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Bayesian QTL analyses using pedigreed families of an outcrossing species,with application to fruit firmness in apple |
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| Authors: | M. C. A. M. Bink J. Jansen M. Madduri R. E. Voorrips C.-E. Durel A. B. Kouassi F. Laurens F. Mathis C. Gessler D. Gobbin F. Rezzonico A. Patocchi M. Kellerhals A. Boudichevskaia F. Dunemann A. Peil A. Nowicka B. Lata M. Stankiewicz-Kosyl K. Jeziorek E. Pitera A. Soska K. Tomala K. M. Evans F. Fernández-Fernández W. Guerra M. Korbin S. Keller M. Lewandowski W. Plocharski K. Rutkowski E. Zurawicz F. Costa S. Sansavini S. Tartarini M. Komjanc D. Mott A. Antofie M. Lateur A. Rondia L. Gianfranceschi W. E. van de Weg |
| Affiliation: | 1. Biometris, Wageningen University and Research Centre, Droevendaalsesteeg 1, P.O. Box 16, 6700 AA, Wageningen, The Netherlands 2. Plant Breeding, Wageningen UR, Droevendaalsesteeg 1, P.O. Box 16, 6700 AA, Wageningen, The Netherlands 3. INRA, UMR1345 Institut de Recherche en Horticulture et Semences, SFR 4207 Quasav, Pres L’UNAM, 49071, Beaucouzé, France 4. UMR1345 Institut de Recherche en Horticulture et Semences, Université d’Angers, 49045, Angers, France 5. UMR1345 Institut de Recherche en Horticulture et Semences, AgroCampus-Ouest, 49045, Angers, France 19. Université Félix Houphho?t-Boigny, Unité de Formation et de Recherche (UFR) ‘Biosciences’, Laboratoire de Génétique, 22BP 582 Abidjan 22, Abidjan, C?te d’Ivoire 20. Fabienne Mathis, VEGEPOLYS, P?le de compétitivité, 7 rue Dixmeras, 49044, Angers Cedex 01, France 6. Plant Pathology, Institute of Integrative Biology (IBZ), ETH Zurich, 8092, Zurich, Switzerland 21. Tecan Group Ltd., 8708, M?nnedorf, Switzerland 26. Research Group Environmental Genomics and Systems Biology, Institute of Natural Resource Sciences, Zürich University of Applied Sciences ZHAW, Grüental, 8820, W?denswil, Switzerland 7. Research Station Agroscope, Schloss 1, 8820, W?denswil, Switzerland 22. Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK), Corrensstr. 3, 06466, Gatersleben, Germany 8. Institute for Breeding Research on Horticultural Crops, Julius Kühn-Institut, Pillnitzer Platz 3a, 01326, Dresden, Germany 23. Julius Kühn-Institut, Institute for Breeding Research on Horticultural Crops, Erwin Baur Str. 27, 06484, Quedlinburg, Germany 9. Department of Experimental Design and Bioinformatics, Warsaw University of Life Sciences, SGGW, 02-776, Warsaw, Poland 10. Laboratory of Basic Research in Horticulture, Faculty of Horticulture, Biotechnology, and Landscape Architecture, Warsaw University of Life Sciences SGGW, 02-776, Warsaw, Poland 11. Department of Pomology, Faculty of Horticulture, Biotechnology and Landscape Architecture, Warsaw University of Life Sciences, SGGW, 02-776, Warsaw, Poland 12. East Malling Research, New Road, East Malling, Kent, ME19 6BJ, UK 24. Washington State University (WSU-TFREC), 1100 N. Western Avenue, Wenatchee, WA, 98801, USA 13. Research Centre for Agriculture and Forestry Laimburg, 39040, Vadena, BZ, Italy 14. Research Institute of Horticulture, 96-100, Skierniewice, Poland 15. Department of Fruit and Woody Plant Science, Current Department of Agricultural Sciences, University of Bologna, Via Fanin 46, 40127, Bologna, Italy 16. Department of Genetics and Biology of Fruit Crops, Research and Innovation Centre, Foundation Edmund Mach, Via Mach 1, 38010, Trento, Italy 17. Walloon Agricultural Research Centre (CRA-W), Liroux 9, 5030, Gembloux, Belgium 25. Direction Générale Qualité et Sécurité, Métrologie Légale SPF Economie, PME, Classes Moyennes et Energie, North Gate, Bd du Roi Albert II, 16, 1000, Bruxelles, Belgium 18. Department of Biosciences, University of Milan, Via Celoria 26, 20133, Milan, Italy |
| Abstract: | Key messageProof of concept of Bayesian integrated QTL analyses across pedigree-related families from breeding programs of an outbreeding species. Results include QTL confidence intervals, individuals’ genotype probabilities and genomic breeding values.AbstractBayesian QTL linkage mapping approaches offer the flexibility to study multiple full sib families with known pedigrees simultaneously. Such a joint analysis increases the probability of detecting these quantitative trait loci (QTL) and provide insight of the magnitude of QTL across different genetic backgrounds. Here, we present an improved Bayesian multi-QTL pedigree-based approach on an outcrossing species using progenies with different (complex) genetic relationships. Different modeling assumptions were studied in the QTL analyses, i.e., the a priori expected number of QTL varied and polygenic effects were considered. The inferences include number of QTL, additive QTL effect sizes and supporting credible intervals, posterior probabilities of QTL genotypes for all individuals in the dataset, and QTL-based as well as genome-wide breeding values. All these features have been implemented in the FlexQTL? software. We analyzed fruit firmness in a large apple dataset that comprised 1,347 individuals forming 27 full sib families and their known ancestral pedigrees, with genotypes for 87 SSR markers on 17 chromosomes. We report strong or positive evidence for 14 QTL for fruit firmness on eight chromosomes, validating our approach as several of these QTL were reported previously, though dispersed over a series of studies based on single mapping populations. Interpretation of linked QTL was possible via individuals’ QTL genotypes. The correlation between the genomic breeding values and phenotypes was on average 90 %, but varied with the number of detected QTL in a family. The detailed posterior knowledge on QTL of potential parents is critical for the efficiency of marker-assisted breeding. |
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