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Genomic selection in forest tree breeding: the concept and an outlook to the future

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Abstract

Using large numbers of DNA markers to predict genetic merit [genomic selection (GS)] is a new frontier in plant and animal breeding programs. GS is now routinely used to select superior bulls in dairy cattle breeding. In forest trees, a few empirical proof of-concept studies suggest that GS could be successful. However, application of GS in forest tree breeding is still in its infancy. The major hurdle is lack of high throughput genotyping platforms for trees, and the high genotyping costs, though, the cost of genotyping will likely decrease in the future. There has been a growing interest in GS among tree breeders, forest geneticists, and tree improvement managers. A broad overview of pedigree reconstruction and GS is presented. Underlying reasons for failures of marker-assisted selection were summarized and compared with GS. Challenges of GS in forest tree breeding and the outlook for the future are discussed, and a GS plan for a cloned loblolly pine breeding population is presented. This review is intended for tree breeders, forest managers, scientist and students who are not necessarily familiar with genomic or quantitative genetics jargon.

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References

  • Aguilar I, Misztal I, Johnson DL, Legarra A, Tsuruta S, Lawlor TJ (2010) Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. J Dairy Sci 93(2):743–752. doi:10.3168/jds.2009-2730

    Article  CAS  PubMed  Google Scholar 

  • Anderson EC, Garza JC (2006) The power of single-nucleotide polymorphisms for large-scale parentage inference. Genetics 172(4):2567–2582. doi:10.1534/genetics.105.048074

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Beavis WD (1994) The power and deceit of QTL experiments: lessons from comparative QTL studies. In: Proceedings of the forty-ninth annual corn and sorghum industry research conference. American Seed Trade Association, Washington, DC, pp 250–266

  • Bernardo R (2008) Molecular markers and selection for complex traits in plants: learning from the last 20 years. Crop Sci 48(5):1649. doi:10.2135/cropsci2008.03.0131

    Article  Google Scholar 

  • Birol I, Raymond A, Jackman SD, Pleasance S, Coope R, Taylor GA, Saint Yuen MM et al (2013) Assembling the 20 Gb white spruce (Picea glauca) genome from whole-genome shotgun sequencing data. Bioinformatics. doi:10.1093/bioinformatics/btt178

  • Blouin MS (2003) DNA-based methods for pedigree reconstruction and kinship analysis in natural populations. Trends Ecol Evol 18(10):503–511. doi:10.1016/S0169-5347(03)00225-8

    Article  Google Scholar 

  • Boichard D, Guillaume F, Baur A, Croiseau P, Rossignol MN, Boscher MY, Druet T et al (2012) Genomic selection in French dairy cattle. Anim Prod Sci 52(3):115. doi:10.1071/AN11119

    Article  Google Scholar 

  • Calus MPL, Veerkamp RF (2007) Accuracy of breeding values when using and ignoring the polygenic effect in genomic breeding value estimation with a marker density of one SNP per cM. J Anim Breed Genet 124(6):362–368. doi:10.1111/j.1439-0388.2007.00691.x

    Article  CAS  PubMed  Google Scholar 

  • Chagné D, Brown G, Lalanne C, Madur D, Pot D, Neale D, Plomion C (2003) Comparative genome and QTL mapping between maritime and loblolly pines. Mol Breeding 12(3):185–195. doi:10.1023/A:1026318327911

    Article  Google Scholar 

  • Chen CY, Misztal I, Aguilar I, Legarra A, Muir WM (2011) Effect of different genomic relationship matrices on accuracy and scale. J Anim Sci 89(9):2673–2679. doi:10.2527/jas.2010-3555

    Article  CAS  PubMed  Google Scholar 

  • Chen C, Mitchell SE, Elshire RJ, Buckler ES, El-Kassaby YA (2013) Mining conifers’ mega-genome using rapid and efficient multiplexed high-throughput genotyping-by-sequencing (GBS) SNP discovery platform. Tree Genet Genomes 9(6):1537–1544. doi:10.1007/s11295-013-0657-1

    Article  Google Scholar 

  • Collard BCY, Jahufer MZZ, Brouwer JB, Pang ECK (2005) An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: the basic concepts. Euphytica 142(1–2):169–196

    Article  CAS  Google Scholar 

  • Davey JW, Hohenlohe PA, Etter PD, Boone JQ, Catchen JM, Blaxter ML (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet 12(7):499–510. doi:10.1038/nrg3012

    Article  CAS  PubMed  Google Scholar 

  • Dekkers JCM (2004) Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons. J Anim Sci 82(13 suppl):E313–E328

    PubMed  Google Scholar 

  • Dekkers JCM, Hospital F (2002) Multifactorial genetics the use of molecular genetics in the improvement of agricultural populations. Nat Rev Genet 3(1):22–32. doi:10.1038/nrg701

    Article  CAS  PubMed  Google Scholar 

  • Devey ME, Carson SD, Nolan MF, Matheson AC, Te Riini C, Hohepa J (2004) QTL associations for density and diameter in Pinus radiata and the potential for marker-aided selection. Theor Appl Genet 108(3):516–524. doi:10.1007/s00122-003-1446-2

    Article  CAS  PubMed  Google Scholar 

  • Doerksen TK, Herbinger CM (2010) Impact of reconstructed pedigrees on progeny-test breeding values in red spruce. Tree Genet Genomes 6(4):591–600. doi:10.1007/s11295-010-0274-1

    Article  Google Scholar 

  • Eckert AJ, van Heerwaarden J, Wegrzyn JL, Nelson CD, Ross-Ibarra J, González-Martínez 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(3):969–982. doi:10.1534/genetics.110.115543

  • Eggen A (2012) The development and application of genomic selection as a new breeding paradigm. Anim Front 2(1):10–15. doi:10.2527/af.2011-0027

    Article  Google Scholar 

  • El-Kassaby Y, Lstibůrek M (2009) Breeding without breeding. Genet Res 91(02):111–120. doi:10.1017/S001667230900007X

    Google Scholar 

  • El-Kassaby YA, Funda T, Lai BSK (2010) Female reproductive success variation in a Pseudotsuga menziesii seed orchard as revealed by pedigree reconstruction from a bulk seed collection. J Hered 101(2):164–168. doi:10.1093/jhered/esp126

    Article  PubMed  Google Scholar 

  • El-Kassaby YA, Cappa EP, Liewlaksaneeyanawin C, Klápště J, Lstibůrek M (2011) Breeding without breeding: is a complete pedigree necessary for efficient breeding? PLoS One 6(10):e25737

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6(5):e19379. doi:10.1371/journal.pone.0019379

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • 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(1–2):119–124. doi:10.1007/s001220050539

    Article  CAS  Google Scholar 

  • Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics, 4th edn. Longman Technical, Essex

    Google Scholar 

  • Forni S, Aguilar I, Misztal I (2011) Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information. Genet Sel Evol 43(1). http://www.biomedcentral.com/content/pdf/1297-9686-43-1.pdf

  • Ganal MW, Durstewitz G, Polley A, Bérard A, Buckler ES, Charcosset A, Clarke JD et al (2011) A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. PLoS One 6(12):e28334. doi:10.1371/journal.pone.0028334

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Goddard M (2009) Genomic selection: prediction of accuracy and maximisation of long term response. Genetica 136(2):245–257. doi:10.1007/s10709-008-9308-0

    Article  PubMed  Google Scholar 

  • Goddard Me, Hayes BJ (2007) Genomic selection. J Anim Breed Genet 124(6):323–330. doi:10.1111/j.1439-0388.2007.00702.x

    Article  CAS  PubMed  Google Scholar 

  • Goddard ME, Hayes BJ, Meuwissen THE (2011) Genomic selection in livestock populations. Genet Res 92(5):413

    Google Scholar 

  • Grattapaglia D, Resende MDV (2011) Genomic selection in forest tree breeding. Tree Genet Genomes 7(2):241–255

    Article  Google Scholar 

  • Grattapaglia D, Ribeiro VJ, Rezende GDSP (2004) Retrospective selection of elite parent trees using paternity testing with microsatellite markers: an alternative short term breeding tactic for eucalyptus. Theor Appl Genet 109(1):192–199. doi:10.1007/s00122-004-1617-9

    Article  CAS  PubMed  Google Scholar 

  • Groover A, Devey M, Fiddler T, Lee J, Megraw R, Mitchel-Olds T, Sherman B, Vujcic S, Williams C, Neale D (1994) Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine. Genetics 138(4):1293–1300

    CAS  PubMed Central  PubMed  Google Scholar 

  • Guimarães EP (2007) Marker-assisted selection: current status and future perspectives in crops, livestock, forestry and fish. Food & Agriculture Org, Rome, Italy

  • Gupta PK, Rustgi S, Mir RR (2008) Array-based high-throughput DNA markers for crop improvement. Heredity 101(1):5–18. doi:10.1038/hdy.2008.35

    Article  CAS  PubMed  Google Scholar 

  • Hansen OK, McKinney LV (2010) Establishment of a quasi-field trial in Abies nordmanniana—test of a new approach to forest tree breeding. Tree Genet Genomes 6(2):345–355. doi:10.1007/s11295-009-0253-6

    Article  Google Scholar 

  • Hansen OK, Nielsen UB (2010) Microsatellites used to establish full pedigree in a half-sib trial and correlation between number of male strobili and paternal success. Ann For Sci 67(7):703. doi:10.1051/forest/2010028

    Article  Google Scholar 

  • Hayes B, Goddard M (2010) Genome-wide association and genomic selection in animal breeding. Genome 53(11):876–883. doi:10.1139/G10-076

    Article  CAS  PubMed  Google Scholar 

  • Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME (2009) Invited review: genomic selection in dairy cattle: progress and challenges. J Dairy Sci 92(2):433–443. doi:10.3168/jds.2008-1646

    Article  CAS  PubMed  Google Scholar 

  • Hayes BJ, Cogan NOI, Pembleton LW, Goddard ME, Wang J, Spangenberg GC, Forster JW (2013) Prospects for genomic selection in forage plant species. Plant Breeding 132(2):133–143. doi:10.1111/pbr.12037

    Article  Google Scholar 

  • Heffner EL, Sorrells ME, Jannink JL (2009) Genomic selection for crop improvement. Crop Sci 49(1):1–12

    Article  CAS  Google Scholar 

  • Henderson CR (1975) Best linear unbiased estimation and prediction under a selection model. Biometrics 31(2):423. doi:10.2307/2529430

    Article  CAS  PubMed  Google Scholar 

  • Hill WG, Goddard ME, Visscher PM (2008) Data and theory point to mainly additive genetic variance for complex traits. PLoS Genet 4(2):e1000008. doi:10.1371/journal.pgen.1000008

    Article  PubMed Central  PubMed  Google Scholar 

  • Holland JB (2004) Implementation of molecular markers for quantitative traits in breeding programs—challenges and opportunities. In: New directions for a diverse planet. Proceedings of the 4th international crop science congress, The Regional Institute Ltd., Gosford, NSW, Australia (www.Cropscience.Org.Au). http://cropscience.org.au/icsc2004/pdf/203_hollandjb.pdf

  • Howe GT, Aitken SN, Neale DB, Jermstad KD, Wheeler NC, Chen THH (2003) From genotype to phenotype: unraveling the complexities of cold adaptation in forest trees. Can J Bot 81(12):1247–1266. doi:10.1139/B03-141

    Article  CAS  Google Scholar 

  • Ingvarsson PK, Street NR (2011) Association genetics of complex traits in plants. New Phytol 189(4):909–922. doi:10.1111/j.1469-8137.2010.03593.x

    Article  PubMed  Google Scholar 

  • Isik F, Amerson HV, Whetten RW, Garcia SA, McKeand SE (2012) Interactions of Fr genes and mixed-pathogen inocula in the loblolly pine-fusiform rust pathosystem. Tree Genet Genomes 8(1):15–25. doi:10.1007/s11295-011-0416-0

    Article  Google Scholar 

  • Ivanova NV, Fazekas AJ, Hebert PDN (2008) Semi-automated, membrane-based protocol for DNA isolation from plants. Plant Mol Biol Report 26(3):186–198. doi:10.1007/s11105-008-0029-4

    Article  CAS  Google Scholar 

  • Jannink J-L, Lorenz AJ, Iwata H (2010) Genomic selection in plant breeding: from theory to practice. Brief Funct Genomics 9(2):166–177. doi:10.1093/bfgp/elq001

    Article  CAS  PubMed  Google Scholar 

  • Jayawickrama KJS, Carson MJ (2000) A breeding strategy for the New Zealand radiata pine breeding cooperative. Silvae Genetica 49(2):82–89

    Google Scholar 

  • 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(8):1142–1151. doi:10.1007/s001220000505

    Article  CAS  Google Scholar 

  • Jones AG, Ardren WR (2003) Methods of parentage analysis in natural populations. Mol Ecol 12(10):2511–2523. doi:10.1046/j.1365-294X.2003.01928.x

    Article  CAS  PubMed  Google Scholar 

  • Jones AG, Small CM, Paczolt KA, Ratterman NL (2010) A practical guide to methods of parentage analysis. Mol Ecol Resour 10(1):6–30. doi:10.1111/j.1755-0998.2009.02778.x

    Article  PubMed  Google Scholar 

  • Kranis A, Gheyas AA, Boschiero C, Turner F, Le Y, Smith S, Talbot R et al (2013) Development of a high density 600K SNP genotyping array for chicken. BMC Genom 14(1):59. doi:10.1186/1471-2164-14-59

    Article  CAS  Google Scholar 

  • Kumar S, Garrick DJ (2001) Genetic response to within-family selection using molecular markers in some radiata pine breeding schemes. Can J For Res 31(5):779–785. doi:10.1139/x01-009

    Article  Google Scholar 

  • Kumar S, Gerber S, Richardson TE, Gea L (2007) Testing for unequal paternal contributions using nuclear and chloroplast SSR markers in polycross families of radiata pine. Tree Genet Genomes 3(3):207–214. doi:10.1007/s11295-006-0056-y

    Article  Google Scholar 

  • Lambeth C, Lee BC, O’Malley D, Wheeler N (2001) Polymix breeding with parental analysis of progeny: an alternative to full-sib breeding and testing. Theor Appl Genet 103:930–943

    Article  Google Scholar 

  • Legarra A, Aguilar I, Misztal I (2009) A relationship matrix including full pedigree and genomic information. J Dairy Sci 92(9):4656–4663. doi:10.3168/jds.2009-2061

    Article  CAS  PubMed  Google Scholar 

  • Lerceteau E, 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 Breeding 6(5):451–458. doi:10.1023/A:1026548716320

    Article  CAS  Google Scholar 

  • Lorenzana RE, Bernardo R (2009) Accuracy of genotypic value predictions for marker-based selection in biparental plant populations. Theor Appl Genet 120(1):151–161. doi:10.1007/s00122-009-1166-3

    Article  PubMed  Google Scholar 

  • Mc Parland S, Kearney JF, Rath M, Berry DP (2007) Inbreeding trends and pedigree analysis of Irish dairy and beef cattle populations. J Anim Sci 85(2):322–331. doi:10.2527/jas.2006-367

    Article  CAS  PubMed  Google Scholar 

  • McKeand SE, Jokela EJ, Huber DA, Byram TD, Lee Allen H, Bailian L, Mullin TJ (2006) Performance of improved genotypes of loblolly pine across different soils, climates, and silvicultural inputs. For Ecol Manage 227(1–2):178–184. doi:10.1016/j.foreco.2006.02.016

    Article  Google Scholar 

  • Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829

    CAS  PubMed Central  PubMed  Google Scholar 

  • Morgante M, Salamini F (2003) From plant genomics to breeding practice. Curr Opin Biotechnol 14(2):214–219. doi:10.1016/S0958-1669(03)00028-4

    Article  CAS  PubMed  Google Scholar 

  • Moriguchi Y, Taira H, Tani N, Tsumura Y (2004) Variation of paternal contribution in a seed orchard of cryptomeria japonica determined using microsatellite markers. Can J For Res 34(8):1683–1690. doi:10.1139/x04-029

    Article  Google Scholar 

  • Myburg A, Grattapaglia D, Tuskan G, Jenkins J, Schmutz J, Mizrachi E, Hefer C et al (2011) The Eucalyptus grandis genome project: genome and transcriptome resources for comparative analysis of woody plant biology. BMC Proc 5(Suppl 7):120. doi:10.1186/1753-6561-5-S7-I20

    Article  Google Scholar 

  • Neale DB, Savolainen O (2004) Association genetics of complex traits in conifers. Trends Plant Sci 9(7):325–330

    Article  CAS  PubMed  Google Scholar 

  • Nystedt B, Street NR, Wetterbom A, Zuccolo A, Lin Y-C, Scofield DG, Vezzi F et al (2013) The Norway spruce genome sequence and conifer genome evolution. Nature 497(7451):579–584. doi:10.1038/nature12211

    Article  CAS  PubMed  Google Scholar 

  • O’Malley DM, McKeand SE (1994) Marker assisted selection for breeding value in forest trees. Forest Genetics 1(4):207–218

    Google Scholar 

  • Ogut F (2012) Predictions of genetic merit in tree breeding using factor analytic linear mixed models and blended genomic relationship matrices. Thesis, North Carolina State University, Raleigh, NC, USA. http://www.lib.ncsu.edu/resolver/1840.16/8252

  • Pemberton JM (2008) Wild pedigrees: the way forward. Proc R Soc B Biol Sci 275(1635):613–621. doi:10.1098/rspb.2007.1531

    Article  CAS  Google Scholar 

  • Perkel J (2008) SNP genotyping: six technologies that keyed a revolution. Nat Methods 5(5):447–453. doi:10.1038/nmeth0508-447

    Article  CAS  Google Scholar 

  • Pflieger S, Lefebvre V, Causse M (2001) The candidate gene approach in plant genetics: a review. Mol Breeding 7(4):275–291

    Article  CAS  Google Scholar 

  • Plomion C, Durel C-E, O’Malley DM (1996) Genetic dissection of height in maritime pine seedlings raised under accelerated growth conditions. Theor Appl Genet 93(5–6):849–858. doi:10.1007/BF00224085

    Article  CAS  PubMed  Google Scholar 

  • Pot D, Rodrigues J-C, 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(1):10–24. doi:10.1007/s11295-005-0026-9

    Article  Google Scholar 

  • Resende MFR Jr, Munoz P, Acosta JJ, Peter GF, Davis JM, Grattapaglia D, Resende MDV, Kirst M (2011) Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments. New Phytol. doi:10.1111/j.1469-8137.2011.03895.x/full

  • Resende MFR Jr, Muñoz P, Resende MDV, Garrick DJ, Fernando RL, Davis JM, Jokela EJ, Martin TA, Peter GF, Kirst M (2012a) Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.). Genetics 190(4):1503–1510

    Article  PubMed Central  PubMed  Google Scholar 

  • Resende MDV, Resende Jr MFR, Sansaloni CP, Petroli CD, Missiaggia AA, Aguiar AM, Abad JM, Takahashi EK, Rosado AM, Faria DA (2012) Genomic selection for growth and wood quality in eucalyptus: capturing the missing heritability and accelerating breeding for complex traits in forest trees. New Phytol. doi:10.1111/j.1469-8137.2011.04038.x/full

  • Schaeffer LR (2006) Strategy for applying genome-wide selection in dairy cattle. J Anim Breed Genet 123(4):218–223

    Article  CAS  PubMed  Google Scholar 

  • Schefers JM, Weigel KA (2012) Genomic selection in dairy cattle: integration of DNA testing into breeding programs. Anim Front 2(1):4–9. doi:10.2527/af.2011-0032

    Article  Google Scholar 

  • Sederoff R (2013) Genomics: a spruce sequence. Nature 497(7451):569–570. doi:10.1038/nature12250

    Article  CAS  PubMed  Google Scholar 

  • 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):1273–1281. doi:10.1007/s001220051607

    Article  CAS  Google Scholar 

  • Strauss S, Lande R, Namkoong G (1992) Limitations of molecular-marker-aided selection in forest tree breeding. Can J For Res 22:1051–1061

    Article  Google Scholar 

  • Stuber CW, Polacco M, Lynn Senior M (1999) Synergy of empirical breeding, marker-assisted selection, and genomics to increase crop yield potential. Crop Sci 39(6):1571. doi:10.2135/cropsci1999.3961571x

    Article  Google Scholar 

  • Tabor HK, Risch NJ, Myers RM (2002) Candidate-gene approaches for studying complex genetic traits: practical considerations. Nat Rev Genet 3(5):391–396

    Article  CAS  PubMed  Google Scholar 

  • Tuskan GA, DiFazio S, Jansson S, Bohlmann J, Grigoriev I, Hellsten U, Putnam N et al (2006) The genome of black cottonwood, Populus trichocarpa (Torr. & Gray). Science 313(5793):1596–1604. doi:10.1126/science.1128691

    Article  CAS  PubMed  Google Scholar 

  • VanRaden PM (2008) Efficient methods to compute genomic predictions. J Dairy Sci 91(11):4414–4423

    Article  CAS  PubMed  Google Scholar 

  • VanRaden PM, Van Tassell CP, Wiggans GR, Sonstegard TS, Schnabel RD, Taylor JF, Schenkel FS (2009) Invited review: reliability of genomic predictions for North American Holstein bulls. J Dairy Sci 92(1):16–24. doi:10.3168/jds.2008-1514

    Article  CAS  PubMed  Google Scholar 

  • White TL, Adams TW, Neale DB (2007) Forest genetics. CABI, Cambridge, MA, USA

  • Wilcox PL, Amerson HV, Kuhlman EG, Liu BH, O’Malley DM, Sederoff RR (1996) Detection of a major gene for resistance to fusiform rust disease in loblolly pine by genomic mapping. Proc Natl Acad Sci USA 93(9):3859–3864

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Wilcox PL, Carson SD, Richardson TE, Ball RD, Horgan GP, Carter P (2001) Benefit-cost analysis of DNA marker-based selection in progenies of Pinus radiata seed orchard parents. Can J For Res 31(12):2213–2224. doi:10.1139/x01-144

    Google Scholar 

  • Williams CG, Neale DB (1992) Conifer wood quality and marker-aided selection: a case study. Can J For Res 22(7):1009–1017. doi:10.1139/x92-135

    Article  Google Scholar 

  • Wu HX, Colin MA (2005) Genotype by environment interactions in an Australia-wide radiata pine diallel mating experiment: implications for regionalized breeding. For Sci 51(1):29–40

    Google Scholar 

  • Würschum T, Reif JC, Kraft T, Janssen G, Zhao Y (2013) Genomic selection in sugar beet breeding populations. BMC Genetics 14(1):85. doi:10.1186/1471-2156-14-85

    Google Scholar 

  • Xu Y, Crouch JH (2008) Marker-assisted selection in plant breeding: from publications to practice. Crop Sci 48(2):391. doi:10.2135/cropsci2007.04.0191

    Article  Google Scholar 

  • Zapata-Valenzuela J, Isik F, Maltecca C, Wegrzyn J, Neale D, McKeand S, Whetten R (2012) SNP markers trace familial linkages in a cloned population of Pinus taeda—prospects for genomic selection. Tree Genet Genomes. doi:10.1007/s11295-012-0516-5

  • Zapata-Valenzuela J, Whetten RW, Neale DB, McKeand SE, Isik F (2013) Genomic estimated breeding values using genomic relationship matrices in a cloned population of loblolly pine. G3: Genes|Genomes|Genetics. doi:10.1534/g3.113.005975. http://www.g3journal.org/content/early/2013/03/29/g3.113.005975

  • Zhao Y, Gowda M, Liu W, Würschum T, Maurer HP, Longin FH, Ranc N, Reif JC (2012) Accuracy of genomic selection in european maize elite breeding populations. Theor Appl Genet 124(4):769–776. doi:10.1007/s00122-011-1745-y

    Google Scholar 

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Acknowledgments

This work was supported by the Conifer Translational Genomics Network Coordinated Agricultural Project (USDA NRI #2007-02781 and AFRI #2009-01879), the NC State University Cooperative Tree Improvement Program, and the Department of Forestry and Environmental Resources at NCSU. Funding was also provided by the Southeastern Partnership for Integrated Biomass Supply Systems (IBSS), a coordinated agricultural project funded by the USDA Agriculture and Food Research Initiative (AFRI) Sustainable Bioenergy Program; and by the Pine Integrated Network: Education, Mitigation, and Adaptation project (PINEMAP) A Coordinated Agricultural Project funded by the USDA National Institute of Food and Agriculture. I thank my colleagues Drs. Steve McKeand, Ross Whetten John Frampton (North Carolina State University, USA) and Christophe Plomion (INRA Pierroton, France) for valuable discussions on the manuscript. I am thankful to two anonymous reviewers for their excellent suggestions and editorial edits (reviewer 1) to improve the manuscript. I used several web resources for definitions of some technical terms. The following are worth to mention http://ghr.nlm.nih.gov/glossary and http://www.ndsu.edu/pubweb/~mcclean/plsc431/linkage/linkage2.htm.

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Isik, F. Genomic selection in forest tree breeding: the concept and an outlook to the future. New Forests 45, 379–401 (2014). https://doi.org/10.1007/s11056-014-9422-z

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