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

Genomics-assisted breeding for designing salinity-smart future crops

Climate change induces many abiotic stresses, including soil salinity, significantly challenging global agriculture. Salinity stress tolerance (SST) is a complex trait, both physiologically and genetically, and is conferred at various levels of plant functional organization. As both the sustainability and profitability of agricultural production systems are critically dependent on SST, plant breeders are trying to design and develop salinity-smart crop plants capable of thriving under high salinity conditions. The accessibility of extreme-quality reference genomes for cultivated crops, naturally salinity-smart plants, and crop wild relatives has fast-tracked the discovery of key genes and quantitative trait loci (QTLs), marker development, genotyping assays and molecular breeding products with improved SST. Employing fast-forward breeding tools, namely genomic selection (GS), haplotype-based breeding (HBB), artificial intelligence (AI) and high-throughput phenotyping (HTP), has shown influence not only for fast-tracking genetic gains but also for reducing the time and cost of developing commercial cultivars with enhanced SST and yield stability. This review discusses the advancement and prospects of various genomics-assisted breeding (GAB) tools, including genome sequencing, QTL mapping, GWAS, GS, HBB, pan-genomics, single-cell/tissue genomics and phenotyping, epigenomics and transgenomics, to exploit the genetic landscape for improving SST. Additionally, we explore the integration of HTP and AI, which demonstrates how these innovative approaches can optimize breeding efficiency and guide large-scale breeding efforts for designing salinity-smart crops to ensure sustainable agriculture and global food security. The collective adoption of these tools suggests bridging the gap between research and field application to deliver stress-smart varieties designed for saline-affected regions worldwide.

What Are We Learning from Plant Pangenomes?

A single reference genome does not fully capture species diversity. By contrast, a pangenome incorporates multiple genomes to capture the entire set of nonredundant genes in a given species, along with its genome diversity. New sequencing technologies enable researchers to produce multiple high-quality genome sequences and catalog diverse genetic variations with better precision. Pangenomic studies have detected structural variants in plant genomes, dissected the genetic architecture of agronomic traits, and helped unravel molecular underpinnings and evolutionary origins of plant phenotypes. The pangenome concept has further evolved into a so-called super-pangenome that includes wild relatives within a genus or clade and shifted to graph-based reference systems. Nevertheless, building pangenomes and representing complex structural variants remain challenging in many crops. Standardized computing pipelines and common data structures are needed to compare and interpret pangenomes. The growing body of plant pangenomics data requires new algorithms, huge data storage capacity, and training to help researchers and breeders take advantage of newly discovered genes and genetic variants.

Graphical pangenomics-enabled characterization of structural variant impact on gene expression in Brassica napus

KEY MESSAGE

Pangenome graphs enable population-scale genotyping and improve expression analysis, revealing that structural variations (SVs), particularly transposable elements (TEs), significantly contribute to gene expression variation in winter oilseed rape. Structural variations (SVs) impact important traits, from yield to flowering behaviour and stress responses. Pangenome graphs capture population-level diversity, including SVs, within a single data structure and provide a robust framework for downstream applications. They have the potential to serve as unbiased references for SV genotyping, pan-transcriptomic analyses, and association studies, offering significant advantages over single reference genomes. However, their full potential for expression quantitative trait locus (eQTL) analysis is yet to be explored. We combined long and short-read whole genome sequencing data with expression profiling of Brassica napus (oilseed rape) to assess the impact of SVs on gene expression regulation and explored the utility of pangenome graphs for eQTL analysis. Over 90,000 SVs were discovered from 57 long-read datasets. Pangenome graph as reference was evaluated and used for SV genotyping with short reads and transcript expression quantification. Using SVs genotyped from the graph and 100 expression datasets, we identified 267 gene proximal (cis) SV-eQTLs. Over 70% of eQTL-SVs had similarity to transposable elements (TEs), especially Helitrons. The highest proportion of cis-eQTL-SVs were found in promoter regions. About a third of transcripts whose expression was associated with SVs, had no associated SNPs, suggesting that including SVs allows capturing of relationship which would be missed in SNP-only analyses. This study demonstrated that pangenome graphs provide a unifying framework for eQTL analysis by allowing population-scale SV genotyping and gene expression quantification. We also showed that SVs make an appreciable contribution to gene expression variation in winter oilseed rape.

Brassica Panache: A multi-species graph pangenome representing presence absence variation across forty-one Brassica genomes

Brassicas are an economically important crop species that provide a source of healthy oil and vegetables. With the rising population and the impact of climate change on agriculture, there is an increasing need to improve agronomically important traits of crops such as Brassica. The genomes of plant species have significant sequence presence absence variation (PAV), which is a source of genetic variation that can be used for crop improvement, and this species variation can be captured through the construction of pangenomes. Graph pangenomes are a recent reference format that represent the genomic variation with a species or population as alternate paths in a sequence graph. Graph pangenomes contain information on alignment, PAV, and annotation. Here we present the first multi-species graph pangenome for Brassica visualized with pangenome analyzer with chromosomal exploration (Panache).

Transposon proliferation drives genome architecture and regulatory evolution in wild and domesticated peppers

Pepper (Capsicum spp.) is a widely consumed vegetable with exceptionally large genomes in Solanaceae, yet its genomic evolutionary history remains largely unknown. Here we present 11 high-quality Capsicum genome assemblies, including two gap-free genomes, covering four wild and all five domesticated pepper species. We reconstructed the ancestral karyotype and inferred the evolutionary trajectory of peppers. The expanded and variable genome sizes were attributed to differential transposable element accumulations, which shaped 3D chromatin architecture and introduced mutations associated with traits such as fruit orientation and colour. Using a chromatin accessibility atlas of Capsicum, we highlight the influence of transposable elements on regulatory element evolution. Furthermore, by constructing a haploblock map of 124 pepper core germplasms, we uncover frequent introgressions that facilitate the formation of sweet blocky pepper and the acquisition of important traits such as resistance to pepper mild mottle virus. These findings on the genomic and functional evolution of Capsicum will benefit pepper breeding.

Impact of structural variations and genome partitioning on bread wheat hybrid performance

The agronomical interest of hybrid wheat has long been a matter of debate. Compared to maize where hybrids have been successfully grown for decades, the mixed results obtained in wheat have been attributed at least partially to the lack of heterotic groups. The wheat genome is known to be strongly partitioned and characterized by numerous presence/absence variations and alien introgressions which have not been thoroughly considered in hybrid breeding. The objective was to investigate the relationships between hybrid performance and genomic diversity. For this, we characterized a set of 124 hybrids as well as their 19 female and 16 male parents. Phenotyping for yield and yield components was conducted during two years in three locations. Parental lines were genotyped using a 410 K SNP array as well as through sequence capture of roughly 200,000 loci. This led to the identification of 180 structural variations including presence-absence variations and alien introgressions. Twenty-six of them were associated to hybrid performance through either additivity or dominance effects. While no correlation was observed at the whole genome level, the genetic distance for 25 genomic regions resulting from the structural and functional partitioning of the chromosomes shown positive or negative correlation with agronomic traits including yield. Large introgressions, like the Aegilops ventricosa 2NS-2AS translocation, can correspond to entire chromosomal regions, such as the R1 region, with an impact on yield. Our results suggest hybrid breeding should consider both structural variations and chromosome partitioning rather than maximizing whole-genome genetic distance, and according to genomic regions to combine homozygosity and heterozygosity.

Genomic and cell-specific regulation of benzylisoquinoline alkaloid biosynthesis in opium poppy

Opium poppy is a crop of great commercial value as a source of several opium alkaloids for the pharmaceutical industries including morphine, codeine, thebaine, noscapine, and papaverine. Most enzymes involved in benzylisoquinoline alkaloid (BIA) biosynthesis in opium poppy have been functionally characterized, and opium poppy currently serves as a model system to study BIA metabolism in plants. BIA biosynthesis in opium poppy involves two biosynthetic gene clusters associated respectively with the morphine and noscapine branches. Recent reports have shown that genes in the same cluster are co-expressed, suggesting they might also be co-regulated. However, the transcriptional regulation of opium poppy BIA biosynthesis is not well studied. Opium poppy BIA biosynthesis involves three cell types associated with the phloem system: companion cells, sieve elements, and laticifers. The transcripts and enzymes associated with BIA biosynthesis are distributed across cell types, requiring the translocation of key enzymes and pathway intermediates between cell types. Together, these suggest that the regulation of BIA biosynthesis in opium poppy is multilayered and complex, involving biochemical, genomic, and physiological mechanisms. In this review, we highlight recent advances in genome sequencing and single cell and spatial transcriptomics with a focus on how these efforts can improve our understanding of the genomic and cell-specific regulation of BIA biosynthesis. Such knowledge is vital for opium poppy genetic improvement and metabolic engineering efforts targeting the modulation of alkaloid yield and composition.

Pangenome graphs and their applications in biodiversity genomics

Complete datasets of genetic variants are key to biodiversity genomic studies. Long-read sequencing technologies allow the routine assembly of highly contiguous, haplotype-resolved reference genomes. However, even when complete, reference genomes from a single individual may bias downstream analyses and fail to adequately represent genetic diversity within a population or species. Pangenome graphs assembled from aligned collections of high-quality genomes can overcome representation bias by integrating sequence information from multiple genomes from the same population, species or genus into a single reference. Here, we review the available tools and data structures to build, visualize and manipulate pangenome graphs while providing practical examples and discussing their applications in biodiversity and conservation genomics across the tree of life.

The pan-NLRome analysis based on 23 genomes reveals the diversity of NLRs in Brassica napus

Brassica napus, a globally significant oilseed crop, exhibits a wide distribution across diverse climatic zones. B. napus is being increasingly susceptible to distinct diseases, such as blackleg, clubroot and sclerotinia stem rot, leading to substantial reductions in yield. Nucleotide-binding site leucine-rich repeat genes (NLRs), the most pivotal family of resistance genes, can be effectively harnessed by identifying and uncovering their diversity to acquire premium disease-resistant gene resources. Here, we collected the genomes of 23 accessions and established the first comprehensive pan-NLRome in B. napus by leveraging multiple genomic resources. We observe significant variation in the number of NLR genes across different B. napus accessions, ranging from 189 to 474. Notably, TNL (TIR-NBS-LRR) genes constitute approximately half of the total count, indicating their predominant presence in B. napus. The number of NLRs in the C subgenome is significantly higher than that in the A subgenome, and chromosome C09 exhibits the highest density of NLR genes with featuring multiple NLR clusters. Domain analysis reveals that the integrated domains significantly enhance the diversity of NLRs, with B3 DNA binding, VQ, and zinc fingers being the most prevalent integrated domains. Pan-genomic analysis reveals that the core type of NLR genes, which is present in most accessions, constitutes approximately 58% of the total NLRs. Furthermore, we conduct a comparative analysis of the diversity of NLR genes across distinct ecotypes, leading to the identification of ecotype-specific NLRs and their integrated domains. In conclusion, our study effectively addresses the limitations of a single reference genome and provides valuable insights into the diversity of NLR genes in B. napus, thereby contributing to disease resistance breeding.

PangeBlocks: customized construction of pangenome graphs via maximal blocks

BACKGROUND

The construction of a pangenome graph is a fundamental task in pangenomics. A natural theoretical question is how to formalize the computational problem of building an optimal pangenome graph, making explicit the underlying optimization criterion and the set of feasible solutions. Current approaches build a pangenome graph with some heuristics, without assuming some explicit optimization criteria. Thus it is unclear how a specific optimization criterion affects the graph topology and downstream analysis, like read mapping and variant calling.

RESULTS

In this paper, by leveraging the notion of maximal block in a Multiple Sequence Alignment (MSA), we reframe the pangenome graph construction problem as an exact cover problem on blocks called Minimum Weighted Block Cover (MWBC). Then we propose an Integer Linear Programming (ILP) formulation for the MWBC problem that allows us to study the most natural objective functions for building a graph. We provide an implementation of the ILP approach for solving the MWBC and we evaluate it on SARS-CoV-2 complete genomes, showing how different objective functions lead to pangenome graphs that have different properties, hinting that the specific downstream task can drive the graph construction phase.

CONCLUSION

We show that a customized construction of a pangenome graph based on selecting objective functions has a direct impact on the resulting graphs. In particular, our formalization of the MWBC problem, based on finding an optimal subset of blocks covering an MSA, paves the way to novel practical approaches to graph representations of an MSA where the user can guide the construction.

Omics-Driven Strategies for Developing Saline-Smart Lentils: A Comprehensive Review

A number of consequences of climate change, notably salinity, put global food security at risk by impacting the development and production of lentils. Salinity-induced stress alters lentil genetics, resulting in severe developmental issues and eventual phenotypic damage. Lentils have evolved sophisticated signaling networks to combat salinity stress. Lentil genomics and transcriptomics have discovered key genes and pathways that play an important role in mitigating salinity stress. The development of saline-smart cultivars can be further revolutionized by implementing proteomics, metabolomics, miRNAomics, epigenomics, phenomics, ionomics, machine learning, and speed breeding approaches. All these cutting-edge approaches represent a viable path toward creating saline-tolerant lentil cultivars that can withstand climate change and meet the growing demand for high-quality food worldwide. The review emphasizes the gaps that must be filled for future food security in a changing climate while also highlighting the significant discoveries and insights made possible by omics and other state-of-the-art biotechnological techniques.

Epistasis and pleiotropy-induced variation for plant breeding

Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability.

Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding

Inversions, a type of chromosomal structural variation, significantly influence plant adaptation and gene functions by impacting gene expression and recombination rates. However, compared with other structural variations, their roles in functional biology and crop improvement remain largely unexplored. In this review, we highlight technological and methodological advancements that have allowed a comprehensive understanding of inversion variants through the pangenome framework and machine learning algorithms. Genome editing is an efficient method for inducing or reversing inversion mutations in plants, providing an effective mechanism to modify local recombination rates. Given the potential of inversions in crop breeding, we anticipate increasing attention on inversions from the scientific community in future research and breeding applications.

Recent advances in plant translational genomics for crop improvement

The growing population, climate change, and limited agricultural resources put enormous pressure on agricultural systems. A plateau in crop yields is occurring and extreme weather events and urbanization threaten the livelihood of farmers. It is imperative that immediate attention is paid to addressing the increasing food demand, ensuring resilience against emerging threats, and meeting the demand for more nutritious, safer food. Under uncertain conditions, it is essential to expand genetic diversity and discover novel crop varieties or variations to develop higher and more stable yields. Genomics plays a significant role in developing abundant and nutrient-dense food crops. An alternative to traditional breeding approach, translational genomics is able to improve breeding programs in a more efficient and precise manner by translating genomic concepts into practical tools. Crop breeding based on genomics offers potential solutions to overcome the limitations of conventional breeding methods, including improved crop varieties that provide more nutritional value and are protected from biotic and abiotic stresses. Genetic markers, such as SNPs and ESTs, contribute to the discovery of QTLs controlling agronomic traits and stress tolerance. In order to meet the growing demand for food, there is a need to incorporate QTLs into breeding programs using marker-assisted selection/breeding and transgenic technologies. This chapter primarily focuses on the recent advances that are made in translational genomics for crop improvement and various omics techniques including transcriptomics, metagenomics, pangenomics, single cell omics etc. Numerous genome editing techniques including CRISPR Cas technology and their applications in crop improvement had been discussed.

The chromosome-scale genome of Magnolia sinica (Magnoliaceae) provides insights into the conservation of plant species with extremely small populations (PSESP)

Magnolia sinica (Magnoliaceae) is a highly threatened tree endemic to southeast Yunnan, China. In this study, we generated for the first time a high-quality chromosome-scale genome sequence from M. sinica, by combining Illumina and ONT data with Hi-C scaffolding methods. The final assembled genome size of M. sinica was 1.84 Gb, with a contig N50 of ca. 45 Mb and scaffold N50 of 92 Mb. Identified repeats constituted approximately 57% of the genome, and 43,473 protein-coding genes were predicted. Phylogenetic analysis shows that the magnolias form a sister clade with the eudicots and the order Ceratophyllales, while the monocots are sister to the other core angiosperms. In our study, a total of 21 individuals from the 5 remnant populations of M. sinica, as well as 22 specimens belonging to 8 related Magnoliaceae species, were resequenced. The results showed that M. sinica had higher genetic diversity (θw = 0.01126 and θπ = 0.01158) than other related species in the Magnoliaceae. However, population structure analysis suggested that the genetic differentiation among the 5 M. sinica populations was very low. Analyses of the demographic history of the species using different models consistently revealed that 2 bottleneck events occurred. The contemporary effective population size of M. sinica was estimated to be 10.9. The different patterns of genetic loads (inbreeding and numbers of deleterious mutations) suggested constructive strategies for the conservation of these 5 different populations of M. sinica. Overall, this high-quality genome will be a valuable genomic resource for conservation of M. sinica.

A comprehensive lettuce variation map reveals the impact of structural variations in agronomic traits

BACKGROUND

As an important vegetable crop, cultivated lettuce is grown worldwide and a great variety of agronomic traits have been preserved within germplasm collections. The mechanisms underlying these phenotypic variations remain to be elucidated in association with sequence variations. Compared with single nucleotide polymorphisms, structural variations (SVs) that have more impacts on gene functions remain largely uncharacterized in the lettuce genome.

RESULTS

Here, we produced a comprehensive SV set for 333 wild and cultivated lettuce accessions. Comparison of SV frequencies showed that the SVs prevalent in L. sativa affected the genes enriched in carbohydrate derivative catabolic and secondary metabolic processes. Genome-wide association analysis of seven agronomic traits uncovered potentially causal SVs associated with seed coat color and leaf anthocyanin content.

CONCLUSION

Our work characterized a great abundance of SVs in the lettuce genome, and provides a valuable genomic resource for future lettuce breeding.

The pig pangenome provides insights into the roles of coding structural variations in genetic diversity and adaptation

Structural variations have emerged as an important driving force for genome evolution and phenotypic variation in various organisms, yet their contributions to genetic diversity and adaptation in domesticated animals remain largely unknown. Here we constructed a pangenome based on 250 sequenced individuals from 32 pig breeds in Eurasia and systematically characterized coding sequence presence/absence variations (PAVs) within pigs. We identified 308.3-Mb nonreference sequences and 3438 novel genes absent from the current reference genome. Gene PAV analysis showed that 16.8% of the genes in the pangene catalog undergo PAV. A number of newly identified dispensable genes showed close associations with adaptation. For instance, several novel swine leukocyte antigen (SLA) genes discovered in nonreference sequences potentially participate in immune responses to productive and respiratory syndrome virus (PRRSV) infection. We delineated previously unidentified features of the pig mobilome that contained 490,480 transposable element insertion polymorphisms (TIPs) resulting from recent mobilization of 970 TE families, and investigated their population dynamics along with influences on population differentiation and gene expression. In addition, several candidate adaptive TE insertions were detected to be co-opted into genes responsible for responses to hypoxia, skeletal development, regulation of heart contraction, and neuronal cell development, likely contributing to local adaptation of Tibetan wild boars. These findings enhance our understanding on hidden layers of the genetic diversity in pigs and provide novel insights into the role of SVs in the evolutionary adaptation of mammals.

Engineering the Crop Microbiota Through Host Genetics

The microbiota populating the plant-soil continuum defines an untapped resource for sustainable crop production. The host plant is a driver for the taxonomic composition and function of these microbial communities. In this review, we illustrate how the host genetic determinants of the microbiota have been shaped by plant domestication and crop diversification. We discuss how the heritable component of microbiota recruitment may represent, at least partially, a selection for microbial functions underpinning the growth, development, and health of their host plants and how the magnitude of this heritability is influenced by the environment. We illustrate how host-microbiota interactions can be treated as an external quantitative trait and review recent studies associating crop genetics with microbiota-based quantitative traits. We also explore the results of reductionist approaches, including synthetic microbial communities, to establish causal relationships between microbiota and plant phenotypes. Lastly, we propose strategies to integrate microbiota manipulation into crop selection programs. Although a detailed understanding of when and how heritability for microbiota composition can be deployed for breeding purposes is still lacking, we argue that advances in crop genomics are likely to accelerate wider applications of plant-microbiota interactions in agriculture.

Plant genome resequencing and population genomics: Current status and future prospects

Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.

Ideotype breeding and genome engineering for legume crop improvement

Ideotype breeding is a strategy whereby traits are modeled a priori and then introduced into a model or crop species to assess their impact on yield. Thus, knowledge about the connection between genotype and phenotype is required for ideotype breeding to be deployed successfully. The growing understanding of the genetic basis of yield-related traits, combined with increasingly efficient genome engineering tools, improved transformation efficiency, and high-throughput genotyping of regenerants paves the way for the widespread adoption of ideotype breeding as a complement to conventional breeding. We briefly discuss how ideotype breeding, coupled with such state-of-the-art biotechnological tools, could contribute to knowledge-based legume breeding and accelerate yield gains to ensure food security in the coming decades.

k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives

Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses

The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.

Human Pangenomics: Promises and Challenges of a Distributed Genomic Reference

A pangenome is a collection of the common and unique genomes that are present in a given species. It combines the genetic information of all the genomes sampled, resulting in a large and diverse range of genetic material. Pangenomic analysis offers several advantages compared to traditional genomic research. For example, a pangenome is not bound by the physical constraints of a single genome, so it can capture more genetic variability. Thanks to the introduction of the concept of pangenome, it is possible to use exceedingly detailed sequence data to study the evolutionary history of two different species, or how populations within a species differ genetically. In the wake of the Human Pangenome Project, this review aims at discussing the advantages of the pangenome around human genetic variation, which are then framed around how pangenomic data can inform population genetics, phylogenetics, and public health policy by providing insights into the genetic basis of diseases or determining personalized treatments, targeting the specific genetic profile of an individual. Moreover, technical limitations, ethical concerns, and legal considerations are discussed.

Transgressive and parental dominant gene expression and cytosine methylation during seed development in Brassica napus hybrids

KEY MESSAGE

Transcriptomic and epigenomic profiling of gene expression and small RNAs during seed and seedling development reveals expression and methylation dominance levels with implications on early stage heterosis in oilseed rape. The enhanced performance of hybrids through heterosis remains a key aspect in plant breeding; however, the underlying mechanisms are still not fully elucidated. To investigate the potential role of transcriptomic and epigenomic patterns in early expression of hybrid vigor, we investigated gene expression, small RNA abundance and genome-wide methylation in hybrids from two distant Brassica napus ecotypes during seed and seedling developmental stages using next-generation sequencing. A total of 31117, 344, 36229 and 7399 differentially expressed genes, microRNAs, small interfering RNAs and differentially methylated regions were identified, respectively. Approximately 70% of the differentially expressed or methylated features displayed parental dominance levels where the hybrid followed the same patterns as the parents. Via gene ontology enrichment and microRNA-target association analyses during seed development, we found copies of reproductive, developmental and meiotic genes with transgressive and paternal dominance patterns. Interestingly, maternal dominance was more prominent in hypermethylated and downregulated features during seed formation, contrasting to the general maternal gamete demethylation reported during gametogenesis in angiosperms. Associations between methylation and gene expression allowed identification of putative epialleles with diverse pivotal biological functions during seed formation. Furthermore, most differentially methylated regions, differentially expressed siRNAs and transposable elements were in regions that flanked genes without differential expression. This suggests that differential expression and methylation of epigenomic features may help maintain expression of pivotal genes in a hybrid context. Differential expression and methylation patterns during seed formation in an F₁ hybrid provide novel insights into genes and mechanisms with potential roles in early heterosis.

Benchmarking Oxford Nanopore read alignment-based insertion and deletion detection in crop plant genomes

Structural variations (SVs) are larger polymorphisms (> 50 bp in length), which consist of insertions, deletions, inversions, duplications, and translocations. They can have a strong impact on agronomical traits and play an important role in environmental adaptation. The development of long-read sequencing technologies, including Oxford Nanopore, allows for comprehensive SV discovery and characterization even in complex polyploid crop genomes. However, many of the SV discovery pipeline benchmarks do not include complex plant genome datasets. In this study, we benchmarked insertion and deletion detection by popular long-read alignment-based SV detection tools for crop plant genomes. We used real and simulated Oxford Nanopore reads for two crops, allotetraploid Brassica napus (oilseed rape) and diploid Solanum lycopersicum (tomato), and evaluated several read aligners and SV callers across 5×, 10×, and 20× coverages typically used in re-sequencing studies. We further validated our findings using maize and soybean datasets. Our benchmarks provide a useful guide for designing Oxford Nanopore re-sequencing projects and SV discovery pipelines for crop plants.

Diversifying agrifood systems to ensure global food security following the Russia–Ukraine crisis

The recent Russia–Ukraine conflict has raised significant concerns about global food security, leaving many countries with restricted access to imported staple food crops, particularly wheat and sunflower oil, sending food prices soaring with other adverse consequences in the food supply chain. This detrimental effect is particularly prominent for low-income countries relying on grain imports, with record-high food prices and inflation affecting their livelihoods. This review discusses the role of Russia and Ukraine in the global food system and the impact of the Russia–Ukraine conflict on food security. It also highlights how diversifying four areas of agrifood systems—markets, production, crops, and technology can contribute to achieving food supply chain resilience for future food security and sustainability.

Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication

Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.

Genome and pan-genome assembly of asparagus bean (Vigna unguiculata ssp. sesquipedialis) reveal the genetic basis of cold adaptation

Asparagus bean (Vigna unguiculata ssp. sesquipedialis) is an important cowpea subspecies. We assembled the genomes of Ningjiang 3 (NJ, 550.31 Mb) and Dubai bean (DB, 564.12 Mb) for comparative genomics analysis. The whole-genome duplication events of DB and NJ occurred at 64.55 and 64.81 Mya, respectively, while the divergence between soybean and Vigna occurred in the Paleogene period. NJ genes underwent positive selection and amplification in response to temperature and abiotic stress. In species-specific gene families, NJ is mainly enriched in response to abiotic stress, while DB is primarily enriched in respiration and photosynthesis. We established the pan-genomes of four accessions (NJ, DB, IT97K-499-35 and Xiabao II) and identified 20,336 (70.5%) core genes present in all the accessions, 6,507 (55.56%) variable genes in two individuals, and 2,004 (6.95%) unique genes. The final pan genome is 616.35 Mb, and the core genome is 399.78 Mb. The variable genes are manifested mainly in stress response functions, ABC transporters, seed storage, and dormancy control. In the pan-genome sequence variation analysis, genes affected by presence/absence variants were enriched in biological processes associated with defense responses, immune system processes, signal transduction, and agronomic traits. The results of the present study provide genetic data that could facilitate efficient asparagus bean genetic improvement, especially in producing cold-adapted asparagus bean.

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.

Graph Pangenomes Track Genetic Variants for Crop Improvement

Global climate change and the urgency to transform crops require an exhaustive genetic evaluation. The large polyploid genomes of food crops, such as cereals, make it difficult to identify candidate genes with confirmed hereditary. Although genome-wide association studies (GWAS) have been proficient in identifying genetic variants that are associated with complex traits, the resolution of acquired heritability faces several significant bottlenecks such as incomplete detection of structural variants (SV), genetic heterogeneity, and/or locus heterogeneity. Consequently, a biased estimate is generated with respect to agronomically complex traits. The graph pangenomes have resolved this missing heritability and provide significant details in terms of specific loci segregating among individuals and evolving to variations. The graph pangenome approach facilitates crop improvements through genome-linked fast breeding.

The Global Assessment of Oilseed Brassica Crop Species Yield, Yield Stability and the Underlying Genetics

The global demand for oilseeds is increasing along with the human population. The family of Brassicaceae crops are no exception, typically harvested as a valuable source of oil, rich in beneficial molecules important for human health. The global capacity for improving Brassica yield has steadily risen over the last 50 years, with the major crop Brassica napus (rapeseed, canola) production increasing to ~72 Gt in 2020. In contrast, the production of Brassica mustard crops has fluctuated, rarely improving in farming efficiency. The drastic increase in global yield of B. napus is largely due to the demand for a stable source of cooking oil. Furthermore, with the adoption of highly efficient farming techniques, yield enhancement programs, breeding programs, the integration of high-throughput phenotyping technology and establishing the underlying genetics, B. napus yields have increased by >450 fold since 1978. Yield stability has been improved with new management strategies targeting diseases and pests, as well as by understanding the complex interaction of environment, phenotype and genotype. This review assesses the global yield and yield stability of agriculturally important oilseed Brassica species and discusses how contemporary farming and genetic techniques have driven improvements.

Pangenome-wide analysis of cyclic nucleotide-gated channel (CNGC) gene family in citrus Spp. Revealed their intraspecies diversity and potential roles in abiotic stress tolerance

Cyclic nucleotide-gated channels (CNGC) gene family has been found to be involved in physiological processes including signaling pathways, environmental stresses, plant growth, and development. This gene family of non-selective cation channels is known to regulate the uptake of calcium and is reported in several plant species. The pangenome-wide studies enable researchers to understand the genetic diversity comprehensively; as a comparative analysis of multiple plant species or member of a species at once helps to better understand the evolutionary relationships and diversity present among them. In the current study, pangenome-wide analysis of the CNGC gene family has been performed on five Citrus species. As a result, a total of 32 genes in Citrus sinensis, 27 genes in Citrus recticulata, 30 genes in Citrus grandis, 31 genes in Atalantia buxfolia, and 30 genes in Poncirus trifoliata were identified. In addition, two unique genes CNGC13 and CNGC14 were identified, which may have potential roles. All the identified CNGC genes were unevenly distributed on 9 chromosomes except P. trifoliata had genes distributed on 7 chromosomes and were classified into four major groups and two sub-groups namely I, II, III, IV-A, and IV-B. Cyclic nucleotide binding (CNB) motif, calmodulin-binding motif (CaMB), and motif for IQ-domain were conserved in Citrus Spp. Intron exon structures of citrus species were not exactly as same as the gene structures of Arabidopsis. The majority of cis-regulatory elements (CREs) were light responsive and others include growth, development, and stress-related indicating potential roles of the CNGC gene family in these functions. Both segmental and tandem duplication were involved in the expansion of the CNGC gene family in Citrus Spp. The miRNAs are involved in the response of CsCNGC genes towards drought stress along with having regulatory association in the expression of these genes. Protein- Protein interaction (PPI) analysis also showed the interaction of CNGC proteins with other CNGCs which suggested their potential role in pathways regulating different biological processes. GO enrichment revealed that CNGC genes were involved in the transport of ions across membranes. Furthermore, tissue-specific expression patterns of leaves sample of C. sinensis were studied under drought stress. Out of 32 genes of C. sinensis 3 genes i.e., CsCNGC1.4, CsCNGC2.1, and CsCNGC4.2 were highly up-regulated, and only CsCNGC4.6 was highly down-regulated. The qRT-PCR analysis also showed that CNGC genes were highly expressed after treatment with drought stress, while gene expression was lower under controlled conditions. This work includes findings based on multiple genomes instead of one, therefore, this will provide more genomic information rather than single genome-based studies. These findings will serve as a basis for further functional insights into the CNGC gene family.

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.