Genome-wide DNA methylation profiles in hematopoietic stem and progenitor cells reveal ...

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Research
Genome-wide DNA methylation profiles in
hematopoietic stem and progenitor cells reveal
overrepresentation of ETS transcription factor
binding sites
Amber Hogart,1 Jens Lichtenberg,1 Subramanian S. Ajay,2 Stacie Anderson,1,3
NIH Intramural Sequencing Center,4 Elliott H. Margulies,2 and David M. Bodine1,5
1GeneticsandMolecularBiologyBranch,NationalHumanGenomeResearchInstitute,NationalInstitutesofHealth,Bethesda,
Maryland20892,USA;2GenomeTechnologyBranch,NationalHumanGenomeResearchInstitute,NationalInstitutesofHealth,
Bethesda,Maryland20892,USA;3FlowCytometryCoreFacility,NationalHumanGenomeResearchInstitute,NationalInstitutes
ofHealth,Bethesda,Maryland20892,USA;4NIHIntramuralSequencingCenter,NationalHumanGenomeResearchInstitute,
NIH,Rockville,Maryland20852,USA
DNAmethylationisanessentialepigeneticmarkthatisrequiredfornormaldevelopment.KnockoutoftheDNAmethyl-
transferaseenzymesinthemousehematopoieticcompartmentrevealsthatmethylationiscriticalforhematopoieticdiffer-
entiation. To better understand the role of DNA methylation in hematopoiesis, we characterized genome-wide DNA
methylationin primarymouse hematopoieticstem cells (HSCs), commonmyeloid progenitors(CMPs),and erythroblasts
(ERYs).Methylbindingdomainprotein2(MBD)enrichmentofDNAfollowedbymassivelyparallelsequencing(MBD-seq)
was used to map genome-wideDNAmethylation. Globally,DNA methylationwas most abundant in HSCs, witha 40%
reductioninCMPs,anda67%reductioninERYs.Only3%ofpeaksariseduringdifferentiation,demonstratingagenome-
widedeclineinDNAmethylationduringerythroiddevelopment.Analysisofgenomicfeaturesrevealedthat98%ofpro-
moterCpGislandsarehypomethylated,while20%–25%ofnon-promoterCpGislandsaremethylated.Proximalpromoter
sequencesofexpressedgenesarehypomethylatedinallcelltypes,whilegenebodymethylationpositivelycorrelateswith
geneexpressioninHSCsandCMPs.Elevatedgenome-wideDNAmethylationinHSCsandthepositiveassociationbetween
methylationandgeneexpressiondemonstratesthatDNAmethylationisamarkofcellularplasticityinHSCs.Usingdenovo
motifdiscovery,weidentifiedoverrepresentedtranscriptionfactorconsensusbindingmotifsinmethylatedsequences.Motifs
forseveralETStranscriptionfactors,includingGABPAandELF1,areoverrepresentedinmethylatedregions.Ourgenome-
widesurveydemonstratesthatDNAmethylationismarkedlyalteredduringmyeloiddifferentiationandidentifiescritical
regionsofthegenomeandtranscriptionfactorprogramsthatcontributetohematopoiesis.
[Supplementalmaterialisavailableforthisarticle.]
Epigeneticmechanismsofgeneregulationareheritable,reversible Methyl-binding domain proteins are a family of DNA-binding
modificationsthatarecriticalfortheorganizationofchromatin proteins that recognize methylated DNA and modify gene ex-
and regulation of tissue-specific geneexpression.DNA methyla- pression by forming complexes with other regulatory proteins.
tionisadynamicepigeneticmarkprimarilylocalizedtocytosine StudiesofmouseknockoutmodelsoftheMBDproteinsdemon-
residuesinthecontextofaCpGdinucleotideinmammals.Tar- strate unique but nonessential roles for most of these proteins
geteddisruptionofthegenesresponsiblefordenovomethylation (Bogdanovic and Veenstra 2009). Of the MBD proteins, MBD2
and maintenance of DNA methylation during replication dem- appearstoplayanimportantroleinhematopoiesis,withspecific
onstratethatDNAmethylationisessentialforproperdevelopment rolesinglobingeneswitching(Ruponetal.2006).
inthemouse(Lagetetal.2010;Maetal.2010).Whilethecritical Thehematopoieticsystemisidealforthestudyofmethyla-
role for DNAmethylationin early development is clearlyestab- tionduringdifferentiationbecauseprimarycellsatspecificstages
lished,theroleforDNAmethylationintissuespecificationisless canbeseparatedfromotherhematopoieticcellsbyflowcytometry.
understood. Thehematopoieticstemcell(HSC)givesrisetoallcellsinthepe-
DNAmethylationhaslongbeenrecognizedasanimportant ripheralblood.Thecommonmyeloidprogenitor(CMP)generates
markinestablishingandmaintainingimprintedgeneexpression onlymyeloidcells(redcells,platelets,granulocytes,monocytes,
and X-chromosome inactivation. Apart from these specialized andeosinophils),butnotlymphoidcells(T-andB-lymphocytes).
roles for DNA methylation, little is known about how DNA Erythroblasts(ERYs)arenucleatedredbloodcellsthathavecom-
methylationleadstomoregeneralalterationsingeneexpression. mittedtoterminaldifferentiation.Conditionalknockoutmicein
whichthegenesforthedenovomethyltransferasesDnmt3aand
Dnmt3baredeletedinHSCsretaintheabilitytodifferentiateinto
5Correspondingauthor bothmyeloidandlymphoidlineages,butlong-termrepopulation
[email protected]
of the hematopoietic system is impaired (Tadokoro et al. 2007).
Articlepublishedonlinebeforeprint.Article,supplementalmaterial,andpub-
licationdateareathttp://www.genome.org/cgi/doi/10.1101/gr.132878.111. SerialtransplantationofDnmt3adeficientHSCsrevealedimpaired
22:1407–1418 (cid:2)2012,PublishedbyColdSpringHarborLaboratoryPress;ISSN1088-9051/12;www.genome.org GenomeResearch 1407
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Hogart et al.
differentiation as well asimpaired repopulation (Challen et al.
2012).Similarly,conditionalknockoutmiceinwhichthegene
forthemaintenanceDNAmethyltransferaseDnmt1isdeletedin
HSCs demonstrated severe impairment of repopulating ability
and inappropriate enhancement of mature myeloid lineages
(Broske et al. 2009; Trowbridge et al. 2009). Together these
studies demonstrate a profound role for DNA methylation in
hematopoiesis.
WhiletheimportanceofDNAmethylationinhematopoietic
differentiationhasbeenwellestablished,thegenome-widelocal-
izationofmethylatedDNAatspecificstagesofmyeloiddifferen-
tiationremainstobeelucidated.Recentadvancesinsequencing
technology have allowed comprehensive surveys of DNA meth-
ylationwithvaryingdegreesofresolution.Thehighest-resolution
techniquesusebisulfitesequencingapproachesthathavethead-
vantageofsingle-baseresolutionbutdonotdistinguishbetween
5-methylcytosineand5-hydroxymethylcytosine(Kriaucionisand
Figure1. OverviewofMBDsequencingresults.(A)Schematicrepre-
Heintz2009;Tahilianietal.2009).Inthisstudy,weusedarecombi- sentationofhematopoiesishighlightingthethreecelltypesenrichedfor
nant methyl-binding domain protein to enrich 5-methylcytosine methylation analysis. HSC and CMP cell populations were lineage de-
modified regions of the genome for massively parallel sequence pleted(Lin(cid:2))andthenpositivelyselectedwiththecellsurfacemarkers
Sca1andc-kit.Erythroblastcellswerepositivelyselectedwithantibodies
analysis(MBD-seq).Usingthisapproach,wecomparedgenome-
forTer119andCD71.(B)Totalnumberofmethylationpeakscalledineach
widemethylationinpurifiedpopulationsofmurineHSCs,CMPs, ofthethreecellpopulations.(C)Totalmethylationpeakcountperchro-
andERYs.Byfocusingonmethylationchangesdefinedbypeaks mosomeforeachcellpopulation:HSC(blue);CMP(orange);ERY(red).
asopposedtosite-specificmethylation,wewereabletoidentify
discrete regions of the genome where dynamic methylation
changesoccurduringhematopoiesis.Ourstudyrevealsthatthe Toquantifygenome-wideDNAmethylationlevels,mapped
greatestnumberof methylation peaksoccursinHSCsandthat sequencingreadswereanalyzedtodeterminestatisticallysignifi-
thesepeaksarespecificallyandsuccessivelylostduringmyeloid cant peaks of methylation. In a conservative filteringapproach,
differentiation,consistentwiththebiasinmyeloidlineagesseen MBD-seqpeakswerecallediftheywerepresentinbothbiological
in Dnmt1 knockout mice (Broske et al. 2009; Trowbridge et al. replicatesand overlappedby at least200 bp.The average distri-
2009).Theidentificationofregionswheremethylationchanges bution of peak lengths was also investigated, with the average
duringhematopoiesiswillfacilitatemechanisticstudiesofhow peaks occupying slightly more than 800 bp in each cell type
DNAmethylationregulateshematopoieticdifferentiation. (SupplementalTableS2).Comparisonofoverallpeakcountfrom
eachcelltyperevealedthatDNAmethylationpeaksweremost
abundant in HSCs (85,797), with decreasing levels in CMPs
Results
(50,638) and fewer in ERYs (27,839) (Fig. 1B). The decrease in
methylation reflects a global genomic decrease that is demon-
Genome-wideDNAmethylationdeclinesduringmyeloid
stratedbythesimilarrelativedistributionofmethylationpeakson
differentiation
eachchromosomebetweencelltypesdespitethereductioninthe
Whole-genome sequencing in human embryonic stem cells has total number of methylation peaks (Fig. 1C). Among the auto-
demonstratedthatasmuchas80%ofallCpGdinucleotidesinthe somes,chromosome5hasthegreatestnumberofDNAmethyla-
genomearemethylated(Laurentetal.2010),yetitisunlikelythat tionpeaksinallcelltypes,whilethefewestnumberofpeakswas
allofthesesitesarerelevanttodifferentiation.MBD-seqidentifies foundonchromosome19.TheXchromosomeissubjecttoran-
regions of the genome bound by a DNA methylation-binding domX-chromosomeinactivationinfemales,aprocessassociated
protein, highlighting loci containing multiple methylated CpG withDNAmethylation.WhileallanimalsincludedintheHSCand
sites.RecombinantMBD2pull-downofmethylatedgenomicDNA CMP data sets were female, the fetal tissues used for ERY also
combinedwithmassivelyparallelsequencingwasusedtoidentify includedmalesresultinginaslightlylowerdensityofpeaksonthe
methylatedgenomiclociinenrichedpopulationsoflineageneg- XchromosomeinERYs.
ativeSca1+c-kit+cells(apopulationofcellsenrichedforlong-and BothinsilicovalidationofCpGcontentwithinpeaksaswell
short-term HSCs and multipotent progenitors, which we have asbisulfitesequencingofselectedpeakswereperformedtovalidate
designatedasHSCs),commonmyeloidprogenitors(CMPs),and that the MBD-seq approach specifically recognizes methylated
erythroblasts(ERYs)(Fig.1A).Twobiologicalreplicateswerein- DNA.ThedistributionofpeaklengthisshowninSupplemental
cludedforeachofthethreecelltypeswiththetotalnumberof TableS2,andthedistributionofCpGcontentisshowninTableS3.
readsrangingfrom32to46million.Acompletesummaryofthe Atleast99.96%ofallpeakscalledcontainedoneCpGsitewiththe
sequencing reads is provided in Supplemental Table S1. Non- average CpG count rangingfrom 21 to 24 CpGs per peak (Sup-
enrichedgenomicDNAwassequencedtodetermineastandard plemental Table S3). Random sampling of sequences of similar
backgroundforsubsequentanalysis.SupplementalFigureS2il- length revealed that the MBD-enrichment approachresults in a
lustratesthesequencingresultsforaregioncontainingtheim- statisticallysignificanthigherpercentageofpeakswithCpGsites
printingcontrolregionoftheimprintedgeneSnrpn.Consistent thanisexpectedbychance(P-value=0.00507)andwithasignifi-
with the observation that Snrpn is imprinted within all cells, cantly higher average CG content (P-value = 0.00391). Bisulfite
specificpeaksofDNAmethylationweredetectedinallthreecell sequencingof10genomiclocicontainingMBD-seqpeaks(fivecom-
types. montoallthreedatasets,fourpeaksuniquetoHSCsorprogenitors
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Genome-wide DNA methylation in hematopoiesis
[HSCs+CMPs],andonepeakuniquetoERYs)werefoundtohave largestcategorywaspeakspresentinHSCsandCMPs,butabsentin
atleast47%methylationattheCpGsitesperregioninvestigated ERYs(progenitor;27%).Approximately3%ofthetotalmethyl-
with an average of ;80% methylation (Supplemental Fig. S5; ation peaks were unique to either ERYs or CMPs, and an even
SupplementalTableS4).Bisulfitesequencingatgenomicregions smallerfractionofpeaks(0.3%)wereabsentinHSCsbutpresentin
thatwerenotidentifiedasstatisticallysignificantpeaksrevealedan the more differentiated cell types (myeloid). Figure 3A demon-
averageof30.7%methylatedCpGsites,consistentwiththeob- strates examples of HSCs and progenitor-specific methylation
servationthatCpGmethylationisrelativelycommonthroughout peaks upstream of the important hematopoietic transcription
thegenome.Thepresenceoflow-to-intermediatelevelsofmeth- factorgeneGata2.AnexampleofanERY-specificpeakintheMeis1
ylationinregionsexcludedfrompeaksconfirmsthattheMBD-seq locus is shown in Figure 3B. Overall, the distribution of peaks
approach identifies regions of the genome with high-density withineachofthecelltypesdemonstratesaprogressiveglobalde-
methylation.AnadditionalvalidationofourMBD-seqdatasetwas creaseinmethylationduringdifferentiationwithlittleacquisitionof
achieved by comparing our methylation peaks to the recently newmethylationpeaksduringthelaterstagesofdifferentiation.
published(Shearstoneetal.2011)reducedrepresentationbisulfite
sequencing(RRBS)datafrommouseerythroblasts.Supplemental
DNAmethylationisoverrepresentedinthecodingportion
Figure S6 shows the degree of overlap between the erythroblast
ofthegenome
MBD-seqpeaksandtheRRBSdata.Consistentwiththeconven-
tionalbisulfitesequencingvalidation,theoverlapbetweenthetwo We next investigated the genomic distribution of methylation
datasetsincreasesdramaticallywhentheRRBSvaluesexceed30%– peaks. The genome was divided into five partitions defined by
40%methylation(SupplementalFig.S6). RefSeq genes. The proximal promoter was defined as sequences
Becauseglobal DNA methylation peaks decrease with mye- 1kbupstreamofthetranscriptionstartsite(TSS)throughthefirst
loid differentiation, we determined whether methylation peaks 50bppastthetranscriptionalstartsite.Genebodymethylation
were shared among the cell types or whether the peaks were wasdefinedbytheRefSeqgenecoordinatesminusthefirst50bp
unique to each of the three cell types. Seven categories of DNA pasttheTSS.Additionally,welookedatthe10-kbregionsupstream
methylationpeaksbasedonpresenceinoneormorecelltypesare of and downstream from gene boundaries because we expected
showninFigure2.ThelargestcategoryofDNAmethylationpeaks, theseflankingsequencestoalsocontaincisregulatoryelements.
composingnearly40%ofallpeaks,wereuniquetoHSCs.Meth- Theremainderofthegenomeconstitutestheintergenicpartition.
ylationpeakscommontoallthreecelltypeswerethenextlargest Thedistributionofmethylationpeaksineachcell-typecategory
category, representing 28% of all methylation peaks. The third was compared with the relative percentage of sequence in each
partitiontothetotalnonrepetitiveportionofthegenome(geno-
micaverage).Significantdeviationfromtheexpecteddistribution
wasobservedforcommonpeaksandforpeaksinallmultipotent
categories(Table1).Anoverrepresentationofmethylationpeaks
wasseenintheRefSeqportionofthegenome,andmethylation
peakswereunderrepresentedinintergenicsequences.Methylation
peaks were overrepresented in the downstream flanking regions
and were similar to the expected percentage in both the distal
promoterand59-flankingregionsinallpeakcategories.
WenextinvestigatedthedistributionofpeakswithintheRefSeq
portionofthegenome.TheRefSeqsequencesweredividedintofour
categories: 59-untranslated sequences (8.7%), 39-untranslated se-
quences(6.8%),exons(5.3%),andintrons(79.2%).Althoughexons
represent;5%ofthegenesequence,methylationpeaksweresig-
nificantlyoverrepresentedin theexons(7%–25%ofall thegenic
DNAmethylationpeaks)(Table1)andunderrepresentedinthein-
tronsinmostcategories.Sincethenumberofpotentialmethylation
sitesisvariablewithingenicregions,wenextdeterminedtherelative
contributionofCpGdinucleotidesineachpartitionandcompared
this with peak distributions. Table 2 demonstrates that MBD-seq
peakdensitydoesnotfollowCpGdistribution,becausemethylation
peaksexceedtherelativecontributionofCGinbothexonsandin-
trons,whilemethylationpeaksarefoundatlessthantheexpected
frequencyinboththe59and39UTRcompartments(Table2).
CpGislandmethylationisrareinhematopoieticstem
cell–specificpeaks
Figure2. Analysisofpeaksharingbetweencellpopulations.(A)Venn
diagramillustratingthedegreeofoverlapinmethylationpeaksbetween Previous studies have shown that CpG islands in characterized
cellpopulations.(B)Totalpeakcountforeachcellpopulation,thenumber promotersofgenesremainunmethylatedinmostinstances,while
ofpeakssharedbetweeneachcelltype,andthepercentagethateach CpGislandsnotassociatedwithknownpromoters,orphanCpG
categorycontributestothetotalnumber.Progenitorpeaksaredefinedas
islands,aremuchmorelikelytobemethylated(Illingworthetal.
presentinHSCsandCMPsbutabsentinERYs.Myeloidpeaksareabsentin
HSCsbutpresentinCMPsandERYs.(Other)Peaksthatwereabsentinthe 2010).ConsistentwithapreviousreportofmethylatedCpGislands
CMPbutpresentinHSCsandERYs. inwholemouseblood(Illingworthetal.2010),wefound;2%of
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Figure 3. MBD-seq peaks at selected loci. UCSC Genome Browser view of the Gata2locusonChr6(A)andtheMeis1locusonChr11(B).Raw
sequencingdataforeachcellpopulation:blue(HSC),orange(CMP),andred(ERY),withsignificantpeaksshownasblackbarsbeloweachsample.The
y-axisindicatespeakheight,definedbythemaximumnumberofsequencingtagsseeninthehighestvisiblepeakineachwindow.Transcriptionfactor
consensussites(TRANSFACIDs)areindicatedabovetheMBD-seqdatainregionsofsignificantpeaks.ThegenestructureisindicatedbelowtheMBD-seq
datawithCpGislandsshowningreen.Bisulfitesequencingdataconfirmingthecell-type-specificmethylationareshownbelow.(Blackcircles)Methylated
CpGsites;(opencircles)unmethylatedCpGsites.Eachhorizontallineindicatesauniqueclone.
promoterCpGislandsmethylatedinHSCs,andasmallerpercent in the progenitor category (HSCs + CMPs) compared with com-
methylated in the more differentiated hematopoietic cell types monandHSC-specificpromoters(Fig.4B).Incontrast,themeth-
(Fig.4A).OrphanCpGislandswerearound10-foldmorelikelyto ylation of orphan CpG islands varied between peak-type cate-
bemethylatedineachofthecelltypes,consistentwiththegreater gories.ThelargestpercentageofmethylatedorphanCpGislands
roleintissue-specificmethylation. wasamongthecommonmethylation peaks(20%) (Fig.4B).Al-
Investigation of cell-type-specific methylation peaks revealed thoughHSCisthemostmethylatedcelltype,thepercentageof
thatthevastmajorityofallpromoterCpGislandsareunmethylated HSC-specificmethylationpeaksinorphanCpGislandswas10-fold
inallcategories.Increasedpromoter-associatedmethylationobserved less than common peaks and around threefold lower than the
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Genome-wide DNA methylation in hematopoiesis
Table1. Distributionofmethylationpeaksingenomicpartitions(%inpartition)
Distal Proximal
promoter promoter RefSeq 59UTR Exon Intron 39UTR Downstream Intergenic P-value
Genomicaverage 7.22 0.84 36.12 8.72 5.29 79.15 6.84 7.69 48.13
Common 9.13 2.11 52.16 8.13 24.72 61.39 5.76 13.36 23.24 1.61303310(cid:2)18
HSC 8.46 1.40 47.90 7.89 11.14 74.84 6.13 11.00 31.23 0.016898107
Progenitor 8.47 2.93 45.51 8.88 14.83 69.77 6.52 10.87 32.23 7.02049310(cid:2)05
CMP 6.82 2.35 42.65 8.36 11.84 73.40 6.41 10.76 37.41 0.04120891
Myeloid 7.41 1.54 32.10 12.75 6.86 78.43 1.96 9.57 49.38 0.5006945
ERY 8.62 1.55 40.95 7.30 7.51 78.90 6.29 11.72 37.16 0.501189395
progenitor category (Fig. 4B). These results suggest that the re- Furtheranalysisofgeneswithmethylationinthreeormorepar-
quirementofDNAmethylationformaintenanceofHSCsisnot titionsrevealedthat10-foldmoreexpressedgeneshadmethyla-
primarilyduetosilencingofgenesviamethylatedCpGislands. tioninthegenebodyandflankingregionsthaninallfourparti-
tions in each of the three cell types. Therefore, while proximal
DNAmethylationinexpressedgenesvaries promotermethylationisrareinexpressedgenes,methylationinthe
bygenomicpartition genebodyandflankingregionsoutsideoftheproximalpromoter
occursofteninexpressedgenes.
To investigate the role that DNA methylation plays in gene ex-
pression,wecomparedthegenomicdistributionofDNAmethyl-
Denovomotifdiscoveryrevealsdifferentiallymethylated
ationpeakstogeneexpressiondataobtainedfromBloodExpress,
adatabasecontaininggeneexpressionprofilesfromalargenum- transcriptionfactorbindingsitesignaturesofhematopoietic
ber of mouse hematopoietic cell types (Miranda-Saavedra et al. differentiation
2009).BasedongeneexpressionprofilesformouseHSC,CMP,and Toelucidatedevelopmentalprogramspotentiallymodifiedbythe
ERY cell types, thegreatestnumberof genesis expressedin the presenceofDNAmethylation,weinvestigatedthesequencesun-
HSCs(8594),followedbyCMPs(7122),andthefewestnumberof derneath the methylation peaks for recurring motifs. De novo
expressed genes are seen in ERYs (4223). Peaks assigned to the motifdiscoverywasperformedonalldatasetsandgenomicpar-
upstream10kb,proximalpromoter,RefSeqgeneboundary,and titions independently. The top 25 overrepresented motifs were
downstream10kbwerecomparedinexpressedgenes.Consistent queried againstthe TRANSFAC (Matys et al.2006) transcription
with the observations of Hodges et al. (2011), the majority of factordatabase,andtranscriptionfactorswithcharacterizedbinding
expressed genes lacked methylation peaks in the proximal pro- sites were identified. Figure 6 contains a summary of the tran-
moter, with a similar trend seen in the more upstream 10 kb scriptionfactorswithoverrepresentedmotifsoccurringatsitesof
(Fig.5A,B).Incontrast,themajorityofexpressedgenesinHSCs DNAmethylationwithinthefivegenomicpartitions(identified
and CMPs contained methylation peaks within the gene body ontheleft)ineachpeakcategory(shownontheright).Theheatmap
(RefSeq) (Fig. 5A). Methylation peaks were also investigated in highlightstranscriptionfactorsthatoccurinonlyonepeakcategory
genesthatwerenotexpressedineachcelltype.Consistentwith (red)suchasMATH1inHSCproximalpromoterpeaks,twocate-
thelargerabsolutenumberofnonexpressedgenes,thenumberof gories(green),threecategories(teal),andtranscriptionfactorsthat
methylated nonexpressed genes exceeds the numberof methyl- are overrepresented in almost all data sets (dark blue) such as
ated expressed genes for each partition (Supplemental Fig. S7). GABPA.
While the ratio of unexpressed methylated genes to expressed Comparison of the overrepresented transcription factor
methylatedgenesissimilarbetweentheupstream,downstream, binding sites revealed that >10% of all overrepresented motifs
andRefSeqpartitions,thisratioiselevatedintheproximalpro- corresponded to ETS transcription factors. Although the ETS
moterforeachcelltypeandmarkedlyelevatedinERYs.Thesedata transcription factor (ELF1, ETS2, FLI1, and GABPA) binding
furthersupporttherolethatproximalpromotermethylationplays sites were overrepresented in all five genomic partitions, the
ingenesilencing. distribution within cell-type-specific categories was quite dif-
Onaverage,geneshadmultiplemethylationpeaks,withthe ferent. Common methylation peaks had overrepresentation of
RefSeqpartitionspecificallyaveraging3.75peakspergeneinHSCs, allETSfactorsinallpartitionsexceptintheintergenicpartition.
2.7 peaks in CMPs, and 2.1 peaks in ERYs. We investigated the In contrast, HSC-unique peaks lacked overrepresentation of
associationofmethylationpeaksinmultiplegenomicpartitions GABPAin the promoter and flanking partitions but exhibited
simultaneously to ascertain if specific patterns were associated
withpositivegeneexpression.Figure5Cshowsthepercentageof
Table2. Peakpartitiondistributionwithingenescomparedwith
expressedgeneswithmethylationpeaksintwoormoreofthefour CGcontent
partitions:upstream10kb(UP),proximalpromoter(PP),RefSeq
geneboundaries(CDS),and10kbdownstream(DS).Consistent 59UTR Exon Intron 39UTR P-value
withthesinglepartitionanalysis,expressedgenesareunlikelyto
%oftotalCG 27.94 7.38 40.9 23.78
havemethylationintheproximalpromoterincombinationwith Common 8.13 24.72 61.39 5.76 5.80995310(cid:2)17
any other genomic region. Of the two-partition correlations, HSC 7.89 11.14 74.84 6.13 1.94352310(cid:2)12
methylationmostfrequentlyoccurredtogetherinthegenebodies Progenitor 8.88 14.83 69.77 6.52 1.48518310(cid:2)11
(CDS)andthe10kbdownstream(DS)partitions,ineachofthe CMP 8.36 11.84 73.4 6.41 7.10713310(cid:2)12
Myeloid 12.75 6.86 78.43 1.96 1.51578310(cid:2)13
celltypes,withtheminimaltwo-partitioncorrelationoccurringin
ERY 7.3 7.51 78.9 6.29 1.09267310(cid:2)13
theproximalpromoterandthedownstreampartitions(Fig.5C).
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Hogart et al.
etic cell line, a multipotent cell that can be differentiated into
variousmyeloidlineages(PintodoO´ etal.1998).Overlapbetween
transcriptionfactorpeaksandMBD-seqpeaksinCMPsandHSCs
areshowninTable3.Thegenomiccoverageofeachtranscription
factordatasetandmethylationpeakdatasetwasusedtogenerate
randomdatasetstocalculatetheexpectedgenomicoverlapsbased
onchance.Asignificantunderrepresentationofoverlapbetween
transcriptionfactorsitesandmethylationpeaksoccurredinboth
CMPs and HSCs (Table 3). The only transcription factor with
significant co-occurrence with methylation was FLI1 in HSC
methylation peaks. Of the 10 key hematopoietic transcrip-
tionfactorsincludedinthestudybyWilsonetal.(2010),FLI1
is the only factor with an annotated consensus site that was
overrepresentedinourDNAmethylationpeaks.
Figure4. OverlapofMBD-seqpeakswithCpGislands.(A)MBD-seq
peaksinthethreecelltypescomparedwiththecompletegenomicCpG ChromatinimmunoprecipitationofFLI1andELF1reveals
islandsclassifiedbyIllingworthetal.(2010).Thepercentofmethylated
co-occupancyoftranscriptionfactorsandmethylation
promoterCpGislands(blue)ororphan(non-promoter)CpGislands(red)
isshownforeachcelltype.(B)MethylatedpromoterandorphanCpG
TofurtherinvestigatetherelationshipbetweenDNAmethylation
islandsincommonandcell-type-specificpeaks,asapercentageoftotal
andtranscriptionfactorbinding,wenextidentifiedthepresence
CpGislands.
of CpG sites in the overrepresented transcription factor motifs.
Table 4 contains a list of all transcription factors with known
overrepresentationofmultipleETSsiteswithintheintergenicpar- binding sites that were overrepresented in our analysis of the
tition.Thesecomplementarypatternsoftranscriptionfactormotifs proximalpromoterpartition.Ofthe19transcriptionfactormotifs
suggest that DNA methylation may modulate ETS transcription associatedwithsequencesoverrepresentedinmethylatedproximal
factor occupancy during hematopoietic
development.
Other transcription factor motifs
suchas the NFAT (nuclearfactorof acti-
vatedT-cells)werehighlyspecifictosingle
partitionsorcelltypes.TheNFAT1-binding
site is overrepresented in CMP-unique
methylation and myeloid-specific peaks
located in the proximal promoter. The
NFAT2motifisoverrepresentedinCMP-
uniquemethylationpeakslocatedinthe
proximal promoter and downstream re-
gions,andinthedistalpromoterofmy-
eloidpeaks.Incontrast,theNFAT3motif
is overrepresented in common and pro-
genitormethylationpeakslocatedinthe
proximal promoter. The striking differ-
ence between overrepresented motifs in
cell-type-specific methylation profiles
demonstrates that hematopoietic line-
agescontainuniquesignaturesofmethyl-
ation patterns that may regulate changes
thatoccurduringdifferentiation.
Minimalgenome-wideco-occupancy
ofhematopoietictranscriptionfactors
withDNAmethylationpeaks
To assess the relationship between ge-
nome-wide DNA methylation and tran-
Figure5. Methylationingenicpartitionsofexpressedgenes.Geneexpressionwasobtainedfromthe
scription factor binding, we compared
BloodExpress(Miranda-Saavedraetal.2009)geneexpressiondatabaseforeachcelltypeandcompared
ourmethylationdatawithgenome-wide withMBD-seqpeaks.(A)Thenumberofexpressedgenes(y-axis)ineachcelltypewithmethylation
occupancydataforasetof10keyhema- peaksinthedistalpromoter,proximalpromoter,RefSeqgenebody,anddownstreamregion.(B)The
topoietic transcription factors (Wilson numberofexpressedgenes(y-axis)lackingmethylationpeaksineachofthegenicpartitionsforeachcell
type.(C)Combinatorialanalysisofmethylationpeaksoccurringinallfourgenicpartitionsinexpressed
etal.2010).Transcriptionfactorbinding
genes.(UP)Upstream10kb;(PP)proximalpromoter;(CDS)RefSeqgeneboundary;(DS)downstream.
in Wilson et al. was ascertained in the Thepresence(+)orabsence((cid:2))ofmethylationintheindicatedpartitionisshownbelowthex-axis.The
immortalized HPC-7 mouse hematopoi- y-axisshowsthepercentageofexpressedgeneswitheachmethylationpattern.
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Genome-wide DNA methylation in hematopoiesis
differentiallymethylatedsiteswereobservedintwointronicpeaks
ofEng.Themethylationpeakinthefirstintron(site2)doesnot
overlap a functional conserved element, while the methylation
peakinintron11(site3)correspondstoaconservedelementthat
hasnotbeenassayedforfunction.Inbothcases,themoremeth-
ylatedsitewasoccupiedbyFLI1andELF1(Fig.7B,C).Overall,we
foundthatfourofsixregionswithstatisticallysignificantdiffer-
encesintranscriptionfactoroccupancyshowedincreasedbinding
inthemethylatedcelltype,whiletwoofsixregionshadsignifi-
cantlymore bindingin the less methylatedcell type (Fig. 7B,C;
Supplemental Fig. S8). We conclude that methylation does not
preventthebindingofELF1orFLI1.
Discussion
Thewidespreaduseofmassivelyparallelsequencingapproacheshas
ledtobreakthroughsingenomics,especiallyintheareaofepige-
neticcontrolofgeneregulation.Avarietyofapproacheshavebeen
developed to map DNA methylation including whole-genome
bisulfite sequencing (MethylC-seq), reduced representation bi-
Figure6. Heatmapofoverrepresentedmethylatedtranscriptionfactor
sulfitesequencing(RRBS),andtheenrichment-basedsequencing
binding motifs. The top 25 overrepresented sequence motifs for each
peakcategoryandeachgenomicpartitionarecompiledintoaheatmap. methods MeDIP-seq and MBD-seq. MethylC-seq requires more
(Top) Transcription factors (TRANSFAC IDs) with confirmed consensus sequencing reads (503) than enrichment approaches to yield
sequences.(Right)Eachgenomicpartitionwithcell-typecategories.(Red a comparable level of genome coverage, but provides single-
boxes) Transcription factor binding sites that are unique to one cell-
nucleotide resolution (Harris et al. 2010). Reduced representation
typepeakinaparticularpartition.Greenboxesarepresentintwocell-type
categories,tealboxesrepresentthreecategories,andblueboxesindicate bisulfitesequencingprovidesanalternativetowhole-genomebi-
presenceinthreeormorecell-typespecificcategories.Grayindicatesthat sulfitesequencing;however,itprovideshigh-resolutiondatafor
thetranscriptionfactorisnotoverrepresentedinthedataset. onlyalimitedportionofthegenome(Meissneretal.2005).The
enrichmentapproachesdetectmethylatedDNAfragmentsgenome-
wideandassumemethylationofnearbyCpGsites.Comprehensive
promoters, five contained CpG siteswithinthe consensus rec- comparison of the genome-wide method of MethylC-seq to the
ognitionsequence,andfivecontainedaCpGdinucleotideim- MBD-seq and MeDIP-seq enrichment methods revealed a >97%
mediately adjacent to the binding sequence. Many consensus concordance rate for methylation calls throughout the genome
bindingsitesinour datasetlack CpGsites;therefore,itisun- (Harrisetal.2010).WeconcludethattheMBD-seqisanaccurate
clearifmethylationdirectlyimpactsbindingofthetranscription andcost-effectiveapproachtosurveygenome-wideDNAmethyl-
factors. ation in small numbers of primary cells. In this study, we used
Totestthehypothesisthatdifferentialmethylationdirectly MBD-seqcombinedwithpeakcallingalgorithmstodescribeDNA
impactsthebindingoftranscriptionfac-
tors revealed by our de novo motif dis-
Table3. Overlapbetweentranscriptionfactoroccupancyandmethylationpeaks
covery, we performed chromatin immu-
noprecipitation of the ETS factors ELF1 Occupied Number Exp.overlapping
and FLI1. Methylation peaks primarily Transcriptionfactors sites overlapping (mean) Z-score P-value
localized to promoter regions of 10 dis-
MethylationCMP(50,639)
tinctgenes,aswellasseveralgenicpeaks
ERG 36,166 966 1983 (cid:2)20.80 2.16310(cid:2)96
were selected for validation. ELF1 and FLI1 19,601 348 1075 (cid:2)21.32 3.70310(cid:2)101
FLI1 occupancy was compared in these GATA2 9234 278 507 (cid:2)9.87 2.81310(cid:2)23
regions of differential methylation in GFI1B 8853 235 486 (cid:2)11.04 1.23310(cid:2)28
LMO2 9604 174 528 (cid:2)14.66 5.81310(cid:2)49
chromatin from CMPs and ERYs. Figure
LYL1 4350 101 238 (cid:2)8.52 7.98310(cid:2)18
7Ashowsthedatafortheendoglin(Eng) MEIS1 8401 207 461 (cid:2)11.17 2.86310(cid:2)29
locus,whereseveralconservedfunctional PU1 22,743 973 1248 (cid:2)7.35 9.91310(cid:2)14
elements have been identified (Pimanda RUNX1 5269 97 290 (cid:2)11.11 5.61310(cid:2)29
etal.2006,2008).Consistentwithpro- SCL 7096 146 389 (cid:2)12.26 7.42310(cid:2)35
moter methylation corresponding to
MethylationHSC(85,797)
genesilencing,thisgeneisunmethylated ERG 36,166 1357 3204 (cid:2)29.95 2.20310(cid:2)197
and expressed in CMPs, and uniquely FLI1 19,601 5333 1737 80.61 0
methylated and silenced in ERYs, as GATA2 9234 468 819 (cid:2)11.51 5.87310(cid:2)31
GFI1B 8853 340 784 (cid:2)15.51 1.48310(cid:2)54
determined by BloodExpress (Miranda- LMO2 9604 296 850 (cid:2)18.27 7.17310(cid:2)75
Saavedraetal.2009).Althoughsilenced, LYL1 4350 156 386 (cid:2)11.50 6.60310(cid:2)31
significantlyincreasedenrichmentofboth MEIS1 8401 343 744 (cid:2)13.97 1.19310(cid:2)44
FLI1 and ELF1 was observed in the ERY PU1 22743 1315 2015 (cid:2)14.69 3.74310(cid:2)49
RUNX1 5269 166 467 (cid:2)12.80 8.20310(cid:2)38
promoter methylation peak (Fig. 7B,C).
SCL 7096 195 629 (cid:2)16.83 7.36310(cid:2)64
Significantdifferencesinbindingbetween
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Hogart et al.
Table4. Overrepresentedmotifsinproximalpromoter differential methylation at CpG islands
ismoreimportantforearlystagesofline-
Transcriptionfactor TRANSFACbindingsite Identifiedmotif CpGproximity
age specification than for final cell fate
determination.
CKROX(ZBTB7B) cccctcccc CCCTCCC CpGwithinbindingsite
gccctcccc CCTCCCC A comparison of DNA methylation
cccctcccg CCTCCC inpluripotentembryonicstemcellsand
ELF1 aggaag AGGAAG lineage-committed cells has demon-
cggaag CACGGAAGC
strated a positive association between
ETS2 cttcccg CTTCCC
cttcctg CTTCCTG global DNA methylation levels and the
attcctg TTCCTG ability to differentiate into multiple cell
cttcctc CTTCCT types (Lister et al. 2009; Laurent et al.
LMAF(MAFA) acacagcag CAGCAG 2010).Similartowhatwehaveobserved
cgtcagcag
in hematopoietic stem cells, studies of
ggtcagcag
SP4 gcccctccccc CCCTCCC embryonic stem cells have shown that
tcccctccccg CCTCCC methylation is not restricted to tran-
gcccctcccac GCCCCGCCC scriptional repression, because many
gccccgcccct GCCCCGCCCC
expressed genes in stem cells contain
GABPALPHA(GABPA) cttccc CTTCCC CpGimmediatelyadjacent
Cttcct CTTCCTG DNAmethylationwithinthegenebody
MAFA Acagcag CAGCAG (Lister et al. 2009; Laurent et al. 2010).
Tcagcag Additionally, the correlation between
MATH1(ATOH1) gcagctggtg CAGCTG
DNAmethylationandtherepressivehis-
NFAT2(NFATC1) Tttcctg TTCCTG
WT1 ccctcctcc CTCCTCC tonemodificationH3K27me3isnotob-
cacacatac CACACATACA served in pluripotent embryonic stem
ccctcctcc TCCTCC cells(Laurentetal.2010).Thesefindings
IK tctgggagga CTGGGA CpGwithin1bp
suggest that DNA methylation in stem
cctgggagag CCTGGG
cttgggaggc GGGAGG cells is not directly involved in in-
cttgggaggt activation of genes, but may instead be
gttgggagga amarkenablinggenomicplasticity.Our
KAISO(ZBTB33) ctcctgctgt CTCCTGC
genome-widesurveyofDNAmethylation
CTGCTG
demonstrating high levels of methyla-
NFAT1(NFATC2) ggaaag GGAAAG
ggaagc CACGGAAGC tion in the multipotent hematopoietic
FLI1 aaggaaggaag AGGAAG CpG2+bp stem cell with progressive loss of meth-
NFAT3(NFATC4) ggaatttctt TTTCTT ylation during erythroid specification
PARP(PARP1) agagaaagag AGAAA
supports the positive role for DNA
GAGAAA
SF1 tgacctccc CCTCCC methylationincellularplasticity.
TR4(NR2C2) tctgacctctg CCTCTG DNA methylation dramatically de-
TERALPHA(T3A) ctggaggtgac CTGGAG creases as differentiation proceeds from
hematopoietic stem cells to lineage-re-
Where different from TRANSFAC IDs, Mouse Genome Informatics-approved symbols are listed in
strictedcommonmyeloidprogenitorcells
parentheses.
and the terminally committed erythro-
blast.Thesedataareconsistentwiththe
observationsofShearstoneetal.(2011),
methylation. Direct comparison of our MBD-seq data with the whohavealsodemonstratedglobaldemethylationinterminally
reduced representation bisulfite sequencing (RRBS) data in pri- differentiating erythroid cells. These genome-wide profiles
marymouseerythroblastsdemonstratedthatourMBD-seqpeaks complementseveralotherrecenthigh-throughputsurveysofDNA
arebiasedtowardgenomicregionswith>30%–40%CpGmethyl- methylationinprimarylymphoid(B-andT-)cells(Jietal.2010;
ation(SupplementalFig.S6). Deatonetal.2011;Shearstoneetal.2011).Jietal.(2010)usedan
Inmousehematopoieticcells,wefound2%–3%methylated array-based method to investigate methylation at ;4.6 million
promoterCpGislandsinallcelltypes,consistentwithMBD-seq CpGsitesineightdistincthematopoieticcelltypesincludingHSC/
andMeDIP-seqstudiesinothermouseandhumantissues(Weber multipotent progenitor cells, CMPs, lymphoid progenitors, and
etal.2007;Illingworthetal.2010).Althoughonlyafewpercentof differentiated T-cells. In contrast to the decreasing global DNA
promoterCpGislandsaremethylated,CpGislandswithingenes methylationweobservedindifferentiatingmyeloidanderythroid
are more likely to be methylated in a tissue-specific manner cells, both Ji et al. (2010) and Deaton et al. (2011) found little
(Maunakeaetal.2010),andinourstudy,weidentifiedthat20%of differenceinthemethylationofprimitiveandmaturelymphoid
non-promoterCpGislandsweremethylatedinallhematopoietic cells.Weconcludethatmethylationalterationsplayamuchlarger
cells.DifferentialmethylationofCpGislands,bothpromoterand roleinthedifferentiationofmyeloidanderythroidcellsthanin
non-promoter,waslesscommonincell-type-specificpeaks.This thedifferentiationoflymphocytes.Thisconclusionissupported
observationisinagreementwiththestudyrecentlypublishedby bytheobservationthatmicedeficientinDnmt1haveincreased
Deatonetal.(2011)inwhichdifferentialmethylationofCpGis- production of myeloid and erythroid cells (Broske et al. 2009;
lands between differentiated lymphoid cells was much less pro- Trowbridgeetal.2009).
foundthanthedifferencesobservedbetweenlymphoidcellsand We observed that regions of DNA methylation were
brain cells. Our results are consistent with the hypothesis that overrepresentedforETStranscriptionfactorbindingsitesandthat
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Genome-wide DNA methylation in hematopoiesis
(Sunetal.2005),andtheETStranscrip-
tion factor ELF1 were overrepresented
intherelativelyrareerythroblast-unique
methylationpeaks.Westudiedtwogenes
thataresilencedinerythroidcells,Meis1
and Eng, which have erythroid-specific
methylation peaksthat containconsen-
sussitesforELF1,andbothofthesesites
are bound by ELF1 in erythroblasts. Al-
thoughELF1hasnotyetbeenreportedto
function as a transcriptional repressor,
the redundant binding of ETS factors
(Hollenhorst et al. 2007; Okada et al.
2011) combined with the recent de-
scriptionsofrepressivefunctionsofre-
latedETSfactorsleadsustohypothesize
thatETSfactorsmaysilencecriticalgenes
forpropererythroiddevelopment.
Insummary,weprovideacompre-
hensive whole-genome map of DNA
methylationthatcanbeeasilyintegrated
withotheroccupancydata.Thesequences
subjecttodifferentialmethylationduring
myeloid development lead us to suggest
thatDNAmethylationmayofferanaddi-
Figure7. FLI1andELF1occupancyofmethylationpeaksintheEnggene.(A)UCSCGenomeBrowser
tional layer of modulation of key hema-
viewoftheEnglocusonchromosome2.Transcriptionfactorconsensussites(TRANSFACIDs)arein-
dicatedabovetheMBD-seqdatainregionsofsignificantpeaks.QPCRdataverifyingenrichedChIP topoietictranscriptionfactors.Thisstudy
bindingofFLI1(B)andELF1(C)atthreesitesofmethylationpeaksthroughoutEng.Site1,anERY- provides insight into the interplay be-
specificpeak,iswithintheproximalpromoter;site2,anERY-specificintronicpeak;andsite3,apro- tween DNA methylation and transcrip-
genitor(HSCandCMP)peakinthe39codingregion.ComparisonofbindinginCMPsandERYsrevealed
tionalnetworksthatareinvolvedinhe-
statisticallysignificantdifferencesofP=0.004(site1,FLI1),P=0.009(site1,ELF1),P=0.021(site2,
ELF1),andP=0.012(site3,FLI1). matopoieticdifferentiation.
Methods
therewaslessthanexpectedoverlapbetweenmethylationpeaks
andtranscriptionfactoroccupancy.TheETStranscriptionfactors
Enrichmentofprimarymousecells
arerequiredforboththemaintenanceofhematopoieticstemcells
andformyeloiddevelopment(Yangetal.2011;Yuetal.2011). Hematopoieticstemcellsandcommonmyeloidprogenitorcells
Whiletypicallyviewedasactivatorsoftranscription,severalrecent were harvested from adult female C57BL/6 bone marrow. After
studies have characterized repressive functions of ETS factors lysisofredcellsinACKlysingbuffer(BioWhittaker),;109cells
(Drydenetal.2012;Leeetal.2012),suggestingthatmodulationof weresubjectedtolineagedepletionusingthefollowingratanti-
the binding of these factors may have complex effects on gene mouseantibodies:CD8a,CD4,CD11b,Ly-6G/Ly-6C,CD45R,and
expression.Ournegativecorrelationbetweenmethylationpeaks Ter119(BDBiosciences).Lineagedepletionwasperformedaspre-
andglobaltranscriptionfactorbindingsuggeststhatmethylation viously described (Nemeth et al. 2003). Lineage-negative cells
negatively impacts the binding of these transcription factors. (lin(cid:2))werestainedwithPEanti-mouseSca1(cloneD7)andAPC
anti-mouseCD117(clone2B8;BDbiosciences).Lin(cid:2)Sca-1+c-kit+
Alternatively,thelackofco-occurrenceofmethylationandtran-
(HSC; 1%–2% of lineage depleted cells) and lin(cid:2) Sca-1(cid:2) c-kit+
scriptionfactoroccupancycouldbeaconsequenceoftranscription
(CMP;10%oflineagedepletedcells)weresortedonaBDFACSAria
factorsbindingprimarilyinmethylation-deficientregionssuchas
instrument.ImagesfromarepresentativesortareshowninSup-
promoters.OurchromatinimmunoprecipitationanalysisofFLI1
plemental Figure S1. Cells from five sorts (HSC) and two sorts
andELF1bindinginpromotersofmultiplegeneswithdifferential
(CMP) were combined to generate sufficient cells (;1 3 106 to
methylationpeaksinCMPsandERYsdemonstratedthatthemore 23106)foranalysis.ErythroblastswereobtainedfromC57BL/6d
methylatedcelltypeoftenexhibitedsignificantlyenrichedbind-
13.5embryonicfetalliversdisruptedintoasingle-cellsuspension
ing,whichindicatesthatneitherinterpretationisentirelycorrect.
witha21-gaugeneedleandstainedwithAPCanti-mouseTer119
Sinceourmethylationpeaksspanregionsofseveralhundredbase andFITCanti-mouseCD71antibodies(BDBiosciences).Thecells
pairs, we do notknowwhetherthe exactnucleotidesboundby were sorted into the five populations described by Zhang et al.
transcriptionfactorsaremethylated.Despitetheselimitations,we (2003). Cytospins were stained with May-Grunwald Giemsa to
concludethatmethylatedregionsmaybeimportantfordifferen- demonstratethattheR3population(CD71+Ter119+)contained
tialregulationofgenesbytranscriptionfactors. latebasophilicerythroblasts(SupplementalFig.S1).
Whilegenomicmethylationismostreducedinerythroblasts,
some functionally important sites of methylation are retained,
MBD2enrichmentofmethylatedDNA
includingtheimprintedlociSnrpn(SupplementalFig.S2)andH19
(Shearstoneetal.2011).Bindingsitesfortranscriptionfactorssuch GenomicDNAwasisolatedfromenrichedcellswiththeQIAGEN
as CKROX, a factor important for specification of CD4 T-cells Puregene kit and sonicated to 200- to 400-bp fragments. MBD2
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Hogart et al.
enrichmentwasperformedwiththeActiveMotifMethylCollector obtained from similar purification strategies were selected and
kit.Approximately1mgofsonicatedgenomicDNAwasincubated compiledforeachcelltype.HSCgeneexpressionrepresentedthe
withMBD2-His-conjugatedproteinandmagneticbeadsaccording union of theLT-HSC, ST-HSC,and MPP datasetsfrom multiple
to the manufacturer’s protocol. Between four and eight MBD2- geneexpressionstudies(Akashietal.2003;Chambersetal.2007;
genomicDNAreactionsforeachbiologicalreplicatewerepurified Mansson et al. 2007; Ficara et al. 2008). CMP gene expression
simultaneously and pooled post-enrichment. After enrichment, representsthecompilationofsimilarlypurifiedc-kit+,sca1(cid:2)pro-
boththemethylatedfractionandsupernatantfractionswerepu- genitorexpressedgenes(Akashietal.2003;Jankovicetal.2007)
rifiedwithQIAGENDNApurificationcolumns.QuantitativePCR and ERY gene expression was determined based from Ter119+
amplification of the differentially methylated regionsregulating normoblasts(Chambersetal.2007).Fulldetailsofthecellsusedin
theimprintingofSnrpnandRasgrf1andtheunmethylatedCpG theBloodExpressdatabaseareavailablefromhttp://hscl.cimr.cam.
island promoter of Actb was performed with SYBR Green PCR ac.uk/bloodexpress/.
master mix (Applied Biosystems), and was used to validate the
enrichment of methylated DNA using the MBD2-pull-down ap-
Motifdiscovery
proach(SupplementalFig.S3).
The complete set of putative binding sites of length 5–10 were
Bisulfitesequencingvalidation enumerated using the WordSeeker approach (Lichtenberg et al.
2010).Eachsitewasevaluatedforitsoverrepresentationinregard
GenomicDNAfromHSCs,CMPs,andERYswasbisulfite-converted toitssequencecoverageusingMarkovchainbackgroundmodels
withtheEZDNAMethylation-Directkit(ZymoResearch).Briefly, (Lichtenbergetal.2009)ofvaryingorder,rangingfrom0tothe
500ngofDNAwasconvertedaccordingtoastandardprotocol. maximumallowedorderforagivenbindingsitelength(maximum
The converted DNA was PCR-amplified with bisulfite primers order=sitelength(cid:2)2).
designedusingMethPrimer(LiandDahiya2002).Theprimerse- Thesetofenumeratedandscoredbindingsiteswassortedin
quences are listed in Supplemental Table S5. PCR-amplified bi- decreasingorderbasedontheoverrepresentationscoreandfiltered
sulfite products were cloned using the TOPO TA Cloning kit according to a word factor–based maximization [a site y is dis-
(Invitrogen) and sequenced. Bisulfite sequences were analyzed cardedifitiscompletelycontainedinasitexofequalorlonger
withtheQuantificationToolforMethylationAnalysis(Kumaki lengthandlargeroverrepresentation:x>yifx=uyvandscore(x)>
etal.2008). score(y),withuandvbeingnon-emptyfactorsthemselves].The
top25putativebindingsiteswereretainedforfurtheranalysis.
Next-generationsequencingofMBD2-enrichedgenomicDNA Thesetofpredictedbindingsiteswascomparedwiththesetof
knowntranscriptionfactorbindingsitesannotatedinTRANSFAC
Twobiologicalreplicatesofeachenrichedcellpopulationandone
(Matysetal.2006).Overlapsbetweenpredictedandknownbinding
supernatant sample per cell type were submitted for high-
siteswerecorrectedforoverlaptoensurethattheTRANSFACsites
throughput sequencing analysis. Between 225 and 540 ng of
colocalizedtothepredictedsitesintheinputsequences.
MBD2-enrichedDNAand1mgofsupernatantforeachcelltype
were used to construct DNA libraries according to the Illumina
protocol.ThelibrariesweresequencedontheIlluminaGenome Signaturegeneration
Analyzer platform, and 36-bp single-end reads were used to
Foreachknownandputativelyinvolvedtranscriptionfactor,the
uniquelyidentifytheMBD2-boundfractionofthemousegenome.
numberofinputdatasetsinwhichitoccurswascomputed.Using
thematrix2pngapplication(PavlidisandNoble2003),aheatmap
MappingandpeakcallingforMBD2enrichment wascreatedcorrelatingeachofthetranscriptionfactorswiththe
Sequencedreadswere mappedto themousegenome(UCSC as- input data sets characterizing the different stages of differentia-
semblymm9,NCBIbuild37)usingtheELAND(AJCox,unpubl.) tion.Thetemperatureofeachmatchisannotatedasthenumberof
short-readalignmentprogram.Peaksforeachcelltypewerecalled datasetsthatsharethetranscriptionfactorinvolvementtoallow
usingMACS(Zhangetal.2008)withaP-valuethresholdofP< highlightingofuniquecombinations.
10(cid:2)5.Sequencedreadsfromthematchedsupernatantwereusedas
a controlforeachcell type. WhenMACSwasunabletobuilda Occupation-methylationcorrelationanalysis
modelfor agiventreatment/controlpair, themodelrestrictions
wereloweredtocompensate.Peakcallsmadeonreplicateswere ChIP-seqlocalizationdataobtainedbyWilsonetal.(2010)were
post-processed to generate a confident set. Replicate peaks that overlappedwiththemethylationpeaks.Randompeaksofequal
overlapped by >200 bp were considered for further analysis; at cardinality and size were generated and used to quantify the
thiscutoffthemajorityofoverlapswereretained(Supplemental overlapexpectedbychance.Basedon1000bootstrappingitera-
Fig.S2). tions, the tabulated expected average overlap and standard de-
Thefinalsetsofpeakswerepartitionedaccordingtothege- viationwerecomputed.Incongruencewiththeobservedoverlap,
nomicsegmentstheyoccupybasedontheRefSeqgenecoordinate Z-scoreswereinferredandsubsequentlyusedtocomputeP-values
mapavailableforthemm9genomebuild.SinceDNAmethylation usingtheRtoolkit(IhakaandGentleman1996).
peaklengthsaverage800bp(SupplementalTableS2),peaksoften
spanintronandexonsegmentboundaries.Toassessthedistribu- Chromatinimmunoprecipitation
tionofDNAmethylationwithinthecontextofmorediscretese-
quenceswithingenes,themeanvalueofapeakrangewasusedto PrimarymouseCMPandERYcellsweresortedasdescribedabove
assignittoapartition. andfixedwith1%formaldehydefor10minatroomtemperature.
Fixationwasquenchedwith0.125Mglycinefor10minatroom
temperature.Cellswerewashedtwicein13PBScontainingpro-
Insilicogeneexpressionanalysis
teaseinhibitorandfrozenat(cid:2)80°C.Chromatinimmunoprecipi-
GeneexpressionwasdeterminedusingtheBloodExpressdatabase tationwasperformedusingtheMagnaChIPA/Gkit(Millipore).
(Miranda-Saavedraetal.2009).Briefly,datasetsrepresentingcells Briefly,cellswerelysedandsonicatedto200-to400-bpfragments;
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