{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Berkner MO"],"funding":["Bundesministerium für Bildung und Forschung","Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK)","European Union's Horizon 2020 research and innovation programme","European Union’s Horizon 2020 research and innovation programme"],"pagination":["4391-4407"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9734214"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["135(12)"],"pubmed_abstract":["<h4>Key message</h4>Genomic prediction of genebank accessions benefits from the consideration of additive-by-additive epistasis and subpopulation-specific marker effects. Wheat (Triticum aestivum L.) and other species of the Triticum genus are well represented in genebank collections worldwide. The substantial genetic diversity harbored by more than 850,000 accessions can be explored for their potential use in modern plant breeding. Characterization of these large number of accessions is constrained by the required resources, and this fact limits their use so far. This limitation might be overcome by engaging genomic prediction. The present study compared ten different genomic prediction approaches to the prediction of four traits, namely flowering time, plant height, thousand grain weight"],"journal":["TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik"],"pubmed_title":["Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model."],"pmcid":["PMC9734214"],"funding_grant_id":["FKZ031B0184A","862613"],"pubmed_authors":["Jiang Y","Oppermann M","Reif JC","Berkner MO","Schulthess AW","Zhao Y"],"additional_accession":[]},"is_claimable":false,"name":"Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model.","description":"<h4>Key message</h4>Genomic prediction of genebank accessions benefits from the consideration of additive-by-additive epistasis and subpopulation-specific marker effects. Wheat (Triticum aestivum L.) and other species of the Triticum genus are well represented in genebank collections worldwide. The substantial genetic diversity harbored by more than 850,000 accessions can be explored for their potential use in modern plant breeding. Characterization of these large number of accessions is constrained by the required resources, and this fact limits their use so far. This limitation might be overcome by engaging genomic prediction. The present study compared ten different genomic prediction approaches to the prediction of four traits, namely flowering time, plant height, thousand grain weight","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Dec","modification":"2026-07-14T15:52:20.806Z","creation":"2024-12-04T06:52:14.804Z"},"accession":"S-EPMC9734214","cross_references":{"pubmed":["36182979"],"doi":["10.1007/s00122-022-04227-4"]}}