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Article Genetic Ancestry and Natural Selection Drive Population Differences in Immune Responses to Pathogens Graphical Abstract Authors YohannNe´de´lec,Joaquı´nSanz, GolshidBaharian,...,JennyTung, VaniaYotova,LuisB.Barreiro Correspondence [email protected] In Brief Differencesinthetranscriptional responsetoinfectioninhuman populationsareunderstronggenetic influence,dictatedbytheirancestryand byrecentnaturalselectionevents. Highlights Data Resources d Thousandsofgenesshowpopulationdifferencesin GSE81046 transcriptionalresponsetoinfection d Africanancestryisassociatedwithastrongerinflammatory response d Populationdifferencesinimmuneresponseareoften geneticallycontrolled d Naturalselectioncontributedtoancestry-associated differencesingeneregulation Ne´de´lecetal.,2016,Cell167,657–669 October20,2016ª2016ElsevierInc. http://dx.doi.org/10.1016/j.cell.2016.09.025 Article Genetic Ancestry and Natural Selection Drive Population Differences in Immune Responses to Pathogens YohannNe´de´lec,1,2,11Joaquı´nSanz,1,2,11GolshidBaharian,1,2,11ZacharyA.Szpiech,3AlainPacis,1,2AnneDumaine,2 Jean-ChristopheGrenier,2AndrewFreiman,4AaronJ.Sams,5StevenHebert,2ArianePage´ Sabourin,2FrancescaLuca,4,6 RanBlekhman,7RyanD.Hernandez,3,8RogerPique-Regi,4,6JennyTung,9VaniaYotova,2andLuisB.Barreiro2,10,12,* 1DepartmentofBiochemistry,FacultyofMedicine,Universite´ deMontre´al,Montreal,QCH3T1J4,Canada 2DepartmentofGenetics,CHUSainte-JustineResearchCenter,Montreal,QCH3T1C5,Canada 3DepartmentofBioengineeringandTherapeuticSciences,UniversityofCalifornia,SanFrancisco,SanFrancisco,CA94143,USA 4DepartmentofObstetricsandGynecology,WayneStateUniversity,Detroit,MI48202,USA 5DepartmentofBiologicalStatistics&ComputationalBiology,CornellUniversity,Ithaca,NY14850,USA 6CenterforMolecularMedicineandGenetics,WayneStateUniversity,Detroit,MI48202,USA 7DepartmentofGenetics,CellBiology,andDevelopmentandDepartmentofEcology,UniversityofMinnesota,TwinCities,MN55108,USA 8InstituteforHumanGeneticsandQuantitativeBiosciencesInstitute,UniversityofCalifornia,SanFrancisco,SanFrancisco,CA94143,USA 9DepartmentsofEvolutionaryAnthropologyandBiologyandDukePopulationResearchInstitute,DukeUniversity,Durham,NC27708,USA 10DepartmentofPediatrics,FacultyofMedicine,Universite´ deMontre´al,Montreal,QCH3T1J4,Canada 11Co-firstauthor 12LeadContact *Correspondence:[email protected] http://dx.doi.org/10.1016/j.cell.2016.09.025 SUMMARY frompathogens(BarreiroandQuintana-Murci,2010;Fumagalli et al., 2011; Karlsson et al., 2014). When human populations Individualsfromdifferentpopulationsvaryconsider- migrated out of Africa, they encountered markedly different ably in their susceptibility to immune-related dis- pathogenicenvironments,likelyresultinginpopulation-specific eases.Tounderstandhowgeneticvariationandnat- selectionontheimmuneresponse(BarreiroandQuintana-Murci, ural selection contribute to these differences, we 2010;Fumagallietal.,2011;Karlssonetal.,2014).Substantial tested for the effects of African versus European evidencesupportsthishypothesisatthegeneticlevel.However, westillknowlittleabouttheextenttowhichneutraloradaptive ancestry on the transcriptional response of primary inter-population genetic differences affect the actual immune macrophages to live bacterial pathogens. A total responsetopathogens. of 9.3% of macrophage-expressed genes show Addressingthisgapisnotonlyimportantforunderstanding ancestry-associated differences in the gene regula- recenthumanevolution,butmayalsohelprevealthemolecu- toryresponsetoinfection,andAfricanancestryspe- larbasisofancestry-relateddifferencesindiseasesusceptibil- cifically predicts a stronger inflammatory response ity. Individuals from different populations vary considerably in and reduced intracellular bacterial growth. A large their susceptibility to many infectious diseases, chronic in- proportion of these differences are under genetic flammatory disorders, and autoimmune disorders. For tuber- control:for804genes,morethan75%ofancestryef- culosis, systemic lupus erythematosus, systemic sclerosis, fectsontheimmuneresponsecanbeexplainedbya psoriasis, and septicemia, African American (AA) and Euro- single cis- or trans-acting expression quantitative pean American (EA) individuals exhibit an up to 3-fold differ- ence in prevalence (reviewed in Brinkworth and Barreiro, trait locus (eQTL). Finally, we show that genetic ef- 2014; Pennington et al., 2009; Richardus and Kunst, 2001). fectsontheimmuneresponsearestronglyenriched These observations argue in favor of significant ancestry- for recent, population-specific signatures of adap- relateddifferencesinimmuneresponse,especiallyinsuscep- tation. Together, our results demonstrate how his- tibilitytoinflammation(Penningtonetal.,2009;Richardusand torical selective events continue to shape human Kunst, 2001). phenotypic diversity today, including for traits that Such differences almost certainly involve major contribu- arekeytocontrollinginfection. tionsfromtheenvironment.However,genome-wideassociation studies (GWAS) also support a keyrole for genetic factors, as manyoftheGWAS-variantsassociatedwithinfectious,autoim- INTRODUCTION mune,andinflammatorydiseasespresentextremedifferencesin allele frequency (F > 0.4) between human populations, again st Asourprimaryinterfacewiththeenvironment,theimmunesys- supporting a possible history of population-specific selection temisthoughttohaveevolvedunderstrongselectivepressure (BrinkworthandBarreiro,2014). Cell167,657–669,October20,2016ª2016ElsevierInc. 657 GWASresultsalsoindicatethatsusceptibilitytomanycom- witheitherListeriaorSalmonella(Figure1A).Wefoundextensive mon immune-related diseases is primarily controlled by non- differencesingeneexpressionlevelsbetweeninfectedandnon- codingvariants(Gusevetal.,2014;Hindorffetal.,2009;Schaub infected cells, with 5,201 (44%) and 6,701 (56%) differentially etal.,2012).Thus,manyancestry-relateddifferencesindisease expressed genes after infection with Listeria and Salmonella, susceptibility may result from genetically controlled transcrip- respectively (see the STAR Methods, false discovery rate tionaldifferencesinimmuneresponsestoinflammatorysignals. [FDR] < 0.01 and jlog (fold change)j > 0.5; Table S2A). As ex- 2 Thisideaisconsistentwithrecentexpressionquantitativetrait pected, the sets of genes that responded to either infection locus (eQTL) mapping studiesin innateimmunecellsexposed were strongly enriched (FDR < 0.01) for gene sets involved in to immune antigens or live infectious agents (Barreiro et al., immune function, including the regulation of inflammatory re- 2012; C¸alısxkan et al., 2015; Fairfax et al., 2014; Lee et al., sponses, cytokine production, T cell activation, and apoptosis 2014). Such immune ‘‘response eQTL’’ studies have identified (TableS3). hundreds of genetic variants that both explain variation in the host immune response and are significantly enriched among Ancestry-RelatedDifferencesintheInnateImmune GWAS-associated loci. However, because studies to date ResponsetoInfection have mostly focused on individuals of European ancestry, the We first aimed to characterize European versus African degree to which such variants contribute to population differ- ancestry-relatedtranscriptionaldifferencesinnon-infectedand encesintheimmuneresponseremainsunclear. infected macrophages. Because self-identified ethnicity is an Here, we report an RNA-sequencing (RNA-seq)-based im- impreciseproxyfortheactualgeneticancestryofanindividual, mune response eQTL study to test for the effects of African we used the genotype data to estimate genome-wide levels versus European ancestry on the transcriptional response to ofEuropeanandAfricanancestryineachsampleusingthepro- several live bacterial pathogens. We integrate statistical and gramADMIXTURE(Alexanderetal.,2009).Consistentwithpre- evolutionary genetic analyses with primary macrophage gene viousreports(Brycetal.,2010;Tishkoffetal.,2009),wefound expression levels, before and after infection, to characterize thatmanyself-identified AA individualshave ahigh proportion ancestry-relateddifferencesintheimmuneresponse.Ourana- of European ancestry (mean = 30%, range 0.9%–100%; Fig- lysesaddressthreefundamentalquestionsaboutrecentevolu- ure S1B). In contrast, self-identified EA showed more limited tioninthehumanimmunesystem:(1)thedegreetowhichinnate levels of African admixture (mean = 0.4%, range 0%–18%; immuneresponsesaredifferentiatedbyEuropeanversusAfrican Figure S1B). Thus, we used these continuous estimates (as ancestry, (2) the genetic variants that account for such differ- opposedtoabinaryclassificationofindividualsintoAfricanor ences,and(3)theevolutionarymechanisms(neutralgeneticdrift Europeanancestry)toidentifyancestry-associateddifferentially versus positive selection) that led to their establishment in expressed genes (i.e., pop-DE genes: genes for which gene modern human populations.Finally, to facilitate theuse of our expression levels are linearly correlated with ancestry levels; databytheresearchcommunity,wehavedevelopedanacces- see the STAR Methods for details on the nested linear model sible, publicly available browser for exploring our results: the usedforthisanalysis). ImmunPopQTLbrowser(http://www.immunpop.com). Of the 11,914 genes we tested, we identified 3,563 pop-DE genes(30%)inatleastoneoftheexperimentalconditions,ex- RESULTS plaining a mean 8.2% of expression variance (range 1.8%– 44%)(FDR<0.05:1,745innon-infected[NI],1,336inListeria- TranscriptionalResponseofMacrophagestoListeria infected[L],and2,417inSalmonella-infected[S]macrophages) andSalmonella (Figures 1B and 1C; Table S2B). These differences pri- Weinfectedmonocyte-derivedmacrophages—phagocyticcells marilyinfluencemeangeneexpressionlevelsacrosstranscript that are essential for fighting foreign invaders, tissue develop- isoforms,asopposedtotheproportionofisoformusagewithin ment,andhomeostasis(OkabeandMedzhitov,2016)—derived genes. Specifically, among genes with at least two annotated from80AAand95EAindividuals(TableS1)witheitherListeria isoforms (n = 10,223), only 62, 39, and 48 genes exhibited monocytogenes (a Gram-positive bacterium) or Salmonella evidence for ancestry-associated differential isoform usage, typhimurium (a Gram-negative bacterium). Following 2 hr of in the non-infected, Listeria-infected, and Salmonella-infected infection, we collected RNA-seq data from matched non-in- conditions, respectively (multivariate generalization of the fectedandinfectedsamples,foratotalof525RNA-seqprofiles Welch’s t test; FDR < 0.05) (Figures 1D and S2A; Table S2D). across individual-treatment combinations (mean = 36 million Theseresultswereunalteredbyusinganalternativeidentifica- readspersample;seetheSTARMethods;FigureS1A).Eachin- tion approach (Wilcoxon rank sum test, as in Lappalainen dividual was genotyped for over 4.6 million single nucleotide etal.,2013;seetheSTARMethodsfordetails)orwhenrelaxing polymorphisms(SNPs),withadditionalimputationto(cid:1)13million the FDR threshold used to define significance (Figure S2B). SNP genotypes (see the STAR Methods). After quality control Despitethelownumberofgenesshowingancestry-associated (Figure S1A), we were able to study 171 individuals with high- differences in isoform usage, many of these genes are key qualityRNA-seqdata,amongwhich168werealsosuccessfully regulators of innate immunity, including OAS1 that encodes genotyped. isoformswithvaryingenzymaticactivityagainstviralinfections Thefirstprincipalcomponentoftheresultinggeneexpression (Bonnevie-Nielsenetal.,2005). dataaccountedfor85%ofthevarianceinourdatasetandsepa- Next we sought to identify genes for which the response to rated non-infected macrophages from macrophages infected infection(i.e.,foldchangeingeneexpressionininfectedversus 658 Cell167,657–669,October20,2016 A B C D E G F Figure1. EuropeanandAfricanAncestry-AssociatedDifferencesinImmuneResponse (A)Principalcomponentanalysisofgeneexpressiondatafromallsamples.PC1(xaxis)andPC2(yaxis)clearlyseparatenon-infectedmacrophagesfrom macrophagesinfectedwitheitherListeriaorSalmonella. (legendcontinuedonnextpage) Cell167,657–669,October20,2016 659 non-infectedmacrophages,culturedinparallel)significantlycor- immune-relatedandtightlyconnectedtoadysregulatedinflam- relates with ancestry (see the STAR Methods). We term these matory response. Further, among the diseases most signifi- genes ‘‘population differentially responsive’’ (pop-DR) genes. cantly enriched for pop-DE genes were rheumatoid arthritis, We detected 1,005 and 206 pop-DR genes (FDR < 0.05) in systemic sclerosis, and ulcerative colitis, all of which have response to Salmonella and Listeria, respectively (Figure 1E; beenreportedtodifferinincidenceordiseaseseveritybetween Table S2C) (the increased power for Salmonella likely results AAandEAindividuals(BrinkworthandBarreiro,2014;Penning- from the stronger transcriptional response induced by Salmo- ton et al., 2009). Thus, ancestry-associated gene regulatory nellarelativetoListeria,seeFigure1A).Thesegenesexplaina differences likely contribute to known ethnic disparities in mean 7.4% (range 2.6%–24%) of variance in transcriptional inflammatory and autoimmune disease susceptibility, in part response to infection. Overall, we found that macrophages throughaffectingtheabilityofmacrophagestocontrolbacterial from individuals of African ancestry produced a markedly infections. stronger transcriptional response to both bacterial infections (Mann-Whitneytest,p<1310(cid:3)15,Figure1F).GOtermenrich- GeneExpressionQTLinNon-infectedandInfected mentanalysesfurtherrevealedthatgenesrelatedtoinflamma- Macrophages tory processes were the most enriched among pop-DR genes Toidentifywhetherpop-DEandpop-DRgenesareexplainedby showingastrongerresponsetoinfectioninAfrican-descentindi- geneticdifferencesbetweenEuropeanandAfricanpopulations, viduals (Figures 1G and S2C). Together, these results indicate wefirstmappedgeneticvariantsthatareassociatedwithgene thatincreasedAfricanancestrypredictsastrongerinflammatory expressionlevels(i.e.,eQTL)ortranscriptisoformusage(alter- responsetoinfection. nativesplicingQTL[asQTL])inthecompletesample.Todoso, We hypothesized that ancestry-associated differences in weusedalinearregressionmodelthataccountsforpopulation the transcriptional response to infection could translate into structure and principal components of the expression data, ancestry-associated differences in the ability of macrophages thus limiting the effect of unknown confounding factors (see tocleartheinfection.Wetestedthishypothesisinasubsetof the STAR Methods for details). Given that our sample size is 89individualsbyquantifyingthenumberofbacteriaremaining toosmalltorobustlydetecttrans-actingeQTL,wefocusedour inside the macrophages rightafter the infectionstep (T0),2hr analyses on local associations that, for simplicity, we refer to (T2),and24hr(T24)post-infection.Forbothbacteria,increased ascis-eQTL.Wedefinecis-eQTLandcis-asQTLhereasSNPs Africanancestrypredictedimprovedcontrolofintracellularbac- locatedinthegenebodyorinthe100kbflankingthegeneof terialgrowth.Thiseffectwasparticularlynoticeableinourinfec- interest. tionexperimentswithListeria.Despitenosignificantdifference We identified cis-eQTL for 1,647 genes (14% of all genes in the initial number of bacteria infecting macrophages (Fig- tested;FDR<0.01)inatleastoneoftheexperimentalconditions ure 2A, p = 0.95), the number of bacteria inside the macro- (875innon-infectedmacrophages,1,087intheListeria-infected phages of individuals with high levels of African ancestry at condition, and 983 in the Salmonella-infected condition; Fig- T24was3.2-foldlowerthanthatofEuropeans(Figure2A,p= ure 3A; Table S4A; Figure S3A for number of eQTL found at 2.0310(cid:3)4). morerelaxedcutoffs).Similarly,wedetectedalargenumberof Finally, we tested if pop-DE genes were enriched among cis-asQTL affecting the ratio of alternative isoforms used for GWAS-associated genes. We found seven diseases for which the same gene (1,120 genes, 10% of all genes tested; FDR < susceptibility genes reported by GWAS were significantly en- 0.01[Figure3A;TableS4C]:886innon-infectedmacrophages, riched among genes classified as pop-DE, in at least one 746inListeria-infectedsamples,and615inSalmonella-infected experimental condition (Figure 2B). Contributing to these en- samples). richments are several HLA genes (HLA-DQA1, HLA-DPA1, Outofallgeneswithcis-eQTL,alargefraction(21.8%)were HLA-DRB1, HLA-DPB1, HLA-DRA), known to be the main associated with an eQTL only in infected macrophages. In genetic risk factors for several immune disorders. Strikingly, contrast, only 7.3% of genes showed an infection-specific six of these seven diseases (all but Parkinson’s disease) are cis-asQTL (Figures 3A and 3B). Infection-specific cis-eQTL (B)Venndiagramillustratingthenumberofpop-DEgenes(FDR<0.05)innon-infected(black),Listeria-infected(yellow),andSalmonella-infected(orange) macrophages. (C)Exampleofagene,thechemokineCCL15,forwhichexpressionlevelsinallconditionsaresignificantlyassociatedwithlevelsofAfricanversusEuropean ancestry.Theaveragesequencingdepthforeachbase(normalizedpermillionmappedreads)isshownontheyaxis. (D)Exampleofthreegenes(POLR1A,NDUFS5,andOAS1)forwhichancestrypredictsdifferencesinisoformusage. (E)Exampleofthreeimmune-relatedpop-DRgenes.Theyaxisshowsthelog2foldchangesingeneexpressionlevelsinresponsetoListeriaandSalmonella,asa functionofcontinuousdifferencesinAfricanancestry(xaxis). (F)Absolutedifferenceinthelog2foldchangeresponsetoSalmonella(toppanel)andListeriainfection(bottompanel)betweenEuropeanandAfricanindividuals (xaxis),amongallpop-DRgenes(red)andpop-DRgenesassociatedwiththeinflammatoryresponse(blue).Thenullexpectationfrompermutingadmixturelevels acrossindividualsisshowninlightgrayforcomparison.AshiftinthedistributiontotherightreflectsastrongerresponsetoinfectioninAfrican-ancestry individuals. (G)GOenrichmentanalysisforgenesshowingasignificantinteractionbetweenancestryandtheresponsetoSalmonella.OnlyGOtermswithanenrichmentat FDR<0.1aredisplayed,andGOtermsarecolor-codedintofunctionallyrelatedtermsbasedontheoverlapamonggenesets(Bindeaetal.,2009).ForeachGO term,theaverageinteractioneffectisplottedonthexaxisandthemeanlog2foldchangeingeneexpressionlevelsinresponsetoinfectionisplottedontheyaxis. SeealsoTablesS2andS3. 660 Cell167,657–669,October20,2016 Listeria Salmonella Figure 2. Increased African Ancestry Pre- A dictsImprovedControlofBacterialGrowth 3 2 insideMacrophages d ratio 1 d ratio 12 (n(Ayu)amxBbisoe)xrimpolfomtbesadcisatheteroilawyiiannfgsteidrtehineifnefqcetucioatenndt(ilTme0a),nc2ororhmprhapaliogzseetds- e 0 e z z 0 infection (T2), and 24 hr post-infection (T24) mali−1 mali−1 (xaxis).Wequantilenormalizeddataacrossin- r r dividuals and time points. Analyses were con- o o N−2 N−2 ductedusingacontinuousmeasureofancestry; P = 0.95 P = 0.05 P = 2e-4 P = 0.69 P = 0.16 P = 1.1e-2 however,forvisualizationpurposes,Africanand −3 −3 Europeansamplesweredefinedasthosewithan T0 T2 T24 T0 T2 T24 estimated African ancestry >75% (green) and Timepoints Timepoints <25%(pink),respectively. (B) Fold enrichment of pop-DE genes (y axis) European-American African-American amonggenesidentifiedindiseasesusceptibility GWAS,atprogressivelystringentpvaluethresh- B olds(xaxis).Grey,yellowandorangelinesshow 25 FDR < 0.1 significantenrichments(filledcirclesatanFDR< 0.1 and open circles at anominal p <0.05) for Pvalue < 0.05 pop-DE genes identified in non-infected and Listeria- and Salmonella-infected macrophages, 20 rheumatoid arthrittiiss respectively.Lightgraylinesshownon-significant nt multiple e sclerosis diseases/traits. m SeealsoFigureS2. h 15 nric ssycsleteromsiics ulcecraotliivties E old 10 F Parkinson's disease tle interaction effects: eQTL can be Parkinson's sharedacrossconditionsaslongastheir disease 5 effect size differs between infected and non-infectedsamples.Wedetected244 Inflammatory bowel disease and 503 genes with a cis-reQTL (FDR < 0 0.01,TableS4B)fortheresponsetoLis- teriaandSalmonella,respectively.Inter- 10 15 20 40 estingly,amonggenesassociatedwitha GWAS -log (P) 10 cis-reQTL, we found several key regu- latorsoftheimmuneresponse,including the transcription factors STAT4 and werefurthersupportedbyanalysisofallele-specificexpression IRF2 (Figure 3D). We also found cis-reQTL for known suscep- (ASE) levels, which provides independent but complementary tibility loci for ulcerative colitis (e.g., HLA-A, HLA-DQA2, evidence for functional cis-regulatory variation. As expected, PMPCA), systemic lupus erythematosus (ITGAX, HLA-DQA1), geneswithcis-eQTLweresignificantlyenrichedforgeneswith and the infectious diseases hepatitis B and leprosy (e.g., ASE,comparedtothebackgroundofall9,588genestested(Fig- HLA-C,NOD2). ure S3B, Fisher’s exact test, p < 13 10(cid:3)15 for all conditions). To investigate the regulatory mechanisms that account for Further, genes harboring infection-specific eQTL also tended immune reQTL, we next profiled the genome-wide chromatin toexhibitinfection-specificASEinthesamecondition(Listeria accessibility landscape of non-infected and Listeria and Sal- or Salmonella) in which the eQTL was identified (Figure 3C, monella-infected cells using assay for transposase-accessible (cid:1)27 fold-enrichment of infection-specific ASE among infec- chromatin using sequencing (ATAC-seq) (Buenrostro et al., tion-specific eQTL, relative to shared eQTL; p < 1 3 10(cid:3)15). 2013).Thisapproachallowedustoidentifytranscriptionfactor Thus, in agreement with previous studies (Fairfax et al., 2014; (TF) binding motifs likely to be occupied by their respective Lee et al., 2014), genotype-environment (G 3 E) interactions TFs,inbothconditions(seetheSTARMethods).Wefoundthat are common in the context of immune responses to infection, SNPswithinaccessibleTFbindingsitesweregreaterthanfour albeitmoresoformeanexpressionlevelsthanalternativeiso- timesmorelikelytobeidentifiedasreQTL(Figure3E).Further, formusage. reQTL in our analyses were strongly enriched (>20-fold) for AcomplementaryapproachtoidentifyingG3Einteractions PU.1bindingsites(apioneerTFinvolvedinregulatingenhancer forexpressionlevelsistodirectlymapresponseeQTL(reQTL): activityinmacrophages)(Garberetal.,2012)andforvirtuallyall QTL associated with the magnitude of change in expression TFsthatorchestrateinnateimmuneresponsestoinfection(Fig- levelsafterinfection(Barreiroetal.,2012;C¸alısxkanetal.,2015; ure3E)(e.g.,nuclearfactorkB[NF-kB]:>50-fold;AP1:>55-fold; Lee et al., 2014). In contrast to condition-specific eQTL (an and IRFs: 14-fold for Salmonella only). In striking contrast, we extremecaseofG3Einteraction),reQTLcancapturemoresub- found no such enrichment for eQTL identified in non-infected Cell167,657–669,October20,2016 661 A C B D E Figure3. eQTLandASEAnalysesRevealExtensivecis-RegulationofGeneExpressionResponsestoPathogensinMacrophages (A)Schematicrepresentationofthenumberofcis-eQTLandcis-asQTLsharedacrossallconditions,oronlyfoundinnon-infectedmacrophagesorListeriaand/or Salmonellainfectedmacrophages.Infection-specificeQTLweredefinedasthoseshowingverystrongevidenceofeQTLintheinfectedstate(FDRalwayslower than0.01),andverylimitedinthenon-infectedstate(FDRalwayshigherthan0.3). (B)Examplesofacis-eQTLobservedinallconditions(HLA-DQB1),acis-eQTLobservedonlyininfectedmacrophages(ADSS),andacis-eQTLobservedonlyin Salmonella-infectedmacrophages(HLA-C).PinkandgreendotsinsidetheboxplotsdistinguishAfrican(>75%Africanancestry)andEuropean(<25%African ancestry)samples,respectively. (C)PlotcontrastingtheevidenceforASE(-log10pvalues)innon-infectedmacrophages(yaxis)andinmacrophagesinfectedwithSalmonella(xaxis),forgenes whereweidentifiedcis-eQTLinbothconditions(purple),genesforwhichcis-eQTLwereonlyfoundinnon-infectedmacrophages(gray),andgenesforwhichcis- eQTLwereonlyfoundinSalmonella-infectedmacrophages(orange).Qualitativelysimilarresultswereobtainedwhencontrastingnon-infectedandListeria- infectedcells(FigureS3C). (D)Examplesoftwocis-reQTLwheregenotype(xaxis)hasasignificanteffectontheresponseofSTAT4(left)andIRF2(right)toSalmonellainfection. (E)reQTLenrichments(xaxis)inactivelyregulatedTFbindingsitesannotatedbyATAC-seqfootprinting.Errorbarsshow95%confidenceintervals.Bindingsites weregroupedintofunctionallyoverlapping‘‘TFclusters’’usingsequencesimilarityandco-localizationinthegenome(TableS6;STARMethods). SeealsoTableS4. macrophages(p>0.05forNF-kB,AP1,andIRFs)(FigureS3D). GeneticBasisofAncestry-AssociatedDifferencesinthe TheseresultsshowthatreQTLvariantsareoftenconditionallysi- ImmuneResponsetoPathogens lent in resting macrophages but become functionally relevant Wehypothesizedthatdifferencesinallelefrequenciesforsome post-infection, and this transition is explained by disruption of of the eQTL identified above could explain the observed bindingsitesforimmuneresponse-activatedTFs. ancestry-associateddifferencesinthetranscriptionalresponse 662 Cell167,657–669,October20,2016 A B C D Figure4. ContributionofcisandtransGeneticVariationtopop-DEandpop-DRGenes (A)Theproportionofpop-DE,pop-DR,andgenesthatexhibitancestry-associatedisoformusagethatareassociatedwithacis-eQTL,cis-reQTL,orcis-asQTL, respectively(FDR<0.01).Nullexpectations(basedonthegenome-wideproportionofgenesassociatedwitheachQTLclass)areshowningray.Similarresults areobtainedwhenfocusingontranscriptionalQTLidentifiedatanFDRof0.05(FigureS4B). (B)AverageDPSTobtained(±SE)whenregressingoutthegenotypeeffectoftheleadcis-ortheleadtrans-SNPforpop-DEandpop-DRgenes(yaxis),defined usingprogressivelystringentFDRcutoffs(xaxis).ColoredlinesshowaverageDPSTvaluesbasedontherealdata;graylinesshowthesamevalueswhenre- gressingoutthegenotypeeffectoftheleadSNPidentifiedbasedonpermutedgenotypes. (C)Numberofgenesidentifiedaspop-DEandpop-DRatanFDR<0.05(yaxis)before(dashedbars)andafter(filledbars)regressingouttheeffectoftheleadcis- SNPassociatedwiththesegenes. (D)Examplesofgenesforwhichtheleadcis-(blue)ortheleadtrans-SNP(green),explainsatleast75%ofthedifferencesingeneexpressionassociatedwith AfricanversusEuropeanancestry. to infection. In support of this hypothesis, we found that pop- proportionofoverallgeneexpressionvarianceexplainedbybe- DEgeneswereenrichedupto3.3-foldforgeneswithcis-eQTL tween-populationphenotypicdivergence(asopposedtowithin- (p < 1 3 10(cid:3)10), and pop-DR genes were enriched up to 5.8- populationdiversity).P valuesrangefrom0to1,withvalues ST fold for genes with cis-reQTL (p < 1 3 10(cid:3)10) (Figures 4A and closeto1implyingthatthemajorityofagene’sexpressionvari- S4A).Additionally,(cid:1)60%ofgenesthatexhibitedancestry-asso- ance is due to differences between populations. Our score, ciated isoform usage were associated with an asQTL (up to deltaP (DP ),isdefinedasthedifferencebetweenP values ST ST ST 24-fold enrichment, p < 1 3 10(cid:3)10). Thus, although rare, beforeandafterregressingouttheeffectofthecis-SNPthatwas ancestry-associatedchangesinisoformusagearelargelygenet- moststronglyassociatedwiththetargetgene’sexpressionlevel icallydriven. (regardless of significance level), divided by the P value ST To explicitly quantify the contribution of our eQTL set to observedbeforeremovingthegenotypeeffect.DP therefore ST transcriptional differences detected between populations, we quantifiestheproportionofancestry-associatedexpressionlevel devised a new score based on P estimates (Leinonen etal., differencesthatstemfromthestrongestcis-associatedvariant. ST 2013; Pujol et al., 2008). P is the phenotypic analog of the Among all pop-DE genes, we found that cis-regulatory ST population genetic parameter F , providing a measure of the variants explained an average of 31%, 31%, and 26% of ST Cell167,657–669,October20,2016 663 ancestry-related differences in expression observed in non- (MAF) >5% in the CEU and YRI samples. In contrast to F , ST infected, Listeria-infected and Salmonella-infected samples, iHSisawithin-populationmeasureofrecentpositiveselection respectively(Figure4B).Further,thelargertheeffectofancestry that is not affected by the levels of population differentiation in the original pop-DE analysis, the larger the contribution of (Voightetal.,2006). cis-regulatoryvariationtothesedifferences:forpop-DEgenes Our analyses identified significantly higher mean F values ST identifiedatastringentFDRof1310(cid:3)4,cis-regulatoryvariation among genes that were pop-DE, pop-DR, or showing differ- explained close to 50% (on average) of ancestry effects (Fig- ences in isoform usage between populations (p % 1 3 10(cid:3)3; ure4B).Weobservedasimilarpatternforpop-DRgenesafter Figures5AandS5Aforsimilarresultswhenusingalternativewin- regressing out the genotype effect of the lead cis-reQTL SNP dowsizes).Further,variantsidentifiedascis-eQTLweresignifi- (Figure 4B). In support of the substantial role of cis-regulatory cantly enriched ((cid:1)2-fold) for high iHS values (i.e., iHS > 99th variationinexplainingpop-DEandpop-DRgenes,geneexpres- percentile of genome-wide distribution, Figure 5B, p < 1 3 sion values for 30% and 45% of pop-DE and pop-DR genes, 10(cid:3)8),consistentwiththeimportanceofregulatorygeneticvari- respectively, were no longer significantly associated with ation in recent human evolution (Fraser, 2013). cis-reQTL and ancestryonceweregressedoutcis-geneticeffects(Figure4C). cis-asQTL were even more strongly enriched among high iHS Importantly, DP values never exceeded 5% when we re- values(upto3.6-fold;Figure5B,p<1310(cid:3)5). ST gressedouteither(1)thegenotypeeffectofrandomlyselected Overall,withinthesetofcis-eQTL-,cis-reQTL-,orcis-asQTL- SNPsmatchedfortheallelefrequencyoftheleadcis-SNP,or associated genes, 258 carried a signature of recent positive (2)leadcis-SNPsidentifiedafterpermutingthegenotypedata. selectionineitherCEUorYRIsamples(jiHSjR99thpercentile Thus, our results cannot be simply explained by population ofthegenome-widedistribution)(Figure5C;TableS5A).These structure(Figure4B). variantswerealsosignificantlyenrichedforhighXP-EHHvalues Based on their known importance in the genetic control of (Sabetietal.,2007)((cid:1)6-fold,p<1310(cid:3)10,FigureS5C),further generegulationandbecauseofpowerlimitations,ourmainanal- supporting that these variants have been important in recent, ysis of ancestry-associated gene expression patterns focused population-specific human adaptation. However, because ontheroleofcis-eQTL.However,inaseparateanalysis,were- outlier methods for detecting selection can be susceptible calculatedDP usingtheleadtrans-SNPforeachgeneinplace to false positives (Kelley et al., 2006), we complemented our ST of the lead cis-SNP (although only 51, 21, and 22 trans- iHS analysis with a model-based approach. Specifically, we eQTL genes survived genome-wide multiple testing correction comparedtheobservediHSvalueforeachputativelyselected (FDR<0.1)innon-infected,Listeria-infectedandSalmonella-in- allele to those observed under neutral coalescent simulations fected samples, respectively). Intriguingly, we found that lead matchedtotheknowndemographichistoryofAfricanandEuro- trans-SNPs accounted for an average of (cid:1)23% and (cid:1)20% of peanpopulations(Gutenkunstetal.,2009),thecandidateallele’s ancestry effects on gene expression levels for pop-DE and observedfrequency,andthelocalrecombinationrate.Thevast pop-DR genes, respectively (Figure 4B; at least 2-fold more majority (92%) of all sites tested exhibited significantly larger thanestimatesbasedonpermuteddata,p<1310(cid:3)10).These observed iHS statistics than expected under a neutral model resultssuggestthatleadtrans-SNPs,althoughdifficulttodetect (p<0.01,TableS5B),providingstrongconvergentsupportfor atagenome-widesignificancelevel,areenrichedfortruetrans- recentpositiveselectionattheseloci.Farmoreofthesegenes associations that could be resolved with larger sample sizes. are pop-DE or pop-DR than expected by chance (47% and Together, a single cis- or trans-acting variant was sufficient to 23%,respectively:Figure 5D,p <0.001),showing thatnatural explainalmostallancestryeffects(DP >75%)ongeneexpres- selectionhascontributedtopresent-dayinter-populationdiffer- ST sionlevelsfor804pop-DEgenesandpop-DRgenes(Figure4D), encesininnateimmuneresponsestoinfection. includingformasterregulatorsoftheimmuneresponsesuchas Neanderthalancestrymakesup(cid:1)2%oftheancestryofliving CASP1,STAT4,andMICA.Ourresultsthusprovideacompre- humans found outside of Africa (Kelso and Pru¨fer, 2014). It hensive genome-wide map of cis- and trans-genetic variants is therefore plausible that interbreeding between Neanderthal associated with African and European ancestry-related differ- and modern human populations could also contribute to encesintheimmuneresponsetoinfection. some of the ancestry-related differences in gene expression we observed, especially if it enabled the ancestors of modern NaturalSelectionandGeneticAncestryEffectsonGene Europeans to more rapidly adapt to a new pathogen environ- ExpressionDivergence ment(Se´gurelandQuintana-Murci,2014).Totestthishypothe- Finally, we sought to determine the impact of recent local sis,weidentifiedsiteswherethederivedalleleissharedbetween positive selection ineither African orEuropean populations on Neanderthalsandnon-Africanpopulations,butisabsentinsub- ancestry-related divergence in gene expression levels. To do SaharanAfricanssamplesconsidered.Thisclassofsites,which so, we first calculated F values between the Yoruba African wecall‘‘Neanderthal-likesites’’(NLS),isaconservativeindicator ST (YRI) and the western European population (CEU) in Phase 3 of Neanderthal introgression (Sankararaman et al., 2014). data from the 1000 Genomes Project (Auton et al., 2015). To Among the 18,862 NLS tested in our cis-QTL analyses, 297 generate gene-specific estimates, we averaged F values for were significantly associated with transcriptional variation of ST variantswithinawindowof10kbaroundthetranscriptionstart 145 genes (NLS-QTL). Among these 145 genes, 46% (FDR < site (TSS) of each gene we analyzed (11,914 genes). As a 0.05) were differentially regulated in at least one experimental complementaryapproach,wealsocalculatedintegratedhaplo- condition (non-infected, Listeria-infected, Salmonella-infected, type scores (iHS) for all SNPs with a minor allele frequency orintheresponsetoeithertypeofinfection)betweenEuropeans 664 Cell167,657–669,October20,2016 A B C D Figure5. NaturalSelectiononeQTLandItsContributiontoAncestry-AssociatedRegulatoryDifferences (A)MeanF valuesinawindowof±10kbaroundtheTSSofallgenes,pop-DEgenes,pop-DRgenes,andgenesshowingdifferencesinisoformusagebetween ST populations(toppanel). (B)ProportionofallSNPs,cis-eQTL,cis-reQTL,andcis-asQTLwithaniHSvalueabovethe99thpercentileofthegenome-widedistributionintheCEU(jiHSj> 2.70)andtheYRI(jiHSj>2.68)populations.SeeFigureS5BforsimilarresultsconsideringQTLidentifiedatanFDR<0.05(insteadof0.01). (C)Manhattanplotofagenome-widescanforselectioninCEU(top)andYRI(bottom)forSNPsidentifiedasregulatoryQTLinmacrophages.Thedashedline representsthe99thpercentileofthegenome-widedistribution.DarkershadesofbluerepresentlargerFSTvaluesforSNPswithelevatedjiHSjvalues;bluecircled dotshighlightgenesthatshowoneormoretranscriptionalassociationswithAfricanversusEuropeanancestry.GenesinredareregulatedbyNLSwithelevated jiHSjvaluesinCEU(jiHSj>2.7),supportingadaptiveintrogressionfromNeanderthalsintotheancestorsofmodernEuropeans. (D)ProportionofgenesregulatedbyeQTLandtargetedbyrecentpositiveselection(amongthe258representedbythebluecirclesinC)thatarepop-DE, pop-DR,orshowpopulationdifferencesinisoformusage(bluetriangles),comparedtorandomexpectationswhensamplingthesametotalnumberofgenes 10,000timesfromallgenestested(violinplots). SeealsoTableS5. and Africans (63% at a more relaxed FDR < 0.1). Thus, a ofLCL lines, which were generated more than 20 years apart non-negligible proportion of ancestry-related gene expression (Daussetet al., 1990). divergence probably results from introgression of functional Oneofthemoststrikingobservationsfromourstudywasthe Neanderthalvariantsintotheancestors ofmodernEuropeans. markedly stronger response to infection induced in macro- Interestingly,someofthesevariants(n=16)alsohaveelevated phagesfromindividualsofAfricandescent,particularlyamong iHS values (jiHSj R 2) (Figure 5C; Table S5A) and therefore inflammatoryresponsegenes.Thisresultagreeswithprevious representnewcandidatesforadaptiveintrogressioninhumans. reports showing that AAs have higher frequencies of alleles associatedwithanincreasedpro-inflammatoryresponse(Ness DISCUSSION et al., 2004), increased levels of circulating C-reactive protein (Kelley-Hedgepethetal.,2008),andamuchhigherrateofinflam- Together, our results provide a comprehensive characteriza- matory diseases than EA individuals (Pennington et al., 2009). tion of genes for which the transcriptional responses of pri- Althoughtheexactcausallinkbetweenancestryandthepro-in- mary cells to live pathogenic bacteria differs depending on flammatory response has yet to be established, we speculate European versus African ancestry. We show that 34% of thatthestrongerinflammatoryresponseassociatedwithAfrican genes expressed in macrophages show at least one type of ancestry accounts for the increased ability of macrophages in ancestry-related transcriptional divergence, whether in the African ancestry individuals to control bacterial growth post- form of differences in gene expression (30%), the transcrip- infection. tional response to infection (9.3%), or, less commonly, differ- Nevertheless, the evolutionary pressures that explain these encesinisoformusage(1%).Notably,themodestcontribution differencesremainanopenquestion.Onepossibilityisthat,after ofdifferencesinisoformusagetoancestry-relatedexpression humanpopulationsmigratedoutofAfrica,theywereexposedto levelsdiffersfrompreviousresultsinlymphoblastoidcelllines lowerpathogenlevels(Guernieretal.,2004),whichreducedthe (LCLs),wheretheywerefoundtobequitecommon(Lappalai- needforstrong,costlypro-inflammatorysignals.Changeinthis nen et al., 2013). The discrepancy between our results and directionmayhavebeenfavoredduetothedetrimentalconse- those reported for LCLs may be related to differences in quencesofacuteorchronicinflammation,whicharekeycontrib- the experimental procedures used to produce the two sets utorstothedevelopmentofautoinflammatoryandautoimmune Cell167,657–669,October20,2016 665

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Ness, R.B., Haggerty, C.L., Harger, G., and Ferrell, R. (2004). Differential dis- · tribution of allelic variants in cytokine genes among African Americans
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