Genomics of growth traits in forest trees

Available online at www.sciencedirect.com Genomics of growth traits in forest trees Dario Grattapaglia1, Christophe Plomion2, Matias Kirst3 and Ronald R Sederoff4 Growth traits in trees are fundamental components of adaptation in a forest ecosystem and of productivity in planted forests. A number of processes determine tree growth, which are controlled by genetic and epigenetic factors that respond dynamically to environmental signals throughout centuries. Advances in genomics have allowed an increased comprehension of the complex mechanisms of tree growth and adaptation. Yet, the application of genomics to improving forest productivity and sustainability still entails capturing a large proportion of the total genetic variation controlling the component traits. Nonetheless, genetics and genomics are unifying disciplines that will serve well to dissect the variables and mechanisms of tree growth and development. Addresses 1 EMBRAPA Genetic Resources and Biotechnology, CP 2372, Brası́lia 70770-970 DF, and Graduate Program in Genomic Sciences and Biotechnology, Universidade Católica de Brası́lia – SGAN 916 módulo B, Brası́lia 70790-160 DF, Brazil 2 INRA,UMR 1202, 69 Route d’Arcachon, F-33612 Cestas, France 3 School of Forest Resources and Conservation, Graduate Program in Plant Molecular and Cellular Biology, and University of Florida Genetics Institute, University of Florida, PO Box 110410, Gainesville, FL 32611, USA 4 Department of Forestry and Environmental Resources, North Carolina State University Campus Box 7247, Raleigh, NC 27695-7247, USA Corresponding author: Grattapaglia, Dario ([email protected]) Current Opinion in Plant Biology 2009, 12:148–156 This review comes from a themed issue on Genome studies and molecular genetics Edited by Masahiro Yano and Roberto Tuberosa Available online 29th January 2009 1369-5266/$ – see front matter # 2008 Elsevier Ltd. All rights reserved. DOI 10.1016/j.pbi.2008.12.008 Introduction A distinctive feature of trees compared to herbaceous plants is their massive stature, propelled by decades to centuries of height and radial secondary growth. Secondary growth derives from the vascular cambium, which consists of secondary meristematic stem cells that differentiate into bark to the outside (secondary phloem) and wood to the inside (secondary xylem). Tree growth is determined by cell division and expansion in the apical and cambial meristems, developmental and seasonal growth transitions, efficiency of photosynthesis, nutrient and water uptake and transport, and the ability to respond Current Opinion in Plant Biology 2009, 12:148–156 to biotic and abiotic stresses. These processes are controlled by a myriad of genetic and epigenetic factors that respond dynamically to environmental signals. Growth ultimately results in the structures that provide mechanical support, defense mechanisms and translocate water, solutes, and signaling molecules over extensive distances. Growth related traits in trees are fundamental components of survival and productivity in natural and planted forests (Box 1). The growth-to-dormancy transition is vital for survival of perennial plants in temperate and boreal climates. Rapid height growth for light or root growth toward water tables, are key features of pioneer species. From a utilitarian perspective, growth in trees is synonymous to productivity. It represents the foremost target trait for intensive woody biomass production in any tree breeding program, whether the final application is structural wood, engineered wood products, pulp and paper, or energy. Sustainability of any forest-based industry depends on a constant supply of wood, optimal land use, and the efficiency of scale in a capital-intensive operation. Hence, understanding tree growth will have a significant impact on the management of adaptive genetic variation needed for forest survival in changing environments and on the efficiency of selective breeding for genetic gain in wood productivity. Tremendous progress has recently been made in understanding fundamental aspects of plant growth and development. Suites of genes affecting hormone action, transcriptional control, and other regulatory factors have been described, largely from studies in the model plant Arabidopsis thaliana [1]. The majority of that work has focused on the primary meristems of shoot and root apices because Arabidopsis has little secondary growth. While primary meristems are basic to growth and development of all plants, the secondary meristem has greater significance for wood production. Recent reviews have highlighted the molecular evidence that genes involved in wood formation are not unique to trees and that shoot apical meristems and vascular cambium share overlapping regulatory systems [2]. In this review we discuss recent advances toward a genomic understanding of tree growth, and the potential applications to forest productivity and sustainability Attention will be given to five complementary approaches used to identify genomic regions, genes, or polymorphisms involved in the control of growth traits in trees (Box 1 www.sciencedirect.com Genomics of growth traits in forest trees Grattapaglia et al. 149 Box 1 Main traits impacting tree growth and genomic approaches employed to understand and manipulate them. Arrows indicate direction of the genomic approach, whether trait-based (forward) or gene-based (reverse). While QTL mapping involves forward genomics, association and population genomics operates on the basis of candidate genes. All other approaches proceed in both directions. For example, transgenics is used forwardly to generate novel phenotypes by activation tagging or reversely by silencing specific candidate genes. Genome-wide selection uses phenotypes to develop genotype-based predictive models that are then used reversely to infer phenotypes. and Table 1). The availability of a reference genome sequence for Populus trichocarpa [3], the forthcoming genome sequence of a Eucalyptus grandis tree [4,5], and the prospects of a conifer genome sequence will www.sciencedirect.com accelerate the pace of all these experimental approaches, especially in light of the renewed interest in converting biomass-to-biofuel [5], and the rapidly evolving highthroughput sequencing and genotyping technologies. Current Opinion in Plant Biology 2009, 12:148–156 150 Genome studies and molecular genetics Table 1 Summary of recent genomic studies, examining growth related traits in forest tree species, categorized by the genomic approach employed. Owing to the time period covered and the scope of the review, with a few exceptions, only papers published within the past three years are included. Association genetics and population genomics Transgenic expression and activation tagging Eucalyptus [37,52,72] Pinus [25] Populus [55,56] Pinus [49,50] Eucalyptus [37,72–74] Picea [51] Populus [75] Eucalyptus [22] Pinus [24,25] Populus [11] Castanea [71] Picea [76] Quercus [77] Populus [45,46] Populus [20,33] Picea [32] Biotic stress resistance Eucalyptus [79,80] Populus [81] Pinus [82] Pinus [26] Picea [32] Carbon assimilation, storage, and distribution Abiotic stress (drought tolerance, cold hardiness) Populus [8,83] Growth related traits QTL mapping Expression-QTL Transcriptomics Volume growth (height and/or radial growth) Populus [6,7,8,9,11,12] Pinus [67] Eucalyptus [52,68,69] Pseudotsuga [70] Castanea [71] Eucalyptus [52] Wood density and related traits Pseudotsuga [70] Pinus [67] Eucalyptus [68] Eucalyptus [53] Bud phenology Populus [10,16,83] Quercus [84] Pinus [23] Populus [10] QTL mapping: the first step to understanding complex growth related traits QTL mapping has been an entry to dissecting the genetic basis of complex traits. It is an unbiased forward genomics approach where the phenotype reveals the location of regulatory genes or genomic regions affecting the trait. QTL analysis has been attractive for multi-factorial traits such as growth, where a priori definition of candidate genes is elusive. A recent series of QTL studies in trees had growth related traits as the main targets [6,7,8,9,10,11,12]. Growth can be measured with precision, especially in clonally replicated trials where microenvironmental effects are taken into account in the variance components analysis. It is the main target trait of breeding programs, particularly for biomass production, and given its low heritability, it is the trait where breeders have the greatest hope for marker assisted selection. QTL mapping for growth in trees relied on RFLPs, RAPD, AFLP and microsatellites [13]. Recently, high density SNP maps [14] and microarray-based markers such as Single Feature Polymorphisms (SFP) for Populus [Drost D and Kirst M, unpublished] and Diversity Arrays Technology (DArT) for Eucalyptus [Grattapaglia D and Kilian A, unpublished] are becoming available. Unlike crop species, where parental lines are chosen to maximize differences in target traits, QTL mapping in trees has been carried out in pedigrees where both parents were generally ‘good growers’. Still, QTLs for growth related traits have been detected in all the major planted tree species [13]. Major effect QTLs for growth explainCurrent Opinion in Plant Biology 2009, 12:148–156 Populus [78] Populus [85] Pinus [23,31] Picea [32] ing between 10 and 30% of the phenotypic variation were found, as a result of the high heterozygosity of trees, although the magnitude of effects are probably overestimated owing to the experimental designs [15]. Genetic heterogeneity is probably responsible for variation in growth QTL positions and effects among unrelated pedigrees and significant interaction with temporal and environmental variation [6,7,12,16]. Growth QTLs may be due to variation of different kinds. We tend to consider that a growth QTL reflects the presence of an allele that improves breeding value for growth. However, a growth QTL may instead identify a segregating semilethal gene in a cross, or even a lethal gene at high frequency in a population [17]. Interest has been renewed in QTL mapping for growth and biomass traits especially for Populus. Development of microsatellites, that are transferable across pedigrees, now allow the comparative analysis of QTLs for growth traits across studies [6,7,12]. This consolidated QTL positional information, and an annotated genome sequence, promise to identify strong candidate genes for growth. The identification of such genes within QTL intervals in a sequenced genome, has been successful in several plant species for complex traits [18]. As large pedigrees and higher resolution mapping with new genotyping technologies become available in forest trees, QTL positional information will increasingly be a powerful alternative to the approaches that rely on tentative candidate genes for association genetics. In Populus earlier mapping studies showed that QTLs for bud set and bud flush co-located www.sciencedirect.com Genomics of growth traits in forest trees Grattapaglia et al. 151 with a phytochrome B2 gene ( phyB2) [19]. A recent association genetic study identified two non-synonymous SNPs in the phytochrome B2 gene associated with variation in the timing of bud set [20]. Association genetics and population genomics: promising ways to find genes controlling growth in forest trees Adopted from human, animal, and crop genetics, the association or linkage disequilibrium (LD) mapping paradigm was proposed in forest trees [21]. It was pioneered in Eucalyptus [22] and applied in a number of studies as sequencing information has become available [20,23,24–26]. The approach quickly gained interest because it could be readily applied to large random mating tree populations, potentially overcoming the logistic and time limitations and poor resolution of QTL mapping in forest trees. Because of the limited LD, high nucleotide diversity, and lack of reference genome sequences, association genetics has relied on SNP genotyping of candidate genes. Gene-trait associations have been reported for wood property traits [22,24,25], bud phenology [20], disease resistance [26] and drought tolerance [23], which indirectly impact growth. However, the magnitude of effect of individual associations has been small, rarely exceeding 10%, even for high heritability traits [26]. Besides the current limitation of scanning only a few hundred genes, association studies in tree species have explored almost exclusively the coding regions of genes, while largely ignoring the regulatory regions. Owing to the rapid decay of LD commonly observed in natural populations of forest trees, mutations that alter gene expression may not be detected by indirect associations with SNPs in coding regions and could be overlooked in the candidate gene approach. The focus on alleles of moderate to high frequency has also excluded from the analysis the rare SNP variant, which are difficult to be detected with the current populations and statistical approaches. Much like in humans, some of these rare alleles may be of particular interest as they can generate extreme phenotypes of value for breeding. Association studies have also been underpowered by the use of sample sizes of only a few hundred individuals, and are theoretically inadequate for detection of alleles of small effect [27]. These results reaffirm the complex nature of the traits studied so far, and further challenge the expectations of applying association genetics based on candidate genes to more complex traits such as volume growth. As growth is fundamental for adaptation, growth components are excellent targets for the identification of genes of evolutionary importance in natural tree populations. Population genomics integrates genome-wide sampling with population genetic to understand evolutionary processes. Two main principles guide population www.sciencedirect.com genomics: (1) neutral loci across the genome will be similarly affected by demography and the evolutionary history of populations; (2) loci under selection will often behave differently and reveal ‘outlier’ patterns of variation. Large, randomly mating natural populations of forest trees, occupying diverse sets of environments, offer unique opportunities to identify polymorphisms involved in adaptive population differentiation [28]. This approach has been successful in detecting genes with contrasting patterns of variation in a number of forest trees, including Oak (Quercus sp.) [29] Cryptomeria japonica [30], maritime pine (Pinus pinaster) [31] and white spruce (Picea glauca) [32]. However, in Populus no evidence was found for population genetic differentiation at SNPs in phenology candidate genes that had previously shown significant clinal variation [33]. Although population genomics may represent a promising approach to identify genes for growth and adaptive traits, limitations still exist, especially regarding the selection of candidate genes. There is an ascertainment bias associated with SNP discovery, and functional information about the genes’ role is needed to validate candidates. Furthermore, with high gene flow and spatially variable selection – typical of forest trees – large population differences in mean adaptive traits can occur, despite small changes in frequencies of the underlying QTLs [34], suggesting epistatic interactions, epigenomics or the movement of transposable elements. Transcriptomics and genetical genomics of growth and development As tree growth results from cell division and expansion in the apical and cambial meristems, the transcriptome in these regions has been the focus of several studies. A review addressing the role of specific genes in tree development and growth has been published elsewhere [35]. Expressed sequence tag sequencing from stems and other vegetative tissues laid the foundation for a genomic understanding of tree growth in several commercially relevant tree genera [36,37,38,39]. Studies that followed created detailed transcriptional roadmaps of cambial growth, primarily in Populus, where the existence of a well-defined gene expression program during xylem differentiation was demonstrated [40]. The gene expression program in the cambial meristem was shown to have many similarities to that of shoot and root apical meristems [41]. Attention has also been given to the role of indole acetic acid (auxin) and gibberellins in Populus wood formation suggesting that auxin concentrations control the expression of some key regulators, which in turn activate a cascade of downstream genes essential for wood formation [42]. Extensive allele-specific variation in gene expression was detected in Populus F1 hybrids that show strong heterosis for growth when compared to the parental species [43]. Although no specific evidence was revealed by that study, altered gene regulation in F1 hybrids could be involved in generating the heterotic Current Opinion in Plant Biology 2009, 12:148–156 152 Genome studies and molecular genetics phenotypes for growth observed not only in Populus but also in several other tree species. Transcriptome studies have begun to address the global gene expression changes during seasonal shifts. A small number of transcriptional regulators appear to control these seasonal transitions along with epigenetic modifications in acquisition of and release from dormancy [44,45]. Changes in the leaf seasonal transcriptome in Populus also showed significant shifts in gene expression [46]. Many transcriptome shifts during autumn senescence were similar to those described in annual plants, where degradation of the photosynthetic machinery is accompanied by an increase in proteases. Senescence and the genes regulating its progression may be substantially conserved between perennial and annual plants, as observed for other essential physiological processes such as photosynthesis [47]. In conifers, a major focus has been toward understanding gene regulation of the seasonal change from earlywood (spring) to latewood summer and fall), characterized by changes in chemical and physical properties of the wood. This transition was evaluated by a large genomic survey [48] that detected two gene expression clusters and a similar proportion of genes associated with earlywood and latewood formation in Pinus pinaster. Other studies in pines focused on the analysis of transcriptional variation along the vertical axis of conifers [49,50]. Secondary cambium produced from the apical meristem is younger than that produced from the cambial meristem at the base—expectedly, the difference was reflected in a larger number of genes implicated in cell division and protein synthesis in the former, while genes for carbohydrate metabolism and lignification are over-represented in the latter. Recently an attempt was made to identify conserved transcripts between angiosperms and gymnosperms. Comparative analysis of the conifer white spruce and Arabidopsis found a set of 31 transcripts that appear conserved in the xylem of the two species [51]. It has long been suggested that there could be a negative correlation between growth and lignin content because of the large amount of fixed carbon that flows irreversibly into the phenylpropanoid polymer. Transcriptome analysis has provided insight into the mechanism involved in this major level of control [52]. Expression of many genes in the monolignol biosynthetic pathway is strongly correlated, negatively with growth and positively with lignin content and high syringyl subunit composition. Transcript levels of coniferaldehyde 5-hydroxylase (also called ferulate 5-hydroxylase—F5H) have the highest correlation. This enzyme is the branch point for the synthesis of coniferyl alcohol and sinapyl alcohol, the two major precursors for lignin. High expression is correlated with slower growth, higher lignin, and a high S/G (syringyl/guaiacyl lignin subunit) ratio. Expression QTL (eQTL) analysis indicated that several transacting factors Current Opinion in Plant Biology 2009, 12:148–156 (not yet identified) simultaneously regulate many genes in the monolignol pathway [52,53]. There appears to be metabolic control of carbohydrate metabolism and cell division that regulates carbon flow either into aromatic amino acid biosynthesis and the carbohydrates of the secondary wall, or to increase cambial cell division. Transgenic approaches to discover growth genes An alternative strategy to the identification of genes responsible for growth and biomass production is to produce mutants that suppress or activate a target gene and screen them for phenotypes. Gene-tagging approaches that use insertional mutagenesis to create mutant phenotypes are well suited for trees [54]. When the over-expressed gene is dominant, a phenotype may be visible in the primary transformant, thus detectable before collecting second generation progeny that takes several years in trees. Activation tagging pilot populations in Populus [55,56] enable strong dominant alleles to be studied. Such variants would be rare in natural populations because of strong purifying selection. Screening for developmental abnormalities related to woody perennial growth has identified genes affecting leaf size and structure, stem development, timing of bud flush, secondary metabolism, and leaf senescence [54,56]. Candidate loci identified for these traits included members of the GRAS gene family containing a DELLA domain, which may mediate GA responses. Busov et al. [57] tagged a gibberellin catabolism gene (GA 2-Oxidase) that regulates tree stature. Gene/enhancer trapping has identified genes involved in vascular development and wood formation [58]. In combination with QTL and association studies, the analysis of genome-wide insertional mutant populations, will be a powerful tool for gene discovery related to biomass production when the populations are screened for a wide range of phenotypes. Genomic-based breeding for growth: from phenotype dissection to genome-wide selection in forest trees In spite of the recent advances in the theory and practice of association genetics in forest trees, single gene-trait association discovery may not be sufficient to impact breeding for complex traits such as growth in forest trees, unless it can capture a large proportion of the phenotypic variation in growth among individuals and populations. Until then, quantitative genetics approaches are likely to be more efficient. In conifers, efforts are underway to increase the number of genes sampled to several thousand to translate genomics into breeding applications [26]. However, challenges exist owing to the low range LD in the large breeding populations targeted. How much of the phenotypic variation in complex traits is controlled directly by coding regions and not by regulatory elements remains to be determined. In cereals, noncoding polymorphisms in distant (>10–50 kbp) cis-acting www.sciencedirect.com Genomics of growth traits in forest trees Grattapaglia et al. 153 regulatory regions have been shown to be key components of plant adaptation throughout breeding and evolution [59]. Similar mechanisms may be common to forest trees. It has been widely assumed that before genomic-based breeding could be implemented in forest trees, complex traits have to be dissected to their individual components [26]. In the case of growth, and several other quantitative traits in trees, the ‘dissection approach’ will not effectively advance forest tree breeding in a reasonable time. Rather, genome-wide, predictive, ‘black-box’ methodologies, precluding information on QTLs and focusing on the genetic improvement of the target traits, have a greater probability of application. Such an approach, called genome-wide or genomic selection (GS) may be defined as the simultaneous selection for many thousands of markers, covering the entire genome so that all genes are expected to be in linkage disequilibrium with at least some of the markers [60]. Only recently, however, with a drop in genotyping costs, has GS become feasible, attracting the attention of crop [61] and perennial plant [62] breeders. Genome-wide and cost-efficient marker systems are needed to apply GS to forest trees. Furthermore, dedicated GS breeding populations with effective population sizes (Ne) of around 20–50 individuals must be adopted to increase the extent of LD and fit into currently achievable genotyping densities of a few hundred markers per Morgan [63] as LD is a function of 4Nec where c is the recombination fraction between two markers. In genetically heterogenous forest trees such populations still encompass large amounts of genetic variation for sustained genetic gains. Recent experimental results in mice, relevant to outbred trees, indicate that GS has better predictive ability than the classical polygenic model [64]. A GS scheme is being tested in Eucalyptus where predictive equations for multiple traits are developed on the basis of high density genotyping and precise phenotyping of several hundred clones of a discovery population (training set) involving Ne in the range of 15– 50. Selection accuracy of the predictive models is then assessed in a validation population, targeting the application of early GS at the individual tree level in progeny trials [Resende MDV and Grattapaglia D, unpublished]. Conclusions and perspectives Some aspects of the growth have already been relatively well described at the genomic level, particularly the cambial meristem and its derivatives, which is unique to woody plants. The contribution of factors such as nutrient and water uptake and transport or photosynthetic capacity still remains to be better understood. The genomic control of wood formation has mostly been seen from a generalized perspective that ignores major differences between woody angiosperms and gymnosperms. The genomes of conifers and woody angiosperms may have evolved distinctively since their www.sciencedirect.com separation over 300 million years ago. Many of the genetic and epigenetic factors that contribute to growth variation may be different. Angiosperms have often undergone genome duplication, creating opportunities for gene neo-functionalization and specialization. Conifer genomes, however, appear to have conserved ploidy over the same time [65], although more transposon activity is associated with larger genome sizes. Epigenetic mechanisms such as genome methylation have been shown to vary dramatically during aging in certain conifer species [66], and could play a prominent role in their development. Such differences may guide future approaches to a genetic and genomic understanding of growth and development. In humans, gene copy number variation and epigenetic factors are increasingly viewed as major contributors to phenotypic diversity, particularly for disease susceptibility. In plants, the most significant sources of genetic variation that contribute to growth and development are still unclear. In forest trees we are only beginning to look at variation at the level of single nucleotide polymorphisms. Structural and epigenetic variation both within and between species, still an unexplored field in forest trees, might reveal key elements for the control of growth traits and could be directly involved in the strong heterosis for growth found in Populus and Eucalyptus F1 interspecific hybrids. Ongoing re-sequencing of a few Populus genotypes (Tuskan J, personal communication) and similar possibilities with the forthcoming reference genome of Eucalyptus, should provide a better view of the sources of genetic diversity, possibly revealing novel genomic-based ways to breed trees for improved and sustainable growth. Acknowledgements The preparation of this article was supported by the Brazilian National Research Council (CNPq) through a research fellowship awarded to DG, NovelTree UE project awarded to CP, US Department of Energy, National Science Foundation, and the Consortium for Plant Biotechnology Research grants to MK. References and recommended reading Papers of particular interest, published within the period of review, have been highlighted as:  of special interest  of outstanding interest 1. Busov VB, Brunner AM, Strauss SH: Genes for control of plant  stature and form. New Phytol 2008, 177:589-607. A thorough review on the progress in the identification of genes useful for control of plant architecture, focusing on modifiers of stature and form that may be useful for directed modification of plant architecture. 2. Groover A, Robischon M: Developmental mechanisms regulating secondary growth in woody plants. Curr Opin Plant Biol 2006, 9:55-58. 3. Tuskan GA, Difazio S, Jansson S, Bohlmann J, Grigoriev I, Hellsten U, Putnam N, Ralph S, Rombauts S, Salamov A et al.: The genome of black cottonwood, Populus trichocarpa (Torr. & Gray). Science 2006, 313:1596-1604. 4.  Grattapaglia D, Kirst M: Eucalyptus applied genomics: from gene sequences to breeding tools. New Phytol 2008, 179:911-929. Current Opinion in Plant Biology 2009, 12:148–156 154 Genome studies and molecular genetics This review links current breeding practices with existing and emerging genomic tools for the most widely planted hardwood crop in the tropical and subtropical world. Authors discuss the challenges and opportunities to integrate genomic information into directional selective breeding in light of the upcoming draft of the Eucalyptus grandis genome. 5. Rubin EM: Genomics of cellulosic biofuels. Nature 2008, 454:841-845. 6. Rae A, Pinel M, Bastien C, Sabatti M, Street N, Tucker J, Dixon C, Marron N, Dillen S, Taylor G: QTL for yield in bioenergy Populus: identifying G x E interactions from growth at three contrasting sites. Tree Genet & Genomes 2008, 4:97-112. 7. Dillen S, Storme V, Marron N, Bastien C, Neyrinck S, Steenackers M, Ceulemans R, Boerjan W: Genomic regions involved in productivity of two interspecific poplar families in Europe. 1. Stem height, circumference and volume. Tree Genet & Genomes 2009, 5:147-164. 8.  Rae AM, Tricker PJ, Bunn SM, Taylor G: Adaptation of tree growth to elevated CO2: quantitative trait loci for biomass in Populus. New Phytol 2007, 175:59-69. A QTL mapping approach was used to identify genomic regions determining above-ground and below-ground biomass responses to elevated CO2 concentration. This study provides some of the first data on the genomic regions determining tree growth response to future high CO2 atmospheres. 9. Zhang D, Zhang Z, Yang K: QTL analysis of growth and wood chemical content traits in an interspecific backcross family of white poplar (Populus tomentosa x P. bolleana) x P. tomentosa. Can J Forest Res 2006, 36:2015-2023. 10. Street NR, Skogstrom O, Sjodin A, Tucker J, Rodriguez-Acosta M,  Nilsson P, Jansson S, Taylor G: The genetics and genomics of the drought response in Populus. Plant J 2006, 48:321-341. The authors use a genetical genomics approach to provide information on adaptation for drought at the gene expression level. A dramatic segregation within the population in the abscission response to drought, and comparison of the transcriptional response of a set of high-abscission and low-abscission genotypes revealed a striking degree of separation. 11. Rae AM, Ferris R, Tallis MJ, Taylor G: Elucidating genomic regions determining enhanced leaf growth and delayed senescence in elevated CO2. Plant Cell Environ 2006, 29:1730-1741. 12. Wullschleger S, Yin TM, DiFazio SP, Tschaplinski TJ, Gunter LE, Davis MF, Tuskan GA: Phenotypic variation in growth and biomass distribution for two advanced-generation pedigrees of hybrid poplar. Can J Forest Res 2005, 35:1779-1789. 13. Kirst M, Myburg A, Sederoff R: Genetic mapping in forest trees: markers, linkage analysis and genomics. Genet Eng (N Y) 2004, 26:105-141. 14. Pavy N, Pelgas B, Beauseigle S, Blais S, Gagnon F, Gosselin I, Lamothe M, Isabel N, Bousquet J: 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 2008, 9:21. 15. Beavis WD: QTL analyses: power, precision, and accuracy. In Molecular Dissection of Complex Traits. Edited by Patterson AH. CRC Publishing; 1998:145-162. 16. Tschaplinski TJ, Tuskan GA, Sewell MM, Gebre GM, Donald ETI, Pendleyi C: Phenotypic variation and quantitative trait locus identification for osmotic potential in an interspecific hybrid inbred F-2 poplar pedigree grown in contrasting environments. Tree Physiol 2006, 26:595-604. 17. Remington DL, O’Malley DM: Evaluation of major genetic loci contributing to inbreeding depression for survival and early growth in a selfed family of Pinus taeda. Evolution 2000, 54:1580-1589. 18. Price AH: Believe it or not, QTLs are accurate! Trends Plant Sci 2006, 11:213-216. 19. Frewen BE, Chen THH, Howe GT, Davis J, Rohde A, Boerjan W, Bradshaw HD: Quantitative trait loci and candidate gene mapping of bud set and bud flush in Populus. Genetics 2000, 154:837-845. Current Opinion in Plant Biology 2009, 12:148–156 20. Ingvarsson PK, Garcia MV, Luquez V, Hall D, Jansson S:  Nucleotide polymorphism and phenotypic associations within and around the phytochrome B2 Locus in European aspen (Populus tremula, Salicaceae). Genetics 2008, 178:2217-2226. This study reveals two non-synonymous SNPs in the phytochrome B2 gene associated with variation in the timing of bud set, explaining between 1.5 and 5% of the observed phenotypic variation in bud set. This study corroborates previous findings where the frequencies of both these SNPs were found to vary clinally with latitude. 21. Neale DB, Savolainen O: Association genetics of complex traits in conifers. Trends Plant Sci 2004, 9:325-330. 22. Thumma BR, Nolan MF, Evans R, Moran GF: Polymorphisms in cinnamoyl CoA reductase (CCR) are associated with variation in microfibril angle in Eucalyptus spp. Genetics 2005, 171:1257-1265. 23. Gonzalez-Martinez SC, Huber D, Ersoz E, Davis JM, Neale DB:  Association genetics in Pinus taeda L. II. Carbon isotope discrimination. Heredity 2008, 101:19-26. A family-based approach to detect genotype/phenotype association was used for the first time in plants by applying the quantitative transmission disequilibrium test. A set of 41 disease and abiotic stressinducible genes were tested for association with carbon isotope discrimination at two sites. Two promising candidate genes were detected, reaffirming the challenge of dissecting complex traits, but providing important insights for designing second-generation association studies in forest trees. 24. Gonzalez-Martinez SC, Wheeler NC, Ersoz E, Nelson CD, Neale DB: Association genetics in Pinus taeda L. I. Wood property traits. Genetics 2007, 175:399-409. 25. Yu Q, Li B, Nelson C, McKeand S, Batista V, Mullin T: Association of the cad-n1 allele with increased stem growth and wood density in full-sib families of loblolly pine. Tree Genet & Genomes 2006, 2:98-108. 26. Neale DB: Genomics to tree breeding and forest health. Curr Opin Genet Dev 2007, 17:539-544. 27. Long AD, Langley CH: The power of association studies to detect the contribution of candidate genetic loci to variation in complex traits. Genome Res 1999, 9:720-731. 28. Gonzalez-Martinez SC, Krutovsky KV, Neale DB: Forest-tree population genomics and adaptive evolution. New Phytol 2006, 170:227-238. 29. Scotti-Saintagne C, Mariette S, Porth I, Goicoechea PG, Barreneche T, Bodenes K, Burg K, Kremer A: Genome scanning for interspecific differentiation between two closely related oak species [Quercus robur L. and Q petraea (Matt.) Liebl.]. Genetics 2004, 168:1615-1626. 30. Tsumura Y, Kado T, Takahashi T, Tani N, Ujino-Ihara T, Iwata H: Genome scan to detect genetic structure and adaptive genes of natural populations of Cryptomeria japonica. Genetics 2007, 176:2393-2403. 31. Eveno E, Collada C, Guevara MA, Leger V, Soto A, Diaz L, Leger P,  Gonzalez-Martinez SC, Cervera MT, Plomion C et al.: Contrasting patterns of selection at Pinus pinaster Ait. Drought stress candidate genes as revealed by genetic differentiation analyses. Mol Biol Evol 2008, 25:417-437. In this population genomics study, a set of candidate genes for drought stress tolerance was scanned for patterns of nucleotide diversity and genetic differentiation in phenotypically contrasted Pinus pinaster populations. Some genes were deemed candidates for future association studies. 32. Namroud MC, Beaulieu J, Juge N, Laroche J, Bousquet J:  Scanning the genome for gene single nucleotide polymorphisms involved in adaptive population differentiation in white spruce. Mol Ecol 2008, 17:3599-3613. This is the first large scale population genomics study in a forest tree where 534 SNPs representing 345 expressed genes were sampled, revealing a set of candidate genes for local adaptation in white spruce (Picea glauca). The adaptive trends found were consistent with the genes’ putative functions and the divergence in quantitative traits among the populations.The authors also draw attention to the challenges and future perspectives of this genomic approach. www.sciencedirect.com Genomics of growth traits in forest trees Grattapaglia et al. 155 33. Hall D, Luquez V, Garcia VM, St Onge KR, Jansson S,  Ingvarsson PK: Adaptive population differentiation in phenology across a latitudinal gradient in European aspen (Populus tremula, L.): a comparison of neutral markers, candidate genes and phenotypic traits. Evolution 2007, 61:2849-2860. This study finds little evidence for a greater genetic differentiation at SNPs or SSRs sampled from phenology candidate genes in comparison to neutral SSR markers. This key result fits theoretical expectations that genetic differentiation at QTLs should be better described by FST at neutral loci rather than by QST at the quantitative traits themselves, highlighting the fact that large population differences in mean phenotypes can occur despite small changes in frequencies of the underlying QTLs. 45. Ruttink T, Arend M, Morreel K, Storme V, Rombauts S, Fromm J,  Bhalerao RP, Boerjan W, Rohde A: A molecular timetable for apical bud formation and dormancy induction in poplar. Plant Cell 2007, 19:2370-2390. In this thorough study, metabolite and gene expression dynamics were used to reconstruct the temporal sequence of events during bud development dissected into bud formation, acclimation to dehydration and cold, and dormancy in poplar. Specific sets of regulatory and marker genes and metabolites were found to be associated with each one of these processes. The identification of a large set of genes commonly expressed during the growth-to-dormancy transitions in poplar apical buds, cambium, or Arabidopsis thaliana seeds suggests parallels in the underlying molecular mechanisms in different plant organs. 34. Le Corre V, Kremer A: Genetic variability at neutral markers, quantitative trait loci and trait in a subdivided population under selection. Genetics 2003, 164:1205-1219. 46. Schrader J, Moyle R, Bhalerao R, Hertzberg M, Lundeberg J, Nilsson P, Bhalerao RP: Cambial meristem dormancy in trees involves extensive remodelling of the transcriptome. Plant J 2004, 40:173-187. 35. Demura T, Fukuda H: Transcriptional regulation in wood  formation. Trends Plant Sci 2007, 12:64-70. This review provides an up-to-date coverage on the recent findings concerning the regulation of genes by transcription factors involved in wood formation. 36. Sterky F, Bhalerao RR, Unneberg P, Segerman B, Nilsson P, Brunner AM, Charbonnel-Campaa L, Lindvall JJ, Tandre K, Strauss SH et al.: A Populus EST resource for plant functional genomics. Proc Natl Acad Sci U S A 2004, 101:13951-13956. 37. Novaes E, Drost DR, Farmerie WG, Pappas GJ Jr, Grattapaglia D,  Sederoff RR, Kirst M: High-throughput gene and SNP discovery in Eucalyptus grandis, an uncharacterized genome. BMC Genomics 2008, 9:312. This is the first study to exploit the power of next-generation sequencing technologies in a forest tree to create a large database of expressed sequences for Eucalyptus. It shows that SNPs sampled in large-scale can be used to detect evolutionary signatures among genes for a non-model plant species. 38. Pavy N, Paule C, Parsons L, Crow JA, Morency MJ, Cooke J, Johnson JE, Noumen E, Guillet-Claude C, Butterfield Y et al.: Generation, annotation, analysis and database integration of 16,500 white spruce EST clusters. BMC Genomics 2005, 6:144. 47. Quesada T, Li Z, Dervinis C, Li Y, Bocock PN, Tuskan GA,  Casella G, Davis JM, Kirst M: Comparative analysis of the transcriptomes of Populus trichocarpa and Arabidopsis thaliana suggests extensive evolution of gene expression regulation in angiosperms. New Phytol 2008, 180:408-420. This comparative analysis of the transcriptome in vegetative organs of Populus and Arabidopsis thaliana revealed a core set of genes expressed in common among vegetative organs, as well as organ-specific genes in a woody perennial and an annual herbaceous species. Despite separation of the two lineages for over 100 million years, the authors suggest that selection has limited transcriptional divergence of genes associated with some essential functions but that the extensive remodeling of transcriptional networks indicates that expression regulation may be a key determinant of plant diversity. 48. Paiva JA, Garnier-Gere PH, Rodrigues JC, Alves A, Santos S,  Graca J, Le Provost G, Chaumeil P, Da Silva-Perez D, Bosc A et al.: Plasticity of maritime pine (Pinus pinaster) wood-forming tissues during a growing season. New Phytol 2009, 179:1180-1194. See annotation for [47]. 40. Hertzberg M, Aspeborg H, Schrader J, Andersson A, Erlandsson R, Blomqvist K, Bhalerao R, Uhlen M, Teeri TT, Lundeberg J et al.: A transcriptional roadmap to wood formation. Proc Natl Acad Sci U S A 2001, 98:14732-14737. 49. Paiva JA, Garces M, Alves A, Garnier-Gere P, Rodrigues JC,  Lalanne C, Porcon S, Le Provost G, Perez Dda S, Brach J et al.: Molecular and phenotypic profiling from the base to the crown in maritime pine wood-forming tissue. New Phytol 2008, 178:283-301. The authors of these two interesting papers use a combined approach involving infrared spectroscopy and analytical pyrolysis on wood samples, together with ESTs sequencing, gene expression profiling, and quantitative proteomics analysis, to explore the phenotypic variation observed along the tree stem and along the growing season in Pinus pinaster. Both studies provide a list of candidate genes for wood properties and for the phenotypic differences between earlywood and latewood to be tested in forward genetics approaches. 41. Schrader J, Nilsson J, Mellerowicz E, Berglund A, Nilsson P, Hertzberg M, Sandberg G: A high-resolution transcript profile across the wood-forming meristem of poplar identifies potential regulators of cambial stem cell identity. Plant Cell 2004, 16:2278-2292. 50. Cato S, McMillan L, Donaldson L, Richardson T, Echt C, Gardner R: Wood formation from the base to the crown in Pinus radiata: gradients of tracheid wall thickness, wood density, radial growth rate and gene expression. Plant Mol Biol 2006, 60:565-581. 42. Nilsson J, Karlberg A, Antti H, Lopez-Vernaza M, Mellerowicz E,  Perrot-Rechenmann C, Sandberg G, Bhalerao RP: Dissecting the molecular basis of the regulation of wood formation by auxin in hybrid aspen. Plant Cell 2008, 20:843-855. An elegant study dissecting the role of auxin in wood formation by identifying the auxin-responsive transcriptome in wood-forming tissues, and investigating alterations in wood formation in transgenic hybrid aspen plants. 51. Pavy N, Boyle B, Nelson C, Paule C, Giguere I, Caron S,  Parsons LS, Dallaire N, Bedon F, Berube H et al.: Identification of conserved core xylem gene sets: conifer cDNA microarray development, transcript profiling and computational analyses. New Phytol 2008, 180:766-786. This study provides a comprehensive comparative analysis of the transcriptome between angiosperms and gymnosperms identifying a set of 31 transcripts that appear conserved in the xylem of the two species in terms of both sequence and xylem expression. 39. Futamura N, Totoki Y, Toyoda A, Igasaki T, Nanjo T, Seki M, Sakaki Y, Mari A, Shinozaki K, Shinohara K: Characterization of expressed sequence tags from a full-length enriched cDNA library of Cryptomeria japonica male strobili. BMC Genomics 2008, 9:383. 43. Zhuang Y, Adams KL: Extensive allelic variation in gene expression in Populus F-1 hybrids. Genetics 2007, 177:1987-1996. 44. Druart N, Johansson A, Baba K, Schrader J, Sjodin A,  Bhalerao RR, Resman L, Trygg J, Moritz T, Bhalerao RP: Environmental and hormonal regulation of the activitydormancy cycle in the cambial meristem involves stagespecific modulation of transcriptional and metabolic networks. Plant J 2007, 50:557-573. By performing transcript and metabolite profiling of isolated cambial meristem cells of Populus, this study reveals potential targets of environmental and hormonal signals in the regulation of the activity–dormancy cycle in cambial meristem. www.sciencedirect.com 52. Kirst M, Myburg AA, De Leon JPG, Kirst ME, Scott J, Sederoff R: Coordinated genetic regulation of growth and lignin revealed by quantitative trait locus analysis of cDNA microarray data in an interspecific backcross of Eucalyptus. Plant Physiol 2004, 135:2368-2378. 53. Kirst M, Basten CJ, Myburg AA, Zeng ZB, Sederoff RR: Genetic architecture of transcript-level variation in differentiating xylem of a eucalyptus hybrid. Genetics 2005, 169:2295-2303. 54. Busov VB, Brunner AM, Meilan R, Filichkin S, Ganio L, Gandhi S, Strauss SH: Genetic transformation: a powerful tool for dissection of adaptive traits in trees. New Phytol 2005, 167:9-18. Current Opinion in Plant Biology 2009, 12:148–156 156 Genome studies and molecular genetics 55. Busov V, Meilan R, Pearce DW, Rood SB, Ma CP, Tschaplinski TJ, Strauss SH: Transgenic modification of gai or rgl1 causes dwarfing and alters gibberellins, root growth, and metabolite profiles in Populus. Planta 2006, 224:288-299. loci for adaptive traits between oak and chestnut based on an expressed sequence tag consensus map. Genetics 2006, 172:533-546. 56. Harrison EJ, Bush M, Plett JM, McPhee DP, Vitez R, O’Malley B, Sharma V, Bosnich W, Seguin A, MacKay J et al.: Diverse developmental mutants revealed in an activation-tagged population of poplar. Can J Bot 2007, 85:1071-1081. 72. Gallo de Carvalho MCdC, Caldas DGG, Carneiro RT, Moon DH, Salvatierra GR, Franceschini LvM, de Andrade A, Celedon PAF, Oda S, Labate CA: SAGE transcript profiling of the juvenile cambial region of Eucalyptus grandis. Tree Physiol 2008, 28:905-919. 57. Busov VB, Meilan R, Pearce DW, Ma CP, Rood SB, Strauss SH: Activation tagging of a dominant gibberellin catabolism gene (GA 2-oxidase) from poplar that regulates tree stature. Plant Physiol 2003, 132:1283-1291. 73. Paux EVC, Marques C, de Sousa AM, Borralho N, Sivadon P, Grima-Pettenati J: Transcript profiling of Eucalyptus xylem genes during tension wood formation. New Phytol 2005, 167:89-100. 58. Groover A, Fontana JR, Dupper G, Ma CP, Martienssen R, Strauss S, Meilan R: Gene and enhancer trap tagging of vascular-expressed genes in poplar trees. Plant Physiol 2004, 134:1742-1751. 74. Foucart C, Paux E, Ladouce N, San-Clemente H, GrimaPettenati J, Sivadon P: Transcript profiling of a xylem vs phloem cDNA subtractive library identifies new genes expressed during xylogenesis in Eucalyptus. New Phytol 2006, 170:739-752. 59. Salvi S, Sponza G, Morgante M, Tomes D, Niu X, Fengler KA, Meeley R, Ananiev EV, Svitashev S, Bruggemann E et al.: Conserved noncoding genomic sequences associated with a flowering-time quantitative trait locus in maize. Proc Natl Acad Sci U S A 2007, 104:11376-11381. 60. Meuwissen TH, Hayes BJ, Goddard ME: Prediction of total genetic value using genome-wide dense marker maps. Genetics 2001, 157:1819-1829. 61. Bernardo R, Yu JM: Prospects for genomewide selection for quantitative traits in maize. Crop Sci 2007, 47:1082-1090. 62. Wong CK, Bernardo R: Genomewide selection in oil palm: increasing selection gain per unit time and cost with small populations. Theor Appl Genetics 2008, 116:815-824. 63. Solberg TR, Sonesson AK, Woolliams JA, Meuwissen TH:  Genomic selection using different marker types and densities. J Anim Sci 2008, 86:2447-2454. This paper provides some very useful practical predictions on the factors driving the accuracy of genomic selection for quantitative traits. Marker density and marker type (microsatellite and SNP), and the use of marker haplotypes versus marker genotypes alone are evaluated. By simulating the accuracy of predicted breeding values as a function of effective population size, the results show that LD is the key factor in driving the genomic prediction process. Although the focus is on animal breeding, the results are fully relevant to the application of genomic selection to forest trees for traits such as growth. 64. Lee SH, van der Werf JH, Hayes BJ, Goddard ME, Visscher PM: Predicting unobserved phenotypes for complex traits from whole-genome SNP data. PLoS Genet 2008, 4:e1000231. 65. Cui LY, Wall PK, Leebens-Mack JH, Lindsay BG, Soltis DE, Doyle JJ, Soltis PS, Carlson JE, Arumuganathan K, Barakat A et al.: Widespread genome duplications throughout the history of flowering plants. Genome Res 2006, 16:738-749. 66. Fraga MF, Rodriguez R, Canal MJ: Genomic DNA methylationdemethylation during aging and reinvigoration of Pinus radiata. Tree Physiol 2002, 22:813-816. 67. Pot D, Rodrigues JC, Rozenberg P, Chantre G, Tibbits J, Cahalan C, Pichavant F, Plomion C: QTLs and candidate genes for wood properties in maritime pine (Pinus pinaster Ait.). Tree Genet & Genomes 2006, 2:10-24. 68. Bundock P, Potts B, Vaillancourt R: Detection and stability of quantitative trait loci (QTL) in Eucalyptus globulus. Tree Genet & Genomes 2008, 4:85-95. 69. Marques CM, Carocha VJ, de Sa ARP, Oliveira MR, Pires AM, Sederoff R, Borralho NMG: Verification of QTL linked markers for propagation traits in Eucalyptus. Tree Genet & Genomes 2005, 1:103-108. 70. Ukrainetz NK, Ritland K, Mansfield SD: Identification of quantitative trait loci for wood quality and growth across eight full-sib coastal Douglas-fir families. Tree Genet & Genomes 2008, 4:159-170. 71. Casasoli M, Derory J, Morera-Dutrey C, Brendel O, Porth I, Guehl JM, Villani F, Kremer A: Comparison of quantitative trait Current Opinion in Plant Biology 2009, 12:148–156 75. Moreau C, Aksenov N, Lorenzo MG, Segerman B, Funk C, Nilsson P, Jansson S, Tuominen H: A genomic approach to investigate developmental cell death in woody tissues of Populus trees. Genome Biol 2005, 6:R34. 76. Yakovlev I, Fossdal C-G, Johnsen Ø, Junttila O, Skrøppa T: Analysis of gene expression during bud burst initiation in Norway spruce via ESTs from subtracted cDNA libraries. Tree Genet & Genomes 2006, 2:39-52. 77. Derory J, Leger P, Garcia V, Schaeffer J, Hauser MT, Salin F, Luschnig C, Plomion C, Glossl J, Kremer A: Transcriptome analysis of bud burst in sessile oak (Quercus petraea). New Phytol 2006, 170:723-738. 78. Bohlenius H, Huang T, Charbonnel-Campaa L, Brunner AM,  Jansson S, Strauss SH, Nilsson O: CO/FT regulatory module controls timing of flowering and seasonal growth cessation in trees. Science 2006, 312:1040-1043. This landmark study shows that a regulatory module that controls flowering time in response to variations in day-length in annual plants not only controls flowering but also the short-day-induced growth cessation and bud set occurring in the fall in aspen trees. 79. Freeman JS, Potts BM, Vaillancourt RE: Few Mendelian genes underlie the quantitative response of a forest tree, Eucalyptus globulus, to a natural fungal epidemic. Genetics 2008, 178:563-571. 80. Freeman JS, O’Reilly-Wapstra JM, Vaillancourt RE, Wiggins N, Potts BM: Quantitative trait loci for key defensive compounds affecting herbivory of eucalypts in Australia. New Phytol 2008, 178:846-851. 81. Ralph SG, Chun HJ, Cooper D, Kirkpatrick R, Kolosova N, Gunter L, Tuskan GA, Douglas CJ, Holt RA, Jones SJ et al.: Analysis of 4,664 high-quality sequence-finished poplar fulllength cDNA clones and their utility for the discovery of genes responding to insect feeding. BMC Genomics 2008, 9:57. 82. Adomas A, Heller G, Olson A, Osborne J, Karlsson M, Nahalkova J, Van Zyl L, Sederoff R, Stenlid J, Finlay R et al.: Comparative analysis of transcript abundance in Pinus sylvestris after challenge with a saprotrophic, pathogenic or mutualistic fungus. Tree Physiol 2008, 28:885-897. 83. Dillen SY, Marron N, Koch B, Ceulemans R: Genetic variation of stomatal traits and carbon isotope discrimination in two hybrid poplar families (Populus deltoides ‘S9-2’ x P. nigra ‘Ghoy’ and P. deltoides ‘S9-2’ x P. trichocarpa ‘V24’). Ann Bot 2008, 102:399-407. 84. Brendel O, Le Thiec D, Scotti-Saintagne C, Bodénès C, Kremer A, Guehl J-M: Quantitative trait loci controlling water use efficiency and related traits in Quercus robur L. Tree Genet & Genomes 2008, 4:263-278. 85. Plomion C, Lalanne C, Claverol S, Meddour H, Kohler A, BogeatTriboulot MB, Barre A, Le Provost G, Dumazet H, Jacob D et al.: Mapping the proteome of poplar and application to the discovery of drought-stress responsive proteins. Proteomics 2006, 6:6509-6527. www.sciencedirect.com