r e s o u r c e

Transcriptional programs define molecular characteristics of classes and subsets

Michelle L Robinette1, Anja Fuchs2, Victor S Cortez1, Jacob S Lee3, Yaming Wang1, Scott K Durum4, Susan Gilfillan1, Marco Colonna1 & the Immunological Genome Consortium5

The recognized diversity of innate lymphoid cells (ILCs) is rapidly expanding. Three ILC classes have emerged, ILC1, ILC2 and ILC3, with ILC1 and ILC3 including several subsets. The classification of some subsets is unclear, and it remains controversial whether natural killer (NK) cells and ILC1 cells are distinct cell types. To address these issues, we analyzed expression in ILCs and NK cells from mouse small intestine, and , as part of the Immunological Genome Project. The results showed unique gene-expression patterns for some ILCs and overlapping patterns for ILC1 cells and NK cells, whereas other ILC subsets remained indistinguishable. We identified a transcriptional program shared by small intestine ILCs and a core ILC signature. We revealed and discuss transcripts that suggest previously unknown functions and developmental paths for ILCs.

The Immunological Genome (ImmGen) Project is a collaborative at least five subsets of mouse ILC3 cells have been reported, four effort by immunologists and computational biologists who seek, of which are found in the greatest numbers during steady state in through rigorously controlled protocols for data generation and the adult small intestine, and one in the adult large intestine. These analysis, to delineate gene-expression patterns of cell types across include CD4+ and CD4− subsets of NKp46−RORγt+ lymphoid tissue– the so as to better understand the immune response inducer (LTi)-like cells5; RORγt+T-bet+ Notch–dependent and comprehensively define its regulatory networks1. In this con- NKp46+ ILC3 cells5–9; a potential ILC3-ILC1 transitional subset that text, we investigated the global gene-expression profiles of innate has downregulated RORγt, produces IFN-γ and expresses T-bet and lymphoid cells (ILCs) from mice following the ImmGen Project’s larger amounts of the activating natural killer (NK) cell receptor stringent standards1. NK1.1 compared to NKp46+ ILC3 cells (‘ex-RORγt+ ILC3 cells’)4; and ILCs are non-T, non-B lymphocytes present throughout the body IL17-producing RORγt+NKp46− ILC3 cells in the large intestine10. Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature that show enrichment in frequency at mucosal surfaces2,3. Developing ILC1 cells have the most complicated and controversial distinction, from an Id2+ common helper-like ILC progenitor4, three classes of both of the ILC class itself and between subsets within the class. ILC1 ILCs, now known as ILC1, ILC2 and ILC3, have emerged that mirror cells and NK cells have functional similarities, mainly IFN-γ produc- npg helper T cells in both their cytokine-production profiles and their tion, and share expression of T-bet and many cell-surface markers, transcriptional circuitry2,3. Functionally, T-bet+ ILC1 cells respond such as NKp46 and NK1.1. However, NK cells are currently thought to interleukin 12 (IL-12), IL-15 and IL-18 to produce interferon-γ to have more cytotoxic potential than ILC1 cells have. Surface expres- (IFN-γ); GATA-3+ ILC2 cells react to IL-33, IL-25 and thymic stromal sion of CD127 and the integrin subunit CD49a are used to distinguish lymphopoietin to produce type 2 cytokines, including IL-5 and IL-13; ILC1 cells from NK cells in many but not all mouse tissues, as there is and RORγt+ ILC3 cells are activated by IL-1 and IL-23 to produce considerable diversity of ILC1 subsets among tissues2. Lineage-tracing IL-22 and/or IL-17. As innate sources of distinct cytokines, ILCs have experiments have shown that ILC1 cells and NK cells originate from roles in early defense against infections, modulation of the adaptive distinct progenitors4,11, and mature NK cells are dependent on the immune response, the development of lymphoid tissue, and repair factor (Eomes), whereas ILC1 cells are and homeostasis of tissues2,3. not. However, immature NK cells also share many markers with ILC1 Whereas shared transcription factors, cell-surface markers and cells12 and lack expression of Eomes12,13. functional properties of cytokine production define classes, devia- The breadth of polarization and relationships among ILC sub- tions in one or more categories by subpopulations define subsets of sets has remained incompletely understood. To better understand ILCs within the larger class. In the mouse, ILC2 seems to be the most the functional differences between ILC classes and reported subsets homogeneous class, defined by expression of the IL-7 receptor (IL-7R; within a class, we discriminated seven populations of ILCs in the also called CD127), Sca-1 and the IL-33 receptor ST2. In comparison, small intestine lamina propria (siLP) (NK cells, ILC1 cells, ILC2 cells

1Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA. 2Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA. 3Merck Research Laboratories, Palo Alto, California, USA. 4Cancer and Inflammation Program, Center for Research, National Cancer Institute, Frederick, Maryland, USA. 5A list of members and affiliations appears at the end of the paper. Correspondence should be addressed to M.C. ([email protected]).

Received 17 October 2014; accepted 22 December 2014; published online 26 January 2015; doi:10.1038/ni.3094

306 VOLUME 16 NUMBER 3 MARCH 2015 nature immunology r e s o u r c e

and four subsets of ILC3 cells); three additional subsets of ILC1 cells transcripts were specifically expressed by the index subset (Fig. 2a–h). from liver, spleen and small intestine intraepithelial lymphocytes We found the greatest number of characteristic transcripts in the siLP (siIELs); and two NK cell subsets from liver and spleen. Our find- ILC2 cells, with 100 transcripts showing expression more than two- ings provide a molecular definition of ILC classes and subsets, and fold higher than that in other subsets (Supplementary Table 1) and also identify a core signature in ILCs distinct from that in NK cells. 34 transcripts showing expression more than fourfold higher than that We also identify novel targets for future investigation and generate in other subsets (Fig. 2a). These included expected transcripts, such as a comprehensive, high-quality and publically available resource of Il13, Il5, IL4, Il9r and Il17rb (which encodes the IL-25 receptor)17–19, ILC transcriptomes. as well as several transcripts not previously shown to be expressed by ILC2 (to our knowledge), including Rxrg, Pparg, Mc5r, Dgat2 and RESULTS Alox5 (Fig. 2a). The transcriptional repressor RXRγ, which binds the Analysis of ILC frequency and diversity vitamin A metabolite 9-cis retinoic acid20, has not been previously We isolated all reported ILC subsets in the siLP of 6-week-old C57BL/6 described in ILC2 cells. However, vitamin A is known to directly male mice. We isolated ILC2 cells from wild-type C57BL/6 mice inhibit ILC2 differentiation by an unknown mechanism21, which sug- and isolated all other subsets from RORγteGFP reporter mice, which gests that RXRγ may mediate this effect. We also found previously express enhanced green fluorescent (eGFP) driven by the gene unrecognized expression of the gene encoding the encoding RORγt. These subsets included CD127− NK cells, CD127+ PPARγ (Fig. 2a), which forms heterodimers with repressor retinoid ILC1 cells, CD4−NKp46− and CD4+NKp46− LTi-like ILC3 cells, X receptors and transcriptionally mediates lipid homeostasis20. ILC2 NKp46+RORγthi ILC3 cells and NKp46+RORγtlo ILC3 cells (Fig. 1a). cells expressed several other encoding molecules linked to lipid Notably, NKp46+RORγthi and NKp46+RORγtlo ILC3 cells cannot be metabolism. These included genes encoding Dgat2, which mediates discriminated by intracellular staining of RORγt in wild-type C57BL/6 the final reaction of triglyceride synthesis; Mc5r, a receptor that causes mice, in which only one NKp46+RORγt+ subset is detectable; thus, lipid mobilization in adipocytes; and Alox5, a lipoxygenase that cata- the use of RORγteGFP reporter mice provided the unique opportu- lyzes synthesis of leukotriene A4 (Fig. 2a). ILC2 cells are known to nity to profile RORγtlo and RORγthi subsets, as described14. As the regulate the cellular immune system within visceral adipose tissues22, RORγtlo ILC3 subset had higher expression of NK1.1 than RORγthi but our data suggested that ILC2 cells might also directly sense lipids ILC3 cells had (Supplementary Fig. 1a–c), we reasoned that this and produce lipid mediators. subset would show enrichment for converted or actively converting NKp46− LTi-like ILC3 subsets expressed the second greatest ‘ex-RORγt+’ ILC3 cells. We also profiled liver CD49b+TRAIL− NK number of characteristic transcripts. As suggested by clustering cells and CD49b−TRAIL+ ILC1 cells and spleen CD127− NK cells analysis (Fig. 1e), CD4+ and CD4− LTi-like cells had overlapping and CD27+CD127+ ILC1 cells (Fig. 1a), the last of which have been gene-expression patterns. CD4+ LTi-like cells expressed only four reported but have not previously been called ‘ILC1 cells’15. Small transcripts more than twofold higher when compared to all other intestine intraepithelial ILC1 cells were isolated from the intestinal subsets, one of which was Cd4, encoding the monomorphic corecep- epithelium as NK1.1+NKp46+ (Fig. 1a). These cells are phenotypically tor CD4; in contrast, no transcripts had characteristic higher expres- distinct from NK cells as a result of imprinting with transforming sion in CD4− LTi-like ILC3 cells (Fig. 2b). However, 65 transcripts growth factor-β16, although their developmental origin and transcrip- had expression more than twofold higher in both subsets together tional relationship to siLP ILC subsets remain unclear. relative to other subsets (Supplementary Table 1), and 9 of these tran- Cytospins showed that ILC subsets were morphologically pure lym- scripts were expressed more than fourfold higher than in other subsets Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature phoid populations (Fig. 1b). We assessed the frequency of these 12 (Fig. 2b). Eight additional transcripts were expressed at least fourfold ILC subsets within the lymphocyte populations of the small intestine, higher than in other subsets by either CD4+ LTi-like or CD4− LTi-like liver and spleen in naive mice (Fig. 1c). ILCs were most abundant ILC3 cells, with differences in expression among LTi-like ILC3 subsets

npg in the siLP, followed by liver and spleen; siIEL populations had the probably due to replicate variation (Fig. 2b). Transcripts expressed at lowest frequency of ILCs. Next we sorted these populations accord- higher levels by both LTi-like ILC3 subsets included those encoding ing to the ImmGen Project’s standardized protocol for data genera- the CCR6, which has been used as a marker for tion and analyzed by means of whole-mouse genome LTi-like ILC3 cells7, and the chemokine receptor CXCR5 (Fig. 2b). array. Principal-component analysis (PCA) showed a greater degree We also found several genes not previously described in LTi-like ILC3 of diversity generated by ILC2 and ILC3 subsets than by ILC1 cells cells (to our knowledge), including Gucy1a3, Cntn1, Slc6a7, Cacna1g (Fig. 1d and Supplementary Fig. 1e). In hierarchical clustering, three and Nrp1 (Fig. 2b). Gucy1a3 encodes the α-subunit of the soluble pairs of ILC subsets were computationally indistinguishable (Fig. 1e): guanylate cyclase receptor, which transduces signals from nitric splenic and liver NK cells, RORγthiNKp46+ and RORγtloNKp46+ ILC3 oxide; however, we found no expression in LTi-like ILC3 cells of the cells, and CD4+NKp46− and CD4−NKp46− LTi-like ILC3 cells were other components of the guanylate cyclase receptor (data not shown). intermixed. All ILC1 subsets clustered separately from NK cells from Cntn1, which encodes a glycosylphosphatidylinositol-linked member the same tissue. However, siIEL ILC1 cells, siLP NK cells and siLP of the immunoglobulin family, is best known for its role in regulating ILC1 cells clustered in a separate branch of the dendrogram from axonal guidance and neural system development23 and has not previ- liver and spleen NK cells and ILC1 subsets. We concluded that beyond ously been studied in an immune context. The L-proline transporter classical polarizations, environmental factors in the small intestine encoded by Slc6a7 and the voltage-gated calcium channel encoded differentiated intestinal subsets from those in liver and spleen. by Cacna1g are similarly atypical and are not expressed in other cells of the immune system (data not shown). We concluded that LTi-like Expression profiles of individual ILC subsets ILC3 cells specifically expressed several transcripts that are unique We assessed the gene-expression profile of each sorted subset (Fig. 2a–h) in the immune system, including those encoding putative factors by identifying characteristic transcripts that were expressed at least involved in neural crosstalk. twofold or fourfold higher in the index subset than in all other profiled The remaining ILC subsets had fewer candidate characteristic mark- subsets. Heat maps demonstrate the extent to which the identified ers, probably because of multiple comparisons with other subsets in

nature immunology VOLUME 16 NUMBER 3 MARCH 2015 307 r e s o u r c e

the same class. As indicated by PCA, siLP NKp46+RORγthi ILC3 cells higher in NKp46+RORγthi ILC3 cells than in all other profiled ILCs and siLP NKp46+RORγtlo ILC3 cells had overlapping gene-expression except NKp46+RORγtlo ILC3 cells, although a heat map revealed that profiles. Sixteen transcripts showed expression that was twofold most of these genes were also expressed at lower levels by other siLP

a c T CD3+ B CD19+ – siLP silEL Liver Spleen NK CD127 SI + Spleen NKp46+NK1.1+CD127– ILC1 CD127 SI ILC3 NKp46+ RORγtlo SI ILC3 NKp46+ RORγthi SI ILC3 NKp46– CD4– SI – + + + + – ILC3 NKp46 CD4 SI NK Liver NKp46 NK1.1 CD49b TRAIL ILC2 SI ILC1 IEL NK CD49b+ Lv ILC1 CD49b– Lv – + + – siLP RORγt NKp46 NK1.1 CD127 NK CD127– Sp ILC1 CD127+ Sp d Spleen NKp46+NK1.1+CD127+ 10 NK.CD127– .Sp ILC1 NK.CD49b+ .Lv 5 – Liver NKp46+NK1.1+CD49b– TRAIL+ NK.CD127 .SI ILC1.IEL.SI 0 NK ILC3 ILC1.CD127+ .Sp ILC1 –5 ILC1.CD49b– .Lv + siLP RORγt– NKp46+NK1.1+CD127+ ILC1.CD127 .SI –10 + Io ILC3.NKp46 .RORγt .SI ILC3.NKp46+ .RORγthi.SI –15 – –

PC3 = 10.25% ILC3.NKp46 .4 .SI – + silEL NKp46+NK1.1+ –20 ILC3.NKp46 .4 .SI ILC2.SI –25 ILC2 –30 –40 + + + + 30 –20 ILC2 siLP CD127 Sca-1 ST2 KLRG1 20 10 0 0 –10 20 PC1 = 49.68% –20 –30 40 PC2 = 20.54%

ROR t+ NKp46– CD4– siLP γ e

RORγt+ NKp46– CD4+ siLP

ILC3

hi + siLP RORγt NKp46 NK.CD127– .Sp (1) NK.CD49b+ .Lv (1) NK.CD127– .Sp (2) NK.CD127– .Sp (3) NK.CD49b+ .Lv (2) Io + NK.CD49b+ .Lv (3) Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature siLP RORγt NKp46 ILC1.CD127+ .Sp (1) ILC1.CD127+ .Sp (2) ILC1.CD127+ .Sp (3) ILC1.CD49b– .Lv (1) ILC1.CD49b– .Lv (2) ILC1.CD49b– .Lv (3) ILC1.IEL.SI (1) npg b ILC1.IEL.SI (2) siLP siLP siLP siLP siLP ILC1.IEL.SI (3) CD127+ siLP RORγthi RORγtIo CD4– CD4+ NK.CD127– .SI (1) NK.CD127– .SI (2) ILC1 ILC2 ILC3 ILC3 LTi-like LTi-like ILC1.CD127+ .SI (1) ILC1.CD127+ .SI (2) ILC3.NKp46+ .RORγtIo.SI (1) ILC3.NKp46+ .RORγtIo.SI (3) ILC3.NKp46+ .RORγthi.SI (3) ILC3.NKp46+ .RORγtIo.SI (2) ILC3.NKp46+ .RORγthi.SI (2) ILC3.NKp46+ .RORγthi.SI (1) ILC3.NKp46– .4– .SI (1) ILC3.NKp46– .4– .SI (2) ILC3.NKp46– .4+ .SI (2) ILC3.NKp46– .4– .SI (3) ILC3.NKp46– .4+ .SI (1) ILC2.SI (1) siLP silEL Liver Liver Spleen Spleen ILC2.SI (2) CD127– ILC1 CD49b+ CD49b– CD127– CD127+ Expression (relative) NK NK ILC1 NK ILC1 Row min Row

Figure 1 Analysis of ILC frequency and diversity. (a) Sorting strategy for array analysis after gating on live CD45+ and CD3−CD19− cells. (b) Cytospins of cells using sorting strategies presented in a for each population (above and below images). Original length (of each panel), 14.6 µm. (c) Flow cytometry of cells from various tissues, showing the frequency of ILCs among the lymphocyte population. The gating strategy in a was used to distinguish CD3+ T cells, CD19+ B cells and ILCs within the same sample, except the siLP ILC2 cell marker KLRG1 and the spleen ILC1 cell marker CD27 were excluded and liver ILCs were distinguished with NKp46, CD49b and CD49a. T, ; B, B cell; NK, NK cell; SI, small intestine; Lv, liver; Sp, spleen. (d) PCA of gene expression by subsets of ILCs and NK cells. Numbers along axes indicate relative scaling of the principal variables. ImmGen nomenclature: spleen NK, NK.CD127−.Sp; liver NK, NK.CD49b+.Lv; siLP NK, NK.CD127−.SI; siIEL ILC1, ILC1.IEL.SI; spleen ILC1, ILC1. CD127+.Sp; liver ILC1, ILC1.CD49b−.Lv; siLP ILC1, ILC1.CD127+.SI; siLP NKp46+RORγtlo ILC3, ILC3.NKp46+.RORγtlo.SI; siLP NKp46+RORγthi ILC3, ILC3.NKp46+.RORγthi.SI; siLP NKp46−CD4− LTi-like ILC3, ILC3.NKp46−.4−.SI; siLP NKp46−CD4+ LTi-like ILC3, ILC3.NKp46−.4+.SI; and siLP ILC2, ILC2.SI. (e) Hierarchical clustering of subsets of ILCs and NK cells based on the 10% of genes with the greatest variability. ImmGen nomenclature as in d. Data are representative of two independent experiments (b,c) with n = 1–2 mice per tissue (b) or n = 2–4 mice per tissue (c) or are pooled from one to three experiments per sample with cells pooled from 3–5 mice each (d,e).

308 VOLUME 16 NUMBER 3 MARCH 2015 nature immunology r e s o u r c e

subsets (Fig. 2c). Liver and splenic ILC1 cells each expressed some but we found no transcripts with relative expression greater than characteristic transcripts with a change in expression of greater than twofold higher in siLP ILC1 cells. This suggested there were few twofold relative to their expression in all other subsets (Fig. 2d,e), characteristic factors expressed by individual ILC1 subsets among

a c lo .SI hi .SI h lo .SIhi .SI lo .SI hi .SI t t t t t t γ γ γ γ γ – .SI+ .SI – .SI + .SI – .SI + .SI + .Sp– .Lv+ .SI + .ROR+ .ROR– .4 – .4 + .Sp– .Lv + .SI + .ROR+ .ROR– .4 – .4 + .Sp– .Lv + .SI + .ROR+ γ.ROR– .4 – .4 – .Sp+ .Lv – .SI – .Sp+ .Lv – .SI – .Sp + .Lv – .SI 7 6 6

NK.CD127NK.CD49bNK.CD127ILC1.IEL.SIILC1.CD127ILC1.CD49bILC1.CD12ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC2.SI NK.CD127NK.CD49bNK.CD127ILC1.IEL.SIILC1.CD127ILC1.CD49bILC1.CD127ILC3.NKp4ILC3.NKp4ILC3.NKp46ILC3.NKp46ILC2.SI NK.CD127NK.CD49bNK.CD127ILC1.IEL.SIILC1.CD127ILC1.CD49bILC1.CD127ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC2.SI

Nmbr Hist1h2bb Hes1 Fah Gpx8 Pdcd1 B3galt2 2010012O05Rik Ccl1 Gjb2 Rad51l1 Cym Upp1 48314216l19Rik Lrrc52 Dpep2 Cma1 Slc7a8 Gstm5 Nrarp ll9r Eps8l3 Gm10522 Pparg II1r2 Cyp17a1 ll4 Gda Mcam Ccr8 Ryk Cdc20b 4930412O12Rik Capg Lair1 Ptgir Dusp4 Sord A630001O12Rik Tmtc2 As3mt Ppp2r3a A830080D01Rik Itgam Cmklr1 Alox5 Ccne2 Expression (relative) Car5b Rxrg St5 Hs3st1 Prr5l Row min Row max ll17rb S1pr5

ll13 – .Lv A430084P05Rik ll1rl1 d Acpl2 Ccr4 Zeb2 Dgat2 Klra1 Stxbp6 ILC1.CD49b Expression (relative) ll5 Row min Row max Neb Tnfsf10 Tph1 Cd200r2 Mc5r LOC100503878 lo .Sl hi .Sl t t Calca i γ γ Cd3g R ll6 – .Sl + .Sl Expression (relative) + .SI + .ROR+ .RO– 4 – .4 Ptpn13 – .SI 7 Lpcat2 Row min Row max Ar + .Sp Acer2 e NK.CD127 ILC1.CD12ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC2.SI Cybb Expression (relative)

ILC1.CD127 Cd83 Row min Row max Pde7b Csf2 b – .SI + .SI H2-Ob Ramp3 – .4 – .4 Sidt1 6 Cnnm2 Cd22 Rora Treml2 Epas1 Gpr15 Lztfl1

Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature ILC3.NKp4ILC3.NKp46 Dapl1 Irak3 Cd3e Gjb2 Cd3d Tiparp Serpine2 Expression (relative) Maff Fermt2 Atf3 Sdc2 Row min Row max Fam110a npg Cacna1g Odc1 Slc6a7 Rnf19b f Idi1 Parvb Ern1 Dsg2 ILC1.IEL.SI Ifrd1 Olfr1342 siLP Tex2 Pcyt1a Gm626 Itgae Gucy1a3 Dgat1 Expression (relative) Igfbp4 Nrip1 Per1 Cxcr5 Row min Row max Tgif1 P2ry1 Nr4a1 g – .SI Ccr6 Bhlhe40 Ptges Csrnp1 Cntn1 Nfkbia Stom NK.CD127 Sik1 Irs2 Nrp1 Cd69 Gria3 Tfam Dtx4 Hmgn3 Vegfa Arrdc4 Cd4 II2ra Ccbl2 Expression (relative) Expression (relative) Expression (relative) Row min Row max Row min Row max Row min Row max

Figure 2 Characteristic transcripts of individual ILC subsets. Transcripts upregulated more than fourfold (red font) or twofold (black font) in individual subsets (a,d–g), two similar subsets (b,c,h) or all subsets from siLP (i), based on pairwise comparisons between the index subset(s) (in bold above heat map) and all other subsets (full gene lists, Supplementary Table 1). For similar ILC3 cell subsets consisting of NKp46−CD4+ LTi-like and CD4− LTi-like cells (b) or NKp46+RORγthi and NKp46+RORγtlo cells (c), some transcripts had expression that was more than fourfold higher (b) or twofold higher (c) in one subset but not the other; in this case, blue indicates shared transcripts expressed by both subsets. Gray (b, right margin) indicates four transcripts with twofold higher expression in CD4+ LTi-like ILC3 cells than in CD4− LTi-like ILC3 cells and fourfold higher expression in CD4+ LTi-like ILC3 cells than in all other subsets. ImmGen nomenclature as in Figure 1. Data are pooled from one to three experiments per sample with cells pooled from three to five mice each; two to three replicate samples are shown per subset.

nature immunology VOLUME 16 NUMBER 3 MARCH 2015 309 r e s o u r c e

all ILCs and NK cells. Unexpectedly, the only transcript that showed by Nr4a1) (Fig. 2i), were expressed at levels similar to those of expression greater than twofold higher in siIEL ILC1 cells compared lineage-defining transcription factors (Fig. 3a). Collectively, these to other ILC subsets was Itgae, which encodes CD103 (integrin αEβ7) data suggested a substantial role for the intestinal microenviron- (Fig. 2f). Human IEL ILC1 cells express CD10316, but it was not pre- ment in the expression of certain transcription factors, which might viously known to be expressed by mouse IEL ILC1 cells, which lack subsequently have diverging roles among ILC classes. Analysis of surface expression of CD103; this would suggest post-transcriptional chemokines and their receptors (Fig. 3b), as well as of cytokines and regulation of CD103 in mouse IEL ILC1 cells. Focusing on NK cells, their receptors (Fig. 3c), revealed both shared and distinct expres- we identified four genes with expression that was twofold higher in sion patterns. Beyond the known signature cytokine and chemokine siLP NK cells than in all ILCs (Fig. 2g). Splenic and liver NK cells circuitries, we identified a candidate feed-forward loop for ILC2 cells, expressed no characteristic transcripts. However, when we assessed which expressed both the chemokine receptor CCR8 and its ligand both liver and spleen NK cells as a group, we found 25 transcripts with CCL1 (Fig. 3b). We also identified ILC2 cell expression of Bmp7 and expression that was at least twofold higher than in all other subsets, Bmp2, the latter of which encodes a protein known to modulate intes- although siLP NK cells, IEL ILC1 cells and splenic ILC1 cells also tinal peristalsis by binding the BMP receptor on enteric neurons33. expressed these transcripts at lower levels (Fig. 2h). We concluded In addition, we found expression of Il2 in several ILC populations that within our dataset, the mRNA profiles of ILC2 cells and LTi-like (Fig. 3c), which suggested that ILCs might be able to activate T cells ILC3 cells were unique, whereas the profiles of NKp46+ ILC3 cells, or other ILCs through signaling via its receptor, IL-2R. ILC1 cells and NK cells showed considerable overlap. Shared and distinct expression profiles among siLP subsets A transcriptional signature shared by all siLP subsets We next focused our analysis of transcriptional profiles on the four We next sought to determine whether there were any transcripts that major CD127+ ILC subsets within the siLP: ILC1 cells, ILC2 cells, were expressed in all subsets from an individual tissue among siLP, NKp46+ RORγthi ILC3 cells and CD4− LTi-like ILC3 cells (Fig. 3d). liver and spleen. Given that siLP NK cells and ILC1 cells were found to Comparison of siLP ILC subsets revealed overlapping patterns of gene cluster further from liver and splenic subsets by hierarchical clustering expression that were not identified in individual subset signatures and PCA, we focused on the siLP (Fig. 1d,e). Pairwise comparisons of (Fig. 3d and Supplementary Table 2). For example, ILC2 cells and all subsets from the siLP with remaining subsets from liver and spleen LTi-like ILC3 cells shared 17 transcripts, including Arg1 and Ret. revealed that all siLP subsets expressed a core 35-transcript signa- Arginase-1 (encoded by Arg1) marks fetal and adult ILCs and facili- ture (Fig. 2i), which included several transcription factor–encoding tates the identification of developing ILCs in the siLP34. The receptor transcripts such as Rora, Atf3, Nr4a1, Maff, Epas1, Bhlhe40 and Per1. tyrosine kinase encoded by Ret is also expressed by fetal CD11c+ Furthermore, all siLP-resident ILCs had high expression of transcript lymphoid tissue initiator cells and is required for the development of encoding the activation marker CD69 and varied expression of Csf2, Peyer’s patches35, but it has not, to our knowledge, been previously which encodes the cytokine GM-CSF. Although the production of reported to be expressed by fetal or adult ILCs, including LTi or GM-CSF by ILC2 cells18, ILC3 cells24,25 and NK cells26 is known, LTi-like ILC3 cells. Together these results suggested that, at least its production by ILC1 cells has not been reported, to our knowl- in fetal mice, ILC2 cells and LTi-like ILC3 cells share a common edge. Thus, ILC subsets in the siLP seemed to be more activated than progenitor34, although their functional relevance in adult siLP ILCs in other tissues, probably because of their constant exposure ILCs remains to be investigated. ILC1 cells and ILC2 cells shared to varied environmental signals from the microbiome and incom- 19 transcripts, including Ets2. Ets-1 and Ets-2 interact with Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature ing nutrients, including well-documented transcriptional activa- of the Id family, and whereas Ets-1 has been linked to the early tors such as vitamin A21,27 and ligands of the transcription factor development of NK cells36, Ets-2 has not. Thus, Ets-2 might be AhR (aryl hydrocarbon receptor)6,28. relevant to the development or maintenance of ILC1 and ILC2 cells. + npg NKp46 and LTi-like ILC3 cells have long been known to share Transcription factors, cytokines and chemokines of ILC subsets many characteristics, owing to their mutual production of IL-22 To address broad patterns of gene expression among ILC subsets and expression of RORγt. However, NKp46+ ILC3 cells and NKp46+ and classes, we investigated the expression of previously reported ILC1 cells shared higher relative expression of a greater number of and other (unreported) transcription factors, chemokines, cytokines transcripts (Tbx21, Ifng and Il12rb) than did NKp46+ ILC3 cells and and other secreted factors. The transcription factors with the highest LTi-like ILC3 cells (Fig. 3d and Supplementary Table 2). Although relative expression included the well-documented ILC-defining Id2 T-bet is required for the development of NKp46+ ILC3 cells8–10, these (encoded by Id2), the ILC3 class–defining RORγt (encoded by Rorc), cells produced little IFN-γ in response to IL-12 and IL-23 (data not the ILC1- and NKp46+ ILC3-defining T-bet (encoded by Tbx21) and shown). Because IFN-γ is well documented as being post-transcrip- the NK cell–defining Eomes (encoded by Eomes) (Fig. 3a). ILC2 cells tionally regulated37, the presence of the Ifng transcript in NKp46+ showed higher expression of the ILC2-defining transcription factors ILC3 cells suggested that T-bet might be sufficient to induce tran- GATA-3 (encoded by Gata3) and RORα (encoded by Rora), but these scription but that other factors are needed for protein production, were also expressed by all ILCs (Fig. 3a), consistent with an early such as bacterial infections in vivo4. In addition to their shared tran- role in ILC development, at least for GATA-3 (ref. 19). Nfil3, which scripts, NKp46+ ILC3 cells and NKp46+ ILC1 cells had significantly encodes the transcription factor NFIL3 (also known as E4BP4), is different expression (by greater than twofold) of 213 genes, with the required for the development of NK cells29,30, ILC2 cells and ILC3 genes upregulated in NKp46+ ILC3 cells including many genes that cells31,32, and had its highest expression in siLP subsets; NKp46+ ILC3 were also expressed at higher levels by LTi-like ILC3 cells (Fig. 3e). cells, ILC1 cells and NK cells showed the highest Nfil3 transcript lev- Thus, NKp46+ ILC3 cells had a transcriptional profile with character- els, followed by LTi-like ILC3 and ILC2 cells, whereas much lower istics intermediate between those of NKp46− LTi-like ILC3 cells and Nfil3 transcript levels were present in liver and spleen ILC1 and NK NKp46+ ILC1 cells, which might enable functional plasticity. Their cells (Fig. 3a). Furthermore, two transcription factors identified in functional polarization toward ILC3 or ILC1 cells probably depends the siLP signature, ATF3 (encoded by Atf3) and Nur77 (encoded on the tissue microenvironment.

310 VOLUME 16 NUMBER 3 MARCH 2015 nature immunology r e s o u r c e

As discussed above, a pairwise comparison did not identify char- also had substantial expression of Il21r, which encodes a member of acteristic transcripts in siLP ILC1 cells compared to all profiled ILC the common γ-chain cytokine family (Fig. 3d). When we included an subsets. However, in comparisons only to siLP ILC2 cells and ILC3 additional comparison between ILC1 cells and NK cells in the siLP, subsets, we found 75 transcripts expressed at least twofold higher we found that ILC1 cells expressed only four transcripts at least two- in ILC1 cells (Fig. 3d). For example, ILC1 cells demonstrated a fold higher than other siLP subsets: Gpr55, Trat1, Mmp9 and Cpne7 greater cytotoxic capacity, as indicated by their expression of Gzma (Supplementary Table 2). Thus, although ILC1 cells from the small and Prf1 (Fig. 3d), which respectively encode granzyme A and per- intestine were more like NK cells than were other ILC subsets from forin, although this might have been due to an imperfect distinction the small intestine, they showed no obvious characteristic markers between siLP ILC1 cells and NK cells (discussed below). ILC1 cells when we included NK cells in our comparisons.

Io .SI hi .SI Io .SIhi .SI Io .SI hi .SI t t a t t b t t c – .SI + .SI – .SI+ .SI – .SI + .SI + .Sp – .Lv + .SI + .ROR+ γ.ROR–γ.4 – .4 – .Sp + .Lv – .SI + .Sp– .Lv+ .SI + .ROR+ .RORγ – .4γ – .4 + .Sp – .Lv + .SI + .ROR+γ.ROR– γ.4 – .4 – .Sp + .Lv– .SI – .Sp + .Lv – .SI b 7 b 7 7 7

NK.CD12NK.CD49NK.CD12ILC1.IEL.SIILC1.CD127ILC1.CD49bILC1.CD127ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC2.SI NK.CD127NK.CD49bNK.CD127ILC1.IEL.SIILC1.CD127ILC1.CD49bILC1.CD127ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC2.SI NK.CD12NK.CD49bNK.CD12ILC1.IEL.SIILC1.CD127ILC1.CD49ILC1.CD127ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC2.SI

II9r Id2 Cxcr4 Rara II4 Tox2 Ccl4 II5 Rorc Ccl3 II1rI1 Tox Ccl5 II13 Nfil3 Ccr5 II17rb Maff II6 Ahr Cx3cr1 Nr4a1 Cxcr3 Bmp2 Atf3 CcI1 Csf2 Rora Ccr8 Areg Zbtb16 Bmp7 Ccr4 Rxrg Ifngr2 CcI17 Pparg II18r1 Gata3 Ccr6 II1r1 Gfi1 Cxcr5 Hnf1a II17re Tbx21 Ccr9 II22 Notch1 Cxcr6 II23r Irf8 Ccr1 II7r Eomes Expression (relative) II2ra Expression (relative) II17f Row min Row max II17a Heat map min Heat map max II1r2 II2 II12rb1 d ILC2 & NKp46– CD4– ILC3 ILC2 ILC2 & ILC1 Prf1 – – Gzma NKp46 CD4 ILC3 ILC1 II17ra NKp46– CD4– ILC3 & NKp46+ ILC3 NKp46+ ILC3 NKp46+ ILC3 & ILC1 Ifngr1 II4ra Ifng +256 17 Ccr8 II17rb 137 19 II12rb2 +128 Ccr4 II5 II2rb Ret II10ra Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature II21r +64 Pdcd1 II4 Calca Cd27 II17b +32 Cd81 II17c Expression (relative) +16

ILC3 Arg1 Ets2 npg hi +8 Row min Row max t Vipr2 +4 Myc Gzma Nrp1 ROR γ e 0 + +2 10 94 119 Cntn1 II21r II23r +1 109 75 Rorc Itgax Ptges 10–1 CcI5 KIra10 –2 Prf1 II22 Cd27 Upp1 Expression (fold) –4 Stom CcI5 10–2 Gzma –8 Cxcr5

Cxcr5 Klrd1 P Cd2 Igfbp7 –16 –3 II21r siLP ILC2/siLP NKp46 II1r1 10 –32 Itgax II1r1 Igfbp7 Tbx21 II1r2 –64 Upp1 CcI3 –4 10 1300014I06Rik Chad –128 Rorc CtIa4 Ifng XcI1 II12rb2 KIrd1 Lrrc49 II22 II23r –5 –256 61 17 KIrb1f Ncr1 122 10 +1–2–4–8–16–32–64–128–256 +256+128+64+32+16+8+4+2 –64 –32 –16 –8 –4 –2 +1 +2 +4 +8 +16 +32 +64 Fold change Expression (fold) + hi – – siLP NKp46 ROR t ILC3/siLP ILC1 siLP ILC1/siLP NKp46 CD4 ILC3 γ

Figure 3 Spectrum of distinct and shared transcriptional profiles among ILC subsets. (a) Heat map of the expression of selected transcription factors, normalized by expression within the entire heat map. (b,c) Heat maps of the expression of selected chemokine receptors and ligands (b) and of cytokine receptors and ligands (c), normalized by expression within each row. (d) Transcripts upregulated by a single subset or two subsets among selected siLP ILCs (colors in plot match key; full gene lists, Supplementary Table 2). Numbers in plot indicate transcripts upregulated by at least twofold in that subset (colors match key). (e) Comparison of gene expression in RORγthiNKp46+ ILC3 cells (n = 3 replicates) versus that in ILC1 cells (n = 2 replicates) by volcano plot; numbers in corners indicate transcripts significantly upregulated by at least twofold. P ≤ 0.05 (t-test). ImmGen nomenclature as in Figure 1. Data are pooled from one to three (a–c) or one to two (d,e) experiments per sample with cells pooled from three to five mice each; two to three replicate samples are shown per subset (a–c).

nature immunology VOLUME 16 NUMBER 3 MARCH 2015 311 r e s o u r c e

Defining novel transcripts within ILC3 cells most highly and most significantly upregulated by CD4− LTi-like ILC3 Pairwise comparison of all ILC3 subsets versus other profiled cells cells, we found Nrp1. Also identified as part of our LTi-like ILC3 cell revealed a 42-transcript ILC3 cell signature (Fig. 4a). This signa- signature (Fig. 2b), Nrp1 is a coreceptor for several ligands, including ture included well-studied transcripts such as Il23r, Rorc and Il22, the immunoregulatory factor VEGF, transforming growth factor-β1 as well as several molecules previously unreported to be expressed and semaphorins, and may have a function in negatively regulating by ILC3 cells, such as Pram1, a target of retinoic acid and activator the immune response, in part through enhanced survival of regula- of the kinase Jnk. This result supported the role for retinoic acid in tory T cells38. It is also one of a few markers that distinguish natu- the development of ILC3 cells21,27. Notably, Il17 was not among the ral regulatory T cells from peripherally generated mucosa-derived transcripts with expression more than twofold higher in ILC3 cells induced regulatory T cells39,40. However, to our knowledge, until now than in other ILCs, nor was it expressed uniquely by any individual Nrp1 has never been reported to be expressed by LTi-like ILC3 cells. ILC3 cell subset (Fig. 2b,c). This result suggested that IL-17 was not We confirmed by flow cytometry that Nrp1 was expressed in greater a major product of ILC3 cells in the small intestine, at least in young amounts in LTi-like ILC3 cells than in other siLP subsets (Fig. 4c). adult mice at steady state. We also found higher expression of CD25 protein in LTi-like ILC3 Comparison of the major adult LTi-like population, CD4− LTi- cells than in other siLP subsets (Fig. 4c). Gating on Nrp1+CD25+ cells like ILC3 cells, with NKp46+RORγthi ILC3 cells revealed a total of among CD3−CD19− siLP lymphocytes resulted in a cell population 508 genes with a significant difference in expression of greater than with considerable enrichment for LTi-like ILC3 cells (Fig. 4d) and twofold (Fig. 4b and Supplementary Table 3). Among the transcripts production of IL-22 in naive IL-22 reporter mice41 (Fig. 4e). Among

0 a b 100 295 213 f 10 3 1 Io .SI hi .SI t t γ 10–1 – .SI + .SI Sl6a20a Vipr2 + .Sp – .Lv + .SI + .ROR+ .ROR– γ.4 – .4 –1 – .Sp + .Lv – .Sl Klri2 10 Parvb 10–2 Ccl3 Ccr6 –3 Ret Zfp319 10 P –2 NK.CD127NK.CD49bNK.CD127ILC1.IEL.SIILC1.CD127ILC1.CD49bILC1.CD127ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC2.SI P 10 Ncr1 –4 Ptges 10 ll12rb2 Tbx21 ll1r1 Cd81 GIt25d2 –5 Cd4 10 10–3 Smyd2 Fasl Nrp1 Rhobtb1 10–6 P2yr1 Ncoa7 Ncr1 ll22 –7 –8 –4 –2 +1 +2 +4 +8 Chad 10 –32 –16 +16 +32 Tns3 –128 –64 –32 –16 –4–8 –2 +32+16+8+4+2+1 Expression (fold) Scpep1 NKp46–CD4– ILC3/NKp46–CD4+ ILC3 Nr1d1 Expression (fold) NKp46–CD4– ILC3/NKp46+RORγthi ILC3 Ly86 0 Dlg5 c g 10 11 3 Pram1 Zfp57 Tnfrsf21 10–1 Prelid2 Cxcr5 Ablim3 Lipo1 Ccr5 10–2 P Vegfa Cd93 NK Rorc NK Klrd1 Lingo4 ILC1 ILC1 Cxcr4 + Io + Io Eps8l3 NKp46 RORγt ILC3 NKp46 RORγt ILC3 10–3 + hi Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature + hi Tifa NKp46 RORγt ILC3 NKp46 RORγt ILC3 Fnbp1l NKp46–CD4– ILC3 NKp46–CD4– ILC3 Ccl5 Gpr157 NKp46–CD4+ ILC3 NKp46–CD4+ ILC3 –4 Cells St3gal3 Cells 10 Serinc2 Nrp1 CD25 Ras/11a –8 –4 –2 +1 +2 +4 +8 npg lgfbp7 Expression (fold) Mapk10 + hi + lo Asphd2 d Gated on CD45+CD3–CD19– e NKp46 RORγt ILC3/NKp46 RORγt ILC3 II17re 5 5 0.073 5.54 3.1 2.59 100 II23r 10 10 5 Tacstd2 10 80 Ucp3 4 4 Kcnk1 10 10 104 Large 14.5 60 Cxcr5 103 103 3 Lrrc49 10 40 Ccr1 2 2 Hs6st2 10 10 102 20 Xkrx 0 0 0.097 0 NKp46 94.3 Nrp1

Nrp1 85.8 8.52 Cells 0 Expression (relative) 0 102 103 104 105 0 102 103 104 105 0 102 103 104 105 0 102 103 104 105 Row min Row max CD25 RORγt CD25 IL-22 reporter

Figure 4 ILC3-specific transcriptional programs and cell-surface markers. (a) Heat map of mRNA transcripts upregulated more than fourfold (red font) or twofold (black font) in RORγt+ ILC3 cell subsets relative to their expression in all other subsets. ImmGen nomenclature as in Figure 1. (b) Comparison of gene expression in NKp46+RORγthi ILC3 cells with that in CD4− LTi-like ILC3 cells (n = 3 replicates each), by volcano plot; numbers in corners indicate transcripts significantly upregulated (P ≤ 0.05 (t-test)) by at least twofold (colors in plot match those below plot; full gene lists, Supplementary Table 3). (c) Expression of Nrp1 and CD25 by siLP NK cell, ILC1 cell, NKp46+RORγtlo ILC3 cell, NKp46+RORγthi ILC3 cell, NKp46−CD4− LTi-like ILC3 cell and NKp46−CD4+ LTi-like ILC3 cell subsets from RORγteGFP reporter mice. (d) Percentage of siLP cells from C57BL/6 wild-type mice electronically gated on CD45+ and CD3−CD19− cells that expressed both CD25 and Nrp1 (left), and extent of LTi-like ILC3 phenotype among these cells (from left outlined area) based on surface NKp46 and intracellular RORγt stainings (right). Number adjacent to outlined area (left) indicates percent Nrp1+CD25+ cells; numbers in quadrants (right) indicate percent cells in each throughout. (e) Production of the IL-22 reporter (right) by cells obtained from naive IL-22 reporter mice and shown (left) with gating on CD45+, CD3−CD19− and NKp46− cells (colors of lines (left) match those in quadrants (right)). (f,g) Comparison of gene expression in CD4+ LTi-like cells (n = 2 replicates) with that in CD4− LTi-like ILC3 cells (n = 3 replicates) (f) and in NKp46+RORγthi ILC3 cells with that in NKp46+RORγtlo ILC3 cells (n = 3 replicates each) (g) by volcano plot (additional information, Supplementary Table 3). P ≤ 0.05 (t-test). Data in c–e are representative of three experiments.

312 VOLUME 16 NUMBER 3 MARCH 2015 nature immunology r e s o u r c e

0 a b 10 190 175 c 100 57 126 Liver Spleen siLP 5 5 5 –1 Gzma 10 10 10 10 Prf1 ll7r –1 10 Gzmb 64.9 –2 4 4 4 27.6 10 Tnfsf10 Ltb 10 10 10 –2 Eomes 21 10 P CXCR6 P Klrg1 103 103 8.95 103 10–3 Klrg1 ll7r –3 Eomes Gzmc 10 –4 102 102 102 10 Ahr 72.7 86.8 Prf1 0 0 0 Sell Cd200r1 10–4 NK1.1 TRAIL –5 CD127 10 Cd200r2 2 3 4 5 2 3 4 5 2 3 4 5 Klra1 ltga1 ll2ra Tcrg-v3 0 10 10 10 10 0 10 10 10 10 0 10 10 10 10 –8 –4 –2 +1 +2 +4 +8 –8 –4 –2 +1 +2 +4 +8 CD49b CD27 CD127 –64–32 –16 +16+32+64 –64 –32 –16 +16 +32 +64 –128 +128 Expression (fold) Expression (fold) Liver ILC1/Liver NK Spleen ILC1/Spleen NK Figure 5 Transcripts expressed differently by NK cells versus ILC1 cells.

d 0 e 0 (a) Gating strategy for liver, spleen and siLP ILC1 and NK cells after the 10 68 106 10 191 73 Gzma CXCR6 first round of sorting from pooled samples. (b–e) Comparison of gene Itga2 Sell ll7r –1 expression in liver ILC1 cells with that in liver NK cells (n = 3 replicates 10–1 10 Cxcr4 ltga1 Kit each) (b), in spleen ILC1 cells versus spleen NK cells (n = 3 replicates –2 Gzmc Eomes 10 Eomes Gzmb 10–2 P each) (c), in siLP ILC1 cells versus siLP NK cells (n = 2 replicates each) (d), P Cmah 10–3 and in liver ILC1 cells versus spleen ILC1 cells (e), by volcano plot; Klrg1 Lmo4 –3 S1pr1 10 –4 numbers in corners indicate transcripts significantly upregulated Klra10 10 Mmp9 Klra9 Npas2 (P ≤ 0.05 (t-test)) by at least twofold (colors in plot match those below Entpd1 –4 10–5 Sell plot; full gene lists, Supplementary Table 4). (f) Expression of CD127 and 10 Tmem64

Eomes in ILC1 cells and NK cells from liver, spleen and siLP, as well as –8 –4 –2 +1 +2 +4 +8 –8 –4 –2 +1 +2 +4 +8 –16 +16 –64–32 –16 +16+32+64 staining with isotype-matched control immunoglobulin (Isotype). Expression (fold) Expression (fold) Data are representative of four to six experiments (a), are pooled from siLP ILC1/siLP NK Liver ILC1/Spleen ILC1 one to three (b–e) experiments per sample with cells pooled from three Liver Spleen siLP to five mice each, or are representative of two experiments (f). f 100 Isotype NK 80 ILC1 LTi-like ILC3 cells, distinctions in gene expression between CD4+ and 60 CD4− subsets were not robust and probably do not have functional 40 significance (Fig. 4f), although they might reflect different devel- 20 opmental lineages5,9. Similarly, comparison of siLP NKp46+RORγtlo Cells 0 2 3 4 5 + γ hi 0 10 10 10 10 ILC3 cells with siLP NKp46 ROR t ILC3 cells revealed substantial CD127 overlap in gene expression, with few significant differences (Fig. 4g 100 and Supplementary Table 3). The greater expression of NK cell–like 80 γ lo transcripts such as Ccl5 and Klrd1 in siLP ROR t ILC3 cells than in 60 siLP RORγthi ILC3 cells suggested that the population of siLP RORγtlo 40 ILC3 cells might have included a minor ILC3 cell population ‘convert- 20 ing’ into ‘ex-RORγt+’ ILC3 cells. Robust identification of ‘converting’

Cells 0 Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature ILC3 cells can be established only through fate mapping experiments, 0 102 103 104 105 as has been described4. Eomes

npg Transcriptional differences between ILC1 cells and NK cells higher levels by NK cells than by ILC1 cells (Supplementary Table 4). One subject that has been particularly controversial is the difference In fact, granzyme A and granzyme C had higher expression in liver between ILC1 cells and NK cells, in part because of a lack of markers ILC1 cells than in liver NK cells (Fig. 5b and Supplementary Table 4), characteristically and consistently expressed in NK cells and ILC1 cells consistent with the reported cytolytic activity of liver ILC1 cells43. in various organs. We used different sorting strategies in each tissue Liver and spleen ILC1 cells selectively expressed transcripts encod- to discriminate between ILC1 cells and NK cells, consistent with what ing known ILC1 cell-surface markers. In liver ILC1 cells, these tran- has been reported before2,42. We achieved the best separation of sub- scripts included Itga1 and Tnfrsf10 (Fig. 5b), which encode CD49a sets in the liver and the worst such separation in the siLP (Fig. 5a). and TRAIL, markers that have been used for separating liver ILC1 Comparisons of NK cells and ILC1 cells from liver, spleen and siLP cells from NK cells40. Splenic ILC1 cells had high expression of IL2ra reflected the degree of separation between populations during sorting, and IL7r (Fig. 5c), which encode cytokine receptors that collectively with the greatest number of significantly differently expressed genes enable this population to escape regulation by regulatory T cells15. The in the liver and the least in the siLP. Nonetheless, ILC1 replicates clus- transcripts with the most significant higher expression in siLP ILC1 tered together (Fig. 1e) and were transcriptionally distinct from NK cells than in siLP NK cells included only previously uncharacterized cells in liver, spleen and siLP (Fig. 5b–d and Supplementary Table 4). transcripts such as Tmem64, Npas2 and Lmo4; however, these tran- As expected, Eomes expression was significantly different, with a scripts were expressed in other ILCs of the small intestine (Fig. 5d) difference in expression of greater than twofold in NK cells relative and therefore probably would not be useful markers. Comparison to its expression in ILC1 cells in all tissues analyzed (Fig. 5b–d and of splenic and liver ILC1 cell subsets revealed that splenic ILC1 cells Supplementary Table 4). The amount of transcripts encoding pro- expressed markers of immature and mature NK cells, including CXCR4, teins of the cytotoxic machinery was generally greater in NK cells c-Kit and Eomes13,42 (Fig. 5e). These differences in transcription could than in ILC1 cells (Fig. 5b–d). However, in the siLP, the number of be explained by the finding that our sorting strategy based on CD127 perforin-encoding transcripts was only 1.7-fold greater in NK cells and CD27 included an Eomes+ subset among the splenic ILC1 cells than in ILC1 cells, and in the liver, only granzyme K was expressed at (Fig. 5f). We also noted that the siLP NK cell subset identified by

nature immunology VOLUME 16 NUMBER 3 MARCH 2015 313 r e s o u r c e

Io .SI hi .SI a Spleen & liver NK Spleen & liver ILC1 b Spleen, liver & siLP NK Spleen, liver & siLP ILC1 – .SI + .SI + .Sp – .Lv + .SI + .ROR+γt .ROR–γt.4 – .4 – .SP + .Lv – .SI +128 17 IL7r Tcrg-V2 Tcrg-V3 +64 59 Tmem176a Tmem176b NK.CD127NK.CD49bNK.CD127ILC1.IEL.SIILC1.CD127ILC1.CD49bILC1.CD127ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC3.NKp46ILC2.SI +32 Tcrg-C II2ra Atp8a2 +16 CXCR6 Socs2 Tnf Tcrg-V3 Ahr Tcrg-V2 +8 II2ra II7r +4 Ckb Itga1 Gpr97 Tnfsf10 Podnl1 +2 Tmem176a Tmem176b Cdon 1 Gpr114 Tmem154 Slc27a6 –2 St6gaInac3 Eomes Cxcr6 –4 Klrg1 Klra1 Khdc1a Serpinb9b –8 Serpinb9b Cym Klra3 Zeb2 –16 A430084P05Rik Klrg1 CmkIr1 Expression (fold) spleen ILC1/spleen NK Khdc1a Car5b –32 Itgam Klra1 –64 Eomes 15 Klra3 Klra9 –128 36 Klra10 Irf8 –128 –64 –32 –16 –8 –4 –2 1 +2 +4 +8 +16 +32 +64 +128 Expression (relative) Expression (fold) liver ILC1/liver NK Row min Row max c d IEL γδ siLP ILC2 Sp ILC1 Sp NK Lv ILC1 Lv NK 5 5 5 Chr 13 105 54.8 39.8 105 99.9 0.06 10 3.7 0.10 10 98.5 1.54 10 100 0 4 4 4 4 4 qA1 qA2 qA3.2 qA4 qB1 qB3 qC1 qC3 qD1 qD2.2 10 10 10 10 10 103 103 103 103 103 20 kb 26 kb 19,428 kb 19,430 kb 19,432 kb 19,434 kb 19,436 kb 19,438 kb 19,440 kb 19,442 kb 19,444 kb 19,44 2 102 10 102 102 102 0 0.32 0 0 0 0.03 0 0 0 0 [0 – 109] CD3 & CD19 IL7R NKp46 ST2 NKp46 Spleen NK CD49b+(1) 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 0 10 10 10 10 0 10 10 10 10 0 10 10 10 10 0 10 10 10 10 0 10 10 10 10 [0 – 111] Spleen NK CD49b+(2) Extracellular anti-TCR δ [0 – 102] Liver NK CD49b+(1) IEL γδ siLP ILC2 Sp ILC1 Sp NK Lv ILC1 Lv NK [0 – 75] + 5 5 5 5 5 Liver NK CD49b (2) 10 10.2 29.8 10 100 0 10 3.81 0.04 10 100 0 10 100 0 [0 – 160] + 104 104 104 104 104 Liver ILC1 CD49a (1) 3 [0 – 125] + 103 103 10 103 103 Liver ILC1 CD49a (2) 2 102 102 10 102 102 NKp46 NKp46 0 0.07 0 IL7R 0 0.03 0 0 0 0 RefSeq annotation ST2 0 anti-TCR δ

Extracellular 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 0 10 10 10 10 0 10 10 10 10 010 10 10 10 0 10 10 10 10 0 10 10 10 10 tcrgv2 tcrgv1 tcrgj4 tcrgc4 Intracellular anti-TCRδ siLP NK IEL ILC1/siLP ILC1 100 eGFP/eGFP e f 80 Cxcr6 g sILP NK & ILC1 IEL ILC1/siLP ILC1 & NK 75 eGFP/+ siLP ILC1 IEL ILC1/NK 70 Cxcr6 80 *** 65 Eomes Klra3 Itgae +4 Irgm1 Sell CD160 Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature cells (%)

60 cells (%) – 20 +2 Serpinb9b

eGFP+ 40 +1 CD19 – 10 –2 CXCR6 20 CD3 npg –4 Expression Tcrg-V3 0 0 –8 Tcrg-V2

(fold) IEL ILC1/siLP NK II2ra Plekhg1 –16 B3gaIt5 Icos Serpinab1a – ILC3+ ILC3 – ILC3+ ILC3 siLP NK siLP NK siLP ILC2 siLP ILC1 Liver NK siLP ILC2 siLP ILC1 Liver NK –8 –4 –2 +2 +4 silEL ILC1 Liver ILC1 Spleen NK silEL ILC1 Liver ILC1 Spleen NK Spleen ILC1 Spleen ILC1 Expression (fold) siLP NKp46siLP NKp46 siLP NKp46siLP NKp46 IEL ILC1/siLP ILC1

Figure 6 Generation of a core ILC signature distinct from that of NK cells. (a) Transcripts expressed differently by ILC1 cells relative to their expression by NK cells from various tissues (colors in plot indicate transcripts upregulated by two or three subsets and match those in key); numbers in plot indicate transcripts with a significant (P ≤ 0.05 (t-test)) difference in expression of at least twofold in liver and spleen ILC1 and NK cells (n = 3 replicates each) or with an additional filter for difference in expression of at least twofold in siLP ILC1 cells versus NK cells (n = 2 replicates each). (b) Gene signatures generated according to data in a (colors on left match those in a); red font indicates transcripts upregulated by at least fourfold in all three comparisons of ILC1 cells versus NK cells (full gene lists, Supplementary Tables 5 and 6). (c) Extracellular and intracellular staining of TCRδ on (or in) ILCs and NK cells (electronically gated as in Fig. 1c, except splenocytes were positively selected with beads coated with anti-CD49b) and IEL γδ T cells (positive control), assessed by flow cytometry; for intracellular staining, phycoerythrin-conjugated monoclonal antibody to TCRδ was used to stain IELs extracellularly before intracellular staining with fluorescein isothiocyanate–conjugated anti-TCRδ. Numbers in outlined areas (gates) indicate percent TCRδ+ cells (outline colors (red and blue) match those in keys above plots), except IEL γδ cells, which are shown as a percentage of CD45+ cells (additional information, Supplementary Fig. 2). Sp, spleen; Lv, liver. (d) 3′ end targeted RNA-sequencing data from a publicly available data set (GEO accession code GSE52043), showing the encoding TCRγ (chr13:19,426,000–19,446,000). (e) Frequency of CXCR6+ cells in each ILC subset from Cxcr6eGFP/+ reporter mice. Each symbol represents an individual mouse (three or four per genotype per tissue); small horizontal lines indicate the mean (±sem). *P ≤ 0.05 (one-way analysis of variance (ANOVA) with multiple comparisons). (f) Frequency of ILCs in Cxcr6eGFP/+ and Cxcr6eGFP/eGFP mice. All comparisons are not significant (two-way ANOVA with multiple comparisons). (g) Gene expression in siLP ILC1 cells, siLP NK cells and siIEL ILC1 cells; colors indicate transcripts upregulated by one or two subsets (match key above plot). Data are representative of one to three experiments per sample with cells pooled from three to five mice each (a,b,g; n = 2–3 replicates each), two independent experiments (c,d) or three independent experiments (e,f; error bars, mean ± sem of three or four mice per genotype per tissue).

314 VOLUME 16 NUMBER 3 MARCH 2015 nature immunology r e s o u r c e

cell-surface markers contained a large population of Eomes− cells of both NK cell and ILC1 populations (Fig. 6g). Whereas the NK cell (Fig. 5f). Thus, NK cells and ILC1 cells could not be discriminated signature transcripts Eomes and Klra3 (Fig. 6b) had higher expression on the basis of CD127 and/or CD27 in the spleen and siLP. The use of by IEL ILC1 cells than siLP ILC1 cells, the ILC1 signature transcripts EomeseGFP reporter mice might be useful in future attempts to better Tcrg-V2 and Tcrg-V3 (Fig. 6b) were more abundant in IEL ILC1 cells discriminate NK cells from ILC1 cells, as has been described4,42. than in siLP NK cells (Fig. 6g). It remains unclear whether IEL ILC1 cells are a single, unique subset with distinct developmental and func- A core, NK cell–distinct ILC signature tional characteristics, or whether siLP NK cells and ILC1 cells both If ILC1 cells are different from NK cells as a class, we reasoned that traffic to the epithelium, where they become phenotypically indistin- there should be transcripts common among ILC1 cells from all tis- guishable, possibly in response to tissue factors in the epithelium. sues that differ from those of NK cell subsets, and vice versa (Fig. 6a). Spleen and liver ILC1 cells shared expression of genes previously DISCUSSION reported to be expressed by ILC1 cells,8,13,15,42,43 such as Tnfsf10, Tnf Here we have provided the first comprehensive transcriptional analysis and Il2 (Fig. 6a and Supplementary Table 5), although Il2 was filtered of the spectrum of ILC subsets reported in the siLP, liver and spleen, to out by our methods because of variability between replicates (Fig. 3c). our knowledge. The transcriptional programs we found should allow Transcripts with higher expression in NK cell subsets included Eomes, better definition of the individual ILC classes, as well as of ILC subsets Itgam (which encodes CD11b (integrin αM)) and members of the within a class. ILC2 was the most homogeneous and distinguishable Klra family of genes (which encode receptors of the Ly49 family) ILC class and expressed the greatest number of characteristic genes, (Supplementary Table 5). This NK cell–specific signature was con- with many transcripts expressed more than fourfold higher than in any sistent with that identified in a more limited data set comparing other subset. These genes encoded well-documented factors as well as NK cells with ILC1 cells and ex-RORγt+ ILC3 cells from the siLP4. previously unrecognized genes, including the nuclear receptors RXRγ Visualization of genes expressed differently in the liver, spleen and and PPARγ and several other molecules involved in lipid metabolism. siLP for the entire data set revealed that with few exceptions, genes Within the ILC3 class, LTi-like ILC3 cells expressed several charac- upregulated in ILC1 cells relative to their expression in NK cells had teristic genes at higher levels than in other subsets, including genes even higher expression in many other ILC subsets (Fig. 6b). Genes previously unknown to be expressed in cells of the immune system, upregulated in all NK cells were consistently not expressed in other including Cntn1, Slc6a7 and Cacna1g. These cells were distinct from ILCs (Fig. 6b), except for low transcript levels in ILC1 cells. The tran- NKp46+ ILC3 cells and were effectively marked by the previously unre- scripts with the highest expression in ILCs relative to their expression ported LTi-like factor Nrp1, as well as by CD25. The definition of the in NK cells (Fig. 6a) were Tcrg-V3, Tmem176a, Tmem176b, Il7r and ILC1 class was the most problematic, because in comparisons of ILC1 Cxcr6 (Fig. 6b and Supplementary Table 6). The high expression cells with all other ILCs and NK cells, we found no markers specific for of several TCRg transcripts by all ILC subsets compared to NK cells siLP ILC1 cells and few for liver and spleen ILC1 cells. The transcript (Fig. 6a,b) was unexpected, as ILCs by definition do not express encoding CD103 was an unexpected characteristic transcript for siIEL recombined antigen receptors. We first used flow cytometry to con- ILC1 cells, given that it was not present as CD103 protein in this subset firm that no T cell antigen receptor (TCR) δ-chains were expressed in in mouse studies and has been noted only in human cells16. Among any of our cell types, either extracellularly or intracellularly (Fig. 6c siLP subsets, we also found a previously unrecognized ‘intestinal’ sig- and Supplementary Fig. 2a); this suggested that they lacked func- nature composed of activation markers such as CD69 and many tran- tional TCRγδ expression. Furthermore, from a published RNA- scription factors, including those encoded by Rora, Atf3, Nr4a1 and Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature sequencing data set that included liver ILC1 cells, liver NK cells and Maff, probably reflective of continuous environmental exposure. spleen NK cells from mice deficient in recombination-activating Beyond the unique factors, ILC classes also shared many transcripts. gene 1 (Rag1−/− mice)43, we found high levels of the 3′ end of the For example, siLP NKp46+RORγt+ ILC3 cells shared many transcripts

npg locus encoding TCRγ, annotated as the ‘Tcrg C4’ transcript, present with siLP ILC1 cells, including Ifng and Il12rb2. These data, which in liver ILC1 cells but not in NK cells from liver or spleen (Fig. 6d). were consistent with published reports4,14, provide a basis for the pro- By PCR, we confirmed that the transcript encoding TCRγ-V3 was posal of functional plasticity of siLP NKp46+RORγt+ ILC3 cells, which a germline transcript (data not shown). As cytokines IL-7 and IL- become similar to ILC1 cells in certain conditions yet to be defined. 15, which activate the transcription factor STAT5, are well known Furthermore, ILC1 cells and ILC2 cells shared expression of the tran- to mediate germline expression of the locus encoding TCRγ44,45, we scription factor–encoding transcript Ets-2, which would suggest pre- concluded that ILCs had open chromatin at the locus encoding TCRγ viously unknown transcriptional pathways shared by ILC1 cells and and germline transcription, probably due to signaling through IL-7. ILC2 cells. Notably, ILC2 cells and LTi-like ILC3 cells expressed genes We also assessed the ability to use CXCR6 as an ILC marker through that would suggest a function in neural and glial crosstalk. ILC2 cells the use of a Cxcr6eGFP reporter mouse. Although we found significant expressed Bmp2, which encodes a molecule that has been found to differences between ILC1 and NK cell populations in their frequency modulate enteric motility in response to the microbiota33; given the of CXCR6+ cells (Fig. 6e and Supplementary Fig. 2b), not all ILCs importance of motility in clearing helminth infections, this obser- were labeled (Fig. 6e and Supplementary Fig. 2b). Additionally, at vation might indicate a previously unknown mechanism of innate steady state, CXCR6 was not required for the development or tissue defense. We discovered that both ILC2 cells and LTi-like ILC3 cells also homing of ILCs, as we found no difference between Cxcr6eGFP/+ mice expressed Ret, a proto-oncogene that encodes a receptor for the glia- and Cxcr6eGFP/eGFP mice in their frequency of ILCs (Fig. 6f). derived neurotrophic family of molecules, which are known to drive Finally, we sought to determine whether intestinal intraepithelial the development of Peyer’s patches37 but currently remain unstudied ILC1 cells should be classified as an ILC1 or NK cell population, as this in ILCs. Thus, in the siLP, ILCs may engage in crosstalk with population has unique transcription factors and cell-surface markers and glia in the steady state and during an immune response. that prevent it from fitting clearly into an ILC1 or NK cell designa- We generated a core ILC signature that included 17 genes, with the tion16. Comparisons of IEL ILC1 cells, siLP ILC1 cells and siLP NK highest expression of germline transcripts encoding TCRγ, as well as cells revealed that IEL ILC1 cells expressed transcripts characteristic Cxcr6, Tmem176a, Tmem176b and Il7r. We were surprised to find that

nature immunology VOLUME 16 NUMBER 3 MARCH 2015 315 r e s o u r c e

the gene with the highest expression by all ILCs relative to its expres- A. Rhodes, for contributions and technical assistance; M. Artyomov, G. Krishnan sion in NK cells was the TCRγ-V3 germline transcript, which has not and J. Siegel for computational assistance; D. Sojka for discussion; E. Lantelme and been previously reported in ILCs, to our knowledge, but has been D. Brinja for sorting assistance; P. Wang for microscopy assistance; and eBioscience and Affymetrix for support of the ImmGen Project. Supported by the US National 46 reported in a putative ILC3 cell line . We postulate that this might Institutes of Health (R24AI072073 to the ImmGen Consortium; 1U01AI095542, reflect signaling by IL-7R, which is expressed by all ILCs but not by R01DE021255 and R21CA16719 to the Colonna laboratory; MSTP T32 GM07200 mature NK cells44. In our study, we confirmed that all ILCs had higher to M.L.R.; and Infectious Disease Training Grant T32 AI 7172-34 to V.S.C.). expression of Cxcr6 than did NK cells. Two published studies have AUTHOR CONTRIBUTIONS also investigated CXCR6 expression in ILCs. The first study demon- M.L.R. analyzed data; A.F., M.L.R., J.S.L. and Y.W. sorted cell subsets; strated that a CXCR6+ early progenitor gives rise to both NK cells and M.L.R., A.F. and V.S.C. performed follow-up experiments and analyzed data; ILCs but not T cells47. The second study found that CXCR6 deficiency S.G. maintained mice; S.K.D. provided critical reagents; M.L.R., A.F., S.G. and ‘preferentially’ affects the frequency and function of NKp46+ ILC3 M.C. designed studies; M.L.R. and M.C. wrote the paper; and the ImmGen Consortium contributed to the experimental design and data collection. cells by preventing appropriate interactions with CD11b+ intestinal 48 dendritic cells . We found that CXCR6 did not mark the entire popu- COMPETING FINANCIAL INTERESTS lation, nor were any ILC frequencies affected by its loss; however, it The authors declare no competing financial interests. is possible that loss of CXCR6 affects ILC function, and this should Reprints and permissions information is available online at http://www.nature.com/ be tested in all ILC classes. Notably, Tmem176b has been reported to reprints/index.html. be a marker of innate lymphocytes as one of only three transcripts 49 shared by NK cells, NKT cells and γδ T cells , although in our data 1. Heng, T.S. & Painter, M.W. The Immunological Genome Project: networks of gene set we found that ILC1, ILC2 and ILC3 cells had significantly higher expression in immune cells. Nat. Immunol. 9, 1091–1094 (2008). expression of Tmem176b than did NK cells. These data suggest that 2. Diefenbach, A., Colonna, M. & Koyasu, S. Development, differentiation, and diversity of innate lymphoid cells. Immunity 41, 354–365 (2014). the core ILC signature identified here may also extend to other innate 3. McKenzie, A.N., Spits, H. & Eberl, G. Innate lymphoid cells in inflammation and and/or tissue-resident lymphoid cells. immunity. Immunity 41, 366–374 (2014). IFN-γ-producing ILC1 cells and NK cells can develop from differ- 4. Klose, C.S. et al. Differentiation of type 1 ILCs from a common progenitor to all helper-like innate lymphoid cell lineages. Cell 157, 340–356 (2014). ent progenitors and are, respectively, independent of and dependent 5. Sawa, S. et al. Lineage relationship analysis of RORgammat+ innate lymphoid cells. on Eomes4,11. However, in tissues they show overlapping phenotypes Science 330, 665–669 (2010). 6. Lee, J.S. et al. AHR drives the development of gut ILC22 cells and postnatal and functional programs. NK cells are well known to have cytolytic lymphoid tissues via pathways dependent on and independent of Notch. ability, but liver ILC1 cells express granzyme A and granzyme C and Nat. Immunol. 13, 144–151 (2011). have also been shown to be cytolytic42,43,50. In our study, liver ILC1 7. Klose, C.S. et al. A T-bet gradient controls the fate and function of CCR6-Rorγt+ innate lymphoid cells. Nature 494, 262–265 (2013). cells were clearly separated by TRAIL and CD49a, but cell-surface 8. Sciumé, G. et al. Distinct requirements for T-bet in gut innate lymphoid cells. markers of CD127 with and without CD27 in the spleen and siLP, J. Exp. Med. 209, 2331–2338 (2012). respectively, were insufficient to discriminate Eomes− ILC1 cells from 9. Rankin, L.C. et al. The transcription factor T-bet is essential for the development of NKp46+ innate lymphocytes via the Notch pathway. Nat. Immunol. 14, 389–395 + Eomes NK cells. Thus, transcriptional data generated using Eomes (2013). reporter mice might be useful for comparison to our data set4,42. 10. Buonocore, S. et al. Innate lymphoid cells drive interleukin-23-dependent innate intestinal pathology. Nature 464, 1371–1375 (2010). Moreover, the induction of cytokines such as IL-15 and/or IL-2 in 11. Constantinides, M.G., McDonald, B.D., Verhoef, P.A. & Bendelac, A. A committed certain pathologic conditions might further increase the phenotypic precursor to innate lymphoid cells. Nature 508, 397–401 (2014). and functional similarity of ILC1 cells and NK cells. Thus, it remains 12. Yu, J., Freud, A.G. & Caligiuri, M.A. Location and cellular stages of natural killer cell development. Trends Immunol. 34, 573–582 (2013). Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature unclear whether ILC1 cells and NK cells are truly distinct lineages or 13. Gordon, S.M. et al. The transcription factors T-bet and Eomes control key checkpoints a spectrum of cells within a single lineage that includes ILC1 cells, of natural killer cell maturation. Immunity 36, 55–67 (2012). immature NK cells and mature NK cells. 14. Reynders, A. et al. Identity, regulation and in vivo function of gut NKp46+RORγt+ and NKp46+RORγt– lymphoid cells. EMBO J. 30, 2934–2947 (2011).

npg Our data offer the most complete transcriptional profile of ILCs 15. Gasteiger, G., Hemmers, S., Bos, B.D., Sun, J.C. & Rudensky, A.Y. IL-2-dependent and NK cells so far, to our knowledge, and provide a comprehensive adaptive control of NK cell homeostasis. J. Exp. Med. 210, 1179–1187 (2013). 16. Fuchs, A. et al. Intraepithelial type 1 innate lymphoid cells are a unique subset of view of the relationships among ILC subsets at steady state. Our find- IL-12- and IL-15-responsive IFN-γ-producing cells. Immunity 38, 769–781 ings should help define new avenues of research and should aid in (2013). the production of new tools for studying ILCs, especially with the 17. Turner, J.E. et al. IL-9-mediated survival of type 2 innate lymphoid cells promotes damage control in helminth-induced lung inflammation. J. Exp. Med. identification of several molecular targets with high expression by all 210, 2951–2965 (2013). ILCs. Finally, they should also be a valuable resource for the scientific 18. Mjösberg, J. et al. The transcription factor GATA3 is essential for the function of community, with access to our data set and comparisons to other human type 2 innate lymphoid cells. Immunity 37, 649–659 (2012). 19. Yagi, R. et al. The transcription factor GATA3 is critical for the development of all published data sets generated under the same rigorous conditions, IL-7Rα-expressing innate lymphoid cells. Immunity 40, 378–388 (2014). provided by the ImmGen Project. 20. Evans, R.M. & Mangelsdorf, D.J. Nuclear receptors, RXR, and the Big Bang. Cell 157, 255–266 (2014). 21. Spencer, S.P. et al. Adaptation of innate lymphoid cells to a micronutrient deficiency Methods promotes type 2 barrier immunity. Science 343, 432–437 (2014). Methods and any associated references are available in the online 22. Molofsky, A.B. et al. Innate lymphoid type 2 cells sustain visceral adipose tissue eosinophils and alternatively activated macrophages. J. Exp. Med. 210, 535–549 version of the paper. (2013). 23. Mohebiany, A.N., Harroch, S. & Bouyain, S. in Cell Adhesion Molecules: Implications in Neurological Diseases, Advances in Neurobiology Vol. 8 (eds. Berezin, V. & Accession codes. GEO: microarray data, GSE37448. Walmod, P.S.) Chapter 8 (Springer Science+Business Media, 2014). 24. Cella, M. et al. A human natural killer cell subset provides an innate source of Note: Any Supplementary Information and Source Data files are available in the IL-22 for mucosal immunity. Nature 457, 722–725 (2009). online version of the paper. 25. Mortha, A. et al. Microbiota-dependent crosstalk between macrophages and ILC3 promotes intestinal tolerance. Science 343, 1249288 (2014). Acknowledgments 26. Levitt, L.J. et al. Production of granulocyte/macrophage-colony stimulating factor We thank our colleagues in the ImmGen consortium, especially C. Benoist and by human natural killer cells. Modulation by the p75 subunit of the interleukin 2 L. Lanier, for input and discussion; the core ImmGen team, K. Rothamel and and by the CD2 receptor. J. Clin. Invest. 88, 67–75 (1991).

316 VOLUME 16 NUMBER 3 MARCH 2015 nature immunology r e s o u r c e

27. van de Pavert, S.A. et al. Maternal retinoids control type 3 innate lymphoid cells 40. Weiss, J.M. et al. Neuropilin 1 is expressed on -derived natural regulatory and set the offspring immunity. Nature 508, 123–127 (2014). T cells, but not mucosa-generated induced Foxp3+ T reg cells. J. Exp. Med. 209, 28. Kiss, E.A. et al. Natural aryl hydrocarbon receptor ligands control organogenesis of 1723–1742 (2012). intestinal lymphoid follicles. Science 334, 1561–1565 (2011). 41. Shen, W. et al. Adaptive immunity to murine skin commensals. Proc. Natl. Acad. 29. Gascoyne, D.M. et al. The basic transcription factor E4BP4 is Sci. USA 111, E2977–E2986 (2014). essential for natural killer cell development. Nat. Immunol. 10, 1118–1124 42. Daussy, C. et al. T-bet and Eomes instruct the development of two distinct natural (2009). killer cell lineages in the liver and in the bone marrow. J. Exp. Med. 211, 563–577 30. Kamizono, S. et al. Nfil3/E4bp4 is required for the development and maturation (2014). of NK cells in vivo. J. Exp. Med. 206, 2977–2986 (2009). 43. Sojka, D.K. et al. Tissue-resident natural killer (NK) cells are cell lineages distinct 31. Seillet, C. et al. Nfil3 is required for the development of all innate lymphoid cell from thymic and conventional splenic NK cells. Elife 3, e01659 (2014). subsets. J. Exp. Med. 211, 1733–1740 (2014). 44. Ye, S.K. et al. Induction of germline transcription in the Tcrγ locus by Stat5: 32. Geiger, T.L. et al. Nfil3 is crucial for development of innate lymphoid cells and host implications for accessibility control by the IL-7 receptor. Immunity 11, 213–223 protection against intestinal pathogens. J. Exp. Med. 211, 1723–1731 (2014). (1999). 33. Muller, P.A. et al. Crosstalk between muscularis macrophages and enteric neurons 45. Zhao, H., Nguyen, H. & Kang, J. Interleukin 15 controls the generation of restricted regulates gastrointestinal motility. Cell 158, 300–313 (2014). T cell receptor repertoire of intraepithelial lymphocytes. Nat. Immunol. 6, 34. Bando, J.K., Liang, H.E. & Locksley, R.M. Identification and distribution of 1263–1271 (2005). developing innate lymphoid cells in the fetal mouse intestine. Nat. Immunol. http:// 46. Allan, D.S. et al. An in vitro model of innate lymphoid cell function and www.nature.com/ni/journal/vaop/ncurrent/full/ni.3057.html (2014). differentiation. Mucosal Immunol. http://www.nature.com/mi/journal/vaop/ncurrent/ 35. Veiga-Fernandes, H. et al. Tyrosine receptor RET is a key regulator of Peyer’s patch full/mi201471a.html (2014). organogenesis. Nature 446, 547–551 (2007). 47. Yu, X. et al. The basic leucine zipper transcription factor NFIL3 directs the 36. Ramirez, K. et al. Gene deregulation and chronic activation in natural killer cells development of a common innate lymphoid cell progenitor. Elife 10, e04406 deficient in the transcription factor ETS1. Immunity 36, 921–932 (2012). (2014). 37. Carpenter, S., Ricci, E.P., Mercier, B.C., Moore, M.J. & Fitzgerald, K.A. Post- 48. Satoh-Takayama, N. et al. The chemokine receptor CXCR6 controls the functional transcriptional regulation of gene expression in innate immunity. Nat. Rev. Immunol. topograophy of interluekin-22 producing intestinal innate lymphoid cells. Immunity 14, 361–376 (2014). 41, 776–788 (2014). 38. Kumanogoh, A. & Kikutani, H. Immunological functions of the neuropillins and 49. Bezman, N.A. et al. ImmGen report: molecular definition of natural killer cell identity plexins as receptors for semaphorins. Nat. Rev. Immunol. 13, 802–814 (2013). and activation. Nat. Immunol. 13, 1000–1009 (2012). 39. Yadav, M. et al. Neuropilin-1 distinguishes natural and inducible regulatory T cells 50. Peng, H. et al. Liver-resident NK cells confer adaptive immunity in skin-contact among regulatory T cell subsets in vivo. J. Exp. Med. 209, 1713–1722 (2012). inflammation. J. Clin. Invest. 123, 1444–1456 (2013).

The complete list of authors is as follows: Laura Shaw6, Bingfei Yu6, Ananda Goldrath6, Sara Mostafavi7, Aviv Regev8, Edy Y Kim9, Dan F Dwyer9, Michael B Brenner9, K Frank Austen9, Andrew Rhoads10, Devapregasan Moodley10, Hideyuki Yoshida10, Diane Mathis10, Christophe Benoist10, Tsukasa Nabekura11, Viola Lam11, Lewis L Lanier11, Brian Brown12, Miriam Merad12, Viviana Cremasco13, Shannon Turley13, Paul Monach14, Michael L Dustin15, Yuesheng Li16, Susan A Shinton16, Richard R Hardy16, Tal Shay17, Yilin Qi18, Katelyn Sylvia18, Joonsoo Kang18, Keke Fairfax1, Gwendalyn J Randolph1, Michelle L Robinette1, Anja Fuchs2 & Marco Colonna1

6Division of Biological Sciences, University of California San Diego, La Jolla, California, USA. 7Computer Science Department, Stanford University, Stanford, California, USA. 8Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. 9Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature Hospital, Boston, Massachusetts, USA. 10Division of Immunology, Department of Microbiology & Immunobiology, Harvard Medical School, Boston, Massachusetts, USA. 11Department of Microbiology & Immunology, University of California San Francisco, San Francisco, California, USA. 12Icahn Medical Institute, Mount Sinai Hospital, New York, New York, USA. 13Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA and Department of Cancer Immunology, Genentech, San Francisco, California, USA. 14Department of Medicine, Boston University, Boston, Massachusetts, USA. 15Skirball Institute of 16 npg Biomolecular Medicine, New York University School of Medicine, New York, New York, USA. Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA. 17Department of Life Sciences, Ben-Gurion University of the Negev, Be’er Sheva, Israel. 18Department of Pathology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.

nature immunology VOLUME 16 NUMBER 3 MARCH 2015 317 ONLINE METHODS then fixed and stained with Diff-Quik. Pictures were taken at ×60 with oil Mice. Consistent with ImmGen Project standards, 6- to 8-week-old male immersion using a Nikon Eclipse E800 and Leica Application Suite software. C57BL/6J mice and male B6.129P2(Cg)-Rorctm2Litt/J mice (with the sequence encoding enhanced green fluorescent protein (EGFP) inserted into the locus Microarray and data analysis. Two to three replicates of RNA were obtained encoding RORγt) obtained from Jackson Laboratories and maintained at from each sample that passed quality control. RNA amplification and hybridi- the Washington University School of Medicine (WUSM) under specific zation to the Affymetrix Mouse Gene 1.0 ST array were carried out by ImmGen pathogen–free conditions were used for cell-sorting and validation with a standardized TRIzol extraction protocol (https://www.immgen.org/ experiments. B6.129P2-Cxcr6tm1Litt/J mice with the sequence encoding EGFP Protocols/Total%20RNA%20Extraction%20with%20Trizol.pdf). Data genera- inserted into the locus encoding CXCR6, obtained from Jackson Laboratories, tion and quality-control documentation also followed the ImmGen protocol; were used for validation experiments in which mice were littermates or these methods can be found online (https://www.immgen.org/Protocols/Imm age-matched, gender-matched and co-housed when possible. Il-22 tdTomato Gen%20QC%20Documentation_ALL-DataGeneration_0612.pdf), along with reporter BAC transgenic mice were used for validation experiments41. The quality-control data, replicate information, and batch information from each WUSM Animal Studies Committee approved all experiments. sample. Data were analyzed with GenePattern software51 (Broad Institute). Raw data were normalized with RMA. Differences in gene expression were Antibodies and flow cytometry. Anti-CD3e (145-2C11), anti-CD19 identified with the Multiplot Studio function of GenePattern, from a filtered (eBio1D3), anti-CD27 (LG.7F9), anti-CD49b (HMa2, DX5), anti-γδ (UC7- subset of genes with coefficients of variation less than 0.1 in all samples and 13D5; eBioGL3), anti-CD127 (A7R34; eBioSB/199), anti-CD49a (HMa1), anti- expression of at least 120 relative units in one subset by the class mean func- Nkp46 (29A1.4), anti-CD304 (3DS304M), anti-NK1.1 (PK136), anti-Sca-1 tions, a value that corresponds to 95% confidence of true expression across the (D7), anti-ST2 (RMST2-2), anti-TRAIL (eBioN2B2), anti-CD4 (GK1.5), anti- ImmGen data set. For gene-expression signatures of individual subsets, pair- KLRG1 (2F1), anti-RORγt (AFKJS-9), anti-Eomes (Dan11mag), SAv-PE/Cy7, wise comparisons were made between subsets, filtering for a change in expres- and isotype-matched control monoclonal antibodies were obtained from sion of twofold or fourfold. For comparisons of two to four samples, probe sets eBioscience. Anti-CD25 (PCB1) and 7-AAD were from BD Biosciences. were considered to have differences of expression for transcripts that expressed Anti-CD45 (30-F11) was from Miltenyi Biotec. LIVE/DEAD Fixable Aqua >120 relative units, with a change in expression of greater than twofold and and SAv-APC were from Life Technologies. Monoclonal anti-NKp46 (Cs96; P values of <0.05 (Student’s t-test), except between siLP ILC1 and siLP NK rat immunoglobulin G) was produced and biotinylated in the Colonna lab at cells, where the P value was not considered. Volcano plots and plots comparing WUSM. Fc receptors were blocked before surface staining with supernatant change in expression (fold) versus change in expression (fold) were produced from hybridoma cells producing monoclonal antibody to CD32 (HB-197; in Multiplot, and the degree of overlapping genes between subsets was cal- ATCC). For intracellular staining, the FOXP3 staining kit (eBioscience) was culated in MATLAB. Heat maps were generated with Gene-E (http://www. used. Data were acquired on a BD FACSCanto II and analyzed with FlowJo broadinstitute.org/cancer/software/GENE-E/). Data were log2-transformed software (Treestar). and visualized by ‘relative’ expression per row or ‘global’ expression in the heat map, as indicated, and rows were clustered with the Hierarchical Clustering Cell identification, isolation and microscopy. All cells were stained and function with the Pearson correlation as a metric. Where more than one probe sorted according to the published standard operations protocol on the ImmGen set with the same gene annotation was found, the probe set with highest aver- website (http://www.immgen.org/Protocols/ImmGen%20Cell%20prep%20an age expression was used. For PCA, the top 10% of the most variable probe sets d%20sorting%20SOP.pdf). Cells were isolated from 3 to 15 mice per sample. was calculated with the PopulationDistances PCA program (S. Davis, Harvard For isolation of siLP and siIEL, small intestine beginning half a centimeter after Medical School). This program identifies differently expressed genes through the pylorus and ending half a centimeter before the cecum with Peyer’s patches ANOVA using the geometric standard deviation of populations to weight genes removed was dissociated using the Miltenyi Lamina Propria Dissociation kit, that vary in multiple populations. The data set for the top 10% of genes with which includes two dithiothreitol/EDTA washes and an enzymatic diges- the most variability was log2-transformed in MATLAB and used to generate tion step of 30 min. For liver and spleen isolation, mice were perfused with a PCA with the functions pca and scatter3. Hierarchical clustering of sample Nature America, Inc. All rights reserved. America, Inc. © 201 5 Nature 20 mL of cold PBS, and tissue was dissociated through a 70 µm cell strainer. replicates was carried out in Gene-E from the same data set, with the Pearson Lymphocytes were enriched at the interface between a gradient of 40% and correlation used as a metric. For RNA sequencing analysis, data from GEO 70% Percoll in HBSS. siIELs were further preenriched by negative selection accession code GSE52043 were visualized in Integrative Genomics Viewer and

npg with anti-CD8 MicroBeads (Miltenyi). Liver and spleen were pre-enriched by aligned to the mm9 National Center for Biotechnology Information assembly negative selection with anti-CD19 and anti-CD4 MicroBeads (Miltenyi). Cells of the mouse genome, as described43. were double-sorted directly into TRIzol with a Becton-Dickinson FACSAria II. The data browser of the ImmGen Project website shows flow cytometry plots Statistics. Prism (GraphPad Software) was used for statistical analysis of flow from gating strategies and purity from the first round of sorting. Cytospins cytometry data. Data were tested using either one-way ANOVA or two-way were prepared according to the same ImmGen standards, except from only one ANOVA, as indicated. to three mice; splenic samples were positively pre-enriched with DX5-coated beads (Miltenyi). Sorted cells were spun onto slides, left to dry overnight, and 51. Reich, M. et al. GenePattern 2.0. Nat. Genet. 38, 500–501 (2006).

nature immunology doi:10.1038/ni.3094