Plant Molecular Biology

, Volume 80, Issue 6, pp 555–569 | Cite as

Towards decoding the conifer giga-genome

  • John Mackay
  • Jeffrey F. D. Dean
  • Christophe Plomion
  • Daniel G. Peterson
  • Francisco M. Cánovas
  • Nathalie Pavy
  • Pär K. Ingvarsson
  • Outi Savolainen
  • M. Ángeles Guevara
  • Silvia Fluch
  • Barbara Vinceti
  • Dolores Abarca
  • Carmen Díaz-Sala
  • María-Teresa Cervera
Review

Abstract

Several new initiatives have been launched recently to sequence conifer genomes including pines, spruces and Douglas-fir. Owing to the very large genome sizes ranging from 18 to 35 gigabases, sequencing even a single conifer genome had been considered unattainable until the recent throughput increases and cost reductions afforded by next generation sequencers. The purpose of this review is to describe the context for these new initiatives. A knowledge foundation has been acquired in several conifers of commercial and ecological interest through large-scale cDNA analyses, construction of genetic maps and gene mapping studies aiming to link phenotype and genotype. Exploratory sequencing in pines and spruces have pointed out some of the unique properties of these giga-genomes and suggested strategies that may be needed to extract value from their sequencing. The hope is that recent and pending developments in sequencing technology will contribute to rapidly filling the knowledge vacuum surrounding their structure, contents and evolution. Researchers are also making plans to use comparative analyses that will help to turn the data into a valuable resource for enhancing and protecting the world’s conifer forests.

Keywords

Conifers Giga-genome sequencing Functional genomics Comparative genomics Integrative studies 

References

  1. Acheré V, Faivre-Rampant P, Jeandroz S, Besnard G, Markussen T, Aragones A, Fladung M, Ritter E, Favre JM (2004) A full saturated linkage map of Picea abies including AFLP, SSR, ESTP, 5S rDNA and morphological markers. Theor Appl Genet 108:1602–1613PubMedCrossRefGoogle Scholar
  2. Bagal UR, Leebens-Mack JH, Lorenz WW, Dean JFD (2012) Phylogenomic analysis of the phenylalanine ammonia Iyase gene family in loblolly pine (Pinus taeda L.). BMC Genomics 13:S1PubMedGoogle Scholar
  3. Ball RD (2001) Bayesian methods for quantitative trait loci mapping based on model selection: approximate analysis using the Bayesian information criterion. Genetics 159:1351–1364PubMedGoogle Scholar
  4. Bautista R, Villalobos DP, Diaz-Moreno S, Canton FR, Canovas FM, Claros MG (2007) Toward a Pinus pinaster bacterial artificial chromosome library. Ann Forest Sci 64:855–864CrossRefGoogle Scholar
  5. Beaulieu J, Doerksen T, Boyle B, Clément S, Deslauriers M, Beauseigle S, Blais S, Poulin P-L, Lenz P, Caron S, Rigault P, Bicho P, Bousquet J, MacKay J (2011) Association genetics of wood physical traits in the conifer white spruce and relationships with gene expression. Genetics 188:197–214PubMedCrossRefGoogle Scholar
  6. Bennett MD, Leitch IJ (2005) Angiosperm DNA C-values database. http://www.kew.org/cvalues/. Release 6.0, accessed Oct 2005
  7. Bennetzen JL (2002) Mechanism and rates of genome expansion and contraction in flowering plants. Genetica 115:29–36PubMedCrossRefGoogle Scholar
  8. Brendel O, Pot D, Plomion C, Rozenberg P, Guehl JM (2002) Genetic parameters and QTL analysis of d13 in maritime pine. Plant Cell Environ 25:945–953CrossRefGoogle Scholar
  9. 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 164:1537–1546PubMedGoogle Scholar
  10. Buckler ES, Holland JB, Bradbury PJ, Acharya CB, Brown PJ, Browne C, Ersoz E, Flint-Garcia S, Garcia A, Glaubitz JC, Goodman MM, Harjes C, Guill K, Kroon DE, Larsson S, Lepak NK, Li H, Mitchell SE, Pressoir G, Peiffer JA, Rosas MO, Rocheford TR, Romay MC, Romero S, Salvo S, Villeda HS, Sofia da Silva H, Sun Q, Tian F, Upadyayula N, Ware D, Yates H, Yu J, Zhang Z, Kresovich S, McMullen MD (2009) The genetic architecture of maize flowering time. Science 325:714–718PubMedCrossRefGoogle Scholar
  11. Chagné D, Brown G, Lalanne C, Madur D, Pot D, Neale D, Plomion C (2003) Molecular breeding—comparative genome and QTL mapping between maritime and loblolly pines. Mol Breed 12:185–195. doi:10.1023/a1026318327911 CrossRefGoogle Scholar
  12. Chancerel E, Lepoittevin C, Le Provost G, Lin YC, Jaramillo-Correa JP, Eckert AJ, Wegrzyn JL, Zelenika D, Boland A, Frigerio JM, Chaumeil P, Garnier-Géré P, Boury C, Grivet D, González-Martínez SC, Rouzé P, Van de Peer Y, Neale DB, Cervera MT, Kremer A, Plomion Ch (2011) Development and implementation of a highly multiplexed SNP array for genetic mapping in maritime pine and comparative mapping with loblolly pine. BMC Genomics 12:368PubMedCrossRefGoogle Scholar
  13. Dean JFD (2011) Future prospects. In: Plomion C, Bousquet J, Kole C (eds) Genetics, genomics and breeding of conifers trees. Edenbridge Science Publishers and CRC Press, New York, pp 404–438Google Scholar
  14. Devey ME, Carson SD, Nolan MF, Matheson AC, Te Riini C, Hohepa J (2004a) QTL associations for density and diameter in Pinus radiata and the potential for marker-aided selection. Theor Appl Genet 108:516–524PubMedCrossRefGoogle Scholar
  15. Devey ME, Groom KA, Nolan MF, Bell JC, Dudzinski MJ, Old KM, Matheson AC, Moran GF (2004b) Detection and verification of quantitative trait loci for resistance to Dothistroma needle blight in Pinus radiata. Theor Appl Genet 108:516–524. doi:10.1007/s00122-003-1446-2 PubMedCrossRefGoogle Scholar
  16. Dillon SK, Nolan M, Li W, Bell C, Wu HX, Southerton SG (2010) Allelic variation in cell wall candidate genes affecting solid wood properties in natural populations and land races of Pinus radiata. Genetics 185:1477–1487PubMedCrossRefGoogle Scholar
  17. Dolgosheina EV, Morin RD, Aksay G, Sahinalp SC, Magrini V, Mardis ER, Mattsson J, Unrau PJ (2008) Conifers have a unique small RNA silencing signature. RNA 14:1508–1515PubMedCrossRefGoogle Scholar
  18. Echt CS, Saha S, Krutovsky KV, Wimalanathan K, Erpelding JE, Liang C, Nelson CD (2011) An annotated genetic map of loblolly pine based on microsatellite and cDNA markers. BMC Genet 12:17PubMedCrossRefGoogle Scholar
  19. Eckert AJ, Bower AD, Wegrzyn JL, Pande B, Jermstad KD, Krutovsky KV, Neale DB, Clair JB (2009a) Association genetics of coastal Douglas fir (Pseudotsuga menziesii var. menziesii, Pinaceae). I. Cold-hardiness related traits. Genetics 182:1289–1302PubMedCrossRefGoogle Scholar
  20. Eckert AJ, Pande B, Ersoz ES, Wright MH, Rashbrook VK, Nicolet CM, Neale DB (2009b) High-throughput genotyping and mapping of single nucleotide polymorphisms in loblolly pine (Pinus taeda L.). Tree Genet Genomes 5:225–234CrossRefGoogle Scholar
  21. Eckert AJ, van Heerwaarden J, Wegrzyn JL, Nelson CD, Ross-Ibarra J, González-Martinez SC, Neale DB (2010) Patterns of population structure and environmental associations to aridity across the range of loblolly pine (Pinus taeda L., Pinaceae). Genetics 185:969–982PubMedCrossRefGoogle Scholar
  22. Eckert AJ, Wegrzyn JL, Cumbie WP, Goldfarb B, Huber DA, Tolstikov V, Fiehn O, Neale DB (2012) Association genetics of the loblolly pine (Pinus taeda, Pinaceae) metabolome. New Phytol 193:890–902. doi:10.1111/j.1469-8137.2011.03976.x PubMedCrossRefGoogle Scholar
  23. El Kayal W, Allen CC, Ju CJ, Adams E, King-Jones S, Zaharia LI, Abrams SR, Cooke JE (2011) Molecular events of apical bud formation in white spruce, Picea glauca. Plant Cell Environ 34:480–500PubMedCrossRefGoogle Scholar
  24. Emebiri LC, Devey ME, Matheson AC, Slee MU (1997) Linkage of RAPD markers to NESTUR, a stem growth index in radiata pine seedlings. Theor Appl Genet 95:119–124CrossRefGoogle Scholar
  25. Emebiri LC, Devey ME, Matheson AC, Slee MU (1998a) Age-related changes in the expression of QTLs for growth in radiata pine seedlings. Theor Appl Genet 97:1053–1061CrossRefGoogle Scholar
  26. Emebiri LC, Devey ME, Matheson AC, Slee MU (1998b) Interval mapping of quantitative trait loci affecting NESTUR, a stem growth efficiency index of radiata pine seedlings. Theor Appl Genet 97:1062–1068CrossRefGoogle Scholar
  27. Farjon A (2008) A natural history of conifers. Timber Press, Portland 304 pGoogle Scholar
  28. Futamura N, Totoki Y, Toyoda A, Igasaki T, Nanjo T, Seki M, Sakaki Y, Mari A, Shinozaki K, Shohara K (2008) Characterization of expressed sequence tags from a full-length enriched cDNA library of Cryptomeria japonica male strobili. BMC Genomics 9:383PubMedCrossRefGoogle Scholar
  29. Gaut BS, Ross-Ibarra J (2008) Selection of angiosperm genomes. Science 320:484–486PubMedCrossRefGoogle Scholar
  30. Gernandt DS, Willyard A, Syring JV, Liston A (2011) The conifers (Pinophyta). In: Plomion C, Bousquet J, Kole C (eds) Genetics, genomics and breeding of conifers trees. Edenbridge Science Publishers and CRC Press, New York, pp 1–39Google Scholar
  31. González-Martinez SC, Huber D, Ersoz E, Davis JM, Neale DB (2008) Association genetics in Pinus taeda L. II. Carbon isotope discrimination. Heredity 101:19–26PubMedCrossRefGoogle Scholar
  32. González-Martínez SC, Wheeler NC, Ersoz E, Nelson CD, Neale DB (2007) Association genetics in Pinus taeda L. I. Wood property traits. Genetics 175:399–409PubMedCrossRefGoogle Scholar
  33. Grattapaglia D, Resende MDV (2011) Genomic selection in forest tree breeding. Tree Genet Genomes 7:241–255CrossRefGoogle Scholar
  34. Groover AT, Devey ME, Lee JM, Megraw R, Mitchell-Olds T, Sherman B, Vujcic S, Williams C, Neale DB (1994) Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine. Genetics 138:1293–1300PubMedGoogle Scholar
  35. Guillet-Claude C, Isabel N, Pelgas B, Bousquet J (2004) The evolutionary implications of knox-I gene duplications in conifers: correlated evidence from phylogeny, gene mapping, and analysis of functional divergence. Mol Biol Evol 21:2232–2245PubMedCrossRefGoogle Scholar
  36. Gwaze DP, Zhou Y, Reyes-Valdés MH, Al-Rababah MA, Williams CG (2003) Haplotypic QTL mapping in an outbred pedigree. Genet Res 81:43–50PubMedCrossRefGoogle Scholar
  37. Hamberger B, Hall D, Yuen M, Oddy C, Hamberger B, Keeling CI, Ritland C, Ritland K, Bohlmann J (2009) Targeted isolation, sequence assembly and characterization of two white spruce (Picea glauca) BAC clones for terpenoid synthase and cytochrome P450 genes involved in conifer defence reveal insights into a conifer genome. BMC Plant Biol 9:106PubMedCrossRefGoogle Scholar
  38. Holliday JA, Ralph SG, White R, Bohlmann J, Aitken SN (2008) Global monitoring of autumn gene expression within and among phenotypically divergent populations of Sitka spruce (Picea sitchensis). New Phytol 178:103–122PubMedCrossRefGoogle Scholar
  39. Holliday JA, Ritland K, Aitken SN (2010) Widespread, ecologically relevant genetic markers developed from association mapping of climate-related traits in Sitka spruce (Picea sitchensis). New Phytol 188:501–514PubMedCrossRefGoogle Scholar
  40. Hurme P, Sillanpaa MJ, Arjas E, Repo T, Savolainen O (2000) Genetic basis of climatic adaptation in scots pine by Bayesian quantitative trait locus analysis. Genetics 156:1309–1322PubMedGoogle Scholar
  41. Islam-Faridi MN, Nelson CD, Kubisiak T (2007) Reference karyotype and cytomolecular map for loblolly pine (Pinus taeda L.). Genome 50:241–251PubMedCrossRefGoogle Scholar
  42. Iwata H, Hayashi T, Tsumura Y (2011) Prospects for genomic selection in conifer breeding: a simulation study of Cryptomeria japonica. Tree Genet Genomes 7:747–758CrossRefGoogle Scholar
  43. Jermstad KD, Bassoni DL, Jech KS, Wheeler NC, Neale DB (2001) Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. I. Timing of vegetative bud flush. Theor Appl Genet 102:1142–1151CrossRefGoogle Scholar
  44. 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 165:1489–1506PubMedGoogle Scholar
  45. Jermstad KD, Eckert AJ, Wegrzyn JL, Delfino-Mix A, Davis DA, Burton DC, Neale DB (2011) Comparative mapping in Pinus: sugar pine (Pinus lambertiana Dougl.) and loblolly pine (Pinus taeda L.). Tree Genet Genomes 7:457–468CrossRefGoogle Scholar
  46. Kang BY, Mann IK, Major JE, Rajora OP (2010) Near-saturated and complete genetic linkage map of black spruce (Picea mariana). BMC Genomics 11:515PubMedCrossRefGoogle Scholar
  47. Kaya Z, Sewell MM, Neale DB (1999) Identification of quantitative trait loci influencing annual height- and diameter-increment growth in loblolly pine (Pinus taeda L.). Theor Appl Genet 98:586–592CrossRefGoogle Scholar
  48. Kenrick P (1999) The family tree flowers. Nature 402:358–359PubMedCrossRefGoogle Scholar
  49. Knott S, Neale DN, Sewell MM, Haley C (1997) Multiple marker mapping of quantitative trait loci in an outbred pedigree of loblolly pine. Theor Appl Genet 94:810–820CrossRefGoogle Scholar
  50. Komulainen P, Brown GR, Mikkonen M, Karhu A, Garcia-Gil MR, O’Malley D, Lee B, Neale DB, Savolainen O (2003) Comparing EST-based genetic maps between Pinus sylvestris and Pinus taeda. Theor Appl Genet 107:667–678PubMedCrossRefGoogle Scholar
  51. Kovach A, Wegrzyn JL, Parra G, Holt C, Bruening GE, Loopstra CA, Hartigan J, Yandell M, Langley CH, Korf I, Neale DB (2010) The Pinus taeda genome is characterized by diverse and highly diverged repetitive sequences. BMC Genomics 11:420PubMedCrossRefGoogle Scholar
  52. Kubisiak TL, Nelson CD, Nowak J, Friend AL (2000) Genetic linkage mapping of genomic regions conferring tolerance to high aluminum in slash pine. J Sustain Forest 10:69–78CrossRefGoogle Scholar
  53. Kumar S, Spelman R, Garrick D, Richardson TE, Wilcox PL (2000) Multiple marker mapping of quantitative trait loci on chromosome three in an outbred pedigree of radiata pine. Theor Appl Genet 100:926–933CrossRefGoogle Scholar
  54. Le Dantec L, Chagné D, Pot D, Cantin O, Garnier-Géré P, Bedon F, Frigerio JM, Chaumeil P, Léger P, Garcia V, Laigret F, de Daruvar A, Plomion C (2004) Automated SNP detection in expressed sequence tags: statistical considerations and application to maritime pine sequences. Plant Mol Biol 54:461–470PubMedCrossRefGoogle Scholar
  55. Lerceteau EC, Plomion C, Andersson B (2000) AFLP mapping and detection of quantitative trait loci (QTLs) for economically important traits in Pinus sylvestris: a preliminary study. Mol Breed 6:451–459CrossRefGoogle Scholar
  56. Li X, Wu HX, Southerton SG (2010) Comparative genomics reveals conservative evolution of the xylem transcriptome in vascular plants. BMC Evol Biol 10: Article 190Google Scholar
  57. Liewlaksaneeyanawin C, Zhuang J, Tang M, Farzaneh N, Lueng G, Cullis C, Findlay S, Ritland CE, Bohlmann J, Ritland K (2009) Identification of COS markers in the Pinaceae. Tree Genet Genomes 5:247–255CrossRefGoogle Scholar
  58. Lorenz WW, Dean JFD (2002) SAGE profiling and demonstration of differential gene expression along the axial developmental gradient of lignifying xylem in loblolly pine (Pinus taeda). Tree Physiol 22:301–310PubMedCrossRefGoogle Scholar
  59. Lorenz WW, Alba R, Yu Y-S, Bordeaux JM, Simões M, Dean JFD (2011) Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.). BMC Genomics 12:264PubMedCrossRefGoogle Scholar
  60. Lorenz WW, Neale DB, Jermstad KD, Howe GT, Rogers DL, Bordeaux JM, Ayyampalayam S, Dean JFD (2012) Conifer DBMagic: a database housing multiple de novo transcriptome assemblies for twelve diverse conifer species. Tree Genet Genomes. doi:10.1007/s11295-012-0547-y Google Scholar
  61. Lynch M (2007) The origins of genome architecture. Sinauer Associates Inc, SunderlandGoogle Scholar
  62. MacKay JJ, Dean JFD (2011) Transcriptomics. In: Plomion C, Bousquet J, Kole C (eds) Genetics, genomics and breeding of conifers trees. Edenbridge Science Publishers and CRC Press, New York, pp 323–357Google Scholar
  63. Magbanua ZV, Ozkan S, Bartlett BD, Chouvarine P, Saski CA, Liston A, Cronn RC, Nelson CD, Peterson DG (2011) Adventures in the enormous: a 1.8 million clone BAC library for the 21.7 Gb genome of loblolly pine. PLoS One 6:e16214Google Scholar
  64. Markussen T, Fladung M, Achere V, Favre JM, Faivre-Rampant P, Aragones A, Da Silva P, Havengt L, Ritter E (2003) Identification of QTLs controlling growth, chemical and physical wood property traits in Pinus pinaster (Ait.). Silvae Genetica 52:8–15Google Scholar
  65. Morgante M, De Paoli E (2011) Toward the conifer genome sequence. In: Plomion C, Bousquet J, Kole C (eds) Genetics, genomics and breeding of conifers trees. Edenbridge Science Publishers and CRC Press, New York, pp 389–403Google Scholar
  66. Moriguchi Y, Ujino-Ihara T, Futamura N, Saito M, Ueno S, Matsumoto A, Tani N, Taira H, Shinohara K, Tsumura Y (2012) The construction of a high-density linkage map for identifying SNP markers that are tightly linked to a nuclear-recessive major gene for male sterility in in Cryptomeria japonica D. Don. BMC Genomics 19:95CrossRefGoogle Scholar
  67. Morin RD, Aksay G, Dolgosheina E, Ebhardt HA, Magrini V, Mardis ER, Sahinalp SC, Unrau PJ (2008) Comparative analysis of the small RNA transcriptomes of Pinus contorta and Oryza sativa. Genome Res 18:571–584PubMedCrossRefGoogle Scholar
  68. Morse AM, Peterson DG, Islam-Faridi MN, Smith KE, Magbanua Z, Garcia SA, Kubisiak TL, Amerson HV, Carloson JE, Nelson CD, Davis JM (2009) Evolution of genome size and complexity in Pinus. PLoS One 4:e4332PubMedCrossRefGoogle Scholar
  69. Murray BG, Leitch IJ, Bennett MD (2004) Gymnosperm DNA C-values database. http://www.kew.org/cvalues/. Release 3.0, accessed Dec 2004
  70. Neale DB, Ingvarsson PK (2008) Population, quantitative and comparative genomics of adaptation in forest trees. Curr Opin Plant Biol 11:149–155PubMedCrossRefGoogle Scholar
  71. Neale DB, Kremer A (2011) Forest tree genomics: growing resources and applications. Nat Rev Genet 12:111–122PubMedCrossRefGoogle Scholar
  72. Nelson CD, Johnsen KH (2008) Genomic and physiological approaches to advancing forest tree improvement. Tree Physiol 28:1135–1143PubMedCrossRefGoogle Scholar
  73. Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, Shaffer T, Wong M, Bhattacharjee A, Eichler EE, Bamshad M, Nickerson DA, Shendure J (2009) Targeted capture and massively parallel sequencing of 12 human exomes. Nature 461:272–276PubMedCrossRefGoogle Scholar
  74. Parchman T, Geist K, Grahnen J, Benkman C, Buerkle A (2010) Transcriptome sequencing in an ecologically important tree species: assembly, annotation and marker discovery. BMC Genomics 11:180PubMedCrossRefGoogle Scholar
  75. Parchman TL, Gompert Z, Mudge J, Schilkey FD, Benkman CW, Buerkle C (2012) Genome-wide association genetics of an adaptive trait in lodgepole pine. Mol Ecol 21:2991–3005PubMedCrossRefGoogle Scholar
  76. Pavy N, Parsons LS, Paule C, MacKay J, Bousquet J (2006) Automated SNP detection from a large collection of white spruce expressed sequences: contributing factors and approaches for the categorization of SNPs. BMC Genomics 7:174PubMedCrossRefGoogle Scholar
  77. Pavy N, Boyle B, Nelson C, Paule C, Giguère I, Caron S, Parsons LS, Dallaire N, Bedon F, Bérubé H, Cooke J, Mackay J (2008a) Identification of conserved core xylem gene sets: conifer cDNA microarray development, transcript profiling and computational analyses. New Phytol 180:766–786PubMedCrossRefGoogle Scholar
  78. Pavy N, Pelgas B, Beauseigle S, Blais S, Gagnon F, Gosselin I, Lamothe M, Isabel N, Bousquet J (2008b) Enhancing genetic mapping of complex genomes through the design of highly-multiplexed SNP arrays: application to the large and unsequenced genomes of white spruce and black spruce. BMC Genomics 9:21PubMedCrossRefGoogle Scholar
  79. Pavy N, Namroud MC, Gagnon F, Isabel N, Bousquet J (2012) The heterogeneous levels of linkage disequilibrium in white spruce genes and comparative analysis with other conifers. Heredity 108:273–284PubMedCrossRefGoogle Scholar
  80. Pelgas B, Beauseigle S, Acheré V, Jeandroz S, Bousquet J, Isabel N (2006) Comparative genome mapping among Picea glauca, P. abies and P. mariana × rubens, and correspondence with other Pinaceae. Theor Appl Genet 113:1371–1393PubMedCrossRefGoogle Scholar
  81. Pelgas B, Bousquet J, Meirmans PG, Ritland K, Isabel N (2011) QTL mapping in white spruce: gene maps and genomic regions underlying adaptive traits across pedigrees, years and environments. BMC Genomics 12:145PubMedCrossRefGoogle Scholar
  82. Peterson DG, Schulze SR, Sciara EB, Lee SA, Bowers JE, Nagel A, Jiang N, Tibbitts DC, Wessler SR, Paterson AH (2002) Integration of Cot analysis, DNA cloning, and high-throughput sequencing facilitates genome characterization and gene discovery. Genome Res 12:795–807PubMedCrossRefGoogle Scholar
  83. Philippe R, Choulet F, Paux E, van Oeveren J, Tang J, Wittenberg AH, Janssen A, van Eijk MJ, Stormo K, Alberti A, Wincker P, Akhunov E, van der Vossen E, Feuillet C (2012) Whole genome profiling provides a robust framework for physical mapping and sequencing in the highly complex and repetitive wheat genome. BMC Genomics 13:47PubMedCrossRefGoogle Scholar
  84. Plomion C, Durel CE, O’Malley DM (1996a) Genetic dissection of height in maritime pine seedlings raised under accelerated growth conditions. Theor Appl Genet 93:849–858CrossRefGoogle Scholar
  85. Plomion C, Yani A, Marpeau A (1996b) Genetic determinism of δ3-carene in maritime pine using RAPD markers. Genome 39:1123–1127PubMedCrossRefGoogle Scholar
  86. Plomion C, Chagné D, Pot D, Kumar S, Wilcox PL, Burdon RD, Prat DG, Paiva J, Chaumeil P, Vendramin GG, Sebastiani F, Nelson CD, Echt CS, Savolainen O, Kubisiak TL, Cervera MT, de Maria N, Islam-Faridi MN (2007) Pines. In: Genome mapping and molecular breeding in plants: volume 7, Forest Trees. Springer, Berlin, pp 29–92Google Scholar
  87. Plomion C, Bousquet J, Kole C (2011) Genetics, genomics, and breeding of conifers. CRC Press, Boca Ratón p 456Google Scholar
  88. Pot D, Rodrigues JC, Rozenberg P, Chantre G, Tibbits J, Cahalan C, Pichavant F, Plomion C (2006) QTLs and candidate genes for wood properties in maritime pine (Pinus pinaster Ait.). Tree Genet Genomes 2:10–24CrossRefGoogle Scholar
  89. Pozo NF, Canales J, Fernandez DG, Villalobos D, Moreno SD, Bautista R, Monterroso AF, Guevara MA, Perdiguero P, Collada C, Cervera MT, Soto A, Ordas R, Canton FR, Avila C, Canovas FM, Claros MG (2011) EuroPineDB: a high-coverage web database for maritime pine transcriptome. BMC Genomics 12:366CrossRefGoogle Scholar
  90. Prunier J, Laroche J, Beaulieu J, Bousquet J (2011) Scanning the genome for gene SNPs related to climate adaptation and estimating selection at the molecular level in boreal black spruce. Mol Ecol 20:1702–1716PubMedCrossRefGoogle Scholar
  91. Rabinowicz PD, Citek R, Budiman MA, Nunberg A, Bedell JA, Lakey N, O’Shaughnessy AL, Nascimento LU, McCombie WR, Martienssen RA (2005) Differential methylation of genes and repeats in land plants. Genome Res 15:1431–1440PubMedCrossRefGoogle Scholar
  92. Ralph S, Chun H, Kolosova N, Cooper D, Oddy C, Ritland C, Kirkpatrick R, Moore R, Barber S, Holt R, Jones SJM, Marra MA, Douglas CJ, Ritland K, Bohlmann J (2008) A conifer genomics resource of 200,000 spruce (Picea spp.) ESTs and 6,464 high-quality, sequence-finished full-length cDNAs for Sitka spruce (Picea sitchensis). BMC Genomics 9:484PubMedCrossRefGoogle Scholar
  93. Raven PH, Evert RF, Eichhorn SE (2005) Biology of plants, 7th edn. W.H. Freeman and Co., New York p 686Google Scholar
  94. Rigault P, Boyle B, Lepage P, Cooke J, Bousquet J, MacKay J (2011) A white spruce gene catalog for conifer genome analyses. Plant Physiol 157:14–28PubMedCrossRefGoogle Scholar
  95. Ritland K, Krutovsky KV, Tsumura Y, Pelgas B, Isabel N, Bousquet J (2011) Genetic mapping in conifers. In: Plomion C, Bousquet J, Kole C (eds) Genetics, genomics and breeding of conifers trees. Edenbridge Science Publishers and CRC Press, New York, pp 196–238Google Scholar
  96. 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 101:1273–1281CrossRefGoogle Scholar
  97. 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 104:214–222PubMedCrossRefGoogle Scholar
  98. Shepherd M, Cross M, Dieters MJ, Henry R (2002) Branch architecture QTL for Pinus elliottii var. elliottii x Pinus caribea var. hondurensis hybrids. Ann Forest Sci 59:617–625CrossRefGoogle Scholar
  99. Shepherd M, Huang S, Eggler P, Cross M, Dale G, Dieters M, Henry R (2006) Congruence in QTL for adventitious rooting in Pinus elliottii × Pinus caribaea hybrids resolves between and within-species effects. Mol Breed 18:11–28CrossRefGoogle Scholar
  100. Springer NM, Xu XQ, Barbazuk WB (2004) Utility of different gene enrichment approaches toward identifying and sequencing the maize gene space. Plant Physiol 136:3023–3033PubMedCrossRefGoogle Scholar
  101. Ukrainetz NK, Ritland K, Mansfield SD (2008) Identification of quantitative trait loci for wood quality and growth across eight full-sib coastal Douglas-fir families. Tree Genet Genomes 4:159–170CrossRefGoogle Scholar
  102. Wall PK, Leebens-Mack J, Chanderbali AS, Barakat A, Wolcott E, Liang HY, Landherr L, Tomsho LP, Hu Y, Carlson JE, Ma H, Schuster SC, Soltis DE, Soltis PS, Altman N, dePamphilis CW (2009) Comparison of next generation sequencing technologies for transcriptome characterization. BMC Genomics 10:347PubMedCrossRefGoogle Scholar
  103. Weng C, Kubisiak TL, Nelson CD, Stine M (2002) Mapping quantitative trait loci controlling early growth in a (longleaf pine × slash pine) × slash pine BC1 family. Theor Appl Genet 104:852–859PubMedCrossRefGoogle Scholar
  104. 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 15:145–156CrossRefGoogle Scholar
  105. White TL, Adams WT, Neale DB (2007) Forest genetics. CABI, Cambridge p 682CrossRefGoogle Scholar
  106. Yakovlev IA, Fossdal CG, Johnsen O (2010) MicroRNAs, the epigenetic memory and climatic adaptation in Norway spruce. New Phytol 187:1154–1169PubMedCrossRefGoogle Scholar
  107. Yazdani R, Nilsson JE, Plomion C, Mathur G (2003) Marker trait association for autumn cold acclimatation and growth rhythm in Pinus sylvestris. Scand J For Res 18:29–38Google Scholar
  108. Zhang Y, Zhang S, Han S, Li X, Qi L (2012) Transcriptome profiling and in silico analysis of somatic embryos in Japanese larch (Larix leptolepis). Plant Cell Rep. doi:10.1007/s00299-012-1277-1 Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • John Mackay
    • 1
  • Jeffrey F. D. Dean
    • 2
  • Christophe Plomion
    • 3
  • Daniel G. Peterson
    • 4
  • Francisco M. Cánovas
    • 5
  • Nathalie Pavy
    • 1
  • Pär K. Ingvarsson
    • 6
  • Outi Savolainen
    • 7
  • M. Ángeles Guevara
    • 8
  • Silvia Fluch
    • 9
  • Barbara Vinceti
    • 10
  • Dolores Abarca
    • 11
  • Carmen Díaz-Sala
    • 11
  • María-Teresa Cervera
    • 8
  1. 1.Center for Forest Research, Institute for Integrative and Systems BiologyUniversité Laval, QuébecQuébecCanada
  2. 2.Department of Biochemistry and Molecular Biology, Warnell School of Forestry and Natural Resources, Davison Life SciencesUniversity of GeorgiaAthensUSA
  3. 3.UMR BIOGECOINRACestasFrance
  4. 4.Institute for Genomics, Biocomputing and Biotechnology (IGBB)Mississippi State UniversityMississippi StateUSA
  5. 5.Departamento de Biología Molecular y Bioquímica, Facultad de CienciasUniversidad de MálagaMálagaSpain
  6. 6.Department of Ecology and Environmental Science, Umeå Plant Science CentreUmeå UniversityUmeåSweden
  7. 7.Department of Biology and Biocenter OuluUniversity of OuluOuluFinland
  8. 8.Genomics and Forest Ecology, Forest Research Centre INIA-CIFORNational Research Institute for Agricultural and Food Technology (INIA)MadridSpain
  9. 9.Health and Environment Department, Platform for Integrated Clone Management (PICME)AIT Austrian Institute of Technology GmbHTullnAustria
  10. 10.Bioversity InternationalMaccarese (Fiumicino) RomeItaly
  11. 11.Department of Plant BiologyUniversity of AlcaláAlcalá de Henares, MadridSpain

Personalised recommendations