Skip to main content

X-ray computed tomography to decipher the genetic architecture of tree branching traits: oak as a case study

Abstract

A new method for obtaining internal views of tree trunks was recently developed using X-ray computed tomography (CT). This technology makes it possible to observe and measure rameal traces that are left by latent buds, sequential branches, and epicormic branches in the wood. Epicormic branches are undesirable for producing high-value solid wood, especially in Quercus robur, an important hardwood forest tree species in Europe, which is prone to epicormic branches that develop from abundant latent buds. For the very first time, branching-related traits deduced from X-ray CT observation make it possible to analyze the genetic architecture of oak branching through a quantitative trait locus (QTL) analysis. Highly significant QTLs were detected for traits related to latent buds and epicormic branches. The number and effect of these QTLs suggest a moderate genetic determinism for the formation of latent buds and the development of epicormic branches. Three hotspots were found, grouping QTLs for different branching traits. An analysis of the common physiological denominators of these coincident traits suggests that their genetic controls are related to either the regulation of the axillary meristem initiation or to bud dormancy. Conversely, the position of only the separate QTL related to the number of sequential branches suggests an independent genetic control.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  • Barton NH, Keightley PD (2002) Understanding quantitative genetic variation. Nat Rev Genet 3:11–21. doi:10.1038/nrg700

    CAS  Article  PubMed  Google Scholar 

  • Beavis WD (1994) The power and deceit of QTL experiments: lessons from comparative QTL studies. Proc Forty-Ninth Annu Corn Sorghum Ind Res Conf 250–266

  • Bodénès C, Chancerel E, Ehrenmann F et al (2016) High-density linkage mapping and distribution of segregation distortion regions in the oak genome. DNA Res. doi:10.1093/dnares/dsw001

    PubMed  PubMed Central  Google Scholar 

  • Bradshaw HD, Stettled RF (1995) Molecular genetics of growth and development in populus. Genetics 973:963–973

    Google Scholar 

  • Brendel O, Thiec D, Scotti-Saintagne C et al (2008) Quantitative trait loci controlling water use efficiency and related traits in Quercus robur L. Tree Genet Genomes 4:263–278. doi:10.1007/s11295-007-0107-z

    Article  Google Scholar 

  • Chaar H, Colin F (1999) Impact of late frost on height growth in young sessile oak regenerations. Ann For Sci 56:417–429. doi:10.1051/forest:19990506

    Article  Google Scholar 

  • Chatfield SP, Stirnberg P, Forde BG, Leyser O (2000) The hormonal regulation of axillary bud growth in Arabidopsis. Plant J 24:159–169. doi:10.1046/j.1365-313X.2000.00862.x

    CAS  Article  PubMed  Google Scholar 

  • Colin F, Ducousso A, Fontaine F (2010a) Epicormics in 13-year-old Quercus petraea: small effect of provenance and large influence of branches and growth unit limits. Ann For Sci 67:312–312. doi:10.1051/forest/2009118

    Article  Google Scholar 

  • Colin F, Fontaine F, Morisset JB, et al. (2012) Gourmands et bourgeons latents dans le bois. Conséquences pour la sylviculture. Forêts Fr. no. 550 39–41.

  • Colin F, Mothe F, Freyburger C et al (2010b) Tracking rameal traces in sessile oak trunks with X-ray computer tomography: biological bases, preliminary results and perspectives. Trees 24:953–967. doi:10.1007/s00468-010-0466-1

    Article  Google Scholar 

  • Colin F, Nicolas R, Jean-louis D, Fontaine F (2008) Initial spacing has little influence on transient epicormic shoots in a 20-year-old sessile oak plantation.

  • Conner PJ, Brown SK, Weeden NF (1998) Molecular-marker analysis of quantitative traits for growth and development in juvenile apple trees. Theor Appl Genet 96:1027–1035. doi:10.1007/s001220050835

    CAS  Article  Google Scholar 

  • Darvasi A, Soller M (1997) A simple method to calculate resolving power and confidence interval of QTL map location. Behav Genet 27:125–132

    CAS  Article  PubMed  Google Scholar 

  • Epskamp S, Cramer AOJ, Waldorp LJ et al (2012) {qgraph}: network visualizations of relationships in psychometric data. J Stat Softw 48:1–18

    Article  Google Scholar 

  • Fabbrini F, Gaudet M, Bastien C et al (2012) Phenotypic plasticity, QTL mapping and genomic characterization of bud set in black poplar. BMC Plant Biol 12:47. doi:10.1186/1471-2229-12-47

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Fontaine F, Kiefer E, Clément C et al (1999) Ontogeny of the proventitious epicormic buds in Quercus petraea. II. From 6 to 40 years of the tree’s life. Trees 14:83–90. doi:10.1007/PL00009755

    Google Scholar 

  • Fontaine F, Mothe F, Colin F, Duplat P (2004) Structural relationships between the epicormic formations on the trunk surface and defects induced in the wood of Quercus petraea. Trees - Struct Funct 18:295–306. doi:10.1007/s00468-003-0306-7

    Article  Google Scholar 

  • Forêts de France (2015) n°583 Mars

  • Freeman JS, Potts BM, Downes GM, et al. (2013) Stability of quantitative trait loci for growth and wood properties across multiple pedigrees and environments in Eucalyptus globulus. 1121–1134.

  • Frewen BE, Chen THH, Howe GT et al (2000) Quantitative trait loci and candidate gene mapping of bud set and bud flush in populus. Genetics 154:837–845

    CAS  PubMed  PubMed Central  Google Scholar 

  • Freyburger C, Mothe F, Colin F, Fontaine F (2007) Exploitation d’images tomographiques RX pour l’analyse de la structure interne des gourmands de chêne. Procédure d’utilisation du plugin “Gourmands” avec ImageJ.

  • Gailing O, Langenfeld-Heyser R, Polle A, Finkeldey R (2008) Quantitative trait loci affecting stomatal density and growth in a Quercus robur progeny: implications for the adaptation to changing environments. Glob Chang Biol 14:1934–1946. doi:10.1111/j.1365-2486.2008.01621.x

    Article  Google Scholar 

  • Harmer R (1989) Some aspects of bud in young oak activity and branch formation. Ann des Sci For 46:217–219

    Article  Google Scholar 

  • Heuret P, Barthélémy D, Nicolini E, Atger C (2000) Analyse des composantes de la croissance en hauteur et de la formation du tronc chez le chêne sessile, Quercus petraea (Matt.) Liebl. (Fagaceae) en sylviculture dynamique. Can J Bot 78:361–373. doi:10.1139/b00-012

    Google Scholar 

  • IGN (2013) La France par zonage écoforestier.

  • Jensen JS, Wellendorf H, Jager K et al (1997) Analysis of a 17-year old dutch open-pollinated progeny trial with Quercus robur (l.). For Genet 4:139–147

    Google Scholar 

  • Kao CH, Zeng ZB, Teasdale RD (1999) Multiple interval mapping for quantitative trait loci. Genetics 152:1203–1216

    CAS  PubMed  PubMed Central  Google Scholar 

  • Korol AB, Ronin YI, Nevo E, Hayes PM (1998) Multi-interval mapping of correlated trait complexes. 80:273–284

  • Leyser O (2009) The control of shoot branching: an example of plant information processing. Plant Cell Environ 32:694–703. doi:10.1111/j.1365-3040.2009.01930.x

    CAS  Article  PubMed  Google Scholar 

  • McSteen P, Leyser O (2005) Shoot branching. Annu Rev Plant Biol 56:353–374. doi:10.1146/annurev.arplant.56.032604.144122

    CAS  Article  PubMed  Google Scholar 

  • Meadows JS, Burkhardt EC (2001) Epicormic branches affect lumber grade and value in willow oak. South J Appl For 25:136–141

    Google Scholar 

  • Meier A, Saunders MR (2013) Assessing internal epicormic dynamics in Quercus alba L. using CT scanning: the strong effects of shoot development and tree growth relative to progeny level genetic variation. Trees 27:865–877. doi:10.1007/s00468-013-0840-x

    Article  Google Scholar 

  • Meier AR, Saunders MR, Michler CH (2012) Epicormic buds in trees: a review of bud establishment, development and dormancy release. Tree Physiol 32:565–584. doi:10.1093/treephys/tps040

    Article  PubMed  Google Scholar 

  • Morisset JB (2012) Tomographie à rayons X; analyse et modélisation de l’ontogénèse des épicormiques du chêne sessile (Quercus petraea (L.) Matt.).

  • Morisset JB, Mothe F, Bock J et al (2012a) Epicormic ontogeny in Quercus petraea constrains the highly plausible control of epicormic sprouting by water and carbohydrates. Ann Bot 109:365–377. doi:10.1093/aob/mcr292

    CAS  Article  PubMed  Google Scholar 

  • Morisset JB, Mothe F, Colin F (2012b) Observation of Quercus petraea epicormics with X-ray CT reveals strong pith-to-bark correlations: Silvicultural and ecological implications. For Ecol Manag 278:127–137. doi:10.1016/j.foreco.2012.05.015

    Article  Google Scholar 

  • Nicolini E, Barthélémy D, Heuret P (2000) Influence de la densité du couvert forestier sur le développement architectural de jeunes chênes sessiles, Quercus petraea (Matt.) Liebl. (Fagaceae), en régénération forestière. Can J Bot 78:1531–1544. doi:10.1139/b00-125

    Google Scholar 

  • Parelle J, Zapater M, Scotti-Saintagne C et al (2007) Quantitative trait loci of tolerance to waterlogging in a European oak (Quercus robur L.): physiological relevance and temporal effect patterns. Plant Cell Environ 30:422–434. doi:10.1111/j.1365-3040.2006.01629.x

    Article  PubMed  Google Scholar 

  • Plomion C, Aury J, Elle JO et al (2016) Decoding the oak genome : public release of sequence data, assembly, annotation and publication strategies. Mol Ecol Resour 16:254–265. doi:10.1111/1755-0998.12425

    CAS  Article  PubMed  Google Scholar 

  • R Core Team (2015) R: a language and environment for statistical computing. R Found Stat Comput Vienna, Austria doi: ISBN 3-900051-07-0,

  • Saintagne C, Bodénès C, Barreneche T et al (2004) Distribution of genomic regions differentiating oak species assessed by QTL detection. Heredity (Edinb) 92:20–30. doi:10.1038/sj.hdy.6800358

    CAS  Article  Google Scholar 

  • Savill PS, Kanowski P (1993) Tree improvement programs for European oaks: goals and strategies. Ann Des Sci For 50:368s–383s. doi:10.1051/forest:19930741

    Article  Google Scholar 

  • Scalfi M, Troggio M, Piovani P et al (2004) A RAPD, AFLP and SSR linkage map, and QTL analysis in European beech (Fagus sylvatica L.). Theor Appl Genet 108:433–441. doi:10.1007/s00122-003-1461-3

    CAS  Article  PubMed  Google Scholar 

  • Scotti-Saintagne C, Bertocchi E, Barreneche T et al (2005) Quantitative trait loci mapping for vegetative propagation in pedunculate oak. Ann For Sci 62:369–374. doi:10.1051/forest

    CAS  Article  Google Scholar 

  • Scotti-Saintagne C, Bodénès C, Barreneche T et al (2004) Detection of quantitative trait loci controlling bud burst and height growth in Quercus robur L. Theor Appl Genet 109:1648–1659. doi:10.1007/s00122-004-1789-3

    CAS  Article  PubMed  Google Scholar 

  • Segura V, Durel C-E, Costes E (2008) Dissecting apple tree architecture into genetic, ontogenetic and environmental effects: QTL mapping. Tree Genet Genomes 5:165–179. doi:10.1007/s11295-008-0181-x

    Article  Google Scholar 

  • Shepherd M, Cross M, Dieters MJ, Henry R (2002) Branch architecture QTL for Pinus elliottii var. elliottii × Pinus caribaea var. hondurensis hybrids. Ann For Sci 59:617–625. doi:10.1051/forest

    Article  Google Scholar 

  • Socquet-Juglard D, Christen D, Devènes G et al (2012) Mapping architectural, phenological, and fruit quality QTLs in apricot. Plant Mol Biol Report 31:387–397. doi:10.1007/s11105-012-0511-x

    Article  Google Scholar 

  • Sosnowski O, Charcosset A, Joets J (2012) Biomercator V3: an upgrade of genetic map compilation and quantitative trait loci meta-analysis algorithms. Bioinformatics 28:2082–2083. doi:10.1093/bioinformatics/bts313

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Teichmann T, Muhr M (2015) Shaping plant architecture. Front Plant Sci 6:1–18. doi:10.3389/fpls.2015.00233

    Article  Google Scholar 

  • Voorrips RE (2002) Computer note MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered 93:77–78

    CAS  Article  PubMed  Google Scholar 

  • Wu RL (1998) Genetic mapping of QTLs affecting tree growth and architecture in populus: implication for ideotype breeding. Theor Appl Genet 96:447–457. doi:10.1007/s001220050761

    CAS  Article  PubMed  Google Scholar 

  • Zhang D, Zhang Z, Yang K (2006) QTL analysis of growth and wood chemical content traits in an interspecific backcross family of white poplar (Populus tomentosa × P-bolleana) × P-tomentosa. Can J For Res Can Rech For 36:2015–2023. doi:10.1139/x06-103

    CAS  Article  Google Scholar 

Download references

Acknowledgements

J. Song received a PhD fellowship from the Jinan Bayle Wine Import Co. The experimental site was provided by UMR 1202 Biogeco (INRA-Univ. Bordeaux). The medical CT scanner was provided by UMR 1092 LERFoB (INRA-AgroParisTech). LERFoB is supported by a grant overseen by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). We warmly thank B. Garnier and C. Freyburger for the preparation of the CT scanning, JB. Morisset and P-A. Dherouville for their help with the interpretation of the scanned images, B. Dencausse, D. Rittié, and G. Maréchal for wood preparation, and F. Ehrenmann for data submission. We also thank P. Duba for an initial English revision.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Francis Colin.

Additional information

Data archiving statement

The genetic maps are available in Quercus Portal:

http://w3.pierroton.inra.fr/QuercusPortal/

CMap Comparative Map Viewer for female parental LGs:

http://w3.pierroton.inra.fr/cgi-bin/cmap/viewer?mapMenu=&featureMenu=&corrMenu=&displayMenu=&advancedMenu=&ref_map_accs=-1&ref_map_start=&ref_map_stop=&ft_SNP=2&ft_DEFAULT=2&sub=Draw+selected+maps&prev_ref_species_acc=2&prev_ref_map_accs=&ref_map_set_acc=44&ref_species_acc=2&data_source=CMAP+OAK+DATABASE

CMap Comparative Map Viewer for male parental LGs:

http://w3.pierroton.inra.fr/cgi-bin/cmap/viewer?mapMenu=&featureMenu=&corrMenu=&displayMenu=&advancedMenu=&ref_map_accs=-1&ref_map_start=&ref_map_stop=&ft_SNP=2&ft_DEFAULT=2&sub=Draw+selected+maps&prev_ref_species_acc=2&prev_ref_map_accs=&ref_map_set_acc=44&ref_species_acc=2&data_source=CMAP+OAK+DATABASE

The phenotypic measurements were submitted in QuercusMap: https://w3.pierroton.inra.fr/QuercusPortal/index.php?p=qmap

Communicated by D. Grattapaglia

Electronic supplementary material

Online resource 1

(PDF 136 kb)

Online resource 2

(PDF 1106 kb)

Online resource 3

(PDF 1621 kb)

Online resource 4

(PDF 282 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Song, J., Brendel, O., Bodénès, C. et al. X-ray computed tomography to decipher the genetic architecture of tree branching traits: oak as a case study. Tree Genetics & Genomes 13, 5 (2017). https://doi.org/10.1007/s11295-016-1083-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11295-016-1083-y

Keywords

  • Pedunculate oak
  • Computed tomography
  • Epicormic
  • Latent bud
  • QTL