Supplementary Methods Microarray Data AnalysisSupplementary Methods Microarray Data Analysis Gene...

19
Supplementary Methods Microarray Data Analysis Gene expression data were obtained by hybridising a total of 24 samples from 6 experimental groups (n=4 per group) to Illumina HumanHT-12 Expression BeadChips. Raw data were exported from the Illumina GenomeStudio software (v1.0.6) for further processing and analysis using R statistical software 1 (v2.10) and BioConductor packages. Raw signal intensities were background corrected using array-specific measures of background intensity based on negative control probes, prior to being transformed and normalised using the ‘vsn’ package 2 . Quality control analyses did not reveal any outlier samples. The dataset was then filtered to remove probes not detected (detection score <0.95) in any of the samples, resulting in a final dataset of 25,620 probes. Statistical analysis was performed using the Linear Models for Microarray Analysis (limma) package 3 . Differential expression between the experimental groups was assessed by generating relevant contrasts corresponding to the relevant comparisons. Raw p-values were corrected for multiple testing using the false discovery rate controlling procedure of Benjamini and Hochberg 4 , adjusted p-values below 0.01 were considered significant. Significant probe lists were then annotated using the relevant annotation file (HumanHT-12_V3_0_R2_11283641_A) that was downloaded from the Illumina website (http://www.illumina.com) for further biological investigation. Bioinformatics and statistical analyses The nucleotide sequence were inspected with transcription factor binding site searching software JASPAR (http://jaspar.cgb.ki.se/) 5 and Genomatrix (http://www.genomatix.de/) for the presence of putative ISRE sites (Supplementary Table S1). Statistical analysis was performed using One-way ANOVA with Dunnett’s multiple comparison post test or Student’s T-test where appropriate (*p< 0.05, **p<0.01, ***p<0.001). References 1. Team, R.D.C. in R Foundation for Statistical Computing, Vol. Vienna Austria, 20102010). 2. Huber, W., von Heydebreck, A., Sultmann, H., Poustka, A. & Vingron, M. Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics 18 Suppl 1, S96-104 (2002). 3. Smyth, G.K. et al. Limma: linear models for microarray data, in Bioinformatics and Computational Biology Solutions using R and Bioconductor 397-420 (Springer, New York, 2005). 4. Benjamini, Y. & Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological) 57, 289-300 (1995). 5. Vlieghe, D. et al. A new generation of JASPAR, the open-access repository for transcription factor binding site profiles. Nucleic Acids Res 34, D95-97 (2006). Nature Immunology: doi:10.1038/ni.1990

Transcript of Supplementary Methods Microarray Data AnalysisSupplementary Methods Microarray Data Analysis Gene...

Supplementary Methods

Microarray Data Analysis

Gene expression data were obtained by hybridising a total of 24 samples from 6

experimental groups (n=4 per group) to Illumina HumanHT-12 Expression BeadChips.

Raw data were exported from the Illumina GenomeStudio software (v1.0.6) for further

processing and analysis using R statistical software 1 (v2.10) and BioConductor

packages. Raw signal intensities were background corrected using array-specific

measures of background intensity based on negative control probes, prior to being

transformed and normalised using the ‘vsn’ package 2. Quality control analyses did not

reveal any outlier samples. The dataset was then filtered to remove probes not detected

(detection score <0.95) in any of the samples, resulting in a final dataset of 25,620

probes. Statistical analysis was performed using the Linear Models for Microarray

Analysis (limma) package 3. Differential expression between the experimental groups

was assessed by generating relevant contrasts corresponding to the relevant

comparisons. Raw p-values were corrected for multiple testing using the false discovery

rate controlling procedure of Benjamini and Hochberg 4, adjusted p-values below 0.01

were considered significant. Significant probe lists were then annotated using the

relevant annotation file (HumanHT-12_V3_0_R2_11283641_A) that was downloaded

from the Illumina website (http://www.illumina.com) for further biological investigation.

Bioinformatics and statistical analyses

The nucleotide sequence were inspected with transcription factor binding site searching

software JASPAR (http://jaspar.cgb.ki.se/) 5 and Genomatrix

(http://www.genomatix.de/) for the presence of putative ISRE sites (Supplementary

Table S1). Statistical analysis was performed using One-way ANOVA with Dunnett’s

multiple comparison post test or Student’s T-test where appropriate (*p< 0.05,

**p<0.01, ***p<0.001).

References

1. Team, R.D.C. in R Foundation for Statistical Computing, Vol. Vienna Austria, 20102010).

2. Huber, W., von Heydebreck, A., Sultmann, H., Poustka, A. & Vingron, M. Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics 18 Suppl 1, S96-104 (2002).

3. Smyth, G.K. et al. Limma: linear models for microarray data, in Bioinformatics and Computational Biology Solutions using R and Bioconductor 397-420 (Springer, New York, 2005).

4. Benjamini, Y. & Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological) 57, 289-300 (1995).

5. Vlieghe, D. et al. A new generation of JASPAR, the open-access repository for transcription factor binding site profiles. Nucleic Acids Res 34, D95-97 (2006).

Nature Immunology: doi:10.1038/ni.1990

Supplementary Figure legends

Figure S1:

IRF5 expression is induced by M1 macrophage maturation protocols

(a) M1 and M2 macrophages from the same donor were stimulated with LPS (10ng/ml)

for 24h and the secretion of IL-12p70, IL-23 and IL-10 was determined by ELISA. Data

shown are the mean ± SEM from 4 independent experiments each using macrophages

derived from a different donor: *p< 0.05, **p<0.01 (One-way ANOVA).

(b) IRF5 protein expression was analysed in total cell lysates of monocytes, M1 and M2

macrophages by Western blotting. Densitometric analysis was performed using Quantity

One software and data were normalised to actin. Shown are the mean ± SEM from 3

independent experiments presented as % of increase in IRF5 protein levels relative to

monocytes. *p<0.05 (One-way ANOVA with Dunnett's Multiple Comparison Post Test).

(c) M2 macrophages were left untreated or treated with GM-CSF (50ng/ml), IFN-

(50ng/ml), or LPS (10ng/ml) plus IFN- for 24h and total protein extracts were subjected

to Western blot analysis followed by densitometry. Data shown are the mean ± SEM

from 6 independent experiments presented as % of increase in IRF5 (protein levels

relative to untreated cells. **p<0.01 (One-way ANOVA with Dunnett's Multiple

Comparison Post Test).

(d) p50 protein expression was analysed in total cell lysates of monocytes, M1 and M2

macrophages by Western blotting. Actin was used as a loading control. Representative

blots of at least 4 independent experiments, each using cells derived from a different

donor are shown.

(e) M2 macrophages were left untreated or treated with GM-CSF (50ng/ml), IFN-

(50ng/ml), or LPS (10ng/ml) plus IFN- for 24h and total protein extracts were subjected

to Western blot analysis followed by densitometry. Data shown are the mean ± SEM

from 6 independent experiments presented as % of increase in p50 protein levels

relative to untreated cells.

Figure S2:

Plasticity of macrophage polarization

(a, c) For M2->M1 cytokine profiles, M-CSF-derived M2 macrophages at day 5 were

either left in M-CSF containing medium or exchanged for GM-CSF (100ng/ml) containing

medium and after 24h subjected to LPS stimulation (10ng/ml).

(b, d) For M1->M2 cytokine profiles, GM-CSF derived M1 macrophages at day 5 were

either left in GM-CSF containing medium or exchanged for M-CSF (100ng/ml) containing

medium and after 24h subjected to LPS stimulation (10ng/ml).

(a, b) The change in secretion of IL-12p70, IL-23 and IL-10 was determined by ELISA.

Nature Immunology: doi:10.1038/ni.1990

(c, d) The change in IRF5 protein expression was analysed by Western blotting followed

by densitometric analysis using Quantity One software. The IRF5 measurements were

normalised to actin. Shown are the mean ± SEM from 4 independent experiments

presented as % of increase (c) or decrease (d) in IRF5 protein levels relative to the

initial condition: *p<0.05 (One-way ANOVA with Dunnett's Multiple Comparison Post

Test).

(e) For M2->M1->M2 cytokine profiles, M2 macrophages at day 5 were either left in M-

CSF containing medium, or exchanged for IFN- (50ng/ml) containing medium, or

further reversed to M-CSF containing medium (100ng/ml) and after 48h subjected to

LPS stimulation (10ng/ml).

The amount of secreted IL-12p70, IL-23 and IL-10 protein following 24h of LPS

stimulation was determined by ELISA. Data shown are the mean ± SEM of 3

independent experiments each using macrophages derived from a different donor.

Figure S3:

IRF5 defines the production of lineage specific cytokines in human

macrophages

(a) M2 macrophages were infected as in (Fig. 2 A) and left unstimulated or stimulated

with LPS (10ng/ml) for 4, 8, 24, 32 and 48h. The amount of secreted IL-12p70 and IL-

23 protein was determined by ELISA. Data shown are the mean ± SD and are

representative of 3 independent experiments each using macrophages derived from a

different donor.

(b) M2 macrophages were infected with adenoviral vectors encoding IRF5, IRF3 or

empty vector (pENTR) and stimulated with LPS for 24h. The amount of secreted IL-1

and TNF protein was determined by ELISA. Data show the trend of cytokine secretion in

4-8 independent experiments each using M2 macrophages derived from a different

donor: ***p<0.001, ** p<0.01 (One-way ANOVA with Dunnett's Multiple Comparison

Post Test).

(c) M1 macrophages were transfected with siRNA targeting IRF5 (siIRF5) or control

siRNA (siC). ~50% of IRF5 protein was degraded estimated by serial dilutions of the siC

control sample analysed by Western blotting.

Figure S4:

IRF5 induces T cell proliferation and expression of T cell subset specific

markers

(a) M2 macrophages were infected with adenoviral vectors encoding IRF5 or empty

vector (pENTR) and cultured with T lymphocytes from unmatched donors. After 4 days,

cells were stimulated for 3h with PMA/ionomycine/Brefeldin A. The percentage of

Nature Immunology: doi:10.1038/ni.1990

CD4+/IL-17+ or CD4+/IFN+ cells was determined by ICC staining and representative

FACS plots are shown.

(b) M2 macrophages were infected with adenoviral vectors encoding IRF5, IRF3 or

empty vector (pENTR) and cultured in triplicate for 72h with T lymphocytes from

unmatched donors. Cultures were pulsed with thymidine for the last 16h to measure

DNA synthesis. Control cultures contained macrophages or T-cells alone. Results are

expressed as counts per minute (CPM) minus proliferation of macrophage-only cultures.

Data are shown as the mean ± SEM of 6 independent experiments each using cells

derived from a different donor: ***p<0.001 (One-way ANOVA with Dunnett's Multiple

Comparison Post Test).

(c, e) M2 macrophages were infected with adenoviral vectors encoding IRF5, IRF3 or

empty vector (pENTR) and cultured with T lymphocytes from unmatched donors. After 4

days, cells were stimulated for 3h with PMA/ionomycine/Brefeldin A and IFN- and IL-17

expression were determined by ICC staining. Data are shown as the percentage of IFN-

+/IL-17- (c) or IFN--/ IL-17+ (e) cells ± SEM of 8 independent experiments.

(d, f) M2 macrophages were infected with adenoviral vectors encoding IRF5, IRF3 or

empty vector (pENTR) and cultured with T lymphocytes from unmatched donors. IFN-

(d) or IL-17A, IL-17F, IL-21, IL-22, IL-26, IL-23R (f) mRNA expression was analysed

after 2 days of co-culture. Data are shown as the mean ± SEM of 6-9 independent

experiments each using cells derived from a different donor: *p<0.05, **p<0.01,

***p<0.001 (One-way ANOVA with Dunnett's Multiple Comparison Post Test).

Figure S5:

IRF5 drives expression of IL12p40 mRNA and production of selected M1 and M2

cytokines

(a) M2 macrophages were infected with adenoviral vectors encoding IRF5 or empty

vector (pENTR) and left unstimulated or stimulated with LPS (10ng/ml) for 4, 8, 16 and

24h. IL12p40 mRNA expression was compared to unstimulated pENTR control cells. Data

shown are the mean ± SD and are representative of 3 independent experiments each

using macrophages derived from a different donor.

(b) M1 macrophages were transfected with siRNA targeting IRF5 (siIRF5) or control

siRNA (siC) and left unstimulated or stimulated with LPS (10ng/ml) for 2, 4, 8, 16 and

24h. IL-12p40 mRNA expression was compared to control cells transfected with non-

targeting siRNA (siC). Data shown are the mean ± SD of representative experiments

presented as a % of reduction in IL-12p40 mRNA levels by siIRF5.

Nature Immunology: doi:10.1038/ni.1990

(c, d, e) M2 macrophages were infected with adenoviral vectors encoding IRF5 or empty

vector (pENTR) and stimulated with LPS for 24h. The amount of secreted CCL5 (c);

CCL2, CCL13 (d) or CCL22, CXCL10 (e) protein was determined by ELISA. The amount

of CD40 (c) or CD163 (c) surface expression was determined by FACS and expressed as

MFI. Data are shown as the mean ± SEM of 4-6 independent experiments each using

M2 macrophages derived from a different donor: ** p<0.01, *p<0.05 (Student's t-test).

Figure S6:

IRF5 activates transcription of the human IL-12p35 gene

HEK-293-TLR4/MD2 cells were co-transfected with IL-12p35 wild type (IL-12p35-Luc wt)

reporter plasmid or the IL-12p35 plasmid in which site-specific mutation was introduced

into the ISRE site as described in Ref 37 and constructs coding for IRF5 (black bars), IRF5

DNA-binding mutant (IRF5DBD) (grey bars) or empty vector (pENTR) (white bars).

Luciferase activity was measured 24h post-infection. Data are presented as the mean ±

SD from a representative out of 3 independent experiments.

Figure S7:

Impaired production of M1 cytokines in Irf5-/- mice

Littermate wild type (n = 10) and Irf5-/- (n = 10) mice were intraperitoneally injected

with LPS (20ug/ml). Mice were sacrificed after 3h and serum concentrations of Il-1, Il-6

and Tnf were measured by BDTM cytrometric bead assay. Data are shown as the mean ±

SEM of 8-10 serum samples from 3 independent experiments: ** p<0.01, *p<0.05

(Student's t-test).

Nature Immunology: doi:10.1038/ni.1990

Figure S1

d

cb

Mono

GM-CSF

M-CSF

0

50

100

150

200

250

300

350

IRF5

pro

tein

leve

l, no

rmal

ised

(%)

*

*

n=3

untre

ated

GM-CSF

IFN-γ

LPS+IF

N-γ0

25

50

75

100

125

150

175

IRF5

pro

tein

leve

l, no

rmal

ised

(%)

** ****

n=6

untre

ated

GM-CSF

IFN-γ

LPS+IF

N-γ0

100

200

300

p50

prot

ein

leve

l, no

rmal

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(%)

n=3

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M-CSF

GM-CSF

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2p70

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ml

IL-23

M-CSF

GM-CSF

0

50

100

150

200

250

IL-2

3, p

g/m

l

IL-10

M-CSF

GM-CSF

0

5

10

IL-1

0, n

g/m

l

n=4 n=4 n=5

** **

*

a

e

actin

- + - + - +LPS:Mono

M-CSF

GM-CSF

p50

M1M2

Nature Immunology: doi:10.1038/ni.1990

Figure S2

IL-12p70

M-CSF

GM-CSF

0

50

100

150

200

IL-1

2p70

, pg/

ml

IL-23

M-CSF

GM-CSF

100

200

300

400

IL-2

3, p

g/m

l

IL-10

M-CSF

GM-CSF

0

500

1000

1500

2000

IL-1

0, p

g/m

l

M2->M1

a

M1->M2

b

c

IL-12p70

GM-CSF

M-CSF

0

50

100

150

IL-1

2p70

, pg/

ml

GM-CSF

M-CSF

0

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600

800

1000

IL-2

3, p

g/m

l

IL-23

GM-CSF

M-CSF

0

200

400

600

800

IL-1

0, p

g/m

l

IL-10

M2 M10

50

100

150

200

n=4

*

IRF5

pro

tein

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l, no

rmal

ized

(%)

d

M1 M20

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100

n=4

*

IRF5

pro

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(%)

M2->M1->M2

M-CSF

IFN-γ

M-CSF

0

1000

2000

3000

4000

IL-1

2p70

, pg/

ml

e

IL-12p70

Nature Immunology: doi:10.1038/ni.1990

0 8 16 24 32 40 480

5

10

pENTR IRF3 IRF5

time after LPS, hours

IL-1

2p70

, ng/

ml

IL-23

0 8 16 24 32 40 480

200

400

600

800

1000

time after LPS, hours

IL-2

3, p

g/m

l

IL-12p70a

Figure S3

c

b

IRF5

actin

100%

50%

25% siI

RF5siC

IL-1β

pENTR

IRF3

IRF5

0

10

20

30

40 **

n=4

TNF,

ng/

ml

TNF

pENTR

IRF3

IRF5

0

50

100

150

200

250

***

n=8

IL-1β ,

pg/

ml

Nature Immunology: doi:10.1038/ni.1990

a

Figure S4

n=6

***

pENTR

IRF3

IRF5

0

10000

20000

30000

CP

M

T cell proliferation CD4+/IFN-γ+b c d

IFN-γ

IL-17

pENTR IRF5

pENTR

IRF3

IRF5

0

5

10

15

20

***

n=8

% p

ositi

ve c

ells

CD4IFN-γ mRNA

pENTR

IRF3

IRF5

0

10

20

30

40 ***

n=9IF

N-g

mRN

A (A

U)

Nature Immunology: doi:10.1038/ni.1990

Figure S4

e

IL-17A mRNA

pENTR

IRF3

IRF5

0

5

10

15

***

IL-1

7 m

RNA

(AU)

n=8

IL-22 mRNA

pENTR

IRF3

IRF5

0

50

100

150

**

n=6

IL-2

2 m

RNA

(AU)

IL-23R mRNA

pENTR

IRF3

IRF5

0

20

40

60

80

100

IL-1

7F m

RNA

(AU)

IL-17F mRNA

n=5

pENTR

IRF3

IRF5

0

5

10

15

20

25

***

n=6

IL-2

1 m

RNA

(AU)

IL-26 mRNAIL-21 mRNA

f

pENTR

IRF3

IRF5

0

10

20

30

40

*

n=6

IL-2

6 m

RNA

(AU)

pENTR

IRF3

IRF5

0

10

20

30 **

n=6

IL-2

3R m

RNA

(AU)

CD4+/IL-17+

pENTR

IRF3

IRF5

0.0

0.2

0.4

0.6

0.8

1.0 ***

n=8

% p

ositi

ve c

ells

Nature Immunology: doi:10.1038/ni.1990

0 8 16 240

250

500

750

1000

pENTRIRF5

time after LPS, hours

IL-1

2p40

mR

NA

(AU

)

0 8 16 240

20

40

60

80

100

siCsiIRF5

time after LPS, hours

IL-1

2p40

mR

NA

,%in

hibi

tion

Figure S5

aIL-12p40 mRNA

bIL-12p40 mRNA

c dM1 M2

CCL22

CD40 CCL2 CD163CCL13

CXCL10

pENTR

IRF5

0

20

40

60

80

100

**

n=4

CC

L22,

ng/

ml

pENTR

IRF5

0

100

200

300

400

*

n=5

CD

40, M

FI

pENTR

IRF5

0

2

4

6

8

10

*

n=4

CC

L2, n

g/m

l

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IRF5

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150

**

n=6

CC

L13,

pg/

ml

pENTR

IRF5

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1

2

3

*

n=5C

D16

3, M

FIx1

000

e

pENTR

IRF5

0

5

10

15

***

n=6

CXC

L10,

ng/

ml

pENTR

IRF5

0

1000

2000

3000

4000*

n=5

CC

L5, p

g/m

l

CCL5

Nature Immunology: doi:10.1038/ni.1990

Figure S6

IL-12p35-luc

wt

ISREmut wt

ISREmut wt

ISREmut

0

10

20

30

pENTR IRF5 IRF5DDBD

luci

fera

se a

ctivi

ty (A

U)

Nature Immunology: doi:10.1038/ni.1990

wtIrf5

-/-0

25

50

75

100

125

*

n=8

IL-1β ,

pg/

ml

IL-1β TNF

wtIrf5

-/-0

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400

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800

*

n=10

TNF,

pg/m

l

wtIrf5

-/-0

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20

30

40

50

*

n=10

ILl-6

, ng/

mL

IL-6

i

Figure S7Nature Immunology: doi:10.1038/ni.1990

Supplementary Table S1:

Genes up-regulated by ectopic IRF5

Gene symbol Entrez Gene ID Fold change

CXCR3 2883 2.9

CXCR4 7852 3.8

CXCR5 643 9.4

CXCR7 57007 4.1

EBI3 10148 38.2

TNFSF4 7292 17.9

TNFSF9 8744 15.0

LTA 4049 13.1

LTB 4050 8.9

IFN- 3458 2.5

CCL1 6346 18.6

CCL3 6348 8.1

CXCL5 6374 7.4

IL-19 29949 4.2

IL-32 9235 4.2

Genes down-regulated by ectopic IRF5

Gene symbol Entrez Gene ID Fold change

CSF1R 1436 0.28

IL-1R2 7850 0.28

IL-1RA 3557 0.38

TGF1 7045 0.42

Nature Immunology: doi:10.1038/ni.1990

Supplementary Table S2: putative IRF5 binding sites in -2000/+2000 nt

relative to the TSSs of selected genes

Table S2.1 – genes up-regulated by IRF5

Gene Number of IRF sites Sequence Strand Core sim Matrix sim

TNFSF4 9 aatgtactttacaTTTCccac - 1 0.88

cacaaacTTTCtcttttaagt - 1 0.903

tgcctcaTTTCcattttttct - 1 0.851

agatcttTTTCtttttctttg - 1 0.932

agaccagTTCCactttcccat - 0.75 0.892

taaaataTTTCcatttttctt - 1 0.851

atttttcTTTCactttattct - 1 0.965

attattttttcttATTCagta - 0.937 0.885

cacctccaatGAAAccagaat + 1 0.957

EBi3 8 ctctgtgTTTCtctttctgtt - 1 0.948

gtttctcTTTCtgtttccatc - 1 0.959

gtatctcTGTCactttctctg - 0.75 0.854

ctgtcacTTTCtctgtcatct - 1 0.858

cctttggTTTCtttttggttt - 1 0.925

tttttggttttgtTTTTtgag - 0.75 0.726

ccagGAATtcgagaccagcct + 0.75 0.741

gcaacatagtGAAAccggacc + 1 0.884

TNFSF7 14 ctgcctcattcagTTTCtgtt - 1 0.883

cattcagTTTCtgtttctgtt - 1 0.98

gtttctgTTTCtgttttcaca - 1 0.89

agggGAATaggaagattgaat + 0.937 0.877

catgGAAAtggaagatgactc + 1 906

ccagGAAAacgattcgggaaa + 1 0.725

aaaataaaatGAAAtaaaatc + 1 0.876

gagggaaacgGAGAgggggag + 0.758 0.864

agaaGAAGgggaaagaaagaa + 0.821 0.863

cggagaaagaGAAAaaagaca + 1 0.939

aagaagaaagGAAAagaaaaa + 1 0.941

aaaagaaaaaGAAAgaaagga + 1 0.939

aaaggaaaaaGAAAgaagaaa + 1 0.955

agaagaaagaGAAAaaaagaa + 1 0.939

TNFSF9 6 tcaacacTGTCcctttcttgc - 0.758 0.871

gagacaaagaGAGActaaaga + 0.75 0.818

cagaGATAacggagccagaga + 0.75 0.69

agggagaaagGAACctggagc + 0.75 0.814

gccggaaacgGAAAggagagc + 1 0.967

gtaccccTCTCcctttcaaga - 0.758 0.851

CCL1 6 ttcatgaTTTCaatgcctaga - 1 0.943

aacaaaaaggGAAAattcccc + 1 0.879

aatagaaatgGCAAatatcta + 0.774 0.865

gtgtGAATatgaatttgggta + 0.937 0.898

actctacTTTCtctatcagtg - 1 0.866

actggaaagaGCAAgggaacc + 0.774 0.851

Nature Immunology: doi:10.1038/ni.1990

CCL3 12 gctttcaTTTCtttttctact - 1 0.937

caaagaaatgGGAAatcaaga + 0.758 0.858

ccattgaacaGAAActtcagc + 1 0.852

ttcagaaaaaGAAAaaaataa + 1 0.932

ctcatgcTTTCtattcctcca - 1 0.973

cccccagattccaTTTCccca - 1 0.915

gcccccaagaGAAAagagaac + 1 0.941

cttggtcTTTCtctttaagac - 1 0.878

cagagaaacaGAGAacccact + 0.758 0.863

agaggaaaggGACAggaagaa + 0.758 0.851

aatttattttcgaTTTCacag - 1 0.992

agtttggttttgtTTTCctgg - 1 0.869

IL-2Ra 5 ggagggtTTTCtttttgttaa - 1 0.883

aattGAACttgaaaaaaaaaa + 0.821 0.875

caatgaatttcctTTTAttct - 0.758 0.868

tgcaaattttaaaTTTCattc + 1 0.885

ccaaGAACaggaaaatcttga + 0.821 0.896

CCR7 9 tcaagaaagtGAAAagatgat + 1 0.946

aaaaaaaaaaGAAAaaagaaa + 1 0.951

tcaacaaTTTCacttctaggt - 1 0.814

agctaaaaggGAAAacagccc + 1 0.907

ttcaGAATaggaaaatctata + 0.937 0.936

aaagGAAAaggaagggagggg + 1 0.862

accccagactaggTTTAgggg - 0.75 0.693

gggagggTTTCtgttacacaa - 1 0.823

tacacaaaatGAAAactccca + 1 0.926

CXCR5 8 ttggtgaTTTCactttttttt - 1 0.963

tttttttTTTCttttagagac - 1 0.951

aagttgaTTTCatttttgtct - 1 0.931

tgagGAAAatgaaggtttgga + 1 0.918

gtggtggTTTCattacaagtt - 1 0.949

gaaaGAAGctgaaatgcttga + 0.821 0.867

caaaaaaacaGAAAagaccca + 1 0.856

aatgcaaaatGAAAacatggg + 1 0.926

IL23a 6 accaggaagtGAAAcaaagag + 1 0.859

gggtagaTTTCcatttttttt - 1 0.882

gtgatgaaatcggTGTCagtg - 0.75 0.727

ccatGAAAccaggaccatcca + 1 0.693

ctgaGAAAaagaagcccgttt + 1 0.862

ttgggaaagaGAAAtcgatgg + 1 0.958

TNF 10 agccaagactGAAAccagcat + 1 0.96

gggtcagaatGAAAgaagaag + 1 0.945

agaagaaaccGAGAcagaagg + 0.758 0.878

caggcagGTTCtcttcctctc - 0.75 0.835

ccctGGAAaggacaccatgag + 0.75 0.718

catgagcactGAAAgcatgat + 1 0.953

ttctgggtttgggTTTGgggg - 0.75 0.781

ggggGAAAtttaaagttttgg + 1 0.892

Nature Immunology: doi:10.1038/ni.1990

IL12p35 9 gctctcaTTTCtttttctttc - 1 0.937

atgtaaattaGAAActgtgtc + 1 0.887

gcgaacaTTTCgctttcattt - 1 0.965

atttcgcTTTCattttgggcc - 1 0.94

atccGAAAgcgccgcaagccc + 1 0.701

gaaggagacaGAAAgcaagag + 1 0.943

tcgtagaggaGAAActgaggc + 1 0.846

cacctggtctgggTTTCcctg - 1 0.795

tgtctccagaGAAAgcaagag + 1 0.94

IL12p40 8 gttacagTTTTttttttttaa - 0.75 0.829

cccgggtTTCCcatttccccc - 0.758 0.853

gagggtaTTTCactttctgct - 1 0.947

aagtcagTTTCtagtttaagt - 1 0.85

tttctagtttaagTTTCcatc - 1 0.879

tgtacagTGTCcattttaaaa - 0.75 0.817

gttaaaaaatGAAAagctatt + 1 0.887

actgGAATctgaaattgtatg + 0.937 0.951

Table S2.2 – genes down-regulated by IRF5

Gene name Number of IRF sites Sequence Strand Core sim Matrix sim

CD163 10 ggatgaaactGGAAaccatca + 0.759 0.865

ttgctaatttttgTTTCacca - 1 0.862

gtatGAAAtggaacctcagct + 1 0.905

gtagcctTTTCattttcatga - 1 0.934

tcatGAAAgtgaagtgatttt + 1 0.871

gatgttgTTTCcattttccag - 1 0.886

gccctctTTTCtttttcacag - 1 0.932

caaaggaggaGAAActtcaga + 1 0.82

agataagTTTCagtctagcgt - 1 0.812

ctagtcttttcatCTTCataa - 0.821 0.864

IL-10 7 cttgttatttcaaCTTCttcc - 0.821 0.878

acaactaaaaGAAActctaag + 1 0.841

acgcGAATgagaacccacagc + 0.75 0.7

tgcaaaaattGAAAactaagt + 1 0.928

caggGAAAtttaaattgcctc + 1 0.888

cttctgcTTTCccttcaaaat - 1 0.983

ttgctcaTTTCtctttgagca - 1 0.895

MS4A6A 12 aaagacaagaGAAAggagaat + 1 0.946

agccaaaatgGAAAaaaaaag + 1 0.951

cgctGAGAactaatccagcct + 0.75 0.724

tgactggctctggTTTCcttg - 1 0.724

tgggGAATtagaaaagcaaga + 0.937 0.89

ttagaaaactGAAGcttcaag + 0.75 0.826

aatttaacttGAAActccttg + 1 0.817

gaaggagTATCtgtttttaac - 0.75 0.81

ccgtGAAAagggatccaagct + 1 0.714

tccatacTATCagtttctttc - 0.774 0.885

Nature Immunology: doi:10.1038/ni.1990

ctatcagTTTCtttctctaat - 1 0.844

gactgagTTACtgtttttgga - 0.75 0.816

CXCL10 9 caactaaaatAAAActgtcac + 0.75 0.813

tttgcctTTCCggtttcccac - 0.758 0.869

cttttttTTTCtttttctttg - 1 0.951

caacctgTTTCccttctgtct - 1 0.817

atgatgtTTTCattcagggac - 1 0.817

tataagacgtGAAActtgttt + 1 0.814

tttggaaagtGAAAcctaatt + 1 1

catgcagagtGAAActtaaat + 1 0.814

ttaggaaacgGCAAtcttggg + 0.75 0.883

CLEC4a 5 gacttggtgtgggTTTCagaa - 1 0.77

gaaagacaatGAAAgcaggtt + 1 0.856

gagaGAAAtccactccagttc + 1 0.701

tagagtacaaGAAActatggg + 1 0.818

actatagTTACgctttctaaa - 0.758 0.885

IL-1R2 isoform1 13 ggcatggttttgcTTCCtctc - 0.75 0.713

ccaaatatttcacCTTCtaat - 0.821 0.871

gtaaGAAAatgaagatctgca + 1 0.91

ctctGAAAacaaaacaaaaca + 1 0.748

gaaaaataggGAAActtatgc + 1 0.811

cagagaaacaGAGAcagaaag + 0.758 0.858

cagagaaacaGACAgagatag + 0.758 0.856

gacaGAGAcagagaccaagac + 0.75 0.713

gctctcgggtggtTTTCtggg - 1 0.706

ctcagggTCTCcatttccacc - 0.758 0.862

ctctctgTCTCtgtttctctc - 0.758 0.858

ctctatgTCTCtgtttctccc - 0.758 0.858

taattgcattcccTTTTgggg - 0.75 0.701

IL-1R2 isoform2 10 ttcactcTTCCagtttctcac - 0.758 0.859

tttgctcTCTCcctttcctgg - 0.758 0.851

gaacaaaattTAAActgttct + 0.75 0.833

acgatggcttcacTTACatgg - 0.75 0.693

ttataagacaGAAAgcaaaat + 1 0.96

tttaGAAActgaagctgtatc + 1 0.913

tgaacactttcttTTTGcagc - 0.758 0.862

gggaGAATttgaagcctgtgg + 0.937 0.871

ttgaatgagcGAAAacatgag + 1 0.954

ccatctgTATCagtttctgcc - 0.774 0.868

IL-1RA isoform1 9 ggaaGAAAtccaatctatttc + 1 0.697

aatctagtttctgATTCttta - 0.937 0.928

agagGAAAttgaaggccctta + 1 0.898

attctgaTTTCattatatata - 1 0.959

ctctaattttaagTTTCtaat - 1 0.876

taaataaaatGAAAtaaaata + 1 0.876

agaggaaatgGATAtagagag + 0.774 0.851

actcggactgGAAActggaag + 1 0.818

Nature Immunology: doi:10.1038/ni.1990

actggaaactGGAAgggtgag + 0.758 0.859

IL-1RA isoform4 9 tacaaaaaatGAAAatgaact + 1 0.906

cacacagTTTGaattcctggg - 0.75 0.815

tgggaaaactGAATctcaaaa + 0.75 0.85

ctcaGAAAaggaagctggttt + 1 0.9

ggaggaaaatGCAAattgaaa + 0.774 0.858

aatgcaaattGAAAagttgct + 1 0.874

ccttgctTTTCcctttgaatg - 1 0.858

aagaggaataGGAActgcacc + 0.75 0.821

cctcttccttcagTTTCagct - 1 0.877

Nature Immunology: doi:10.1038/ni.1990