A Case of Need: Linking Traits to Genebank Accessions

Abstract

Genebanks are responsible for collecting, maintaining, characterizing, documenting, and distributing plant genetic resources for research, education, and breeding purposes. The rationale for requests of plant materials varies highly from areas of anthropology, social science, small-holder farmers, the commercial sector, rehabilitation of degraded systems, all the way to crop improvement and basic research. Matching “the right” accessions to a particular request is not always a straightforward process especially when genetic resource collections are large and the user does not already know which accession or even which species they want to study. Some requestors have limited knowledge of the crop; therefore, they do not know where to begin and thus, initiate the search by consultation with crop curators to help direct their request to the most suitable germplasm. One way to enhance the use of genebank material and aid in the selection of genetic resources is to have thoroughly cataloged agronomic, biochemical, genomic, and other traits linked to genebank accessions. In general, traits of importance to most users include genotypes that thrive under various biotic and abiotic stresses, morphological traits (color, shape, size of fruits), plant architecture, disease resistance, nutrient content, yield, and crop specific quality traits. In this review, we discuss methods for linking traits to genebank accessions, examples of linked traits, and some of the complexities involved, while reinforcing why it is critical to have well characterized accessions with clear trait data publicly available.

Predictive Characterization for Seed Morphometric Traits for Genebank Accessions Using Genomic Selection

“…However, characterization of large number of accessions held in the global collections is resources consuming. Several solutions have been developed and tested to address this issue, including core collections, FIGS, and GWAS (Anglin et al, 2018). The performance of core collection and GWAS to link a trait of interest to a genebank accession has been evaluated (Anglin et al, 2018); however, the application of FIGS has yet not been examined for quantitative morphological traits such as grain traits.…”

“…Several solutions have been developed and tested to address this issue, including core collections, FIGS, and GWAS (Anglin et al, 2018). The performance of core collection and GWAS to link a trait of interest to a genebank accession has been evaluated (Anglin et al, 2018); however, the application of FIGS has yet not been examined for quantitative morphological traits such as grain traits. In this research, we reported the efficiency of genome-wide prediction to predict the ICARDA genebank wheat landraces using highdensity DartSeq TM markers.…”

“…The major obstacle to enhance the use of genebank material is the lack of adequate characterization and evaluation data, and thus, the inability to adequately respond to inquiries for these accessions that directly meet the needs of the users. Several methods of linking traits to a genebank accession have been reviewed (Anglin et al, 2018) including phenotyping of large or random samples, core and mini core collections, the focused identification of the germplasm strategy (FIGS) and Generation Challenge Program subsets and use of molecular techniques and genome wide association studies (GWAS). FIGS is a useful approach developed at the International Center for Agricultural Research in the Dry Area (ICARDA) to identify subset of accessions with a high probability of containing specific target traits based on the ecogeographical information of the sites where the populations were collected (Mackay and Street, 2004).…”

SNP Markers and Evaluation of Duplicate Holdings of Brassica oleracea in Two European Genebanks

“…Recent developments such as using passport data with digital object identifiers (DOI) on accessions and transactions [12], large-scale morphological characterization and phenotyping [13], and molecular studies with next-generation sequencing platforms [14][15][16][17][18] have all improved the possibilities to identify duplicates. Regardless of the approach, proper data and transparent genebank information systems are needed to facilitate duplication assessments [19,20].…”

First method for dissolving zinc thiazole and re-evaluation of its antibacterial properties against rice bacterial blight disease

“…Therefore, it is extremely necessary to explore new methodologies, tools and processes to support and improve crop production (Shunmugam et al 2018). Plant diseases, mainly caused by bacterial (Mansfield et al 2012), viral (Scholthof et al 2011) and fungal pathogens (Dean et al 2012), and parasitic nematodes (Jones et al 2013), are the main limiting factors of crop yields (Anglin et al 2018). For example, rice bacterial blight (BB) leads to leaf blight during the growing season, hindering photosynthesis and diminishing the production and quality of rice (Kim and Reinke 2019).…”