Finding invisible quantitative trait loci with missing data

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.

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

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

Homoeologous non-reciprocal translocation explains a major QTL for seed lignin content in oilseed rape (Brassica napus L.)

A homoeologous non-reciprocal translocation was identified in the major QTL for seed lignin content in the low lignin line SGDH14. The lignin biosynthetic gene PAL4 was deleted. Oilseed rape is a major oil crop and a valuable protein source for animal and human nutrition. Lignin is a non-digestible, major component of the seed coat with negative effect on sensory quality, bioavailability and usage of oilseed rape's protein. Hence, seed lignin reduction is of economic and nutritional importance. In this study, the major QTL for reduced lignin content found on chromosome C05 in the DH population SGDH14 x Express 617 was further examined. SGDH14 had lower seed lignin content than Express 617. Harvested seeds from a F2 population of the same cross were additionally field tested and used for seed quality analysis. The F2 population showed a bimodal distribution for seed lignin content. F2 plants with low lignin content had thinner seed coats compared to high lignin lines. Both groups showed a dark seed colour with a slightly lighter colour in the low lignin group indicating that a low lignin content is not necessarily associated with yellow seed colour. Mapping of genomic long-reads from SGDH14 against the Express 617 genome assembly revealed a homoeologous non-reciprocal translocation (HNRT) in the confidence interval of the major QTL for lignin content. A homologous A05 region is duplicated and replaced the C05 region in SGDH14. As consequence several genes located in the C05 region were lost in SGDH14. Thus, a HNRT was identified in the major QTL region for reduced lignin content in the low lignin line SGDH14. The most promising candidate gene related to lignin biosynthesis on C05, PAL4, was deleted.

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.

A catalogue of resistance gene homologs and a chromosome-scale reference sequence support resistance gene mapping in winter wheat

A resistance gene atlas is an integral component of the breeder's arsenal in the fight against evolving pathogens. Thanks to high-throughput sequencing, catalogues of resistance genes can be assembled even in crop species with large and polyploid genomes. Here, we report on capture sequencing and assembly of resistance gene homologs in a diversity panel of 907 winter wheat genotypes comprising ex situ genebank accessions and current elite cultivars. In addition, we use accurate long-read sequencing and chromosome conformation capture sequencing to construct a chromosome-scale genome sequence assembly of cv. Attraktion, an elite variety representative of European winter wheat. We illustrate the value of our resource for breeders and geneticists by (i) comparing the resistance gene complements in plant genetic resources and elite varieties and (ii) conducting genome-wide associations scans (GWAS) for the fungal diseases yellow rust and leaf rust using reference-based and reference-free GWAS approaches. The gene content under GWAS peaks was scrutinized in the assembly of cv. Attraktion.

Homoeologous chromosome exchange explains the creation of a QTL affecting soil-borne pathogen resistance in tobacco

Crop plant partial resistance to plant pathogens controlled by quantitative trait loci (QTL) is desirable in cultivar development programmes because of its increased durability. Mechanisms underlying such resistance are difficult to study. We performed RNA-seq analyses for tobacco (Nicotiana tabacum) nearly isogenic lines (NILs) with and without favourable allele(s) at Phn7.1, a major QTL influencing partial resistance to the soil-borne pathogens Phytophthora nicotianae and Ralstonia solanacearum. Based upon combined analyses of transcriptome-based sequence variation and gene expression profiles, we concluded that allelic variability at the Phn7.1 locus was likely generated from homoeologous exchange, which led to deletion of low-expressing members of the SAR8.2 gene family and duplication of high-expressing SAR8.2 genes from a different subgenome of allotetraploid tobacco. The high expression of endogenous Phn7.1-associated SAR8.2 genes was correlated with observed resistance to P. nicotianae. Our findings suggest a role for genomic rearrangements in the generation of favourable genetic variability affecting resistance to pathogens in plants.

Dissection of Quantitative Blackleg Resistance Reveals Novel Variants of Resistance Gene Rlm9 in Elite Brassica napus

Blackleg is one of the major fungal diseases in oilseed rape/canola worldwide. Most commercial cultivars carry R gene-mediated qualitative resistances that confer a high level of race-specific protection against Leptosphaeria maculans, the causal fungus of blackleg disease. However, monogenic resistances of this kind can potentially be rapidly overcome by mutations in the pathogen's avirulence genes. To counteract pathogen adaptation in this evolutionary arms race, there is a tremendous demand for quantitative background resistance to enhance durability and efficacy of blackleg resistance in oilseed rape. In this study, we characterized genomic regions contributing to quantitative L. maculans resistance by genome-wide association studies in a multiparental mapping population derived from six parental elite varieties exhibiting quantitative resistance, which were all crossed to one common susceptible parental elite variety. Resistance was screened using a fungal isolate with no corresponding avirulence (AvrLm) to major R genes present in the parents of the mapping population. Genome-wide association studies revealed eight significantly associated quantitative trait loci (QTL) on chromosomes A07 and A09, with small effects explaining 3-6% of the phenotypic variance. Unexpectedly, the qualitative blackleg resistance gene Rlm9 was found to be located within a resistance-associated haploblock on chromosome A07. Furthermore, long-range sequence data spanning this haploblock revealed high levels of single-nucleotide and structural variants within the Rlm9 coding sequence among the parents of the mapping population. The results suggest that novel variants of Rlm9 could play a previously unknown role in expression of quantitative disease resistance in oilseed rape.

The application of pangenomics and machine learning in genomic selection in plants

Genomic selection approaches have increased the speed of plant breeding, leading to growing crop yields over the last decade. However, climate change is impacting current and future yields, resulting in the need to further accelerate breeding efforts to cope with these changing conditions. Here we present approaches to accelerate plant breeding and incorporate nonadditive effects in genomic selection by applying state-of-the-art machine learning approaches. These approaches are made more powerful by the inclusion of pangenomes, which represent the entire genome content of a species. Understanding the strengths and limitations of machine learning methods, compared with more traditional genomic selection efforts, is paramount to the successful application of these methods in crop breeding. We describe examples of genomic selection and pangenome-based approaches in crop breeding, discuss machine learning-specific challenges, and highlight the potential for the application of machine learning in genomic selection. We believe that careful implementation of machine learning approaches will support crop improvement to help counter the adverse outcomes of climate change on crop production.

Homoeologous recombination is recurrent in the nascent synthetic allotetraploid Arachis ipaënsis × Arachis correntina4x and its derivatives

Genome instability in newly synthesized allotetraploids of peanut has breeding implications that have not been fully appreciated. Synthesis of wild species-derived neo-tetraploids offers the opportunity to broaden the gene pool of peanut; however, the dynamics among the newly merged genomes creates predictable and unpredictable variation. Selfed progenies from the neo-tetraploid Arachis ipaënsis × Arachis correntina (A. ipaënsis × A. correntina)4x and F1 hybrids and F2 progenies from crosses between A. hypogaea × [A. ipaënsis × A. correntina]4x were genotyped by the Axiom Arachis 48 K SNP array. Homoeologous recombination between the A. ipaënsis and A. correntina derived subgenomes was observed in the S0 generation. Among the S1 progenies, these recombined segments segregated and new events of homoeologous recombination emerged. The genomic regions undergoing homoeologous recombination segregated mostly disomically in the F2 progenies from A. hypogaea × [A. ipaënsis × A. correntina]4x crosses. New homoeologous recombination events also occurred in the F2 population, mostly found on chromosomes 03, 04, 05, and 06. From the breeding perspective, these phenomena offer both possibilities and perils; recombination between genomes increases genetic diversity, but genome instability could lead to instability of traits or even loss of viability within lineages.

A 598-bp InDel Variation in the Promoter Region of Bna.SOC1.A05 Is Predominantly Present in Winter Type Rapeseeds

During rapeseed domestication and breeding, genetic diversity allowed to adapt it to different eco-geographical regions and to shape its useful traits. Structural variations (SVs), including presence/absence variations (PAVs), are thought to play a major role in the genetic diversity and phenotypic plasticity of rapeseed. In this study, we detected a 598-bp PAV within the promoter region of an Arabidopsis ortholog of a major flowering time gene and a downstream target of FLC, SOC1, which is one of the first genes that are upregulated in rapeseed during vernalization. Further analysis showed that the insertion is present predominantly in winter types while absent in spring types. The 589-bp sequence is present only in the A sub-genome indicating that it originated from Brassica rapa. Since the genomic region around Bna.SOC1.A05 showed a strong reduction in nucleotide diversity, the insertion might represent a larger selected sweep for rapeseed adaptation. Cis-element analysis showed that the insertion contains an ACGTG box, which is the strongest binding motif for the HY5 transcription factor in Arabidopsis. In addition, expression analyses showed that mRNA levels of Bna.SOC1.A05 were lower in accessions carrying the insertion compared to the ones that had no insertion.

Local Duplication of TIR-NBS-LRR Gene Marks Clubroot Resistance in Brassica napus cv. Tosca

Clubroot, caused by Plasmodiophora brassicae infection, is a disease of growing importance in cruciferous crops, including oilseed rape (Brassica napus). The affected plants exhibit prominent galling of the roots that impairs their capacity for water and nutrient uptake, which leads to growth retardation, wilting, premature ripening, or death. Due to the scarcity of effective means of protection against the pathogen, breeding of resistant varieties remains a crucial component of disease control measures. The key aspect of the breeding process is the identification of genetic factors associated with variable response to the pathogen exposure. Although numerous clubroot resistance loci have been described in Brassica crops, continuous updates on the sources of resistance are necessary. Many of the resistance genes are pathotype-specific, moreover, resistance breakdowns have been reported. In this study, we characterize the clubroot resistance locus in the winter oilseed rape cultivar "Tosca." In a series of greenhouse experiments, we evaluate the disease severity of P. brassicae-challenged "Tosca"-derived population of doubled haploids, which we genotype with Brassica 60 K array and a selection of SSR/SCAR markers. We then construct a genetic map and narrow down the resistance locus to the 0.4 cM fragment on the A03 chromosome, corresponding to the region previously described as Crr3. Using Oxford Nanopore long-read genome resequencing and RNA-seq we review the composition of the locus and describe a duplication of TIR-NBS-LRR gene. Further, we explore the transcriptomic differences of the local genes between the clubroot resistant and susceptible, inoculated and control DH lines. We conclude that the duplicated TNL gene is a promising candidate for the resistance factor. This study provides valuable resources for clubroot resistance breeding programs and lays a foundation for further functional studies on clubroot resistance.

A novel deletion in FLOWERING LOCUS T modulates flowering time in winter oilseed rape

A novel structural variant was discovered in the FLOWERING LOCUS T orthologue BnaFT.A02 by long-read sequencing. Nested association mapping in an elite winter oilseed rape population revealed that this 288 bp deletion associates with early flowering, putatively by modification of binding-sites for important flowering regulation genes. Perfect timing of flowering is crucial for optimal pollination and high seed yield. Extensive previous studies of flowering behavior in Brassica napus (canola, rapeseed) identified mutations in key flowering regulators which differentiate winter, semi-winter and spring ecotypes. However, because these are generally fixed in locally adapted genotypes, they have only limited relevance for fine adjustment of flowering time in elite cultivar gene pools. In crosses between ecotypes, the ecotype-specific major-effect mutations mask minor-effect loci of interest for breeding. Here, we investigated flowering time in a multiparental mapping population derived from seven elite winter oilseed rape cultivars which are fixed for major-effect mutations separating winter-type rapeseed from other ecotypes. Association mapping revealed eight genomic regions on chromosomes A02, C02 and C03 associating with fine modulation of flowering time. Long-read genomic resequencing of the seven parental lines identified seven structural variants coinciding with candidate genes for flowering time within chromosome regions associated with flowering time. Segregation patterns for these variants in the elite multiparental population and a diversity set of winter types using locus-specific assays revealed significant associations with flowering time for three deletions on chromosome A02. One of these was a previously undescribed 288 bp deletion within the second intron of FLOWERING LOCUS T on chromosome A02, emphasizing the advantage of long-read sequencing for detection of structural variants in this size range. Detailed analysis revealed the impact of this specific deletion on flowering-time modulation under extreme environments and varying day lengths in elite, winter-type oilseed rape.

Long-read sequencing reveals widespread intragenic structural variants in a recent allopolyploid crop plant

Genome structural variation (SV) contributes strongly to trait variation in eukaryotic species and may have an even higher functional significance than single-nucleotide polymorphism (SNP). In recent years, there have been a number of studies associating large chromosomal scale SV ranging from hundreds of kilobases all the way up to a few megabases to key agronomic traits in plant genomes. However, there have been little or no efforts towards cataloguing small- (30-10 000 bp) to mid-scale (10 000-30 000 bp) SV and their impact on evolution and adaptation-related traits in plants. This might be attributed to complex and highly duplicated nature of plant genomes, which makes them difficult to assess using high-throughput genome screening methods. Here, we describe how long-read sequencing technologies can overcome this problem, revealing a surprisingly high level of widespread, small- to mid-scale SV in a major allopolyploid crop species, Brassica napus. We found that up to 10% of all genes were affected by small- to mid-scale SV events. Nearly half of these SV events ranged between 100 bp and 1000 bp, which makes them challenging to detect using short-read Illumina sequencing. Examples demonstrating the contribution of such SV towards eco-geographical adaptation and disease resistance in oilseed rape suggest that revisiting complex plant genomes using medium-coverage long-read sequencing might reveal unexpected levels of functional gene variation, with major implications for trait regulation and crop improvement.

Applications of Multi-Omics Technologies for Crop Improvement

Multiple "omics" approaches have emerged as successful technologies for plant systems over the last few decades. Advances in next-generation sequencing (NGS) have paved a way for a new generation of different omics, such as genomics, transcriptomics, and proteomics. However, metabolomics, ionomics, and phenomics have also been well-documented in crop science. Multi-omics approaches with high throughput techniques have played an important role in elucidating growth, senescence, yield, and the responses to biotic and abiotic stress in numerous crops. These omics approaches have been implemented in some important crops including wheat (Triticum aestivum L.), soybean (Glycine max), tomato (Solanum lycopersicum), barley (Hordeum vulgare L.), maize (Zea mays L.), millet (Setaria italica L.), cotton (Gossypium hirsutum L.), Medicago truncatula, and rice (Oryza sativa L.). The integration of functional genomics with other omics highlights the relationships between crop genomes and phenotypes under specific physiological and environmental conditions. The purpose of this review is to dissect the role and integration of multi-omics technologies for crop breeding science. We highlight the applications of various omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, phenomics, and ionomics, and the implementation of robust methods to improve crop genetics and breeding science. Potential challenges that confront the integration of multi-omics with regard to the functional analysis of genes and their networks as well as the development of potential traits for crop improvement are discussed. The panomics platform allows for the integration of complex omics to construct models that can be used to predict complex traits. Systems biology integration with multi-omics datasets can enhance our understanding of molecular regulator networks for crop improvement. In this context, we suggest the integration of entire omics by employing the "phenotype to genotype" and "genotype to phenotype" concept. Hence, top-down (phenotype to genotype) and bottom-up (genotype to phenotype) model through integration of multi-omics with systems biology may be beneficial for crop breeding improvement under conditions of environmental stresses.

Overcoming polyploidy pitfalls: a user guide for effective SNP conversion into KASP markers in wheat

Conversion of SNP chip assays into locus-specific KASP markers requires adapted strategies in polyploid species with high genome homeology. Procedures are exemplified by QTL-associated SNPs in hexaploid wheat. Kompetitive allele-specific PCR (KASP) markers are commonly used in marker-assisted commercial plant breeding due to their cost-effectiveness and throughput for high sample volumes. However, conversion of trait-linked SNP markers from array-based SNP detection technologies into KASP markers is particularly challenging in polyploid crop species, due to the presence of highly similar homeologous and paralogous genome sequences. We evaluated strategies and identified key requirements for successful conversion of Illumina Infinium assays from the wheat 90 K SNP array into robust locus-specific KASP markers. Numerous examples showed that commonly used software for semiautomated KASP primer design frequently fails to achieve locus-specificity of KASP assays in wheat. Instead, alignment of SNP probes with multiple reference genomes and Sanger sequencing of relevant genotypes, followed by visual KASP primer placement, was critical for locus-specificity. To identify KASP assays resulting in false calling of heterozygous individuals, validation of KASP assays using extended reference genotype sets including heterozygous genotypes is strongly advised for polyploid crop species. Applying this strategy, we developed highly reproducible, stable KASP assays that are predictive for root biomass QTL haplotypes from highly homoeologous wheat chromosome regions. Due to their locus-specificity, these assays predicted root biomass considerably better than the original trait-associated markers from the Illumina array.

Global Role of Crop Genomics in the Face of Climate Change

The development of climate change resilient crops is necessary if we are to meet the challenge of feeding the growing world's population. We must be able to increase food production despite the projected decrease in arable land and unpredictable environmental conditions. This review summarizes the technological and conceptual advances that have the potential to transform plant breeding, help overcome the challenges of climate change, and initiate the next plant breeding revolution. Recent developments in genomics in combination with high-throughput and precision phenotyping facilitate the identification of genes controlling critical agronomic traits. The discovery of these genes can now be paired with genome editing techniques to rapidly develop climate change resilient crops, including plants with better biotic and abiotic stress tolerance and enhanced nutritional value. Utilizing the genetic potential of crop wild relatives (CWRs) enables the domestication of new species and the generation of synthetic polyploids. The high-quality crop plant genome assemblies and annotations provide new, exciting research targets, including long non-coding RNAs (lncRNAs) and cis-regulatory regions. Metagenomic studies give insights into plant-microbiome interactions and guide selection of optimal soils for plant cultivation. Together, all these advances will allow breeders to produce improved, resilient crops in relatively short timeframes meeting the demands of the growing population and changing climate.

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.

Chromosome-Scale Assembly of Winter Oilseed Rape Brassica napus

Rapeseed (Brassica napus), the second most important oilseed crop globally, originated from an interspecific hybridization between B. rapa and B. oleracea. After this genome collision, B. napus underwent extensive genome restructuring, via homoeologous chromosome exchanges, resulting in widespread segmental deletions and duplications. Illicit pairing among genetically similar homoeologous chromosomes during meiosis is common in recent allopolyploids like B. napus, and post-polyploidization restructuring compounds the difficulties of assembling a complex polyploid plant genome. Specifically, genomic rearrangements between highly similar chromosomes are challenging to detect due to the limitation of sequencing read length and ambiguous alignment of reads. Recent advances in long read sequencing technologies provide promising new opportunities to unravel the genome complexities of B. napus by encompassing breakpoints of genomic rearrangements with high specificity. Moreover, recent evidence revealed ongoing genomic exchanges in natural B. napus, highlighting the need for multiple reference genomes to capture structural variants between accessions. Here we report the first long-read genome assembly of a winter B. napus cultivar. We sequenced the German winter oilseed rape accession 'Express 617' using 54.5x of long reads. Short reads, linked reads, optical map data and high-density genetic maps were used to further correct and scaffold the assembly to form pseudochromosomes. The assembled Express 617 genome provides another valuable resource for Brassica genomics in understanding the genetic consequences of polyploidization, crop domestication, and breeding of recently-formed crop species.

Chromosome-Scale Assembly of Winter Oilseed Rape Brassica napus

Rapeseed (Brassica napus), the second most important oilseed crop globally, originated from an interspecific hybridization between B. rapa and B. oleracea. After this genome collision, B. napus underwent extensive genome restructuring, via homoeologous chromosome exchanges, resulting in widespread segmental deletions and duplications. Illicit pairing among genetically similar homoeologous chromosomes during meiosis is common in recent allopolyploids like B. napus, and post-polyploidization restructuring compounds the difficulties of assembling a complex polyploid plant genome. Specifically, genomic rearrangements between highly similar chromosomes are challenging to detect due to the limitation of sequencing read length and ambiguous alignment of reads. Recent advances in long read sequencing technologies provide promising new opportunities to unravel the genome complexities of B. napus by encompassing breakpoints of genomic rearrangements with high specificity. Moreover, recent evidence revealed ongoing genomic exchanges in natural B. napus, highlighting the need for multiple reference genomes to capture structural variants between accessions. Here we report the first long-read genome assembly of a winter B. napus cultivar. We sequenced the German winter oilseed rape accession 'Express 617' using 54.5x of long reads. Short reads, linked reads, optical map data and high-density genetic maps were used to further correct and scaffold the assembly to form pseudochromosomes. The assembled Express 617 genome provides another valuable resource for Brassica genomics in understanding the genetic consequences of polyploidization, crop domestication, and breeding of recently-formed crop species.

Pangenomics Comes of Age: From Bacteria to Plant and Animal Applications

The pangenome refers to a collection of genomic sequence found in the entire species or population rather than in a single individual; the sequence can be core, present in all individuals, or accessory (variable or dispensable), found in a subset of individuals only. While pangenomic studies were first undertaken in bacterial species, developments in genome sequencing and assembly approaches have allowed construction of pangenomes for eukaryotic organisms, fungi, plants, and animals, including two large-scale human pangenome projects. Analysis of the these pangenomes revealed key differences, most likely stemming from divergent evolutionary histories, but also surprising similarities.

Crop Genomics Goes Beyond a Single Reference Genome

The inadequacy of a single reference genome to capture the full landscape of genetic diversity within a species constrains exploration of genetic variation for crop improvement. A recent study by Yang et al. has demonstrated the value of multiple reference-quality genomes in capturing structural variants and guiding biological discovery.

Transcriptomic and presence/absence variation in the barley genome assessed from multi-tissue mRNA sequencing and their power to predict phenotypic traits

Background

Barley is the world’s fourth most cultivated cereal and is an important crop model for genetic studies. One layer of genomic information that remains poorly explored in barley is presence/absence variation (PAV), which has been suggested to contribute to phenotypic variation of agronomic importance in various crops.

Results

An mRNA sequencing approach was used to study genomic PAV and transcriptomic variation in 23 spring barley inbreds. 1502 new genes identified here were physically absent from the Morex reference sequence, and 11,523 previously unannotated genes were not expressed in Morex. The procedure applied to detect expression PAV revealed that more than 50% of all genes of our data set are not expressed in all inbreds. Interestingly, expression PAV were not in strong linkage disequilibrium with neighboring sequence variants (SV), and therefore provided an additional layer of genetic information. Optimal combinations of expression PAV, SV, and gene abundance data could enhance the prediction accuracy of predicting three different agronomic traits.

Conclusions

Our results highlight the advantage of mRNA sequencing for genomic prediction over other technologies, as it allows extracting multiple layers of genomic data from a single sequencing experiment. Finally, we propose low coverage mRNA sequencing based characterization of breeding material harvested as seedlings in petri dishes as a powerful and cost efficient approach to replace current single nucleotide polymorphism (SNP) based characterizations.

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.

Exploring and Exploiting Pan-genomics for Crop Improvement

Genetic variation ranging from single-nucleotide polymorphisms to large structural variants (SVs) can cause variation of gene content among individuals within the same species. There is an increasing appreciation that a single reference genome is insufficient to capture the full landscape of genetic diversity of a species. Pan-genome analysis offers a platform to evaluate the genetic diversity of a species via investigation of its entire genome repertoire. Although a recent wave of pan-genomic studies has shed new light on crop diversity and improvement using advanced sequencing technology, the potential applications of crop pan-genomics in crop improvement are yet to be fully exploited. In this review, we highlight the progress achieved in understanding crop pan-genomics, discuss biological activities that cause SVs, review important agronomical traits affected by SVs, and present our perspective on the application of pan-genomics in crop improvement.

A Comparison of Mainstream Genotyping Platforms for the Evaluation and Use of Barley Genetic Resources

We compared the performance of two commonly used genotyping platforms, genotyping-by-sequencing (GBS) and single nucleotide polymorphism-arrays (SNP), to investigate the extent and pattern of genetic variation within a collection of 1,000 diverse barley genotypes selected from the German Federal ex situ GenBank hosted at IPK Gatersleben. Each platform revealed equivalent numbers of robust bi-allelic SNPs (39,733 and 37,930 SNPs for the 50K SNP-array and GBS datasets respectively). A small overlap of 464 SNPs was common to both platforms, indicating that the methodologies we used selectively access informative polymorphism in different portions of the barley genome. Approximately half of the GBS dataset was comprised of SNPs with minor allele frequencies (MAFs) below 1%, illustrating the power of GBS to detect rare alleles in diverse germplasm collections. While desired for certain applications, the highly robust calling of alleles at the same SNPs across multiple populations is an advantage of the SNP-array, allowing direct comparisons of data from related or unrelated studies. Overall MAFs and diversity statistics (π) were higher for the SNP-array data, potentially reflecting the conscious removal of markers with a low MAF in the ascertainment population. A comparison of similarity matrices revealed a positive correlation between both approaches, supporting the validity of using either for entire GenBank characterization. To explore the potential of each dataset for focused genetic analyses we explored the outcomes of their use in genome-wide association scans for row type, growth habit and non-adhering hull, and discriminant analysis of principal components for the drivers of sub-population differentiation. Interpretation of the results from both types of analysis yielded broadly similar conclusions indicating that choice of platform used for such analyses should be determined by the research question being asked, group preferences and their capabilities to extract and interpret the different types of output data easily and quickly. Access to the requisite infrastructure for running, processing, analyzing, querying, storing, and displaying either datatype is an additional consideration. Our investigations reveal that for barley the cost per genotyping assay is less for SNP-arrays than GBS, which translates to a cost per informative datapoint being significantly lower for the SNP-array.