Candidate genes for stress response in silver fir (Abies alba Mill.)
The aim of this thesis was the identification and analysis of candidate genes for stress response in silver fir (Abies alba Mill.). This ecologically and economically important forest tree species is native to many mountainous regions of Europe but little is known about its ecological characterist...
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|Summary:||The aim of this thesis was the identification and analysis of candidate genes for stress response in
silver fir (Abies alba Mill.). This ecologically and economically important forest tree species is native
to many mountainous regions of Europe but little is known about its ecological characteristics.
Silver fir populations were heavily transformed by human activity, which results in a mismatch
between past and current distribution. Recent studies suggest that silver fir can occupy warmer
and dryer climates than it currently does. However, the species also suffered considerably during
the 1970s and 1980s, including foliar damage, radial growth depression and local diebacks in
Germany. This is attributed mainly to the peak in air pollution during this period, especially sulfur
dioxide (SO2), which seems to heavily increase drought sensitivity in silver fir. The combination of
both stressors, SO2 and drought events, negatively affected silver fir even in regions where drought
is usually not a problem.
In the context of anthropogenic global climate change that will very likely lead to an increase
in temperature in Europe and to more extreme events such as severe drought periods, the question
arises, how silver fir will cope with these environmental changes. Given the speed of the predicted
changes and the increasing landscape fragmentation, silver fir might not be able to evade it via
seed dispersal. As a sessile organism, the only other option is adaptation, which will likely draw
from standing genetic variation.
To successfully predict the fate of silver fir, especially in the face of global climate change, and
to potentially manage populations based on such predictions, the genetic architecture of silver fir
in the context of such important stressors as drought and air pollution has to be understood. There
exist, however, little genomic resources for silver fir and conifers in general. This is due to their
large and complex genomes and the long generational cycle, which makes conifers typical nonmodel
species. As such, methods for the identification of the genetic basis of stress response are
effectively limited to a candidate gene approach.
The candidate gene approach includes the identification of functional candidate genes by measuring
differential gene expression between a stressed and a control group. In the context of this
thesis, the water content of silver fir seedlings was monitored in a laboratory using a novel terahertz
spectroscopy setup. One group of seedlings was regularly irrigated while the other group
was drought stressed. Continually measuring the water content allowed to harvest needles from
both groups at a time when the water status was comparable between the individuals within each
group. A differential expression analysis between the needles from both groups then revealed 296
genes that were significantly up- or down-regulated in response to drought stress. Of those genes,
approximately 45% have not been previously described in any organism and are potentially unique
to silver fir or conifers in general. However, since only needles of seedlings were analyzed at a
specific level of drought stress, the results are limited in scope to the source material and stress intensity
and cannot be directly applied to silver fir or drought stress in general. Also, this approach
implies a cause-effect relationship between gene expression and a specific level of drought stress.
Thus, it is very important that confounding factors are excluded from the experiment. Chlorophyll
content in the needles, for example, might change over the course of the monitoring period due to
the drought treatment. To test if the chlorophyll content could potentially influence the terahertz
signal, chlorophyll was extracted from silver fir needles, in the course of this thesis, and different concentrations were measured using terahertz spectroscopy, showing that chlorophyll content does
not influence terahertz monitoring.
Another aspect of the candidate gene approach involves the variation within a polymorphic
gene and its potential association with the variation in a phenotypic trait. Since the growth depression
period of silver fir in the 1970s and 1980s was mostly influenced by the combination
of air pollution and drought, in the context of this thesis, genetic variation, in the form of single
nucleotide polymorphims (SNPs) in pre-selected genes, was associated with tree-ring derived
phenotypes for individual trees in the Bavarian Forest National Park. These so called ’dendrophenotypes’
were measures for resistance, resilience and recovery during the depression period, as well
as the drought year 1976. Using general linear models and feature selection techniques based on
the machine learning algorithm random forest, 15 out of 103 polymorphic candidate genes for trait
variation could be identified. Since the associated dendrophenotyes are potentially adaptively relevant,
the variation in this candidate genes could influence the stress coping capability of individual
trees. However, this approach is of an observational nature and thus, cause-effect relationships
cannot be derived from this type of experiment. The identified SNPs might be the causal variant or
physically close to the true causal variant or it might just be a spurious correlation. Further, reliance
on advanced statistical techniques can be troublesome, as could be demonstrated in the course of
this thesis for a random forest based feature selection technique, developed for genetic association
studies in conifers. Replicating this study and evaluating the algorithm, non-uniqueness of the
results could be demonstrated, which not only hinders biological interpretation but can severely
negatively influence downstream analyses, such as tests for interaction between SNPs.
In conclusion, this thesis presents new techniques to add to the current methodology for candidate
gene selection and analysis in the stress response of the non-model organism silver fir and
other conifer species. Both approaches should be combined, for example by drawing polymorphic
candidate genes for trait variation from the pool of functional candidate genes to ensure the involvement
of the studied genes in the variation of the trait of interest. Further, the results of this
thesis add to the growing molecular resources in silver fir and thereby, hopefully, contribute to the
successful prediction and management of this important forest tree species in the face of rapidly
changing environmental conditions.|
|Physical Description:||115 Pages|