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

Scaling metabolic model reconstruction up to the pan-genome level: A systematic review and prospective applications to photosynthetic organisms

Advances in genomics technologies have generated large data sets that provide tremendous insights into the genetic diversity of taxonomic groups. However, it remains challenging to pinpoint the effect of genetic diversity on different traits without performing resource-intensive phenotyping experiments. Pan-genome-scale metabolic models (panGEMs) extend traditional genome-scale metabolic models by considering the entire reaction repertoire that enables the prediction and comparison of metabolic capabilities within a taxonomic group. Here, we systematically review the state-of-the-art methodologies for constructing panGEMs, focusing on used tools, databases, experimental datasets, and orthology relationships. We highlight the unique advantages of panGEMs compared to single-species GEMs in predicting metabolic phenotypes and in guiding the experimental validation of genome annotations. In addition, we emphasize the disparity between the available (pan-)genomic data on photosynthetic organisms and their under-representation in current (pan)GEMs. Finally, we propose a perspective for tackling the reconstruction of panGEMs for photosynthetic eukaryotes that can help advance our understanding of the metabolic diversity in this taxonomic group.

RNA signaling in medicinal plants: An overlooked mechanism for phytochemical regulation

Background/objective

Medicinal plants are invaluable sources of bioactive phytochemicals critical for global health. This mini review explores the role of RNA signaling in regulating phytochemical production in medicinal plants, highlighting its potential for optimizing their therapeutic potential.

Methods

This mini review integrates insights from recent studies published in Scopus and Web of Science (2019-2025) on RNA-mediated signaling, including small RNAs (sRNAs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs).

Results

RNA signaling is revealed as a pivotal mechanism in secondary metabolite regulation, mediating stress-induced compound synthesis and environmental interactions. Notable findings include the role of siRNAs in activating alkaloid pathways and lncRNAs in regulating phenolic compound biosynthesis. RNA-directed DNA methylation and systemic RNA signaling further highlight its versatility in phytochemical regulation.

Conclusion

RNA signaling enhances medicinal plant research, unlocking therapeutic potential through bioactive compound production. The study calls for focused research to bridge knowledge gaps and translate laboratory findings into field applications.

Application and Progress of Genomics in Deciphering the Genetic Regulation Mechanisms of Plant Secondary Metabolites

This review aims to systematically dissect the genetic regulatory mechanisms of plant secondary metabolites in the era of genomics, while comprehensively summarizing the progress and potential impact of genomics in plant secondary metabolism research. By integrating methodologies such as high-throughput sequencing, structural genomics, comparative genomics, and functional genomics, we elucidate the principles underlying plant secondary metabolism and identify functional genes. The application of these technologies has deepened our understanding of secondary metabolic pathways and driven advancements in plant molecular genetics and genomics. The development of genomics has enabled scientists to gain profound insights into the biosynthetic pathways of secondary metabolites in plants such as ginseng (Panax ginseng) and grapevine (Vitis vinifera), while offering novel possibilities for precise regulation of these pathways. Despite remarkable progress in studying the genetic regulation of plant secondary metabolites, significant challenges persist. Future research must focus on integrating multi-omics data, developing advanced bioinformatics tools, and exploring effective genetic improvement strategies to fully harness the medicinal potential of plants and enhance their capacity to synthesize secondary metabolites.

Pan-Genome-Based Characterization of the SRS Transcription Factor Family in Foxtail Millet

The Short Internodes-Related Sequence (SRS) family, a class of plant-specific transcription factors crucial for diverse biological processes, was systematically investigated in foxtail millet using pan-genome data from 110 core germplasm resources as well as two high-quality genomes (xm and Yu1). We identified SRS members and analyzed their intra-species distribution patterns, including copy number variation (CNV) and interchromosomal translocations. A novel standardized nomenclature (Accession_SiSRSN[.n]_xDy or xTy) was proposed to unify gene family nomenclature, enabling the direct visualization of member number variation across germplasms and the identification of core/variable members while highlighting chromosomal translocations. Focusing on the two high-quality genomes, both harboring six core SRS members, we performed whole-genome collinearity analysis with Arabidopsis, rice, maize, soybean, and green foxtail. Ka/Ks analysis of collinear gene pairs revealed purifying selection acting on SiSRS genes. Promoter analysis identified abundant stress-responsive cis-elements. Among core members, the xm_SiSRS5 gene exhibited the highest expression during vegetative growth but showed significant downregulation under drought and salt stress, suggesting its role as a key negative regulator in abiotic stress responses. This study demonstrates the utility of pan-genomics in resolving gene family dynamics and establishes SiSRS5 as a critical target for stress tolerance engineering in foxtail millet.

Research Progress of Genomics Applications in Secondary Metabolites of Medicinal Plants: A Case Study in Safflower

Medicinal plants, recognized as significant natural resources, have gained prominence in response to the increasing global demand for herbal medicines, necessitating the large-scale production of these plants and their derivatives. Medicinal plants are exposed to a variety of internal and external factors that interact to influence the biosynthesis and accumulation of secondary metabolites. With the rapid development of omics technologies such as genomics, transcriptomics, proteomics, and metabolomics, multi-omics technologies have become important tools for revealing the complexity and functionality of organisms. They are conducive to further uncovering the biological activities of secondary metabolites in medicinal plants and clarifying the molecular mechanisms underlying the production of secondary metabolites. Also, artificial intelligence (AI) technology accelerates the comprehensive utilization of high-dimensional datasets and offers transformative potential for multi-omics analysis. However, there is currently no systematic review summarizing the genomic mechanisms of secondary metabolite biosynthesis in medicinal plants. Safflower (Carthamus tinctorius L.) has rich and diverse bioactive flavonoids, among of which Hydroxysafflor yellow A (HSYA) is specific to safflower and emerging as a potential medication for treating a wide range of diseases. Hence, significant progress has been made in the study of safflower as an excellent example for the regulation of secondary metabolites in medicinal plants in recent years. Here, we review the progress on the understanding of the regulation of main secondary metabolites at the multi-omics level, and summarize the influence of various factors on their types and contents, with a particular focus on safflower flavonoids. This review aims to provide a comprehensive insight into the regulatory mechanisms of secondary metabolite biosynthesis from the perspective of genomics.

Comprehensive Analysis of Ghd7 Variations Using Pan-Genomics and Prime Editing in Rice

The Ghd7 gene in rice plays a crucial role in determining heading date, plant height, and grain yield. However, the variations in Ghd7 and their functional implications across different rice accessions are not fully understood. Based on the release of a large amount of rice genome data in recent years, we investigated Ghd7 through pan-genome analysis of 372 diverse rice varieties and figured out the structural variations (SVs) in the Ghd7 locus. However, due to the high cost of pan-genomes, most genomes are based on next-generation sequencing (NGS) data now. Therefore, we developed a method for identifying SVs using NGS data and Polymerase Chain Reaction (PCR) based on the results of pan-genome analysis and identified 977 accessions carrying such SVs of Ghd7. Furthermore, we identified 46 single-nucleotide polymorphisms (SNPs) and one insertion-deletion (InDel) in the coding region of Ghd7. They are classified into 49 haplotypes. Notably, a splice-site mutation in haplotype H6 causes aberrant mRNA splicing. Using prime editing (PE) technology, we successfully restored the functional of Ghd7 in Yixiang 1B (YX1B), delaying the heading date by approximately 16 days. This modification synchronized the heading date between YX1B and the restorer line Yahui 2115 (YH2115R), enhancing the hybrid rice seed production efficiency. In conclusion, our findings highlight the potential of integrating pan-genomics and precision gene editing to accelerate crop improvement and enhance agronomic traits.

PlantPan: A comprehensive multi-species plant pan-genome database

The pan-genome represents the complete genomic diversity of specific species, serving as a valuable resource for studying species evolution, crop domestication, and guiding crop breeding and improvement. While there are several single-species-specific plant pan-genome databases, the availability of multi-species pan-genome databases is limited. Additionally, variations in methods and data types used for plant pan-genome analysis across different databases hinder the comparison and integration of pan-genome information from various projects at multi-species or single-species levels. To tackle this challenge, we introduce PlantPan, a comprehensive database housing the results of pan-genome analysis for 195 genomes from 11 plant species. PlantPan aims to provide extensive information, including gene-centric and sequence-centric pan-genome information, graph-based pan-genome, pan-genome openness profiles, gene functions and its variation characteristics, homologous genes, and gene clusters across different species. Statistically, PlantPan incorporates 9 163 011 genes, 694 191 gene clusters, 526 973 370 genome variations, and 1 616 089 non-redundant genome variation groups at the species level, 33 455,098 genome synteny, and 177 827 non-redundant genome synteny groups at the species level. Regarding functional genes, PlantPan contains 5 222 720 genes related to transcription factors, 395 247 literature-reported resistance genes, 455 748 predicted microbial/disease resistance genes, and 1 612 112 genes related to molecular pathways. In summary, PlantPan is a vital platform for advancing the application of pan-genomes in molecular breeding for crops and evolutionary research for plants.

Guidelines for gene and genome assembly nomenclature

The rapid increase in the number of reference-quality genome assemblies presents significant new opportunities for genomic research. However, the absence of standardized naming conventions for genome assemblies and annotations across datasets creates substantial challenges. Inconsistent naming hinders the identification of correct assemblies, complicates the integration of bioinformatics pipelines, and makes it difficult to link assemblies across multiple resources. To address this, we developed a specification for standardizing the naming of reference genome assemblies, to improve consistency across datasets and facilitate interoperability. This specification was created with FAIR (Findable, Accessible, Interoperable, and Reusable) practices in mind, ensuring that reference assemblies are easier to locate, access, and reuse across research communities. Additionally, it has been designed to comply with primary genomic data repositories, including members of the International Nucleotide Sequence Database Collaboration consortium, ensuring compatibility with widely used databases. While initially tailored to the agricultural genomics community, the specification is adaptable for use across different taxa. Widespread adoption of this standardized nomenclature would streamline assembly management, better enable cross-species analyses, and improve the reproducibility of research. It would also enhance natural language processing applications that depend on consistent reference assembly names in genomic literature, promoting greater integration and automated analysis of genomic data. This is a good time to consider more consistent genomic data nomenclature as many research communities and data resources are now finding themselves juggling multiple datasets from multiple data providers.

The evolution, variation and expression patterns of the annexin gene family in the maize pan-genome

Annexins (Anns) are a family of evolutionarily conserved, calcium-dependent, phospholipid-binding proteins that play critical roles in plant growth, development, and stress responses. Utilizing the pan-genome of 26 high-quality maize genomes, we identified 12 Ann genes, comprising 9 core genes (present in all 26 lines) and 3 near-core genes (present in 24-25 lines). This highlights the limitations of studying ZmAnn genes based on a single reference genome. Evaluating the Ka/Ks values of Ann genes in 26 varieties revealed that ZmAnn10 was under positive selection in certain varieties, while the remaining genes had Ka/Ks values less than 1, indicating purifying selection. Phylogenetic analysis divided ZmAnn proteins into six groups, with group VI containing only ZmAnn12. Structural variation in certain varieties altered the conserved domains, generating many atypical genes. Transcriptome analysis showed that different Ann members have distinct expression patterns in various tissues and under different abiotic and biotic stress treatments. Weighted gene co-expression network analysis of transcriptome data from various maize tissues under cold stress identified four Ann genes (ZmAnn2, ZmAnn6, ZmAnn7, ZmAnn9) involved in co-expression modules. Overall, this study utilized high-quality maize pangenomes to perform a bioinformatic analysis of ZmAnn genes, providing a foundation for further research on ZmAnn genes.

The developments and prospects of plant super-pangenomes: Demands, approaches, and applications

By integrating genomes from different accessions, pangenomes provide a more comprehensive and reference-bias-free representation of genetic information within a population compared to a single reference genome. With the rapid accumulation of genomic sequencing data and the expanding scope of plant research, plant pangenomics has gradually evolved from single-species to multi-species studies. This shift has given rise to the concept of a super-pangenome that covers all genomic sequences within a genus-level taxonomic group. By incorporating both cultivated and wild species, the super-pangenome has greatly enhanced the resolution of research in various areas such as plant genetic diversity, evolution, domestication, and molecular breeding. In this review, we present a comprehensive overview of the plant super-pangenome, emphasizing its development requirements, construction strategies, potential applications, and notable achievements. We also highlight the distinctive advantages and promising prospects of super-pangenomes while addressing current challenges and future directions.

The role of pangenomics in orphan crop improvement

Global food security depends heavily on a few staple crops, while orphan crops, despite being less studied, offer the potential benefits of environmental adaptation and enhanced nutritional traits, especially in a changing climate. Major crops have benefited from genomics-based breeding, initially using single genomes and later pangenomes. Recent advances in DNA sequencing have enabled pangenome construction for several orphan crops, offering a more comprehensive understanding of genetic diversity. Orphan crop research has now entered the pangenomics era and applying these pangenomes with advanced selection methods and genome editing technologies can transform these neglected species into crops of broader agricultural significance.

A population genomics approach to unlock the genetic potential of lablab (Lablab purpureus (L.) Sweet), an underutilized tropical forage crop

BACKGROUND

Lablab is one of the conventionally grown multi-purpose crops that originated in Africa. It is an annual or short-lived perennial forage legume which has versatile uses (as a vegetable and dry seeds, as food or feed, or as green manure) but is yet to receive adequate research attention and hence remains underexploited. To develop new and highly productive lablab varieties, using genomics-assisted selection, the present study aimed to identify quantitative trait loci associated with agronomically important traits in lablab and to assess the stability of these traits across two different agro-ecologies in Ethiopia. Here, we resequenced one hundred and forty-two lablab accessions, utilised whole genome genotyping approaches, and conducted multi-locational phenotyping over two years.

RESULTS

The selected lablab accessions displayed significant agro-morphological variation in eight analysed traits, including plant height, total fresh weight, and total dry weight. Furthermore, the agronomic performance of the accessions was significantly different across locations and years, highlighting substantial genotype-by-environment interactions. The population genetic structure of the lablab accessions, based on ~ 500,000 informative single nucleotide polymorphisms (SNPs), revealed an independent domestication pattern for two-seeded and four-seeded lablab accessions. Finally, based on multi-environmental trial data, a genome-wide association study (GWAS) identified useful SNPs and k-mers for key traits, such as plant height and total dry weight.

CONCLUSIONS

The publicly available genomic tools and field evaluation data from this study will offer a valuable resource for plant breeders and researchers to inform a new cycle of lablab breeding. With the aid of these tools, the breeding cycle will be significantly reduced and livestock farmers will have access to improved lablab varieties in a shorter time-frame.

New perspectives of post-GWAS analyses: From markers to causal genes for more precise crop breeding

Crop breeding advancement is hindered by the imperfection of methods to reveal genes underlying key traits. Genome-wide Association Study (GWAS) is one such method, identifying genomic regions linked to phenotypes. Post-GWAS analyses predict candidate genes and assist in causative mutation (CM) recognition. Here, we assess post-GWAS approaches, address limitations in omics data integration and stress the importance of evaluating associated variants within a broader context of publicly available datasets. Recent advances in bioinformatics tools and genomic strategies for CM identification and allelic variation exploration are reviewed. We discuss the role of markers and marker panel development for more precise breeding. Finally, we highlight the perspectives and challenges of GWAS-based CM prediction for complex quantitative traits.

Genomic variation of 363 diverse tea accessions unveils the genetic diversity, domestication, and structural variations associated with tea adaptation

Domestication has shaped the population structure and agronomic traits of tea plants, yet the complexity of tea population structure and genetic variation that determines these traits remains unclear. We here investigated the resequencing data of 363 diverse tea accessions collected extensively from almost all tea distributions and found that the population structure of tea plants was divided into eight subgroups, which were basically consistent with their geographical distributions. The genetic diversity of tea plants in China decreased from southwest to east as latitude increased. Results also indicated that Camellia sinensis var. assamica (CSA) illustrated divergent selection signatures with Camellia sinensis var. sinensis (CSS). The domesticated genes of CSA were mainly involved in leaf development, flavonoid and alkaloid biosynthesis, while the domesticated genes in CSS mainly participated in amino acid metabolism, aroma compounds biosynthesis, and cold stress. Comparative population genomics further identified ~730 Mb novel sequences, generating 6,058 full-length protein-encoding genes, significantly expanding the gene pool of tea plants. We also discovered 217,376 large-scale structural variations and 56,583 presence and absence variations (PAVs) across diverse tea accessions, some of which were associated with tea quality and stress resistance. Functional experiments demonstrated that two PAV genes (CSS0049975 and CSS0006599) were likely to drive trait diversification in cold tolerance between CSA and CSS tea plants. The overall findings not only revealed the genetic diversity and domestication of tea plants, but also underscored the vital role of structural variations in the diversification of tea plant traits.

A Haplotype-resolved, Chromosome-scale Genome for Malus domestica Borkh. 'WA 38'

Genome sequencing for agriculturally important Rosaceous crops has made rapid progress both in completeness and annotation quality. Whole genome sequence and annotation gives breeders, researchers, and growers information about cultivar specific traits such as fruit quality and disease resistance, and informs strategies to enhance postharvest storage. Here we present a haplotype-phased, chromosomal level genome of Malus domestica, 'WA 38', a new apple cultivar released to market in 2017 as Cosmic Crisp®. Using both short and long read sequencing data with a k-mer based approach, chromosomes originating from each parent were assembled and segregated. This is the first pome fruit genome fully phased into parental haplotypes in which chromosomes from each parent are identified and separated into their unique, respective haplomes. The two haplome assemblies, 'Honeycrisp' originated HapA and 'Enterprise' originated HapB, are about 650 Megabases each, and both have a BUSCO score of 98.7% complete. A total of 53,028 and 54,235 genes were annotated from HapA and HapB, respectively. Additionally, we provide genome-scale comparisons to 'Gala', 'Honeycrisp', and other relevant cultivars highlighting major differences in genome structure and gene family circumscription. This assembly and annotation was done in collaboration with the American Campus Tree Genomes project that includes 'WA 38' (Washington State University), 'd'Anjou' pear (Auburn University), and many more. To ensure transparency, reproducibility, and applicability for any genome project, our genome assembly and annotation workflow is recorded in detail and shared under a public GitLab repository. All software is containerized, offering a simple implementation of the workflow.

Engineering the future cereal crops with big biological data: toward intelligence-driven breeding by design

How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades, especially under an unpredicted climate change. Crop breeding, initiating from the phenotype-based selection by local farmers and developing into current biotechnology-based breeding, has played a critical role in securing the global food supply. However, regarding the changing environment and ever-increasing human population, can we breed outstanding crop varieties fast enough to achieve high productivity, good quality, and widespread adaptability? This review outlines the recent achievements in understanding cereal crop breeding, including the current knowledge about crop agronomic traits, newly developed techniques, crop big biological data research, and the possibility of integrating them for intelligence-driven breeding by design, which ushers in a new era of crop breeding practice and shapes the novel architecture of future crops. This review focuses on the major cereal crops, including rice, maize, and wheat, to explain how intelligence-driven breeding by design is becoming a reality.

Transcriptomics and metabolomics analyses provide insights into resistance genes of tree ferns

As ancient organisms, tree ferns play a crucial role as an evolutionary bridge between lower and higher plant species, providing various utilitarian benefits. However, they face challenges such as overexploitation, climate change, adverse environmental conditions, and insect pests, resulting in conservation concerns. In this study, we provide an overview of metabolic and transcriptomic resources of leaves in two typical tree ferns, A. spinulosa and A. metteniana, and explore the resistance genes for the first time. The landscape of metabolome showed that the compound skimmin may hold medicinal significance. A total of 111 differentially accumulated metabolites (DAMs) were detected, with pathway enrichment analysis highlighting 14 significantly enriched pathways, including 2-oxocarboxylic acid metabolism possibly associated with environmental adaptations. A total of 14,639 differentially expressed genes (DEGs) were found, among which 606 were resistance (R) genes. We identified BAM1 as a significantly differentially expressed R gene, which is one of the core genes within the R gene interaction network. Both the maximum-likelihood phylogenetic tree and the PPI network revealed a close relationship between BAM1, FLS2, and TMK. Moreover, BAM1 showed a significant positive correlation with neochlorogenic acid and kaempferol-7-O-glucoside. These metabolites, known for their antioxidant and anti-inflammatory properties, likely play a crucial role in the defense response of tree ferns. This research provides valuable insights into the metabolic and transcriptomic differences between A. spinulosa and A. metteniana, enhancing our understanding of resistance genes in tree ferns.

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet

MAIN CONCLUSION

Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Comparative metabolomics combined with genome sequencing provides insights into novel wolfberry-specific metabolites and their formation mechanisms

Wolfberry (Lycium, of the family Solanaceae) has special nutritional benefits due to its valuable metabolites. Here, 16 wolfberry-specific metabolites were identified by comparing the metabolome of wolfberry with those of six species, including maize, rice, wheat, soybean, tomato and grape. The copy numbers of the riboflavin and phenyllactate degradation genes riboflavin kinase (RFK) and phenyllactate UDP-glycosyltransferase (UGT1) were lower in wolfberry than in other species, while the copy number of the phenyllactate synthesis gene hydroxyphenyl-pyruvate reductase (HPPR) was higher in wolfberry, suggesting that the copy number variation of these genes among species may be the main reason for the specific accumulation of riboflavin and phenyllactate in wolfberry. Moreover, the metabolome-based neighbor-joining tree revealed distinct clustering of monocots and dicots, suggesting that metabolites could reflect the evolutionary relationship among those species. Taken together, we identified 16 specific metabolites in wolfberry and provided new insight into the accumulation mechanism of species-specific metabolites at the genomic level.

PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome

Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG .

Plant genome information facilitates plant functional genomics

MAIN CONCLUSION

In this review, we give an overview of plant sequencing efforts and how this impacts plant functional genomics research. Plant genome sequence information greatly facilitates the studies of plant biology, functional genomics, evolution of genomes and genes, domestication processes, phylogenetic relationships, among many others. More than two decades of sequencing efforts have boosted the number of available sequenced plant genomes. The first plant genome, of Arabidopsis, was published in the year 2000 and currently, 4604 plant genomes from 1482 plant species have been published. Various large sequence initiatives are running, which are planning to produce tens of thousands of sequenced plant genomes in the near future. In this review, we give an overview on the status of sequenced plant genomes and on the use of genome information in different research areas.

GWAS supported by computer vision identifies large numbers of candidate regulators of in planta regeneration in Populus trichocarpa

Plant regeneration is an important dimension of plant propagation and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. Association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants; however, the performance of these methods depends on the accuracy and scale of phenotyping. To enable a large-scale GWAS of in planta callus and shoot regeneration in the model tree Populus, we developed a phenomics workflow involving semantic segmentation to quantify regenerating plant tissues over time. We found that the resulting statistics were of highly non-normal distributions, and thus employed transformations or permutations to avoid violating assumptions of linear models used in GWAS. We report over 200 statistically supported quantitative trait loci (QTLs), with genes encompassing or near to top QTLs including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. Our results encourage models of hormonal signaling during plant regeneration to consider keystone roles of stress-related signaling (e.g. involving jasmonates and salicylic acid), in addition to the auxin and cytokinin pathways commonly considered. The putative regulatory genes and biological processes we identified provide new insights into the biological complexity of plant regeneration, and may serve as new reagents for improving regeneration and transformation of recalcitrant genotypes and species.

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.

The Evolution, Expression Patterns, and Domestication Selection Analysis of the Annexin Gene Family in the Barley Pan-Genome

Plant annexins constitute a conserved protein family that plays crucial roles in regulating plant growth and development, as well as in responses to both biotic and abiotic stresses. In this study, a total of 144 annexin genes were identified in the barley pan-genome, comprising 12 reference genomes, including cultivated barley, landraces, and wild barley. Their chromosomal locations, physical-chemical characteristics, gene structures, conserved domains, and subcellular localizations were systematically analyzed to reveal the certain differences between wild and cultivated populations. Through a cis-acting element analysis, co-expression network, and large-scale transcriptome analysis, their involvement in growth, development, and responses to various stressors was highlighted. It is worth noting that HvMOREXann5 is only expressed in pistils and anthers, indicating its crucial role in reproductive development. Based on the resequencing data from 282 barley accessions worldwide, genetic variations in thefamily were investigated, and the results showed that 5 out of the 12 identified HvMOREXanns were affected by selection pressure. Genetic diversity and haplotype frequency showed notable reductions between wild and domesticated barley, suggesting that a genetic bottleneck occurred on the annexin family during the barley domestication process. Finally, qRT-PCR analysis confirmed the up-regulation of HvMOREXann7 under drought stress, along with significant differences between wild accessions and varieties. This study provides some insights into the genome organization and genetic characteristics of the annexin gene family in barley at the pan-genome level, which will contribute to better understanding its evolution and function in barley and other crops.

Genomic decoding of Theobroma grandiflorum (cupuassu) at chromosomal scale: evolutionary insights for horticultural innovation

BACKGROUND

Theobroma grandiflorum (Malvaceae), known as cupuassu, is a tree indigenous to the Amazon basin, valued for its large fruits and seed pulp, contributing notably to the Amazonian bioeconomy. The seed pulp is utilized in desserts and beverages, and its seed butter is used in cosmetics. Here, we present the sequenced telomere-to-telomere genome of cupuassu, disclosing its genomic structure, evolutionary features, and phylogenetic relationships within the Malvaceae family.

FINDINGS

The cupuassu genome spans 423 Mb, encodes 31,381 genes distributed in 10 chromosomes, and exhibits approximately 65% gene synteny with the Theobroma cacao genome, reflecting a conserved evolutionary history, albeit punctuated with unique genomic variations. The main changes are pronounced by bursts of long-terminal repeat retrotransposons at postspecies divergence, retrocopied and singleton genes, and gene families displaying distinctive patterns of expansion and contraction. Furthermore, positively selected genes are evident, particularly among retained and dispersed tandem and proximal duplicated genes associated with general fruit and seed traits and defense mechanisms, supporting the hypothesis of potential episodes of subfunctionalization and neofunctionalization following duplication, as well as impact from distinct domestication process. These genomic variations may underpin the differences observed in fruit and seed morphology, ripening, and disease resistance between cupuassu and the other Malvaceae species.

CONCLUSIONS

The cupuassu genome offers a foundational resource for both breeding improvement and conservation biology, yielding insights into the evolution and diversity within the genus Theobroma.

Deprivation of Sexual Reproduction during Garlic Domestication and Crop Evolution

Garlic, originating in the mountains of Central Asia, has undergone domestication and subsequent widespread introduction to diverse regions. Human selection for adaptation to various climates has resulted in the development of numerous garlic varieties, each characterized by specific morphological and physiological traits. However, this process has led to a loss of fertility and seed production in garlic crops. In this study, we conducted morpho-physiological and transcriptome analyses, along with whole-genome resequencing of 41 garlic accessions from different regions, in order to assess the variations in reproductive traits among garlic populations. Our findings indicate that the evolution of garlic crops was associated with mutations in genes related to vernalization and the circadian clock. The decline in sexual reproduction is not solely attributed to a few mutations in specific genes, but is correlated with extensive alterations in the genetic regulation of the annual cycle, stress adaptations, and environmental requirements. The regulation of flowering ability, stress response, and metabolism occurs at both the genetic and transcriptional levels. We conclude that the migration and evolution of garlic crops involve substantial and diverse changes across the entire genome landscape. The construction of a garlic pan-genome, encompassing genetic diversity from various garlic populations, will provide further insights for research into and the improvement of garlic crops.

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans' genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits' genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.

Selection of Flax Genotypes for Pan-Genomic Studies by Sequencing Tagmentation-Based Transcriptome Libraries

Flax (Linum usitatissimum L.) products are used in the food, pharmaceutical, textile, polymer, medical, and other industries. The creation of a pan-genome will be an important advance in flax research and breeding. The selection of flax genotypes that sufficiently cover the species diversity is a crucial step for the pan-genomic study. For this purpose, we have adapted a method based on Illumina sequencing of transcriptome libraries prepared using the Tn5 transposase (tagmentase). This approach reduces the cost of sample preparation compared to commercial kits and allows the generation of a large number of cDNA libraries in a short time. RNA-seq data were obtained for 192 flax plants (3-6 individual plants from 44 flax accessions of different morphology and geographical origin). Evaluation of the genetic relationship between flax plants based on the sequencing data revealed incorrect species identification for five accessions. Therefore, these accessions were excluded from the sample set for the pan-genomic study. For the remaining samples, typical genotypes were selected to provide the most comprehensive genetic diversity of flax for pan-genome construction. Thus, high-throughput sequencing of tagmentation-based transcriptome libraries showed high efficiency in assessing the genetic relationship of flax samples and allowed us to select genotypes for the flax pan-genomic analysis.

PanKmer: k-mer-based and reference-free pangenome analysis

SUMMARY

Pangenomes are replacing single reference genomes as the definitive representation of DNA sequence within a species or clade. Pangenome analysis predominantly leverages graph-based methods that require computationally intensive multiple genome alignments, do not scale to highly complex eukaryotic genomes, limit their scope to identifying structural variants (SVs), or incur bias by relying on a reference genome. Here, we present PanKmer, a toolkit designed for reference-free analysis of pangenome datasets consisting of dozens to thousands of individual genomes. PanKmer decomposes a set of input genomes into a table of observed k-mers and their presence-absence values in each genome. These are stored in an efficient k-mer index data format that encodes SNPs, INDELs, and SVs. It also includes functions for downstream analysis of the k-mer index, such as calculating sequence similarity statistics between individuals at whole-genome or local scales. For example, k-mers can be "anchored" in any individual genome to quantify sequence variability or conservation at a specific locus. This facilitates workflows with various biological applications, e.g. identifying cases of hybridization between plant species. PanKmer provides researchers with a valuable and convenient means to explore the full scope of genetic variation in a population, without reference bias.

AVAILABILITY AND IMPLEMENTATION

PanKmer is implemented as a Python package with components written in Rust, released under a BSD license. The source code is available from the Python Package Index (PyPI) at https://pypi.org/project/pankmer/ as well as Gitlab at https://gitlab.com/salk-tm/pankmer. Full documentation is available at https://salk-tm.gitlab.io/pankmer/.

Exploring Pan-Genomes: An Overview of Resources and Tools for Unraveling Structure, Function, and Evolution of Crop Genes and Genomes

The availability of multiple sequenced genomes from a single species made it possible to explore intra- and inter-specific genomic comparisons at higher resolution and build clade-specific pan-genomes of several crops. The pan-genomes of crops constructed from various cultivars, accessions, landraces, and wild ancestral species represent a compendium of genes and structural variations and allow researchers to search for the novel genes and alleles that were inadvertently lost in domesticated crops during the historical process of crop domestication or in the process of extensive plant breeding. Fortunately, many valuable genes and alleles associated with desirable traits like disease resistance, abiotic stress tolerance, plant architecture, and nutrition qualities exist in landraces, ancestral species, and crop wild relatives. The novel genes from the wild ancestors and landraces can be introduced back to high-yielding varieties of modern crops by implementing classical plant breeding, genomic selection, and transgenic/gene editing approaches. Thus, pan-genomic represents a great leap in plant research and offers new avenues for targeted breeding to mitigate the impact of global climate change. Here, we summarize the tools used for pan-genome assembly and annotations, web-portals hosting plant pan-genomes, etc. Furthermore, we highlight a few discoveries made in crops using the pan-genomic approach and future potential of this emerging field of study.

Application of Multi-Perspectives in Tea Breeding and the Main Directions

Tea plants are an economically important crop and conducting research on tea breeding contributes to enhancing the yield and quality of tea leaves as well as breeding traits that satisfy the requirements of the public. This study reviews the current status of tea plants germplasm resources and their utilization, which has provided genetic material for the application of multi-omics, including genomics and transcriptomics in breeding. Various molecular markers for breeding were designed based on multi-omics, and available approaches in the direction of high yield, quality and resistance in tea plants breeding are proposed. Additionally, future breeding of tea plants based on single-cellomics, pangenomics, plant-microbe interactions and epigenetics are proposed and provided as references. This study aims to provide inspiration and guidance for advancing the development of genetic breeding in tea plants, as well as providing implications for breeding research in other crops.

Opportunities and Challenges of In Vitro Tissue Culture Systems in the Era of Crop Genome Editing

Currently, the development of genome editing (GE) tools has provided a wide platform for targeted modification of plant genomes. However, the lack of versatile DNA delivery systems for a large variety of crop species has been the main bottleneck for improving crops with beneficial traits. Currently, the generation of plants with heritable mutations induced by GE tools mostly goes through tissue culture. Unfortunately, current tissue culture systems restrict successful results to only a limited number of plant species and genotypes. In order to release the full potential of the GE tools, procedures need to be species and genotype independent. This review provides an in-depth summary and insights into the various in vitro tissue culture systems used for GE in the economically important crops barley, wheat, rice, sorghum, soybean, maize, potatoes, cassava, and millet and uncovers new opportunities and challenges of already-established tissue culture platforms for GE in the crops.

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.

CRISPR/Cas9-Mediated Enrichment Coupled to Nanopore Sequencing Provides a Valuable Tool for the Precise Reconstruction of Large Genomic Target Regions

Complete and accurate identification of genetic variants associated with specific phenotypes can be challenging when there is a high level of genomic divergence between individuals in a study and the corresponding reference genome. We have applied the Cas9-mediated enrichment coupled to nanopore sequencing to perform a targeted de novo assembly and accurately reconstruct a genomic region of interest. This approach was used to reconstruct a 250-kbp target region on chromosome 5 of the common bean genome (Phaseolus vulgaris) associated with the shattering phenotype. Comparing a non-shattering cultivar (Midas) with the reference genome revealed many single-nucleotide variants and structural variants in this region. We cut five 50-kbp tiled sub-regions of Midas genomic DNA using Cas9, followed by sequencing on a MinION device and de novo assembly, generating a single contig spanning the whole 250-kbp region. This assembly increased the number of Illumina reads mapping to genes in the region, improving their genotypability for downstream analysis. The Cas9 tiling approach for target enrichment and sequencing is a valuable alternative to whole-genome sequencing for the assembly of ultra-long regions of interest, improving the accuracy of downstream genotype-phenotype association analysis.

Plant pan-genomics and its applications

Plant genomes are so highly diverse that a substantial proportion of genomic sequences are not shared among individuals. The variable DNA sequences, along with the conserved core sequences, compose the more sophisticated pan-genome that represents the collection of all non-redundant DNA in a species. With rapid progress in genome sequencing technologies, pan-genome research in plants is now accelerating. Here we review recent advances in plant pan-genomics, including major driving forces of structural variations that constitute the variable sequences, methodological innovations for representing the pan-genome, and major successes in constructing plant pan-genomes. We also summarize recent efforts toward decoding the remaining dark matter in telomere-to-telomere or gapless plant genomes. These new genome resources, which have remarkable advantages over numerous previously assembled less-than-perfect genomes, are expected to become new references for genetic studies and plant breeding.

From single- to multi-omics: future research trends in medicinal plants

Medicinal plants are the main source of natural metabolites with specialised pharmacological activities and have been widely examined by plant researchers. Numerous omics studies of medicinal plants have been performed to identify molecular markers of species and functional genes controlling key biological traits, as well as to understand biosynthetic pathways of bioactive metabolites and the regulatory mechanisms of environmental responses. Omics technologies have been widely applied to medicinal plants, including as taxonomics, transcriptomics, metabolomics, proteomics, genomics, pangenomics, epigenomics and mutagenomics. However, because of the complex biological regulation network, single omics usually fail to explain the specific biological phenomena. In recent years, reports of integrated multi-omics studies of medicinal plants have increased. Until now, there have few assessments of recent developments and upcoming trends in omics studies of medicinal plants. We highlight recent developments in omics research of medicinal plants, summarise the typical bioinformatics resources available for analysing omics datasets, and discuss related future directions and challenges. This information facilitates further studies of medicinal plants, refinement of current approaches and leads to new ideas.

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.

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.

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.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.