Unverified paper record
Genomic and phenomic predictions help capture low-effect alleles promoting seed germination in oilseed rape in addition to QTL analyses.
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 11 Jun 2024 · 10.1007/s00122-024-04659-0
Abstract
Key message Phenomic prediction implemented on a large diversity set can efficiently predict seed germination, capture low-effect favorable alleles that are not revealed by GWAS and identify promising genetic resources. Oilseed rape faces many challenges, especially at the beginning of its developmental cycle. Achieving rapid and uniform seed germination could help to ensure a successful establishment and therefore enabling the crop to compete with weeds and tolerate stresses during the earliest developmental stages. The polygenic nature of seed germination was highlighted in several studies, and more knowledge is needed about low- to moderate-effect underlying loci in order to enhance seed germination effectively by improving the genetic background and incorporating favorable alleles. A total of 17 QTL were detected for seed germination-related traits, for which the favorable alleles often corresponded to the most frequent alleles in the panel. Genomic and phenomic predictions methods provided moderate-to-high predictive abilities, demonstrating the ability to capture small additive and non-additive effects for seed germination. This study also showed that phenomic prediction estimated phenotypic values closer to phenotypic values than GEBV. Finally, as the predictive ability of phenomic prediction was less influenced by the genetic structure of the panel, it is worth using this prediction method to characterize genetic resources, particularly with a view to design prebreeding populations.
Plant phenotyping relevance
種子発芽という植物形質を対象に、フェノミック予測法をゲノミック予測やQTL解析と比較し、予測性能と遺伝資源評価への有用性を検証しているため、方法の適用・評価が中心です。
abstractGenomic and phenomic predictions methods provided moderate-to-high predictive abilities, demonstrating the ability to capture small additive and non-additive effects for seed germination.
abstractThis study also showed that phenomic prediction estimated phenotypic values closer to phenotypic values than GEBV.
Code and data availability
The paper describes germination phenotyping (PHENOTIC platform), NIRS spectra, SNP genotyping, and GP/PP analyses of 223 Brassica napus lines. A data availability statement points to a repository deposit, but the link is a private review-only URL (not among the allowed URLs) and the deposit is stated to become public '
No evidence-backed public reproduction asset is currently recorded.
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