Integrative Genomics-Based Discovery of Novel Regulators of the Innate Antiviral Response

35 Pages·2015·1.05 MB·English

RESEARCHARTICLE
Integrative Genomics-Based Discovery of
Novel Regulators of the Innate Antiviral
Response
RobinvanderLee1*,QianFeng2☯¤a,MartijnA.Langereis2☯,RobterHorst1,
RadekSzklarczyk1¤b,MihaiG.Netea3,ArnoC.Andeweg4,FrankJ.M.vanKuppeveld2,
MartijnA.Huynen1*
1 CentreforMolecularandBiomolecularInformatics,RadboudInstituteforMolecularLifeSciences,
Radbouduniversitymedicalcenter,Nijmegen,TheNetherlands,2 VirologyDivision,Departmentof
InfectiousDiseasesandImmunology,FacultyofVeterinaryMedicine,UniversityofUtrecht,Utrecht,The
Netherlands,3 DepartmentofInternalMedicineandRadboudCenterforInfectiousDiseases,Radboud
universitymedicalcenter,Nijmegen,TheNetherlands,4 DepartmentofViroscience,ErasmusMedical
Center,Rotterdam,TheNetherlands
☯Theseauthorscontributedequallytothiswork.
¤a Currentaddress:InstituteofBiochemistry,ETHZurich,Zurich,Switzerland
¤b Currentaddress:DepartmentofClinicalGenetics,UnitClinicalGenomics,MaastrichtUniversityMedical
OPENACCESS Centre,Maastricht,TheNetherlands
*[email protected](RvdL);[email protected](MAH)
Citation:vanderLeeR,FengQ,LangereisMA,ter
HorstR,SzklarczykR,NeteaMG,etal.(2015)
IntegrativeGenomics-BasedDiscoveryofNovel
Abstract
RegulatorsoftheInnateAntiviralResponse.PLoS
ComputBiol11(10):e1004553.doi:10.1371/journal.
pcbi.1004553 TheRIG-I-likereceptor(RLR)pathwayisessentialfordetectingcytosolicviralRNAtotrig-
Editor:BjoernPeters,LaJollaInstituteforAllergy gertheproductionoftypeIinterferons(IFNα/β)thatinitiateaninnateantiviralresponse.
andImmunology,UNITEDSTATES Throughsystematicassessmentofawidevarietyofgenomicsdata,wediscovered10
Received:September3,2015 molecularsignaturesofknownRLRpathwaycomponentsthatcollectivelypredictnovel
members.WedemonstratethatRLRpathwaygenes,amongothers,tendtoevolverapidly,
Accepted:September12,2015
interactwithviralproteins,containalimitedsetofproteindomains,areregulatedbyspecific
Published:October20,2015
transcriptionfactors,andformatightlyconnectedinteractionnetwork.UsingaBayesian
Copyright:©2015vanderLeeetal.Thisisanopen approachtointegratethesesignatures,weproposelikelynovelRLRregulators.RNAi
accessarticledistributedunderthetermsofthe
knockdownexperimentsrevealedahighpredictionaccuracy,identifying94genesamong
CreativeCommonsAttributionLicense,whichpermits
unrestricteduse,distribution,andreproductioninany 187candidatestested(~50%)thataffectedviralRNA-inducedproductionofIFNβ.Thedis-
medium,providedtheoriginalauthorandsourceare coveredantiviralregulatorsmayparticipateinawiderangeofprocessesthathighlightthe
credited. complexityofantiviraldefense(e.g.MAP3K11,CDK11B,PSMA3,TRIM14,HSPA9B,
DataAvailabilityStatement:Allrelevantdata CDC37,NUP98,G3BP1),andincludeuncharacterizedfactors(DDX17,C6orf58,C16orf57,
supportingtheresultsofthispaperareavailablein PKN2,SNW1).OurvalidatedRLRpathwaylist(http://rlr.cmbi.umcn.nl/),obtainedusinga
theSupplementalTablesandathttp://rlr.cmbi.umcn.
combinationofintegrativegenomicsandexperiments,isanewresourceforinnateantiviral
nl/.
immunityresearch.
Funding:RvdL,QF,ACAandMAHweresupported
bytheVirgoconsortium,fundedbytheDutch
government(FES0908),andbytheNetherlands
GenomicsInitiative(050-060-452).QFandMALwere
fundedbypersonalgrantsfromtheNetherlands
OrganizationforScientificResearch(NWO-
017.006.043andNWO-863.13.008,respectively).RS
issupportedbytheMetakidsFoundation.MGNwas
PLOSComputationalBiology|DOI:10.1371/journal.pcbi.1004553 October20,2015 1/35
IntegrativeGenomicsoftheRLRPathway
supportedbyanERCConsolidatorGrant(#310372).
FJMvKwassupportedbyaECHOgrantfromthe AuthorSummary
NetherlandsOrganizationforScientificResearch
Virusesposeacontinuousthreattohumanhealth,eventhoughourimmunesystemshave
(NWO-CW-700.59.007).Thefundershadnorolein
studydesign,datacollectionandanalysis,decisionto evolvedtoneutralizeinvadingviruses.Aspartoftheinnateimmunesystem,theRIG-I-
publish,orpreparationofthemanuscript. likereceptors(RLRs)areessentialfordetectingvirusesduringinfection.Recognitionof
viralRNAbytheRLRstriggersanantiviralresponsethatinhibitsviralreplication,protects
CompetingInterests:Theauthorshavedeclared
thatnocompetinginterestsexist. uninfectedcells,andattractsspecializedimmunecells.Betterunderstandingoftheinnate
antiviralresponsemayrevealnoveltargetsforantiviraltherapeuticsandvaccinedevelop-
ment.However,thatrequiresknowledgeaboutwhichgenesandproteinsareinvolved.In
thepresentstudy,wesystematicallyinvestigatedthewealthofavailablegenomicsdata
(includinggeneexpression,proteininteractions,transcriptionregulationandgenome
sequences)anddiscoverednolessthan10distinctivepropertiesofgenesknowntobepart
oftheantiviralRLRpathway.Bycombiningthesepropertiesinastatisticalframework,we
predicted187novelRLRpathwaycomponents.Ourvalidationexperimentsshowedthat
~50%ofthepredictedcandidategeneshaveasignificanteffectonantiviralsignaling.
Theseresults,togetherwithindependentcomputationalandliterature-basedconfirma-
tion,demonstratedthevalidityofourcombinedbioinformaticsandexperimental
approach.Ourstudyexpandsthecollectionofknownantiviralgenes,openingupnewave-
nuesforresearchintoinnateantiviralimmunity.
Introduction
Virusesareamajorcauseofhumandisease,ashighlightedbythepandemicsofinfluenza
viruses,HIV–1,andthecurrentoutbreakoftheEbolavirus.Patternrecognitionreceptors
(PRR)areamongthefirstmoleculesthatdetectvirusesduringinfection.TheRIG-I-likerecep-
tors(RLRs,oneclassofPRRs)arepartoftheRLRpathway,whichformsacrucialinnateanti-
viraldefensesystem[1,2].TwoRLRs,RIG-IandMDA5,resideinthecytosolwherethey
recognizenon-self5’-triphosphateRNAmoleculeswithshortdouble-strandedregionsand
longdouble-strandedRNAs(dsRNA),respectively[3].Activationofthereceptorstriggersa
complexsignalingnetwork,keystepsofwhicharetheactivationofthemitochondrialadapter
MAVS,subsequentrecruitmentoftheTBK1andIKKcomplexes,phosphorylation/activation
ofIRF3andNFκB,andtranslocationofthesetranscriptionfactorstothenucleus.Thesesteps
ultimatelyleadtotheproductionoftypeIinterferons(IFNα/β)andproinflammatorycyto-
kines,whicharecrucialforestablishinganantiviralstateininfectedaswellasneighboring
cells,andalsomodulatetheadaptiveimmuneresponse[4]
TheimportanceoftheRLRsystemisfurtherdemonstratedbytheobservationthatviruses
ofalltypesemploystrategiestointerferewithitsactivation,oftenatmultiplesteps[5,6].Better
understandingofviralinteractionwiththepathwayhasresultedinnoveltargetsforthedevel-
opmentofantiviraltherapeuticsandattenuatedlivevaccines,forexampleviruseslackingfunc-
tionalRLRantagonists[7].Furthermore,mutationsinRIG-I,MDA5,MAVSandotherRLR
pathwaycomponentsareassociatednotonlywithstrongsusceptibilitytoinfections,butalso
IFN-associatedautoimmunedisorders[8–10].
Previousstudiesintovirus-hostinteractionsandtheinnateantiviralpathwayshaveused
genomicsapproaches,oftengeneratinglargedatasetsdescribingphysicalorgeneticinterac-
tions[11–14].Otherpublicationshavetakenacomparativeapproachbasedonmodelorgan-
isms[15]orusedover-expressionscreeningsystems[16,17].Together,thesestudieshave
identifiednumerousgeneswithantiviralactivity,includingmembersoftheRLRpathway.
However,itremainsimportanttosystematicallyassessthequalityofindividualdatasetsas
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IntegrativeGenomicsoftheRLRPathway
suchscreensreportdistinctsetsofgenes,oftenwithlimitedoverlapbetweenthem.Combining
themanyavailablegenomicsdatasetsinastatisticalframeworkpotentiallyallowsforamore
systematicdiscoveryandcategorizationofgenesinvolvedintheRLRpathway.Indeed,Bayes-
ianintegrationoflarge-scaledatathatincludesweighingindividualdatasetsfortheirpredictive
potentialhasbeensuccessfulinothercellularsystems,forexampleidentifyingnovelprotein
interactions[18],mitochondrialdiseasegenes[19],andsmallRNApathwaygenes[20].
Inthisworkwesystematicallyexploitthewealthofavailable(gen)omicsdata,including
transcriptomicsandproteomicsdata,genomesequences,proteindomaininformation,and
functionalgenomics,todiscoverdescriptivemolecularsignaturesoftheRLRpathwaysystem.
Bayesianintegrationofthesedata,togetherwithcomprehensivecomputationalandexperi-
mentalvalidation,confidentlyidentifiesnovelgenesinvolvedinantiviralRIG-Isignaling.
Results
TheRIG-I-likereceptor(RLR)pathwayisahighlyinterconnectedanddiversemolecularsys-
tem.Weinvestigatedwhetheravailablegenomicsdatacontainsufficientsignaltoaccurately
describeRLRpathwaycomponents,andwhethersuchdatacouldbeusedtoprioritizenovel
genesforapossibleroleinRLRsignaling.
TenmolecularsignaturesofRLRpathwaycomponentsingenomics
data
TodiscovermolecularsignaturesthatdistinguishRLRpathwaycomponentsfromothergenes,
weexploredawidevarietyofgenome-scaledatadescribingdifferentaspectsofthevirology
andbiologyofthepathway.Someofthesedataweuseddirectly,whileotherdatawereusedas
thebasisforfurthercalculations(Table1).Wequantitativelyassessedthepredictivepowerof
eachdatasetusingaliterature-curatedstandardof49knownRLRpathwaycomponentsfrom
InnateDB[21](‘RLRgenes’,S1Fig)andasetof5,818‘non-RLRgenes’thatareunlikelytobe
partofthepathway(i.e.geneswithknownfunctionsnotdirectlyrelatedtotheinnateantiviral
response,suchasdevelopment,housekeepingandneurologicalprocesses,seeMethods).Below
wedescribe10signaturesforpredictingnovelRLRpathwaycomponents.Thefirstfivesigna-
turesarebasedontherelationshipofRLRgeneswithviruses,whereasthesecondsetoffivesig-
naturesarebasedonpropertiesoftheRLRpathwayitself.
Virus-basedsignatures
Positiveselectioninprimates. Virusesevaderecognitionorinterferewiththeimmune
systemsoftheirhoststoachievesuccessfulinfection[7].Thisinvolvesinteractionsbetween
viralandhostproteins,theinterfacesofwhichareunderconstantpressuretochange[22].We
collecteddataonrecurrentpositiveselectionintheprimatelineage,basedonmaximumlikeli-
hoodanalysisofsequencealignments[23].RLRpathwaycomponents,e.g.themitochondrial
signalingadapterMAVS[24]andtranscriptionfactorIRF7[25],areenrichedforrapidly
evolvinggenes(9%of49RLRgenes)comparedtogenesthatareunlikelytobepartofthepath-
way(5%of5,818non-RLRgenes,1.7-foldenrichment,non-significantP=0.38,one-tailed
Fisher’sexacttest,Fig1A,Tables1andS1).
Protein-proteininteractions(PPI)withviruses. Thenextsignatureisbasedonthephys-
icalinteractionsbetweenhostRLRpathwaycomponentsandviruses.Viralproteinsoften
interactwithmanyhostproteinsduringtheirinfectioncycle,includingthoseinvolvedinanti-
viraldefense[26,27].Extractionofvirus-humanPPIsfromspecializeddatabases[28]revealed
~2,600humanproteinsthatarereportedtointeractwithatleastoneviralprotein(virus-inter-
actinghumanproteins,S2Fig).Thesevirus-interactinghumanproteinsincludethemajority
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IntegrativeGenomicsoftheRLRPathway
Table1. TenmolecularsignaturesfromgenomicsdatausedforpredictingnovelRLRpathwaycomponents.
Group Molecular Datasetdescription Typea References Numberof Likelihoodratio
signature genesb scoreb,c
Virus-based Positiveselectionin Rapidlyevolvinggenesintheprimateslineage, d [23] 926 1.7
primates detectedusingmaximumlikelihoodanalysisof
nucleotidealignments
PPIwithviruses Virus-interactinghumanproteinsextractedfromPPI c [28] 2,587 4.2
databases
ViralmiRNAtarget Likelihoodscoresoftargetingofhumantranscriptsby c [30] 6,761 1.3
viralmiRNAs,basedonpredictedtargetsites
Differential Genesshowingdifferentialexpressioninlung c see 1,680 3.5
expressionupon epithelialcellsinfectedwithfourrespiratoryviruses Methods
infection
Antiviralhostfactor Metaanalysisofgeneswithantiviralactivityfrom c seeS3 173 2.1
sevenRNAiscreensstudyingavarietyofviruses Table
Pathway- Co-expressionwith Weightedco-expressionwithknownRLRgenes c [32] 4,149 2.4
based RLRpathway across>450humangeneexpressionstudies
RLRpathwayprotein Proteinscontainingoneofthe25domainsthatare c [66] 711 8.9
domain significantlyenrichedinknownRLRproteins
InnateantiviralTF GeneswithIRF,AP–1,NFκB,orSTATTFbinding c [33] 4,508 2.3
bindingmotifs motifsintheirpromoters,basedonconservation
across29mammals
NFκBactivation Hitsfromagenome-widesiRNAscreenofEpstein- d [34] 154 19.8
mediator Barrvirus-inducedNFκBactivation
RLRpathwayPPI ProteinsthatinteractwithknownRLRproteins, c [35] 1,750 4.3
calculatedfromPPIdata
Integration RLRscore Bayesianintegrationofthe10molecularsignaturestopredictnovelRLRpathwaycomponents
aDatauseddirectly(d)orasbasisforfurthercalculation(c)
bCombinationofallbinswithpositivelikelihoodratioscoresperfeature,derivedfromFig1A
cRLRgenesversusnon-RLRgenes:P(D |RLRgenes)/P(D |non-RLRgenes),seeMethods.
i i
Notethat,toavoidcircularity,thepredictiveabilityoftheco-expression,proteindomainandRLRpathwayPPIdatasetswasassessedusingthesetof
TLR,CLR,NLR,cytDNAgenesinsteadoftheRLRgenes(seeMethods).
SeealsoFig1AandS1Table.
doi:10.1371/journal.pcbi.1004553.t001
ofRLRpathwaycomponents(35/49=71%),whiletheyincludeasignificantlysmallerfraction
ofnon-RLRgenes(1,000/5,818=17%,4.2-foldenrichment,P=1.4×10−16,one-tailedFisher’s
exacttest,Fig1AandTable1).AmongtheRLRgenes,TRAF2(4PPIs),DDX3,MAPK9,and
theNFκBsubunitRELA(3PPIseach)havereportedinteractionswiththelargestnumberof
distinctvirusspecies.
ViralmiRNAtarget. Anothermechanismthatvirusesusetointerferewiththeantiviral
activityofhumancellsisdown-regulationofgeneexpressionbymiRNAs[29].Wecollected
128miRNAsencodedbynine,mainlyherpesDNAviruses(S2Table)[30],mostofwhich
haveconfirmedphysiologicalrelevance.PredictedtargetsitesofthesemiRNAstothe3’UTRof
humantranscriptswerethenusedtocalculateforeachgeneascorerepresentingthelikelihood
thatvirusesaffectitsexpression(viralmiRNAtargetingscore).Forexample,ourmethod
assignedIKBKE(IKKε)arelativelystrongviralmiRNAtargetingscoreof2.7.Indeed,Kaposi’s
sarcoma-associatedherpesvirusmiR-K12-11hasbeenshowntoinhibittranslationofIKKε
transcripts,leadingtosuppressionofinterferonsignaling[31].AnalysisoftheviralmiRNA
targetingscoresrevealedthatRLRgenestendtohavestrongerscoresthannon-RLRgenes
(P=0.03,one-tailedMann-WhitneyUtest).Althoughthestatisticalsignificanceofthistrend
isonlymarginal,weincludeditasamolecularsignatureofRLRgenesasitstillprovidesa
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IntegrativeGenomicsoftheRLRPathway
Fig1.BayesianintegrationoftenmolecularsignaturesofRLRpathwaycomponentsfromgenomicsdata.(A)Distributionsofthe49knownRLR
pathwaycomponents(RLRgenes,green)and5,818genesunlikelytobepartofthepathway(non-RLRgenes,red)acrossthe10molecularsignaturedata
setsweidentifiedaspredictiveoftheRLRsystem(seealsoTable1).Datasetswerebinnedintodiscreteintervalsandfractionsof(non-)RLRgenesaddup
toone.ArrowsindicatethebehaviorofRIG-Iacrossthedata.ThetopfivesignaturesdescribetherelationshipofRLRsignalingwithviruses;thebottomfive
describepropertiesofthepathwayitself.(B)Boxplotsofthegenome-wideintegratedRLRscore(Bayesianposteriorprobabilityscore).Genesweregrouped
intooneoffiveclasses:knownRLRgenes(green,see[A]),componentsofotherPRRsignalingpathways(‘TLR,CLR,NLR,cytDNA’;purple),genes
functioninginotheraspectsoftheinnateimmuneresponse(‘innateimmunity’;blue),andnon-RLRgenes(red,see[A]).Theremaininggenesareclassified
as‘other’(gray).(C)The50geneswiththehighestRLRscores.RepresentativeRLRandotherinnateantiviralresponsegenesareindicated.Thepiechart
showstheoccurrencesofthedifferentgeneclassesinthetop354RLRranks.(D)Receiveroperatingcharacteristic(ROC)curveillustratingtheperformance
oftheintegratedRLRscore(solidblackline)andtheindividualmolecularsignatures(blackdots)forpredictingknownRLRversusnon-RLRgenes.
Sensitivityandspecificitywerecalculatedatvariousscorethresholds(fortheRLRscore),oratspecificthresholdsthatincludeallbinswithpositivelikelihood
ratioscores(fortheindividualdatasets;see(A)).Theasteriskdenotesthesensitivityandspecificitycorrespondingtoafalsediscoveryrate(FDR)of57%
(top354genes).Notethat,toavoidcircularity,thepredictiveabilityoftheco-expression,proteindomainandRLRpathwayPPIdatasetsin(A)and(D)was
assessedusingthesetofTLR,CLR,NLR,cytDNAgenesinsteadoftheRLRgenes(seeMethods).
doi:10.1371/journal.pcbi.1004553.g001
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IntegrativeGenomicsoftheRLRPathway
moderateenrichmentovernon-RLRgenes(1.3-foldenrichmentamonggeneswiththestron-
gestviralmiRNAtargetingscores,Table1),andevenweakfeaturescansubstantiallyimprove
thepredictionsfornovelRLRgenes.
Differentialexpressionuponinfection. Next,weaskedwhetherRLRpathwaygenesare
differentiallyexpresseduponvirusinfection.Toanswerthis,weusedin-housegeneexpression
dataofhumanlungepithelialcells(A549)exposedtofourrespiratoryviruses(respiratorysyn-
cytialvirus,humanmetapneumovirus,parainfluenzavirus,ormeaslesvirus),forwhichgene
expressionwasmeasuredat6,12and24hoursafterinfection(seeMethods).Analysisofthe
transcriptomesrevealedthatmanyRLRgenes(31%)underwentsubstantialexpressionchanges
(log foldchange>0.5)incellsinfectedwiththerespiratoryviruses,comparedtotheunin-
2
fectedcells.Thiscomparestoamuchsmallerfractionofnon-RLRgenes(9%,3.5-foldenrich-
ment,P=1.3×10−5,one-tailedFisher’sexacttest,Fig1AandTable1).Thedifferentially
expressedRLRgenesincludewell-knowninterferon-stimulatedgenes(ISGs)likeISG15,
DDX58(RIG-I),IRF7,IFIH1(MDA5),andTRIM25,whicharethetopfiveRLRgenesmost
inducedbytherespiratoryvirusesstudied(log foldchange>1.5comparedtouninfectedcells,
2
S3Fig).Thus,eventhoughweexpectmanyRLRgenestoalreadybeexpressedbeforeviral
infection,theirexpressionlevelsarereinforcedininfectedcells.
Antiviralhostfactor. RNAiscreeningpotentiallyallowstheidentificationofhostfactors
thatlimitvirusreplication,suchasgenesinvolvedintheinnateantiviralresponse,although
moststudiesfocusonhitswiththeoppositeeffect(i.e.factorsrequiredbyvirusesforreplica-
tion)[11].Weperformedametaanalysisofhitsfromsevenlarge-scaleRNAistudiesinhuman
cells,identifying173geneswithantiviralactivityagainstHIV–1,influenza,hepatitisC(HCV),
WestNile,orenterovirusinfection(S3Table).IncontrasttoourexpectationthatRLRgenes
wouldbecommonamongtheseantiviralhostfactors,thisdatasetisoneoftheweakerpredic-
torsofRLRgenes:the173antiviralhostfactorscontainonlyasinglegene(IRF3)thatbelongs
tothesetof49knownRLRgenes(~2%)comparedto56of5,818non-RLRgenes(~1%,
2.1-foldenrichment,non-significantP=0.38,one-tailedFisher’sexacttest,Fig1Aand
Table1).
Pathway-basedsignatures
Co-expressionwithRLRpathway. ToaidinfindingnovelRLRgenes,wescreened>450
humanexpressionstudiesforgenesthatco-expresswithknownRLRpathwaycomponents
usingatwo-stepapproach[32].First,weweighedindividualexpressiondatasetsfortheir
propensitytopredictnewRLRgenes:experimentsinwhichthewholegroupofknownRLR
genesshowhighco-expressionwitheachotherreceivedahigherweightandcontributedmost
tothecalculations.Inthesecondstep,wecalculatedtheco-expressionofallgeneswiththe
RLRgenes.Asexpected,RLRgenesdisplaysignificantlyhigherco-expressionscoreswitheach
otherthanwiththerestofthegenomeorwithnon-RLRgenes(P(cid:1)10−27forbothcompari-
sons,one-tailedMann-WhitneyUtest,S4Fig).However,RLRgenesalsoscorehigher
thancomponentsofotherPRRsignalingpathways(Toll-likereceptor[TLR],C-typelectin
receptor[CLR],NOD-likereceptor[NLR],andcytosolicdsDNAsensing[cytDNA]pathways;
P=4.5×10−13,one-tailedMann-WhitneyUtest).Cross-validationbyleave-one-outanalysis
confirmsthattheweightedco-expressionapproachretrievesRLRgenesmorereadilythan
otherPRRpathwaygenes,orgenesinvolvedinotheraspectsofinnateimmunity(S4DFig),
demonstratingspecificityforidentifyingRLRgenesintheco-expressiondata.
RLRpathwayproteindomain. AnalysisofRLRpathwayproteinsequencesrevealedthe
presenceof40uniquedomains,25ofwhichweresignificantlyover-representedcomparedto
thefullhumanproteome(Benjamini-Hochberg-correctedFisher’sexactP<0.01,S4Table).
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IntegrativeGenomicsoftheRLRPathway
Theseincludeproteinkinasedomains(12-foldenrichment,P=1.1×10−8;presentinIKKα/β/
ε,MAPkinases,TBK1),theTBK1/IKKibindingdomain(TANK,TBK1BP1,AZI2),caspase
anddeathdomains(CASP8/10,FADD),IRFdomains(IRF3/7),andtheDExD/HboxRNA
helicasedomain(15-foldenrichment,P=2.7×10−3;RIG-I,MDA5,LGP2).Wethenassessed
thedomainorganizationsofallhumanproteinsanddeterminedasetof711proteinscontain-
ingoneormoreofthedomainsenrichedinRLRcomponents.Theseproteinsarepredictivefor
RLRcomponentswithanenrichmentscoreof8.9(Table1).
Innateantiviraltranscriptionfactor(TF)bindingmotifs. SignalingthroughtheRLR
pathwaytriggerstheactivationofkeytranscriptionfactors(TFs)likeIRF3,IRF7,AP–1and
NFκB.ActivationoftheseTFsleadstotheproductionoftypeIinterferonsandproinflamma-
torycytokinesthateventuallyactivateSTAT1andSTAT2[2].STAT1andSTAT2inturnstim-
ulatetranscriptionofinterferon-stimulatedgenes(ISGs),whichincludemanyRLRpathway
components.TofurtherexplorethetranscriptionregulationofRLRpathwaycomponents,we
analyzedtheirgenepromotersforthepresenceofTFbindingmotifsthatarehighlyconserved
acrossthegenomesof29placentalmammals,suchasprimates,rodentsandmanyfarmani-
mals[33].ConservedIRFandNFκBmotifsarehighlyabundantinthepromotersofRLR
genes(Fisher’sexactP=3.3×10−3andP=2.0×10−4,respectively;S5Table),suggestingthe
pathwayispartlyself-regulatingashasbeenobservedforindividualcomponents.Interestingly,
aconservedIRFmotifwasdetectednotonlyinthepromotersofIRF7itselfandinallthree
RIG-I-likereceptorfamilymembers(DDX58[RIG-I],IFIH1[MDA5],DHX58[LGP2]),but
alsoinTRIM25,ISG15,andCYLD;threefactorscontrollingRIG-Isignalingactivationbyregu-
latingthelevelofK63polyubiquitination.InordertopredictnovelRLRcomponents,we
searchedforgenescontainingconservedIRFbindingmotifs(severalmotifvariants,collectively
recognizedbyIRF1-9),STATbindingmotifs(severalmotifvariants,collectivelyrecognizedby
STAT1-6),AP–1bindingmotifs,orNFκBbindingmotifs(Fig1A).Wefound3,558genes
acrossthehumangenomecontainingoneofthesemotifsintheirpromoters.Thislargenum-
berpartiallystemsfromsimilaritiesintheDNAbindingpreferencesofTFsthatbelongtothe
samefamily,butdoesnotmeanthatallidentifiedgenesareregulatedbytheRLRpathway.For
example,STATmotifsnotonlyoccurinthepromotersofISGs,butalsoingenesinvolvedin
cellularproliferation,differentiationandapoptosis.Nevertheless,genescontainingoneofthe
fourconservedTFmotifsalreadyshowagoodpredictivevalueforRLRpathwaycomponents
(enrichmentscoreof2.2,S1Table).Geneswithmorethanonemotifareevenmorelikelytobe
RLRgenes:789genescontaintwomotifs(2.6-foldenrichment)and161genescontainthreeor
allfourmotifs(2.4-foldenrichment).
NFκBactivationmediator. HostfactorsthatregulateNFκBactivationoftenalsoaffect
theRLRpathway.Indeed,the154hitsthatwerepickedupinagenome-widesiRNAscreenof
Epstein-Barrvirus-inducedNFκBactivation[34]includeamuchlargerfractionofknownRLR
genes(6/49=12%)thannon-RLRgenes(36/5,818<1%,20-foldenrichment,P=1.0×10−6,
one-tailedFisher’sexacttest,Fig1AandTable1).Thus,these154NFκBactivationmediators
arelikelytocontainnovelRLRpathwaycomponentsaswell.
RLRpathwayPPI. Finally,tofindnovelRLRgenesweassessedthehumanproteininterac-
tionnetworkconnectingtheRLRpathway.PPIdatabases[35]report3,504interactionsbetween
1,750uniqueproteinsand47ofthe49RLRcomponents,theonlyexceptionsbeingDAKand
NLRX1.Ofthe47RLRproteinswithreportedPPIs,41areinvolvedinatotalof147interactions
withinthepathway(i.e.betweentwopathwaymembers).ThisnetworkofRLRcomponentshas
significantlymoreconnectionswitheachotherthandorandomnetworksofthesamesizeand
interactiondegreedistribution(physicalinteractionenrichmentscore=3.6,P<1.0×10−6[36]).
UsingthePPIdata,weobtainedforeachhumanproteinthenumberofinteractingRLRpathway
components(Fig1A).Wefoundatotalof1,397proteinsreportedtointeractwithoneortwo
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IntegrativeGenomicsoftheRLRPathway
RLRproteins.TheseproteinsarepredictiveforRLRcomponentswithanenrichmentscoreof1.8
(S1Table).Afurther221proteinsinteractwiththreeoffourRLRproteins(6.3-foldenrichment)
and132proteinsinteractwithfiveormoreRLRproteins(15.8-foldenrichment).TBK1(18inter-
actions),TRAF2andMAVS(both16)topthelist,supportingtheirrolesascentralplayersinthe
RLRsystem[12].Thus,anincreasingnumberofinteractionswithRLRproteinsindicatesa
higherlikelihoodthataproteinispartoftheRLRpathway.
Bayesianintegrationofmolecularsignaturesprovidesgenome-wide
probabilitiesforRLRpathwaycomponents
TheRLRpathwaycomponentspublishedthusfarprobablyconstituteonlypartofthetotal
proteinswithafunctioninthispathway.Toprioritizenovelhigh-confidencegenesforarolein
theRLRpathway,weintegratedthe10identifiedmolecularsignaturesofRLRgenesinanaive
Bayesianclassifier[18,19](seeMethods).Thisapproachweighsdatasetsbasedontheirpre-
dictivevalue(i.e.theirabilitytoseparateknownpositivesandnegatives;Fig1A,Tables1and
S1)sothat‘better’datacontributemoretothepredictions.Eachhumangenereceivedaposte-
riorprobabilityscore(‘RLRscore’)reflectingthelikelihoodthatthegeneispartoftheRLR
pathwaybasedonitsbehaviorinthecollectedgenomicsdata.Ascoreofzeroindicatesequal
probabilitiesofagenebeinganRLRversusanon-RLRgene.S6Tablepresentsthegenome-
widerankingofRLRscores(alsoavailableathttp://rlr.cmbi.umcn.nl/).
Asexpected,knownRLRpathwaycomponentshavethehighestRLRscores(Figs1Band
S5).Two-thirds(32/49)oftheserankwithinthefirst150genes.Thetoprankinggenesare
IRF7,RIG-I,IKKε,subunitsofNFκB,TRADD,TRAF2,MDA5,andIKKγ(NEMO)(Fig1C).
Otherexamplesofwell-describedRLRpathwaycomponentsincludeIRF3(rank51),ISG15
(52),MAVS(102),andLGP2(114).Genesthatareunlikelytoplayaroleinthepathway(the
setofnon-RLRgenes)generallyhaveverylowRLRscores,althoughsomeofthesereceived
highscoresaswell(Fig1B).Thisisnotunexpected,aseventhoughthislargesetofgeneswas
selectedfromfunctionannotationsgenerallyunrelatedtotheinnateantiviralresponse,this
doesnotprecludethatindividualgenes(also)functionintheRLRpathway.
TogaininsightintowhatkindofgenesarepresentamongtheRLRpredictions,weexamined
theirfunctionsbypathwayandgeneontologyenrichmentanalyses.Thetop354geneswiththe
highestRLRscores(correspondingtohigh-confidencepredictions,seebelow)havestronglinks
withotherpathwaysoftheinnateimmuneresponse,suchasTLR,NLR,interferon,andcytokine
signaling(S6andS7Figs).Antiviraldefensefunctionsarealsoamongthemostfrequentandsig-
nificanttermsassociatedwiththehigh-scoringgenes(S8FigandS7Table).Otherimportant
biologicalprocessesincludevariousapoptosis-relatedfunctions,cancerandcellcyclepathways,
andregulationofmetabolicprocessesandproteinlocalization.Furthermore,thetoppredictions
includeawiderangeofproteinfamilies,notablyproteasomesubunits,ubiquitin(-like)conjugat-
ingenzymes,andgenesinvolvedinphosphatidylinositolsignaling(whichwasrecentlyshownto
affectthetypeIIFNresponse[14]).Finally,22%ofthetoppredictionsareinducedincells
treatedwithinterferons(i.e.theyareinterferon-stimulatedgenes,ISGs)and~18%arepartofthe
commonhosttranscriptionresponsetopathogens(Table2).Together,theseobservationsindi-
catethatourframeworksuccessfullypredictsgeneswithalikelyroleintheinnateantiviral
responseandsuggestsothercellularsystemsandfunctionsrequiredforthisresponse.
Performanceestimatesandindependentdataestablishthereliabilityof
theRLRscore
WefurthercomputationallyassessedthereliabilityoftheintegratedRLRscorebyestimating
thesensitivity,specificityandfalsediscoveryrate(FDR)ofthepredictionsusingthepositive
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IntegrativeGenomicsoftheRLRPathway
Table2. Overlapbetweeninnate(antiviral)responsedatasetsandthetop354RLRpredictionsexcludingknownRLRgenes.
Dataset References Numberofgenes Fraction(number)ofdatasetgenes One-tailedFisher’s
indataset intop354predictions exactP
Interferon-stimulatedgenes(ISGs) [16] 354 22.0%(78) 1.2×10−67
ISGswithvalidatedantiviralactivity [16,91] 45 42.2%(19) 4.9×10−23
Commonhosttranscriptionresponseto [92] 496 17.7%(88) 5.2×10−68
pathogens
InteractorsofthetypeIIFNproteinnetworkduring [12] 241 11.2%(27) 1.2×10−15
patternrecognition(HCIP)a
HCIPwithconfirmedeffectsonIFNβexpression [12] 22 22.7%(5) 1.9×10−5
andantiviralactivity
Tripartitemotif(TRIM)familygenes [17] 71 12.7%(9) 1.6×10−6
TRIMsthatenhanceRIG-I-inducedactivationof [17] 34 14.7%(5) 1.7×10−4
IFNβ,NFκBandISREpromoters
Humaninteractorsofinnateimmune-modulating [37] 569 6.7%(38) 4.7×10−14
viralORFsb
GenesexpressedinPBMCsstimulatedwith [38] 89 43.8%(39) 4.7×10−47
Candida(CRG)
CRGwithalteredexpressioninCMCpatients [38] 23 65.2%(15) 2.6×10−22
TypeIIFNresponsemediators [14] 226 4.0%(9) 9.5×10−3
aThesePPIswerenotpartoftheRLRinteractionnetworkusedfortheRLRpredictions(i.e.forthe‘RLRpathwayPPI’signature)
bTheseinteractionswerenotusedtodeterminethevirus-interactinghumanproteinsusedfortheRLRpredictions(i.e.forthe‘PPIwithviruses’signature)
doi:10.1371/journal.pcbi.1004553.t002
(RLRgenes)andnegative(non-RLRgenes)standards.Integrationofthedatasetsachievedbet-
tersensitivityandspecificitythananyoftheindividualdatasets(Fig1D),therebyenriching
forRLRgenesanddepletingfalsepositives(S5,S9andS10Figs).AtanRLRrankthresholdof
354(RLRscore-1.10),theframeworkcorrectlypredicts78%oftheknownRLRgeneswitha
specificityof98.4%(Fig1D).Atthisthreshold,only~57%ofthenovelpredictionsareesti-
matedtobefalse(S11Fig,adjustedFDRtomatchtheexpectedtotalnumberofgenesinvolved
intheRLRpathway,seeMethods).Thiscomparestoagenome-widefalsediscoveryrate
(i.e.whenpredictinggenesrandomly)of~99%.Thus,theintegratedRLRscoreincreasesthe
probabilityofcorrectlyidentifyingnovelRLRgenesbyafactorof43comparedtorandom
classification.
BecauseweusedthesamegenesetsforcalculatingtheRLRscoresandestimatingtheper-
formanceoftheresultingpredictions(i.e.withoutsystematiccross-validation),thereexistsa
dangerofcircularreasoning.Therefore,wealsocarefullyvalidatedthequalityoftheresults
usingvariousindependentandexternaldatasets.First,weexaminedthehighRLRscoresfor
genesthathaveaknownfunctionininnateimmunity,butnotintheRLRpathway,andthere-
forewerenotpartofourtrainingset.ComponentsofotherPRRsignalingpathways(TLR,
CLR,NLR,cytDNA)havelowerscoresthanRLRgenes,butmuchhigherscoresthantherest
ofthegenome(Fig1B).Thesameistrueforgenesfunctioninginotheraspectsoftheinnate
immuneresponse(Fig1B).Ofthe225novelpredictions(i.e.thosegenesthatarenotpartof
thetrainingsets)inthetop354(FDRof57%,seeabove),142(~63%)arepartoftheseinnate
immunitygenelists(Fig1C).Thus,themajorityofhigh-scoringgeneswithnoknownlinkto
theRLRpathwayinfacthaveafunctioninotherPRRpathwaysorotherpartsofinnateimmu-
nity,supportingtherelevanceofourpredictions.
Second,wecomparedourpredictionstosixrecentdatasetsthatarerelevanttotheinnate
(antiviral)responsebutthatwereinnowaypartoftheRLRscorecalculations.Theoverlap
withthe354topgenes,excludingknownRLRgenes,issignificantlylargerthanexpectedby
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IntegrativeGenomicsoftheRLRPathway
chanceforallthesedatasets(Table2).Forexample,thetoppredictionsinclude:(i)19of45
(42%)interferon-stimulatedgeneswithvalidatedantiviralactivityagainste.g.HIV–1,HCV,
yellowfever,WestNileorchikungunyavirus[16],(ii)27proteinsfromasetof241(11%)that
interactwiththetypeIIFNproteinnetworkduringpatternrecognition,amongwhicharefive
confirmedmodulatorsofIFNβexpressionandantiviralactivity[12],(iii)ninetripartitemotif
(TRIM)familygenes,fiveofwhichenhanceRIG-I-inducedactivationofIFNβ,NFκBand
ISRE(IFN-stimulatedresponseelement)promoters[17],and(iv)38humanproteinsinteract-
ingwithinnateimmune-modulatingviralopenreadingframes(viORFs)from30viruses[37].
(v)Furthermore,thetypeIIFNresponsehasrecentlybeenproposedtoplayaroleinantifun-
galimmunity[38,39]andthetopRLRpredictionsarestronglyenrichedforgenesexpressedin
PBMCsstimulatedwiththefungalpathogenCandidaalbicans:almosthalf(39/89=44%)
oftheseoccurinourtoppredictions(P=4.7×10−47,one-tailedFisher’sexacttest,Table2).
(vi)Finally,theoverlapbetweenourpredictionsandagenome-widescreenforregulatorsof
RIG-I-mediatedIFNβproductionis,atonlynine,marginalbutsignificant(9/226genes=4%,
P=9.5×10−3,one-tailedFisher’sexacttest,Table2)[14].Insummary,thesediverseandinde-
pendentexperimentaldatasupportthevalidityofourintegratedRLRscoreforpredicting
geneswitharoleintheinnateantiviralresponse.
RNAivalidationscreensconfirmthehighpredictivevalueofthe
integratedRLRscore
Tofurtherdeterminethepredictivepowerofourinsilicopredictions,weselected187candi-
dateRLRgenesforexperimentalvalidation(S6andS8Tables).Theseinclude127high-confi-
dencecandidatesfromthetop354,whichhavenotbeenpreviouslylinkedtotheRLRpathway,
supplementedwith60candidatesweselectedfromthetop1000predictions,mainlyonthe
basisoflimitedfunctionalcharacterizationingeneral(Fig2A).Importantly,candidateswitha
knownroleinRLRsignaling,otherbranchesofPRRpathways,orapoptosiswereexcludedas
weweremostinterestedinfindingnovelcomponentsoftheRLRpathway.
Fortheselectedcandidatesweperformedamedium-throughputRNAiscreen(RNAiscreen
1)usingHeLacellsstablyexpressinganIFNβpromoter-controlledfireflyluciferasereporter
(HeLa-IFNβ-Fluc).ToactivatetheRLRpathwayandinduceFlucreporterexpressionweused
aknownsmall5’-ppp-containingRIG-Iligand[40].Thissetupledtospecificactivationof
RIG-I,asRIG-IorMAVSsiRNAtransfection,butnotMDA5orscrambledsiRNAs,resulted
inlossofreporteractivity(Figs2B,S12andS13).Allnegativecontrols(non-transfected,
scrambledandMDA5siRNAs)scoredwithin1.25medianabsolutedeviationsoftheplatenor-
malizedIFNβinductionlevels(Z-scorecutoff<-1.25or>1.25,Fig2B).Atthiscutoff,siRNA
knockdownof94candidates(50%ofallcandidatestested)affectedRIG-I-mediatedIFNβ
induction(Figs2AandS13A–S13DandS8Table).Amongthese,knockdownof59genes
decreasedRIG-I-mediatedIFNβinduction(down-hits)and35genesincreasedIFNβinduction
(up-hits).ItisimportanttonotethattheexperimentalapproachonlyactivatestheRIG-I
branchoftheRLRpathwayandwillnotconfirmpredictedRLRcandidatesthatregulate
MDA5activationanddownstreamsignalingtoMAVS.Thus,amongthe93non-confirmed
candidates,theremightstillbenovelregulatorsoftheMDA5-mediatedIFNβinductionpath-
way,whichshouldbefurtherinvestigated.Altogether,theintegratedRLRscoreisclearlya
strongandreliablepredictorfornovelregulatorsoftheRIG-Ipathway.
Fromthe94confirmedhits,wepickedthe57tophitswiththelargesteffect(stringentZ-
score<-2or>2)forasecondRNAiscreenusingadifferentsetofsiRNAs(RNAiscreen2,
Fig2A).InthissecondRNAiscreen,onlyasingleup-hit(7%of15up-hitstested)showedaZ-
score>1.25.Besidesthishit,twonegativecontrolwellsalsohadaZ-score>1.25(Figs2B,
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