A fundamental aspect of evolutionary biology is natural
selection on trait variation. Classically, selection has been estimated
primarily on external morphological traits such as beak size and
coloration, or on easily-assayable physiological traits such as
heat-tolerance. As technologies and methods improved, evolutionary
biologists began examining selection on molecular traits such as protein
sequences and cellular processes. In a From the Cover manuscript in this
issue of Molecular Ecology, Ahmad et al. (2021) continue this
trend by estimating parasite driven selection on the molecular trait of
transcript abundance in a wild population of brown trout (Salmo
trutta) by uniquely combining a mark-recapture experimental design with
non-invasive RNA sampling. Using transcript abundance to estimate
selection allows for many different traits (each unique gene’s
transcript counts) to be tested in a single experiment, providing the
opportunity to examine trends in selection. Ahmad et al.(2021)
find directional selection strength on transcript counts is generally
low and normally distributed. Surprisingly, transcripts under non-linear
selection showed a disruptive selection bias contradicting previous
comparative studies and theoretical work. This highlights the importance
of within-generation selection studies, where mechanisms may differ from
longer time frames. Their manuscript also highlights the benefits of an
improved 3’ RNA sequencing technique to measure gene expression.
For their study Ahmad et al. (2021), perform a
mark-recapture study on a brown trout population that has a high
prevalence of the parasite Tetracapsuloides bryosalmonae which
causes the temperature-dependent proliferative kidney disease (PKD) in
salmonid fishes. PKD is an economically and ecologically important
disease which causes significant mortality in salmonid species when
water temperatures reach over 15°C (Hedrick, MacConnell, & de Kinkelin,
1993). The mark-recapture experiment was performed by capturing and
clipping the pelvic fin of 278 wild young-of-the-year fish, releasing
them back into their native stream, followed by an extensive effort to
recapture nearly all (150) survivors one month later (Figure 1). By
timing the initial sampling to shortly follow mass T bryosalmonaespore release, the authors aimed to capture the transcriptomic response
of individuals to infection, with mortality during the one month period
between samplings thought to be primarily due to PKD infection.
Estimating selection on transcript abundance in a wild environment is a
departure from previous studies on evolution of gene regulation which
have used comparative approaches on divergent taxa. Highlighting the
complementarity of these approaches, Ahmad et al . (2021), show an
agreement with previous estimates of selection in finding that
directional selection strength on transcript counts is quite weak and
normally distributed(Groen et al., 2020; Siepielski, Dibattista, &
Carlson, 2009). However, previous comparative work and theory suggests
selection on gene expression regulation is primarily through stabilizing
selection, while Ahmad et al . (2021) show that in their
experiment the most common and strongest form of non-linear selection on
transcript abundance was disruptive selection (reviewed by Bedford &
Hartl, 2009; Gilad et al ., 2006). The implications of this
deviation from previous work will require further investigation to
understand. One explanation is that the disruptive selection bias may be
common for within generation selection in response to disease state,
while long term adaptation to a specific environment may more frequently
act through stabilizing selection on gene regulation. Specifically,
Ahmad et al . (2021) propose optimal strategies for PKD tolerance
in brown trout may be either large and energetically-expensive responses
that lead to successful suppression of T bryosalmonae , or the
conservation of energy but allowing disease-associated damage, with
intermediate responses incurring costs without substantial benefits.
An interesting approach used in the study was to sample fin tissue for
RNA isolation; the small fin biopsy should not significantly affect fish
survival. This differs from the common approach to focus on gene
expression in tissues of interest (i.e. kidney/liver in immune studies)
which typically requires lethal sampling. Measurement of gene expression
from fin tissue may fail to capture interesting gene expression changes
in immune organs in response to infection but allows a fundamentally new
experimental design. Consistent with this, none of the gene expression
networks that predicted survival were related to immune function. This
should not be seen as a limitation, but rather a strength of their
approach. Being able to non-lethally sample for RNA allows for selection
on transcript abundance to be directly measured by survival and may shed
light on new processes important to survival in the wild. To highlight
this, a key gene expression network associated with parasite load and
negatively correlated to survival identified from this work involved
upregulation of many cell cycle genes, which the authors argue were
associated with response to T. bryosalmonae infection and were
not part of a generalized stress response, as stress is associated with
downregulation of cell cycle processes(Burgess, Rasouli, & Rogers,
2014). While many RNA-seq studies have wide ranging implications their
ecological importance is often unclear. For example a family of genes
may be upregulated in response to some environmental change, but how
this effects survival or reproduction is typically not measured. The
experimental design exemplified by Ahmad et al . (2021) reveals
new insight into PKD disease pathology and highlights how to perform an
RNA-seq experiment in an ecologically relevant context.
Advances in sequencing technologies and techniques has led to a rise in
gene expression studies in ecology, with the sequencing of mRNA
(RNA-seq) becoming the most popular method for measuring gene
expression. Traditional RNA-seq sequences entire mRNA transcripts, which
gives splice variant information. However for most ecological
applications, researchers are interested primarily in the amount of each
gene being transcribed, and not concerned about splice variants.
Obtaining full mRNA sequences thus represents wasted sequencing effort.
A newly developed method termed TagSeq focuses only on the 3’ end of
transcripts, which in combination with a reference genome, is
sufficiently informative to identify individual genes, thus increasing
the number of individuals that can be reliably sequenced although at the
cost of losing splice information(Meyer, Aglyamova, & Matz, 2011).
Briefly, this method involves isolating total RNA, fragmentation, and
cDNA synthesis with a poly-dT oligo to focus primarily on the 3’ end of
transcripts. This protocol has been demonstrated to be more accurate and
replicable than traditional NEBNext® RNA libraries (Lohman, Weber, &
Bolnick, 2016). The reduced costs and increased sampling allowed by
TagSeq represent a step forward for ecologists who are interested in
gene expression quantification, and Ahmad et al. (2021) implement
an optimized and commercially available version of TagSeq library
preparation to measure transcript counts (Moll, Ante, Seitz, & Reda,
2014).
Overall, using improved RNA-seq methods to estimate within generation
selection on transcript abundance in the wild demonstrates progress made
in molecular ecology and the power of non-invasive sampling. The ability
to cheaply and reliably measure transcript abundance in a large number
of individuals should encourage more researchers to use transcript
abundance as a measurable trait. Opening this avenue should lead to new
insights on how natural selection pressure acts on gene expression
regulation.
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