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

The Multi-Pistil Phenomenon in Higher Plants

Correct floral morphology determines the accuracy of fruit formation, which is crucial for reproductive success in higher plants. Despite this, an abnormal, multi-pistil phenotype has been observed in the flowers of many plants. In this review, we gather information on the multi-pistil phenomenon in various species and highlight potential causes, as well as possible consequences, of the trait. Our assessment of the reported multi-pistil phenotype in rice (Oryza sativa L.), wheat (Triticum aestivum L.), tomato (Solanum lycopersicum L.), Medicago, sweet cherry (Prunus avium L.), rye (Secale cereale L.), and rapeseed (Brassica napus L. and B. campestris L.) leads us to conclude that hybridization and mutation are the main factors that give rise to this phenotype. We also delve into the inheritance patterns of the multi-pistil phenotype and factors that influence this trait, such as nuclear-cytoplasmic interactions, temperature conditions, and shading. Finally, we discuss the effects of multi-pistil flowers on the yield of these plants. This analysis increases our understanding of floral development and lays the foundation for the potential utilization of the multi-pistil trait to increase seed production in crops.

Targeted mutagenesis and functional marker development of two Bna.TAC1s conferring novel rapeseed germplasm with compact architecture

KEY MESSAGE

Simultaneous disruption of two Bna.TAC1s, redundantly controlling the branch angle, generates a compact architecture in rapeseed, and two functional markers are developed to facilitate breeding rapeseed cultivars with compact architecture. Shoot branch angle is a key factor in determining the aerial plant architecture. A narrow branch angle can increase yields by facilitating mechanized harvest and high-density planting in rapeseed, a globally important oil crop. However, the available rapeseed varieties with narrow branch angle are very limited. In this study, two Bna.TAC1 members named BnaA5.TAC1 and BnaC4.TAC1 were found to have the four canonical domains of TAC1-like members, including domains I, II, III and IV in rapeseed. Each Bna.TAC1 exhibits dominant expression in the lateral branch with gradual dynamic response to light and encodes a protein localized in the plasma membrane. CRISPR/Cas9-mediated editing system was used to simultaneously knock out the two Bna.TAC1s to obtain two different Bna.tac1 double mutants, designed as CR-Bna.tac1-1 and CR-Bna.tac1-2. These two mutants displayed different degrees of compact architecture without affecting plant height and yield-related traits. The two Bna.TAC1s were also shown to play a redundant role in controlling branch angle by regulating the gravitropic response. In addition, we developed two specific gel-based functional markers in each Bna.TAC1 for the transgene-free mutant CR-Bna.tac1-1, which co-segregate with narrower branch angle and could help to identify the mutant alleles in a segregating population. We also found that the genomic variation of the two Bna.TAC1s is not associated with branch angle variation in the natural rapeseed population. Overall, these results reveal the key roles of Bna.TAC1s in regulation of rapeseed branch angle and provide a novel germplasm and functional markers for breeding superior varieties with compact architecture in rapeseed.

Genome-wide association study reveals genetic loci for seed density per silique in rapeseed (Brassica napus L.)

KEY MESSAGE

Two stable QTLs controlling seed density per silique were detected on chromosomes A09 and C05 in rapeseed via GWAS, and ARF18 was the only causal gene of QTL qSDPS-A09. Seed density per silique (SDPS) is a key agronomic trait that directly or indirectly affects seed yield in rapeseed (Brassica napus L.). Exploring the genetic control of SDPS is beneficial for increasing rapeseed production. In this study, we evaluated the SDPS phenotypes of 413 rapeseed cultivars (lines) across five natural environments and genotyped them by resequencing. A GWAS analysis was performed using 5,277,554 high-quality variants with the MLM_PCA + K and FarmCPU models. A total of 51 loci were identified to be significantly (p < - log10(1.88 × 10-6)) associated with SDPS, of which 5 were detected in all environments (except for SNP-2095656) by both GWAS models. Among the five loci, three were located on chromosome A09, whereas the other two loci were located on chromosome C05. The three loci on chromosome A09 and the two loci on chromosome C05 were physically close to each other. Therefore, only the two common candidate QTLs were integrated and named QTL qSDPS-A09 (320 kb) and qSDPS-C05 (331.48 kb), respectively. Sixty-seven and forty-eight candidate genes were initially identified on A09 and C05 and then narrowed down to 17 and 13 candidate genes, respectively, via LD block analyses. Gene-based association studies, haplotype analyses and expression analyses confirmed that three homologs of Arabidopsis auxin-response factor 18 (BnaA09G0559300ZS) was the most likely candidate genes underlying the QTL qSDPS-A09. ARF18Hap4 was identified as a favorable haplotype for high SDPS. These findings will aid in elucidating the genetic and molecular mechanisms of SDPS and promoting genetic modifications in rapeseed breeding.

Integrated Transcriptome and Metabolome Analysis Reveals the Resistance Mechanisms of Brassica napus Against Xanthomonas campestris

Rapeseed (Brassica napus L.) is an important crop for healthy edible oil and stockfeed worldwide. However, its growth and yield are severely hampered by black rot, a destructive disease caused by Xanthomonas campestris pv. campestris (Xcc). Despite the identification of several quantitative trait loci (QTLs) associated with resistance to black rot in Brassica crops, the underlying molecular mechanisms remain largely unexplored. In this study, we investigated Xcc-induced transcriptomic and metabolic changes in the leaves of two rapeseed varieties: Westar (susceptible) and ZS5 (resistant). Our findings indicated that Xcc infection elicited more pronounced overall transcriptomic and metabolic changes in Westar compared to ZS5. Transcriptomic analyses revealed that the phenylpropanoid biosynthesis, cutin, suberine and wax biosynthesis, tryptophan metabolism, and phenylalanine metabolism were enriched in both varieties. Notably, photosynthesis was down-regulated in Westar after infection, whereas this down-regulation occurred at a later stage in ZS5. Integrated analyses of transcriptome and metabolome revealed that the tryptophan metabolism pathway was enriched in both varieties. Indolic glucosinolates and indole-3-acetic acid (IAA) are two metabolites derived from tryptophan. The expression of genes involved in the indolic glucosinolate pathway and the levels of indolic glucosinolates were significantly elevated in both varieties post-infection. Additionally, exogenous application of IAA promoted the development of black rot, whereas the use of an IAA synthesis inhibitor attenuated black rot development in both resistant and susceptible rapeseed varieties. These findings provide valuable molecular insights into the interactions between rapeseed and Xcc, facilitating the advancement of black rot resistance breeding in Brassica crops.

Zinc finger transcription factors BnaSTOP2s regulate sulfur metabolism and confer Sclerotinia sclerotiorum resistance in Brassica napus

Rapeseed (Brassica napus L.) exhibits high-sulfur requirements to achieve optimal growth, development, and pathogen resistance. Despite the importance of sulfur, the mechanisms regulating its metabolism and disease resistance are not fully understood. In this study, we found that the zinc finger transcription factors BnaSTOP2s play a pivotal role in sulfur metabolism and Sclerotinia sclerotiorum resistance. Our findings indicate that BnaSTOP2s are involved in sulfur metabolism, as evidenced by extensive protein interaction screening. BnaSTOP2s knockout reduced the content of essential sulfur-containing metabolites, including glucosinolate and glutathione, which is consistent with the significantly lowered transcriptional levels of BnaMYB28s and BnaGTR2s, key factors involved in glucosinolate synthesis and transportation, respectively. Comprehensive RNA-seq analysis revealed the substantial effect of BnaSTOP2s on sulfur metabolism from roots to siliques, which serve as pivotal sources and sinks for sulfur metabolism, respectively. Furthermore, we found that leaf lesion size significantly decreased and increased in the BnaSTOP2-OE and Bnastop2 mutants, respectively, compared with the wild-type during S. sclerotiorum infection, suggesting a vital role of BnaSTOP2s in plant defense response. In conclusion, BnaSTOP2s act as global regulators of sulfur metabolism and confer resistance to S. sclerotiorum infection in B. napus. Thus, they have potential implications for improving crop resilience.

Breeding and biotechnology approaches to enhance the nutritional quality of rapeseed byproducts for sustainable alternative protein sources- a critical review

Global protein consumption is increasing exponentially, which requires efficient identification of potential, healthy, and simple protein sources to fulfil the demands. The existing sources of animal proteins are high in fat and low in fiber composition, which might cause serious health risks when consumed regularly. Moreover, protein production from animal sources can negatively affect the environment, as it often requires more energy and natural resources and contributes to greenhouse gas emissions. Thus, finding alternative plant-based protein sources becomes indispensable. Rapeseed is an important oilseed crop and the world's third leading oil source. Rapeseed byproducts, such as seed cakes or meals, are considered the best alternative protein source after soybean owing to their promising protein profile (30%-60% crude protein) to supplement dietary requirements. After oil extraction, these rapeseed byproducts can be utilized as food for human consumption and animal feed. However, anti-nutritional factors (ANFs) like glucosinolates, phytic acid, tannins, and sinapines make them unsuitable for direct consumption. Techniques like microbial fermentation, advanced breeding, and genome editing can improve protein quality, reduce ANFs in rapeseed byproducts, and facilitate their usage in the food and feed industry. This review summarizes these approaches and offers the best bio-nutrition breakthroughs to develop nutrient-rich rapeseed byproducts as plant-based protein sources.

Multiomics dissection of Brassica napus L. lateral roots and endophytes interactions under phosphorus starvation

Many plants associate with endophytic microbes that improve root phosphorus (P) uptake. Understanding the interactions between roots and endophytes can enable efforts to improve P utilization. Here, we characterize the interactions between lateral roots of endophytes in a core collection of 50 rapeseed (Brassica napus L.) genotypes with differing sensitivities to low P conditions. With the correlation analysis result between bacterial abundance and plant physiological indices of rapeseeds, and inoculation experiments on plates and soil, we identify one Flavobacterium strain (C2) that significantly alleviates the P deficiency phenotype of rapeseeds. The underlying mechanisms are explored by performing the weighted gene coexpression network analysis (WGCNA), and conducting genome-wide association studies (GWAS) using Flavobacterium abundance as a quantitative trait. Under P-limited conditions, C2 regulates fatty acid and lipid metabolic pathways. For example, C2 improves metabolism of linoleic acid, which mediates root suberin biosynthesis, and enhances P uptake efficiency. In addition, C2 suppresses root jasmonic acid biosynthesis, which depends on α-linolenic acid metabolism, improving C2 colonization and activating P uptake. This study demonstrates that adjusting the endophyte composition can modulate P uptake in B. napus plants, providing a basis for developing agricultural microbial agents.

Increasing oil content in Brassica oilseed species

Brassica oilseed species are the third most important in the world, providing approximately 15 % of the total vegetable oils. Three species (Brassica rapa, B. juncea, B. napus) dominate with B. napus being the most common in Canada, China and Europe. Originally, B. napus was a crop producing seed with high erucic acid content, which still persists today, to some extent, and is used for industrial purposes. In contrast, cultivars which produce seed used for food and feed are low erucic acid cultivars which also have reduced glucosinolate content. Because of the limit to agricultural land, recent efforts have been made to increase productivity of oil crops, including Brassica oilseed species. In this article, we have detailed research in this regard. We have covered modern genetic, genomic and metabolic control analysis approaches to identifying potential targets for the manipulation of seed oil content. Details of work on the use of quantitative trait loci, genome-wide association and comparative functional genomics to highlight factors influencing seed oil accumulation are given and functional proteins which can affect this process are discussed. In summary, a wide variety of inputs are proving useful for the improvement of Brassica oilseed species, as major sources of global vegetable oil.

Genome Analysis of BnCNGC Gene Family and Function Exploration of BnCNGC57 in Brassica napus L

The cyclic nucleotide-gated ion channel (CNGC), as a non-selective cation channel, plays a pivotal role in plant growth and stress response. A systematic analysis and identification of the BnCNGC gene family in Brassica napus is crucial for uncovering its biological functions and potential applications in plant science. In this study, we identified 61 BnCNGC members in the B. napus genome, which are phylogenetically similar to Arabidopsis and can be classified into Groups I-IV (with Group IV further subdivided into IV-a and IV-b). Collinearity analysis with other species provided insights into the evolution of BnCNGC. By homology modeling, we predicted the three-dimensional structure of BnCNGC proteins and analyzed cis-acting elements in their promoters, revealing diverse roles in hormone regulation, growth, and stress response. Notably, overexpression of BnCNGC57 (BnaC09g42460D) significantly increased seed size, possibly through regulating cell proliferation via the MAPK signaling pathway. Our findings contribute to a better understanding of the BnCNGC gene family and highlight the potential regulatory role of BnCNGC57 in the seed development of B. napus.

Genome-Wide Profiling of the ACTIN Gene Family and Its Implications for Agronomic Traits in Brassica napus: A Bioinformatics Study

ACTINs are key structural proteins in plants, which form the actin cytoskeleton and are engaged in numerous routine cellular processes. Meanwhile, ACTIN, recognized as a housekeeping gene, has not yet been thoroughly investigated in Brassica napus. The current research has led to the detection of 69 actin genes in B. napus, which were organized into six distinct subfamilies on the basis of phylogenetic relationships. Functional enrichment analysis, along with the construction of protein interaction networks, suggested that BnACTINs play roles in Preserving cell morphology and facilitating cytoplasmic movement, plant development, and adaptive responses to environmental stress. Moreover, the BnACTIN genes presented a wide range of expression levels among different tissues, whereas the majority experienced a substantial increase in expression when subjected to various abiotic stresses, demonstrating a pronounced sensitivity to abiotic factors. Furthermore, association mapping analysis indicated that some BnACTINs potentially affected certain key agronomic traits. Overall, our research deepens the knowledge of BnACTIN genes, promotes the cultivation of improved B. napus strains, and lays the groundwork for subsequent functional research.

Brassica napus cytochrome P450 superfamily: Origin from parental species and involvement in diseases resistance, abiotic stresses tolerance, and seed quality traits

Cytochromes P450 monooxygenases (CYP450s) constitute the largest enzymic protein family that is widely present in plants, animals, and microorganisms, participate in numerous metabolic pathways, and play diverse roles in development, metabolism, and defense. Rapeseed (Brassica napus) is an important oil crop worldwide and have many versions of reference genome. However, there is no systemically comparative genome-wide analysis of CYP450 family genes in rapeseed and its parental species B. rapa and B. oleracea. In this study, we identified 765, 293 and 437 CYP450 genes in B. napus, B. rapa and B. oleracea, respectively, which were unevenly located in A01-A10 and/or C01-C09 chromosomes in corresponding species. Phylogenetic relationship analysis indicated that 1745 CYP450 proteins from three Brassica species and Arabidopsis were divided into 4 groups. Whole genome duplication (WGD) or segmental duplication resulted in gene expansion of CYP450 family in three Brassica species. There were 33-83 SSR loci in CYP450 genes of three Brassica species, and numerous transcription factor binding sites were identified in their promoters. A total of 459-777 miRNAs were predicted to target 174-426 CYP450 genes in three Brassica species. Based on transcriptome data, BnCYP450s, BrCYP450s and BoCYP450s were differentially expressed in various tissues. There existed numerous BnCYP450 DEGs in response to pathogens and abiotic stresses. Besides, many BnCYP450 DEGs were involved in the regulation of important traits, such as seed germination, seed ALA content, and yellow-seed. The qRT-PCR experiment confirmed the transcriptome analysis results by validating two representative Sclerotinia-responsive BnCYP450 DEGs as an example. Three BnCYP450s genes (CYP707A1, CYP81F1, CYP81H1) might be regulated by seed-specific transcription factors BnTT1 and BnbZIP67 to participate in the development and metabolism of seed coat and embryo by undertaking related metabolic reactions.

Rapeseed Flower Counting Method Based on GhP2-YOLO and StrongSORT Algorithm

Accurately quantifying flora and their respective anatomical structures within natural ecosystems is paramount for both botanical breeders and agricultural cultivators. For breeders, precise plant enumeration during the flowering phase is instrumental in discriminating genotypes exhibiting heightened flowering frequencies, while for growers, such data inform potential crop rotation strategies. Moreover, the quantification of specific plant components, such as flowers, can offer prognostic insights into the potential yield variances among different genotypes, thereby facilitating informed decisions pertaining to production levels. The overarching aim of the present investigation is to explore the capabilities of a neural network termed GhP2-YOLO, predicated on advanced deep learning techniques and multi-target tracking algorithms, specifically tailored for the enumeration of rapeseed flower buds and blossoms from recorded video frames. Building upon the foundation of the renowned object detection model YOLO v8, this network integrates a specialized P2 detection head and the Ghost module to augment the model's capacity for detecting diminutive targets with lower resolutions. This modification not only renders the model more adept at target identification but also renders it more lightweight and less computationally intensive. The optimal iteration of GhP2-YOLOm demonstrated exceptional accuracy in quantifying rapeseed flower samples, showcasing an impressive mean average precision at 50% intersection over union metric surpassing 95%. Leveraging the virtues of StrongSORT, the subsequent tracking of rapeseed flower buds and blossom patterns within the video dataset was adeptly realized. By selecting 20 video segments for comparative analysis between manual and automated counts of rapeseed flowers, buds, and the overall target count, a robust correlation was evidenced, with R-squared coefficients measuring 0.9719, 0.986, and 0.9753, respectively. Conclusively, a user-friendly "Rapeseed flower detection" system was developed utilizing a GUI and PyQt5 interface, facilitating the visualization of rapeseed flowers and buds. This system holds promising utility in field surveillance apparatus, enabling agriculturalists to monitor the developmental progress of rapeseed flowers in real time. This innovative study introduces automated tracking and tallying methodologies within video footage, positioning deep convolutional neural networks and multi-target tracking protocols as invaluable assets in the realms of botanical research and agricultural administration.

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.

The story of a decade: Genomics, functional genomics, and molecular breeding in Brassica napus

Rapeseed (Brassica napus L.) is one of the major global sources of edible vegetable oil and is also used as a feed and pioneer crop and for sightseeing and industrial purposes. Improvements in genome sequencing and molecular marker technology have fueled a boom in functional genomic studies of major agronomic characters such as yield, quality, flowering time, and stress resistance. Moreover, introgression and pyramiding of key functional genes have greatly accelerated the genetic improvement of important traits. Here we summarize recent progress in rapeseed genomics and genetics, and we discuss effective molecular breeding strategies by exploring these findings in rapeseed. These insights will extend our understanding of the molecular mechanisms and regulatory networks underlying agronomic traits and facilitate the breeding process, ultimately contributing to more sustainable agriculture throughout the world.

Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

Nectar Characteristics and Honey Production Potential of Five Rapeseed Cultivars and Two Wildflower Species in South Korea

The growing beekeeping industry in South Korea has led to the establishment of new honey plant complexes. However, studies on honey production from each species are limited. This study aimed to assess the honey production potential of various Brassica napus cultivars and two wildflower species. The nectar characteristics of B. napus varied significantly among the cultivars. Absolute sugar concentrations differed among the cultivars, but sugar composition ratios were similar. In contrast, the amino acid content remained relatively uniform regarding percentage values, irrespective of the absolute concentrations. Estimations of honey potential production per hectare (kg/ha) resulted in the following ranking among cultivars: 'JM7003' (107.1) > 'YS' (73.0) > 'JM7001' (63.7) > 'TL' (52.7) > 'TM' (42.4). The nectar volume of Pseudolysimachion rotundum var. subintegrum and Leonurus japonicus increased during the flowering stage. P. rotundum var. subintegrum was sucrose-rich and L. japonicus was sucrose-dominant. Both species predominantly contained phenylalanine, P. rotundum var. subintegrum had glutamine as the second most abundant amino acid, and L. japonicus had tyrosine. The honey production potential was 152.4 kg/ha for P. rotundum var. subintegrum and 151.3 kg/ha for L. japonicus. These findings provide a basis for identifying food resources for pollinators and selecting plant species to establish honey plant complexes.

Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.)

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

Segmentation and Phenotype Calculation of Rapeseed Pods Based on YOLO v8 and Mask R-Convolution Neural Networks

Rapeseed is a significant oil crop, and the size and length of its pods affect its productivity. However, manually counting the number of rapeseed pods and measuring the length, width, and area of the pod takes time and effort, especially when there are hundreds of rapeseed resources to be assessed. This work created two state-of-the-art deep learning-based methods to identify rapeseed pods and related pod attributes, which are then implemented in rapeseed pots to improve the accuracy of the rapeseed yield estimate. One of these methods is YOLO v8, and the other is the two-stage model Mask R-CNN based on the framework Detectron2. The YOLO v8n model and the Mask R-CNN model with a Resnet101 backbone in Detectron2 both achieve precision rates exceeding 90%. The recognition results demonstrated that both models perform well when graphic images of rapeseed pods are segmented. In light of this, we developed a coin-based approach for estimating the size of rapeseed pods and tested it on a test dataset made up of nine different species of Brassica napus and one of Brassica campestris L. The correlation coefficients between manual measurement and machine vision measurement of length and width were calculated using statistical methods. The length regression coefficient of both methods was 0.991, and the width regression coefficient was 0.989. In conclusion, for the first time, we utilized deep learning techniques to identify the characteristics of rapeseed pods while concurrently establishing a dataset for rapeseed pods. Our suggested approaches were successful in segmenting and counting rapeseed pods precisely. Our approach offers breeders an effective strategy for digitally analyzing phenotypes and automating the identification and screening process, not only in rapeseed germplasm resources but also in leguminous plants, like soybeans that possess pods.

Comparative transcriptome profiling reveals the multiple levels of crosstalk in phytohormone networks in Brassica napus

Plant hormones are the intrinsic factors that control plant development. The integration of different phytohormone pathways in a complex network of synergistic, antagonistic and additive interactions has been elucidated in model plants. However, the systemic level of transcriptional responses to hormone crosstalk in Brassica napus is largely unknown. Here, we present an in-depth temporal-resolution study of the transcriptomes of the seven hormones in B. napus seedlings. Differentially expressed gene analysis revealed few common target genes that co-regulated (up- and down-regulated) by seven hormones; instead, different hormones appear to regulate distinct members of protein families. We then constructed the regulatory networks between the seven hormones side by side, which allowed us to identify key genes and transcription factors that regulate the hormone crosstalk in B. napus. Using this dataset, we uncovered a novel crosstalk between gibberellin and cytokinin in which cytokinin homeostasis was mediated by RGA-related CKXs expression. Moreover, the modulation of gibberellin metabolism by the identified key transcription factors was confirmed in B. napus. Furthermore, all data were available online from http://yanglab.hzau.edu.cn/BnTIR/hormone. Our study reveals an integrated hormone crosstalk network in Brassica napus, which also provides a versatile resource for future hormone studies in plant species.

BnIR: A multi-omics database with various tools for Brassica napus research and breeding

In the post-genome-wide association study era, multi-omics techniques have shown great power and potential for candidate gene mining and functional genomics research. However, due to the lack of effective data integration and multi-omics analysis platforms, such techniques have not still been applied widely in rapeseed, an important oil crop worldwide. Here, we report a rapeseed multi-omics database (BnIR; http://yanglab.hzau.edu.cn/BnIR), which provides datasets of six omics including genomics, transcriptomics, variomics, epigenetics, phenomics, and metabolomics, as well as numerous "variation-gene expression-phenotype" associations by using multiple statistical methods. In addition, a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets. BnIR is the most comprehensive multi-omics database for rapeseed so far, and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms.

Large-scale population structure and genetic architecture of agronomic traits of garlic

Garlic, an asexually propagated crop, is the second important bulb crop after the onion and is used as a vegetable and medicinal plant. Abundant and diverse garlic resources have been formed over thousands of years of cultivation. However, genome variation, population structure and genetic architecture of garlic agronomic traits were still not well elucidated. Here, 1 100 258 single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing in 606 garlic accessions collected from 43 countries. Population structure, principal component and phylogenetic analysis showed that these accessions were divided into five subpopulations. Twenty agronomic traits, including above-ground growth traits, bulb-related and bolt-related traits in two consecutive years were implemented in a genome-wide association study. In total, 542 SNPs were associated with these agronomic traits, among which 188 SNPs were repeatedly associated with more than two traits. One SNP (chr6: 1896135972) was repeatedly associated with ten traits. These associated SNPs were located within or near 858 genes, 56 of which were transcription factors. Interestingly, one non-synonymous SNP (Chr4: 166524085) in ribosomal protein S5 was repeatedly associated with above-ground growth and bulb-related traits. Additionally, gene ontology enrichment analysis of candidate genes for genomic selection regions between complete-bolting and non-bolting accessions showed that these genes were significantly enriched in 'vegetative to reproductive phase transition of meristem', 'shoot system development', 'reproductive process', etc. These results provide valuable information for the reliable and efficient selection of candidate genes to achieve garlic genetic improvement and superior varieties.

Structural variations and environmental specificities of flowering time-related genes in Brassica napus

We found that the flowering time order of accessions in a genetic population considerably varied across environments, and homolog copies of essential flowering time genes played different roles in different locations. Flowering time plays a critical role in determining the life cycle length, yield, and quality of a crop. However, the allelic polymorphism of flowering time-related genes (FTRGs) in Brassica napus, an important oil crop, remains unclear. Here, we provide high-resolution graphics of FTRGs in B. napus on a pangenome-wide scale based on single nucleotide polymorphism (SNP) and structural variation (SV) analyses. A total of 1337 FTRGs in B. napus were identified by aligning their coding sequences with Arabidopsis orthologs. Overall, 46.07% of FTRGs were core genes and 53.93% were variable genes. Moreover, 1.94%, 0.74%, and 4.49% FTRGs had significant presence-frequency differences (PFDs) between the spring and semi-winter, spring and winter, and winter and semi-winter ecotypes, respectively. SNPs and SVs across 1626 accessions of 39 FTRGs underlying numerous published qualitative trait loci were analyzed. Additionally, to identify FTRGs specific to an eco-condition, genome-wide association studies (GWASs) based on SNP, presence/absence variation (PAV), and SV were performed after growing and observing the flowering time order (FTO) of plants in a collection of 292 accessions at three locations in two successive years. It was discovered that the FTO of plants in a genetic population changed a lot across various environments, and homolog copies of some key FTRGs played different roles in different locations. This study revealed the molecular basis of the genotype-by-environment (G × E) effect on flowering and recommended a pool of candidate genes specific to locations for breeding selection.

Developing multifunctional crops by engineering Brassicaceae glucosinolate pathways

Glucosinolates (GSLs), found mainly in species of the Brassicaceae family, are one of the most well-studied classes of secondary metabolites. Produced by the action of myrosinase on GSLs, GSL-derived hydrolysis products (GHPs) primarily defend against biotic stress in planta. They also significantly affect the quality of crop products, with a subset of GHPs contributing unique food flavors and multiple therapeutic benefits or causing disagreeable food odors and health risks. Here, we explore the potential of these bioactive functions, which could be exploited for future sustainable agriculture. We first summarize our accumulated understanding of GSL diversity and distribution across representative Brassicaceae species. We then systematically discuss and evaluate the potential of exploited and unutilized genes involved in GSL biosynthesis, transport, and hydrolysis as candidate GSL engineering targets. Benefiting from available information on GSL and GHP functions, we explore options for multifunctional Brassicaceae crop ideotypes to meet future demand for food diversification and sustainable crop production. An integrated roadmap is subsequently proposed to guide ideotype development, in which maximization of beneficial effects and minimization of detrimental effects of GHPs could be combined and associated with various end uses. Based on several use-case examples, we discuss advantages and limitations of available biotechnological approaches that may contribute to effective deployment and could provide novel insights for optimization of future GSL engineering.

Fine Mapping of a Pleiotropic Locus (BnUD1) Responsible for the Up-Curling Leaves and Downward-Pointing Siliques in Brassica napus

Leaves and siliques are important organs associated with dry matter biosynthesis and vegetable oil accumulation in plants. We identified and characterized a novel locus controlling leaf and silique development using the Brassica napus mutant Bnud1, which has downward-pointing siliques and up-curling leaves. The inheritance analysis showed that the up-curling leaf and downward-pointing silique traits are controlled by one dominant locus (BnUD1) in populations derived from NJAU5773 and Zhongshuang 11. The BnUD1 locus was initially mapped to a 3.99 Mb interval on the A05 chromosome with a BC₆F₂ population by a bulked segregant analysis-sequencing approach. To more precisely map BnUD1, 103 InDel primer pairs uniformly covering the mapping interval and the BC₅F₃ and BC₆F₂ populations consisting of 1042 individuals were used to narrow the mapping interval to a 54.84 kb region. The mapping interval included 11 annotated genes. The bioinformatic analysis and gene sequencing data suggested that BnaA05G0157900ZS and BnaA05G0158100ZS may be responsible for the mutant traits. Protein sequence analyses showed that the mutations in the candidate gene BnaA05G0157900ZS altered the encoded PME in the trans-membrane region (G45A), the PMEI domain (G122S), and the pectinesterase domain (G394D). In addition, a 573 bp insertion was detected in the pectinesterase domain of the BnaA05G0157900ZS gene in the Bnud1 mutant. Other primary experiments indicated that the locus responsible for the downward-pointing siliques and up-curling leaves negatively affected the plant height and 1000-seed weight, but it significantly increased the seeds per silique and positively affected photosynthetic efficiency to some extent. Furthermore, plants carrying the BnUD1 locus were compact, implying they may be useful for increasing B. napus planting density. The findings of this study provide an important foundation for future research on the genetic mechanism regulating the dicotyledonous plant growth status, and the Bnud1 plants can be used directly in breeding.

Direct access to millions of mutations by whole genome sequencing of an oilseed rape mutant population

Induced mutations are an essential source of genetic variation in plant breeding. Ethyl methanesulfonate (EMS) mutagenesis has been frequently applied, and mutants have been detected by phenotypic or genotypic screening of large populations. In the present study, a rapeseed M₂ population was derived from M₁ parent cultivar 'Express' treated with EMS. Whole genomes were sequenced from fourfold (4×) pools of 1988 M₂ plants representing 497 M₂ families. Detected mutations were not evenly distributed and displayed distinct patterns across the 19 chromosomes with lower mutation rates towards the ends. Mutation frequencies ranged from 32/Mb to 48/Mb. On average, 284 442 single nucleotide polymorphisms (SNPs) per M₂ DNA pool were found resulting from EMS mutagenesis. 55% of the SNPs were C → T and G → A transitions, characteristic for EMS induced ('canonical') mutations, whereas the remaining SNPs were 'non-canonical' transitions (15%) or transversions (30%). Additionally, we detected 88 725 high confidence insertions and deletions per pool. On average, each M₂ plant carried 39 120 canonical mutations, corresponding to a frequency of one mutation per 23.6 kb. Approximately 82% of such mutations were located either 5 kb upstream or downstream (56%) of gene coding regions or within intergenic regions (26%). The remaining 18% were located within regions coding for genes. All mutations detected by whole genome sequencing could be verified by comparison with known mutations. Furthermore, all sequences are accessible via the online tool 'EMSBrassica' (http://www.emsbrassica.plantbreeding.uni-kiel.de), which enables direct identification of mutations in any target sequence. The sequence resource described here will further add value for functional gene studies in rapeseed breeding.

Genome-Wide Association Study of Glucosinolate Metabolites (mGWAS) in Brassica napus L

Glucosinolates (GSLs) are secondary plant metabolites that are enriched in rapeseed and related Brassica species, and they play important roles in defense due to their anti-nutritive and toxic properties. Here, we conducted a genome-wide association study of six glucosinolate metabolites (mGWAS) in rapeseed, including three aliphatic glucosinolates (m145 gluconapin, m150 glucobrassicanapin and m151 progoitrin), one aromatic glucosinolate (m157 gluconasturtiin) and two indole glucosinolates (m165 indolylmethyl glucosinolate and m172 4-hydroxyglucobrassicin), respectively. We identified 113 candidate intervals significantly associated with these six glucosinolate metabolites. In the genomic regions linked to the mGWAS peaks, 187 candidate genes involved in glucosinolate biosynthesis (e.g., BnaMAM1, BnaGGP1, BnaSUR1 and BnaMYB51) and novel genes (e.g., BnaMYB44, BnaERF025, BnaE2FC, BnaNAC102 and BnaDREB1D) were predicted based on the mGWAS, combined with analysis of differentially expressed genes. Our results provide insight into the genetic basis of glucosinolate biosynthesis in rapeseed and should facilitate marker-based breeding for improved seed quality in Brassica species.

Genome-wide analysis of transcriptome and histone modifications in Brassica napus hybrid

Although utilization of heterosis has largely improved the yield of many crops worldwide, the underlying molecular mechanism of heterosis, particularly for allopolyploids, remains unclear. Here, we compared epigenome and transcriptome data of an elite hybrid and its parental lines in three assessed tissues (seedling, flower bud, and silique) to explore their contribution to heterosis in allopolyploid B. napus. Transcriptome analysis illustrated that a small proportion of non-additive genes in the hybrid compared with its parents, as well as parental expression level dominance, might have a significant effect on heterosis. We identified histone modification (H3K4me3 and H3K27me3) variation between the parents and hybrid, most of which resulted from the differences between parents. H3K4me3 variations were positively correlated with gene expression differences among the hybrid and its parents. Furthermore, H3K4me3 and H3K27me3 were rather stable in hybridization and were mainly inherited additively in the B. napus hybrid. Together, our data revealed that transcriptome reprogramming and histone modification remodeling in the hybrid could serve as valuable resources for better understanding heterosis in allopolyploid crops.

Identification of candidate genes regulating seed oil content by QTL mapping and transcriptome sequencing in Brassica napus

Increasing oil production is a major goal in rapeseed (Brassica napus) molecular breeding programs. Identifying seed oil content (SOC)-related candidate genes is an important step towards achieving this goal. We performed quantitative trait locus (QTL) mapping of SOC in B. napus using a high-density SNP genetic map constructed from recombinant inbred lines and the Illumina Infinium^TM 60K SNP array. A total of 26 QTLs were detected in three years on A01, A03, A05, A06, A09, C01, C03 and C05, which accounted for 3.69%~18.47% of the phenotypic variation in SOC. Of these, 13 QTLs are reported here for the first time. 1713 candidate genes in the 26 QTLs confidence interval were obtained. We then identified differentially expressed genes (DEGs) between the high- and low-SOC accessions, to narrow down our focus to 21 candidate genes (Y1-Y21) related to SOC, and we will focus on 11 (Y1-Y11) candidate genes that contribute to the formation of high-SOC. In addition to providing insight into the genetic basis of SOC in B. napus, the loci identified and candidate genes in this study can be used in molecular breeding strategies to increase SOC in this important seed crop.

Machine learning assisted dynamic phenotypes and genomic variants help understand the ecotype divergence in rapeseed

Three ecotypes of rapeseed, winter, spring, and semi-winter, have been formed to enable the plant to adapt to different geographic areas. Although several major loci had been found to contribute to the flowering divergence, the genomic footprints and associated dynamic plant architecture in the vegetative growth stage underlying the ecotype divergence remain largely unknown in rapeseed. Here, a set of 41 dynamic i-traits and 30 growth-related traits were obtained by high-throughput phenotyping of 171 diverse rapeseed accessions. Large phenotypic variation and high broad-sense heritability were observed for these i-traits across all developmental stages. Of these, 19 i-traits were identified to contribute to the divergence of three ecotypes using random forest model of machine learning approach, and could serve as biomarkers to predict the ecotype. Furthermore, we analyzed genomic variations of the population, QTL information of all dynamic i-traits, and genomic basis of the ecotype differentiation. It was found that 213, 237, and 184 QTLs responsible for the differentiated i-traits overlapped with the signals of ecotype divergence between winter and spring, winter and semi-winter, and spring and semi-winter, respectively. Of which, there were four common divergent regions between winter and spring/semi-winter and the strongest divergent regions between spring and semi-winter were found to overlap with the dynamic QTLs responsible for the differentiated i-traits at multiple growth stages. Our study provides important insights into the divergence of plant architecture in the vegetative growth stage among the three ecotypes, which was contributed to by the genetic differentiation, and might contribute to environmental adaption and yield improvement.

Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus

BACKGROUND

Regulation of gene expression plays an essential role in controlling the phenotypes of plants. Brassica napus (B. napus) is an important source for the vegetable oil in the world, and the seed oil content is an important trait of B. napus.

RESULTS

We perform a comprehensive analysis of the transcriptional variability in the seeds of B. napus at two developmental stages, 20 and 40 days after flowering (DAF). We detect 53,759 and 53,550 independent expression quantitative trait loci (eQTLs) for 79,605 and 76,713 expressed genes at 20 and 40 DAF, respectively. Among them, the local eQTLs are mapped to the adjacent genes more frequently. The adjacent gene pairs are regulated by local eQTLs with the same open chromatin state and show a stronger mode of expression piggybacking. Inter-subgenomic analysis indicates that there is a feedback regulation for the homoeologous gene pairs to maintain partial expression dosage. We also identify 141 eQTL hotspots and find that hotspot87-88 co-localizes with a QTL for the seed oil content. To further resolve the regulatory network of this eQTL hotspot, we construct the XGBoost model using 856 RNA-seq datasets and the Basenji model using 59 ATAC-seq datasets. Using these two models, we predict the mechanisms affecting the seed oil content regulated by hotspot87-88 and experimentally validate that the transcription factors, NAC13 and SCL31, positively regulate the seed oil content.

CONCLUSIONS

We comprehensively characterize the gene regulatory features in the seeds of B. napus and reveal the gene networks regulating the seed oil content of B. napus.

GROP: A genomic information repository for oilplants

Biomass energy is an essential component of the agriculture economy and represents an important and particularly significant renewable energy source in the fight against fossil fuel depletion and global warming. The recognition that many plants naturally synthesize hydrocarbons makes these oil plants indispensable resources for biomass energy, and the advancement of next-generation sequencing technology in recent years has now made available mountains of data on plants that synthesize oil. We have utilized a combination of bioinformatic protocols to acquire key information from this massive amount of genomic data and to assemble it into an oil plant genomic information repository, built through website technology, including Django, Bootstrap, and echarts, to create the Genomic Information Repository for Oil Plants (GROP) portal (http://grop.site/) for genomics research on oil plants. The current version of GROP integrates the coding sequences, protein sequences, genome structure, functional annotation information, and other information from 18 species, 22 genome assemblies, and 46 transcriptomes. GROP also provides BLAST, genome browser, functional enrichment, and search tools. The integration of the massive amounts of oil plant genomic data with key bioinformatics tools in a database with a user-friendly interface allows GROP to serve as a central information repository to facilitate studies on oil plants by researchers worldwide.

Genome-wide characterization of ovate family protein gene family associated with number of seeds per silique in Brassica napus

Ovate family proteins (OFPs) were firstly identified in tomato as proteins controlling the pear shape of the fruit. Subsequent studies have successively proved that OFPs are a class of negative regulators of plant development, and are involved in the regulation of complex traits in different plants. However, there has been no report about the functions of OFPs in rapeseed growth to date. Here, we identified the OFPs in rapeseed at the genomic level. As a result, a total of 67 members were obtained. We then analyzed the evolution from Arabidopsis thaliana to Brassica napus, illustrated their phylogenetic and syntenic relationships, and compared the gene structure and conserved domains between different copies. We also analyzed their expression patterns in rapeseed, and found significant differences in the expression of different members and in different tissues. Additionally, we performed a GWAS for the number of seeds per silique (NSPS) in a rapeseed population consisting of 204 natural accessions, and identified a new gene BnOFP13_2 significantly associated with NSPS, which was identified as a novel function of OFPs. Haplotype analysis revealed that the accessions with haplotype 3 had a higher NSPS than other accessions, suggesting that BnOFP13_2 is associated with NSPS. Transcript profiling during the five stages of silique development demonstrated that BnOFP13_2 negatively regulates NSPS. These findings provide evidence for functional diversity of OFP gene family and important implications for oilseed rape breeding.

Further insight into decreases in seed glucosinolate content based on QTL mapping and RNA-seq in Brassica napus L

The QTL hotspots determining seed glucosinolate content instead of only four HAG1 loci and elucidation of a potential regulatory model for rapeseed SGC variation. Glucosinolates (GSLs) are amino acid-derived, sulfur-rich secondary metabolites that function as biopesticides and flavor compounds, but the high seed glucosinolate content (SGC) reduces seed quality for rapeseed meal. To dissect the genetic mechanism and further reduce SGC in rapeseed, QTL mapping was performed using an updated high-density genetic map based on a doubled haploid (DH) population derived from two parents that showed significant differences in SGC. In 15 environments, a total of 162 significant QTLs were identified for SGC and then integrated into 59 consensus QTLs, of which 32 were novel QTLs. Four QTL hotspot regions (QTL-HRs) for SGC variation were discovered on chromosomes A09, C02, C07 and C09, including seven major QTLs that have previously been reported and four novel major QTLs in addition to HAG1 loci. SGC was largely determined by superimposition of advantage allele in the four QTL-HRs. Important candidate genes directly related to GSL pathways were identified underlying the four QTL-HRs, including BnaC09.MYB28, BnaA09.APK1, BnaC09.SUR1 and BnaC02.GTR2a. Related differentially expressed candidates identified in the minor but environment stable QTLs indicated that sulfur assimilation plays an important rather than dominant role in SGC variation. A potential regulatory model for rapeseed SGC variation constructed by combining candidate GSL gene identification and differentially expressed gene analysis based on RNA-seq contributed to a better understanding of the GSL accumulation mechanism. This study provides insights to further understand the genetic regulatory mechanism of GSLs, as well as the potential loci and a new route to further diminish the SGC in rapeseed.

Genome-Wide Identification and Characterization of Oil-Body-Membrane Proteins in Polyploid Crop Brassica napus

Oil-body-membrane proteins (OBMPs) are essential structural molecules of oil bodies and also versatile metabolic enzymes involved in multiple cellular processes such as lipid metabolism, hormone signaling and stress responses. However, the global landscape for OBMP genes in oil crops is still lacking. Here, we performed genome-wide identification and characterization of OBMP genes in polyploid crop Brassica napus. B. napus contains up to 88 BnaOBMP genes including 53 oleosins, 20 caleosins and 15 steroleosins. Both whole-genome and tandem duplications have contributed to the expansion of the BnaOBMP gene family. These BnaOBMP genes have extensive sequence polymorphisms, and some harbor strong selection signatures. Various cis-acting regulatory elements involved in plant growth, phytohormones and abiotic and biotic stress responses are detected in their promoters. BnaOBMPs exhibit differential expression at various developmental stages from diverse tissues. Importantly, some BnaOBMP genes display spatiotemporal patterns of seed-specific expression, which could be orchestrated by transcriptional factors such as EEL, GATA3, HAT2, SMZ, DOF5.6 and APL. Altogether, our data lay the foundations for studying the regulatory mechanism of the seed oil storage process and provide candidate genes and alleles for the genetic improvement and breeding of rapeseed with high seed oil content.

Mapping‑by‑Sequencing Reveals Genomic Regions Associated with Seed Quality Parameters in Brassica napus

Rapeseed (Brassica napus L.) is an important oil crop and has the potential to serve as a highly productive source of protein. This protein exhibits an excellent amino acid composition and has high nutritional value for humans. Seed protein content (SPC) and seed oil content (SOC) are two complex quantitative and polygenic traits which are negatively correlated and assumed to be controlled by additive and epistatic effects. A reduction in seed glucosinolate (GSL) content is desired as GSLs cause a stringent and bitter taste. The goal here was the identification of genomic intervals relevant for seed GSL content and SPC/SOC. Mapping by sequencing (MBS) revealed 30 and 15 new and known genomic intervals associated with seed GSL content and SPC/SOC, respectively. Within these intervals, we identified known but also so far unknown putatively causal genes and sequence variants. A 4 bp insertion in the MYB28 homolog on C09 shows a significant association with a reduction in seed GSL content. This study provides insights into the genetic architecture and potential mechanisms underlying seed quality traits, which will enhance future breeding approaches in B. napus.

Genome-Wide Association Study of Phenylalanine Derived Glucosinolates in Brassica rapa

Glucosinolates (GSLs) are sulfur-containing bioactive compounds usually present in Brassicaceae plants and are usually responsible for a pungent flavor and reduction of the nutritional values of seeds. Therefore, breeding rapeseed varieties with low GSL levels is an important breeding objective. Most GSLs in Brassica rapa are derived from methionine or tryptophan, but two are derived from phenylalanine, one directly (benzylGSL) and one after a round of chain elongation (phenethylGSL). In the present study, two phenylalanine (Phe)-derived GSLs (benzylGSL and phenethylGSL) were identified and quantified in seeds by liquid chromatography and mass spectrometry (LC-MS) analysis. Levels of benzylGSL were low but differed among investigated low and high GSL genotypes. Levels of phenethylGSL (also known as 2-phenylethylGSL) were high but did not differ among GSL genotypes. Subsequently, a genome-wide association study (GWAS) was conducted using 159 B. rapa accessions to demarcate candidate regions underlying 43 and 59 QTNs associated with benzylGSL and phenethylGSL that were distributed on 10 chromosomes and 9 scaffolds, explaining 0.56% to 70.86% of phenotypic variations, respectively. Furthermore, we find that 15 and 18 known or novel candidate genes were identified for the biosynthesis of benzylGSL and phenethylGSL, including known regulators of GSL biosynthesis, such as BrMYB34, BrMYB51, BrMYB28, BrMYB29 and BrMYB122, and novel regulators or structural genes, such as BrMYB44/BrMYB77 and BrMYB60 for benzylGSL and BrCYP79B2 for phenethylGSL. Finally, we investigate the expression profiles of the biosynthetic genes for two Phe-derived GSLs by transcriptomic analysis. Our findings provide new insight into the complex machinery of Phe-derived GSLs in seeds of B. rapa and help to improve the quality of Brassicaceae plant breeding.

Genomic selection and genetic architecture of agronomic traits during modern rapeseed breeding

Rapeseed (Brassica napus L.) is an important oil-producing crop for the world. Its adaptation, yield and quality have been considerably improved in recent decades, but the genomic basis underlying successful breeding selection remains unclear. Hence, we conducted a comprehensive genomic assessment of rapeseed in the breeding process based on the whole-genome resequencing of 418 diverse rapeseed accessions. We unraveled the genomic basis for the selection of adaptation and agronomic traits. Genome-wide association studies identified 628 associated loci-related causative candidate genes for 56 agronomically important traits, including plant architecture and yield traits. Furthermore, we uncovered nonsynonymous mutations in plausible candidate genes for agronomic traits with significant differences in allele frequency distributions across the improvement process, including the ribosome recycling factor (BnRRF) gene for seed weight. This study provides insights into the genomic basis for improving rapeseed varieties and a valuable genomic resource for genome-assisted rapeseed breeding.

A major yellow-seed QTL on chromosome A09 significantly increases the oil content and reduces the fiber content of seed in Brassica napus

A major yellow-seed QTL on chromosome A09 significantly increases the oil content and reduces the fiber content of seed in Brassica napus. The yellow-seed trait (YST) has always been a main breeding objective for rapeseed because yellow-seeded B. napus generally contains higher oil contents, fewer pigments and polyphenols and lower fiber content than black-seeded B. napus, although the mechanism controlling this correlation remains unclear. In this study, QTL mapping was implemented for YST based on a KN double haploid population derived from the hybridization of yellow-seeded B. napus N53-2 with a high oil content and black-seeded Ken-C8 with a relatively low oil content. Ten QTLs were identified, including four stable QTLs that could be detected in multiple environments. A major QTL, cqSC-A09, on chromosome A09 was identified by both QTL mapping and BSR-Seq technology, and explained more than 41% of the phenotypic variance. The major QTL cqSC-A09 for YST not only controls the seed color but also affects the oil and fiber contents in seeds. More importantly, the advantageous allele could increase the oil content and reduce the pigment and fiber content at the same time. This is the first QTL reported to control seed color, oil content and fiber content simultaneously with a large effect and has great application value for breeding high oil varieties with high seed quality. Important candidate genes, including BnaA09. JAZ1, BnaA09. GH3.3 and BnaA09. LOX3, were identified for cqSC-A09 by combining sequence variation annotation, expression differences and an interaction network, which lays a foundation for further cloning and breeding applications in the future.

Construction of a Quantitative Genomic Map, Identification and Expression Analysis of Candidate Genes for Agronomic and Disease-Related Traits in Brassica napus

Rapeseed is the second most important oil crop in the world. Improving seed yield and seed oil content are the two main highlights of the research. Unfortunately, rapeseed development is frequently affected by different diseases. Extensive research has been made through many years to develop elite cultivars with high oil, high yield, and/or disease resistance. Quantitative trait locus (QTL) analysis has been one of the most important strategies in the genetic deciphering of agronomic characteristics. To comprehend the distribution of these QTLs and to uncover the key regions that could simultaneously control multiple traits, 4,555 QTLs that have been identified during the last 25 years were aligned in one unique map, and a quantitative genomic map which involved 128 traits from 79 populations developed in 12 countries was constructed. The present study revealed 517 regions of overlapping QTLs which harbored 2,744 candidate genes and might affect multiple traits, simultaneously. They could be selected to customize super-rapeseed cultivars. The gene ontology and the interaction network of those candidates revealed genes that highly interacted with the other genes and might have a strong influence on them. The expression and structure of these candidate genes were compared in eight rapeseed accessions and revealed genes of similar structures which were expressed differently. The present study enriches our knowledge of rapeseed genome characteristics and diversity, and it also provided indications for rapeseed molecular breeding improvement in the future.

A Comparative Transcriptome and Metabolome Combined Analysis Reveals the Key Genes and Their Regulatory Model Responsible for Glucoraphasatin Accumulation in Radish Fleshy Taproots

Radish (Raphanus sativus L.) is rich in specific glucosinolates (GSLs), which benefit human health and special flavor formation. Although the basic GSLs metabolic pathway in Brassicaceae plants is clear, the regulating mechanism for specific glucosinolates content in radish fleshy taproots is not well understood. In this study, we discovered that there was a significant difference in the GSLs profiles and the content of various GSLs components. Glucoraphasatin (GRH) is the most predominant GSL in radish taproots of different genotypes as assessed by HPLC analysis. Further, we compared the taproot transcriptomes of three radish genotypes with high and low GSLs content by employing RNA-seq. Totally, we identified forty-one differentially expressed genes related to GSLs metabolism. Among them, thirteen genes (RsBCAT4, RsIPMDH1, RsMAM1a, RsMAM1b, RsCYP79F1, RsGSTF9, RsGGP1, RsSUR1, RsUGT74C1, RsST5b, RsAPK1, RsGSL-OH, and RsMYB28) were significantly higher co-expressed in the high content genotypes than in low content genotype. Notably, correlation analysis indicated that the expression level of RsMYB28, as an R2R3 transcription factor directly regulating aliphatic glucosinolate biosynthesis, was positively correlated with the GRH content. Co-expression network showed that RsMYB28 probably positively regulated the expression of the above genes, particularly RsSUR1, and consequently the synthesis of GRH. Moreover, the molecular mechanism of the accumulation of this 4-carbon (4C) GSL in radish taproots was explored. This study provides new perspectives on the GSLs accumulation mechanism and genetic improvements in radish taproots.

Genome-Wide Association Reveals Trait Loci for Seed Glucosinolate Accumulation in Indian Mustard (Brassica juncea L.)

Glucosinolates (GSLs) are sulphur- and nitrogen-containing secondary metabolites implicated in the fitness of Brassicaceae and appreciated for their pungency and health-conferring properties. In Indian mustard (Brassica juncea L.), GSL content and composition are seed-quality-determining traits affecting its economic value. Depending on the end use, i.e., condiment or oil, different GSL levels constitute breeding targets. The genetic control of GSL accumulation in Indian mustard, however, is poorly understood, and current knowledge of GSL biosynthesis and regulation is largely based on Arabidopsis thaliana. A genome-wide association study was carried out to dissect the genetic architecture of total GSL content and the content of two major GSLs, sinigrin and gluconapin, in a diverse panel of 158 Indian mustard lines, which broadly grouped into a South Asia cluster and outside-South-Asia cluster. Using 14,125 single-nucleotide polymorphisms (SNPs) as genotyping input, seven distinct significant associations were discovered for total GSL content, eight associations for sinigrin content and 19 for gluconapin. Close homologues of known GSL structural and regulatory genes were identified as candidate genes in proximity to peak SNPs. Our results provide a comprehensive map of the genetic control of GLS biosynthesis in Indian mustard, including priority targets for further investigation and molecular marker development.

Genome- and transcriptome-wide association studies reveal the genetic basis and the breeding history of seed glucosinolate content in Brassica napus

A high content of seed glucosinolates and their degradation products imposes anti-nutritional effects on livestock; therefore, persistent efforts are made to reduce the seed GSL content to increase the commercial value of rapeseed meal. Here, we dissected the genetic structure of SGC by genome-wide association studies (GWAS) combined with transcriptome-wide association studies (TWAS). Fifteen reliable quantitative trait loci (QTLs) were identified to be associated with the reduced SGC in modern B. napus cultivars by GWAS. Analysis of the selection strength and haplotypes at these QTLs revealed that low SGC was predominantly generated by the co-selection of qGSL.A02.2, qGSL.C02.1, qGSL.A09.2, and qGSL.C09.1. Integration of the results from TWAS, comprehensive bioinformatics, and POCKET algorithm analyses indicated that BnaC02.GTR2 (BnaC02g42260D) is a candidate gene underlying qGSL.C02.1. Using CRISPR/Cas9-derived Bna.gtr2s knockout mutants, we experimentally verified that both BnaC02.GTR2 and its three paralogs positively regulate seed GSL accumulation but negatively regulated vegetative tissue GSL contents. In addition, we observed smaller seeds with higher seed oil content in these Bna.gtr2 mutants. Furthermore, both RNA-seq and correlation analyses suggested that Bna.GTR2s might play a comprehensive role in seed development, such as amino acid accumulation, GSL synthesis, sugar assimilation, and oil accumulation. This study unravels the breeding selection history of low-SGC improvement and provides new insights into the molecular function of Bna.GTR2s in both seed GSL accumulation and seed development in B. napus.

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.

Genomic signatures of vegetable and oilseed allopolyploid Brassica juncea and genetic loci controlling the accumulation of glucosinolates

Allopolyploid Brassica juncea crops in Brassicaceae are becoming increasingly revitalized as vegetables and oilseeds owing to wide adaptability and significant economic values. However, the genomic differentiation of diversified vegetables and oilseed B. juncea and the genetic basis underlying glucosinolates accumulation have yet to be elucidated. To address this knowledge gap, we report the sequencing of pairwise genomes of vegetable and oilseed B. juncea at chromosome scale. Comparative genomics analysis unveils panoramic structural variation footprints, particularly the genetic loci of HSP20 and TGA1 associated with abiotic and biotic stresses responses between oilseed and vegetable subgroups. We anchored two major loci of MYB28 (HAG1) orthologues caused by copy number variations on A02 and A09 chromosomes using scored genomic SNPs-based GWAS that are responsible for seed oil quality-determining glucosinolates biosynthesis. These findings will provide valuable repertories of polyploidy genomic information enabling polyploidy genome evolution studies and precise genomic selections for crucial traits like functional components of glucosinolates in B. juncea crops and beyond.

DELLA proteins BnaA6.RGA and BnaC7.RGA negatively regulate fatty acid biosynthesis by interacting with BnaLEC1s in Brassica napus

Seed oil content (SOC) and fatty acid (FA) composition determine the quality and economic value of rapeseed (Brassica napus). Little is known about the role of gibberellic acid (GA) in regulating FA biosynthesis in B. napus. Here, we discovered that four BnaRGAs (B. napus REPRESSOR OF GA), encoding negative regulators of GA signalling, were suppressed during seed development. Compared to the wild type, SOC was reduced in gain-of-function mutants bnaa6.rga-D and ds-3, which also showed reduced oleic acid and increased linoleic acid contents. By contrast, the loss-of-function quadruple mutant bnarga displayed higher SOC during early seed development than the wild type, with increased oleic acid and reduced linoleic acid contents. Notably, only BnaA6.RGA and BnaC7.RGA physically interacted with two BnaLEC1s, which function as essential transcription factors in FA biosynthesis. The FA composition did not significantly differ between bnarga bnalec1 sextuple mutants and bnalec1, suggesting that BnaLEC1s are epistatic to BnaRGAs in the regulation of FA composition. Furthermore, BnaLEC1-induced activation of BnaABI3 expression was repressed by BnaA6.RGA, indicating that GA triggers the degradation of BnaRGAs to relieve their repression of BnaLEC1s, thus promoting the transcription of downstream genes to facilitate oil biosynthesis. Therefore, we uncovered a developmental stage-specific role of GA in regulating oil biosynthesis via the GA-BnaRGA-BnaLEC1 signalling cascade, providing a novel mechanistic understanding of how phytohormones regulate FA biosynthesis in seeds. BnaRGAs represent promising targets for oil crop improvement.

Modeling first order additive × additive epistasis improves accuracy of genomic prediction for sclerotinia stem rot resistance in canola

The fungus Sclerotinia sclerotiorum infects hundreds of plant species including many crops. Resistance to this pathogen in canola (Brassica napus L. subsp. napus) is controlled by numerous quantitative trait loci (QTL). For such polygenic traits, genomic prediction may be useful for breeding as it can capture many QTL at once while also considering nonadditive genetic effects. Here, we test application of common regression models to genomic prediction of S. sclerotiorum resistance in canola in a diverse panel of 218 plants genotyped at 24,634 loci. Disease resistance was scored by infection with an aggressive isolate and monitoring over 3 wk. We found that including first-order additive × additive epistasis in linear mixed models (LMMs) improved accuracy of breeding value estimation between 3 and 40%, depending on method of assessment, and correlation between phenotypes and predicted total genetic values by 14%. Bayesian models performed similarly to or worse than genomic relationship matrix-based models for estimating breeding values or overall phenotypes from genetic values. Bayesian ridge regression, which is most similar to the genomic relationship matrix-based approach in the amount of shrinkage it applies to marker effects, was the most accurate of this family of models. This confirms several studies indicating the highly polygenic nature of sclerotinia stem rot resistance. Overall, our results highlight the use of simple epistasis terms for prediction of breeding values and total genetic values for a complex disease resistance phenotype in canola.

Genetic variation of BnaA3.NIP5;1 expressing in the lateral root cap contributes to boron deficiency tolerance in Brassica napus

Boron (B) is essential for vascular plants. Rapeseed (Brassica napus) is the second leading crop source for vegetable oil worldwide, but its production is critically dependent on B supplies. BnaA3.NIP5;1 was identified as a B-efficient candidate gene in B. napus in our previous QTL fine mapping. However, the molecular mechanism through which this gene improves low-B tolerance remains elusive. Here, we report genetic variation in BnaA3.NIP5;1 gene, which encodes a boric acid channel, is a key determinant of low-B tolerance in B. napus. Transgenic lines with increased BnaA3.NIP5;1 expression exhibited improved low-B tolerance in both the seedling and maturity stages. BnaA3.NIP5;1 is preferentially polar-localized in the distal plasma membrane of lateral root cap (LRC) cells and transports B into the root tips to promote root growth under B-deficiency conditions. Further analysis revealed that a CTTTC tandem repeat in the 5'UTR of BnaA3.NIP5;1 altered the expression level of the gene, which is tightly associated with plant growth and seed yield. Field tests with natural populations and near-isogenic lines (NILs) confirmed that the varieties carried BnaA3.NIP5;1Q allele significantly improved seed yield. Taken together, our results provide novel insights into the low-B tolerance of B. napus, and the elite allele of BnaA3.NIP5;1 could serve as a direct target for breeding low-B-tolerant cultivars.

Genome- and transcriptome-wide association studies provide insights into the genetic basis of natural variation of seed oil content in Brassica napus

Seed oil content (SOC) is a highly important and complex trait in oil crops. Here, we decipher the genetic basis of natural variation in SOC of Brassica napus by genome- and transcriptome-wide association studies using 505 inbred lines. We mapped reliable quantitative trait loci (QTLs) that control SOC in eight environments, evaluated the effect of each QTL on SOC, and analyzed selection in QTL regions during breeding. Six-hundred and ninety-two genes and four gene modules significantly associated with SOC were identified by analyzing population transcriptomes from seeds. A gene prioritization framework, POCKET (prioritizing the candidate genes by incorporating information on knowledge-based gene sets, effects of variants, genome-wide association studies, and transcriptome-wide association studies), was implemented to determine the causal genes in the QTL regions based on multi-omic datasets. A pair of homologous genes, BnPMT6s, in two QTLs were identified and experimentally demonstrated to negatively regulate SOC. This study provides rich genetic resources for improving SOC and valuable insights toward understanding the complex machinery that directs oil accumulation in the seeds of B. napus and other oil crops.