a short period. We identified BC1 plants with a significantly higher share of the recurrent parent genome, thus saving one backcross generation. Furthermore, spring rapeseed as the recurrent parent in a backcrossing program could accelerate breeding by reducing the generation cycle. Our study depicts the potential for reducing the background mutation load while accelerating the generation cycle in EMS-induced winter oilseed rape populations by integrating genomic background selection.

Meiosis in Polyploids and Implications for Genetic Mapping: A Review

Plant cytogenetic studies have provided essential knowledge on chromosome behavior during meiosis, contributing to our understanding of this complex process. In this review, we describe in detail the meiotic process in auto- and allopolyploids from the onset of prophase I through pairing, recombination, and bivalent formation, highlighting recent findings on the genetic control and mode of action of specific proteins that lead to diploid-like meiosis behavior in polyploid species. During the meiosis of newly formed polyploids, related chromosomes (homologous in autopolyploids; homologous and homoeologous in allopolyploids) can combine in complex structures called multivalents. These structures occur when multiple chromosomes simultaneously pair, synapse, and recombine. We discuss the effectiveness of crossover frequency in preventing multivalent formation and favoring regular meiosis. Homoeologous recombination in particular can generate new gene (locus) combinations and phenotypes, but it may destabilize the karyotype and lead to aberrant meiotic behavior, reducing fertility. In crop species, understanding the factors that control pairing and recombination has the potential to provide plant breeders with resources to make fuller use of available chromosome variations in number and structure. We focused on wheat and oilseed rape, since there is an abundance of elucidating studies on this subject, including the molecular characterization of the Ph1 (wheat) and PrBn (oilseed rape) loci, which are known to play a crucial role in regulating meiosis. Finally, we exploited the consequences of chromosome pairing and recombination for genetic map construction in polyploids, highlighting two case studies of complex genomes: (i) modern sugarcane, which has a man-made genome harboring two subgenomes with some recombinant chromosomes; and (ii) hexaploid sweet potato, a naturally occurring polyploid. The recent inclusion of allelic dosage information has improved linkage estimation in polyploids, allowing multilocus genetic maps to be constructed.

The Bnapus50K array: a quick and versatile genotyping tool for Brassica napus genomic breeding and research

Rapeseed is a globally cultivated commercial crop, primarily grown for its oil. High-density single nucleotide polymorphism (SNP) arrays are widely used as a standard genotyping tool for rapeseed research, including for gene mapping, genome-wide association studies, germplasm resource analysis, and cluster analysis. Although considerable rapeseed genome sequencing data have been released, DNA arrays are still an attractive choice for providing additional genetic data in an era of high-throughput whole-genome sequencing. Here, we integrated re-sequencing DNA array data (32,216, 304 SNPs) from 505 inbred rapeseed lines, allowing us to develop a sensitive and efficient genotyping DNA array, Bnapus50K, with a more consistent genetic and physical distribution of probes. A total of 42,090 high-quality probes were filtered and synthesized, with an average distance between adjacent SNPs of 8 kb. To improve the practical application potential of this array in rapeseed breeding, we also added 1,618 functional probes related to important agronomic traits such as oil content, disease resistance, male sterility, and flowering time. The additional probes also included those specifically for detecting genetically modified material. These probes show a good detection efficiency and are therefore useful for gene mapping, along with crop variety improvement and identification. The novel Bnapus50K DNA array developed in this study could prove to be a quick and versatile genotyping tool for B. napus genomic breeding and research.

Genetic Analysis of Heterosis for Yield Influencing Traits in Brassica juncea Using a Doubled Haploid Population and Its Backcross Progenies

The exploitation of heterosis through hybrid breeding is one of the major breeding objectives for productivity increase in crop plants. This research analyzes the genetic basis of heterosis in Brassica juncea by using a doubled haploid (DH) mapping population derived from F1 between two heterotic inbred parents, one belonging to the Indian and the other belonging to the east European gene pool, and their two corresponding sets of backcross hybrids. An Illumina Infinium Brassica 90K SNP array-based genetic map was used to identify yield influencing quantitative trait loci (QTL) related to plant architecture, flowering, and silique- and seed-related traits using five different data sets from multiple trials, allowing the estimation of additive and dominance effects, as well as digenic epistatic interactions. In total, 695 additive QTL were detected for the 14 traits in the three trials using five data sets, with overdominance observed to be the predominant type of effect in determining the expression of heterotic QTL. The results indicated that the design in the present study was efficient for identifying common QTL across multiple trials and populations, which constitute a valuable resource for marker-assisted selection and further research. In addition, a total of 637 epistatic loci were identified, and it was concluded that epistasis among loci without detectable main effects plays an important role in controlling heterosis in yield of B. juncea.

Genome-wide association study and transcriptome analysis reveal key genes affecting root growth dynamics in rapeseed

BACKGROUND

In terms of global demand, rapeseed is the third-largest oilseed crop after soybeans and palm, which produces vegetable oil for human consumption and biofuel for industrial production. Roots are vital organs for plant to absorb water and attain mineral nutrients, thus they are of great importance to plant productivity. However, the genetic mechanisms regulating root development in rapeseed remain unclear. In the present study, seven root-related traits and shoot biomass traits in 280 Brassica napus accessions at five continuous vegetative stages were measured to establish the genetic basis of root growth in rapeseed.

RESULTS

The persistent and stage-specific genetic mechanisms were revealed by root dynamic analysis. Sixteen persistent and 32 stage-specific quantitative trait loci (QTL) clusters were identified through genome-wide association study (GWAS). Root samples with contrasting (slow and fast) growth rates throughout the investigated stages and those with obvious stage-specific changes in growth rates were subjected to transcriptome analysis. A total of 367 differentially expressed genes (DEGs) with persistent differential expressions throughout root development were identified, and these DEGs were significantly enriched in GO terms, such as energy metabolism and response to biotic or abiotic stress. Totally, 485 stage-specific DEGs with different expressions at specific stage were identified, and these DEGs were enriched in GO terms, such as nitrogen metabolism. Four candidate genes were identified as key persistent genetic factors and eight as stage-specific ones by integrating GWAS, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. These candidate genes were speculated to regulate root system development, and they were less than 100 kb away from peak SNPs of QTL clusters. The homologs of three genes (BnaA03g52990D, BnaA06g37280D, and BnaA09g07580D) out of 12 candidate genes have been reported to regulate root development in previous studies.

CONCLUSIONS

Sixteen QTL clusters and four candidate genes controlling persistently root development, and 32 QTL clusters and eight candidate genes stage-specifically regulating root growth in rapeseed were detected in this study. Our results provide new insights into the temporal genetic mechanisms of root growth by identifying key candidate QTL/genes in rapeseed.

A gene-for-gene interaction involving a 'late' effector contributes to quantitative resistance to the stem canker disease in Brassica napus

The control of stem canker disease of Brassica napus (rapeseed), caused by the fungus Leptosphaeria maculans is based largely on plant genetic resistance: single-gene specific resistance (Rlm genes) or quantitative, polygenic, adult-stage resistance. Our working hypothesis was that quantitative resistance partly obeys the gene-for-gene model, with resistance genes 'recognizing' fungal effectors expressed during late systemic colonization. Five LmSTEE (stem-expressed effector) genes were selected and placed under the control of the AvrLm4-7 promoter, an effector gene highly expressed at the cotyledon stage of infection, for miniaturized cotyledon inoculation test screening of a gene pool of 204 rapeseed genotypes. We identified a rapeseed genotype, 'Yudal', expressing hypersensitive response to LmSTEE98. The LmSTEE98-RlmSTEE98 interaction was further validated by inactivation of the LmSTEE98 gene with a CRISPR-Cas9 approach. Isolates with mutated versions of LmSTEE98 induced more severe stem symptoms than the wild-type isolate in 'Yudal'. This single-gene resistance was mapped in a 0.6 cM interval of the 'Darmor_bzh' × 'Yudal' genetic map. One typical gene-for-gene interaction contributes partly to quantitative resistance when L. maculans colonizes the stems of rapeseed. With numerous other effectors specific to stem colonization, our study provides a new route for resistance gene discovery, elucidation of quantitative resistance mechanisms and selection for durable resistance.

Unraveling the impact on agronomic traits of the genetic architecture underlying plant-density responses in canola

Plant density defines vegetative architecture and the competition for light between individuals. Brassica napus (canola, rapeseed) presents a radically different plant architecture compared to traditional crops commonly cultivated at high density, and can act as a model system of indeterminate growth. Using a panel of 152 spring-type accessions and a double-haploid population of 99 lines from a cross between the cultivars Lynx and Monty, we performed genome-wide association studies (GWAS) and quantitative trait locus (QTL) mapping for 12 growth and yield traits at two contrasting plant densities of 15 and 60 plants m-2. The most significant associations were found for time to flowering, biomass at harvest, plant height, silique and seed numbers, and seed yield. These were generally independent of plant density, but some density-dependent associations were found in low-density populations. RNA-seq transcriptomic analysis revealed distinctive latent gene-regulatory responses to simulated shade between Lynx and Monty. Having identified candidate genes within the canola QTLs, we further examined their influence on density responses in Arabidopsis lines mutated in certain homologous genes. The results suggested that TCP1 might promote growth independently of plant density, while HY5 could increase biomass and seed yield specifically at high plant density. For flowering time, the results suggested that PIN genes might accelerate flowering in plant a density-dependent manner whilst FT, HY5, and TCP1 might accelerate it in a density-independent. This work highlights the advantages of using agronomic field experiments together with genetic and transcriptomic approaches to decipher quantitative complex traits that potentially mediate improved crop productivity.

Identification and Development of KASP Markers for Novel Mutant BnFAD2 Alleles Associated With Elevated Oleic Acid in Brassica napus

The fatty acid desaturase FAD2 genes are the main contributors to oleic acid content, and different FAD2 alleles can result in different oleic acid contents in rapeseed oil. Hence, identification of allelic variation in FAD2 is an extremely desirable breeding goal. By performing QTL mapping using 190 F_2:3 lines genotyped by genome-wide single nucleotide polymorphism (SNP) markers assayed by the Brassica 60 K Infinium BeadChip Array, four quantitative trait loci (QTL) for C18:1 content were mapped on chromosomes A01, A05, A09 and C05 over 3 years in a population segregating for oleic acid content. Two BnFAD2 genes on A05 and C05 were anchored within the QTL intervals, explaining 45-52 and 15-44% of the observed variation for C18:1 content. Sequence polymorphisms between the corresponding coding regions of the parental lines found two single-nucleotide polymorphisms (SNPs) in BnFAD2.A05 and BnFAD2.C05, respectively, which led to the amino acid changes (C421T and G1073E) in the corresponding proteins. The mutation sites of Bnfad2.A05 and Bnfad2.C05 alleles were located within the second H-box and near the third H-box motif of the protein, respectively, and were found to be novel mutant alleles. Lines resulting from the combination of these two alleles contained up to 88% oleic acid in their seed oil, compared with 63% in wild-type controls. Two competitive allele-specific PCR (KASP) markers based on these two mutation sites were successfully developed and validated in segregating F₂ populations. These markers will facilitate breeding for ultra-high seed oleic acid content in oilseed rape.

Clubroot resistance derived from the European Brassica napus cv. 'Tosca' is not effective against virulent Plasmodiophora brassicae isolates from Alberta, Canada

In this study, clubroot resistance in the resynthesized European winter Brassica napus cv. 'Tosca' was introgressed into a Canadian spring canola line '11SR0099', which was then crossed with the clubroot susceptible spring line '12DH0001' to produce F₁ seeds. The F₁ plants were used to develop a doubled haploid (DH) mapping population. The parents and the DH lines were screened against 'old' pathotypes 2F, 3H, 5I, 6M and 8N of the clubroot pathogen, Plasmodiophora brassicae, as well as against the 'new' pathotypes 5X, 5L, 2B, 3A, 3D, 5G, 8E, 5C, 8J, 5K, 3O and 8P. Genotyping was conducted using a Brassica 15K SNP array. The clubroot screening showed that 'Tosca, '11SR0099' and the resistant DH lines were resistant to three (2F, 3H and 5I) of the five 'old' pathotypes and four (2B, 3O, 8E and 8P) of the 12 'new' pathotypes, while being moderately resistant to the 'old' pathotype 8N and the 'new' pathotypes 3D and 5G. 'Tosca' was susceptible to isolates representing pathotype 3A (the most common among the 'new' pathotypes) as well as pathotypes 6M, 5X, 5L, 5K and 8J. Linkage analysis and QTL mapping identified a ca. 0.88-0.95 Mb genomic region on the A03 chromosome of 'Tosca' as conferring resistance to pathotypes 2F, 3H, 5I, 2B, 3D, 5G, 8E, 3O and 8P. The identified QTL genomic region housed the CRk, Crr3 and CRd gene(s). However, the susceptibility of 'Tosca' to most of the common virulent pathotypes makes it unattractive as a sole CR donor in the breeding of commercial canola varieties in western Canada.

Mapping of seed quality traits in the C genome of Brassica napus by using a population carrying genome content of B. oleracea and their effect on other traits

Increasing seed oil and protein contents and reducing the content of seed glucosinolates (GSLs) in Brassica oilseed crops are important objectives in breeding. By using an oilseed rape (B. napus L.) doubled-haploid (DH) population carrying genome content introgressed from Chinese kale (B. oleracea L.), we mapped quantitative trait loci (QTL) for these seed quality traits and investigated their effect on other traits including seed yield. A stable QTL for seed oil content was identified on chromosome C5 at 40-42 Mb position and a QTL for seed GSL content was identified on C9 at 7-8 Mb position. The C5 and C9 QTL alleles for high oil and GSL contents were derived from Chinese kale, demonstrating that high-oil QTL allele can be found in the parental species of oilseed rape. The low-GSL QTL allele of C9 exerted a significant positive effect on seed protein content, demonstrating that selection for this QTL allele contributed to higher protein content in canola seed. These two QTL were not affected by field environmental conditions and did not exert a significant effect on days to flowering and seed yield. Thus, the genomic regions and the molecular markers identified in this study should be useful in molecular breeding of the seed quality traits in oilseed rape.