A user guide to the Brassica 60K Illumina Infinium™ SNP genotyping array

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.

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.

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.

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.

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.

Frequent spontaneous structural rearrangements promote rapid genome diversification in a Brassica napus F1 generation

In a cross between two homozygous Brassica napus plants of synthetic and natural origin, we demonstrate that novel structural genome variants from the synthetic parent cause immediate genome diversification among F1 offspring. Long read sequencing in twelve F1 sister plants revealed five large-scale structural rearrangements where both parents carried different homozygous alleles but the heterozygous F1 genomes were not identical heterozygotes as expected. Such spontaneous rearrangements were part of homoeologous exchanges or segmental deletions and were identified in different, individual F1 plants. The variants caused deletions, gene copy-number variations, diverging methylation patterns and other structural changes in large numbers of genes and may have been causal for unexpected phenotypic variation between individual F1 sister plants, for example strong divergence of plant height and leaf area. This example supports the hypothesis that spontaneous de novo structural rearrangements after de novo polyploidization can rapidly overcome intense allopolyploidization bottlenecks to re-expand crops genetic diversity for ecogeographical expansion and human selection. The findings imply that natural genome restructuring in allopolyploid plants from interspecific hybridization, a common approach in plant breeding, can have a considerably more drastic impact on genetic diversity in agricultural ecosystems than extremely precise, biotechnological genome modifications.

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.

Plant Genotype to Phenotype Prediction Using Machine Learning

Genomic prediction tools support crop breeding based on statistical methods, such as the genomic best linear unbiased prediction (GBLUP). However, these tools are not designed to capture non-linear relationships within multi-dimensional datasets, or deal with high dimension datasets such as imagery collected by unmanned aerial vehicles. Machine learning (ML) algorithms have the potential to surpass the prediction accuracy of current tools used for genotype to phenotype prediction, due to their capacity to autonomously extract data features and represent their relationships at multiple levels of abstraction. This review addresses the challenges of applying statistical and machine learning methods for predicting phenotypic traits based on genetic markers, environment data, and imagery for crop breeding. We present the advantages and disadvantages of explainable model structures, discuss the potential of machine learning models for genotype to phenotype prediction in crop breeding, and the challenges, including the scarcity of high-quality datasets, inconsistent metadata annotation and the requirements of ML models.

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.

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.

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.

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.

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.

QTL Mapping and Diurnal Transcriptome Analysis Identify Candidate Genes Regulating Brassica napus Flowering Time

Timely flowering is important for seed formation and maximization of rapeseed (Brassica napus) yield. Here, we performed flowering-time quantitative trait loci (QTL) mapping using a double haploid (DH) population grown in three environments to study the genetic architecture. Brassica 60 K Illumina Infinium™ single nucleotide polymorphism (SNP) array and simple sequence repeat (SSR) markers were used for genotyping of the DH population, and a high-density genetic linkage map was constructed. QTL analysis of flowering time from the three environments revealed five consensus QTLs, including two major QTLs. A major QTL located on chromosome A03 was detected specifically in the semi-winter rapeseed growing region, and the one on chromosome C08 was detected in all environments. Ribonucleic acid sequencing (RNA-seq) was performed on the parents’ leaves at seven time-points in a day to determine differentially expressed genes (DEGs). The biological processes and pathways with significant enrichment of DEGs were obtained. The DEGs in the QTL intervals were analyzed, and four flowering time-related candidate genes were found. These results lay a foundation for the genetic regulation of rapeseed flowering time and create a rapeseed gene expression library for seven time-points in a day.

Candidate Rlm6 resistance genes against Leptosphaeria. maculans identified through a genome-wide association study in Brassica juncea (L.) Czern

One hundred and sixty-seven B. juncea varieties were genotyped on the 90K Brassica assay (42,914 SNPs), which led to the identification of sixteen candidate genes for Rlm6. Brassica species are at high risk of severe crop loss due to pathogens, especially Leptosphaeria maculans (the causal agent of blackleg). Brassica juncea (L.) Czern is an important germplasm resource for canola improvement, due to its good agronomic traits, such as heat and drought tolerance and high blackleg resistance. The present study is the first using genome-wide association studies to identify candidate genes for blackleg resistance in B. juncea based on genome-wide SNPs obtained from the Illumina Infinium 90 K Brassica SNP array. The verification of Rlm6 in B. juncea was performed through a cotyledon infection test. Genotyping 42,914 single nucleotide polymorphisms (SNPs) in a panel of 167 B. juncea lines revealed a total of seven SNPs significantly associated with Rlm6 on chromosomes A07 and B04 in B. juncea. Furthermore, 16 candidate Rlm6 genes were found in these regions, defined as nucleotide binding site leucine-rich-repeat (NLR), leucine-rich repeat RLK (LRR-RLK) and LRR-RLP genes. This study will give insights into the blackleg resistance in B. juncea and facilitate identification of functional blackleg resistance genes which can be used in Brassica breeding.

Untangling structural factors driving genome stabilization in nascent Brassica napus allopolyploids

Allopolyploids have globally higher fitness than their diploid progenitors; however, by comparison, most resynthesized allopolyploids have poor fertility and highly unstable genome. Elucidating the evolutionary processes promoting genome stabilization and fertility is thus essential to comprehend allopolyploid success. Using the Brassica model, we mimicked the speciation process of a nascent allopolyploid species by resynthesizing allotetraploid Brassica napus and systematically selecting for euploid individuals over eight generations in four independent allopolyploidization events with contrasted genetic backgrounds, cytoplasmic donors, and polyploid formation type. We evaluated the evolution of meiotic behavior and fertility and identified rearrangements in S₁ to S₉ lineages to explore the positive consequences of euploid selection on B. napus genome stability. Recurrent selection of euploid plants for eight generations drastically reduced the percentage of aneuploid progenies as early as the fourth generation, concomitantly with a decrease in number of newly fixed homoeologous rearrangements. The consequences of homoeologous rearrangements on meiotic behavior and seed number depended strongly on the genetic background and cytoplasm donor. The combined use of both self-fertilization and recurrent euploid selection allowed identification of genomic regions associated with fertility and meiotic behavior, providing complementary evidence to explain B. napus speciation success.

How Population Structure Impacts Genomic Selection Accuracy in Cross-Validation: Implications for Practical Breeding

Over the last two decades, the application of genomic selection has been extensively studied in various crop species, and it has become a common practice to report prediction accuracies using cross validation. However, genomic prediction accuracies obtained from random cross validation can be strongly inflated due to population or family structure, a characteristic shared by many breeding populations. An understanding of the effect of population and family structure on prediction accuracy is essential for the successful application of genomic selection in plant breeding programs. The objective of this study was to make this effect and its implications for practical breeding programs comprehensible for breeders and scientists with a limited background in quantitative genetics and genomic selection theory. We, therefore, compared genomic prediction accuracies obtained from different random cross validation approaches and within-family prediction in three different prediction scenarios. We used a highly structured population of 940 Brassica napus hybrids coming from 46 testcross families and two subpopulations. Our demonstrations show how genomic prediction accuracies obtained from among-family predictions in random cross validation and within-family predictions capture different measures of prediction accuracy. While among-family prediction accuracy measures prediction accuracy of both the parent average component and the Mendelian sampling term, within-family prediction only measures how accurately the Mendelian sampling term can be predicted. With this paper we aim to foster a critical approach to different measures of genomic prediction accuracy and a careful analysis of values observed in genomic selection experiments and reported in literature.

Linkage mapping and QTL analysis of flowering time using ddRAD sequencing with genotype error correction in Brassica napus

BACKGROUND

Brassica napus is an important oilseed crop cultivated worldwide. During domestication and breeding of B. napus, flowering time has been a target of selection because of its substantial impact on yield. Here we use double digest restriction-site associated DNA sequencing (ddRAD) to investigate the genetic basis of flowering in B. napus. An F2 mapping population was derived from a cross between an early-flowering spring type and a late-flowering winter type.

RESULTS

Flowering time in the mapping population differed by up to 25 days between individuals. High genotype error rates persisted after initial quality controls, as suggested by a genotype discordance of ~ 12% between biological sequencing replicates. After genotype error correction, a linkage map spanning 3981.31 cM and compromising 14,630 single nucleotide polymorphisms (SNPs) was constructed. A quantitative trait locus (QTL) on chromosome C2 was detected, covering eight flowering time genes including FLC.

CONCLUSIONS

These findings demonstrate the effectiveness of the ddRAD approach to sample the B. napus genome. Our results also suggest that ddRAD genotype error rates can be higher than expected in F2 populations. Quality filtering and genotype correction and imputation can substantially reduce these error rates and allow effective linkage mapping and QTL analysis.

The Use of Genetic and Gene Technologies in Shaping Modern Rapeseed Cultivars (Brassica napus L.)

Since their domestication, Brassica oilseed species have undergone progressive transformation allied with the development of breeding and molecular technologies. The canola (Brassica napus) crop has rapidly expanded globally in the last 30 years with intensive innovations in canola varieties, providing for a wider range of markets apart from the food industry. The breeding efforts of B. napus, the main source of canola oil and canola meal, have been mainly focused on improving seed yield, oil quality, and meal quality along with disease resistance, abiotic stress tolerance, and herbicide resistance. The revolution in genetics and gene technologies, including genetic mapping, molecular markers, genomic tools, and gene technology, especially gene editing tools, has allowed an understanding of the complex genetic makeup and gene functions in the major bioprocesses of the Brassicales, especially Brassica oil crops. Here, we provide an overview on the contributions of these technologies in improving the major traits of B. napus and discuss their potential use to accomplish new improvement targets.

Tool for genomic selection and breeding to evolutionary adaptation: Development of a 100K single nucleotide polymorphism array for the honey bee

High-throughput high-density genotyping arrays continue to be a fast, accurate, and cost-effective method for genotyping thousands of polymorphisms in high numbers of individuals. Here, we have developed a new high-density SNP genotyping array (103,270 SNPs) for honey bees, one of the most ecologically and economically important pollinators worldwide. SNPs were detected by conducting whole-genome resequencing of 61 honey bee drones (haploid males) from throughout Europe. Selection of SNPs for the chip was done in multiple steps using several criteria. The majority of SNPs were selected based on their location within known candidate regions or genes underlying a range of honey bee traits, including hygienic behavior against pathogens, foraging, and subspecies. Additionally, markers from a GWAS of hygienic behavior against the major honey bee parasite Varroa destructor were brought over. The chip also includes SNPs associated with each of three major breeding objectives-honey yield, gentleness, and Varroa resistance. We validated the chip and make recommendations for its use by determining error rates in repeat genotypings, examining the genotyping performance of different tissues, and by testing how well different sample types represent the queen's genotype. The latter is a key test because it is highly beneficial to be able to determine the queen's genotype by nonlethal means. The array is now publicly available and we suggest it will be a useful tool in genomic selection and honey bee breeding, as well as for GWAS of different traits, and for population genomic, adaptation, and conservation questions.

A Genome-Wide Association Study Identifying Genetic Variants Associated with Growth, Carcass and Meat Quality Traits in Rabbits

Growth, carcass characteristics and meat quality are the most important traits used in the rabbit industry. Identification of the candidate markers and genes significantly associated with these traits will be beneficial in rabbit breeding. In this study, we enrolled 465 rabbits, including 16 male Californian rabbits and 17 female Kangda5 line rabbits as the parental generation, along with their offspring (232 male and 200 female), in a genome-wide association study (GWAS) based on SLAF-seq technology. Bodyweight at 35, 42, 49, 56, 63 and 70 d was recorded for growth traits; and slaughter liveweight (84 d) and dressing out percentage were measured as carcass traits; and cooking loss and drip loss were measured as meat quality traits. A total of 5,223,720 SLAF markers were obtained by digesting the rabbit genome using RsaI + EcoRV-HF® restriction enzymes. After quality control, a subset of 317,503 annotated single-nucleotide polymorphisms (SNPs) was retained for subsequent analysis. A total of 28, 81 and 10 SNPs for growth, carcass and meat quality traits, respectively, were identified based on genome-wide significance (p < 3.16 × 10-7). Additionally, 16, 71 and 9 candidate genes were identified within 100 kb upstream or downstream of these SNPs. Further analysis is required to determine the biological roles of these candidate genes in determining rabbit growth, carcass traits and meat quality.

Role of NGS and SNP genotyping methods in sugarcane improvement programs

Sugarcane (Saccharum spp.) is one of the most economically significant crops because of its high sucrose content and it is a promising biomass feedstock for biofuel production. Sugarcane genome sequencing and analysis is a difficult task due to its heterozygosity and polyploidy. Long sequence read technologies, PacBio Single-Molecule Real-Time (SMRT) sequencing, the Illumina TruSeq, and the Oxford Nanopore sequencing could solve the problem of genome assembly. On the applications side, next generation sequencing (NGS) technologies played a major role in the discovery of single nucleotide polymorphism (SNP) and the development of low to high throughput genotyping platforms. The two mainstream high throughput genotyping platforms are the SNP microarray and genotyping by sequencing (GBS). This paper reviews the NGS in sugarcane genomics, genotyping methodologies, and the choice of these methods. Array-based SNP genotyping is robust, provides consistent SNPs, and relatively easier downstream data analysis. The GBS method identifies large scale SNPs across the germplasm. A combination of targeted GBS and array-based genotyping methods should be used to increase the accuracy of genomic selection and marker-assisted breeding.

Gene presence-absence variation associates with quantitative Verticillium longisporum disease resistance in Brassica napus

Although copy number variation (CNV) and presence-absence variation (PAV) have been discovered in selected gene families in most crop species, the global prevalence of these polymorphisms in most complex genomes is still unclear and their influence on quantitatively inherited agronomic traits is still largely unknown. Here we analyze the association of gene PAV with resistance of oilseed rape (Brassica napus) against the important fungal pathogen Verticillium longisporum, as an example for a complex, quantitative disease resistance in the strongly rearranged genome of a recent allopolyploid crop species. Using Single Nucleotide absence Polymorphism (SNaP) markers to efficiently trace PAV in breeding populations, we significantly increased the resolution of loci influencing V. longisporum resistance in biparental and multi-parental mapping populations. Gene PAV, assayed by resequencing mapping parents, was observed in 23-51% of the genes within confidence intervals of quantitative trait loci (QTL) for V. longisporum resistance, and high-priority candidate genes identified within QTL were all affected by PAV. The results demonstrate the prominent role of gene PAV in determining agronomic traits, suggesting that this important class of polymorphism should be exploited more systematically in future plant breeding.

Strong temporal dynamics of QTL action on plant growth progression revealed through high-throughput phenotyping in canola

A major challenge of plant biology is to unravel the genetic basis of complex traits. We took advantage of recent technical advances in high-throughput phenotyping in conjunction with genome-wide association studies to elucidate genotype-phenotype relationships at high temporal resolution. A diverse Brassica napus population from a commercial breeding programme was analysed by automated non-invasive phenotyping. Time-resolved data for early growth-related traits, including estimated biovolume, projected leaf area, early plant height and colour uniformity, were established and complemented by fresh and dry weight biomass. Genome-wide SNP array data provided the framework for genome-wide association analyses. Using time point data and relative growth rates, multiple robust main effect marker-trait associations for biomass and related traits were detected. Candidate genes involved in meristem development, cell wall modification and transcriptional regulation were detected. Our results demonstrate that early plant growth is a highly complex trait governed by several medium and many small effect loci, most of which act only during short phases. These observations highlight the importance of taking the temporal patterns of QTL/allele actions into account and emphasize the need for detailed time-resolved analyses to effectively unravel the complex and stage-specific contributions of genes affecting growth processes that operate at different developmental phases.

Identification of QTLs Containing Resistance Genes for Sclerotinia Stem Rot in Brassica napus Using Comparative Transcriptomic Studies

Sclerotinia stem rot is a major disease in Brassica napus that causes yield losses of 10-20% and reaching 80% in severely infected fields. SSR not only causes yield reduction but also causes low oil quality by reducing fatty acid content. There is a need to identify resistant genetic sources with functional significance for the breeding of SSR-resistant cultivars. In this study, we identified 17 QTLs involved in SSR resistance in three different seasons using SNP markers and disease lesion development after artificial inoculation. There were no common QTLs in all 3 years, but there were three QTLs that appeared in two seasons covering all seasons with a shared QTL. The QTLs identified in the 2 years were SRA9a, SRC2a and SRC3a with phenotypic effect variances of 14.75 and 11.57% for SRA9a, 7.49 and 10.38% for SRC3a and 7.73 and 6.81% for SRC2a in their 2 years, respectively. The flowering time was also found to have a negative correlation with disease resistance, i.e., early-maturing lines were more susceptible to disease. The stem width has shown a notably weak effect on disease development, causing researchers to ignore its effect. Given that flowering time is an important factor in disease resistance, we used comparative RNA-sequencing analysis of resistant and susceptible lines with consistent performance in 3 years with almost the same flowering time to identify the resistance genes directly involved in resistance within the QTL regions. Overall, there were more genes differentially expressed in resistant lines 19,970 than in susceptible lines 3936 compared to their mock-inoculated lines, demonstrating their tendency to cope with disease. We identified 36 putative candidate genes from the resistant lines that were upregulated in resistant lines compared to resistant mock and susceptible lines that might be involved in resistance to SSR.

Variation in Expression of the HECT E3 Ligase UPL3 Modulates LEC2 Levels, Seed Size, and Crop Yields in Brassica napus

Identifying genetic variation that increases crop yields is a primary objective in plant breeding. We used association analyses of oilseed rape/canola (Brassica napus) accessions to identify genetic variation that influences seed size, lipid content, and final crop yield. Variation in the promoter region of the HECT E3 ligase gene BnaUPL3 C03 made a major contribution to variation in seed weight per pod, with accessions exhibiting high seed weight per pod having lower levels of BnaUPL3 C03 expression. We defined a mechanism in which UPL3 mediated the proteasomal degradation of LEC2, a master transcriptional regulator of seed maturation. Accessions with reduced UPL3 expression had increased LEC2 protein levels, larger seeds, and prolonged expression of lipid biosynthetic genes during seed maturation. Natural variation in BnaUPL3 C03 expression appears not to have been exploited in current B napus breeding lines and could therefore be used as a new approach to maximize future yields in this important oil crop.

"Doubled-haploid" allohexaploid Brassica lines lose fertility and viability and accumulate genetic variation due to genomic instability

Microspore culture stimulates immature pollen grains to develop into plants via tissue culture and is used routinely in many crop species to produce "doubled haploids": homozygous, true-breeding lines. However, microspore culture is also often used on material that does not have stable meiosis, such as interspecific hybrids. In this case, the resulting progeny may lose their "doubled haploid" homozygous status as a result of chromosome missegregation and homoeologous exchanges. However, little is known about the frequency of these effects. We assessed fertility, meiosis and genetic variability in self-pollinated progeny sets (the MDL2 population) resulting from first-generation plants (the MDL1 population) derived from microspores of a near-allohexaploid interspecific hybrid from the cross (Brassica napus × B. carinata) × B. juncea. Allelic inheritance and copy number variation were predicted using single nucleotide polymorphism marker data from the Illumina Infinium 60K Brassica array. Seed fertility and viability decreased substantially from the MDL1 to the MDL2 generation. In the MDL2 population, 87% of individuals differed genetically from their MDL1 parent. These genetic differences resulted from novel homoeologous exchanges between chromosomes, chromosome loss and gain, and segregation and instability of pre-existing karyotype abnormalities. Novel karyotype change was extremely common, with 2.2 new variants observed per MDL2 individual. Significant differences between progeny sets in the number of novel genetic variants were also observed. Meiotic instability clearly has the potential to dramatically change karyotypes (often without detectable effects on the presence or absence of alleles) in putatively homozygous, microspore-derived lines, resulting in loss of fertility and viability.

Overexpression of Acyl-ACP Thioesterases, CpFatB4 and CpFatB5, Induce Distinct Gene Expression Reprogramming in Developing Seeds of Brassica napus

We examined the substrate preference of Cuphea paucipetala acyl-ACP thioesterases, CpFatB4 and CpFatB5, and gene expression changes associated with the modification of lipid composition in the seed, using Brassica napus transgenic plants overexpressing CpFatB4 or CpFatB5 under the control of a seed-specific promoter. CpFatB4 seeds contained a higher level of total saturated fatty acid (FA) content, with 4.3 times increase in 16:0 palmitic acid, whereas CpFatB5 seeds showed approximately 3% accumulation of 10:0 and 12:0 medium-chain FAs, and a small increase in other saturated FAs, resulting in higher levels of total saturated FAs. RNA-Seq analysis using entire developing pods at 8, 25, and 45 days after flowering (DAF) showed up-regulation of genes for β-ketoacyl-acyl carrier protein synthase I/II, stearoyl-ACP desaturase, oleate desaturase, and linoleate desaturase, which could increase unsaturated FAs and possibly compensate for the increase in 16:0 palmitic acid at 45 DAF in CpFatB4 transgenic plants. In CpFatB5 transgenic plants, many putative chloroplast- or mitochondria-encoded genes were identified as differentially expressed. Our results report comprehensive gene expression changes induced by alterations of seed FA composition and reveal potential targets for further genetic modifications.

Inherited allelic variants and novel karyotype changes influence fertility and genome stability in Brassica allohexaploids

Synthetic allohexaploid Brassica hybrids (2n = AABBCC) do not exist naturally, but can be synthesized by crosses between diploid and/or allotetraploid Brassica species. Using these hybrids, we aimed to identify how novel allohexaploids restore fertility and normal meiosis after formation. Chromosome inheritance, genome structure, fertility and meiotic behaviour were assessed in three segregating allohexaploid populations derived from the cross (B. napus × B. carinata) × B. juncea using a combination of molecular marker genotyping, phenotyping and cytogenetics. Plants with unbalanced A-C translocations in one direction (where a C-genome chromosome fragment replaces an A-genome fragment) but not the other (where an A-genome fragment replaces a C-genome fragment) showed significantly reduced fertility across all populations. Genomic regions associated with fertility contained several meiosis genes with putatively causal mutations inherited from the parents (copies of SCC2 in the A genome, PAIR1/PRD3, PRD1 and ATK1/KATA/KIN14a in the B genome, and MSH2 and SMC1/TITAN8 in the C genome). Reduced seed fertility associated with the loss of chromosome fragments from only one subgenome following homoeologous exchanges could comprise a mechanism for biased genome fractionation in allopolyploids. Pre-existing meiosis gene variants present in allotetraploid parents may help to stabilize meiosis in novel allohexaploids.

Assessment of low-coverage nanopore long read sequencing for SNP genotyping in doubled haploid canola (Brassica napus L.)

Despite the high accuracy of short read sequencing (SRS), there are still issues with attaining accurate single nucleotide polymorphism (SNP) genotypes at low sequencing coverage and in highly duplicated genomes due to misalignment. Long read sequencing (LRS) systems, including the Oxford Nanopore Technologies (ONT) minION, have become popular options for de novo genome assembly and structural variant characterisation. The current high error rate often requires substantial post-sequencing correction and would appear to prevent the adoption of this system for SNP genotyping, but nanopore sequencing errors are largely random. Using low coverage ONT minION sequencing for genotyping of pre-validated SNP loci was examined in 9 canola doubled haploids. The minION genotypes were compared to the Illumina sequences to determine the extent and nature of genotype discrepancies between the two systems. The significant increase in read length improved alignment to the genome and the absence of classical SRS biases results in a more even representation of the genome. Sequencing errors are present, primarily in the form of heterozygous genotypes, which can be removed in completely homozygous backgrounds but requires more advanced bioinformatics in heterozygous genomes. Developments in this technology are promising for routine genotyping in the future.

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

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

Connecting genome structural variation with complex traits in crop plants

Structural genome variation is a major determinant of useful trait diversity. We describe how genome analysis methods are enabling discovery of trait-associated structural variants and their potential impact on breeding. As our understanding of complex crop genomes continues to grow, there is growing evidence that structural genome variation plays a major role in determining traits important for breeding and agriculture. Identifying the extent and impact of structural variants in crop genomes is becoming increasingly feasible with ongoing advances in the sophistication of genome sequencing technologies, particularly as it becomes easier to generate accurate long sequence reads on a genome-wide scale. In this article, we discuss the origins of structural genome variation in crops from ancient and recent genome duplication and polyploidization events and review high-throughput methods to assay such variants in crop populations in order to find associations with phenotypic traits. There is increasing evidence from such studies that gene presence-absence and copy number variation resulting from segmental chromosome exchanges may be at the heart of adaptive variation of crops to counter abiotic and biotic stress factors. We present examples from major crops that demonstrate the potential of pangenomic diversity as a key resource for future plant breeding for resilience and sustainability.

An APETALA1 ortholog affects plant architecture and seed yield component in oilseed rape (Brassica napus L.)

BACKGROUND

Increasing the productivity of rapeseed as one of the widely cultivated oil crops in the world is of upmost importance. As flowering time and plant architecture play a key role in the regulation of rapeseed yield, understanding the genetic mechanism underlying these traits can boost the rapeseed breeding. Meristem identity genes are known to have pleiotropic effects on plant architecture and seed yield in various crops. To understand the function of one of the meristem identity genes, APETALA1 (AP1) in rapeseed, we performed phenotypic analysis of TILLING mutants under greenhouse conditions. Three stop codon mutant families carrying a mutation in Bna.AP1.A02 paralog were analyzed for different plant architecture and seed yield-related traits.

RESULTS

It was evident that stop codon mutation in the K domain of Bna.AP1.A02 paralog caused significant changes in flower morphology as well as plant architecture related traits like plant height, branch height, and branch number. Furthermore, yield-related traits like seed yield per plant and number of seeds per plants were also significantly altered in the same mutant family. Apart from phenotypic changes, stop codon mutation in K domain of Bna.AP1.A02 paralog also altered the expression of putative downstream target genes like Bna.TFL1 and Bna.FUL in shoot apical meristem (SAM) of rapeseed. Mutant plants carrying stop codon mutations in the COOH domain of Bna.AP1.A02 paralog did not have a significant effect on plant architecture, yield-related traits or the expression of the downstream targets.

CONCLUSIONS

We found that Bna.AP1.A02 paralog has pleiotropic effect on plant architecture and yield-related traits in rapeseed. The allele we found in the current study with a beneficial effect on seed yield can be incorporated into rapeseed breeding pool to develop new varieties.

Finding invisible quantitative trait loci with missing data

Evolutionary processes during plant polyploidization and speciation have led to extensive presence-absence variation (PAV) in crop genomes, and there is increasing evidence that PAV associates with important traits. Today, high-resolution genetic analysis in major crops frequently implements simple, cost-effective, high-throughput genotyping from single nucleotide polymorphism (SNP) hybridization arrays; however, these are normally not designed to distinguish PAV from failed SNP calls caused by hybridization artefacts. Here, we describe a strategy to recover valuable information from single nucleotide absence polymorphisms (SNaPs) by population-based quality filtering of SNP hybridization data to distinguish patterns associated with genuine deletions from those caused by technical failures. We reveal that including SNaPs in genetic analyses elucidate segregation of small to large-scale structural variants in nested association mapping populations of oilseed rape (Brassica napus), a recent polyploid crop with widespread structural variation. Including SNaP markers in genomewide association studies identified numerous quantitative trait loci, invisible using SNP markers alone, for resistance to two major fungal diseases of oilseed rape, Sclerotinia stem rot and blackleg disease. Our results indicate that PAV has a strong influence on quantitative disease resistance in B. napus and that SNaP analysis using cost-effective SNP array data can provide extensive added value from 'missing data'. This strategy might also be applicable for improving the precision of genetic mapping in many important crop species.

Detecting de Novo Homoeologous Recombination Events in Cultivated Brassica napus Using a Genome-Wide SNP Array

The heavy selection pressure due to intensive breeding of Brassica napus has created a narrow gene pool, limiting the ability to produce improved varieties through crosses between B. napus cultivars. One mechanism that has contributed to the adaptation of important agronomic traits in the allotetraploid B. napus has been chromosomal rearrangements resulting from homoeologous recombination between the constituent A and C diploid genomes. Determining the rate and distribution of such events in natural B. napus will assist efforts to understand and potentially manipulate this phenomenon. The Brassica high-density 60K SNP array, which provides genome-wide coverage for assessment of recombination events, was used to assay 254 individuals derived from 11 diverse cultivated spring type B. napus These analyses identified reciprocal allele gain and loss between the A and C genomes and allowed visualization of de novo homoeologous recombination events across the B. napus genome. The events ranged from loss/gain of 0.09 Mb to entire chromosomes, with almost 5% aneuploidy observed across all gametes. There was a bias toward sub-telomeric exchanges leading to genome homogenization at chromosome termini. The A genome replaced the C genome in 66% of events, and also featured more dominantly in gain of whole chromosomes. These analyses indicate de novo homoeologous recombination is a continuous source of variation in established Brassica napus and the rate of observed events appears to vary with genetic background. The Brassica 60K SNP array will be a useful tool in further study and manipulation of this phenomenon.

Tools for Genetic Studies in Experimental Populations of Polyploids

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

Hidden Effects of Seed Quality Breeding on Germination in Oilseed Rape (Brassica napus L.)

Intense selection for specific seed qualities in winter oilseed rape breeding has had an inadvertent negative influence on seed germination performance. In a panel of 215 diverse winter oilseed rape varieties spanning over 50 years of breeding progress in winter-type rapeseed, we found that low seed erucic acid content and reduced seed glucosinolate content were significantly related with prolonged germination time. Genome-wide association mapping revealed that this relationship is caused by linkage drag between important loci for seed quality and germination traits. One QTL for mean germination time on chromosome A09 co-localized with significant but minor QTL for both seed erucic acid and seed glucosinolate content. This suggested either potential pleiotropy or close linkage of minor factors influencing all three traits. Therefore, a reduction in germination performance may be due to inadvertent co-selection of genetic variants associated with 00 seed quality that have a negative influence on germination. Our results suggest that marker-assisted selection of positive alleles for mean germination time within the modern quality pool can help breeders to maintain maximal germination capacity in new 00-quality oilseed rape cultivars.

The effect of INDEHISCENT point mutations on silique shatter resistance in oilseed rape (Brassica napus)

This study elucidates the influence of indehiscent mutations on rapeseed silique shatter resistance. A phenotype with enlarged replum-valve joint area and altered cell dimensions in the dehiscence zone is described. Silique shattering is a major factor reducing the yield stability of oilseed rape (Brassica napus). Attempts to improve shatter resistance often include the use of mutations in target genes identified from Arabidopsis (Arabidopsis thaliana). A variety of phenotyping methods assessing the level of shatter resistance were previously described. However, a comparative and comprehensive evaluation of the methods has not yet been undertaken. We verified the increase of shatter resistance in indehiscent double knock-down mutants obtained by TILLING with a systematic approach comparing three independent phenotyping methods. A positive correlation of silique length and shatter resistance was observed and accounted for in the analyses. Microscopic studies ruled out the influence of different lignification patterns. Instead, we propose a model to explain increased shattering resistance of indehiscent rapeseed mutants by altered cell shapes and sizes within the contact surfaces of replum and valves.

Genome-wide regression models considering general and specific combining ability predict hybrid performance in oilseed rape with similar accuracy regardless of trait architecture

Genomic prediction using the Brassica 60 k genotyping array is efficient in oilseed rape hybrids. Prediction accuracy is more dependent on trait complexity than on the prediction model. In oilseed rape breeding programs, performance prediction of parental combinations is of fundamental importance. Due to the phenomenon of heterosis, per se performance is not a reliable indicator for F₁-hybrid performance, and selection of well-paired parents requires the testing of large quantities of hybrid combinations in extensive field trials. However, the number of potential hybrids, in general, dramatically exceeds breeding capacity and budget. Integration of genomic selection (GS) could substantially increase the number of potential combinations that can be evaluated. GS models can be used to predict the performance of untested individuals based only on their genotypic profiles, using marker effects previously predicted in a training population. This allows for a preselection of promising genotypes, enabling a more efficient allocation of resources. In this study, we evaluated the usefulness of the Illumina Brassica 60 k SNP array for genomic prediction and compared three alternative approaches based on a homoscedastic ridge regression BLUP and three Bayesian prediction models that considered general and specific combining ability (GCA and SCA, respectively). A total of 448 hybrids were produced in a commercial breeding program from unbalanced crosses between 220 paternal doubled haploid lines and five male-sterile testers. Predictive ability was evaluated for seven agronomic traits. We demonstrate that the Brassica 60 k genotyping array is an adequate and highly valuable platform to implement genomic prediction of hybrid performance in oilseed rape. Furthermore, we present first insights into the application of established statistical models for prediction of important agronomical traits with contrasting patterns of polygenic control.

Diversity and Genome Analysis of Australian and Global Oilseed Brassica napus L. Germplasm Using Transcriptomics and Whole Genome Re-sequencing

Intensive breeding of Brassica napus has resulted in relatively low diversity, such that B. napus would benefit from germplasm improvement schemes that sustain diversity. As such, samples representative of global germplasm pools need to be assessed for existing population structure, diversity and linkage disequilibrium (LD). Complexity reduction genotyping-by-sequencing (GBS) methods, including GBS-transcriptomics (GBS-t), enable cost-effective screening of a large number of samples, while whole genome re-sequencing (WGR) delivers the ability to generate large numbers of unbiased genomic single nucleotide polymorphisms (SNPs), and identify structural variants (SVs). Furthermore, the development of genomic tools based on whole genomes representative of global oilseed diversity and orientated by the reference genome has substantial industry relevance and will be highly beneficial for canola breeding. As recent studies have focused on European and Chinese varieties, a global diversity panel as well as a substantial number of Australian spring types were included in this study. Focusing on industry relevance, 633 varieties were initially genotyped using GBS-t to examine population structure using 61,037 SNPs. Subsequently, 149 samples representative of global diversity were selected for WGR and both data sets used for a side-by-side evaluation of diversity and LD. The WGR data was further used to develop genomic resources consisting of a list of 4,029,750 high-confidence SNPs annotated using SnpEff, and SVs in the form of 10,976 deletions and 2,556 insertions. These resources form the basis of a reliable and repeatable system allowing greater integration between canola genomics studies, with a strong focus on breeding germplasm and industry applicability.

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

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

Novel and major QTL for branch angle detected by using DH population from an exotic introgression in rapeseed (Brassica napus L.)

A high-density SNP map was constructed and several novel QTL for branch angle across six environments in Brassica napus were identified. Branch angle is a major determinant for the ideotype of a plant, while the mechanisms underlying this trait in Brassica napus remain elusive. Herein, we developed one doubled haploid population from a cross involving one Capsella bursa-pastoris derived B. napus intertribal introgression line with the compressed branches and wooden stems, and constructed a high-density SNP map covering the genetic distance of 2242.14 cM, with an average marker interval of 0.73 cM. After phenotypic measurements across six environments, the inclusive composite interval mapping algorithm was conducted to analyze the QTL associated with branch angle. In single-environment analysis, a total of 17 QTL were detected and mainly distributed on chromosomes A01, A03, A09 and C03. Of these, three major QTL, qBA.A03-2, qBA.C03-3 and qBA.C03-4 were steadily expressed, each explaining more than 10% of the phenotypic variation in at least two environments. Compared with other results on rapeseed branch angle, these major QTL were newly detected. In QTL by environment interactions (QEI) mapping, 10 QTL were identified, and the QTL average effect and QEI effect were estimated. Of these, 7 QTL were detected in both single-environment analysis and QEI mapping. Based on the physical positions of SNPs and the functional annotation of the Arabidopsis thaliana genome, 27 genes within the QTL regions were selected as candidate genes, including early auxin-responsive genes, small auxin-up RNA, auxin/indoleacetic acid and gretchenhagen-3. These results may pave the way for deciphering the genetic control of branch angle in B. napus.

Mapping of homoeologous chromosome exchanges influencing quantitative trait variation in Brassica napus

Genomic rearrangements arising during polyploidization are an important source of genetic and phenotypic variation in the recent allopolyploid crop Brassica napus. Exchanges among homoeologous chromosomes, due to interhomoeologue pairing, and deletions without compensating homoeologous duplications are observed in both natural B. napus and synthetic B. napus. Rearrangements of large or small chromosome segments induce gene copy number variation (CNV) and can potentially cause phenotypic changes. Unfortunately, complex genome restructuring is difficult to deal with in linkage mapping studies. Here, we demonstrate how high-density genetic mapping with codominant, physically anchored SNP markers can detect segmental homoeologous exchanges (HE) as well as deletions and accurately link these to QTL. We validated rearrangements detected in genetic mapping data by whole-genome resequencing of parental lines along with cytogenetic analysis using fluorescence in situ hybridization with bacterial artificial chromosome probes (BAC-FISH) coupled with PCR using primers specific to the rearranged region. Using a well-known QTL region influencing seed quality traits as an example, we confirmed that HE underlies the trait variation in a DH population involving a synthetic B. napus trait donor, and succeeded in narrowing the QTL to a small defined interval that enables delineation of key candidate genes.

Genome-wide regression models considering general and specific combining ability predict hybrid performance in oilseed rape with similar accuracy regardless of trait architecture

KEY MESSAGE

Genomic prediction using the Brassica 60 k genotyping array is efficient in oilseed rape hybrids. Prediction accuracy is more dependent on trait complexity than on the prediction model. In oilseed rape breeding programs, performance prediction of parental combinations is of fundamental importance. Due to the phenomenon of heterosis, per se performance is not a reliable indicator for F₁-hybrid performance, and selection of well-paired parents requires the testing of large quantities of hybrid combinations in extensive field trials. However, the number of potential hybrids, in general, dramatically exceeds breeding capacity and budget. Integration of genomic selection (GS) could substantially increase the number of potential combinations that can be evaluated. GS models can be used to predict the performance of untested individuals based only on their genotypic profiles, using marker effects previously predicted in a training population. This allows for a preselection of promising genotypes, enabling a more efficient allocation of resources. In this study, we evaluated the usefulness of the Illumina Brassica 60 k SNP array for genomic prediction and compared three alternative approaches based on a homoscedastic ridge regression BLUP and three Bayesian prediction models that considered general and specific combining ability (GCA and SCA, respectively). A total of 448 hybrids were produced in a commercial breeding program from unbalanced crosses between 220 paternal doubled haploid lines and five male-sterile testers. Predictive ability was evaluated for seven agronomic traits. We demonstrate that the Brassica 60 k genotyping array is an adequate and highly valuable platform to implement genomic prediction of hybrid performance in oilseed rape. Furthermore, we present first insights into the application of established statistical models for prediction of important agronomical traits with contrasting patterns of polygenic control.

Development and Evaluation of a Barley 50k iSelect SNP Array

High-throughput genotyping arrays continue to be an attractive, cost-effective alternative to sequencing based approaches. We have developed a new 50k Illumina Infinium iSelect genotyping array for barley, a cereal crop species of major international importance. The majority of SNPs on the array have been extracted from variants called in exome capture data of a wide range of European barley germplasm. We used the recently published barley pseudomolecule assembly to map the exome capture data, which allowed us to generate markers with accurate physical positions and detailed gene annotation. Markers from an existing and widely used barley 9k Infinium iSelect array were carried over onto the 50k chip for backward compatibility. The array design featured 49,267 SNP markers that converted into 44,040 working assays, of which 43,461 were scorable in GenomeStudio. Of the working assays, 6,251 are from the 9k iSelect platform. We validated the SNPs by comparing the genotype calls from the new array to legacy datasets. Rates of agreement averaged 98.1 and 93.9% respectively for the legacy 9k iSelect SNP set (Comadran et al., 2012) and the exome capture SNPs. To test the utility of the 50k chip for genetic mapping, we genotyped a segregating population derived from a Golden Promise × Morex cross (Liu et al., 2014) and mapped over 14,000 SNPs to genetic positions which showed a near exact correspondence to their known physical positions. Manual adjustment of the cluster files used by the interpreting software for genotype scoring improved results substantially, but migration of cluster files between sites led to a deterioration of results, suggesting that local adjustment of cluster files is required on a site-per-site basis. Information relating to the markers on the chip is available online at https://ics.hutton.ac.uk/50k.