The genetic basis of interspecific differences in wood quality traits is poorly understood in Eucalyptus.
Recent developments in forest molecular genetics and forest genomics may vastly increase our knowledge of the genetics of interspecific differentiation in these traits. This paper will discuss new approaches towards
the molecular genetic analysis of wood quality traits in Eucalyptus trees. In particular, results will be reviewed of a molecular marker analysis of near-infrared (NIR) predicted wood properties in an interspecific backcross pedigree of E. grandis and E. globulus.
Fast-growing hybrids of Eucalyptus are some of the most productive biomass producers in the world. They produce large quantities of cellulose and lignin, the two most abundant biopolymers on earth. Cellulose and lignin play important biological roles in trees, mainly as structural components of xylem cell walls. They are also vitally important for the multi-billion dollar pulp and paper industry. Relatively small changes in the chemical composition and physical properties of xylem cell walls can have tremendous cost implications for pulping and papermaking processes1.
Considerable differences in wood property traits exist between different species of Eucalyptus, and desirable characteristics can be identified in eucalypt species that are not commonly used for pulp and
papermaking2. The genes and genetic mechanisms that underlie interspecific differentiation in these traits are of particular interest in Eucalyptus, due to the potential to combine favourable
characteristics of different species through interspecific hybridisation.
Until recently, questions pertaining the genetic control of wood formation were
practically intractable. Forest tree, like humans, carry high amounts of genetic load (recessive deleterious mutations) that can lead to severe inbreeding depression when they are crossed to close relatives3.
This has precluded the application of traditional crop breeding techniques, particularly inbred line development, and has hampered the development of experimental populations that are suitable for detailed genetic
studies. Molecular genetic studies of forest trees are also limited by their long generation times and the large areas of land required for field trials. Furthermore, molecular genetic resources are not well
developed in most forest tree species. This situation may change in the near future, in large part due to the recent technological advancements made in plant genomic research.
We are entering an exciting new era in plant genetic research. The completion of the
first plant genome projects4-6, has meant that for the first time, it may be possible to identify and analyse a complete set of genes involved in wood formation in a single plant species. Soon the first
complete sequence of a tree genome (poplar) will be publicly available7. This information, together with the genome data of model plants such as Arabidopsis8, will advance our understanding of
the genetic control of wood formation in hardwood genera. It will also lead to the identification of many new candidate genes for direct genetic engineering of wood quality in forest trees. However, these approaches
will be severely hampered by the negative public perception of genetically modified (GM) organisms9.
The aim of this paper is to provide a brief overview of progress in the molecular genetic
analysis of wood property traits in Eucalyptus and other forest tree species. In particular, new (non-GM) approaches for the genetic improvement of wood quality in forest plantations will be discussed. Finally, the main findings of a recent molecular genetic analysis of physical and chemical wood property traits in a cross of E. grandis and E. globulus will be reviewed, with the aim to assess the potential use of this technology to breed plantation forest trees with improved wood quality.
GENETIC MAPPING OF WOOD PROPERTY TRAITS IN FOREST TREE GENOMES
Molecular marker technology has enabled geneticists to assay DNA sequence variation in
many plant genomes. Each molecular marker represents a particular DNA variant whose inheritance (and that of closely linked genes) can be accurately followed from one generation to the next. In forest tree species,
it has been shown that complete genome coverage can be achieved if sufficiently large sets of molecular markers are assayed10. This means that the inheritance of essentially all the genes in a tree
genome can be followed from one generation to the next and that the genomic composition (i.e. the unique combination of gene copies, or alleles) of all the progeny of a cross can be determined.
Accurate phenotypic measurement of the progeny of such a cross has allowed the
identification of molecular markers flanking genomic regions that contain genes or regulatory sequences associated with an increase or decrease in the trait of interest. These genomic regions or quantitative trait
loci (QTLs) are identified by statistical analysis of marker-trait association11-13. Recombination between the flanking markers and QTLs leads to decreasing marker-trait association (or increased linkage
equilibrium) over generations and diminishes the utility of the markers for marker-assisted breeding (MAB)14. However, linkage disequilibruim (LD) between markers and genes is maximized in new intra- and
interspecific crosses and marker-trait associations can persist for several generations of within-family (or hybrid) breeding in the progeny of these crosses15.
Wood property traits are generally inherited in a polygenic fashion16 and multiple genes may underlie variation in wood properties in any particular cross. Complete genetic linkage maps are therefore required to determine the genetic architecture of wood property traits in each cross (i.e. the number, location and effects of the genes involved). In Eucalyptus,
nearly complete genetic linkage maps have been constructed in several studies based on intra- and interspecific crosses17-22. The total length of each these maps has generally ranged between 1300 to 1400
centiMorgans (cM) with an average of approximately 120 cM per linkage group (representing the genetic map length of each of the 11 chromosome pairs in Eucalyptus). QTLs for wood properties have been located
in some of these maps to regions of approximately 20 to 30 cM, which represents a selection target of 3 to 5% of the total eucalypt genome23,24.
The first of these studies by Grattapaglia et al23 reported the detection of five QTLs for wood specific gravity. These QTLs explained 24.7% of the phenotypic variation in wood specific gravity measured in 300 individuals of an open pollinated half-sib family of E. grandis.
In this study, 164 individuals were also assayed for cellulose pulp yield, but no QTLs were detected for this trait. In the study by Vehaegen et al24, wood density was measured by pilodyn penetration in
200 F1 trees of an interspecific cross between E. urophylla x E. grandis. Measurements were taken at 18, 26 and 38 months to investigate the stability of QTLs across different ages. Between
1 and 4 QTLs were detected at different ages in each of the two parents and these QTLs jointly explained between 26% and 40% of the total phenotypic variation in the F1 family. Two QTLs in each of the parents were stably expressed in successive ages.
Both of these studies supported the presence of a limited number of major genes
controlling large proportions of the total variation in wood properties is Eucalyptus. These results were consistent with subsequent reports of the genetic architecture of wood properties in other forest tree
species25-27. Similar findings have also been published for a range of agronomical traits in variety of crop plants28. However, as early as 1994, comparative analyses of QTL
experiments performed in different crosses of maize indicated that this finding (small numbers of large-effect QTLs) may be an artefact of the relatively small population sizes that had been used in QTL experiments29. Based on this study, Beavis29 cautioned that in small populations only a small subset of the true number of QTLs may be detected and that the effects of these QTLs are likely to be overestimated.
Recent investigation of the genetic architecture of juvenile wood density in Pinus radiata in a very large full-sib family of more than 2800 individuals30,
confirmed that the effects of wood property QTLs were smaller than previously estimated in small populations (n < 300). It was found that QTLs detected in large populations (n > 1000) might individually account for only 1.3 - 3.1% of phenotypic variation. However, the total proportion of variation explained by QTLs detected in large mapping populations may remain the same, due to the greater number of QTLs detected. It is not clear whether these results resolve an ongoing debate over the distribution of QTL effects in plant genomes15,31.
The results of QTL studies in very large populations seem to support classical quantitative genetic models that are based on the assumption of large (infinite) numbers of genes, each with a very small effect.
Nevertheless, these results suggest that QTL mapping of wood quality traits should be performed in much larger experimental populations to ensure accurate estimation of QTL effects.
The high cost and low throughput of conventional wood property assays has limited genetic
studies of wood property traits in large populations of forest trees. Chemical properties are especially time-consuming and expensive to measure in large numbers of trees and small, non-destructive samples may not
accurately reflect whole-tree properties32. There has been an ongoing effort to develop methods for low-cost, high-throughput measurement of wood properties in forest trees. Examples of these methods
include: computer tomography X-ray densitometry (CT scan) for the measurement of specific gravity33, pyrolysis molecular beam mass spectrometry (pyMBMS) for the measurement of lignin, cellulose and
hemi-cellulose33 and near-infrared (NIR) analysis for the prediction of chemical and physical wood properties34,35. pyMBMS has been successfully used to map QTLs for chemical wood properties in
loblolly pine36, while NIR analysis was recently used for QTL mapping of physical and chemical wood properties in an interspecific backcross pedigree of Eucalyptus37 (see below).
Progress has also been made in the development of high-throughput methods for molecular
marker analysis of forest trees. When the amplified fragment length polymorphism (AFLP) marker system38 was introduced in 1995, it allowed the highest throughput of all DNA-based marker systems to date. More than 100 DNA fragments could be resolved and evaluated for marker polymorphism in a single assay. However, the throughput of the method was still limited, because it required fragment detection by autoradiography. This limitation was overcome by adapting the marker protocol to allow detection of infra-red dye-labeled AFLP fragments on automated DNA sequencers10.
Additional modification of the methodology allowed a throughput of 70,000 polymorphic genotype determinations per week in interspecific backcross progeny of Eucalyptus39. Currently, it is possible
to genotype more than 500 markers in 200 progeny of a full-sib family of Eucalyptus in one month. Nearly complete AFLP genetic maps of the two parents can therefore be constructed within six to eight weeks. This throughput will allow the construction of genetic maps for multiple elite parents in a breeding population, which will facilitate the comparative analysis of wood property QTLs in different crosses and genotypic combinations.
Molecular genetic studies in Eucalyptus will also benefit from the recent development of microsatellite markers for this genus40,41.
These markers are multi-allelic, co-dominant markers, which mean that they can be used to study the effect of different QTL genotypes across many different crosses and pedigrees (as opposed to AFLP markers that tend
to be specific to related crosses). Microsatellite markers have been shown to be highly transportable between different species of Eucalyptus40 , which make them ideal markers for comparative
mapping of eucalypt species. The construction of a genus-wide consensus map will soon be possible and this will provide valuable information on genome evolution in Eucalyptus41.
QTL ANALYSIS OF WOOD PROPERTIES IN AN INTERSPECIFIC HYBRID OF E. GRANDIS AND E. GLOBULUS
Wide interspecific crosses of E. grandis and E. globulus parents may be useful to combine the favourable growth, adaptability and rooting characteristics of E. grandis with the superior wood properties of E. globulus.
Genetic factors that underlie interspecific differentiation in these traits are expected to be heterozygous in the F1 hybrid of these two species and should therefore segregate in F2 backcross progeny of this cross. These hypotheses formed the basis of a recent molecular genetic analysis of chemical and physical wood properties in two interspecific backcross families of E. grandis and E. globulus42.
The F2 backcross families used in this study were developed by crossing a single superior F1 tree to unrelated individuals of the parental species. The backcross progeny were planted in a uniform field site in Uruguay for phenotypic evaluation. After two years, wood discs were taken from breast height and drill cuttings (10 - 20 gr. dry wt.) collected from each disc for NIR analysis. Previously obtained NIR calibrations (kindly provided by Shell Forestry Technical Services, East Malling, UK) were used to predict wood property trait values for a range of characteristics including: pulp yield, alkaline consumption during pulping, lignin content, cellulose content, extractives content, wood density, fibre length, fibre coarseness and heat content.
Genetic linkage maps were constructed for the parents of the two backcross families (i.e.
the F1 hybrid and the two backcross parents) using a high-throughput AFLP protocol developed specifically for Eucalyptus39. These maps covered more than 95% of the parental genomes43 and were therefore suitable for whole-genome analysis of wood property genes segregating in the two backcross families. The population sizes for QTL detection and mapping (number of backcross progeny with NIR predicted trait values and AFLP genotypes) were 265 in the backcross to E. globulus and 277 in the backcross to E. grandis.
Composite interval mapping (CIM) methods11,12 were used to locate putative QTLs for the NIR predicted wood properties in the genetic maps of the three parental trees (the F1 hybrid and the two backcross parents). In addition, principal component analysis (PCA) was used to identify independent components of variation in the NIR spectra of the backcross individuals. The principal components were used as phenotypes for QTL detection in the same way as the predicted wood properties. This resulted in the identification of 18 putative QTLs with significant effects on NIR spectral variation and NIR predicted wood properties in the E. globulus BC family, while 13 putative QTLs with significant effects were identified in the E. grandis BC family. The allelic substitution effects of the individual QTLs ranged from 0.26 to 0.67 phenotypic standard deviations and they jointly explained 3.7 to 24.3% of the total phenotypic variation in each trait. The majority of these QTLs segregated out of the F1 hybrid and may represent genetic factors that are responsible for interspecific differentiation in the NIR predicted wood properties.
Evaluation of the co-localization of putative QTLs for the different NIR predicted traits
suggested that many of the QTLs affected two or more correlated traits. The directions of the shared QTL effects were in most cases consistent with the phenotypic correlation between the traits, which provided a
genetic explanation for the observed trait correlations. QTL analysis of the principal components of the raw NIR spectral variation revealed that many of the putative QTLs that were shared among different NIR
predicted wood properties were also present in QTL profiles of the individual principal components. Four traits in particular, fiber coarseness, cellulose content, lignin content and heat content, had very similar
QTL profiles than one of the principal components of NIR spectral variation. This suggested a strong genetic basis for this principal component, and pointed towards the possible use of raw NIR spectral data for the
detection of QTLs with effects on wood properties.
These results suggested a complex genetic basis for wood quality traits in the F1 hybrid of E.
grandis and E. globulus, which was not unexpected for such a wide interspecific cross. It was also possible to identify F2 backcross individuals with complementary multilocus genotypes at the major wood property QTLs. These individuals may be useful as parents for an F3 intercross or advanced backcross generation. Approximately 100 of the E. grandis backcross individuals have been cloned and will be used in advanced generation crosses based on their QTL genotypes and NIR predicted wood properties.
CONCLUSIONS AND FUTURE PROSPECTS
1. As demonstrated in the E. grandis x E. globulus mapping study, interspecific
backcrosses provide good experimental populations for molecular genetic studies, because large numbers of molecular markers and genes segregate in these populations and parental species can be chosen on the basis of
contrasting trait values.
2. Much larger experimental populations (n > 1000) are required to increase the
power to detect QTLs in forest trees30. Single families of this size generally do not exist in commercial breeding programmes. Therefore, these crosses need to be planned and made specifically for
molecular genetic studies. However, these crosses should be fully integrated with tree improvement programmes to ensure that new superior genotypes can be deployed immediately or used as parents in the breeding
3. There is a need to evaluate the effect of QTLs across different families or crosses.
For example, a half diallel of six parents with at least 200 progeny per full-sib family will result in half-sib families of 1000 or more individuals. Detailed genetic maps can be constructed for all six parents by
genotyping only three of the 15 full-sib families with large numbers of AFLP markers (approx 1000 markers per family). The rest of the families can be analysed with a smaller number of framework markers and
microsatellite markers to integrate the map information. In this design, allelic effects can be analysed across different families and a much better estimate obtained of the breeding value of a QTL allele44.
4. Future genetic markers will be increasingly based on known gene sequences. Single
nucleotide changes are the most abundant form of polymorphism in plant genes and single nucleotide polymorphism (SNP) markers can be used to develop gene- or allele-specific markers in plants45,46. SNP
markers developed in candidate genes can be used to detect association between genes and quantitative traits in natural populations of plants47. Large numbers of genes are currently being sequenced in
forest tree species48,49. SNP analysis of these genes and association-based (LD) mapping will provide a powerful approach to identify genes and alleles for superior wood and fibre traits in forest trees.
Suitable unstructured populations for association genetic studies in Eucalyptus may already exist in the form of first generation breeding populations, but future association genetic studies will be most effective in managed "natural" populations of unrelated individuals.
The wood property study in the interspecific backcross pedigree of E. grandis and E.
globulus formed part of a collaboration between Shell Forestry, UK (Rod Griffin) and North Carolina State University, Raleigh, NC (Ron Sederoff and Ross Whetten). Plant materials were provided by Shell Uruguay Renewables S.A (Pablo Santini and co-workers) and Forestal Oriental SA, Uruguay. Shell Forestry Technical Services, U.K. (Jane Harbard) were responsible for the controlled pollinations that produced the backcross families, and kindly provided facilities and technical assistance to perform the NIR analyses (John Purse, Chris Emerson). This work was supported by funding from the North Carolina State University Forest Biotechnology Industrial Associates Consortium and by the USA National Institutes of Health (Grant GM45344-06). A.A.M. was funded by the Fulbright Program and the National Research Foundation of South Africa.
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