This document summarizes a study investigating genetic adaptation in American pika populations along elevation gradients in British Columbia, Canada in the context of climate change. The study used population genomics techniques including AFLP to screen 1509 loci for signatures of selection. They identified 23 loci (1.5%) under selection across populations. Six of these loci were significantly associated with environmental variables like precipitation and temperature, suggesting they may confer adaptive advantages under changing climatic conditions. The results provide insight into the genetic basis of local adaptation in this climate sensitive species.

1. • The American pika (Fig. 2; Ochotona princeps) is a small
lagomorph that inhabits talus slopes and rocky habitats
throughout mountainous regions of western North America.
They are a climate-change sensitive species that displays
limited dispersal.1
• In the northern most part of their range, the central Coast
Mountains of BC (Fig. 1), pikas are present along altitudinal
gradients ranging from sea level to above 1500m, making
them an ideal system to investigate the genetic basis of local
adaptation to changing environmental conditions.
Adapting to climate change: using genomic scans to detect
signatures of selection in American pika populations
Philippe Henry and Michael A. Russello
Department of Biology, University of British Columbia, Okanagan campus, Kelowna, British Columbia, Canada.
Correspondence: phenry@alumni.ubc.ca
ResultsContext
Objective
Discussion
References
•Alpine species are starting to show responses to global
environmental changes. One obvious example is the upslope
movement of species as they seek to retain their optimal
niches.
•Besides the ability to migrate, species with special habitat
requirements may be constrained to stay put. These species
will have to respond to the environmental changes by adapting
to the changing conditions.
•The development of population genomics has enabled the
investigation of the genetic basis of adaptation in natural
populations of non-model organisms. By screening large
numbers of loci distributed throughout the genome,
researchers are able to tease apart neutral (genome-wide) and
adaptive (locus-specific or “outlier”) effects
Study System
• We have previously shown that pika populations in our study
area display restricted gene flow along elevation transects1
,
suggesting that pikas may have to rely on local adaptation to
persist in a warmer world.
• Here we identify a small fraction of loci that are potentially
under natural selection, and may confer adaptive advantages to
local environmental conditions.
• Outlier loci that were also correlated with environmental
variables may be good candidate markers to assess the
evolutionary potential of the species in the face of climate
change.
• Besides all advantages of using AFLPs, one drawback is that
this type of markers are anonymous and thus it is difficult to
pinpoint the genes or genomic regions under selection.
• Current efforts are directed towards SNP identification and
screening in order to uncover the functional basis of adaptation
in this climate change sensitive mammal.
Methods
Figure 1: Map of the location of the study site: the Bella Coola Valley, British Columbia, Canada
• We used population and landscape genomics to investigate
the genetic basis of adaptation in populations of O. princeps
found along three elevation gradients in the central Coast
Mountains of BC, Canada, ranging from sea level to 1500 m.
• 168 Pikas were sampled from ten populations along three
elevation gradients using non-invasive hair snares2,3
.
• DNA was extracted from 25 hairs using the Promega DNA IQ
system.
• An AFLP genomic scan was used to screen for loci under
selection. The protocol included digestion of 50ng of DNA with
EcoRI and TaqI followed by ligation of adapters, pre-selective
amplification and selective amplification with 20 primer
combinations.
• ScanAFLP3
was used to select the most repeatable and
informative AFLP fragments. Furthermore, loci with less than
5% and more than 95% presence were removed from the
dataset.
• We used a combination of softwares including Bayescan4
,
Mcheza5
, Arlequin6
to evaluate the probability of each locus
being under positive selection. Candidate loci were designated
only if they were identified by at least two independent
methods.
• Additionally we used SAM7
and logistic regression to identify
the main drivers of natural selection in this system.
Figure 3: Graphical representation of outlier loci (red area) for the entire study area. Black circles
indicate loci that are significantly associated with Mean Annual Precipitation.
1. Henry et al. 2012 (PLoS One) 5. Antao & Beaumont 2011 (Bioinformatics)
2. Henry et al., 2011 (JoVE) 6. Excoffier et al. 2009 (Heredity)
3. Henry & Russello 2011 (EJWR) 7. Joost et al. 2008 (MER)
4. Foll & Gagiotti, 2008 (Genetics)
Acknowledgements
We would like to thank the UBCO students that provided
assistance in the field and lab. Kurt Galbreath and
Mary Peacock for kindly providing samples.
• A total of 1509 informative and repeatable loci were retained
for analyzes.
• Our combination of approaches identified that 23 of the 1509
loci (1.5%) showed strong evidence for natural selection in our
populations sampled along three altitudinal gradients (Fig. 3).
• Additionally, six loci displayed significant associations with
environmental variables such as mean annual precipitation and
maximum summer temperatures.
Funding
Figure 2: An American pika emerging from the rocks in the Bella Coola valley, British Columbia
(Philippe Henry Photo)