Heritability and genetic architecture of reproduction-related traits in a temperate oak species
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Reproduction, one of the main components of plant fitness, is highly variable in response to environmental cues, but little is known about the genetic determinism underlying reproduction-related traits in forest tree species. There is therefore an urgent need to characterize the genetic architecture of those traits if we are to predict the evolutionary trajectories of forest populations facing rapidly changing environment and mitigate their impacts. Using a full-sib family of pedunculate oak (Quercus robur), we investigated the within population variability of seed production and mean seed mass during four consecutive years. Reproductive traits were highly variable between trees and between years. The high narrow sense heritability and evolvability estimated underline the important genetic effect on the variability in seed production and mean seed mass. Despite a large variability over years, reproductive traits show significant genetic correlation between years. Furthermore, for the first time in forest tree species, quantitative trait loci (QTLs) associated with seed production and mean mass of a seed have been identified. While it is commonly assumed and observed that fitness traits have low narrow sense heritabilities, our findings show that reproduction-related traits may undergo evolutionary changes under selective pressure and may be determinant for tree adaptation.
KeywordsTree reproduction Seed production Fitness Heritability QTLs Quercus robur
We thank the experimental units of Bourran (UE 0393 INRA, Domaine de la Tour de Rance 47320 Bourran, France) and Toulenne (UE 0393 INRA, Domaine des Jarres 33210 Toulenne, France) for technical support. We thank Jérôme Bartholomé for his assistance in the QTL analysis.
Data archiving statement
T.C. and A.K. conceived the idea for this work; T.C. and B.D. assembled the dataset; T.C and C.B. analyzed the data; T.C. and A.K. wrote the manuscript; and C.B. and S.D. revised the manuscript.
This research was supported by the European Research Council through the Advanced Grant Project TREEPEACE (#FP7-339728). TC received a PhD grant from TREEPEACE and the Initiative of Excellence program (IdEX-03-02) of Bordeaux University. BIOGECO is supported by a grant overseen by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” through the Cluster of Excellence COTE (ANR-10-LABEX45).
- Baliuckas V, Pliūra A, Eriksson G (2004) Forest tree breeding strategies in Nordic and Baltic countries and the possible implications on Lithuanian tree breeding strategy. Balt For 10(1):95–103Google Scholar
- Barzdajn W (2008) Comparison of provenance, family and individual heritability of growth traits in pedunculate oak (Quercus robur L.) in the family-provenance trial in the Milicz Forest district. Sylwan 144(12):57–67 (in Polish)Google Scholar
- Bates D, Maechler M, Bolker B, Walker S et al (2014) lme4: linear mixed-effects models using Eigen and S4. R Package Version 1(7):1–23Google Scholar
- Beavis WD (1998) QTL analyses: power, precision, and accuracy. Molecular dissection of complex traits. CRC Press, New York, pp 145–162Google Scholar
- Bogdan S, Katicic-Trupcevic, Kajab D (2004) Genetic variation in growth traits in a Quercus robur L. open-pollinated progeny test of the Slavonian provenance. Silvae Genet 53:198–201Google Scholar
- Bogdan S, Ivankovic M, Temunovic M, Moric M, Franjic J, Bogdan IK (2017) Adaptive genetic variability and differentiation of Croatian and Austrian Quercus robur L. populations at a drought prone field trial. Annals of. For Res 60:33–46Google Scholar
- Bogdziewicz M, Fernández-Martínez M, Bonal R, Belmonte J, Espelta JM (2017) The Moran effect and environmental vetoes: phenological synchrony and drought drive seed production in a Mediterranean oak. Proc R Soc B 284:20171784Google Scholar
- Derory J, Scotti-Saintagne C, Bertocchi E, Dantec LL, Graignic N, Jauffres A, Casasoli M, Chancerel E, Bodénès C, Alberto F, Kremer A (2010) Contrasting relationships between the diversity of candidate genes and variation of bud burst in natural and segregating populations of European oaks. Heredity 104:438–448CrossRefGoogle Scholar
- Dirlewanger E, Quero-García J, Dantec LL, Lambert P, Ruiz D, Dondini L, Illa E, Quilot-Turion B, Audergon J-M, Tartarini S, Letourmy P, Arús P (2012) Comparison of the genetic determinism of two key phenological traits, flowering and maturity dates, in three Prunus species: peach, apricot and sweet cherry. Heredity 109:280CrossRefGoogle Scholar
- Houel C, Chatbanyong R, Doligez A, Rienth M, Foria S, Luchaire N, Roux C, Adivèze A, Lopez G, Farnos M, Pellegrino A, This P, Romieu C, Torregrosa L (2015) Identification of stable QTLs for vegetative and reproductive traits in the microvine (Vitis vinifera L.) using the 18 K Infinium chip. BMC Plant Biol 15:205CrossRefGoogle Scholar
- Jensen JS, Wellendorf H, Jager K, De Vries SMG, Jensen V (1997) Analysis of a 17-year old Dutch open-pollinated progeny trial with Quercus robur (L.). For Genet 4(3):139–147Google Scholar
- Kroon J, Wennström U, Prescher F, Lindgren D, Mullin TJ (2009) Estimation of clonal variation in seed cone production over time in a scots pine (Pinus sylvestris L.) seed orchard. Silvae Genet 58(1–6):53–62Google Scholar
- Lesur I, Alexandre H, Boury C, Chancerel E, Plomion C, Kremer A (2018) Development of target sequence capture and estimation of genomic relatedness in a mixed oak stand. Front Plant Sci 9:996Google Scholar
- Mutke S, Gordo J, Gil L (2005) Cone yield characterization of a stone pine (Pinus pinea L.) clone bank. Silvae Genet 54(1–6):189–197Google Scholar
- Nepveu G (1984a) Genotypic determination of the anatomical structure of wood in Quercus robur. Silvae Genet 33(2–3):91–95Google Scholar
- Nepveu G (1984b) Hereditary control of density and retractability of wood from 3 oak species (Quercus petraea, Quercus robur and Quercus rubra). Silvae Genet 33(4–5):110–115Google Scholar
- Plomion C, Aury JM, Amselem J, Alaeitabar T, Barbe V, Belser C, Berges H, Bodénès C, Boudet N, Boury C, Canaguier A, Couloux A, Da Silva C, Duplessis S, Ehrenmann F, Estrada-Mairey B, Fouteau S, Francillonne N, Gaspin C, Guichard C, Klopp C, Labadie K, Lalanne C, Le Clainche I, Leplé JC, Le Provost G, Leroy T, Lesur I, Martin F, Mercier J, Michotey C, Murat F, Salin F, Steinbach D, Faivre-Rampant P, Wincker P, Salse J, Quesneville H, Kremer A (2016) Decoding the oak genome: public release of sequence data, assembly, annotation and publication strategies. Mol Ecol Resour 16:254–265CrossRefGoogle Scholar
- R Core Team (2014) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
- Santos del Blanco L, Zas R, Notivol Paíno E, Chambel MR, Majada J, Climent J (2010) Variation of early reproductive allocation in multi-site genetic trials of maritime pine and Aleppo pine. Variación en asignación reproductiva temprana en ensayos multi-localidad de pino carrasco y pino negra. For Syst 19:381–392Google Scholar
- Savill PS, Kanowski PJ, Gourlay ID, Jarvis AR (1993) Genetic and intra tree variation in the number of sapwood rings in Quercus robur and Q. petraea. Silvae Genet 42:371–375Google Scholar
- Sıvacıoglu A, Ayan S, Çelik D (2009) Clonal variation in growth, flowering and cone production in a seed orchard of scots pine (Pinus sylvestris L.) in Turkey. Afr J Biotechnol 8(17):4084–4093Google Scholar
- Traveset A, Heleno R, Nogales M (2014) The ecology of seed dispersal. Seeds: the ecology of regeneration in plant. communities 3:62–93Google Scholar
- White TL, Adams WT, Neale DB (Eds.) (2007) Forest genetics. CabiGoogle Scholar