In my
classes that I teach at Pace University, the theme of parallel and convergent
evolution is a recurrent topic. For example, we’ve discussed parallel evolution
of lactase persistence in human populations from northern Europe and parts of
Africa, and convergent evolution of the camera eye in vertebrates and
cephalopods. Stickleback fish are a classic textbook case of parallel
evolution, adapting repeatedly to freshwaters from marine ancestors, diverging
into benthic and limnetic forms along similar lines in multiple lakes, and
adapting along similar trajectories in lake and stream habitats throughout much
of the northern hemisphere.
I first
began thinking about parallel evolution as a master’s student at McGill when I
was practicing analyzing microsatellite data. A question came to my naïve graduate
student mind: Couldn’t we compare microsatellite and morphological data among
populations to determine the proportion of within-population variation that is
due to constraints versus adaptive evolution? I expected that a high level of
“exchangeability” of neutral genetic markers would reveal a higher level of
morphological “exchangeability” between lake and stream populations from the
same watershed (due to gene flow or shared ancestry), whereas genetic (microsatellite)
distinctiveness would result in morphological traits in lake habitats that are
more similar to fish in other lake habitats than in the stream habitats (and
vice versa) due to adaptation. I proposed that we could use classification
techniques to directly compare genetic markers and morphological traits.
Years
later, my ideas have culminated in a study on stickleback from parapatric lake
and stream habitats from each of six watersheds on Vancouver Island. We used
discriminant analysis to classify individuals to populations for each of
several measures, including diet ecology (stomach contents and stable
isotopes), trophic morphology (body shape, and gill raker number and length),
armor traits (plates and spines), and microsatellites (6 neutral loci, and 6
loci linked to QTL). This approach differed from traditional analyses that
compare means among populations in that “misclassified” individuals could
inform us as to which populations were more “exchangeable”; that is, it could
tell us whether a lake fish would be a better fit into another lake population
than into any stream population, based on any of the traits or loci (and vice
versa for the stream fish).
We found
that populations within watersheds were most exchangeable with respect to
genetic markers, which would make sense if gene flow occurred between lake and
stream habitats. This was less likely to be the case with diet and body shape,
however, for which fish were more likely to be classified into a similar habitat in a different watershed than into a
different habitat. Why are these results important? In addition to shedding
light on the deterministic nature of habitats in shaping parallel patterns of
evolution, these results might provide insight to conservation managers
planning to relocate individuals to new environments, for example when the
native range is under threat or to enhance genetic variation in a bottlenecked
population.
Reference:
Hendry AP,
Kaeuffer R, Crispo E, Peichel CL, Bolnick DI. In press. Evolutionary inferences
from the analysis of exchangeability. Evolution.
DOI: 10.1111/evo.12160
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