Cyberinfrastructure to Improve Forest Health and Productivity: The Role of Tree Databases in Connecting Genomes, Phenomes, and the Environment

Physiological and molecular response to drought in somatic plants from Pinus radiata embryonal masses induced at high temperatures

Drought and heat are among the major abiotic stresses in forest trees and are directly related with the consequences of climatic change. Many responses to abiotic stresses in plants have been associated with plant memory but mechanisms underlying this phenomenon remain unclear. Somatic embryogenesis, which is considered one of the most important methods for large-scale vegetative propagation of plants, is also used for stress induction and study the mechanisms involved in adaptation to abiotic stress. Specifically, heat stress during initiation stage of somatic embryogenesis has shown to have an impact in differential expression of stress related genes in pines. Modifications caused by a previous stress could eventually influence the stress tolerance of somatic plants years later. In this study we analysed the response to drought in 2-year-old radiata pine somatic plants, derived from embryonal masses initiated at 60 °C, at physiological, transcriptomic and amino acid accumulation level. Our results showed a more pronounce response to drought in plants coming from 60 °C treatment, which presented lower values in several physiological parameters as well as higher proline and tyrosine levels. Additionally, the transcriptomic response to drought was stronger in heat primed plants compared to control plants, suggesting a memory acquired two years before.

Evolution of NAC transcription factors from early land plants to domesticated crops

NAC [NO APICAL MERISTEM (NAM), ARABIDOPSIS TRANSCRIPTION ACTIVATOR FACTOR 1/2 (ATAF1/2), and CUP-SHAPED COTYLEDON (CUC2)] transcription factors are key regulators of plant growth, development, and stress responses but were also crucial players during land plant adaptation and crop domestication. Using representative members of green algae, bryophytes, lycophytes, gymnosperms, and angiosperms, we expanded the evolutionary history of NAC transcription factors to unveil the relationships among members of this gene family. We found a massive increase in the number of NAC transcription factors from green algae to lycophytes and an even larger increase in flowering plants. Many of the NAC clades arose later during evolution since we found eudicot- and monocot-specific clades. Cis-elements analysis in NAC promoters showed the presence of abiotic and biotic stress as well as hormonal response elements, which indicate the ancestral function of NAC transcription factor genes in response to environmental stimuli and in plant development. At the transcriptional level, the expression of NAC transcription factors was low or absent in male reproduction, particularly mature pollen, across the plant kingdom. We also identified NAC genes with conserved expression patterns in response to heat stress in Marchantia polymorpha and Oryza sativa. Our study provides further evidence that transcriptional mechanisms associated with stress responses and development emerged early during plant land adaptation and are still conserved in flowering plants and domesticated crops.

The effectiveness of large language models with RAG for auto-annotating trait and phenotype descriptions

Ontologies are highly prevalent in biology and medicine and are always evolving. Annotating biological text, such as observed phenotype descriptions, with ontology terms is a challenging and tedious task. The process of annotation requires a contextual understanding of the input text and of the ontological terms available. While text-mining tools are available to assist, they are largely based on directly matching words and phrases and so lack understanding of the meaning of the query item and of the ontology term labels. Large Language Models (LLMs), however, excel at tasks that require semantic understanding of input text and therefore may provide an improvement for the auto-annotation of text with ontological terms. Here we describe a series of workflows incorporating OpenAI GPT's capabilities to annotate Arabidopsis thaliana and forest tree phenotypic observations with ontology terms, aiming for results that resemble manually curated annotations. These workflows make use of an LLM to intelligently parse phenotypes into short concepts, followed by finding appropriate ontology terms via embedding vector similarity or via Retrieval-Augmented Generation (RAG). The RAG model is a state-of-the-art approach that augments conversational prompts to the LLM with context-specific data to empower it beyond its pre-trained parameter space. We show that the RAG produces the most accurate automated annotations that are often highly similar or identical to expert-curated annotations.

Characterization of pecan PEBP family genes and the potential regulation role of CiPEBP-like1 in fatty acid synthesis

Phosphatidyl ethanolamine-binding protein (PEBP) plays important roles in plant growth and development. However, few studies have investigated the PEBP gene family in pecan (Carya illinoinensis), particularly the function of the PEBP-like subfamily. In this study, we identified 12 PEBP genes from the pecan genome and classified them into four subfamilies: MFT-like, FT-like, TFL1-like and PEBP-like. Multiple sequence alignment, gene structure, and conserved motif analyses indicated that pecan PEBP subfamily genes were highly conserved. Cis-element analysis revealed that many light responsive elements and plant hormone-responsive elements are found in CiPEBPs promoters. Additionally, RNA-seq and RT-qPCR showed that CiPEBP-like1 was highly expressed during kernel filling stage. GO and KEGG enrichment analysis further indicated that CiPEBP-like1 was involved in fatty acid biosynthesis and metabolism progress. Overexpression of CiPEBP-like1 led to earlier flowering and altered fatty acid composition in Arabidopsis seeds. RT-qPCR confirmed that CiPEBP-like1 promoted fatty acid synthesis by regulating the expression of key genes. Overall, this study contributes to a comprehensive understanding of the potential functions of the PEBP family genes and lay a foundation to modifying fatty acid composition in pecan kernel.

A genome sequence for the threatened whitebark pine

Whitebark pine (WBP, Pinus albicaulis) is a white pine of subalpine regions in the Western contiguous United States and Canada. WBP has become critically threatened throughout a significant part of its natural range due to mortality from the introduced fungal pathogen white pine blister rust (WPBR, Cronartium ribicola) and additional threats from mountain pine beetle (Dendroctonus ponderosae), wildfire, and maladaptation due to changing climate. Vast acreages of WBP have suffered nearly complete mortality. Genomic technologies can contribute to a faster, more cost-effective approach to the traditional practices of identifying disease-resistant, climate-adapted seed sources for restoration. With deep-coverage Illumina short reads of haploid megagametophyte tissue and Oxford Nanopore long reads of diploid needle tissue, followed by a hybrid, multistep assembly approach, we produced a final assembly containing 27.6 Gb of sequence in 92,740 contigs (N50 537,007 bp) and 34,716 scaffolds (N50 2.0 Gb). Approximately 87.2% (24.0 Gb) of total sequence was placed on the 12 WBP chromosomes. Annotation yielded 25,362 protein-coding genes, and over 77% of the genome was characterized as repeats. WBP has demonstrated the greatest variation in resistance to WPBR among the North American white pines. Candidate genes for quantitative resistance include disease resistance genes known as nucleotide-binding leucine-rich repeat receptors (NLRs). A combination of protein domain alignments and direct genome scanning was employed to fully describe the 3 subclasses of NLRs. Our high-quality reference sequence and annotation provide a marked improvement in NLR identification compared to previous assessments that leveraged de novo-assembled transcriptomes.

The drivers of intraspecific trait variation and their implications for future tree productivity and survival

Forests are facing unprecedented levels of stress from pest and disease outbreaks, disturbance, fragmentation, development, and a changing climate. These selective agents act to alter forest composition from regional to cellular levels. Thus, a central challenge for understanding how forests will be impacted by future change is how to integrate across scales of biology. Phenotype, or an observable trait, is the product of an individual's genes (G) and the environment in which an organism lives (E). To date, researchers have detailed how environment drives variation in tree phenotypes over long time periods (e.g., long-term ecological research sites [LTERs]) and across large spatial scales (e.g., flux network). In parallel, researchers have discovered the genes and pathways that govern phenotypes, finding high degrees of genetic control and signatures of local adaptation in many plant traits. However, the research in these two areas remain largely independent of each other, hindering our ability to generate accurate predictions of plant response to environment, an increasingly urgent need given threats to forest systems. I present the importance of both genes and environment in determining tree responses to climate stress. I highlight why the difference between G versus E in driving variation is critical for our understanding of climate responses, then propose means of accelerating research that examines G and E simultaneously by leveraging existing long-term, large-scale phenotypic data sets from ecological networks and adding newly affordable sequence (-omics) data to both drill down to find the genes and alleles influencing phenotypes and scale up to find how patterns of demography and local adaptation may influence future response to change.

The genome of the Wollemi pine, a critically endangered "living fossil" unchanged since the Cretaceous, reveals extensive ancient transposon activity

We present the genome of the living fossil, Wollemia nobilis, a southern hemisphere conifer morphologically unchanged since the Cretaceous. Presumed extinct until rediscovery in 1994, the Wollemi pine is critically endangered with less than 60 wild adults threatened by intensifying bushfires in the Blue Mountains of Australia. The 12 Gb genome is among the most contiguous large plant genomes assembled, with extremely low heterozygosity and unusual abundance of DNA transposons. Reduced representation and genome re-sequencing of individuals confirms a relictual population since the last major glacial/drying period in Australia, 120 ky BP. Small RNA and methylome sequencing reveal conservation of ancient silencing mechanisms despite the presence of thousands of active and abundant transposons, including some transferred horizontally to conifers from arthropods in the Jurassic. A retrotransposon burst 8-6 my BP coincided with population decline, possibly as an adaptation enhancing epigenetic diversity. Wollemia, like other conifers, is susceptible to Phytophthora, and a suite of defense genes, similar to those in loblolly pine, are targeted for silencing by sRNAs in leaves. The genome provides insight into the earliest seed plants, while enabling conservation efforts.

Multispecies comparison of host responses to Fusarium circinatum challenge in tropical pines show consistency in resistance mechanisms

Fusarium circinatum poses a threat to both commercial and natural pine forests. Large variation in host resistance exists between species, with many economically important species being susceptible. Development of resistant genotypes could be expedited and optimised by investigating the molecular mechanisms underlying host resistance and susceptibility as well as increasing the available genetic resources. RNA-seq data, from F. circinatum inoculated and mock-inoculated ca. 6-month-old shoot tissue at 3- and 7-days postinoculation, was generated for three commercially important tropical pines, Pinus oocarpa, Pinus maximinoi and Pinus greggii. De novo transcriptomes were assembled and used to investigate the NLR and PR gene content within available pine references. Host responses to F. circinatum challenge were investigated in P. oocarpa (resistant) and P. greggii (susceptible), in comparison to previously generated expression profiles from Pinus tecunumanii (resistant) and Pinus patula (susceptible). Expression results indicated crosstalk between induced salicylate, jasmonate and ethylene signalling is involved in host resistance and compromised in susceptible hosts. Additionally, higher constitutive expression of sulfur metabolism and flavonoid biosynthesis in resistant hosts suggest involvement of these metabolites in resistance.

Multi-faceted CRISPR-Cas9 strategy to reduce plant based food loss and waste for sustainable bio-economy - A review

Currently, international development requires innovative solutions to address imminent challenges like climate change, unsustainable food system, food waste, energy crisis, and environmental degradation. All the same, addressing these concerns with conventional technologies is time-consuming, causes harmful environmental impacts, and is not cost-effective. Thus, biotechnological tools become imperative for enhancing food and energy resilience through eco-friendly bio-based products by valorisation of plant and food waste to meet the goals of circular bioeconomy in conjunction with Sustainable Developmental Goals (SDGs). Genome editing can be accomplished using a revolutionary DNA modification tool, CRISPR-Cas9, through its uncomplicated guided mechanism, with great efficiency in various organisms targeting different traits. This review's main objective is to examine how the CRISPR-Cas system, which has positive features, could improve the bioeconomy by reducing food loss and waste with all-inclusive food supply chain both at on-farm and off-farm level; utilising food loss and waste by genome edited microorganisms through food valorisation; efficient microbial conversion of low-cost substrates as biofuel; valorisation of agro-industrial wastes; mitigating greenhouse gas emissions through forestry plantation crops; and protecting the ecosystem and environment. Finally, the ethical implications and regulatory issues that are related to CRISPR-Cas edited products in the international markets have also been taken into consideration.

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.

From Genome Sequencing to CRISPR-Based Genome Editing for Climate-Resilient Forest Trees

Due to the economic and ecological importance of forest trees, modern breeding and genetic manipulation of forest trees have become increasingly prevalent. The CRISPR-based technology provides a versatile, powerful, and widely accepted tool for analyzing gene function and precise genetic modification in virtually any species but remains largely unexplored in forest species. Rapidly accumulating genetic and genomic resources for forest trees enabled the identification of numerous genes and biological processes that are associated with important traits such as wood quality, drought, or pest resistance, facilitating the selection of suitable gene editing targets. Here, we introduce and discuss the latest progress, opportunities, and challenges of genome sequencing and editing for improving forest sustainability.

qtlXplorer: an online systems genetics browser in the Eucalyptus Genome Integrative Explorer (EucGenIE)

BACKGROUND

Affordable high-throughput DNA and RNA sequencing technologies are allowing genomic analysis of plant and animal populations and as a result empowering new systems genetics approaches to study complex traits. The availability of intuitive tools to browse and analyze the resulting large-scale genetic and genomic datasets remain a significant challenge. Furthermore, these integrative genomics approaches require innovative methods to dissect the flow and interconnectedness of biological information underlying complex trait variation. The Plant Genome Integrative Explorer (PlantGenIE.org) is a multi-species database and domain that houses online tools for model and woody plant species including Eucalyptus. Since the Eucalyptus Genome Integrative Explorer (EucGenIE) is integrated within PlantGenIE, it shares genome and expression analysis tools previously implemented within the various subdomains (ConGenIE, PopGenIE and AtGenIE). Despite the success in setting up integrative genomics databases, online tools for systems genetics modelling and high-resolution dissection of complex trait variation in plant populations have been lacking.

RESULTS

We have developed qtlXplorer ( https://eucgenie.org/QTLXplorer ) for visualizing and exploring systems genetics data from genome-wide association studies including quantitative trait loci (QTLs) and expression-based QTL (eQTL) associations. This module allows users to, for example, find co-located QTLs and eQTLs using an interactive version of Circos, or explore underlying genes using JBrowse. It provides users with a means to build systems genetics models and generate hypotheses from large-scale population genomics data. We also substantially upgraded the EucGenIE resource and show how it enables users to combine genomics and systems genetics approaches to discover candidate genes involved in biotic stress responses and wood formation by focusing on two multigene families, laccases and peroxidases.

CONCLUSIONS

qtlXplorer adds a new dimension, population genomics, to the EucGenIE and PlantGenIE environment. The resource will be of interest to researchers and molecular breeders working in Eucalyptus and other woody plant species. It provides an example of how systems genetics data can be integrated with functional genetics data to provide biological insight and formulate hypotheses. Importantly, integration within PlantGenIE enables novel comparative genomics analyses to be performed from population-scale data.

Recommender-as-a-Service with Chatbot Guided Domain-science Knowledge Discovery in a Science Gateway

Scientists in disciplines such as neuroscience and bioinformatics are increasingly relying on science gateways for experimentation on voluminous data, as well as analysis and visualization in multiple perspectives. Though current science gateways provide easy access to computing resources, datasets and tools specific to the disciplines, scientists often use slow and tedious manual efforts to perform knowledge discovery to accomplish their research/education tasks. Recommender systems can provide expert guidance and can help them to navigate and discover relevant publications, tools, data sets, or even automate cloud resource configurations suitable for a given scientific task. To realize the potential of integration of recommenders in science gateways in order to spur research productivity, we present a novel "OnTimeRecommend" recommender system. The OnTimeRecommend comprises of several integrated recommender modules implemented as microservices that can be augmented to a science gateway in the form of a recommender-as-a-service. The guidance for use of the recommender modules in a science gateway is aided by a chatbot plug-in viz., Vidura Advisor. To validate our OnTimeRecommend, we integrate and show benefits for both novice and expert users in domain-specific knowledge discovery within two exemplar science gateways, one in neuroscience (CyNeuro) and the other in bioinformatics (KBCommons).

Genomic Approaches to Plant-Pathogen Epidemiology and Diagnostics

Diseases have a significant cost to agriculture. Findings from analyses of whole-genome sequences show great promise for informing strategies to mitigate risks from diseases caused by phytopathogens. Genomic approaches can be used to dramatically shorten response times to outbreaks and inform disease management in novel ways. However, the use of these approaches requires expertise in working with big, complex data sets and an understanding of their pitfalls and limitations to infer well-supported conclusions. We suggest using an evolutionary framework to guide the use of genomic approaches in epidemiology and diagnostics of plant pathogens. We also describe steps that are necessary for realizing these as standard approaches in disease surveillance.

Challenges for FAIR-compliant description and comparison of crop phenotype data with standardized controlled vocabularies

Crop phenotypic data underpin many pre-breeding efforts to characterize variation within germplasm collections. Although there has been an increase in the global capacity for accumulating and comparing such data, a lack of consistency in the systematic description of metadata often limits integration and sharing. We therefore aimed to understand some of the challenges facing findable, accesible, interoperable and reusable (FAIR) curation and annotation of phenotypic data from minor and underutilized crops. We used bambara groundnut (Vigna subterranea) as an exemplar underutilized crop to assess the ability of the Crop Ontology system to facilitate curation of trait datasets, so that they are accessible for comparative analysis. This involved generating a controlled vocabulary Trait Dictionary of 134 terms. Systematic quantification of syntactic and semantic cohesiveness of the full set of 28 crop-specific COs identified inconsistencies between trait descriptor names, a relative lack of cross-referencing to other ontologies and a flat ontological structure for classifying traits. We also evaluated the Minimal Information About a Phenotyping Experiment and FAIR compliance of bambara trait datasets curated within the CropStoreDB schema. We discuss specifications for a more systematic and generic approach to trait controlled vocabularies, which would benefit from representation of terms that adhere to Open Biological and Biomedical Ontologies principles. In particular, we focus on the benefits of reuse of existing definitions within pre- and post-composed axioms from other domains in order to facilitate the curation and comparison of datasets from a wider range of crops. Database URL: https://www.cropstoredb.org/cs_bambara.html.

Tripal MegaSearch: a tool for interactive and customizable query and download of big data

Tripal MegaSearch is a Tripal module for querying and downloading biological data stored in Chado. This module allows site users to select data types, restrict the dataset by applying various filters and then customizing fields to view and download through a single interface. Set by site administrators, example data types include gene, germplasm, marker, map, QTL, genotype, phenotype and expression data. When querying for genes, users can restrict the gene dataset using various filters such as name, chromosome position and functional annotation. They can then customize fields to download, such as name, organism, type, chromosome position, various functional annotations such as BLAST, KEGG, InterPro and GO term. FASTA files can also be downloaded for the sequence data. Site administrators can choose from two different data sources to serve data: Tripal MegaSearch materialized views or Chado tables. If neither data source is desired, administrators may also create their own materialized views and serve them through the flexible dynamic Tripal MegaSearch query form. Tripal MegaSearch is currently implemented in several databases including the Genome Database for Rosaceae www.rosaceae.org and TreeGenes www.https://treegenesdb.org/.

TOA: A software package for automated functional annotation in non-model plant species

The increase of sequencing capacity provided by high-throughput platforms has made it possible to routinely obtain large sets of genomic and transcriptomic sequences from model and non-model organisms. Subsequent genomic analysis and gene discovery in next-generation sequencing experiments are, however, bottlenecked by functional annotation. One common way to perform functional annotation of sets of sequences obtained from next-generation sequencing experiments, is by searching for homologous sequences and accessing the related functional information deposited in genomic databases. Functional annotation is especially challenging for non-model organisms, like many plant species. In such cases, existing free and commercial general-purpose applications may not offer complete and accurate results. We present TOA (Taxonomy-oriented annotation), a Python-based user-friendly open source application designed to establish functional annotation pipelines geared towards non-model plant species that can run in Linux/Mac computers, HPCs and cloud servers. TOA performs homology searches against proteins stored in the PLAZA databases, NCBI RefSeq Plant, Nucleotide Database and Non-Redundant Protein Sequence Database, and outputs functional information from several ontology systems: Gene Ontology, InterPro, EC, KEGG, Mapman and MetaCyc. The software performance was validated by comparing the runtimes, total number of annotated sequences and accuracy of the functional information obtained for several plant benchmark data sets with TOA and other functional annotation solutions. TOA outperformed the other software in terms of number of annotated sequences and accuracy of the annotation and constitutes a good alternative to improve functional annotation in plants. TOA is especially recommended for gymnosperms or for low quality sequence data sets of non-model plants.

A Reference Genome Sequence for Giant Sequoia

The giant sequoia (Sequoiadendron giganteum) of California are massive, long-lived trees that grow along the U.S. Sierra Nevada mountains. Genomic data are limited in giant sequoia and producing a reference genome sequence has been an important goal to allow marker development for restoration and management. Using deep-coverage Illumina and Oxford Nanopore sequencing, combined with Dovetail chromosome conformation capture libraries, the genome was assembled into eleven chromosome-scale scaffolds containing 8.125 Gbp of sequence. Iso-Seq transcripts, assembled from three distinct tissues, was used as evidence to annotate a total of 41,632 protein-coding genes. The genome was found to contain, distributed unevenly across all 11 chromosomes and in 63 orthogroups, over 900 complete or partial predicted NLR genes, of which 375 are supported by annotation derived from protein evidence and gene modeling. This giant sequoia reference genome sequence represents the first genome sequenced in the Cupressaceae family, and lays a foundation for using genomic tools to aid in giant sequoia conservation and management.

Genomic basis of white pine blister rust quantitative disease resistance and its relationship with qualitative resistance

The genomic architecture and molecular mechanisms controlling variation in quantitative disease resistance loci are not well understood in plant species and have been barely studied in long-generation trees. Quantitative trait loci mapping and genome-wide association studies were combined to test a large single nucleotide polymorphism (SNP) set for association with quantitative and qualitative white pine blister rust resistance in sugar pine. In the absence of a chromosome-scale reference genome, a high-density consensus linkage map was generated to obtain locations for associated SNPs. Newly discovered associations for white pine blister rust quantitative disease resistance included 453 SNPs involved in wide biological functions, including genes associated with disease resistance and others involved in morphological and developmental processes. In addition, NBS-LRR pathogen recognition genes were found to be involved in quantitative disease resistance, suggesting these newly reported genes are qualitative genes with partial resistance, they are the result of defeated qualitative resistance due to avirulent races, or they have epistatic effects on qualitative disease resistance genes. This study is a step forward in our understanding of the complex genomic architecture of quantitative disease resistance in long-generation trees, and constitutes the first step towards marker-assisted disease resistance breeding in white pine species.

The Utility of Genomic and Transcriptomic Data in the Construction of Proxy Protein Sequence Databases for Unsequenced Tree Nuts

As the apparent incidence of tree nut allergies rises, the development of MS methods that accurately identify tree nuts in food is critical. However, analyses are limited by few available tree nut protein sequences. We assess the utility of translated genomic and transcriptomic data for library construction with Juglans regia, walnut, as a model. Extracted walnuts were subjected to nano-liquid chromatography-mass spectrometry (n-LC-MS/MS), and spectra were searched against databases made from a six-frame translation of the genome (6FT), a transcriptome, and three proteomes. Searches against proteomic databases yielded a variable number of peptides (1156-1275), and only ten additional unique peptides were identified in the 6FT database. Searches against a transcriptomic database yielded results similar to those of the National Center for Biotechnology Information (NCBI) proteome (1200 and 1275 peptides, respectively). Performance of the transcriptomic database was improved via the adjustment of RNA-Seq read processing methods, which increased the number of identified peptides which align to seed allergen proteins by ~20%. Together, these findings establish a path towards the construction of robust proxy protein databases for tree nut species and other non-model organisms.

Cyberinfrastructure and resources to enable an integrative approach to studying forest trees

Sequencing technologies and bioinformatic approaches are now available to resolve the challenges associated with complex and heterozygous genomes. Increased access to less expensive and more effective instrumentation will contribute to a wealth of high-quality plant genomes in the next few years. In the meantime, more than 370 tree species are associated with public projects in primary repositories that are interrogating expression profiles, identifying variants, or analyzing targeted capture without a high-quality reference genome. Genomic data from these projects generates sequences that represent intermediate assemblies for transcriptomes and genomes. These data contribute to forest tree biology, but the associated sequence remains trapped in supplemental files that are poorly integrated in plant community databases and comparative genomic platforms. Successful implementation of life science cyberinfrastructure is improving data standards, ontologies, analytic workflows, and integrated database platforms for both model and non-model plant species. Unique to forest trees with large populations that are long-lived, outcrossing, and genetically diverse, the phenotypic and environmental metrics associated with georeferenced populations are just as important as the genomic data sampled for each individual. To address questions related to forest health and productivity, cyberinfrastructure must keep pace with the magnitude of genomic and phenomic sampling of larger populations. This review examines the current landscape of cyberinfrastructure, with an emphasis on best practices and resources to align community data with the Findable, Accessible, Interoperable, and Reusable (FAIR) guidelines.

Experimental Design and Sample Preparation in Forest Tree Metabolomics

Appropriate experimental design and sample preparation are key steps in metabolomics experiments, highly influencing the biological interpretation of the results. The sample preparation workflow for plant metabolomics studies includes several steps before metabolite extraction and analysis. These include the optimization of laboratory procedures, which should be optimized for different plants and tissues. This is particularly the case for trees, whose tissues are complex matrices to work with due to the presence of several interferents, such as oleoresins, cellulose. A good experimental design, tree tissue harvest conditions, and sample preparation are crucial to ensure consistency and reproducibility of the metadata among datasets. In this review, we discuss the main challenges when setting up a forest tree metabolomics experiment for mass spectrometry (MS)-based analysis covering all technical aspects from the biological question formulation and experimental design to sample processing and metabolite extraction and data acquisition. We also highlight the importance of forest tree metadata standardization in metabolomics studies.