Analysis of Transcription Factor Expression
during Discrete Stages of Postnatal
Thymocyte Differentiation
This information is current as
of June 18, 2017.
Sahba Tabrizifard, Alexandru Olaru, Jason Plotkin,
Mohammad Fallahi-Sichani, Ferenc Livak and Howard T.
Petrie
J Immunol 2004; 173:1094-1102; ;
doi: 10.4049/jimmunol.173.2.1094
http://www.jimmunol.org/content/173/2/1094
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Copyright © 2004 by The American Association of
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Supplementary
Material
The Journal of Immunology
Analysis of Transcription Factor Expression during Discrete
Stages of Postnatal Thymocyte Differentiation1
Sahba Tabrizifard,* Alexandru Olaru,† Jason Plotkin,* Mohammad Fallahi-Sichani,*
Ferenc Livak,†‡ and Howard T. Petrie2*§
T
he continuous, lifelong production of new T cells by the
thymus is an essential requirement in the maintenance of
immune function and homeostasis (1). Thymocyte differentiation is a stepwise process initiated by bone marrow progenitors that home to the thymus via the blood. The earliest intrathymic
progenitors are defined by the absence of mature T lineage markers
(CD4CD8 double-negative; DN3). This population is heterogeneous and can be divided into multiple stages (reviewed in Ref. 2).
The earliest of these, designated DN stage 1 (DN1), can be identified by the expression of CD44 and CD117 and by the absence of
CD25. DN1 cells are not T lineage restricted and can give rise to
multiple other lineages under appropriate conditions (3– 6). After
an average of ⬃10 days of intrathymic residence (7, 8), DN1 cells
asynchronously leave the perimedullary regions, where they first
enter the thymus (8, 9), and enter the cortex proper (8). This movement corresponds to differentiation into the DN2 stage and is
marked by the acquisition of CD25. Cells at the DN2 stage are
more lineage restricted, although they can still give rise to non-T
lineages (3– 6). In contrast, cells at the next stage of development,
designated DN3 (CD25⫹44low117low), bear the irreversible hall-
*Department of Microbiology and Immunology, University of Miami School of Medicine, Miami, FL 33101; and †Department of Microbiology and Immunology and
‡
Graduate Program in Molecular and Cellular Biology, University of Maryland
School of Medicine, Baltimore, MD 21201
Received for publication January 30, 2004. Accepted for publication May 4, 2004.
The costs of publication of this article were defrayed in part by the payment of page
charges. This article must therefore be hereby marked advertisement in accordance
with 18 U.S.C. Section 1734 solely to indicate this fact.
1
This work was supported by U.S. Public Health Service Grants AI33940 and
AI53739 (to H.T.P.) and by funds from Memorial Sloan-Kettering Cancer Center.
2
Address correspondence and reprint requests to Dr. Howard T. Petrie, University of
Miami School of Medicine, P.O. Box 016960 (R-138), Miami, FL 33101. E-mail
address: [email protected]
3
Abbreviations used in this paper: DN, double-negative; DP, double-positive; preDP,
early part of the DP phase; smDP, small DP cells; GO, Gene Ontology Consortium;
HPRT, hypoxanthine-guanine phosphoribosyltransferase; KLF, Krupple-like factor;
PCAF, p300/CBP-associated factor.
Copyright © 2004 by The American Association of Immunologists, Inc.
mark of T lineage commitment, in the form of rearrangements of
the TCR loci (10, 11), particularly D␤-J␤ rearrangements (11).
Nonetheless, the thymus generates numerous T lineage cell types,
including CD4, CD8, ␥␦, NK-T, and T-regulatory cell types (to
name a few), and it remains unclear at what point these lineages
diverge. Thus, although DN3 cells are T lineage restricted, additional lineage specification events continue to be required even
after this stage.
Differentiation onward from the DN3 stage appears to occur
only in cells that have generated productive rearrangements at one
or more of the TCR loci (12, 13) and coincides with expression of
both CD4 and CD8 mature lineage markers (double-positive; DP).
The early part of the DP phase (preDP, commonly but inappropriately referred to as DN4) is characterized by cells with low
surface expression of CD4 and CD8 (14), as well as by the presence of complete, productive V␤-DJ␤ rearrangements (12). The
TCR␤ protein is also expressed on the cell surface at this time (15),
in conjunction with an invariant pre-T ␣-chain (16) and CD3 (14).
Rearrangement of the TCR␣ locus is then initiated (11), and CD4
and CD8 accumulate at high levels on the cell surface. Cytogenesis
then ceases for the most part (17, 18), resulting in the production
of nondividing, small DP cells (smDP). Further differentiation is
associated with selection of those cells from this pool that express
TCRs of the correct specificity. By this point, each thymic homing
progenitor has undergone ⬃1 million-fold expansion in cell number (7), representing 20 serial divisions. This proliferation is not
synchronous throughout the differentiation process. The largest
number of cell divisions occurs at the DN1 stage (7), consistent
with the relatively long cell cycle times (19, 20) and extended
period of development (8) associated with this stage. DN2 and
DN3 cells both divide a few times each (7) but cycle at very different rates (19, 20), indicating further differences in their genetic
programs. The preDP stage is associated with almost as many cell
divisions as DN1 cells (7), but in contrast to DN1, cell cycle times
appear to be extremely short (19 –21), given that these cells must
expand 6- to 8-fold in ⬍2 days before withdrawal from cycle (7).
0022-1767/04/$02.00
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Postnatal T lymphocyte differentiation in the thymus is a multistage process involving serial waves of lineage specification,
proliferative expansion, and survival/cell death decisions. Although these are believed to originate from signals derived from
various thymic stromal cells, the ultimate consequence of these signals is to induce the transcriptional changes that are definitive
of each step. To help to characterize this process, high density microarrays were used to analyze transcription factor gene
expression in RNA derived from progenitors at each stage of T lymphopoietic differentiation, and the results were validated by
a number of appropriate methods. We find a large number of transcription factors to be expressed in developing T lymphocytes,
including many with known roles in the control of differentiation, proliferation, or cell survival/death decisions in other cell types.
Some of these are expressed throughout the developmental process, whereas others change substantially at specific developmental
transitions. The latter are particularly interesting, because stage-specific changes make it increasingly likely that the corresponding transcription factors may be involved in stage-specific processes. Overall, the data presented here represent a large resource
for gene discovery and for confirmation of results obtained through other methods. The Journal of Immunology, 2004, 173:
1094 –1102.
The Journal of Immunology
Materials and Methods
Cell sorting and RNA extraction
Thymocytes were isolated from 4- to 5-wk-old male C57BL/6 mice (The
Jackson Laboratory, Bar Harbor, ME). Early lymphopoietic progenitors
were isolated by first depleting small thymocytes (DP cells) using an isoosmotic gradient of 13.4% Opti-Prep (Greiner Bio-One, Longwood, FL) in
HBSS, followed by staining with a lineage mixture of Abs (CD3, CD4,
CD8, CD11b, Gr1, TER-119) and depletion with paramagnetic beads. Populations were identified as follows: DN1, CD24⫹25⫺44⫹; DN2,
CD24⫹25⫹44⫹; DN3, CD24⫹25⫹44low; preDP, CD24⫹25⫺44low. Additional sort discriminators were 4⬘,6⬘-diamidino-2-phenylindole⫺ (viable),
low side scatter, and singlets (forward scatter pulse area vs width). Small
DP thymocytes were identified as being forward scatter low as well as
expressing high levels of CD4 and CD8. Only sorted populations that were
⬎99% pure were used as template for microarray analysis. RNA was extracted using StrataPrep total RNA kits as recommended by the manufacturer (Stratagene, La Jolla, CA). Overall, purified cells from 16 different
cell sorting days, each including 8 –10 thymuses, were pooled to make a
minimum of 5 ␮g of RNA template for further analysis.
Probe synthesis and chip hybridization
RNA was not amplified before use as a template to generate labeled probes.
All procedures were conducted by the Molecular Genomics Core Facility
at Memorial Sloan-Kettering Cancer Center (New York, NY). Biotin-labeled cRNA probes were prepared as recommended by the chip manufacturer (Affymetrix, Santa Clara, CA). Briefly, 5 ␮g of total cellular RNA
were used to generate double-stranded cDNAs with oligodeoxythymidine
primers and SuperScript reverse transcription reagents (InVitrogen, Carlsbad, CA). The resulting dsDNA was used to prepare biotinylated cRNA
probes with a BioArray High Yield RNA Transcript kit (Affymetrix). Biotin-labeled cRNA was fragmented and hybridized to the MG-U74A array
for 16 h at 45°C as recommended by the manufacturer. Washing was performed using an automated fluidics workstation, and the array was imme-
diately scanned on a Hewlett Packard GeneArray Scanner (Hewlitt Packard, Palo Alto, CA).
Identification of genes expressed at each stage of development
The methods for analysis of the chip image were those recommended by
the manufacturer (Affymetrix). Two primary parameters are of interest for
each gene on the chip, namely, the absolute call (present, absent, or marginal) and the signal intensity. Calculation of these values was achieved as
follows. The difference between probe pair (matched/mismatched) intensities was used to generate a discrimination score. If the discrimination
score was higher than a default predefined threshold (␶ 0.015), the gene
was assigned a call of present; if it was lower, a call of absent or marginal
was assigned. The one-sided Wilcoxon signed rank test was then used to
determine a weighted mean of the discrimination scores for each probe set
(i.e., for each gene). These results were then used to generate confidence
limits that the combined score was different from the default threshold (␶).
When the confidence interval indicated that the weighted mean was significantly different from ␶ ( pnull ⬍ 0.04), the gene product was designated
as being present. A list of genes present in each stage was then prepared,
and for these the signal intensity value was extracted. Signal intensity
represents a quantitative assessment of the relative level of expression for
each individual gene. This is determined by taking the log2 of the difference
in intensity between each matched/mismatched probe pair (negative values
are not used) and then calculating a weighted mean using the one-step
Tukey biweight estimate. This mean value is then expressed relative to the
mean of all genes found to be present on the chip, set to an arbitrary value
(in this case, 500). Thus, genes that are present ( pnull ⬍ 0.04) and have a
signal intensity of 1000 would be categorized as being expressed at roughly
twice the mean level for all genes in that sample.
Identification of differentially expressed genes and transcription
factors
The list of all genes present at one or more stage of differentiation (described above) was merged, and the signal intensities of adjacent stages of
differentiation (e.g., DN1 vs DN2, DN2 vs DN3, etc.) were compared with
identify genes that underwent changes of ⬎2-fold at each developmental
transition. This list was then annotated by submitting a batch query to the
Affymetrix NetAffx website (https://www.affymetrix.com/analysis/query/
interactive_query.jsp) using the probe set identification numbers corresponding to these differentially expressed genes. This annotated list was
then filtered based on Gene Ontology (GO) Consortium designations related to transcription factor activity. Specifically, the following designations were used: GO biological process numbers 16481 (negative regulation of transcription), 45941 (positive regulation of transcription), 6350
(transcription), 6351 (transcription, DNA dependent), 6355 (regulation of
transcription), 6366 (transcription from polII promoter), 6367 transcription
factor from polI promoter; GO cell component numbers 5634 (nucleus) and
5667 (transcription factor complex); GO molecular function numbers16563 (transcription activator), 16564 (transcriptional repressor), 3676
(nucleic acid binding), 3677 (DNA binding), 3700 (transcription factor),
3712 (transcription cofactor), 3713 (transcription coactivator), and 3714
(transcription corepressor. Irrelevant genes emerging from these categories
(e.g., RNA polymerases, histones, etc.) were manually removed from
the list.
Real-time RT-PCR analysis
cDNA was synthesized from DNase-treated RNA from sorted thymocyte
subsets (prepared as described above), using random hexamer primers and
Superscript II reverse transcriptase (InVitrogen). Real time, quantitative
PCRs were performed in duplicate. A standard curve consisting of four
5-fold dilutions of thymus or brain cDNA was included in each experiment
for each primer pair. PCRs were performed for 40 cycles on an ABI 7900
Sequence Analyzer (Applied Biosystems, Foster City, CA) using a
SybrGreen master mix according to the manufacturer’s instructions. After
the final cycle, automatic melting curve analysis was performed to ensure
that only single PCR products were included in the data analysis. The final
product was also analyzed by agarose gel electrophoresis to verify the size
and integrity of the product and to ensure that it corresponded to the single
peak seen with melting curve analysis. Quantitative analysis was performed using SDS2.0 software (Applied Biosystems). The minimum number of cycles required for detection above a threshold (cycle threshold, Ct)
was used to calculate the absolute cDNA amount in each sample by extrapolating Ct values onto the four-point standard curve. Expression of a
housekeeping gene (hypoxanthine-guanine phosphoribosyltransferase;
HPRT) was likewise calculated for each sample. The relative level of expression for each transcription factor gene was then calculated by dividing
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The numerous complex changes that accompany lymphopoiesis
in the postnatal thymus are initiated by signals from stromal cells
that constitute the thymic microenvironment (reviewed in Ref. 22).
Ultimately, however, cellular differentiation is defined by changes
in the expression patterns of the required genes. Gene expression
can be controlled in a variety of ways, but a major regulatory
mechanism is the modulation of transcription, mediated by nuclear
transcription factors. Transcription factors bind to specific cis-regulatory DNA elements (promoters, enhancers, and silencers) to
induce or repress gene expression (23). Transcription factors
present within a cell act in regulatory networks to establish various
patterns of gene expression, and changes in these patterns define
cellular differentiation (24). Consequently, the identification of
transcriptional regulatory networks present in precursor cells vs
their progeny may be used to reveal the mechanisms that drive
differentiation. Recent studies have examined gene expression during hemato- and lymphopoiesis (25, 26) but have not focused on
specific subsets of genes in specific developmental stages. To this
end, we have performed gene expression analyses in progenitor
thymocyte stages associated with the lineage commitment and proliferation processes, using high density microarrays. Here we summarize the results with regard to transcription factors that are expressed at different progenitor stages, with particular emphasis on
those that change with respect to various developmental transitions. This analysis reveals novel patterns of expression of numerous transcription factors, including many not previously known to
be involved in the thymocyte differentiation process. We discuss
some examples of these with respect to their known roles in other
cell types and potential corresponding function in thymocyte progenitors, and/or their relationships to upstream or downstream
components known to be required by developing thymocytes. In
addition, the data provided here constitute a rich informational
resource for interrogation and validation of transcriptional patterns
in developing lymphocytes.
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TRANSCRIPTIONAL CONTROL OF THYMOCYTE DEVELOPMENT
its cDNA value by the corresponding HPRT cDNA value. Primer sequences were as follows. Bcl6: forward, CCGTACCCCTGTGAAATCTG;
reverse, AAGTCGCAGTTGGCTTTTGT. Ezh1: forward, AAAACGGAA
GCGCCATGCTA; reverse, TGTGCACTGAGGGGGAAGTG. Ezh2: forward, TTCGTGCCCTTGTGTGATAG; reverse, AGCATGGACACTGTT
TGGTG. Egr1: forward, CAGGAGTGATGAACGCAAGA; reverse,
TGGGGATGGGTAAGAAGAGA. Klf7: forward, CAAGTGCTCATGG
GAAGGA; reverse, TGGTCAGACCTGGAGAAACA. Klf3: forward,
AGAACCATCCTTCCGTCATC; reverse, GGTGCATTTGTACGGCTTTT.
Irf7: forward, CCTCTTGCTTCAGGTTCTGC; reverse, GCTGCATAG
GGTTCCTCGTA. Irf5: forward, TTCCAGAAGGGCCAGACTAAT; reverse, TGACATCAGGCCATTCTTCTC. BhlhB2: forward, AGCCGTG
GACTTGAAAGAGA; reverse, TGGATGACTGGCACACAGTT. c-Fos:
forward, ATCCTTGGAGCCAGTCAAGA; reverse, TCCCAGTCTGCTG
CATAGAA. c-Jun: forward, TAACAGTGGGTGCCAACTCA; reverse,
CGCAACCAGTCAAGTTCTCA. Rorc: forward, GCCCACCATATTC
CAATACCT; reverse, TAAGTTGGCCGTCAGTGCTAT; Nab1: forward,
GACCCACACAAAGAGGAGGA; reverse, GGGCATTGTCCTTCA
CACAC. Nab2: forward, GAACCAGAGATGGTGCGAAT; reverse,
TTCCGGATCTCCTCTTCCTT. l2ra: forward, AACGGCACCATC
CTAAACTG; reverse, CTGTGTTGGCTTCTGCATGT. Hprt: forward,
ATCAGTCAACGGGGGACATA; reverse, TTGCGCTCATCTTA
GGCTTT.
FIGURE 2. Transcription factors that are differentially expressed during
the DN1 to DN2 transition. Values on the horizontal axis indicate fold
changes in transcription factor expression between stages, as indicated.
Only transcription factors with a ⬎2-fold change are shown. Values for
those factors that changed ⬎10-fold are indicated next to the corresponding
bar. Fold changes depicted as infinite (⬁) indicate that the corresponding
factor was only present in one of the two stages being compared; these
genes are listed in Table I.
Results
Changes in transcription factor expression during inthrathymic
lymphoid progenitor development
To reveal new candidates involved in transcriptional control of T
lymphocyte developmental programs, we performed microarray
analysis using Affymetrix high density mouse arrays (U74A).
RNA was extracted from purified populations of intrathymic lymphopoietic progenitors, including DN1, DN2, DN3, and preDP
cells, as well as small, noncycling DP cells as ␣␤ lineage committed, postmitotic controls. The strategy for identification of transcription factors that might be important during specific developmental transitions is illustrated in Fig. 1. First, a list of all genes
present (see Materials and Methods) in at least one progenitor
stage was prepared. Next, this list was filtered to provide a list of
genes that changed more than 2-fold on transition from one stage
of differentiation to another. This list of all genes that change at
one or more developmental transitions was then annotated by a
batch query of the Affymetrix database. GO designations (www.
geneontology.org) were then used to specifically identify genes
from this list that are associated with transcriptional regulation.
This final list of transcription factors that undergo ⬎2-fold changes
in expression levels at defined developmental transitions was used
to generate the data shown in Figs. 2–5. In addition, genes that are
expressed throughout all subsets but do not change ⬎2-fold at any
individual transition are presented in Supplemental Table I.4 Some
of these may change ⬎2-fold over multiple phases of the transition
from DN1 to smDP. In the interest of space, we have not attempted
to add the numerous additional figures that would be required to
display such changes. For those interested, such findings can be
extracted from Supplemental Table II, which provides the signal
levels and present/absent calls for all genes described in all figures
and tables of this article.
Because of the complexities involved in attempting to describe
gene products in terms of their biological processes or molecular
4
The on-line version of this article contains supplemental material.
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FIGURE 1. Strategy for bulk identification of transcription factors
present during early thymocyte differentiation.
The Journal of Immunology
functions, not all proteins generally considered to be transcription
factors are necessarily revealed when filtered based on GO annotations. However, at the time of this writing, every effort has been
made to ensure that all relevant genes are included, including by
manual inspection of gene lists as described in Materials and
Methods. It is also important that neither c-fos nor c-jun were
identified by microarray analysis, either as genes that change during the differentiation process (Figs. 2–5) or as common genes
(Supplemental Table I). This is not because these genes are not
expressed in progenitor cells (Fig. 6), but rather they result from
poor probe design and performance on the U74A chip; i.e., signal
was detected in the matched oligos but was not significantly different in the single-base mismatch. Despite such occasional problems, the microarray analysis does provide, for the most part, reliable and informative results, as described in further detail below.
A few caveats regarding these data are warranted. First, all populations of progenitor thymocytes contain cells at different stages
of cell cycle (19, 20), including smaller (G1-S phases) and more
blastic (G2-M phases) cells, and the relative proportions of such
cells may influence the gene expression outcomes for any individual phase. Likewise, because differentiation in the steady state thymus is not synchronous, each subset likely includes a proportion of
cells that have already received signals to differentiate to the next
stage, as well as cells that have not yet received such signals, and
the relative proportions of these again may contribute to the gene
expression patterns attributed to any single subset. Finally, without
additional verification (such as by RT-PCR; see Validation of microarray results by analysis of known genes for selected genes in
this category), it may be risky to generalize the fold changes and/or
absolute expression levels described here. Rather, we believe that
our results should be used as guidelines for more critical assessments of gene expression and/or for validation of existing results.
Validation of microarray results by analysis of known genes
To most accurately assess gene expression patterns during intrathymic T lymphocyte development, RNA extracted from purified
FIGURE 4. Transcription factors that are differentially expressed during
the DN3 to preDP transition. Values on the horizontal axis indicate fold
changes in transcription factor expression between stages, as indicated.
Only transcription factors with a ⬎2-fold change are shown. Values for
those factors that changed more than 10-fold are indicated next to the
corresponding bar. Fold changes depicted as infinite (⬁) indicate that the
corresponding factor was only present in one of the two stages being compared; these genes are listed in Table I.
cells was not amplified before probe synthesis. Purification of sufficient RNA template from rare DN1 and DN2 progenitors was
therefore quite costly and very time consuming, making replicate
microarray analysis an unattractive option. Therefore, to validate
microarray results, two other types of confirmatory analyses were
performed. In the first, microarray results for genes with welldocumented changes in expression patterns during thymocyte differentiation were examined. A small panel of these is shown in
Fig. 8. Consistent with what is already known (27), CD3⑀ is not
expressed at statistically significant levels in DN1 cells but increases in expression thereafter. Also consistent with previously
published results (28), the invariant preT␣ component of the preTCR (16) is highest on DN3 cells and lowest on DN1 and DN2
cells. Likewise, the RAG-2 and c-kit expression patterns revealed
by microarray analysis very closely parallel those previously reported by others (29, 30). CD25, which marks intermediate stages
of DN differentiation (30 –32), is found at significant levels only on
DN2 and DN3 cells by microarray analysis, whereas CD4 is upregulated only at the DP stage. We have also reported other consistencies between these microarray results and other methods of
analysis (33). In general, microarray results for genes known to be
differentially regulated during T cell differentiation were remarkably consistent with what would be expected, suggesting that most
transcription factors identified by this method (Figs. 2–5) are likely
to be valid candidates for further investigation.
Validation of microarray results by real-time, quantitative
RT-PCR
To specifically validate microarray data regarding potential transcriptional regulators of thymocyte differentiation, real time RTPCR was performed for 12 selected transcription factors identified
by microarray screening, as well as 1 additional control gene
(CD25). The results of these analyses are shown in Fig. 6. Candidates for confirmation were selected to span the variety of patterns and expression levels found, i.e., genes that went down during differentiation, up during differentiation, or various
combinations thereof, as well as genes that were relatively abundant vs those that were present but less abundant. In general, the
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FIGURE 3. Transcription factors that are differentially expressed during
the DN2 to DN3 transition. Values on the horizontal axis indicate fold
changes in transcription factor expression between stages, as indicated.
Only transcription factors with a ⬎2-fold change are shown. Values for
those factors that changed ⬎10-fold are indicated next to the corresponding
bar. Fold changes depicted as infinite (⬁) indicate that the corresponding
factor was only present in one of the two stages being compared; these
genes are listed in Table I.
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TRANSCRIPTIONAL CONTROL OF THYMOCYTE DEVELOPMENT
patterns of gene expression revealed by real time PCR were remarkably consistent with those found by microarray analysis. The
only significant exception to this was Ezh2, which appears to remain high or increase slightly at the DN2, DN3, and preDP stages
by microarray results, while decreasing over the same period by
real time PCR. In other cases, such as Irf7, the patterns of expression were similar, but the overall fold changes were slightly different between real time and microarray results. Bhlhb2 and Nab2
exhibited similar trends by both microarray and real time PCR but
differed slightly at a single transition (DN1/DN2 or DN2/DN3,
respectively). Overall, however, both the patterns and relative fold
changes appear to be very similar for both types of analysis. Together with the comparisons described earlier, these findings suggest that, in general, the microarray results reflect a fairly true
assessment of gene expression and have the potential to reveal
novel transcriptional candidates important in control of the intrathymic differentiation process.
Discussion
The differentiation of T lymphocytes in the postnatal thymus is
initiated by signals originating from stromal elements that form the
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FIGURE 5. Transcription factors that are
differentially expressed during the preDP to
smDP transition. Values on the horizontal axis
indicate fold changes in transcription factor
expression between stages, as indicated. Only
transcription factors with a ⬎2-fold change are
shown. Values for those factors that changed
⬎10-fold are indicated next to the corresponding bar. Fold changes depicted as infinite (⬁)
indicate that the corresponding factor was only
present in one of the two stages being compared; these genes are listed in Table I.
thymic microenvironment (reviewed in Ref. 22). The variety of
signals assimilated by individual precursor cells are subsequently
manifest as changes in transcriptional activity, many of which are,
in turn, a consequence of changes in transcription factor expression. Thus, the identification of transcription factors that are expressed by all early thymocytes (Supplemental Table I), and especially those that fluctuate during the differentiation process
(Figs. 2–5), represents an essential step in characterizing the biology of the lymphopoietic process. The advent of high density microarray analysis, as presented here, represents a high throughput
method for accomplishing this goal. In particular, we have focused
on the lymphopoietic stages of intrathymic differentiation, i.e.,
those stages that derive from non-self-renewing blood-borne progenitors and that generate the raw materials for positive and negative selection (i.e., smDP cells).
To accurately assess the expression of transcription factor genes
in early thymocyte progenitors, RNA was isolated directly from
cells and used without further amplification. Instead, numerous
samples were pooled from multiple days of purification and cell
sorting to make adequate RNA (5 ␮g) for the labeling and hybridization processes. Analysis of predicted patterns of expression (see
The Journal of Immunology
1099
FIGURE 6. Analysis of c-fos and c-jun by real time quantitative PCR.
As described in the text, the U74A array gave poor results for two transcription factors known to be expressed in thymocytes, namely c-fos and
c-jun. Visual examination of these probe images (not shown) revealed high
levels of hybridization to mismatched oligonucleotides, indicating that the
absent calls resulting from Wilcoxon signed rank analysis were a result of
poor probe design in these cases. To rectify this, PCR analysis was performed, and as shown here, c-fos and c-jun are expressed in early DN
progenitors. The y-axis values represent relative fos or jun expression,
compared with that of a housekeeping gene (HPRT), nominally defined as
equal to 1.
FIGURE 8. Validation of a panel of microarray results by quantitative
real time RT-PCR. A panel of 12 transcription factors were selected to span
the variety of expression patterns and expression levels revealed by microarray analysis, and these were further analyzed by quantitative real time
RT-PCR. Expression patterns found by RT-PCR (f) are shown on the left
axis; units are a ratio of cDNA levels calculated from the standard curve
(see Materials and Methods) for the gene of interest compared with that of
a housekeeping gene (HPRT). Values shown for RT-PCR are the mean of
two separate experiments. Expression patterns found by microarray (E) are
shown on the right axis relative to all genes expressed, where mean gene
expression levels are set at 500 (see Materials and Methods). In general,
patterns observed by RT-PCR very closely parallel those found by microarray, confirming the validity of microarray data.
stantially up-regulated (Fig. 2). In Tcf1 mutant mice (36), differentiation is impaired just before the DP stage, a stage at which our
data indicate that Tcf1 is up-regulated (Table I). Consistencies
were also noted between our data and published findings for Egrs
(37) c-Myb (38), GATA-3 (39), Lmo1 (40), Heb (41), Runx1 (42),
and many others. Overall, these consistencies together with the
documentation provided by known genes (Fig. 8) and quantitative
PCR (Fig. 6) indicate that the additional novel transcription factors
revealed by this study are very likely to be authentic regulators of
thymocyte differentiation. Although the sheer volume of factors
revealed by these studies precludes a discussion of all of them, a
few examples, together with their potential relevance, are discussed below.
Regulation of proliferation during early thymic lymphopoiesis
FIGURE 7. Analysis of expression of genes known to be differentially
regulated during thymocyte progenitor differentiation. As discussed in the
text, microarray results (shown here) correlate extremely well with known
gene expression patterns in developing thymocytes. For instance, CD3⑀ is
very low in DN1 cells and increases thereafter, as does CD4 and RAG-2,
whereas CD25 marks mainly the DN2 and DN3 progenitor stages, and c-kit
the DN1 and DN2 stages. Values on the y-axis are global expression units
(mean ⫽ 500; see text for an explanation).
Bone marrow thymocyte progenitors expand 1 million-fold on entry into the thymus but ultimately withdraw from the cell cycle
before maturation and export to the periphery (7). Expansion at
later intrathymic stages (i.e., at the DN/DP transition) is associated
with expression of components of the TCR (43). However, the
regulation of proliferation at earlier stages is still largely uncharacterized. Of particular interest is the down-regulation of proliferative status that occurs at the transition from DN2 to DN3 (19, 20).
Evaluation of our microarray data revealed a profound decrease in
Lyl1 associated with this transition (Table I). Breakpoint translocation fusing Lyl1 to the TCR␤ locus is a cytogenetic abnormality
Downloaded from http://www.jimmunol.org/ by guest on June 18, 2017
Fig. 8) confirmed the usefulness of this approach, as the vast majority of genes for which expression patterns are known were corroborated by this analysis (additional data not shown). Further, real
time quantitative PCR analysis for randomly selected transcription
factors identified by the present studies also confirmed the validity
of the results (Fig. 6).
In addition to the validations described above, comparison of
transcription factors already known to be involved in the T cell
differentiation process correlated extremely well with gene expression results by microarray. For instance. forced expression of Sfpi1
(PU.1) caused a block at the DN2/DN3 transition (34), indicating
that down-regulation of this transcription factor is required for this
transition to occur normally. Consistent with this, our data show
that DN1 and DN2 cells express Sfpi1, but it is absent after DN3
(Table I). Deficiency in Gfi1 leads to developmental arrest at the
DN2 stage (35), a stage at which our data indicate that it is sub-
1100
TRANSCRIPTIONAL CONTROL OF THYMOCYTE DEVELOPMENT
Table I. Transcription factor genes that turn on or off at specific developmental transitionsa
DN1/DN2 Transition
DN2/DN3 Transition
DN3/preDP Transition
PreDP/smDP Transition
Turned ON
Turned OFF
Turned ON
Turned OFF
Turned ON
Turned OFF
Turned ON
1190001I08Rik
4921515A04Rik
4930565N07Rik
4930565N07Rik
4930566A11Rik
Ankrd2
Atbf1
Atf3
Batf
Bcl3
C2ta
Cebpa
Cebpd
Clock
Dri1
Egr1
Eif2ak3
Fos
Gata6
Hipk2
Hlx
Hmga2
Hoxa2
Hoxa4
Hoxa9
Idb3
Irf4
Irf7
Irf7
Junb
Klf4
Klf5
Lef1
Lisch7-pending
Lmo2
Lmyc1
Nab2
Nr4a1
Nr6a1
Pax5
Pax6
Pbx1
Pbx3
Prdm1
Rbpsuhl
Relb
Spib
Tceb2
Tnfrsf5
Zfp105
Zfp36
Zfp46
4833408P15Rik
Atm
Bard1
Bn51t-pending
Dedd
Dlx6
Ets2
Fhl2
Hivep2
Hoxa7
Ikbkg
Mad3
Mllt10
Mybl2
Myst2
Nfatc2
Nfkbie
Nr1h2
Pknox1
Pla2g6
Rfx2
Rfxank
Sap18
Sox3
Sox7
Tal1
Tcf20
Tle4
Zfp26
Zfp260
Zfp358
Zfp97
2610110L04Rik
9130025P16Rik
9130211I03Rik
Bhlhb2
C630022N07Rik
Creg
Ctbp2
Deaf1
Dedd
Dlx6
Elk3
Gfi1b
Hoxa6
Hoxa7
Hoxb8
Hoxd3
Irf5
Lmo1
Lyl1
Mafg
Mllt10
Nfatc2
Nfil3
Nfkbie
Pou2af1
Rab25
Rfx2
Sfpi1
Sox3
Sox7
Tal1
Tle4
Zfp26
Zfp288
Zfp358
Zfp422
Creb1
Egr1
Esr1
Hes5
Idb3
Kcnh2
Lef1
Nab2
Nr1d1
Nr3c1
Nr4a1
Pax6
Pbx3
Pou6f1
Rbpsuhl
Sox15
Spib
Tceb2
Trp63
Trpc4
Zfp105
Zfp46
Zfp60
Zfy2
1110037D23Rik
4833408P15Rik
Atm
Creb1
Ddit3
Esr1
Gata1
Hes5
Hhex
Madh7
Nfe2
Nmyc1
Nr1d1
Nr1h2
Nr2c1
Nr3c1
Pax6
Pbx3
Per1
Sox15
Spib
Tbx6
Tcf1
Trpc4
Zfp29
Zfp385
Zfp46
Zfp60
Zfp61
Zfp99
Zfy2
2610110L04Rik
C630022N07Rik
D930018N21Rik
Deaf1
Dlx6
DP1
Dri1
Egr2
Ets1
Hand1
Hoxb7
Hoxb8
Hoxd3
Irx3
Mcmd6
Mllt10
Nr1h4
Pou2af1
Pou2f3
Prdm1
Ptrf
Rorc
Sox3
Zfp26
Zfp422
Znfn1a1
2610110L04Rik
Bard1
Bn51t-pending
Gcn512
Hand1
Hes1
Hoxb8
Hoxd3
Htr5a
Irx3
Klf9
Mcmd6
Nfix
Nr1h4
Pou2af1
Pou2f3
Ptrf
Rbpsuhl
Sox3
Tmpo
Zfp239
1110037D23Rik
4930566A11Rik
Arnt
Atm
C2ta
Clock
Creb1
D11Ertd714e
Ddit3
Dedd
Dusp16
E2f3
E2f5
Elf4
Elk3
Gata6
Hhex
Hoxb8
Irf6
Junb
Mef2b
Mllt2h
Mrg2
Mtf1
Nfatc3
Nfil3
Npas1
Nr1d1
Nr21
Nr3c1
Per1
Phf1
Pparbp
Rara
Rfx2
Rnf4
Rora
Sp4
Tbx6
Tcf1
Tle1
Zfp276
Zfp288
Zfp29
Zfp358
Zfp36
Zfp385
Zfp46
Zfp61
Zfp99
a
These genes are designated as infinite (⫺) fold changes in Figs. 2–5. A categorical summary of this table (i.e., by transcription factor family) can be found in Supplemental
Table III.
associated with ⬃20% of human T cell acute lymphocytic leukemias (44, 45), suggesting a role for Lyl1 in T cell in proliferation.
TCR␤ gene rearrangements also initiate at the DN2/DN3 transition
(11, 30), further strengthening the association and suggesting that
mistakes in the somatic (VDJ) recombination process in developing T cells may contribute to aberrant proliferation and oncogenic
transformation. Lyl1 is highly expressed early in T cell development (DN1 and DN2) but is completely repressed in DN3 cells
(Table I), consistent with RT-PCR results of others (46). Thus, our
data indicate the possibility that down-regulation of Lyl1 may represent a critical step in repressing cell cycle activity during VDJ
recombination in developing lymphocytes.
Transcriptional control of Notch signaling
The mammalian homologs of the Drosophila hairy-enhancer of
split (Hes) genes encode at least seven basic helix-loop-helix transcription factors (Hes1–7). Hes gene products are major transcriptional mediators of Notch signaling (reviewed in Ref. 47). Notch
plays an important role in T lymphopoiesis (reviewed in Ref. 48),
and regulation of Hes genes can therefore impact T cell differentiation by regulating Notch signals. For instance, inactivation of
either Notch1 or Hes1 results in similar arrest at early stages of
intrathymic T cell differentiation (49, 50). In the present data, Hes1
was expressed in the DN1–3 stages, significantly down-regulated
Downloaded from http://www.jimmunol.org/ by guest on June 18, 2017
Turned OFF
The Journal of Immunology
Cell cycle arrest and cell death or survival at the DP stage
Another cluster of transcriptional regulatory complexes that appears to be up-regulated at the transition to smDP (Fig. 5) includes
the Krupple-like factors (KLFs), the CBP/p300 transcriptional coactivator Cited2, and p300/CBP-associated factor (PCAF). A number of KLFs are up-regulated in smDP cells, including Klf3, 7, and
13 (Fig. 5). KLFs are heavily implicated in cell differentiation, cell
cycle regulation, and cell survival/death decisions (reviewed in
Ref. 58), all of which are characteristic of smDP cells (7). KLFs
have already been shown to have various roles in cells of the T
lineage, including differentiation, cell cycle withdrawal, and survival (for reviews, see Refs. 59 and 60). One particularly interesting factor in this family is KLF13. KLF13 has a role in the differentiation of effector T lymphocytes (61, 62). KLF13
transcriptional activity is regulated by the transcriptional coactivators CBP/p300 and PCAF (63), and PCAF and Cited2 are upregulated simultaneously with KLF13 at the smDP stage (Fig. 5).
Another factor, Klf7, has been implicated in exit from cell cycle by
inducing expression of cell cycle inhibitors (64), many of which
we find to be up-regulated in smDP cells (not shown). Thus, our
data indicate that the activity of KLFs, and in particular KLF7
and/or 13 and their regulatory partners, may represent good candidates for further characterization of the poorly understood networks that control cell cycle arrest, homeostasis, and cell survival/
death of smDP thymocytes.
Overall, the data presented here provide numerous novel observations regarding the transcriptional control of thymic T lymphocyte differentiation. Our confidence in the data is such that a number of these are already being followed up in our laboratories,
using transgenic and knockout approaches. However, the sheer
volume of factors found is daunting, and thus we believe that these
data provide a rich resource for gene discovery by others. In addition, these findings may be used to confirm gene expression analysis derived from other methods, such as RT-PCR and to break
those findings down into discrete subset results when whole thymocytes have been used as template.
References
1. Haynes, B. F., and L. P. Hale. 1999. Thymic function, aging, and AIDS. Hosp.
Pract. (Off. Ed.) 34:59.
2. Ceredig, R., and T. Rolink. 2002. A positive look at double-negative thymocytes.
Nat. Rev. Immunol. 2:888.
3. Manz, M. G., D. Traver, T. Miyamoto, I. L. Weissman, and K. Akashi. 2001.
Dendritic cell potentials of early lymphoid and myeloid progenitors. Blood
97:3333.
4. Michie, A. M., J. R. Carlyle, T. M. Schmitt, B. Ljutic, S. K. Cho, Q. Fong, and
J. C. Zuniga-Pflucker. 2000. Clonal characterization of a bipotent T cell and NK
cell progenitor in the mouse fetal thymus. J. Immunol. 164:1730.
5. Ikawa, T., H. Kawamoto, S. Fujimoto, and Y. Katsura. 1999. Commitment of
common T/natural killer (NK) progenitors to unipotent T and NK progenitors in
the murine fetal thymus revealed by a single progenitor assay. J. Exp. Med.
190:1617.
6. Ardavin, C., L. Wu, C. L. Li, and K. Shortman. 1993. Thymic dendritic cells and
T cells develop simultaneously in the thymus from a common precursor population. Nature 362:761.
7. Shortman, K., M. Egerton, G. J. Spangrude, and R. Scollay. 1990. The generation
and fate of thymocytes. Semin. Immunol. 2:3.
8. Porritt, H. E., K. Gordon, and H. T. Petrie. 2003. Kinetics of steady-state differentiation and mapping of intrathymic-signaling environments by stem cell transplantation in nonirradiated mice. J. Exp. Med. 198:957.
9. Lind, E. F., S. E. Prockop, H. E. Porritt, and H. T. Petrie. 2001. Mapping precursor movement through the postnatal thymus reveals specific microenvironments supporting defined stages of early lymphoid development. J. Exp. Med.
194:127.
10. Livak, F., M. Tourigny, D. G. Schatz, and H. T. Petrie. 1999. Characterization of
TCR gene rearrangements during adult murine T cell development. J. Immunol.
162:2575.
11. Petrie, H. T., F. Livak, D. Burtrum, and S. Mazel. 1995. T cell receptor gene
recombination patterns and mechanisms: cell death, rescue, and T cell production. J. Exp. Med. 182:121.
12. Dudley, E. C., H. T. Petrie, L. M. Shah, M. J. Owen, and A. C. Hayday. 1994.
T cell receptor ␤ chain gene rearrangement and selection during thymocyte development in adult mice. Immunity 1:83.
13. Burtrum, D. B., S. Kim, E. C. Dudley, A. C. Hayday, and H. T. Petrie. 1996. TCR
gene recombination and ␣␤-␥␦ lineage divergence: productive TCR-␤ rearrangement is neither exclusive nor preclusive of ␥␦ cell development. J. Immunol.
157:4293.
14. Petrie, H. T., M. Pearse, R. Scollay, and K. Shortman. 1990. Development of
immature thymocytes: initiation of CD3, CD4, and CD8 acquisition parallels
down-regulation of the interleukin 2 receptor ␣ chain. Eur. J. Immunol. 20:2813.
15. Petrie, H. T., R. Scollay, and K. Shortman. 1992. Commitment to the T cell
receptor-␣␤ or -␥␦ lineages can occur just prior to the onset of CD4 and CD8
expression among immature thymocytes. Eur. J. Immunol. 22:2185.
16. Groettrup, M., K. Ungewiss, O. Azogui, R. Palacios, M. J. Owen, A. C. Hayday,
and H. von Boehmer. 1993. A novel disulfide-linked heterodimer on pre-T cells
consists of the T cell receptor ␤ chain and a 33 kd glycoprotein. Cell 75:283.
17. Egerton, M., K. Shortman, and R. Scollay. 1990. The kinetics of immature murine thymocyte development in vivo. Int. Immunol. 2:501.
18. Penit, C., F. Vasseur, and M. Papiernik. 1988. In vivo dynamics of CD4⫺8⫺
thymocytes: proliferation, renewal and differentiation of different cell subsets
studied by DNA biosynthetic labeling and surface antigen detection. Eur. J. Immunol. 18:1343.
19. Tourigny, M. R., S. Mazel, D. B. Burtrum, and H. T. Petrie. 1997. T cell receptor
(TCR)-␤ gene recombination: dissociation from cell cycle regulation and developmental progression during T cell ontogeny. J. Exp. Med. 185:1549.
20. Penit, C., B. Lucas, and F. Vasseur. 1995. Cell expansion and growth arrest
phases during the transition from precursor (CD4⫺8⫺) to immature (CD4⫹8⫹)
thymocytes in normal and genetically modified mice. J. Immunol. 154:5103.
21. Hoffman, E. S., L. Passoni, T. Crompton, T. M. Leu, D. G. Schatz, A. Koff,
M. J. Owen, and A. C. Hayday. 1996. Productive T-cell receptor ␤-chain gene
rearrangement: coincident regulation of cell cycle and clonality during development in vivo. Genes Dev. 10:948.
22. Petrie, H. T. 2002. Role of thymic organ structure and stromal composition in
steady-state postnatal T-cell production. Immunol. Rev. 189:8.
23. Orphanides, G., and D. Reinberg. 2002. A unified theory of gene expression. Cell
108:439.
24. Davidson, E. H., J. P. Rast, P. Oliveri, A. Ransick, C. Calestani, C. H. Yuh,
T. Minokawa, G. Amore, V. Hinman, C. Arenas-Mena, et al. 2002. A genomic
regulatory network for development. Science 295:1669.
25. Park, I. K., Y. He, F. Lin, O. D. Laerum, Q. Tian, R. Bumgarner, C. A. Klug,
K. Li, C. Kuhr, M. J. Doyle, et al. 2002. Differential gene expression profiling of
adult murine hematopoietic stem cells. Blood 99:488.
26. Hoffmann, R., L. Bruno, T. Seidl, A. Rolink, and F. Melchers. 2003. Rules for
gene usage inferred from a comparison of large-scale gene expression profiles of
T and B lymphocyte development. J. Immunol. 170:1339.
27. Wilson, A., and H. R. MacDonald. 1995. Expression of genes encoding the preTCR and CD3 complex during thymus development. Int. Immunol. 7:1659.
28. Wilson, A., J. P. de Villartay, and H. R. MacDonald. 1996. T cell receptor ␦ gene
rearrangement and T early ␣ (TEA) expression in immature ␣␤ lineage thymocytes: implications for ␣␤/␥␦ lineage commitment. Immunity 4:37.
29. Wilson, A., W. Held, and H. R. MacDonald. 1994. Two waves of recombinase
gene expression in developing thymocytes. J. Exp. Med. 179:1355.
30. Godfrey, D. I., J. Kennedy, T. Suda, and A. Zlotnik. 1993. A developmental
pathway involving four phenotypically and functionally distinct subsets of
Downloaded from http://www.jimmunol.org/ by guest on June 18, 2017
upon the transition to preDP, and lost in smDP thymocytes. The expression of Hes1 thus strongly parallels published data regarding patterns of Notch1 expression (51) and signaling during the DN to DP
transition (52). There is also a modest, ⬍2-fold, up-regulation of Hes1
during the DN1 to DN2 transition (not shown), likewise in accordance
with published data (53), again corroborating the validity of microarray results presented here. However, our data also provide new insights regarding the regulation of Notch signaling in T cell development. Hes1 acts as a transcriptional corepressor upon interaction with
members of the Groucho family of proteins (reviewed in Ref. 54).
One member of this family, Groucho-5 (also known as amino-terminal enhancer of split, Aes), is specifically up-regulated on transition to
the DN3 stage and down-regulated again in preDP cells, mirroring the
expression peaks for Hes1 (Table I). Of interest, Groucho-5 is again
up-regulated at the smDP stage (Table I). Thus, down-regulation of
Groucho-5 appears to correlate specifically with the DN to DP transition, where Notch activity is known to be required (55). The upregulation of Groucho-5 at the smDP stage, where Hes1 is downregulated (Table I) may seem counterintuitive. However, Groucho
proteins also interact with a large variety of transcription factors other
than Hes (54). Further, we find Hes6 (Supplemental Table I) and
Notch3 (data not shown) are both expressed at the smDP stage, suggesting that Groucho-5 may alternatively interact with these. It is also
possible that interaction of Groucho-5 with Hes6 (56) could interfere
with the activity of Hes1, thus promoting terminal differentiation in
DP cells similar to its role in the nervous system (57).
1101
1102
31.
32.
33.
34.
35.
36.
37.
38.
40.
41.
42.
43.
44.
45.
CD3⫺CD4⫺CD8⫺ triple-negative adult mouse thymocytes defined by CD44 and
CD25 expression. J. Immunol. 150:4244.
Pearse, M., L. Wu, M. Egerton, A. Wilson, K. Shortman, and R. Scollay. 1989.
A murine early thymocyte developmental sequence is marked by transient expression of the interleukin 2 receptor. Proc. Natl. Acad. Sci. USA 86:1614.
Shimonkevitz, R. P., L. A. Husmann, M. J. Bevan, and I. N. Crispe. 1987. Transient expression of IL-2 receptor precedes the differentiation of immature thymocytes. Nature 329:157.
Plotkin, J., S. E. Prockop, A. Lepique, and H. T. Petrie. 2003. Critical role for
CXCR4 signaling in progenitor localization and T cell differentiation in the postnatal thymus. J. Immunol. 171:4521.
Anderson, M. K., A. H. Weiss, G. Hernandez-Hoyos, C. J. Dionne, and
E. V. Rothenberg. 2002. Constitutive expression of PU. 1 in fetal hematopoietic
progenitors blocks T cell development at the pro-T cell stage. Immunity 16:285.
Yucel, R., H. Karsunky, L. Klein-Hitpass, and T. Moroy. 2003. The transcriptional repressor Gfi1 affects development of early, uncommitted c-Kit⫹ T cell
progenitors and CD4/CD8 lineage decision in the thymus. J. Exp. Med. 197:831.
Verbeek, S., D. Izon, F. Hofhuis, E. Robanus-Maandag, H. te Riele,
M. van de Wetering, M. Oosterwegel, A. Wilson, H. R. MacDonald, and
H. Clevers. 1995. An HMG-box-containing T-cell factor required for thymocyte
differentiation. Nature 374:70.
Carleton, M., M. C. Haks, S. A. Smeele, A. Jones, S. M. Belkowski,
M. A. Berger, P. Linsley, A. M. Kruisbeek, and D. L. Wiest. 2002. Early growth
response transcription factors are required for development of CD4⫺CD8⫺ thymocytes to the CD4⫹CD8⫹ stage. J. Immunol. 168:1649.
Allen, R. D., 3rd, T. P. Bender, and G. Siu. 1999. c-Myb is essential for early T
cell development. Genes Dev. 13:1073.
Hendriks, R. W., M. C. Nawijn, J. D. Engel, H. van Doominck, F. Grosveld, and
A. Karis. 1999. Expression of the transcription factor GATA-3 is required for the
development of the earliest T cell progenitors and correlates with stages of cellular proliferation in the thymus. Eur. J. Immunol. 29:1912.
Chervinsky, D. S., X. F. Zhao, D. H. Lam, M. Ellsworth, K. W. Gross, and
P. D. Aplan. 1999. Disordered T-cell development and T-cell malignancies in
SCL LMO1 double-transgenic mice: parallels with E2A-deficient mice. Mol.
Cell. Biol. 19:5025.
Barndt, R., M. F. Dai, and Y. Zhuang. 1999. A novel role for HEB downstream
or parallel to the pre-TCR signaling pathway during ␣␤ thymopoiesis. J. Immunol. 163:3331.
Woolf, E., C. Xiao, O. Fainaru, J. Lotem, D. Rosen, V. Negreanu, Y. Bernstein,
D. Goldenberg, O. Brenner, G. Berke, D. Levanon, and Y. Groner. 2003. Runx3
and Runx1 are required for CD8 T cell development during thymopoiesis. Proc.
Natl. Acad. Sci. USA 100:7731.
Fehling, H. J., and H. von Boehmer. 1997. Early ␣␤ T cell development in the
thymus of normal and genetically altered mice. Curr. Opin. Immunol. 9:263.
Saltman, D. L., J. D. Mellentin, S. D. Smith, and M. L. Cleary. 1990. Mapping
of translocation breakpoints on the short arm of chromosome 19 in acute leukemias by in situ hybridization. Genes Chromosomes Cancer 2:259.
Ferrando, A. A., and A. T. Look. 2003. Gene expression profiling in T-cell acute
lymphoblastic leukemia. Semin. Hematol. 40:274.
46. Ferrando, A. A., S. Herblot, T. Palomero, M. Hansen, T. Hoang, E. A. Fox, and
A. T. Look. 2004. Biallelic transcriptional activation of oncogenic transcription
factors in T-cell acute lymphoblastic leukemia. Blood 103:1909.
47. Artavanis-Tsakonas, S., M. D. Rand, and R. J. Lake. 1999. Notch signaling: cell
fate control and signal integration in development. Science 284:770.
48. Guidos, C. J. 2002. Notch signaling in lymphocyte development. Semin. Immunol. 14:395.
49. Radtke, F., A. Wilson, G. Stark, M. Bauer, M. J. van, H. R. MacDonald, and
M. Aguet. 1999. Deficient T cell fate specification in mice with an induced
inactivation of Notch1. Immunity 10:547.
50. Tomita, K., M. Hattori, E. Nakamura, S. Nakanishi, N. Minato, and
R. Kageyama. 1999. The bHLH gene Hes1 is essential for expansion of early T
cell precursors. Genes Dev. 13:1203.
51. Hasserjian, R. P., J. C. Aster, F. Davi, D. S. Weinberg, and J. Sklar. 1996.
Modulated expression of notch1 during thymocyte development. Blood 88:970.
52. Deftos, M. L., E. Huang, E. W. Ojala, K. A. Forbush, and M. J. Bevan. 2000.
Notch1 signaling promotes the maturation of CD4 and CD8 SP thymocytes.
Immunity 13:73.
53. Reizis, B., and P. Leder. 2002. Direct induction of T lymphocyte-specific gene
expression by the mammalian Notch signaling pathway. Genes Dev. 16:295.
54. Fisher, A. L., and M. Caudy. 1998. Groucho proteins: transcriptional corepressors
for specific subsets of DNA-binding transcription factors in vertebrates and invertebrates. Genes Dev. 12:1931.
55. Huang, E. Y., A. M. Gallegos, S. M. Richards, S. M. Lehar, and M. J. Bevan.
2003. Surface expression of Notch1 on thymocytes: correlation with the doublenegative to double-positive transition. J. Immunol. 171:2296.
56. Gao, X., T. Chandra, M. O. Gratton, I. Quelo, J. Prud’homme, S. Stifani, and
R. St.-Arnaud. 2001. HES6 acts as a transcriptional repressor in myoblasts and
can induce the myogenic differentiation program. J. Cell Biol. 154:1161.
57. Bae, S., Y. Bessho, M. Hojo, and R. Kageyama. 2000. The bHLH gene Hes6, an
inhibitor of Hes1, promotes neuronal differentiation. Development 127:2933.
58. Dang, D. T., J. Pevsner, and V. W. Yang. 2000. The biology of the mammalian
Kruppel-like family of transcription factors. Int. J. Biochem. Cell Biol. 32:1103.
59. Yusuf, I., and D. A. Fruman. 2003. Regulation of quiescence in lymphocytes.
Trends Immunol. 24:380.
60. Song, A., T. Nikolcheva, and A. M. Krensky. 2000. Transcriptional regulation of
RANTES expression in T lymphocytes. Immunol. Rev. 177:236.
61. Song, A., A. Patel, K. Thamatrakoln, C. Liu, D. Feng, C. Clayberger, and
A. M. Krensky. 2002. Functional domains and DNA-binding sequences of
RFLAT-1/KLF13, a Kruppel-like transcription factor of activated T lymphocytes.
J. Biol. Chem. 277:30055.
62. Nikolcheva, T., S. Pyronnet, S. Y. Chou, N. Sonenberg, A. Song, C. Clayberger,
and A. M. Krensky. 2002. A translational rheostat for RFLAT-1 regulates RANTES expression in T lymphocytes. J. Clin. Invest. 110:119.
63. Song, C. Z., K. Keller, Y. Chen, and G. Stamatoyannopoulos. 2003. Functional
interplay between CBP and PCAF in acetylation and regulation of transcription
factor KLF13 activity. J. Mol. Biol. 329:207.
64. Laub, F., R. Aldabe, V. J. Friedrich, S. Ohnishi, T. Yoshida, and F. Ramirez.
2001. Developmental expression of mouse Kruppel-like transcription factor
KLF7 suggests a potential role in neurogenesis. Dev. Biol. 233:305.
Downloaded from http://www.jimmunol.org/ by guest on June 18, 2017
39.
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