Integrating Phenomics and Multi-Omics for Plant Genetic Resource Characterization

Plant genetic resource characterization is increasingly moving beyond the separate analysis of phenotypes and genotypes toward integrated, data-rich approaches. Although declining sequencing costs have made large-scale genotyping and genome analysis routine, phenotyping remains a major bottleneck in linking genetic diversity to agronomically valuable traits. High-throughput imaging, sensing, remote phenotyping and machine learning are expanding the scale and precision of trait measurement, while pangenomics, transcriptomics, proteomics, metabolomics and epigenomics are revealing the molecular basis of plant variation. However, questions remain about how reliably these heterogeneous data layers can be aligned across environments, species, platforms and institutions. Current advances in genotype–phenotype association, genomic and phenomic prediction, multi-environment modelling and environmental characterization are improving the analysis of complex traits, but interoperability, reproducibility, validation and the reuse of data remain insufficiently developed. A more integrated investigation is needed to convert diverse germplasm resources—including wild relatives, landraces, introgression lines and synthetic polyploids—into knowledge and breeding applications.This Research Topic aims to advance methods, computational frameworks and research infrastructures that enable the coordinated characterization and interpretation of plant genetic resources using phenomic, multi-omic and environmental data. It will address how improved measurement, data integration and interoperability can support the discovery of genetic architecture, strengthen genotype–phenotype prediction and accelerate the identification of variation associated with abiotic stress tolerance, resource-use efficiency, yield stability and other complex traits. Contributions may also examine how standardized metadata, FAIR data practices, benchmarking and reproducible workflows can improve the transferability and long-term value of characterization data across crops, environments and research institutions.To gather further insights in the integrated characterization of crop, horticultural and forest genetic resources, this Research Topic welcomes studies focused on methodological, computational, infrastructural and data-reuse challenges. Descriptive analyses of a single genotype without a methodological or integrative advance are outside the scope. Themes include:• High-throughput phenotyping platforms for field and controlled-environment research• RGB, multispectral, thermal, chlorophyll-fluorescence and three-dimensional imaging• UAV, proximal and remote sensing for plant and plot-level trait characterization• Root, rhizosphere and below-ground phenotyping• Machine learning and computer vision for trait extraction and phenotypic prediction• Genome assembly, pangenomes, resequencing and genotyping-by-sequencing in germplasm collections• Transcriptomics, proteomics, metabolomics and epigenomics of plant genetic resources• GWAS, genomic selection, phenomic selection and genotype–phenotype association• Multi-trait, multi-environment and genotype-by-environment modelling• Environmental covariates, envirotyping and prediction of trait performance• Genetic architecture of abiotic stress tolerance, resource-use efficiency and yield stability• Wild relatives, landraces, introgression lines and synthetic polyploids, including synthetic hexaploid wheat• Phenotypic and environmental standards, ontologies, MIAPPE and Crop Ontology• FAIR data practices, databases, platforms and interoperable metadata systems• Benchmarking, validation, method comparison and reproducible analytical pipelines• Open resources and workflows for cross-institutional and cross-crop data reuseContributions are welcome as Original Research, Methods, Technology and Code, Data Reports, Reviews and Perspectives. Topic editors: Georgios Koubouris, Aureliano Bombarely Gomez, Yanbo Hu, Giuseppe Montanaro Source: https://www.frontiersin.org/research-topics/84861/integrating-phenomics-and-multi-omics-for-plant-genetic-resource-characterization