Tree Genetics & Genomes

, Volume 4, Issue 2, pp 159–170 | Cite as

Identification of quantitative trait loci for wood quality and growth across eight full-sib coastal Douglas-fir families

  • Nicholas K. Ukrainetz
  • Kermit Ritland
  • Shawn D. MansfieldEmail author
Original Paper


Typical linkage and quantitative trait locus (QTL) analyses in forest trees have been conducted in single pedigrees with sex-averaged linkage maps. The results of a QTL analysis for wood quality and growth traits of coastal Douglas-fir using eight full-sib families, each consisting of 40 progeny, replicated on four sites are presented. The resulting map of segregating genetic markers consisted of 120 amplified fragment length polymorphism (AFLP) loci distributed across 19 linkage groups. The wood quality traits represent the widest suite of traits yet examined for QTL analysis in a tree species in a single study. Wood fiber traits showed the lowest number of QTLs (3) with relatively small effect (ca. 4%); wood density traits also showed just three QTLs but with slightly larger effect; wood chemistry traits showed more QTLs (7), while ring density traits showed many QTLs with large numbers of QTLs (78) and interesting patterns of temporal variation. Growth traits gave just five QTLs but of major effect (10–16%). Trees, with their long generation times, provide a rich resource for studies of temporal variation of QTL expression.


QTL mapping Wood quality traits Douglas-fir 



The authors would like to acknowledge funding (to SDM) from Natural Resources Canada (NRCan) Value-to-Wood Program for this project. The authors also gratefully acknowledge Alvin Yanchuk and Michael Stoehr of the BC Ministry of Forests for access to the Douglas-fir breeding trials.


  1. Arcade A, Faivre-Rampant P, Paques LE, Prat D (2002) Localisation of genomic regions controlling microdensitometric parameters of wood characteristics in hybrid larches. Ann For Sci 59(5–6):607–615CrossRefGoogle Scholar
  2. Aubry CA, Adams WT, Fahey TD (1998) Determination of relative economic weights for multitrait selection in coastal Douglas-fir. Can J For Res 28(8):1164–1170CrossRefGoogle Scholar
  3. Beavis WD (1998) QTL analyses: power, precision and accuracy. In: Molecular dissection of complex traits. CRC, Raleigh, North Carolina, pp 145–162Google Scholar
  4. Bradshaw HD, Stettler RF (1995) Molecular genetics of growth and development in Populus. IV. Mapping QTLs with large effects on growth, form, and phenology traits in a forest tree. Genetics 139:963–973PubMedGoogle Scholar
  5. Brown GR, Bassoni DL, Gill GP, Fontana JR, Wheeler NC, Megraw RA, Davis MF, Sewell MM, Tuskan GA, Neale DB (2003) Identification of quantitative trait loci influencing wood property traits in loblolly pine (Pinus taeda L.). III. QTL verification and candidate gene mapping. Genetics 164(4):1537–1546PubMedGoogle Scholar
  6. Byrne M, Murrell JC, Owen JV, Williams ER, Moran GF (1997) Mapping of quantitative trait loci influencing frost tolerance in Eucalyptus nitens. Theor Appl Genet 95(5–6):975–979CrossRefGoogle Scholar
  7. Chagne D, Lalanne C, Madur D, Kumar S, Frigerio JM, Krier C, Decroocq S, Savoure A, Bou-Dagher-Kharrat M, Bertocchi E, Brach J, Plomion C (2002) A high density genetic map of maritime pine based on AFLPs. Ann For Sci 59(5–6):627–636CrossRefGoogle Scholar
  8. Cramer S, Kretschmann D, Lakes R, Schmidt T (2005) Earlywood and latewood elastic properties in loblolly pine. Holzforschung 59:531–538CrossRefGoogle Scholar
  9. Chantre G, Rozenberg P, Baonza V, Macchioni N, Le Turcq A, Rueff M, Petit-Conil M, Heois B (2002) Genetic selection within Douglas-fir (Pseudotsuga menziesii) in Europe for papermaking uses. Ann For Sci 59(5–6):583–593CrossRefGoogle Scholar
  10. Evans R, Ilic J (2001) Rapid prediction of wood stiffness from microfibril angle and density. For Prod J 51(3):53–57Google Scholar
  11. Grattapaglia D, Bertolucci FLG, Penchel R, Sederoff RR (1996) Genetic mapping of quantitative trait loci controlling growth and wood quality traits in Eucalyptus grandis using a maternal half-sib family and RAPD markers. Genetics 144:1205–1214PubMedGoogle Scholar
  12. Haseman JK, Elston RC (1972) Investigation of linkage between a quantitative trait and a marker locus. Behav Genet 2(1):3–9PubMedCrossRefGoogle Scholar
  13. Hu X-S, Goodwillie C, Ritland KM (2004) Joining genetic linkage maps using a joint likelihood function. Theor Appl Genet 109:996–1004PubMedCrossRefGoogle Scholar
  14. Huntley SK, Ellis D, Gilbert M, Chapple CS, Mansfield SD (2003) Significant increases in pulping efficiency in C4H-F5H-transformed poplars: improved chemical savings and reduced environmental toxins. J Agric Food Chem 51:6178–6183PubMedCrossRefGoogle Scholar
  15. Jermstad KD, Bassoni DL, Wheeler NC, Neale DB (1998) A sex-averaged genetic linkage map in coastal Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco var ‘menziesii’) based on RFLP and RAPD markers. Theor Appl Genet 97:762–770CrossRefGoogle Scholar
  16. Jermstad KD, Bassoni DL, Jech KS, Wheeler NC, Neale DB (2001a) Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. I. Timing of vegetative bud flush. Theor Appl Genet 102(8):1142–1151CrossRefGoogle Scholar
  17. Jermstad KD, Bassoni DL, Wheeler NC, Anekonda TS, Aitken SN, Adams WT, Neale DB (2001b) Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. II. Spring and fall cold-hardiness. Theor Appl Genet 102:1152–1158CrossRefGoogle Scholar
  18. Jermstad KD, Bassoni DL, Jech KS, Ritchie GA, Wheeler NC, Neale DB (2003) Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. III. Quantitative trait loci-by-environment interactions. Genetics 165(3):1489–1506PubMedGoogle Scholar
  19. Johnson GR, Gartner BL (2006) Genetic variation in basic density and modulus of elasticity of coastal Douglas-fir. Tree Genet Genomes 3:25–33CrossRefGoogle Scholar
  20. Johnson GR, Wheeler NC, Strauss SS (2000) Financial feasibility of marker-aided selection in Douglas-fir. Can J For Res 30(12):1942–1952CrossRefGoogle Scholar
  21. Markussen T, Fladung M, Achere V, Favre JM, Faivre-Rampant P, Aragones A, Perez DD, Harvengt L, Espinel S, Ritter E (2003) Identification of QTLs controlling growth, chemical and physical wood property traits in Pinus pinaster (Ait.). Silvae Genet 52(1):8–15Google Scholar
  22. Megraw RA, Leaf G, Bremer D (1998) Longitudinal shrinkage and microfibril angle in loblolly pine. In: Microfibril angle in wood. University of Canterbury Press, Christchurch, New Zealand, pp 27–61Google Scholar
  23. Neale DB, Sewell MM, Brown GR (2002) Molecular dissection of the quantitative inheritance of wood property traits in loblolly pine. Ann For Sci 59(5–6):595–605CrossRefGoogle Scholar
  24. Otto SP, Jones CD (2000) Detecting the undetected: estimating the total number of loci underlying a quantitative trait. Genetics 156:2093–2197PubMedGoogle Scholar
  25. Remington DL, Whetten RW, Liu B-H, O’Malley DM (1999) Construction of an AFLP genetic map with nearly complete genome coverage in Pinus taeda. Theor Appl Genet 98:1279–1292PubMedCrossRefGoogle Scholar
  26. SAS (2003) SAS System for Windows version 9.1. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute. SAS Institute, Cary, NC, USAGoogle Scholar
  27. Seaton G, Haley CS, Knott SA, Kearsey M, Visscher PM (2002) QTL express: mapping quantitative trait loci in simple and complex pedigrees. Bioinformatics 18(2):339–340PubMedCrossRefGoogle Scholar
  28. Seth RS, Kingsland MA (1990) The reinforcing properties of softwood kraft pulps. Pulp Pap Can 91(7):68–72, 74–75Google Scholar
  29. Sewell MM, Sherman BK, Neale DB (1999) A consensus map for loblolly pine (Pinus taeda L.). I. Construction and integration of individual linkage maps from two outbred three-generation pedigrees. Genetics 151(1):321–330PubMedGoogle Scholar
  30. Sewell MM, Bassoni DL, Megraw RA, Wheeler NC, Neale DB (2000) Identification of QTLs influencing wood property traits in loblolly pine (Pinus taeda L.). I. Physical wood properties. Theor Appl Genet 101(8):1273–1281CrossRefGoogle Scholar
  31. Sewell MM, Davis MF, Tuskan GA, Wheeler NC, Elam CC, Bassoni DL, Neale DB (2002) Identification of QTLs influencing wood property traits in loblolly pine (Pinus taeda L.). II. Chemical wood properties. Theor Appl Genet 104(2–3):214–222PubMedCrossRefGoogle Scholar
  32. St. Clair JB (1994) Genetic variation in tree structure and its relation to size in Douglas-fir. I. Biomass partitioning, foliage efficiency, stem form, and wood density. Can J For Res 24(6):1226–1235Google Scholar
  33. Strauss SH, Lande R, Namkoong G (1992) Limitations of molecular-marker-aided selection in forest tree breeding. Can J For Res 22(7):1050–1061CrossRefGoogle Scholar
  34. Tappi Useful Method (1991) UM-250: acid-soluble lignin in wood and pulp. TAPPI Press, AtlantaGoogle Scholar
  35. Thamarus K, Groom K, Bradley A, Raymond CA, Schimleck LR, Williams ER, Moran GF (2004) Identification of quantitative trait loci for wood and fibre properties in two full-sib pedigrees of Eucalyptus globulus. Theor Appl Genet 109(4):856–864PubMedCrossRefGoogle Scholar
  36. Travis SE, Ritland K, Whitham TG, Keim P (1998) A genetic linkage map of Pinyon pine (Pinus edulis) based on amplified fragment length polymorphisms. Theor App Genet 97(5–6):871–880CrossRefGoogle Scholar
  37. Ukrainetz NK, Ritland K, Mansfield SD (2007) An AFLP linkage map for Douglas-fir based upon multiple full-sib families. Tree Genet Genomes DOI  10.1007/s11295-007-0099-8
  38. USDA (2000) Wood handbook: wood as an engineering material. University Press of the Pacific, Madison, Wisconsin, p 463Google Scholar
  39. Van Ooijen JW, Voorrips RE (2001) JoinMap 3.0, software for the calculation of genetic linkage maps. Plant Research International, Wageningen, The NetherlandsGoogle Scholar
  40. Vargas-Hernandez J, Adams WT (1991) Genetic variation of wood density components in young coastal Douglas-fir—implications for tree breeding. Can J For Res 21(12):1801–1807CrossRefGoogle Scholar
  41. Vargas-Hernandez J, Adams WT (1992) Age–age correlations and early selection for wood density in young coastal Douglas-fir. For Sci 38(2):467–478Google Scholar
  42. Vargas-Hernandez J, Adams WT, Krahmer RL (1994) Family variation in age trends of wood density traits in young coastal Douglas-fir. Wood Fiber Sci 26(2):229–236Google Scholar
  43. Visscher PM, Hopper JL (2001) Power of regression and maximum likelihood methods to map QTL from sib-pair and DZ twin data. Ann Hum Genet 65:583–601PubMedCrossRefGoogle Scholar
  44. Wang HH, Drummond JG, Reath SM, Hunt K, Watson PA (2001) An improved fibril angle measurement method for wood fibres. Wood Sci Technol 34:493–503CrossRefGoogle Scholar
  45. Wheeler NC, Jermstad KD, Krutovsky K, Aitken SN, Howe GT, Krakowski J, Neale DB (2005) Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. IV. Cold-hardiness QTL verification and candidate gene mapping. Mol Breed 15(2):145–156CrossRefGoogle Scholar
  46. Wu RL (1998) Genetic mapping of QTLs affecting tree growth and architecture in Populus: implications for ideotype breeding. Theor Appl Genet 96:447–457CrossRefGoogle Scholar
  47. Wu HX (2002) Study of early selection in tree breeding. 4. Efficiency of marker-aided early selection (MAES). Silvae Genet 51(5–6):261–269Google Scholar
  48. Wu RL, Han YF, Hu JJ, Fang JJ, Li L, Li ML, Zeng ZB (2000) An integrated genetic map of Populus deltoides based on amplified fragment length polymorphisms. Theor Appl Genet 100(8):1249–1256CrossRefGoogle Scholar
  49. Yoshimaru H, Ohba K, Tsurumi K, Tomaru N, Murai M, Mukai Y, Suyama Y Tsumura Y, Kawahara T, Sakamaki Y (1998) Detection of quantitative trait loci for juvenile growth, flower bearing and rooting ability based on a linkage map of sugi (Cryptomeria japonica D. Don). Theor Appl Genet 97:45–50CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Nicholas K. Ukrainetz
    • 1
  • Kermit Ritland
    • 2
  • Shawn D. Mansfield
    • 1
    Email author
  1. 1.Department of Wood ScienceUniversity of British ColumbiaVancouverCanada
  2. 2.Department of Forest ScienceUniversity of British ColumbiaVancouverCanada

Personalised recommendations