Unlocking genome-based prediction and selection in conifers: the key role of within-family prediction accuracy illustrated in maritime pine (Pinus pinaster Ait.)
| hal.structure.identifier | Biodiversité, Gènes et Ecosystèmes [BioGeCo] | |
| hal.structure.identifier | Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement [INRAE] | |
| dc.contributor.author | PAPIN, Victor | |
| hal.structure.identifier | The Roslin Institute and Royal School of Veterinary Studies | |
| dc.contributor.author | GORJANC, Gregor | |
| dc.contributor.author | POCRNIC, Ivan | |
| hal.structure.identifier | Biodiversité, Gènes & Communautés [BioGeCo] | |
| dc.contributor.author | BOUFFIER, Laurent | |
| hal.structure.identifier | Biologie intégrée pour la valorisation de la diversité des Arbres et de la Forêt [BioForA] | |
| dc.contributor.author | SANCHEZ, Leopoldo | |
| dc.date.accessioned | 2025-01-25T03:01:58Z | |
| dc.date.available | 2025-01-25T03:01:58Z | |
| dc.date.issued | 2024-12-30 | |
| dc.identifier.issn | 1286-4560 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/204563 | |
| dc.description.abstractEn | Abstract Key message Based on experimental and simulated data for maritime pine ( Pinus pinaster Ait.) in a genomic selection context, our study reveals that the often-highlighted equivalence between genome-based and pedigree-based prediction accuracies of breeding values is associated with a zero accuracy of genome-based prediction within families, which can be attributed to the still insufficient size of the genomic training sets for conifers. Context Genomic selection is a promising approach for forest tree breeding. However, its advantage in terms of prediction accuracy over conventional pedigree-based methods is unclear and within-family accuracy is rarely assessed. Aims We used a pedigree-based model (ABLUP) with corrected pedigree data as a baseline reference for assessing the prediction accuracy of genome-based model (GBLUP) at the global and within-family levels in maritime pine ( Pinus pinaster Ait). Methods We considered 39 full-sib families, each comprising 10 to 40 individuals, to constitute an experimental population of 833 individuals. A stochastic simulation model was also developed to explore other scenarios of heritability, training set size, and marker density. Results Prediction accuracies with GBLUP and ABLUP were similar, and within-family accuracy with GBLUP was on average zero with large variation between families. Simulations revealed that the number of individuals in the training set was the principal factor limiting GBLUP accuracy in our study and likely in many forest tree breeding programmes. Accurate within-family prediction is possible if 40–65 individuals per full-sib family are included in the genomic training set, from a total of 1600–2000 individuals in the training set. Conclusions The increase in the number of individuals per family in the training set lead to a significant advantage of GBLUP over ABLUP in terms of prediction accuracy and more clearly justify the switch to genome-based prediction and selection in forest trees. | |
| dc.language.iso | en | |
| dc.publisher | Springer Nature (since 2011)/EDP Science (until 2010) | |
| dc.subject.en | Breeding programme | |
| dc.subject.en | Genomic selection | |
| dc.subject.en | Maritime pine | |
| dc.subject.en | Progeny validation | |
| dc.subject.en | Stochastic simulation | |
| dc.subject.en | Within-family variability | |
| dc.subject.en | Breeding programme Genomic selection Maritime pine Progeny validation Stochastic simulation Within-family variability | |
| dc.subject.en | Breeding programme | |
| dc.title.en | Unlocking genome-based prediction and selection in conifers: the key role of within-family prediction accuracy illustrated in maritime pine (Pinus pinaster Ait.) | |
| dc.type | Article de revue | |
| dc.identifier.doi | 10.1186/s13595-024-01269-0 | |
| dc.subject.hal | Sciences du Vivant [q-bio] | |
| dc.description.sponsorshipEurope | Adaptive BREEDING for productive, sustainable and resilient FORESTs under climate change | |
| bordeaux.journal | Annals of Forest Science | |
| bordeaux.page | 52 | |
| bordeaux.volume | 81 | |
| bordeaux.hal.laboratories | BioGeCo (Biodiversité Gènes & Communautés) - UMR 1202 | * |
| bordeaux.issue | 1 | |
| bordeaux.institution | Université de Bordeaux | |
| bordeaux.institution | INRAE | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-04872604 | |
| hal.version | 1 | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-04872604v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Annals%20of%20Forest%20Science&rft.date=2024-12-30&rft.volume=81&rft.issue=1&rft.spage=52&rft.epage=52&rft.eissn=1286-4560&rft.issn=1286-4560&rft.au=PAPIN,%20Victor&GORJANC,%20Gregor&POCRNIC,%20Ivan&BOUFFIER,%20Laurent&SANCHEZ,%20Leopoldo&rft.genre=article |
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