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© Bernd Degen
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Institute of

FG Forest Genetics

Project

Genetic Inventories BWI



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© Thünen-Institut/WO
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Genetic inventories as part of the German National Forest Inventory 2021-2022

The German National Forest Inventory studies how much forest there is in Germany, how it looks like, and how it changes. Genetic analyses will help us in answering these questions in more detail in the future.

Background and Objective

So far, site-representative samples of the major tree species covering the area of the Federal Republic of Germany for use in genetic analyses are not available. For this reason, systematic DNA-sampling of European beech, sessile and pedunculate oak, Scots pine, Norway spruce, silver fir, and Douglas fir will be implemented in the next BWI. The goal is to obtain and archive a DNA sample representing the genetic composition of these seven forest tree species within the boundaries of the Federal Republic of Germany and to make it available to all federal states to be used in genetic analyses.

The samples will be used in genetic analyses and surveys. Due to recent advances in Next-Generation-Sequencing technologies, several methods are now available to study the following aspects:

    1. Genetic diversity (spatial distribution, genetic differentiation, identification of candidate stands for gene-conservation characterized by high genetic diversity or unique genetic composition)
    2. Local adaptation
      • Origin and provenience of current stands
      • Information on extent and routes of human transfer of seeds
      • Predisposition against drought stress, selected pest insects, and fungi
    3. Revision of the classification of provenience areas regarding forest reproductive material

Approach

Over all seven tree species, a total of 20,000 DNA-samples will be collected at selected inventory tracts. The selection of sampling-tracts is based on National Forest Inventory data on the distribution of the selected tree species. At each sampling-tract, DNA-samples will be taken from five individuals of each target species occurring at this tract. This procedure will yield a total of 1,000 to 5,000 DNA-samples per target species. The sample size reflects the proportional frequency of occurrence of each species. A minimum of 1,000 samples constitutes the lowermost sample-size needed to generate representative conclusions.


DNA can best be extracted from leaves, needles, or buds. Samples will be taken from adult trees or seedlings and dried on silica gel. A storage center will be equipped for long-term storage of DNA and backup samples. A specialized database to facilitate standardized registration and labelling of samples is already in use and can be extended as needed. Once archived, the material will be made available for subsequent analyses to a wide group of users, in particular the forest research organizations of the federal states. The long-term storage ensures that subsequent genetic analyses of the samples will be possible for several decades.


Molecular methods develop rapidly at the moment. This is especially true for DNA-sequencing using “Next-Generation-Sequencing” techniques and the identification of genes and their functions. Depending of the specific research question, the samples can be analyzed using a multitude of molecular methods. One of these are so-called DNA-chips. These can be used very efficiently to identify matches between a sample and several thousand DNA target-sequences. Target-sequences that show intraspecific variation (e.g. SNPs, InDels) can be used to identify genes of adaptive or economic importance. Neutral variation in target-sequences can be used to analyze genetic diversity, geographic differentiation, or to identify closely related species. Currently such DNA-chips are available for European oaks and pines as well as different American conifer species. It is likely that DNA-chips will become available for additional economically and ecologically important tree species in the near future. Using this method, genotyping follows three steps: DNA-extraction, genotyping, and data evaluation. All of these can be performed by multiple partners.

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