Super-Pangenome by Integrating the Wild Side of a Species for Accelerated Crop Improvement

Strategies for utilization of crop wild relatives in plant breeding programs

Crop wild relatives (CWRs) are weedy and wild relatives of the domesticated and cultivated crops, which usually occur and are maintained in natural forms in their centres of origin. These include the ancestors or progenitors of all cultivated species and comprise rich sources of diversity for many important traits useful in plant breeding. CWRs can play an important role in broadening genetic bases and introgression of economical traits into crops, but their direct use by breeders for varietal improvement program is usually not advantageous due to the presence of crossing or chromosome introgression barriers with cultivated species as well as their high frequencies of agronomically undesirable alleles. Linkage drag may subsequently result in unfavourable traits in the subsequent progeny when segments of the genome linked with quantitative trait loci (QTL), or a phenotype, are introgressed from wild germplasm. Here, we first present an overview in regards to the contribution that wild species have made to improve biotic, abiotic stress tolerances and yield-related traits in crop varieties, and secondly summarise the various challenges which are experienced in interspecific hybridization along with their probable solutions. We subsequently suggest techniques for readily harnessing these wild relatives for fast and effective introgression of exotic alleles in pre-breeding research programs.

The Key to the Future Lies in the Past: Insights from Grain Legume Domestication and Improvement Should Inform Future Breeding Strategies

Crop domestication is a co-evolutionary process that has rendered plants and animals significantly dependent on human interventions for survival and propagation. Grain legumes have played an important role in the development of Neolithic agriculture some 12,000 years ago. Despite being early companions of cereals in the origin and evolution of agriculture, the understanding of grain legume domestication has lagged behind that of cereals. Adapting plants for human use has resulted in distinct morpho-physiological changes between the wild ancestors and domesticates, and this distinction has been the focus of several studies aimed at understanding the domestication process and the genetic diversity bottlenecks created. Growing evidence from research on archeological remains, combined with genetic analysis and the geographical distribution of wild forms, has improved the resolution of the process of domestication, diversification and crop improvement. In this review, we summarize the significance of legume wild relatives as reservoirs of novel genetic variation for crop breeding programs. We describe key legume features, which evolved in response to anthropogenic activities. Here, we highlight how whole genome sequencing and incorporation of omics-level data have expanded our capacity to monitor the genetic changes accompanying these processes. Finally, we present our perspective on alternative routes centered on de novo domestication and re-domestication to impart significant agronomic advances of novel crops over existing commodities. A finely resolved domestication history of grain legumes will uncover future breeding targets to develop modern cultivars enriched with alleles that improve yield, quality and stress tolerance.

Application of crop wild relatives in modern breeding: An overview of resources, experimental and computational methodologies

Global agricultural industries are under pressure to meet the future food demand; however, the existing crop genetic diversity might not be sufficient to meet this expectation. Advances in genome sequencing technologies and availability of reference genomes for over 300 plant species reveals the hidden genetic diversity in crop wild relatives (CWRs), which could have significant impacts in crop improvement. There are many ex-situ and in-situ resources around the world holding rare and valuable wild species, of which many carry agronomically important traits and it is crucial for users to be aware of their availability. Here we aim to explore the available ex-/in- situ resources such as genebanks, botanical gardens, national parks, conservation hotspots and inventories holding CWR accessions. In addition we highlight the advances in availability and use of CWR genomic resources, such as their contribution in pangenome construction and introducing novel genes into crops. We also discuss the potential and challenges of modern breeding experimental approaches (e.g. de novo domestication, genome editing and speed breeding) used in CWRs and the use of computational (e.g. machine learning) approaches that could speed up utilization of CWR species in breeding programs towards crop adaptability and yield improvement.

Molecular Breeding and Drought Tolerance in Chickpea

Cicer arietinum L. is the third greatest widely planted imperative pulse crop worldwide, and it belongs to the Leguminosae family. Drought is the utmost common abiotic factor on plants, distressing their water status and limiting their growth and development. Chickpea genotypes have the natural ability to fight drought stress using certain strategies viz., escape, avoidance and tolerance. Assorted breeding methods, including hybridization, mutation, and marker-aided breeding, genome sequencing along with omics approaches, could be used to improve the chickpea germplasm lines(s) against drought stress. Root features, for instance depth and root biomass, have been recognized as the greatest beneficial morphological factors for managing terminal drought tolerance in the chickpea. Marker-aided selection, for example, is a genomics-assisted breeding (GAB) strategy that can considerably increase crop breeding accuracy and competence. These breeding technologies, notably marker-assisted breeding, omics, and plant physiology knowledge, underlined the importance of chickpea breeding and can be used in future crop improvement programmes to generate drought-tolerant cultivars(s).

Legume Pangenome: Status and Scope for Crop Improvement

In the last decade, legume genomics research has seen a paradigm shift due to advances in genome sequencing technologies, assembly algorithms, and computational genomics that enabled the construction of high-quality reference genome assemblies of major legume crops. These advances have certainly facilitated the identification of novel genetic variants underlying the traits of agronomic importance in many legume crops. Furthermore, these robust sequencing technologies have allowed us to study structural variations across the whole genome in multiple individuals and at the species level using 'pangenome analysis.' This review updates the progress of constructing pangenome assemblies for various legume crops and discusses the prospects for these pangenomes and how to harness the information to improve various traits of economic importance through molecular breeding to increase genetic gain in legumes and tackle the increasing global food crisis.

Molecular mechanisms, genetic mapping, and genome editing for insect pest resistance in field crops

Improving crop resistance against insect pests is crucial for ensuring future food security. Integrating genomics with modern breeding methods holds enormous potential in dissecting the genetic architecture of this complex trait and accelerating crop improvement. Insect resistance in crops has been a major research objective in several crop improvement programs. However, the use of conventional breeding methods to develop high-yielding cultivars with sustainable and durable insect pest resistance has been largely unsuccessful. The use of molecular markers for identification and deployment of insect resistance quantitative trait loci (QTLs) can fastrack traditional breeding methods. Till date, several QTLs for insect pest resistance have been identified in field-grown crops, and a few of them have been cloned by positional cloning approaches. Genome editing technologies, such as CRISPR/Cas9, are paving the way to tailor insect pest resistance loci for designing crops for the future. Here, we provide an overview of diverse defense mechanisms exerted by plants in response to insect pest attack, and review recent advances in genomics research and genetic improvements for insect pest resistance in major field crops. Finally, we discuss the scope for genomic breeding strategies to develop more durable insect pest resistant crops.

The grain quality of wheat wild relatives in the evolutionary context

KEY MESSAGE

We evaluated the potential of wheat wild relatives for the improvement in grain quality characteristics including micronutrients (Fe, Zn) and gluten and identified diploid wheats and the timopheevii lineage as the most promising resources. Domestication enabled the advancement of civilization through modification of plants according to human requirements. Continuous selection and cultivation of domesticated plants induced genetic bottlenecks. However, ancient diversity has been conserved in crop wild relatives. Wheat (Triticum aestivum L.; Triticum durum Desf.) is one of the most important staple foods and was among the first domesticated crop species. Its evolutionary diversity includes diploid, tetraploid and hexaploid species from the Triticum and Aegilops taxa and different genomes, generating an AA, BBAA/GGAA and BBAADD/GGAAAmAm genepool, respectively. Breeding and improvement in wheat altered its grain quality. In this review, we identified evolutionary patterns and the potential of wheat wild relatives for quality improvement regarding the micronutrients Iron (Fe) and Zinc (Zn), the gluten storage proteins α-gliadins and high molecular weight glutenin subunits (HMW-GS), and the secondary metabolite phenolics. Generally, the timopheevii lineage has been neglected to date regarding grain quality studies. Thus, the timopheevii lineage should be subject to grain quality research to explore the full diversity of the wheat gene pool.

Biotechnological Advances to Improve Abiotic Stress Tolerance in Crops

The major challenges that agriculture is facing in the twenty-first century are increasing droughts, water scarcity, flooding, poorer soils, and extreme temperatures due to climate change. However, most crops are not tolerant to extreme climatic environments. The aim in the near future, in a world with hunger and an increasing population, is to breed and/or engineer crops to tolerate abiotic stress with a higher yield. Some crop varieties display a certain degree of tolerance, which has been exploited by plant breeders to develop varieties that thrive under stress conditions. Moreover, a long list of genes involved in abiotic stress tolerance have been identified and characterized by molecular techniques and overexpressed individually in plant transformation experiments. Nevertheless, stress tolerance phenotypes are polygenetic traits, which current genomic tools are dissecting to exploit their use by accelerating genetic introgression using molecular markers or site-directed mutagenesis such as CRISPR-Cas9. In this review, we describe plant mechanisms to sense and tolerate adverse climate conditions and examine and discuss classic and new molecular tools to select and improve abiotic stress tolerance in major crops.

Improved pea reference genome and pan-genome highlight genomic features and evolutionary characteristics

Complete and accurate reference genomes and annotations provide fundamental resources for functional genomics and crop breeding. Here we report a de novo assembly and annotation of a pea cultivar ZW6 with contig N50 of 8.98 Mb, which features a 243-fold increase in contig length and evident improvements in the continuity and quality of sequence in complex repeat regions compared with the existing one. Genome diversity of 118 cultivated and wild pea demonstrated that Pisum abyssinicum is a separate species different from P. fulvum and P. sativum within Pisum. Quantitative trait locus analyses uncovered two known Mendel's genes related to stem length (Le/le) and seed shape (R/r) as well as some candidate genes for pod form studied by Mendel. A pan-genome of 116 pea accessions was constructed, and pan-genes preferred in P. abyssinicum and P. fulvum showed distinct functional enrichment, indicating the potential value of them as pea breeding resources in the future.

A super pan-genomic landscape of rice

Pan-genomes from large natural populations can capture genetic diversity and reveal genomic complexity. Using de novo long-read assembly, we generated a graph-based super pan-genome of rice consisting of a 251-accession panel comprising both cultivated and wild species of Asian and African rice. Our pan-genome reveals extensive structural variations (SVs) and gene presence/absence variations. Additionally, our pan-genome enables the accurate identification of nucleotide-binding leucine-rich repeat genes and characterization of their inter- and intraspecific diversity. Moreover, we uncovered grain weight-associated SVs which specify traits by affecting the expression of their nearby genes. We characterized genetic variants associated with submergence tolerance, seed shattering and plant architecture and found independent selection for a common set of genes that drove adaptation and domestication in Asian and African rice. This super pan-genome facilitates pinpointing of lineage-specific haplotypes for trait-associated genes and provides insights into the evolutionary events that have shaped the genomic architecture of various rice species.

The banana genome hub: a community database for genomics in the Musaceae

The Banana Genome Hub provides centralized access for genome assemblies, annotations, and the extensive related omics resources available for bananas and banana relatives. A series of tools and unique interfaces are implemented to harness the potential of genomics in bananas, leveraging the power of comparative analysis, while recognizing the differences between datasets. Besides effective genomic tools like BLAST and the JBrowse genome browser, additional interfaces enable advanced gene search and gene family analyses including multiple alignments and phylogenies. A synteny viewer enables the comparison of genome structures between chromosome-scale assemblies. Interfaces for differential expression analyses, metabolic pathways and GO enrichment were also added. A catalogue of variants spanning the banana diversity is made available for exploration, filtering, and export to a wide variety of software. Furthermore, we implemented new ways to graphically explore gene presence-absence in pangenomes as well as genome ancestry mosaics for cultivated bananas. Besides, to guide the community in future sequencing efforts, we provide recommendations for nomenclature of locus tags and a curated list of public genomic resources (assemblies, resequencing, high density genotyping) and upcoming resources-planned, ongoing or not yet public. The Banana Genome Hub aims at supporting the banana scientific community for basic, translational, and applied research and can be accessed at https://banana-genome-hub.southgreen.fr.

High-quality chromosome-scale genomes facilitate effective identification of large structural variations in hot and sweet peppers

Pepper (Capsicum annuum) is an important vegetable crop that has been subjected to intensive breeding, resulting in limited genetic diversity, especially for sweet peppers. Previous studies have reported pepper draft genome assemblies using short read sequencing, but their capture of the extent of large structural variants (SVs), such as presence-absence variants (PAVs), inversions, and copy-number variants (CNVs) in the complex pepper genome falls short. In this study, we sequenced the genomes of representative sweet and hot pepper accessions by long-read and/or linked-read methods and advanced scaffolding technologies. First, we developed a high-quality reference genome for the sweet pepper cultivar 'Dempsey' and then used the reference genome to identify SVs in 11 other pepper accessions and constructed a graph-based pan-genome for pepper. We annotated an average of 42 972 gene families in each pepper accession, defining a set of 19 662 core and 23 115 non-core gene families. The new pepper pan-genome includes informative variants, 222 159 PAVs, 12 322 CNVs, and 16 032 inversions. Pan-genome analysis revealed PAVs associated with important agricultural traits, including potyvirus resistance, fruit color, pungency, and pepper fruit orientation. Comparatively, a large number of genes are affected by PAVs, which is positively correlated with the high frequency of transposable elements (TEs), indicating TEs play a key role in shaping the genomic landscape of peppers. The datasets presented herein provide a powerful new genomic resource for genetic analysis and genome-assisted breeding for pepper improvement.

A pan-Zea genome map for enhancing maize improvement

Background

Maize (Zea mays L.) is at the vanguard facing the upcoming breeding challenges. However, both a super pan-genome for the Zea genus and a comprehensive genetic variation map for maize breeding are still lacking.

Results

Here, we construct an approximately 6.71-Gb pan-Zea genome that contains around 4.57-Gb non-B73 reference sequences from fragmented de novo assemblies of 721 pan-Zea individuals. We annotate a total of 58,944 pan-Zea genes and find around 44.34% of them are dispensable in the pan-Zea population. Moreover, 255,821 common structural variations are identified and genotyped in a maize association mapping panel. Further analyses reveal gene presence/absence variants and their potential roles during domestication of maize. Combining genetic analyses with multi-omics data, we demonstrate how structural variants are associated with complex agronomic traits.

Conclusions

Our results highlight the underexplored role of the pan-Zea genome and structural variations to further understand domestication of maize and explore their potential utilization in crop improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02742-7.

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

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

Pangenomics and Crop Genome Adaptation in a Changing Climate

During crop domestication and breeding, wild plant species have been shaped into modern high-yield crops and adapted to the main agro-ecological regions. However, climate change will impact crop productivity in these regions, and agriculture needs to adapt to support future food production. On a global scale, crop wild relatives grow in more diverse environments than crop species, and so may host genes that could support the adaptation of crops to new and variable environments. Through identification of individuals with increased climate resilience we may gain a greater understanding of the genomic basis for this resilience and transfer this to crops. Pangenome analysis can help to identify the genes underlying stress responses in individuals harbouring untapped genomic diversity in crop wild relatives. The information gained from the analysis of these pangenomes can then be applied towards breeding climate resilience into existing crops or to re-domesticating crops, combining environmental adaptation traits with crop productivity.

Plant pan-genomics: recent advances, new challenges, and roads ahead

Pan-genomics can encompass most of the genetic diversity of a species or population and has proved to be a powerful tool for studying genomic evolution and the origin and domestication of species, and for providing information for plant improvement. Plant genomics has greatly progressed because of improvements in sequencing technologies and the rapid reduction of sequencing costs. Nevertheless, pan-genomics still presents many challenges, including computationally intensive assembly methods, high costs with large numbers of samples, ineffective integration of big data, and difficulty in applying it to downstream multi-omics analysis and breeding research. In this review, we summarize the definition and recent achievements of plant pan-genomics, computational technologies used for pan-genome construction, and the applications of pan-genomes in plant genomics and molecular breeding. We also discuss challenges and perspectives for future pan-genomics studies and provide a detailed pipeline for sample selection, genome assembly and annotation, structural variation identification, and construction and application of graph-based pan-genomes. The aim is to provide important guidance for plant pan-genome research and a better understanding of the genetic basis of genome evolution, crop domestication, and phenotypic diversity for future studies.

Harnessing the hidden allelic diversity of wild Cicer to accelerate genomics-assisted chickpea crop improvement

Chickpea, commonly called Bengal gram or Garbanzo bean, faces a productivity crisis around the globe due to numerous biotic and abiotic stresses. The eroded genetic base of the cultivated Cicer gene pool is becoming a significant bottleneck in developing stress-resilient chickpea cultivars. In this scenario, the crop wild relatives (CWR) of chickpea, with the useful genomic wealth of their wild adaptation, give a ray of hope to improve the genetic background of the cultivated Cicer gene pool. To extrapolate these unearthed genomic diversities of wild, we require a thorough understanding of the pre-historic domestication episodes that are changing their shape with the expansion of the available scientific evidence. Keeping aforesaid in view, the current review article provides a glimpsed overview on several efforts done so far to reveal the mysterious origin and evolution of the Cicer gene pool, along with the constraints in their utilization for chickpea crop improvement. It encapsulates various stress-resilient CWR of chickpea and their use in several pre-breeding programs to develop numerous breeding populations for crop genetic enhancement. Further, this review will recapitulate the significant contributions of structural, functional and comparative genomics, pan-genomics and diverse genomics-assisted breeding strategy in dissecting the untapped trait-specific allelic/gene diversity and domestication pattern behind the CWR of chickpea, along with their potential and promises. We expect the newly explored genetic variations may be used in the breeding programs for re-wilding the cultigens' genomic background to open a new avenue for genetic gain and crop improvement capacity of chickpea.

Advancing designer crops for climate resilience through an integrated genomics approach

Climate change and exponential population growth are exposing an immediate need for developing future crops that are highly resilient and adaptable to changing environments to maintain global food security in the next decade. Rigorous selection from long domestication history has rendered cultivated crops genetically disadvantaged, raising concerns in their ability to adapt to these new challenges and limiting their usefulness in breeding programmes. As a result, future crop improvement efforts must rely on integrating various genomic strategies ranging from high-throughput sequencing to machine learning, in order to exploit germplasm diversity and overcome bottlenecks created by domestication, expansive multi-dimensional phenotypes, arduous breeding processes, complex traits and big data.

Pan-Genomes Provide Insights into the Genetic Basis of Auricularia heimuer Domestication

In order to reveal the genetic variation signals of Auricularia heimuer that have occurred during their domestication and to find potential functional gene families, we constructed a monokaryotic pan-genome of A. heimuer representing four cultivated strains and four wild strains. The pan-genome contained 14,089 gene families, of which 67.56% were core gene families and 31.88% were dispensable gene families. We screened substrate utilization-related genes such as the chitinase gene ahchi1 of the glycoside hydrolase (GH) 18 family and a carbohydrate-binding module (CBM)-related gene from the dispensable families of cultivated populations. The genomic difference in the ahchi1 gene between the wild and cultivated genomes was caused by a 33 kb presence/absence variation (PAV). The detection rate of the ahchi1 gene was 93.75% in the cultivated population, significantly higher than that in the wild population (17.39%), indicating that it has been selected in cultivated strains. Principal component analysis (PCA) of the polymorphic markers in fragments near the ahchi1 gene was enriched in cultivated strains, and this was caused by multiple independent instances of artificial selection. We revealed for the first time the genetic basis of the ahchi1 gene in domestication, thereby providing a foundation for elucidating the potential function of the ahchi1 gene in the breeding of A. heimuer.

Oxford Nanopore and Bionano Genomics technologies evaluation for plant structural variation detection

BACKGROUND

Structural Variations (SVs) are genomic rearrangements derived from duplication, deletion, insertion, inversion, and translocation events. In the past, SVs detection was limited to cytological approaches, then to Next-Generation Sequencing (NGS) short reads and partitioned assemblies. Nowadays, technologies such as DNA long read sequencing and optical mapping have revolutionized the understanding of SVs in genomes, due to the enhancement of the power of SVs detection. This study aims to investigate performance of two techniques, 1) long-read sequencing obtained with the MinION device (Oxford Nanopore Technologies) and 2) optical mapping obtained with Saphyr device (Bionano Genomics) to detect and characterize SVs in the genomes of the two ecotypes of Arabidopsis thaliana, Columbia-0 (Col-0) and Landsberg erecta 1 (Ler-1).

RESULTS

We described the SVs detected from the alignment of the best ONT assembly and DLE-1 optical maps of A. thaliana Ler-1 against the public reference genome Col-0 TAIR10.1. After filtering (SV > 1 kb), 1184 and 591 Ler-1 SVs were retained from ONT and Bionano technologies respectively. A total of 948 Ler-1 ONT SVs (80.1%) corresponded to 563 Bionano SVs (95.3%) leading to 563 common locations. The specific locations were scrutinized to assess improvement in SV detection by either technology. The ONT SVs were mostly detected near TE and gene features, and resistance genes seemed particularly impacted.

CONCLUSIONS

Structural variations linked to ONT sequencing error were removed and false positives limited, with high quality Bionano SVs being conserved. When compared with the Col-0 TAIR10.1 reference genome, most of the detected SVs discovered by both technologies were found in the same locations. ONT assembly sequence leads to more specific SVs than Bionano one, the latter being more efficient to characterize large SVs. Even if both technologies are complementary approaches, ONT data appears to be more adapted to large scale populations studies, while Bionano performs better in improving assembly and describing specificity of a genome compared to a reference.

Dynamic evolution of small signalling peptide compensation in plant stem cell control

Gene duplications are a hallmark of plant genome evolution and a foundation for genetic interactions that shape phenotypic diversity^1-5. Compensation is a major form of paralogue interaction^6-8 but how compensation relationships change as allelic variation accumulates is unknown. Here we leveraged genomics and genome editing across the Solanaceae family to capture the evolution of compensating paralogues. Mutations in the stem cell regulator CLV3 cause floral organs to overproliferate in many plants^9-11. In tomato, this phenotype is partially suppressed by transcriptional upregulation of a closely related paralogue¹². Tobacco lost this paralogue, resulting in no compensation and extreme clv3 phenotypes. Strikingly, the paralogues of petunia and groundcherry nearly completely suppress clv3, indicating a potent ancestral state of compensation. Cross-species transgenic complementation analyses show that this potent compensation partially degenerated in tomato due to a single amino acid change in the paralogue and cis-regulatory variation that limits its transcriptional upregulation. Our findings show how genetic interactions are remodelled following duplications and suggest that dynamic paralogue evolution is widespread over short time scales and impacts phenotypic variation from natural and engineered mutations.

Pangenomics in Microbial and Crop Research: Progress, Applications, and Perspectives

Advances in sequencing technologies and bioinformatics tools have fueled a renewed interest in whole genome sequencing efforts in many organisms. The growing availability of multiple genome sequences has advanced our understanding of the within-species diversity, in the form of a pangenome. Pangenomics has opened new avenues for future research such as allowing dissection of complex molecular mechanisms and increased confidence in genome mapping. To comprehensively capture the genetic diversity for improving plant performance, the pangenome concept is further extended from species to genus level by the inclusion of wild species, constituting a super-pangenome. Characterization of pangenome has implications for both basic and applied research. The concept of pangenome has transformed the way biological questions are addressed. From understanding evolution and adaptation to elucidating host–pathogen interactions, finding novel genes or breeding targets to aid crop improvement to design effective vaccines for human prophylaxis, the increasing availability of the pangenome has revolutionized several aspects of biological research. The future availability of high-resolution pangenomes based on reference-level near-complete genome assemblies would greatly improve our ability to address complex biological problems.

Pangenomics in crop improvement-from coding structural variations to finding regulatory variants with pangenome graphs

Since the first reported crop pangenome in 2014, advances in high-throughput and cost-effective DNA sequencing technologies facilitated multiple such studies including the pangenomes of oilseed rape (Brassica napus L.), soybean [Glycine max (L.) Merr.], rice (Oryza sativa L.), wheat (Triticum aestivum L.), and barley (Hordeum vulgare L.). Compared with single-reference genomes, pangenomes provide a more accurate representation of the genetic variation present in a species. By combining the genomic data of multiple accessions, pangenomes allow for the detection and annotation of complex DNA polymorphisms such as structural variations (SVs), one of the major determinants of genetic diversity within a species. In this review we summarize the current literature on crop pangenomics, focusing on their application to find candidate SVs involved in traits of agronomic interest. We then highlight the potential of pangenomes in the discovery and functional characterization of noncoding regulatory sequences and their variations. We conclude with a summary and outlook on innovative data structures representing the complete content of plant pangenomes including annotations of coding and noncoding elements and outcomes of transcriptomic and epigenomic experiments.

Phylogenomics of the genus Glycine sheds light on polyploid evolution and life-strategy transition

Polyploidy and life-strategy transitions between annuality and perenniality often occur in flowering plants. However, the evolutionary propensities of polyploids and the genetic bases of such transitions remain elusive. We assembled chromosome-level genomes of representative perennial species across the genus Glycine including five diploids and a young allopolyploid, and constructed a Glycine super-pangenome framework by integrating 26 annual soybean genomes. These perennial diploids exhibit greater genome stability and possess fewer centromere repeats than the annuals. Biased subgenomic fractionation occurred in the allopolyploid, primarily by accumulation of small deletions in gene clusters through illegitimate recombination, which was associated with pre-existing local subgenomic differentiation. Two genes annotated to modulate vegetative-reproductive phase transition and lateral shoot outgrowth were postulated as candidates underlying the perenniality-annuality transition. Our study provides insights into polyploid genome evolution and lays a foundation for unleashing genetic potential from the perennial gene pool for soybean improvement.

Pangenomes as a Resource to Accelerate Breeding of Under-Utilised Crop Species

Pangenomes are a rich resource to examine the genomic variation observed within a species or genera, supporting population genetics studies, with applications for the improvement of crop traits. Major crop species such as maize (Zea mays), rice (Oryza sativa), Brassica (Brassica spp.), and soybean (Glycine max) have had pangenomes constructed and released, and this has led to the discovery of valuable genes associated with disease resistance and yield components. However, pangenome data are not available for many less prominent crop species that are currently under-utilised. Despite many under-utilised species being important food sources in regional populations, the scarcity of genomic data for these species hinders their improvement. Here, we assess several under-utilised crops and review the pangenome approaches that could be used to build resources for their improvement. Many of these under-utilised crops are cultivated in arid or semi-arid environments, suggesting that novel genes related to drought tolerance may be identified and used for introgression into related major crop species. In addition, we discuss how previously collected data could be used to enrich pangenome functional analysis in genome-wide association studies (GWAS) based on studies in major crops. Considering the technological advances in genome sequencing, pangenome references for under-utilised species are becoming more obtainable, offering the opportunity to identify novel genes related to agro-morphological traits in these species.

Expanding Gene-Editing Potential in Crop Improvement with Pangenomes

Pangenomes aim to represent the complete repertoire of the genome diversity present within a species or cohort of species, capturing the genomic structural variance between individuals. This genomic information coupled with phenotypic data can be applied to identify genes and alleles involved with abiotic stress tolerance, disease resistance, and other desirable traits. The characterisation of novel structural variants from pangenomes can support genome editing approaches such as Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR associated protein Cas (CRISPR-Cas), providing functional information on gene sequences and new target sites in variant-specific genes with increased efficiency. This review discusses the application of pangenomes in genome editing and crop improvement, focusing on the potential of pangenomes to accurately identify target genes for CRISPR-Cas editing of plant genomes while avoiding adverse off-target effects. We consider the limitations of applying CRISPR-Cas editing with pangenome references and potential solutions to overcome these limitations.

Revisiting the Domestication Process of African Vigna Species (Fabaceae): Background, Perspectives and Challenges

Legumes are one of the most economically important and biodiverse families in plants recognised as the basis to develop functional foods. Among these, the Vigna genus stands out as a good representative because of its relatively recent African origin as well as its outstanding potential. Africa is a great biodiversity centre in which a great number of species are spread, but only three of them, Vigna unguiculata, Vigna subterranea and Vigna vexillata, were successfully domesticated. This review aims at analysing and valorising these species by considering the perspective of human activity and what effects it exerts. For each species, we revised the origin history and gave a focus on where, when and how many times domestication occurred. We provided a brief summary of bioactive compounds naturally occurring in these species that are fundamental for human wellbeing. The great number of wild lineages is a key point to improve landraces since the domestication process caused a loss of gene diversity. Their genomes hide a precious gene pool yet mostly unexplored, and genes lost during human activity can be recovered from the wild lineages and reintroduced in cultivated forms through modern technologies. Finally, we describe how all this information is game-changing to the design of future crops by domesticating de novo.

Detecting major introgressions in wheat and their putative origins using coverage analysis

Introgressions from crop wild relatives (CWRs) have been used to introduce beneficial traits into cultivated plants. Introgressions have traditionally been detected using cytological methods. Recently, single nucleotide polymorphism (SNP)-based methods have been proposed to detect introgressions in crosses for which both parents are known. However, for unknown material, no method was available to detect introgressions and predict the putative donor species. Here, we present a method to detect introgressions and the putative donor species. We demonstrate the utility of this method using 10 publicly available wheat genome sequences and identify nine major introgressions. We show that the method can distinguish different introgressions at the same locus. We trace introgressions to early wheat cultivars and show that natural introgressions were utilised in early breeding history and still influence elite lines today. Finally, we provide evidence that these introgressions harbour resistance genes.

Detecting major introgressions in wheat and their putative origins using coverage analysis

Introgressions from crop wild relatives (CWRs) have been used to introduce beneficial traits into cultivated plants. Introgressions have traditionally been detected using cytological methods. Recently, single nucleotide polymorphism (SNP)-based methods have been proposed to detect introgressions in crosses for which both parents are known. However, for unknown material, no method was available to detect introgressions and predict the putative donor species. Here, we present a method to detect introgressions and the putative donor species. We demonstrate the utility of this method using 10 publicly available wheat genome sequences and identify nine major introgressions. We show that the method can distinguish different introgressions at the same locus. We trace introgressions to early wheat cultivars and show that natural introgressions were utilised in early breeding history and still influence elite lines today. Finally, we provide evidence that these introgressions harbour resistance genes.

Water stress resilient cereal crops: Lessons from wild relatives

Cereal crops are significant contributors to global diets. As climate change disrupts weather patterns and wreaks havoc on crops, the need for generating stress-resilient, high-yielding varieties is more urgent than ever. One extremely promising avenue in this regard is to exploit the tremendous genetic diversity expressed by the wild ancestors of current day crop species. These crop wild relatives thrive in a range of environments and accordingly often harbor an array of traits that allow them to do so. The identification and introgression of these traits into our staple cereal crops can lessen yield losses in stressful environments. In the last decades, a surge in extreme drought and flooding events have severely impacted cereal crop production. Climate models predict a persistence of this trend, thus reinforcing the need for research on water stress resilience. Here we review: (i) how water stress (drought and flooding) impacts crop performance; and (ii) how identification of tolerance traits and mechanisms from wild relatives of the main cereal crops, that is, rice, maize, wheat, and barley, can lead to improved survival and sustained yields in these crops under water stress conditions.

Broadening the horizon of crop research: a decade of advancements in plant molecular genetics to divulge phenotype governing genes

Advancements in sequencing, genotyping, and computational technologies during the last decade (2011-2020) enabled new forward-genetic approaches, which subdue the impediments of precise gene mapping in varied crops. The modern crop improvement programs rely heavily on two major steps-trait-associated QTL/gene/marker's identification and molecular breeding. Thus, it is vital for basic and translational crop research to identify genomic regions that govern the phenotype of interest. Until the advent of next-generation sequencing, the forward-genetic techniques were laborious and time-consuming. Over the last 10 years, advancements in the area of genome assembly, genotyping, large-scale data analysis, and statistical algorithms have led faster identification of genomic variations regulating the complex agronomic traits and pathogen resistance. In this review, we describe the latest developments in genome sequencing and genotyping along with a comprehensive evaluation of the last 10-year headways in forward-genetic techniques that have shifted the focus of plant research from model plants to diverse crops. We have classified the available molecular genetic methods under bulk-segregant analysis-based (QTL-seq, GradedPool-Seq, QTG-Seq, Exome QTL-seq, and RapMap), target sequence enrichment-based (RenSeq, AgRenSeq, and TACCA), and mutation-based groups (MutMap, NIKS algorithm, MutRenSeq, MutChromSeq), alongside improvements in classical mapping and genome-wide association analyses. Newer methods for outcrossing, heterozygous, and polyploid plant genetics have also been discussed. The use of k-mers has enriched the nature of genetic variants which can be utilized to identify the phenotype-causing genes, independent of reference genomes. We envisage that the recent methods discussed herein will expand the repertoire of useful alleles and help in developing high-yielding and climate-resilient crops.

Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs

The last decade witnessed an unprecedented increase in the adoption of genomic selection (GS) and phenomics tools in plant breeding programs, especially in major cereal crops. GS has demonstrated the potential for selecting superior genotypes with high precision and accelerating the breeding cycle. Phenomics is a rapidly advancing domain to alleviate phenotyping bottlenecks and explores new large-scale phenotyping and data acquisition methods. In this review, we discuss the lesson learned from GS and phenomics in six self-pollinated crops, primarily focusing on rice, wheat, soybean, common bean, chickpea, and groundnut, and their implementation schemes are discussed after assessing their impact in the breeding programs. Here, the status of the adoption of genomics and phenomics is provided for those crops, with a complete GS overview. GS’s progress until 2020 is discussed in detail, and relevant information and links to the source codes are provided for implementing this technology into plant breeding programs, with most of the examples from wheat breeding programs. Detailed information about various phenotyping tools is provided to strengthen the field of phenomics for a plant breeder in the coming years. Finally, we highlight the benefits of merging genomic selection, phenomics, and machine and deep learning that have resulted in extraordinary results during recent years in wheat, rice, and soybean. Hence, there is a potential for adopting these technologies into crops like the common bean, chickpea, and groundnut. The adoption of phenomics and GS into different breeding programs will accelerate genetic gain that would create an impact on food security, realizing the need to feed an ever-growing population.

Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance

Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.

An SGSGeneloss-Based Method for Constructing a Gene Presence-Absence Table Using Mosdepth

Presence-absence variants (PAV) are genomic regions present in some individuals of a species, but not others. PAVs have been shown to contribute to genomic diversity, especially in bacteria and plants. These structural variations have been linked to traits and can be used to track a species' evolutionary history. PAVs are usually called by aligning short read sequence data from one or more individuals to a reference genome or pangenome assembly, and then comparing coverage. Regions where reads do not align define absence in that individual, and the regions are classified as PAVs. The method below details how to align sequence reads to a reference and how to use the sequencing-coverage calculator Mosdepth to identify PAVs and construct a PAV table for use in downstream comparative genome analysis.

Making a Pangenome Using the Iterative Mapping Approach

Pangenomes have replaced single reference genomes as genetic references, as they contain a better scope of the diversity found in a single species. This protocol outlines the iterative mapping approach in constructing a pangenome, including how to check the raw data, align the data to a reference, how to assemble the data, and how to remove potential contaminants from the final assembly.

Genome editing techniques in plants: a comprehensive review and future prospects toward zero hunger

Promoting sustainable agriculture and improving nutrition are the main united nation sustainable development goals by 2030. New technologies are required to achieve zero hunger, and genome editing technology is the most promising one. In the last decade, genome editing (GE) using the CRISPR/Cas system has attracted researchers as a safer and easy tool for genome editing in several living organisms. GE has revolutionized the field of agriculture by improving biotic and abiotic stresses and yield improvement. GE technologies were developed fast lately to avoid the obstacles that face GM crops. GE technology, depending on site directed nuclease (SDN), is divided into three categories according to the modification methods. Developing transgenic-free edited plants without introducing foreign DNA meet the acceptance and regulatory ratification of several countries. There are several ongoing efforts from different countries that are rapidly expanding to adopt the current technological innovations. This review summarizes the different GE technologies and their application as a way to help in ending hunger.

Advances in Multi-Omics Approaches for Molecular Breeding of Black Rot Resistance in Brassica oleracea L

Brassica oleracea is one of the most important species of the Brassicaceae family encompassing several economically important vegetables produced and consumed worldwide. But its sustainability is challenged by a range of pathogens, among which black rot, caused by Xanthomonas campestris pv. campestris (Xcc), is the most serious and destructive seed borne bacterial disease, causing huge yield losses. Host-plant resistance could act as the most effective and efficient solution to curb black rot disease for sustainable production of B. oleracea. Recently, 'omics' technologies have emerged as promising tools to understand the host-pathogen interactions, thereby gaining a deeper insight into the resistance mechanisms. In this review, we have summarized the recent achievements made in the emerging omics technologies to tackle the black rot challenge in B. oleracea. With an integrated approach of the omics technologies such as genomics, proteomics, transcriptomics, and metabolomics, it would allow better understanding of the complex molecular mechanisms underlying black rot resistance. Due to the availability of sequencing data, genomics and transcriptomics have progressed as expected for black rot resistance, however, other omics approaches like proteomics and metabolomics are lagging behind, necessitating a holistic and targeted approach to address the complex questions of Xcc-Brassica interactions. Genomic studies revealed that the black rot resistance is a complex trait and is mostly controlled by quantitative trait locus (QTL) with minor effects. Transcriptomic analysis divulged the genes related to photosynthesis, glucosinolate biosynthesis and catabolism, phenylpropanoid biosynthesis pathway, ROS scavenging, calcium signalling, hormonal synthesis and signalling pathway are being differentially expressed upon Xcc infection. Comparative proteomic analysis in relation to susceptible and/or resistance interactions with Xcc identified the involvement of proteins related to photosynthesis, protein biosynthesis, processing and degradation, energy metabolism, innate immunity, redox homeostasis, and defence response and signalling pathways in Xcc-Brassica interaction. Specifically, most of the studies focused on the regulation of the photosynthesis-related proteins as a resistance response in both early and later stages of infection. Metabolomic studies suggested that glucosinolates (GSLs), especially aliphatic and indolic GSLs, its subsequent hydrolysis products, and defensive metabolites synthesized by jasmonic acid (JA)-mediated phenylpropanoid biosynthesis pathway are involved in disease resistance mechanisms against Xcc in Brassica species. Multi-omics analysis showed that JA signalling pathway is regulating resistance against hemibiotrophic pathogen like Xcc. So, the bonhomie between omics technologies and plant breeding is going to trigger major breakthroughs in the field of crop improvement by developing superior cultivars with broad-spectrum resistance. If multi-omics tools are implemented at the right scale, we may be able to achieve the maximum benefits from the minimum. In this review, we have also discussed the challenges, future prospects, and the way forward in the application of omics technologies to accelerate the breeding of B. oleracea for disease resistance. A deeper insight about the current knowledge on omics can offer promising results in the breeding of high-quality disease-resistant crops.

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

Genomic Approaches for Improvement of Tropical Fruits: Fruit Quality, Shelf Life and Nutrient Content

The breeding of tropical fruit trees for improving fruit traits is complicated, due to the long juvenile phase, generation cycle, parthenocarpy, polyploidy, polyembryony, heterozygosity and biotic and abiotic factors, as well as a lack of good genomic resources. Many molecular techniques have recently evolved to assist and hasten conventional breeding efforts. Molecular markers linked to fruit development and fruit quality traits such as fruit shape, size, texture, aroma, peel and pulp colour were identified in tropical fruit crops, facilitating Marker-assisted breeding (MAB). An increase in the availability of genome sequences of tropical fruits further aided in the discovery of SNP variants/Indels, QTLs and genes that can ascertain the genetic determinants of fruit characters. Through multi-omics approaches such as genomics, transcriptomics, metabolomics and proteomics, the identification and quantification of transcripts, including non-coding RNAs, involved in sugar metabolism, fruit development and ripening, shelf life, and the biotic and abiotic stress that impacts fruit quality were made possible. Utilizing genomic assisted breeding methods such as genome wide association (GWAS), genomic selection (GS) and genetic modifications using CRISPR/Cas9 and transgenics has paved the way to studying gene function and developing cultivars with desirable fruit traits by overcoming long breeding cycles. Such comprehensive multi-omics approaches related to fruit characters in tropical fruits and their applications in breeding strategies and crop improvement are reviewed, discussed and presented here.

Current status of structural variation studies in plants

Structural variations (SVs) including gene presence/absence variations and copy number variations are a common feature of genomes in plants and, together with single nucleotide polymorphisms and epigenetic differences, are responsible for the heritable phenotypic diversity observed within and between species. Understanding the contribution of SVs to plant phenotypic variation is important for plant breeders to assist in producing improved varieties. The low resolution of early genetic technologies and inefficient methods have previously limited our understanding of SVs in plants. However, with the rapid expansion in genomic technologies, it is possible to assess SVs with an ever-greater resolution and accuracy. Here, we review the current status of SV studies in plants, examine the roles that SVs play in phenotypic traits, compare current technologies and assess future challenges for SV studies.

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.

Reap the crop wild relatives for breeding future crops

Crop wild relatives (CWRs) have provided breeders with several 'game-changing' traits or genes that have boosted crop resilience and global agricultural production. Advances in breeding and genomics have accelerated the identification of valuable CWRs for use in crop improvement. The enhanced genetic diversity of breeding pools carrying optimum combinations of favorable alleles for targeted crop-growing regions is crucial to sustain genetic gain. In parallel, growing sequence information on wild genomes in combination with precise gene-editing tools provide a fast-track route to transform CWRs into ideal future crops. Data-informed germplasm collection and management strategies together with adequate policy support will be equally important to improve access to CWRs and their sustainable use to meet food and nutrition security targets.

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

KEY MESSAGE

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

Rewilding crops for climate resilience: economic analysis and de novo domestication strategies

To match predicted population growth, annual food production should be doubled by 2050. This is not achievable by current agronomical and breeding practices, due to the impact of climate changes and associated abiotic stresses on agricultural production systems. Here, we analyze the impact of global climate trends on crop productivity and show that the overall loss in crop production from climate-driven abiotic stresses may exceed US$170 billion year-1 and represents a major threat to global food security. We also show that abiotic stress tolerance had been present in wild progenitors of modern crops but was lost during their domestication. We argue for a major shift in our paradigm of crop breeding, focusing on climate resilience, and call for a broader use of wild relatives as a major tool in this process. We argue that, while molecular tools are currently in place to harness the potential of climate-resilient genes present in wild relatives, the complex polygenic nature of tolerance traits remains a major bottleneck in this process. Future research efforts should be focused not only on finding appropriate wild relatives but also on development of efficient cell-based high-throughput phenotyping platforms allowing assessment of the in planta operation of key genes.

Fast-forward breeding for a food-secure world

Crop production systems need to expand their outputs sustainably to feed a burgeoning human population. Advances in genome sequencing technologies combined with efficient trait mapping procedures accelerate the availability of beneficial alleles for breeding and research. Enhanced interoperability between different omics and phenotyping platforms, leveraged by evolving machine learning tools, will help provide mechanistic explanations for complex plant traits. Targeted and rapid assembly of beneficial alleles using optimized breeding strategies and precise genome editing techniques could deliver ideal crops for the future. Realizing desired productivity gains in the field is imperative for securing an adequate future food supply for 10 billion people.