To test our hypotheses, we

will sample 20 trees of each

species of interest in the

radiation exposed zone

(exclusion zone) in blue to

trees outside of the radiation

exposed zone (green). 

 

We are choosing 3 species, all of which are found throughout Japan.  These include:

Spruce

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Ginkgo

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Beech

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First, we will look for an increase in the number of mutations for trees that have been exposed. Mutations come in many forms, including Single Nucleotide Polymorphisms (SNPs). The SNP listed below is called a Missense mutation, because it changed the amino acid that was coded for from the original sequence.

Example 1.  If our original sequence starts like this:

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-----C A T C A T C A T C A T C A T C A T C A T C A T ------

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And gets changed to this:

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-----C A T C A T C A A C A T C A T C A T C A T C A T ------

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It is called a SNP, or Single Nucleotide Polymorphism.

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Example 2. We will also look for chromosomal inversions that start with this:

 

-----C A T C A T C A T C A T C A T C A T C A T C A T ------

 

That get changed to this:

 

----C A T C A T T A C T A C C A T C A T C A T C A T ------

 

Example 3. We will also look for chromosomal duplications that start out like this:

 

------C A T C A T C A T C A T C A T C A T C A T C A T ------

 

That get changed to this:

 

------C A T CCC A T C A T C A T C A T C A T C A T C A T ------

 

Initially we will be looking for and counting the new mutations, and using that data to infer mutation rates when compared to trees outside of the exclusion zone. Historically, an increased mutation rate has been shown in many radiation studies for exposed plants as well as animals (Tobias and Silverman, 2023).

 

We also plan to translate these mutations to the amino acid level (shown above in example 1) as well as potential adaptive genetic changes that may allow the trees to survive the harsh conditions of this radiation. Such adaptive genetic changes have been shown to happen to plants in other stressful conditions, and will likely be detected in our samples as well.

 

Because we do not know exactly where these changes will happen in the genome, we plan to use what is called next generation sequencing, whereby we sequence the entire genome for our samples.  Using this method, the genomic DNA from each sample is first cut into pieces using restriction enzymes.  Then, these samples are sorted by size, and then have what is known as an adapter added to them.  Once the adapter has been added, samples are amplified (copied) and the resulting DNA code (the order of As, Cs, Gs, and Ts) is recorded and ready for comparison. 

 

 

 

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Image courtesy of Illumina technology.

This will allow us to detect any changes throughout the genomes, anything from SNPs (single nucleotide polymorphisms) to inversions (flipped parts of the chromosomes) to insertions and deletions.

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Once we quantify and document the number and type of mutations we detect through this revolutionary sequencing technology in our sampled trees, we will determine how much this differs from trees sampled outside of the exposed regions (our control trees).  Once we determine how many and what type differ from our control trees and plot this data against the reported released radiation doses, we can calibrate our number of mutations with quantified radiation and create a calibration curve for anyone to use.

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Once we create our curve, we then plan to translate the proteins that are coded for by these genes (known as the proteome) and see if we can detect any that may help the trees survive such extreme increases in radiation (NIH 2023).

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Protein analysis includes translating the detect sequences to determine what proteins are encoded for.   This can then be compared to known data on protein function and can allow us to infer if these new mutations code for proteins that help the trees survive the radiation exposure.

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C.A. Tobias, and J. Silverman.  2023.  Damage to genes (mutations). Encyclopedia Britannica.  Retrieved from: https://www.britannica.com/science/radiation/Damage-to-genes-mutations. 

Illumina.  2023.  Retrieved from https://www.illumina.com/science/technology/next-generation-sequencing.html

National Institute of Health (NIH).  2023.  Retrieved from https://www.ncbi.nlm.nih.gov/protein/

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