pika genetics and adaptation

•  The American pika (Fig. 2; Ochotona princeps) is a smalllagomorphthatinhabitstalusslopesandrockyhabitatsthroughoutmountainousregionsofwesternNorthAmerica.•  In the northern most part of their range, the central CoastMountains of BC (Fig. 1), pikas are present along altitudinalgradientsrangingfromsealeveltoabove1500m,makingthemanidealsystemtoinvestigatethegeneticbasisoflocaladaptationtochangingenvironmentalconditions.

Investigating the genetic basis of local adaptation in American pika using genomic scans

Philippe Henry and Michael A. Russello Department of Biology and Centre for Species at Risk and Habitat Studies (SARAHS), University of British Columbia Okanagan, Kelowna, BC, Canada.

Correspondence: phenry@interchange.ubc.ca Results Context

Objective

Discussion

References

•  Alpine species are starting to show responses to globalenvironmental changes. One obvious example is the upslopemovementofspeciesastheyseektoretaintheiroptimalniches.•  Besides the ability to migrate, species with special habitatrequirements maybeconstrainedto stay put. Thesespecies willhavetorespondtotheenvironmentalchangesbyadaptingtothechangingconditions.•  Theirresponsestoenvironmentalchangeswilllargelydependonthe underlying adaptive genetics variability present in itspopulations.•  Todatethetaskofidentifyinggenomicregionsunderselectionfromenvironmentalchangeshasbeenadifficultone,mostlyowingtothelackofgeneticmarkersfornaturalpopulations.•  Technicaladvancesthathaveleadtotheidentificationofalargenumberofgeneticmarkersalongwithstatisticaldevelopmentshaveallowedresearcherstoteaseapart adaptivefromneutral geneticvariation by comparing levels of genetic differentiation betweenloci,whereoutlierlociwithhighdifferentiationareinterpretedasbeensubjecttonaturalselection.

Study Species

•  The advent of molecular markers such as AFLP have enabledresearchertostudytheadaptivegeneticvariationinwild,non‐modelspecies.• Inthepresentstudyweshowthatasmallfractionoflocifoundinpikas are potentially under natural selection, while most loci areselectivelyneutral.• Theselociwereonlypresentinsamplesfromhigh(A,C,E)andlow(B,D)elevationsbutabsentfromthemidelevationsite.• Thispointsuggeststhattheoutlierlociareresponsibleforthelocaladaptationtoenvironmentalconditionsthatvarywithaltitude.Yetitis importanttobear inmindthattheseresults arepreliminaryastheywereobtainedfromonly32samples.• Besidesall advantagesofusingAFLPs, onedrawbackis thatthistypeofmarkersareanonymousandthusitisdifficulttopinpointthegenesorgenomicregionsunderselection.• Othercomplementaryapproaches(SAM)canalsobeusedtoshedlightontheassociationbetweenlociandeco‐climaticvariables.• Thislatterapproachwillbeimplementedinthefutureonalargerdataset, andwill hopefully identifythemaindriverof selection inAmericanpikasfromtheBellaCoolavalley.

Figure2:AnAmericanpikaemergingfromtherocksintheBellaCoolavalley,BritishColumbia(PhilippeHenryPhoto)

Methods

Figure 1: Map of thelocationofthestudysite:the Bella Coola Valley,BritishColumbia,Canada.This site is of particularinterest since pikas aredistributed along ana l t i tud ina l grad ientranging fromthebottomofthevalleyat300m,upto1500moververyshortgeographical distances.The highway descendingfromtheChilcotinplateauintotheBellaCoolavalleyoffers ideal access topopulations at differentaltitudes.

• Use a genomic scanapproach to identify candidate loci undernaturalselectionthatmayberesponsibleforlocaladaptationintheAmericanpika.

A.Samples• Pika populations were sampled from five populations at threedifferent elevations: 300m (N=3), 800m (N=1) and 1500m (N=1)abovesealevelintheBellaCoolaValley,BritishColumbia,Canada.• Non‐invasivesnares1wereusedtocollecthairfrom32individuals.B.Labwork• DNA was extracted from25 hairs using the Promega DNA IQsystem.•  A genomic scan was undertaken using AFLPs. The protocolincludeddigestionof50ngofDNAwithEcoRIandTaqIfollowedbyligation of adapters, pre‐selective amplification and selectiveamplificationwithatotalof64primercombinations2.• 44primercombinationsproducedbandsthatwererunontoanABI3130XLgenotyperandvisualizedusingGenemapper3.7.C.Analyzes• ThesoftwarescanAFLP3wasusedtoselectthemostrepeatableandinformativeprimercombinations.15primercombinationswithhighsignaltonoiseratiosandlowerrorrateswerethusretained.Furthermore,lociwithlessthan5%andmorethan95%presencewereremovedfromthedataset.•  The program Bayescan4 which uses a Bayesian approach todirectlycalculatetheprobabilityofbeenunderselectionforeachlocuswasusedtodetectcandidatelocipotentially undernaturalselection.

Figure 3: Bayescananalysis graphic with,on the x‐axis, theposteriorprobabilityfora locus to be undernatural selection. Thevertical line indicatesthe threshold beyondwhich there is strongevidence for selectiontoact.5outof1238locishow strong evidenceforselection:A‐E32T35_115,B–E43T44_123,C–E43T35_83,D–E31T37_96,E–E43T35_73.

1.  Henry&Russello(Submitted)2.  Boninetal.,20053.  Herrmannetal.,20104.  Foll&Gagiotti,2008

AcknowledgementsWewouldliketothankthemembersoftheECGLforhelp

inthefieldandlab,KurtGalbreathandMaryPeacockfor kindly providing samples. Sarka Jahodova isthanked for providing guidance with AFLP.

•  A total of 1238 loci were obtained with 15 selective primercombinationsthatprovedtobeinformativeandrepeatable.• Bayescananalysisdetectedthat5ofthe1238loci(0.4%)showedstrong evidence for natural selection in our populations sampledalonganaltitudinalgradient(Fig.3).

Funding