Metabolomic and transcriptomic analyses of yellow-flowered crocuses to infer alternative sources of saffron metabolites.

BACKGROUND: The increasing demand for saffron metabolites in various commercial industries, including medicine, food, cosmetics, and dyeing, is driven by the discovery of their diverse applications. Saffron, derived from Crocus sativus stigmas, is the most expensive spice, and there is a need to explore additional sources to meet global consumption demands. In this study, we focused on yellow-flowering crocuses and examined their tepals to identify saffron-like compounds. RESULTS: Through metabolomic and transcriptomic approaches, our investigation provides valuable insights into the biosynthesis of compounds in yellow-tepal crocuses that are similar to those found in saffron. The results of our study support the potential use of yellow-tepal crocuses as a source of various crocins (crocetin glycosylated derivatives) and flavonoids. CONCLUSIONS: Our findings suggest that yellow-tepal crocuses have the potential to serve as a viable excessive source of some saffron metabolites. The identification of crocins and flavonoids in these crocuses highlights their suitability for meeting the demands of various industries that utilize saffron compounds. Further exploration and utilization of yellow-tepal crocuses could contribute to addressing the growing global demand for saffron-related products.

Haplotype-resolved assembly of a tetraploid potato genome using long reads and low-depth offspring data.

Potato is one of the world's major staple crops, and like many important crop plants, it has a polyploid genome. Polyploid haplotype assembly poses a major computational challenge. We introduce a novel strategy for the assembly of polyploid genomes and present an assembly of the autotetraploid potato cultivar Altus. Our method uses low-depth sequencing data from an offspring population to achieve chromosomal clustering and haplotype phasing on the assembly graph. Our approach generates high-quality assemblies of individual chromosomes with haplotype-specific sequence resolution of whole chromosome arms and can be applied in common breeding scenarios where collections of offspring are available.

Depicting the genetic and metabolic panorama of chemical diversity in the tea plant.

As a frequently consumed beverage worldwide, tea is rich in naturally important bioactive metabolites. Combining genetic, metabolomic and biochemical methodologies, here, we present a comprehensive study to dissect the chemical diversity in tea plant. A total of 2837 metabolites were identified at high-resolution with 1098 of them being structurally annotated and 63 of them were structurally identified. Metabolite-based genome-wide association mapping identified 6199 and 7823 metabolic quantitative trait loci (mQTL) for 971 and 1254 compounds in young leaves (YL) and the third leaves (TL), respectively. The major mQTL (i.e., P < 1.05 × 10-5, and phenotypic variation explained (PVE) > 25%) were further interrogated. Through extensive annotation of the tea metabolome as well as network-based analysis, this study broadens the understanding of tea metabolism and lays a solid foundation for revealing the natural variations in the chemical composition of the tea plant. Interestingly, we found that galloylations, rather than hydroxylations or glycosylations, were the largest class of conversions within the tea metabolome. The prevalence of galloylations in tea is unusual, as hydroxylations and glycosylations are typically the most prominent conversions of plant specialized metabolism. The biosynthetic pathway of flavonoids, which are one of the most featured metabolites in tea plant, was further refined with the identified metabolites. And we demonstrated the further mining and interpretation of our GWAS results by verifying two identified mQTL (including functional candidate genes CsUGTa, CsUGTb, and CsCCoAOMT) and completing the flavonoid biosynthetic pathway of the tea plant.

Ontologies for increasing the FAIRness of plant research data.

The importance of improving the FAIRness (findability, accessibility, interoperability, reusability) of research data is undeniable, especially in the face of large, complex datasets currently being produced by omics technologies. Facilitating the integration of a dataset with other types of data increases the likelihood of reuse, and the potential of answering novel research questions. Ontologies are a useful tool for semantically tagging datasets as adding relevant metadata increases the understanding of how data was produced and increases its interoperability. Ontologies provide concepts for a particular domain as well as the relationships between concepts. By tagging data with ontology terms, data becomes both human- and machine- interpretable, allowing for increased reuse and interoperability. However, the task of identifying ontologies relevant to a particular research domain or technology is challenging, especially within the diverse realm of fundamental plant research. In this review, we outline the ontologies most relevant to the fundamental plant sciences and how they can be used to annotate data related to plant-specific experiments within metadata frameworks, such as Investigation-Study-Assay (ISA). We also outline repositories and platforms most useful for identifying applicable ontologies or finding ontology terms.

Metabolomics and machine learning technique revealed that germination enhances the multi-nutritional properties of pigmented rice.

Enhancing the dietary properties of rice is crucial to contribute to alleviating hidden hunger and non-communicable diseases in rice-consuming countries. Germination is a bioprocessing approach to increase the bioavailability of nutrients in rice. However, there is a scarce information on how germination impacts the overall nutritional profile of pigmented rice sprouts (PRS). Herein, we demonstrated that germination resulted to increase levels of certain dietary compounds, such as free phenolics and micronutrients (Ca, Na, Fe, Zn, riboflavin, and biotin). Metabolomic analysis revealed the preferential accumulation of dipeptides, GABA, and flavonoids in the germination process. Genome-wide association studies of the PRS suggested the activation of specific genes such as CHS1 and UGT genes responsible for increasing certain flavonoid compounds. Haplotype analyses showed a significant difference (P < 0.05) between alleles associated with these genes. Genetic markers associated with these flavonoids were incorporated into the random forest model, improving the accuracy of prediction of multi-nutritional properties from 89.7% to 97.7%. Deploying this knowledge to breed rice with multi-nutritional properties will be timely to address double burden nutritional challenges.

PLANTdataHUB: a collaborative platform for continuous FAIR data sharing in plant research.

In modern reproducible, hypothesis-driven plant research, scientists are increasingly relying on research data management (RDM) services and infrastructures to streamline the processes of collecting, processing, sharing, and archiving research data. FAIR (i.e., findable, accessible, interoperable, and reusable) research data play a pivotal role in enabling the integration of interdisciplinary knowledge and facilitating the comparison and synthesis of a wide range of analytical findings. The PLANTdataHUB offers a solution that realizes RDM of scientific (meta)data as evolving collections of files in a directory - yielding FAIR digital objects called ARCs - with tools that enable scientists to plan, communicate, collaborate, publish, and reuse data on the same platform while gaining continuous quality control insights. The centralized platform is scalable from personal use to global communities and provides advanced federation capabilities for institutions that prefer to host their own satellite instances. This approach borrows many concepts from software development and adapts them to fit the challenges of the field of modern plant science undergoing digital transformation. The PLANTdataHUB supports researchers in each stage of a scientific project with adaptable continuous quality control insights, from the early planning phase to data publication. The central live instance of PLANTdataHUB is accessible at (https://git.nfdi4plants.org), and it will continue to evolve as a community-driven and dynamic resource that serves the needs of contemporary plant science.

Understanding protein import in diverse non-green plastids.

The spectacular diversity of plastids in non-green organs such as flowers, fruits, roots, tubers, and senescing leaves represents a Universe of metabolic processes in higher plants that remain to be completely characterized. The endosymbiosis of the plastid and the subsequent export of the ancestral cyanobacterial genome to the nuclear genome, and adaptation of the plants to all types of environments has resulted in the emergence of diverse and a highly orchestrated metabolism across the plant kingdom that is entirely reliant on a complex protein import and translocation system. The TOC and TIC translocons, critical for importing nuclear-encoded proteins into the plastid stroma, remain poorly resolved, especially in the case of TIC. From the stroma, three core pathways (cpTat, cpSec, and cpSRP) may localize imported proteins to the thylakoid. Non-canonical routes only utilizing TOC also exist for the insertion of many inner and outer membrane proteins, or in the case of some modified proteins, a vesicular import route. Understanding this complex protein import system is further compounded by the highly heterogeneous nature of transit peptides, and the varying transit peptide specificity of plastids depending on species and the developmental and trophic stage of the plant organs. Computational tools provide an increasingly sophisticated means of predicting protein import into highly diverse non-green plastids across higher plants, which need to be validated using proteomics and metabolic approaches. The myriad plastid functions enable higher plants to interact and respond to all kinds of environments. Unraveling the diversity of non-green plastid functions across the higher plants has the potential to provide knowledge that will help in developing climate resilient crops.

The giant diploid faba genome unlocks variation in a global protein crop.

Increasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity1. However, plant protein production is hampered by the lack of a cool-season legume equivalent to soybean in agronomic value2. Faba bean (Vicia faba L.) has a high yield potential and is well suited for cultivation in temperate regions, but genomic resources are scarce. Here, we report a high-quality chromosome-scale assembly of the faba bean genome and show that it has expanded to a massive 13 Gb in size through an imbalance between the rates of amplification and elimination of retrotransposons and satellite repeats. Genes and recombination events are evenly dispersed across chromosomes and the gene space is remarkably compact considering the genome size, although with substantial copy number variation driven by tandem duplication. Demonstrating practical application of the genome sequence, we develop a targeted genotyping assay and use high-resolution genome-wide association analysis to dissect the genetic basis of seed size and hilum colour. The resources presented constitute a genomics-based breeding platform for faba bean, enabling breeders and geneticists to accelerate the improvement of sustainable protein production across the Mediterranean, subtropical and northern temperate agroecological zones.

QTL analysis for ascorbic acid content in strawberry fruit reveals a complex genetic architecture and association with GDP-L-galactose phosphorylase.

Strawberry (Fragaria × ananassa) fruits are an excellent source of L-ascorbic acid (AsA), a powerful antioxidant for plants and humans. Identifying the genetic components underlying AsA accumulation is crucial for enhancing strawberry nutritional quality. Here, we unravel the genetic architecture of AsA accumulation using an F1 population derived from parental lines 'Candonga' and 'Senga Sengana', adapted to distinct Southern and Northern European areas. To account for environmental effects, the F1 and parental lines were grown and phenotyped in five locations across Europe (France, Germany, Italy, Poland and Spain). Fruit AsA content displayed normal distribution typical of quantitative traits and ranged five-fold, with significant differences among genotypes and environments. AsA content in each country and the average in all of them was used in combination with 6,974 markers for quantitative trait locus (QTL) analysis. Environmentally stable QTLs for AsA content were detected in linkage group (LG) 3A, LG 5A, LG 5B, LG 6B and LG 7C. Candidate genes were identified within stable QTL intervals and expression analysis in lines with contrasting AsA content suggested that GDP-L-Galactose Phosphorylase FaGGP(3A), and the chloroplast-located AsA transporter gene FaPHT4;4(7C) might be the underlying genetic factors for QTLs on LG 3A and 7C, respectively. We show that recessive alleles of FaGGP(3A) inherited from both parental lines increase fruit AsA content. Furthermore, expression of FaGGP(3A) was two-fold higher in lines with high AsA. Markers here identified represent a useful resource for efficient selection of new strawberry cultivars with increased AsA content.

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.

Dissecting the impact of environment, season and genotype on blackcurrant fruit quality traits.

This work aims to determine the effect of genotype x environment (GxE) interaction that influence blackcurrant (Ribes nigrum) fruit quality. We applied metabolomics-driven analysis on fruits from four cultivars grown in contrasting European-locations over two seasons. By integrating metabolomics and sensory analysis, we also defined specific metabolic signatures associated with consumer acceptance. Our results showed that rainfall is a crucial factor associated with accumulation of delphinidin- and cyanidin-3-O-glucoside, the two mayor blackcurrant pigments meanwhile temperature affects the main organic acid levels which can be decisive for fruit taste. Sensorial analysis showed that increases in terpenoid and acetate ester volatiles were strongly associated with higher appreciation score, while proacacipetalin, a cyanogenic-glycoside, was positively associated to bitter taste. Our results pave the way for the selection of high-quality cultivars and suitable production sites for blackcurrant cultivation.

Solanaceae pangenomes are coming of graphical age to bring heritability back.

Two recent articles describe a pangenome of potato and a graph-based pangenome for tomato, respectively. The latter improves our understanding of the tomato genomics architecture even further and the use of this graph-based pangenome versus a single reference dramatically improves heritability in tomato.

Genetic polyploid phasing from low-depth progeny samples.

An important challenge in genome assembly is haplotype phasing, that is, to reconstruct the different haplotype sequences of an individual genome. Phasing becomes considerably more difficult with increasing ploidy, which makes polyploid phasing a notoriously hard computational problem. We present a novel genetic phasing method for plant breeding with the aim to phase two deep-sequenced parental samples with the help of a large number of progeny samples sequenced at low depth. The key ideas underlying our approach are to (i) integrate the individually weak Mendelian progeny signals with a Bayesian log-likelihood model, (ii) cluster alleles according to their likelihood of co-occurrence, and (iii) assign them to haplotypes via an interval scheduling approach. We show on two deep-sequenced parental and 193 low-depth progeny potato samples that our approach computes high-quality sparse phasings and that it scales to whole genomes.

Towards smart and sustainable development of modern berry cultivars in Europe.

Fresh berries are a popular and important component of the human diet. The demand for high-quality berries and sustainable production methods is increasing globally, challenging breeders to develop modern berry cultivars that fulfill all desired characteristics. Since 1994, research projects have characterized genetic resources, developed modern tools for high-throughput screening, and published data in publicly available repositories. However, the key findings of different disciplines are rarely linked together, and only a limited range of traits and genotypes has been investigated. The Horizon2020 project BreedingValue will address these challenges by studying a broader panel of strawberry, raspberry and blueberry genotypes in detail, in order to recover the lost genetic diversity that has limited the aroma and flavor intensity of recent cultivars. We will combine metabolic analysis with sensory panel tests and surveys to identify the key components of taste, flavor and aroma in berries across Europe, leading to a high-resolution map of quality requirements for future berry cultivars. Traits linked to berry yields and the effect of environmental stress will be investigated using modern image analysis methods and modeling. We will also use genetic analysis to determine the genetic basis of complex traits for the development and optimization of modern breeding technologies, such as molecular marker arrays, genomic selection and genome-wide association studies. Finally, the results, raw data and metadata will be made publicly available on the open platform Germinate in order to meet FAIR data principles and provide the basis for sustainable research in the future.

Capsicum Leaves under Stress: Using Multi-Omics Analysis to Detect Abiotic Stress Network of Secondary Metabolism in Two Species.

The plant kingdom contains an enormous diversity of bioactive compounds which regulate plant growth and defends against biotic and abiotic stress. Some of these compounds, like flavonoids, have properties which are health supporting and relevant for industrial use. Many of these valuable compounds are synthesized in various pepper (Capsicum sp.) tissues. Further, a huge amount of biomass residual remains from pepper production after harvest, which provides an important opportunity to extract these metabolites and optimize the utilization of crops. Moreover, abiotic stresses induce the synthesis of such metabolites as a defense mechanism. Two different Capsicum species were therefore exposed to chilling temperature (24/18 ℃ vs. 18/12 ℃), to salinity (200 mM NaCl), or a combination thereof for 1, 7 and 14 days to investigate the effect of these stresses on the metabolome and transcriptome profiles of their leaves. Both profiles in both species responded to all stresses with an increase over time. All stresses resulted in repression of photosynthesis genes. Stress involving chilling temperature induced secondary metabolism whereas stresses involving salt repressed cell wall modification and solute transport. The metabolome analysis annotated putatively many health stimulating flavonoids (apigetrin, rutin, kaempferol, luteolin and quercetin) in the Capsicum biomass residuals, which were induced in response to salinity, chilling temperature or a combination thereof, and supported by related structural genes of the secondary metabolism in the network analysis.

A Solanum lycopersicoides reference genome facilitates insights into tomato specialized metabolism and immunity.

Wild relatives of tomato are a valuable source of natural variation in tomato breeding, as many can be hybridized to the cultivated species (Solanum lycopersicum). Several, including Solanum lycopersicoides, have been crossed to S. lycopersicum for the development of ordered introgression lines (ILs), facilitating breeding for desirable traits. Despite the utility of these wild relatives and their associated ILs, few finished genome sequences have been produced to aid genetic and genomic studies. Here we report a chromosome-scale genome assembly for S. lycopersicoides LA2951, which contains 37 938 predicted protein-coding genes. With the aid of this genome assembly, we have precisely delimited the boundaries of the S. lycopersicoides introgressions in a set of S. lycopersicum cv. VF36 × LA2951 ILs. We demonstrate the usefulness of the LA2951 genome by identifying several quantitative trait loci for phenolics and carotenoids, including underlying candidate genes, and by investigating the genome organization and immunity-associated function of the clustered Pto gene family. In addition, syntenic analysis of R2R3MYB genes sheds light on the identity of the Aubergine locus underlying anthocyanin production. The genome sequence and IL map provide valuable resources for studying fruit nutrient/quality traits, pathogen resistance, and environmental stress tolerance. We present a new genome resource for the wild species S. lycopersicoides, which we use to shed light on the Aubergine locus responsible for anthocyanin production. We also provide IL boundary mappings, which facilitated identifying novel carotenoid quantitative trait loci of which one was likely driven by an uncharacterized lycopene ß-cyclase whose function we demonstrate.

GXP: Analyze and Plot Plant Omics Data in Web Browsers.

Next-generation sequencing and metabolomics have become very cost and work efficient and are integrated into an ever-growing number of life science research projects. Typically, established software pipelines analyze raw data and produce quantitative data informing about gene expression or concentrations of metabolites. These results need to be visualized and further analyzed in order to support scientific hypothesis building and identification of underlying biological patterns. Some of these tools already exist, but require installation or manual programming. We developed "Gene Expression Plotter" (GXP), an RNAseq and Metabolomics data visualization and analysis tool entirely running in the user's web browser, thus not needing any custom installation, manual programming or uploading of confidential data to third party servers. Consequently, upon receiving the bioinformatic raw data analysis of RNAseq or other omics results, GXP immediately enables the user to interact with the data according to biological questions by performing knowledge-driven, in-depth data analyses and candidate identification via visualization and data exploration. Thereby, GXP can support and accelerate complex interdisciplinary omics projects and downstream analyses. GXP offers an easy way to publish data, plots, and analysis results either as a simple exported file or as a custom website. GXP is freely available on GitHub (see introduction).

Ancient Artworks and Crocus Genetics Both Support Saffron's Origin in Early Greece.

Saffron crocus (Crocus sativus) is a male-sterile, triploid flower crop, and source of the spice and colorant saffron. For over three millennia, it was cultivated across the Mediterranean, including ancient Greece, Persia, and other cultures, later spreading all over the world. Despite saffron crocus' early omnipresence, its origin has been the matter of a century-old debate, in terms of area and time as well as parental species contribution. While remnants of the ancient arts, crafts, and texts still provide hints on its origin, modern genetics has the potential to efficiently follow these leads, thus shedding light on new possible lines of descent. In this review, we follow ancient arts and recent genetics to trace the evolutionary origin of saffron crocus. We focus on the place and time of saffron domestication and cultivation, and address its presumed autopolyploid origin involving cytotypes of wild Crocus cartwrightianus. Both ancient arts from Greece, Iran, and Mesopotamia as well as recent cytogenetic and comparative next-generation sequencing approaches point to saffron's emergence and domestication in ancient Greece, showing how both disciplines converge in tracing its origin.