A gene regulatory network armature for T lymphocyte specification Constantin Georgescua, William J. R. Longabaughb, Deirdre D. Scripture-Adamsa, Elizabeth-Sharon David-Funga, Mary A. Yuia, Mark A. Zarnegara, Hamid Bolouria,b,1, and Ellen V. Rothenberga,1 aDivision of Biology 156-29, California Institute of Technology, Pasadena, CA 91125; and bInstitute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103 Edited by Michael S. Levine, University of California, Berkeley, CA, and approved September 8, 2008 (received for review July 6, 2008) Choice of a T lymphoid fate by hematopoietic progenitor cells network architecture may lie at the core of stem cell-based depends on sustained Notch–Delta signaling combined with tightly cell-type specification. regulated activities of multiple transcription factors. To dissect the An extreme case of this mode of specification is mammalian regulatory network connections that mediate this process, we T lymphocyte development. In T cell specification, cells preserve have used high-resolution analysis of regulatory gene expression a variety of developmental options and a capacity for extensive trajectories from the beginning to the end of specification, tests of proliferation throughout and even after commitment to a T cell the short-term Notch dependence of these gene expression fate. T cell development begins with the migration of multipotent changes, and analyses of the effects of overexpression of two hematopoietic precursors into the thymus, where these cells essential transcription factors, namely PU.1 and GATA-3. Quanti- adopt T lineage characteristics and gradually give up the ability tative expression measurements of >50 transcription factor and to give rise to other kinds of blood cells. Lineage exclusion is not marker genes have been used to derive the principal components only slow but discontinuous for T cell precursors in the thymus: of regulatory change through which T cell precursors progress there is a delay of multiple cell cycles between the time cells lose from primitive multipotency to T lineage commitment. Our anal- certain non-T options (red blood cell, B cell) and the time they yses reveal separate contributions of Notch signaling, GATA-3 finally become committed to a T cell fate (reviewed in ref. 4). activity, and down-regulation of PU.1. Using BioTapestry (www. Unlike B cell specification, a feed-forward cascade with critical BioTapestry.org), the results have been assembled into a draft roles for two lineage-specific transcription factors (5), T cell gene regulatory network for the specification of T cell precursors specification appears to use few, if any, dedicated factors (re- and the choice of T as opposed to myeloid/dendritic or mast-cell viewed in refs. 4 and 6). T cell identity emerges through the fates. This network also accommodates effects of E proteins and combined activities of at least eight, mostly lineage nonspecific, mutual repression circuits of Gfi1 against Egr-2 and of TCF-1 against transcription factors under the influence of Notch pathway PU.1 as proposed elsewhere, but requires additional functions that signals from the thymic microenvironment. The challenge has remain unidentified. Distinctive features of this network structure been to understand the mechanisms operating in this multicom- include the intense dose dependence of GATA-3 effects, the gene- ponent system. specific modulation of PU.1 activity based on Notch activity, the Here, we seek to make explicit the regulatory structures and lack of direct opposition between PU.1 and GATA-3, and the need some aspects of combinatorial control that underlie T lineage for a distinct, late-acting repressive function or functions to extin- specification in mice. This synthesis combines evidence from: (i) guish stem and progenitor-derived regulatory gene expression. purifying staged T cell precursors from the stem cell through the commitment stage; (ii) defining multiple transcription factor GATA-3 ͉ Notch ͉ PU.1 ͉ T cell development ͉ transcriptional regulation gene expression changes that distinguish these stages in vivo;(iii) characterizing the impacts of Notch signaling on gene expression xclusion of alternative fates is integral to cell-type specifica- at individual stages, using in vitro culture systems to control Etion and one of the key features explained by the gene delivery of Notch signals; and (iv) a perturbation analysis based regulatory networks for development in well studied embryo- on manipulation of two key transcription factors that are thought logical systems. Cell type-specific gene activation is tightly to drive opposing network subcircuits in the T cell development coupled with blockade of alternative gene programs, through process. We compare the likely inputs of three regulators on the three basic elements of gene network architecture: positive developmental trajectory of the cells and present a combinato- autoregulation of major cell type-specific transcription factors, rial map of regulatory connections as a testable framework for feed-forward relationships between these factors and their col- reconstructing the full process. laborators, and mutual antagonisms between the drivers of alternative cell fates. The collective impact of these mechanisms This paper results from the Arthur M. Sackler Colloquium of the National Academy of is usually to create within tight spatial and temporal boundaries Sciences, ‘‘Gene Networks in Animal Development and Evolution,’’ held February 15–16, a swift cascade of regulatory changes that become effectively 2008, at the Arnold and Mabel Beckman Center of the National Academies of Sciences and irreversible (1). Yet this is not the only way that cell type Engineering in Irvine, CA. The complete program and audio files of most presentations are specification can occur. In stem cell-based systems like those in available on the NAS web site at: http://www.nasonline.org/SACKLER_Gene_Networks. adult mammals, multipotency is actively maintained over many Author contributions: H.B. and E.V.R. designed research; D.D.S.-A., E.-S.D.-F., M.A.Y., and M.A.Z. performed research; C.G., W.J.R.L., and H.B. contributed new reagents/analytic cell cycles. Even as differentiation of these precursors begins, tools; C.G., W.J.R.L., D.D.S.-A., E.-S.D.-F., M.A.Y., M.A.Z., H.B., and E.V.R. analyzed data; and there can be considerable delay before the cell fate decision is C.G., H.B., and E.V.R. wrote the paper. determined. For example, many of the cell fate decisions of The authors declare no conflict of interest. mouse hematopoietic stem cell progeny may be controlled by This article is a PNAS Direct Submission. ␣ dynamic balances of regulatory factors such as PU.1, C/EBP , 1To whom correspondence may be addressed. E-mail: [email protected] or and GATA-2 throughout the intermediate stages of the process. [email protected]. Even in collaboration, these factors appear to drive up to four This article contains supporting information online at www.pnas.org/cgi/content/full/ different cell fates depending on the ratios and fluxes of their 0806501105/DCSupplemental. activities (2, 3). This behavior is a clue that a distinctive gene © 2008 by The National Academy of Sciences of the USA 20100–20105 ͉ PNAS ͉ December 23, 2008 ͉ vol. 105 ͉ no. 51 www.pnas.org͞cgi͞doi͞10.1073͞pnas.0806501105 Downloaded by guest on September 27, 2021 Table 1. Gene expression changes marking transitions in T-cell development FEATURE Specification, SACKLER SPECIAL Initiation, DN2 entry, DN1–DN3 continuous Commitment, DN3 stage ␤-Selection stem to DN1 DN1 to DN2 Gene category increase increase Increase Decrease Increase Decrease Increase Decrease Transcription factors GATA-3 Bcl11b GATA-3 PU.1 Ets2 PU.1 Aiolos SpiB TCF-1 HEB-alt TCF-1 (Tcf7) SCL Pou6f1 SCL SATB1 HES1 HES1 HEB (Tcf12) GATA-2 SpiB Tbet Myb Ikaros Id2 HES1 Runx1 Gfi1 Runx2 LEF-1 HEB-alt Runx1 Runx3 Id3 Erg Ets1 Gfi1B Id2 C/EBP␣ (and others) (& others) Targets/other Deltex1 CD3␥ IL-7R␣ Mac-1 Deltex1 c-Kit TCR-C␣ Deltex1 CD3␧ CD25 pT␣ (Ptcra) IL-7R␣ Rag-1 Rag-1 pT␣ (Ptcra) CD3␧ Notch3 Rag-1 Lck Lck CD25 LAT LAT ZAP70 Bcl2 ZAP70 ZAP70 Notch1 Results and Discussion stant expression are placed near the origin (center of the graph). Early T Cell Developmental Progression Through Regulatory Gene Genes with the highest change in expression are furthest from Expression Space. Mouse T cell precursors go through canonical the center. The more similar the patterns of expression of two BIOLOGY genes, the smaller the angle between them from the center. stages between entry into the thymus and full commitment to the DEVELOPMENTAL T cell lineage, distinguishable by changes in surface markers and Fig. 1A and Fig. S1 show that the first principal component (x quantitatively distinct patterns of gene expression. The same axis) accounts for most of the gene expression differences stages are used in fetal T cell development, adult T cell devel- between the DN1 and the DN3a/3b stages. The second principal opment, and when T cell precursors are induced to differentiate component (y axis) accounts mostly for differences between in stromal culture in vitro, although the kinetics of the progres- DN3a cells and ␤-selected cells. Subtler changes are captured in sion differ among fetal, adult, and in vitro development (7–9) the third and fourth principal components. The first part of the (D.D.S.-A., unpublished data). Cells proliferate in each of the developmental path toward commitment is nearly parallel to the first two or three stages for several days before moving on to the first principal component axis, as the cells abandon their use of next one. Thus, unlike embryonic systems where autonomous prethymically expressed regulatory genes such as Sfpi1 (encod- progression from state to state is ‘‘hard-wired’’ in the regulatory ing PU.1), Tal1 (encoding SCL), Gata2, and Gfi1b (at the DN1/2 circuitry, T cell specification is inherently discontinuous: pro- end of the axis).