Developments in and applications of forest biotechnology are rapidly expanding. They are becoming both more complex and more accessible throughout the world. There are fundamental differences in public perception and potential applications of biotechnology in forestry relative to agriculture. These differences stem from the multifaceted cultural and utilitarian role forests play, and their relatively recent history of domestication compared to that of agricultural crops. This report represents an attempt to describe these activities and anticipate their contribution in forestry.
Many recent publications, including working groups and conferences of the FAO, have dealt with various aspects of biotechnology in the forestry context (e.g. Krutovskii and Neale 2001; Yanchuk 2001; FAO 2002). During the past 15 years, this field has seen rapid development of new technology and a large increase in the number of groups involved in research and applications around the world (Ellis et al. 2001; Campbell et al. 2003). Research and testing of modern biotechnology in the initial stages requires up-to-date laboratory facilities. While the technological tools for forest biotechnology are typically adapted from an agricultural background, the subsequent applications and impacts differ substantially when applied to trees (Owusu 1999; FAO 2002). Biotechnology in forestry, for example its use in intensively managed plantations, engenders a host of issues not addressed by agricultural models, and central to those is the relatively long rotation required for forest crops to reach economic maturity. The majority of these differences originate from the fundamental life history characteristics of trees as sessile, long-lived, outcrossing organisms which can disperse pollen and seed across very long distances, and would likely be planted in potential mating proximity to wild, compatible populations or related species (DiFazio et al. 1999). Other differences between agriculture and forestry which must be taken into account stem from public perception: people often regard trees as essential components of forest ecosystems which perform many functions and provide many tangible and metaphysical values simultaneously, unlike most crop plants (Owusu 1999; FAO 2002).
Although anthropological influences are traceable in most of the world’s forests, and managed forests have been the norm in parts of the world for centuries, trees have been partly domesticated only in the past half century. In effect, very few of these trees are removed more than two or three generations from their wild congeners (Libby 1973). Since trees have fairly long generation times, breeding and deployed populations and even clonal lines produced through various vegetative propagation techniques, including biotechnological methods, are still very similar to their wild contemporaries, unlike many agricultural crop plants (Campbell et al. 2003). For example, teosinte has been transformed through millenia of traditional and intensive breeding into a narrow range of maize or corn lines, with a drastically different mating system, range, phenology, physiology and associated genetic characteristics.
Recent literature varies in how it categorizes forest biotechnology (e.g. Haines 1994; Yanchuk 2001; FAO 2001). Owing to the gradual evolution of our understanding of genetics, and the consequent development of new tools and technologies by refining and combining new knowledge with prior research, these categories overlap to some degree. The author used five major categories, each of which can be applied to a characteristic subset of applications (see Tables 2.4.1 and 2.4.2):
1. Markers (biochemical and molecular).
2. Propagation and multiplication.
3. Genomics (functional, structural, comparative, associative, statistical).
4. Marker-assisted selection (MAS) and breeding.
5. Genetic modification.
These tools and their utility are applicable on different scales, from the individual cell or plant to the landscape level (see Table 2.4.1). The only category which results in genetic manipulation of living trees is number 5, although development of some markers and DNA libraries for genomics may involve transformation of bacteria in the laboratory. The impact of these biotechnologies will therefore vary with the specific use, as will the associated benefits and risks (see Table 2.4.2; Arntzen et al. 2003). Certification of forest products, forest companies and lands is also potentially affected by the application of biotechnology. There are many certification agencies around the world, and some, such as the Forest Stewardship Council (FSC), have specifically excluded genetically modified (GM) trees from certifiability, or the land on which they grow, or other products obtained from stands containing these trees (FSC 1996). Some clonal forestry operations are certified, but most agencies have no explicit guidelines concerning genetic applications. Industrial processes which utilize genetic transformation of enzymes to chemically break down lignin in the harvested wood, e.g. pulping using enzyme digestion, have been certified on the grounds that this reduces toxic chemical use and discharge. Thus, certification standards vary among agencies, countries, products, processes and applications. Public opinion regarding genetic modification is more amenable to downstream (post-harvest) than upstream (pre-harvest) applications; the main cause for concern appears to be the potential for release of GM trees into the environment, which is an issue only for the latter (Pew Initiative on Food and Biotechnology 2001; Gartland et al. 2002).
Developed countries and developing countries or countries in transition have different priorities and applications for biotechnology (see Table 2.4.2; Anonymous 2003). DNA-based applications (some markers, genomics and genetic modification) require a large initial outlay of resources, may have continuing high costs depending on the project, and entail a highly trained work force (Ritland and Ritland 2000; Industry Canada – Life Sciences Branch 2001). Developed nations have so far been leaders in developing and applying these technologies for a variety of purposes (breeding, commerce and conservation; public and private uses), but it should be noted, based on the agriculture model, that barriers to the flow of capital and expertise associated with the introduction of biotechnology to new territories are virtually non-existent. In other words, the introduction of forest biotechnology tools to developing countries and countries in transition could be rapid as long as economic opportunities are present. Government agencies in developed countries typically provide much of the funding and infrastructure for the development of basic biotechnology research; however, it should be noted that applied research and development associated with any potential commercialization are mainly driven by the private sector.
The shift of funds supporting biotechnology from the public to the private sectors requires a new way of viewing the introduction of these tools into the forest sector. Thus, published information indicates that the majority of known forest biotechnology activities in developing countries and countries in transition have been more restricted in their scope, primarily to the use of markers and propagation, although other tools may have been introduced into the private sectors but, if so, information on the types of biotechnology application, their places of introduction and their frequency are unknown. The FAO Biotechnology in Developing Countries (FAO-BioDeC) database39 could be a useful storage facility for such forestry biotechnology information.
The flow of some biotechnology through teams including partners both from developed countries and from developing countries and countries in transition, such as CAMCORE (International Cooperative for Tree Conservation and Domestication), have provided increased access to these resources and tools.
Risk assessment is a critical application of many of the new biotechnological tools, and must, in turn, be applied to innovations as they are developed (Government of Canada 1985; Owusu 1999). Targeted gene engineering is of key concern, both with respect to inserting and eliminating gene function. Gene flow assessments are being conducted for poplars (e.g. DiFazio et al. 1999), but much more information is required to allay public concerns and deal with ecological hazards surrounding the potential for gene escape (Pew Initiative on Food and Biotechnology 2001; FAO 2002; Giles 2003). This applies to pollen and seed dispersal, as well as the ability of species to sprout via roots or stumps, become vigorous weeds, or hybridize with wild sympatric congeners (Government of Canada 1985; Crawley et al. 2001; Dalton 2002; Pilate et al. 2002; Adam 2003). Escapes and introgression of agricultural genes have been documented, as has unauthorized planting of GM crop seeds, leading to assessment, monitoring and regulatory problems. The relative fitness effects conferred by each novel trait must be evaluated in the environmental and genetic context of the field in order to assess risks properly (Johnson and Kirby 2001; Dalton 2002; Pilate et al. 2002; Anonymous 2003). Promoter genes and other biosensors are being investigated as means of tracking GM material, a necessary precondition prior to approval for field testing or deployment. Experts have widely concurred that a case-by-case examination is necessary for approval of GM trees (Government of Canada 1985; Heron and Kough 2001; FAO 2002; Arntzen et al. 2003).
The high cost of biotechnology will probably steer its commercial use towards short-rotation plantations as opposed to less intensively managed forests, but some applications are suitable for all forest types and can guide forest conservation activities (see Tables 2.4.1 and 2.4.2) (Sedjo 1999; Yanchuk 2001). An attempt to indicate the status of each tool and likely future trends in its use will be made in the following sections.
Biotechnology has progressed from phenotype to genotype, and has been trying to quantify relationships between the two ever since. Early work focused on biochemistry (e.g. terpene analysis), progressed to biosynthetic constitutive or induced protein expression (isoenzymes) and is now utilizing DNA-based tools (e.g. microsatellites, quantitative trait loci [QTLs]) since the advent of PCR (polymerase chain reaction) technology.
Molecular markers can be either dominant (only the dominant allele is expressed if both parents are genetically different at a given locus) or codominant (the genotypes of both parents are quantifiable at a locus). Dominant markers (amplified fragment length polymorphisms [AFLPs], randomly amplified polymorphic DNAs [RAPDs]) require larger sample sizes for statistical analysis than codominant markers (isoenzymes, microsatellites/simple sequence repeats [SSRs], restricted fragment length polymorphisms [RFLPs], sequence-tagged sites [STSs], expressed sequence tags [ESTs], single nucleotide polymorphisms [SNPs]).
The different markers all have varying benefits, drawbacks, costs and ease of development and all can be applied to a limited range of optimal applications, generally focused on neutral or non-adaptive genetic variation (see Table 2.4.1, Ritland and Ritland 2000, Krutovskii and Neale 2001, and others for reviews). Molecular tools have been widely used to measure gene flow and genetic diversity of natural and artificial populations of forest trees and associated species, and the impacts of anthropogenic disturbance on their evolutionary potential (Haines 1994; Ritland and Ritland 2000; Yanchuk 2001). The long-term viability of species and endemics subject to influences such as pollution or climate change can be modelled using genetic data. There are still no highly repeatable, easily assayed markers directly linked to quantitative traits. Although progress has been made in identifying QTLs for some adaptive traits in some species, a good genomic linkage map is essential, as are breeding and identification and sequencing of candidate genes for quantitative traits of interest. The application of marker technology in forestry is by far the most extensive use of other tools. It is not restricted to either developed countries or developing countries and countries in transition, but the type of markers, the speed of use and the frequency of utilization differs with the status of marker development and the biometrical methods needed for data analyses (see Tables 2.4.1 and 2.4.2).
Clonal forestry using both broadleaves and conifers is gaining in popularity due to the resulting uniformity and ease of silviculture, harvesting and processing. More importantly, it allows the capture of levels of genetic gain that cannot be attained through sexual reproduction. This technology is restricted to organogenesis and somatic embryogenesis, which require extremely detailed understanding of cell biology, multiplication, biochemical signalling, differentiation and the production of copies or clones in a laboratory setting. Both of the above methods capitalize on plant species’ ability to regenerate an entire genetically identical individual from a single cell or group of differentiated or undifferentiated cells via in vitro tissue culture. Individuals with selected traits or the highest performers from testing trials or breeding programmes can be replicated on a large scale, capturing both additive and non-additive genetic variation from traditional breeding. The advantage of these methods is the ability to store regenerated tissues indefinitely in liquid nitrogen or under laboratory conditions (i.e. hold the genotype constant) while field testing is underway to identify elite lines. This allows selected lines with desirable attributes to be further multiplied for operational deployment. Currently some operational scale production is underway both in developed countries and in developing countries and countries in transition, but it should be noted that the scale of production in broadleaves is larger than that in conifers.
Our understanding of fundamental biology and evolution is also being enriched through collaborative efforts using model species in genomics research around the world (Krutovskii and Neale 2001). Evolutionary synteny among taxa, even those as distantly related as algae and angiosperms, can be quantified and candidate genes or groups of proteins (microarrays) involved in biochemical pathways of interest can be identified easily: this process of identifying putative genes controlling certain traits is called gene discovery. Expression of key gene families or microarrays and their relative up- or down-regulation following stress or environmental changes can be gauged, possibly leading to identification of compounds of significance, and their interactions with genotype and the environment. Characterization of genetic components of disease or pest resistance is a rapidly expanding field (Ellis et al. 2001; Gartland et al. 2002). Genomics is a fairly new field with many subdisciplines (Krutovskii and Neale 2001), which requires substantial investment for start-up and maintenance: high-technology automata, costly supplies and chemicals, PCR and other machines, highly trained laboratory staff, marker (EST, SNP) development, as well as vast bioinformatics and associated statistical capacity are necessary. At present, the majority of activity in this area is at the research level.
While the phenotype is the desired end result of breeding, variation associated with differences in expression, genotype-by-environment interaction and non-additive or epistatic genetic variability necessitates large, costly and time-consuming field trials for trees with traits of interest (Haines 1994; Yanchuk 2001). Mendelian inheritance and our increasing ability to understand and target specific genes have enabled the development of MAS to complement traditional breeding (Haines 1994; Campbell et al. 2003). This technique has been used with tremendous success in agricultural crop breeding for various genes and traits over the past two decades, and is increasing in importance as more comprehensive genetic maps, and the locations of QTLs on those maps, are developed for each species. If MAS can be used to characterize and select tree genotypes, substantial cost savings may be realized by a much shorter breeding cycle (i.e. more rapid turnover between generations) (Haines 1994; Sedjo 1999). Although based on tools developed using markers, it requires the use of material of known pedigree and integrates the study of specific structural, functional and morphological attributes of species’ genomes. Although this work is experimental at this stage, several studies both in developed countries and in developing countries and countries in transition on broadleaves and conifers are underway. Information on the progress of these studies is sketchy owing to their often mixed funding nature (i.e. public and private).
Research on and the potential for deployment of GM trees have caused widespread public concern. Regulatory agencies have called for more research on gene flow, likelihood of horizontal and vertical gene transfer via escapes, hybridization and introgression, and a range of ecological impacts of GM material in the field (Owusu 1999; Johnson and Kirby 2001; Pew Initiative on Food and Biotechnology 2001; Gartland et al. 2002; Anonymous 2003). Concerns about GM trees share similarities with those about agricultural crops, but while the latter are grown and used for research and consumer products throughout many developed and developing nations, transforming trees has only recently begun, and is currently mainly at the experimental stage. In the laboratory, transformation has been achieved using biolistics and Agrobacterium species for conifer and broad-leaved genera of commercial importance.
Specific genes and regions, primarily conferring insect or disease resistance, sterility, and wood quality attributes, have been the focus of nearly all of the research (Pilate et al. 2002; Campbell et al. 2003). Some promoter and marker genes have also been tested. In some regions, pulp and paper processing has achieved dramatic reductions in the use of highly toxic chlorine and other chemicals by employing enzymes genetically modified to digest lignin (Ellis et al. 2001; Pilate et al 2002; Campbell et al. 2003). The use of genetic modification during industrial processing does not currently appear to cause public concern, especially when the outcome includes substantial environmental benefits. It is difficult to give an accurate account of this type of work since the majority of it is being conducted by the private sector.
Table 2.4.1 summarizes the anticipated contribution to and scale of impact of each broad area of biotechnology on elements of forest populations. For instance, the table shows the various forestry practices in which these tools will play a significant role as well as the spatial scale of their use (from the individual tree to population to landscape). Additionally, the specific component activities that these tools will contribute to are broken down into individual activities that are associated with knowledge accumulation in terms of the forest resource, selection, breeding, testing, forest management, IPM (integrated pest management), and downstream activities such as pulping. This table highlights biotechnology categories that are in frequent use, and the development and/or research status of the remaining categories (El-Kassaby and Krakowski 2005).
A summary of the various broad technologies where biotechnology is expected to play a significant role is presented in Table 2.4.2. It shows the broad application and overlapping functions of these categories in relation to various activities. For instance, each broad biotechnology category encompasses its use and a description of its specific tools (markers, tools, traits, areas of use), their frequency of use (from no use to very common), and a brief description of how they are used.
There is, to date, no single system systematically collating the different forest biotechnology activities around the world. This would be necessary to gauge current concerns and predict future trends, impacts and needs in this rapidly expanding field. International regulation of biotechnology is inconsistent, and even varies between jurisdictions. Research and development being done in the private sector subject to confidentiality or intellectual property agreements, patent protection and corporate competition preclude or prevent dissemination of some types of information. Other forestry biotechnology applications occur on private lands, or in areas where there is no requirement or framework to report their implementation or extent.
Technical development of forestry, in most cases, mirrors that of agriculture. The use of biotechnology tools in forestry has already caused confusion. As stated above, only one out of five possible biotechnology categories in forestry involves genetic modification and its state-of-the-art is mainly experimental (however, see Section 2.4.4.5, above). Nonetheless, public perception may preclude the use or affect the usefulness of the other biotechnology categories in forestry. The diversity of topics and the variable levels of competence in the field of forestry biotechnology require cross-functional team effort at national and international levels. Wide-ranging contributions that give species and geographic representation are required to ensure accuracy and balance.
Adam, D. 2003. Transgenic crop trial’s gene flow turns weeds into wimps. Nature (London), 421: 462.
Anonymous. 2003. Missing the big picture. Nature (London), 421: 675.
Arntzen, C.J., Coghlan, A., Johnson, B., Peacock, J. & Rodemeyer, M. 2003. GM crops: science, politics and communication. Nat. Rev. Genet., 4: 839–843.
Campbell, M.M., Brunner, A.M., Jones, H.M. & Strauss, S.H. 2003. Forestry’s fertile crescent: the application of biotechnology to forest trees. For. Biotechnol., 1: 141–154.
Crawley, M.J., Brown, S.L., Hails, R.S., Kohn, D.D. & Rees, M. 2001. Transgenic crops in natural habitats. Nature (London), 409: 682–683.
Dalton, R. 2002 Superweed study falters as seed firms deny access to transgene. Nature (London), 419: 655.
DiFazio, S.P., Leonardi, S., Cheng, S. & Strauss, S.H. 1999. Assessing potential risks of transgene escape from fiber plantations. In P. Lutman, ed. Proceedings, Symposium on Gene Flow and Agriculture: Relevance for Transgenic Crops. No. 72. Farnham, UK, British Crop Protection Council.
Ellis, D., Mellan, R., Pilate, G. & Skinner, J.S. 2001. Transgenic trees: where are we now? In S.H. Strauss & H.D. Bradshaw, eds. Proceedings, 1st International Symposium on Ecological and Societal Aspects of Transgenic Plantations, pp. 113–123. College of Forestry, Oregon State University, Corvallis, OR, USA.
El-Kassaby, Y.A. & J. Krakowski. 2005. Forest biotechnology deliverables. In: Proceedings, North New Century, New Trees: Biotechnology as a Tool for Forestry in North America, Research Triangle Park, NC, USA, 16–17 November 2004. (in press)
FAO. 2001. Biotechnology in the forest sector (available at www.fao.org/biotech/sector5.asp)
FAO. 2002. Gene flow from GM to non-GM populations in the crop, forestry, animal and fishery sectors. Summary document to Conference 7 (31 May to 5 July 2002) of the FAO Biotechnology Forum. (available at www.fao.org/biotech/logs/C7/summary.htm)
FSC. 1996, revised 2000. FSC Principles and criteria. Forest Stewardship Council Document 1.2, Principle 6.
Gartland, K.M.A., Kellison, R.C. & Fenning, T.M. 2002. Forest biotechnology and Europe’s forests of the future. Proceedings, Forest biotechnology in Europe: impending barriers, policy and implications, Edinburgh, UK.
Government of Canada. 1985, revised 2003. Seeds Act. c. S-8. (available at: http://laws.justice.gc.ca/en/S-8/98571.html)
Haines, R.J. 1994. Biotechnology in forest tree improvement: research directions and priorities. Forestry Paper No. 118. Rome.
Heron, D.S. & Kough, J.L. 2001. Regulation of transgenic plants in the United States. In S.H. Strauss & H.D. Bradshaw, eds. Proceedings, 1st International Symposium on Ecological and Societal Aspects of Transgenic Plantations, pp. 101–104. College of Forestry, Oregon State University, Corvallis, OR, USA.
Industry Canada – Life Sciences Branch. 2001. Biotechnology in the forestry sector. Natural Resources Canada (available at http://strategis.ic.gc.ca/bo01532e.html)
Johnson, B. & Kirby, K. 2001. Potential impacts of genetically modified trees on biodiversity of forestry plantations: a global perspective. In S.H. Strauss & H.D. Bradshaw, eds. Proceedings, 1st International Symposium on Ecological and Societal Aspects of Transgenic Plantations, pp. 176–186. College of Forestry, Oregon State University, Corvallis, OR, USA.
Krutovskii, K.V. & Neale, D.B. 2001. Forest genomics for conserving adaptive genetic diversity. Forest Genetics Working Paper FGR/3. Forest Resources Development Service, Forest Resources Division, FAO. Rome.
Libby, W.J. 1973. Domestication strategies for forest trees. Can. J. For. Res., 3: 265–276.
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Table 2.4.1. Current global applications and projected future importance and trends of forest tree biotechnology
Broad technologies |
Components1 |
Current applications2 |
||
A |
B | |||
Large databases |
3 |
1 |
||
Bioinformatics |
Targeted DNA sequence |
3 |
0 |
The storage, retrieval, analysis, and interpretation of large amounts of biological data will cross boundaries of all broad biotechnologies. Capability with and application range of this tool will continue to increase dramatically. Mining the massively increasing amounts of data at all scales, and integrated analyses and syntheses of these data will greatly increase power to detect genes and understand their functions. Bioinformatics research requires resource-intensive, multidisciplinary teamwork, naturally leading towards more international cooperation over a range of study scales and systems. Opportunities are opening up for developing countries and countries in transition. |
Proteomic |
2 |
0 | ||
Gene mapping & markers |
3 |
2 | ||
Microarray |
2 |
0 | ||
Phenotypic |
3 |
2 | ||
Integrated applications |
1 |
0 | ||
|
Diversity measurement |
mtDNA |
2 |
0 |
The use of molecular markers for studying natural and artificial forest tree populations has undergone unprecedented expansion due to the vast array of population genetics applications they have enabled. These topics include measurement of genetic diversity within and among populations, comparisons among taxa, historical reconstruction and prediction of species’ range shifts, gene flow, assessment of natural and artificial (e.g. seed orchard) population mating system parameters, introgression and hybridization. Markers have also been used to evaluate the impacts of domestication and silviculture. Genomic and QTL mapping have recently expanded owing to the development of unlimited numbers of markers. Anticipated development cost reductions for SNPs will trigger an increase in their use in all forest genetics resources applications. |
cpDNA |
2 |
0 | ||
RAPD, AFLP, RFLP |
3 |
2 | ||
Microsatellite (SSR, STS) |
1 |
0 | ||
SNP, ESTP |
3 |
1 | ||
Gene discovery |
Phenotypic traits |
3 |
3 |
Phenotypic and quantitative trait measurements represent the backbone of all conventional tree breeding. Their proven efficacy and ease of use has resulted in significant gains in many species worldwide. |
QTL mapping |
3 |
1 |
QTLs will likely increase in importance, particularly for important or hard to measure traits, especially those which require older material for assessments (e.g. all wood properties, disease and insect resistance). The focus is shifting from flanking region markers to markers within the actual gene or QTL of interest. | |
Genome & |
2 |
0 |
Massive, redundant conifer genomes will restrict sequencing to a few regions of interest. EST sequencing for commercially important species will accelerate within 5 years. Whole genome sequencing has begun for Populus; the data will be freely available; other economically and ecologically important species will follow. International collaboration is important for species whose ranges cross international borders. | |
Microarray analysis |
2 |
0 |
As microarrays become available for gene discovery for growth and yield, wood quality and adaptive attributes (e.g. disease and insect resistance and stress tolerance), more reliable oligo-based arrays will likely replace cheaper clone-based arrays. The potential benefits and challenges will spur international collaboration. This new field is likely to prove most cost-effective for understanding gene function, and for rapid production technology development for advanced breeding programmes and in high yield plantations. | |
Proteomic analysis |
2 |
0 |
Notes for microarray analysis also apply here. Proteomics aims to elucidate protein variation beyond simple transcriptional regulation, including levels of expression, interactions and post-translational modification. | |
Metabolomics |
1 |
0 |
Still in the initial stages, metabolomics assesses the presence/absence of non-protein structural precursors of essential components in biochemical pathways. | |
|
Molecular genetic modification |
Gene insertion/ |
2 |
1 |
Inserting foreign targeted genes into tree genomes has profound potential. This method will enable cross-species gene transfer in cases where it is not possible via conventional breeding. Transformation has engendered major public contention and strict biosecurity protocols for testing and deployment. Some countries and organizations have restricted testing and planting GM trees. Potential for gene escape into wild populations needs further study for risk assessment. Reproduction must be eliminated or postponed past rotation age. The technique could potentially improve fibre yield and quality as well as other important qualitative, quantitative and adaptive attributes. |
Gene targeting/ |
1 |
0 |
Silencing gene function is the complement of gene insertion. This technique will expand as the results of microarray and proteomic analyses accrue. Similarly, there is a broad spectrum of potential functional genomics applications and associated ethical issues. | |
|
Product verification |
Pedigree verification |
3 |
1 |
Development of larger-scale, lower-cost application platforms will increase accessibility by genetic improvement programmes to this technology, expanding the prevalent uses: retroactive pedigree verification and verifying clonal identies in seed orchards. Other potential applications include determining the efficacy of seed orchard management techniques on a large scale, and consequent growth and yield determination of resulting crops. |
Quality control/ Quality assurance |
1 |
0 |
Rapid developments in product description systems, commonly used in food manufacturing facilities, will result in increasing support for research and application of automated product verification systems. The main technology is PCR-based, e.g. DNA markers to detect mislabelled products (e.g. clones). Functional genomics is expected to yield suites of gene markers that can be used to check process efficiencies during mass production of clonal seedlings. | |
Cloning |
Organogenesis |
1 |
1 |
Micropropagation (organogenesis) and gametic or somatic embryogenesis require treating tissue explants with growth regulators to induce bud or shoot formation. Most of the shortcomings of organogenesis can be overcome using somatic embryogenesis, but methodology and success are species dependent. These methods are currently in production and cloning will be a significant element in high yield plantation forestry. |
Somatic embryogenesis |
1 |
0 | ||
Biosensing |
Simple biosensors |
1 |
0 |
Measuring and monitoring components of clonal production will increasingly employ sensors comprising physical, chemical and molecular markers to detect specific biological processes, e.g. expression-tagged genetic markers to quantify or detect presence/absence of metabolic pathway components of interest. |
1 AFLP: Amplified fragment length polymorphism; cpDNA: chloroplast DNA; mtDNA: mitochondrial DNA; EST: Expressed sequence tag; ESTP: Expressed sequence tag polymorphism; PCR: polymerase chain reaction; QTL: Quantitative trait locus; RAPD: Random amplified polymorphic DNA; RFLP: Restriction fragment length polymorphism; SNP: Single nucleotide polymorphism; SSR: Single sequence repeat; STS: Sequence-tagged site.
2A = developed countries; B = developing countries and countries in transition; on a scale of 0–3: 0 = nil, 3 = common.
Table 2.4.2. Anticipated contribution to and scale of impact of each broad area of biotechnology on elements of natural and artificial forest populations
Applicable forestry component |
Spatial scale |
Development elements relevant to biotechnology |
Broad technologies | ||||||
Cloning/ Regeneration | |||||||||
Bioinformatics |
Diversity measurement |
Gene discovery |
Genetic modification |
Simple biosensors |
Product verification | ||||
tree–population |
genetic resources characterization |
X |
X |
X |
|||||
population |
mating system/gene flow |
X |
|||||||
population–landscape |
conserving diversity |
X |
|||||||
population–landscape |
silvicultural impact assessment |
X |
|||||||
Breeding populations |
tree |
selection |
X |
X |
X |
||||
tree–population |
mating designs |
X |
X | ||||||
tree |
progeny testing |
X |
X |
X |
X |
X | |||
tree |
attribute assessments |
X |
X |
X |
X |
||||
population |
diversity management |
X |
X |
||||||
Production populations |
population |
mating system |
X |
X |
X | ||||
population |
gene flow/contamination |
X |
X |
X |
X | ||||
population |
seed orchard management |
X |
X |
X |
|||||
population |
seed orchard design |
X |
X |
X |
X | ||||
population–landscape |
silvicultural impact assessment |
X |
X |
X | |||||
Regeneration |
stand |
natural |
X |
X |
X |
X | |||
stand |
artificial |
X |
X |
X |
X |
X | |||
Domestication |
population |
native species diversity |
X |
X |
X |
X |
X |
||
population–landscape |
native species growth/yield |
X |
X |
X |
|||||
population |
exotic species risk assessment |
X |
X |
X |
X |
X |
|||
population–landscape |
exotic species growth/yield |
X |
X |
X |
|||||
Gene conservation |
population |
diversity assessment |
X |
X |
|||||
population |
gene flow/contamination |
X |
X |
X | |||||
population |
effective population size |
X |
|||||||
tree |
reproduction |
X |
X |
X |
X | ||||
Forest health |
tree–stand |
risk/hazard assessment |
X |
X |
X |
||||
tree |
resistance screening |
X |
X |
X |
X |
X |
X | ||
stand |
IPM options |
X |
X |
||||||
tree–landscape |
other pest control |
X |
X |
X |
X |
X | |||
Processing/ |
stand |
pulp processing |
X |
X |
X |
X |
X |
||
stand |
wood treatment |
X |
X |
X |
X |
X |
|||
Marketing |
tree |
chain of custody |
X |
X |
X |
||||
stand–landscape |
certification |
X |
X |
X |
X |
X | |||
stand |
product description |
X |
X |
X |
X |
||||
39 See: www.fao.org/biotech/inventory_admin/dep/default.asp.
