The pangenome of banana highlights differences between genera and genomes

Technological Development and Advances for Constructing and Analyzing Plant Pangenomes

A pangenome captures the genomic diversity for a species, derived from a collection of genetic sequences of diverse populations. Advances in sequencing technologies have given rise to three primary methods for pangenome construction and analysis: de novo assembly and comparison, reference genome-based iterative assembly, and graph-based pangenome construction. Each method presents advantages and challenges in processing varying amounts and structures of DNA sequencing data. With the emergence of high-quality genome assemblies and advanced bioinformatic tools, the graph-based pangenome is emerging as an advanced reference for exploring the biological and functional implications of genetic variations.

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.

Importance of genetic architecture in marker selection decisions for genomic prediction

KEY MESSAGE

We demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on the genetic architecture of the trait. Breeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy, but it is highly dependent on the genetic architecture of the trait and the relative gain in accuracy is minimal. When SVs are the only causative variant type, 70% of the time SV predictors outperform SNP predictors. However, the improvement in accuracy in these instances is only 1.5% on average. Further simulations with predictors in varying degrees of LD with causative variants of different types (e.g., SNPs, SVs, SNPs and SVs) showed that prediction accuracy increased as linkage disequilibrium between causative variants and predictors increased regardless of the marker type. This study demonstrates that knowing the genetic architecture of a trait in deciding what markers to use in large-scale genomic prediction modeling in a breeding program is more important than what types of markers to use.

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.

The Progression in Developing Genomic Resources for Crop Improvement

Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis techniques.

Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals

Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.

Genetic Mapping, Candidate Gene Identification and Marker Validation for Host Plant Resistance to the Race 4 of Fusarium oxysporum f. sp. cubense Using Musa acuminata ssp. malaccensis

Fusarium wilt of banana is a devastating disease that has decimated banana production worldwide. Host resistance to Fusarium oxysporum f. sp. Cubense (Foc), the causal agent of this disease, is genetically dissected in this study using two Musa acuminata ssp. Malaccensis segregating populations, segregating for Foc Tropical (TR4) and Subtropical (STR4) race 4 resistance. Marker loci and trait association using 11 SNP-based PCR markers allowed the candidate region to be delimited to a 12.9 cM genetic interval corresponding to a 959 kb region on chromosome 3 of 'DH-Pahang' reference assembly v4. Within this region, there was a cluster of pattern recognition receptors, namely leucine-rich repeat ectodomain containing receptor-like protein kinases, cysteine-rich cell-wall-associated protein kinases, and leaf rust 10 disease-resistance locus receptor-like proteins, positioned in an interspersed arrangement. Their transcript levels were rapidly upregulated in the resistant progenies but not in the susceptible F₂ progenies at the onset of infection. This suggests that one or several of these genes may control resistance at this locus. To confirm the segregation of single-gene resistance, we generated an inter-cross between the resistant parent 'Ma850' and a susceptible line 'Ma848', to show that the STR4 resistance co-segregated with marker '28820' at this locus. Finally, an informative SNP marker 29730 allowed the locus-specific resistance to be assessed in a collection of diploid and polyploid banana plants. Of the 60 lines screened, 22 lines were predicted to carry resistance at this locus, including lines known to be TR4-resistant, such as 'Pahang', 'SH-3362', 'SH-3217', 'Ma-ITC0250', and 'DH-Pahang/CIRAD 930'. Additional screening in the International Institute for Tropical Agriculture's collection suggests that the dominant allele is common among the elite 'Matooke' NARITA hybrids, as well as in other triploid or tetraploid hybrids derived from East African highland bananas. Fine mapping and candidate gene identification will allow characterization of molecular mechanisms underlying the TR4 resistance. The markers developed in this study can now aid the marker-assisted selection of TR4 resistance in breeding programs around the world.

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.

Resequencing of durian genomes reveals large genetic variations among different cultivars

Durian (Durio zibethinus), which yields the fruit known as the "King of Fruits," is an important economic crop in Southeast Asia. Several durian cultivars have been developed in this region. In this study, we resequenced the genomes of three popular durian cultivars in Thailand, including Kradumthong (KD), Monthong (MT), and Puangmanee (PM) to investigate genetic diversities of cultivated durians. KD, MT, and PM genome assemblies were 832.7, 762.6, and 821.6 Mb, and their annotations covered 95.7, 92.4, and 92.7% of the embryophyta core proteins, respectively. We constructed the draft durian pangenome and analyzed comparative genomes with related species in Malvales. Long terminal repeat (LTR) sequences and protein families in durian genomes had slower evolution rates than that in cotton genomes. However, protein families with transcriptional regulation function and protein phosphorylation function involved in abiotic and biotic stress responses appeared to evolve faster in durians. The analyses of phylogenetic relationships, copy number variations (CNVs), and presence/absence variations (PAVs) suggested that the genome evolution of Thai durians was different from that of the Malaysian durian, Musang King (MK). Among the three newly sequenced genomes, the PAV and CNV profiles of disease resistance genes and the expressions of methylesterase inhibitor domain containing genes involved in flowering and fruit maturation in MT were different from those in KD and PM. These genome assemblies and their analyses provide valuable resources to gain a better understanding of the genetic diversity of cultivated durians, which may be useful for the future development of new durian cultivars.

Identification of a Major QTL-Controlling Resistance to the Subtropical Race 4 of Fusarium oxysporum f. sp. cubense in Musa acuminata ssp. malaccensis

Vascular wilt caused by the ascomycete fungal pathogen Fusarium oxysporum f. sp. cubense (Foc) is a major constraint of banana production around the world. The virulent race, namely Tropical Race 4, can infect all Cavendish-type banana plants and is now widespread across the globe, causing devastating losses to global banana production. In this study, we characterized Foc Subtropical Race 4 (STR4) resistance in a wild banana relative which, through estimated genome size and ancestry analysis, was confirmed to be Musa acuminata ssp. malaccensis. Using a self-derived F₂ population segregating for STR4 resistance, quantitative trait loci sequencing (QTL-seq) was performed on bulks consisting of resistant and susceptible individuals. Changes in SNP index between the bulks revealed a major QTL located on the distal end of the long arm of chromosome 3. Multiple resistance genes are present in this region. Identification of chromosome regions conferring resistance to Foc can facilitate marker assisted selection in breeding programs and paves the way towards identifying genes underpinning resistance.

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.

A pangenome analysis pipeline provides insights into functional gene identification in rice

BACKGROUND

A pangenome aims to capture the complete genetic diversity within a species and reduce bias in genetic analysis inherent in using a single reference genome. However, the current linear format of most plant pangenomes limits the presentation of position information for novel sequences. Graph pangenomes have been developed to overcome this limitation. However, bioinformatics analysis tools for graph format genomes are lacking.

RESULTS

To overcome this problem, we develop a novel strategy for pangenome construction and a downstream pangenome analysis pipeline (PSVCP) that captures genetic variants' position information while maintaining a linearized layout. Using PSVCP, we construct a high-quality rice pangenome using 12 representative rice genomes and analyze an international rice panel with 413 diverse accessions using the pangenome as the reference. We show that PSVCP successfully identifies causal structural variations for rice grain weight and plant height. Our results provide insights into rice population structure and genomic diversity. We characterize a new locus (qPH8-1) associated with plant height on chromosome 8 undetected by the SNP-based genome-wide association study (GWAS).

CONCLUSIONS

Our results demonstrate that the pangenome constructed by our pipeline combined with a presence and absence variation-based GWAS can provide additional power for genomic and genetic analysis. The pangenome constructed in this study and the associated genome sequence and genetic variants data provide valuable genomic resources for rice genomics research and improvement in future.

Investigating Pangenome Graphs Using Wheat Panache

Pangenome graphs quickly become the central data structure representing the diversity of variation we see across related genomes. Pangenome graphs have been published for some species, including plants of agronomic interest. However, visualizing these graphs is not easy as the graphs are large, and variants within these graphs are complex. Tools are needed to visualize graph data structures. Here, we present a workflow to search and visualize a wheat pangenome graph using Wheat Panache. The approach presented assists researchers interested in wheat genomics.

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.

Wheat Panache: A pangenome graph database representing presence-absence variation across sixteen bread wheat genomes

Bread wheat (Triticum aestivum L.) is one of humanity's most important staple crops, characterized by a large and complex genome with a high level of gene presence-absence variation (PAV) between cultivars, hampering genomic approaches for crop improvement. With the growing global population and the increasing impact of climate change on crop yield, there is an urgent need to apply genomic approaches to accelerate wheat breeding. With recent advances in DNA sequencing technology, a growing number of high-quality reference genomes are becoming available, reflecting the genetic content of a diverse range of cultivars. However, information on the presence or absence of genomic regions has been hard to visualize and interrogate because of the size of these genomes and the lack of suitable bioinformatics tools. To address this limitation, we have produced a wheat pangenome graph maintained within an online database to facilitate interrogation and comparison of wheat cultivar genomes. The database allows users to visualize regions of the pangenome to assess PAV between bread wheat genomes.

The Musa troglodytarum L. genome provides insights into the mechanism of non-climacteric behaviour and enrichment of carotenoids

BACKGROUND

Karat (Musa troglodytarum L.) is an autotriploid Fe'i banana of the Australimusa section. Karat was domesticated independently in the Pacific region, and karat fruit are characterized by a pink sap, a deep yellow-orange flesh colour, and an abundance of β-carotene. Karat fruit showed non-climacteric behaviour, with an approximately 215-day bunch filling time. These features make karat a valuable genetic resource for studying the mechanisms underlying fruit development and ripening and carotenoid biosynthesis.

RESULTS

Here, we report the genome of M. troglodytarum, which has a total length of 603 Mb and contains 37,577 predicted protein-coding genes. After divergence from the most recent common ancestors, M. troglodytarum (T genome) has experienced fusion of ancestral chromosomes 8 and 9 and multiple translocations and inversions, unlike the high synteny with few rearrangements found among M. schizocarpa (S genome), M. acuminata (A genome) and M. balbisiana (B genome). Genome microsynteny analysis showed that the triplication of MtSSUIIs due to chromosome rearrangement may lead to the accumulation of carotenoids and ABA in the fruit. The expression of duplicated MtCCD4s is repressed during ripening, leading to the accumulation of α-carotene, β-carotene and phytoene. Due to a long terminal repeat (LTR)-like fragment insertion upstream of MtERF11, karat cannot produce large amounts of ethylene but can produce ABA during ripening. These lead to non-climacteric behaviour and prolonged shelf-life, which contributes to an enrichment of carotenoids and riboflavin.

CONCLUSIONS

The high-quality genome of M. troglodytarum revealed the genomic basis of non-climacteric behaviour and enrichment of carotenoids, riboflavin, flavonoids and free galactose and provides valuable resources for further research on banana domestication and breeding and the improvement of nutritional and bioactive qualities.

Genomic and Bioinformatic Resources for Perennial Fruit Species

In the post-genomic era, data management and development of bioinformatic tools are critical for the adequate exploitation of genomics data. In this review, we address the actual situation for the subset of crops represented by the perennial fruit species. The agronomical singularity of these species compared to plant and crop model species provides significant challenges on the implementation of good practices generally not addressed in other species. Studies are usually performed over several years in non-controlled environments, usage of rootstock is common, and breeders heavily rely on vegetative propagation. A reference genome is now available for all the major species as well as many members of the economically important genera for breeding purposes. Development of pangenome for these species is beginning to gain momentum which will require a substantial effort in term of bioinformatic tool development. The available tools for genome annotation and functional analysis will also be presented.

Genome Assembly and Analysis of the Flavonoid and Phenylpropanoid Biosynthetic Pathways in Fingerroot Ginger (Boesenbergia rotunda)

Boesenbergia rotunda (Zingiberaceae), is a high-value culinary and ethno-medicinal plant of Southeast Asia. The rhizomes of this herb have a high flavanone and chalcone content. Here we report the genome analysis of B. rotunda together with a complete genome sequence as a hybrid assembly. B. rotunda has an estimated genome size of 2.4 Gb which is assembled as 27,491 contigs with an N50 size of 12.386 Mb. The highly heterozygous genome encodes 71,072 protein-coding genes and has a 72% repeat content, with class I TEs occupying ~67% of the assembled genome. Fluorescence in situ hybridization of the 18 chromosome pairs at the metaphase showed six sites of 45S rDNA and two sites of 5S rDNA. An SSR analysis identified 238,441 gSSRs and 4604 EST-SSRs with 49 SSR markers common among related species. Genome-wide methylation percentages ranged from 73% CpG, 36% CHG and 34% CHH in the leaf to 53% CpG, 18% CHG and 25% CHH in the embryogenic callus. Panduratin A biosynthetic unigenes were most highly expressed in the watery callus. B rotunda has a relatively large genome with a high heterozygosity and TE content. This assembly and data (PRJNA71294) comprise a source for further research on the functional genomics of B. rotunda, the evolution of the ginger plant family and the potential genetic selection or improvement of gingers.

Genetic and Genomic Resources for Soybean Breeding Research

Soybean (Glycine max) is a legume species of significant economic and nutritional value. The yield of soybean continues to increase with the breeding of improved varieties, and this is likely to continue with the application of advanced genetic and genomic approaches for breeding. Genome technologies continue to advance rapidly, with an increasing number of high-quality genome assemblies becoming available. With accumulating data from marker arrays and whole-genome resequencing, studying variations between individuals and populations is becoming increasingly accessible. Furthermore, the recent development of soybean pangenomes has highlighted the significant structural variation between individuals, together with knowledge of what has been selected for or lost during domestication and breeding, information that can be applied for the breeding of improved cultivars. Because of this, resources such as genome assemblies, SNP datasets, pangenomes and associated databases are becoming increasingly important for research underlying soybean crop improvement.

Comparative plastome analysis of Musaceae and new insights into phylogenetic relationships

Background

Musaceae is an economically important family consisting of 70-80 species. Elucidation of the interspecific relationships of this family is essential for a more efficient conservation and utilization of genetic resources for banana improvement. However, the scarcity of herbarium specimens and quality molecular markers have limited our understanding of the phylogenetic relationships in wild species of Musaceae. Aiming at improving the phylogenetic resolution of Musaceae, we analyzed a comprehensive set of 49 plastomes for 48 species/subspecies representing all three genera of this family.

Results

Musaceae plastomes have a relatively well-conserved genomic size and gene content, with a full length ranging from 166,782 bp to 172,514 bp. Variations in the IR borders were found to show phylogenetic signals to a certain extent in Musa. Codon usage bias analysis showed different preferences for the same codon between species and three genera and a common preference for A/T-ending codons. Among the two genes detected under positive selection (dN/dS > 1), ycf2 was indicated under an intensive positive selection. The divergent hotspot analysis allowed the identification of four regions (ndhF-trnL, ndhF, matK-rps16, and accD) as specific DNA barcodes for Musaceae species.

Bayesian and maximum likelihood phylogenetic analyses using full plastome resulted in nearly identical tree topologies with highly supported relationships between species. The monospecies genus Musella is sister to Ensete, and the genus Musa was divided into two large clades, which corresponded well to the basic number of n = x = 11 and n = x =10/9/7, respectively. Four subclades were divided within the genus Musa. A dating analysis covering the whole Zingiberales indicated that the divergence of Musaceae family originated in the Palaeocene (59.19 Ma), and the genus Musa diverged into two clades in the Eocene (50.70 Ma) and then started to diversify from the late Oligocene (29.92 Ma) to the late Miocene. Two lineages (Rhodochlamys and Australimusa) radiated recently in the Pliocene /Pleistocene periods.

Conclusions

The plastome sequences performed well in resolving the phylogenetic relationships of Musaceae and generated new insights into its evolution. Plastome sequences provided valuable resources for population genetics and phylogenetics at lower taxon.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08454-3.

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.

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.

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.

Panache: a Web Browser-Based Viewer for Linearized Pangenomes

Motivation

Pangenomics evolved since its first applications on bacteria, extending from the study of genes for a given population to the study of all of its sequences available. While multiple methods are being developed to construct pangenomes in eukaryotic species there is still a gap for efficient and user-friendly visualization tools. Emerging graph representations come with their own challenges, and linearity remains a suitable option for user-friendliness.

Results

We introduce Panache, a tool for the visualization and exploration of linear representations of gene-based and sequence-based pangenomes. It uses a layout similar to genome browsers to display presence absence variations and additional tracks along a linear axis with a pangenomics perspective.

Availability and implementation

Panache is available at github.com/SouthGreenPlatform/panache under the MIT License.