Supplementary Materials for · 2016. 8. 3. · Specification of tissue-resident macrophages during organogenesis Elvira Mass, Ivan Ballesteros, Matthias Farlik, Florian Halbritter,

www.sciencemag.org/cgi/content/full/science.aaf4238/DC1

Supplementary Materials for

Specification of tissue-resident macrophages during organogenesis

Elvira Mass, Ivan Ballesteros, Matthias Farlik, Florian Halbritter, Patrick Günther,

Lucile Crozet, Christian E. Jacome-Galarza, Kristian Händler, Johanna Klughammer,

Yasuhiro Kobayashi, Elisa Gomez-Perdiguero, Joachim L. Schultze, Marc Beyer,

Christoph Bock, Frederic Geissmann*

*Corresponding author. Email: [email protected]

Published 4 August 2016 on Science First Release

DOI: 10.1126/science.aaf4238

This PDF file includes:

Supplementary Text

Figs. S1 to S13

Captions for Tables S1 to S6

Other Supplementary Material for this manuscript includes the following:

(available at www.sciencemag.org/cgi/content/full/science.aaf4238/DC1)

Tables S1 ro S6 (Excel files)

Mass et al., Fig. S1 C

Developmental stage (time in days)

EMP à MΦ 954 genes 1396 transcripts

YS FL YS FL

head caudal

YS liver

head brain limb

skin/epi. kidney

lung

EM

P pM

ac

MΦ

birth

A

B

● ●

●

●

●

●

●

●

−100 0 100 200 300

−150

−100

−50

0

50

100

150

200

Principal component 1 (18.9%)

Prin

cipa

l com

pone

nt 2

(11.

1%)

●

●

●

EMPpMacMac

● headcaudalFLYS

D EMP pMac MΦ

head caudal FL YS

0 1 2 3 4

05

1015

Average expression

Dis

pers

ion

4632428N05RikAdam15

Adgrg1

AdslAgpsAnxa3

Apbb1ip

Apoe

Aur kaBclaf1Brd4

C1qa C1qbC1qc

Caprin1

Cbfa2t3Ccnb1

Ccnd2Cd34

Cd47Cd53Cdk6Cdt1CebpbChchd4Cited2

Clint1CluhCnn2CopaCreg1 Csf1r

CtsbCtsc

CtslCx3cr1

Dab2

Ddx17

Def6Dnajc2Dpysl2 Efhd2Ehd4

Eif5aEmbEmilin2Evl

Fcgr1

Fcgr3Fmnl1Fth1

Ftl1Fzr1

Galk1GlulGrnGrpel1

H19 Hba−a1

Hba−xHbb−bh1

Hmga2

Hnr npa2b1Hnr nph1Hp

Hsp90aa1

Ifi30

Ifngr1Igfbp4

IghmIl17r a

Il4raImp3Iqgap1

Irf8Itga4 Lgals1

LgmnLmo2LplLsp1Lyz2Maea

Maf

Malat1

MarcksMef2c

MpoMrc1

Mrto4

Mt1

Ncf1Nedd4Nhp2l1Nop10

Nop56NptnNudt4Ogfr l1 Pabpc1Pfdn6

Plac8Plk1

Pou2f2Prdx2Prpf40a

Pr tn3

Pycard Rap1bRhoaRpa2Runx1Scd2

Sepp1SetSlc25a12

Smc4

Snx2

Spns2

SrmSrrm2

Stab1

Thg1lTimm9Tm6sf1 Top2aTpm4

Tuba4a

Tubb2aTub b4b

Tubb6Ube2c

Ube2q1Ugcg VimYbx1

Zfpm1

Zmiz1

B

A

B C

D

E F

Single-cell RNA-seq of 576

CD45low/+ cells

576 cells - 17766 genes

QA/ QC

removal of low quality cells

408 cells - 8657 genes

Dimensionality reduction and computational

clustering

Mapping of gene signature

expression scores to tSNE clusters

Pseudotemporal ordering of single

cells

ATCA

TCTA CTAC

-20

-10

0

10

20

-20 0 20 PC1

PC

2

0 5

10 15

0 1 2 3 5 9 10 Number of clusters

F r e q u e

n c y a m

o n g a l l

i n d i c e s

Cluster 1

Cluster 3 Cluster 2

-20

-10

0

10

20

-20 0 20 PC1

PC

2

-3

-2

-1

0

1

-2 0 2 Component 2

Cluster 1

Cluster 3 Cluster 2

-1 1 z-score expression

Com

pone

nt 1

G

Mass et al., Fig. S2

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

CD16.2 CD64 Tim4 CD206

AYS

FL

head

limbs

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

1000 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

Il4ra Il13ra1 Tnfr2 Ifngr

Kit+

pMacs

MΦ

E10.25 Csf1rMeriCreMer; Rosa26LSL-YFP+ OH-TAM @E8.5, gated on YFP+ cells

Il4ra Il13ra1 Tnfr2 Ifngr

brain

liver

lung

skin

Dectin-1 CD64 Tim4 CD206

E14.5 Csf1rMeriCreMer; Rosa26LSL-YFP+ OH-TAM @E8.5 B

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

1000 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

1000 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

1000 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

FMO, YFP+

FMO, all

all YFP+

Gated on MΦ


0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

YFP Dectin-1 Iba1 merge

E14.5 Csf1rMeriCreMer; Rosa26LSL-YFP+ OH-TAM @8.5

lung

YFP Iba1 F4/80

kidn

ey

head

merge

liver

brai

n liv

er

YFP Iba1 F4/80

kidn

ey

lung

E18.5 Csf1rMeriCreMer; Rosa26LSL-YFP+ OH-TAM @E8.5

merge

YFP Grn F4/80 merge

lung

he

ad

liver

E14.5 Csf1rMeriCreMer; Rosa26LSL-YFP+ OH-TAM @E8.5

E10.25 Csf1rMeriCreMer; Rosa26LSL-YFP+ OH-TAM @E8.5 C

D

E

F

YFP Kit F4/80 merge

E9.5 Csf1riCre; Rosa26LSL-YFP

head

ca

udal

YFP F4/80 merge Iba1 B

Mass et al., Fig. S4 E10.25 Csf1rMeriCreMer; Rosa26LSL-YFP+ OH-TAM @E8.5

merge YFP CD206 Iba1

YFP Iba1 Ifngr

YFP Iba1 Tnfr2

merge

merge

YFP Dectin-1 Iba1

merge YFP Iba1 F4/80

merge

YFP Iba1 Trem2 merge

YFP Iba1 CD16/32 merge

YFP Iba1 Grn merge

caud

al

head

ca

udal

he

ad

caud

al

head

ca

udal

he

ad

caud

al

head

ca

udal

ca

udal

he

ad

caud

al

head

he

ad

Aliv

er

0 102 103 104 105

0

102

103

104

105

0 102 103 104 105

0

102

103

104

105

CD45

Kit

F4/8

0

CD11b YFP

0 102 103 104 1050

20

40

60

80

100

0 102 103 104 1050

20

40

60

80

100

Tnfrsf11aCre; Rosa26LSL-YFP E10.25 (YS)

0 102 103 104 105

0

102

103

104

105

0 102 103 104 1050

20

40

60

80

100

CD48

CD

150

0 102 103 104 1050

20

40

60

80

100

YFP 0 102 103 104 105

0

20

40

60

80

100

LSK LT-HSCs

ST-HSCs MPPs

E14.5 Tnfrsf11aCre; Rosa26LSL-YFP

brai

n ki

dney

merge YFP Iba1 F4/80

A

B


liver kidneybrain epidermis0

10

20

30

40

50

0

6

12

0

50

100

150

200

250

0.00

0.01

0.02

0.03 Cx3cr1+/-Cx3cr1-/-

0

5

10

15

lung

p < 0.001

merge

head

ca

udal

GFP Iba1 F4/80

E10.25 Cx3cr1gfp/+

F4/8

0+ /

g of

org

an (x

106)

cells

/ ea

r (x1

06)

E14.5

adult (3-4 months)

F4/8

0+ /

orga

n (x

104 )

F4/8

0+ /

org

an (%

)

E12.5

brain limbsliver0.0

0.2

0.4

0.6

0.8

1.0

0

1

2

3

4

5

0.0

0.1

0.2

0.3

0.4

brain kidneyliver0.0

0.5

1.0

1.5

0.00

0.03

0.06

0.09

0.12

0

1

2

3

4

5

cells

/org

an (1

04 )

0.0

0.2

0.4

0.6

lung

p = 0.015

A

B C

D


A

pMacMac

Mac

vs.

pM

acsi

gnat

ure

Mac

vs.

EM

Psi

gnat

ure

pMac

vs.

EM

Psi

gnat

ure

EMPMac EMPpMacRanked by expression (higher expression in ...)

B

Nor

mal

ized

enr

ichm

ent s

core

D

C

EMPpMacMac

Cell type:

****

***

*

***

***

***

***

***

0

1

2

3

4

5

0

1

2

3

4

5

0

1

2

3

4

5

Cell typescompared

Cell typescompared

Nor

mal

ized

enr

ichm

ent s

core

Gau

tier

et a

l. (2

012)

Cor

e MΦ

sig

natu

re

**

***

***

0

1

2

3

4

5

...

# % #%

GSEA result summary (panels B, D):

MΦ MΦ

MΦ

MΦ

MΦ MΦ

MΦ

(2012)

B

D

C A


A

Thbs1

C

Pu.1 Cebpα Cebpβ

Maf Stat1 Stat6

Irf8 JunB Rela Atf3

35

100

100

300

300

200

250

70

100

300 50 kb

Mrc1

50 kb

Pu.1 Cebpα Cebpβ

Maf Stat1 Stat6

Irf8 JunB Rela Atf3 35

100

100

300

300

200

250 70

100

300 50 kb 50 kb

Emr1 Cx3cr1

Pu.1 Cebpα Cebpβ

Maf Stat1 Stat6

Irf8 JunB Rela Atf3 35

100

100

300

300

200

250

70

100

300 50 kb 50 kb

Myod1 Gata1

B

E2f1

Spi1

Suz12 Irf1 Hif1a Ring1 Rela Atf3 Batf3 Cebpa Irf8 Egr1 JunB Maf Cebpb Stat1 Ezh2 Stat6 Relb Rel Stat3 Stat5b Gfi1b

6 -6

Rel

ativ

e ex

pres

sion

(Log

2)

E9.

5 ca

udal

E

9.5

head

E

9.5

YS

E10

.5 h

ead

E10

.25

FL

E10

.25

YS

E10

.5 li

mbs

E

10.2

5 lim

bs

E10

.25

YS

E

10.2

5 FL

E10

.25

FL

E10

.25

limbs

EMP pMac

E10

.25

head

E10

.5 F

L

E10

.25

head

E10

.5 Y

S

E9

YS

E10

.25

YS

MΦ

Myb


Cell type:EMPpMacMac

Time:E9E9.5E10.25E10.5E12.5E14.5E18.5P2P8P21

Tissue:Limbs / skinHead / brainKidneyLiverLungYolksac

1.00.50.0-0.5-1.0

Row

z-s

core

Samples (n = 91)

Diff

eren

tially

exp

ress

ed g

enes

(n =

13,

717)

CA

��

Tissue:Limbs / skinHead / brainKidneyLiverLungYolksac

Cell type:EMPpMacMac

�200 �100 0 100 200

�200

�100

0

100

200

Principal component 1

Prin

cipa

l com

pone

nt 2

Head / brainLimbs / skin Kidney

Liver YolksacLung

E10.25

P21

P21 E10.25E14.5

P21

E10.25

E10.5

E14.5

P21P21

E10.25

Time (days)

��

�

�

��

��

��

��

��

��

��

� � � �

�

��

� �

��

��

�

��

��

��

�

��

�

� � � ��

��

��

��

��

��

��

� � � ��

� ��

� �

�

��

��

� ��

��

��

��

� � ��

��

��

� � ��

��

��

�

� �

�

� � ��

��

��

��

� � ��

��

��

��

��

��

��

�

��

� ��

�

��

�

��

Gen

e ex

pres

sion

rela

tive

to m

axim

um (m

ean

+/- s

.d.)

Limbs / skin signature

Head / brain signature

Kidney signature

Liver signature

Lung signature100%

50%

0%

100%

50%

100%

50%

100%

50%

100%

50%

E10.25, 10.5

E12.5E14.5

E18.5P2 P8 P21

B�

�

Limbs / skinHead / brain

�

�

KidneyLiver

�

�

LungYolksac

B A C


limbs/skin brain liver lung kidney

6 -6

Relative expression (Log2)

P8

P21

P21

P21

P8

P2

E12

.5

E14

.5

E18

.5

P8

P2

E12

.5

E14

.5

E18

.5

P8

P2

E12

.5

E14

.5

E18

.5

P8

P2

E14

.5

E18

.5

P2

E14

.5

E18

.5

P21

P21

D

E

Id1 Id3 Sall1 Sall3

6 -6

Relative expression (Log2) E9.

5 ca

udal

E

9.5

head

E

9.5

YS

E10

.25

FL

E10

.25

YS

E10

.25

YS

E

10.2

5 FL

E10

.25

limbs

EMP pMac

E10

.25

head

E9

YS

B

A

C



Dimensionality reduction and computational

clustering

Mapping of gene (co-)expression to

tSNE plot (Fig. 6B)

Calculation of macrophage tissue signatures from bulk RNA-seq data

all MΦ 10.25/10.5 all MΦ 10.25/10.5 all MΦ 10.25/10.5

brain MΦ 14.5/18.5 skin MΦ

14.5/18.5 liver MΦ 14.5/18.5

Common signature Tissue signatures

|FC| > 1.5, FDR < 0.05 Mapping of tissue

signatures to PCA of pMacs (Fig. 6C)

A

Kit

0.0

0.5

1.0

1.5

EMP pMA CS MA CS

n o r m a l i z e

d e x p r e s

s i o n

Stab1

0.0

0.5

1.0

1.5

2.0

EMP pMA CS MA CS

n o r m a l i z e

d e x p r e s

s i o n

Maf

0.0

0.5 1.0 1.5 2.0 2.5

EMP pMA CS MA CS

n o r m a l i z e

d e x p r e s

s i o n

Cx3cr1

0.0 0.5 1.0 1.5 2.0 2.5

EMP pMA CS MA CS

n o r m a l i z e

d e x p r e s

s i o n

B

Id1

0.0

0.5

1.0

1.5

2.0

EMP pMA CS MA CS

n o r m a l i z e

d e x p r e s

s i o n

Id3

0.0

0.5

1.0

EMP pMA CS MA CS

n o r m a l i z e

d e x p r e s

s i o n

Sall3

0.0

0.5

1.0

1.5

2.0

EMP pMA CS MA CS

n o r m a l i z e

d e x p r e s

s i o n

C

D Id1 Id3 Sall3 relative expression

0.00 0.05 0.10

0.00 0.02 0.04 0.06

0.00 0.01 0.02 0.03 0.04 0.05

relative expression

-20

-10

0

10

20

-20 0 20 tSNE_1

tSN

E_2

-20

-10

0

10

20

-20 0 20 tSNE_1

tSN

E_2

-20

-10

0

10

20

-20 0 20 tSNE_1

tSN

E_2

relative expression

Skin

Liver

Brain

EMP

pMac

Mac

Common

Cluster 6Cluster 5Cluster 4

Cluster 3Cluster 2Cluster 1

0 0.05 1

E

E

14 0

Expression (Log2)

Id3+/- Id3-/-

Kupffe

r cell

s

hepa

tocyte

s0

1

2

3

4

5

rela

tive

expr

essi

on

(nor

mal

ized

to G

AP

DH

) Id3

Kupffe

r cell

s

hepa

tocyte

s0.0

0.5

1.0

1.5Nr1h3A YFP ID3 DAPI F4/80

Id3+/-

Id3-/- C

D31

+ ar

ea (u

m2 /

mm

2 )

Id3-/-

Id3+/-

Id3+/- Id3-/- F4/80 CD31

B

C D

Cre+

Cre-

0

200

400

600Id3-/-Id3+/-

0

200

400

600RankCre+ Id3f/fRankCre- Id3+/f

CD

31+

area

(um

2 / m

m2 )

merge

Cre+; Id3f/f Cre-; Id3f/+


liver

br

ain

GO Term (273 genes) corrected p-value

negative regulation of apoptotic process 0.0420 negative regulation of metabolic process 0.0420 response to cytokine 0.0420 negative regulation of programmed cell death 0.0420 negative regulation of macromolecule metabolic process 0.0420 signal transduction 0.0420 negative regulation of macromolecule biosynthetic process 0.0420 negative regulation of biosynthetic process 0.0420 negative regulation of protein kinase activity 0.0495

GO Term (1320 genes) corrected p-value

carboxylic acid metabolic process 3.36E-25 monocarboxylic acid metabolic process 2.44E-24 organic acid metabolic process 1.06E-23 oxoacid metabolic process 8.79E-23 arachidonic acid monooxygenase activity 2.09E-17 blood microparticle 3.04E-17 small molecule metabolic process 3.70E-17 fatty acid metabolic process 2.88E-16 xenobiotic metabolic process 4.40E-16 drug catabolic process 6.32E-16

Id3-/- > Id3+/-

genes 2-fold enriched with t-test <0.05, FDR <0.05

Id3+/- > Id3-/-

genes 2-fold enriched with t-test <0.05, FDR <0.05; (Top 10 GO-terms)

F

Expression (Log2)

Batf3 Pparg Erg1 Atf3 Relb Ring1 Lmo2 Phf19 Jun Stat5a Gata3 Rel Cebpa Stat5b Maf E2f1 Stat3 Tcf3 Hif1a Irf1 Cebpb Ezh2 Irf8 Rela Suz12 Gfi1b Runx1 Lyl1 Spi1

3.5 3.2 3.0 7.8 7.7 8.3 7.9 8.4 8.0 8.0 8.3 6.8 7.1 8.3 7.8 7.8 7.4 7.4 6.2 6.7 7.7 7.8 6.2 4.5 5.5 7.5 2.6 2.6 3.1 5.1 5.7 5.4 5.2 6.3 6.2 5.4 5.6 7.4 5.5 3.5 5.0 6.7 3.6 5.1 3.2 4.2 4.8 4.5 5.2 6.8 5.0 5.8 3.2 4.6 4.4 7.1 6.7 6.4 4.8 6.7 8.0 3.3 4.9 4.6 4.4 3.8 5.2 5.4 5.1 3.5 3.9 7.7 4.6 7.2 5.5 5.4 5.2 4.9 3.4 3.1 4.0 6.8 6.1 6.7 3.6 3.7 8.1 6.6 7.9 8.2 8.7 6.5 8.4 6.8 7.8 8.2 6.8 9.6 9.3 7.9 8.8 9.9 6.1 8.8 3.4 5.5 4.5 5.4 4.5 4.8 4.7 5.5 3.0 4.0 3.7 4.6 5.9 3.6 4.3 5.4 6.5 7.1 4.4 4.5 5.6 6.5 5.8 7.5 3.8 4.7 4.4 4.1 5.3 3.8 4.6 5.0 3.6 3.8 3.9 3.2 4.6 3.8 4.5 3.8 3.7 5.0 5.4 4.1 4.0 5.7 3.3 3.9 3.9 5.5 4.0 5.4 5.0 4.5 5.3 5.2 6.0 5.9 5.6 6.4 5.8 5.0 6.0 5.9 6.1 7.3 6.1 7.4 5.6 5.7 4.5 7.8 4.8 8.1 8.3 7.9 8.0 6.3 5.0 4.7 7.1 4.4 4.0 3.7 3.6 3.3 4.1 4.9 4.3 3.1 4.9 5.2 5.8 5.0 4.5 5.7 4.9 4.5 5.9 4.1 5.8 4.1 7.4 5.7 6.2 6.2 6.2 8.2 8.6 8.5 7.9 6.0 8.7 6.9 8.8 9.8 7.5 7.7 8.2 7.8 8.9 9.2 7.8 9.7 7.9 10 10 8.7 9.6 7.3 7.1 5.5 6.3 7.9 6.1 6.4 7.1 7.7 7.4 7.1 6.7 6.2 6.4 7.4 6.1 6.7 5.6 5.6 5.2 6.3 5.5 5.8 5.5 5.8 7.0 5.8 6.3 7.4 6.2 5.2 5.3 4.2 3.9 5.3 4.8 4.0 4.8 4.5 5.6 5.0 5.6 7.6 5.1 4.4 7.9 5.4 4.1 5.2 5.4 5.7 5.7 5.2 5.8 7.3 5.1 6.9 7.8 7.9 8.0 7.6 6.8 8.0 7.7 7.9 6.8 8.8 6.5 8.3 7.8 7.5 5.7 8.4 6.7 8.9 8.2 7.6 8.3 7.4 7.5 5.8 6.5 7.2 7.8 7.8 7.4 7.8 7.7 7.3 7.0 7.0 7.0 7.1 6.8 7.2 6.4 7.3 6.5 8.6 7.1 8.4 7.7 6.7 7.1 6.6 7.2 8.2 7.3 7.2 6.9 8.0 7.1 7.5 7.5 7.7 8.2 9.5 8.2 8.3 7.0 7.5 7.7 7.3 6.8 5.7 7.1 8.8 9.6 8.0 5.4 6.2 7.4 6.4 4.9 9.9 8.9 7.9 9.3 9.5 9.0 9.8 10 9.4 10 10 9.6 9.7 7.4 11 7.5 10 9.4 9.7 9.4 9.6 11 10 8.0 5.5 7.4 8.5 8.4 6.9 8.1 9.1 8.4 8.3 8.4 7.7 8.5 8.5 7.6 5.4 8.7 9.0 6.5 6.8 7.0 6.4 8.3 9.2 6.5 6.8 7.5 9.0 7.8 7.4 7.5 8.2 6.8 6.2 7.6 7.3 6.4 8.9 7.1 6.0 5.6 3.6 6.7 6.7 7.0 8.2 6.1 5.8 7.3 8.5 6.9 6.2 6.9 5.7 7.4 5.8 5.7 6.4 6.1 6.6 5.9 5.7 5.5 6.5 6.3 5.2 7.2 5.3 7.4 7.0 7.3 5.5 6.7 5.6 5.1 6.3 6.5 7.3 8.0 9.0 9.3 7.7 8.1 7.5 6.9 7.6 7.1 7.5 7.9 7.9 8.3 8.3 9.6 7.6 8.4 7.7 8.2 8.2 7.2 4.8 9.8 6.3 6.6 6.8 7.6 8.9 7.0 6.7 7.3 7.1 7.2 6.5 6.2 6.5 6.7 7.8 6.2 6.4 6.5 6.9 7.0 7.2 6.6 9.6 9.7 10 8.6 9.5 9.6 8.6 8.6 7.0 7.9 7.9 8.4 7.3 8.0 7.6 7.9 7.6 7.9 9.1 7.6 8.2 8.3 8.2 7.7 9.1 5.4 7.6 8.4 8.1 7.4 8.5 7.5 9.1 9.1 9.3 8.8 9.3 9.1 8.8 9.1 9.4 9.1 9.8 8.7 6.5 8.0 8.4 7.9 8.8 8.9 7.1 9.2 7.5 7.7 8.5 7.0 8.8 8.8 8.2 9.4 8.7 8.2 11 11 12 11 11 12 12 11 11 11 11 12 11 10 11.1 8.7 13 10 12 12 12 11 12 8.7 9.7 7.4 8.0 8.5 8.0 8.1 7.5 8.7 8.1 8.9 11 7.9 7.0 8.0 8.5 9.0 10 8.2 7.6 9.0 8.9 10 9.5 8.5 7.3 9.3 8.7 9.0 10 10 10 9.9 10 9.9 10 9.5 8.8 9.8 9.0 8.6 10 9.8 9.0 8.9 9.9 9.4 10 8.3 9.8 9.6 7.6 9.2 11 10 6.1 7.2 4.4 7.2 4.3 7.8 5.3 5.0 8.3 3.7 3.7 5.2 7.7 3.2 3.6 2.9 3.7 9.1 7.1 4.3 3.6 3.7 5.9 10 10 10 9.4 9.8 10.0 9.3 9.4 9.9 8.8 8.9 8.7 9.5 8.6 9.2 8.9 9.2 9.2 7.1 9.4 7.8 4.9 10 9.6 9.3 8.9 11 11 11 10 11 10 10 9.1 9.9 9.5 10 12 10 11 9.6 8.9 10 11.6 7.9 9.9 10 11 12 11 11 12 11 12 11 12 12 12 12 11 12 12 12 13 11 12 11 10 11 12 9.8 11 12 12 12 11 10 12

Ccr1 Cx3cr1 Ccr5 Cxcr2 Cxcr3 Ccr3 Cxcr4 Cxcr6 Ccr9 Ccr7 Cxcr5 Xcr1 Ccr2

E10

.25

head

E9.

5 ca

udal

E

9.5

head

E

9.5

YS

E10

.5 h

ead

E10

.25

FL

E10

.25

YS

E10

.5 li

mb

E10

.25

limb

E10

.5 Y

S

E10

.5 l

iver

E10

.25

head

E9

YS

E

10.2

5 Y

S

E10

.25

FL

E12

.5 b

rain

E

14.5

bra

in

E10

.25

liver

E10

.25

limbs

E12

.5 li

ver

E14

.5 li

ver

E12

.5 li

mbs

E

14.5

ski

n

E14

.5 k

idne

y E

14.5

lung

6.0 6.6 6.4 9.2 8.7 10.0 10.3 9.4 11.1 10.5 11.1 11.2 10.9 11.0 11.2 10.7 10.1 11.4 9.1 9.6 8.3 5.5 11.0 12.5 11.3 10.1 4.3 4.3 4.6 7.9 7.8 7.4 7.9 8.8 8.1 8.5 8.1 7.0 9.3 8.7 8.8 8.2 7.9 8.4 4.9 6.5 2.8 3.9 3.7 3.6 3.7 3.5 5.4 4.8 5.0 7.9 7.0 8.5 8.5 8.1 8.6 9.0 9.5 8.5 7.9 8.8 7.8 8.6 7.6 8.4 3.1 7.2 3.2 7.5 3.8 4.8 6.2 4.6 6.6 8.0 5.2 6.5 7.2 7.8 6.5 8.2 6.0 7.4 5.6 5.0 4.1 3.6 3.7 3.8 4.0 3.5 3.2 4.2 3.1 4.1 4.1 3.8 3.9 3.7 6.1 8.7 4.9 4.7 4.8 4.5 2.8 3.8 3.0 6.3 4.5 3.6 5.7 4.9 4.7 4.6 4.8 5.5 6.2 4.0 2.7 4.6 3.7 4.1 4.0 3.6 2.6 3.3 3.2 4.6 2.9 3.2 2.4 3.5 5.7 2.5 4.2 3.1 4.2 3.7 3.9 3.1 3.1 3.4 5.0 4.1 4.4 5.8 3.8 4.1 6.7 4.0 2.6 4.3 3.1 3.6 3.9 3.7 3.2 3.7 3.0 2.8 3.5 4.6 4.6 3.5 4.1 3.7 3.3 3.5 3.5 4.3 3.2 5.7 6.9 8.1 5.4 6.8 3.6 3.0 3.2 2.5 3.4 4.8 2.6 3.3 2.8 2.7 3.7 4.8 5.3 4.0 3.9 3.5 5.0 5.5 4.8 3.8 3.2 4.0 4.1 5.8 6.1 3.5 4.7 2.9 4.2 2.7 3.9 3.8 2.9 3.9 3.2 3.4 5.0 4.6 3.6 3.8 3.7 3.8 2.9 3.5 7.4 9.9 6.2 6.4 9.8 9.8 7.8 7.4 5.6 7.4 3.0 7.8 3.2 5.0 5.5 3.7 3.3 3.1 3.4 3.4 3.5 3.6 3.8 3.6 2.9 3.5 2.7 3.8 2.9 3.9 3.9 3.7 3.7 3.5 2.8 2.6 3.0 6.4 4.5 3.4 2.8 3.7 3.0 2.8 4.0 3.3 3.7 3.6 3.8 3.7 4.8 4.1 7.8 11 9.7 8.0 10.0 5.4 6.6 6.3 3.5 2.7 5.3 4.8 5.7 5.2 5.4 6.4 3.3 5.3 4.7 4.0 4.9 4.2 4.2 4.6 3.7 4.1 2.6 3.8 2.8 3.9 3.7 3.6 4.0 6.1 4.4 7.3 6.0 8.1 6.2 7.1 7.5 7.6 7.8 6.9 5.7 5.4 5.6 8.8 7.2 8.1 4.9 5.8 3.5 4.7 3.5 4.0 4.9 4.6 4.6 4.0

EMP pMac MΦ

E10

.25

YS

S100a4

S100a8

S100a1

S100a14

S100a6

S100a10 S100a11

S100a9

S100a13

S100a16 4.1 6.4 4.6 2.4 3.0 3.2 3.0 3.6 2.5 3.7 3.9 3.1 4.2 3.4 3.9 4.0 3.6 3.3 6.5 3.9 8.9 9.2 3.7 3.9 3.9 4.2 2.6 2.7 3.1 2.5 3.0 3.2 2.7 3.5 2.9 2.6 3.2 3.2 3.5 3.5 3.8 3.5 3.0 3.4 2.4 3.9 2.7 4.0 3.6 3.8 3.8 3.6 2.7 2.5 3.0 2.4 3.5 3.5 3.7 4.0 7.0 4.0 4.5 4.9 3.7 3.6 5.0 7.9 3.4 3.5 3.5 3.8 3.0 4.4 3.9 3.6 3.7 4.0 2.8 2.5 2.9 2.7 4.0 3.7 2.9 4.2 4.4 3.2 5.2 5.2 3.7 3.7 3.7 7.2 2.8 3.6 2.8 3.7 2.8 3.9 3.8 3.6 3.6 3.8 3.5 5.2 6.1 6.8 4.8 5.4 5.2 3.1 4.7 5.6 6.2 6.2 5.8 5.0 7.6 5.7 4.8 5.8 3.8 5.5 3.7 4.2 3.8 4.2 3.9 3.8 5.6 6.4 6.2 7.0 6.8 6.9 6.5 7.2 6.9 7.0 7.7 9.1 6.5 7.0 8.0 7.0 6.4 7.2 3.4 4.4 3.9 4.4 4.9 4.4 4.7 4.5 6.6 8.0 8.0 6.0 7.0 6.9 6.5 7.6 7.2 6.8 7.3 8.0 5.8 8.2 6.8 6.7 7.1 8.1 6.8 5.8 6.7 7.1 6.6 6.5 7.0 6.0 8.0 9.7 9.5 7.7 7.7 7.6 7.9 9.0 8.0 8.6 9.2 10.5 8.5 9.0 9.7 8.1 8.2 8.5 7.2 4.8 8.6 6.0 8.4 8.3 7.0 8.8 7.0 7.1 7.1 7.5 7.2 7.5 7.9 8.9 8.2 8.2 8.4 8.7 7.9 8.6 7.6 7.7 7.4 7.7 6.3 8.0 7.6 7.7 7.9 7.9 7.2 8.4 6.3 7.0 7.0 7.1 4.9 5.9 6.9 8.1 7.1 7.2 7.1 8.0 8.4 7.3 7.9 7.9 6.8 7.0 6.3 5.8 7.9 5.3 8.6 7.4 7.5 6.5


Supplementary figure legends Fig. S1: Quality control and analysis of bulk RNA-seq. (A) Number of reliably detected transcripts (covered with a least 25 reads) in each library. The colored circles underneath indicate the batch (sequencing flow cell), time, cell type, and tissue of each sample with the color code as given below panel B. (B) Hierarchical clustering with Euclidean distance and complete linkage of all samples based on their RNA-seq gene expression profiles. The colored circles underneath the cluster dendrogram indicate the batch (sequencing flow cell), time, cell type, and tissue of each sample with the color code as given below. (C) Scorecard analysis of differentially up-regulated genes (DESeq2 Wald test, adjusted p-value<0.05, BH-correction) in early macrophages (E10.25, E10.5) in comparison to EMPs. The table shows the relative enrichment of differentially upregulated genes in macrophages across cell types and tissues (y-axis) and developmental time points (x-axis, from E9 to P21). See Methods for details of the scorecard. (D) Principal component analysis (PCA) plot of EMPs (red, E9-E10.25), pMacs (yellow, E9.5-E10.25) and macrophages (purple, E10.25-E10.5) from the head, caudal, fetal liver (FL) and yolk sac (YS). The shape of each dot indicates the tissue the sample was taken from. The first and second principal component explain 18.9% and 11.1% of the entire variation in the data, respectively. Fig. S2: Quality control and analysis of single-cell RNA-seq. (A) Workflow of the MARS-seq single cell data analysis. (B) Mean-variability plot shows average expression and dispersion for each gene. This analysis was used to determine highly variable genes (labeled by gene symbol). These 138 highly variable genes were used to perform a dimensionality reduction of the single-cell data by a principal component analysis. (C) The highest gene loadings in the first and second principal component from the PCA of 408 high quality cells, colored by batch association, showed even distribution of cells among the PCA plot based on the 138 most highly variable genes. (D) Heatmap of 138 highly variable genes among single-cell clusters as defined by DBScan clustering. (E) Optimal cluster number was identified by calculation of diverse indices for determining the best clustering scheme using the NbClust R package. (F) PCA plot of 408 single cells colored by cluster association. Clusters were defined by PCA + DBScan clustering. (G) Kinetic diagram shows the pseudotemporal ordering of single cells as determined by Monocle 2. Dots indicate individual cells and are colored according to the cluster association as in (F). Black line indicates the progression of single cells over developmental pseudotime. Fig. S3 Expression of surface markers on EMP-derived cells during development. (A) Flow cytometry analysis of E10.25 Csf1rMeriCreMer; Rosa26LSL-YFP (OH-TAM at E8.5) tissues showing expression of Il4ra, Il13ra1, Tnfr2, Ifngr, CD16.2, CD64, Tim4, and CD206 on YFP+ Kit+ progenitors (gray), pMacs (blue) and macrophages (orange). Histograms represent the fluorescence intensity for each antibody in each cell subset. Data are representative of n=4 independent experiments with 4-6 embryos per marker. (B,C) Flow cytometry analysis of Csf1rMeriCreMer; Rosa26LSL-YFP (OH-TAM at E8.5) liver, brain, lung, and skin F4/80+ cells from E14.5 embryos showing expression of Il4ra, Il13ra1, Tnfr2, Ifngr, Dectin-1, CD64, Tim4, and CD206. Black dotted line depicts expression by all macrophages (CD45+CD11blowF4/80high) and green tinted line shows expression by the subsets of YFP+ macrophages. Gray histograms show the fluorescence intensity of the FMO controls for all macrophages (grey line) and YFP+ macrophages (grey tinted line). Data are representative of n=2 independent experiments with 3-4 embryos per marker. Fig. S4 Expression of the core macrophage program on EMP-derived cells. (A) Immunostaining on cryosections from E10.25 Csf1rMeriCreMer; Rosa26LSL-YFP embryos, pulse-labeled with OH-TAM at E8.5 with antibodies against YFP (green), Iba1

(red/cyan), and CD206 (red), Ifngr (red), Tnfr2 (red), Dectin-1 (red), Trem2 (red), CD16/32 (red), Granulin (Grn, red), or F4/80 (cyan). Scale bars represent 10 µm. Data are representative of n=3 embryos for each marker. (B) Whole mount immunostaining of E9.5 Csf1riCre; Rosa26LSL-YFP embryo labeled with antibodies against YFP (green), Iba1 (red), F4/80 (cyan) and DAPI (white). Scale bars represent 10 µm. Data are representative of n=3 embryos. (C) Immunostaining on cryosections from E10.25 Csf1rMeriCreMer; Rosa26LSL-YFP embryo liver, pulse-labeled with OH-TAM at E8.5 with antibodies against YFP (green), Dectin-1 (red) and Iba1 (cyan) (upper panel) or YFP (green), Kit (red) and F4/80 (cyan) (lower panel) Scale bars represent 15 µm. Data are representative of n=4 embryos. (D, E, F) Immunostaining on cryosections from E14.5 (D,F) and E18.5 (E) Csf1rMeriCreMer; Rosa26LSL-YFP mouse embryos stained with antibodies against YFP (green), Iba1 (red) or Grn (red), and F4/80 (cyan). Data are representative of n=3 embryos. Scale bars represent 10 µm. Fig. S5 Analysis of Tnfrsf11aCre; Rosa26LSL-YFP mice. (A) Gating strategy for Tnfrsf11aCre; Rosa26LSL-YFP embryos in E10.25 YS pMacs (Kit- CD45+ F4/80- CD11blow

Gr1- Ter119-; green) and macrophages (CD45+F4/80+CD11blo; blue) (upper panel), and in E14.5 fetal liver LT-HSCs (Lin-Kit+Sca1+CD150+CD48-; orange), ST-HSCs (Lin-

Kit+Sca1+CD150-CD48-; blue) and MPPs (Lin-Kit+Sca1+CD150-CD48+; purple) (lower panel). Histograms represent YFP expression in Tnfrsf11aCre-; Rosa26LSL-YFP (grey) and Tnfrsf11aCre+; Rosa26LSL-YFP (color for cell type indicated in gating strategy). Data are representative of n=2 independent experiments. (B) Immunostaining on cryosection from E14.5 Tnfrsf11aCre; Rosa26LSL-YFP embryo, with antibodies against YFP (green), Iba1 (red) and F4/80 (cyan). Data are representative of n=2 embryos. Scale bars represent 10 µm. Fig. S6 Analysis of Cx3cr1-deficient mice. (A) Immunostaining on cryosection from E10.25 Cx3cr1gfp/+ embryo with antibodies against GFP (green), Iba1 (red) and F4/80 (cyan). Data are representative of n=2 embryos. (B, C, D) Flow cytometry analysis in Cx3cr1+/- and Cx3cr1-/- of F4/80+ macrophages from liver, brain, and limbs at E12.5 (B), liver, brain, limbs, and lung from at E14.5 (C) and liver, brain, limbs, lung, and epidermis from 12 week-old mice (D). Circles represent individual mice from n=7 independent experiments. Fig. S7 Gene set enrichment analysis (GSEA) of cell type-specific expression patterns. (A) GSEA plots illustrating the relative enrichment of genes that we found statistically significantly upregulated (see Methods) in the comparison of macrophage vs. pMac (top row), macrophage vs. EMP (middle row), or pMac vs. EMP (bottom row). The black bars in the middle of each plot indicate the transcripts which are in each respective lists. The order in which transcripts were input into the analysis was defined by the relative expression change (logarithmic fold change) in macrophage vs. pMac (left), macrophage vs. EMP (center), or pMac vs. EMP (right), respectively. (B) The GSEA results from panel A are summarized here by the normalized enrichment score (NES) of each analysis. The colored squares indicate the two cell types compared with the color code as defined at the bottom right of this figure. Asterisks adjacent to bars indicate significance (FDR-corrected p-value); *: q≤0.05, **: q≤0.01, ***: q≤0.001. (C) Comparison of transcripts upregulated in macrophage vs. pMac, macrophage vs. EMP, and pMac vs. EMP, and the core macrophage signature extracted from Gautier et al. (2012). After translating gene denominators to Ensembl transcript IDs, Gautier's list matches 179 transcripts, only 27 of which occur in one of the lists of upregulated genes in this study. (D) GSEA results of Gautier's core macrophage signature genes in the comparisons of macrophage vs. pMac, macrophage vs. EMP, or pMac vs. EMP from this study (same gene rankings used in panels A and B). In all three comparisons, the core macrophage signature is enriched significantly (q≤0.01).

Fig. S8 LOLA enrichment analysis and enhancer regions. (A) Results of a LOLA enrichment analysis of promoter-adjacent regions (TSS +/- 20kb) of upregulated genes during transition from EMPs to pMacs (upper panel) or EMPs to early macrophages (E10.25-E10.5; lower panel). Each dot represents one single ChIP-seq experiment with the size relative to the quantity of enrichment (log odds ratio) and colors indicating the cell type used in the respective experiment. The key below the plots denominates the color coding. The numbers (“x/y”) given behind the cell type specify the number of enriched (x) out of all available datasets (y) from the respective cell type. Shown are all transcription factors of the genomic binding locations, which are significantly enriched (adjusted p-value <0.001, Benjamini Yekutieli correction) in at least one dataset in either comparison. All transcription factors shown are expressed in at least one sample examined, with the exception of Gcgr and Maff (greyed out and marked with an asterisk). (B) Heat map representation of the expression of the transcription factors shown in (A) in EMPs, pMacs and early macrophages (E10.25-E10.5) (C) Genome browser tracks showing ChIP-seq signals for the indicated transcription factors at the Emr1, Cx3cr1, Mrc1, Thbs1, Gata1 and Myod1 loci. The tracks display ChIP-seq data from macrophage populations, except for Maf (T cells), and Irf8 (dendritic cells). Fig. S9 Coordinated changes of gene expression identified during the specification of tissue-resident macrophages. (A) Top panel shows an unsupervised, low-dimensional projection via principal component analysis of the RNA-seq data in this study. The color of each dot indicates the tissue the sample was taken from. Bottom panels show only the macrophage datasets from one tissue at a time (gray dots). The mean of the coordinates at each time point was calculated and indicated as a colored dot (with the same color code as above). Consecutive time points were then connected with arrows to visualize the differentiation trajectory described by the transcriptional profiles of these samples. (B) Line plots illustrating average expression of tissue-specific gene signatures in macrophages over time. Each panel corresponds to one list of differentially upregulated tissue-specific genes (Table S3) and each line to the average of all macrophage samples of one tissue at the given time. Shaded areas indicate +/- standard deviation. (C) Heatmap showing the expression levels of all RNA-seq datasets across all transcript differentially upregulated in any tissue in either stage (early embryonic, fetal, postnatal). Expression values have been scaled as z-scores per row, resulting in a color scheme in which red values represent highly expressed and blue values represent lowly expressed transcripts. Hierarchical Ward clustering with Euclidean distance was used to arrange the samples and genes and the resulting dendrogram was cut at equal height into seven (column-wise) or ten (row-wise) clusters to highlight the strongest clusters of genes and samples more clearly. The color bars on top of the heatmap indicate the time, cell type, and tissue of each sample. Fig. S10 Gene set enrichment analysis (GSEA) of tissue-specific expression patterns in adult macrophages. (A) GSEA plots illustrating the relative enrichment of genes that were found to be statistically significantly upregulated (see Methods) in the comparison to Langerhans cells, microglia, kidney macrophages, Kupffer cells, and alveolar macrophages (from left to right) in comparison to the respective other adult macrophage populations. The black bars in the middle of each plot indicate the transcripts, which are in each respective lists. The order in which transcripts were input into the analysis was defined by the relative expression change (logarithmic fold change) in macrophages in the corresponding tissue (e.g. head/brain for microglia) compared to other macrophages at the same developmental stage (from top to bottom: early, fetal, or postnatal). The colored hashes (#) beneath each plot link to the bars in panel B. (B) The GSEA results from (A) are summarized here by the normalized enrichment score (NES) of each analysis. The colored squares underneath the bar plots indicate the tissue, cell type, and developmental stage of the sample for which

enrichment is shown, following the color code as used in panel C. The bars highlighted in color correspond to the plots shown in panel A. Additionally, these and other bars from samples from a tissue related to the signature at hand are indicated by shading. Asterisks adjacent to bars indicate significance (FDR-corrected p-value); *: q≤0.05, **: q≤0.01, ***: q≤0.001. (C) GSEA results against externally defined gene signatures extracted from Gautier et al. (2012), Gorgani et al. (2008), and Lavin et al. (2014). The same color code, shading, and annotations are used as in panel B. (D) Hierarchical clustering of differentially up-regulated genes (2-fold change, adj. P-value < 0.05, BH-correction) in post-natal (P2-P21) brain, liver, kidney, epidermis or lung macrophages comparing one population vs. the others (see also Table S3). Each sample represents the mean of at least two biological replicates and two technical replicates, except for E14.5 liver macrophages and P8 and P21 lung macrophages, which consist of one biological replicate and two technical replicates. (E) Heatmap representation of the expression of Id1, Id3, Sall1, and Sall3 in EMPs and pMacs from bulk RNA-seq data. Fig. S11 scRNA-seq analysis of specification of tissue-resident macrophages. (A) Workflow for overlaying transcription factor co-expression and tissue macrophage-specific signatures onto the tSNE plots. (B) Normalized expression of Kit, Stab1, Maf, and Cx3cr1 within EMPs, pMacs, and macrophages. (C) Normalized expression of Id1, Id3, and Sall3 within EMPs, pMacs, and macrophages. (D) tSNE plots showing expression of Id1, Id3, and Sall3. (E) Heatmap depicting enrichment of tissue macrophage-specific signatures as in Fig. 6C or differentiation signatures as in Fig. 1E in pMacs on gene clusters defined by multimodal gene expression with subsequent hierarchical clustering of scRNA-seq data. Fig. S12 Role of Id3 in Kupffer cell development (A) Relative expression of Id3 and Nr3h1 transcript by qRT-PCR (normalized to GAPDH) in sorted Kupffer cells and hepatocytes of C57BL/6 mice n=3. (B) Immunostaining with antibodies against YFP (green), ID3 (red) and F4/80 (cyan) on cryosection from adult (4 week-old) liver (upper panel) or brain (lower panel) from a pulse labeled Csf1rMeriCreMer; Rosa26LSL-YFP mouse (OH-TAM at E8.5). Nuclei were counterstained with DAPI (white). Scale bar represents 10 µm. Data are representative of n=3 mice. (C) Immunostaining with antibodies against CD31 and F4/80 on liver cryosections from 4 week-old Id3-/- and Id3+/- mice. The figure displays isovolume-rendered images. Scale bars represent 150 µm for the overview of the adult tissue and 50 µm for insets. Data are representative of n=5 mice. (D) CD31+ area quantification on liver sections from Id3+/- and Id3-/- 4 week-old mice (left panels) or from Tnfrsf11aCre+; Id3+/f and Tnfrsf11aCre+; Id3f/f 2 week-old mice (right panels). Data are representative of n=3 independent experiments. (E) Unsupervised hierarchical clustering on whole transcriptome from Id3+/- and Id3-/- Kupffer cells (Distance metric: Euclidian, linkage rule: Ward’s, number of genes: 18882) from three Id3+/- and two Id3-/- replicates. (F) Significantly enriched Gene Ontology (GO) terms identified for 2-fold up-regulated (left table) or down-regulated (right table) genes in Id3-

/- vs. Id3+/- Kupffer cells enriched by a t-test (P<0.05; FDR<0.05). GO analysis was performed using GeneSpring. GO terms are depicted and raked by corrected P-value (FDR false discovery rate corrected for multiple testing). Fig. S13 Heat map representation of the normalized counts (log2) reads of S100a mRNA found in our dataset.

Supplementary tables (Tables published online in Excel format) Supplementary Table S1: Genes differentially regulated in pMacs and macrophages (E10.25-E10.5) in bulk RNA-seq experiments Supplementary Table S2: Gene signatures derived from bulk RNA-seq experiments used for single cell RNA-seq analysis Supplementary Table S3: Genes differentially regulated in postnatal macrophages (P2-P21) in bulk RNA-seq experiments Supplementary Table S4: antibodies used for Flow cytometry Supplementary Table S5: complete bulk RNA-seq data http://www.biomedical-sequencing.at/bocklab/fhalbrit/macro/data/EC7D8Y7EL5QDMYIOL7GW2SECRWZUN1CWPQCUSJ47FFRO1WHD.zip Supplementary Table S6: RNA-seq analysis on Kupffer cells from Id3KO and control littermates Author contribution. FG, EM designed the study and wrote the manuscript. EM, IB performed cell sorting, flow cytometry, fate-mapping, immunostaining experiments and RNA-seq analysis on Id3-deficicient and control Kupffer cells. LC and CEJG helped with analysis of Tnfrsf11aCre+; Rosa26LSL-YFP mice. EGP assisted with the design of cell sorting experiments. MF designed and prepared bulk RNA-seq libraries. FH, JK, CB performed primary and differential analysis of the bulk RNA-seq data. KH and MB generated single-cell RNA-seq libraries and performed single-cell RNA-seq, PG, MB and JLS analyzed single cell RNA-seq data. All authors contributed to the manuscript.

Documents

Supplementary Materials for · 2016. 8. 3. · Specification of tissue-resident macrophages during organogenesis Elvira Mass, Ivan Ballesteros, Matthias Farlik, Florian Halbritter,